diff --git a/.Rbuildignore b/.Rbuildignore index 193cecdbd2..0de63dff4d 100644 --- a/.Rbuildignore +++ b/.Rbuildignore @@ -29,3 +29,5 @@ demo/pandas ^TAGS$ ^\.dir-locals\.el$ ^vignettes/rsconnect$ +^docs$ +^_pkgdown\.yml$ diff --git a/README.md b/README.md index cd53da0f81..e49774106f 100755 --- a/README.md +++ b/README.md @@ -115,13 +115,13 @@ They all work as similarly as possible across the range of data sources. The mai ``` r system.time(carriers_df %>% summarise(delay = mean(arr_delay))) #> user system elapsed -#> 0.053 0.001 0.054 +#> 0.052 0.001 0.053 system.time(carriers_db1 %>% summarise(delay = mean(arr_delay)) %>% collect()) #> user system elapsed -#> 0.233 0.135 0.369 +#> 0.230 0.136 0.372 system.time(carriers_db2 %>% summarise(delay = mean(arr_delay)) %>% collect()) #> user system elapsed -#> 0.010 0.000 0.128 +#> 0.012 0.000 0.198 ``` Data frame methods are much much faster than the plyr equivalent. The database methods are slower, but can work with data that don't fit in memory. @@ -130,7 +130,7 @@ Data frame methods are much much faster than the plyr equivalent. The database m system.time(plyr::ddply(flights, "carrier", plyr::summarise, delay = mean(arr_delay, na.rm = TRUE))) #> user system elapsed -#> 0.118 0.039 0.158 +#> 0.122 0.042 0.165 ``` Multiple table verbs diff --git a/_pkgdown.yml b/_pkgdown.yml new file mode 100644 index 0000000000..e1ef7186fe --- /dev/null +++ b/_pkgdown.yml @@ -0,0 +1,3 @@ +template: + package: tidytemplate + default_assets: false diff --git a/docs/LICENSE b/docs/LICENSE new file mode 100644 index 0000000000..338a6b1173 --- /dev/null +++ b/docs/LICENSE @@ -0,0 +1,2 @@ +YEAR: 2013-2015 +COPYRIGHT HOLDER: RStudio diff --git a/docs/articles/data_frames.html b/docs/articles/data_frames.html new file mode 100644 index 0000000000..e53ebb38b9 --- /dev/null +++ b/docs/articles/data_frames.html @@ -0,0 +1,171 @@ + + + + + + + +Data frame performance • dplyr + + + + + + +
+
+ + + +
+
+
+

Data frame performance

+ +

2017-04-04

+
+ + + +
+

One of the reasons that dplyr is fast is that it’s very careful about when to make copies. This section describes how this works, and gives you some useful tools for understanding the memory usage of data frames in R.

+

The first tool we’ll use is dplyr::location(). It tells us the memory location of three components of a data frame object:

+
    +
  • the data frame itself
    • +
  • each column
    • +
  • each attribute
    • +
+
location(iris)
+#> <0x7f91413bd4e8>
+#> Variables:
+#>  * Sepal.Length: <0x7f913d4a1600>
+#>  * Sepal.Width:  <0x7f913d51e800>
+#>  * Petal.Length: <0x7f913d527000>
+#>  * Petal.Width:  <0x7f913d52ca00>
+#>  * Species:      <0x7f913b618540>
+#> Attributes:
+#>  * names:        <0x7f91413bd480>
+#>  * row.names:    <0x7f913b6139b0>
+#>  * class:        <0x7f91413cc8f8>
+

It’s useful to know the memory address, because if the address changes, then you’ll know that R has made a copy. Copies are bad because they take time to create. This isn’t usually a bottleneck if you have a few thousand values, but if you have millions or tens of millions of values it starts to take significant amounts of time. Unnecessary copies are also bad because they take up memory.

+

R tries to avoid making copies where possible. For example, if you just assign iris to another variable, it continues to the point same location:

+
iris2 <- iris
+location(iris2)
+#> <0x7f91413bd4e8>
+#> Variables:
+#>  * Sepal.Length: <0x7f913d4a1600>
+#>  * Sepal.Width:  <0x7f913d51e800>
+#>  * Petal.Length: <0x7f913d527000>
+#>  * Petal.Width:  <0x7f913d52ca00>
+#>  * Species:      <0x7f913b618540>
+#> Attributes:
+#>  * names:        <0x7f91413bd480>
+#>  * row.names:    <0x7f913b61b240>
+#>  * class:        <0x7f91413cc8f8>
+

Rather than having to compare hard to read memory locations, we can instead use the dplyr::changes() function to highlights changes between two versions of a data frame. The code below shows us that iris and iris2 are identical: both names point to the same location in memory.

+
changes(iris2, iris)
+#> <identical>
+

What do you think happens if you modify a single column of iris2? In R 3.1.0 and above, R knows to modify only that one column and to leave the others pointing to their existing locations:

+
iris2$Sepal.Length <- iris2$Sepal.Length * 2
+changes(iris, iris2)
+#> Changed variables:
+#>              old            new           
+#> Sepal.Length 0x7f913d4a1600 0x7f913ca85e00
+#> 
+#> Changed attributes:
+#>              old            new           
+#> row.names    0x7f913b5452c0 0x7f913b545540
+

(This was not the case prior to version 3.1.0, where R created a deep copy of the entire data frame.)

+

dplyr is equally smart:

+
iris3 <- mutate(iris, Sepal.Length = Sepal.Length * 2)
+changes(iris3, iris)
+#> Changed variables:
+#>              old            new           
+#> Sepal.Length 0x7f913d3be600 0x7f913d4a1600
+#> 
+#> Changed attributes:
+#>              old            new           
+#> class        0x7f91411399a8 0x7f91413cc8f8
+#> names        0x7f9141132b48 0x7f91413bd480
+#> row.names    0x7f913b624e60 0x7f913b6250e0
+

It creates only one new column while all the other columns continue to point at their original locations. You might notice that the attributes are still copied. However, this has little impact on performance. Because attributes are usually short vectors, the internal dplyr code needed to copy them is also considerably simpler.

+

dplyr never makes copies unless it has to:

+
    +

  • tbl_df() and group_by() don’t copy columns

    • +

  • select() never copies columns, even when you rename them

    • +

  • mutate() never copies columns, except when you modify an existing column

    • +

  • arrange() must always copy all columns because you’re changing the order of every one. This is an expensive operation for big data, but you can generally avoid it using the order argument to window functions

    • +

  • summarise() creates new data, but it’s usually at least an order of magnitude smaller than the original data.

    • +
+

In short, dplyr lets you work with data frames with very little memory overhead.

+

data.table takes this idea one step further: it provides functions that modify a data table in place. This avoids the need to make copies of pointers to existing columns and attributes, and speeds up operations when you have many columns. dplyr doesn’t do this with data frames (although it could) because I think it’s safer to keep data immutable: even if the resulting data frame shares practically all the data of the original data frame, all dplyr data frame methods return a new data frame.

+
+
+ + + +
+ + + +
+ + + diff --git a/docs/articles/disabled/benchmark-baseball.Rmd b/docs/articles/disabled/benchmark-baseball.Rmd new file mode 100644 index 0000000000..d0eda5d246 --- /dev/null +++ b/docs/articles/disabled/benchmark-baseball.Rmd @@ -0,0 +1,182 @@ + + +```{r, echo = FALSE, message = FALSE} +library(dplyr) +library(microbenchmark) +library(data.table) +library(Lahman) +knitr::opts_chunk$set( + comment = "#>", + error = FALSE, + tidy = FALSE +) + +options(digits = 3, microbenchmark.unit = "ms") +``` + +# Benchmarks: baseball data + +The purpose of these benchmarks is to be as fair as possible, to help understand the relatively performance tradeoffs of the different approaches. If you think my implementation of base or data.table equivalents is suboptimal, please let me know better ways. + +Also note that I consider any significant performance difference between `dt` and `dt_raw` to be a bug in dplyr: for individual operations there should be very little overhead to calling data.table via dplyr. However, data.table may be significantly faster when performing the same sequence of operations as dplyr. This is because currently dplyr uses an eager evaluation approach so the individual calls to `[.data.table` don't get as much information about the desired result as the single call to `[.data.table` would if you did it by hand. + +Thanks go to Matt Dowle and Arun Srinivasan for their extensive feedback on these benchmarks. + +## Data setup + +The following benchmarks explore the performance on a somewhat realistic example: the `Batting` dataset from the Lahman package. It contains `r nrow(Batting)` records on the batting careers of `r length(Batting$playerID)` players from `r min(Batting$yearID)` to `r max(Batting$yearID)`. + +The first code block defines two alternative backends for the Batting dataset. Grouping operations are performed inline in each benchmark. This represents the common scenario where you group the data and immediately use it. + +```{r setup} +batting_df <- tbl_df(Batting) +batting_dt <- tbl_dt(Batting) +``` + +## Summarise + +Compute the average number of at bats for each player: + +```{r summarise-mean} +microbenchmark( + dplyr_df = batting_df %>% group_by(playerID) %>% summarise(ab = mean(AB)), + dplyr_dt = batting_dt %>% group_by(playerID) %>% summarise(ab = mean(AB)), + dt_raw = batting_dt[, list(ab = mean(AB)), by = playerID], + base = tapply(batting_df$AB, batting_df$playerID, FUN = mean), + times = 5 +) +``` + +NB: base implementation captures computation but not output format, giving considerably less output. + +However, this comparison is slightly unfair because both data.table and `summarise()` use tricks to find a more efficient implementation of `mean()`. Data table calls a `C` implementation of the `mean (using `.External(Cfastmean, B, FALSE)` and thus avoiding the overhead of S3 method dispatch). `dplyr::summarise` uses a hybrid evaluation technique, where common functions are implemented purely in C++, avoiding R function call overhead. + +```{r sumarise-mean_} +mean_ <- function(x) .Internal(mean(x)) +microbenchmark( + dplyr_df = batting_df %>% group_by(playerID) %>% summarise(ab = mean_(AB)), + dplyr_dt = batting_dt %>% group_by(playerID) %>% summarise(ab = mean_(AB)), + dt_raw = batting_dt[, list(ab = mean_(AB)), by = playerID], + base = tapply(batting_df$AB, batting_df$playerID, FUN = mean_), + times = 5 +) +``` + +## Arrange + +Arrange by year within each player: + +```{r arrange} +microbenchmark( + dplyr_df = batting_df %>% arrange(playerID, yearID), + dplyr_dt = batting_dt %>% arrange(playerID, yearID), + dt_raw = setkey(copy(batting_dt), playerID, yearID), + base = batting_dt[order(batting_df$playerID, batting_df$yearID), ], + times = 2 +) +``` + +## Filter + +Find the year for which each player played the most games: + +```{r filter} +microbenchmark( + dplyr_df = batting_df %>% group_by(playerID) %>% filter(G == max(G)), + dplyr_dt = batting_dt %>% group_by(playerID) %>% filter(G == max(G)), + dt_raw = batting_dt[batting_dt[, .I[G == max(G)], by = playerID]$V1], + base = batting_df[ave(batting_df$G, batting_df$playerID, FUN = max) == + batting_df$G, ], + times = 2 +) +``` + +I'm not aware of a single line data table equivalent ([see SO 16573995](http://stackoverflow.com/questions/16573995/)). Suggetions welcome. dplyr currently doesn't support hybrid evaluation for logical comparison, but it is scheduled for 0.2 (see [#113](https://github.com/hadley/dplyr/issues/113)), this should give an additional speed up. + +## Mutate + +Rank years based on number of at bats: + +```{r mutate} +microbenchmark( + dplyr_df = batting_df %>% group_by(playerID) %>% mutate(r = rank(desc(AB))), + dplyr_dt = batting_dt %>% group_by(playerID) %>% mutate(r = rank(desc(AB))), + dt_raw = copy(batting_dt)[, rank := rank(desc(AB)), by = playerID], + times = 2 +) +``` + +(The `dt_raw` code needs to explicitly copy the data.table so the it doesn't modify in place, as is the data.table default. This is an example where it's difficult to compare data.table and dplyr directly because of different underlying philosophies.) + +Compute year of career: + +```{r mutate2} +microbenchmark( + dplyr_df = batting_df %>% group_by(playerID) %>% + mutate(cyear = yearID - min(yearID) + 1), + dplyr_dt = batting_dt %>% group_by(playerID) %>% + mutate(cyear = yearID - min(yearID) + 1), + dt_raw = copy(batting_dt)[, cyear := yearID - min(yearID) + 1, + by = playerID], + times = 5 +) +``` + +Rank is a relatively expensive operation and `min()` is relatively cheap, showing the the relative performance overhead of the difference techniques. + +dplyr currently has some support for hybrid evaluation of window functions. This yields substantial speed-ups where available: + +```{r mutate_hybrid} +min_rank_ <- min_rank +microbenchmark( + hybrid = batting_df %>% group_by(playerID) %>% mutate(r = min_rank(AB)), + regular = batting_df %>% group_by(playerID) %>% mutate(r = min_rank_(AB)), + times = 2 +) +``` + +## Joins + +We conclude with some quick comparisons of joins. First we create two new datasets: `master` which contains demographic information on each player, and `hall_of_fame` which contains all players inducted into the hall of fame. + +```{r} +master_df <- tbl_df(Master) %>% select(playerID, birthYear) +hall_of_fame_df <- tbl_df(HallOfFame) %>% filter(inducted == "Y") %>% + select(playerID, votedBy, category) + +master_dt <- tbl_dt(Master) %>% select(playerID, birthYear) +hall_of_fame_dt <- tbl_dt(HallOfFame) %>% filter(inducted == "Y") %>% + select(playerID, votedBy, category) +``` + + +```{r} +microbenchmark( + dplyr_df = left_join(master_df, hall_of_fame_df, by = "playerID"), + dplyr_dt = left_join(master_dt, hall_of_fame_dt, by = "playerID"), + base = merge(master_df, hall_of_fame_df, by = "playerID", all.x = TRUE), + times = 10 +) + +microbenchmark( + dplyr_df = inner_join(master_df, hall_of_fame_df, by = "playerID"), + dplyr_dt = inner_join(master_dt, hall_of_fame_dt, by = "playerID"), + base = merge(master_df, hall_of_fame_df, by = "playerID"), + times = 10 +) + +microbenchmark( + dplyr_df = semi_join(master_df, hall_of_fame_df, by = "playerID"), + dplyr_dt = semi_join(master_dt, hall_of_fame_dt, by = "playerID"), + times = 10 +) + +microbenchmark( + dplyr_df = anti_join(master_df, hall_of_fame_df, by = "playerID"), + dplyr_dt = anti_join(master_dt, hall_of_fame_dt, by = "playerID"), + times = 10 +) +``` diff --git a/docs/articles/hybrid-evaluation.html b/docs/articles/hybrid-evaluation.html new file mode 100644 index 0000000000..e7098704a2 --- /dev/null +++ b/docs/articles/hybrid-evaluation.html @@ -0,0 +1,348 @@ + + + + + + + +Hybrid evaluation • dplyr + + + + + + +
+
+ + + +
+
+
+

Hybrid evaluation

+ +

2017-04-04

+
+ + + +
+

Consider this call to summarise :

+
summarise(per_day, flights = sum(flights))
+

One of the ways dplyr achieves dramatic speedups is that expressions might not be evaluated by R, but by alternative code that is faster and uses less memory.

+

Conceptually the call to summarise above evaluates the expression sum(flights) on each subset of flights controlled by the grouping of per_day. This involves creating a new R vector to store the chunk and evaluate the R expression.

+

Evaluating the R expression might carry costs that can be avoided, i.e. S3 dispatch, …

+

dplyr recognizes the expression sum(flights) as the sum function applied to a known column of the data, making it possible to handle the dispatch early and once, avoid unneeded memory allocations and compute the result faster.

+

Hybrid evaluation is able to work on subexpressions. Consider:

+
foo <- function(x) x*x 
+summarise(per_day, flights = foo(sum(flights)) )
+

dplyr will substitute the subexpressions it knows how to handle and leave the rest to standard R evaluation. Instead of evaluating foo(sum(flights)), R will only have to evaluate foo(z) where z is the result of the internal evaluation of sum(flights).

+
+

+Implementation

+

Hybrid evaluation is designed to be extensible. Before we start registering custom hybrid evaluation handlers, we need to understand the system.

+

The first building block we need to cover is the Result class.

+
namespace dplyr {
+    class Result {
+    public:
+        Result(){}
+        virtual ~Result(){} ;
+        
+        virtual SEXP process( const GroupedDataFrame& gdf) = 0 ;
+        
+        virtual SEXP process( const FullDataFrame& df ) = 0 ;
+        
+        virtual SEXP process( const SlicingIndex& index ){
+            return R_NilValue ;    
+        }
+        
+    } ;
+}
+

The two first methods deal with grouped and ungrouped data frames. We will mainly focus on the last method that operates on a SlicingIndex.

+

SlicingIndex is a class that encapsulates indices of a single chunk of a grouped data frame.

+

Hybrid evaluation really just is deriving from the Result class. Let’s consider a simpler version of sum that only handles numeric vectors. (The internal version is more complete, handles missing values, …).

+
class Sum : public Result {
+  public:
+    Sum( NumericVector data_ ): data(data_){}
+    
+    SEXP process( const SlicingIndex& index ){
+      double res = 0.0 ;
+      for( int i=0; i<index.size(); i++) res += data[ index[i] ] ;
+      return NumericVector::create( res );
+    }
+    
+    virtual SEXP process( const GroupedDataFrame& gdf){
+      ...
+    }
+    virtual SEXP process( const FullDataFrame& df ){
+      ...
+    }
+        
+  private:
+    NumericVector data ;
+} ;
+
+

+Using Processor

+

Implementation of Result derived classes can be facilitated by the template class Processor. Processor is templated by two template parameters:

+
    +
  • the R output type (REALSXP, STRSXP, …)
    • +
  • the class you are defining. (This uses the CRTP pattern).
    • +
+

When using Processor we only have to supply a process_chunk method that takes a const SlicingIndex& as input and returns an object suitable to go into a vector of the type controlled by the first template parameter.

+

The purpose of the Processor template is then to generate the boiler plate code for the three process methods defined by the Result interface.

+

A possible Sum implementation would then look something like this:

+
class Sum : public Processor<REALSXP, Sum> {
+  public:
+    Sum( NumericVector data_ ): data(data_){}
+    
+    double process_chunk( const SlicingIndex& index ){
+      double res = 0.0 ;
+      for( int i=0; i<index.size(); i++) res += data[ index[i] ] ;
+      return res;
+    }
+    
+  private:
+    NumericVector data ;
+}
+

Recognizing genericity here, we might want to make Sum a template class in order to handle more than just numeric vector :

+
template <int RTYPE>
+class Sum : public Processor<REALSXP, Sum<RTYPE> > {
+  public:
+    typedef typename Rcpp::traits::storage_type<RTYPE>::type STORAGE ;
+    
+    Sum( Vector<RTYPE> data_ ): data(data_){}
+    
+    STORAGE process_chunk( const SlicingIndex& index ){
+      STORAGE res = 0.0 ;
+      for( int i=0; i<index.size(); i++) res += data[ index[i] ] ;
+      return res;
+    }
+    
+  private:
+    Vector<RTYPE> data ;
+}
+

Aside from not dealing with missing data and using internal knowledge of the SlicingIndex class, this implementation of Sum is close to the internal implementation in dplyr.

+
+
+

+Retrieving hybrid handlers

+

dplyr functions use the get_handler function to retrieve handlers for particular expressions.

+
Result* get_handler( SEXP call, const ILazySubsets& subsets ){
+    int depth = Rf_length(call) ;
+    HybridHandlerMap& handlers = get_handlers() ;
+    SEXP fun_symbol = CAR(call) ;
+    if( TYPEOF(fun_symbol) != SYMSXP ) return 0 ;
+    
+    HybridHandlerMap::const_iterator it = handlers.find( fun_symbol ) ;
+    if( it == handlers.end() ) return 0 ;
+    
+    return it->second( call, subsets, depth - 1 );
+}
+

The get_handler performs a lookup in a hash table of type HybridHandlerMap.

+
typedef dplyr::Result* (*HybridHandler)(SEXP, const dplyr::ILazySubsets&, int) ;
+typedef dplyr_hash_map<SEXP,HybridHandler> HybridHandlerMap ;
+

HybridHandlerMap is simply a hash map where the map key is the symbol of the function and the map value type is a function pointer defined by HybridHandler.

+

The parameters of the HybridHandler function pointer type are:

+
    +
  • The call we want to hybridify, e.g. something like sum(flights) +
    • +
  • a ILazySubsets reference. The only thing that is relevant about this class here is that it defines a get_variable method that takes a symbol SEXP and returns the corresponding variable from the data frame.
    • +
  • The number of arguments of the call. For example for sum(flights), the number of arguments is 1.
    • +
+

The purpose of the hybrid handler function is to return a Result* if it can handle the call or 0 if it cannot.

+

with our previous Sum template class, we could define a hybrid handler function like this:

+
Result* sum_handler(SEXP call, const ILazySubsets& subsets, int nargs ){
+  // we only know how to deal with argument
+  if( nargs != 1 ) return 0 ;
+  
+  // get the first argument
+  SEXP arg = CADR(call) ;
+  
+  // if this is a symbol, extract the variable from the subsets
+  if( TYPEOF(arg) == SYMSXP ) arg = subsets.get_variable(arg) ;
+  
+  // we know how to handle integer vectors and numeric vectors
+  switch( TYPEOF(arg) ){
+  case INTSXP: return new Sum<INTSXP>(arg) ;
+  case REALSXP: return new Sum<REALSXP>(arg) ;
+  default: break ;
+  }
+  
+  // we are here if we could not handle the call
+  return 0 ;
+}
+
+
+

+Registering hybrid handlers

+

dplyr enables users, most likely packages, to register their own hybrid handlers through the registerHybridHandler.

+
void registerHybridHandler( const char* , HybridHandler ) ;
+

To register the handler we created above, we then simply:

+
registerHybridHandler( "sum", sum_handler )  ;
+
+
+

+Putting it all together

+

We are going to register a handler called hitchhiker that always returns the answer to everything, i.e. 42.

+

The code below is suitable to run through sourceCpp.

+
#include <dplyr.h>
+// [[Rcpp::depends(dplyr,BH)]]
+
+using namespace dplyr ;
+using namespace Rcpp ;
+
+// the class that derives from Result through Processor
+class Hitchhiker : public Processor<INTSXP,Hitchhiker>{
+public:
+    
+    // always returns 42, as it is the answer to everything
+    int process_chunk( const SlicingIndex& ){
+        return 42 ;    
+    }
+} ;
+
+// we actually don't need the arguments
+// we can just let this handler return a new Hitchhiker pointer
+Result* hitchhiker_handler( SEXP, const ILazySubsets&, int ){
+    return new Hitchhiker ;        
+}
+
+// registration of the register, called from R, so exprted through Rcpp::export
+// [[Rcpp::export]]
+void registerHitchhiker(){
+    registerHybridHandler( "hitchhiker", hitchhiker_handler );    
+}
+
+/*** R
+    require(dplyr)
+    registerHitchhiker()
+    
+    n  <- 10000
+    df <- group_by( tbl_df( data.frame( 
+        id = sample( letters[1:4], 1000, replace = TRUE ), 
+        x  = rnorm(n)
+        ) ), id )
+    summarise( df, y = hitchhiker() )
+    # Source: local data frame [4 x 2]
+    # Groups:
+    # 
+    #   id  y
+    # 1  a 42
+    # 2  b 42
+    # 3  c 42
+    # 4  d 42
+    
+    summarise(df, y = mean(x) + hitchhiker())
+    # Source: local data frame [4 x 2]
+    # Groups:
+    # 
+    #   id        y
+    # 1  a 42.00988
+    # 2  b 42.00988
+    # 3  c 42.01440
+    # 4  d 41.99160
+*/
+
+
+

+Registering hybrid handlers with a package

+

To register custom handlers in packages, the best place is the init entry point that R automatically calls when a package is loaded.

+

Instead of exposing the registerHitchhiker function as above, packages would typically register handlers like this:

+
#include <Rcpp.h>
+#include <dplyr.h>
+
+// R automatically calls this function when the maypack package is loaded. 
+extern "C" void R_init_mypack( DllInfo* info ){
+  registerHybridHandler( "hitchhiker", hitchhiker_handler );
+}
+

For this your package must know about Rcpp and dplyr’s headers, which requires this information in the DESCRIPTION file:

+
LinkingTo: Rcpp, dplyr, BH
+

The Makevars and Makevars.win are similar to those used for any package that uses Rcpp features. See the Rcpp vignettes for details.

+
+
+
+
+ + + +
+ + + +
+ + + diff --git a/docs/articles/index.html b/docs/articles/index.html new file mode 100644 index 0000000000..852f56a649 --- /dev/null +++ b/docs/articles/index.html @@ -0,0 +1,123 @@ + + + + + + + + +Articles • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+

Vignette reference version 0.5.0.9001

+
+ +
+
+
+

All vignettes

+

+ + +
+
+
+ + +
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+ + + +
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+

Introduction to dplyr

+ +

2017-04-04

+
+ + + +
+

When working with data you must:

+
    +

  • Figure out what you want to do.

    • +

  • Describe those tasks in the form of a computer program.

    • +

  • Execute the program.

    • +
+

The dplyr package makes these steps fast and easy:

+
    +

  • By constraining your options, it simplifies how you can think about common data manipulation tasks.

    • +

  • It provides simple “verbs”, functions that correspond to the most common data manipulation tasks, to help you translate those thoughts into code.

    • +

  • It uses efficient data storage backends, so you spend less time waiting for the computer.

    • +
+

This document introduces you to dplyr’s basic set of tools, and shows you how to apply them to data frames. Other vignettes provide more details on specific topics:

+
    +

  • databases: Besides in-memory data frames, dplyr also connects to out-of-memory, remote databases. And by translating your R code into the appropriate SQL, it allows you to work with both types of data using the same set of tools.

    • +

  • benchmark-baseball: see how dplyr compares to other tools for data manipulation on a realistic use case.

    • +

  • window-functions: a window function is a variation on an aggregation function. Where an aggregate function uses n inputs to produce 1 output, a window function uses n inputs to produce n outputs.

    • +
+
+

+Data: nycflights13

+

To explore the basic data manipulation verbs of dplyr, we’ll start with the built in nycflights13 data frame. This dataset contains all 336776 flights that departed from New York City in 2013. The data comes from the US Bureau of Transportation Statistics, and is documented in ?nycflights13

+
library(nycflights13)
+dim(flights)
+#> [1] 336776     19
+head(flights)
+#> # A tibble: 6 × 19
+#>    year month   day dep_time sched_dep_time dep_delay arr_time
+#>   <int> <int> <int>    <int>          <int>     <dbl>    <int>
+#> 1  2013     1     1      517            515         2      830
+#> 2  2013     1     1      533            529         4      850
+#> 3  2013     1     1      542            540         2      923
+#> 4  2013     1     1      544            545        -1     1004
+#> # ... with 2 more rows, and 12 more variables: sched_arr_time <int>,
+#> #   arr_delay <dbl>, carrier <chr>, flight <int>, tailnum <chr>,
+#> #   origin <chr>, dest <chr>, air_time <dbl>, distance <dbl>, hour <dbl>,
+#> #   minute <dbl>, time_hour <dttm>
+

dplyr can work with data frames as is, but if you’re dealing with large data, it’s worthwhile to convert them to a tbl_df: this is a wrapper around a data frame that won’t accidentally print a lot of data to the screen.

+
+
+

+Single table verbs

+

Dplyr aims to provide a function for each basic verb of data manipulation:

+ +

If you’ve used plyr before, many of these will be familar.

+
+
+

+Filter rows with filter() +

+

filter() allows you to select a subset of rows in a data frame. The first argument is the name of the data frame. The second and subsequent arguments are the expressions that filter the data frame:

+

For example, we can select all flights on January 1st with:

+
filter(flights, month == 1, day == 1)
+#> # A tibble: 842 × 19
+#>    year month   day dep_time sched_dep_time dep_delay arr_time
+#>   <int> <int> <int>    <int>          <int>     <dbl>    <int>
+#> 1  2013     1     1      517            515         2      830
+#> 2  2013     1     1      533            529         4      850
+#> 3  2013     1     1      542            540         2      923
+#> 4  2013     1     1      544            545        -1     1004
+#> # ... with 838 more rows, and 12 more variables: sched_arr_time <int>,
+#> #   arr_delay <dbl>, carrier <chr>, flight <int>, tailnum <chr>,
+#> #   origin <chr>, dest <chr>, air_time <dbl>, distance <dbl>, hour <dbl>,
+#> #   minute <dbl>, time_hour <dttm>
+

This is equivalent to the more verbose code in base R:

+
flights[flights$month == 1 & flights$day == 1, ]
+

filter() works similarly to subset() except that you can give it any number of filtering conditions, which are joined together with & (not && which is easy to do accidentally!). You can also use other boolean operators:

+
filter(flights, month == 1 | month == 2)
+

To select rows by position, use slice():

+
slice(flights, 1:10)
+#> # A tibble: 10 × 19
+#>    year month   day dep_time sched_dep_time dep_delay arr_time
+#>   <int> <int> <int>    <int>          <int>     <dbl>    <int>
+#> 1  2013     1     1      517            515         2      830
+#> 2  2013     1     1      533            529         4      850
+#> 3  2013     1     1      542            540         2      923
+#> 4  2013     1     1      544            545        -1     1004
+#> # ... with 6 more rows, and 12 more variables: sched_arr_time <int>,
+#> #   arr_delay <dbl>, carrier <chr>, flight <int>, tailnum <chr>,
+#> #   origin <chr>, dest <chr>, air_time <dbl>, distance <dbl>, hour <dbl>,
+#> #   minute <dbl>, time_hour <dttm>
+
+
+

+Arrange rows with arrange() +

+

arrange() works similarly to filter() except that instead of filtering or selecting rows, it reorders them. It takes a data frame, and a set of column names (or more complicated expressions) to order by. If you provide more than one column name, each additional column will be used to break ties in the values of preceding columns:

+
arrange(flights, year, month, day)
+#> # A tibble: 336,776 × 19
+#>    year month   day dep_time sched_dep_time dep_delay arr_time
+#>   <int> <int> <int>    <int>          <int>     <dbl>    <int>
+#> 1  2013     1     1      517            515         2      830
+#> 2  2013     1     1      533            529         4      850
+#> 3  2013     1     1      542            540         2      923
+#> 4  2013     1     1      544            545        -1     1004
+#> # ... with 336,772 more rows, and 12 more variables: sched_arr_time <int>,
+#> #   arr_delay <dbl>, carrier <chr>, flight <int>, tailnum <chr>,
+#> #   origin <chr>, dest <chr>, air_time <dbl>, distance <dbl>, hour <dbl>,
+#> #   minute <dbl>, time_hour <dttm>
+

Use desc() to order a column in descending order:

+
arrange(flights, desc(arr_delay))
+#> # A tibble: 336,776 × 19
+#>    year month   day dep_time sched_dep_time dep_delay arr_time
+#>   <int> <int> <int>    <int>          <int>     <dbl>    <int>
+#> 1  2013     1     9      641            900      1301     1242
+#> 2  2013     6    15     1432           1935      1137     1607
+#> 3  2013     1    10     1121           1635      1126     1239
+#> 4  2013     9    20     1139           1845      1014     1457
+#> # ... with 336,772 more rows, and 12 more variables: sched_arr_time <int>,
+#> #   arr_delay <dbl>, carrier <chr>, flight <int>, tailnum <chr>,
+#> #   origin <chr>, dest <chr>, air_time <dbl>, distance <dbl>, hour <dbl>,
+#> #   minute <dbl>, time_hour <dttm>
+

dplyr::arrange() works the same way as plyr::arrange(). It’s a straightforward wrapper around order() that requires less typing. The previous code is equivalent to:

+
flights[order(flights$year, flights$month, flights$day), ]
+flights[order(flights$arr_delay, decreasing = TRUE), ] or flights[order(-flights$arr_delay), ]
+
+
+

+Select columns with select() +

+

Often you work with large datasets with many columns but only a few are actually of interest to you. select() allows you to rapidly zoom in on a useful subset using operations that usually only work on numeric variable positions:

+
# Select columns by name
+select(flights, year, month, day)
+#> # A tibble: 336,776 × 3
+#>    year month   day
+#>   <int> <int> <int>
+#> 1  2013     1     1
+#> 2  2013     1     1
+#> 3  2013     1     1
+#> 4  2013     1     1
+#> # ... with 336,772 more rows
+# Select all columns between year and day (inclusive)
+select(flights, year:day)
+#> # A tibble: 336,776 × 3
+#>    year month   day
+#>   <int> <int> <int>
+#> 1  2013     1     1
+#> 2  2013     1     1
+#> 3  2013     1     1
+#> 4  2013     1     1
+#> # ... with 336,772 more rows
+# Select all columns except those from year to day (inclusive)
+select(flights, -(year:day))
+#> # A tibble: 336,776 × 16
+#>   dep_time sched_dep_time dep_delay arr_time sched_arr_time arr_delay
+#>      <int>          <int>     <dbl>    <int>          <int>     <dbl>
+#> 1      517            515         2      830            819        11
+#> 2      533            529         4      850            830        20
+#> 3      542            540         2      923            850        33
+#> 4      544            545        -1     1004           1022       -18
+#> # ... with 336,772 more rows, and 10 more variables: carrier <chr>,
+#> #   flight <int>, tailnum <chr>, origin <chr>, dest <chr>, air_time <dbl>,
+#> #   distance <dbl>, hour <dbl>, minute <dbl>, time_hour <dttm>
+

This function works similarly to the select argument in base::subset(). Because the dplyr philosophy is to have small functions that do one thing well, it’s its own function in dplyr.

+

There are a number of helper functions you can use within select(), like starts_with(), ends_with(), matches() and contains(). These let you quickly match larger blocks of variables that meet some criterion. See ?select for more details.

+

You can rename variables with select() by using named arguments:

+
select(flights, tail_num = tailnum)
+#> # A tibble: 336,776 × 1
+#>   tail_num
+#>      <chr>
+#> 1   N14228
+#> 2   N24211
+#> 3   N619AA
+#> 4   N804JB
+#> # ... with 336,772 more rows
+

But because select() drops all the variables not explicitly mentioned, it’s not that useful. Instead, use rename():

+
rename(flights, tail_num = tailnum)
+#> # A tibble: 336,776 × 19
+#>    year month   day dep_time sched_dep_time dep_delay arr_time
+#>   <int> <int> <int>    <int>          <int>     <dbl>    <int>
+#> 1  2013     1     1      517            515         2      830
+#> 2  2013     1     1      533            529         4      850
+#> 3  2013     1     1      542            540         2      923
+#> 4  2013     1     1      544            545        -1     1004
+#> # ... with 336,772 more rows, and 12 more variables: sched_arr_time <int>,
+#> #   arr_delay <dbl>, carrier <chr>, flight <int>, tail_num <chr>,
+#> #   origin <chr>, dest <chr>, air_time <dbl>, distance <dbl>, hour <dbl>,
+#> #   minute <dbl>, time_hour <dttm>
+
+
+

+Extract distinct (unique) rows

+

Use distinct()to find unique values in a table:

+
distinct(flights, tailnum)
+#> # A tibble: 4,044 × 1
+#>   tailnum
+#>     <chr>
+#> 1  N14228
+#> 2  N24211
+#> 3  N619AA
+#> 4  N804JB
+#> # ... with 4,040 more rows
+distinct(flights, origin, dest)
+#> # A tibble: 224 × 2
+#>   origin  dest
+#>    <chr> <chr>
+#> 1    EWR   IAH
+#> 2    LGA   IAH
+#> 3    JFK   MIA
+#> 4    JFK   BQN
+#> # ... with 220 more rows
+

(This is very similar to base::unique() but should be much faster.)

+
+
+

+Add new columns with mutate() +

+

Besides selecting sets of existing columns, it’s often useful to add new columns that are functions of existing columns. This is the job of mutate():

+
mutate(flights,
+  gain = arr_delay - dep_delay,
+  speed = distance / air_time * 60)
+#> # A tibble: 336,776 × 21
+#>    year month   day dep_time sched_dep_time dep_delay arr_time
+#>   <int> <int> <int>    <int>          <int>     <dbl>    <int>
+#> 1  2013     1     1      517            515         2      830
+#> 2  2013     1     1      533            529         4      850
+#> 3  2013     1     1      542            540         2      923
+#> 4  2013     1     1      544            545        -1     1004
+#> # ... with 336,772 more rows, and 14 more variables: sched_arr_time <int>,
+#> #   arr_delay <dbl>, carrier <chr>, flight <int>, tailnum <chr>,
+#> #   origin <chr>, dest <chr>, air_time <dbl>, distance <dbl>, hour <dbl>,
+#> #   minute <dbl>, time_hour <dttm>, gain <dbl>, speed <dbl>
+

dplyr::mutate() works the same way as plyr::mutate() and similarly to base::transform(). The key difference between mutate() and transform() is that mutate allows you to refer to columns that you’ve just created:

+
mutate(flights,
+  gain = arr_delay - dep_delay,
+  gain_per_hour = gain / (air_time / 60)
+)
+#> # A tibble: 336,776 × 21
+#>    year month   day dep_time sched_dep_time dep_delay arr_time
+#>   <int> <int> <int>    <int>          <int>     <dbl>    <int>
+#> 1  2013     1     1      517            515         2      830
+#> 2  2013     1     1      533            529         4      850
+#> 3  2013     1     1      542            540         2      923
+#> 4  2013     1     1      544            545        -1     1004
+#> # ... with 336,772 more rows, and 14 more variables: sched_arr_time <int>,
+#> #   arr_delay <dbl>, carrier <chr>, flight <int>, tailnum <chr>,
+#> #   origin <chr>, dest <chr>, air_time <dbl>, distance <dbl>, hour <dbl>,
+#> #   minute <dbl>, time_hour <dttm>, gain <dbl>, gain_per_hour <dbl>
+
transform(flights,
+  gain = arr_delay - delay,
+  gain_per_hour = gain / (air_time / 60)
+)
+#> Error: object 'gain' not found
+

If you only want to keep the new variables, use transmute():

+
transmute(flights,
+  gain = arr_delay - dep_delay,
+  gain_per_hour = gain / (air_time / 60)
+)
+#> # A tibble: 336,776 × 2
+#>    gain gain_per_hour
+#>   <dbl>         <dbl>
+#> 1     9      2.378855
+#> 2    16      4.229075
+#> 3    31     11.625000
+#> 4   -17     -5.573770
+#> # ... with 336,772 more rows
+
+
+

+Summarise values with summarise() +

+

The last verb is summarise(). It collapses a data frame to a single row (this is exactly equivalent to plyr::summarise()):

+
summarise(flights,
+  delay = mean(dep_delay, na.rm = TRUE))
+#> # A tibble: 1 × 1
+#>      delay
+#>      <dbl>
+#> 1 12.63907
+

Below, we’ll see how this verb can be very useful.

+
+
+

+Randomly sample rows with sample_n() and sample_frac() +

+

You can use sample_n() and sample_frac() to take a random sample of rows: use sample_n() for a fixed number and sample_frac() for a fixed fraction.

+
sample_n(flights, 10)
+#> # A tibble: 10 × 19
+#>    year month   day dep_time sched_dep_time dep_delay arr_time
+#>   <int> <int> <int>    <int>          <int>     <dbl>    <int>
+#> 1  2013    11    27     1638           1621        17     1911
+#> 2  2013     5     1     1153           1200        -7     1251
+#> 3  2013     5    19      937            940        -3     1045
+#> 4  2013     2     7     1218           1221        -3     1405
+#> # ... with 6 more rows, and 12 more variables: sched_arr_time <int>,
+#> #   arr_delay <dbl>, carrier <chr>, flight <int>, tailnum <chr>,
+#> #   origin <chr>, dest <chr>, air_time <dbl>, distance <dbl>, hour <dbl>,
+#> #   minute <dbl>, time_hour <dttm>
+sample_frac(flights, 0.01)
+#> # A tibble: 3,368 × 19
+#>    year month   day dep_time sched_dep_time dep_delay arr_time
+#>   <int> <int> <int>    <int>          <int>     <dbl>    <int>
+#> 1  2013     1    13     1821           1820         1     2007
+#> 2  2013     5     8     1416           1052       204     1727
+#> 3  2013     3    16     1802           1800         2     1927
+#> 4  2013    11     3     1829           1729        60     2047
+#> # ... with 3,364 more rows, and 12 more variables: sched_arr_time <int>,
+#> #   arr_delay <dbl>, carrier <chr>, flight <int>, tailnum <chr>,
+#> #   origin <chr>, dest <chr>, air_time <dbl>, distance <dbl>, hour <dbl>,
+#> #   minute <dbl>, time_hour <dttm>
+

Use replace = TRUE to perform a bootstrap sample. If needed, you can weight the sample with the weight argument.

+
+
+

+Commonalities

+

You may have noticed that the syntax and function of all these verbs are very similar:

+
    +

  • The first argument is a data frame.

    • +

  • The subsequent arguments describe what to do with the data frame. Notice that you can refer to columns in the data frame directly without using $.

    • +

  • The result is a new data frame

    • +
+

Together these properties make it easy to chain together multiple simple steps to achieve a complex result.

+

These five functions provide the basis of a language of data manipulation. At the most basic level, you can only alter a tidy data frame in five useful ways: you can reorder the rows (arrange()), pick observations and variables of interest (filter() and select()), add new variables that are functions of existing variables (mutate()), or collapse many values to a summary (summarise()). The remainder of the language comes from applying the five functions to different types of data. For example, I’ll discuss how these functions work with grouped data.

+
+
+

+Grouped operations

+

These verbs are useful on their own, but they become really powerful when you apply them to groups of observations within a dataset. In dplyr, you do this with the group_by() function. It breaks down a dataset into specified groups of rows. When you then apply the verbs above on the resulting object they’ll be automatically applied “by group”. Most importantly, all this is achieved by using the same exact syntax you’d use with an ungrouped object.

+

Grouping affects the verbs as follows:

+
    +

  • grouped select() is the same as ungrouped select(), except that grouping variables are always retained.

    • +

  • grouped arrange() orders first by the grouping variables

    • +

  • mutate() and filter() are most useful in conjunction with window functions (like rank(), or min(x) == x). They are described in detail in vignette("window-functions").

    • +

  • sample_n() and sample_frac() sample the specified number/fraction of rows in each group.

    • +

  • slice() extracts rows within each group.

    • +

  • summarise() is powerful and easy to understand, as described in more detail below.

    • +
+

In the following example, we split the complete dataset into individual planes and then summarise each plane by counting the number of flights (count = n()) and computing the average distance (dist = mean(Distance, na.rm = TRUE)) and arrival delay (delay = mean(ArrDelay, na.rm = TRUE)). We then use ggplot2 to display the output.

+
by_tailnum <- group_by(flights, tailnum)
+delay <- summarise(by_tailnum,
+  count = n(),
+  dist = mean(distance, na.rm = TRUE),
+  delay = mean(arr_delay, na.rm = TRUE))
+delay <- filter(delay, count > 20, dist < 2000)
+
+# Interestingly, the average delay is only slightly related to the
+# average distance flown by a plane.
+ggplot(delay, aes(dist, delay)) +
+  geom_point(aes(size = count), alpha = 1/2) +
+  geom_smooth() +
+  scale_size_area()
+

+

You use summarise() with aggregate functions, which take a vector of values and return a single number. There are many useful examples of such functions in base R like min(), max(), mean(), sum(), sd(), median(), and IQR(). dplyr provides a handful of others:

+
    +

  • n(): the number of observations in the current group

    • +

  • n_distinct(x):the number of unique values in x.

    • +

  • first(x), last(x) and nth(x, n) - these work similarly to x[1], x[length(x)], and x[n] but give you more control over the result if the value is missing.

    • +
+

For example, we could use these to find the number of planes and the number of flights that go to each possible destination:

+
destinations <- group_by(flights, dest)
+summarise(destinations,
+  planes = n_distinct(tailnum),
+  flights = n()
+)
+#> # A tibble: 105 × 3
+#>    dest planes flights
+#>   <chr>  <int>   <int>
+#> 1   ABQ    108     254
+#> 2   ACK     58     265
+#> 3   ALB    172     439
+#> 4   ANC      6       8
+#> # ... with 101 more rows
+

You can also use any function that you write yourself. For performance, dplyr provides optimised C++ versions of many of these functions. If you want to provide your own C++ function, see the hybrid-evaluation vignette for more details.

+

When you group by multiple variables, each summary peels off one level of the grouping. That makes it easy to progressively roll-up a dataset:

+
daily <- group_by(flights, year, month, day)
+(per_day   <- summarise(daily, flights = n()))
+#> Source: local data frame [c(2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 
+#> 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 
+#> 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 
+#> 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 
+#> 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013) x c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 
+#> 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 
+#> 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12) x c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 
+#> 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 
+#> 29, 30, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31) x c(842, 943, 914, 915, 720, 832, 933, 899, 902, 932, 930, 690, 828, 928, 894, 901, 927, 924, 674, 786, 912, 890, 897, 925, 922, 680, 823, 923, 890, 900, 928, 926, 682, 814, 932, 896, 901, 932, 930, 684, 829, 929, 893, 918, 956, 954, 738, 848, 948, 943, 949, 961, 957, 743, 880, 961, 938, 945, 964, 958, 765, 913, 977, 965, 972, 980, 979, 765, 908, 980, 966, 974, 982, 979, 767, 907, 981, 967, 970, 980, 977, 767, 905, 978, 973, 977, 982, 974, 769, 897, 970, 983, 992, 985, 981, 770, 911, 981, 975, 989, 
+#> 992, 989, 770, 917, 995, 974, 988, 992, 988, 766, 919, 985, 965, 976, 983, 981, 757, 913, 983, 960, 964, 983, 978, 745, 912, 980, 955, 965, 981, 978, 738, 896, 979, 955, 967, 982, 980, 749, 911, 983, 962, 972, 988, 978, 728, 729, 928, 981, 974, 989, 986, 754, 911, 982, 960, 970, 976, 975, 779, 908, 987, 980, 983, 989, 989, 801, 918, 990, 982, 985, 995, 993, 812, 923, 994, 993, 995, 995, 994, 812, 918, 966, 945, 983, 737, 822, 805, 934, 1004, 1001, 1004, 1006, 1002, 811, 931, 999, 996, 1001, 1003, 
+#> 999, 810, 929, 1000, 997, 1000, 1003, 999, 811, 930, 999, 997, 1001, 1000, 999, 809, 929, 1000, 996, 1001, 1001, 999, 807, 929, 1001, 995, 997, 1000, 998, 780, 914, 996, 986, 990, 990, 989, 774, 903, 982, 965, 973, 979, 965, 680, 718, 929, 956, 948, 969, 967, 688, 908, 991, 961, 947, 992, 996, 686, 900, 992, 961, 972, 992, 994, 693, 904, 993, 960, 976, 996, 996, 682, 914, 993, 965, 975, 995, 995, 687, 917, 994, 964, 974, 994, 991, 676, 902, 987, 963, 974, 995, 993, 684, 915, 991, 964, 975, 992, 989, 
+#> 685, 910, 983, 965, 973, 922, 986, 689, 902, 978, 967, 973, 991, 986, 715, 895, 983, 973, 976, 988, 985, 714, 896, 985, 973, 977, 1000, 999, 744, 896, 942, 989, 1014, 634, 661, 857, 987, 1004, 973, 958, 969, 970, 691, 875, 962, 943, 954, 968, 970, 692, 880, 964, 949, 956, 974, 980, 811, 895, 985, 761, 719, 936, 963, 814, 888, 968, 776)]
+#> Groups: year, month [?]
+#> 
+#>    year month   day flights
+#>   <int> <int> <int>   <int>
+#> 1  2013     1     1     842
+#> 2  2013     1     2     943
+#> 3  2013     1     3     914
+#> 4  2013     1     4     915
+#> # ... with 361 more rows
+(per_month <- summarise(per_day, flights = sum(flights)))
+#> Source: local data frame [c(2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013) x 1:12 x c(27004, 24951, 28834, 28330, 28796, 28243, 29425, 29327, 27574, 28889, 27268, 28135)]
+#> Groups: year [?]
+#> 
+#>    year month flights
+#>   <int> <int>   <int>
+#> 1  2013     1   27004
+#> 2  2013     2   24951
+#> 3  2013     3   28834
+#> 4  2013     4   28330
+#> # ... with 8 more rows
+(per_year  <- summarise(per_month, flights = sum(flights)))
+#> # A tibble: 1 × 2
+#>    year flights
+#>   <int>   <int>
+#> 1  2013  336776
+

However you need to be careful when progressively rolling up summaries like this: it’s ok for sums and counts, but you need to think about weighting for means and variances (it’s not possible to do this exactly for medians).

+
+

+Chaining

+

The dplyr API is functional in the sense that function calls don’t have side-effects. You must always save their results. This doesn’t lead to particularly elegant code, especially if you want to do many operations at once. You either have to do it step-by-step:

+
a1 <- group_by(flights, year, month, day)
+a2 <- select(a1, arr_delay, dep_delay)
+a3 <- summarise(a2,
+  arr = mean(arr_delay, na.rm = TRUE),
+  dep = mean(dep_delay, na.rm = TRUE))
+a4 <- filter(a3, arr > 30 | dep > 30)
+

Or if you don’t want to save the intermediate results, you need to wrap the function calls inside each other:

+
filter(
+  summarise(
+    select(
+      group_by(flights, year, month, day),
+      arr_delay, dep_delay
+    ),
+    arr = mean(arr_delay, na.rm = TRUE),
+    dep = mean(dep_delay, na.rm = TRUE)
+  ),
+  arr > 30 | dep > 30
+)
+#> Adding missing grouping variables: `year`, `month`, `day`
+#> Source: local data frame [c(2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013, 2013) x c(1, 1, 2, 2, 3, 3, 4, 4, 4, 4, 4, 4, 5, 5, 5, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 7, 7, 7, 7, 7, 7, 7, 7, 8, 8, 8, 8, 8, 9, 9, 10, 10, 12, 12, 12, 12, 12, 12, 12) x c(16, 31, 11, 27, 8, 18, 10, 12, 18, 19, 22, 25, 8, 23, 24, 2, 10, 13, 18, 24, 25, 26, 27, 28, 30, 1, 7, 8, 9, 10, 22, 23, 28, 1, 8, 9, 22, 28, 2, 12, 7, 11, 5, 8, 9, 10, 14, 17, 23) x c(34.2473622508792, 32.602853745541, 36.2900943396226, 31.2524916943522, 85.8621553884712, 41.2918918918919, 38.4123112659698, 36.0481400437637, 36.0284810126582, 47.9116972477064, 37.812166488794, 33.68125, 39.6091825307951, 61.9708994708995, 24.2574152542373, 26.0755176613885, 28.0222929936306, 63.7536889897843, 37.6480263157895, 51.1768082663605, 41.5136842105263, 27.3174097664544, 44.783295711061, 44.9768518518519, 43.5102781136638, 58.2805017103763, 40.3063781321185, 29.6488469601677, 31.3343653250774, 
+#> 59.6264775413712, 62.7634032634033, 44.9598214285714, 49.8317757009346, 35.9892588614393, 55.481162540366, 43.3136412459721, 29.9767441860465, 35.2030735455543, 45.5184304399524, 58.9124183006536, 39.017259978425, 18.9229946524064, 51.6662546353523, 36.911801242236, 42.5755555555556, 44.5087956698241, 46.397504456328, 55.8718562874252, 32.2260416666667) x c(24.612865497076, 28.6583629893238, 39.0735981308411, 37.7632743362832, 83.5369211514393, 30.1179596174283, 33.0236753100338, 34.8384279475983, 34.9153605015674, 46.1278280542986, 30.6425531914894, 23.3395638629283, 43.2177777777778, 51.1447196870926, 30.3407172995781, 34.0133657351154, 30.6194503171247, 45.7908277404922, 35.9507658643326, 47.1574178935447, 43.063025210084, 30.6117523609654, 40.8912319644839, 48.8277841561424, 44.1881785283474, 56.2338251986379, 36.6174496644295, 37.2966457023061, 
+#> 30.711498973306, 52.8607021517554, 46.6670467502851, 44.7416851441242, 37.7101616628176, 34.574034334764, 43.3499469777306, 34.6918976545842, 33.6004206098843, 40.5268935236004, 53.0295508274232, 49.95875, 39.1467098166127, 31.2318376068376, 52.327990135635, 21.5153374233129, 34.8002207505519, 26.4654939106901, 28.3615520282187, 40.7056019070322, 32.2541493775934)]
+#> Groups: year, month [11]
+#> 
+#>    year month   day      arr      dep
+#>   <int> <int> <int>    <dbl>    <dbl>
+#> 1  2013     1    16 34.24736 24.61287
+#> 2  2013     1    31 32.60285 28.65836
+#> 3  2013     2    11 36.29009 39.07360
+#> 4  2013     2    27 31.25249 37.76327
+#> # ... with 45 more rows
+

This is difficult to read because the order of the operations is from inside to out. Thus, the arguments are a long way away from the function. To get around this problem, dplyr provides the %>% operator. x %>% f(y) turns into f(x, y) so you can use it to rewrite multiple operations that you can read left-to-right, top-to-bottom:

+
flights %>%
+  group_by(year, month, day) %>%
+  select(arr_delay, dep_delay) %>%
+  summarise(
+    arr = mean(arr_delay, na.rm = TRUE),
+    dep = mean(dep_delay, na.rm = TRUE)
+  ) %>%
+  filter(arr > 30 | dep > 30)
+
+
+
+

+Other data sources

+

As well as data frames, dplyr works with data that is stored in other ways, like data tables, databases and multidimensional arrays.

+
+

+Data table

+

dplyr also provides data table methods for all verbs through dtplyr. If you’re using data.tables already this lets you to use dplyr syntax for data manipulation, and data.table for everything else.

+

For multiple operations, data.table can be faster because you usually use it with multiple verbs simultaneously. For example, with data table you can do a mutate and a select in a single step. It’s smart enough to know that there’s no point in computing the new variable for rows you’re about to throw away.

+

The advantages of using dplyr with data tables are:

+
    +

  • For common data manipulation tasks, it insulates you from the reference semantics of data.tables, and protects you from accidentally modifying your data.

    • +

  • Instead of one complex method built on the subscripting operator ([), it provides many simple methods.

    • +
+
+
+

+Databases

+

dplyr also allows you to use the same verbs with a remote database. It takes care of generating the SQL for you so that you can avoid the cognitive challenge of constantly switching between languages. To use these capabilities, you’ll need to install the dbplyr package and then read vignette("dbplyr") for the details.

+
+
+

+Multidimensional arrays / cubes

+

tbl_cube() provides an experimental interface to multidimensional arrays or data cubes. If you’re using this form of data in R, please get in touch so I can better understand your needs.

+
+
+
+

+Comparisons

+

Compared to all existing options, dplyr:

+
    +

  • abstracts away how your data is stored, so that you can work with data frames, data tables and remote databases using the same set of functions. This lets you focus on what you want to achieve, not on the logistics of data storage.

    • +

  • provides a thoughtful default print() method that doesn’t automatically print pages of data to the screen (this was inspired by data table’s output).

    • +
+

Compared to base functions:

+
    +

  • dplyr is much more consistent; functions have the same interface. So once you’ve mastered one, you can easily pick up the others

    • +

  • base functions tend to be based around vectors; dplyr is based around data frames

    • +
+

Compared to plyr, dplyr:

+
    +

  • is much much faster

    • +

  • provides a better thought out set of joins

    • +

  • only provides tools for working with data frames (e.g. most of dplyr is equivalent to ddply() + various functions, do() is equivalent to dlply())

    • +
+

Compared to virtual data frame approaches:

+
    +

  • it doesn’t pretend that you have a data frame: if you want to run lm etc, you’ll still need to manually pull down the data

    • +

  • it doesn’t provide methods for R summary functions (e.g. mean(), or sum())

    • +
+
+
+
+ + + +
+ + + +
+ + + diff --git a/docs/articles/introduction_files/figure-html/unnamed-chunk-20-1.png b/docs/articles/introduction_files/figure-html/unnamed-chunk-20-1.png new file mode 100644 index 0000000000..61e58670e9 Binary files /dev/null and b/docs/articles/introduction_files/figure-html/unnamed-chunk-20-1.png differ diff --git a/docs/articles/nse.html b/docs/articles/nse.html new file mode 100644 index 0000000000..fdd9f90089 --- /dev/null +++ b/docs/articles/nse.html @@ -0,0 +1,101 @@ + + + + + + + +Non-standard evaluation • dplyr + + + + + + +
+
+ + + +
+
+
+

Non-standard evaluation

+ +

2017-04-04

+
+ + + +
+

Non-standard evaluation is now handled with the tidy evaluation framework. Please see vignette("programming").

+
+
+ + + +
+ + + +
+ + + diff --git a/docs/articles/programming.html b/docs/articles/programming.html new file mode 100644 index 0000000000..6962f391b9 --- /dev/null +++ b/docs/articles/programming.html @@ -0,0 +1,649 @@ + + + + + + + +Programming with dplyr • dplyr + + + + + + +
+
+ + + +
+
+
+

Programming with dplyr

+ +
+ + + +
+

Most dplyr functions use non-standard evaluation (NSE). This is a catch-all term that means they don’t follow the usual R rules of evaluation. Instead, they capture the expression that you typed and evaluate it in a custom way. This has two main benefits for dplyr code:

+
    +

  • Operations on data frames can be expressed succinctly because you don’t need to repeat the name of the data frame. For example, you can write filter(df, x == 1, y == 2, z == 3) instead of df[df$x == 1 & df$y ==2 & df$z == 3, ].

    • +

  • dplyr can choose to compute results in a different way to base R. This is important for database backends because dplyr itself doesn’t do any work, but instead generates the SQL that tells the database what to do.

    • +
+

Unfortunately these benefits do not come for free. There are two main drawbacks:

+
    +
  • +

    Most dplyr arguments are not referentially transparent. That means you can’t replace a value with a seemingly equivalent object that you’ve defined elsewhere. In other words, this code:

    +
    df <- tibble(x = 1:3, y = 3:1)
+filter(df, x == 1)
+#> # A tibble: 1 × 2
+#>       x     y
+#>   <int> <int>
+#> 1     1     3
    +

    Is not equivalent to this code:

    +
    my_var <- x
+#> Error in eval(expr, envir, enclos): object 'x' not found
+filter(df, var == 1)
+#> Error in filter_impl(.data, quo): comparison (1) is possible only for atomic and list types
    +

    nor to this code:

    +
    my_var <- "x"
+filter(df, my_var == 1)
+#> # A tibble: 0 × 2
+#> # ... with 2 variables: x <int>, y <int>
    +

    This makes it hard to create functions with arguments that change how dplyr verbs are computed.

    +
    • +
  • +

    dplyr code is ambiguous. Depending on what variables are defined where, filter(df, x == y) could be equivalent to any of:

    +
    df[df$x == df$y, ]
+df[df$x == y, ]
+df[x == df$y, ]
+df[x == y, ]
    +

    This is useful when working interactively (because it saves typing and you quickly spot problems) but makes functions more unpredictable than you might desire.

    +
    • +
+

Fortunately, dplyr provides tools to overcome these challenges. They require a little more typing, but a small amount of upfront work is worth it because they help you save time in the long run.

+

This vignette has two goals:

+
    +

  • Show you how to use dplyr’s pronouns and quasiquotation to write reliable functions that reduce duplication in your data analysis code.

    • +

  • To teach you the underlying theory including quosures, the data structure that stores both an expression and an environment, and and tidyeval, the underlying toolkit.

    • +
+

We’ll start with a warmup, tying this problem to something you’re more familiar with, then move on to some practical tools, then dive into the deeper theory.

+
+

+Warm up

+

You might not have realised it, but you’re already accomplished at solving this type of problem in another domain: strings. It’s obvious that this function doesn’t do what you want:

+
greet <- function(name) {
+  "How do you do, name?"
+}
+greet("Hadley")
+#> [1] "How do you do, name?"
+

That’s because " “quotes” its input: it doesn’t interpret what you’ve typed, it just stores it in a string. One way to make the function do what you want is to use paste() to build up the string piece by piece:

+
greet <- function(name) {
+  paste0("How do you do, ", name, "?")
+}
+greet("Hadley")
+#> [1] "How do you do, Hadley?"
+

Another approach is exemplified by the glue package: it allows you to “unquote” components of a string, replacing the string, with the value of the R expression. This allows an elegant implementation of our function because {name} is replaced with the value of the name argument.

+
greet <- function(name) {
+  glue::glue("How do you do, {name}?")
+}
+greet("Hadley")
+#> How do you do, Hadley?
+
+
+

+Programming recipes

+

The following recipes walk you through the basics of tidyeval, with the nominal goal of reducing duplication in dplyr code. The examples here are somewhat inauthentic because we’ve reduced them down to very simple components to make them easier to understand. They’re so simple that you might wonder why we bother writing a function at all. But it’s a good idea to learn the ideas on simple examples, so that you’re better prepared to apply them to the more complex situations you’ll see in your own code.

+
+

+Different data sets

+

You already know how to write functions that work with the first argument of dplyr verbs: the data. That’s because dplyr doesn’t do anything special with that argument, so it’s referentially transparent. For example, if you saw repeated code like this:

+
mutate(df1, y = a + x)
+mutate(df2, y = a + x)
+mutate(df3, y = a + x)
+mutate(df4, y = a + x)
+

You could already write a function to capture that duplication:

+
mutate_y <- function(df) {
+  mutate(df, y = a + x)
+}
+

Unfortunately, there’s a drawback to this simple approach: it can fail silently if one of the variables isn’t present in the data frame, but is present in the global environment.

+
df1 <- tibble(x = 1:3)
+a <- 10
+mutate_y(df1)
+#> # A tibble: 3 × 2
+#>       x     y
+#>   <int> <dbl>
+#> 1     1    11
+#> 2     2    12
+#> 3     3    13
+

We can fix that ambiguity by being more explicit and using the .data pronoun. This will throw an informative error if the variable doesn’t exist:

+
mutate_y <- function(df) {
+  mutate(df, y = .data$a + .data$x)
+}
+
+mutate_y(df1)
+#> Error in mutate_impl(.data, dots): incompatible size (0), expecting 3 (the number of rows) or one
+# Before dplyr is released, this will give a nice error message
+

If this function is in a package, using .data also prevents R CMD check from giving a NOTE about undefined global variables (provided that you’ve also imported rlang::.data with @importFrom rlang .data).

+
+
+

+Different expressions

+

Writing a function is hard if you want one of the arguments to be a variable name (like x) or an expression (like x + y). That’s because dplyr automatically “quotes” those inputs, so they are not referentially transparent. Let’s start with a simple case: you want to vary the grouping variable for a data summarization.

+
df <- tibble(
+  g1 = c(1, 1, 2, 2, 2),
+  g2 = c(1, 2, 1, 2, 1),
+  a = sample(5), 
+  b = sample(5)
+)
+
+df %>%
+  group_by(g1) %>%
+  summarise(a = mean(a))
+#> # A tibble: 2 × 2
+#>      g1        a
+#>   <dbl>    <dbl>
+#> 1     1 4.000000
+#> 2     2 2.333333
+
+df %>%
+  group_by(g2) %>%
+  summarise(a = mean(a))
+#> # A tibble: 2 × 2
+#>      g2     a
+#>   <dbl> <dbl>
+#> 1     1   2.0
+#> 2     2   4.5
+

You might hope that this will work:

+
my_summarise <- function(df, group_var) {
+  df %>%
+    group_by(group_var) %>%
+    summarise(a = mean(a))
+}
+
+my_summarise(df, g1)
+#> Error in grouped_df_impl(data, unname(vars), drop): unknown column 'group_var'
+

But it doesn’t.

+

Maybe providing the variable name as a string will fix things?

+
my_summarise(df, "g2")
+#> Error in grouped_df_impl(data, unname(vars), drop): unknown column 'group_var'
+

Nope.

+

If you look carefully at the error message, you’ll see that it’s the same in both cases. group_by() works like to ": it doesn’t evaluate its input; it quotes it.

+

To make this function work, we need to do two things. We need to quote the input ourselves (so my_summarise() can take a bare variable name like group_by), and then we need to tell group_by() not to quote its input (because we’ve done the quoting).

+

How do we quote the input? We can’t use "" to quote the input, because that gives us a string. Instead we need a function that captures the expression and its environment (we’ll come back to why this is important later on). There are two possible options we could use in base R, the function quote() and the operator ~. Neither of these work quite the way we want, so we need a new function: quo().

+

quo() works like ": it quotes its input rather than evaluating it.

+
quo(g1)
+#> ~g1
+#> <environment: 0x7fa6d189eca0>
+quo(a + b + c)
+#> ~a + b + c
+#> <environment: 0x7fa6d189eca0>
+quo("a")
+#> ~"a"
+#> <environment: R_EmptyEnv>
+

quo() returns a quosure, which is a special type of formula. You’ll learn more about quosures later on.

+

Now that we’ve captured this expression, how do we use it with group_by()? It doesn’t work if we just shove it into our naive approach:

+
my_summarise(df, quo(g1))
+#> Error in grouped_df_impl(data, unname(vars), drop): unknown column 'group_var'
+

We get the same error as before, because we haven’t yet told group_by() that we’re taking care of the quoting. In other words, we need to tell group_by() not to quote its input, because it has been pre-quoted by my_summarise(). Yet another way of saying the same thing is that we want to unquotethemy_var`.

+

In dplyr (and in the tidyeval in general) you use !! to say that you want to unquote an input so that it’s evaluated, not quoted. This gives us a funtion that actually does what we want.

+
my_summarise <- function(df, group_var) {
+  df %>%
+    group_by(!!group_var) %>%
+    summarise(a = mean(a))
+}
+
+my_summarise(df, quo(g1))
+#> # A tibble: 2 × 2
+#>      g1        a
+#>   <dbl>    <dbl>
+#> 1     1 4.000000
+#> 2     2 2.333333
+

Huzzah!

+

There’s just one step left: we want to call this function like we call group_by():

+
my_summarise(df, g1)
+

This doesn’t work because there’s no object called g1. We need to capture what the user of the function typed and quote it for them. You might try using quo() to do that:

+
my_summarise <- function(df, group_by) {
+  quo_group_by <- quo(group_by)
+  print(quo_group_by)
+
+  df %>%
+    group_by(!!quo_group_by) %>%
+    summarise(a = mean(a))
+}
+
+my_summarise(df, g1)
+#> ~group_by
+#> <environment: 0x7fa6d27db990>
+#> Error in function_list[[i]](value): object 'g1' not found
+

I’ve added a print() call to make it obvious what’s going wrong here: quo(group_by) always returns ~group_by. It is being too literal! We want it to substitute the value that the user supplied, i.e. to return ~g1.

+

By analogy to strings, we don’t want "", instead we want some function that turns an argument into a string. That’s the job of enquo(). enquo() uses some dark magic too look at the argument, see what the user typed, and return that value as a quosure. (Technically, this works because function arguments are evaluated lazily, using a special data structure called a promise.)

+
my_summarise <- function(df, group_by) {
+  group_by <- enquo(group_by)
+  print(group_by)
+
+  df %>%
+    group_by(!!group_by) %>%
+    summarise(a = mean(a))
+}
+
+my_summarise(df, g1)
+#> ~g1
+#> <environment: 0x7fa6d189eca0>
+#> # A tibble: 2 × 2
+#>      g1        a
+#>   <dbl>    <dbl>
+#> 1     1 4.000000
+#> 2     2 2.333333
+

(If you’re familiar with quote() and substitute() in base R, quo() is equivalent to quote() and enquo() is equivalent to substitute().)

+

You might wonder how to extend this to handle multiple grouping variables: we’ll come back to that a little later.

+
+
+

+Different input variable

+

Now let’s tackle something a bit more complicated. The code below shows a duplicate summarise() statement where we compute three summaries, varying the input variable.

+
summarise(df, mean = mean(a), sum = sum(a), n = n())
+#> # A tibble: 1 × 3
+#>    mean   sum     n
+#>   <dbl> <int> <int>
+#> 1     3    15     5
+summarise(df, mean = mean(a * b), sum = sum(a * b), n = n())
+#> # A tibble: 1 × 3
+#>    mean   sum     n
+#>   <dbl> <int> <int>
+#> 1   9.2    46     5
+

To turn this into a function, we start by testing the basic approach interactively: we quote the variable with quo(), then unquoting it in the dplyr call with !!. Notice that we can unquote anywhere inside a complicated expression.

+
my_var <- quo(a)
+summarise(df, mean = mean(!!my_var), sum = sum(!!my_var), n = n())
+#> # A tibble: 1 × 3
+#>    mean   sum     n
+#>   <dbl> <int> <int>
+#> 1     3    15     5
+

You can also wrap quo() around the dplyr call to see what will happen from dplyr’s perspective. This is a very useful tool for debugging.

+
quo(summarise(df, 
+  mean = mean(!!my_var),
+  sum = sum(!!my_var),
+  n = n()
+))
+#> ~summarise(df, mean = mean(~a), sum = sum(~a), n = n())
+#> <environment: 0x7fa6d189eca0>
+

Now we can turn our code into a function (remembering to replace quo() with enquo()), and check that it works:

+
my_summarise2 <- function(df, expr) {
+  expr <- enquo(expr)
+  
+  summarise(df, 
+    mean = mean(!!expr),
+    sum = sum(!!expr),
+    n = n()
+  )
+}
+my_summarise2(df, a)
+#> # A tibble: 1 × 3
+#>    mean   sum     n
+#>   <dbl> <int> <int>
+#> 1     3    15     5
+my_summarise2(df, a * b)
+#> # A tibble: 1 × 3
+#>    mean   sum     n
+#>   <dbl> <int> <int>
+#> 1   9.2    46     5
+
+
+

+Different input and output variable

+

The next challenge is to vary the name of the output variables:

+
mutate(df, mean_a = mean(a), sum_a = sum(a))
+#> # A tibble: 5 × 6
+#>      g1    g2     a     b mean_a sum_a
+#>   <dbl> <dbl> <int> <int>  <dbl> <int>
+#> 1     1     1     3     3      3    15
+#> 2     1     2     5     2      3    15
+#> 3     2     1     2     5      3    15
+#> 4     2     2     4     4      3    15
+#> # ... with 1 more rows
+mutate(df, mean_b = mean(b), sum_b = sum(b))
+#> # A tibble: 5 × 6
+#>      g1    g2     a     b mean_b sum_b
+#>   <dbl> <dbl> <int> <int>  <dbl> <int>
+#> 1     1     1     3     3      3    15
+#> 2     1     2     5     2      3    15
+#> 3     2     1     2     5      3    15
+#> 4     2     2     4     4      3    15
+#> # ... with 1 more rows
+

This code is similar to the previous example, but there are two new wrinkles:

+
    +

  • We create the new names by pasting together strings, so we need quo_name() to convert the input expression to a string.

    • +

  • !!mean_name = mean(!!expr) isn’t valid R code, so we need to use the := helper provided by rlang.

    • +
+
my_mutate <- function(df, expr) {
+  expr <- enquo(expr)
+  mean_name <- paste0("mean_", quo_name(expr))
+  sum_name <- paste0("sum_", quo_name(expr))
+  
+  mutate(df, 
+    !!mean_name := mean(!!expr), 
+    !!sum_name := sum(!!expr)
+  )
+}
+
+my_mutate(df, a)
+#> # A tibble: 5 × 6
+#>      g1    g2     a     b mean_a sum_a
+#>   <dbl> <dbl> <int> <int>  <dbl> <int>
+#> 1     1     1     3     3      3    15
+#> 2     1     2     5     2      3    15
+#> 3     2     1     2     5      3    15
+#> 4     2     2     4     4      3    15
+#> # ... with 1 more rows
+
+
+

+Capturing multiple variables

+

It would be nice to extend my_summarise() to accept any number of grouping variables. We need to make three changes:

+
    +

  • Use ... in the function definition so our function can accept any number of arguments.

    • +

  • Use quos() to capture all the ... as a list of formulas.

    • +

  • Use !!! instead of !! to splice the arguments into group_by().

    • +
+
my_summarise <- function(df, ...) {
+  group_by <- quos(...)
+
+  df %>%
+    group_by(!!!group_by) %>%
+    summarise(a = mean(a))
+}
+
+my_summarise(df, g1, g2)
+#> Source: local data frame [c(1, 1, 2, 2) x c(1, 2, 1, 2) x c(3, 5, 1.5, 4)]
+#> Groups: g1 [?]
+#> 
+#>      g1    g2     a
+#>   <dbl> <dbl> <dbl>
+#> 1     1     1   3.0
+#> 2     1     2   5.0
+#> 3     2     1   1.5
+#> 4     2     2   4.0
+

!!! takes a list of elements and splices them into to the current call. Look at the bottom of the !!! and think ....

+
args <- list(na.rm = TRUE, trim = 0.25)
+quo(mean(x, !!! args))
+#> ~mean(x, na.rm = TRUE, trim = 0.25)
+#> <environment: 0x7fa6d189eca0>
+
+args <- list(quo(x), na.rm = TRUE, trim = 0.25)
+quo(mean(!!! args))
+#> ~mean(~x, na.rm = TRUE, trim = 0.25)
+#> <environment: 0x7fa6d189eca0>
+

Now that you’ve learned the basics of tidyeval through some practical examples, we’ll dive into the theory. This will help you generalise what you’ve learned here to new situations.

+
+
+
+

+Quoting

+

Quoting is the action of capturing an expression instead of evaluating it. All expression-based functions quote their arguments and get the R code as an expression rather than the result of evaluating that code. If you are an R user, you probably quote expressions on a regular basis. One of the most important quoting operators in R is the formula. It is famously used for the specification of statistical models:

+
disp ~ cyl + drat
+#> disp ~ cyl + drat
+#> <environment: 0x7fa6d189eca0>
+

The other quoting operator in base R is quote(). It returns a raw expression rather than a formula:

+
# Computing the value of the expression:
+toupper(letters[1:5])
+#> [1] "A" "B" "C" "D" "E"
+
+# Capturing the expression:
+quote(toupper(letters[1:5]))
+#> toupper(letters[1:5])
+

(Note that despite being called the double quote, " is not a quoting operator in this context, because it generates a string, not an expression.)

+

In practice, the formula is the better of the two options because captures the code and its execution environment. This important because even simple expression can yield different values in different environments. For example, the x in the following two expressions refers to different values:

+
f <- function(x) {
+  ~ x
+}
+
+x1 <- f(10)
+x2 <- f(100)
+

It might look like the expressions are the same if you print them out. But look carefully at the environments — they’re different.

+
x1
+#> ~x
+#> <environment: 0x7fa6d2835238>
+x2
+#> ~x
+#> <environment: 0x7fa6d288c8b0>
+

When we evaluate those formulas using rlang::eval_tidy(), we see that they yield different values:

+
library(rlang)
+
+eval_tidy(x1)
+#> [1] 10
+eval_tidy(x2)
+#> [1] 100
+

This is a key property of R: one name can refer to different values in different environments. This is also important for dplyr, because it allows you to combine variables and objects in a call:

+
user_var <- 1000
+mtcars %>% summarise(cyl = mean(cyl) * user_var)
+#>      cyl
+#> 1 6187.5
+

When an object keep tracks of an environment, it is said to have an enclosure. This is the reason that functions in R are sometimes referred to as closures:

+
typeof(mean)
+#> [1] "closure"
+

For this reason we use a special name to refer to one-sided formulas: quosures. One-sided formulas are quotes (they carry an expression) with an environment.

+

Quosures are regular R objects. They can be stored in a variable and inspected:

+
var <- ~toupper(letters[1:5])
+var
+#> ~toupper(letters[1:5])
+#> <environment: 0x7fa6d189eca0>
+
+# You can extract its expression:
+get_expr(var)
+#> toupper(letters[1:5])
+
+# Or inspect its enclosure:
+get_env(var)
+#> <environment: 0x7fa6d189eca0>
+
+
+

+Quasiquotation

+
+

Put simply, quasi-quotation enables one to introduce symbols that stand for a linguistic expression in a given instance and are used as that linguistic expression in a different instance. — Willard van Orman Quine

+
+

Automatic quoting makes dplyr very convenient for interactive use. But if you want to program with dplyr, you need some way to refer to variables indirectly. The solution to this problem is quasiquotation, which allows you to evaluate directly inside an expression that is otherwise quoted.

+

Quasiquotation was coined by Willard van Orman Quine in the 1940s, and was adopted for programming by the LISP community in the 1970s. All expression-based functions in the tidyeval framework support quasiquotation. Unquoting cancels quotation of parts of an expression. There are three types of unquoting:

+
    +
  • basic
    • +
  • unquote splicing
    • +
  • unquoting names
    • +
+
+

+Unquoting

+

The first important operation is the basic unquote, which comes in a functional form, UQ(), and as syntactic-sugar, !!.

+
# Here we capture `letters[1:5]` as an expression:
+quo(toupper(letters[1:5]))
+#> ~toupper(letters[1:5])
+#> <environment: 0x7fa6d189eca0>
+
+# Here we capture the value of `letters[1:5]`
+quo(toupper(!!letters[1:5]))
+#> ~toupper(c("a", "b", "c", "d", "e"))
+#> <environment: 0x7fa6d189eca0>
+quo(toupper(UQ(letters[1:5])))
+#> ~toupper(c("a", "b", "c", "d", "e"))
+#> <environment: 0x7fa6d189eca0>
+

It is also possible to unquote other quoted expressions. Unquoting such symbolic objects provides a powerful a way of manipulating expressions.

+
var1 <- quo(letters[1:5])
+quo(toupper(!!var1))
+#> ~toupper(~letters[1:5])
+#> <environment: 0x7fa6d189eca0>
+

You can safely unquote quosures because they track their environments, and tidyeval functions know how to evaluate them. This allows any depth of quoting and unquoting.

+
my_mutate <- function(x) {
+  mtcars %>%
+    select(cyl) %>%
+    slice(1:4) %>%
+    mutate(cyl2 = cyl + (!! x))
+}
+
+f <- function(x) quo(x)
+expr1 <- f(100)
+expr2 <- f(10)
+
+my_mutate(expr1)
+#> # A tibble: 4 × 2
+#>     cyl  cyl2
+#>   <dbl> <dbl>
+#> 1     6   106
+#> 2     6   106
+#> 3     4   104
+#> 4     6   106
+my_mutate(expr2)
+#> # A tibble: 4 × 2
+#>     cyl  cyl2
+#>   <dbl> <dbl>
+#> 1     6    16
+#> 2     6    16
+#> 3     4    14
+#> 4     6    16
+

The functional form is useful in cases where the precedence of ! causes problems:

+
my_fun <- quo(fun)
+quo(!!my_fun(x, y, z))
+#> Error in (function (x) : could not find function "my_fun"
+quo(UQ(my_fun)(x, y, z))
+#> ~(~fun)(x, y, z)
+#> <environment: 0x7fa6d189eca0>
+
+my_var <- quo(x)
+quo(filter(df, !!my_var == 1))
+#> ~filter(df, FALSE)
+#> <environment: 0x7fa6d189eca0>
+quo(filter(df, UQ(my_var) == 1))
+#> ~filter(df, (~x) == 1)
+#> <environment: 0x7fa6d189eca0>
+

You’ll note above that UQ() yields an quosure containing a formula. That ensures that when the quosure is evaluated, it’ll be looked up in the right environment. In certain code-generation scenarios you just want to use expression and ignore the environment. That’s the job of UQE():

+
quo(UQE(my_fun)(x, y, z))
+#> ~fun(x, y, z)
+#> <environment: 0x7fa6d189eca0>
+quo(filter(df, UQE(my_var) == 1))
+#> ~filter(df, x == 1)
+#> <environment: 0x7fa6d189eca0>
+

UQE() is for expert use only as you’ll have to carefully analyse the environments to ensure that the generated code is correct.

+
+
+

+Unquote-splicing

+

The second unquote operation is unquote-splicing. Its functional form is UQS() and the syntactic shortcut is !!!. It takes a vector and inserts each element of the vector in the surrounding function call:

+
quo(list(!!! letters[1:5]))
+#> ~list("a", "b", "c", "d", "e")
+#> <environment: 0x7fa6d189eca0>
+

A very useful feature of unquote-splicing is that the vector names become argument names:

+
x <- list(foo = 1L, bar = quote(baz))
+quo(list(!!! x))
+#> ~list(foo = 1L, bar = baz)
+#> <environment: 0x7fa6d189eca0>
+

This makes it easy to program with dplyr verbs that take named dots:

+
args <- list(mean = ~mean(cyl), count = ~n())
+mtcars %>%
+  group_by(am) %>%
+  summarise(!!! args)
+#> # A tibble: 2 × 3
+#>      am     mean count
+#>   <dbl>    <dbl> <int>
+#> 1     0 6.947368    19
+#> 2     1 5.076923    13
+
+
+

+Setting variable names

+

The final unquote operation is setting argument names. You’ve seen one way to do that above, but you can also use the definition operator := instead of =. := supports supports unquoting on both the LHS and the RHS.

+

The rules on the LHS are slightly different: the unquoted operand should evaluate to a string or a symbol.

+
mean_nm <- "mean"
+count_nm <- "count"
+
+mtcars %>%
+  group_by(am) %>%
+  summarise(
+    !!mean_nm := mean(cyl),
+    !!count_nm := n()
+  )
+#> # A tibble: 2 × 3
+#>      am     mean count
+#>   <dbl>    <dbl> <int>
+#> 1     0 6.947368    19
+#> 2     1 5.076923    13
+
+
+
+
+ + + +
+ + + +
+ + + diff --git a/docs/articles/rsconnect/documents/programming.Rmd/rpubs.com/rpubs/Document.dcf b/docs/articles/rsconnect/documents/programming.Rmd/rpubs.com/rpubs/Document.dcf new file mode 100644 index 0000000000..954f2739eb --- /dev/null +++ b/docs/articles/rsconnect/documents/programming.Rmd/rpubs.com/rpubs/Document.dcf @@ -0,0 +1,8 @@ +name: Document +title: +account: rpubs +server: rpubs.com +appId: https://api.rpubs.com/api/v1/document/260900/65a13912ccc7477681f11558f48fd975 +bundleId: https://api.rpubs.com/api/v1/document/260900/65a13912ccc7477681f11558f48fd975 +url: http://rpubs.com/publish/claim/260900/d6cb179fa84c4e99aa571f94c6f4610f +when: 1490197062.83402 diff --git a/docs/articles/rsconnect/documents/programming.Rmd/rpubs.com/rpubs/Publish Document.dcf b/docs/articles/rsconnect/documents/programming.Rmd/rpubs.com/rpubs/Publish Document.dcf new file mode 100644 index 0000000000..2c72b02769 --- /dev/null +++ b/docs/articles/rsconnect/documents/programming.Rmd/rpubs.com/rpubs/Publish Document.dcf @@ -0,0 +1,8 @@ +name: Publish Document +title: +account: rpubs +server: rpubs.com +appId: https://api.rpubs.com/api/v1/document/260900/65a13912ccc7477681f11558f48fd975 +bundleId: https://api.rpubs.com/api/v1/document/260900/65a13912ccc7477681f11558f48fd975 +url: http://rpubs.com/hadley/260900 +when: 1490983436.19532 diff --git a/docs/articles/two-table.html b/docs/articles/two-table.html new file mode 100644 index 0000000000..812b569adf --- /dev/null +++ b/docs/articles/two-table.html @@ -0,0 +1,469 @@ + + + + + + + +Two-table verbs • dplyr + + + + + + +
+
+ + + +
+
+
+

Two-table verbs

+ +

2017-04-04

+
+ + + +
+

It’s rare that a data analysis involves only a single table of data. In practice, you’ll normally have many tables that contribute to an analysis, and you need flexible tools to combine them. In dplyr, there are three families of verbs that work with two tables at a time:

+
    +

  • Mutating joins, which add new variables to one table from matching rows in another.

    • +

  • Filtering joins, which filter observations from one table based on whether or not they match an observation in the other table.

    • +

  • Set operations, which combine the observations in the data sets as if they were set elements.

    • +
+

(This discussion assumes that you have tidy data, where the rows are observations and the columns are variables. If you’re not familiar with that framework, I’d recommend reading up on it first.)

+

All two-table verbs work similarly. The first two arguments are x and y, and provide the tables to combine. The output is always a new table with the same type as x.

+
+

+Mutating joins

+

Mutating joins allow you to combine variables from multiple tables. For example, take the nycflights13 data. In one table we have flight information with an abbreviation for carrier, and in another we have a mapping between abbreviations and full names. You can use a join to add the carrier names to the flight data:

+
library("nycflights13")
+# Drop unimportant variables so it's easier to understand the join results.
+flights2 <- flights %>% select(year:day, hour, origin, dest, tailnum, carrier)
+
+flights2 %>% 
+  left_join(airlines)
+#> Joining, by = "carrier"
+#> # A tibble: 336,776 × 9
+#>    year month   day  hour origin  dest tailnum carrier
+#>   <int> <int> <int> <dbl>  <chr> <chr>   <chr>   <chr>
+#> 1  2013     1     1     5    EWR   IAH  N14228      UA
+#> 2  2013     1     1     5    LGA   IAH  N24211      UA
+#> 3  2013     1     1     5    JFK   MIA  N619AA      AA
+#> 4  2013     1     1     5    JFK   BQN  N804JB      B6
+#> 5  2013     1     1     6    LGA   ATL  N668DN      DL
+#> # ... with 3.368e+05 more rows, and 1 more variables: name <chr>
+
+

+Controlling how the tables are matched

+

As well as x and y, each mutating join takes an argument by that controls which variables are used to match observations in the two tables. There are a few ways to specify it, as I illustrate below with various tables from nycflights13:

+
    +
  • +

    NULL, the default. dplyr will will use all variables that appear in both tables, a natural join. For example, the flights and weather tables match on their common variables: year, month, day, hour and origin.

    +
    flights2 %>% left_join(weather)
+#> Joining, by = c("year", "month", "day", "hour", "origin")
+#> # A tibble: 336,776 × 18
+#>    year month   day  hour origin  dest tailnum carrier  temp  dewp humid
+#>   <dbl> <dbl> <int> <dbl>  <chr> <chr>   <chr>   <chr> <dbl> <dbl> <dbl>
+#> 1  2013     1     1     5    EWR   IAH  N14228      UA    NA    NA    NA
+#> 2  2013     1     1     5    LGA   IAH  N24211      UA    NA    NA    NA
+#> 3  2013     1     1     5    JFK   MIA  N619AA      AA    NA    NA    NA
+#> 4  2013     1     1     5    JFK   BQN  N804JB      B6    NA    NA    NA
+#> 5  2013     1     1     6    LGA   ATL  N668DN      DL 39.92 26.06 57.33
+#> # ... with 3.368e+05 more rows, and 7 more variables: wind_dir <dbl>,
+#> #   wind_speed <dbl>, wind_gust <dbl>, precip <dbl>, pressure <dbl>,
+#> #   visib <dbl>, time_hour <dttm>
    +
    • +
  • +

    A character vector, by = "x". Like a natural join, but uses only some of the common variables. For example, flights and planes have year columns, but they mean different things so we only want to join by tailnum.

    +
    flights2 %>% left_join(planes, by = "tailnum")
+#> # A tibble: 336,776 × 16
+#>   year.x month   day  hour origin  dest tailnum carrier year.y
+#>    <int> <int> <int> <dbl>  <chr> <chr>   <chr>   <chr>  <int>
+#> 1   2013     1     1     5    EWR   IAH  N14228      UA   1999
+#> 2   2013     1     1     5    LGA   IAH  N24211      UA   1998
+#> 3   2013     1     1     5    JFK   MIA  N619AA      AA   1990
+#> 4   2013     1     1     5    JFK   BQN  N804JB      B6   2012
+#> 5   2013     1     1     6    LGA   ATL  N668DN      DL   1991
+#> # ... with 3.368e+05 more rows, and 7 more variables: type <chr>,
+#> #   manufacturer <chr>, model <chr>, engines <int>, seats <int>,
+#> #   speed <int>, engine <chr>
    +

    Note that the year columns in the output are disambiguated with a suffix.

    +
    • +
  • +

    A named character vector: by = c("x" = "a"). This will match variable x in table x to variable a in table b. The variables from use will be used in the output.

    +

    Each flight has an origin and destination airport, so we need to specify which one we want to join to:

    +
    flights2 %>% left_join(airports, c("dest" = "faa"))
+#> # A tibble: 336,776 × 15
+#>    year month   day  hour origin  dest tailnum carrier
+#>   <int> <int> <int> <dbl>  <chr> <chr>   <chr>   <chr>
+#> 1  2013     1     1     5    EWR   IAH  N14228      UA
+#> 2  2013     1     1     5    LGA   IAH  N24211      UA
+#> 3  2013     1     1     5    JFK   MIA  N619AA      AA
+#> 4  2013     1     1     5    JFK   BQN  N804JB      B6
+#> 5  2013     1     1     6    LGA   ATL  N668DN      DL
+#> # ... with 3.368e+05 more rows, and 7 more variables: name <chr>,
+#> #   lat <dbl>, lon <dbl>, alt <int>, tz <dbl>, dst <chr>, tzone <chr>
+flights2 %>% left_join(airports, c("origin" = "faa"))
+#> # A tibble: 336,776 × 15
+#>    year month   day  hour origin  dest tailnum carrier                name
+#>   <int> <int> <int> <dbl>  <chr> <chr>   <chr>   <chr>               <chr>
+#> 1  2013     1     1     5    EWR   IAH  N14228      UA Newark Liberty Intl
+#> 2  2013     1     1     5    LGA   IAH  N24211      UA          La Guardia
+#> 3  2013     1     1     5    JFK   MIA  N619AA      AA John F Kennedy Intl
+#> 4  2013     1     1     5    JFK   BQN  N804JB      B6 John F Kennedy Intl
+#> 5  2013     1     1     6    LGA   ATL  N668DN      DL          La Guardia
+#> # ... with 3.368e+05 more rows, and 6 more variables: lat <dbl>,
+#> #   lon <dbl>, alt <int>, tz <dbl>, dst <chr>, tzone <chr>
    +
    • +
+
+
+

+Types of join

+

There are four types of mutating join, which differ in their behaviour when a match is not found. We’ll illustrate each with a simple example:

+
(df1 <- data_frame(x = c(1, 2), y = 2:1))
+#> # A tibble: 2 × 2
+#>       x     y
+#>   <dbl> <int>
+#> 1     1     2
+#> 2     2     1
+(df2 <- data_frame(x = c(1, 3), a = 10, b = "a"))
+#> # A tibble: 2 × 3
+#>       x     a     b
+#>   <dbl> <dbl> <chr>
+#> 1     1    10     a
+#> 2     3    10     a
+
    +
  • +

    inner_join(x, y) only includes observations that match in both x and y.

    +
    df1 %>% inner_join(df2) %>% knitr::kable()
+#> Joining, by = "x"
    + + + + + + + + + + + + + +
    xyab
    1210a
    +
    • +
  • +

    left_join(x, y) includes all observations in x, regardless of whether they match or not. This is the most commonly used join because it ensures that you don’t lose observations from your primary table.

    +
    df1 %>% left_join(df2)
+#> Joining, by = "x"
+#> # A tibble: 2 × 4
+#>       x     y     a     b
+#>   <dbl> <int> <dbl> <chr>
+#> 1     1     2    10     a
+#> 2     2     1    NA  <NA>
    +
    • +
  • +

    right_join(x, y) includes all observations in y. It’s equivalent to left_join(y, x), but the columns will be ordered differently.

    +
    df1 %>% right_join(df2)
+#> Joining, by = "x"
+#> # A tibble: 2 × 4
+#>       x     y     a     b
+#>   <dbl> <int> <dbl> <chr>
+#> 1     1     2    10     a
+#> 2     3    NA    10     a
+df2 %>% left_join(df1)
+#> Joining, by = "x"
+#> # A tibble: 2 × 4
+#>       x     a     b     y
+#>   <dbl> <dbl> <chr> <int>
+#> 1     1    10     a     2
+#> 2     3    10     a    NA
    +
    • +
  • +

    full_join() includes all observations from x and y.

    +
    df1 %>% full_join(df2)
+#> Joining, by = "x"
+#> # A tibble: 3 × 4
+#>       x     y     a     b
+#>   <dbl> <int> <dbl> <chr>
+#> 1     1     2    10     a
+#> 2     2     1    NA  <NA>
+#> 3     3    NA    10     a
    +
    • +
+

The left, right and full joins are collectively know as outer joins. When a row doesn’t match in an outer join, the new variables are filled in with missing values.

+
+
+

+Observations

+

While mutating joins are primarily used to add new variables, they can also generate new observations. If a match is not unique, a join will add all possible combinations (the Cartesian product) of the matching observations:

+
df1 <- data_frame(x = c(1, 1, 2), y = 1:3)
+df2 <- data_frame(x = c(1, 1, 2), z = c("a", "b", "a"))
+
+df1 %>% left_join(df2)
+#> Joining, by = "x"
+#> # A tibble: 5 × 3
+#>       x     y     z
+#>   <dbl> <int> <chr>
+#> 1     1     1     a
+#> 2     1     1     b
+#> 3     1     2     a
+#> 4     1     2     b
+#> 5     2     3     a
+
+
+
+

+Filtering joins

+

Filtering joins match obserations in the same way as mutating joins, but affect the observations, not the variables. There are two types:

+ +

These are most useful for diagnosing join mismatches. For example, there are many flights in the nycflights13 dataset that don’t have a matching tail number in the planes table:

+
library("nycflights13")
+flights %>% 
+  anti_join(planes, by = "tailnum") %>% 
+  count(tailnum, sort = TRUE)
+#> # A tibble: 722 × 2
+#>   tailnum     n
+#>     <chr> <int>
+#> 1    <NA>  2512
+#> 2  N725MQ   575
+#> 3  N722MQ   513
+#> 4  N723MQ   507
+#> 5  N713MQ   483
+#> # ... with 717 more rows
+

If you’re worried about what observations your joins will match, start with a semi_join() or anti_join(). semi_join() and anti_join() never duplicate; they only ever remove observations.

+
df1 <- data_frame(x = c(1, 1, 3, 4), y = 1:4)
+df2 <- data_frame(x = c(1, 1, 2), z = c("a", "b", "a"))
+
+# Four rows to start with:
+df1 %>% nrow()
+#> [1] 4
+# And we get four rows after the join
+df1 %>% inner_join(df2, by = "x") %>% nrow()
+#> [1] 4
+# But only two rows actually match
+df1 %>% semi_join(df2, by = "x") %>% nrow()
+#> [1] 2
+
+
+

+Set operations

+

The final type of two-table verb is set operations. These expect the x and y inputs to have the same variables, and treat the observations like sets:

+ +

Given this simple data:

+
(df1 <- data_frame(x = 1:2, y = c(1L, 1L)))
+#> # A tibble: 2 × 2
+#>       x     y
+#>   <int> <int>
+#> 1     1     1
+#> 2     2     1
+(df2 <- data_frame(x = 1:2, y = 1:2))
+#> # A tibble: 2 × 2
+#>       x     y
+#>   <int> <int>
+#> 1     1     1
+#> 2     2     2
+

The four possibilities are:

+
intersect(df1, df2)
+#> # A tibble: 1 × 2
+#>       x     y
+#>   <int> <int>
+#> 1     1     1
+# Note that we get 3 rows, not 4
+union(df1, df2)
+#> # A tibble: 3 × 2
+#>       x     y
+#>   <int> <int>
+#> 1     2     2
+#> 2     2     1
+#> 3     1     1
+setdiff(df1, df2)
+#> # A tibble: 1 × 2
+#>       x     y
+#>   <int> <int>
+#> 1     2     1
+setdiff(df2, df1)
+#> # A tibble: 1 × 2
+#>       x     y
+#>   <int> <int>
+#> 1     2     2
+
+
+

+Coercion rules

+

When joining tables, dplyr is a little more conservative than base R about the types of variable that it considers equivalent. This is mostly likely to surprise if you’re working factors:

+
    +
  • +

    Factors with different levels are coerced to character with a warning:

    +
    df1 <- data_frame(x = 1, y = factor("a"))
+df2 <- data_frame(x = 2, y = factor("b"))
+full_join(df1, df2) %>% str()
+#> Joining, by = c("x", "y")
+#> Warning in full_join_impl(x, y, by$x, by$y, suffix$x, suffix$y,
+#> accept_na_match): joining factors with different levels, coercing to
+#> character vector
+#> Classes 'tbl_df', 'tbl' and 'data.frame':    2 obs. of  2 variables:
+#>  $ x: num  1 2
+#>  $ y: chr  "a" "b"
+#>  - attr(*, "vars")= chr
    +
    • +
  • +

    Factors with the same levels in a different order are coerced to character with a warning:

    +
    df1 <- data_frame(x = 1, y = factor("a", levels = c("a", "b")))
+df2 <- data_frame(x = 2, y = factor("b", levels = c("b", "a")))
+full_join(df1, df2) %>% str()
+#> Joining, by = c("x", "y")
+#> Warning in full_join_impl(x, y, by$x, by$y, suffix$x, suffix$y,
+#> accept_na_match): joining factors with different levels, coercing to
+#> character vector
+#> Classes 'tbl_df', 'tbl' and 'data.frame':    2 obs. of  2 variables:
+#>  $ x: num  1 2
+#>  $ y: chr  "a" "b"
+#>  - attr(*, "vars")= chr
    +
    • +
  • +

    Factors are preserved only if the levels match exactly:

    +
    df1 <- data_frame(x = 1, y = factor("a", levels = c("a", "b")))
+df2 <- data_frame(x = 2, y = factor("b", levels = c("a", "b")))
+full_join(df1, df2) %>% str()
+#> Joining, by = c("x", "y")
+#> Classes 'tbl_df', 'tbl' and 'data.frame':    2 obs. of  2 variables:
+#>  $ x: num  1 2
+#>  $ y: Factor w/ 2 levels "a","b": 1 2
+#>  - attr(*, "vars")= chr
    +
    • +
  • +

    A factor and a character are coerced to character with a warning:

    +
    df1 <- data_frame(x = 1, y = "a")
+df2 <- data_frame(x = 2, y = factor("a"))
+full_join(df1, df2) %>% str()
+#> Joining, by = c("x", "y")
+#> Warning in full_join_impl(x, y, by$x, by$y, suffix$x, suffix$y,
+#> accept_na_match): joining factor and character vector, coercing into
+#> character vector
+#> Classes 'tbl_df', 'tbl' and 'data.frame':    2 obs. of  2 variables:
+#>  $ x: num  1 2
+#>  $ y: chr  "a" "a"
+#>  - attr(*, "vars")= chr
    +
    • +
+

Otherwise logicals will be silently upcast to integer, and integer to numeric, but coercing to character will raise an error:

+
df1 <- data_frame(x = 1, y = 1L)
+df2 <- data_frame(x = 2, y = 1.5)
+full_join(df1, df2) %>% str()
+#> Joining, by = c("x", "y")
+#> Classes 'tbl_df', 'tbl' and 'data.frame':    2 obs. of  2 variables:
+#>  $ x: num  1 2
+#>  $ y: num  1 1.5
+#>  - attr(*, "vars")= chr
+
+df1 <- data_frame(x = 1, y = 1L)
+df2 <- data_frame(x = 2, y = "a")
+full_join(df1, df2) %>% str()
+#> Joining, by = c("x", "y")
+#> Error in full_join_impl(x, y, by$x, by$y, suffix$x, suffix$y, accept_na_match): Can't join on 'y' x 'y' because of incompatible types (character / integer)
+
+
+

+Multiple-table verbs

+

dplyr does not provide any functions for working with three or more tables. Instead use Reduce(), as described in Advanced R, to iteratively combine the two-table verbs to handle as many tables as you need.

+
+
+
+ + + +
+ + + +
+ + + diff --git a/docs/articles/window-functions.html b/docs/articles/window-functions.html new file mode 100644 index 0000000000..9172620fed --- /dev/null +++ b/docs/articles/window-functions.html @@ -0,0 +1,4219 @@ + + + + + + + +Window functions and grouped mutate/filter • dplyr + + + + + + +
+
+ + + +
+
+
+

Window functions and grouped mutate/filter

+ +

2017-04-04

+
+ + + +
+

A window function is a variation on an aggregation function. Where an aggregation function, like sum() and mean(), takes n inputs and return a single value, a window function returns n values. The output of a window function depends on all its input values, so window functions don’t include functions that work element-wise, like + or round(). Window functions include variations on aggregate functions, like cumsum() and cummean(), functions for ranking and ordering, like rank(), and functions for taking offsets, like lead() and lag().

+

In this vignette, we’ll use a small sample of the Lahman batting dataset, including the players that have won an award.

+
library(Lahman)
+
+batting <- Lahman::Batting %>%
+  as_tibble() %>%
+  select(playerID, yearID, teamID, G, AB:H) %>%
+  arrange(playerID, yearID, teamID) %>%
+  semi_join(Lahman::AwardsPlayers, by = "playerID")
+
+players <- batting %>% group_by(playerID)
+

Window functions are used in conjunction with mutate() and filter() to solve a wide range of problems. Here’s a selection:

+
# For each player, find the two years with most hits
+filter(players, min_rank(desc(H)) <= 2 & H > 0)
+# Within each player, rank each year by the number of games played
+mutate(players, G_rank = min_rank(G))
+
+# For each player, find every year that was better than the previous year
+filter(players, G > lag(G))
+# For each player, compute avg change in games played per year
+mutate(players, G_change = (G - lag(G)) / (yearID - lag(yearID)))
+
+# For each player, find all where they played more games than average
+filter(players, G > mean(G))
+# For each, player compute a z score based on number of games played
+mutate(players, G_z = (G - mean(G)) / sd(G))
+

Before reading this vignette, you should be familiar with mutate() and filter(). If you want to use window functions with SQL databases, you should also be familiar with the basics of dplyr’s SQL translation.

+
+

+Types of window functions

+

There are five main families of window functions. Two families are unrelated to aggregation functions:

+
    +

  • Ranking and ordering functions: row_number(), min_rank (RANK in SQL), dense_rank(), cume_dist(), percent_rank(), and ntile(). These functions all take a vector to order by, and return various types of ranks.

    • +

  • Offsets lead() and lag() allow you to access the previous and next values in a vector, making it easy to compute differences and trends.

    • +
+

The other three families are variations on familiar aggregate functions:

+
    +

  • Cumulative aggregates: cumsum(), cummin(), cummax() (from base R), and cumall(), cumany(), and cummean() (from dplyr).

    • +

  • Rolling aggregates operate in a fixed width window. You won’t find them in base R or in dplyr, but there are many implementations in other packages, such as RcppRoll.

    • +

  • Recycled aggregates, where an aggregate is repeated to match the length of the input. These are not needed in R because vector recycling automatically recycles aggregates where needed. They are important in SQL, because the presence of an aggregation function usually tells the database to return only one row per group.

    • +
+

Each family is described in more detail below, focussing on the general goals and how to use them with dplyr. For more details, refer to the individual function documentation.

+
+
+

+Ranking functions

+

The ranking functions are variations on a theme, differing in how they handle ties:

+
x <- c(1, 1, 2, 2, 2)
+
+row_number(x)
+#> [1] 1 2 3 4 5
+min_rank(x)
+#> [1] 1 1 3 3 3
+dense_rank(x)
+#> [1] 1 1 2 2 2
+

If you’re familiar with R, you may recognise that row_number() and min_rank() can be computed with the base rank() function and various values of the ties.method argument. These functions are provided to save a little typing, and to make it easier to convert between R and SQL.

+

Two other ranking functions return numbers between 0 and 1. percent_rank() gives the percentage of the rank; cume_dist() gives the proportion of values less than or equal to the current value.

+
cume_dist(x)
+#> [1] 0.4 0.4 1.0 1.0 1.0
+percent_rank(x)
+#> [1] 0.0 0.0 0.5 0.5 0.5
+

These are useful if you want to select (for example) the top 10% of records within each group. For example:

+
filter(players, cume_dist(desc(G)) < 0.1)
+#> Source: local data frame [c("bondto01", "hinespa01", "hinespa01", "radboch01", "keefeti01", "clarkjo01", "duffyhu01", "youngcy01", "lajoina01", "lajoina01", "mathech01", "chaseha01", "crigelo01", "sullibi03", "crawfsa01", "walshed01", "donovbi01", "cobbty01", "cobbty01", "wallabo01", "wallabo01", "bresnro01", "klingjo01", "donlimi01", "clarkfr01", "clarkfr01", "brownmo01", "wagneho01", "tennefr02", "eversjo01", "reulbed01", "schulfr01", "collied01", "speaktr01", "speaktr01", "planked01", "johnswa01", "johnswa01", "mullige01", 
+#> "woodjo02", "gibsoge01", "adamsba01", "chancfr01", "leachto01", "hofmaso01", "coombja01", "bendech01", "archeji01", "mageesh01", "bakerfr01", "stanaos01", "jacksjo01", "dooinre01", "alexape01", "daubeja01", "doylela01", "loberha01", "marquru01", "mcinnst01", "gardnla01", "ainsmed01", "wagnehe01", "zimmehe01", "paskedo01", "schanwa01", "falkecy01", "barryja01", "cravaga01", "wheatza01", "schalra01", "leonadu01", "maranra01", "wingoiv01", "burnsge01", "grohhe01", "snydefr01", "bancrda01", "mamaual01", 
+#> "ruthba01", "ruthba01", "herzobu01", "hornsro01", "hornsro01", "gowdyha01", "roberda01", "cicoted01", "killebi01", "roushed01", "careyma01", "oneilst01", "hoopeha01", "vaughhi01", "grimebu01", "grimebu01", "peckiro01", "stockmi01", "myershy01", "barneje01", "ricesa01", "covelst01", "shockur01", "scottev01", "faberre01", "maysca01", "kellyge01", "bigbeca01", "nehfar01", "duganjo01", "bushjo01", "rommeed01", "rixeyep01", "rixeyep01", "ruethdu01", "heilmha01", "ehmkeho01", "grimmch01", "ofarrbo01", 
+#> "ofarrbo01", "luquedo01", "vanceda01", "judgejo01", "judgejo01", "jamiech01", "pennohe01", "jackstr01", "traynpi01", "hartnga01", "bluegos01", "ruelmu01", "cochrmi01", "simmoal01", "simmoal01", "gosligo01", "lyonste01", "lyonste01", "cuyleki01", "bottoji01", "smithea02", "donohpe01", "burnsge02", "kammwi01", "manushe01", "grovele01", "wilsoha01", "lazzeto01", "hoytwa01", "thomato02", "rootch01", "haineje01", "wanerpa01", "wilsoji01", "wanerll01", "wanerll01", "crowdal01", "bentola01", "hafeych01", 
+#> "lindsfr01", "fonsele01", "dykesji01", "dykesji01", "combsea01", "earnsge01", "ferrewe01", "kressre01", "lucasre01", "hubbeca01", "odoulle01", "foxxji01", "foxxji01", "averiea01", "cronijo01", "hallabi01", "melilsk01", "walberu01", "branded01", "derripa01", "fitzsfr01", "kleinch01", "gomezle01", "warnelo01", "hermabi01", "clarkwa02", "deandi01", "bartedi01", "dickebi01", "higgipi01", "westsa01", "whiteea01", "bridgto01", "bergewa01", "lopezal01", "medwijo01", "cantwbe01", "werbebi01", "rowesc01", 
+#> "ottme01", "ottme01", "moorejo02", "schumha02", "greenha01", "vosmijo01", "foxpe01", "martipe01", "dimagjo01", "kenneve01", "allenjo02", "moseswa01", "applilu01", "hackst01", "suhrgu01", "frencla01", "mizejo01", "ruffire01", "ruffire01", "hemslro01", "hemslro01", "heathje01", "newsobo01", "newsobo01", "vandejo01", "mccorfr01", "lombaer01", "leebi02", "gordojo01", "johnsbo01", "fellebo01", "willite01", "waltebu01", "waltebu01", "daviscu01", "freylo01", "cliftha01", "hayesfr01", "kellech01", "nichobi01", 
+#> "milleed03", "leeth01", "travice01", "camildo01", "wyattwh01", "higbeki01", "slaugen01", "slaugen01", "jurgebi01", "keltnke01", "chandsp01", "coopemo01", "marioma01", "owenmi01", "peskyjo01", "troutdi01", "smithal03", "sewelri01", "coopewa01", "coopewa01", "dimagvi01", "stirnsn01", "newhoha01", "elliobo01", "doerrbo01", "gromest01", "cullero01", "cavarph01", "cavarph01", "pafkoan01", "brechha01", "borowha01", "holmeto01", "barrere01", "vernomi01", "vernomi01", "kellge01", "boudrlo01", "polleho01", 
+#> "stanked01", "mcculcl01", "ennisde01", "sainjo01", "reesepe01", "dimagdo01", "mcquige02", "reynoal01", "henrito01", "edwarbr01", "blackew01", "kinerra01", "spahnwa01", "spahnwa01", "marshwi01", "tebbebi01", "lemonbo01", "raschvi01", "masiph01", "schmijo01", "darkal01", "michaca01", "wertzvi01", "wertzvi01", "hodgegi01", "gordosi01", "newcodo01", "kindeel01", "rizzuph01", "dropowa01", "houttar01", "konstji01", "furilca01", "snidedu01", "hamnegr01", "dobyla01", "mayswi01", "maglisa01", "roepr01", "shantbo01", 
+#> "sauerha01", "roberro01", "roberro01", "martibi02", "gilliji01", "schoere01", "schoere01", "grimbo01", "moonwa01", "kluszte01", "avilabo01", "antonjo02", "podrejo01", "virdobi01", "foxne01", "matheed01", "kalinal01", "kalinal01", "bankser01", "larsedo01", "aparilu01", "robinfr02", "boyerke01", "aaronha01", "aaronha01", "piercbi02", "burdele01", "burdele01", "malzofr01", "lollash01", "minosmi01", "mcmilro01", "sanfoja02", "bunniji01", "howarel01", "turlebo01", "bollifr01", "piersji01", "siebeno01", 
+#> "mazerbi01", "crandde01", "haddiha01", "jenseja01", "cepedor01", "thomafr03", "frienbo01", "sherrla01", "wynnea01", "wynnea01", "brandja01", "allisbo01", "mccovwi01", "jonessa02", "lawve01", "robinbr01", "robinbr01", "batteea01", "marisro01", "whitebi03", "hansero02", "skowrbi01", "fornimi01", "mcdanli01", "mcdanli01", "richabo01", "laryfr01", "rosebjo01", "clemero01", "pinsova01", "willsma01", "willibi01", "cashno01", "colavro01", "burgesm01", "jayjo01", "millest01", "wagnele01", "terryra01", "drysddo01", 
+#> "kaatji01", "davenji01", "donovdi01", "davisto02", "davisto02", "purkebo01", "facero01", "koufasa01", "yastrca01", "edwarjo01", "floodcu01", "winebo01", "peterga01", "rosepe01", "rosepe01", "pepitjo01", "maricju01", "callijo01", "gibsobo01", "chancde01", "davalvi01", "santoro01", "amaroru01", "olivato01", "allendi01", "stuardi01", "killeha01", "fregoji01", "huntro01", "mcbeaal01", "cardele01", "hallji02", "grantmu01", "stottme01", "johnsde01", "johnsde01", "stargwi01", "stargwi01", "fisheed02", "abernte02", 
+#> "ageeto01", "alleyge01", "wilsoea01", "aloufe01", "akerja01", "reganph01", "perezto01", "perezto01", "brocklo01", "lonboji01", "mccormi03", "scottge02", "hundlra01", "carewro01", "seaveto01", "mccarti01", "mccarti01", "wynnji01", "jenkife01", "lolicmi01", "mclaide01", "smithre06", "stanlmi01", "beckegl01", "benchjo01", "bahnsst01", "hortowi01", "hortowi01", "woodwi01", "cuellmi01", "johnsda02", "belanma01", "boyercl02", "pinielo01", "sizemte01", "jacksre01", "jacksre01", "petrori01", "carltst01", 
+#> "carltst01", "alouma01", "jonescl01", "perraro01", "clenddo01", "perryji01", "spencji01", "fossera01", "berryke01", "raderdo02", "munsoth01", "mcdowsa01", "merriji01", "bluevi01", "otisam01", "bondsbo01", "daviswi02", "harrebu01", "chambch01", "rojasco01", "murcebo01", "retteme01", "palmeji01", "mayle01", "sanguma01", "sandeke01", "giustda01", "morgajo02", "tenacge01", "perryga01", "perryga01", "fiskca01", "fiskca01", "brinked01", "cedence01", "bowala01", "rudijo01", "scheiri01", "speiech01", "speiech01", 
+#> "lylesp01", "carrocl02", "campabe01", "grichbo01", "jorgemi01", "metzgro01", "hillejo01", "bumbral01", "matthga01", "maybejo01", "holtzke01", "evansda01", "russebi01", "marshmi01", "garvest01", "greendi01", "hunteca01", "geronce01", "messean01", "conceda01", "burroje01", "mcbriba01", "schmimi01", "ziskri01", "forstte01", "fingero01", "madlobi01", "tiantlu01", "lynnfr01", "reitzke01", "maddoga01", "nolanga01", "montejo01", "nettlgr01", "nettlgr01", "riceji01", "harrato01", "oliveal01", "parkeda01", 
+#> "gossari01", "gossari01", "hraboal01", "rodriau01", "sundbji01", "manniri01", "johnto01", "suttodo01", "suttodo01", "campbbi02", "zachrpa01", "brettge01", "brettge01", "mcraeha01", "tananfr01", "rivermi01", "montawi01", "boonebo01", "griffke01", "griffke01", "beniqju01", "cowenal01", "bakerdu01", "murraed02", "dawsoan01", "randowi01", "hislela01", "ryanno01", "ryanno01", "burleri01", "simmote01", "simmote01", "reuscri01", "reuscri01", "templga01", "milleri01", "lopesda01", "valenel01", "niekrph01", 
+#> "niekrph01", "whitalo01", "staubru01", "staubru01", "yountro01", "clarkja01", "flanami01", "suttebr01", "bellbu01", "lezcasi01", "trillma01", "winfida01", "winfida01", "baylodo01", "thornan01", "kernji01", "sutclri01", "porteda02", "singlke01", "smallro02", "kingmda01", "niekrjo01", "niekrjo01", "mcgratu01", "stonest01", "murphdw01", "wilsowi02", "trammal01", "flynndo01", "cartega01", "quiseda01", "howest01", "parrila02", "oglivbe01", "hendrge01", "ceronri01", "bibbyji01", "humeto01", "valenfe01", 
+#> "henderi01", "henderi01", "hootobu01", "lansfca01", "armasto01", "guerrpe01", "yeagest01", "vuckope01", "ripkeca01", "saxst01", "garcida01", "decindo01", "durhale01", "robindo01", "zahnge01", "thomago01", "smithlo01", "boddimi01", "dempsri01", "dempsri01", "dennyjo01", "penato01", "mcgeewi01", "knighra01", "kittlro01", "strawda01", "boggswa01", "mosebll01", "rayjo01", "kennete02", "thondi01", "hubbagl01", "mcwilla01", "raineti01", "smithle02", "smithle02", "gibsoki01", "hernawi01", "andujjo01", "gwynnto01", 
+#> "rhoderi01", "mattido01", "pettiga01", "wallati01", "reardje01", "guilloz01", "colemvi01", "brookhu01", "baineha01", "baineha01", "herrto01", "tudorjo01", "clemero02", "scottmi03", "gaettga01", "gaettga01", "barfije01", "fernato01", "davisjo02", "leonade01", "worreto01", "cansejo01", "bernato01", "gedmari01", "violafr01", "bedrost01", "langsma01", "pendlte01", "lavalmi01", "daviser01", "molitpa01", "leonaje01", "mcgwima01", "santibe01", "samueju01", "keyji01", "eckerde01", "eckerde01", "steinte01", 
+#> "hershor01", "reynoha01", "whitede03", "vanslan01", "oestero01", "francjo01", "francjo01", "weisswa01", "francju01", "francju01", "greenmi01", "galaran01", "bonilbo01", "learyti01", "larkiba01", "whitter01", "stewada01", "clarkwi02", "jacksda02", "mcreyke01", "davisma01", "darliro01", "mitchke01", "russeje01", "olsongr01", "mcgrifr01", "mcgrifr01", "tettlmi01", "sierrru01", "sierrru01", "johnsho01", "dunstsh01", "dunstsh01", "hatchbi01", "drabedo01", "alomasa02", "alomasa02", "burksel01", "griffke02", 
+#> "griffke02", "maddugr01", "breamsi01", "myersra01", "justida01", "fieldce01", "willima04", "sciosmi01", "rijojo01", "glavito02", "glavito02", "alomaro01", "pagnoto01", "wegmabi01", "hrbekke01", "averyst01", "knoblch01", "gantro01", "abbotji01", "rodriiv01", "rodriiv01", "gracema01", "walkela01", "smoltjo01", "smoltjo01", "karroer01", "martied01", "gonzaju03", "frymatr01", "sheffga01", "sheffga01", "daultda01", "devermi01", "mcdowja01", "jonesdo01", "bordepa01", "bordepa01", "vizquom01", "vizquom01", 
+#> "thompro01", "manwaki01", "grissma02", "olerujo01", "schilcu01", "schilcu01", "montgje01", "salmoti01", "piazzmi01", "baergca01", "stanlmi02", "belleal01", "dykstle01", "coneda01", "lewisda01", "beckro01", "aloumo01", "cordewi01", "coninje01", "johnsra05", "snowjt01", "caminke01", "johnsch04", "finlest01", "mesajo01", "mesajo01", "henketo01", "nomohi01", "ramirma02", "valenjo02", "castivi02", "bicheda01", "thomeji01", "thomeji01", "edmonji01", "mussimi01", "schoupe01", "sandere02", "willibe02", "buhneja01", 
+#> "lopezja01", "wettejo01", "brantje01", "hollato01", "younger01", "pettian01", "leiteal01", "martipe02", "hernali01", "hernali01", "rolensc01", "martiti02", "blausje01", "neaglde01", "riverma01", "wellsda01", "wellsda01", "brosisc01", "boonebr01", "jonesan01", "hitchst01", "gordoto01", "gordoto01", "woodke02", "easleda01", "palmede01", "vaughgr01", "brownke01", "greensh01", "liebemi01", "caseyse01", "jonesch06", "perezed02", "wagnebi02", "beltrca01", "willisc01", "alfoned01", "guerrvl01", "hamptmi01", 
+#> "moyerja01", "limajo01", "urbinug01", "dyeje01", "rogerke01", "rogerke01", "mathemi01", "giambja01", "giambja01", "jonesto02", "alfonan01", "furcara01", "glaustr01", "posadjo01", "renteed01", "mientdo01", "chaveer01", "camermi01", "hunteto01", "vinafe01", "ausmubr01", "counscr01", "benitar01", "aurilri01", "nenro01", "kennead01", "valenbo02", "molinbe01", "graveda01", "hinsker01", "soriaal01", "anderga01", "beckejo02", "leede02", "castilu01", "cruzjo02", "muellbi02", "wellsve01", "vidrojo01", "lowelmi01", 
+#> "wolfra02", "ortizda01", "santajo01", "izturce01", "bayja01", "morame01", "martivi01", "loretma01", "beltrad01", "wilsoja02", "konerpa01", "drewjd01", "nathajo01", "carpech01", "hudsoor01", "varitja01", "oswalro01", "streehu01", "howarry01", "barremi01", "marquja01", "lopezfe01", "damonjo01", "youngmi02", "loducpa01", "polanpl01", "eckstda01", "johnsji04", "grudzma01", "morneju01", "rodrifr03", "verlaju01", "ramirha01", "mauerjo01", "utleych01", "mccanbr01", "zambrca01", "reyesjo01", "berkmla01", 
+#> "papeljo01", "penaca01", "youngdm01", "peavyja01", "youklke01", "rowanaa01", "rolliji01", "sweenmi01", "timlimi01", "timlimi01", "putzjj01", "valvejo01", "borowjo01", "garzama01", "hamelco01", "leecl02", "lidgebr01", "gonzaad01", "phillbr01", "molinya01", "mclouna01", "victosh01", "ramirar01", "sotoge01", "huffau01", "ludwiry01", "hillaa01", "greinza01", "zimmery01", "bournmi01", "bellhe01", "frankry01", "hudsoti01", "arroybr01", "tulowtr01", "bautijo02", "rossco01", "wakefti01", "soriara01", "ugglada01", 
+#> "youngde03", "cabreme01", "dickera01", "rodnefe01", "hardyjj01", "larocad01", "scutama01", "pierzaj01", "willijo03", "cuddymi01", "youngch03") x c(1880, 1887, 1888, 1883, 1883, 1889, 1898, 1891, 1908, 1910, 1908, 1917, 1905, 1908, 1914, 1908, 1902, 1909, 1915, 1898, 1905, 1908, 1903, 1908, 1908, 1909, 1911, 1915, 1908, 1906, 1908, 1911, 1917, 1912, 1914, 1904, 1915, 1918, 1907, 1922, 1909, 1913, 1906, 1914, 1909, 1908, 1913, 1912, 1915, 1914, 1911, 1916, 1909, 1911, 1922, 1910, 1908, 1911, 1923, 1914, 1917, 1908, 1917, 1911, 1921, 1914, 1910, 1915, 1910, 1920, 1916, 1914, 1917, 1922, 1915, 1915, 1922, 1916, 1924, 1928, 1915, 1927, 1929, 1914, 
+#> 1916, 1917, 1917, 1920, 1914, 1920, 1910, 1916, 1920, 1928, 1914, 1920, 1920, 1917, 1917, 1917, 1922, 1917, 1915, 1921, 1920, 1922, 1921, 1924, 1924, 1923, 1920, 1928, 1922, 1924, 1924, 1922, 1923, 1926, 1923, 1928, 1921, 1928, 1923, 1925, 1924, 1931, 1930, 1931, 1924, 1932, 1925, 1932, 1924, 1930, 1933, 1926, 1926, 1925, 1926, 1926, 1928, 1928, 1927, 1930, 1926, 1934, 1926, 1927, 1920, 1927, 1927, 1928, 1931, 1933, 1926, 1933, 1928, 1929, 1921, 1932, 1927, 1930, 1935, 1930, 1931, 1934, 1929, 1932, 
+#> 1936, 1937, 1931, 1935, 1932, 1925, 1934, 1936, 1927, 1930, 1931, 1934, 1939, 1930, 1935, 1932, 1937, 1937, 1936, 1927, 1936, 1931, 1934, 1937, 1933, 1934, 1943, 1932, 1934, 1935, 1936, 1938, 1932, 1938, 1933, 1942, 1943, 1936, 1937, 1943, 1939, 1936, 1934, 1940, 1928, 1929, 1934, 1935, 1941, 1934, 1938, 1948, 1939, 1934, 1938, 1941, 1936, 1946, 1947, 1934, 1936, 1939, 1940, 1937, 1944, 1942, 1944, 1944, 1936, 1941, 1939, 1932, 1948, 1942, 1946, 1935, 1939, 1946, 1939, 1941, 1942, 1947, 1944, 1936, 
+#> 1939, 1942, 1947, 1943, 1944, 1944, 1943, 1943, 1944, 1944, 1935, 1944, 1952, 1946, 1947, 1944, 1944, 1947, 1952, 1950, 1940, 1946, 1945, 1941, 1949, 1952, 1949, 1948, 1939, 1945, 1946, 1947, 1950, 1948, 1951, 1952, 1947, 1948, 1950, 1949, 1946, 1946, 1951, 1949, 1949, 1950, 1951, 1951, 1959, 1953, 1950, 1953, 1948, 1950, 1951, 1953, 1950, 1954, 1962, 1950, 1944, 1963, 1952, 1954, 1955, 1953, 1962, 1950, 1952, 1957, 1955, 1951, 1952, 1956, 1958, 1962, 1961, 1963, 1956, 1961, 1965, 1962, 1968, 1962, 
+#> 1964, 1963, 1968, 1953, 1959, 1966, 1962, 1959, 1960, 1965, 1966, 1957, 1964, 1955, 1958, 1956, 1962, 1967, 1959, 1954, 1958, 1962, 1956, 1956, 1962, 1947, 1948, 1960, 1961, 1965, 1959, 1954, 1961, 1964, 1962, 1961, 1963, 1965, 1961, 1960, 1960, 1965, 1961, 1961, 1966, 1964, 1963, 1962, 1965, 1966, 1961, 1955, 1962, 1963, 1964, 1962, 1965, 1982, 1963, 1956, 1962, 1974, 1957, 1956, 1965, 1969, 1969, 1964, 1970, 1964, 1974, 1979, 1964, 1963, 1964, 1966, 1962, 1964, 1965, 1961, 1964, 1964, 1963, 1967, 
+#> 1966, 1971, 1965, 1964, 1963, 1970, 1969, 1965, 1970, 1969, 1973, 1965, 1965, 1966, 1965, 1964, 1968, 1966, 1969, 1968, 1969, 1973, 1966, 1959, 1966, 1968, 1976, 1970, 1964, 1966, 1967, 1966, 1971, 1968, 1971, 1973, 1968, 1974, 1980, 1975, 1979, 1968, 1970, 1973, 1974, 1962, 1972, 1969, 1968, 1975, 1971, 1972, 1973, 1969, 1968, 1969, 1965, 1969, 1976, 1973, 1965, 1970, 1975, 1965, 1969, 1974, 1970, 1973, 1968, 1970, 1978, 1966, 1973, 1971, 1970, 1969, 1977, 1971, 1973, 1971, 1973, 1964, 1965, 1978, 
+#> 1985, 1973, 1971, 1974, 1974, 1972, 1971, 1982, 1977, 1966, 1968, 1973, 1975, 1973, 1973, 1980, 1982, 1976, 1973, 1973, 1973, 1974, 1980, 1971, 1970, 1974, 1975, 1974, 1976, 1979, 1974, 1976, 1972, 1977, 1982, 1966, 1978, 1975, 1978, 1970, 1976, 1973, 1978, 1978, 1982, 1980, 1986, 1977, 1980, 1976, 1973, 1975, 1982, 1965, 1967, 1969, 1983, 1984, 1975, 1976, 1977, 1974, 1975, 1978, 1985, 1977, 1978, 1976, 1977, 1973, 1984, 1983, 1979, 1976, 1973, 1974, 1975, 1973, 1975, 1980, 1986, 1978, 1973, 1975, 
+#> 1978, 1967, 1978, 1983, 1971, 1978, 1988, 1982, 1991, 1984, 1979, 1976, 1976, 1979, 1980, 1979, 1982, 1979, 1980, 1979, 1973, 1979, 1985, 1975, 1977, 1979, 1980, 1980, 1980, 1982, 1979, 1984, 1985, 1982, 1983, 1982, 1977, 1980, 1974, 1980, 1986, 1980, 1986, 1984, 1979, 1980, 1989, 1975, 1977, 1996, 1988, 1984, 1982, 1985, 1984, 1980, 1980, 1982, 1984, 1978, 1985, 1983, 1983, 1987, 1980, 1983, 1987, 1985, 1984, 1982, 1982, 1983, 1983, 1986, 1984, 1982, 1992, 1985, 1984, 1979, 1986, 1986, 1986, 1986, 
+#> 1990, 1982, 1990, 1986, 1985, 1982, 1985, 1985, 1985, 1987, 1986, 1984, 1985, 1987, 1986, 1983, 1978, 1987, 1987, 1985, 1985, 1986, 1983, 1986, 1989, 1987, 1988, 1996, 1989, 1990, 1991, 1985, 1984, 1991, 1992, 1996, 1984, 1991, 1987, 1987, 1983, 1986, 1988, 1993, 1984, 1985, 1990, 1996, 1989, 1987, 1999, 1985, 1983, 1988, 1987, 1986, 1985, 1985, 1989, 1989, 1991, 1989, 1996, 1992, 1989, 1991, 1987, 1986, 1988, 1988, 1989, 1990, 1996, 1996, 1998, 1999, 1991, 1986, 1993, 1993, 1991, 1990, 1987, 1988, 
+#> 1988, 1996, 1991, 1991, 1995, 1985, 1998, 1997, 1993, 1991, 1996, 1997, 1999, 1997, 2002, 2004, 1997, 1997, 1992, 1992, 1996, 2003, 1993, 1992, 1991, 1992, 1992, 1993, 1993, 2000, 1986, 1993, 1992, 1999, 1991, 1992, 1990, 2000, 1997, 1992, 1999, 1998, 1993, 1988, 1998, 1998, 1998, 1997, 1993, 1993, 1999, 1989, 1999, 1992, 2002, 2006, 1987, 2002, 2003, 1998, 1998, 1998, 2000, 2003, 1998, 1996, 1993, 2002, 1999, 1993, 2004, 1993, 1991, 1996, 2000, 2006, 1993, 1993, 2002, 2004, 1998, 1999, 1993, 1992, 
+#> 2004, 1989, 1990, 1998, 2003, 1999, 1998, 2004, 2005, 2008, 2001, 1996, 1998, 1998, 2000, 1999, 1999, 1998, 2003, 2003, 2002, 2002, 1999, 2002, 1994, 1987, 1997, 1999, 1999, 1989, 1992, 2003, 1999, 2003, 2002, 2004, 2006, 2001, 2000, 2003, 2001, 2005, 2002, 2007, 1998, 2000, 2005, 1999, 2001, 2001, 2000, 1972, 2008, 1999, 2004, 2006, 2001, 2006, 2002, 2003, 2000, 2000, 2003, 2000, 2002, 2010, 2005, 2003, 2004, 2005, 2006, 2013, 2006, 2013, 2005, 2005, 2006, 2003, 2010, 2006, 1999, 2004, 2006, 2008, 
+#> 2004, 2006, 2007, 1998, 2006, 2002, 2009, 2005, 2013, 1997, 2008, 2012, 2009, 2006, 2015, 2006, 2008, 2010, 2005, 2004, 2012, 2012, 2003, 2007, 2006, 2007, 2007, 2000, 2004, 2005, 2006, 2011, 2002, 2010, 2008, 2011, 2004, 2008, 2007, 2009, 2008, 2009, 2001, 2008, 2003, 2008, 2007, 2007, 2007, 2009, 2007, 2008, 2001, 2008, 2007, 2010, 2009, 2000, 2009, 2011, 2007, 2015, 2003, 2012, 2013, 2012, 2010, 2006, 2012, 2010, 2015) x c(26, 147, 62, 107, 92, 26, 26, 42, 45, 45, 89, 38, 16, 33, 52, 33, 22, 52, 52, 42, 123, 89, 35, 89, 106, 106, 35, 106, 89, 35, 35, 35, 33, 16, 16, 101, 140, 140, 52, 45, 106, 106, 35, 35, 35, 101, 101, 35, 26, 101, 52, 33, 102, 102, 38, 89, 38, 89, 26, 16, 140, 16, 89, 102, 93, 63, 101, 102, 22, 33, 16, 26, 38, 38, 38, 125, 89, 106, 93, 93, 38, 89, 35, 26, 89, 33, 102, 38, 106, 45, 16, 35, 22, 106, 93, 125, 22, 26, 140, 45, 123, 16, 33, 93, 89, 106, 89, 93, 93, 101, 102, 38, 22, 52, 16, 106, 35, 
+#> 125, 38, 22, 140, 140, 45, 93, 89, 106, 35, 140, 140, 101, 101, 101, 140, 33, 33, 106, 125, 106, 38, 45, 33, 123, 101, 35, 93, 106, 33, 35, 125, 106, 102, 106, 106, 140, 26, 38, 89, 45, 101, 101, 93, 101, 16, 123, 38, 89, 102, 101, 16, 45, 140, 125, 123, 101, 26, 38, 89, 102, 93, 35, 35, 22, 125, 102, 93, 16, 123, 52, 52, 26, 22, 125, 26, 16, 102, 89, 89, 89, 89, 52, 45, 52, 125, 93, 45, 45, 101, 33, 35, 106, 106, 125, 16, 16, 123, 123, 45, 123, 123, 38, 38, 38, 35, 93, 101, 45, 16, 102, 102, 125, 
+#> 38, 123, 101, 93, 35, 38, 45, 140, 22, 52, 106, 125, 125, 35, 45, 93, 125, 125, 22, 16, 52, 89, 106, 125, 89, 106, 93, 52, 106, 16, 45, 45, 35, 35, 22, 125, 35, 26, 26, 140, 140, 52, 45, 125, 22, 35, 102, 93, 22, 16, 123, 45, 93, 22, 38, 106, 26, 26, 89, 16, 45, 93, 26, 35, 89, 33, 52, 52, 22, 26, 38, 16, 93, 52, 52, 102, 22, 22, 102, 45, 117, 89, 106, 125, 35, 102, 102, 93, 72, 125, 125, 93, 125, 38, 45, 89, 72, 106, 33, 80, 52, 52, 35, 117, 33, 38, 125, 80, 4, 33, 80, 30, 16, 33, 33, 94, 30, 52, 
+#> 93, 93, 52, 16, 64, 106, 80, 125, 16, 117, 106, 106, 72, 140, 140, 5, 79, 117, 117, 106, 5, 5, 79, 93, 125, 33, 93, 16, 125, 35, 93, 52, 72, 106, 38, 72, 35, 52, 52, 38, 38, 5, 45, 93, 72, 125, 117, 33, 72, 5, 106, 106, 72, 16, 58, 125, 86, 33, 38, 102, 93, 117, 102, 125, 71, 45, 35, 102, 79, 102, 16, 79, 30, 86, 106, 38, 79, 96, 93, 38, 102, 106, 106, 33, 35, 33, 106, 16, 4, 64, 35, 38, 38, 125, 16, 117, 16, 35, 79, 94, 125, 125, 58, 35, 52, 52, 16, 52, 35, 38, 86, 52, 116, 33, 5, 4, 5, 93, 66, 
+#> 72, 96, 96, 16, 102, 102, 106, 94, 79, 106, 79, 33, 96, 33, 58, 93, 45, 38, 96, 66, 117, 72, 94, 93, 102, 93, 5, 5, 38, 96, 83, 106, 58, 96, 117, 117, 16, 33, 52, 58, 102, 96, 66, 117, 86, 93, 4, 96, 5, 86, 58, 52, 5, 102, 66, 96, 4, 72, 72, 72, 96, 96, 38, 72, 38, 131, 102, 102, 106, 33, 114, 106, 45, 16, 125, 102, 38, 117, 93, 93, 16, 45, 131, 38, 106, 93, 125, 52, 131, 45, 33, 72, 72, 35, 72, 66, 66, 66, 30, 30, 94, 30, 38, 38, 131, 66, 4, 5, 86, 93, 79, 30, 30, 16, 125, 125, 35, 106, 125, 16, 
+#> 72, 86, 4, 4, 52, 86, 52, 83, 117, 5, 125, 131, 83, 35, 114, 114, 30, 45, 131, 72, 66, 86, 79, 96, 58, 58, 102, 5, 96, 66, 52, 94, 86, 66, 72, 52, 83, 114, 93, 131, 38, 72, 96, 93, 72, 30, 96, 125, 72, 134, 5, 72, 134, 30, 35, 106, 79, 83, 125, 5, 5, 5, 102, 106, 125, 38, 33, 94, 16, 134, 106, 114, 58, 4, 106, 86, 35, 125, 52, 52, 58, 114, 106, 93, 30, 86, 86, 33, 125, 86, 33, 33, 125, 125, 16, 58, 79, 79, 134, 134, 35, 66, 125, 96, 45, 16, 79, 4, 116, 125, 106, 38, 79, 116, 96, 114, 102, 134, 96, 
+#> 96, 96, 72, 116, 30, 106, 38, 38, 38, 55, 45, 45, 16, 51, 106, 72, 38, 134, 72, 117, 66, 114, 117, 94, 117, 131, 5, 134, 4, 52, 131, 131, 94, 35, 35, 58, 106, 45, 45, 51, 116, 116, 35, 106, 35, 4, 52, 117, 72, 38, 4, 4, 134, 125, 83, 79, 16, 79, 4, 30, 131, 131, 35, 51, 4, 4, 72, 116, 131, 52, 55, 4, 102, 5, 33, 58, 134, 134, 116, 45, 117, 117, 86, 94, 58, 102, 66, 2, 72, 45, 16, 33, 102, 94, 16, 35, 58, 16, 55, 116, 117, 58, 5, 58, 102, 51, 134, 72, 16, 16, 51, 51, 45, 102, 2, 5, 94, 117, 93, 116, 
+#> 5, 86, 117, 72, 35, 58, 134, 72, 117, 86, 102, 93, 4, 106, 93, 134, 134, 93, 116, 4, 114, 93, 93, 35, 52, 131, 114, 114, 72, 102, 38, 4, 78, 58, 66, 38, 94, 86, 58, 35, 58, 86, 66, 131, 131, 125, 96, 93, 51, 4, 72, 2, 93, 125, 79, 96, 116, 79, 78, 52, 3, 94, 117, 117, 2, 72, 117, 38, 134, 137, 2, 16, 55, 55, 134, 117, 134, 86, 55, 78, 16, 79, 72, 106, 5, 52, 16, 131, 106, 33, 72, 117, 125, 3, 16, 58, 96, 102, 35, 125, 137, 66, 131, 72, 52, 125, 5, 86, 79, 78, 52, 55, 79, 102, 4, 35, 94, 58, 102, 
+#> 130, 52, 114, 16, 102, 102, 66, 16, 16, 116, 52, 35, 130, 102, 102, 58, 114, 38, 125, 106, 102, 106, 35, 130, 125, 134, 66, 137, 58, 114, 125, 96, 38, 51, 134, 55, 16, 4, 4, 130, 33, 131, 130, 5, 137, 16, 33, 79, 79, 66) x c(76, 123, 133, 89, 70, 73, 152, 55, 157, 159, 56, 152, 109, 137, 157, 66, 48, 156, 156, 154, 156, 140, 132, 155, 151, 152, 53, 156, 156, 154, 46, 154, 156, 153, 158, 46, 64, 65, 70, 142, 150, 43, 136, 153, 153, 78, 48, 120, 156, 150, 141, 155, 141, 50, 156, 151, 155, 45, 154, 155, 125, 153, 150, 153, 134, 49, 145, 150, 156, 151, 48, 156, 121, 156, 160, 144, 156, 45, 153, 154, 155, 155, 156, 128, 150, 49, 125, 149, 156, 149, 155, 44, 43, 48, 157, 155, 154, 53, 155, 46, 48, 157, 50, 51, 155, 150, 
+#> 42, 148, 60, 56, 43, 43, 67, 153, 46, 154, 131, 147, 43, 38, 153, 153, 152, 47, 151, 155, 141, 152, 149, 139, 153, 154, 154, 57, 51, 157, 154, 109, 47, 151, 155, 154, 51, 155, 155, 48, 44, 48, 48, 155, 128, 152, 154, 52, 45, 144, 153, 148, 155, 153, 152, 49, 75, 154, 97, 49, 154, 154, 155, 156, 156, 40, 154, 53, 48, 51, 42, 156, 40, 52, 156, 44, 53, 154, 140, 153, 152, 41, 39, 156, 140, 156, 49, 152, 82, 154, 153, 155, 46, 155, 153, 155, 145, 154, 38, 37, 154, 155, 156, 156, 49, 155, 60, 60, 123, 
+#> 144, 151, 50, 46, 41, 156, 132, 44, 156, 153, 48, 156, 83, 64, 63, 150, 155, 155, 152, 156, 155, 43, 152, 157, 43, 56, 152, 156, 146, 154, 34, 47, 155, 133, 155, 51, 43, 52, 125, 140, 157, 154, 47, 156, 155, 44, 154, 146, 152, 150, 37, 41, 155, 42, 154, 154, 157, 155, 40, 153, 125, 154, 47, 155, 155, 154, 44, 150, 130, 40, 156, 42, 52, 155, 128, 72, 38, 133, 42, 156, 154, 155, 149, 158, 150, 61, 69, 155, 152, 43, 74, 158, 153, 157, 153, 162, 47, 39, 55, 151, 45, 51, 149, 160, 153, 152, 46, 152, 154, 
+#> 150, 49, 42, 156, 159, 158, 153, 153, 163, 52, 157, 162, 162, 161, 160, 42, 52, 54, 156, 140, 154, 157, 50, 45, 150, 36, 154, 155, 162, 163, 150, 61, 154, 162, 157, 49, 58, 54, 73, 145, 159, 160, 50, 50, 163, 163, 148, 161, 162, 162, 150, 70, 65, 71, 162, 42, 142, 155, 162, 165, 164, 160, 163, 116, 39, 71, 163, 43, 58, 62, 147, 44, 163, 158, 48, 69, 43, 162, 151, 162, 159, 54, 163, 163, 160, 42, 162, 46, 50, 150, 164, 135, 161, 162, 157, 163, 162, 152, 62, 163, 156, 72, 39, 159, 159, 145, 148, 82, 
+#> 84, 160, 153, 54, 160, 66, 71, 160, 160, 160, 46, 47, 162, 160, 156, 42, 143, 150, 158, 60, 45, 44, 159, 157, 155, 160, 57, 159, 162, 88, 41, 157, 155, 158, 151, 159, 154, 157, 158, 41, 40, 162, 147, 75, 162, 47, 150, 143, 157, 156, 157, 43, 42, 40, 159, 160, 160, 157, 162, 156, 160, 141, 44, 158, 152, 83, 67, 160, 160, 46, 49, 157, 153, 162, 161, 162, 158, 134, 157, 156, 72, 73, 159, 162, 144, 154, 65, 160, 162, 161, 41, 161, 162, 106, 163, 144, 43, 150, 44, 160, 158, 151, 162, 155, 63, 78, 154, 
+#> 46, 150, 161, 155, 37, 38, 160, 159, 163, 162, 163, 162, 72, 64, 68, 160, 155, 152, 39, 43, 41, 82, 58, 159, 159, 162, 39, 155, 159, 150, 154, 158, 145, 162, 159, 162, 159, 153, 155, 41, 42, 158, 161, 157, 44, 43, 155, 143, 155, 151, 46, 45, 161, 162, 162, 162, 157, 64, 71, 162, 145, 158, 159, 162, 162, 161, 71, 44, 157, 162, 162, 158, 40, 44, 65, 49, 159, 161, 157, 157, 159, 84, 66, 155, 159, 152, 147, 41, 78, 39, 158, 153, 54, 157, 158, 162, 135, 53, 163, 160, 152, 153, 153, 53, 38, 162, 156, 35, 
+#> 136, 132, 36, 151, 153, 162, 145, 154, 161, 158, 162, 153, 154, 148, 50, 160, 72, 70, 154, 80, 46, 160, 41, 162, 154, 161, 75, 160, 154, 156, 161, 160, 159, 37, 36, 38, 162, 160, 159, 163, 151, 40, 75, 159, 153, 144, 37, 70, 37, 162, 121, 135, 161, 150, 156, 152, 161, 63, 67, 69, 145, 45, 161, 159, 157, 157, 74, 70, 158, 160, 160, 159, 159, 163, 39, 161, 139, 46, 162, 36, 158, 77, 42, 154, 71, 72, 161, 159, 157, 162, 161, 157, 150, 155, 145, 40, 132, 127, 156, 161, 160, 39, 154, 74, 157, 162, 159, 
+#> 142, 49, 42, 39, 161, 140, 38, 158, 39, 156, 157, 34, 153, 150, 161, 153, 75, 73, 162, 155, 155, 161, 161, 155, 147, 156, 35, 80, 138, 138, 158, 156, 149, 130, 159, 162, 56, 42, 73, 158, 152, 161, 136, 163, 161, 35, 155, 81, 159, 140, 162, 36, 161, 161, 135, 162, 74, 79, 72, 34, 154, 153, 162, 161, 158, 159, 154, 36, 41, 140, 158, 158, 150, 70, 67, 149, 153, 38, 34, 66, 36, 36, 160, 159, 161, 56, 74, 54, 43, 152, 159, 162, 39, 80, 79, 65, 154, 154, 158, 36, 162, 145, 151, 160, 107, 78, 162, 63, 158, 
+#> 161, 44, 39, 52, 71, 158, 73, 81, 141, 158, 156, 79, 79, 159, 161, 151, 157, 151, 160, 158, 160, 159, 150, 150, 77, 156, 79, 156, 119, 145, 75, 155, 159, 161, 33, 162, 152, 162, 153, 161, 153, 160, 36, 159, 45, 159, 162, 155, 159, 155, 161, 158, 158, 146, 78, 35, 157, 144, 36, 69, 162, 134, 46, 154, 161, 162, 149, 153, 158, 74, 156, 163, 78, 35, 158, 158, 160, 145, 42, 161, 160, 70, 160, 155, 37, 147, 161, 162, 159, 76, 81, 72, 75, 73, 33, 36, 35, 80, 162, 158, 140, 152, 156, 158, 141, 162, 152, 
+#> 160, 52, 162, 157, 81, 74, 36, 40, 155, 161, 151, 52, 77, 161, 162, 158, 38, 76, 159, 154, 150, 140, 145, 157, 34) x c(282, 478, 513, 381, 259, 262, 568, 174, 581, 591, 129, 602, 313, 430, 582, 157, 161, 573, 563, 593, 587, 449, 491, 593, 551, 550, 91, 566, 583, 533, 99, 577, 564, 580, 571, 129, 147, 150, 157, 505, 510, 114, 474, 577, 527, 220, 78, 385, 571, 570, 503, 592, 468, 138, 610, 575, 570, 104, 607, 553, 350, 526, 585, 560, 424, 125, 487, 522, 606, 485, 85, 586, 399, 631, 587, 473, 651, 110, 529, 536, 579, 568, 602, 366, 587, 112, 409, 579, 593, 489, 584, 104, 111, 131, 570, 639, 582, 101, 586, 97, 115, 
+#> 528, 84, 143, 590, 614, 89, 610, 124, 101, 101, 104, 125, 570, 126, 593, 452, 492, 104, 96, 622, 542, 644, 99, 596, 615, 508, 570, 501, 518, 654, 670, 579, 122, 91, 614, 603, 329, 106, 603, 552, 638, 80, 585, 589, 56, 86, 122, 108, 623, 443, 659, 681, 102, 78, 568, 646, 566, 613, 558, 648, 114, 150, 614, 153, 117, 638, 585, 585, 609, 611, 56, 612, 64, 96, 90, 87, 648, 83, 113, 623, 68, 128, 614, 530, 570, 533, 78, 118, 617, 439, 633, 85, 623, 120, 566, 582, 681, 74, 556, 621, 634, 599, 610, 52, 87, 
+#> 649, 585, 641, 583, 84, 579, 121, 114, 431, 504, 585, 93, 124, 78, 630, 417, 101, 588, 566, 124, 528, 300, 121, 105, 563, 571, 581, 544, 582, 536, 41, 608, 565, 78, 48, 591, 609, 519, 587, 94, 69, 547, 421, 638, 133, 73, 55, 438, 515, 580, 643, 120, 581, 604, 73, 571, 589, 614, 551, 83, 56, 631, 75, 600, 569, 641, 627, 87, 555, 418, 610, 71, 617, 648, 617, 85, 565, 471, 89, 555, 116, 112, 587, 446, 136, 83, 397, 70, 646, 561, 608, 559, 582, 550, 105, 29, 617, 606, 56, 37, 667, 590, 637, 577, 621, 
+#> 66, 53, 7, 567, 122, 107, 587, 588, 642, 620, 9, 593, 607, 597, 89, 71, 663, 606, 547, 617, 586, 612, 25, 622, 609, 628, 631, 606, 87, 104, 8, 619, 505, 591, 528, 22, 94, 550, 82, 610, 601, 600, 639, 518, 93, 548, 625, 588, 97, 17, 120, 106, 511, 556, 540, 85, 52, 668, 612, 522, 590, 658, 587, 561, 15, 26, 8, 662, 108, 445, 622, 652, 695, 645, 603, 583, 421, 90, 16, 641, 106, 130, 12, 460, 90, 665, 626, 45, 26, 113, 603, 496, 679, 501, 120, 652, 628, 613, 112, 654, 100, 65, 577, 608, 381, 672, 632, 
+#> 612, 547, 611, 520, 27, 597, 497, 9, 101, 616, 574, 522, 522, 29, 18, 629, 500, 73, 662, 21, 15, 625, 629, 650, 54, 66, 601, 553, 605, 95, 465, 543, 594, 51, 115, 111, 618, 602, 643, 621, 9, 615, 646, 22, 112, 559, 493, 566, 574, 590, 553, 593, 553, 117, 100, 698, 509, 24, 612, 93, 518, 492, 472, 576, 597, 95, 77, 0, 620, 643, 643, 564, 625, 626, 616, 491, 113, 607, 571, 14, 13, 583, 510, 56, 64, 571, 543, 515, 611, 669, 593, 450, 601, 530, 0, 30, 642, 581, 445, 580, NA, 645, 616, 594, 0, 595, 615, 
+#> 34, 658, 475, 90, 474, 108, 594, 604, 582, 568, 581, 19, 20, 568, 36, 541, 592, 598, 82, 78, 552, 587, 677, 602, 656, 637, 23, 0, 7, 555, 472, 562, 59, 75, 98, 10, 6, 634, 645, 641, NA, 616, 609, 460, 585, 614, 478, 606, 604, 588, 633, 574, 581, 0, NA, 580, 619, 581, 82, 70, 647, 441, 618, 570, 57, 120, 643, 599, 642, 621, 563, 0, 10, 670, 513, 582, 597, 558, 628, 589, 0, 27, 533, 560, 621, 592, 14, 50, 6, 0, 573, 705, 489, 555, 596, NA, 7, 605, 602, 541, 519, NA, 16, 109, 591, 608, 14, 654, 628, 
+#> 570, 452, NA, 640, 632, 633, 575, 542, 31, NA, 628, 592, 0, 441, 362, 77, 542, 620, 618, 520, 532, 653, 592, 647, 562, 619, 517, 29, 622, 16, 0, 581, 0, 57, 642, 90, 677, 539, 626, 10, 516, 600, 605, 608, 640, 596, 94, NA, 95, 588, 560, 590, 687, 510, NA, 10, 630, 500, 498, NA, 19, NA, 613, 340, 472, 660, 566, 523, 580, 663, NA, 0, NA, 514, 50, 631, 639, 564, 549, 4, 1, 500, 658, 636, 610, 626, 616, 23, 583, 412, 7, 575, NA, 560, 12, 76, 543, NA, 0, 551, 617, 525, 634, 661, 554, 581, 575, 530, 77, 
+#> 445, 418, 613, 633, 606, 88, 522, 2, 585, 624, 617, 461, 37, 60, 76, 637, 459, 0, 593, 1, 611, 606, NA, 639, 597, 593, 568, 2, 2, 628, 542, 584, 659, 519, 576, 510, 653, NA, 4, 480, 488, 560, 613, 549, 432, 653, 581, 3, 64, NA, 568, 556, 657, 427, 609, 637, 80, 585, 1, 584, 570, 595, 0, 570, 585, 426, 607, 0, 1, 0, 63, 569, 588, 645, 662, 557, 578, 599, NA, 32, 505, 591, 563, 579, 4, 3, 478, 607, 62, NA, 4, 64, 81, 601, 589, 597, 11, 0, NA, NA, 530, 622, 592, 50, 1, 0, 0, 585, 582, 573, 82, 610, 
+#> 510, 594, 601, 350, 2, 637, 0, 628, 614, 1, 61, 3, 5, 608, NA, NA, 441, 575, 535, 3, 1, 654, 588, 505, 587, 543, 625, 545, 600, 637, 523, 578, 5, 636, 1, 598, 391, 530, 5, 570, 647, 672, 7, 581, 595, 603, 560, 678, 606, 597, 77, 601, 3, 670, 599, 624, 605, 635, 631, 587, 575, 494, 1, 72, 579, 483, 71, 0, 610, 456, 78, 603, 642, 691, 580, 618, 630, 0, 649, 623, 0, 2, 633, 592, 658, 509, 52, 696, 544, 0, 497, 562, 73, 569, 612, 716, 618, 0, 0, 0, 0, 7, 3, 76, 75, 1, 616, 650, 481, 597, 620, 603, 494, 
+#> 636, 538, 608, 1, 653, 606, 0, 0, 8, 61, 609, 569, 559, 2, 0, 600, 645, 629, 1, 0, 601, 571, 632, 509, 519, 609, 4) x c(27, 83, 84, 59, 39, 36, 97, 23, 77, 94, 11, 71, 33, 40, 74, 10, 16, 116, 144, 81, 67, 70, 67, 71, 83, 97, 8, 68, 101, 65, 10, 105, 91, 136, 101, 9, 14, 10, 16, 74, 42, 13, 103, 80, 60, 24, 7, 35, 72, 84, 45, 91, 42, 12, 114, 97, 71, 9, 70, 50, 38, 62, 61, 96, 77, 5, 64, 89, 78, 64, 2, 74, 37, 104, 72, 41, 117, 13, 143, 163, 61, 133, 156, 42, 88, 6, 28, 81, 76, 63, 81, 4, 9, 17, 55, 85, 83, 4, 77, 1, 14, 40, 11, 18, 69, 113, 9, 105, 13, 13, 6, 4, 12, 107, 14, 64, 73, 63, 8, 7, 87, 78, 130, 6, 81, 
+#> 81, 84, 82, 50, 118, 122, 144, 100, 20, 11, 113, 98, 34, 8, 97, 70, 104, 8, 146, 79, 2, 5, 15, 6, 114, 50, 121, 90, 7, 3, 77, 99, 97, 88, 71, 137, 11, 25, 94, 15, 9, 152, 151, 130, 121, 103, 8, 71, 6, 14, 7, 6, 158, 8, 12, 111, 5, 18, 118, 87, 88, 78, 4, 10, 94, 58, 111, 9, 129, 14, 119, 119, 108, 9, 144, 106, 91, 122, 123, 8, 12, 113, 63, 112, 111, 8, 111, 12, 9, 47, 57, 89, 6, 9, 6, 99, 42, 10, 104, 91, 9, 125, 36, 12, 10, 102, 103, 62, 106, 116, 48, 3, 106, 105, 7, 4, 100, 100, 69, 84, 9, 4, 50, 
+#> 53, 106, 18, 11, 5, 58, 79, 64, 125, 10, 82, 78, 11, 98, 85, 106, 76, 2, 5, 93, 5, 77, 71, 114, 97, 2, 128, 41, 92, 4, 132, 127, 101, 1, 92, 53, 7, 104, 8, 10, 102, 54, 21, 7, 52, 3, 114, 73, 96, 99, 118, 96, 10, 3, 125, 61, 2, 0, 93, 132, 78, 94, 130, 3, 4, 0, 89, 11, 12, 72, 83, 81, 91, 1, 86, 74, 102, 7, 5, 82, 67, 82, 96, 116, 79, 3, 55, 134, 100, 121, 84, 4, 14, 0, 74, 63, 89, 44, 1, 10, 63, 7, 91, 91, 114, 62, 65, 16, 83, 105, 69, 7, 0, 6, 9, 73, 83, 93, 3, 10, 89, 82, 58, 132, 106, 61, 76, 
+#> 2, 0, 0, 80, 13, 47, 95, 96, 130, 115, 98, 129, 67, 7, 1, 94, 6, 18, 0, 40, 10, 120, 67, 3, 2, 4, 96, 52, 97, 40, 9, 110, 90, 71, 6, 101, 11, 1, 64, 88, 34, 109, 125, 81, 105, 78, 89, 2, 61, 88, 0, 9, 92, 66, 89, 106, 3, 1, 98, 47, 19, 72, 1, 0, 93, 103, 110, 5, 3, 73, 41, 97, 9, 53, 50, 102, 6, 9, 7, 85, 81, 98, 108, 1, 62, 77, 0, 6, 84, 54, 85, 65, 69, 82, 91, 82, 6, 6, 105, 63, 1, 89, 8, 53, 37, 51, 90, 83, 5, 6, 0, 91, 131, 86, 72, 81, 77, 83, 81, 13, 85, 42, 1, 1, 87, 83, 0, 4, 94, 85, 55, 85, 
+#> 97, 73, 60, 74, 41, 0, 2, 87, 82, 58, 67, NA, 118, 89, 76, 0, 114, 55, 2, 78, 58, 10, 73, 8, 70, 71, 82, 108, 91, 1, 0, 92, 0, 75, 43, 62, 4, 3, 65, 81, 121, 100, 96, 89, 0, 0, 0, 46, 45, 71, 4, 4, 6, 0, 0, 84, 94, 104, NA, 70, 66, 37, 117, 90, 49, 98, 101, 97, 104, 98, 81, 0, NA, 66, 62, 80, 4, 7, 82, 65, 108, 75, 4, 5, 94, 94, 75, 92, 90, 0, 0, 89, 53, 42, 97, 89, 120, 90, 0, 1, 101, 100, 94, 66, 1, 2, 0, 0, 86, 133, 66, 35, 75, NA, 0, 80, 92, 75, 70, NA, 2, 5, 111, 130, 0, 114, 87, 60, 34, NA, 
+#> 94, 70, 79, 94, 58, 6, NA, 78, 120, 1, 41, 54, 7, 51, 76, 71, 75, 108, 107, 97, 79, 75, 81, 65, 2, 106, 2, 0, 96, 0, 3, 107, 9, 117, 93, 69, 0, 61, 94, 67, 89, 86, 97, 9, NA, 7, 55, 71, 89, 91, 56, NA, 0, 81, 73, 66, NA, 0, NA, 83, 33, 81, 99, 69, 87, 60, 101, NA, 0, NA, 79, 4, 95, 103, 93, 63, 0, 0, 50, 82, 97, 71, 119, 96, 1, 108, 55, 0, 102, NA, 89, 0, 9, 100, NA, 0, 98, 81, 82, 101, 110, 93, 66, 69, 79, 1, 60, 53, 142, 120, 123, 8, 73, 0, 90, 102, 87, 44, 2, 6, 8, 88, 38, 0, 78, 2, 117, 113, 
+#> NA, 116, 98, 107, 143, 0, 0, 86, 104, 77, 87, 118, 126, 90, 76, NA, 0, 47, 38, 68, 101, 73, 48, 99, 107, 0, 3, NA, 108, 104, 92, 59, 113, 143, 2, 95, 0, 104, 82, 75, 0, 93, 71, 58, 84, 0, 0, 0, 3, 117, 113, 108, 97, 106, 111, 115, NA, 2, 75, 116, 91, 83, 0, 0, 64, 98, 4, NA, 0, 6, 2, 120, 95, 110, 0, 0, NA, NA, 86, 111, 97, 5, 0, 0, 0, 77, 98, 112, 4, 98, 84, 103, 123, 26, 1, 114, 0, 123, 106, 0, 3, 0, 0, 96, NA, NA, 43, 115, 97, 0, 0, 113, 100, 92, 96, 77, 92, 84, 94, 101, 75, 85, 0, 114, 0, 82, 
+#> 42, 46, 0, 66, 119, 83, 2, 95, 99, 91, 97, 118, 101, 88, 11, 119, 0, 90, 110, 96, 68, 75, 88, 60, 98, 84, 0, 2, 87, 70, 1, 0, 105, 55, 8, 70, 104, 93, 74, 82, 90, 0, 76, 97, 0, 0, 119, 69, 131, 68, 5, 99, 104, 0, 72, 78, 8, 100, 105, 139, 105, 0, 0, 0, 0, 1, 0, 3, 6, 0, 103, 107, 45, 113, 102, 83, 66, 91, 104, 87, 0, 99, 97, 0, 0, 1, 4, 104, 109, 73, 0, 0, 88, 65, 70, 0, 0, 66, 76, 92, 65, 85, 93, 0) x c(62, 147, 144, 108, 57, 54, 169, 29, 168, 227, 20, 167, 62, 82, 183, 27, 28, 216, 208, 160, 159, 127, 146, 198, 146, 158, 23, 155, 149, 136, 23, 173, 163, 222, 193, 31, 34, 40, 34, 150, 135, 33, 151, 152, 150, 56, 12, 109, 160, 182, 133, 202, 105, 24, 205, 164, 167, 17, 191, 143, 67, 130, 174, 153, 134, 21, 126, 149, 172, 131, 17, 144, 106, 180, 170, 141, 209, 21, 200, 173, 153, 205, 229, 89, 180, 20, 112, 196, 144, 157, 156, 14, 34, 42, 127, 204, 177, 24, 177, 13, 22, 127, 11, 49, 157, 215, 18, 
+#> 184, 42, 24, 25, 18, 26, 197, 28, 173, 144, 144, 21, 17, 187, 166, 222, 20, 180, 183, 172, 155, 142, 152, 253, 216, 199, 38, 26, 197, 180, 103, 33, 216, 170, 241, 10, 208, 162, 10, 16, 27, 19, 237, 122, 221, 214, 19, 12, 172, 231, 209, 168, 148, 231, 26, 52, 192, 43, 23, 254, 213, 198, 182, 187, 8, 148, 10, 23, 18, 18, 250, 11, 22, 191, 14, 30, 189, 176, 172, 148, 16, 25, 199, 120, 237, 12, 200, 36, 180, 190, 201, 16, 175, 194, 186, 189, 186, 12, 14, 208, 192, 191, 182, 16, 182, 38, 35, 133, 146, 
+#> 199, 17, 31, 11, 209, 127, 20, 162, 165, 16, 181, 78, 29, 40, 150, 175, 144, 159, 167, 112, 5, 218, 164, 15, 10, 188, 183, 125, 191, 14, 16, 138, 109, 207, 36, 10, 11, 123, 157, 144, 205, 29, 183, 163, 19, 162, 162, 197, 158, 11, 7, 195, 13, 159, 143, 218, 185, 14, 143, 95, 184, 19, 172, 185, 195, 8, 142, 139, 13, 147, 22, 18, 171, 125, 37, 13, 106, 9, 196, 173, 185, 172, 156, 158, 32, 11, 200, 150, 11, 4, 197, 198, 172, 157, 189, 8, 7, 1, 153, 15, 27, 151, 159, 177, 188, 1, 175, 157, 179, 14, 9, 
+#> 164, 152, 144, 194, 190, 162, 5, 164, 208, 185, 201, 174, 11, 21, 1, 175, 134, 184, 128, 3, 20, 172, 11, 164, 176, 185, 167, 133, 18, 157, 191, 166, 16, 2, 33, 23, 130, 136, 149, 11, 12, 192, 194, 146, 159, 200, 138, 150, 6, 6, 0, 173, 25, 123, 211, 204, 208, 203, 168, 169, 129, 15, 5, 162, 20, 39, 0, 116, 20, 230, 181, 5, 5, 20, 154, 115, 211, 116, 25, 185, 208, 154, 20, 179, 20, 4, 156, 173, 98, 217, 201, 160, 147, 154, 145, 6, 150, 129, 2, 18, 177, 147, 160, 156, 4, 3, 172, 126, 15, 210, 2, 1, 
+#> 176, 185, 193, 5, 7, 147, 125, 200, 17, 134, 149, 148, 7, 15, 18, 175, 147, 189, 174, 1, 169, 180, 2, 10, 151, 111, 154, 179, 160, 138, 150, 139, 23, 16, 231, 151, 2, 184, 16, 131, 126, 103, 145, 190, 12, 11, 0, 176, 182, 161, 137, 171, 168, 187, 156, 17, 169, 157, 0, 4, 149, 132, 3, 10, 162, 129, 122, 161, 184, 174, 135, 141, 136, 0, 3, 177, 146, 116, 145, NA, 205, 173, 138, 0, 167, 163, 8, 200, 116, 18, 133, 17, 167, 143, 163, 160, 168, 10, 1, 181, 4, 161, 159, 172, 13, 8, 129, 162, 213, 183, 209, 
+#> 174, 5, 0, 0, 123, 94, 152, 10, 10, 15, 1, 2, 195, 215, 191, NA, 175, 156, 114, 186, 177, 122, 189, 174, 180, 189, 155, 158, 0, NA, 146, 192, 193, 13, 11, 181, 115, 162, 165, 7, 27, 206, 186, 175, 190, 154, 0, 0, 200, 146, 139, 184, 154, 186, 161, 0, 4, 155, 169, 168, 141, 3, 7, 1, 0, 157, 230, 126, 135, 175, NA, 0, 163, 147, 168, 144, NA, 3, 24, 179, 160, 1, 188, 175, 177, 103, NA, 178, 175, 180, 173, 153, 9, NA, 150, 182, 0, 114, 92, 13, 163, 177, 163, 132, 151, 240, 166, 182, 166, 177, 136, 4, 
+#> 192, 1, 0, 167, 0, 5, 211, 25, 238, 139, 185, 1, 144, 139, 163, 165, 198, 180, 13, NA, 12, 154, 138, 155, 213, 138, NA, 1, 162, 137, 147, NA, 2, NA, 162, 102, 129, 225, 144, 123, 155, 175, NA, 0, NA, 140, 10, 160, 168, 165, 145, 0, 0, 133, 188, 183, 181, 190, 173, 7, 171, 101, 1, 162, NA, 161, 3, 13, 158, NA, 0, 148, 182, 125, 194, 203, 147, 145, 143, 142, 8, 129, 110, 211, 180, 173, 18, 140, 1, 158, 163, 171, 122, 2, 11, 22, 188, 121, 0, 165, 0, 178, 166, NA, 192, 187, 183, 208, 0, 0, 167, 179, 
+#> 152, 175, 163, 190, 131, 180, NA, 0, 116, 124, 143, 176, 149, 119, 180, 173, 1, 10, NA, 165, 201, 205, 120, 200, 194, 12, 157, 0, 182, 160, 174, 0, 156, 149, 107, 177, 0, 0, 0, 4, 185, 145, 206, 219, 150, 154, 184, NA, 7, 126, 202, 153, 183, 0, 0, 139, 180, 12, NA, 0, 15, 20, 174, 155, 182, 0, 0, NA, NA, 159, 183, 163, 7, 0, 0, 0, 146, 163, 156, 17, 164, 153, 197, 188, 95, 0, 174, 0, 191, 206, 0, 14, 0, 0, 179, NA, NA, 111, 181, 134, 0, 0, 196, 147, 145, 194, 166, 168, 130, 172, 198, 139, 148, 0, 
+#> 206, 0, 159, 107, 155, 0, 140, 179, 194, 3, 157, 187, 146, 150, 215, 200, 165, 19, 180, 1, 193, 183, 171, 182, 181, 199, 151, 163, 140, 0, 8, 166, 130, 10, 0, 153, 131, 14, 148, 178, 217, 163, 176, 185, 0, 177, 187, 0, 0, 185, 157, 203, 153, 12, 190, 172, 0, 98, 167, 17, 159, 189, 212, 206, 0, 0, 0, 0, 2, 0, 17, 15, 0, 172, 187, 141, 165, 181, 181, 141, 198, 161, 177, 0, 174, 173, 0, 0, 0, 12, 177, 148, 151, 0, 0, 140, 186, 172, 1, 0, 158, 155, 174, 150, 135, 165, 2)]
+#> Groups: playerID [906]
+#> 
+#>    playerID yearID teamID     G    AB     R     H
+#>       <chr>  <int> <fctr> <int> <int> <int> <int>
+#> 1  bondto01   1880    BSN    76   282    27    62
+#> 2 hinespa01   1887    WS8   123   478    83   147
+#> 3 hinespa01   1888    IN3   133   513    84   144
+#> 4 radboch01   1883    PRO    89   381    59   108
+#> # ... with 991 more rows
+

Finally, ntile() divides the data up into n evenly sized buckets. It’s a coarse ranking, and it can be used in with mutate() to divide the data into buckets for further summary. For example, we could use ntile() to divide the players within a team into four ranked groups, and calculate the average number of games within each group.

+
by_team_player <- group_by(batting, teamID, playerID)
+by_team <- summarise(by_team_player, G = sum(G))
+by_team_quartile <- group_by(by_team, quartile = ntile(G, 4))
+summarise(by_team_quartile, mean(G))
+#> # A tibble: 4 × 2
+#>   quartile `mean(G)`
+#>      <int>     <dbl>
+#> 1        1  27.16460
+#> 2        2  97.61757
+#> 3        3 271.80831
+#> 4        4 976.00873
+

All ranking functions rank from lowest to highest so that small input values get small ranks. Use desc() to rank from highest to lowest.

+
+
+

+Lead and lag

+

lead() and lag() produce offset versions of a input vector that is either ahead of or behind the original vector.

+
x <- 1:5
+lead(x)
+#> [1]  2  3  4  5 NA
+lag(x)
+#> [1] NA  1  2  3  4
+

You can use them to:

+
    +
  • +

    Compute differences or percent changes.

    +
    # Compute the relative change in games played
+mutate(players, G_delta = G - lag(G))
    +

    Using lag() is more convenient than diff() because for n inputs diff() returns n - 1 outputs.

    +
    • +
  • +

    Find out when a value changes.

    +
    # Find when a player changed teams
+filter(players, teamID != lag(teamID))
    +
    • +
+

lead() and lag() have an optional argument order_by. If set, instead of using the row order to determine which value comes before another, they will use another variable. This important if you have not already sorted the data, or you want to sort one way and lag another.

+

Here’s a simple example of what happens if you don’t specify order_by when you need it:

+
df <- data.frame(year = 2000:2005, value = (0:5) ^ 2)
+scrambled <- df[sample(nrow(df)), ]
+
+wrong <- mutate(scrambled, running = cumsum(value))
+arrange(wrong, year)
+#>   year value running
+#> 1 2000     0      39
+#> 2 2001     1       1
+#> 3 2002     4      39
+#> 4 2003     9      35
+#> 5 2004    16      55
+#> 6 2005    25      26
+
+right <- mutate(scrambled, running = order_by(year, cumsum(value)))
+arrange(right, year)
+#>   year value running
+#> 1 2000     0       0
+#> 2 2001     1       1
+#> 3 2002     4       5
+#> 4 2003     9      14
+#> 5 2004    16      30
+#> 6 2005    25      55
+
+
+

+Cumulative aggregates

+

Base R provides cumulative sum (cumsum()), cumulative min (cummin()) and cumulative max (cummax()). (It also provides cumprod() but that is rarely useful). Other common accumulating functions are cumany() and cumall(), cumulative versions of || and &&, and cummean(), a cumulative mean. These are not included in base R, but efficient versions are provided by dplyr.

+

cumany() and cumall() are useful for selecting all rows up to, or all rows after, a condition is true for the first (or last) time. For example, we can use cumany() to find all records for a player after they played a year with 150 games:

+
filter(players, cumany(G > 150))
+

Like lead and lag, you may want to control the order in which the accumulation occurs. None of the built in functions have an order_by argument so dplyr provides a helper: order_by(). You give it the variable you want to order by, and then the call to the window function:

+
x <- 1:10
+y <- 10:1
+order_by(y, cumsum(x))
+#>  [1] 55 54 52 49 45 40 34 27 19 10
+

This function uses a bit of non-standard evaluation, so I wouldn’t recommend using it inside another function; use the simpler but less concise with_order() instead.

+
+
+

+Recycled aggregates

+

R’s vector recycling make it easy to select values that are higher or lower than a summary. I call this a recycled aggregate because the value of the aggregate is recycled to be the same length as the original vector. Recycled aggregates are useful if you want to find all records greater than the mean or less than the median:

+
filter(players, G > mean(G))
+filter(players, G < median(G))
+

While most SQL databases don’t have an equivalent of median() or quantile(), when filtering you can achieve the same effect with ntile(). For example, x > median(x) is equivalent to ntile(x, 2) == 2; x > quantile(x, 75) is equivalent to ntile(x, 100) > 75 or ntile(x, 4) > 3.

+
filter(players, ntile(G, 2) == 2)
+

You can also use this idea to select the records with the highest (x == max(x)) or lowest value (x == min(x)) for a field, but the ranking functions give you more control over ties, and allow you to select any number of records.

+

Recycled aggregates are also useful in conjunction with mutate(). For example, with the batting data, we could compute the “career year”, the number of years a player has played since they entered the league:

+
mutate(players, career_year = yearID - min(yearID) + 1)
+#> Source: local data frame [c("bondto01", "bondto01", "bondto01", "bondto01", "bondto01", "bondto01", "bondto01", "bondto01", "bondto01", "bondto01", "bondto01", "hinespa01", "hinespa01", "hinespa01", "hinespa01", "hinespa01", "hinespa01", "hinespa01", "hinespa01", "hinespa01", "hinespa01", "hinespa01", "hinespa01", "hinespa01", "hinespa01", "hinespa01", "hinespa01", "hinespa01", "hinespa01", "hinespa01", "hinespa01", "hinespa01", "heckegu01", "heckegu01", "heckegu01", "heckegu01", "heckegu01", "heckegu01", "heckegu01", "heckegu01", 
+#> "heckegu01", "radboch01", "radboch01", "radboch01", "radboch01", "radboch01", "radboch01", "radboch01", "radboch01", "radboch01", "radboch01", "radboch01", "radboch01", "oneilti01", "oneilti01", "oneilti01", "oneilti01", "oneilti01", "oneilti01", "oneilti01", "oneilti01", "oneilti01", "oneilti01", "keefeti01", "keefeti01", "keefeti01", "keefeti01", "keefeti01", "keefeti01", "keefeti01", "keefeti01", "keefeti01", "keefeti01", "keefeti01", "keefeti01", "keefeti01", "keefeti01", "keefeti01", "clarkjo01", 
+#> "clarkjo01", "clarkjo01", "clarkjo01", "clarkjo01", "clarkjo01", "clarkjo01", "clarkjo01", "clarkjo01", "clarkjo01", "clarkjo01", "clarkjo01", "clarkjo01", "rusieam01", "rusieam01", "rusieam01", "rusieam01", "rusieam01", "rusieam01", "rusieam01", "rusieam01", "rusieam01", "rusieam01", "duffyhu01", "duffyhu01", "duffyhu01", "duffyhu01", "duffyhu01", "duffyhu01", "duffyhu01", "duffyhu01", "duffyhu01", "duffyhu01", "duffyhu01", "duffyhu01", "duffyhu01", "duffyhu01", "duffyhu01", "duffyhu01", "duffyhu01", 
+#> "youngcy01", "youngcy01", "youngcy01", "youngcy01", "youngcy01", "youngcy01", "youngcy01", "youngcy01", "youngcy01", "youngcy01", "youngcy01", "youngcy01", "youngcy01", "youngcy01", "youngcy01", "youngcy01", "youngcy01", "youngcy01", "youngcy01", "youngcy01", "youngcy01", "youngcy01", "youngcy01", "lajoina01", "lajoina01", "lajoina01", "lajoina01", "lajoina01", "lajoina01", "lajoina01", "lajoina01", "lajoina01", "lajoina01", "lajoina01", "lajoina01", "lajoina01", "lajoina01", "lajoina01", "lajoina01", 
+#> "lajoina01", "lajoina01", "lajoina01", "lajoina01", "lajoina01", "lajoina01", "wadderu01", "wadderu01", "wadderu01", "wadderu01", "wadderu01", "wadderu01", "wadderu01", "wadderu01", "wadderu01", "wadderu01", "wadderu01", "wadderu01", "wadderu01", "wadderu01", "mathech01", "mathech01", "mathech01", "mathech01", "mathech01", "mathech01", "mathech01", "mathech01", "mathech01", "mathech01", "mathech01", "mathech01", "mathech01", "mathech01", "mathech01", "mathech01", "mathech01", "mathech01", "chaseha01", 
+#> "chaseha01", "chaseha01", "chaseha01", "chaseha01", "chaseha01", "chaseha01", "chaseha01", "chaseha01", "chaseha01", "chaseha01", "chaseha01", "chaseha01", "chaseha01", "chaseha01", "chaseha01", "chaseha01", "lordha01", "lordha01", "lordha01", "lordha01", "lordha01", "lordha01", "lordha01", "lordha01", "lordha01", "lordha01", "crigelo01", "crigelo01", "crigelo01", "crigelo01", "crigelo01", "crigelo01", "crigelo01", "crigelo01", "crigelo01", "crigelo01", "crigelo01", "crigelo01", "crigelo01", "crigelo01", 
+#> "crigelo01", "crigelo01", "sullibi03", "sullibi03", "sullibi03", "sullibi03", "sullibi03", "sullibi03", "sullibi03", "sullibi03", "sullibi03", "sullibi03", "sullibi03", "sullibi03", "sullibi03", "sullibi03", "sullibi03", "sullibi03", "crawfsa01", "crawfsa01", "crawfsa01", "crawfsa01", "crawfsa01", "crawfsa01", "crawfsa01", "crawfsa01", "crawfsa01", "crawfsa01", "crawfsa01", "crawfsa01", "crawfsa01", "crawfsa01", "crawfsa01", "crawfsa01", "crawfsa01", "crawfsa01", "crawfsa01", "stonege01", "stonege01", 
+#> "stonege01", "stonege01", "stonege01", "stonege01", "stonege01", "walshed01", "walshed01", "walshed01", "walshed01", "walshed01", "walshed01", "walshed01", "walshed01", "walshed01", "walshed01", "walshed01", "walshed01", "walshed01", "walshed01", "jossad01", "jossad01", "jossad01", "jossad01", "jossad01", "jossad01", "jossad01", "jossad01", "jossad01", "donovbi01", "donovbi01", "donovbi01", "donovbi01", "donovbi01", "donovbi01", "donovbi01", "donovbi01", "donovbi01", "donovbi01", "donovbi01", "donovbi01", 
+#> "donovbi01", "donovbi01", "donovbi01", "donovbi01", "donovbi01", "donovbi01", "cobbty01", "cobbty01", "cobbty01", "cobbty01", "cobbty01", "cobbty01", "cobbty01", "cobbty01", "cobbty01", "cobbty01", "cobbty01", "cobbty01", "cobbty01", "cobbty01", "cobbty01", "cobbty01", "cobbty01", "cobbty01", "cobbty01", "cobbty01", "cobbty01", "cobbty01", "cobbty01", "cobbty01", "wallabo01", "wallabo01", "wallabo01", "wallabo01", "wallabo01", "wallabo01", "wallabo01", "wallabo01", "wallabo01", "wallabo01", "wallabo01", 
+#> "wallabo01", "wallabo01", "wallabo01", "wallabo01", "wallabo01", "wallabo01", "wallabo01", "wallabo01", "wallabo01", "wallabo01", "wallabo01", "wallabo01", "wallabo01", "wallabo01", "devliar01", "devliar01", "devliar01", "devliar01", "devliar01", "devliar01", "devliar01", "devliar01", "devliar01", "devliar01", "bresnro01", "bresnro01", "bresnro01", "bresnro01", "bresnro01", "bresnro01", "bresnro01", "bresnro01", "bresnro01", "bresnro01", "bresnro01", "bresnro01", "bresnro01", "bresnro01", "bresnro01", 
+#> "bresnro01", "bresnro01", "bresnro01", "klingjo01", "klingjo01", "klingjo01", "klingjo01", "klingjo01", "klingjo01", "klingjo01", "klingjo01", "klingjo01", "klingjo01", "klingjo01", "klingjo01", "klingjo01", "klingjo01", "donlimi01", "donlimi01", "donlimi01", "donlimi01", "donlimi01", "donlimi01", "donlimi01", "donlimi01", "donlimi01", "donlimi01", "donlimi01", "donlimi01", "donlimi01", "donlimi01", "clarkfr01", "clarkfr01", "clarkfr01", "clarkfr01", "clarkfr01", "clarkfr01", "clarkfr01", "clarkfr01", 
+#> "clarkfr01", "clarkfr01", "clarkfr01", "clarkfr01", "clarkfr01", "clarkfr01", "clarkfr01", "clarkfr01", "clarkfr01", "clarkfr01", "clarkfr01", "clarkfr01", "clarkfr01", "brownmo01", "brownmo01", "brownmo01", "brownmo01", "brownmo01", "brownmo01", "brownmo01", "brownmo01", "brownmo01", "brownmo01", "brownmo01", "brownmo01", "brownmo01", "brownmo01", "brownmo01", "ruckena01", "ruckena01", "ruckena01", "ruckena01", "ruckena01", "ruckena01", "ruckena01", "ruckena01", "ruckena01", "ruckena01", "wagneho01", 
+#> "wagneho01", "wagneho01", "wagneho01", "wagneho01", "wagneho01", "wagneho01", "wagneho01", "wagneho01", "wagneho01", "wagneho01", "wagneho01", "wagneho01", "wagneho01", "wagneho01", "wagneho01", "wagneho01", "wagneho01", "wagneho01", "wagneho01", "wagneho01", "tennefr02", "tennefr02", "tennefr02", "tennefr02", "tennefr02", "tennefr02", "tennefr02", "tennefr02", "tennefr02", "tennefr02", "tennefr02", "tennefr02", "tennefr02", "tennefr02", "tennefr02", "tennefr02", "tennefr02", "eversjo01", "eversjo01", 
+#> "eversjo01", "eversjo01", "eversjo01", "eversjo01", "eversjo01", "eversjo01", "eversjo01", "eversjo01", "eversjo01", "eversjo01", "eversjo01", "eversjo01", "eversjo01", "eversjo01", "eversjo01", "eversjo01", "eversjo01", "willivi01", "willivi01", "willivi01", "willivi01", "willivi01", "willivi01", "willivi01", "willivi01", "willivi01", "willivi01", "willivi01", "willivi01", "willivi01", "reulbed01", "reulbed01", "reulbed01", "reulbed01", "reulbed01", "reulbed01", "reulbed01", "reulbed01", "reulbed01", 
+#> "reulbed01", "reulbed01", "reulbed01", "reulbed01", "reulbed01", "schulfr01", "schulfr01", "schulfr01", "schulfr01", "schulfr01", "schulfr01", "schulfr01", "schulfr01", "schulfr01", "schulfr01", "schulfr01", "schulfr01", "schulfr01", "schulfr01", "schulfr01", "schulfr01", "schulfr01", "collied01", "collied01", "collied01", "collied01", "collied01", "collied01", "collied01", "collied01", "collied01", "collied01", "collied01", "collied01", "collied01", "collied01", "collied01", "collied01", "collied01", 
+#> "collied01", "collied01", "collied01", "collied01", "collied01", "collied01", "collied01", "collied01", "carribi02", "carribi02", "carribi02", "carribi02", "carribi02", "carribi02", "carribi02", "carribi02", "carribi02", "carribi02", "streega01", "streega01", "streega01", "streega01", "streega01", "streega01", "streega01", "streega01", "streega01", "streega01", "speaktr01", "speaktr01", "speaktr01", "speaktr01", "speaktr01", "speaktr01", "speaktr01", "speaktr01", "speaktr01", "speaktr01", "speaktr01", 
+#> "speaktr01", "speaktr01", "speaktr01", "speaktr01", "speaktr01", "speaktr01", "speaktr01", "speaktr01", "speaktr01", "speaktr01", "speaktr01", "planked01", "planked01", "planked01", "planked01", "planked01", "planked01", "planked01", "planked01", "planked01", "planked01", "planked01", "planked01", "planked01", "planked01", "planked01", "planked01", "planked01", "johnswa01", "johnswa01", "johnswa01", "johnswa01", "johnswa01", "johnswa01", "johnswa01", "johnswa01", "johnswa01", "johnswa01", "johnswa01", 
+#> "johnswa01", "johnswa01", "johnswa01", "johnswa01", "johnswa01", "johnswa01", "johnswa01", "johnswa01", "johnswa01", "johnswa01", "mullige01", "mullige01", "mullige01", "mullige01", "mullige01", "mullige01", "mullige01", "mullige01", "mullige01", "mullige01", "mullige01", "mullige01", "mullige01", "mullige01", "mullige01", "woodjo02", "woodjo02", "woodjo02", "woodjo02", "woodjo02", "woodjo02", "woodjo02", "woodjo02", "woodjo02", "woodjo02", "woodjo02", "woodjo02", "woodjo02", "woodjo02", "bushdo01", 
+#> "bushdo01", "bushdo01", "bushdo01", "bushdo01", "bushdo01", "bushdo01", "bushdo01", "bushdo01", "bushdo01", "bushdo01", "bushdo01", "bushdo01", "bushdo01", "bushdo01", "bushdo01", "bushdo01", "gibsoge01", "gibsoge01", "gibsoge01", "gibsoge01", "gibsoge01", "gibsoge01", "gibsoge01", "gibsoge01", "gibsoge01", "gibsoge01", "gibsoge01", "gibsoge01", "gibsoge01", "gibsoge01", "adamsba01", "adamsba01", "adamsba01", "adamsba01", "adamsba01", "adamsba01", "adamsba01", "adamsba01", "adamsba01", "adamsba01", 
+#> "adamsba01", "adamsba01", "adamsba01", "adamsba01", "adamsba01", "adamsba01", "adamsba01", "adamsba01", "adamsba01", "chancfr01", "chancfr01", "chancfr01", "chancfr01", "chancfr01", "chancfr01", "chancfr01", "chancfr01", "chancfr01", "chancfr01", "chancfr01", "chancfr01", "chancfr01", "chancfr01", "chancfr01", "chancfr01", "chancfr01", "leachto01", "leachto01", "leachto01", "leachto01", "leachto01", "leachto01", "leachto01", "leachto01", "leachto01", "leachto01", "leachto01", "leachto01", "leachto01", 
+#> "leachto01", "leachto01", "leachto01", "leachto01", "leachto01", "leachto01", "leachto01", "camniho01", "camniho01", "camniho01", "camniho01", "camniho01", "camniho01", "camniho01", "camniho01", "camniho01", "camniho01", "camniho01", "camniho01", "hofmaso01", "hofmaso01", "hofmaso01", "hofmaso01", "hofmaso01", "hofmaso01", "hofmaso01", "hofmaso01", "hofmaso01", "hofmaso01", "hofmaso01", "hofmaso01", "hofmaso01", "hofmaso01", "hofmaso01", "hofmaso01", "thomair01", "thomair01", "thomair01", "thomair01", 
+#> "thomair01", "thomair01", "thomair01", "thomair01", "thomair01", "thomair01", "sweened01", "sweened01", "sweened01", "sweened01", "sweened01", "sweened01", "sweened01", "sweened01", "sweened01", "coombja01", "coombja01", "coombja01", "coombja01", "coombja01", "coombja01", "coombja01", "coombja01", "coombja01", "coombja01", "coombja01", "coombja01", "coombja01", "coombja01", "bendech01", "bendech01", "bendech01", "bendech01", "bendech01", "bendech01", "bendech01", "bendech01", "bendech01", "bendech01", 
+#> "bendech01", "bendech01", "bendech01", "bendech01", "bendech01", "bendech01", "archeji01", "archeji01", "archeji01", "archeji01", "archeji01", "archeji01", "archeji01", "archeji01", "archeji01", "archeji01", "archeji01", "archeji01", "archeji01", "archeji01", "mageesh01", "mageesh01", "mageesh01", "mageesh01", "mageesh01", "mageesh01", "mageesh01", "mageesh01", "mageesh01", "mageesh01", "mageesh01", "mageesh01", "mageesh01", "mageesh01", "mageesh01", "mageesh01", "mageesh01", "coleki01", "coleki01", 
+#> "coleki01", "coleki01", "coleki01", "coleki01", "coleki01", "bakerfr01", "bakerfr01", "bakerfr01", "bakerfr01", "bakerfr01", "bakerfr01", "bakerfr01", "bakerfr01", "bakerfr01", "bakerfr01", "bakerfr01", "bakerfr01", "bakerfr01", "stanaos01", "stanaos01", "stanaos01", "stanaos01", "stanaos01", "stanaos01", "stanaos01", "stanaos01", "stanaos01", "stanaos01", "stanaos01", "stanaos01", "stanaos01", "stanaos01", "greggve01", "greggve01", "greggve01", "greggve01", "greggve01", "greggve01", "greggve01", 
+#> "greggve01", "greggve01", "jacksjo01", "jacksjo01", "jacksjo01", "jacksjo01", "jacksjo01", "jacksjo01", "jacksjo01", "jacksjo01", "jacksjo01", "jacksjo01", "jacksjo01", "jacksjo01", "jacksjo01", "jacksjo01", "dooinre01", "dooinre01", "dooinre01", "dooinre01", "dooinre01", "dooinre01", "dooinre01", "dooinre01", "dooinre01", "dooinre01", "dooinre01", "dooinre01", "dooinre01", "dooinre01", "dooinre01", "dooinre01", "meyerch01", "meyerch01", "meyerch01", "meyerch01", "meyerch01", "meyerch01", "meyerch01", 
+#> "meyerch01", "meyerch01", "meyerch01", "alexape01", "alexape01", "alexape01", "alexape01", "alexape01", "alexape01", "alexape01", "alexape01", "alexape01", "alexape01", "alexape01", "alexape01", "alexape01", "alexape01", "alexape01", "alexape01", "alexape01", "alexape01", "alexape01", "alexape01", "alexape01", "daubeja01", "daubeja01", "daubeja01", "daubeja01", "daubeja01", "daubeja01", "daubeja01", "daubeja01", "daubeja01", "daubeja01", "daubeja01", "daubeja01", "daubeja01", "daubeja01", "daubeja01", 
+#> "doylela01", "doylela01", "doylela01", "doylela01", "doylela01", "doylela01", "doylela01", "doylela01", "doylela01", "doylela01", "doylela01", "doylela01", "doylela01", "doylela01", "doylela01", "loberha01", "loberha01", "loberha01", "loberha01", "loberha01", "loberha01", "loberha01", "loberha01", "loberha01", "loberha01", "loberha01", "loberha01", "loberha01", "loberha01", "marquru01", "marquru01", "marquru01", "marquru01", "marquru01", "marquru01", "marquru01", "marquru01", "marquru01", "marquru01", 
+#> "marquru01", "marquru01", "marquru01", "marquru01", "marquru01", "marquru01", "marquru01", "marquru01", "marquru01", "mcinnst01", "mcinnst01", "mcinnst01", "mcinnst01", "mcinnst01", "mcinnst01", "mcinnst01", "mcinnst01", "mcinnst01", "mcinnst01", "mcinnst01", "mcinnst01", "mcinnst01", "mcinnst01", "mcinnst01", "mcinnst01", "mcinnst01", "mcinnst01", "mcinnst01", "gardnla01", "gardnla01", "gardnla01", "gardnla01", "gardnla01", "gardnla01", "gardnla01", "gardnla01", "gardnla01", "gardnla01", "gardnla01", 
+#> "gardnla01", "gardnla01", "gardnla01", "gardnla01", "gardnla01", "gardnla01", "ainsmed01", "ainsmed01", "ainsmed01", "ainsmed01", "ainsmed01", "ainsmed01", "ainsmed01", "ainsmed01", "ainsmed01", "ainsmed01", "ainsmed01", "ainsmed01", "ainsmed01", "ainsmed01", "ainsmed01", "ainsmed01", "ainsmed01", "wagnehe01", "wagnehe01", "wagnehe01", "wagnehe01", "wagnehe01", "wagnehe01", "wagnehe01", "wagnehe01", "wagnehe01", "wagnehe01", "wagnehe01", "wagnehe01", "zimmehe01", "zimmehe01", "zimmehe01", "zimmehe01", 
+#> "zimmehe01", "zimmehe01", "zimmehe01", "zimmehe01", "zimmehe01", "zimmehe01", "zimmehe01", "zimmehe01", "zimmehe01", "zimmehe01", "paskedo01", "paskedo01", "paskedo01", "paskedo01", "paskedo01", "paskedo01", "paskedo01", "paskedo01", "paskedo01", "paskedo01", "paskedo01", "paskedo01", "paskedo01", "paskedo01", "paskedo01", "wilsoch01", "wilsoch01", "wilsoch01", "wilsoch01", "wilsoch01", "wilsoch01", "wilsoch01", "wilsoch01", "wilsoch01", "tesreje01", "tesreje01", "tesreje01", "tesreje01", "tesreje01", 
+#> "tesreje01", "tesreje01", "schanwa01", "schanwa01", "schanwa01", "schanwa01", "schanwa01", "schanwa01", "schanwa01", "schanwa01", "schanwa01", "schanwa01", "schanwa01", "schanwa01", "schanwa01", "schanwa01", "schanwa01", "schanwa01", "schanwa01", "schanwa01", "schanwa01", "falkecy01", "falkecy01", "falkecy01", "falkecy01", "falkecy01", "falkecy01", "falkecy01", "falkecy01", "falkecy01", "falkecy01", "falkecy01", "falkecy01", "falkecy01", "falkecy01", "barryja01", "barryja01", "barryja01", "barryja01", 
+#> "barryja01", "barryja01", "barryja01", "barryja01", "barryja01", "barryja01", "barryja01", "barryja01", "vioxji01", "vioxji01", "vioxji01", "vioxji01", "vioxji01", "cravaga01", "cravaga01", "cravaga01", "cravaga01", "cravaga01", "cravaga01", "cravaga01", "cravaga01", "cravaga01", "cravaga01", "cravaga01", "cravaga01", "wheatza01", "wheatza01", "wheatza01", "wheatza01", "wheatza01", "wheatza01", "wheatza01", "wheatza01", "wheatza01", "wheatza01", "wheatza01", "wheatza01", "wheatza01", "wheatza01", 
+#> "wheatza01", "wheatza01", "wheatza01", "wheatza01", "wheatza01", "schalra01", "schalra01", "schalra01", "schalra01", "schalra01", "schalra01", "schalra01", "schalra01", "schalra01", "schalra01", "schalra01", "schalra01", "schalra01", "schalra01", "schalra01", "schalra01", "schalra01", "schalra01", "leonadu01", "leonadu01", "leonadu01", "leonadu01", "leonadu01", "leonadu01", "leonadu01", "leonadu01", "leonadu01", "leonadu01", "leonadu01", "maranra01", "maranra01", "maranra01", "maranra01", "maranra01", 
+#> "maranra01", "maranra01", "maranra01", "maranra01", "maranra01", "maranra01", "maranra01", "maranra01", "maranra01", "maranra01", "maranra01", "maranra01", "maranra01", "maranra01", "maranra01", "maranra01", "maranra01", "maranra01", "wingoiv01", "wingoiv01", "wingoiv01", "wingoiv01", "wingoiv01", "wingoiv01", "wingoiv01", "wingoiv01", "wingoiv01", "wingoiv01", "wingoiv01", "wingoiv01", "wingoiv01", "wingoiv01", "wingoiv01", "wingoiv01", "wingoiv01", "burnsge01", "burnsge01", "burnsge01", "burnsge01", 
+#> "burnsge01", "burnsge01", "burnsge01", "burnsge01", "burnsge01", "burnsge01", "burnsge01", "burnsge01", "burnsge01", "burnsge01", "burnsge01", "jamesbi02", "jamesbi02", "jamesbi02", "jamesbi02", "maisefr01", "maisefr01", "maisefr01", "maisefr01", "maisefr01", "maisefr01", "scottji01", "scottji01", "scottji01", "scottji01", "scottji01", "scottji01", "scottji01", "scottji01", "scottji01", "grohhe01", "grohhe01", "grohhe01", "grohhe01", "grohhe01", "grohhe01", "grohhe01", "grohhe01", "grohhe01", "grohhe01", 
+#> "grohhe01", "grohhe01", "grohhe01", "grohhe01", "grohhe01", "grohhe01", "grohhe01", "snydefr01", "snydefr01", "snydefr01", "snydefr01", "snydefr01", "snydefr01", "snydefr01", "snydefr01", "snydefr01", "snydefr01", "snydefr01", "snydefr01", "snydefr01", "snydefr01", "snydefr01", "snydefr01", "snydefr01", "bancrda01", "bancrda01", "bancrda01", "bancrda01", "bancrda01", "bancrda01", "bancrda01", "bancrda01", "bancrda01", "bancrda01", "bancrda01", "bancrda01", "bancrda01", "bancrda01", "bancrda01", "bancrda01", 
+#> "bancrda01", "saiervi01", "saiervi01", "saiervi01", "saiervi01", "saiervi01", "saiervi01", "saiervi01", "saiervi01", "willicy01", "willicy01", "willicy01", "willicy01", "willicy01", "willicy01", "willicy01", "willicy01", "willicy01", "willicy01", "willicy01", "willicy01", "willicy01", "willicy01", "willicy01", "willicy01", "willicy01", "willicy01", "willicy01", "mamaual01", "mamaual01", "mamaual01", "mamaual01", "mamaual01", "mamaual01", "mamaual01", "mamaual01", "mamaual01", "mamaual01", "mamaual01", 
+#> "mamaual01", "sislege01", "sislege01", "sislege01", "sislege01", "sislege01", "sislege01", "sislege01", "sislege01", "sislege01", "sislege01", "sislege01", "sislege01", "sislege01", "sislege01", "sislege01", "sislege01", "ruthba01", "ruthba01", "ruthba01", "ruthba01", "ruthba01", "ruthba01", "ruthba01", "ruthba01", "ruthba01", "ruthba01", "ruthba01", "ruthba01", "ruthba01", "ruthba01", "ruthba01", "ruthba01", "ruthba01", "ruthba01", "ruthba01", "ruthba01", "ruthba01", "ruthba01", "herzobu01", "herzobu01", 
+#> "herzobu01", "herzobu01", "herzobu01", "herzobu01", "herzobu01", "herzobu01", "herzobu01", "herzobu01", "herzobu01", "herzobu01", "herzobu01", "herzobu01", "herzobu01", "herzobu01", "hornsro01", "hornsro01", "hornsro01", "hornsro01", "hornsro01", "hornsro01", "hornsro01", "hornsro01", "hornsro01", "hornsro01", "hornsro01", "hornsro01", "hornsro01", "hornsro01", "hornsro01", "hornsro01", "hornsro01", "hornsro01", "hornsro01", "hornsro01", "hornsro01", "hornsro01", "hornsro01", "hornsro01", "gowdyha01", 
+#> "gowdyha01", "gowdyha01", "gowdyha01", "gowdyha01", "gowdyha01", "gowdyha01", "gowdyha01", "gowdyha01", "gowdyha01", "gowdyha01", "gowdyha01", "gowdyha01", "gowdyha01", "gowdyha01", "gowdyha01", "gowdyha01", "gowdyha01", "gowdyha01", "roberda01", "roberda01", "roberda01", "roberda01", "roberda01", "roberda01", "roberda01", "roberda01", "roberda01", "roberda01", "roberda01", "weavebu01", "weavebu01", "weavebu01", "weavebu01", "weavebu01", "weavebu01", "weavebu01", "weavebu01", "weavebu01", "felscha01", 
+#> "felscha01", "felscha01", "felscha01", "felscha01", "felscha01", "cicoted01", "cicoted01", "cicoted01", "cicoted01", "cicoted01", "cicoted01", "cicoted01", "cicoted01", "cicoted01", "cicoted01", "cicoted01", "cicoted01", "cicoted01", "cicoted01", "cicoted01", "chapmra01", "chapmra01", "chapmra01", "chapmra01", "chapmra01", "chapmra01", "chapmra01", "chapmra01", "chapmra01", "killebi01", "killebi01", "killebi01", "killebi01", "killebi01", "killebi01", "killebi01", "killebi01", "killebi01", "killebi01", 
+#> "killebi01", "killebi01", "killebi01", "roushed01", "roushed01", "roushed01", "roushed01", "roushed01", "roushed01", "roushed01", "roushed01", "roushed01", "roushed01", "roushed01", "roushed01", "roushed01", "roushed01", "roushed01", "roushed01", "roushed01", "roushed01", "roushed01", "careyma01", "careyma01", "careyma01", "careyma01", "careyma01", "careyma01", "careyma01", "careyma01", "careyma01", "careyma01", "careyma01", "careyma01", "careyma01", "careyma01", "careyma01", "careyma01", "careyma01", 
+#> "careyma01", "careyma01", "careyma01", "careyma01", "coopewi01", "coopewi01", "coopewi01", "coopewi01", "coopewi01", "coopewi01", "coopewi01", "coopewi01", "coopewi01", "coopewi01", "coopewi01", "coopewi01", "coopewi01", "coopewi01", "coopewi01", "coopewi01", "oneilst01", "oneilst01", "oneilst01", "oneilst01", "oneilst01", "oneilst01", "oneilst01", "oneilst01", "oneilst01", "oneilst01", "oneilst01", "oneilst01", "oneilst01", "oneilst01", "oneilst01", "oneilst01", "oneilst01", "hoopeha01", "hoopeha01", 
+#> "hoopeha01", "hoopeha01", "hoopeha01", "hoopeha01", "hoopeha01", "hoopeha01", "hoopeha01", "hoopeha01", "hoopeha01", "hoopeha01", "hoopeha01", "hoopeha01", "hoopeha01", "hoopeha01", "hoopeha01", "vaughhi01", "vaughhi01", "vaughhi01", "vaughhi01", "vaughhi01", "vaughhi01", "vaughhi01", "vaughhi01", "vaughhi01", "vaughhi01", "vaughhi01", "vaughhi01", "vaughhi01", "vaughhi01", "holloch01", "holloch01", "holloch01", "holloch01", "holloch01", "holloch01", "holloch01", "cutshge01", "cutshge01", "cutshge01", 
+#> "cutshge01", "cutshge01", "cutshge01", "cutshge01", "cutshge01", "cutshge01", "cutshge01", "cutshge01", "cutshge01", "grimebu01", "grimebu01", "grimebu01", "grimebu01", "grimebu01", "grimebu01", "grimebu01", "grimebu01", "grimebu01", "grimebu01", "grimebu01", "grimebu01", "grimebu01", "grimebu01", "grimebu01", "grimebu01", "grimebu01", "grimebu01", "grimebu01", "grimebu01", "grimebu01", "grimebu01", "grimebu01", "peckiro01", "peckiro01", "peckiro01", "peckiro01", "peckiro01", "peckiro01", "peckiro01", 
+#> "peckiro01", "peckiro01", "peckiro01", "peckiro01", "peckiro01", "peckiro01", "peckiro01", "peckiro01", "peckiro01", "peckiro01", "peckiro01", "stockmi01", "stockmi01", "stockmi01", "stockmi01", "stockmi01", "stockmi01", "stockmi01", "stockmi01", "stockmi01", "stockmi01", "stockmi01", "stockmi01", "stockmi01", "stockmi01", "myershy01", "myershy01", "myershy01", "myershy01", "myershy01", "myershy01", "myershy01", "myershy01", "myershy01", "myershy01", "myershy01", "myershy01", "myershy01", "myershy01", 
+#> "myershy01", "myershy01", "barneje01", "barneje01", "barneje01", "barneje01", "barneje01", "barneje01", "barneje01", "barneje01", "barneje01", "barneje01", "barneje01", "barneje01", "barneje01", "barneje01", "ricesa01", "ricesa01", "ricesa01", "ricesa01", "ricesa01", "ricesa01", "ricesa01", "ricesa01", "ricesa01", "ricesa01", "ricesa01", "ricesa01", "ricesa01", "ricesa01", "ricesa01", "ricesa01", "ricesa01", "ricesa01", "ricesa01", "ricesa01", "bagbyji01", "bagbyji01", "bagbyji01", "bagbyji01", "bagbyji01", 
+#> "bagbyji01", "bagbyji01", "bagbyji01", "bagbyji01", "covelst01", "covelst01", "covelst01", "covelst01", "covelst01", "covelst01", "covelst01", "covelst01", "covelst01", "covelst01", "covelst01", "covelst01", "covelst01", "covelst01", "shockur01", "shockur01", "shockur01", "shockur01", "shockur01", "shockur01", "shockur01", "shockur01", "shockur01", "shockur01", "shockur01", "shockur01", "shockur01", "scottev01", "scottev01", "scottev01", "scottev01", "scottev01", "scottev01", "scottev01", "scottev01", 
+#> "scottev01", "scottev01", "scottev01", "scottev01", "scottev01", "scottev01", "scottev01", "schmiwa01", "schmiwa01", "schmiwa01", "schmiwa01", "schmiwa01", "schmiwa01", "schmiwa01", "schmiwa01", "schmiwa01", "schmiwa01", "youngro01", "youngro01", "youngro01", "youngro01", "youngro01", "youngro01", "youngro01", "youngro01", "youngro01", "youngro01", "faberre01", "faberre01", "faberre01", "faberre01", "faberre01", "faberre01", "faberre01", "faberre01", "faberre01", "faberre01", "faberre01", "faberre01", 
+#> "faberre01", "faberre01", "faberre01", "faberre01", "faberre01", "faberre01", "faberre01", "faberre01", "maysca01", "maysca01", "maysca01", "maysca01", "maysca01", "maysca01", "maysca01", "maysca01", "maysca01", "maysca01", "maysca01", "maysca01", "maysca01", "maysca01", "maysca01", "maysca01", "friscfr01", "friscfr01", "friscfr01", "friscfr01", "friscfr01", "friscfr01", "friscfr01", "friscfr01", "friscfr01", "friscfr01", "friscfr01", "friscfr01", "friscfr01", "friscfr01", "friscfr01", "friscfr01", 
+#> "friscfr01", "friscfr01", "friscfr01", "kellyge01", "kellyge01", "kellyge01", "kellyge01", "kellyge01", "kellyge01", "kellyge01", "kellyge01", "kellyge01", "kellyge01", "kellyge01", "kellyge01", "kellyge01", "kellyge01", "kellyge01", "kellyge01", "kellyge01", "kellyge01", "bigbeca01", "bigbeca01", "bigbeca01", "bigbeca01", "bigbeca01", "bigbeca01", "bigbeca01", "bigbeca01", "bigbeca01", "bigbeca01", "bigbeca01", "nehfar01", "nehfar01", "nehfar01", "nehfar01", "nehfar01", "nehfar01", "nehfar01", "nehfar01", 
+#> "nehfar01", "nehfar01", "nehfar01", "nehfar01", "nehfar01", "nehfar01", "nehfar01", "nehfar01", "nehfar01", "nehfar01", "duganjo01", "duganjo01", "duganjo01", "duganjo01", "duganjo01", "duganjo01", "duganjo01", "duganjo01", "duganjo01", "duganjo01", "duganjo01", "duganjo01", "duganjo01", "duganjo01", "duganjo01", "bushjo01", "bushjo01", "bushjo01", "bushjo01", "bushjo01", "bushjo01", "bushjo01", "bushjo01", "bushjo01", "bushjo01", "bushjo01", "bushjo01", "bushjo01", "bushjo01", "bushjo01", "bushjo01", 
+#> "bushjo01", "bushjo01", "bushjo01", "rommeed01", "rommeed01", "rommeed01", "rommeed01", "rommeed01", "rommeed01", "rommeed01", "rommeed01", "rommeed01", "rommeed01", "rommeed01", "rommeed01", "rommeed01", "rixeyep01", "rixeyep01", "rixeyep01", "rixeyep01", "rixeyep01", "rixeyep01", "rixeyep01", "rixeyep01", "rixeyep01", "rixeyep01", "rixeyep01", "rixeyep01", "rixeyep01", "rixeyep01", "rixeyep01", "rixeyep01", "rixeyep01", "rixeyep01", "rixeyep01", "rixeyep01", "rixeyep01", "ruethdu01", "ruethdu01", 
+#> "ruethdu01", "ruethdu01", "ruethdu01", "ruethdu01", "ruethdu01", "ruethdu01", "ruethdu01", "ruethdu01", "ruethdu01", "ruethdu01", "ruethdu01", "pippwa01", "pippwa01", "pippwa01", "pippwa01", "pippwa01", "pippwa01", "pippwa01", "pippwa01", "pippwa01", "pippwa01", "pippwa01", "pippwa01", "pippwa01", "pippwa01", "pippwa01", "perkicy01", "perkicy01", "perkicy01", "perkicy01", "perkicy01", "perkicy01", "perkicy01", "perkicy01", "perkicy01", "perkicy01", "perkicy01", "perkicy01", "perkicy01", "perkicy01", 
+#> "perkicy01", "perkicy01", "perkicy01", "heilmha01", "heilmha01", "heilmha01", "heilmha01", "heilmha01", "heilmha01", "heilmha01", "heilmha01", "heilmha01", "heilmha01", "heilmha01", "heilmha01", "heilmha01", "heilmha01", "heilmha01", "heilmha01", "heilmha01", "uhlege01", "uhlege01", "uhlege01", "uhlege01", "uhlege01", "uhlege01", "uhlege01", "uhlege01", "uhlege01", "uhlege01", "uhlege01", "uhlege01", "uhlege01", "uhlege01", "uhlege01", "uhlege01", "uhlege01", "uhlege01", "uhlege01", "ehmkeho01", 
+#> "ehmkeho01", "ehmkeho01", "ehmkeho01", "ehmkeho01", "ehmkeho01", "ehmkeho01", "ehmkeho01", "ehmkeho01", "ehmkeho01", "ehmkeho01", "ehmkeho01", "ehmkeho01", "ehmkeho01", "ehmkeho01", "ehmkeho01", "seweljo01", "seweljo01", "seweljo01", "seweljo01", "seweljo01", "seweljo01", "seweljo01", "seweljo01", "seweljo01", "seweljo01", "seweljo01", "seweljo01", "seweljo01", "seweljo01", "grimmch01", "grimmch01", "grimmch01", "grimmch01", "grimmch01", "grimmch01", "grimmch01", "grimmch01", "grimmch01", "grimmch01", 
+#> "grimmch01", "grimmch01", "grimmch01", "grimmch01", "grimmch01", "grimmch01", "grimmch01", "grimmch01", "grimmch01", "grimmch01", "ofarrbo01", "ofarrbo01", "ofarrbo01", "ofarrbo01", "ofarrbo01", "ofarrbo01", "ofarrbo01", "ofarrbo01", "ofarrbo01", "ofarrbo01", "ofarrbo01", "ofarrbo01", "ofarrbo01", "ofarrbo01", "ofarrbo01", "ofarrbo01", "ofarrbo01", "ofarrbo01", "ofarrbo01", "ofarrbo01", "ofarrbo01", "ofarrbo01", "ofarrbo01", "ofarrbo01", "luquedo01", "luquedo01", "luquedo01", "luquedo01", "luquedo01", 
+#> "luquedo01", "luquedo01", "luquedo01", "luquedo01", "luquedo01", "luquedo01", "luquedo01", "luquedo01", "luquedo01", "luquedo01", "luquedo01", "luquedo01", "luquedo01", "luquedo01", "luquedo01", "morrijo04", "morrijo04", "morrijo04", "morrijo04", "morrijo04", "morrijo04", "morrijo04", "morrijo04", "morrijo04", "morrijo04", "vanceda01", "vanceda01", "vanceda01", "vanceda01", "vanceda01", "vanceda01", "vanceda01", "vanceda01", "vanceda01", "vanceda01", "vanceda01", "vanceda01", "vanceda01", "vanceda01", 
+#> "vanceda01", "vanceda01", "vanceda01", "vanceda01", "judgejo01", "judgejo01", "judgejo01", "judgejo01", "judgejo01", "judgejo01", "judgejo01", "judgejo01", "judgejo01", "judgejo01", "judgejo01", "judgejo01", "judgejo01", "judgejo01", "judgejo01", "judgejo01", "judgejo01", "judgejo01", "judgejo01", "judgejo01", "judgejo01", "bassljo01", "bassljo01", "bassljo01", "bassljo01", "bassljo01", "bassljo01", "bassljo01", "bassljo01", "bassljo01", "jamiech01", "jamiech01", "jamiech01", "jamiech01", "jamiech01", 
+#> "jamiech01", "jamiech01", "jamiech01", "jamiech01", "jamiech01", "jamiech01", "jamiech01", "jamiech01", "jamiech01", "jamiech01", "jamiech01", "jamiech01", "jamiech01", "jamiech01", "thurssl01", "thurssl01", "thurssl01", "thurssl01", "thurssl01", "thurssl01", "thurssl01", "thurssl01", "thurssl01", "thurssl01", "pennohe01", "pennohe01", "pennohe01", "pennohe01", "pennohe01", "pennohe01", "pennohe01", "pennohe01", "pennohe01", "pennohe01", "pennohe01", "pennohe01", "pennohe01", "pennohe01", "pennohe01", 
+#> "pennohe01", "pennohe01", "pennohe01", "pennohe01", "pennohe01", "pennohe01", "pennohe01", "pennohe01", "jackstr01", "jackstr01", "jackstr01", "jackstr01", "jackstr01", "jackstr01", "jackstr01", "jackstr01", "jackstr01", "jackstr01", "jackstr01", "jackstr01", "jackstr01", "jackstr01", "jackstr01", "traynpi01", "traynpi01", "traynpi01", "traynpi01", "traynpi01", "traynpi01", "traynpi01", "traynpi01", "traynpi01", "traynpi01", "traynpi01", "traynpi01", "traynpi01", "traynpi01", "traynpi01", "traynpi01", 
+#> "traynpi01", "hartnga01", "hartnga01", "hartnga01", "hartnga01", "hartnga01", "hartnga01", "hartnga01", "hartnga01", "hartnga01", "hartnga01", "hartnga01", "hartnga01", "hartnga01", "hartnga01", "hartnga01", "hartnga01", "hartnga01", "hartnga01", "hartnga01", "hartnga01", "bluegos01", "bluegos01", "bluegos01", "bluegos01", "bluegos01", "bluegos01", "bluegos01", "bluegos01", "bluegos01", "bluegos01", "bluegos01", "bluegos01", "bluegos01", "bluegos01", "bluegos01", "bluegos01", "bluegos01", "bluegos01", 
+#> "ruelmu01", "ruelmu01", "ruelmu01", "ruelmu01", "ruelmu01", "ruelmu01", "ruelmu01", "ruelmu01", "ruelmu01", "ruelmu01", "ruelmu01", "ruelmu01", "ruelmu01", "ruelmu01", "ruelmu01", "ruelmu01", "ruelmu01", "ruelmu01", "ruelmu01", "ruelmu01", "cochrmi01", "cochrmi01", "cochrmi01", "cochrmi01", "cochrmi01", "cochrmi01", "cochrmi01", "cochrmi01", "cochrmi01", "cochrmi01", "cochrmi01", "cochrmi01", "cochrmi01", "simmoal01", "simmoal01", "simmoal01", "simmoal01", "simmoal01", "simmoal01", "simmoal01", "simmoal01", 
+#> "simmoal01", "simmoal01", "simmoal01", "simmoal01", "simmoal01", "simmoal01", "simmoal01", "simmoal01", "simmoal01", "simmoal01", "simmoal01", "simmoal01", "simmoal01", "gosligo01", "gosligo01", "gosligo01", "gosligo01", "gosligo01", "gosligo01", "gosligo01", "gosligo01", "gosligo01", "gosligo01", "gosligo01", "gosligo01", "gosligo01", "gosligo01", "gosligo01", "gosligo01", "gosligo01", "gosligo01", "gosligo01", "lyonste01", "lyonste01", "lyonste01", "lyonste01", "lyonste01", "lyonste01", "lyonste01", 
+#> "lyonste01", "lyonste01", "lyonste01", "lyonste01", "lyonste01", "lyonste01", "lyonste01", "lyonste01", "lyonste01", "lyonste01", "lyonste01", "lyonste01", "lyonste01", "lyonste01", "cuyleki01", "cuyleki01", "cuyleki01", "cuyleki01", "cuyleki01", "cuyleki01", "cuyleki01", "cuyleki01", "cuyleki01", "cuyleki01", "cuyleki01", "cuyleki01", "cuyleki01", "cuyleki01", "cuyleki01", "cuyleki01", "cuyleki01", "cuyleki01", "cuyleki01", "wrighgl01", "wrighgl01", "wrighgl01", "wrighgl01", "wrighgl01", "wrighgl01", 
+#> "wrighgl01", "wrighgl01", "wrighgl01", "wrighgl01", "wrighgl01", "bottoji01", "bottoji01", "bottoji01", "bottoji01", "bottoji01", "bottoji01", "bottoji01", "bottoji01", "bottoji01", "bottoji01", "bottoji01", "bottoji01", "bottoji01", "bottoji01", "bottoji01", "bottoji01", "smithea02", "smithea02", "smithea02", "smithea02", "smithea02", "smithea02", "smithea02", "smithea02", "smithea02", "smithea02", "smithea02", "smithea02", "smithea02", "smithea02", "smithea02", "donohpe01", "donohpe01", "donohpe01", 
+#> "donohpe01", "donohpe01", "donohpe01", "donohpe01", "donohpe01", "donohpe01", "donohpe01", "donohpe01", "donohpe01", "donohpe01", "donohpe01", "burnsge02", "burnsge02", "burnsge02", "burnsge02", "burnsge02", "burnsge02", "burnsge02", "burnsge02", "burnsge02", "burnsge02", "burnsge02", "burnsge02", "burnsge02", "burnsge02", "burnsge02", "burnsge02", "burnsge02", "burnsge02", "burnsge02", "kammwi01", "kammwi01", "kammwi01", "kammwi01", "kammwi01", "kammwi01", "kammwi01", "kammwi01", "kammwi01", "kammwi01", 
+#> "kammwi01", "kammwi01", "kammwi01", "kammwi01", "manushe01", "manushe01", "manushe01", "manushe01", "manushe01", "manushe01", "manushe01", "manushe01", "manushe01", "manushe01", "manushe01", "manushe01", "manushe01", "manushe01", "manushe01", "manushe01", "manushe01", "manushe01", "manushe01", "mostijo01", "mostijo01", "mostijo01", "mostijo01", "mostijo01", "mostijo01", "mostijo01", "mostijo01", "mostijo01", "mostijo01", "grovele01", "grovele01", "grovele01", "grovele01", "grovele01", "grovele01", 
+#> "grovele01", "grovele01", "grovele01", "grovele01", "grovele01", "grovele01", "grovele01", "grovele01", "grovele01", "grovele01", "grovele01", "kremera01", "kremera01", "kremera01", "kremera01", "kremera01", "kremera01", "kremera01", "kremera01", "kremera01", "kremera01", "wilsoha01", "wilsoha01", "wilsoha01", "wilsoha01", "wilsoha01", "wilsoha01", "wilsoha01", "wilsoha01", "wilsoha01", "wilsoha01", "wilsoha01", "wilsoha01", "wilsoha01", "carlsha01", "carlsha01", "carlsha01", "carlsha01", "carlsha01", 
+#> "carlsha01", "carlsha01", "carlsha01", "carlsha01", "carlsha01", "carlsha01", "carlsha01", "carlsha01", "carlsha01", "carlsha01", "pettyje01", "pettyje01", "pettyje01", "pettyje01", "pettyje01", "pettyje01", "pettyje01", "pettyje01", "gehrilo01", "gehrilo01", "gehrilo01", "gehrilo01", "gehrilo01", "gehrilo01", "gehrilo01", "gehrilo01", "gehrilo01", "gehrilo01", "gehrilo01", "gehrilo01", "gehrilo01", "gehrilo01", "gehrilo01", "gehrilo01", "gehrilo01", "lazzeto01", "lazzeto01", "lazzeto01", "lazzeto01", 
+#> "lazzeto01", "lazzeto01", "lazzeto01", "lazzeto01", "lazzeto01", "lazzeto01", "lazzeto01", "lazzeto01", "lazzeto01", "lazzeto01", "lazzeto01", "hoytwa01", "hoytwa01", "hoytwa01", "hoytwa01", "hoytwa01", "hoytwa01", "hoytwa01", "hoytwa01", "hoytwa01", "hoytwa01", "hoytwa01", "hoytwa01", "hoytwa01", "hoytwa01", "hoytwa01", "hoytwa01", "hoytwa01", "hoytwa01", "hoytwa01", "hoytwa01", "hoytwa01", "hoytwa01", "hoytwa01", "hoytwa01", "hoytwa01", "thomato02", "thomato02", "thomato02", "thomato02", "thomato02", 
+#> "thomato02", "thomato02", "thomato02", "thomato02", "thomato02", "thomato02", "thomato02", "thomato02", "thomato02", "thomato02", "rootch01", "rootch01", "rootch01", "rootch01", "rootch01", "rootch01", "rootch01", "rootch01", "rootch01", "rootch01", "rootch01", "rootch01", "rootch01", "rootch01", "rootch01", "rootch01", "rootch01", "haineje01", "haineje01", "haineje01", "haineje01", "haineje01", "haineje01", "haineje01", "haineje01", "haineje01", "haineje01", "haineje01", "haineje01", "haineje01", 
+#> "haineje01", "haineje01", "haineje01", "haineje01", "haineje01", "haineje01", "wanerpa01", "wanerpa01", "wanerpa01", "wanerpa01", "wanerpa01", "wanerpa01", "wanerpa01", "wanerpa01", "wanerpa01", "wanerpa01", "wanerpa01", "wanerpa01", "wanerpa01", "wanerpa01", "wanerpa01", "wanerpa01", "wanerpa01", "wanerpa01", "wanerpa01", "wanerpa01", "wanerpa01", "wanerpa01", "terrybi01", "terrybi01", "terrybi01", "terrybi01", "terrybi01", "terrybi01", "terrybi01", "terrybi01", "terrybi01", "terrybi01", "terrybi01", 
+#> "terrybi01", "terrybi01", "terrybi01", "wilsoji01", "wilsoji01", "wilsoji01", "wilsoji01", "wilsoji01", "wilsoji01", "wilsoji01", "wilsoji01", "wilsoji01", "wilsoji01", "wilsoji01", "wilsoji01", "wilsoji01", "wilsoji01", "wilsoji01", "wilsoji01", "wilsoji01", "wilsoji01", "wilsoji01", "wanerll01", "wanerll01", "wanerll01", "wanerll01", "wanerll01", "wanerll01", "wanerll01", "wanerll01", "wanerll01", "wanerll01", "wanerll01", "wanerll01", "wanerll01", "wanerll01", "wanerll01", "wanerll01", "wanerll01", 
+#> "wanerll01", "wanerll01", "wanerll01", "wanerll01", "crowdal01", "crowdal01", "crowdal01", "crowdal01", "crowdal01", "crowdal01", "crowdal01", "crowdal01", "crowdal01", "crowdal01", "crowdal01", "crowdal01", "crowdal01", "crowdal01", "morried02", "morried02", "morried02", "morried02", "morried02", "bentola01", "bentola01", "bentola01", "bentola01", "bentola01", "bentola01", "bentola01", "bentola01", "bentola01", "bentola01", "bentola01", "bentola01", "bentola01", "bentola01", "bentola01", "hafeych01", 
+#> "hafeych01", "hafeych01", "hafeych01", "hafeych01", "hafeych01", "hafeych01", "hafeych01", "hafeych01", "hafeych01", "hafeych01", "hafeych01", "hafeych01", "sherdbi01", "sherdbi01", "sherdbi01", "sherdbi01", "sherdbi01", "sherdbi01", "sherdbi01", "sherdbi01", "sherdbi01", "sherdbi01", "sherdbi01", "sherdbi01", "sherdbi01", "sherdbi01", "sherdbi01", "sherdbi01", "sherdbi01", "lindsfr01", "lindsfr01", "lindsfr01", "lindsfr01", "lindsfr01", "lindsfr01", "lindsfr01", "lindsfr01", "lindsfr01", "lindsfr01", 
+#> "lindsfr01", "lindsfr01", "lindsfr01", "fonsele01", "fonsele01", "fonsele01", "fonsele01", "fonsele01", "fonsele01", "fonsele01", "fonsele01", "fonsele01", "fonsele01", "fonsele01", "fonsele01", "fonsele01", "gehrich01", "gehrich01", "gehrich01", "gehrich01", "gehrich01", "gehrich01", "gehrich01", "gehrich01", "gehrich01", "gehrich01", "gehrich01", "gehrich01", "gehrich01", "gehrich01", "gehrich01", "gehrich01", "gehrich01", "gehrich01", "gehrich01", "dykesji01", "dykesji01", "dykesji01", "dykesji01", 
+#> "dykesji01", "dykesji01", "dykesji01", "dykesji01", "dykesji01", "dykesji01", "dykesji01", "dykesji01", "dykesji01", "dykesji01", "dykesji01", "dykesji01", "dykesji01", "dykesji01", "dykesji01", "dykesji01", "dykesji01", "dykesji01", "combsea01", "combsea01", "combsea01", "combsea01", "combsea01", "combsea01", "combsea01", "combsea01", "combsea01", "combsea01", "combsea01", "combsea01", "earnsge01", "earnsge01", "earnsge01", "earnsge01", "earnsge01", "earnsge01", "earnsge01", "earnsge01", "earnsge01", 
+#> "earnsge01", "earnsge01", "graydo02", "graydo02", "graydo02", "graydo02", "graydo02", "graydo02", "graydo02", "graydo02", "graydo02", "graydo02", "ferrewe01", "ferrewe01", "ferrewe01", "ferrewe01", "ferrewe01", "ferrewe01", "ferrewe01", "ferrewe01", "ferrewe01", "ferrewe01", "ferrewe01", "ferrewe01", "ferrewe01", "ferrewe01", "ferrewe01", "ferrewe01", "ferrewe01", "kressre01", "kressre01", "kressre01", "kressre01", "kressre01", "kressre01", "kressre01", "kressre01", "kressre01", "kressre01", "kressre01", 
+#> "kressre01", "kressre01", "kressre01", "kressre01", "kressre01", "kressre01", "malonpa02", "malonpa02", "malonpa02", "malonpa02", "malonpa02", "malonpa02", "malonpa02", "malonpa02", "malonpa02", "malonpa02", "lucasre01", "lucasre01", "lucasre01", "lucasre01", "lucasre01", "lucasre01", "lucasre01", "lucasre01", "lucasre01", "lucasre01", "lucasre01", "lucasre01", "lucasre01", "lucasre01", "lucasre01", "lucasre01", "hubbeca01", "hubbeca01", "hubbeca01", "hubbeca01", "hubbeca01", "hubbeca01", "hubbeca01", 
+#> "hubbeca01", "hubbeca01", "hubbeca01", "hubbeca01", "hubbeca01", "hubbeca01", "hubbeca01", "hubbeca01", "hubbeca01", "odoulle01", "odoulle01", "odoulle01", "odoulle01", "odoulle01", "odoulle01", "odoulle01", "odoulle01", "odoulle01", "odoulle01", "odoulle01", "odoulle01", "foxxji01", "foxxji01", "foxxji01", "foxxji01", "foxxji01", "foxxji01", "foxxji01", "foxxji01", "foxxji01", "foxxji01", "foxxji01", "foxxji01", "foxxji01", "foxxji01", "foxxji01", "foxxji01", "foxxji01", "foxxji01", "foxxji01", 
+#> "foxxji01", "foxxji01", "averiea01", "averiea01", "averiea01", "averiea01", "averiea01", "averiea01", "averiea01", "averiea01", "averiea01", "averiea01", "averiea01", "averiea01", "averiea01", "averiea01", "cronijo01", "cronijo01", "cronijo01", "cronijo01", "cronijo01", "cronijo01", "cronijo01", "cronijo01", "cronijo01", "cronijo01", "cronijo01", "cronijo01", "cronijo01", "cronijo01", "cronijo01", "cronijo01", "cronijo01", "cronijo01", "cronijo01", "cronijo01", "hallabi01", "hallabi01", "hallabi01", 
+#> "hallabi01", "hallabi01", "hallabi01", "hallabi01", "hallabi01", "hallabi01", "hallabi01", "hallabi01", "hallabi01", "hallabi01", "melilsk01", "melilsk01", "melilsk01", "melilsk01", "melilsk01", "melilsk01", "melilsk01", "melilsk01", "melilsk01", "melilsk01", "melilsk01", "melilsk01", "melilsk01", "walberu01", "walberu01", "walberu01", "walberu01", "walberu01", "walberu01", "walberu01", "walberu01", "walberu01", "walberu01", "walberu01", "walberu01", "walberu01", "walberu01", "walberu01", "walberu01", 
+#> "branded01", "branded01", "branded01", "branded01", "branded01", "branded01", "branded01", "branded01", "branded01", "branded01", "branded01", "derripa01", "derripa01", "derripa01", "derripa01", "derripa01", "derripa01", "derripa01", "derripa01", "derripa01", "derripa01", "derripa01", "derripa01", "derripa01", "derripa01", "derripa01", "derripa01", "fitzsfr01", "fitzsfr01", "fitzsfr01", "fitzsfr01", "fitzsfr01", "fitzsfr01", "fitzsfr01", "fitzsfr01", "fitzsfr01", "fitzsfr01", "fitzsfr01", "fitzsfr01", 
+#> "fitzsfr01", "fitzsfr01", "fitzsfr01", "fitzsfr01", "fitzsfr01", "fitzsfr01", "fitzsfr01", "fitzsfr01", "kleinch01", "kleinch01", "kleinch01", "kleinch01", "kleinch01", "kleinch01", "kleinch01", "kleinch01", "kleinch01", "kleinch01", "kleinch01", "kleinch01", "kleinch01", "kleinch01", "kleinch01", "kleinch01", "kleinch01", "kleinch01", "kleinch01", "gomezle01", "gomezle01", "gomezle01", "gomezle01", "gomezle01", "gomezle01", "gomezle01", "gomezle01", "gomezle01", "gomezle01", "gomezle01", "gomezle01", 
+#> "gomezle01", "gomezle01", "warnelo01", "warnelo01", "warnelo01", "warnelo01", "warnelo01", "warnelo01", "warnelo01", "warnelo01", "warnelo01", "warnelo01", "warnelo01", "warnelo01", "warnelo01", "warnelo01", "warnelo01", "warnelo01", "hermabi01", "hermabi01", "hermabi01", "hermabi01", "hermabi01", "hermabi01", "hermabi01", "hermabi01", "hermabi01", "hermabi01", "hermabi01", "hermabi01", "hermabi01", "hermabi01", "hermabi01", "hermabi01", "hermabi01", "clarkwa02", "clarkwa02", "clarkwa02", "clarkwa02", 
+#> "clarkwa02", "clarkwa02", "clarkwa02", "clarkwa02", "clarkwa02", "clarkwa02", "clarkwa02", "clarkwa02", "clarkwa02", "clarkwa02", "deandi01", "deandi01", "deandi01", "deandi01", "deandi01", "deandi01", "deandi01", "deandi01", "deandi01", "deandi01", "deandi01", "deandi01", "bartedi01", "bartedi01", "bartedi01", "bartedi01", "bartedi01", "bartedi01", "bartedi01", "bartedi01", "bartedi01", "bartedi01", "bartedi01", "bartedi01", "bartedi01", "bartedi01", "bartedi01", "bartedi01", "bartedi01", "bartedi01", 
+#> "bartedi01", "dickebi01", "dickebi01", "dickebi01", "dickebi01", "dickebi01", "dickebi01", "dickebi01", "dickebi01", "dickebi01", "dickebi01", "dickebi01", "dickebi01", "dickebi01", "dickebi01", "dickebi01", "dickebi01", "dickebi01", "higgipi01", "higgipi01", "higgipi01", "higgipi01", "higgipi01", "higgipi01", "higgipi01", "higgipi01", "higgipi01", "higgipi01", "higgipi01", "higgipi01", "higgipi01", "higgipi01", "higgipi01", "westsa01", "westsa01", "westsa01", "westsa01", "westsa01", "westsa01", 
+#> "westsa01", "westsa01", "westsa01", "westsa01", "westsa01", "westsa01", "westsa01", "westsa01", "westsa01", "westsa01", "westsa01", "whiteea01", "whiteea01", "whiteea01", "whiteea01", "whiteea01", "whiteea01", "whiteea01", "whiteea01", "whiteea01", "whiteea01", "whiteea01", "whiteea01", "whiteea01", "whiteea01", "whiteea01", "whiteea01", "whiteea01", "bridgto01", "bridgto01", "bridgto01", "bridgto01", "bridgto01", "bridgto01", "bridgto01", "bridgto01", "bridgto01", "bridgto01", "bridgto01", "bridgto01", 
+#> "bridgto01", "bridgto01", "bridgto01", "bridgto01", "bergewa01", "bergewa01", "bergewa01", "bergewa01", "bergewa01", "bergewa01", "bergewa01", "bergewa01", "bergewa01", "bergewa01", "bergewa01", "bergewa01", "bergewa01", "bergewa01", "lopezal01", "lopezal01", "lopezal01", "lopezal01", "lopezal01", "lopezal01", "lopezal01", "lopezal01", "lopezal01", "lopezal01", "lopezal01", "lopezal01", "lopezal01", "lopezal01", "lopezal01", "lopezal01", "lopezal01", "lopezal01", "lopezal01", "lopezal01", "medwijo01", 
+#> "medwijo01", "medwijo01", "medwijo01", "medwijo01", "medwijo01", "medwijo01", "medwijo01", "medwijo01", "medwijo01", "medwijo01", "medwijo01", "medwijo01", "medwijo01", "medwijo01", "medwijo01", "medwijo01", "medwijo01", "medwijo01", "medwijo01", "cantwbe01", "cantwbe01", "cantwbe01", "cantwbe01", "cantwbe01", "cantwbe01", "cantwbe01", "cantwbe01", "cantwbe01", "cantwbe01", "cantwbe01", "cantwbe01", "cantwbe01", "vaughar01", "vaughar01", "vaughar01", "vaughar01", "vaughar01", "vaughar01", "vaughar01", 
+#> "vaughar01", "vaughar01", "vaughar01", "vaughar01", "vaughar01", "vaughar01", "vaughar01", "werbebi01", "werbebi01", "werbebi01", "werbebi01", "werbebi01", "werbebi01", "werbebi01", "werbebi01", "werbebi01", "werbebi01", "werbebi01", "werbebi01", "rowesc01", "rowesc01", "rowesc01", "rowesc01", "rowesc01", "rowesc01", "rowesc01", "rowesc01", "rowesc01", "rowesc01", "rowesc01", "rowesc01", "rowesc01", "rowesc01", "rowesc01", "rowesc01", "hardeme01", "hardeme01", "hardeme01", "hardeme01", "hardeme01", 
+#> "hardeme01", "hardeme01", "hardeme01", "hardeme01", "hardeme01", "hardeme01", "hardeme01", "hardeme01", "hardeme01", "hardeme01", "hardeme01", "hardeme01", "hardeme01", "hardeme01", "hardeme01", "knickbi01", "knickbi01", "knickbi01", "knickbi01", "knickbi01", "knickbi01", "knickbi01", "knickbi01", "knickbi01", "knickbi01", "ottme01", "ottme01", "ottme01", "ottme01", "ottme01", "ottme01", "ottme01", "ottme01", "ottme01", "ottme01", "ottme01", "ottme01", "ottme01", "ottme01", "ottme01", "ottme01", 
+#> "ottme01", "ottme01", "ottme01", "ottme01", "ottme01", "ottme01", "moorejo02", "moorejo02", "moorejo02", "moorejo02", "moorejo02", "moorejo02", "moorejo02", "moorejo02", "moorejo02", "moorejo02", "moorejo02", "moorejo02", "schumha02", "schumha02", "schumha02", "schumha02", "schumha02", "schumha02", "schumha02", "schumha02", "schumha02", "schumha02", "schumha02", "schumha02", "schumha02", "greenha01", "greenha01", "greenha01", "greenha01", "greenha01", "greenha01", "greenha01", "greenha01", "greenha01", 
+#> "greenha01", "greenha01", "greenha01", "greenha01", "cramedo01", "cramedo01", "cramedo01", "cramedo01", "cramedo01", "cramedo01", "cramedo01", "cramedo01", "cramedo01", "cramedo01", "cramedo01", "cramedo01", "cramedo01", "cramedo01", "cramedo01", "cramedo01", "cramedo01", "cramedo01", "cramedo01", "cramedo01", "vosmijo01", "vosmijo01", "vosmijo01", "vosmijo01", "vosmijo01", "vosmijo01", "vosmijo01", "vosmijo01", "vosmijo01", "vosmijo01", "vosmijo01", "vosmijo01", "vosmijo01", "foxpe01", "foxpe01", 
+#> "foxpe01", "foxpe01", "foxpe01", "foxpe01", "foxpe01", "foxpe01", "foxpe01", "foxpe01", "foxpe01", "foxpe01", "foxpe01", "martipe01", "martipe01", "martipe01", "martipe01", "martipe01", "martipe01", "martipe01", "martipe01", "martipe01", "martipe01", "martipe01", "martipe01", "martipe01", "owenma01", "owenma01", "owenma01", "owenma01", "owenma01", "owenma01", "owenma01", "owenma01", "owenma01", "dimagjo01", "dimagjo01", "dimagjo01", "dimagjo01", "dimagjo01", "dimagjo01", "dimagjo01", "dimagjo01", 
+#> "dimagjo01", "dimagjo01", "dimagjo01", "dimagjo01", "dimagjo01", "kenneve01", "kenneve01", "kenneve01", "kenneve01", "kenneve01", "kenneve01", "kenneve01", "kenneve01", "kenneve01", "kenneve01", "kenneve01", "kenneve01", "kenneve01", "kenneve01", "kenneve01", "kenneve01", "allenjo02", "allenjo02", "allenjo02", "allenjo02", "allenjo02", "allenjo02", "allenjo02", "allenjo02", "allenjo02", "allenjo02", "allenjo02", "allenjo02", "allenjo02", "allenjo02", "allenjo02", "moseswa01", "moseswa01", "moseswa01", 
+#> "moseswa01", "moseswa01", "moseswa01", "moseswa01", "moseswa01", "moseswa01", "moseswa01", "moseswa01", "moseswa01", "moseswa01", "moseswa01", "moseswa01", "moseswa01", "moseswa01", "moseswa01", "applilu01", "applilu01", "applilu01", "applilu01", "applilu01", "applilu01", "applilu01", "applilu01", "applilu01", "applilu01", "applilu01", "applilu01", "applilu01", "applilu01", "applilu01", "applilu01", "applilu01", "applilu01", "applilu01", "applilu01", "hackst01", "hackst01", "hackst01", "hackst01", 
+#> "hackst01", "hackst01", "hackst01", "hackst01", "hackst01", "hackst01", "hackst01", "hackst01", "hackst01", "hackst01", "hackst01", "hackst01", "suhrgu01", "suhrgu01", "suhrgu01", "suhrgu01", "suhrgu01", "suhrgu01", "suhrgu01", "suhrgu01", "suhrgu01", "suhrgu01", "suhrgu01", "suhrgu01", "frencla01", "frencla01", "frencla01", "frencla01", "frencla01", "frencla01", "frencla01", "frencla01", "frencla01", "frencla01", "frencla01", "frencla01", "frencla01", "frencla01", "frencla01", "macfada01", "macfada01", 
+#> "macfada01", "macfada01", "macfada01", "macfada01", "macfada01", "macfada01", "macfada01", "macfada01", "macfada01", "macfada01", "macfada01", "macfada01", "macfada01", "macfada01", "macfada01", "macfada01", "macfada01", "lawsoro01", "lawsoro01", "lawsoro01", "lawsoro01", "lawsoro01", "lawsoro01", "lawsoro01", "lawsoro01", "lawsoro01", "lawsoro01", "whitnpi01", "whitnpi01", "whitnpi01", "whitnpi01", "whitnpi01", "whitnpi01", "whitnpi01", "whitnpi01", "whitnpi01", "whitnpi01", "whitnpi01", "whitnpi01", 
+#> "whitnpi01", "whitnpi01", "fettelo01", "fettelo01", "fettelo01", "fettelo01", "fettelo01", "fettelo01", "mizejo01", "mizejo01", "mizejo01", "mizejo01", "mizejo01", "mizejo01", "mizejo01", "mizejo01", "mizejo01", "mizejo01", "mizejo01", "mizejo01", "mizejo01", "mizejo01", "mizejo01", "mizejo01", "demarfr02", "demarfr02", "demarfr02", "demarfr02", "demarfr02", "demarfr02", "demarfr02", "demarfr02", "demarfr02", "demarfr02", "demarfr02", "demarfr02", "demarfr02", "turneji01", "turneji01", "turneji01", 
+#> "turneji01", "turneji01", "turneji01", "turneji01", "turneji01", "turneji01", "turneji01", "rolfere01", "rolfere01", "rolfere01", "rolfere01", "rolfere01", "rolfere01", "rolfere01", "rolfere01", "rolfere01", "rolfere01", "ruffire01", "ruffire01", "ruffire01", "ruffire01", "ruffire01", "ruffire01", "ruffire01", "ruffire01", "ruffire01", "ruffire01", "ruffire01", "ruffire01", "ruffire01", "ruffire01", "ruffire01", "ruffire01", "ruffire01", "ruffire01", "ruffire01", "ruffire01", "ruffire01", "ruffire01", 
+#> "ruffire01", "hemslro01", "hemslro01", "hemslro01", "hemslro01", "hemslro01", "hemslro01", "hemslro01", "hemslro01", "hemslro01", "hemslro01", "hemslro01", "hemslro01", "hemslro01", "hemslro01", "hemslro01", "hemslro01", "hemslro01", "hemslro01", "hemslro01", "hemslro01", "hemslro01", "hemslro01", "heathje01", "heathje01", "heathje01", "heathje01", "heathje01", "heathje01", "heathje01", "heathje01", "heathje01", "heathje01", "heathje01", "heathje01", "heathje01", "heathje01", "heathje01", "newsobo01", 
+#> "newsobo01", "newsobo01", "newsobo01", "newsobo01", "newsobo01", "newsobo01", "newsobo01", "newsobo01", "newsobo01", "newsobo01", "newsobo01", "newsobo01", "newsobo01", "newsobo01", "newsobo01", "newsobo01", "newsobo01", "newsobo01", "newsobo01", "newsobo01", "newsobo01", "newsobo01", "newsobo01", "newsobo01", "newsobo01", "newsobo01", "newsobo01", "newsobo01", "vandejo01", "vandejo01", "vandejo01", "vandejo01", "vandejo01", "vandejo01", "vandejo01", "vandejo01", "vandejo01", "vandejo01", "vandejo01", 
+#> "vandejo01", "vandejo01", "mccorfr01", "mccorfr01", "mccorfr01", "mccorfr01", "mccorfr01", "mccorfr01", "mccorfr01", "mccorfr01", "mccorfr01", "mccorfr01", "mccorfr01", "mccorfr01", "mccorfr01", "mccorfr01", "lombaer01", "lombaer01", "lombaer01", "lombaer01", "lombaer01", "lombaer01", "lombaer01", "lombaer01", "lombaer01", "lombaer01", "lombaer01", "lombaer01", "lombaer01", "lombaer01", "lombaer01", "lombaer01", "lombaer01", "danniha01", "danniha01", "danniha01", "danniha01", "danniha01", "danniha01", 
+#> "danniha01", "danniha01", "danniha01", "danniha01", "leebi02", "leebi02", "leebi02", "leebi02", "leebi02", "leebi02", "leebi02", "leebi02", "leebi02", "leebi02", "leebi02", "leebi02", "leebi02", "leebi02", "leebi02", "leebi02", "goodmiv01", "goodmiv01", "goodmiv01", "goodmiv01", "goodmiv01", "goodmiv01", "goodmiv01", "goodmiv01", "goodmiv01", "goodmiv01", "gordojo01", "gordojo01", "gordojo01", "gordojo01", "gordojo01", "gordojo01", "gordojo01", "gordojo01", "gordojo01", "gordojo01", "gordojo01", 
+#> "johnsbo01", "johnsbo01", "johnsbo01", "johnsbo01", "johnsbo01", "johnsbo01", "johnsbo01", "johnsbo01", "johnsbo01", "johnsbo01", "johnsbo01", "johnsbo01", "johnsbo01", "fellebo01", "fellebo01", "fellebo01", "fellebo01", "fellebo01", "fellebo01", "fellebo01", "fellebo01", "fellebo01", "fellebo01", "fellebo01", "fellebo01", "fellebo01", "fellebo01", "fellebo01", "fellebo01", "fellebo01", "fellebo01", "leonadu02", "leonadu02", "leonadu02", "leonadu02", "leonadu02", "leonadu02", "leonadu02", "leonadu02", 
+#> "leonadu02", "leonadu02", "leonadu02", "leonadu02", "leonadu02", "leonadu02", "leonadu02", "leonadu02", "leonadu02", "leonadu02", "leonadu02", "leonadu02", "willite01", "willite01", "willite01", "willite01", "willite01", "willite01", "willite01", "willite01", "willite01", "willite01", "willite01", "willite01", "willite01", "willite01", "willite01", "willite01", "willite01", "willite01", "willite01", "waltebu01", "waltebu01", "waltebu01", "waltebu01", "waltebu01", "waltebu01", "waltebu01", "waltebu01", 
+#> "waltebu01", "waltebu01", "waltebu01", "waltebu01", "waltebu01", "waltebu01", "waltebu01", "waltebu01", "waltebu01", "waltebu01", "waltebu01", "waltebu01", "waltebu01", "daviscu01", "daviscu01", "daviscu01", "daviscu01", "daviscu01", "daviscu01", "daviscu01", "daviscu01", "daviscu01", "daviscu01", "daviscu01", "daviscu01", "daviscu01", "daviscu01", "daviscu01", "freylo01", "freylo01", "freylo01", "freylo01", "freylo01", "freylo01", "freylo01", "freylo01", "freylo01", "freylo01", "freylo01", "freylo01", 
+#> "freylo01", "freylo01", "freylo01", "freylo01", "lavagco01", "lavagco01", "lavagco01", "lavagco01", "lavagco01", "lavagco01", "lavagco01", "lavagco01", "lavagco01", "lavagco01", "leibeha01", "leibeha01", "leibeha01", "leibeha01", "leibeha01", "leibeha01", "leibeha01", "leibeha01", "leibeha01", "leibeha01", "cliftha01", "cliftha01", "cliftha01", "cliftha01", "cliftha01", "cliftha01", "cliftha01", "cliftha01", "cliftha01", "cliftha01", "cliftha01", "cliftha01", "cliftha01", "hayesfr01", "hayesfr01", 
+#> "hayesfr01", "hayesfr01", "hayesfr01", "hayesfr01", "hayesfr01", "hayesfr01", "hayesfr01", "hayesfr01", "hayesfr01", "hayesfr01", "hayesfr01", "hayesfr01", "hayesfr01", "hayesfr01", "hayesfr01", "kellech01", "kellech01", "kellech01", "kellech01", "kellech01", "kellech01", "kellech01", "kellech01", "kellech01", "kellech01", "kellech01", "kellech01", "kellech01", "nichobi01", "nichobi01", "nichobi01", "nichobi01", "nichobi01", "nichobi01", "nichobi01", "nichobi01", "nichobi01", "nichobi01", "nichobi01", 
+#> "nichobi01", "nichobi01", "nichobi01", "nichobi01", "nichobi01", "milleed03", "milleed03", "milleed03", "milleed03", "milleed03", "milleed03", "milleed03", "milleed03", "milleed03", "milleed03", "milleed03", "milleed03", "milleed03", "milleed03", "taborji01", "taborji01", "taborji01", "taborji01", "taborji01", "taborji01", "taborji01", "taborji01", "taborji01", "leeth01", "leeth01", "leeth01", "leeth01", "leeth01", "leeth01", "leeth01", "leeth01", "leeth01", "leeth01", "leeth01", "leeth01", "leeth01", 
+#> "leeth01", "leeth01", "leeth01", "newsodi01", "newsodi01", "newsodi01", "travice01", "travice01", "travice01", "travice01", "travice01", "travice01", "travice01", "travice01", "travice01", "travice01", "travice01", "travice01", "camildo01", "camildo01", "camildo01", "camildo01", "camildo01", "camildo01", "camildo01", "camildo01", "camildo01", "camildo01", "camildo01", "camildo01", "camildo01", "brownji03", "brownji03", "brownji03", "brownji03", "brownji03", "brownji03", "brownji03", "brownji03", 
+#> "wyattwh01", "wyattwh01", "wyattwh01", "wyattwh01", "wyattwh01", "wyattwh01", "wyattwh01", "wyattwh01", "wyattwh01", "wyattwh01", "wyattwh01", "wyattwh01", "wyattwh01", "wyattwh01", "wyattwh01", "wyattwh01", "wyattwh01", "whiteer01", "whiteer01", "whiteer01", "whiteer01", "whiteer01", "whiteer01", "whiteer01", "riddlel01", "riddlel01", "riddlel01", "riddlel01", "riddlel01", "riddlel01", "riddlel01", "riddlel01", "riddlel01", "riddlel01", "crespcr01", "crespcr01", "crespcr01", "crespcr01", "crespcr01", 
+#> "reisepe01", "reisepe01", "reisepe01", "reisepe01", "reisepe01", "reisepe01", "reisepe01", "reisepe01", "reisepe01", "reisepe01", "higbeki01", "higbeki01", "higbeki01", "higbeki01", "higbeki01", "higbeki01", "higbeki01", "higbeki01", "higbeki01", "higbeki01", "higbeki01", "higbeki01", "higbeki01", "higbeki01", "higbeki01", "slaugen01", "slaugen01", "slaugen01", "slaugen01", "slaugen01", "slaugen01", "slaugen01", "slaugen01", "slaugen01", "slaugen01", "slaugen01", "slaugen01", "slaugen01", "slaugen01", 
+#> "slaugen01", "slaugen01", "slaugen01", "slaugen01", "slaugen01", "slaugen01", "slaugen01", "slaugen01", "jurgebi01", "jurgebi01", "jurgebi01", "jurgebi01", "jurgebi01", "jurgebi01", "jurgebi01", "jurgebi01", "jurgebi01", "jurgebi01", "jurgebi01", "jurgebi01", "jurgebi01", "jurgebi01", "jurgebi01", "jurgebi01", "jurgebi01", "hassebu01", "hassebu01", "hassebu01", "hassebu01", "hassebu01", "hassebu01", "hassebu01", "keltnke01", "keltnke01", "keltnke01", "keltnke01", "keltnke01", "keltnke01", "keltnke01", 
+#> "keltnke01", "keltnke01", "keltnke01", "keltnke01", "keltnke01", "keltnke01", "hughste01", "hughste01", "hughste01", "hughste01", "hughste01", "hughste01", "hughste01", "hughste01", "bonhati01", "bonhati01", "bonhati01", "bonhati01", "bonhati01", "bonhati01", "bonhati01", "bonhati01", "bonhati01", "bonhati01", "bagbyji02", "bagbyji02", "bagbyji02", "bagbyji02", "bagbyji02", "bagbyji02", "bagbyji02", "bagbyji02", "bagbyji02", "bagbyji02", "marchph01", "marchph01", "marchph01", "marchph01", "marchph01", 
+#> "marchph01", "marchph01", "marchph01", "marchph01", "chandsp01", "chandsp01", "chandsp01", "chandsp01", "chandsp01", "chandsp01", "chandsp01", "chandsp01", "chandsp01", "chandsp01", "chandsp01", "spencst01", "spencst01", "spencst01", "spencst01", "spencst01", "spencst01", "spencst01", "spencst01", "spencst01", "spencst01", "stephve01", "stephve01", "stephve01", "stephve01", "stephve01", "stephve01", "stephve01", "stephve01", "stephve01", "stephve01", "stephve01", "stephve01", "stephve01", "stephve01", 
+#> "stephve01", "stephve01", "stephve01", "coopemo01", "coopemo01", "coopemo01", "coopemo01", "coopemo01", "coopemo01", "coopemo01", "coopemo01", "coopemo01", "coopemo01", "coopemo01", "coopemo01", "coopemo01", "hugheto04", "hugheto04", "hugheto04", "hugheto04", "hugheto04", "beazljo01", "beazljo01", "beazljo01", "beazljo01", "beazljo01", "beazljo01", "marioma01", "marioma01", "marioma01", "marioma01", "marioma01", "marioma01", "marioma01", "marioma01", "marioma01", "marioma01", "marioma01", "marioma01", 
+#> "marioma01", "owenmi01", "owenmi01", "owenmi01", "owenmi01", "owenmi01", "owenmi01", "owenmi01", "owenmi01", "owenmi01", "owenmi01", "owenmi01", "owenmi01", "owenmi01", "peskyjo01", "peskyjo01", "peskyjo01", "peskyjo01", "peskyjo01", "peskyjo01", "peskyjo01", "peskyjo01", "peskyjo01", "peskyjo01", "peskyjo01", "peskyjo01", "yorkru01", "yorkru01", "yorkru01", "yorkru01", "yorkru01", "yorkru01", "yorkru01", "yorkru01", "yorkru01", "yorkru01", "yorkru01", "yorkru01", "yorkru01", "yorkru01", "johnsbi03", 
+#> "johnsbi03", "johnsbi03", "johnsbi03", "johnsbi03", "johnsbi03", "johnsbi03", "johnsbi03", "johnsbi03", "johnsbi03", "troutdi01", "troutdi01", "troutdi01", "troutdi01", "troutdi01", "troutdi01", "troutdi01", "troutdi01", "troutdi01", "troutdi01", "troutdi01", "troutdi01", "troutdi01", "troutdi01", "troutdi01", "troutdi01", "smithal03", "smithal03", "smithal03", "smithal03", "smithal03", "smithal03", "smithal03", "smithal03", "smithal03", "smithal03", "smithal03", "smithal03", "wakefdi01", "wakefdi01", 
+#> "wakefdi01", "wakefdi01", "wakefdi01", "wakefdi01", "wakefdi01", "wakefdi01", "wakefdi01", "musiast01", "musiast01", "musiast01", "musiast01", "musiast01", "musiast01", "musiast01", "musiast01", "musiast01", "musiast01", "musiast01", "musiast01", "musiast01", "musiast01", "musiast01", "musiast01", "musiast01", "musiast01", "musiast01", "musiast01", "musiast01", "musiast01", "sewelri01", "sewelri01", "sewelri01", "sewelri01", "sewelri01", "sewelri01", "sewelri01", "sewelri01", "sewelri01", "sewelri01", 
+#> "sewelri01", "sewelri01", "sewelri01", "coopewa01", "coopewa01", "coopewa01", "coopewa01", "coopewa01", "coopewa01", "coopewa01", "coopewa01", "coopewa01", "coopewa01", "coopewa01", "coopewa01", "coopewa01", "coopewa01", "coopewa01", "coopewa01", "coopewa01", "coopewa01", "coopewa01", "coopewa01", "coopewa01", "dimagvi01", "dimagvi01", "dimagvi01", "dimagvi01", "dimagvi01", "dimagvi01", "dimagvi01", "dimagvi01", "dimagvi01", "dimagvi01", "dimagvi01", "dimagvi01", "stirnsn01", "stirnsn01", "stirnsn01", 
+#> "stirnsn01", "stirnsn01", "stirnsn01", "stirnsn01", "stirnsn01", "stirnsn01", "stirnsn01", "stirnsn01", "newhoha01", "newhoha01", "newhoha01", "newhoha01", "newhoha01", "newhoha01", "newhoha01", "newhoha01", "newhoha01", "newhoha01", "newhoha01", "newhoha01", "newhoha01", "newhoha01", "newhoha01", "newhoha01", "newhoha01", "elliobo01", "elliobo01", "elliobo01", "elliobo01", "elliobo01", "elliobo01", "elliobo01", "elliobo01", "elliobo01", "elliobo01", "elliobo01", "elliobo01", "elliobo01", "elliobo01", 
+#> "elliobo01", "elliobo01", "sandera01", "sandera01", "sandera01", "sandera01", "sandera01", "sandera01", "sandera01", "verbaem01", "verbaem01", "verbaem01", "verbaem01", "verbaem01", "verbaem01", "verbaem01", "verbaem01", "verbaem01", "verbaem01", "voisebi01", "voisebi01", "voisebi01", "voisebi01", "voisebi01", "voisebi01", "voisebi01", "voisebi01", "voisebi01", "voisebi01", "doerrbo01", "doerrbo01", "doerrbo01", "doerrbo01", "doerrbo01", "doerrbo01", "doerrbo01", "doerrbo01", "doerrbo01", "doerrbo01", 
+#> "doerrbo01", "doerrbo01", "doerrbo01", "doerrbo01", "walkedi02", "walkedi02", "walkedi02", "walkedi02", "walkedi02", "walkedi02", "walkedi02", "walkedi02", "walkedi02", "walkedi02", "walkedi02", "walkedi02", "walkedi02", "walkedi02", "walkedi02", "walkedi02", "walkedi02", "walkedi02", "walkedi02", "walkedi02", "ettenni01", "ettenni01", "ettenni01", "ettenni01", "ettenni01", "ettenni01", "ettenni01", "ettenni01", "ettenni01", "cuccito01", "cuccito01", "cuccito01", "cuccito01", "cuccito01", "cuccito01", 
+#> "cuccito01", "cuccito01", "cuccito01", "cuccito01", "cuccito01", "cuccito01", "cuccito01", "cuccito01", "cuccito01", "cuccito01", "cuccito01", "richapa01", "richapa01", "richapa01", "richapa01", "richapa01", "richapa01", "richapa01", "richapa01", "richapa01", "ferrida01", "ferrida01", "ferrida01", "ferrida01", "ferrida01", "ferrida01", "gromest01", "gromest01", "gromest01", "gromest01", "gromest01", "gromest01", "gromest01", "gromest01", "gromest01", "gromest01", "gromest01", "gromest01", "gromest01", 
+#> "gromest01", "gromest01", "gromest01", "gromest01", "gromest01", "wolffro01", "wolffro01", "wolffro01", "wolffro01", "wolffro01", "wolffro01", "wolffro01", "wolffro01", "cullero01", "cullero01", "cullero01", "cullero01", "cullero01", "cullero01", "cullero01", "cullero01", "cullero01", "cullero01", "cullero01", "cullero01", "cullero01", "cullero01", "cavarph01", "cavarph01", "cavarph01", "cavarph01", "cavarph01", "cavarph01", "cavarph01", "cavarph01", "cavarph01", "cavarph01", "cavarph01", "cavarph01", 
+#> "cavarph01", "cavarph01", "cavarph01", "cavarph01", "cavarph01", "cavarph01", "cavarph01", "cavarph01", "cavarph01", "cavarph01", "kurowwh01", "kurowwh01", "kurowwh01", "kurowwh01", "kurowwh01", "kurowwh01", "kurowwh01", "kurowwh01", "kurowwh01", "pafkoan01", "pafkoan01", "pafkoan01", "pafkoan01", "pafkoan01", "pafkoan01", "pafkoan01", "pafkoan01", "pafkoan01", "pafkoan01", "pafkoan01", "pafkoan01", "pafkoan01", "pafkoan01", "pafkoan01", "pafkoan01", "pafkoan01", "pafkoan01", "brechha01", "brechha01", 
+#> "brechha01", "brechha01", "brechha01", "brechha01", "brechha01", "brechha01", "brechha01", "brechha01", "brechha01", "brechha01", "borowha01", "borowha01", "borowha01", "borowha01", "borowha01", "borowha01", "borowha01", "borowha01", "borowha01", "borowha01", "borowha01", "borowha01", "borowha01", "holmeto01", "holmeto01", "holmeto01", "holmeto01", "holmeto01", "holmeto01", "holmeto01", "holmeto01", "holmeto01", "holmeto01", "holmeto01", "barrere01", "barrere01", "barrere01", "barrere01", "barrere01", 
+#> "barrere01", "barrere01", "barrere01", "barrere01", "barrere01", "barrere01", "barrere01", "wyseha01", "wyseha01", "wyseha01", "wyseha01", "wyseha01", "wyseha01", "wyseha01", "wyseha01", "wyseha01", "rosengo01", "rosengo01", "rosengo01", "rosengo01", "rosengo01", "rosengo01", "rosengo01", "mayoed01", "mayoed01", "mayoed01", "mayoed01", "mayoed01", "mayoed01", "mayoed01", "mayoed01", "mayoed01", "vernomi01", "vernomi01", "vernomi01", "vernomi01", "vernomi01", "vernomi01", "vernomi01", "vernomi01", 
+#> "vernomi01", "vernomi01", "vernomi01", "vernomi01", "vernomi01", "vernomi01", "vernomi01", "vernomi01", "vernomi01", "vernomi01", "vernomi01", "vernomi01", "vernomi01", "kellge01", "kellge01", "kellge01", "kellge01", "kellge01", "kellge01", "kellge01", "kellge01", "kellge01", "kellge01", "kellge01", "kellge01", "kellge01", "kellge01", "kellge01", "kellge01", "kellge01", "kellge01", "kellge01", "robinaa01", "robinaa01", "robinaa01", "robinaa01", "robinaa01", "robinaa01", "robinaa01", "robinaa01", 
+#> "robinaa01", "boudrlo01", "boudrlo01", "boudrlo01", "boudrlo01", "boudrlo01", "boudrlo01", "boudrlo01", "boudrlo01", "boudrlo01", "boudrlo01", "boudrlo01", "boudrlo01", "boudrlo01", "boudrlo01", "boudrlo01", "polleho01", "polleho01", "polleho01", "polleho01", "polleho01", "polleho01", "polleho01", "polleho01", "polleho01", "polleho01", "polleho01", "polleho01", "polleho01", "polleho01", "polleho01", "polleho01", "polleho01", "stanked01", "stanked01", "stanked01", "stanked01", "stanked01", "stanked01", 
+#> "stanked01", "stanked01", "stanked01", "stanked01", "stanked01", "stanked01", "mcculcl01", "mcculcl01", "mcculcl01", "mcculcl01", "mcculcl01", "mcculcl01", "mcculcl01", "mcculcl01", "mcculcl01", "mcculcl01", "mcculcl01", "mcculcl01", "mcculcl01", "mcculcl01", "mcculcl01", "ennisde01", "ennisde01", "ennisde01", "ennisde01", "ennisde01", "ennisde01", "ennisde01", "ennisde01", "ennisde01", "ennisde01", "ennisde01", "ennisde01", "ennisde01", "ennisde01", "ennisde01", "sainjo01", "sainjo01", "sainjo01", 
+#> "sainjo01", "sainjo01", "sainjo01", "sainjo01", "sainjo01", "sainjo01", "sainjo01", "sainjo01", "sainjo01", "sainjo01", "reesepe01", "reesepe01", "reesepe01", "reesepe01", "reesepe01", "reesepe01", "reesepe01", "reesepe01", "reesepe01", "reesepe01", "reesepe01", "reesepe01", "reesepe01", "reesepe01", "reesepe01", "reesepe01", "dimagdo01", "dimagdo01", "dimagdo01", "dimagdo01", "dimagdo01", "dimagdo01", "dimagdo01", "dimagdo01", "dimagdo01", "dimagdo01", "dimagdo01", "mcquige02", "mcquige02", "mcquige02", 
+#> "mcquige02", "mcquige02", "mcquige02", "mcquige02", "mcquige02", "mcquige02", "mcquige02", "mcquige02", "mcquige02", "berrayo01", "berrayo01", "berrayo01", "berrayo01", "berrayo01", "berrayo01", "berrayo01", "berrayo01", "berrayo01", "berrayo01", "berrayo01", "berrayo01", "berrayo01", "berrayo01", "berrayo01", "berrayo01", "berrayo01", "berrayo01", "berrayo01", "reynoal01", "reynoal01", "reynoal01", "reynoal01", "reynoal01", "reynoal01", "reynoal01", "reynoal01", "reynoal01", "reynoal01", "reynoal01", 
+#> "reynoal01", "reynoal01", "henrito01", "henrito01", "henrito01", "henrito01", "henrito01", "henrito01", "henrito01", "henrito01", "henrito01", "henrito01", "henrito01", "edwarbr01", "edwarbr01", "edwarbr01", "edwarbr01", "edwarbr01", "edwarbr01", "edwarbr01", "edwarbr01", "edwarbr01", "edwarbr01", "edwarbr01", "blackew01", "blackew01", "blackew01", "blackew01", "blackew01", "blackew01", "blackew01", "blackew01", "blackew01", "blackew01", "blackew01", "kinerra01", "kinerra01", "kinerra01", "kinerra01", 
+#> "kinerra01", "kinerra01", "kinerra01", "kinerra01", "kinerra01", "kinerra01", "kinerra01", "brancra01", "brancra01", "brancra01", "brancra01", "brancra01", "brancra01", "brancra01", "brancra01", "brancra01", "brancra01", "brancra01", "brancra01", "brancra01", "brancra01", "spahnwa01", "spahnwa01", "spahnwa01", "spahnwa01", "spahnwa01", "spahnwa01", "spahnwa01", "spahnwa01", "spahnwa01", "spahnwa01", "spahnwa01", "spahnwa01", "spahnwa01", "spahnwa01", "spahnwa01", "spahnwa01", "spahnwa01", "spahnwa01", 
+#> "spahnwa01", "spahnwa01", "spahnwa01", "spahnwa01", "marshwi01", "marshwi01", "marshwi01", "marshwi01", "marshwi01", "marshwi01", "marshwi01", "marshwi01", "marshwi01", "marshwi01", "marshwi01", "marshwi01", "robinja02", "robinja02", "robinja02", "robinja02", "robinja02", "robinja02", "robinja02", "robinja02", "robinja02", "robinja02", "fainfe01", "fainfe01", "fainfe01", "fainfe01", "fainfe01", "fainfe01", "fainfe01", "fainfe01", "fainfe01", "fainfe01", "tebbebi01", "tebbebi01", "tebbebi01", "tebbebi01", 
+#> "tebbebi01", "tebbebi01", "tebbebi01", "tebbebi01", "tebbebi01", "tebbebi01", "tebbebi01", "tebbebi01", "tebbebi01", "tebbebi01", "tebbebi01", "lemonbo01", "lemonbo01", "lemonbo01", "lemonbo01", "lemonbo01", "lemonbo01", "lemonbo01", "lemonbo01", "lemonbo01", "lemonbo01", "lemonbo01", "lemonbo01", "lemonbo01", "lemonbo01", "lemonbo01", "raschvi01", "raschvi01", "raschvi01", "raschvi01", "raschvi01", "raschvi01", "raschvi01", "raschvi01", "raschvi01", "raschvi01", "raschvi01", "masiph01", "masiph01", 
+#> "masiph01", "masiph01", "masiph01", "masiph01", "masiph01", "masiph01", "masiph01", "masiph01", "masiph01", "masiph01", "masiph01", "masiph01", "masiph01", "schmijo01", "schmijo01", "schmijo01", "schmijo01", "schmijo01", "schmijo01", "schmijo01", "schmijo01", "schmijo01", "schmijo01", "schmijo01", "schmijo01", "schmijo01", "schmijo01", "schmijo01", "schmijo01", "schmijo01", "schmijo01", "darkal01", "darkal01", "darkal01", "darkal01", "darkal01", "darkal01", "darkal01", "darkal01", "darkal01", "darkal01", 
+#> "darkal01", "darkal01", "darkal01", "darkal01", "darkal01", "darkal01", "darkal01", "pagejo01", "pagejo01", "pagejo01", "pagejo01", "pagejo01", "pagejo01", "pagejo01", "pagejo01", "michaca01", "michaca01", "michaca01", "michaca01", "michaca01", "michaca01", "michaca01", "michaca01", "michaca01", "michaca01", "michaca01", "michaca01", "michaca01", "michaca01", "michaca01", "parneme01", "parneme01", "parneme01", "parneme01", "parneme01", "parneme01", "parneme01", "parneme01", "parneme01", "parneme01", 
+#> "wertzvi01", "wertzvi01", "wertzvi01", "wertzvi01", "wertzvi01", "wertzvi01", "wertzvi01", "wertzvi01", "wertzvi01", "wertzvi01", "wertzvi01", "wertzvi01", "wertzvi01", "wertzvi01", "wertzvi01", "wertzvi01", "wertzvi01", "wertzvi01", "wertzvi01", "wertzvi01", "wertzvi01", "hodgegi01", "hodgegi01", "hodgegi01", "hodgegi01", "hodgegi01", "hodgegi01", "hodgegi01", "hodgegi01", "hodgegi01", "hodgegi01", "hodgegi01", "hodgegi01", "hodgegi01", "hodgegi01", "hodgegi01", "hodgegi01", "hodgegi01", "hodgegi01", 
+#> "gordosi01", "gordosi01", "gordosi01", "gordosi01", "gordosi01", "gordosi01", "gordosi01", "gordosi01", "gordosi01", "gordosi01", "gordosi01", "gordosi01", "gordosi01", "gordosi01", "camparo01", "camparo01", "camparo01", "camparo01", "camparo01", "camparo01", "camparo01", "camparo01", "camparo01", "camparo01", "newcodo01", "newcodo01", "newcodo01", "newcodo01", "newcodo01", "newcodo01", "newcodo01", "newcodo01", "newcodo01", "newcodo01", "newcodo01", "newcodo01", "sievero01", "sievero01", "sievero01", 
+#> "sievero01", "sievero01", "sievero01", "sievero01", "sievero01", "sievero01", "sievero01", "sievero01", "sievero01", "sievero01", "sievero01", "sievero01", "sievero01", "sievero01", "sievero01", "kindeel01", "kindeel01", "kindeel01", "kindeel01", "kindeel01", "kindeel01", "kindeel01", "kindeel01", "kindeel01", "kindeel01", "kindeel01", "kindeel01", "kindeel01", "rizzuph01", "rizzuph01", "rizzuph01", "rizzuph01", "rizzuph01", "rizzuph01", "rizzuph01", "rizzuph01", "rizzuph01", "rizzuph01", "rizzuph01", 
+#> "rizzuph01", "rizzuph01", "colemje01", "colemje01", "colemje01", "colemje01", "colemje01", "colemje01", "colemje01", "colemje01", "colemje01", "dropowa01", "dropowa01", "dropowa01", "dropowa01", "dropowa01", "dropowa01", "dropowa01", "dropowa01", "dropowa01", "dropowa01", "dropowa01", "dropowa01", "dropowa01", "dropowa01", "dropowa01", "dropowa01", "houttar01", "houttar01", "houttar01", "houttar01", "houttar01", "houttar01", "houttar01", "houttar01", "houttar01", "houttar01", "houttar01", "houttar01", 
+#> "houttar01", "houttar01", "konstji01", "konstji01", "konstji01", "konstji01", "konstji01", "konstji01", "konstji01", "konstji01", "konstji01", "konstji01", "konstji01", "konstji01", "konstji01", "furilca01", "furilca01", "furilca01", "furilca01", "furilca01", "furilca01", "furilca01", "furilca01", "furilca01", "furilca01", "furilca01", "furilca01", "furilca01", "furilca01", "furilca01", "snidedu01", "snidedu01", "snidedu01", "snidedu01", "snidedu01", "snidedu01", "snidedu01", "snidedu01", "snidedu01", 
+#> "snidedu01", "snidedu01", "snidedu01", "snidedu01", "snidedu01", "snidedu01", "snidedu01", "snidedu01", "snidedu01", "jansela01", "jansela01", "jansela01", "jansela01", "jansela01", "jansela01", "jansela01", "jansela01", "jansela01", "hamnegr01", "hamnegr01", "hamnegr01", "hamnegr01", "hamnegr01", "hamnegr01", "hamnegr01", "hamnegr01", "hamnegr01", "hamnegr01", "hamnegr01", "hamnegr01", "hamnegr01", "hamnegr01", "hamnegr01", "hamnegr01", "hamnegr01", "hamnegr01", "jethrsa01", "jethrsa01", "jethrsa01", 
+#> "jethrsa01", "dobyla01", "dobyla01", "dobyla01", "dobyla01", "dobyla01", "dobyla01", "dobyla01", "dobyla01", "dobyla01", "dobyla01", "dobyla01", "dobyla01", "dobyla01", "dobyla01", "mcdougi01", "mcdougi01", "mcdougi01", "mcdougi01", "mcdougi01", "mcdougi01", "mcdougi01", "mcdougi01", "mcdougi01", "mcdougi01", "mayswi01", "mayswi01", "mayswi01", "mayswi01", "mayswi01", "mayswi01", "mayswi01", "mayswi01", "mayswi01", "mayswi01", "mayswi01", "mayswi01", "mayswi01", "mayswi01", "mayswi01", "mayswi01", 
+#> "mayswi01", "mayswi01", "mayswi01", "mayswi01", "mayswi01", "mayswi01", "mayswi01", "maglisa01", "maglisa01", "maglisa01", "maglisa01", "maglisa01", "maglisa01", "maglisa01", "maglisa01", "maglisa01", "maglisa01", "maglisa01", "maglisa01", "maglisa01", "maglisa01", "roepr01", "roepr01", "roepr01", "roepr01", "roepr01", "roepr01", "roepr01", "roepr01", "roepr01", "roepr01", "roepr01", "roepr01", "shantbo01", "shantbo01", "shantbo01", "shantbo01", "shantbo01", "shantbo01", "shantbo01", "shantbo01", 
+#> "shantbo01", "shantbo01", "shantbo01", "shantbo01", "shantbo01", "shantbo01", "shantbo01", "shantbo01", "shantbo01", "shantbo01", "shantbo01", "sauerha01", "sauerha01", "sauerha01", "sauerha01", "sauerha01", "sauerha01", "sauerha01", "sauerha01", "sauerha01", "sauerha01", "sauerha01", "sauerha01", "sauerha01", "sauerha01", "sauerha01", "sauerha01", "byrdha01", "byrdha01", "byrdha01", "byrdha01", "byrdha01", "byrdha01", "byrdha01", "byrdha01", "blackjo02", "blackjo02", "blackjo02", "blackjo02", "blackjo02", 
+#> "blackjo02", "blackjo02", "mantlmi01", "mantlmi01", "mantlmi01", "mantlmi01", "mantlmi01", "mantlmi01", "mantlmi01", "mantlmi01", "mantlmi01", "mantlmi01", "mantlmi01", "mantlmi01", "mantlmi01", "mantlmi01", "mantlmi01", "mantlmi01", "mantlmi01", "mantlmi01", "roberro01", "roberro01", "roberro01", "roberro01", "roberro01", "roberro01", "roberro01", "roberro01", "roberro01", "roberro01", "roberro01", "roberro01", "roberro01", "roberro01", "roberro01", "roberro01", "roberro01", "roberro01", "roberro01", 
+#> "roberro01", "roberro01", "eastelu01", "eastelu01", "eastelu01", "eastelu01", "eastelu01", "eastelu01", "martibi02", "martibi02", "martibi02", "martibi02", "martibi02", "martibi02", "martibi02", "martibi02", "martibi02", "martibi02", "martibi02", "martibi02", "martibi02", "rosenal01", "rosenal01", "rosenal01", "rosenal01", "rosenal01", "rosenal01", "rosenal01", "rosenal01", "rosenal01", "rosenal01", "kuennha01", "kuennha01", "kuennha01", "kuennha01", "kuennha01", "kuennha01", "kuennha01", "kuennha01", 
+#> "kuennha01", "kuennha01", "kuennha01", "kuennha01", "kuennha01", "kuennha01", "kuennha01", "kuennha01", "kuennha01", "gilliji01", "gilliji01", "gilliji01", "gilliji01", "gilliji01", "gilliji01", "gilliji01", "gilliji01", "gilliji01", "gilliji01", "gilliji01", "gilliji01", "gilliji01", "gilliji01", "schoere01", "schoere01", "schoere01", "schoere01", "schoere01", "schoere01", "schoere01", "schoere01", "schoere01", "schoere01", "schoere01", "schoere01", "schoere01", "schoere01", "schoere01", "schoere01", 
+#> "schoere01", "schoere01", "schoere01", "schoere01", "schoere01", "portebo01", "portebo01", "portebo01", "portebo01", "portebo01", "portebo01", "portebo01", "portebo01", "portebo01", "portebo01", "portebo01", "portebo01", "portebo01", "portebo01", "portebo01", "portebo01", "rhodedu01", "rhodedu01", "rhodedu01", "rhodedu01", "rhodedu01", "rhodedu01", "rhodedu01", "grimbo01", "grimbo01", "grimbo01", "grimbo01", "grimbo01", "grimbo01", "grimbo01", "grimbo01", "grimbo01", "grimbo01", "grimbo01", "moonwa01", 
+#> "moonwa01", "moonwa01", "moonwa01", "moonwa01", "moonwa01", "moonwa01", "moonwa01", "moonwa01", "moonwa01", "moonwa01", "moonwa01", "kluszte01", "kluszte01", "kluszte01", "kluszte01", "kluszte01", "kluszte01", "kluszte01", "kluszte01", "kluszte01", "kluszte01", "kluszte01", "kluszte01", "kluszte01", "kluszte01", "kluszte01", "kluszte01", "avilabo01", "avilabo01", "avilabo01", "avilabo01", "avilabo01", "avilabo01", "avilabo01", "avilabo01", "avilabo01", "avilabo01", "avilabo01", "avilabo01", "avilabo01", 
+#> "antonjo02", "antonjo02", "antonjo02", "antonjo02", "antonjo02", "antonjo02", "antonjo02", "antonjo02", "antonjo02", "antonjo02", "antonjo02", "antonjo02", "antonjo02", "ayalabo01", "ayalabo01", "ayalabo01", "ayalabo01", "ayalabo01", "ayalabo01", "ayalabo01", "ayalabo01", "ayalabo01", "podrejo01", "podrejo01", "podrejo01", "podrejo01", "podrejo01", "podrejo01", "podrejo01", "podrejo01", "podrejo01", "podrejo01", "podrejo01", "podrejo01", "podrejo01", "podrejo01", "podrejo01", "podrejo01", "scorehe01", 
+#> "scorehe01", "scorehe01", "scorehe01", "scorehe01", "scorehe01", "scorehe01", "scorehe01", "virdobi01", "virdobi01", "virdobi01", "virdobi01", "virdobi01", "virdobi01", "virdobi01", "virdobi01", "virdobi01", "virdobi01", "virdobi01", "virdobi01", "virdobi01", "foxne01", "foxne01", "foxne01", "foxne01", "foxne01", "foxne01", "foxne01", "foxne01", "foxne01", "foxne01", "foxne01", "foxne01", "foxne01", "foxne01", "foxne01", "foxne01", "foxne01", "foxne01", "foxne01", "matheed01", "matheed01", "matheed01", 
+#> "matheed01", "matheed01", "matheed01", "matheed01", "matheed01", "matheed01", "matheed01", "matheed01", "matheed01", "matheed01", "matheed01", "matheed01", "matheed01", "matheed01", "matheed01", "kalinal01", "kalinal01", "kalinal01", "kalinal01", "kalinal01", "kalinal01", "kalinal01", "kalinal01", "kalinal01", "kalinal01", "kalinal01", "kalinal01", "kalinal01", "kalinal01", "kalinal01", "kalinal01", "kalinal01", "kalinal01", "kalinal01", "kalinal01", "kalinal01", "kalinal01", "fordwh01", "fordwh01", 
+#> "fordwh01", "fordwh01", "fordwh01", "fordwh01", "fordwh01", "fordwh01", "fordwh01", "fordwh01", "fordwh01", "fordwh01", "fordwh01", "fordwh01", "fordwh01", "fordwh01", "bankser01", "bankser01", "bankser01", "bankser01", "bankser01", "bankser01", "bankser01", "bankser01", "bankser01", "bankser01", "bankser01", "bankser01", "bankser01", "bankser01", "bankser01", "bankser01", "bankser01", "bankser01", "bankser01", "larsedo01", "larsedo01", "larsedo01", "larsedo01", "larsedo01", "larsedo01", "larsedo01", 
+#> "larsedo01", "larsedo01", "larsedo01", "larsedo01", "larsedo01", "larsedo01", "larsedo01", "larsedo01", "larsedo01", "larsedo01", "aparilu01", "aparilu01", "aparilu01", "aparilu01", "aparilu01", "aparilu01", "aparilu01", "aparilu01", "aparilu01", "aparilu01", "aparilu01", "aparilu01", "aparilu01", "aparilu01", "aparilu01", "aparilu01", "aparilu01", "aparilu01", "robinfr02", "robinfr02", "robinfr02", "robinfr02", "robinfr02", "robinfr02", "robinfr02", "robinfr02", "robinfr02", "robinfr02", "robinfr02", 
+#> "robinfr02", "robinfr02", "robinfr02", "robinfr02", "robinfr02", "robinfr02", "robinfr02", "robinfr02", "robinfr02", "robinfr02", "robinfr02", "boyerke01", "boyerke01", "boyerke01", "boyerke01", "boyerke01", "boyerke01", "boyerke01", "boyerke01", "boyerke01", "boyerke01", "boyerke01", "boyerke01", "boyerke01", "boyerke01", "boyerke01", "boyerke01", "boyerke01", "aaronha01", "aaronha01", "aaronha01", "aaronha01", "aaronha01", "aaronha01", "aaronha01", "aaronha01", "aaronha01", "aaronha01", "aaronha01", 
+#> "aaronha01", "aaronha01", "aaronha01", "aaronha01", "aaronha01", "aaronha01", "aaronha01", "aaronha01", "aaronha01", "aaronha01", "aaronha01", "aaronha01", "piercbi02", "piercbi02", "piercbi02", "piercbi02", "piercbi02", "piercbi02", "piercbi02", "piercbi02", "piercbi02", "piercbi02", "piercbi02", "piercbi02", "piercbi02", "piercbi02", "piercbi02", "piercbi02", "piercbi02", "piercbi02", "burdele01", "burdele01", "burdele01", "burdele01", "burdele01", "burdele01", "burdele01", "burdele01", "burdele01", 
+#> "burdele01", "burdele01", "burdele01", "burdele01", "burdele01", "burdele01", "burdele01", "burdele01", "burdele01", "burdele01", "burdele01", "burdele01", "malzofr01", "malzofr01", "malzofr01", "malzofr01", "malzofr01", "malzofr01", "malzofr01", "malzofr01", "malzofr01", "malzofr01", "malzofr01", "malzofr01", "lollash01", "lollash01", "lollash01", "lollash01", "lollash01", "lollash01", "lollash01", "lollash01", "lollash01", "lollash01", "lollash01", "lollash01", "lollash01", "lollash01", "lollash01", 
+#> "lollash01", "lollash01", "lollash01", "minosmi01", "minosmi01", "minosmi01", "minosmi01", "minosmi01", "minosmi01", "minosmi01", "minosmi01", "minosmi01", "minosmi01", "minosmi01", "minosmi01", "minosmi01", "minosmi01", "minosmi01", "minosmi01", "minosmi01", "minosmi01", "mcmilro01", "mcmilro01", "mcmilro01", "mcmilro01", "mcmilro01", "mcmilro01", "mcmilro01", "mcmilro01", "mcmilro01", "mcmilro01", "mcmilro01", "mcmilro01", "mcmilro01", "mcmilro01", "mcmilro01", "mcmilro01", "mcmilro01", "kubekto01", 
+#> "kubekto01", "kubekto01", "kubekto01", "kubekto01", "kubekto01", "kubekto01", "kubekto01", "kubekto01", "sanfoja02", "sanfoja02", "sanfoja02", "sanfoja02", "sanfoja02", "sanfoja02", "sanfoja02", "sanfoja02", "sanfoja02", "sanfoja02", "sanfoja02", "sanfoja02", "sanfoja02", "sanfoja02", "bunniji01", "bunniji01", "bunniji01", "bunniji01", "bunniji01", "bunniji01", "bunniji01", "bunniji01", "bunniji01", "bunniji01", "bunniji01", "bunniji01", "bunniji01", "bunniji01", "bunniji01", "bunniji01", "bunniji01", 
+#> "bunniji01", "howarel01", "howarel01", "howarel01", "howarel01", "howarel01", "howarel01", "howarel01", "howarel01", "howarel01", "howarel01", "howarel01", "howarel01", "howarel01", "howarel01", "howarel01", "turlebo01", "turlebo01", "turlebo01", "turlebo01", "turlebo01", "turlebo01", "turlebo01", "turlebo01", "turlebo01", "turlebo01", "turlebo01", "turlebo01", "turlebo01", "powervi01", "powervi01", "powervi01", "powervi01", "powervi01", "powervi01", "powervi01", "powervi01", "powervi01", "powervi01", 
+#> "powervi01", "powervi01", "powervi01", "powervi01", "powervi01", "bollifr01", "bollifr01", "bollifr01", "bollifr01", "bollifr01", "bollifr01", "bollifr01", "bollifr01", "bollifr01", "bollifr01", "bollifr01", "bollifr01", "piersji01", "piersji01", "piersji01", "piersji01", "piersji01", "piersji01", "piersji01", "piersji01", "piersji01", "piersji01", "piersji01", "piersji01", "piersji01", "piersji01", "piersji01", "piersji01", "piersji01", "piersji01", "piersji01", "siebeno01", "siebeno01", "siebeno01", 
+#> "siebeno01", "siebeno01", "siebeno01", "siebeno01", "siebeno01", "siebeno01", "siebeno01", "siebeno01", "siebeno01", "siebeno01", "mazerbi01", "mazerbi01", "mazerbi01", "mazerbi01", "mazerbi01", "mazerbi01", "mazerbi01", "mazerbi01", "mazerbi01", "mazerbi01", "mazerbi01", "mazerbi01", "mazerbi01", "mazerbi01", "mazerbi01", "mazerbi01", "mazerbi01", "crandde01", "crandde01", "crandde01", "crandde01", "crandde01", "crandde01", "crandde01", "crandde01", "crandde01", "crandde01", "crandde01", "crandde01", 
+#> "crandde01", "crandde01", "crandde01", "crandde01", "haddiha01", "haddiha01", "haddiha01", "haddiha01", "haddiha01", "haddiha01", "haddiha01", "haddiha01", "haddiha01", "haddiha01", "haddiha01", "haddiha01", "haddiha01", "haddiha01", "haddiha01", "jenseja01", "jenseja01", "jenseja01", "jenseja01", "jenseja01", "jenseja01", "jenseja01", "jenseja01", "jenseja01", "jenseja01", "jenseja01", "jenseja01", "pearsal02", "pearsal02", "pearsal02", "pearsal02", "pearsal02", "pearsal02", "pearsal02", "pearsal02", 
+#> "pearsal02", "pearsal02", "cepedor01", "cepedor01", "cepedor01", "cepedor01", "cepedor01", "cepedor01", "cepedor01", "cepedor01", "cepedor01", "cepedor01", "cepedor01", "cepedor01", "cepedor01", "cepedor01", "cepedor01", "cepedor01", "cepedor01", "cepedor01", "cepedor01", "thomafr03", "thomafr03", "thomafr03", "thomafr03", "thomafr03", "thomafr03", "thomafr03", "thomafr03", "thomafr03", "thomafr03", "thomafr03", "thomafr03", "thomafr03", "thomafr03", "thomafr03", "thomafr03", "thomafr03", "thomafr03", 
+#> "thomafr03", "thomafr03", "frienbo01", "frienbo01", "frienbo01", "frienbo01", "frienbo01", "frienbo01", "frienbo01", "frienbo01", "frienbo01", "frienbo01", "frienbo01", "frienbo01", "frienbo01", "frienbo01", "frienbo01", "frienbo01", "frienbo01", "sherrla01", "sherrla01", "sherrla01", "sherrla01", "sherrla01", "sherrla01", "sherrla01", "sherrla01", "sherrla01", "sherrla01", "sherrla01", "sherrla01", "wynnea01", "wynnea01", "wynnea01", "wynnea01", "wynnea01", "wynnea01", "wynnea01", "wynnea01", "wynnea01", 
+#> "wynnea01", "wynnea01", "wynnea01", "wynnea01", "wynnea01", "wynnea01", "wynnea01", "wynnea01", "wynnea01", "wynnea01", "wynnea01", "wynnea01", "wynnea01", "wynnea01", "nealch01", "nealch01", "nealch01", "nealch01", "nealch01", "nealch01", "nealch01", "nealch01", "nealch01", "brandja01", "brandja01", "brandja01", "brandja01", "brandja01", "brandja01", "brandja01", "brandja01", "brandja01", "brandja01", "brandja01", "brandja01", "brandja01", "allisbo01", "allisbo01", "allisbo01", "allisbo01", "allisbo01", 
+#> "allisbo01", "allisbo01", "allisbo01", "allisbo01", "allisbo01", "allisbo01", "allisbo01", "allisbo01", "mccovwi01", "mccovwi01", "mccovwi01", "mccovwi01", "mccovwi01", "mccovwi01", "mccovwi01", "mccovwi01", "mccovwi01", "mccovwi01", "mccovwi01", "mccovwi01", "mccovwi01", "mccovwi01", "mccovwi01", "mccovwi01", "mccovwi01", "mccovwi01", "mccovwi01", "mccovwi01", "mccovwi01", "mccovwi01", "mccovwi01", "jonessa02", "jonessa02", "jonessa02", "jonessa02", "jonessa02", "jonessa02", "jonessa02", "jonessa02", 
+#> "jonessa02", "jonessa02", "jonessa02", "jonessa02", "lawve01", "lawve01", "lawve01", "lawve01", "lawve01", "lawve01", "lawve01", "lawve01", "lawve01", "lawve01", "lawve01", "lawve01", "lawve01", "lawve01", "lawve01", "lawve01", "robinbr01", "robinbr01", "robinbr01", "robinbr01", "robinbr01", "robinbr01", "robinbr01", "robinbr01", "robinbr01", "robinbr01", "robinbr01", "robinbr01", "robinbr01", "robinbr01", "robinbr01", "robinbr01", "robinbr01", "robinbr01", "robinbr01", "robinbr01", "robinbr01", 
+#> "robinbr01", "robinbr01", "batteea01", "batteea01", "batteea01", "batteea01", "batteea01", "batteea01", "batteea01", "batteea01", "batteea01", "batteea01", "batteea01", "batteea01", "batteea01", "landiji01", "landiji01", "landiji01", "landiji01", "landiji01", "landiji01", "landiji01", "landiji01", "landiji01", "landiji01", "landiji01", "landiji01", "landiji01", "marisro01", "marisro01", "marisro01", "marisro01", "marisro01", "marisro01", "marisro01", "marisro01", "marisro01", "marisro01", "marisro01", 
+#> "marisro01", "marisro01", "whitebi03", "whitebi03", "whitebi03", "whitebi03", "whitebi03", "whitebi03", "whitebi03", "whitebi03", "whitebi03", "whitebi03", "whitebi03", "whitebi03", "whitebi03", "groatdi01", "groatdi01", "groatdi01", "groatdi01", "groatdi01", "groatdi01", "groatdi01", "groatdi01", "groatdi01", "groatdi01", "groatdi01", "groatdi01", "groatdi01", "groatdi01", "groatdi01", "hansero02", "hansero02", "hansero02", "hansero02", "hansero02", "hansero02", "hansero02", "hansero02", "hansero02", 
+#> "hansero02", "hansero02", "hansero02", "hansero02", "hansero02", "hansero02", "hansero02", "howarfr01", "howarfr01", "howarfr01", "howarfr01", "howarfr01", "howarfr01", "howarfr01", "howarfr01", "howarfr01", "howarfr01", "howarfr01", "howarfr01", "howarfr01", "howarfr01", "howarfr01", "howarfr01", "howarfr01", "skowrbi01", "skowrbi01", "skowrbi01", "skowrbi01", "skowrbi01", "skowrbi01", "skowrbi01", "skowrbi01", "skowrbi01", "skowrbi01", "skowrbi01", "skowrbi01", "skowrbi01", "skowrbi01", "skowrbi01", 
+#> "skowrbi01", "brogler01", "brogler01", "brogler01", "brogler01", "brogler01", "brogler01", "brogler01", "brogler01", "brogler01", "fornimi01", "fornimi01", "fornimi01", "fornimi01", "fornimi01", "fornimi01", "fornimi01", "fornimi01", "fornimi01", "fornimi01", "fornimi01", "fornimi01", "fornimi01", "fornimi01", "fornimi01", "mcdanli01", "mcdanli01", "mcdanli01", "mcdanli01", "mcdanli01", "mcdanli01", "mcdanli01", "mcdanli01", "mcdanli01", "mcdanli01", "mcdanli01", "mcdanli01", "mcdanli01", "mcdanli01", 
+#> "mcdanli01", "mcdanli01", "mcdanli01", "mcdanli01", "mcdanli01", "mcdanli01", "mcdanli01", "mcdanli01", "estrach01", "estrach01", "estrach01", "estrach01", "estrach01", "estrach01", "estrach01", "richabo01", "richabo01", "richabo01", "richabo01", "richabo01", "richabo01", "richabo01", "richabo01", "richabo01", "richabo01", "richabo01", "richabo01", "laryfr01", "laryfr01", "laryfr01", "laryfr01", "laryfr01", "laryfr01", "laryfr01", "laryfr01", "laryfr01", "laryfr01", "laryfr01", "laryfr01", "laryfr01", 
+#> "laryfr01", "laryfr01", "rosebjo01", "rosebjo01", "rosebjo01", "rosebjo01", "rosebjo01", "rosebjo01", "rosebjo01", "rosebjo01", "rosebjo01", "rosebjo01", "rosebjo01", "rosebjo01", "rosebjo01", "rosebjo01", "clemero01", "clemero01", "clemero01", "clemero01", "clemero01", "clemero01", "clemero01", "clemero01", "clemero01", "clemero01", "clemero01", "clemero01", "clemero01", "clemero01", "clemero01", "clemero01", "clemero01", "clemero01", "pinsova01", "pinsova01", "pinsova01", "pinsova01", "pinsova01", 
+#> "pinsova01", "pinsova01", "pinsova01", "pinsova01", "pinsova01", "pinsova01", "pinsova01", "pinsova01", "pinsova01", "pinsova01", "pinsova01", "pinsova01", "pinsova01", "willsma01", "willsma01", "willsma01", "willsma01", "willsma01", "willsma01", "willsma01", "willsma01", "willsma01", "willsma01", "willsma01", "willsma01", "willsma01", "willsma01", "willsma01", "schwado01", "schwado01", "schwado01", "schwado01", "schwado01", "schwado01", "schwado01", "schwado01", "willibi01", "willibi01", "willibi01", 
+#> "willibi01", "willibi01", "willibi01", "willibi01", "willibi01", "willibi01", "willibi01", "willibi01", "willibi01", "willibi01", "willibi01", "willibi01", "willibi01", "willibi01", "willibi01", "cashno01", "cashno01", "cashno01", "cashno01", "cashno01", "cashno01", "cashno01", "cashno01", "cashno01", "cashno01", "cashno01", "cashno01", "cashno01", "cashno01", "cashno01", "cashno01", "cashno01", "colavro01", "colavro01", "colavro01", "colavro01", "colavro01", "colavro01", "colavro01", "colavro01", 
+#> "colavro01", "colavro01", "colavro01", "colavro01", "colavro01", "colavro01", "colavro01", "colavro01", "burgesm01", "burgesm01", "burgesm01", "burgesm01", "burgesm01", "burgesm01", "burgesm01", "burgesm01", "burgesm01", "burgesm01", "burgesm01", "burgesm01", "burgesm01", "burgesm01", "burgesm01", "burgesm01", "burgesm01", "burgesm01", "burgesm01", "burgesm01", "jayjo01", "jayjo01", "jayjo01", "jayjo01", "jayjo01", "jayjo01", "jayjo01", "jayjo01", "jayjo01", "jayjo01", "jayjo01", "jayjo01", "jayjo01", 
+#> "jayjo01", "arroylu01", "arroylu01", "arroylu01", "arroylu01", "arroylu01", "arroylu01", "arroylu01", "arroylu01", "millest01", "millest01", "millest01", "millest01", "millest01", "millest01", "millest01", "millest01", "millest01", "millest01", "millest01", "millest01", "millest01", "millest01", "millest01", "millest01", "millest01", "wagnele01", "wagnele01", "wagnele01", "wagnele01", "wagnele01", "wagnele01", "wagnele01", "wagnele01", "wagnele01", "wagnele01", "wagnele01", "wagnele01", "wagnele01", 
+#> "terryra01", "terryra01", "terryra01", "terryra01", "terryra01", "terryra01", "terryra01", "terryra01", "terryra01", "terryra01", "terryra01", "terryra01", "terryra01", "terryra01", "terryra01", "drysddo01", "drysddo01", "drysddo01", "drysddo01", "drysddo01", "drysddo01", "drysddo01", "drysddo01", "drysddo01", "drysddo01", "drysddo01", "drysddo01", "drysddo01", "drysddo01", "kaatji01", "kaatji01", "kaatji01", "kaatji01", "kaatji01", "kaatji01", "kaatji01", "kaatji01", "kaatji01", "kaatji01", "kaatji01", 
+#> "kaatji01", "kaatji01", "kaatji01", "kaatji01", "kaatji01", "kaatji01", "kaatji01", "kaatji01", "kaatji01", "kaatji01", "kaatji01", "kaatji01", "kaatji01", "kaatji01", "kaatji01", "kaatji01", "kaatji01", "hubbske01", "hubbske01", "hubbske01", "davenji01", "davenji01", "davenji01", "davenji01", "davenji01", "davenji01", "davenji01", "davenji01", "davenji01", "davenji01", "davenji01", "davenji01", "davenji01", "treshto01", "treshto01", "treshto01", "treshto01", "treshto01", "treshto01", "treshto01", 
+#> "treshto01", "treshto01", "treshto01", "donovdi01", "donovdi01", "donovdi01", "donovdi01", "donovdi01", "donovdi01", "donovdi01", "donovdi01", "donovdi01", "donovdi01", "donovdi01", "donovdi01", "donovdi01", "donovdi01", "donovdi01", "davisto02", "davisto02", "davisto02", "davisto02", "davisto02", "davisto02", "davisto02", "davisto02", "davisto02", "davisto02", "davisto02", "davisto02", "davisto02", "davisto02", "davisto02", "davisto02", "davisto02", "davisto02", "davisto02", "davisto02", "davisto02", 
+#> "davisto02", "davisto02", "purkebo01", "purkebo01", "purkebo01", "purkebo01", "purkebo01", "purkebo01", "purkebo01", "purkebo01", "purkebo01", "purkebo01", "purkebo01", "purkebo01", "purkebo01", "radatdi01", "radatdi01", "radatdi01", "radatdi01", "radatdi01", "radatdi01", "radatdi01", "radatdi01", "radatdi01", "radatdi01", "facero01", "facero01", "facero01", "facero01", "facero01", "facero01", "facero01", "facero01", "facero01", "facero01", "facero01", "facero01", "facero01", "facero01", "facero01", 
+#> "facero01", "facero01", "koufasa01", "koufasa01", "koufasa01", "koufasa01", "koufasa01", "koufasa01", "koufasa01", "koufasa01", "koufasa01", "koufasa01", "koufasa01", "koufasa01", "yastrca01", "yastrca01", "yastrca01", "yastrca01", "yastrca01", "yastrca01", "yastrca01", "yastrca01", "yastrca01", "yastrca01", "yastrca01", "yastrca01", "yastrca01", "yastrca01", "yastrca01", "yastrca01", "yastrca01", "yastrca01", "yastrca01", "yastrca01", "yastrca01", "yastrca01", "yastrca01", "versazo01", "versazo01", 
+#> "versazo01", "versazo01", "versazo01", "versazo01", "versazo01", "versazo01", "versazo01", "versazo01", "versazo01", "versazo01", "versazo01", "edwarjo01", "edwarjo01", "edwarjo01", "edwarjo01", "edwarjo01", "edwarjo01", "edwarjo01", "edwarjo01", "edwarjo01", "edwarjo01", "edwarjo01", "edwarjo01", "edwarjo01", "edwarjo01", "floodcu01", "floodcu01", "floodcu01", "floodcu01", "floodcu01", "floodcu01", "floodcu01", "floodcu01", "floodcu01", "floodcu01", "floodcu01", "floodcu01", "floodcu01", "floodcu01", 
+#> "floodcu01", "winebo01", "winebo01", "winebo01", "winebo01", "winebo01", "winebo01", "winebo01", "winebo01", "winebo01", "winebo01", "winebo01", "winebo01", "peterga01", "peterga01", "peterga01", "peterga01", "peterga01", "peterga01", "peterga01", "peterga01", "peterga01", "peterga01", "peterga01", "peterga01", "peterga01", "peterga01", "rosepe01", "rosepe01", "rosepe01", "rosepe01", "rosepe01", "rosepe01", "rosepe01", "rosepe01", "rosepe01", "rosepe01", "rosepe01", "rosepe01", "rosepe01", "rosepe01", 
+#> "rosepe01", "rosepe01", "rosepe01", "rosepe01", "rosepe01", "rosepe01", "rosepe01", "rosepe01", "rosepe01", "rosepe01", "rosepe01", "pepitjo01", "pepitjo01", "pepitjo01", "pepitjo01", "pepitjo01", "pepitjo01", "pepitjo01", "pepitjo01", "pepitjo01", "pepitjo01", "pepitjo01", "pepitjo01", "pepitjo01", "pepitjo01", "maricju01", "maricju01", "maricju01", "maricju01", "maricju01", "maricju01", "maricju01", "maricju01", "maricju01", "maricju01", "maricju01", "maricju01", "maricju01", "maricju01", "maricju01", 
+#> "maricju01", "callijo01", "callijo01", "callijo01", "callijo01", "callijo01", "callijo01", "callijo01", "callijo01", "callijo01", "callijo01", "callijo01", "callijo01", "callijo01", "callijo01", "callijo01", "callijo01", "gibsobo01", "gibsobo01", "gibsobo01", "gibsobo01", "gibsobo01", "gibsobo01", "gibsobo01", "gibsobo01", "gibsobo01", "gibsobo01", "gibsobo01", "gibsobo01", "gibsobo01", "gibsobo01", "gibsobo01", "gibsobo01", "gibsobo01", "chancde01", "chancde01", "chancde01", "chancde01", "chancde01", 
+#> "chancde01", "chancde01", "chancde01", "chancde01", "chancde01", "chancde01", "chancde01", "davalvi01", "davalvi01", "davalvi01", "davalvi01", "davalvi01", "davalvi01", "davalvi01", "davalvi01", "davalvi01", "davalvi01", "davalvi01", "davalvi01", "davalvi01", "davalvi01", "davalvi01", "davalvi01", "davalvi01", "davalvi01", "davalvi01", "santoro01", "santoro01", "santoro01", "santoro01", "santoro01", "santoro01", "santoro01", "santoro01", "santoro01", "santoro01", "santoro01", "santoro01", "santoro01", 
+#> "santoro01", "santoro01", "amaroru01", "amaroru01", "amaroru01", "amaroru01", "amaroru01", "amaroru01", "amaroru01", "amaroru01", "amaroru01", "amaroru01", "amaroru01", "olivato01", "olivato01", "olivato01", "olivato01", "olivato01", "olivato01", "olivato01", "olivato01", "olivato01", "olivato01", "olivato01", "olivato01", "olivato01", "olivato01", "olivato01", "allendi01", "allendi01", "allendi01", "allendi01", "allendi01", "allendi01", "allendi01", "allendi01", "allendi01", "allendi01", "allendi01", 
+#> "allendi01", "allendi01", "allendi01", "allendi01", "stuardi01", "stuardi01", "stuardi01", "stuardi01", "stuardi01", "stuardi01", "stuardi01", "stuardi01", "stuardi01", "stuardi01", "stuardi01", "killeha01", "killeha01", "killeha01", "killeha01", "killeha01", "killeha01", "killeha01", "killeha01", "killeha01", "killeha01", "killeha01", "killeha01", "killeha01", "killeha01", "killeha01", "killeha01", "killeha01", "killeha01", "killeha01", "killeha01", "killeha01", "killeha01", "fregoji01", "fregoji01", 
+#> "fregoji01", "fregoji01", "fregoji01", "fregoji01", "fregoji01", "fregoji01", "fregoji01", "fregoji01", "fregoji01", "fregoji01", "fregoji01", "fregoji01", "fregoji01", "fregoji01", "fregoji01", "fregoji01", "fregoji01", "fregoji01", "huntro01", "huntro01", "huntro01", "huntro01", "huntro01", "huntro01", "huntro01", "huntro01", "huntro01", "huntro01", "huntro01", "huntro01", "huntro01", "torrejo01", "torrejo01", "torrejo01", "torrejo01", "torrejo01", "torrejo01", "torrejo01", "torrejo01", "torrejo01", 
+#> "torrejo01", "torrejo01", "torrejo01", "torrejo01", "torrejo01", "torrejo01", "torrejo01", "torrejo01", "torrejo01", "mcbeaal01", "mcbeaal01", "mcbeaal01", "mcbeaal01", "mcbeaal01", "mcbeaal01", "mcbeaal01", "mcbeaal01", "mcbeaal01", "mcbeaal01", "mcbeaal01", "mcbeaal01", "freehbi01", "freehbi01", "freehbi01", "freehbi01", "freehbi01", "freehbi01", "freehbi01", "freehbi01", "freehbi01", "freehbi01", "freehbi01", "freehbi01", "freehbi01", "freehbi01", "freehbi01", "cardele01", "cardele01", "cardele01", 
+#> "cardele01", "cardele01", "cardele01", "cardele01", "cardele01", "cardele01", "cardele01", "cardele01", "cardele01", "cardele01", "cardele01", "cardele01", "cardele01", "blefacu01", "blefacu01", "blefacu01", "blefacu01", "blefacu01", "blefacu01", "blefacu01", "blefacu01", "blefacu01", "blefacu01", "lefebji01", "lefebji01", "lefebji01", "lefebji01", "lefebji01", "lefebji01", "lefebji01", "lefebji01", "whitffr01", "whitffr01", "whitffr01", "whitffr01", "whitffr01", "whitffr01", "whitffr01", "whitffr01", 
+#> "whitffr01", "hallji02", "hallji02", "hallji02", "hallji02", "hallji02", "hallji02", "hallji02", "hallji02", "hallji02", "hallji02", "hallji02", "hallji02", "grantmu01", "grantmu01", "grantmu01", "grantmu01", "grantmu01", "grantmu01", "grantmu01", "grantmu01", "grantmu01", "grantmu01", "grantmu01", "grantmu01", "grantmu01", "grantmu01", "grantmu01", "grantmu01", "grantmu01", "grantmu01", "stottme01", "stottme01", "stottme01", "stottme01", "stottme01", "stottme01", "stottme01", "stottme01", "stottme01", 
+#> "stottme01", "stottme01", "johnsde01", "johnsde01", "johnsde01", "johnsde01", "johnsde01", "johnsde01", "johnsde01", "johnsde01", "johnsde01", "johnsde01", "johnsde01", "johnsde01", "johnsde01", "johnsde01", "johnsde01", "johnsde01", "johnsde01", "johnsde01", "johnsde01", "johnsde01", "johnsde01", "stargwi01", "stargwi01", "stargwi01", "stargwi01", "stargwi01", "stargwi01", "stargwi01", "stargwi01", "stargwi01", "stargwi01", "stargwi01", "stargwi01", "stargwi01", "stargwi01", "stargwi01", "stargwi01", 
+#> "stargwi01", "stargwi01", "stargwi01", "stargwi01", "stargwi01", "fisheed02", "fisheed02", "fisheed02", "fisheed02", "fisheed02", "fisheed02", "fisheed02", "fisheed02", "fisheed02", "fisheed02", "fisheed02", "fisheed02", "fisheed02", "fisheed02", "fisheed02", "fisheed02", "fisheed02", "fisheed02", "abernte02", "abernte02", "abernte02", "abernte02", "abernte02", "abernte02", "abernte02", "abernte02", "abernte02", "abernte02", "abernte02", "abernte02", "abernte02", "abernte02", "abernte02", "abernte02", 
+#> "abernte02", "knoopbo01", "knoopbo01", "knoopbo01", "knoopbo01", "knoopbo01", "knoopbo01", "knoopbo01", "knoopbo01", "knoopbo01", "knoopbo01", "ageeto01", "ageeto01", "ageeto01", "ageeto01", "ageeto01", "ageeto01", "ageeto01", "ageeto01", "ageeto01", "ageeto01", "ageeto01", "ageeto01", "ageeto01", "alleyge01", "alleyge01", "alleyge01", "alleyge01", "alleyge01", "alleyge01", "alleyge01", "alleyge01", "alleyge01", "alleyge01", "alleyge01", "helmsto01", "helmsto01", "helmsto01", "helmsto01", "helmsto01", 
+#> "helmsto01", "helmsto01", "helmsto01", "helmsto01", "helmsto01", "helmsto01", "helmsto01", "helmsto01", "helmsto01", "helmsto01", "powelbo01", "powelbo01", "powelbo01", "powelbo01", "powelbo01", "powelbo01", "powelbo01", "powelbo01", "powelbo01", "powelbo01", "powelbo01", "powelbo01", "powelbo01", "powelbo01", "powelbo01", "powelbo01", "powelbo01", "casanpa01", "casanpa01", "casanpa01", "casanpa01", "casanpa01", "casanpa01", "casanpa01", "casanpa01", "casanpa01", "casanpa01", "wilsoea01", "wilsoea01", 
+#> "wilsoea01", "wilsoea01", "wilsoea01", "wilsoea01", "wilsoea01", "wilsoea01", "wilsoea01", "wilsoea01", "wilsoea01", "wilsoea01", "wilsoea01", "aloufe01", "aloufe01", "aloufe01", "aloufe01", "aloufe01", "aloufe01", "aloufe01", "aloufe01", "aloufe01", "aloufe01", "aloufe01", "aloufe01", "aloufe01", "aloufe01", "aloufe01", "aloufe01", "aloufe01", "aloufe01", "aloufe01", "akerja01", "akerja01", "akerja01", "akerja01", "akerja01", "akerja01", "akerja01", "akerja01", "akerja01", "akerja01", "akerja01", 
+#> "akerja01", "akerja01", "akerja01", "reganph01", "reganph01", "reganph01", "reganph01", "reganph01", "reganph01", "reganph01", "reganph01", "reganph01", "reganph01", "reganph01", "reganph01", "reganph01", "reganph01", "reganph01", "perezto01", "perezto01", "perezto01", "perezto01", "perezto01", "perezto01", "perezto01", "perezto01", "perezto01", "perezto01", "perezto01", "perezto01", "perezto01", "perezto01", "perezto01", "perezto01", "perezto01", "perezto01", "perezto01", "perezto01", "perezto01", 
+#> "perezto01", "perezto01", "brocklo01", "brocklo01", "brocklo01", "brocklo01", "brocklo01", "brocklo01", "brocklo01", "brocklo01", "brocklo01", "brocklo01", "brocklo01", "brocklo01", "brocklo01", "brocklo01", "brocklo01", "brocklo01", "brocklo01", "brocklo01", "brocklo01", "brocklo01", "lonboji01", "lonboji01", "lonboji01", "lonboji01", "lonboji01", "lonboji01", "lonboji01", "lonboji01", "lonboji01", "lonboji01", "lonboji01", "lonboji01", "lonboji01", "lonboji01", "lonboji01", "mccormi03", "mccormi03", 
+#> "mccormi03", "mccormi03", "mccormi03", "mccormi03", "mccormi03", "mccormi03", "mccormi03", "mccormi03", "mccormi03", "mccormi03", "mccormi03", "mccormi03", "mccormi03", "mccormi03", "mccormi03", "scottge02", "scottge02", "scottge02", "scottge02", "scottge02", "scottge02", "scottge02", "scottge02", "scottge02", "scottge02", "scottge02", "scottge02", "scottge02", "scottge02", "scottge02", "scottge02", "blairpa01", "blairpa01", "blairpa01", "blairpa01", "blairpa01", "blairpa01", "blairpa01", "blairpa01", 
+#> "blairpa01", "blairpa01", "blairpa01", "blairpa01", "blairpa01", "blairpa01", "blairpa01", "blairpa01", "blairpa01", "blairpa01", "parkewe01", "parkewe01", "parkewe01", "parkewe01", "parkewe01", "parkewe01", "parkewe01", "parkewe01", "parkewe01", "hundlra01", "hundlra01", "hundlra01", "hundlra01", "hundlra01", "hundlra01", "hundlra01", "hundlra01", "hundlra01", "hundlra01", "hundlra01", "hundlra01", "hundlra01", "hundlra01", "carewro01", "carewro01", "carewro01", "carewro01", "carewro01", "carewro01", 
+#> "carewro01", "carewro01", "carewro01", "carewro01", "carewro01", "carewro01", "carewro01", "carewro01", "carewro01", "carewro01", "carewro01", "carewro01", "carewro01", "seaveto01", "seaveto01", "seaveto01", "seaveto01", "seaveto01", "seaveto01", "seaveto01", "seaveto01", "seaveto01", "seaveto01", "seaveto01", "seaveto01", "seaveto01", "seaveto01", "seaveto01", "seaveto01", "seaveto01", "seaveto01", "seaveto01", "seaveto01", "seaveto01", "seaveto01", "mccarti01", "mccarti01", "mccarti01", "mccarti01", 
+#> "mccarti01", "mccarti01", "mccarti01", "mccarti01", "mccarti01", "mccarti01", "mccarti01", "mccarti01", "mccarti01", "mccarti01", "mccarti01", "mccarti01", "mccarti01", "mccarti01", "mccarti01", "mccarti01", "mccarti01", "mccarti01", "mccarti01", "mccarti01", "wynnji01", "wynnji01", "wynnji01", "wynnji01", "wynnji01", "wynnji01", "wynnji01", "wynnji01", "wynnji01", "wynnji01", "wynnji01", "wynnji01", "wynnji01", "wynnji01", "wynnji01", "wynnji01", "jenkife01", "jenkife01", "jenkife01", "jenkife01", 
+#> "jenkife01", "jenkife01", "jenkife01", "jenkife01", "jenkife01", "jenkife01", "jenkife01", "jenkife01", "jenkife01", "jenkife01", "jenkife01", "jenkife01", "jenkife01", "jenkife01", "jenkife01", "jenkife01", "rojasmi01", "rojasmi01", "rojasmi01", "lolicmi01", "lolicmi01", "lolicmi01", "lolicmi01", "lolicmi01", "lolicmi01", "lolicmi01", "lolicmi01", "lolicmi01", "lolicmi01", "lolicmi01", "lolicmi01", "lolicmi01", "lolicmi01", "lolicmi01", "lolicmi01", "mclaide01", "mclaide01", "mclaide01", "mclaide01", 
+#> "mclaide01", "mclaide01", "mclaide01", "mclaide01", "mclaide01", "mclaide01", "mclaide01", "smithre06", "smithre06", "smithre06", "smithre06", "smithre06", "smithre06", "smithre06", "smithre06", "smithre06", "smithre06", "smithre06", "smithre06", "smithre06", "smithre06", "smithre06", "smithre06", "smithre06", "smithre06", "stanlmi01", "stanlmi01", "stanlmi01", "stanlmi01", "stanlmi01", "stanlmi01", "stanlmi01", "stanlmi01", "stanlmi01", "stanlmi01", "stanlmi01", "stanlmi01", "stanlmi01", "stanlmi01", 
+#> "stanlmi01", "beckegl01", "beckegl01", "beckegl01", "beckegl01", "beckegl01", "beckegl01", "beckegl01", "beckegl01", "beckegl01", "beckegl01", "beckegl01", "benchjo01", "benchjo01", "benchjo01", "benchjo01", "benchjo01", "benchjo01", "benchjo01", "benchjo01", "benchjo01", "benchjo01", "benchjo01", "benchjo01", "benchjo01", "benchjo01", "benchjo01", "benchjo01", "benchjo01", "maxvida01", "maxvida01", "maxvida01", "maxvida01", "maxvida01", "maxvida01", "maxvida01", "maxvida01", "maxvida01", "maxvida01", 
+#> "maxvida01", "maxvida01", "maxvida01", "maxvida01", "maxvida01", "maxvida01", "maxvida01", "bahnsst01", "bahnsst01", "bahnsst01", "bahnsst01", "bahnsst01", "bahnsst01", "bahnsst01", "bahnsst01", "bahnsst01", "bahnsst01", "bahnsst01", "bahnsst01", "bahnsst01", "bahnsst01", "bahnsst01", "bahnsst01", "bahnsst01", "bahnsst01", "bahnsst01", "harreke01", "harreke01", "harreke01", "harreke01", "harreke01", "harreke01", "harreke01", "harreke01", "harreke01", "harreke01", "harreke01", "harreke01", "harreke01", 
+#> "hortowi01", "hortowi01", "hortowi01", "hortowi01", "hortowi01", "hortowi01", "hortowi01", "hortowi01", "hortowi01", "hortowi01", "hortowi01", "hortowi01", "hortowi01", "hortowi01", "hortowi01", "hortowi01", "hortowi01", "hortowi01", "hortowi01", "hortowi01", "hortowi01", "mcnalda01", "mcnalda01", "mcnalda01", "mcnalda01", "mcnalda01", "mcnalda01", "mcnalda01", "mcnalda01", "mcnalda01", "mcnalda01", "mcnalda01", "mcnalda01", "mcnalda01", "mcnalda01", "kessido01", "kessido01", "kessido01", "kessido01", 
+#> "kessido01", "kessido01", "kessido01", "kessido01", "kessido01", "kessido01", "kessido01", "kessido01", "kessido01", "kessido01", "kessido01", "kessido01", "kessido01", "woodwi01", "woodwi01", "woodwi01", "woodwi01", "woodwi01", "woodwi01", "woodwi01", "woodwi01", "woodwi01", "woodwi01", "woodwi01", "woodwi01", "woodwi01", "woodwi01", "woodwi01", "woodwi01", "woodwi01", "woodwi01", "weisal01", "weisal01", "weisal01", "weisal01", "weisal01", "weisal01", "weisal01", "weisal01", "weisal01", "weisal01", 
+#> "cuellmi01", "cuellmi01", "cuellmi01", "cuellmi01", "cuellmi01", "cuellmi01", "cuellmi01", "cuellmi01", "cuellmi01", "cuellmi01", "cuellmi01", "cuellmi01", "cuellmi01", "cuellmi01", "cuellmi01", "johnsda02", "johnsda02", "johnsda02", "johnsda02", "johnsda02", "johnsda02", "johnsda02", "johnsda02", "johnsda02", "johnsda02", "johnsda02", "johnsda02", "johnsda02", "johnsda02", "belanma01", "belanma01", "belanma01", "belanma01", "belanma01", "belanma01", "belanma01", "belanma01", "belanma01", "belanma01", 
+#> "belanma01", "belanma01", "belanma01", "belanma01", "belanma01", "belanma01", "belanma01", "belanma01", "millafe01", "millafe01", "millafe01", "millafe01", "millafe01", "millafe01", "millafe01", "millafe01", "millafe01", "millafe01", "millafe01", "millafe01", "boyercl02", "boyercl02", "boyercl02", "boyercl02", "boyercl02", "boyercl02", "boyercl02", "boyercl02", "boyercl02", "boyercl02", "boyercl02", "boyercl02", "boyercl02", "boyercl02", "boyercl02", "boyercl02", "pinielo01", "pinielo01", "pinielo01", 
+#> "pinielo01", "pinielo01", "pinielo01", "pinielo01", "pinielo01", "pinielo01", "pinielo01", "pinielo01", "pinielo01", "pinielo01", "pinielo01", "pinielo01", "pinielo01", "pinielo01", "pinielo01", "sizemte01", "sizemte01", "sizemte01", "sizemte01", "sizemte01", "sizemte01", "sizemte01", "sizemte01", "sizemte01", "sizemte01", "sizemte01", "sizemte01", "sizemte01", "jacksre01", "jacksre01", "jacksre01", "jacksre01", "jacksre01", "jacksre01", "jacksre01", "jacksre01", "jacksre01", "jacksre01", "jacksre01", 
+#> "jacksre01", "jacksre01", "jacksre01", "jacksre01", "jacksre01", "jacksre01", "jacksre01", "jacksre01", "jacksre01", "jacksre01", "petrori01", "petrori01", "petrori01", "petrori01", "petrori01", "petrori01", "petrori01", "petrori01", "petrori01", "petrori01", "petrori01", "petrori01", "petrori01", "carltst01", "carltst01", "carltst01", "carltst01", "carltst01", "carltst01", "carltst01", "carltst01", "carltst01", "carltst01", "carltst01", "carltst01", "carltst01", "carltst01", "carltst01", "carltst01", 
+#> "carltst01", "carltst01", "carltst01", "carltst01", "carltst01", "carltst01", "carltst01", "carltst01", "carltst01", "carltst01", "carltst01", "alouma01", "alouma01", "alouma01", "alouma01", "alouma01", "alouma01", "alouma01", "alouma01", "alouma01", "alouma01", "alouma01", "alouma01", "alouma01", "alouma01", "alouma01", "alouma01", "alouma01", "jonescl01", "jonescl01", "jonescl01", "jonescl01", "jonescl01", "jonescl01", "jonescl01", "jonescl01", "jonescl01", "jonescl01", "jonescl01", "jonescl01", 
+#> "jonescl01", "perraro01", "perraro01", "perraro01", "perraro01", "perraro01", "perraro01", "perraro01", "perraro01", "perraro01", "perraro01", "perraro01", "perraro01", "perraro01", "perraro01", "perraro01", "grangwa01", "grangwa01", "grangwa01", "grangwa01", "grangwa01", "grangwa01", "grangwa01", "grangwa01", "grangwa01", "grangwa01", "clenddo01", "clenddo01", "clenddo01", "clenddo01", "clenddo01", "clenddo01", "clenddo01", "clenddo01", "clenddo01", "clenddo01", "clenddo01", "clenddo01", "clenddo01", 
+#> "perryji01", "perryji01", "perryji01", "perryji01", "perryji01", "perryji01", "perryji01", "perryji01", "perryji01", "perryji01", "perryji01", "perryji01", "perryji01", "perryji01", "perryji01", "perryji01", "perryji01", "perryji01", "perryji01", "spencji01", "spencji01", "spencji01", "spencji01", "spencji01", "spencji01", "spencji01", "spencji01", "spencji01", "spencji01", "spencji01", "spencji01", "spencji01", "spencji01", "spencji01", "spencji01", "spencji01", "fossera01", "fossera01", "fossera01", 
+#> "fossera01", "fossera01", "fossera01", "fossera01", "fossera01", "fossera01", "fossera01", "fossera01", "fossera01", "fossera01", "berryke01", "berryke01", "berryke01", "berryke01", "berryke01", "berryke01", "berryke01", "berryke01", "berryke01", "berryke01", "berryke01", "berryke01", "berryke01", "berryke01", "raderdo02", "raderdo02", "raderdo02", "raderdo02", "raderdo02", "raderdo02", "raderdo02", "raderdo02", "raderdo02", "raderdo02", "raderdo02", "raderdo02", "conigto01", "conigto01", "conigto01", 
+#> "conigto01", "conigto01", "conigto01", "conigto01", "conigto01", "munsoth01", "munsoth01", "munsoth01", "munsoth01", "munsoth01", "munsoth01", "munsoth01", "munsoth01", "munsoth01", "munsoth01", "munsoth01", "mortoca01", "mortoca01", "mortoca01", "mortoca01", "mortoca01", "mortoca01", "mortoca01", "mortoca01", "mcdowsa01", "mcdowsa01", "mcdowsa01", "mcdowsa01", "mcdowsa01", "mcdowsa01", "mcdowsa01", "mcdowsa01", "mcdowsa01", "mcdowsa01", "mcdowsa01", "mcdowsa01", "mcdowsa01", "mcdowsa01", "mcdowsa01", 
+#> "mcdowsa01", "merriji01", "merriji01", "merriji01", "merriji01", "merriji01", "merriji01", "merriji01", "merriji01", "merriji01", "merriji01", "merriji01", "tolanbo01", "tolanbo01", "tolanbo01", "tolanbo01", "tolanbo01", "tolanbo01", "tolanbo01", "tolanbo01", "tolanbo01", "tolanbo01", "tolanbo01", "tolanbo01", "tolanbo01", "tolanbo01", "bluevi01", "bluevi01", "bluevi01", "bluevi01", "bluevi01", "bluevi01", "bluevi01", "bluevi01", "bluevi01", "bluevi01", "bluevi01", "bluevi01", "bluevi01", "bluevi01", 
+#> "bluevi01", "bluevi01", "bluevi01", "otisam01", "otisam01", "otisam01", "otisam01", "otisam01", "otisam01", "otisam01", "otisam01", "otisam01", "otisam01", "otisam01", "otisam01", "otisam01", "otisam01", "otisam01", "otisam01", "otisam01", "bondsbo01", "bondsbo01", "bondsbo01", "bondsbo01", "bondsbo01", "bondsbo01", "bondsbo01", "bondsbo01", "bondsbo01", "bondsbo01", "bondsbo01", "bondsbo01", "bondsbo01", "bondsbo01", "bondsbo01", "daviswi02", "daviswi02", "daviswi02", "daviswi02", "daviswi02", "daviswi02", 
+#> "daviswi02", "daviswi02", "daviswi02", "daviswi02", "daviswi02", "daviswi02", "daviswi02", "daviswi02", "daviswi02", "daviswi02", "daviswi02", "daviswi02", "daviswi02", "harrebu01", "harrebu01", "harrebu01", "harrebu01", "harrebu01", "harrebu01", "harrebu01", "harrebu01", "harrebu01", "harrebu01", "harrebu01", "harrebu01", "harrebu01", "harrebu01", "harrebu01", "harrebu01", "chambch01", "chambch01", "chambch01", "chambch01", "chambch01", "chambch01", "chambch01", "chambch01", "chambch01", "chambch01", 
+#> "chambch01", "chambch01", "chambch01", "chambch01", "chambch01", "chambch01", "chambch01", "chambch01", "williea02", "williea02", "williea02", "williea02", "williea02", "williea02", "williea02", "williea02", "williea02", "rojasco01", "rojasco01", "rojasco01", "rojasco01", "rojasco01", "rojasco01", "rojasco01", "rojasco01", "rojasco01", "rojasco01", "rojasco01", "rojasco01", "rojasco01", "rojasco01", "rojasco01", "rojasco01", "rojasco01", "murcebo01", "murcebo01", "murcebo01", "murcebo01", "murcebo01", 
+#> "murcebo01", "murcebo01", "murcebo01", "murcebo01", "murcebo01", "murcebo01", "murcebo01", "murcebo01", "murcebo01", "murcebo01", "murcebo01", "murcebo01", "murcebo01", "retteme01", "retteme01", "retteme01", "retteme01", "retteme01", "retteme01", "retteme01", "retteme01", "retteme01", "retteme01", "retteme01", "retteme01", "retteme01", "palmeji01", "palmeji01", "palmeji01", "palmeji01", "palmeji01", "palmeji01", "palmeji01", "palmeji01", "palmeji01", "palmeji01", "palmeji01", "palmeji01", "palmeji01", 
+#> "palmeji01", "palmeji01", "palmeji01", "palmeji01", "palmeji01", "palmeji01", "mayle01", "mayle01", "mayle01", "mayle01", "mayle01", "mayle01", "mayle01", "mayle01", "mayle01", "mayle01", "mayle01", "mayle01", "mayle01", "mayle01", "mayle01", "mayle01", "mayle01", "mayle01", "sanguma01", "sanguma01", "sanguma01", "sanguma01", "sanguma01", "sanguma01", "sanguma01", "sanguma01", "sanguma01", "sanguma01", "sanguma01", "sanguma01", "sanguma01", "sandeke01", "sandeke01", "sandeke01", "sandeke01", "sandeke01", 
+#> "sandeke01", "sandeke01", "sandeke01", "sandeke01", "sandeke01", "sandeke01", "sandeke01", "sandeke01", "sandeke01", "giustda01", "giustda01", "giustda01", "giustda01", "giustda01", "giustda01", "giustda01", "giustda01", "giustda01", "giustda01", "giustda01", "giustda01", "giustda01", "giustda01", "giustda01", "giustda01", "morgajo02", "morgajo02", "morgajo02", "morgajo02", "morgajo02", "morgajo02", "morgajo02", "morgajo02", "morgajo02", "morgajo02", "morgajo02", "morgajo02", "morgajo02", "morgajo02", 
+#> "morgajo02", "morgajo02", "morgajo02", "morgajo02", "morgajo02", "morgajo02", "morgajo02", "morgajo02", "tenacge01", "tenacge01", "tenacge01", "tenacge01", "tenacge01", "tenacge01", "tenacge01", "tenacge01", "tenacge01", "tenacge01", "tenacge01", "tenacge01", "tenacge01", "tenacge01", "tenacge01", "perryga01", "perryga01", "perryga01", "perryga01", "perryga01", "perryga01", "perryga01", "perryga01", "perryga01", "perryga01", "perryga01", "perryga01", "perryga01", "perryga01", "perryga01", "perryga01", 
+#> "perryga01", "perryga01", "perryga01", "perryga01", "perryga01", "perryga01", "perryga01", "perryga01", "perryga01", "griffdo01", "griffdo01", "griffdo01", "griffdo01", "griffdo01", "griffdo01", "griffdo01", "griffdo01", "fiskca01", "fiskca01", "fiskca01", "fiskca01", "fiskca01", "fiskca01", "fiskca01", "fiskca01", "fiskca01", "fiskca01", "fiskca01", "fiskca01", "fiskca01", "fiskca01", "fiskca01", "fiskca01", "fiskca01", "fiskca01", "fiskca01", "fiskca01", "fiskca01", "fiskca01", "fiskca01", "fiskca01", 
+#> "brinked01", "brinked01", "brinked01", "brinked01", "brinked01", "brinked01", "brinked01", "brinked01", "brinked01", "brinked01", "brinked01", "brinked01", "brinked01", "brinked01", "brinked01", "brinked01", "brinked01", "cedence01", "cedence01", "cedence01", "cedence01", "cedence01", "cedence01", "cedence01", "cedence01", "cedence01", "cedence01", "cedence01", "cedence01", "cedence01", "cedence01", "cedence01", "cedence01", "cedence01", "cedence01", "bowala01", "bowala01", "bowala01", "bowala01", 
+#> "bowala01", "bowala01", "bowala01", "bowala01", "bowala01", "bowala01", "bowala01", "bowala01", "bowala01", "bowala01", "bowala01", "bowala01", "bowala01", "matlajo01", "matlajo01", "matlajo01", "matlajo01", "matlajo01", "matlajo01", "matlajo01", "matlajo01", "matlajo01", "matlajo01", "matlajo01", "matlajo01", "matlajo01", "rudijo01", "rudijo01", "rudijo01", "rudijo01", "rudijo01", "rudijo01", "rudijo01", "rudijo01", "rudijo01", "rudijo01", "rudijo01", "rudijo01", "rudijo01", "rudijo01", "rudijo01", 
+#> "rudijo01", "scheiri01", "scheiri01", "scheiri01", "scheiri01", "scheiri01", "scheiri01", "scheiri01", "scheiri01", "scheiri01", "scheiri01", "scheiri01", "speiech01", "speiech01", "speiech01", "speiech01", "speiech01", "speiech01", "speiech01", "speiech01", "speiech01", "speiech01", "speiech01", "speiech01", "speiech01", "speiech01", "speiech01", "speiech01", "speiech01", "speiech01", "speiech01", "speiech01", "speiech01", "speiech01", "lylesp01", "lylesp01", "lylesp01", "lylesp01", "lylesp01", 
+#> "lylesp01", "lylesp01", "lylesp01", "lylesp01", "lylesp01", "lylesp01", "lylesp01", "lylesp01", "lylesp01", "lylesp01", "lylesp01", "lylesp01", "lylesp01", "carrocl02", "carrocl02", "carrocl02", "carrocl02", "carrocl02", "carrocl02", "carrocl02", "carrocl02", "carrocl02", "carrocl02", "carrocl02", "carrocl02", "carrocl02", "carrocl02", "carrocl02", "carrocl02", "carrocl02", "campabe01", "campabe01", "campabe01", "campabe01", "campabe01", "campabe01", "campabe01", "campabe01", "campabe01", "campabe01", 
+#> "campabe01", "campabe01", "campabe01", "campabe01", "campabe01", "campabe01", "campabe01", "campabe01", "campabe01", "campabe01", "grichbo01", "grichbo01", "grichbo01", "grichbo01", "grichbo01", "grichbo01", "grichbo01", "grichbo01", "grichbo01", "grichbo01", "grichbo01", "grichbo01", "grichbo01", "grichbo01", "grichbo01", "grichbo01", "grichbo01", "jorgemi01", "jorgemi01", "jorgemi01", "jorgemi01", "jorgemi01", "jorgemi01", "jorgemi01", "jorgemi01", "jorgemi01", "jorgemi01", "jorgemi01", "jorgemi01", 
+#> "jorgemi01", "jorgemi01", "jorgemi01", "jorgemi01", "jorgemi01", "jorgemi01", "jorgemi01", "jorgemi01", "metzgro01", "metzgro01", "metzgro01", "metzgro01", "metzgro01", "metzgro01", "metzgro01", "metzgro01", "metzgro01", "metzgro01", "metzgro01", "metzgro01", "hillejo01", "hillejo01", "hillejo01", "hillejo01", "hillejo01", "hillejo01", "hillejo01", "hillejo01", "hillejo01", "hillejo01", "hillejo01", "hillejo01", "hillejo01", "hillejo01", "hillejo01", "bumbral01", "bumbral01", "bumbral01", "bumbral01", 
+#> "bumbral01", "bumbral01", "bumbral01", "bumbral01", "bumbral01", "bumbral01", "bumbral01", "bumbral01", "bumbral01", "bumbral01", "matthga01", "matthga01", "matthga01", "matthga01", "matthga01", "matthga01", "matthga01", "matthga01", "matthga01", "matthga01", "matthga01", "matthga01", "matthga01", "matthga01", "matthga01", "matthga01", "matthga01", "maybejo01", "maybejo01", "maybejo01", "maybejo01", "maybejo01", "maybejo01", "maybejo01", "maybejo01", "maybejo01", "maybejo01", "maybejo01", "maybejo01", 
+#> "maybejo01", "maybejo01", "maybejo01", "maybejo01", "bandosa01", "bandosa01", "bandosa01", "bandosa01", "bandosa01", "bandosa01", "bandosa01", "bandosa01", "bandosa01", "bandosa01", "bandosa01", "bandosa01", "bandosa01", "bandosa01", "bandosa01", "bandosa01", "holtzke01", "holtzke01", "holtzke01", "holtzke01", "holtzke01", "holtzke01", "holtzke01", "holtzke01", "holtzke01", "holtzke01", "holtzke01", "holtzke01", "holtzke01", "holtzke01", "holtzke01", "holtzke01", "holtzke01", "evansda01", "evansda01", 
+#> "evansda01", "evansda01", "evansda01", "evansda01", "evansda01", "evansda01", "evansda01", "evansda01", "evansda01", "evansda01", "evansda01", "evansda01", "evansda01", "evansda01", "evansda01", "evansda01", "evansda01", "evansda01", "evansda01", "evansda01", "bryanro01", "bryanro01", "bryanro01", "bryanro01", "bryanro01", "bryanro01", "bryanro01", "bryanro01", "russebi01", "russebi01", "russebi01", "russebi01", "russebi01", "russebi01", "russebi01", "russebi01", "russebi01", "russebi01", "russebi01", 
+#> "russebi01", "russebi01", "russebi01", "russebi01", "russebi01", "russebi01", "russebi01", "marshmi01", "marshmi01", "marshmi01", "marshmi01", "marshmi01", "marshmi01", "marshmi01", "marshmi01", "marshmi01", "marshmi01", "marshmi01", "marshmi01", "marshmi01", "marshmi01", "marshmi01", "marshmi01", "marshmi01", "garvest01", "garvest01", "garvest01", "garvest01", "garvest01", "garvest01", "garvest01", "garvest01", "garvest01", "garvest01", "garvest01", "garvest01", "garvest01", "garvest01", "garvest01", 
+#> "garvest01", "garvest01", "garvest01", "garvest01", "greendi01", "greendi01", "greendi01", "greendi01", "greendi01", "greendi01", "greendi01", "greendi01", "greendi01", "greendi01", "greendi01", "greendi01", "hunteca01", "hunteca01", "hunteca01", "hunteca01", "hunteca01", "hunteca01", "hunteca01", "hunteca01", "hunteca01", "hunteca01", "hunteca01", "hunteca01", "hunteca01", "hunteca01", "hunteca01", "geronce01", "geronce01", "geronce01", "geronce01", "geronce01", "geronce01", "geronce01", "geronce01", 
+#> "geronce01", "geronce01", "geronce01", "geronce01", "geronce01", "geronce01", "geronce01", "messean01", "messean01", "messean01", "messean01", "messean01", "messean01", "messean01", "messean01", "messean01", "messean01", "messean01", "messean01", "conceda01", "conceda01", "conceda01", "conceda01", "conceda01", "conceda01", "conceda01", "conceda01", "conceda01", "conceda01", "conceda01", "conceda01", "conceda01", "conceda01", "conceda01", "conceda01", "conceda01", "conceda01", "conceda01", "thompda01", 
+#> "thompda01", "thompda01", "thompda01", "thompda01", "thompda01", "thompda01", "thompda01", "burroje01", "burroje01", "burroje01", "burroje01", "burroje01", "burroje01", "burroje01", "burroje01", "burroje01", "burroje01", "burroje01", "burroje01", "burroje01", "burroje01", "burroje01", "burroje01", "hargrmi01", "hargrmi01", "hargrmi01", "hargrmi01", "hargrmi01", "hargrmi01", "hargrmi01", "hargrmi01", "hargrmi01", "hargrmi01", "hargrmi01", "hargrmi01", "hargrmi01", "mcbriba01", "mcbriba01", "mcbriba01", 
+#> "mcbriba01", "mcbriba01", "mcbriba01", "mcbriba01", "mcbriba01", "mcbriba01", "mcbriba01", "mcbriba01", "mcbriba01", "schmimi01", "schmimi01", "schmimi01", "schmimi01", "schmimi01", "schmimi01", "schmimi01", "schmimi01", "schmimi01", "schmimi01", "schmimi01", "schmimi01", "schmimi01", "schmimi01", "schmimi01", "schmimi01", "schmimi01", "schmimi01", "gulledo01", "gulledo01", "gulledo01", "gulledo01", "gulledo01", "gulledo01", "gulledo01", "gulledo01", "gulledo01", "ziskri01", "ziskri01", "ziskri01", 
+#> "ziskri01", "ziskri01", "ziskri01", "ziskri01", "ziskri01", "ziskri01", "ziskri01", "ziskri01", "ziskri01", "ziskri01", "forstte01", "forstte01", "forstte01", "forstte01", "forstte01", "forstte01", "forstte01", "forstte01", "forstte01", "forstte01", "forstte01", "forstte01", "forstte01", "forstte01", "forstte01", "forstte01", "fingero01", "fingero01", "fingero01", "fingero01", "fingero01", "fingero01", "fingero01", "fingero01", "fingero01", "fingero01", "fingero01", "fingero01", "fingero01", "fingero01", 
+#> "fingero01", "fingero01", "fingero01", "madlobi01", "madlobi01", "madlobi01", "madlobi01", "madlobi01", "madlobi01", "madlobi01", "madlobi01", "madlobi01", "madlobi01", "madlobi01", "madlobi01", "madlobi01", "madlobi01", "madlobi01", "madlobi01", "madlobi01", "madlobi01", "tiantlu01", "tiantlu01", "tiantlu01", "tiantlu01", "tiantlu01", "tiantlu01", "tiantlu01", "tiantlu01", "tiantlu01", "tiantlu01", "tiantlu01", "tiantlu01", "tiantlu01", "tiantlu01", "tiantlu01", "tiantlu01", "tiantlu01", "tiantlu01", 
+#> "tiantlu01", "lynnfr01", "lynnfr01", "lynnfr01", "lynnfr01", "lynnfr01", "lynnfr01", "lynnfr01", "lynnfr01", "lynnfr01", "lynnfr01", "lynnfr01", "lynnfr01", "lynnfr01", "lynnfr01", "lynnfr01", "lynnfr01", "lynnfr01", "lynnfr01", "reitzke01", "reitzke01", "reitzke01", "reitzke01", "reitzke01", "reitzke01", "reitzke01", "reitzke01", "reitzke01", "reitzke01", "reitzke01", "maddoga01", "maddoga01", "maddoga01", "maddoga01", "maddoga01", "maddoga01", "maddoga01", "maddoga01", "maddoga01", "maddoga01", 
+#> "maddoga01", "maddoga01", "maddoga01", "maddoga01", "maddoga01", "maddoga01", "nolanga01", "nolanga01", "nolanga01", "nolanga01", "nolanga01", "nolanga01", "nolanga01", "nolanga01", "nolanga01", "nolanga01", "nolanga01", "montejo01", "montejo01", "montejo01", "montejo01", "montejo01", "montejo01", "montejo01", "montejo01", "montejo01", "montejo01", "montejo01", "montejo01", "montejo01", "montejo01", "nettlgr01", "nettlgr01", "nettlgr01", "nettlgr01", "nettlgr01", "nettlgr01", "nettlgr01", "nettlgr01", 
+#> "nettlgr01", "nettlgr01", "nettlgr01", "nettlgr01", "nettlgr01", "nettlgr01", "nettlgr01", "nettlgr01", "nettlgr01", "nettlgr01", "nettlgr01", "nettlgr01", "nettlgr01", "nettlgr01", "riceji01", "riceji01", "riceji01", "riceji01", "riceji01", "riceji01", "riceji01", "riceji01", "riceji01", "riceji01", "riceji01", "riceji01", "riceji01", "riceji01", "riceji01", "riceji01", "harrato01", "harrato01", "harrato01", "harrato01", "harrato01", "harrato01", "harrato01", "harrato01", "harrato01", "harrato01", 
+#> "harrato01", "harrato01", "harrato01", "harrato01", "harrato01", "harrato01", "harrato01", "jonesra01", "jonesra01", "jonesra01", "jonesra01", "jonesra01", "jonesra01", "jonesra01", "jonesra01", "jonesra01", "jonesra01", "luzingr01", "luzingr01", "luzingr01", "luzingr01", "luzingr01", "luzingr01", "luzingr01", "luzingr01", "luzingr01", "luzingr01", "luzingr01", "luzingr01", "luzingr01", "luzingr01", "luzingr01", "oliveal01", "oliveal01", "oliveal01", "oliveal01", "oliveal01", "oliveal01", "oliveal01", 
+#> "oliveal01", "oliveal01", "oliveal01", "oliveal01", "oliveal01", "oliveal01", "oliveal01", "oliveal01", "oliveal01", "oliveal01", "oliveal01", "oliveal01", "oliveal01", "parkeda01", "parkeda01", "parkeda01", "parkeda01", "parkeda01", "parkeda01", "parkeda01", "parkeda01", "parkeda01", "parkeda01", "parkeda01", "parkeda01", "parkeda01", "parkeda01", "parkeda01", "parkeda01", "parkeda01", "parkeda01", "parkeda01", "parkeda01", "gossari01", "gossari01", "gossari01", "gossari01", "gossari01", "gossari01", 
+#> "gossari01", "gossari01", "gossari01", "gossari01", "gossari01", "gossari01", "gossari01", "gossari01", "gossari01", "gossari01", "gossari01", "gossari01", "gossari01", "gossari01", "gossari01", "gossari01", "gossari01", "hraboal01", "hraboal01", "hraboal01", "hraboal01", "hraboal01", "hraboal01", "hraboal01", "hraboal01", "hraboal01", "hraboal01", "hraboal01", "hraboal01", "hraboal01", "fostege01", "fostege01", "fostege01", "fostege01", "fostege01", "fostege01", "fostege01", "fostege01", "fostege01", 
+#> "fostege01", "fostege01", "fostege01", "fostege01", "fostege01", "fostege01", "fostege01", "fostege01", "fostege01", "fostege01", "fostege01", "rodriau01", "rodriau01", "rodriau01", "rodriau01", "rodriau01", "rodriau01", "rodriau01", "rodriau01", "rodriau01", "rodriau01", "rodriau01", "rodriau01", "rodriau01", "rodriau01", "rodriau01", "rodriau01", "rodriau01", "rodriau01", "rodriau01", "rodriau01", "sundbji01", "sundbji01", "sundbji01", "sundbji01", "sundbji01", "sundbji01", "sundbji01", "sundbji01", 
+#> "sundbji01", "sundbji01", "sundbji01", "sundbji01", "sundbji01", "sundbji01", "sundbji01", "sundbji01", "sundbji01", "evansdw01", "evansdw01", "evansdw01", "evansdw01", "evansdw01", "evansdw01", "evansdw01", "evansdw01", "evansdw01", "evansdw01", "evansdw01", "evansdw01", "evansdw01", "evansdw01", "evansdw01", "evansdw01", "evansdw01", "evansdw01", "evansdw01", "evansdw01", "manniri01", "manniri01", "manniri01", "manniri01", "manniri01", "manniri01", "manniri01", "manniri01", "manniri01", "manniri01", 
+#> "manniri01", "manniri01", "manniri01", "manniri01", "johnto01", "johnto01", "johnto01", "johnto01", "johnto01", "johnto01", "johnto01", "johnto01", "johnto01", "johnto01", "johnto01", "johnto01", "johnto01", "johnto01", "johnto01", "johnto01", "johnto01", "johnto01", "johnto01", "johnto01", "johnto01", "johnto01", "johnto01", "johnto01", "johnto01", "johnto01", "johnto01", "johnto01", "suttodo01", "suttodo01", "suttodo01", "suttodo01", "suttodo01", "suttodo01", "suttodo01", "suttodo01", "suttodo01", 
+#> "suttodo01", "suttodo01", "suttodo01", "suttodo01", "suttodo01", "suttodo01", "suttodo01", "suttodo01", "suttodo01", "suttodo01", "suttodo01", "suttodo01", "suttodo01", "suttodo01", "suttodo01", "suttodo01", "campbbi02", "campbbi02", "campbbi02", "campbbi02", "campbbi02", "campbbi02", "campbbi02", "campbbi02", "campbbi02", "campbbi02", "campbbi02", "campbbi02", "campbbi02", "campbbi02", "campbbi02", "eastwra01", "eastwra01", "eastwra01", "eastwra01", "eastwra01", "eastwra01", "eastwra01", "eastwra01", 
+#> "eastwra01", "eastwra01", "fidryma01", "fidryma01", "fidryma01", "fidryma01", "fidryma01", "metzgbu01", "metzgbu01", "metzgbu01", "metzgbu01", "metzgbu01", "metzgbu01", "zachrpa01", "zachrpa01", "zachrpa01", "zachrpa01", "zachrpa01", "zachrpa01", "zachrpa01", "zachrpa01", "zachrpa01", "zachrpa01", "zachrpa01", "brettge01", "brettge01", "brettge01", "brettge01", "brettge01", "brettge01", "brettge01", "brettge01", "brettge01", "brettge01", "brettge01", "brettge01", "brettge01", "brettge01", "brettge01", 
+#> "brettge01", "brettge01", "brettge01", "brettge01", "brettge01", "brettge01", "mcraeha01", "mcraeha01", "mcraeha01", "mcraeha01", "mcraeha01", "mcraeha01", "mcraeha01", "mcraeha01", "mcraeha01", "mcraeha01", "mcraeha01", "mcraeha01", "mcraeha01", "mcraeha01", "mcraeha01", "mcraeha01", "mcraeha01", "mcraeha01", "mcraeha01", "tananfr01", "tananfr01", "tananfr01", "tananfr01", "tananfr01", "tananfr01", "tananfr01", "tananfr01", "tananfr01", "tananfr01", "tananfr01", "tananfr01", "tananfr01", "tananfr01", 
+#> "tananfr01", "tananfr01", "tananfr01", "tananfr01", "tananfr01", "tananfr01", "tananfr01", "tananfr01", "tananfr01", "rivermi01", "rivermi01", "rivermi01", "rivermi01", "rivermi01", "rivermi01", "rivermi01", "rivermi01", "rivermi01", "rivermi01", "rivermi01", "rivermi01", "rivermi01", "rivermi01", "rivermi01", "rivermi01", "montawi01", "montawi01", "montawi01", "montawi01", "montawi01", "montawi01", "montawi01", "montawi01", "montawi01", "montawi01", "montawi01", "montawi01", "montawi01", "montawi01", 
+#> "montawi01", "montawi01", "montawi01", "montawi01", "montawi01", "montawi01", "boonebo01", "boonebo01", "boonebo01", "boonebo01", "boonebo01", "boonebo01", "boonebo01", "boonebo01", "boonebo01", "boonebo01", "boonebo01", "boonebo01", "boonebo01", "boonebo01", "boonebo01", "boonebo01", "boonebo01", "boonebo01", "boonebo01", "griffke01", "griffke01", "griffke01", "griffke01", "griffke01", "griffke01", "griffke01", "griffke01", "griffke01", "griffke01", "griffke01", "griffke01", "griffke01", "griffke01", 
+#> "griffke01", "griffke01", "griffke01", "griffke01", "griffke01", "griffke01", "griffke01", "griffke01", "whitefr01", "whitefr01", "whitefr01", "whitefr01", "whitefr01", "whitefr01", "whitefr01", "whitefr01", "whitefr01", "whitefr01", "whitefr01", "whitefr01", "whitefr01", "whitefr01", "whitefr01", "whitefr01", "whitefr01", "whitefr01", "beniqju01", "beniqju01", "beniqju01", "beniqju01", "beniqju01", "beniqju01", "beniqju01", "beniqju01", "beniqju01", "beniqju01", "beniqju01", "beniqju01", "beniqju01", 
+#> "beniqju01", "beniqju01", "beniqju01", "beniqju01", "beniqju01", "cowenal01", "cowenal01", "cowenal01", "cowenal01", "cowenal01", "cowenal01", "cowenal01", "cowenal01", "cowenal01", "cowenal01", "cowenal01", "cowenal01", "cowenal01", "cowenal01", "bakerdu01", "bakerdu01", "bakerdu01", "bakerdu01", "bakerdu01", "bakerdu01", "bakerdu01", "bakerdu01", "bakerdu01", "bakerdu01", "bakerdu01", "bakerdu01", "bakerdu01", "bakerdu01", "bakerdu01", "bakerdu01", "bakerdu01", "bakerdu01", "bakerdu01", "murraed02", 
+#> "murraed02", "murraed02", "murraed02", "murraed02", "murraed02", "murraed02", "murraed02", "murraed02", "murraed02", "murraed02", "murraed02", "murraed02", "murraed02", "murraed02", "murraed02", "murraed02", "murraed02", "murraed02", "murraed02", "murraed02", "murraed02", "murraed02", "dawsoan01", "dawsoan01", "dawsoan01", "dawsoan01", "dawsoan01", "dawsoan01", "dawsoan01", "dawsoan01", "dawsoan01", "dawsoan01", "dawsoan01", "dawsoan01", "dawsoan01", "dawsoan01", "dawsoan01", "dawsoan01", "dawsoan01", 
+#> "dawsoan01", "dawsoan01", "dawsoan01", "dawsoan01", "randowi01", "randowi01", "randowi01", "randowi01", "randowi01", "randowi01", "randowi01", "randowi01", "randowi01", "randowi01", "randowi01", "randowi01", "randowi01", "randowi01", "randowi01", "randowi01", "randowi01", "randowi01", "randowi01", "hislela01", "hislela01", "hislela01", "hislela01", "hislela01", "hislela01", "hislela01", "hislela01", "hislela01", "hislela01", "hislela01", "hislela01", "hislela01", "hislela01", "ryanno01", "ryanno01", 
+#> "ryanno01", "ryanno01", "ryanno01", "ryanno01", "ryanno01", "ryanno01", "ryanno01", "ryanno01", "ryanno01", "ryanno01", "ryanno01", "ryanno01", "ryanno01", "ryanno01", "ryanno01", "ryanno01", "ryanno01", "ryanno01", "ryanno01", "ryanno01", "ryanno01", "ryanno01", "ryanno01", "ryanno01", "ryanno01", "burleri01", "burleri01", "burleri01", "burleri01", "burleri01", "burleri01", "burleri01", "burleri01", "burleri01", "burleri01", "burleri01", "burleri01", "burleri01", "simmote01", "simmote01", "simmote01", 
+#> "simmote01", "simmote01", "simmote01", "simmote01", "simmote01", "simmote01", "simmote01", "simmote01", "simmote01", "simmote01", "simmote01", "simmote01", "simmote01", "simmote01", "simmote01", "simmote01", "simmote01", "simmote01", "reuscri01", "reuscri01", "reuscri01", "reuscri01", "reuscri01", "reuscri01", "reuscri01", "reuscri01", "reuscri01", "reuscri01", "reuscri01", "reuscri01", "reuscri01", "reuscri01", "reuscri01", "reuscri01", "reuscri01", "reuscri01", "reuscri01", "reuscri01", "reuscri01", 
+#> "templga01", "templga01", "templga01", "templga01", "templga01", "templga01", "templga01", "templga01", "templga01", "templga01", "templga01", "templga01", "templga01", "templga01", "templga01", "templga01", "templga01", "dentbu01", "dentbu01", "dentbu01", "dentbu01", "dentbu01", "dentbu01", "dentbu01", "dentbu01", "dentbu01", "dentbu01", "dentbu01", "dentbu01", "dentbu01", "guidrro01", "guidrro01", "guidrro01", "guidrro01", "guidrro01", "guidrro01", "guidrro01", "guidrro01", "guidrro01", "guidrro01", 
+#> "guidrro01", "guidrro01", "guidrro01", "guidrro01", "milleri01", "milleri01", "milleri01", "milleri01", "milleri01", "milleri01", "milleri01", "milleri01", "milleri01", "milleri01", "milleri01", "milleri01", "milleri01", "milleri01", "milleri01", "hernake01", "hernake01", "hernake01", "hernake01", "hernake01", "hernake01", "hernake01", "hernake01", "hernake01", "hernake01", "hernake01", "hernake01", "hernake01", "hernake01", "hernake01", "hernake01", "hernake01", "hernake01", "lopesda01", "lopesda01", 
+#> "lopesda01", "lopesda01", "lopesda01", "lopesda01", "lopesda01", "lopesda01", "lopesda01", "lopesda01", "lopesda01", "lopesda01", "lopesda01", "lopesda01", "lopesda01", "lopesda01", "lopesda01", "lopesda01", "valenel01", "valenel01", "valenel01", "valenel01", "valenel01", "valenel01", "valenel01", "valenel01", "valenel01", "valenel01", "valenel01", "niekrph01", "niekrph01", "niekrph01", "niekrph01", "niekrph01", "niekrph01", "niekrph01", "niekrph01", "niekrph01", "niekrph01", "niekrph01", "niekrph01", 
+#> "niekrph01", "niekrph01", "niekrph01", "niekrph01", "niekrph01", "niekrph01", "niekrph01", "niekrph01", "niekrph01", "niekrph01", "niekrph01", "niekrph01", "niekrph01", "niekrph01", "whitalo01", "whitalo01", "whitalo01", "whitalo01", "whitalo01", "whitalo01", "whitalo01", "whitalo01", "whitalo01", "whitalo01", "whitalo01", "whitalo01", "whitalo01", "whitalo01", "whitalo01", "whitalo01", "whitalo01", "whitalo01", "whitalo01", "hornebo01", "hornebo01", "hornebo01", "hornebo01", "hornebo01", "hornebo01", 
+#> "hornebo01", "hornebo01", "hornebo01", "hornebo01", "staubru01", "staubru01", "staubru01", "staubru01", "staubru01", "staubru01", "staubru01", "staubru01", "staubru01", "staubru01", "staubru01", "staubru01", "staubru01", "staubru01", "staubru01", "staubru01", "staubru01", "staubru01", "staubru01", "staubru01", "staubru01", "staubru01", "staubru01", "staubru01", "yountro01", "yountro01", "yountro01", "yountro01", "yountro01", "yountro01", "yountro01", "yountro01", "yountro01", "yountro01", "yountro01", 
+#> "yountro01", "yountro01", "yountro01", "yountro01", "yountro01", "yountro01", "yountro01", "yountro01", "yountro01", "clarkja01", "clarkja01", "clarkja01", "clarkja01", "clarkja01", "clarkja01", "clarkja01", "clarkja01", "clarkja01", "clarkja01", "clarkja01", "clarkja01", "clarkja01", "clarkja01", "clarkja01", "clarkja01", "clarkja01", "clarkja01", "flanami01", "flanami01", "flanami01", "flanami01", "flanami01", "flanami01", "flanami01", "flanami01", "flanami01", "flanami01", "flanami01", "flanami01", 
+#> "flanami01", "flanami01", "flanami01", "flanami01", "flanami01", "flanami01", "flanami01", "suttebr01", "suttebr01", "suttebr01", "suttebr01", "suttebr01", "suttebr01", "suttebr01", "suttebr01", "suttebr01", "suttebr01", "suttebr01", "suttebr01", "coopece01", "coopece01", "coopece01", "coopece01", "coopece01", "coopece01", "coopece01", "coopece01", "coopece01", "coopece01", "coopece01", "coopece01", "coopece01", "coopece01", "coopece01", "coopece01", "coopece01", "bellbu01", "bellbu01", "bellbu01", 
+#> "bellbu01", "bellbu01", "bellbu01", "bellbu01", "bellbu01", "bellbu01", "bellbu01", "bellbu01", "bellbu01", "bellbu01", "bellbu01", "bellbu01", "bellbu01", "bellbu01", "bellbu01", "bellbu01", "bellbu01", "lezcasi01", "lezcasi01", "lezcasi01", "lezcasi01", "lezcasi01", "lezcasi01", "lezcasi01", "lezcasi01", "lezcasi01", "lezcasi01", "lezcasi01", "lezcasi01", "lezcasi01", "trillma01", "trillma01", "trillma01", "trillma01", "trillma01", "trillma01", "trillma01", "trillma01", "trillma01", "trillma01", 
+#> "trillma01", "trillma01", "trillma01", "trillma01", "trillma01", "trillma01", "trillma01", "trillma01", "winfida01", "winfida01", "winfida01", "winfida01", "winfida01", "winfida01", "winfida01", "winfida01", "winfida01", "winfida01", "winfida01", "winfida01", "winfida01", "winfida01", "winfida01", "winfida01", "winfida01", "winfida01", "winfida01", "winfida01", "winfida01", "winfida01", "winfida01", "baylodo01", "baylodo01", "baylodo01", "baylodo01", "baylodo01", "baylodo01", "baylodo01", "baylodo01", 
+#> "baylodo01", "baylodo01", "baylodo01", "baylodo01", "baylodo01", "baylodo01", "baylodo01", "baylodo01", "baylodo01", "baylodo01", "baylodo01", "baylodo01", "thornan01", "thornan01", "thornan01", "thornan01", "thornan01", "thornan01", "thornan01", "thornan01", "thornan01", "thornan01", "thornan01", "thornan01", "thornan01", "thornan01", "thornan01", "kernji01", "kernji01", "kernji01", "kernji01", "kernji01", "kernji01", "kernji01", "kernji01", "kernji01", "kernji01", "kernji01", "kernji01", "kernji01", 
+#> "kernji01", "kernji01", "castijo01", "castijo01", "castijo01", "castijo01", "castijo01", "castijo01", "griffal01", "griffal01", "griffal01", "griffal01", "griffal01", "griffal01", "griffal01", "griffal01", "griffal01", "griffal01", "griffal01", "griffal01", "griffal01", "griffal01", "griffal01", "griffal01", "griffal01", "griffal01", "sutclri01", "sutclri01", "sutclri01", "sutclri01", "sutclri01", "sutclri01", "sutclri01", "sutclri01", "sutclri01", "sutclri01", "sutclri01", "sutclri01", "sutclri01", 
+#> "sutclri01", "sutclri01", "sutclri01", "sutclri01", "sutclri01", "sutclri01", "porteda02", "porteda02", "porteda02", "porteda02", "porteda02", "porteda02", "porteda02", "porteda02", "porteda02", "porteda02", "porteda02", "porteda02", "porteda02", "porteda02", "porteda02", "porteda02", "porteda02", "singlke01", "singlke01", "singlke01", "singlke01", "singlke01", "singlke01", "singlke01", "singlke01", "singlke01", "singlke01", "singlke01", "singlke01", "singlke01", "singlke01", "singlke01", "smallro02", 
+#> "smallro02", "smallro02", "smallro02", "smallro02", "smallro02", "smallro02", "smallro02", "smallro02", "smallro02", "smallro02", "smallro02", "smallro02", "smallro02", "smallro02", "smallro02", "kingmda01", "kingmda01", "kingmda01", "kingmda01", "kingmda01", "kingmda01", "kingmda01", "kingmda01", "kingmda01", "kingmda01", "kingmda01", "kingmda01", "kingmda01", "kingmda01", "kingmda01", "kingmda01", "kingmda01", "kingmda01", "kingmda01", "morenom01", "morenom01", "morenom01", "morenom01", "morenom01", 
+#> "morenom01", "morenom01", "morenom01", "morenom01", "morenom01", "morenom01", "morenom01", "morenom01", "morenom01", "niekrjo01", "niekrjo01", "niekrjo01", "niekrjo01", "niekrjo01", "niekrjo01", "niekrjo01", "niekrjo01", "niekrjo01", "niekrjo01", "niekrjo01", "niekrjo01", "niekrjo01", "niekrjo01", "niekrjo01", "niekrjo01", "niekrjo01", "niekrjo01", "niekrjo01", "niekrjo01", "niekrjo01", "niekrjo01", "niekrjo01", "niekrjo01", "niekrjo01", "mcgratu01", "mcgratu01", "mcgratu01", "mcgratu01", "mcgratu01", 
+#> "mcgratu01", "mcgratu01", "mcgratu01", "mcgratu01", "mcgratu01", "mcgratu01", "mcgratu01", "mcgratu01", "mcgratu01", "mcgratu01", "mcgratu01", "mcgratu01", "mcgratu01", "mcgratu01", "stonest01", "stonest01", "stonest01", "stonest01", "stonest01", "stonest01", "stonest01", "stonest01", "stonest01", "stonest01", "stonest01", "murphdw01", "murphdw01", "murphdw01", "murphdw01", "murphdw01", "murphdw01", "murphdw01", "murphdw01", "murphdw01", "murphdw01", "murphdw01", "murphdw01", "wilsowi02", "wilsowi02", 
+#> "wilsowi02", "wilsowi02", "wilsowi02", "wilsowi02", "wilsowi02", "wilsowi02", "wilsowi02", "wilsowi02", "wilsowi02", "wilsowi02", "wilsowi02", "wilsowi02", "wilsowi02", "wilsowi02", "wilsowi02", "wilsowi02", "wilsowi02", "norrimi01", "norrimi01", "norrimi01", "norrimi01", "norrimi01", "norrimi01", "norrimi01", "norrimi01", "norrimi01", "norrimi01", "trammal01", "trammal01", "trammal01", "trammal01", "trammal01", "trammal01", "trammal01", "trammal01", "trammal01", "trammal01", "trammal01", "trammal01", 
+#> "trammal01", "trammal01", "trammal01", "trammal01", "trammal01", "trammal01", "trammal01", "trammal01", "flynndo01", "flynndo01", "flynndo01", "flynndo01", "flynndo01", "flynndo01", "flynndo01", "flynndo01", "flynndo01", "flynndo01", "flynndo01", "flynndo01", "flynndo01", "flynndo01", "cartega01", "cartega01", "cartega01", "cartega01", "cartega01", "cartega01", "cartega01", "cartega01", "cartega01", "cartega01", "cartega01", "cartega01", "cartega01", "cartega01", "cartega01", "cartega01", "cartega01", 
+#> "cartega01", "cartega01", "smithoz01", "smithoz01", "smithoz01", "smithoz01", "smithoz01", "smithoz01", "smithoz01", "smithoz01", "smithoz01", "smithoz01", "smithoz01", "smithoz01", "smithoz01", "smithoz01", "smithoz01", "smithoz01", "smithoz01", "smithoz01", "smithoz01", "quiseda01", "quiseda01", "quiseda01", "quiseda01", "quiseda01", "quiseda01", "quiseda01", "quiseda01", "quiseda01", "quiseda01", "quiseda01", "quiseda01", "quiseda01", "charbjo01", "charbjo01", "charbjo01", "howest01", "howest01", 
+#> "howest01", "howest01", "howest01", "howest01", "howest01", "howest01", "howest01", "howest01", "howest01", "howest01", "howest01", "parrila02", "parrila02", "parrila02", "parrila02", "parrila02", "parrila02", "parrila02", "parrila02", "parrila02", "parrila02", "parrila02", "parrila02", "parrila02", "parrila02", "parrila02", "parrila02", "parrila02", "parrila02", "parrila02", "parrila02", "oglivbe01", "oglivbe01", "oglivbe01", "oglivbe01", "oglivbe01", "oglivbe01", "oglivbe01", "oglivbe01", "oglivbe01", 
+#> "oglivbe01", "oglivbe01", "oglivbe01", "oglivbe01", "oglivbe01", "oglivbe01", "oglivbe01", "hendrge01", "hendrge01", "hendrge01", "hendrge01", "hendrge01", "hendrge01", "hendrge01", "hendrge01", "hendrge01", "hendrge01", "hendrge01", "hendrge01", "hendrge01", "hendrge01", "hendrge01", "hendrge01", "hendrge01", "hendrge01", "hendrge01", "hendrge01", "forscbo01", "forscbo01", "forscbo01", "forscbo01", "forscbo01", "forscbo01", "forscbo01", "forscbo01", "forscbo01", "forscbo01", "forscbo01", "forscbo01", 
+#> "forscbo01", "forscbo01", "forscbo01", "forscbo01", "forscbo01", "ceronri01", "ceronri01", "ceronri01", "ceronri01", "ceronri01", "ceronri01", "ceronri01", "ceronri01", "ceronri01", "ceronri01", "ceronri01", "ceronri01", "ceronri01", "ceronri01", "ceronri01", "ceronri01", "ceronri01", "ceronri01", "bibbyji01", "bibbyji01", "bibbyji01", "bibbyji01", "bibbyji01", "bibbyji01", "bibbyji01", "bibbyji01", "bibbyji01", "bibbyji01", "bibbyji01", "bibbyji01", "bibbyji01", "bibbyji01", "humeto01", "humeto01", 
+#> "humeto01", "humeto01", "humeto01", "humeto01", "humeto01", "humeto01", "humeto01", "humeto01", "humeto01", "humeto01", "ceyro01", "ceyro01", "ceyro01", "ceyro01", "ceyro01", "ceyro01", "ceyro01", "ceyro01", "ceyro01", "ceyro01", "ceyro01", "ceyro01", "ceyro01", "ceyro01", "ceyro01", "ceyro01", "ceyro01", "valenfe01", "valenfe01", "valenfe01", "valenfe01", "valenfe01", "valenfe01", "valenfe01", "valenfe01", "valenfe01", "valenfe01", "valenfe01", "valenfe01", "valenfe01", "valenfe01", "valenfe01", 
+#> "valenfe01", "valenfe01", "valenfe01", "squirmi01", "squirmi01", "squirmi01", "squirmi01", "squirmi01", "squirmi01", "squirmi01", "squirmi01", "squirmi01", "squirmi01", "henderi01", "henderi01", "henderi01", "henderi01", "henderi01", "henderi01", "henderi01", "henderi01", "henderi01", "henderi01", "henderi01", "henderi01", "henderi01", "henderi01", "henderi01", "henderi01", "henderi01", "henderi01", "henderi01", "henderi01", "henderi01", "henderi01", "henderi01", "henderi01", "henderi01", "henderi01", 
+#> "henderi01", "henderi01", "henderi01", "hootobu01", "hootobu01", "hootobu01", "hootobu01", "hootobu01", "hootobu01", "hootobu01", "hootobu01", "hootobu01", "hootobu01", "hootobu01", "hootobu01", "hootobu01", "hootobu01", "hootobu01", "hootobu01", "righeda01", "righeda01", "righeda01", "righeda01", "righeda01", "righeda01", "righeda01", "righeda01", "righeda01", "righeda01", "righeda01", "righeda01", "righeda01", "righeda01", "righeda01", "righeda01", "righeda01", "lansfca01", "lansfca01", "lansfca01", 
+#> "lansfca01", "lansfca01", "lansfca01", "lansfca01", "lansfca01", "lansfca01", "lansfca01", "lansfca01", "lansfca01", "lansfca01", "lansfca01", "lansfca01", "armasto01", "armasto01", "armasto01", "armasto01", "armasto01", "armasto01", "armasto01", "armasto01", "armasto01", "armasto01", "armasto01", "armasto01", "armasto01", "armasto01", "morrija02", "morrija02", "morrija02", "morrija02", "morrija02", "morrija02", "morrija02", "morrija02", "morrija02", "morrija02", "morrija02", "morrija02", "morrija02", 
+#> "morrija02", "morrija02", "morrija02", "morrija02", "morrija02", "guerrpe01", "guerrpe01", "guerrpe01", "guerrpe01", "guerrpe01", "guerrpe01", "guerrpe01", "guerrpe01", "guerrpe01", "guerrpe01", "guerrpe01", "guerrpe01", "guerrpe01", "guerrpe01", "guerrpe01", "guerrpe01", "yeagest01", "yeagest01", "yeagest01", "yeagest01", "yeagest01", "yeagest01", "yeagest01", "yeagest01", "yeagest01", "yeagest01", "yeagest01", "yeagest01", "yeagest01", "yeagest01", "yeagest01", "vuckope01", "vuckope01", "vuckope01", 
+#> "vuckope01", "vuckope01", "vuckope01", "vuckope01", "vuckope01", "vuckope01", "vuckope01", "vuckope01", "murphda05", "murphda05", "murphda05", "murphda05", "murphda05", "murphda05", "murphda05", "murphda05", "murphda05", "murphda05", "murphda05", "murphda05", "murphda05", "murphda05", "murphda05", "murphda05", "murphda05", "murphda05", "murphda05", "ripkeca01", "ripkeca01", "ripkeca01", "ripkeca01", "ripkeca01", "ripkeca01", "ripkeca01", "ripkeca01", "ripkeca01", "ripkeca01", "ripkeca01", "ripkeca01", 
+#> "ripkeca01", "ripkeca01", "ripkeca01", "ripkeca01", "ripkeca01", "ripkeca01", "ripkeca01", "ripkeca01", "ripkeca01", "saxst01", "saxst01", "saxst01", "saxst01", "saxst01", "saxst01", "saxst01", "saxst01", "saxst01", "saxst01", "saxst01", "saxst01", "saxst01", "saxst01", "garcida01", "garcida01", "garcida01", "garcida01", "garcida01", "garcida01", "garcida01", "garcida01", "garcida01", "garcida01", "garcida01", "decindo01", "decindo01", "decindo01", "decindo01", "decindo01", "decindo01", "decindo01", 
+#> "decindo01", "decindo01", "decindo01", "decindo01", "decindo01", "decindo01", "decindo01", "decindo01", "decindo01", "durhale01", "durhale01", "durhale01", "durhale01", "durhale01", "durhale01", "durhale01", "durhale01", "durhale01", "durhale01", "durhale01", "robindo01", "robindo01", "robindo01", "robindo01", "robindo01", "robindo01", "robindo01", "robindo01", "robindo01", "robindo01", "robindo01", "robindo01", "robindo01", "robindo01", "robindo01", "robindo01", "robindo01", "zahnge01", "zahnge01", 
+#> "zahnge01", "zahnge01", "zahnge01", "zahnge01", "zahnge01", "zahnge01", "zahnge01", "zahnge01", "zahnge01", "zahnge01", "zahnge01", "zahnge01", "thomago01", "thomago01", "thomago01", "thomago01", "thomago01", "thomago01", "thomago01", "thomago01", "thomago01", "thomago01", "thomago01", "thomago01", "thomago01", "thomago01", "thomago01", "stiebda01", "stiebda01", "stiebda01", "stiebda01", "stiebda01", "stiebda01", "stiebda01", "stiebda01", "stiebda01", "stiebda01", "stiebda01", "stiebda01", "stiebda01", 
+#> "stiebda01", "stiebda01", "stiebda01", "smithlo01", "smithlo01", "smithlo01", "smithlo01", "smithlo01", "smithlo01", "smithlo01", "smithlo01", "smithlo01", "smithlo01", "smithlo01", "smithlo01", "smithlo01", "smithlo01", "smithlo01", "smithlo01", "smithlo01", "smithlo01", "smithlo01", "rogerst01", "rogerst01", "rogerst01", "rogerst01", "rogerst01", "rogerst01", "rogerst01", "rogerst01", "rogerst01", "rogerst01", "rogerst01", "rogerst01", "rogerst01", "boddimi01", "boddimi01", "boddimi01", "boddimi01", 
+#> "boddimi01", "boddimi01", "boddimi01", "boddimi01", "boddimi01", "boddimi01", "boddimi01", "boddimi01", "boddimi01", "boddimi01", "boddimi01", "dempsri01", "dempsri01", "dempsri01", "dempsri01", "dempsri01", "dempsri01", "dempsri01", "dempsri01", "dempsri01", "dempsri01", "dempsri01", "dempsri01", "dempsri01", "dempsri01", "dempsri01", "dempsri01", "dempsri01", "dempsri01", "dempsri01", "dempsri01", "dempsri01", "dempsri01", "dempsri01", "dempsri01", "dempsri01", "hoytla01", "hoytla01", "hoytla01", 
+#> "hoytla01", "hoytla01", "hoytla01", "hoytla01", "hoytla01", "dennyjo01", "dennyjo01", "dennyjo01", "dennyjo01", "dennyjo01", "dennyjo01", "dennyjo01", "dennyjo01", "dennyjo01", "dennyjo01", "dennyjo01", "dennyjo01", "dennyjo01", "dennyjo01", "sandbry01", "sandbry01", "sandbry01", "sandbry01", "sandbry01", "sandbry01", "sandbry01", "sandbry01", "sandbry01", "sandbry01", "sandbry01", "sandbry01", "sandbry01", "sandbry01", "sandbry01", "sandbry01", "penato01", "penato01", "penato01", "penato01", "penato01", 
+#> "penato01", "penato01", "penato01", "penato01", "penato01", "penato01", "penato01", "penato01", "penato01", "penato01", "penato01", "penato01", "penato01", "penato01", "mcgeewi01", "mcgeewi01", "mcgeewi01", "mcgeewi01", "mcgeewi01", "mcgeewi01", "mcgeewi01", "mcgeewi01", "mcgeewi01", "mcgeewi01", "mcgeewi01", "mcgeewi01", "mcgeewi01", "mcgeewi01", "mcgeewi01", "mcgeewi01", "mcgeewi01", "mcgeewi01", "mcgeewi01", "knighra01", "knighra01", "knighra01", "knighra01", "knighra01", "knighra01", "knighra01", 
+#> "knighra01", "knighra01", "knighra01", "knighra01", "knighra01", "knighra01", "knighra01", "hollaal01", "hollaal01", "hollaal01", "hollaal01", "hollaal01", "hollaal01", "hollaal01", "hollaal01", "hollaal01", "hollaal01", "hollaal01", "hollaal01", "kittlro01", "kittlro01", "kittlro01", "kittlro01", "kittlro01", "kittlro01", "kittlro01", "kittlro01", "kittlro01", "kittlro01", "kittlro01", "kittlro01", "strawda01", "strawda01", "strawda01", "strawda01", "strawda01", "strawda01", "strawda01", "strawda01", 
+#> "strawda01", "strawda01", "strawda01", "strawda01", "strawda01", "strawda01", "strawda01", "strawda01", "strawda01", "boggswa01", "boggswa01", "boggswa01", "boggswa01", "boggswa01", "boggswa01", "boggswa01", "boggswa01", "boggswa01", "boggswa01", "boggswa01", "boggswa01", "boggswa01", "boggswa01", "boggswa01", "boggswa01", "boggswa01", "boggswa01", "mosebll01", "mosebll01", "mosebll01", "mosebll01", "mosebll01", "mosebll01", "mosebll01", "mosebll01", "mosebll01", "mosebll01", "mosebll01", "mosebll01", 
+#> "rayjo01", "rayjo01", "rayjo01", "rayjo01", "rayjo01", "rayjo01", "rayjo01", "rayjo01", "rayjo01", "rayjo01", "rayjo01", "kennete02", "kennete02", "kennete02", "kennete02", "kennete02", "kennete02", "kennete02", "kennete02", "kennete02", "kennete02", "kennete02", "kennete02", "kennete02", "kennete02", "cruzjo01", "cruzjo01", "cruzjo01", "cruzjo01", "cruzjo01", "cruzjo01", "cruzjo01", "cruzjo01", "cruzjo01", "cruzjo01", "cruzjo01", "cruzjo01", "cruzjo01", "cruzjo01", "cruzjo01", "cruzjo01", "cruzjo01", 
+#> "cruzjo01", "cruzjo01", "thondi01", "thondi01", "thondi01", "thondi01", "thondi01", "thondi01", "thondi01", "thondi01", "thondi01", "thondi01", "thondi01", "thondi01", "thondi01", "thondi01", "thondi01", "hubbagl01", "hubbagl01", "hubbagl01", "hubbagl01", "hubbagl01", "hubbagl01", "hubbagl01", "hubbagl01", "hubbagl01", "hubbagl01", "hubbagl01", "hubbagl01", "mcwilla01", "mcwilla01", "mcwilla01", "mcwilla01", "mcwilla01", "mcwilla01", "mcwilla01", "mcwilla01", "mcwilla01", "mcwilla01", "mcwilla01", 
+#> "mcwilla01", "mcwilla01", "mcwilla01", "mcwilla01", "raineti01", "raineti01", "raineti01", "raineti01", "raineti01", "raineti01", "raineti01", "raineti01", "raineti01", "raineti01", "raineti01", "raineti01", "raineti01", "raineti01", "raineti01", "raineti01", "raineti01", "raineti01", "raineti01", "raineti01", "raineti01", "raineti01", "raineti01", "raineti01", "smithle02", "smithle02", "smithle02", "smithle02", "smithle02", "smithle02", "smithle02", "smithle02", "smithle02", "smithle02", "smithle02", 
+#> "smithle02", "smithle02", "smithle02", "smithle02", "smithle02", "smithle02", "smithle02", "smithle02", "smithle02", "smithle02", "gibsoki01", "gibsoki01", "gibsoki01", "gibsoki01", "gibsoki01", "gibsoki01", "gibsoki01", "gibsoki01", "gibsoki01", "gibsoki01", "gibsoki01", "gibsoki01", "gibsoki01", "gibsoki01", "gibsoki01", "gibsoki01", "gibsoki01", "hernawi01", "hernawi01", "hernawi01", "hernawi01", "hernawi01", "hernawi01", "hernawi01", "hernawi01", "hernawi01", "hernawi01", "hernawi01", "hernawi01", 
+#> "hernawi01", "hernawi01", "dernibo01", "dernibo01", "dernibo01", "dernibo01", "dernibo01", "dernibo01", "dernibo01", "dernibo01", "dernibo01", "dernibo01", "andujjo01", "andujjo01", "andujjo01", "andujjo01", "andujjo01", "andujjo01", "andujjo01", "andujjo01", "andujjo01", "andujjo01", "andujjo01", "andujjo01", "andujjo01", "andujjo01", "davisal01", "davisal01", "davisal01", "davisal01", "davisal01", "davisal01", "davisal01", "davisal01", "davisal01", "goodedw01", "goodedw01", "goodedw01", "goodedw01", 
+#> "goodedw01", "goodedw01", "goodedw01", "goodedw01", "goodedw01", "goodedw01", "goodedw01", "goodedw01", "goodedw01", "goodedw01", "goodedw01", "goodedw01", "goodedw01", "goodedw01", "gwynnto01", "gwynnto01", "gwynnto01", "gwynnto01", "gwynnto01", "gwynnto01", "gwynnto01", "gwynnto01", "gwynnto01", "gwynnto01", "gwynnto01", "gwynnto01", "gwynnto01", "gwynnto01", "gwynnto01", "gwynnto01", "gwynnto01", "gwynnto01", "gwynnto01", "gwynnto01", "rhoderi01", "rhoderi01", "rhoderi01", "rhoderi01", "rhoderi01", 
+#> "rhoderi01", "rhoderi01", "rhoderi01", "rhoderi01", "rhoderi01", "rhoderi01", "rhoderi01", "rhoderi01", "rhoderi01", "rhoderi01", "rhoderi01", "mattido01", "mattido01", "mattido01", "mattido01", "mattido01", "mattido01", "mattido01", "mattido01", "mattido01", "mattido01", "mattido01", "mattido01", "mattido01", "mattido01", "thurmma01", "thurmma01", "thurmma01", "thurmma01", "thurmma01", "thurmma01", "thurmma01", "thurmma01", "thurmma01", "saberbr01", "saberbr01", "saberbr01", "saberbr01", "saberbr01", 
+#> "saberbr01", "saberbr01", "saberbr01", "saberbr01", "saberbr01", "saberbr01", "saberbr01", "saberbr01", "saberbr01", "saberbr01", "saberbr01", "saberbr01", "pettiga01", "pettiga01", "pettiga01", "pettiga01", "pettiga01", "pettiga01", "pettiga01", "pettiga01", "pettiga01", "pettiga01", "pettiga01", "pettiga01", "wallati01", "wallati01", "wallati01", "wallati01", "wallati01", "wallati01", "wallati01", "wallati01", "wallati01", "wallati01", "wallati01", "wallati01", "wallati01", "wallati01", "wallati01", 
+#> "wallati01", "wallati01", "wallati01", "reardje01", "reardje01", "reardje01", "reardje01", "reardje01", "reardje01", "reardje01", "reardje01", "reardje01", "reardje01", "reardje01", "reardje01", "reardje01", "reardje01", "reardje01", "reardje01", "reardje01", "reardje01", "guilloz01", "guilloz01", "guilloz01", "guilloz01", "guilloz01", "guilloz01", "guilloz01", "guilloz01", "guilloz01", "guilloz01", "guilloz01", "guilloz01", "guilloz01", "guilloz01", "guilloz01", "guilloz01", "guilloz01", "colemvi01", 
+#> "colemvi01", "colemvi01", "colemvi01", "colemvi01", "colemvi01", "colemvi01", "colemvi01", "colemvi01", "colemvi01", "colemvi01", "colemvi01", "colemvi01", "colemvi01", "bellge02", "bellge02", "bellge02", "bellge02", "bellge02", "bellge02", "bellge02", "bellge02", "bellge02", "bellge02", "bellge02", "bellge02", "brookhu01", "brookhu01", "brookhu01", "brookhu01", "brookhu01", "brookhu01", "brookhu01", "brookhu01", "brookhu01", "brookhu01", "brookhu01", "brookhu01", "brookhu01", "brookhu01", "brookhu01", 
+#> "baineha01", "baineha01", "baineha01", "baineha01", "baineha01", "baineha01", "baineha01", "baineha01", "baineha01", "baineha01", "baineha01", "baineha01", "baineha01", "baineha01", "baineha01", "baineha01", "baineha01", "baineha01", "baineha01", "baineha01", "baineha01", "baineha01", "baineha01", "baineha01", "baineha01", "baineha01", "baineha01", "bradlph01", "bradlph01", "bradlph01", "bradlph01", "bradlph01", "bradlph01", "bradlph01", "bradlph01", "bradlph01", "herrto01", "herrto01", "herrto01", 
+#> "herrto01", "herrto01", "herrto01", "herrto01", "herrto01", "herrto01", "herrto01", "herrto01", "herrto01", "herrto01", "herrto01", "herrto01", "herrto01", "tudorjo01", "tudorjo01", "tudorjo01", "tudorjo01", "tudorjo01", "tudorjo01", "tudorjo01", "tudorjo01", "tudorjo01", "tudorjo01", "tudorjo01", "tudorjo01", "tudorjo01", "barrema02", "barrema02", "barrema02", "barrema02", "barrema02", "barrema02", "barrema02", "barrema02", "barrema02", "barrema02", "clemero02", "clemero02", "clemero02", "clemero02", 
+#> "clemero02", "clemero02", "clemero02", "clemero02", "clemero02", "clemero02", "clemero02", "clemero02", "clemero02", "clemero02", "clemero02", "clemero02", "clemero02", "clemero02", "clemero02", "clemero02", "clemero02", "clemero02", "clemero02", "clemero02", "scottmi03", "scottmi03", "scottmi03", "scottmi03", "scottmi03", "scottmi03", "scottmi03", "scottmi03", "scottmi03", "scottmi03", "scottmi03", "scottmi03", "scottmi03", "gaettga01", "gaettga01", "gaettga01", "gaettga01", "gaettga01", "gaettga01", 
+#> "gaettga01", "gaettga01", "gaettga01", "gaettga01", "gaettga01", "gaettga01", "gaettga01", "gaettga01", "gaettga01", "gaettga01", "gaettga01", "gaettga01", "gaettga01", "gaettga01", "gaettga01", "gaettga01", "barfije01", "barfije01", "barfije01", "barfije01", "barfije01", "barfije01", "barfije01", "barfije01", "barfije01", "barfije01", "barfije01", "barfije01", "barfije01", "puckeki01", "puckeki01", "puckeki01", "puckeki01", "puckeki01", "puckeki01", "puckeki01", "puckeki01", "puckeki01", "puckeki01", 
+#> "puckeki01", "puckeki01", "fernato01", "fernato01", "fernato01", "fernato01", "fernato01", "fernato01", "fernato01", "fernato01", "fernato01", "fernato01", "fernato01", "fernato01", "fernato01", "fernato01", "fernato01", "fernato01", "fernato01", "fernato01", "fernato01", "davisjo02", "davisjo02", "davisjo02", "davisjo02", "davisjo02", "davisjo02", "davisjo02", "davisjo02", "davisjo02", "davisjo02", "davisjo02", "leonade01", "leonade01", "leonade01", "leonade01", "leonade01", "leonade01", "leonade01", 
+#> "leonade01", "leonade01", "leonade01", "leonade01", "leonade01", "worreto01", "worreto01", "worreto01", "worreto01", "worreto01", "worreto01", "worreto01", "worreto01", "worreto01", "worreto01", "worreto01", "cansejo01", "cansejo01", "cansejo01", "cansejo01", "cansejo01", "cansejo01", "cansejo01", "cansejo01", "cansejo01", "cansejo01", "cansejo01", "cansejo01", "cansejo01", "cansejo01", "cansejo01", "cansejo01", "cansejo01", "cansejo01", "cansejo01", "davisgl01", "davisgl01", "davisgl01", "davisgl01", 
+#> "davisgl01", "davisgl01", "davisgl01", "davisgl01", "davisgl01", "davisgl01", "bernato01", "bernato01", "bernato01", "bernato01", "bernato01", "bernato01", "bernato01", "bernato01", "bernato01", "bernato01", "bernato01", "bernato01", "gedmari01", "gedmari01", "gedmari01", "gedmari01", "gedmari01", "gedmari01", "gedmari01", "gedmari01", "gedmari01", "gedmari01", "gedmari01", "gedmari01", "gedmari01", "gedmari01", "higuete01", "higuete01", "higuete01", "higuete01", "higuete01", "higuete01", "higuete01", 
+#> "higuete01", "higuete01", "violafr01", "violafr01", "violafr01", "violafr01", "violafr01", "violafr01", "violafr01", "violafr01", "violafr01", "violafr01", "violafr01", "violafr01", "violafr01", "violafr01", "violafr01", "violafr01", "bedrost01", "bedrost01", "bedrost01", "bedrost01", "bedrost01", "bedrost01", "bedrost01", "bedrost01", "bedrost01", "bedrost01", "bedrost01", "bedrost01", "bedrost01", "bedrost01", "bedrost01", "langsma01", "langsma01", "langsma01", "langsma01", "langsma01", "langsma01", 
+#> "langsma01", "langsma01", "langsma01", "langsma01", "langsma01", "langsma01", "langsma01", "langsma01", "langsma01", "langsma01", "langsma01", "pendlte01", "pendlte01", "pendlte01", "pendlte01", "pendlte01", "pendlte01", "pendlte01", "pendlte01", "pendlte01", "pendlte01", "pendlte01", "pendlte01", "pendlte01", "pendlte01", "pendlte01", "pendlte01", "lavalmi01", "lavalmi01", "lavalmi01", "lavalmi01", "lavalmi01", "lavalmi01", "lavalmi01", "lavalmi01", "lavalmi01", "lavalmi01", "lavalmi01", "lavalmi01", 
+#> "lavalmi01", "daviser01", "daviser01", "daviser01", "daviser01", "daviser01", "daviser01", "daviser01", "daviser01", "daviser01", "daviser01", "daviser01", "daviser01", "daviser01", "daviser01", "daviser01", "daviser01", "daviser01", "daviser01", "molitpa01", "molitpa01", "molitpa01", "molitpa01", "molitpa01", "molitpa01", "molitpa01", "molitpa01", "molitpa01", "molitpa01", "molitpa01", "molitpa01", "molitpa01", "molitpa01", "molitpa01", "molitpa01", "molitpa01", "molitpa01", "molitpa01", "molitpa01", 
+#> "molitpa01", "leonaje01", "leonaje01", "leonaje01", "leonaje01", "leonaje01", "leonaje01", "leonaje01", "leonaje01", "leonaje01", "leonaje01", "leonaje01", "leonaje01", "leonaje01", "leonaje01", "leonaje01", "leonaje01", "mcgwima01", "mcgwima01", "mcgwima01", "mcgwima01", "mcgwima01", "mcgwima01", "mcgwima01", "mcgwima01", "mcgwima01", "mcgwima01", "mcgwima01", "mcgwima01", "mcgwima01", "mcgwima01", "mcgwima01", "mcgwima01", "mcgwima01", "santibe01", "santibe01", "santibe01", "santibe01", "santibe01", 
+#> "santibe01", "santibe01", "santibe01", "santibe01", "santibe01", "santibe01", "santibe01", "santibe01", "santibe01", "santibe01", "santibe01", "santibe01", "santibe01", "santibe01", "santibe01", "nokesma01", "nokesma01", "nokesma01", "nokesma01", "nokesma01", "nokesma01", "nokesma01", "nokesma01", "nokesma01", "nokesma01", "nokesma01", "nokesma01", "nokesma01", "samueju01", "samueju01", "samueju01", "samueju01", "samueju01", "samueju01", "samueju01", "samueju01", "samueju01", "samueju01", "samueju01", 
+#> "samueju01", "samueju01", "samueju01", "samueju01", "samueju01", "samueju01", "samueju01", "samueju01", "keyji01", "keyji01", "keyji01", "keyji01", "keyji01", "keyji01", "keyji01", "keyji01", "keyji01", "keyji01", "keyji01", "keyji01", "keyji01", "keyji01", "keyji01", "smithza01", "smithza01", "smithza01", "smithza01", "smithza01", "smithza01", "smithza01", "smithza01", "smithza01", "smithza01", "smithza01", "smithza01", "smithza01", "smithza01", "smithza01", "eckerde01", "eckerde01", "eckerde01", 
+#> "eckerde01", "eckerde01", "eckerde01", "eckerde01", "eckerde01", "eckerde01", "eckerde01", "eckerde01", "eckerde01", "eckerde01", "eckerde01", "eckerde01", "eckerde01", "eckerde01", "eckerde01", "eckerde01", "eckerde01", "eckerde01", "eckerde01", "eckerde01", "eckerde01", "eckerde01", "steinte01", "steinte01", "steinte01", "steinte01", "steinte01", "steinte01", "steinte01", "steinte01", "steinte01", "steinte01", "steinte01", "steinte01", "steinte01", "steinte01", "hershor01", "hershor01", "hershor01", 
+#> "hershor01", "hershor01", "hershor01", "hershor01", "hershor01", "hershor01", "hershor01", "hershor01", "hershor01", "hershor01", "hershor01", "hershor01", "hershor01", "hershor01", "hershor01", "reynoha01", "reynoha01", "reynoha01", "reynoha01", "reynoha01", "reynoha01", "reynoha01", "reynoha01", "reynoha01", "reynoha01", "reynoha01", "reynoha01", "whitede03", "whitede03", "whitede03", "whitede03", "whitede03", "whitede03", "whitede03", "whitede03", "whitede03", "whitede03", "whitede03", "whitede03", 
+#> "whitede03", "whitede03", "whitede03", "whitede03", "whitede03", "vanslan01", "vanslan01", "vanslan01", "vanslan01", "vanslan01", "vanslan01", "vanslan01", "vanslan01", "vanslan01", "vanslan01", "vanslan01", "vanslan01", "vanslan01", "vanslan01", "oestero01", "oestero01", "oestero01", "oestero01", "oestero01", "oestero01", "oestero01", "oestero01", "oestero01", "oestero01", "oestero01", "oestero01", "oestero01", "francjo01", "francjo01", "francjo01", "francjo01", "francjo01", "francjo01", "francjo01", 
+#> "francjo01", "francjo01", "francjo01", "francjo01", "francjo01", "francjo01", "francjo01", "francjo01", "francjo01", "francjo01", "francjo01", "francjo01", "francjo01", "francjo01", "weisswa01", "weisswa01", "weisswa01", "weisswa01", "weisswa01", "weisswa01", "weisswa01", "weisswa01", "weisswa01", "weisswa01", "weisswa01", "weisswa01", "weisswa01", "weisswa01", "saboch01", "saboch01", "saboch01", "saboch01", "saboch01", "saboch01", "saboch01", "saboch01", "saboch01", "saboch01", "francju01", "francju01", 
+#> "francju01", "francju01", "francju01", "francju01", "francju01", "francju01", "francju01", "francju01", "francju01", "francju01", "francju01", "francju01", "francju01", "francju01", "francju01", "francju01", "francju01", "francju01", "francju01", "francju01", "francju01", "francju01", "francju01", "greenmi01", "greenmi01", "greenmi01", "greenmi01", "greenmi01", "greenmi01", "greenmi01", "greenmi01", "greenmi01", "greenmi01", "greenmi01", "greenmi01", "galaran01", "galaran01", "galaran01", "galaran01", 
+#> "galaran01", "galaran01", "galaran01", "galaran01", "galaran01", "galaran01", "galaran01", "galaran01", "galaran01", "galaran01", "galaran01", "galaran01", "galaran01", "galaran01", "galaran01", "galaran01", "bonilbo01", "bonilbo01", "bonilbo01", "bonilbo01", "bonilbo01", "bonilbo01", "bonilbo01", "bonilbo01", "bonilbo01", "bonilbo01", "bonilbo01", "bonilbo01", "bonilbo01", "bonilbo01", "bonilbo01", "bonilbo01", "bonilbo01", "bonilbo01", "bonilbo01", "learyti01", "learyti01", "learyti01", "learyti01", 
+#> "learyti01", "learyti01", "learyti01", "learyti01", "learyti01", "learyti01", "learyti01", "learyti01", "learyti01", "learyti01", "learyti01", "larkiba01", "larkiba01", "larkiba01", "larkiba01", "larkiba01", "larkiba01", "larkiba01", "larkiba01", "larkiba01", "larkiba01", "larkiba01", "larkiba01", "larkiba01", "larkiba01", "larkiba01", "larkiba01", "larkiba01", "larkiba01", "larkiba01", "whitter01", "whitter01", "whitter01", "whitter01", "whitter01", "whitter01", "whitter01", "whitter01", "whitter01", 
+#> "whitter01", "whitter01", "whitter01", "whitter01", "whitter01", "whitter01", "stewada01", "stewada01", "stewada01", "stewada01", "stewada01", "stewada01", "stewada01", "stewada01", "stewada01", "stewada01", "stewada01", "stewada01", "stewada01", "stewada01", "stewada01", "stewada01", "stewada01", "stewada01", "stewada01", "clarkwi02", "clarkwi02", "clarkwi02", "clarkwi02", "clarkwi02", "clarkwi02", "clarkwi02", "clarkwi02", "clarkwi02", "clarkwi02", "clarkwi02", "clarkwi02", "clarkwi02", "clarkwi02", 
+#> "clarkwi02", "clarkwi02", "jacksda02", "jacksda02", "jacksda02", "jacksda02", "jacksda02", "jacksda02", "jacksda02", "jacksda02", "jacksda02", "jacksda02", "jacksda02", "jacksda02", "jacksda02", "jacksda02", "jacksda02", "jacksda02", "jacksda02", "mcreyke01", "mcreyke01", "mcreyke01", "mcreyke01", "mcreyke01", "mcreyke01", "mcreyke01", "mcreyke01", "mcreyke01", "mcreyke01", "mcreyke01", "mcreyke01", "jacksbo01", "jacksbo01", "jacksbo01", "jacksbo01", "jacksbo01", "jacksbo01", "jacksbo01", "jacksbo01", 
+#> "davisma01", "davisma01", "davisma01", "davisma01", "davisma01", "davisma01", "davisma01", "davisma01", "davisma01", "davisma01", "davisma01", "davisma01", "davisma01", "davisma01", "davisma01", "davisma01", "davisma01", "davisma01", "darliro01", "darliro01", "darliro01", "darliro01", "darliro01", "darliro01", "darliro01", "darliro01", "darliro01", "darliro01", "darliro01", "darliro01", "darliro01", "darliro01", "darliro01", "draveda01", "draveda01", "draveda01", "draveda01", "draveda01", "draveda01", 
+#> "draveda01", "draveda01", "draveda01", "mitchke01", "mitchke01", "mitchke01", "mitchke01", "mitchke01", "mitchke01", "mitchke01", "mitchke01", "mitchke01", "mitchke01", "mitchke01", "mitchke01", "mitchke01", "mitchke01", "mitchke01", "russeje01", "russeje01", "russeje01", "russeje01", "russeje01", "russeje01", "russeje01", "russeje01", "russeje01", "russeje01", "russeje01", "russeje01", "russeje01", "russeje01", "russeje01", "russeje01", "olsongr01", "olsongr01", "olsongr01", "olsongr01", "olsongr01", 
+#> "olsongr01", "olsongr01", "olsongr01", "olsongr01", "olsongr01", "olsongr01", "olsongr01", "olsongr01", "olsongr01", "olsongr01", "olsongr01", "olsongr01", "waltoje01", "waltoje01", "waltoje01", "waltoje01", "waltoje01", "waltoje01", "waltoje01", "waltoje01", "waltoje01", "waltoje01", "mcgrifr01", "mcgrifr01", "mcgrifr01", "mcgrifr01", "mcgrifr01", "mcgrifr01", "mcgrifr01", "mcgrifr01", "mcgrifr01", "mcgrifr01", "mcgrifr01", "mcgrifr01", "mcgrifr01", "mcgrifr01", "mcgrifr01", "mcgrifr01", "mcgrifr01", 
+#> "mcgrifr01", "mcgrifr01", "mcgrifr01", "mcgrifr01", "tettlmi01", "tettlmi01", "tettlmi01", "tettlmi01", "tettlmi01", "tettlmi01", "tettlmi01", "tettlmi01", "tettlmi01", "tettlmi01", "tettlmi01", "tettlmi01", "tettlmi01", "tettlmi01", "sierrru01", "sierrru01", "sierrru01", "sierrru01", "sierrru01", "sierrru01", "sierrru01", "sierrru01", "sierrru01", "sierrru01", "sierrru01", "sierrru01", "sierrru01", "sierrru01", "sierrru01", "sierrru01", "sierrru01", "sierrru01", "sierrru01", "sierrru01", "sierrru01", 
+#> "sierrru01", "sierrru01", "sierrru01", "sierrru01", "johnsho01", "johnsho01", "johnsho01", "johnsho01", "johnsho01", "johnsho01", "johnsho01", "johnsho01", "johnsho01", "johnsho01", "johnsho01", "johnsho01", "johnsho01", "johnsho01", "biggicr01", "biggicr01", "biggicr01", "biggicr01", "biggicr01", "biggicr01", "biggicr01", "biggicr01", "biggicr01", "biggicr01", "biggicr01", "biggicr01", "biggicr01", "biggicr01", "biggicr01", "biggicr01", "biggicr01", "biggicr01", "biggicr01", "biggicr01", "finlech01", 
+#> "finlech01", "finlech01", "finlech01", "finlech01", "finlech01", "finlech01", "finlech01", "finlech01", "finlech01", "finlech01", "finlech01", "finlech01", "finlech01", "finlech01", "finlech01", "finlech01", "finlech01", "dunstsh01", "dunstsh01", "dunstsh01", "dunstsh01", "dunstsh01", "dunstsh01", "dunstsh01", "dunstsh01", "dunstsh01", "dunstsh01", "dunstsh01", "dunstsh01", "dunstsh01", "dunstsh01", "dunstsh01", "dunstsh01", "dunstsh01", "dunstsh01", "dunstsh01", "dunstsh01", "dunstsh01", "hatchbi01", 
+#> "hatchbi01", "hatchbi01", "hatchbi01", "hatchbi01", "hatchbi01", "hatchbi01", "hatchbi01", "hatchbi01", "hatchbi01", "hatchbi01", "hatchbi01", "hatchbi01", "hatchbi01", "hatchbi01", "welchbo01", "welchbo01", "welchbo01", "welchbo01", "welchbo01", "welchbo01", "welchbo01", "welchbo01", "welchbo01", "welchbo01", "welchbo01", "welchbo01", "welchbo01", "welchbo01", "welchbo01", "welchbo01", "welchbo01", "drabedo01", "drabedo01", "drabedo01", "drabedo01", "drabedo01", "drabedo01", "drabedo01", "drabedo01", 
+#> "drabedo01", "drabedo01", "drabedo01", "drabedo01", "drabedo01", "grubeke01", "grubeke01", "grubeke01", "grubeke01", "grubeke01", "grubeke01", "grubeke01", "grubeke01", "grubeke01", "grubeke01", "alomasa02", "alomasa02", "alomasa02", "alomasa02", "alomasa02", "alomasa02", "alomasa02", "alomasa02", "alomasa02", "alomasa02", "alomasa02", "alomasa02", "alomasa02", "alomasa02", "alomasa02", "alomasa02", "alomasa02", "alomasa02", "alomasa02", "alomasa02", "alomasa02", "alomasa02", "burksel01", "burksel01", 
+#> "burksel01", "burksel01", "burksel01", "burksel01", "burksel01", "burksel01", "burksel01", "burksel01", "burksel01", "burksel01", "burksel01", "burksel01", "burksel01", "burksel01", "burksel01", "burksel01", "burksel01", "griffke02", "griffke02", "griffke02", "griffke02", "griffke02", "griffke02", "griffke02", "griffke02", "griffke02", "griffke02", "griffke02", "griffke02", "griffke02", "griffke02", "griffke02", "griffke02", "griffke02", "griffke02", "griffke02", "griffke02", "griffke02", "griffke02", 
+#> "griffke02", "bondsba01", "bondsba01", "bondsba01", "bondsba01", "bondsba01", "bondsba01", "bondsba01", "bondsba01", "bondsba01", "bondsba01", "bondsba01", "bondsba01", "bondsba01", "bondsba01", "bondsba01", "bondsba01", "bondsba01", "bondsba01", "bondsba01", "bondsba01", "bondsba01", "bondsba01", "maddugr01", "maddugr01", "maddugr01", "maddugr01", "maddugr01", "maddugr01", "maddugr01", "maddugr01", "maddugr01", "maddugr01", "maddugr01", "maddugr01", "maddugr01", "maddugr01", "maddugr01", "maddugr01", 
+#> "maddugr01", "maddugr01", "maddugr01", "maddugr01", "maddugr01", "maddugr01", "maddugr01", "maddugr01", "maddugr01", "breamsi01", "breamsi01", "breamsi01", "breamsi01", "breamsi01", "breamsi01", "breamsi01", "breamsi01", "breamsi01", "breamsi01", "breamsi01", "breamsi01", "breamsi01", "dibblro01", "dibblro01", "dibblro01", "dibblro01", "dibblro01", "dibblro01", "dibblro01", "dibblro01", "myersra01", "myersra01", "myersra01", "myersra01", "myersra01", "myersra01", "myersra01", "myersra01", "myersra01", 
+#> "myersra01", "myersra01", "myersra01", "myersra01", "myersra01", "myersra01", "thigpbo01", "thigpbo01", "thigpbo01", "thigpbo01", "thigpbo01", "thigpbo01", "thigpbo01", "thigpbo01", "thigpbo01", "thigpbo01", "justida01", "justida01", "justida01", "justida01", "justida01", "justida01", "justida01", "justida01", "justida01", "justida01", "justida01", "justida01", "justida01", "justida01", "justida01", "fieldce01", "fieldce01", "fieldce01", "fieldce01", "fieldce01", "fieldce01", "fieldce01", "fieldce01", 
+#> "fieldce01", "fieldce01", "fieldce01", "fieldce01", "fieldce01", "fieldce01", "fieldce01", "willima04", "willima04", "willima04", "willima04", "willima04", "willima04", "willima04", "willima04", "willima04", "willima04", "willima04", "willima04", "willima04", "willima04", "willima04", "willima04", "willima04", "sciosmi01", "sciosmi01", "sciosmi01", "sciosmi01", "sciosmi01", "sciosmi01", "sciosmi01", "sciosmi01", "sciosmi01", "sciosmi01", "sciosmi01", "sciosmi01", "sciosmi01", "rijojo01", "rijojo01", 
+#> "rijojo01", "rijojo01", "rijojo01", "rijojo01", "rijojo01", "rijojo01", "rijojo01", "rijojo01", "rijojo01", "rijojo01", "rijojo01", "rijojo01", "glavito02", "glavito02", "glavito02", "glavito02", "glavito02", "glavito02", "glavito02", "glavito02", "glavito02", "glavito02", "glavito02", "glavito02", "glavito02", "glavito02", "glavito02", "glavito02", "glavito02", "glavito02", "glavito02", "glavito02", "glavito02", "glavito02", "alomaro01", "alomaro01", "alomaro01", "alomaro01", "alomaro01", "alomaro01", 
+#> "alomaro01", "alomaro01", "alomaro01", "alomaro01", "alomaro01", "alomaro01", "alomaro01", "alomaro01", "alomaro01", "alomaro01", "alomaro01", "alomaro01", "alomaro01", "venturo01", "venturo01", "venturo01", "venturo01", "venturo01", "venturo01", "venturo01", "venturo01", "venturo01", "venturo01", "venturo01", "venturo01", "venturo01", "venturo01", "venturo01", "venturo01", "venturo01", "pagnoto01", "pagnoto01", "pagnoto01", "pagnoto01", "pagnoto01", "pagnoto01", "pagnoto01", "pagnoto01", "pagnoto01", 
+#> "pagnoto01", "pagnoto01", "pagnoto01", "wegmabi01", "wegmabi01", "wegmabi01", "wegmabi01", "wegmabi01", "wegmabi01", "wegmabi01", "wegmabi01", "wegmabi01", "wegmabi01", "wegmabi01", "hrbekke01", "hrbekke01", "hrbekke01", "hrbekke01", "hrbekke01", "hrbekke01", "hrbekke01", "hrbekke01", "hrbekke01", "hrbekke01", "hrbekke01", "hrbekke01", "hrbekke01", "hrbekke01", "averyst01", "averyst01", "averyst01", "averyst01", "averyst01", "averyst01", "averyst01", "averyst01", "averyst01", "averyst01", "averyst01", 
+#> "harvebr01", "harvebr01", "harvebr01", "harvebr01", "harvebr01", "harvebr01", "harvebr01", "harvebr01", "harvebr01", "knoblch01", "knoblch01", "knoblch01", "knoblch01", "knoblch01", "knoblch01", "knoblch01", "knoblch01", "knoblch01", "knoblch01", "knoblch01", "knoblch01", "bagweje01", "bagweje01", "bagweje01", "bagweje01", "bagweje01", "bagweje01", "bagweje01", "bagweje01", "bagweje01", "bagweje01", "bagweje01", "bagweje01", "bagweje01", "bagweje01", "bagweje01", "thomafr04", "thomafr04", "thomafr04", 
+#> "thomafr04", "thomafr04", "thomafr04", "thomafr04", "thomafr04", "thomafr04", "thomafr04", "thomafr04", "thomafr04", "thomafr04", "thomafr04", "thomafr04", "thomafr04", "thomafr04", "thomafr04", "thomafr04", "thomafr04", "cartejo01", "cartejo01", "cartejo01", "cartejo01", "cartejo01", "cartejo01", "cartejo01", "cartejo01", "cartejo01", "cartejo01", "cartejo01", "cartejo01", "cartejo01", "cartejo01", "cartejo01", "cartejo01", "cartejo01", "gantro01", "gantro01", "gantro01", "gantro01", "gantro01", 
+#> "gantro01", "gantro01", "gantro01", "gantro01", "gantro01", "gantro01", "gantro01", "gantro01", "gantro01", "gantro01", "gantro01", "gantro01", "gantro01", "abbotji01", "abbotji01", "abbotji01", "abbotji01", "abbotji01", "abbotji01", "abbotji01", "abbotji01", "abbotji01", "abbotji01", "abbotji01", "rodriiv01", "rodriiv01", "rodriiv01", "rodriiv01", "rodriiv01", "rodriiv01", "rodriiv01", "rodriiv01", "rodriiv01", "rodriiv01", "rodriiv01", "rodriiv01", "rodriiv01", "rodriiv01", "rodriiv01", "rodriiv01", 
+#> "rodriiv01", "rodriiv01", "rodriiv01", "rodriiv01", "rodriiv01", "rodriiv01", "rodriiv01", "gracema01", "gracema01", "gracema01", "gracema01", "gracema01", "gracema01", "gracema01", "gracema01", "gracema01", "gracema01", "gracema01", "gracema01", "gracema01", "gracema01", "gracema01", "gracema01", "lindjo01", "lindjo01", "lindjo01", "lindjo01", "lindjo01", "lindjo01", "lindjo01", "lindjo01", "lindjo01", "lindjo01", "walkela01", "walkela01", "walkela01", "walkela01", "walkela01", "walkela01", "walkela01", 
+#> "walkela01", "walkela01", "walkela01", "walkela01", "walkela01", "walkela01", "walkela01", "walkela01", "walkela01", "walkela01", "walkela01", "smoltjo01", "smoltjo01", "smoltjo01", "smoltjo01", "smoltjo01", "smoltjo01", "smoltjo01", "smoltjo01", "smoltjo01", "smoltjo01", "smoltjo01", "smoltjo01", "smoltjo01", "smoltjo01", "smoltjo01", "smoltjo01", "smoltjo01", "smoltjo01", "smoltjo01", "smoltjo01", "smoltjo01", "smoltjo01", "listapa01", "listapa01", "listapa01", "listapa01", "listapa01", "listapa01", 
+#> "karroer01", "karroer01", "karroer01", "karroer01", "karroer01", "karroer01", "karroer01", "karroer01", "karroer01", "karroer01", "karroer01", "karroer01", "karroer01", "karroer01", "martied01", "martied01", "martied01", "martied01", "martied01", "martied01", "martied01", "martied01", "martied01", "martied01", "martied01", "martied01", "martied01", "martied01", "martied01", "martied01", "martied01", "martied01", "gonzaju03", "gonzaju03", "gonzaju03", "gonzaju03", "gonzaju03", "gonzaju03", "gonzaju03", 
+#> "gonzaju03", "gonzaju03", "gonzaju03", "gonzaju03", "gonzaju03", "gonzaju03", "gonzaju03", "gonzaju03", "gonzaju03", "gonzaju03", "frymatr01", "frymatr01", "frymatr01", "frymatr01", "frymatr01", "frymatr01", "frymatr01", "frymatr01", "frymatr01", "frymatr01", "frymatr01", "frymatr01", "frymatr01", "sheffga01", "sheffga01", "sheffga01", "sheffga01", "sheffga01", "sheffga01", "sheffga01", "sheffga01", "sheffga01", "sheffga01", "sheffga01", "sheffga01", "sheffga01", "sheffga01", "sheffga01", "sheffga01", 
+#> "sheffga01", "sheffga01", "sheffga01", "sheffga01", "sheffga01", "sheffga01", "sheffga01", "sheffga01", "daultda01", "daultda01", "daultda01", "daultda01", "daultda01", "daultda01", "daultda01", "daultda01", "daultda01", "daultda01", "daultda01", "daultda01", "daultda01", "daultda01", "daultda01", "flemida01", "flemida01", "flemida01", "flemida01", "flemida01", "flemida01", "devermi01", "devermi01", "devermi01", "devermi01", "devermi01", "devermi01", "devermi01", "devermi01", "devermi01", "devermi01", 
+#> "devermi01", "devermi01", "devermi01", "mcdowja01", "mcdowja01", "mcdowja01", "mcdowja01", "mcdowja01", "mcdowja01", "mcdowja01", "mcdowja01", "mcdowja01", "mcdowja01", "mcdowja01", "mcdowja01", "jonesdo01", "jonesdo01", "jonesdo01", "jonesdo01", "jonesdo01", "jonesdo01", "jonesdo01", "jonesdo01", "jonesdo01", "jonesdo01", "jonesdo01", "jonesdo01", "jonesdo01", "jonesdo01", "jonesdo01", "jonesdo01", "jonesdo01", "jonesdo01", "bordepa01", "bordepa01", "bordepa01", "bordepa01", "bordepa01", "bordepa01", 
+#> "bordepa01", "bordepa01", "bordepa01", "bordepa01", "bordepa01", "bordepa01", "bordepa01", "bordepa01", "bordepa01", "bordepa01", "bordepa01", "bordepa01", "bordepa01", "bordepa01", "bordepa01", "bordepa01", "loftoke01", "loftoke01", "loftoke01", "loftoke01", "loftoke01", "loftoke01", "loftoke01", "loftoke01", "loftoke01", "loftoke01", "loftoke01", "loftoke01", "loftoke01", "loftoke01", "loftoke01", "loftoke01", "loftoke01", "loftoke01", "loftoke01", "loftoke01", "vizquom01", "vizquom01", "vizquom01", 
+#> "vizquom01", "vizquom01", "vizquom01", "vizquom01", "vizquom01", "vizquom01", "vizquom01", "vizquom01", "vizquom01", "vizquom01", "vizquom01", "vizquom01", "vizquom01", "vizquom01", "vizquom01", "vizquom01", "vizquom01", "vizquom01", "vizquom01", "vizquom01", "vizquom01", "thompro01", "thompro01", "thompro01", "thompro01", "thompro01", "thompro01", "thompro01", "thompro01", "thompro01", "thompro01", "thompro01", "manwaki01", "manwaki01", "manwaki01", "manwaki01", "manwaki01", "manwaki01", "manwaki01", 
+#> "manwaki01", "manwaki01", "manwaki01", "manwaki01", "manwaki01", "manwaki01", "manwaki01", "grissma02", "grissma02", "grissma02", "grissma02", "grissma02", "grissma02", "grissma02", "grissma02", "grissma02", "grissma02", "grissma02", "grissma02", "grissma02", "grissma02", "grissma02", "grissma02", "grissma02", "bellja01", "bellja01", "bellja01", "bellja01", "bellja01", "bellja01", "bellja01", "bellja01", "bellja01", "bellja01", "bellja01", "bellja01", "bellja01", "bellja01", "bellja01", "bellja01", 
+#> "bellja01", "bellja01", "olerujo01", "olerujo01", "olerujo01", "olerujo01", "olerujo01", "olerujo01", "olerujo01", "olerujo01", "olerujo01", "olerujo01", "olerujo01", "olerujo01", "olerujo01", "olerujo01", "olerujo01", "olerujo01", "olerujo01", "olerujo01", "schilcu01", "schilcu01", "schilcu01", "schilcu01", "schilcu01", "schilcu01", "schilcu01", "schilcu01", "schilcu01", "schilcu01", "schilcu01", "schilcu01", "schilcu01", "schilcu01", "schilcu01", "schilcu01", "schilcu01", "schilcu01", "schilcu01", 
+#> "schilcu01", "schilcu01", "montgje01", "montgje01", "montgje01", "montgje01", "montgje01", "montgje01", "montgje01", "montgje01", "montgje01", "montgje01", "montgje01", "montgje01", "montgje01", "salmoti01", "salmoti01", "salmoti01", "salmoti01", "salmoti01", "salmoti01", "salmoti01", "salmoti01", "salmoti01", "salmoti01", "salmoti01", "salmoti01", "salmoti01", "salmoti01", "piazzmi01", "piazzmi01", "piazzmi01", "piazzmi01", "piazzmi01", "piazzmi01", "piazzmi01", "piazzmi01", "piazzmi01", "piazzmi01", 
+#> "piazzmi01", "piazzmi01", "piazzmi01", "piazzmi01", "piazzmi01", "piazzmi01", "piazzmi01", "piazzmi01", "baergca01", "baergca01", "baergca01", "baergca01", "baergca01", "baergca01", "baergca01", "baergca01", "baergca01", "baergca01", "baergca01", "baergca01", "baergca01", "baergca01", "baergca01", "baergca01", "stanlmi02", "stanlmi02", "stanlmi02", "stanlmi02", "stanlmi02", "stanlmi02", "stanlmi02", "stanlmi02", "stanlmi02", "stanlmi02", "stanlmi02", "stanlmi02", "stanlmi02", "stanlmi02", "stanlmi02", 
+#> "stanlmi02", "stanlmi02", "stanlmi02", "belleal01", "belleal01", "belleal01", "belleal01", "belleal01", "belleal01", "belleal01", "belleal01", "belleal01", "belleal01", "belleal01", "belleal01", "dykstle01", "dykstle01", "dykstle01", "dykstle01", "dykstle01", "dykstle01", "dykstle01", "dykstle01", "dykstle01", "dykstle01", "dykstle01", "dykstle01", "dykstle01", "coneda01", "coneda01", "coneda01", "coneda01", "coneda01", "coneda01", "coneda01", "coneda01", "coneda01", "coneda01", "coneda01", "coneda01", 
+#> "coneda01", "coneda01", "coneda01", "coneda01", "coneda01", "coneda01", "coneda01", "lewisda01", "lewisda01", "lewisda01", "lewisda01", "lewisda01", "lewisda01", "lewisda01", "lewisda01", "lewisda01", "lewisda01", "lewisda01", "lewisda01", "lewisda01", "lewisda01", "lewisda01", "beckro01", "beckro01", "beckro01", "beckro01", "beckro01", "beckro01", "beckro01", "beckro01", "beckro01", "beckro01", "beckro01", "beckro01", "beckro01", "beckro01", "hamelbo01", "hamelbo01", "hamelbo01", "hamelbo01", "hamelbo01", 
+#> "hamelbo01", "mondera01", "mondera01", "mondera01", "mondera01", "mondera01", "mondera01", "mondera01", "mondera01", "mondera01", "mondera01", "mondera01", "mondera01", "mondera01", "mondera01", "mondera01", "mondera01", "aloumo01", "aloumo01", "aloumo01", "aloumo01", "aloumo01", "aloumo01", "aloumo01", "aloumo01", "aloumo01", "aloumo01", "aloumo01", "aloumo01", "aloumo01", "aloumo01", "aloumo01", "aloumo01", "aloumo01", "aloumo01", "portuma01", "portuma01", "portuma01", "portuma01", "portuma01", 
+#> "portuma01", "portuma01", "portuma01", "portuma01", "portuma01", "portuma01", "portuma01", "portuma01", "portuma01", "portuma01", "portuma01", "cordewi01", "cordewi01", "cordewi01", "cordewi01", "cordewi01", "cordewi01", "cordewi01", "cordewi01", "cordewi01", "cordewi01", "cordewi01", "cordewi01", "cordewi01", "cordewi01", "cordewi01", "cordewi01", "coninje01", "coninje01", "coninje01", "coninje01", "coninje01", "coninje01", "coninje01", "coninje01", "coninje01", "coninje01", "coninje01", "coninje01", 
+#> "coninje01", "coninje01", "coninje01", "coninje01", "coninje01", "coninje01", "coninje01", "coninje01", "johnsra05", "johnsra05", "johnsra05", "johnsra05", "johnsra05", "johnsra05", "johnsra05", "johnsra05", "johnsra05", "johnsra05", "johnsra05", "johnsra05", "johnsra05", "johnsra05", "johnsra05", "johnsra05", "johnsra05", "johnsra05", "johnsra05", "johnsra05", "johnsra05", "johnsra05", "johnsra05", "johnsra05", "snowjt01", "snowjt01", "snowjt01", "snowjt01", "snowjt01", "snowjt01", "snowjt01", "snowjt01", 
+#> "snowjt01", "snowjt01", "snowjt01", "snowjt01", "snowjt01", "snowjt01", "snowjt01", "snowjt01", "caminke01", "caminke01", "caminke01", "caminke01", "caminke01", "caminke01", "caminke01", "caminke01", "caminke01", "caminke01", "caminke01", "caminke01", "caminke01", "caminke01", "caminke01", "caminke01", "johnsch04", "johnsch04", "johnsch04", "johnsch04", "johnsch04", "johnsch04", "johnsch04", "johnsch04", "johnsch04", "johnsch04", "johnsch04", "johnsch04", "johnsch04", "johnsch04", "finlest01", "finlest01", 
+#> "finlest01", "finlest01", "finlest01", "finlest01", "finlest01", "finlest01", "finlest01", "finlest01", "finlest01", "finlest01", "finlest01", "finlest01", "finlest01", "finlest01", "finlest01", "finlest01", "finlest01", "finlest01", "vaughmo01", "vaughmo01", "vaughmo01", "vaughmo01", "vaughmo01", "vaughmo01", "vaughmo01", "vaughmo01", "vaughmo01", "vaughmo01", "vaughmo01", "vaughmo01", "mesajo01", "mesajo01", "mesajo01", "mesajo01", "mesajo01", "mesajo01", "mesajo01", "mesajo01", "mesajo01", "mesajo01", 
+#> "mesajo01", "mesajo01", "mesajo01", "mesajo01", "mesajo01", "mesajo01", "mesajo01", "mesajo01", "mesajo01", "mesajo01", "mesajo01", "mesajo01", "henketo01", "henketo01", "henketo01", "henketo01", "henketo01", "henketo01", "henketo01", "henketo01", "henketo01", "henketo01", "henketo01", "henketo01", "henketo01", "henketo01", "cordoma01", "cordoma01", "cordoma01", "cordoma01", "cordoma01", "cordoma01", "cordoma01", "cordoma01", "cordoma01", "nomohi01", "nomohi01", "nomohi01", "nomohi01", "nomohi01", 
+#> "nomohi01", "nomohi01", "nomohi01", "nomohi01", "nomohi01", "nomohi01", "nomohi01", "nomohi01", "ramirma02", "ramirma02", "ramirma02", "ramirma02", "ramirma02", "ramirma02", "ramirma02", "ramirma02", "ramirma02", "ramirma02", "ramirma02", "ramirma02", "ramirma02", "ramirma02", "ramirma02", "ramirma02", "ramirma02", "ramirma02", "ramirma02", "ramirma02", "ramirma02", "valenjo02", "valenjo02", "valenjo02", "valenjo02", "valenjo02", "valenjo02", "valenjo02", "valenjo02", "valenjo02", "valenjo02", "valenjo02", 
+#> "castivi02", "castivi02", "castivi02", "castivi02", "castivi02", "castivi02", "castivi02", "castivi02", "castivi02", "castivi02", "castivi02", "castivi02", "castivi02", "castivi02", "castivi02", "castivi02", "castivi02", "castivi02", "bicheda01", "bicheda01", "bicheda01", "bicheda01", "bicheda01", "bicheda01", "bicheda01", "bicheda01", "bicheda01", "bicheda01", "bicheda01", "bicheda01", "bicheda01", "bicheda01", "bicheda01", "sosasa01", "sosasa01", "sosasa01", "sosasa01", "sosasa01", "sosasa01", 
+#> "sosasa01", "sosasa01", "sosasa01", "sosasa01", "sosasa01", "sosasa01", "sosasa01", "sosasa01", "sosasa01", "sosasa01", "sosasa01", "sosasa01", "sosasa01", "thomeji01", "thomeji01", "thomeji01", "thomeji01", "thomeji01", "thomeji01", "thomeji01", "thomeji01", "thomeji01", "thomeji01", "thomeji01", "thomeji01", "thomeji01", "thomeji01", "thomeji01", "thomeji01", "thomeji01", "thomeji01", "thomeji01", "thomeji01", "thomeji01", "thomeji01", "thomeji01", "thomeji01", "thomeji01", "edmonji01", "edmonji01", 
+#> "edmonji01", "edmonji01", "edmonji01", "edmonji01", "edmonji01", "edmonji01", "edmonji01", "edmonji01", "edmonji01", "edmonji01", "edmonji01", "edmonji01", "edmonji01", "edmonji01", "edmonji01", "edmonji01", "edmonji01", "mussimi01", "mussimi01", "mussimi01", "mussimi01", "mussimi01", "mussimi01", "mussimi01", "mussimi01", "mussimi01", "mussimi01", "mussimi01", "mussimi01", "mussimi01", "mussimi01", "mussimi01", "mussimi01", "mussimi01", "mussimi01", "schoupe01", "schoupe01", "schoupe01", "schoupe01", 
+#> "schoupe01", "schoupe01", "schoupe01", "schoupe01", "schoupe01", "schoupe01", "schoupe01", "schoupe01", "sandere02", "sandere02", "sandere02", "sandere02", "sandere02", "sandere02", "sandere02", "sandere02", "sandere02", "sandere02", "sandere02", "sandere02", "sandere02", "sandere02", "sandere02", "sandere02", "sandere02", "willibe02", "willibe02", "willibe02", "willibe02", "willibe02", "willibe02", "willibe02", "willibe02", "willibe02", "willibe02", "willibe02", "willibe02", "willibe02", "willibe02", 
+#> "willibe02", "willibe02", "butlebr01", "butlebr01", "butlebr01", "butlebr01", "butlebr01", "butlebr01", "butlebr01", "butlebr01", "butlebr01", "butlebr01", "butlebr01", "butlebr01", "butlebr01", "butlebr01", "butlebr01", "butlebr01", "butlebr01", "butlebr01", "hentgpa01", "hentgpa01", "hentgpa01", "hentgpa01", "hentgpa01", "hentgpa01", "hentgpa01", "hentgpa01", "hentgpa01", "hentgpa01", "hentgpa01", "hentgpa01", "hentgpa01", "hentgpa01", "buhneja01", "buhneja01", "buhneja01", "buhneja01", "buhneja01", 
+#> "buhneja01", "buhneja01", "buhneja01", "buhneja01", "buhneja01", "buhneja01", "buhneja01", "buhneja01", "buhneja01", "buhneja01", "buhneja01", "lopezja01", "lopezja01", "lopezja01", "lopezja01", "lopezja01", "lopezja01", "lopezja01", "lopezja01", "lopezja01", "lopezja01", "lopezja01", "lopezja01", "lopezja01", "lopezja01", "lopezja01", "lopezja01", "wettejo01", "wettejo01", "wettejo01", "wettejo01", "wettejo01", "wettejo01", "wettejo01", "wettejo01", "wettejo01", "wettejo01", "wettejo01", "wettejo01", 
+#> "brantje01", "brantje01", "brantje01", "brantje01", "brantje01", "brantje01", "brantje01", "brantje01", "brantje01", "brantje01", "brantje01", "brantje01", "brantje01", "brantje01", "jeterde01", "jeterde01", "jeterde01", "jeterde01", "jeterde01", "jeterde01", "jeterde01", "jeterde01", "jeterde01", "jeterde01", "jeterde01", "jeterde01", "jeterde01", "jeterde01", "jeterde01", "jeterde01", "jeterde01", "jeterde01", "jeterde01", "jeterde01", "hollato01", "hollato01", "hollato01", "hollato01", "hollato01", 
+#> "hollato01", "hollato01", "hollato01", "hollato01", "hollato01", "hollato01", "hollato01", "hollato01", "hollato01", "hollato01", "hollato01", "rodrial01", "rodrial01", "rodrial01", "rodrial01", "rodrial01", "rodrial01", "rodrial01", "rodrial01", "rodrial01", "rodrial01", "rodrial01", "rodrial01", "rodrial01", "rodrial01", "rodrial01", "rodrial01", "rodrial01", "rodrial01", "rodrial01", "rodrial01", "rodrial01", "younger01", "younger01", "younger01", "younger01", "younger01", "younger01", "younger01", 
+#> "younger01", "younger01", "younger01", "younger01", "younger01", "younger01", "younger01", "younger01", "younger01", "younger01", "younger01", "pettian01", "pettian01", "pettian01", "pettian01", "pettian01", "pettian01", "pettian01", "pettian01", "pettian01", "pettian01", "pettian01", "pettian01", "pettian01", "pettian01", "pettian01", "pettian01", "pettian01", "pettian01", "leiteal01", "leiteal01", "leiteal01", "leiteal01", "leiteal01", "leiteal01", "leiteal01", "leiteal01", "leiteal01", "leiteal01", 
+#> "leiteal01", "leiteal01", "leiteal01", "leiteal01", "leiteal01", "leiteal01", "leiteal01", "leiteal01", "leiteal01", "leiteal01", "leiteal01", "hoffmtr01", "hoffmtr01", "hoffmtr01", "hoffmtr01", "hoffmtr01", "hoffmtr01", "hoffmtr01", "hoffmtr01", "hoffmtr01", "hoffmtr01", "hoffmtr01", "hoffmtr01", "hoffmtr01", "hoffmtr01", "hoffmtr01", "hoffmtr01", "hoffmtr01", "hoffmtr01", "hoffmtr01", "martipe02", "martipe02", "martipe02", "martipe02", "martipe02", "martipe02", "martipe02", "martipe02", "martipe02", 
+#> "martipe02", "martipe02", "martipe02", "martipe02", "martipe02", "martipe02", "martipe02", "martipe02", "martipe02", "palmera01", "palmera01", "palmera01", "palmera01", "palmera01", "palmera01", "palmera01", "palmera01", "palmera01", "palmera01", "palmera01", "palmera01", "palmera01", "palmera01", "palmera01", "palmera01", "palmera01", "palmera01", "palmera01", "palmera01", "ordonre01", "ordonre01", "ordonre01", "ordonre01", "ordonre01", "ordonre01", "ordonre01", "ordonre01", "ordonre01", "hernali01", 
+#> "hernali01", "hernali01", "hernali01", "hernali01", "hernali01", "hernali01", "hernali01", "hernali01", "hernali01", "hernali01", "hernali01", "hernali01", "hernali01", "hernali01", "hernali01", "hernali01", "hernali01", "hernali01", "hernali01", "hernali01", "hernali01", "shawje01", "shawje01", "shawje01", "shawje01", "shawje01", "shawje01", "shawje01", "shawje01", "shawje01", "shawje01", "shawje01", "shawje01", "shawje01", "shawje01", "garcino01", "garcino01", "garcino01", "garcino01", "garcino01", 
+#> "garcino01", "garcino01", "garcino01", "garcino01", "garcino01", "garcino01", "garcino01", "garcino01", "garcino01", "garcino01", "rolensc01", "rolensc01", "rolensc01", "rolensc01", "rolensc01", "rolensc01", "rolensc01", "rolensc01", "rolensc01", "rolensc01", "rolensc01", "rolensc01", "rolensc01", "rolensc01", "rolensc01", "rolensc01", "rolensc01", "rolensc01", "rolensc01", "martiti02", "martiti02", "martiti02", "martiti02", "martiti02", "martiti02", "martiti02", "martiti02", "martiti02", "martiti02", 
+#> "martiti02", "martiti02", "martiti02", "martiti02", "martiti02", "martiti02", "blausje01", "blausje01", "blausje01", "blausje01", "blausje01", "blausje01", "blausje01", "blausje01", "blausje01", "blausje01", "blausje01", "blausje01", "blausje01", "neaglde01", "neaglde01", "neaglde01", "neaglde01", "neaglde01", "neaglde01", "neaglde01", "neaglde01", "neaglde01", "neaglde01", "neaglde01", "neaglde01", "neaglde01", "neaglde01", "neaglde01", "riverma01", "riverma01", "riverma01", "riverma01", "riverma01", 
+#> "riverma01", "riverma01", "riverma01", "riverma01", "riverma01", "riverma01", "riverma01", "riverma01", "riverma01", "riverma01", "riverma01", "riverma01", "riverma01", "riverma01", "wellsda01", "wellsda01", "wellsda01", "wellsda01", "wellsda01", "wellsda01", "wellsda01", "wellsda01", "wellsda01", "wellsda01", "wellsda01", "wellsda01", "wellsda01", "wellsda01", "wellsda01", "wellsda01", "wellsda01", "wellsda01", "wellsda01", "wellsda01", "wellsda01", "wellsda01", "wellsda01", "wellsda01", "brosisc01", 
+#> "brosisc01", "brosisc01", "brosisc01", "brosisc01", "brosisc01", "brosisc01", "brosisc01", "brosisc01", "brosisc01", "brosisc01", "boonebr01", "boonebr01", "boonebr01", "boonebr01", "boonebr01", "boonebr01", "boonebr01", "boonebr01", "boonebr01", "boonebr01", "boonebr01", "boonebr01", "boonebr01", "boonebr01", "boonebr01", "jonesan01", "jonesan01", "jonesan01", "jonesan01", "jonesan01", "jonesan01", "jonesan01", "jonesan01", "jonesan01", "jonesan01", "jonesan01", "jonesan01", "jonesan01", "jonesan01", 
+#> "jonesan01", "jonesan01", "jonesan01", "hitchst01", "hitchst01", "hitchst01", "hitchst01", "hitchst01", "hitchst01", "hitchst01", "hitchst01", "hitchst01", "hitchst01", "hitchst01", "hitchst01", "hitchst01", "hitchst01", "hitchst01", "gordoto01", "gordoto01", "gordoto01", "gordoto01", "gordoto01", "gordoto01", "gordoto01", "gordoto01", "gordoto01", "gordoto01", "gordoto01", "gordoto01", "gordoto01", "gordoto01", "gordoto01", "gordoto01", "gordoto01", "gordoto01", "gordoto01", "gordoto01", "gordoto01", 
+#> "gordoto01", "grievbe01", "grievbe01", "grievbe01", "grievbe01", "grievbe01", "grievbe01", "grievbe01", "grievbe01", "grievbe01", "grievbe01", "woodke02", "woodke02", "woodke02", "woodke02", "woodke02", "woodke02", "woodke02", "woodke02", "woodke02", "woodke02", "woodke02", "woodke02", "woodke02", "woodke02", "woodke02", "easleda01", "easleda01", "easleda01", "easleda01", "easleda01", "easleda01", "easleda01", "easleda01", "easleda01", "easleda01", "easleda01", "easleda01", "easleda01", "easleda01", 
+#> "easleda01", "easleda01", "easleda01", "easleda01", "palmede01", "palmede01", "palmede01", "palmede01", "palmede01", "palmede01", "palmede01", "palmede01", "palmede01", "palmede01", "palmede01", "palmede01", "palmede01", "palmede01", "palmede01", "vaughgr01", "vaughgr01", "vaughgr01", "vaughgr01", "vaughgr01", "vaughgr01", "vaughgr01", "vaughgr01", "vaughgr01", "vaughgr01", "vaughgr01", "vaughgr01", "vaughgr01", "vaughgr01", "vaughgr01", "vaughgr01", "brownke01", "brownke01", "brownke01", "brownke01", 
+#> "brownke01", "brownke01", "brownke01", "brownke01", "brownke01", "brownke01", "brownke01", "brownke01", "brownke01", "brownke01", "brownke01", "brownke01", "brownke01", "brownke01", "brownke01", "hernaor01", "hernaor01", "hernaor01", "hernaor01", "hernaor01", "hernaor01", "hernaor01", "hernaor01", "hernaor01", "hernaor01", "greensh01", "greensh01", "greensh01", "greensh01", "greensh01", "greensh01", "greensh01", "greensh01", "greensh01", "greensh01", "greensh01", "greensh01", "greensh01", "greensh01", 
+#> "greensh01", "greensh01", "reesepo01", "reesepo01", "reesepo01", "reesepo01", "reesepo01", "reesepo01", "reesepo01", "reesepo01", "liebemi01", "liebemi01", "liebemi01", "liebemi01", "liebemi01", "liebemi01", "liebemi01", "liebemi01", "liebemi01", "liebemi01", "liebemi01", "liebemi01", "liebemi01", "liebemi01", "caseyse01", "caseyse01", "caseyse01", "caseyse01", "caseyse01", "caseyse01", "caseyse01", "caseyse01", "caseyse01", "caseyse01", "caseyse01", "caseyse01", "caseyse01", "jonesch06", "jonesch06", 
+#> "jonesch06", "jonesch06", "jonesch06", "jonesch06", "jonesch06", "jonesch06", "jonesch06", "jonesch06", "jonesch06", "jonesch06", "jonesch06", "jonesch06", "jonesch06", "jonesch06", "jonesch06", "jonesch06", "jonesch06", "perezed02", "perezed02", "perezed02", "perezed02", "perezed02", "perezed02", "perezed02", "perezed02", "perezed02", "perezed02", "perezed02", "wagnebi02", "wagnebi02", "wagnebi02", "wagnebi02", "wagnebi02", "wagnebi02", "wagnebi02", "wagnebi02", "wagnebi02", "wagnebi02", "wagnebi02", 
+#> "wagnebi02", "wagnebi02", "wagnebi02", "wagnebi02", "wagnebi02", "wagnebi02", "beltrca01", "beltrca01", "beltrca01", "beltrca01", "beltrca01", "beltrca01", "beltrca01", "beltrca01", "beltrca01", "beltrca01", "beltrca01", "beltrca01", "beltrca01", "beltrca01", "beltrca01", "beltrca01", "beltrca01", "beltrca01", "beltrca01", "beltrca01", "willisc01", "willisc01", "willisc01", "willisc01", "willisc01", "willisc01", "willisc01", "willisc01", "willisc01", "willisc01", "willisc01", "delgaca01", "delgaca01", 
+#> "delgaca01", "delgaca01", "delgaca01", "delgaca01", "delgaca01", "delgaca01", "delgaca01", "delgaca01", "delgaca01", "delgaca01", "delgaca01", "delgaca01", "delgaca01", "delgaca01", "delgaca01", "alfoned01", "alfoned01", "alfoned01", "alfoned01", "alfoned01", "alfoned01", "alfoned01", "alfoned01", "alfoned01", "alfoned01", "alfoned01", "alfoned01", "alfoned01", "guerrvl01", "guerrvl01", "guerrvl01", "guerrvl01", "guerrvl01", "guerrvl01", "guerrvl01", "guerrvl01", "guerrvl01", "guerrvl01", "guerrvl01", 
+#> "guerrvl01", "guerrvl01", "guerrvl01", "guerrvl01", "guerrvl01", "hamptmi01", "hamptmi01", "hamptmi01", "hamptmi01", "hamptmi01", "hamptmi01", "hamptmi01", "hamptmi01", "hamptmi01", "hamptmi01", "hamptmi01", "hamptmi01", "hamptmi01", "hamptmi01", "hamptmi01", "hamptmi01", "moyerja01", "moyerja01", "moyerja01", "moyerja01", "moyerja01", "moyerja01", "moyerja01", "moyerja01", "moyerja01", "moyerja01", "moyerja01", "moyerja01", "moyerja01", "moyerja01", "moyerja01", "moyerja01", "moyerja01", "moyerja01", 
+#> "moyerja01", "moyerja01", "moyerja01", "moyerja01", "moyerja01", "moyerja01", "moyerja01", "moyerja01", "moyerja01", "limajo01", "limajo01", "limajo01", "limajo01", "limajo01", "limajo01", "limajo01", "limajo01", "limajo01", "limajo01", "limajo01", "limajo01", "limajo01", "limajo01", "urbinug01", "urbinug01", "urbinug01", "urbinug01", "urbinug01", "urbinug01", "urbinug01", "urbinug01", "urbinug01", "urbinug01", "urbinug01", "urbinug01", "urbinug01", "urbinug01", "stottto01", "stottto01", "stottto01", 
+#> "stottto01", "stottto01", "stottto01", "stottto01", "stottto01", "stottto01", "stottto01", "stottto01", "stottto01", "stottto01", "stottto01", "stottto01", "dyeje01", "dyeje01", "dyeje01", "dyeje01", "dyeje01", "dyeje01", "dyeje01", "dyeje01", "dyeje01", "dyeje01", "dyeje01", "dyeje01", "dyeje01", "dyeje01", "dyeje01", "erstada01", "erstada01", "erstada01", "erstada01", "erstada01", "erstada01", "erstada01", "erstada01", "erstada01", "erstada01", "erstada01", "erstada01", "erstada01", "erstada01", 
+#> "rogerke01", "rogerke01", "rogerke01", "rogerke01", "rogerke01", "rogerke01", "rogerke01", "rogerke01", "rogerke01", "rogerke01", "rogerke01", "rogerke01", "rogerke01", "rogerke01", "rogerke01", "rogerke01", "rogerke01", "rogerke01", "rogerke01", "rogerke01", "rogerke01", "mathemi01", "mathemi01", "mathemi01", "mathemi01", "mathemi01", "mathemi01", "mathemi01", "mathemi01", "mathemi01", "mathemi01", "mathemi01", "mathemi01", "mathemi01", "perezne01", "perezne01", "perezne01", "perezne01", "perezne01", 
+#> "perezne01", "perezne01", "perezne01", "perezne01", "perezne01", "perezne01", "perezne01", "perezne01", "perezne01", "perezne01", "heltoto01", "heltoto01", "heltoto01", "heltoto01", "heltoto01", "heltoto01", "heltoto01", "heltoto01", "heltoto01", "heltoto01", "heltoto01", "heltoto01", "heltoto01", "heltoto01", "heltoto01", "heltoto01", "heltoto01", "giambja01", "giambja01", "giambja01", "giambja01", "giambja01", "giambja01", "giambja01", "giambja01", "giambja01", "giambja01", "giambja01", "giambja01", 
+#> "giambja01", "giambja01", "giambja01", "giambja01", "giambja01", "giambja01", "giambja01", "giambja01", "giambja01", "kentje01", "kentje01", "kentje01", "kentje01", "kentje01", "kentje01", "kentje01", "kentje01", "kentje01", "kentje01", "kentje01", "kentje01", "kentje01", "kentje01", "kentje01", "kentje01", "kentje01", "kentje01", "kentje01", "jonesto02", "jonesto02", "jonesto02", "jonesto02", "jonesto02", "jonesto02", "jonesto02", "jonesto02", "jonesto02", "jonesto02", "jonesto02", "jonesto02", 
+#> "jonesto02", "jonesto02", "jonesto02", "jonesto02", "jonesto02", "jonesto02", "jonesto02", "alfonan01", "alfonan01", "alfonan01", "alfonan01", "alfonan01", "alfonan01", "alfonan01", "alfonan01", "alfonan01", "alfonan01", "alfonan01", "sasakka01", "sasakka01", "sasakka01", "sasakka01", "furcara01", "furcara01", "furcara01", "furcara01", "furcara01", "furcara01", "furcara01", "furcara01", "furcara01", "furcara01", "furcara01", "furcara01", "furcara01", "furcara01", "furcara01", "glaustr01", "glaustr01", 
+#> "glaustr01", "glaustr01", "glaustr01", "glaustr01", "glaustr01", "glaustr01", "glaustr01", "glaustr01", "glaustr01", "glaustr01", "glaustr01", "posadjo01", "posadjo01", "posadjo01", "posadjo01", "posadjo01", "posadjo01", "posadjo01", "posadjo01", "posadjo01", "posadjo01", "posadjo01", "posadjo01", "posadjo01", "posadjo01", "posadjo01", "posadjo01", "posadjo01", "ordonma01", "ordonma01", "ordonma01", "ordonma01", "ordonma01", "ordonma01", "ordonma01", "ordonma01", "ordonma01", "ordonma01", "ordonma01", 
+#> "ordonma01", "ordonma01", "ordonma01", "ordonma01", "renteed01", "renteed01", "renteed01", "renteed01", "renteed01", "renteed01", "renteed01", "renteed01", "renteed01", "renteed01", "renteed01", "renteed01", "renteed01", "renteed01", "renteed01", "renteed01", "mientdo01", "mientdo01", "mientdo01", "mientdo01", "mientdo01", "mientdo01", "mientdo01", "mientdo01", "mientdo01", "mientdo01", "mientdo01", "mientdo01", "mientdo01", "chaveer01", "chaveer01", "chaveer01", "chaveer01", "chaveer01", "chaveer01", 
+#> "chaveer01", "chaveer01", "chaveer01", "chaveer01", "chaveer01", "chaveer01", "chaveer01", "chaveer01", "chaveer01", "chaveer01", "chaveer01", "camermi01", "camermi01", "camermi01", "camermi01", "camermi01", "camermi01", "camermi01", "camermi01", "camermi01", "camermi01", "camermi01", "camermi01", "camermi01", "camermi01", "camermi01", "camermi01", "camermi01", "camermi01", "hunteto01", "hunteto01", "hunteto01", "hunteto01", "hunteto01", "hunteto01", "hunteto01", "hunteto01", "hunteto01", "hunteto01", 
+#> "hunteto01", "hunteto01", "hunteto01", "hunteto01", "hunteto01", "hunteto01", "hunteto01", "hunteto01", "hunteto01", "suzukic01", "suzukic01", "suzukic01", "suzukic01", "suzukic01", "suzukic01", "suzukic01", "suzukic01", "suzukic01", "suzukic01", "suzukic01", "suzukic01", "suzukic01", "suzukic01", "suzukic01", "suzukic01", "vinafe01", "vinafe01", "vinafe01", "vinafe01", "vinafe01", "vinafe01", "vinafe01", "vinafe01", "vinafe01", "vinafe01", "vinafe01", "vinafe01", "ausmubr01", "ausmubr01", "ausmubr01", 
+#> "ausmubr01", "ausmubr01", "ausmubr01", "ausmubr01", "ausmubr01", "ausmubr01", "ausmubr01", "ausmubr01", "ausmubr01", "ausmubr01", "ausmubr01", "ausmubr01", "ausmubr01", "ausmubr01", "ausmubr01", "ausmubr01", "cabreor01", "cabreor01", "cabreor01", "cabreor01", "cabreor01", "cabreor01", "cabreor01", "cabreor01", "cabreor01", "cabreor01", "cabreor01", "cabreor01", "cabreor01", "cabreor01", "cabreor01", "cabreor01", "cabreor01", "cabreor01", "counscr01", "counscr01", "counscr01", "counscr01", "counscr01", 
+#> "counscr01", "counscr01", "counscr01", "counscr01", "counscr01", "counscr01", "counscr01", "counscr01", "counscr01", "counscr01", "counscr01", "counscr01", "counscr01", "benitar01", "benitar01", "benitar01", "benitar01", "benitar01", "benitar01", "benitar01", "benitar01", "benitar01", "benitar01", "benitar01", "benitar01", "benitar01", "benitar01", "benitar01", "benitar01", "benitar01", "benitar01", "pujolal01", "pujolal01", "pujolal01", "pujolal01", "pujolal01", "pujolal01", "pujolal01", "pujolal01", 
+#> "pujolal01", "pujolal01", "pujolal01", "pujolal01", "pujolal01", "pujolal01", "pujolal01", "gonzalu01", "gonzalu01", "gonzalu01", "gonzalu01", "gonzalu01", "gonzalu01", "gonzalu01", "gonzalu01", "gonzalu01", "gonzalu01", "gonzalu01", "gonzalu01", "gonzalu01", "gonzalu01", "gonzalu01", "gonzalu01", "gonzalu01", "gonzalu01", "gonzalu01", "gonzalu01", "aurilri01", "aurilri01", "aurilri01", "aurilri01", "aurilri01", "aurilri01", "aurilri01", "aurilri01", "aurilri01", "aurilri01", "aurilri01", "aurilri01", 
+#> "aurilri01", "aurilri01", "aurilri01", "aurilri01", "muldema01", "muldema01", "muldema01", "muldema01", "muldema01", "muldema01", "muldema01", "muldema01", "muldema01", "nenro01", "nenro01", "nenro01", "nenro01", "nenro01", "nenro01", "nenro01", "nenro01", "nenro01", "nenro01", "nenro01", "kennead01", "kennead01", "kennead01", "kennead01", "kennead01", "kennead01", "kennead01", "kennead01", "kennead01", "kennead01", "kennead01", "kennead01", "kennead01", "kennead01", "valenbo02", "valenbo02", "valenbo02", 
+#> "valenbo02", "valenbo02", "valenbo02", "valenbo02", "valenbo02", "valenbo02", "valenbo02", "valenbo02", "valenbo02", "zitoba01", "zitoba01", "zitoba01", "zitoba01", "zitoba01", "zitoba01", "zitoba01", "zitoba01", "zitoba01", "zitoba01", "zitoba01", "zitoba01", "zitoba01", "zitoba01", "zitoba01", "molinbe01", "molinbe01", "molinbe01", "molinbe01", "molinbe01", "molinbe01", "molinbe01", "molinbe01", "molinbe01", "molinbe01", "molinbe01", "molinbe01", "molinbe01", "molinbe01", "graveda01", "graveda01", 
+#> "graveda01", "graveda01", "graveda01", "graveda01", "graveda01", "graveda01", "graveda01", "graveda01", "graveda01", "graveda01", "graveda01", "tejadmi01", "tejadmi01", "tejadmi01", "tejadmi01", "tejadmi01", "tejadmi01", "tejadmi01", "tejadmi01", "tejadmi01", "tejadmi01", "tejadmi01", "tejadmi01", "tejadmi01", "tejadmi01", "tejadmi01", "tejadmi01", "tejadmi01", "kochbi01", "kochbi01", "kochbi01", "kochbi01", "kochbi01", "kochbi01", "kochbi01", "hinsker01", "hinsker01", "hinsker01", "hinsker01", "hinsker01", 
+#> "hinsker01", "hinsker01", "hinsker01", "hinsker01", "hinsker01", "hinsker01", "hinsker01", "hinsker01", "hinsker01", "jennija01", "jennija01", "jennija01", "jennija01", "jennija01", "jennija01", "jennija01", "jennija01", "jennija01", "soriaal01", "soriaal01", "soriaal01", "soriaal01", "soriaal01", "soriaal01", "soriaal01", "soriaal01", "soriaal01", "soriaal01", "soriaal01", "soriaal01", "soriaal01", "soriaal01", "soriaal01", "soriaal01", "soriaal01", "anderga01", "anderga01", "anderga01", "anderga01", 
+#> "anderga01", "anderga01", "anderga01", "anderga01", "anderga01", "anderga01", "anderga01", "anderga01", "anderga01", "anderga01", "anderga01", "anderga01", "anderga01", "lowede01", "lowede01", "lowede01", "lowede01", "lowede01", "lowede01", "lowede01", "lowede01", "lowede01", "lowede01", "lowede01", "lowede01", "lowede01", "lowede01", "lowede01", "lowede01", "lowede01", "lowede01", "lowede01", "beckejo02", "beckejo02", "beckejo02", "beckejo02", "beckejo02", "beckejo02", "beckejo02", "beckejo02", 
+#> "beckejo02", "beckejo02", "beckejo02", "beckejo02", "beckejo02", "beckejo02", "beckejo02", "hallaro01", "hallaro01", "hallaro01", "hallaro01", "hallaro01", "hallaro01", "hallaro01", "hallaro01", "hallaro01", "hallaro01", "hallaro01", "hallaro01", "hallaro01", "hallaro01", "hallaro01", "hallaro01", "gagneer01", "gagneer01", "gagneer01", "gagneer01", "gagneer01", "gagneer01", "gagneer01", "gagneer01", "gagneer01", "gagneer01", "gagneer01", "leede02", "leede02", "leede02", "leede02", "leede02", "leede02", 
+#> "leede02", "leede02", "leede02", "leede02", "leede02", "leede02", "leede02", "leede02", "leede02", "leede02", "leede02", "castilu01", "castilu01", "castilu01", "castilu01", "castilu01", "castilu01", "castilu01", "castilu01", "castilu01", "castilu01", "castilu01", "castilu01", "castilu01", "castilu01", "castilu01", "castilu01", "cruzjo02", "cruzjo02", "cruzjo02", "cruzjo02", "cruzjo02", "cruzjo02", "cruzjo02", "cruzjo02", "cruzjo02", "cruzjo02", "cruzjo02", "cruzjo02", "cruzjo02", "cruzjo02", "cruzjo02", 
+#> "foulkke01", "foulkke01", "foulkke01", "foulkke01", "foulkke01", "foulkke01", "foulkke01", "foulkke01", "foulkke01", "foulkke01", "foulkke01", "foulkke01", "berroan01", "berroan01", "berroan01", "berroan01", "berroan01", "berroan01", "berroan01", "berroan01", "berroan01", "berroan01", "willido03", "willido03", "willido03", "willido03", "willido03", "willido03", "willido03", "willido03", "willido03", "willido03", "muellbi02", "muellbi02", "muellbi02", "muellbi02", "muellbi02", "muellbi02", "muellbi02", 
+#> "muellbi02", "muellbi02", "muellbi02", "muellbi02", "muellbi02", "wellsve01", "wellsve01", "wellsve01", "wellsve01", "wellsve01", "wellsve01", "wellsve01", "wellsve01", "wellsve01", "wellsve01", "wellsve01", "wellsve01", "wellsve01", "wellsve01", "wellsve01", "vidrojo01", "vidrojo01", "vidrojo01", "vidrojo01", "vidrojo01", "vidrojo01", "vidrojo01", "vidrojo01", "vidrojo01", "vidrojo01", "vidrojo01", "vidrojo01", "lowelmi01", "lowelmi01", "lowelmi01", "lowelmi01", "lowelmi01", "lowelmi01", "lowelmi01", 
+#> "lowelmi01", "lowelmi01", "lowelmi01", "lowelmi01", "lowelmi01", "lowelmi01", "gilesma01", "gilesma01", "gilesma01", "gilesma01", "gilesma01", "gilesma01", "gilesma01", "wolfra02", "wolfra02", "wolfra02", "wolfra02", "wolfra02", "wolfra02", "wolfra02", "wolfra02", "wolfra02", "wolfra02", "wolfra02", "wolfra02", "wolfra02", "wolfra02", "wolfra02", "wolfra02", "wolfra02", "wolfra02", "ortizda01", "ortizda01", "ortizda01", "ortizda01", "ortizda01", "ortizda01", "ortizda01", "ortizda01", "ortizda01", 
+#> "ortizda01", "ortizda01", "ortizda01", "ortizda01", "ortizda01", "ortizda01", "ortizda01", "ortizda01", "ortizda01", "ortizda01", "santajo01", "santajo01", "santajo01", "santajo01", "santajo01", "santajo01", "santajo01", "santajo01", "santajo01", "santajo01", "santajo01", "santajo01", "izturce01", "izturce01", "izturce01", "izturce01", "izturce01", "izturce01", "izturce01", "izturce01", "izturce01", "izturce01", "izturce01", "izturce01", "izturce01", "izturce01", "izturce01", "izturce01", "crosbbo01", 
+#> "crosbbo01", "crosbbo01", "crosbbo01", "crosbbo01", "crosbbo01", "crosbbo01", "crosbbo01", "crosbbo01", "bayja01", "bayja01", "bayja01", "bayja01", "bayja01", "bayja01", "bayja01", "bayja01", "bayja01", "bayja01", "bayja01", "bayja01", "bayja01", "teixema01", "teixema01", "teixema01", "teixema01", "teixema01", "teixema01", "teixema01", "teixema01", "teixema01", "teixema01", "teixema01", "teixema01", "teixema01", "teixema01", "teixema01", "morame01", "morame01", "morame01", "morame01", "morame01", 
+#> "morame01", "morame01", "morame01", "morame01", "morame01", "morame01", "morame01", "morame01", "morame01", "martivi01", "martivi01", "martivi01", "martivi01", "martivi01", "martivi01", "martivi01", "martivi01", "martivi01", "martivi01", "martivi01", "martivi01", "martivi01", "martivi01", "loretma01", "loretma01", "loretma01", "loretma01", "loretma01", "loretma01", "loretma01", "loretma01", "loretma01", "loretma01", "loretma01", "loretma01", "loretma01", "loretma01", "loretma01", "loretma01", "beltrad01", 
+#> "beltrad01", "beltrad01", "beltrad01", "beltrad01", "beltrad01", "beltrad01", "beltrad01", "beltrad01", "beltrad01", "beltrad01", "beltrad01", "beltrad01", "beltrad01", "beltrad01", "beltrad01", "beltrad01", "beltrad01", "estrajo01", "estrajo01", "estrajo01", "estrajo01", "estrajo01", "estrajo01", "estrajo01", "estrajo01", "abreubo01", "abreubo01", "abreubo01", "abreubo01", "abreubo01", "abreubo01", "abreubo01", "abreubo01", "abreubo01", "abreubo01", "abreubo01", "abreubo01", "abreubo01", "abreubo01", 
+#> "abreubo01", "abreubo01", "abreubo01", "abreubo01", "abreubo01", "abreubo01", "wilsoja02", "wilsoja02", "wilsoja02", "wilsoja02", "wilsoja02", "wilsoja02", "wilsoja02", "wilsoja02", "wilsoja02", "wilsoja02", "wilsoja02", "wilsoja02", "wilsoja02", "wilsoja02", "konerpa01", "konerpa01", "konerpa01", "konerpa01", "konerpa01", "konerpa01", "konerpa01", "konerpa01", "konerpa01", "konerpa01", "konerpa01", "konerpa01", "konerpa01", "konerpa01", "konerpa01", "konerpa01", "konerpa01", "konerpa01", "konerpa01", 
+#> "drewjd01", "drewjd01", "drewjd01", "drewjd01", "drewjd01", "drewjd01", "drewjd01", "drewjd01", "drewjd01", "drewjd01", "drewjd01", "drewjd01", "drewjd01", "drewjd01", "schmija01", "schmija01", "schmija01", "schmija01", "schmija01", "schmija01", "schmija01", "schmija01", "schmija01", "schmija01", "schmija01", "schmija01", "schmija01", "schmija01", "schmija01", "schmija01", "nathajo01", "nathajo01", "nathajo01", "nathajo01", "nathajo01", "nathajo01", "nathajo01", "nathajo01", "nathajo01", "nathajo01", 
+#> "nathajo01", "nathajo01", "nathajo01", "nathajo01", "nathajo01", "colonba01", "colonba01", "colonba01", "colonba01", "colonba01", "colonba01", "colonba01", "colonba01", "colonba01", "colonba01", "colonba01", "colonba01", "colonba01", "colonba01", "colonba01", "colonba01", "colonba01", "colonba01", "colonba01", "carpech01", "carpech01", "carpech01", "carpech01", "carpech01", "carpech01", "carpech01", "carpech01", "carpech01", "carpech01", "carpech01", "carpech01", "carpech01", "carpech01", "carpech01", 
+#> "hudsoor01", "hudsoor01", "hudsoor01", "hudsoor01", "hudsoor01", "hudsoor01", "hudsoor01", "hudsoor01", "hudsoor01", "hudsoor01", "hudsoor01", "hudsoor01", "varitja01", "varitja01", "varitja01", "varitja01", "varitja01", "varitja01", "varitja01", "varitja01", "varitja01", "varitja01", "varitja01", "varitja01", "varitja01", "varitja01", "varitja01", "oswalro01", "oswalro01", "oswalro01", "oswalro01", "oswalro01", "oswalro01", "oswalro01", "oswalro01", "oswalro01", "oswalro01", "oswalro01", "oswalro01", 
+#> "oswalro01", "oswalro01", "cordech01", "cordech01", "cordech01", "cordech01", "cordech01", "cordech01", "cordech01", "streehu01", "streehu01", "streehu01", "streehu01", "streehu01", "streehu01", "streehu01", "streehu01", "streehu01", "streehu01", "streehu01", "streehu01", "howarry01", "howarry01", "howarry01", "howarry01", "howarry01", "howarry01", "howarry01", "howarry01", "howarry01", "howarry01", "howarry01", "howarry01", "ensbemo01", "ensbemo01", "ensbemo01", "ensbemo01", "ensbemo01", "ensbemo01", 
+#> "ensbemo01", "ensbemo01", "ensbemo01", "barremi01", "barremi01", "barremi01", "barremi01", "barremi01", "barremi01", "barremi01", "barremi01", "barremi01", "barremi01", "barremi01", "barremi01", "barremi01", "cabremi01", "cabremi01", "cabremi01", "cabremi01", "cabremi01", "cabremi01", "cabremi01", "cabremi01", "cabremi01", "cabremi01", "cabremi01", "cabremi01", "cabremi01", "leeca01", "leeca01", "leeca01", "leeca01", "leeca01", "leeca01", "leeca01", "leeca01", "leeca01", "leeca01", "leeca01", "leeca01", 
+#> "leeca01", "leeca01", "leeca01", "leeca01", "marquja01", "marquja01", "marquja01", "marquja01", "marquja01", "marquja01", "marquja01", "marquja01", "marquja01", "marquja01", "marquja01", "marquja01", "marquja01", "marquja01", "marquja01", "marquja01", "marquja01", "lopezfe01", "lopezfe01", "lopezfe01", "lopezfe01", "lopezfe01", "lopezfe01", "lopezfe01", "lopezfe01", "lopezfe01", "lopezfe01", "lopezfe01", "lopezfe01", "lopezfe01", "lopezfe01", "lopezfe01", "lopezfe01", "roberbr01", "roberbr01", "roberbr01", 
+#> "roberbr01", "roberbr01", "roberbr01", "roberbr01", "roberbr01", "roberbr01", "roberbr01", "roberbr01", "roberbr01", "roberbr01", "roberbr01", "damonjo01", "damonjo01", "damonjo01", "damonjo01", "damonjo01", "damonjo01", "damonjo01", "damonjo01", "damonjo01", "damonjo01", "damonjo01", "damonjo01", "damonjo01", "damonjo01", "damonjo01", "damonjo01", "damonjo01", "damonjo01", "youngmi02", "youngmi02", "youngmi02", "youngmi02", "youngmi02", "youngmi02", "youngmi02", "youngmi02", "youngmi02", "youngmi02", 
+#> "youngmi02", "youngmi02", "youngmi02", "youngmi02", "youngmi02", "loducpa01", "loducpa01", "loducpa01", "loducpa01", "loducpa01", "loducpa01", "loducpa01", "loducpa01", "loducpa01", "loducpa01", "loducpa01", "loducpa01", "loducpa01", "polanpl01", "polanpl01", "polanpl01", "polanpl01", "polanpl01", "polanpl01", "polanpl01", "polanpl01", "polanpl01", "polanpl01", "polanpl01", "polanpl01", "polanpl01", "polanpl01", "polanpl01", "polanpl01", "polanpl01", "polanpl01", "eckstda01", "eckstda01", "eckstda01", 
+#> "eckstda01", "eckstda01", "eckstda01", "eckstda01", "eckstda01", "eckstda01", "eckstda01", "eckstda01", "lasorto01", "lasorto01", "lasorto01", "johnsji04", "johnsji04", "johnsji04", "johnsji04", "johnsji04", "johnsji04", "johnsji04", "johnsji04", "johnsji04", "johnsji04", "johnsji04", "johnsji04", "webbbr01", "webbbr01", "webbbr01", "webbbr01", "webbbr01", "webbbr01", "webbbr01", "grudzma01", "grudzma01", "grudzma01", "grudzma01", "grudzma01", "grudzma01", "grudzma01", "grudzma01", "grudzma01", "grudzma01", 
+#> "grudzma01", "grudzma01", "grudzma01", "grudzma01", "grudzma01", "grudzma01", "morneju01", "morneju01", "morneju01", "morneju01", "morneju01", "morneju01", "morneju01", "morneju01", "morneju01", "morneju01", "morneju01", "morneju01", "morneju01", "morneju01", "suppaje01", "suppaje01", "suppaje01", "suppaje01", "suppaje01", "suppaje01", "suppaje01", "suppaje01", "suppaje01", "suppaje01", "suppaje01", "suppaje01", "suppaje01", "suppaje01", "suppaje01", "suppaje01", "suppaje01", "suppaje01", "suppaje01", 
+#> "suppaje01", "rodrifr03", "rodrifr03", "rodrifr03", "rodrifr03", "rodrifr03", "rodrifr03", "rodrifr03", "rodrifr03", "rodrifr03", "rodrifr03", "rodrifr03", "rodrifr03", "rodrifr03", "rodrifr03", "rodrifr03", "rodrifr03", "verlaju01", "verlaju01", "verlaju01", "verlaju01", "verlaju01", "verlaju01", "verlaju01", "verlaju01", "verlaju01", "verlaju01", "verlaju01", "ramirha01", "ramirha01", "ramirha01", "ramirha01", "ramirha01", "ramirha01", "ramirha01", "ramirha01", "ramirha01", "ramirha01", "ramirha01", 
+#> "ramirha01", "canoro01", "canoro01", "canoro01", "canoro01", "canoro01", "canoro01", "canoro01", "canoro01", "canoro01", "canoro01", "canoro01", "credejo01", "credejo01", "credejo01", "credejo01", "credejo01", "credejo01", "credejo01", "credejo01", "credejo01", "credejo01", "mauerjo01", "mauerjo01", "mauerjo01", "mauerjo01", "mauerjo01", "mauerjo01", "mauerjo01", "mauerjo01", "mauerjo01", "mauerjo01", "mauerjo01", "mauerjo01", "utleych01", "utleych01", "utleych01", "utleych01", "utleych01", "utleych01", 
+#> "utleych01", "utleych01", "utleych01", "utleych01", "utleych01", "utleych01", "utleych01", "utleych01", "mccanbr01", "mccanbr01", "mccanbr01", "mccanbr01", "mccanbr01", "mccanbr01", "mccanbr01", "mccanbr01", "mccanbr01", "mccanbr01", "mccanbr01", "hollima01", "hollima01", "hollima01", "hollima01", "hollima01", "hollima01", "hollima01", "hollima01", "hollima01", "hollima01", "hollima01", "hollima01", "hollima01", "zambrca01", "zambrca01", "zambrca01", "zambrca01", "zambrca01", "zambrca01", "zambrca01", 
+#> "zambrca01", "zambrca01", "zambrca01", "zambrca01", "zambrca01", "reyesjo01", "reyesjo01", "reyesjo01", "reyesjo01", "reyesjo01", "reyesjo01", "reyesjo01", "reyesjo01", "reyesjo01", "reyesjo01", "reyesjo01", "reyesjo01", "reyesjo01", "reyesjo01", "wrighda03", "wrighda03", "wrighda03", "wrighda03", "wrighda03", "wrighda03", "wrighda03", "wrighda03", "wrighda03", "wrighda03", "wrighda03", "wrighda03", "berkmla01", "berkmla01", "berkmla01", "berkmla01", "berkmla01", "berkmla01", "berkmla01", "berkmla01", 
+#> "berkmla01", "berkmla01", "berkmla01", "berkmla01", "berkmla01", "berkmla01", "berkmla01", "berkmla01", "papeljo01", "papeljo01", "papeljo01", "papeljo01", "papeljo01", "papeljo01", "papeljo01", "papeljo01", "papeljo01", "papeljo01", "papeljo01", "papeljo01", "penaca01", "penaca01", "penaca01", "penaca01", "penaca01", "penaca01", "penaca01", "penaca01", "penaca01", "penaca01", "penaca01", "penaca01", "penaca01", "penaca01", "penaca01", "penaca01", "youngdm01", "youngdm01", "youngdm01", "youngdm01", 
+#> "youngdm01", "youngdm01", "youngdm01", "youngdm01", "youngdm01", "youngdm01", "youngdm01", "youngdm01", "youngdm01", "sabatcc01", "sabatcc01", "sabatcc01", "sabatcc01", "sabatcc01", "sabatcc01", "sabatcc01", "sabatcc01", "sabatcc01", "sabatcc01", "sabatcc01", "sabatcc01", "sabatcc01", "sabatcc01", "sabatcc01", "sabatcc01", "peavyja01", "peavyja01", "peavyja01", "peavyja01", "peavyja01", "peavyja01", "peavyja01", "peavyja01", "peavyja01", "peavyja01", "peavyja01", "peavyja01", "peavyja01", "peavyja01", 
+#> "peavyja01", "peavyja01", "peavyja01", "youklke01", "youklke01", "youklke01", "youklke01", "youklke01", "youklke01", "youklke01", "youklke01", "youklke01", "youklke01", "youklke01", "sizemgr01", "sizemgr01", "sizemgr01", "sizemgr01", "sizemgr01", "sizemgr01", "sizemgr01", "sizemgr01", "sizemgr01", "sizemgr01", "sizemgr01", "sizemgr01", "martiru01", "martiru01", "martiru01", "martiru01", "martiru01", "martiru01", "martiru01", "martiru01", "martiru01", "martiru01", "francje02", "francje02", "francje02", 
+#> "francje02", "francje02", "francje02", "francje02", "francje02", "francje02", "francje02", "francje02", "francje02", "francje02", "francje02", "rowanaa01", "rowanaa01", "rowanaa01", "rowanaa01", "rowanaa01", "rowanaa01", "rowanaa01", "rowanaa01", "rowanaa01", "rowanaa01", "rowanaa01", "rolliji01", "rolliji01", "rolliji01", "rolliji01", "rolliji01", "rolliji01", "rolliji01", "rolliji01", "rolliji01", "rolliji01", "rolliji01", "rolliji01", "rolliji01", "rolliji01", "rolliji01", "rolliji01", "fieldpr01", 
+#> "fieldpr01", "fieldpr01", "fieldpr01", "fieldpr01", "fieldpr01", "fieldpr01", "fieldpr01", "fieldpr01", "fieldpr01", "fieldpr01", "sweenmi01", "sweenmi01", "sweenmi01", "sweenmi01", "sweenmi01", "sweenmi01", "sweenmi01", "sweenmi01", "sweenmi01", "sweenmi01", "sweenmi01", "sweenmi01", "sweenmi01", "sweenmi01", "sweenmi01", "sweenmi01", "sweenmi01", "timlimi01", "timlimi01", "timlimi01", "timlimi01", "timlimi01", "timlimi01", "timlimi01", "timlimi01", "timlimi01", "timlimi01", "timlimi01", "timlimi01", 
+#> "timlimi01", "timlimi01", "timlimi01", "timlimi01", "timlimi01", "timlimi01", "timlimi01", "timlimi01", "timlimi01", "putzjj01", "putzjj01", "putzjj01", "putzjj01", "putzjj01", "putzjj01", "putzjj01", "putzjj01", "putzjj01", "putzjj01", "putzjj01", "putzjj01", "valvejo01", "valvejo01", "valvejo01", "valvejo01", "valvejo01", "valvejo01", "valvejo01", "valvejo01", "valvejo01", "valvejo01", "valvejo01", "valvejo01", "pedrodu01", "pedrodu01", "pedrodu01", "pedrodu01", "pedrodu01", "pedrodu01", "pedrodu01", 
+#> "pedrodu01", "pedrodu01", "pedrodu01", "braunry02", "braunry02", "braunry02", "braunry02", "braunry02", "braunry02", "braunry02", "braunry02", "braunry02", "owingmi01", "owingmi01", "owingmi01", "owingmi01", "owingmi01", "owingmi01", "owingmi01", "borowjo01", "borowjo01", "borowjo01", "borowjo01", "borowjo01", "borowjo01", "borowjo01", "borowjo01", "borowjo01", "borowjo01", "borowjo01", "borowjo01", "borowjo01", "borowjo01", "garzama01", "garzama01", "garzama01", "garzama01", "garzama01", "garzama01", 
+#> "garzama01", "garzama01", "garzama01", "garzama01", "garzama01", "hamelco01", "hamelco01", "hamelco01", "hamelco01", "hamelco01", "hamelco01", "hamelco01", "hamelco01", "hamelco01", "hamelco01", "hamelco01", "leecl02", "leecl02", "leecl02", "leecl02", "leecl02", "leecl02", "leecl02", "leecl02", "leecl02", "leecl02", "leecl02", "leecl02", "leecl02", "leecl02", "leecl02", "lidgebr01", "lidgebr01", "lidgebr01", "lidgebr01", "lidgebr01", "lidgebr01", "lidgebr01", "lidgebr01", "lidgebr01", "lidgebr01", 
+#> "lidgebr01", "linceti01", "linceti01", "linceti01", "linceti01", "linceti01", "linceti01", "linceti01", "linceti01", "linceti01", "gonzaad01", "gonzaad01", "gonzaad01", "gonzaad01", "gonzaad01", "gonzaad01", "gonzaad01", "gonzaad01", "gonzaad01", "gonzaad01", "gonzaad01", "gonzaad01", "gonzaad01", "phillbr01", "phillbr01", "phillbr01", "phillbr01", "phillbr01", "phillbr01", "phillbr01", "phillbr01", "phillbr01", "phillbr01", "phillbr01", "phillbr01", "phillbr01", "phillbr01", "molinya01", "molinya01", 
+#> "molinya01", "molinya01", "molinya01", "molinya01", "molinya01", "molinya01", "molinya01", "molinya01", "molinya01", "molinya01", "mclouna01", "mclouna01", "mclouna01", "mclouna01", "mclouna01", "mclouna01", "mclouna01", "mclouna01", "mclouna01", "mclouna01", "mclouna01", "mclouna01", "victosh01", "victosh01", "victosh01", "victosh01", "victosh01", "victosh01", "victosh01", "victosh01", "victosh01", "victosh01", "victosh01", "victosh01", "victosh01", "victosh01", "ramirar01", "ramirar01", "ramirar01", 
+#> "ramirar01", "ramirar01", "ramirar01", "ramirar01", "ramirar01", "ramirar01", "ramirar01", "ramirar01", "ramirar01", "ramirar01", "ramirar01", "ramirar01", "ramirar01", "ramirar01", "ramirar01", "ramirar01", "ramirar01", "lestejo01", "lestejo01", "lestejo01", "lestejo01", "lestejo01", "lestejo01", "lestejo01", "lestejo01", "lestejo01", "lestejo01", "lestejo01", "longoev01", "longoev01", "longoev01", "longoev01", "longoev01", "longoev01", "longoev01", "longoev01", "sotoge01", "sotoge01", "sotoge01", 
+#> "sotoge01", "sotoge01", "sotoge01", "sotoge01", "sotoge01", "sotoge01", "sotoge01", "sotoge01", "sotoge01", "sotoge01", "huffau01", "huffau01", "huffau01", "huffau01", "huffau01", "huffau01", "huffau01", "huffau01", "huffau01", "huffau01", "huffau01", "huffau01", "huffau01", "huffau01", "huffau01", "hamiljo03", "hamiljo03", "hamiljo03", "hamiljo03", "hamiljo03", "hamiljo03", "hamiljo03", "hamiljo03", "hamiljo03", "quentca01", "quentca01", "quentca01", "quentca01", "quentca01", "quentca01", "quentca01", 
+#> "quentca01", "quentca01", "ludwiry01", "ludwiry01", "ludwiry01", "ludwiry01", "ludwiry01", "ludwiry01", "ludwiry01", "ludwiry01", "ludwiry01", "ludwiry01", "ludwiry01", "ludwiry01", "ludwiry01", "ludwiry01", "ludwiry01", "crawfca02", "crawfca02", "crawfca02", "crawfca02", "crawfca02", "crawfca02", "crawfca02", "crawfca02", "crawfca02", "crawfca02", "crawfca02", "crawfca02", "crawfca02", "crawfca02", "hillaa01", "hillaa01", "hillaa01", "hillaa01", "hillaa01", "hillaa01", "hillaa01", "hillaa01", "hillaa01", 
+#> "hillaa01", "hillaa01", "hillaa01", "carpech02", "carpech02", "greinza01", "greinza01", "greinza01", "greinza01", "greinza01", "greinza01", "greinza01", "greinza01", "greinza01", "greinza01", "greinza01", "greinza01", "greinza01", "jonesad01", "jonesad01", "jonesad01", "jonesad01", "jonesad01", "jonesad01", "jonesad01", "jonesad01", "jonesad01", "jonesad01", "buehrma01", "buehrma01", "buehrma01", "buehrma01", "buehrma01", "buehrma01", "buehrma01", "buehrma01", "buehrma01", "buehrma01", "buehrma01", 
+#> "buehrma01", "buehrma01", "buehrma01", "buehrma01", "buehrma01", "zimmery01", "zimmery01", "zimmery01", "zimmery01", "zimmery01", "zimmery01", "zimmery01", "zimmery01", "zimmery01", "zimmery01", "zimmery01", "bournmi01", "bournmi01", "bournmi01", "bournmi01", "bournmi01", "bournmi01", "bournmi01", "bournmi01", "bournmi01", "bournmi01", "bournmi01", "bournmi01", "kempma01", "kempma01", "kempma01", "kempma01", "kempma01", "kempma01", "kempma01", "kempma01", "kempma01", "kempma01", "wainwad01", "wainwad01", 
+#> "wainwad01", "wainwad01", "wainwad01", "wainwad01", "wainwad01", "wainwad01", "wainwad01", "wainwad01", "teahema01", "teahema01", "teahema01", "teahema01", "teahema01", "teahema01", "teahema01", "teahema01", "bellhe01", "bellhe01", "bellhe01", "bellhe01", "bellhe01", "bellhe01", "bellhe01", "bellhe01", "bellhe01", "bellhe01", "bellhe01", "bailean01", "bailean01", "bailean01", "bailean01", "bailean01", "bailean01", "coghlch01", "coghlch01", "coghlch01", "coghlch01", "coghlch01", "coghlch01", "coghlch01", 
+#> "lindad01", "lindad01", "lindad01", "lindad01", "lindad01", "lindad01", "lindad01", "lindad01", "lindad01", "lindad01", "ethiean01", "ethiean01", "ethiean01", "ethiean01", "ethiean01", "ethiean01", "ethiean01", "ethiean01", "ethiean01", "ethiean01", "frankry01", "frankry01", "frankry01", "frankry01", "frankry01", "frankry01", "frankry01", "frankry01", "frankry01", "frankry01", "frankry01", "frankry01", "frankry01", "matsuhi01", "matsuhi01", "matsuhi01", "matsuhi01", "matsuhi01", "matsuhi01", "matsuhi01", 
+#> "matsuhi01", "matsuhi01", "matsuhi01", "liriafr01", "liriafr01", "liriafr01", "liriafr01", "liriafr01", "liriafr01", "liriafr01", "liriafr01", "liriafr01", "liriafr01", "liriafr01", "hudsoti01", "hudsoti01", "hudsoti01", "hudsoti01", "hudsoti01", "hudsoti01", "hudsoti01", "hudsoti01", "hudsoti01", "hudsoti01", "hudsoti01", "hudsoti01", "hudsoti01", "hudsoti01", "hudsoti01", "hudsoti01", "hudsoti01", "hernafe02", "hernafe02", "hernafe02", "hernafe02", "hernafe02", "hernafe02", "hernafe02", "hernafe02", 
+#> "hernafe02", "hernafe02", "hernafe02", "gutiefr01", "gutiefr01", "gutiefr01", "gutiefr01", "gutiefr01", "gutiefr01", "gutiefr01", "gutiefr01", "gutiefr01", "gutiefr01", "gonzaca01", "gonzaca01", "gonzaca01", "gonzaca01", "gonzaca01", "gonzaca01", "gonzaca01", "gonzaca01", "arroybr01", "arroybr01", "arroybr01", "arroybr01", "arroybr01", "arroybr01", "arroybr01", "arroybr01", "arroybr01", "arroybr01", "arroybr01", "arroybr01", "arroybr01", "arroybr01", "arroybr01", "tulowtr01", "tulowtr01", "tulowtr01", 
+#> "tulowtr01", "tulowtr01", "tulowtr01", "tulowtr01", "tulowtr01", "tulowtr01", "tulowtr01", "tulowtr01", "bautijo02", "bautijo02", "bautijo02", "bautijo02", "bautijo02", "bautijo02", "bautijo02", "bautijo02", "bautijo02", "bautijo02", "bautijo02", "bautijo02", "bautijo02", "bautijo02", "bautijo02", "bautijo02", "vottojo01", "vottojo01", "vottojo01", "vottojo01", "vottojo01", "vottojo01", "vottojo01", "vottojo01", "vottojo01", "rossco01", "rossco01", "rossco01", "rossco01", "rossco01", "rossco01", 
+#> "rossco01", "rossco01", "rossco01", "rossco01", "rossco01", "rossco01", "rossco01", "rossco01", "rossco01", "wakefti01", "wakefti01", "wakefti01", "wakefti01", "wakefti01", "wakefti01", "wakefti01", "wakefti01", "wakefti01", "wakefti01", "wakefti01", "wakefti01", "wakefti01", "wakefti01", "wakefti01", "wakefti01", "wakefti01", "wakefti01", "wakefti01", "soriara01", "soriara01", "soriara01", "soriara01", "soriara01", "soriara01", "soriara01", "soriara01", "soriara01", "soriara01", "soriara01", "soriara01", 
+#> "soriara01", "soriara01", "felizne01", "felizne01", "felizne01", "felizne01", "felizne01", "felizne01", "felizne01", "felizne01", "poseybu01", "poseybu01", "poseybu01", "poseybu01", "poseybu01", "poseybu01", "poseybu01", "ramiral03", "ramiral03", "ramiral03", "ramiral03", "ramiral03", "ramiral03", "ramiral03", "ramiral03", "ugglada01", "ugglada01", "ugglada01", "ugglada01", "ugglada01", "ugglada01", "ugglada01", "ugglada01", "ugglada01", "ugglada01", "ugglada01", "gallayo01", "gallayo01", "gallayo01", 
+#> "gallayo01", "gallayo01", "gallayo01", "gallayo01", "gallayo01", "gallayo01", "cruzne02", "cruzne02", "cruzne02", "cruzne02", "cruzne02", "cruzne02", "cruzne02", "cruzne02", "cruzne02", "cruzne02", "cruzne02", "freesda01", "freesda01", "freesda01", "freesda01", "freesda01", "freesda01", "freesda01", "ellsbja01", "ellsbja01", "ellsbja01", "ellsbja01", "ellsbja01", "ellsbja01", "ellsbja01", "ellsbja01", "ellsbja01", "kershcl01", "kershcl01", "kershcl01", "kershcl01", "kershcl01", "kershcl01", "kershcl01", 
+#> "kershcl01", "wietema01", "wietema01", "wietema01", "wietema01", "wietema01", "wietema01", "wietema01", "gordoal01", "gordoal01", "gordoal01", "gordoal01", "gordoal01", "gordoal01", "gordoal01", "gordoal01", "gordoal01", "markani01", "markani01", "markani01", "markani01", "markani01", "markani01", "markani01", "markani01", "markani01", "markani01", "aybarer01", "aybarer01", "aybarer01", "aybarer01", "aybarer01", "aybarer01", "aybarer01", "aybarer01", "aybarer01", "aybarer01", "parrage01", "parrage01", 
+#> "parrage01", "parrage01", "parrage01", "parrage01", "parrage01", "parrage01", "parrage01", "butlebi03", "butlebi03", "butlebi03", "butlebi03", "butlebi03", "butlebi03", "butlebi03", "butlebi03", "butlebi03", "axforjo01", "axforjo01", "axforjo01", "axforjo01", "axforjo01", "axforjo01", "axforjo01", "axforjo01", "axforjo01", "hellije01", "hellije01", "hellije01", "hellije01", "hellije01", "hellije01", "kimbrcr01", "kimbrcr01", "kimbrcr01", "kimbrcr01", "kimbrcr01", "kimbrcr01", "avilaal01", "avilaal01", 
+#> "avilaal01", "avilaal01", "avilaal01", "avilaal01", "avilaal01", "grandcu01", "grandcu01", "grandcu01", "grandcu01", "grandcu01", "grandcu01", "grandcu01", "grandcu01", "grandcu01", "grandcu01", "grandcu01", "grandcu01", "cabreas01", "cabreas01", "cabreas01", "cabreas01", "cabreas01", "cabreas01", "cabreas01", "cabreas01", "cabreas01", "cabreas01", "uptonju01", "uptonju01", "uptonju01", "uptonju01", "uptonju01", "uptonju01", "uptonju01", "uptonju01", "uptonju01", "hudsoda01", "hudsoda01", "hudsoda01", 
+#> "hudsoda01", "hudsoda01", "hudsoda01", "hudsoda01", "youngde03", "youngde03", "youngde03", "youngde03", "youngde03", "youngde03", "youngde03", "youngde03", "youngde03", "youngde03", "youngde03", "youngde03", "cabreme01", "cabreme01", "cabreme01", "cabreme01", "cabreme01", "cabreme01", "cabreme01", "cabreme01", "cabreme01", "cabreme01", "cabreme01", "sandopa01", "sandopa01", "sandopa01", "sandopa01", "sandopa01", "sandopa01", "sandopa01", "sandopa01", "dickera01", "dickera01", "dickera01", "dickera01", 
+#> "dickera01", "dickera01", "dickera01", "dickera01", "dickera01", "dickera01", "dickera01", "dickera01", "dickera01", "rodnefe01", "rodnefe01", "rodnefe01", "rodnefe01", "rodnefe01", "rodnefe01", "rodnefe01", "rodnefe01", "rodnefe01", "rodnefe01", "rodnefe01", "rodnefe01", "rodnefe01", "rodnefe01", "priceda01", "priceda01", "priceda01", "priceda01", "priceda01", "priceda01", "priceda01", "priceda01", "priceda01", "priceda01", "reddijo01", "reddijo01", "reddijo01", "reddijo01", "reddijo01", "reddijo01", 
+#> "reddijo01", "hardyjj01", "hardyjj01", "hardyjj01", "hardyjj01", "hardyjj01", "hardyjj01", "hardyjj01", "hardyjj01", "hardyjj01", "hardyjj01", "hardyjj01", "larocad01", "larocad01", "larocad01", "larocad01", "larocad01", "larocad01", "larocad01", "larocad01", "larocad01", "larocad01", "larocad01", "larocad01", "larocad01", "larocad01", "barneda01", "barneda01", "barneda01", "barneda01", "barneda01", "barneda01", "barneda01", "barneda01", "headlch01", "headlch01", "headlch01", "headlch01", "headlch01", 
+#> "headlch01", "headlch01", "headlch01", "headlch01", "headlch01", "mccutan01", "mccutan01", "mccutan01", "mccutan01", "mccutan01", "mccutan01", "mccutan01", "heywaja01", "heywaja01", "heywaja01", "heywaja01", "heywaja01", "heywaja01", "scutama01", "scutama01", "scutama01", "scutama01", "scutama01", "scutama01", "scutama01", "scutama01", "scutama01", "scutama01", "scutama01", "scutama01", "scutama01", "scutama01", "troutmi01", "troutmi01", "troutmi01", "troutmi01", "troutmi01", "harpebr03", "harpebr03", 
+#> "harpebr03", "harpebr03", "pierzaj01", "pierzaj01", "pierzaj01", "pierzaj01", "pierzaj01", "pierzaj01", "pierzaj01", "pierzaj01", "pierzaj01", "pierzaj01", "pierzaj01", "pierzaj01", "pierzaj01", "pierzaj01", "pierzaj01", "pierzaj01", "pierzaj01", "pierzaj01", "pierzaj01", "willijo03", "willijo03", "willijo03", "willijo03", "willijo03", "willijo03", "willijo03", "willijo03", "willijo03", "willijo03", "willijo03", "willijo03", "braunry01", "braunry01", "bruceja01", "bruceja01", "bruceja01", "bruceja01", 
+#> "bruceja01", "bruceja01", "bruceja01", "bruceja01", "strasst01", "strasst01", "strasst01", "strasst01", "strasst01", "strasst01", "desmoia01", "desmoia01", "desmoia01", "desmoia01", "desmoia01", "desmoia01", "desmoia01", "ueharko01", "ueharko01", "ueharko01", "ueharko01", "ueharko01", "ueharko01", "ueharko01", "ueharko01", "scherma01", "scherma01", "scherma01", "scherma01", "scherma01", "scherma01", "scherma01", "scherma01", "hosmeer01", "hosmeer01", "hosmeer01", "hosmeer01", "hosmeer01", "machama01", 
+#> "machama01", "machama01", "machama01", "perezsa02", "perezsa02", "perezsa02", "perezsa02", "perezsa02", "goldspa01", "goldspa01", "goldspa01", "goldspa01", "goldspa01", "arenano01", "arenano01", "arenano01", "gomezca01", "gomezca01", "gomezca01", "gomezca01", "gomezca01", "gomezca01", "gomezca01", "gomezca01", "gomezca01", "gomezca01", "simmoan01", "simmoan01", "simmoan01", "simmoan01", "wachami01", "wachami01", "wachami01", "myerswi01", "myerswi01", "myerswi01", "fernajo02", "fernajo02", "fernajo02", 
+#> "davisch02", "davisch02", "davisch02", "davisch02", "davisch02", "davisch02", "davisch02", "davisch02", "davisch02", "carpema01", "carpema01", "carpema01", "carpema01", "carpema01", "alvarpe01", "alvarpe01", "alvarpe01", "alvarpe01", "alvarpe01", "alvarpe01", "cuddymi01", "cuddymi01", "cuddymi01", "cuddymi01", "cuddymi01", "cuddymi01", "cuddymi01", "cuddymi01", "cuddymi01", "cuddymi01", "cuddymi01", "cuddymi01", "cuddymi01", "cuddymi01", "cuddymi01", "cainlo01", "cainlo01", "cainlo01", "cainlo01", 
+#> "cainlo01", "cainlo01", "rizzoan01", "rizzoan01", "rizzoan01", "rizzoan01", "rizzoan01", "youngch03", "youngch03", "youngch03", "youngch03", "youngch03", "youngch03", "youngch03", "youngch03", "youngch03", "youngch03", "youngch03", "mcgehca01", "mcgehca01", "mcgehca01", "mcgehca01", "mcgehca01", "mcgehca01", "mcgehca01", "mcgehca01", "mcgehca01", "klubeco01", "klubeco01", "klubeco01", "klubeco01", "klubeco01", "seageky01", "seageky01", "seageky01", "seageky01", "seageky01", "keuchda01", "keuchda01", 
+#> "keuchda01", "keuchda01", "lemahdj01", "lemahdj01", "lemahdj01", "lemahdj01", "lemahdj01", "lagarju01", "lagarju01", "lagarju01", "yelicch01", "yelicch01", "yelicch01", "stantmi03", "stantmi03", "stantmi03", "stantmi03", "stantmi03", "stantmi03", "bumgama01", "bumgama01", "bumgama01", "bumgama01", "bumgama01", "bumgama01", "bumgama01", "abreujo02", "abreujo02", "degroja01", "degroja01", "altuvjo01", "altuvjo01", "altuvjo01", "altuvjo01", "altuvjo01", "gomesya01", "gomesya01", "gomesya01", "gomesya01", 
+#> "brantmi02", "brantmi02", "brantmi02", "brantmi02", "brantmi02", "brantmi02", "brantmi02", "walkene01", "walkene01", "walkene01", "walkene01", "walkene01", "walkene01", "walkene01", "rendoan01", "rendoan01", "rendoan01", "escobal02", "escobal02", "escobal02", "escobal02", "escobal02", "escobal02", "escobal02", "escobal02", "harvema01", "harvema01", "harvema01", "arrieja01", "arrieja01", "arrieja01", "arrieja01", "arrieja01", "arrieja01", "arrieja01", "kiermke01", "kiermke01", "kiermke01", "cespeyo01", 
+#> "cespeyo01", "cespeyo01", "cespeyo01", "cespeyo01", "cespeyo01", "calhoko01", "calhoko01", "calhoko01", "calhoko01", "gordode01", "gordode01", "gordode01", "gordode01", "gordode01", "polloaj01", "polloaj01", "polloaj01", "polloaj01", "martest01", "martest01", "martest01", "martest01", "crawfbr01", "crawfbr01", "crawfbr01", "crawfbr01", "crawfbr01", "donaljo02", "donaljo02", "donaljo02", "donaljo02", "donaljo02", "murphda08", "murphda08", "murphda08", "murphda08", "murphda08", "murphda08", "murphda08", 
+#> "correca01", "bryankr01", "moralke01", "moralke01", "moralke01", "moralke01", "moralke01", "moralke01", "moralke01", "moralke01", "moralke01", "moralke01", "martijd02", "martijd02", "martijd02", "martijd02", "martijd02", "bogaexa01", "bogaexa01", "bogaexa01") x c(1874, 1875, 1876, 1877, 1878, 1879, 1880, 1881, 1882, 1884, 1884, 1872, 1873, 1874, 1875, 1876, 1877, 1878, 1879, 1880, 1881, 1882, 1883, 1884, 1885, 1886, 1887, 1888, 1889, 1890, 1890, 1891, 1882, 1883, 1884, 1885, 1886, 1887, 1888, 1889, 1890, 1880, 1881, 1882, 1883, 1884, 1885, 1886, 1887, 1888, 1889, 1890, 1891, 1883, 1884, 1885, 1886, 1887, 1888, 1889, 1890, 1891, 1892, 1880, 1881, 1882, 1883, 1884, 1885, 1886, 1887, 1888, 1889, 1890, 1891, 1891, 1892, 1893, 1882, 1884, 1885, 1886, 1887, 1888, 
+#> 1889, 1890, 1891, 1892, 1892, 1893, 1894, 1889, 1890, 1891, 1892, 1893, 1894, 1895, 1897, 1898, 1901, 1888, 1889, 1890, 1891, 1892, 1893, 1894, 1895, 1896, 1897, 1898, 1899, 1900, 1901, 1904, 1905, 1906, 1890, 1891, 1892, 1893, 1894, 1895, 1896, 1897, 1898, 1899, 1900, 1901, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1911, 1896, 1897, 1898, 1899, 1900, 1901, 1902, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1897, 1899, 1900, 1901, 1901, 
+#> 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1900, 1901, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1916, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1913, 1914, 1914, 1915, 1916, 1917, 1918, 1919, 1907, 1908, 1909, 1910, 1910, 1911, 1912, 1913, 1914, 1915, 1896, 1897, 1898, 1899, 1900, 1901, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1912, 1899, 1900, 1901, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 
+#> 1914, 1916, 1899, 1900, 1901, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1903, 1905, 1906, 1907, 1908, 1909, 1910, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1898, 1899, 1900, 1901, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1915, 1916, 1918, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 
+#> 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1894, 1895, 1896, 1897, 1898, 1899, 1900, 1901, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1897, 1900, 1901, 1902, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1900, 1901, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1910, 1911, 1911, 1912, 1913, 1899, 1900, 1901, 1902, 1903, 1904, 1904, 1905, 
+#> 1906, 1908, 1911, 1911, 1912, 1914, 1894, 1895, 1896, 1897, 1898, 1899, 1900, 1901, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1913, 1914, 1915, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1914, 1915, 1916, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1897, 1898, 1899, 1900, 1901, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1894, 1895, 1896, 1897, 1898, 1899, 1900, 1901, 1902, 1903, 1904, 
+#> 1905, 1906, 1907, 1908, 1909, 1911, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1917, 1922, 1929, 1898, 1899, 1900, 1901, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1913, 1914, 1915, 1916, 1917, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1916, 1917, 1917, 1918, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 
+#> 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1906, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1904, 1905, 1905, 1905, 1908, 1909, 1910, 1911, 1912, 1931, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1901, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 
+#> 1922, 1923, 1924, 1925, 1926, 1927, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1913, 1914, 1915, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1917, 1918, 1919, 1920, 1921, 1922, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1921, 1922, 1923, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1906, 1907, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 
+#> 1926, 1898, 1899, 1900, 1901, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1898, 1899, 1900, 1901, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1912, 1913, 1914, 1915, 1918, 1904, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1913, 1914, 1915, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1912, 1913, 1914, 1915, 1916, 1916, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 
+#> 1919, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1920, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1925, 1904, 1907, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1918, 1918, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1917, 1918, 1919, 1909, 1910, 1911, 1912, 1912, 1914, 1915, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1916, 1917, 1918, 1919, 1921, 1922, 1906, 1909, 
+#> 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1925, 1911, 1912, 1913, 1914, 1914, 1915, 1916, 1918, 1925, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1915, 1916, 1917, 1918, 1919, 1920, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1915, 1916, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1917, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1926, 1927, 1928, 1929, 1930, 1910, 1911, 
+#> 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1916, 1917, 1918, 1919, 1920, 1903, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1908, 1909, 1910, 1911, 
+#> 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1921, 1922, 1923, 1923, 1924, 1902, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1915, 1916, 1918, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1916, 1917, 1918, 1919, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1912, 1913, 1914, 1915, 
+#> 1916, 1917, 1918, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1903, 1905, 1906, 1907, 1908, 1908, 1909, 1910, 1911, 1913, 1914, 1915, 1915, 1917, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1915, 1916, 1917, 1919, 1912, 1913, 1914, 1915, 1916, 1908, 1909, 1909, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 
+#> 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1924, 1925, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1935, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1929, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 
+#> 1913, 1914, 1915, 1919, 1913, 1914, 1915, 1916, 1917, 1918, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1912, 1913, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1915, 1916, 1917, 1918, 1919, 1920, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1919, 1912, 1913, 1914, 1915, 1916, 1917, 
+#> 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1924, 1925, 1926, 1927, 1928, 1928, 1929, 1930, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1908, 1909, 1910, 1911, 1911, 1912, 1913, 1914, 1915, 1916, 1916, 1917, 1918, 1919, 1919, 1920, 1915, 1916, 1917, 1918, 1919, 
+#> 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1933, 1934, 1935, 1936, 1937, 1910, 1911, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1919, 1920, 1921, 1922, 1923, 1923, 1924, 1925, 1929, 1930, 1912, 1914, 1915, 1916, 1917, 1919, 1919, 1920, 1921, 1921, 1922, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1915, 1916, 1917, 1918, 1919, 1920, 1905, 1908, 1909, 1910, 1911, 1912, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1912, 1913, 1914, 1915, 1916, 
+#> 1917, 1918, 1919, 1920, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1913, 1914, 1915, 1916, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1931, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1926, 1927, 1928, 1929, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1926, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 
+#> 1922, 1923, 1924, 1925, 1927, 1928, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1908, 1910, 1911, 1912, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1930, 1931, 1932, 1933, 1933, 1934, 1934, 1934, 1910, 1912, 1913, 1913, 1914, 
+#> 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1909, 1911, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1925, 1925, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1923, 1924, 1925, 1926, 1927, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1912, 1916, 1917, 1918, 1919, 1920, 1921, 
+#> 1922, 1923, 1912, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1925, 1926, 1926, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 
+#> 1915, 1916, 1917, 1918, 1919, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1915, 1916, 1917, 1917, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1930, 1932, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1915, 1916, 1917, 1918, 1919, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1926, 1927, 1927, 1928, 1929, 1917, 1918, 
+#> 1919, 1920, 1921, 1922, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1931, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1926, 1927, 1927, 1928, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1912, 1913, 1914, 1915, 1916, 1917, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1917, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1926, 1927, 1913, 1915, 1916, 1917, 1918, 
+#> 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1915, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1934, 1914, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1932, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1933, 1933, 1934, 1936, 1915, 1916, 1917, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1926, 1927, 1928, 1929, 1930, 1920, 1921, 1922, 1923, 1924, 
+#> 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1916, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1925, 1926, 1927, 1928, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1934, 1935, 1914, 1915, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1929, 1930, 1915, 
+#> 1915, 1918, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1934, 1935, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1933, 1934, 1913, 1914, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1915, 1916, 1917, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1923, 1923, 1924, 1925, 1926, 1927, 1930, 1931, 1932, 1933, 1912, 1913, 1914, 1915, 1915, 1916, 1917, 1919, 
+#> 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1937, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 
+#> 1939, 1915, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1931, 1932, 1933, 1934, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1939, 1940, 1941, 1943, 1944, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 
+#> 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1946, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1935, 1936, 1937, 1938, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1935, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1919, 1920, 1921, 1922, 1923, 1923, 1924, 1924, 1925, 1926, 1927, 1928, 1928, 1929, 1930, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1930, 1931, 
+#> 1931, 1932, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1928, 1929, 1929, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1931, 1932, 1933, 1934, 1935, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1938, 1939, 1918, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1924, 1925, 1926, 
+#> 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1934, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1927, 1928, 1929, 1930, 1921, 1925, 1926, 1927, 1928, 1929, 1930, 1930, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1939, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 
+#> 1927, 1928, 1929, 1930, 1930, 1931, 1931, 1932, 1932, 1933, 1934, 1935, 1936, 1937, 1937, 1938, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1932, 1933, 1934, 1935, 1935, 1936, 1937, 1937, 1923, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1918, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1941, 
+#> 1942, 1943, 1944, 1944, 1945, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1923, 1924, 1925, 1926, 1927, 1928, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1941, 1941, 1942, 1944, 1944, 1945, 1926, 1927, 1927, 1928, 1929, 1930, 1930, 1931, 1932, 1933, 1934, 1934, 1935, 1936, 1922, 1928, 1929, 1930, 1931, 1923, 1924, 1925, 1926, 1927, 1927, 
+#> 1928, 1929, 1930, 1930, 1931, 1932, 1933, 1934, 1935, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1937, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1930, 1931, 1932, 1932, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1921, 1922, 1923, 1924, 1925, 1927, 1928, 1929, 1930, 1931, 1931, 1932, 1933, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 
+#> 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1935, 1936, 1936, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1937, 1938, 1938, 1939, 1940, 1941, 1927, 1928, 1929, 1930, 1931, 1932, 1932, 1933, 1934, 1934, 1935, 1936, 
+#> 1938, 1939, 1939, 1940, 1946, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1919, 1920, 1922, 1923, 1928, 1929, 1930, 1931, 1932, 1933, 1933, 1934, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1942, 1944, 1945, 1929, 1930, 1931, 1932, 
+#> 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1939, 1940, 1941, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1925, 1926, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1936, 1937, 1938, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1935, 1936, 1937, 1923, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1931, 
+#> 1932, 1933, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1936, 1937, 1938, 1939, 1939, 1940, 1941, 1942, 1943, 1944, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1942, 1943, 1945, 
+#> 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1941, 1942, 1943, 1946, 1946, 1947, 1924, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1933, 1934, 1934, 1935, 1936, 1937, 1930, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1947, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1941, 1942, 1943, 1946, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1946, 1930, 1933, 1934, 1935, 1936, 
+#> 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1946, 1946, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1938, 1939, 1940, 1941, 1942, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1945, 1946, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1937, 1938, 1938, 1939, 1940, 1940, 1928, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 
+#> 1939, 1940, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1940, 1941, 1942, 1943, 1943, 1944, 1945, 1945, 1946, 1947, 1948, 1927, 1928, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1937, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1947, 1948, 1930, 1933, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1942, 1943, 1946, 1947, 1948, 
+#> 1949, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1946, 1930, 1933, 1934, 1935, 1936, 1937, 
+#> 1938, 1939, 1940, 1941, 1945, 1946, 1947, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1944, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1928, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1944, 1931, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1946, 1947, 
+#> 1948, 1949, 1950, 1951, 1934, 1935, 1936, 1937, 1938, 1939, 1939, 1940, 1941, 1941, 1942, 1943, 1944, 1944, 1945, 1945, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1941, 1942, 1943, 1943, 1944, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1946, 1947, 1948, 1949, 1950, 1951, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1945, 1946, 1947, 1948, 1949, 1950, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 
+#> 1943, 1944, 1945, 1946, 1947, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1939, 1940, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1941, 1942, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1932, 1933, 1934, 1935, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1943, 1930, 1931, 1933, 1935, 1936, 1937, 1938, 1939, 1939, 1940, 1928, 1929, 1930, 1931, 1932, 1933, 1933, 1934, 1935, 1936, 1936, 1937, 1938, 1939, 1937, 1938, 1939, 1940, 1940, 1945, 1936, 1937, 1938, 
+#> 1939, 1940, 1941, 1942, 1946, 1947, 1948, 1949, 1949, 1950, 1951, 1952, 1953, 1932, 1933, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1941, 1942, 1943, 1944, 1937, 1938, 1939, 1940, 1941, 1942, 1942, 1943, 1944, 1945, 1931, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1945, 1946, 1947, 1928, 1929, 1930, 1931, 1931, 1932, 1933, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 
+#> 1941, 1942, 1942, 1943, 1944, 1946, 1947, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1946, 1947, 1948, 1949, 1929, 1930, 1932, 1934, 1935, 1935, 1936, 1937, 1937, 1938, 1939, 1939, 1940, 1941, 1942, 1942, 1943, 1943, 1943, 1944, 1945, 1946, 1946, 1947, 1947, 1948, 1952, 1952, 1953, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1946, 1947, 1948, 1949, 1950, 1951, 1934, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1947, 1948, 1931, 1932, 1933, 1934, 1935, 1936, 
+#> 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1943, 1944, 1945, 1945, 1946, 1947, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1938, 1939, 1940, 1941, 1942, 1943, 1946, 1947, 1948, 1949, 1950, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1936, 1937, 1938, 1939, 1940, 1941, 1945, 1946, 1947, 1948, 1949, 1950, 1951, 
+#> 1952, 1953, 1954, 1955, 1956, 1933, 1934, 1935, 1936, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1939, 1940, 1941, 1942, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1931, 1932, 1933, 1934, 1934, 1935, 1936, 1937, 1938, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1950, 1934, 1935, 1936, 1936, 1937, 1938, 1939, 1940, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1933, 1934, 1935, 1936, 
+#> 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1946, 1947, 1947, 1948, 1948, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1946, 1947, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1943, 1944, 1945, 1933, 1934, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1942, 1943, 1944, 1945, 1945, 1946, 1946, 1947, 1939, 1940, 1941, 1942, 1943, 1945, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1936, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 
+#> 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1936, 1937, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1950, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1946, 1947, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1941, 1942, 1943, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1945, 1946, 1947, 1933, 1934, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1945, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1946, 1929, 1930, 
+#> 1931, 1932, 1933, 1933, 1934, 1935, 1936, 1937, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1940, 1941, 1942, 1943, 1946, 1947, 1948, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1947, 1948, 1949, 1938, 1939, 1940, 1941, 1942, 1940, 1941, 1942, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1937, 1938, 1939, 1939, 1940, 1941, 1942, 1943, 1946, 1947, 1947, 1948, 1949, 1949, 1950, 1938, 1939, 1940, 1941, 1942, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1955, 1956, 1956, 1957, 1958, 1959, 1959, 
+#> 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1946, 1947, 1948, 1949, 1950, 1941, 1942, 1943, 1944, 1946, 1947, 1948, 1949, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1940, 1941, 1942, 1945, 1946, 1947, 1948, 1949, 1950, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 
+#> 1947, 1940, 1941, 1942, 1943, 1944, 1946, 1947, 1948, 1949, 1949, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1953, 1954, 1955, 1955, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1945, 1946, 1947, 1947, 1949, 1941, 1942, 1946, 1947, 1948, 1941, 1942, 1946, 1947, 1948, 1949, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1950, 1952, 1953, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1949, 1950, 1951, 1954, 1942, 1946, 1947, 1948, 1949, 1950, 
+#> 1951, 1952, 1952, 1953, 1954, 1954, 1934, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1947, 1948, 1943, 1946, 1947, 1948, 1949, 1950, 1951, 1951, 1952, 1953, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1952, 1957, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1941, 1943, 1944, 1946, 1947, 1948, 1949, 1950, 1952, 1941, 1942, 1943, 1944, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 
+#> 1959, 1960, 1961, 1962, 1963, 1932, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1949, 1950, 1950, 1951, 1952, 1953, 1954, 1954, 1955, 1956, 1957, 1937, 1938, 1939, 1940, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1946, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1950, 1950, 1951, 1952, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1939, 1940, 1941, 1942, 1943, 
+#> 1944, 1945, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1953, 1942, 1943, 1944, 1945, 1946, 1948, 1949, 1944, 1945, 1946, 1946, 1947, 1948, 1948, 1949, 1950, 1950, 1942, 1943, 1944, 1945, 1946, 1947, 1947, 1948, 1949, 1950, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1946, 1947, 1948, 1949, 1950, 1951, 1931, 1933, 1934, 1935, 1936, 1936, 1937, 1938, 1939, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1938, 1939, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1930, 1931, 1932, 
+#> 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1940, 1942, 1943, 1943, 1944, 1945, 1932, 1933, 1934, 1935, 1935, 1943, 1944, 1945, 1946, 1945, 1946, 1947, 1948, 1949, 1950, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1953, 1954, 1955, 1956, 1957, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1947, 1938, 1939, 1940, 1940, 1941, 1942, 1942, 1942, 1943, 1944, 1945, 1945, 1946, 1947, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 
+#> 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1950, 1951, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1940, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1942, 1943, 1944, 1945, 1945, 1946, 1947, 1948, 1949, 1950, 1950, 1950, 1951, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1937, 1938, 1939, 1940, 1943, 1944, 1945, 1945, 1946, 1947, 1948, 1949, 1942, 1943, 
+#> 1944, 1945, 1946, 1947, 1950, 1951, 1951, 1937, 1938, 1939, 1944, 1945, 1946, 1946, 1936, 1937, 1938, 1943, 1944, 1945, 1946, 1947, 1948, 1939, 1940, 1941, 1942, 1943, 1946, 1947, 1948, 1949, 1950, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1943, 1944, 1945, 1946, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1952, 1953, 1954, 1954, 1955, 1956, 1956, 1957, 1943, 1945, 1946, 1947, 1948, 1949, 1950, 1951, 1951, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 
+#> 1950, 1951, 1952, 1941, 1942, 1943, 1946, 1947, 1948, 1949, 1950, 1951, 1951, 1952, 1953, 1953, 1954, 1955, 1956, 1956, 1943, 1944, 1944, 1945, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1940, 1941, 1942, 1943, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1959, 1942, 1946, 1947, 1948, 1949, 1950, 1951, 1951, 1952, 1953, 1954, 1955, 1955, 1940, 1941, 1942, 1946, 1947, 1948, 1949, 1950, 1951, 
+#> 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1940, 1941, 1942, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1936, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1965, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1937, 1938, 1939, 1940, 1941, 1942, 1946, 1947, 1948, 1949, 1950, 1946, 1947, 1948, 1949, 1950, 1951, 1951, 1952, 1954, 1955, 1956, 
+#> 1942, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1952, 1953, 1955, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1953, 1954, 1955, 1944, 1945, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1953, 1954, 1954, 1956, 1942, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1965, 1942, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1952, 1953, 1954, 1955, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1947, 1948, 1949, 1950, 
+#> 1951, 1952, 1953, 1954, 1955, 1955, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1946, 1947, 1947, 1948, 1949, 1950, 1951, 1952, 1941, 1942, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1955, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1949, 1950, 1951, 1952, 1941, 1942, 1946, 1947, 1948, 1949, 1950, 1951, 1951, 1952, 1952, 1952, 1953, 1953, 1954, 1955, 1956, 1956, 1946, 1948, 1949, 1950, 
+#> 1951, 1952, 1953, 1954, 1955, 1956, 1956, 1957, 1958, 1958, 1959, 1960, 1960, 1944, 1945, 1946, 1947, 1948, 1949, 1950, 1954, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1950, 1950, 1951, 1952, 1952, 1952, 1953, 1954, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1947, 1948, 1949, 1950, 1951, 1952, 1952, 1953, 1954, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1961, 1962, 1963, 1963, 1943, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 
+#> 1963, 1941, 1942, 1943, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1955, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1949, 1950, 1951, 1954, 1955, 1956, 1957, 1958, 1958, 1959, 1960, 1960, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1964, 1965, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1956, 1957, 1941, 1942, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1949, 1950, 1951, 
+#> 1952, 1953, 1954, 1955, 1956, 1957, 1949, 1950, 1951, 1952, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1958, 1959, 1959, 1960, 1961, 1945, 1946, 1947, 1948, 1949, 1950, 1952, 1953, 1953, 1954, 1955, 1956, 1957, 1957, 1944, 1946, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1954, 1955, 1956, 1956, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1947, 1948, 
+#> 1949, 1950, 1951, 1952, 1953, 1954, 1956, 1944, 1945, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1959, 1962, 1950, 1951, 1952, 1954, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1959, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1951, 1952, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1972, 1973, 1945, 1950, 1951, 1952, 1953, 1954, 1955, 1955, 
+#> 1956, 1956, 1957, 1957, 1958, 1958, 1938, 1944, 1945, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1962, 1963, 1964, 1964, 1964, 1941, 1942, 1945, 1948, 1949, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1950, 1952, 1953, 1954, 1955, 1955, 1956, 1957, 1952, 1953, 1954, 1955, 1955, 1956, 1957, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 
+#> 1967, 1968, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1965, 1966, 1966, 1949, 1950, 1951, 1952, 1953, 1954, 1950, 1951, 1952, 1953, 1955, 1956, 1957, 1957, 1958, 1959, 1960, 1961, 1961, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1965, 1966, 1966, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1945, 
+#> 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1956, 1957, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1948, 1949, 1950, 1951, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1958, 1959, 1959, 1959, 1952, 1953, 1954, 1955, 1956, 1957, 1959, 1954, 1955, 1956, 1957, 1958, 1958, 1959, 1960, 1960, 1960, 1962, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1959, 1960, 1961, 1949, 1950, 
+#> 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1959, 1959, 1948, 1949, 1950, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1961, 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 1999, 1953, 1954, 1955, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1966, 1967, 1969, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1955, 1956, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1968, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 
+#> 1961, 1962, 1963, 1964, 1965, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1967, 1968, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1950, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1953, 1954, 1955, 1956, 
+#> 1957, 1958, 1959, 1960, 1961, 1961, 1962, 1963, 1964, 1964, 1965, 1965, 1967, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1974, 1975, 1976, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1967, 1968, 1968, 1969, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 
+#> 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1945, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1963, 1964, 1964, 1965, 1965, 1966, 1967, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1949, 1951, 1951, 1952, 1953, 1954, 
+#> 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1976, 1980, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1964, 1965, 1966, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1965, 1966, 1967, 1967, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1969, 1970, 1971, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1967, 
+#> 1968, 1951, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1963, 1954, 1955, 1956, 1957, 1958, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1964, 1964, 1965, 1954, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1950, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1963, 1963, 1964, 1965, 1966, 1967, 1956, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1967, 1968, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 
+#> 1967, 1968, 1969, 1970, 1971, 1972, 1949, 1950, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1952, 1953, 1954, 1955, 1956, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1950, 1951, 1952, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1961, 1958, 1959, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1972, 1973, 1974, 1951, 1952, 1953, 1954, 1955, 1956, 
+#> 1957, 1958, 1959, 1960, 1961, 1961, 1962, 1963, 1964, 1964, 1965, 1965, 1965, 1966, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1966, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1967, 1968, 1939, 1941, 1942, 1943, 1944, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1963, 1956, 1956, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 
+#> 1965, 1966, 1967, 1967, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1976, 1977, 1978, 1979, 1980, 1951, 1952, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1950, 1951, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 
+#> 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1967, 1967, 1957, 1958, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1956, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1952, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1967, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 
+#> 1968, 1968, 1969, 1970, 1971, 1972, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1972, 1973, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1964, 1965, 1966, 1967, 1967, 1959, 1960, 1961, 1962, 1963, 1964, 1964, 1965, 1966, 1952, 1953, 1954, 1955, 1956, 1956, 1957, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1963, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 
+#> 1975, 1960, 1961, 1962, 1963, 1964, 1966, 1967, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1964, 1964, 1965, 1965, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 
+#> 1975, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1969, 1970, 1971, 1972, 1961, 1962, 1963, 1964, 1965, 1966, 1966, 1967, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1967, 1968, 1968, 1949, 1951, 1952, 1953, 1954, 1955, 1955, 1956, 1957, 
+#> 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1964, 1965, 1966, 1967, 1953, 1954, 1955, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1966, 1955, 1956, 1957, 1959, 1960, 1961, 1962, 1963, 1952, 1953, 1954, 1956, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1968, 1969, 1956, 1957, 1957, 1958, 1959, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1966, 1967, 1956, 1957, 1958, 1959, 1960, 1961, 
+#> 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1979, 1980, 1980, 1981, 1982, 1983, 1961, 1962, 1963, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1969, 1950, 1951, 1952, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 
+#> 1966, 1967, 1968, 1969, 1969, 1970, 1970, 1970, 1971, 1972, 1972, 1973, 1974, 1975, 1976, 1976, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1962, 1963, 1964, 1965, 1966, 1966, 1967, 1967, 1969, 1969, 1953, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1968, 1969, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 
+#> 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1969, 1971, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1971, 1960, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 
+#> 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1984, 1985, 1986, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1970, 1971, 1972, 1973, 1973, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1961, 1962, 1963, 1964, 1965, 
+#> 1966, 1967, 1968, 1969, 1970, 1970, 1971, 1963, 1964, 1965, 1966, 1967, 1968, 1968, 1969, 1969, 1970, 1971, 1972, 1973, 1973, 1974, 1977, 1978, 1979, 1980, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1958, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1958, 1959, 
+#> 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1966, 1969, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1973, 1974, 1975, 1976, 1977, 1977, 1978, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1974, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1961, 1962, 
+#> 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1969, 1970, 1970, 1961, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1971, 1972, 1972, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1963, 1964, 1965, 1966, 1967, 1968, 1968, 1969, 1969, 1969, 1970, 1970, 1958, 1959, 1960, 1961, 
+#> 1962, 1963, 1964, 1964, 1965, 1966, 1967, 1968, 1969, 1969, 1970, 1970, 1971, 1971, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1960, 1961, 1961, 1962, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1973, 1974, 1974, 1974, 1975, 1975, 1976, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1972, 1973, 
+#> 1973, 1955, 1956, 1957, 1960, 1963, 1964, 1965, 1966, 1966, 1967, 1968, 1969, 1970, 1970, 1970, 1971, 1972, 1964, 1965, 1966, 1967, 1968, 1969, 1969, 1970, 1971, 1972, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1973, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1977, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 
+#> 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1959, 1960, 1962, 1963, 1964, 1965, 1966, 1966, 1967, 1968, 1969, 1970, 1970, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1971, 1972, 1973, 1973, 1974, 1964, 1965, 1966, 1967, 1968, 1969, 1969, 1970, 1971, 1972, 1972, 1973, 1974, 1974, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1968, 1969, 1970, 1971, 1972, 1972, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 
+#> 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986, 1961, 1962, 1963, 1964, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1970, 1971, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1979, 1979, 1964, 1965, 1966, 1967, 1968, 1969, 
+#> 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1979, 1980, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986, 1986, 1959, 1960, 1961, 1963, 1964, 1965, 1966, 1967, 
+#> 1968, 1969, 1970, 1971, 1972, 1972, 1973, 1974, 1974, 1975, 1975, 1976, 1977, 1978, 1979, 1980, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1977, 1965, 1966, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1966, 1967, 1968, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1978, 1979, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1972, 1966, 1967, 
+#> 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1972, 1973, 1973, 1974, 1974, 1975, 1966, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 
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+#> 33, 33, 33, 33, 33, 33, 101, 101, 101, 101, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 38, 26, 38, 38, 140, 140, 140, 140, 93, 125, 16, 16, 16, 16, 16, 16, 16, 16, 16, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 140, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 124, 123, 123, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 140, 63, 87, 16, 16, 16, 16, 16, 16, 16, 16, 
+#> 45, 45, 45, 45, 45, 45, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 140, 140, 140, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 89, 89, 125, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 93, 93, 75, 75, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 35, 106, 35, 35, 38, 106, 106, 106, 106, 106, 106, 106, 106, 106, 102, 106, 109, 109, 106, 35, 35, 35, 35, 
+#> 35, 35, 35, 35, 35, 106, 106, 21, 29, 35, 93, 93, 93, 52, 101, 101, 101, 101, 101, 101, 101, 93, 93, 93, 93, 93, 93, 93, 93, 106, 101, 101, 101, 101, 101, 101, 101, 101, 101, 22, 22, 22, 22, 52, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 13, 102, 102, 33, 106, 52, 35, 35, 35, 35, 35, 35, 35, 35, 35, 22, 38, 106, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 26, 26, 26, 38, 38, 38, 35, 35, 35, 35, 106, 93, 93, 101, 101, 101, 101, 101, 101, 101, 93, 93, 93, 93, 93, 93, 38, 
+#> 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 45, 45, 45, 16, 45, 16, 16, 101, 140, 101, 101, 45, 45, 45, 45, 45, 33, 45, 33, 33, 33, 33, 33, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 38, 89, 89, 89, 89, 89, 89, 89, 89, 89, 22, 22, 26, 102, 102, 102, 102, 102, 102, 102, 35, 35, 35, 35, 35, 35, 35, 35, 35, 125, 125, 125, 125, 102, 22, 22, 22, 22, 22, 22, 22, 22, 22, 38, 38, 38, 38, 38, 38, 89, 89, 89, 89, 89, 89, 89, 89, 89, 35, 89, 35, 89, 89, 89, 106, 35, 38, 38, 38, 
+#> 38, 38, 102, 102, 102, 102, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 22, 89, 22, 22, 22, 22, 22, 38, 26, 26, 26, 26, 101, 101, 101, 101, 101, 101, 101, 101, 101, 16, 16, 16, 16, 45, 26, 26, 106, 106, 102, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 101, 45, 45, 45, 45, 45, 45, 140, 140, 140, 140, 140, 140, 140, 140, 140, 52, 52, 52, 125, 125, 22, 125, 89, 89, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 89, 89, 89, 89, 38, 38, 38, 38, 102, 102, 102, 102, 102, 102, 
+#> 102, 35, 35, 35, 38, 106, 106, 106, 106, 106, 106, 125, 125, 125, 89, 89, 89, 89, 89, 89, 89, 101, 101, 101, 101, 101, 16, 16, 16, 93, 93, 93, 93, 93, 123, 123, 123, 123, 101, 52, 106, 140, 140, 140, 45, 140, 45, 45, 45, 45, 63, 21, 87, 101, 101, 101, 101, 101, 101, 101, 101, 16, 101, 16, 16, 16, 106, 106, 106, 106, 106, 16, 33, 140, 102, 102, 102, 102, 102, 102, 102, 102, 102, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 101, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 
+#> 33, 33, 33, 33, 33, 33, 89, 16, 16, 16, 16, 16, 16, 52, 52, 52, 52, 52, 26, 26, 26, 26, 26, 26, 26, 26, 26, 106, 106, 106, 106, 35, 22, 125, 125, 26, 26, 26, 26, 26, 26, 125, 125, 125, 125, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 38, 38, 38, 102, 26, 26, 26, 26, 93, 93, 93, 93, 93, 123, 33, 33, 33, 33, 33, 33, 33, 33, 33, 89, 38, 89, 38, 38, 38, 38, 38, 38, 38, 38, 89, 89, 89, 89, 89, 106, 125, 125, 125, 125, 125, 125, 125, 89, 125, 89, 89, 
+#> 89, 89, 89, 89, 89, 125, 102, 102, 102, 102, 102, 89, 102, 89, 89, 89, 26, 26, 26, 26, 22, 22, 89, 35, 35, 35, 35, 35, 35, 35, 106, 35, 35, 35, 35, 35, 35, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 106, 106, 106, 106, 106, 22, 22, 22, 22, 22, 22, 93, 123, 123, 123, 123, 123, 123, 123, 123, 123, 123, 123, 123, 26, 140, 26, 26, 16, 16, 16, 16, 16, 16, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 26, 89, 89, 26, 26, 89, 89, 89, 38, 38, 38, 89, 89, 26, 26, 35, 35, 
+#> 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 89, 26, 35, 35, 35, 35, 123, 125, 123, 123, 123, 123, 89, 26, 89, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 89, 89, 89, 26, 26, 89, 89, 89, 89, 89, 35, 89, 35, 35, 106, 89, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 52, 16, 16, 16, 16, 16, 33, 33, 33, 33, 33, 33, 33, 33, 33, 45, 45, 45, 45, 45, 45, 45, 45, 45, 123, 123, 102, 102, 102, 102, 102, 102, 102, 35, 35, 35, 35, 33, 63, 87, 38, 89, 38, 38, 38, 38, 38, 38, 38, 38, 
+#> 38, 38, 89, 89, 89, 38, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 22, 106, 22, 22, 22, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 35, 35, 52, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 16, 93, 123, 123, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 33, 33, 33, 33, 33, 93, 93, 93, 93, 140, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 22, 22, 22, 22, 22, 22, 106, 106, 106, 106, 52, 52, 106, 106, 22, 22, 22, 22, 
+#> 22, 22, 22, 22, 22, 89, 106, 106, 26, 125, 125, 35, 35, 125, 93, 106, 125, 45, 45, 45, 93, 93, 93, 93, 93, 93, 93, 93, 93, 140, 140, 140, 140, 140, 33, 89, 89, 102, 102, 102, 102, 125, 125, 125, 125, 125, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 125, 125, 38, 125, 125, 26, 26, 26, 89, 89, 89, 89, 89, 26, 89, 26, 26, 22, 22, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 45, 38, 45, 45, 45, 45, 45, 45, 45, 106, 101, 45, 45, 45, 45, 45, 
+#> 45, 45, 45, 45, 140, 140, 140, 93, 93, 93, 123, 123, 123, 123, 123, 123, 123, 93, 93, 93, 93, 16, 16, 16, 16, 16, 16, 16, 16, 93, 93, 93, 93, 140, 33, 38, 106, 106, 106, 106, 106, 106, 106, 106, 106, 125, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 16, 16, 16, 16, 16, 93, 93, 93, 93, 93, 38, 38, 38, 38, 38, 89, 89, 89, 89, 89, 89, 89, 89, 89, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 89, 89, 89, 106, 89, 89, 
+#> 89, 89, 89, 89, 89, 89, 38, 38, 38, 35, 38, 22, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 26, 26, 26, 26, 26, 89, 89, 89, 89, 89, 89, 89, 38, 89, 35, 38, 35, 35, 101, 101, 101, 101, 101, 16, 93, 93, 93, 93, 93, 93, 93, 26, 52, 101, 101, 101, 101, 101, 101, 16, 16, 16, 16, 93, 93, 93, 123, 106, 140, 89, 106, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 102, 102, 102, 102, 102, 102, 102, 102, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 35, 38, 38, 38, 38, 
+#> 22, 22, 22, 22, 140, 93, 140, 93, 52, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 38, 38, 38, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 93, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 38, 38, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 52, 52, 52, 52, 52, 89, 93, 93, 45, 29, 52, 52, 52, 52, 52, 52, 16, 16, 16, 16, 101, 101, 101, 101, 101, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 93, 93, 93, 101, 125, 106, 106, 106, 106, 106, 106, 35, 35, 35, 35, 
+#> 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 125, 125, 125, 89, 125, 89, 89, 89, 89, 125, 35, 38, 125, 26, 26, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 22, 22, 89, 89, 89, 89, 106, 106, 106, 106, 106, 106, 106, 106, 22, 22, 93, 106, 93, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 125, 38, 125, 22, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 16, 22, 16, 45, 45, 52, 52, 52, 52, 52, 52, 52, 140, 140, 101, 140, 101, 45, 
+#> 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 33, 123, 33, 33, 33, 140, 22, 22, 22, 22, 101, 101, 101, 16, 101, 16, 16, 16, 16, 16, 16, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 16, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 89, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 
+#> 123, 93, 93, 93, 93, 16, 16, 140, 140, 140, 140, 140, 140, 140, 140, 16, 52, 52, 123, 33, 101, 101, 101, 101, 101, 101, 101, 101, 101, 52, 52, 52, 52, 101, 101, 101, 101, 101, 101, 101, 101, 101, 33, 33, 33, 52, 140, 140, 26, 38, 101, 101, 16, 101, 140, 140, 140, 140, 140, 140, 140, 140, 140, 123, 140, 123, 123, 140, 52, 52, 52, 52, 140, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 106, 106, 106, 106, 106, 106, 106, 35, 35, 35, 35, 35, 35, 35, 35, 38, 38, 38, 
+#> 22, 106, 106, 106, 106, 106, 22, 22, 22, 22, 22, 33, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 38, 38, 38, 123, 123, 89, 89, 89, 89, 26, 89, 26, 106, 106, 106, 106, 106, 125, 125, 125, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 89, 45, 89, 16, 52, 52, 52, 52, 101, 101, 45, 101, 45, 16, 16, 45, 45, 45, 45, 45, 93, 93, 101, 33, 33, 33, 33, 33, 33, 33, 33, 33, 45, 45, 45, 45, 45, 52, 52, 52, 52, 52, 123, 123, 123, 140, 140, 140, 140, 140, 140, 16, 22, 22, 106, 106, 33, 33, 33, 33, 33, 33, 
+#> 33, 33, 33, 33, 101, 101, 101, 101, 101, 101, 101, 101, 101, 16, 16, 16, 16, 16, 16, 16, 16, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 89, 89, 89, 35, 35, 35, 35, 35, 35, 22, 22, 22, 102, 106, 106, 106, 106, 106, 106, 106, 102, 102, 102, 35, 102, 35, 35, 35, 45, 22, 22, 22, 22, 106, 35, 106, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 35, 22, 89, 89, 16, 16, 93, 93, 93, 93, 93, 93, 93, 93, 93, 52, 93, 52, 101, 22, 89, 
+#> 106, 106, 106, 106, 22, 106, 22, 33, 33, 33, 33, 33, 33, 33, 140, 140, 140, 102, 140, 123, 16, 123, 123, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 38, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 22, 26, 26, 22, 22, 93, 93, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 102, 102, 102, 102, 102, 102, 125, 125, 125, 125, 125, 125, 102, 102, 102, 102, 
+#> 102, 38, 38, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 26, 38, 106, 102, 22, 106, 106, 140, 123, 140, 123, 123, 123, 140, 140, 140, 140, 52, 140, 52, 52, 35, 16, 16, 16, 16, 26, 26, 26, 26, 26, 89, 89, 89, 38, 89, 38, 38, 38, 38, 26, 125, 125, 125, 125, 125, 125, 125, 125, 38, 38, 38, 38, 38, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 26, 125, 26, 26, 125, 89, 89, 89, 89, 89, 89, 89, 89, 89, 106, 106, 35, 22, 38, 38, 38, 38, 102, 45, 45, 45, 45, 33, 45, 
+#> 33, 33, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 33, 33, 33, 33, 33, 33, 33, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 101, 101, 101, 101, 101, 101, 33, 22, 33, 22, 125, 101, 101, 101, 101, 123, 123, 123, 123, 123, 123, 45, 45, 45, 45, 45, 45, 45, 16, 16, 16, 16, 140, 93, 140, 93, 22, 26, 123, 123, 123, 123, 123, 33, 123, 33, 33, 140, 140, 140, 123, 52, 123, 52, 89, 35, 35, 35, 35, 
+#> 35, 35, 35, 93, 93, 93, 89, 26, 26, 38, 38, 38, 38, 38, 38, 38, 38, 106, 106, 106, 106, 106, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 93, 93, 93, 16, 89, 102, 102, 22, 22, 22, 89, 89, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 16, 16, 16, 16, 16, 16, 16, 35, 35, 102, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 52, 52, 26, 106, 106, 140, 140, 140, 140, 140, 140, 140, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 125, 125, 125, 125, 125, 125, 125, 125, 125, 38, 125, 
+#> 38, 102, 123, 123, 123, 123, 123, 123, 123, 123, 123, 16, 123, 16, 16, 89, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 16, 16, 16, 16, 26, 26, 26, 26, 26, 26, 26, 26, 22, 106, 106, 125, 125, 38, 125, 38, 38, 38, 38, 38, 38, 38, 38, 38, 35, 35, 35, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 22, 89, 22, 22, 22, 22, 22, 22, 102, 102, 102, 102, 102, 102, 35, 35, 35, 102, 102, 102, 102, 106, 102, 102, 102, 102, 102, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 140, 35, 35, 35, 35, 
+#> 35, 35, 35, 125, 125, 125, 125, 125, 35, 125, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 22, 35, 22, 22, 22, 26, 106, 45, 22, 22, 22, 22, 22, 22, 22, 89, 22, 89, 22, 22, 22, 125, 125, 125, 125, 125, 125, 125, 35, 35, 35, 35, 123, 106, 106, 106, 106, 102, 102, 102, 102, 89, 89, 89, 89, 35, 52, 52, 89, 89, 89, 89, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 101, 101, 101, 101, 101, 16, 16, 52, 52, 52, 52, 52, 52, 16, 52, 140, 140, 140, 140, 140, 140, 123, 123, 123, 123, 
+#> 123, 123, 140, 140, 140, 140, 33, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 140, 140, 140, 140, 45, 45, 35, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 26, 26, 26, 26, 26, 26, 26, 26, 89, 38, 89, 38, 38, 102, 22, 22, 22, 22, 22, 22, 22, 26, 26, 26, 26, 26, 106, 106, 106, 106, 106, 106, 106, 45, 125, 125, 125, 125, 125, 125, 125, 125, 22, 125, 22, 22, 22, 89, 89, 26, 89, 22, 125, 125, 89, 26, 89, 26, 26, 26, 26, 26, 26, 26, 26, 22, 89, 106, 106, 106, 106, 106, 106, 106, 106, 106, 
+#> 106, 22, 22, 22, 22, 93, 16, 93, 16, 16, 16, 101, 101, 38, 38, 38, 89, 52, 52, 52, 52, 52, 52, 52, 52, 52, 22, 52, 102, 102, 102, 102, 102, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 123, 93, 93, 93, 33, 101, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 106, 
+#> 101, 101, 101, 101, 101, 101, 101, 16, 16, 16, 16, 16, 140, 52, 52, 52, 52, 52, 52, 52, 45, 45, 45, 45, 45, 45, 45, 123, 16, 16, 22, 22, 140, 52, 52, 52, 52, 52, 52, 52, 52, 16, 16, 16, 16, 16, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 52, 52, 52, 52, 52, 52, 33, 33, 16, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 33, 33, 33, 33, 52, 52, 123, 123, 123, 140, 45, 45, 45, 102, 38, 102, 93, 93, 93, 93, 45, 45, 45, 45, 45, 22, 123, 22, 22, 89, 89, 101, 101, 101, 101, 101, 
+#> 101, 101, 33, 33, 33, 33, 16, 33, 16, 16, 101, 101, 101, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 106, 106, 106, 106, 106, 106, 106, 106, 106, 102, 106, 102, 106, 106, 106, 106, 106, 106, 35, 35, 35, 35, 35, 35, 22, 35, 22, 16, 16, 16, 16, 16, 16, 16, 93, 93, 93, 26, 38, 26, 26, 26, 26, 106, 140, 26, 45, 45, 52, 52, 52, 52, 52, 52, 123, 123, 102, 102, 102, 102, 102, 26, 102, 26, 26, 26, 102, 102, 
+#> 102, 102, 26, 26, 26, 22, 26, 26, 125, 125, 125, 125, 125, 125, 89, 89, 89, 89, 89, 93, 93, 93, 93, 93, 35, 35, 35, 35, 35, 35, 89, 89, 26, 89, 26, 125, 123, 26, 26, 26, 38, 38, 38, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 16, 16, 16, 16, 16, 16, 16, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 33, 106, 106, 106, 35, 106, 35, 38, 123, 123, 123, 123, 123, 45, 45, 45, 45, 38, 93, 93, 93, 102, 102, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 123, 140, 123, 26, 26, 22, 22, 35, 
+#> 123, 123, 140, 140, 16, 140, 123, 52, 123, 52, 52, 22, 140, 22, 123, 140, 101, 101, 101, 140, 93, 140, 89, 101, 140, 101, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 35, 45, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 102, 26, 102, 26, 22, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 26, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 102, 102, 26, 102, 26, 35, 38, 38, 38, 38, 38, 38, 38, 38, 35, 35, 93, 93, 93, 93, 93, 93, 93, 45, 45, 45, 45, 101, 101, 
+#> 101, 101, 101, 101, 101, 101, 101, 101, 140, 16, 16, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 22, 22, 22, 22, 140, 140, 140, 140, 140, 140, 140, 140, 140, 102, 102, 35, 35, 35, 35, 35, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 26, 26, 16, 16, 102, 102, 102, 102, 38, 102, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 26, 102, 102, 35, 102, 35, 125, 125, 22, 125, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 35, 38, 38, 38, 38, 38, 38, 38, 35, 93, 
+#> 89, 93, 106, 106, 106, 22, 22, 22, 22, 22, 22, 22, 89, 89, 89, 89, 89, 89, 35, 35, 35, 89, 123, 123, 123, 123, 123, 123, 123, 123, 123, 123, 140, 140, 140, 101, 101, 101, 101, 101, 101, 101, 101, 101, 123, 123, 101, 45, 101, 33, 45, 16, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 52, 52, 93, 101, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 102, 102, 102, 102, 102, 38, 38, 26, 26, 26, 26, 38, 38, 38, 38, 38, 102, 102, 125, 16, 16, 16, 16, 16, 16, 16, 102, 102, 45, 45, 45, 45, 33, 33, 33, 33, 33, 33, 33, 33, 
+#> 33, 33, 33, 89, 16, 16, 16, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 35, 35, 102, 102, 102, 102, 22, 22, 22, 22, 22, 22, 16, 125, 125, 125, 125, 125, 125, 125, 106, 52, 52, 52, 52, 33, 52, 33, 33, 33, 45, 22, 22, 22, 22, 22, 22, 102, 125, 125, 125, 125, 26, 26, 26, 38, 38, 38, 38, 38, 38, 38, 38, 106, 106, 125, 125, 125, 125, 125, 22, 22, 22, 22, 22, 22, 26, 26, 106, 45, 35, 35, 35, 102, 102, 22, 22, 22, 22, 22, 106, 106, 89, 106, 89, 125, 125, 125, 125, 125, 125, 125, 125, 125, 
+#> 125, 125, 125, 125, 93, 64, 93, 64, 93, 93, 93, 80, 93, 35, 35, 35, 35, 35, 35, 35, 35, 89, 89, 89, 89, 89, 89, 89, 35, 35, 22, 22, 22, 26, 26, 26, 93, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 16, 16, 16, 16, 16, 16, 16, 16, 16, 93, 93, 93, 93, 93, 93, 93, 106, 106, 106, 16, 16, 16, 45, 45, 45, 45, 45, 16, 106, 101, 101, 101, 101, 101, 101, 101, 101, 16, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 16, 16, 140, 140, 140, 140, 140, 16, 16, 123, 123, 123, 123, 123, 123, 123, 123, 16, 16, 16, 
+#> 16, 16, 33, 123, 5, 5, 33, 125, 125, 125, 125, 125, 125, 125, 26, 125, 26, 26, 89, 35, 102, 102, 102, 102, 38, 125, 125, 125, 26, 26, 26, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 123, 123, 125, 125, 125, 125, 22, 22, 22, 22, 22, 35, 35, 35, 16, 16, 16, 16, 16, 16, 16, 16, 16, 52, 52, 52, 140, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 16, 16, 33, 101, 93, 93, 93, 93, 93, 93, 93, 125, 125, 125, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 16, 52, 5, 89, 89, 89, 89, 102, 102, 45, 
+#> 45, 45, 45, 45, 45, 52, 52, 52, 52, 52, 52, 52, 93, 89, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 52, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 125, 125, 125, 125, 125, 125, 89, 89, 89, 38, 89, 26, 38, 26, 26, 80, 35, 106, 35, 125, 125, 26, 26, 38, 38, 106, 106, 106, 106, 106, 102, 89, 102, 93, 93, 93, 93, 93, 93, 93, 93, 123, 45, 45, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 45, 45, 106, 106, 
+#> 106, 106, 106, 106, 106, 106, 26, 26, 26, 26, 26, 89, 33, 123, 125, 125, 125, 125, 26, 26, 26, 125, 125, 102, 125, 102, 35, 102, 35, 26, 35, 89, 89, 89, 89, 89, 26, 89, 26, 26, 35, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 93, 93, 93, 93, 33, 93, 33, 52, 22, 52, 22, 22, 22, 22, 22, 22, 22, 22, 106, 106, 101, 101, 102, 102, 93, 93, 93, 93, 102, 38, 38, 22, 22, 22, 22, 26, 26, 26, 26, 26, 89, 26, 26, 33, 33, 33, 22, 89, 89, 89, 101, 52, 52, 52, 52, 16, 16, 16, 16, 16, 16, 45, 45, 45, 
+#> 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 52, 52, 52, 52, 52, 101, 101, 101, 140, 140, 140, 45, 106, 52, 52, 22, 123, 123, 93, 123, 140, 45, 45, 45, 52, 52, 52, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 33, 33, 125, 125, 125, 125, 125, 125, 125, 125, 125, 35, 35, 35, 35, 35, 35, 35, 35, 22, 35, 22, 80, 80, 80, 80, 80, 80, 80, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 123, 93, 93, 93, 35, 93, 35, 35, 35, 102, 52, 102, 106, 52, 26, 26, 26, 26, 26, 26, 
+#> 26, 26, 26, 26, 22, 38, 38, 38, 38, 26, 26, 26, 125, 125, 26, 26, 26, 35, 35, 35, 35, 35, 35, 101, 101, 140, 22, 22, 22, 22, 22, 22, 89, 89, 26, 26, 101, 52, 52, 52, 52, 52, 140, 140, 140, 140, 140, 140, 140, 140, 45, 45, 140, 140, 140, 140, 140, 140, 16, 16, 45, 80, 106, 101, 101, 101, 52, 101, 52, 52, 52, 52, 52, 16, 52, 16, 16, 33, 33, 5, 33, 5, 93, 93, 93, 93, 33, 52, 52, 16, 52, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 16, 16, 125, 125, 125, 125, 125, 125, 125, 125, 106, 125, 106, 
+#> 35, 106, 35, 35, 33, 106, 35, 22, 35, 22, 22, 22, 26, 26, 89, 89, 125, 125, 35, 35, 35, 35, 35, 35, 35, 106, 106, 106, 106, 35, 35, 35, 35, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 125, 125, 33, 38, 26, 26, 26, 26, 26, 26, 26, 93, 93, 93, 93, 64, 93, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 72, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 38, 123, 123, 123, 123, 123, 123, 123, 123, 101, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 
+#> 94, 45, 45, 45, 45, 45, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 22, 22, 22, 22, 22, 22, 35, 35, 35, 140, 38, 38, 38, 38, 38, 38, 38, 38, 38, 93, 93, 64, 106, 106, 106, 106, 106, 106, 106, 35, 106, 35, 45, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 52, 52, 93, 22, 26, 26, 26, 26, 26, 26, 26, 26, 80, 80, 80, 80, 80, 80, 80, 80, 80, 80, 80, 80, 94, 117, 89, 89, 89, 89, 89, 26, 26, 26, 38, 38, 33, 33, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 101, 101, 101, 101, 101, 101, 
+#> 33, 33, 45, 52, 52, 52, 52, 52, 52, 52, 52, 52, 16, 52, 16, 16, 16, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 93, 93, 93, 93, 93, 93, 93, 93, 125, 64, 125, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 106, 33, 33, 33, 35, 35, 35, 35, 35, 35, 35, 22, 35, 22, 38, 93, 93, 140, 140, 140, 5, 16, 26, 26, 26, 89, 89, 89, 89, 89, 89, 89, 125, 125, 35, 125, 35, 80, 102, 93, 93, 93, 93, 93, 93, 93, 106, 33, 33, 33, 33, 33, 33, 33, 33, 140, 140, 101, 123, 140, 101, 33, 16, 16, 16, 16, 
+#> 16, 16, 16, 16, 16, 16, 52, 52, 52, 52, 52, 52, 123, 123, 5, 45, 45, 45, 45, 45, 16, 16, 16, 52, 52, 52, 79, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 72, 72, 72, 72, 94, 94, 89, 89, 89, 89, 89, 89, 89, 26, 26, 26, 80, 106, 89, 106, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 38, 72, 38, 38, 45, 123, 123, 123, 123, 123, 140, 140, 140, 140, 140, 140, 33, 33, 102, 102, 102, 141, 141, 123, 123, 16, 16, 16, 16, 16, 16, 16, 16, 33, 125, 33, 93, 93, 93, 93, 93, 93, 93, 93, 
+#> 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 16, 16, 16, 16, 52, 52, 52, 33, 33, 33, 33, 38, 5, 38, 5, 5, 52, 52, 52, 52, 52, 52, 52, 45, 52, 45, 45, 45, 5, 45, 38, 26, 102, 102, 102, 102, 102, 102, 93, 102, 93, 93, 125, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 72, 72, 72, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 72, 72, 72, 72, 72, 94, 117, 89, 89, 89, 89, 89, 89, 89, 89, 38, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 45, 102, 64, 26, 26, 26, 
+#> 106, 45, 45, 45, 45, 45, 45, 45, 45, 45, 33, 33, 45, 33, 52, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 89, 89, 89, 89, 89, 89, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 94, 117, 94, 89, 89, 89, 89, 89, 89, 45, 89, 22, 45, 22, 93, 93, 125, 125, 106, 106, 106, 106, 22, 22, 22, 22, 22, 22, 22, 101, 101, 101, 101, 101, 101, 64, 64, 93, 93, 93, 93, 106, 58, 125, 125, 35, 102, 125, 38, 38, 38, 38, 35, 38, 35, 35, 35, 35, 35, 35, 125, 89, 117, 117, 101, 101, 101, 93, 5, 33, 33, 
+#> 52, 22, 22, 22, 22, 38, 38, 140, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 5, 5, 5, 5, 58, 35, 58, 45, 45, 45, 45, 45, 45, 93, 93, 93, 93, 93, 93, 64, 93, 52, 45, 38, 79, 80, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 52, 52, 52, 52, 52, 52, 52, 52, 45, 117, 117, 117, 117, 35, 117, 35, 102, 22, 22, 22, 22, 22, 72, 72, 72, 72, 72, 72, 72, 72, 72, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 89, 
+#> 125, 80, 89, 80, 80, 80, 125, 125, 125, 93, 93, 93, 93, 140, 140, 140, 140, 140, 16, 16, 16, 106, 35, 106, 106, 89, 89, 89, 89, 89, 89, 117, 93, 93, 93, 93, 64, 93, 64, 38, 45, 125, 64, 125, 125, 125, 125, 125, 72, 72, 72, 72, 72, 72, 72, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 106, 33, 106, 33, 71, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 5, 16, 80, 26, 26, 26, 80, 89, 89, 89, 89, 117, 117, 117, 45, 80, 38, 38, 116, 116, 116, 116, 116, 35, 86, 22, 22, 22, 22, 72, 72, 72, 72, 72, 72, 72, 72, 52, 
+#> 72, 52, 114, 45, 45, 45, 45, 45, 33, 33, 33, 125, 106, 125, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 101, 101, 101, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 58, 58, 26, 80, 80, 80, 80, 80, 80, 80, 80, 80, 80, 80, 80, 80, 4, 52, 58, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 123, 5, 93, 93, 
+#> 93, 93, 93, 64, 33, 64, 117, 117, 58, 117, 5, 58, 35, 33, 33, 33, 33, 33, 33, 33, 5, 5, 5, 5, 5, 33, 33, 33, 16, 16, 16, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 5, 5, 5, 5, 5, 5, 72, 30, 30, 45, 45, 45, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 94, 33, 94, 33, 72, 72, 80, 80, 80, 80, 80, 80, 80, 80, 80, 80, 80, 80, 4, 4, 4, 4, 4, 4, 4, 4, 4, 83, 83, 52, 52, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 117, 117, 117, 93, 26, 26, 80, 80, 80, 80, 80, 80, 80, 80, 80, 80, 80, 125, 
+#> 35, 125, 35, 102, 30, 30, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 30, 45, 93, 93, 123, 123, 123, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 45, 33, 45, 33, 33, 33, 33, 33, 33, 45, 45, 33, 33, 125, 141, 33, 33, 33, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 80, 80, 80, 80, 94, 94, 94, 93, 93, 93, 93, 93, 93, 93, 93, 93, 102, 102, 102, 117, 117, 117, 117, 117, 117, 30, 117, 30, 30, 64, 52, 52, 52, 52, 52, 52, 52, 52, 52, 102, 102, 102, 102, 106, 72, 106, 102, 102, 93, 93, 93, 93, 93, 93, 93, 
+#> 93, 93, 93, 93, 93, 16, 93, 16, 123, 123, 5, 93, 93, 93, 93, 93, 93, 93, 93, 16, 71, 101, 64, 64, 64, 45, 64, 45, 45, 45, 79, 79, 71, 79, 102, 30, 52, 52, 52, 52, 52, 52, 80, 80, 80, 80, 80, 4, 16, 16, 16, 16, 16, 16, 16, 16, 45, 45, 45, 141, 71, 94, 141, 71, 30, 30, 30, 93, 93, 93, 64, 64, 64, 64, 5, 5, 30, 16, 117, 16, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 26, 26, 80, 80, 80, 80, 80, 80, 80, 80, 80, 80, 80, 117, 106, 45, 125, 125, 125, 125, 102, 125, 
+#> 102, 38, 106, 106, 106, 106, 106, 5, 5, 93, 93, 93, 140, 140, 16, 16, 16, 16, 16, 16, 16, 140, 5, 140, 5, 71, 71, 71, 71, 30, 30, 117, 117, 117, 117, 117, 117, 117, 117, 117, 125, 125, 125, 4, 4, 4, 4, 96, 16, 66, 106, 106, 106, 106, 106, 106, 106, 106, 38, 35, 35, 80, 94, 94, 94, 102, 58, 80, 102, 35, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 93, 94, 72, 72, 72, 72, 72, 72, 52, 52, 52, 52, 58, 30, 140, 140, 140, 140, 140, 140, 140, 140, 45, 45, 45, 45, 45, 45, 45, 
+#> 45, 45, 33, 33, 33, 33, 33, 45, 22, 22, 72, 72, 72, 72, 94, 38, 94, 89, 125, 117, 117, 5, 5, 5, 5, 5, 5, 102, 58, 102, 140, 140, 140, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 114, 114, 96, 114, 117, 117, 117, 117, 45, 45, 35, 35, 125, 125, 117, 117, 117, 52, 125, 5, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 33, 33, 33, 
+#> 33, 33, 140, 79, 79, 79, 79, 79, 79, 79, 33, 33, 33, 33, 33, 33, 33, 33, 64, 45, 16, 52, 58, 45, 45, 64, 64, 93, 93, 93, 93, 93, 93, 93, 125, 125, 89, 117, 125, 125, 125, 125, 125, 125, 125, 102, 102, 102, 125, 106, 106, 106, 106, 106, 106, 106, 106, 106, 125, 125, 125, 102, 102, 117, 5, 5, 5, 5, 5, 33, 33, 33, 33, 33, 33, 141, 33, 93, 93, 66, 72, 72, 72, 72, 72, 72, 72, 141, 141, 141, 141, 141, 141, 141, 52, 131, 52, 93, 93, 93, 93, 93, 93, 93, 93, 93, 72, 33, 141, 33, 33, 30, 33, 125, 125, 125, 
+#> 125, 125, 35, 125, 35, 35, 140, 33, 33, 33, 5, 33, 5, 16, 16, 16, 16, 16, 16, 16, 79, 125, 125, 125, 125, 125, 125, 125, 125, 35, 35, 35, 117, 117, 93, 117, 93, 93, 93, 93, 93, 66, 66, 5, 5, 5, 5, 5, 35, 94, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 80, 94, 33, 94, 22, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 79, 79, 141, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 
+#> 38, 125, 45, 45, 30, 30, 66, 66, 72, 72, 72, 72, 72, 72, 72, 72, 106, 106, 72, 86, 72, 72, 72, 16, 16, 106, 106, 106, 4, 106, 4, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 96, 96, 33, 33, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 45, 45, 45, 45, 45, 52, 52, 52, 52, 64, 45, 45, 33, 45, 72, 93, 35, 35, 102, 102, 102, 38, 102, 38, 38, 38, 106, 106, 106, 106, 106, 33, 106, 33, 33, 33, 80, 80, 80, 80, 80, 80, 80, 38, 38, 38, 38, 38, 4, 38, 125, 106, 106, 38, 93, 
+#> 93, 93, 93, 125, 125, 125, 102, 125, 89, 117, 117, 117, 117, 117, 5, 5, 5, 5, 5, 4, 117, 117, 125, 71, 71, 71, 45, 45, 45, 45, 33, 45, 117, 93, 64, 93, 64, 64, 93, 93, 93, 93, 93, 93, 45, 64, 94, 94, 22, 22, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 140, 140, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 33, 79, 33, 33, 102, 102, 102, 93, 102, 93, 125, 125, 125, 125, 35, 35, 35, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 93, 93, 93, 93, 93, 93, 93, 93, 52, 93, 26, 26, 
+#> 26, 52, 33, 33, 33, 33, 33, 33, 141, 45, 45, 45, 45, 72, 72, 72, 72, 72, 72, 72, 72, 94, 33, 58, 115, 35, 58, 96, 96, 5, 35, 5, 5, 5, 30, 66, 106, 106, 106, 106, 38, 38, 38, 38, 38, 38, 38, 125, 106, 16, 16, 16, 16, 16, 45, 35, 45, 52, 86, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 52, 106, 86, 22, 22, 22, 72, 72, 72, 72, 72, 72, 72, 72, 72, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 140, 140, 79, 79, 79, 79, 79, 79, 79, 
+#> 72, 45, 141, 4, 38, 38, 38, 38, 38, 38, 38, 125, 58, 58, 58, 58, 58, 58, 38, 38, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 141, 102, 102, 102, 102, 102, 102, 102, 102, 86, 86, 86, 86, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 16, 16, 16, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 102, 102, 102, 102, 102, 38, 86, 38, 38, 93, 93, 93, 93, 93, 93, 93, 93, 35, 58, 35, 35, 4, 35, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 16, 72, 33, 33, 
+#> 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 35, 35, 93, 93, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 71, 71, 71, 71, 30, 30, 79, 79, 79, 45, 94, 52, 45, 45, 45, 45, 45, 30, 45, 30, 125, 125, 106, 106, 96, 106, 96, 72, 72, 72, 72, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 33, 125, 102, 102, 102, 102, 102, 102, 93, 93, 93, 30, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 102, 102, 102, 102, 102, 102, 102, 125, 72, 33, 33, 
+#> 33, 102, 102, 96, 106, 106, 106, 106, 106, 16, 16, 102, 72, 94, 30, 140, 140, 140, 140, 140, 140, 140, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 66, 71, 71, 71, 71, 30, 30, 30, 30, 30, 30, 30, 94, 94, 131, 131, 131, 131, 106, 131, 106, 94, 94, 94, 94, 72, 117, 117, 117, 86, 86, 86, 86, 125, 80, 80, 80, 80, 80, 80, 4, 4, 4, 125, 125, 125, 125, 125, 125, 94, 94, 94, 106, 106, 106, 106, 106, 106, 106, 106, 72, 114, 72, 106, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 38, 
+#> 38, 38, 38, 38, 38, 38, 38, 38, 79, 79, 79, 30, 45, 131, 131, 5, 5, 5, 5, 58, 93, 93, 96, 96, 114, 72, 72, 72, 72, 72, 72, 72, 72, 125, 45, 45, 45, 45, 45, 38, 38, 86, 79, 79, 79, 79, 30, 30, 45, 35, 45, 93, 4, 35, 45, 45, 45, 45, 45, 45, 45, 79, 79, 79, 79, 72, 86, 125, 96, 106, 96, 106, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 64, 93, 64, 38, 38, 38, 38, 4, 102, 102, 102, 102, 96, 102, 16, 83, 96, 16, 33, 16, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 
+#> 106, 106, 106, 106, 106, 117, 117, 117, 33, 33, 33, 33, 5, 33, 5, 45, 30, 30, 30, 30, 33, 33, 125, 140, 140, 140, 140, 45, 45, 35, 4, 35, 38, 38, 35, 35, 66, 125, 66, 66, 71, 30, 30, 30, 30, 30, 33, 33, 66, 66, 45, 45, 45, 33, 33, 33, 94, 94, 94, 94, 94, 58, 125, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 38, 38, 38, 38, 38, 38, 38, 38, 58, 58, 58, 58, 106, 16, 106, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 45, 45, 72, 141, 141, 141, 141, 141, 141, 141, 4, 4, 4, 16, 16, 16, 16, 16, 16, 
+#> 16, 52, 52, 52, 52, 52, 114, 117, 117, 117, 117, 117, 117, 80, 80, 4, 4, 4, 4, 96, 93, 96, 93, 86, 93, 83, 64, 64, 64, 64, 96, 93, 115, 93, 93, 35, 93, 35, 4, 94, 52, 52, 52, 52, 52, 52, 72, 72, 35, 72, 35, 35, 35, 33, 35, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 86, 86, 86, 16, 16, 16, 102, 38, 38, 38, 35, 35, 35, 35, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 16, 16, 16, 16, 16, 16, 16, 83, 102, 102, 102, 102, 102, 102, 102, 89, 89, 117, 117, 117, 
+#> 117, 117, 5, 5, 141, 141, 117, 117, 117, 93, 117, 66, 16, 16, 16, 16, 16, 16, 83, 83, 83, 83, 83, 16, 16, 16, 66, 93, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 93, 93, 38, 93, 93, 72, 72, 72, 72, 72, 72, 72, 72, 72, 117, 117, 35, 35, 35, 35, 35, 35, 35, 35, 79, 114, 35, 35, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 30, 30, 30, 30, 30, 30, 30, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 38, 94, 38, 38, 38, 38, 38, 94, 33, 33, 16, 33, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 102, 102, 86, 102, 
+#> 125, 16, 125, 16, 102, 102, 102, 102, 102, 102, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 72, 72, 4, 83, 93, 102, 35, 102, 35, 35, 35, 35, 35, 35, 35, 131, 131, 16, 16, 131, 131, 131, 131, 35, 35, 30, 30, 30, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 94, 114, 114, 52, 52, 52, 52, 52, 52, 52, 52, 141, 4, 96, 16, 16, 16, 16, 16, 16, 16, 16, 125, 125, 72, 125, 72, 72, 72, 72, 72, 117, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 35, 35, 35, 35, 35, 35, 35, 35, 35, 114, 114, 
+#> 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 96, 125, 96, 106, 96, 106, 96, 93, 93, 93, 93, 93, 33, 33, 33, 33, 96, 96, 86, 96, 86, 86, 86, 86, 30, 102, 64, 64, 64, 64, 141, 16, 64, 141, 16, 16, 45, 45, 45, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 131, 45, 96, 134, 116, 116, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 86, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 125, 33, 125, 33, 33, 16, 16, 16, 16, 106, 
+#> 106, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 94, 94, 94, 94, 38, 125, 58, 58, 58, 58, 5, 5, 5, 5, 5, 5, 5, 5, 30, 5, 5, 5, 5, 5, 5, 5, 5, 4, 4, 4, 102, 35, 102, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 72, 4, 4, 4, 4, 4, 4, 4, 94, 94, 94, 94, 94, 64, 64, 64, 93, 93, 93, 93, 93, 93, 93, 93, 4, 4, 4, 4, 4, 5, 45, 66, 66, 66, 66, 66, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 72, 72, 125, 125, 125, 125, 125, 72, 102, 102, 16, 35, 16, 64, 96, 96, 96, 96, 96, 
+#> 96, 96, 96, 5, 93, 93, 93, 93, 93, 30, 30, 30, 30, 30, 96, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 125, 125, 125, 125, 125, 125, 125, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 33, 102, 117, 45, 79, 79, 117, 117, 117, 117, 117, 117, 106, 106, 106, 106, 106, 125, 96, 125, 93, 125, 114, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 33, 72, 72, 72, 72, 72, 72, 72, 79, 79, 79, 52, 79, 52, 72, 30, 125, 38, 38, 38, 79, 93, 125, 33, 58, 86, 106, 106, 106, 106, 106, 
+#> 106, 106, 106, 86, 94, 94, 94, 125, 45, 45, 45, 45, 45, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 52, 45, 45, 96, 30, 30, 30, 30, 30, 30, 131, 131, 131, 33, 33, 93, 93, 93, 93, 96, 96, 45, 45, 45, 45, 45, 45, 96, 96, 96, 45, 45, 116, 83, 33, 33, 33, 33, 33, 33, 33, 33, 33, 30, 30, 30, 83, 45, 58, 58, 58, 58, 58, 58, 58, 58, 58, 114, 114, 134, 16, 16, 16, 16, 16, 16, 30, 16, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 86, 86, 86, 86, 4, 4, 4, 4, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 117, 93, 117, 
+#> 93, 106, 79, 79, 79, 79, 38, 38, 38, 38, 131, 131, 131, 125, 125, 125, 125, 38, 38, 38, 38, 114, 114, 102, 102, 106, 114, 96, 96, 96, 96, 96, 96, 96, 96, 96, 117, 117, 117, 117, 66, 66, 117, 117, 94, 94, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 106, 117, 117, 117, 117, 117, 117, 117, 93, 30, 30, 33, 131, 45, 125, 35, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 86, 125, 131, 114, 30, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 102, 102, 131, 45, 45, 45, 45, 93, 93, 
+#> 93, 93, 93, 93, 4, 4, 4, 4, 4, 4, 4, 93, 4, 4, 4, 5, 5, 4, 4, 86, 96, 38, 102, 102, 102, 102, 102, 102, 102, 66, 125, 66, 66, 66, 66, 66, 66, 66, 93, 93, 93, 93, 93, 93, 93, 93, 117, 117, 35, 35, 35, 93, 93, 93, 93, 93, 5, 5, 5, 5, 5, 5, 38, 38, 114, 114, 30, 30, 30, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 38, 38, 38, 38, 38, 38, 38, 58, 58, 58, 5, 5, 5, 5, 5, 5, 66, 66, 106, 106, 106, 106, 106, 106, 106, 106, 106, 96, 106, 106, 106, 64, 16, 64, 96, 83, 83, 83, 45, 79, 30, 45, 94, 
+#> 66, 94, 58, 58, 58, 58, 58, 58, 125, 106, 106, 106, 106, 106, 106, 106, 35, 96, 58, 58, 58, 58, 58, 58, 58, 58, 58, 38, 38, 38, 38, 38, 38, 38, 38, 58, 117, 117, 102, 96, 96, 96, 96, 96, 96, 96, 96, 96, 114, 114, 114, 114, 125, 125, 106, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 45, 45, 45, 45, 131, 131, 131, 114, 114, 93, 131, 4, 116, 66, 116, 30, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 141, 141, 141, 141, 
+#> 141, 141, 141, 141, 141, 141, 52, 52, 52, 52, 93, 125, 131, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 38, 38, 38, 38, 125, 72, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 35, 35, 35, 35, 94, 94, 94, 94, 94, 94, 94, 94, 131, 131, 131, 131, 131, 131, 64, 96, 96, 96, 96, 96, 96, 96, 96, 96, 30, 30, 30, 30, 16, 96, 45, 45, 45, 45, 141, 66, 30, 38, 30, 66, 125, 117, 117, 117, 117, 117, 117, 86, 117, 86, 86, 86, 86, 86, 86, 79, 86, 125, 35, 35, 117, 117, 117, 16, 16, 16, 16, 16, 93, 
+#> 93, 93, 93, 93, 93, 93, 131, 102, 131, 102, 33, 102, 80, 80, 4, 4, 4, 38, 38, 38, 38, 38, 38, 38, 38, 33, 33, 125, 106, 64, 64, 64, 64, 96, 96, 96, 96, 96, 96, 96, 96, 96, 131, 131, 30, 131, 30, 30, 93, 5, 5, 5, 5, 5, 5, 5, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 94, 94, 94, 86, 86, 86, 86, 86, 86, 96, 131, 131, 94, 94, 94, 4, 94, 4, 125, 125, 35, 58, 58, 58, 58, 58, 58, 58, 58, 117, 117, 117, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 114, 
+#> 117, 117, 117, 117, 117, 4, 4, 4, 4, 102, 102, 102, 35, 35, 35, 35, 116, 58, 58, 58, 58, 66, 66, 66, 66, 66, 66, 134, 134, 134, 134, 93, 134, 64, 64, 96, 96, 96, 96, 96, 96, 96, 96, 96, 83, 83, 83, 83, 83, 35, 35, 35, 35, 35, 35, 35, 96, 96, 96, 96, 5, 93, 93, 35, 93, 35, 4, 4, 4, 4, 4, 4, 4, 4, 117, 117, 117, 117, 117, 117, 117, 117, 52, 52, 52, 52, 52, 4, 117, 117, 117, 117, 117, 117, 117, 125, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 52, 115, 58, 86, 86, 86, 86, 
+#> 72, 72, 4, 72, 4, 131, 79, 79, 79, 94, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 114, 114, 114, 114, 114, 64, 64, 64, 64, 64, 96, 96, 96, 96, 96, 96, 96, 64, 64, 64, 96, 96, 96, 96, 96, 96, 96, 93, 93, 93, 93, 93, 58, 58, 58, 38, 38, 38, 38, 38, 38, 38, 38, 38, 66, 66, 66, 30, 30, 30, 30, 30, 72, 72, 72, 4, 4, 93, 72, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 79, 79, 79, 79, 79, 79, 79, 131, 141, 141, 131, 131, 131, 131, 131, 4, 4, 4, 4, 116, 96, 96, 
+#> 96, 134, 131, 131, 131, 131, 131, 45, 114, 45, 45, 45, 45, 45, 45, 125, 125, 125, 125, 102, 125, 102, 102, 102, 102, 45, 45, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 38, 38, 38, 38, 38, 38, 38, 93, 93, 106, 106, 106, 106, 106, 106, 33, 131, 131, 131, 116, 116, 116, 33, 33, 33, 33, 33, 33, 106, 72, 72, 72, 72, 72, 4, 4, 4, 30, 96, 96, 96, 96, 96, 96, 96, 96, 96, 114, 114, 114, 114, 83, 83, 83, 83, 131, 35, 35, 35, 117, 117, 106, 117, 106, 106, 106, 
+#> 106, 106, 72, 106, 72, 52, 72, 45, 45, 45, 45, 45, 45, 79, 16, 16, 16, 16, 16, 16, 16, 16, 93, 93, 106, 30, 16, 16, 16, 16, 16, 16, 16, 30, 30, 30, 30, 5, 5, 5, 5, 52, 52, 114, 125, 125, 125, 125, 117, 125, 125, 125, 125, 35, 106, 117, 117, 117, 102, 117, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 38, 38, 38, 38, 38, 38, 38, 38, 38, 30, 38, 117, 117, 117, 117, 117, 117, 117, 4, 114, 93, 114, 93, 93, 93, 79, 79, 79, 45, 45, 45, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 114, 114, 114, 
+#> 4, 86, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 141, 141, 131, 131, 131, 131, 131, 131, 131, 45, 45, 45, 45, 45, 93, 131, 131, 114, 114, 114, 114, 114, 114, 114, 114, 94, 94, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 33, 33, 33, 33, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 131, 131, 131, 131, 86, 86, 102, 117, 72, 134, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 38, 38, 38, 38, 96, 96, 83, 30, 134, 33, 33, 33, 33, 33, 106, 93, 93, 93, 93, 93, 
+#> 93, 114, 114, 114, 114, 35, 93, 117, 131, 96, 96, 116, 125, 125, 125, 125, 125, 125, 125, 125, 66, 66, 4, 4, 4, 117, 117, 38, 117, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 94, 94, 94, 94, 33, 94, 30, 30, 30, 30, 141, 52, 52, 52, 52, 52, 52, 52, 52, 52, 93, 114, 93, 33, 5, 33, 131, 131, 131, 131, 131, 131, 131, 131, 131, 131, 83, 66, 66, 35, 35, 131, 131, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 5, 45, 45, 45, 45, 45, 45, 45, 45, 45, 83, 83, 83, 83, 83, 45, 45, 33, 
+#> 33, 33, 33, 33, 33, 33, 72, 72, 72, 72, 72, 72, 93, 93, 93, 30, 93, 30, 30, 30, 96, 93, 93, 93, 93, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 58, 58, 83, 83, 83, 30, 96, 30, 30, 72, 79, 79, 79, 79, 16, 16, 16, 16, 16, 35, 35, 102, 125, 52, 86, 38, 38, 38, 38, 125, 93, 102, 102, 66, 35, 52, 52, 52, 52, 52, 117, 114, 114, 114, 125, 94, 38, 38, 94, 94, 94, 94, 94, 94, 72, 72, 102, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 38, 38, 38, 38, 66, 
+#> 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 30, 30, 30, 30, 30, 30, 30, 30, 16, 131, 131, 131, 52, 131, 52, 52, 52, 52, 52, 52, 52, 93, 94, 30, 30, 30, 30, 30, 30, 93, 93, 93, 93, 131, 131, 131, 131, 131, 131, 30, 102, 102, 102, 102, 102, 102, 117, 4, 117, 4, 94, 94, 131, 86, 114, 86, 106, 102, 106, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 30, 30, 30, 30, 30, 30, 30, 66, 66, 38, 38, 38, 38, 38, 38, 38, 38, 38, 93, 93, 93, 93, 4, 93, 4, 4, 38, 38, 38, 116, 116, 66, 66, 66, 66, 
+#> 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 16, 16, 16, 16, 131, 131, 131, 93, 116, 30, 30, 30, 30, 30, 5, 66, 134, 134, 66, 66, 66, 66, 66, 66, 30, 52, 52, 116, 116, 116, 116, 116, 4, 4, 4, 4, 4, 4, 4, 4, 72, 72, 72, 72, 72, 72, 72, 72, 117, 96, 96, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 72, 72, 72, 94, 94, 45, 45, 5, 45, 2, 72, 86, 86, 86, 86, 86, 86, 86, 86, 86, 86, 86, 35, 35, 35, 35, 35, 35, 16, 16, 55, 55, 106, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 72, 72, 96, 83, 94, 
+#> 102, 102, 102, 102, 79, 79, 79, 79, 79, 83, 83, 83, 83, 83, 94, 94, 94, 94, 94, 30, 30, 30, 30, 30, 30, 30, 30, 58, 58, 58, 58, 58, 58, 58, 58, 58, 131, 131, 131, 131, 131, 16, 16, 16, 16, 16, 16, 16, 30, 30, 30, 30, 30, 5, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 83, 83, 83, 83, 83, 4, 4, 4, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 93, 35, 35, 106, 106, 106, 117, 117, 117, 117, 117, 125, 125, 125, 125, 125, 125, 114, 114, 114, 114, 114, 114, 114, 114, 114, 94, 114, 33, 33, 
+#> 33, 33, 93, 93, 93, 93, 93, 93, 131, 131, 66, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 16, 16, 16, 16, 16, 16, 16, 30, 30, 30, 16, 16, 16, 16, 16, 125, 125, 125, 125, 125, 125, 125, 125, 125, 94, 125, 94, 94, 94, 94, 94, 94, 45, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 96, 96, 35, 96, 35, 35, 58, 58, 86, 86, 86, 86, 86, 86, 86, 94, 94, 30, 131, 80, 80, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 93, 93, 45, 4, 45, 134, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 
+#> 52, 52, 52, 52, 52, 4, 4, 4, 4, 4, 4, 4, 4, 4, 125, 58, 58, 58, 58, 58, 58, 86, 86, 86, 94, 94, 94, 94, 52, 52, 52, 52, 86, 131, 94, 94, 94, 94, 94, 83, 83, 83, 83, 83, 83, 83, 83, 83, 83, 83, 83, 83, 83, 83, 83, 83, 83, 83, 83, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 125, 125, 125, 93, 114, 114, 16, 16, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 134, 134, 134, 134, 5, 5, 35, 35, 35, 35, 35, 125, 125, 125, 125, 4, 4, 4, 16, 16, 16, 16, 16, 16, 83, 83, 83, 83, 83, 83, 83, 83, 83, 83, 83, 45, 
+#> 45, 45, 45, 45, 45, 45, 131, 131, 131, 131, 131, 131, 38, 131, 38, 38, 38, 58, 131, 83, 83, 83, 83, 83, 83, 83, 125, 114, 102, 114, 102, 106, 96, 96, 35, 35, 35, 35, 102, 102, 102, 102, 45, 86, 117, 117, 35, 35, 35, 38, 114, 114, 114, 114, 114, 114, 114, 114, 93, 93, 93, 93, 93, 93, 93, 93, 30, 93, 30, 134, 79, 79, 45, 5, 5, 5, 5, 5, 5, 96, 30, 30, 30, 30, 30, 30, 93, 93, 93, 16, 16, 79, 96, 35, 35, 35, 35, 86, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 131, 131, 131, 33, 38, 33, 
+#> 83, 102, 83, 45, 79, 79, 79, 79, 79, 79, 45, 45, 45, 134, 134, 134, 134, 134, 134, 96, 96, 96, 72, 72, 72, 72, 134, 134, 72, 72, 72, 72, 72, 45, 45, 35, 45, 35, 35, 35, 35, 35, 35, 35, 5, 5, 125, 83, 83, 83, 83, 83, 83, 66, 66, 66, 66, 125, 125, 125, 125, 125, 131, 131, 94, 94, 86, 86, 86, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 131, 79, 131, 79, 79, 79, 79, 79, 79, 93, 93, 33, 93, 79, 79, 79, 117, 117, 117, 117, 94, 94, 30, 93, 94, 114, 35, 35, 35, 94, 94, 94, 96, 96, 96, 106, 106, 106, 106, 106, 106, 106, 
+#> 106, 58, 93, 93, 66, 93, 4, 35, 35, 35, 114, 52, 52, 52, 4, 4, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 93, 93, 79, 93, 79, 94, 94, 94, 94, 94, 94, 94, 94, 94, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 117, 117, 33, 35, 35, 35, 33, 33, 5, 5, 5, 96, 96, 96, 96, 96, 96, 96, 96, 96, 96, 52, 102, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 96, 96, 35, 35, 96, 96, 96, 96, 96, 96, 96, 96, 96, 96, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 
+#> 38, 38, 38, 94, 94, 94, 94, 94, 86, 131, 86, 86, 52, 86, 86, 86, 86, 86, 86, 86, 86, 86, 86, 86, 86, 94, 94, 94, 94, 94, 117, 72, 86, 114, 114, 114, 114, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 125, 125, 117, 45, 45, 45, 72, 72, 72, 72, 72, 79, 131, 93, 93, 93, 93, 93, 93, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 102, 102, 30, 30, 30, 30, 116, 45, 106, 134, 16, 16, 16, 52, 52, 52, 52, 83, 83, 83, 83, 83, 83, 83, 83, 83, 96, 
+#> 96, 45, 45, 45, 45, 114, 114, 125, 125, 125, 125, 125, 125, 125, 30, 106, 30, 30, 30, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 58, 125, 58, 45, 45, 134, 134, 134, 93, 93, 93, 93, 93, 4, 83, 93, 16, 16, 93, 94, 86, 125, 125, 131, 131, 45, 131, 45, 45, 106, 106, 106, 106, 106, 131, 38, 38, 38, 38, 38, 38, 38, 38, 38, 102, 38, 102, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 35, 35, 35, 35, 96, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 30, 5, 102, 114, 114, 114, 125, 
+#> 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 96, 96, 96, 96, 96, 96, 93, 93, 93, 93, 93, 96, 96, 96, 96, 96, 134, 96, 96, 114, 2, 114, 96, 94, 94, 116, 114, 16, 72, 35, 35, 35, 35, 35, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 131, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 117, 117, 117, 96, 134, 33, 30, 30, 30, 16, 16, 96, 96, 96, 96, 96, 96, 96, 96, 96, 96, 106, 96, 96, 96, 96, 96, 96, 16, 16, 16, 16, 30, 30, 30, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 79, 134, 134, 45, 72, 72, 72, 72, 
+#> 72, 72, 72, 72, 72, 72, 72, 125, 125, 125, 125, 125, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 116, 33, 33, 134, 125, 125, 125, 83, 83, 83, 83, 83, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 102, 102, 102, 51, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 72, 72, 72, 72, 72, 72, 72, 72, 93, 93, 93, 33, 33, 96, 93, 93, 134, 134, 134, 134, 134, 134, 134, 4, 86, 5, 5, 5, 5, 5, 5, 5, 5, 5, 30, 30, 30, 30, 30, 30, 125, 125, 35, 35, 35, 35, 35, 35, 35, 35, 38, 125, 106, 
+#> 106, 106, 106, 106, 106, 106, 106, 106, 106, 117, 117, 117, 117, 117, 30, 102, 72, 72, 35, 72, 35, 79, 79, 79, 79, 30, 30, 30, 30, 30, 83, 83, 83, 83, 83, 83, 83, 83, 83, 45, 83, 116, 116, 83, 116, 134, 134, 134, 134, 134, 134, 134, 134, 134, 134, 134, 134, 134, 134, 33, 134, 102, 102, 102, 102, 125, 125, 125, 66, 125, 66, 66, 4, 4, 4, 4, 4, 5, 106, 5, 86, 86, 86, 86, 86, 86, 86, 86, 86, 86, 86, 86, 86, 5, 5, 5, 5, 5, 5, 5, 5, 5, 16, 16, 16, 66, 66, 83, 79, 79, 79, 79, 93, 93, 93, 5, 93, 5, 5, 5, 
+#> 5, 5, 5, 5, 5, 5, 5, 45, 72, 72, 72, 83, 5, 33, 33, 33, 33, 33, 33, 114, 114, 125, 125, 125, 125, 125, 125, 45, 45, 45, 102, 102, 102, 102, 38, 102, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 106, 106, 106, 106, 106, 106, 106, 125, 125, 125, 16, 16, 16, 16, 45, 45, 45, 33, 58, 125, 125, 125, 125, 125, 125, 125, 125, 96, 125, 117, 117, 117, 117, 16, 125, 125, 125, 125, 38, 38, 38, 38, 38, 38, 58, 58, 58, 94, 94, 94, 5, 52, 106, 117, 117, 117, 117, 102, 102, 30, 102, 106, 93, 93, 33, 
+#> 33, 33, 33, 33, 93, 93, 45, 33, 5, 33, 33, 94, 94, 94, 94, 94, 94, 94, 94, 72, 72, 72, 117, 93, 93, 93, 93, 93, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 93, 93, 93, 93, 93, 130, 130, 134, 134, 134, 134, 134, 134, 134, 134, 134, 134, 52, 52, 106, 106, 106, 106, 106, 106, 30, 106, 30, 30, 30, 125, 125, 125, 114, 114, 114, 114, 114, 114, 5, 5, 117, 117, 117, 125, 125, 125, 125, 125, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 93, 30, 30, 58, 58, 58, 58, 58, 58, 58, 114, 102, 102, 102, 131, 
+#> 83, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 96, 96, 4, 4, 4, 4, 4, 106, 106, 106, 106, 106, 4, 125, 66, 102, 66, 86, 86, 86, 86, 86, 86, 86, 86, 86, 86, 86, 86, 33, 33, 33, 33, 33, 93, 93, 93, 96, 5, 86, 55, 35, 35, 35, 35, 35, 35, 35, 35, 16, 16, 16, 125, 125, 125, 93, 125, 5, 30, 30, 38, 86, 52, 52, 52, 52, 52, 52, 52, 52, 52, 72, 72, 72, 66, 106, 52, 52, 52, 35, 35, 35, 35, 35, 35, 35, 102, 52, 52, 52, 52, 52, 52, 102, 102, 102, 102, 35, 35, 35, 35, 102, 102, 58, 58, 58, 58, 58, 58, 125, 125, 125, 125, 
+#> 125, 96, 96, 58, 116, 116, 116, 116, 116, 116, 116, 116, 30, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 93, 93, 45, 45, 58, 93, 130, 114, 114, 114, 114, 114, 114, 114, 114, 114, 114, 114, 114, 114, 114, 114, 114, 114, 114, 114, 114, 72, 72, 72, 72, 72, 106, 106, 106, 106, 106, 106, 106, 106, 93, 93, 58, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 114, 114, 114, 52, 114, 52, 5, 5, 117, 66, 66, 66, 66, 66, 66, 66, 66, 94, 94, 94, 51, 94, 16, 16, 16, 16, 30, 30, 30, 30, 30, 30, 52, 52, 
+#> 131, 131, 52, 114, 86, 86, 86, 86, 86, 86, 86, 86, 86, 86, 86, 86, 86, 72, 72, 72, 30, 72, 94, 94, 86, 94, 86, 86, 86, 86, 86, 79, 79, 79, 16, 16, 4, 16, 38, 93, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 4, 5, 4, 130, 125, 125, 125, 125, 125, 125, 94, 94, 94, 66, 66, 116, 38, 52, 134, 134, 134, 134, 134, 134, 134, 134, 134, 35, 33, 33, 94, 94, 94, 94, 94, 86, 86, 86, 86, 86, 72, 94, 30, 66, 66, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 131, 96, 131, 96, 96, 5, 5, 5, 33, 5, 33, 5, 5, 45, 5, 
+#> 33, 33, 116, 116, 116, 116, 116, 102, 5, 5, 33, 125, 125, 125, 125, 125, 125, 125, 125, 125, 79, 125, 102, 94, 102, 94, 117, 16, 16, 16, 16, 16, 106, 125, 125, 125, 72, 125, 72, 125, 16, 16, 16, 16, 16, 16, 16, 16, 16, 114, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 134, 134, 93, 93, 93, 93, 93, 58, 58, 58, 93, 94, 94, 94, 94, 58, 58, 58, 58, 58, 58, 58, 58, 58, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 30, 30, 30, 66, 66, 66, 125, 125, 35, 125, 35, 16, 134, 134, 134, 134, 134, 134, 134, 134, 
+#> 93, 134, 93, 93, 93, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 134, 134, 134, 134, 134, 134, 134, 134, 114, 114, 94, 134, 38, 93, 45, 134, 134, 78, 134, 35, 35, 35, 35, 35, 35, 35, 4, 35, 4, 4, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 125, 125, 125, 125, 125, 125, 72, 72, 72, 72, 72, 96, 96, 96, 96, 96, 96, 96, 96, 131, 131, 131, 16, 16, 96, 134, 130, 93, 130, 33, 58, 58, 58, 58, 58, 58, 58, 5, 5, 5, 86, 86, 33, 33, 33, 116, 45, 45, 45, 45, 96, 52, 16, 16, 16, 16, 16, 16, 16, 16, 16, 
+#> 16, 16, 58, 125, 125, 83, 83, 83, 83, 83, 83, 83, 83, 83, 79, 79, 79, 79, 79, 79, 79, 79, 94, 94, 94, 16, 16, 16, 38, 134, 4, 4, 4, 4, 4, 102, 102, 102, 102, 117, 117, 79, 4, 4, 4, 116, 116, 116, 116, 116, 86, 116, 30, 30, 30, 30, 30, 30, 30, 2, 114, 45, 125, 125, 125, 125, 125, 125, 125, 4, 4, 4, 4, 55, 4, 55, 38, 66, 102, 125, 125, 106, 106, 106, 106, 106, 106, 33, 106, 33, 33, 38, 38, 38, 38, 38, 38, 38, 38, 72, 52, 72, 52, 38, 5, 5, 125, 125, 117, 83, 83, 83, 83, 83, 83, 83, 83, 83, 83, 83, 83, 
+#> 83, 83, 83, 134, 134, 134, 79, 79, 79, 72, 58, 58, 58, 58, 117, 117, 117, 117, 117, 117, 117, 83, 117, 116, 116, 96, 96, 96, 96, 96, 96, 96, 96, 96, 96, 96, 96, 125, 125, 125, 125, 125, 114, 114, 114, 114, 114, 114, 114, 55, 55, 38, 102, 134, 134, 35, 38, 117, 117, 117, 66, 106, 117, 52, 52, 52, 52, 52, 93, 93, 93, 93, 93, 5, 51, 102, 102, 102, 102, 102, 102, 94, 102, 72, 72, 66, 72, 38, 52, 52, 66, 134, 134, 134, 134, 134, 134, 134, 134, 134, 134, 134, 134, 93, 93, 93, 93, 5, 5, 4, 4, 4, 4, 4, 4, 
+#> 86, 86, 106, 106, 106, 106, 106, 16, 106, 45, 45, 45, 16, 16, 16, 16, 16, 16, 16, 35, 35, 35, 96, 96, 96, 96, 96, 96, 96, 96, 96, 125, 125, 16, 96, 96, 96, 96, 96, 96, 96, 96, 96, 96, 96, 79, 79, 79, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 45, 45, 45, 117, 94, 72, 116, 116, 116, 116, 116, 116, 116, 116, 116, 116, 5, 30, 30, 30, 30, 30, 30, 30, 134, 134, 134, 134, 134, 55, 55, 3, 72, 72, 78, 125, 125, 125, 125, 106, 106, 106, 106, 106, 106, 106, 106, 5, 102, 38, 38, 38, 38, 38, 38, 38, 38, 
+#> 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 58, 96, 96, 96, 96, 96, 96, 55, 51, 51, 51, 51, 4, 4, 4, 38, 38, 38, 38, 38, 38, 5, 33, 125, 38, 102, 45, 45, 45, 45, 45, 45, 131, 131, 131, 131, 131, 33, 45, 45, 83, 130, 4, 4, 4, 4, 4, 94, 4, 94, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 86, 86, 86, 86, 86, 86, 86, 125, 51, 51, 51, 51, 51, 4, 4, 117, 131, 86, 117, 2, 33, 106, 106, 106, 106, 106, 106, 94, 94, 94, 5, 94, 5, 55, 55, 72, 94, 4, 
+#> 125, 94, 94, 94, 83, 83, 72, 72, 38, 72, 93, 93, 93, 116, 116, 131, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 16, 134, 134, 134, 134, 134, 134, 134, 134, 134, 134, 134, 134, 4, 5, 72, 72, 72, 72, 131, 131, 102, 131, 96, 102, 96, 96, 96, 96, 96, 96, 134, 134, 96, 117, 117, 117, 117, 117, 117, 117, 117, 131, 131, 131, 131, 131, 5, 5, 125, 66, 66, 66, 66, 66, 38, 38, 38, 35, 35, 106, 102, 102, 125, 125, 114, 125, 114, 114, 114, 114, 94, 94, 94, 94, 94, 66, 66, 94, 66, 
+#> 66, 66, 66, 66, 33, 33, 30, 102, 102, 117, 117, 117, 117, 114, 117, 114, 114, 66, 66, 4, 66, 102, 114, 114, 83, 94, 94, 94, 94, 94, 94, 94, 94, 86, 94, 96, 96, 96, 96, 96, 114, 114, 114, 114, 114, 114, 117, 117, 117, 94, 94, 114, 117, 117, 117, 117, 117, 116, 38, 38, 16, 38, 45, 96, 38, 38, 131, 131, 131, 131, 131, 131, 131, 96, 131, 16, 16, 45, 131, 131, 5, 5, 5, 5, 5, 5, 4, 45, 66, 52, 58, 66, 79, 3, 3, 72, 72, 35, 35, 35, 35, 30, 38, 38, 4, 5, 130, 134, 134, 134, 134, 134, 114, 114, 4, 114, 4, 
+#> 4, 4, 4, 130, 130, 130, 35, 130, 35, 72, 130, 96, 96, 96, 96, 5, 5, 5, 52, 52, 52, 52, 131, 131, 131, 131, 131, 131, 131, 131, 131, 96, 131, 96, 96, 93, 96, 52, 93, 38, 134, 33, 131, 131, 116, 93, 131, 93, 93, 79, 52, 52, 52, 94, 94, 94, 94, 94, 94, 94, 94, 94, 51, 35, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 2, 2, 2, 45, 45, 45, 125, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 117, 35, 106, 45, 117, 94, 125, 125, 
+#> 117, 117, 35, 35, 58, 58, 58, 58, 106, 38, 38, 16, 38, 16, 16, 102, 131, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 96, 96, 96, 96, 96, 96, 96, 93, 106, 106, 106, 106, 106, 106, 58, 58, 58, 58, 33, 5, 134, 134, 134, 134, 134, 134, 134, 134, 134, 30, 114, 114, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 33, 33, 51, 33, 33, 131, 33, 72, 94, 16, 16, 16, 16, 16, 16, 33, 51, 51, 51, 51, 51, 117, 117, 117, 45, 45, 45, 16, 116, 116, 116, 116, 116, 116, 116, 116, 116, 116, 116, 38, 38, 38, 38, 38, 38, 38, 38, 
+#> 33, 38, 116, 116, 106, 106, 106, 106, 106, 106, 106, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 35, 35, 35, 35, 35, 35, 35, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 35, 35, 35, 72, 114, 72, 114, 72, 72, 72, 106, 106, 106, 106, 106, 106, 4, 4, 4, 58, 38, 38, 38, 38, 38, 38, 33, 83, 94, 94, 94, 94, 94, 38, 38, 114, 35, 35, 35, 5, 5, 114, 134, 33, 33, 33, 33, 33, 33, 33, 33, 102, 116, 4, 4, 4, 4, 4, 4, 4, 4, 45, 45, 45, 45, 93, 93, 96, 134, 134, 134, 134, 52, 52, 52, 52, 52, 
+#> 52, 52, 93, 93, 2, 45, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 45, 3, 3, 3, 3, 3, 3, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 93, 96, 96, 96, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 94, 94, 94, 94, 94, 4, 114, 114, 114, 134, 134, 134, 134, 134, 5, 5, 5, 45, 45, 45, 94, 33, 94, 3, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 94, 94, 94, 93, 72, 93, 72, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 83, 83, 83, 83, 83, 
+#> 83, 83, 83, 83, 83, 83, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 4, 4, 4, 4, 4, 4, 4, 16, 16, 38, 52, 30, 30, 30, 30, 30, 30, 55, 55, 55, 79, 79, 79, 79, 79, 79, 79, 93, 93, 93, 93, 66, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 96, 134, 96, 134, 35, 45, 45, 45, 45, 45, 45, 114, 134, 134, 134, 134, 134, 134, 134, 5, 117, 4, 4, 4, 4, 4, 4, 4, 38, 125, 125, 125, 102, 2, 102, 51, 96, 114, 96, 30, 30, 30, 
+#> 30, 93, 93, 30, 33, 30, 33, 78, 131, 131, 131, 131, 131, 131, 131, 131, 131, 131, 131, 131, 55, 52, 52, 52, 52, 52, 93, 58, 131, 137, 137, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 3, 3, 3, 106, 106, 106, 106, 106, 106, 66, 66, 30, 66, 86, 86, 86, 86, 86, 86, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 125, 125, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 16, 125, 83, 83, 83, 83, 83, 58, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 35, 96, 116, 116, 116, 116, 116, 116, 116, 
+#> 116, 116, 116, 116, 116, 116, 116, 116, 116, 116, 116, 131, 131, 131, 131, 131, 131, 131, 131, 131, 131, 131, 52, 45, 131, 131, 66, 45, 52, 52, 52, 52, 52, 52, 52, 52, 45, 45, 45, 45, 45, 83, 83, 83, 83, 114, 55, 114, 55, 55, 55, 55, 55, 72, 72, 72, 72, 4, 4, 93, 93, 93, 52, 52, 94, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 55, 102, 116, 116, 116, 116, 66, 116, 72, 72, 5, 5, 5, 5, 5, 5, 4, 33, 5, 131, 72, 33, 33, 33, 33, 33, 33, 33, 93, 45, 45, 2, 2, 83, 45, 45, 45, 45, 45, 
+#> 45, 58, 58, 102, 5, 35, 83, 83, 45, 78, 96, 96, 134, 134, 134, 134, 134, 134, 134, 58, 66, 30, 33, 125, 45, 45, 45, 134, 116, 116, 116, 79, 116, 116, 58, 45, 45, 45, 45, 45, 4, 45, 45, 45, 45, 33, 117, 35, 106, 93, 102, 72, 45, 131, 116, 116, 116, 116, 116, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 117, 117, 117, 117, 131, 33, 33, 134, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 58, 117, 51, 51, 51, 86, 86, 86, 86, 86, 86, 4, 4, 45, 78, 78, 
+#> 78, 72, 72, 117, 117, 117, 45, 45, 45, 106, 106, 106, 106, 106, 106, 106, 106, 66, 3, 3, 3, 3, 3, 94, 134, 134, 134, 134, 134, 134, 134, 134, 94, 94, 94, 116, 116, 116, 116, 93, 116, 16, 5, 5, 5, 58, 102, 102, 102, 102, 102, 102, 102, 102, 3, 102, 3, 3, 3, 16, 16, 16, 16, 38, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 30, 30, 30, 30, 30, 2, 2, 2, 2, 2, 2, 2, 2, 71, 72, 72, 72, 72, 72, 72, 55, 72, 94, 94, 94, 94, 94, 94, 94, 94, 114, 96, 45, 45, 45, 45, 45, 45, 45, 94, 94, 94, 45, 114, 16, 3, 
+#> 3, 137, 131, 131, 131, 131, 131, 131, 93, 93, 93, 93, 16, 16, 93, 16, 134, 16, 16, 96, 45, 45, 45, 45, 45, 45, 45, 45, 33, 33, 5, 5, 94, 94, 94, 94, 94, 102, 102, 102, 102, 102, 102, 102, 102, 66, 94, 94, 94, 94, 94, 94, 134, 66, 66, 93, 134, 93, 93, 93, 93, 93, 16, 94, 96, 117, 117, 117, 117, 38, 117, 33, 33, 72, 16, 16, 16, 16, 35, 117, 117, 117, 117, 117, 117, 117, 35, 16, 35, 16, 16, 114, 114, 66, 66, 66, 66, 52, 78, 72, 72, 72, 72, 72, 72, 72, 134, 134, 93, 134, 3, 93, 2, 106, 4, 86, 106, 86, 
+#> 86, 86, 86, 86, 55, 58, 58, 58, 35, 35, 35, 117, 117, 94, 94, 79, 79, 79, 79, 58, 58, 58, 58, 58, 117, 38, 117, 38, 102, 102, 16, 86, 86, 86, 86, 16, 16, 33, 45, 45, 106, 45, 45, 86, 86, 55, 137, 66, 66, 55, 55, 55, 55, 55, 66, 5, 5, 5, 5, 5, 55, 55, 55, 5, 102, 38, 94, 86, 86, 116, 116, 116, 116, 116, 116, 116, 116, 116, 58, 116, 3, 3, 3, 3, 3, 3, 93, 93, 3, 3, 117, 93, 30, 30, 30, 30, 117, 117, 117, 117, 117, 117, 117, 117, 117, 16, 117, 58, 58, 58, 58, 58, 58, 58, 58, 114, 114, 114, 114, 58, 58, 
+#> 4, 131, 55, 55, 55, 55, 55, 72, 5, 5, 33, 55, 55, 51, 51, 130, 5, 5, 58, 58, 58, 58, 114, 114, 114, 114, 3, 3, 3, 3, 3, 3, 72, 71, 117, 51, 16, 16, 16, 16, 16, 16, 16, 16, 2, 2, 94, 94, 5, 5, 5, 5, 45, 45, 45, 45, 45, 45, 45, 117, 116, 116, 102, 102, 102, 106, 106, 51, 52, 102, 131, 131, 131, 134, 134, 134, 134, 134, 134, 134, 134, 131, 131, 125, 79, 79, 79, 79, 79, 134, 45, 5, 5, 72, 72, 72, 72, 94, 78, 52, 16, 72, 72, 72, 130, 66, 45, 45, 45, 45, 45, 45, 45, 45, 16, 16, 16, 16, 16, 16, 16, 16, 
+#> 72, 72, 33, 72, 130, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 94, 4, 4, 51, 51, 51, 51, 51, 51, 51, 130, 58, 130, 4, 4, 51, 137, 51, 114, 30, 30, 30, 83, 83, 51, 51, 51, 51, 51, 51, 51, 16, 38, 16, 33, 131, 33, 33, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 5, 131, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 102, 102, 102, 33, 33, 33, 33, 72, 79, 45, 79, 5, 102, 30, 30, 30, 30, 2, 2, 2, 125, 125, 125, 125, 125, 125, 125, 125, 35, 114, 38, 78, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 93, 93, 93, 
+#> 93, 93, 93, 93, 93, 94, 94, 94, 38, 38, 38, 38, 16, 58, 106, 16, 16, 38, 38, 38, 38, 38, 38, 38, 38, 114, 4, 3, 117, 106, 125, 125, 66, 66, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 4, 4, 4, 45, 45, 45, 45, 117, 117, 117, 72, 72, 72, 72, 72, 94, 72, 72, 134, 134, 134, 134, 134, 134, 134, 134, 134, 125, 5, 5, 5, 134, 93, 93, 116, 116, 116, 116, 116, 116, 116, 116, 116, 116, 116, 116, 116, 116, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 5, 5, 5, 16, 72, 72, 72, 86, 86, 86, 93, 93, 131, 
+#> 131, 131, 131, 117, 117, 117, 117, 117, 117, 38, 38, 38, 38, 125, 102, 102, 131, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 72, 72, 72, 72, 72, 51, 72, 51, 51, 131, 55, 35, 4, 35, 38, 45, 116, 116, 116, 116, 116, 116, 116, 131, 131, 131, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 72, 51, 51, 51, 51, 51, 72, 72, 72, 35, 35, 78, 78, 117, 131, 114, 114, 131, 93, 93, 93, 93, 93, 93, 93, 93, 93, 58, 58, 58, 93, 93, 93, 93, 93, 93, 93, 93, 93, 134, 134, 134, 134, 134, 
+#> 134, 134, 55, 55, 94, 94, 94, 94, 94, 94, 94, 55, 93, 55, 114, 114, 114, 114, 114, 114, 114, 114, 114, 114, 114, 114, 114, 114, 114, 114, 78, 78, 72, 72, 86, 86, 86, 86, 16, 16, 16, 16, 16, 16, 16, 94, 94, 94, 94, 102, 35, 35, 35, 131, 131, 131, 131, 131, 5, 5, 5, 5, 5, 131, 131, 131, 131, 131, 5, 5, 94, 94, 94, 94, 94, 94, 94, 130, 35, 55, 55, 55, 55, 117, 117, 117, 117, 86, 86, 137, 3, 137, 3, 51, 79, 94, 137, 137, 137, 4, 78, 45, 45, 45, 86, 86, 33, 86, 38, 38, 38, 72, 72, 72, 72, 16, 16, 16, 
+#> 16, 16, 16, 16, 16, 16, 35, 35, 72, 72, 72, 96, 102, 102, 102, 102, 102, 102, 102, 125, 125, 125, 125, 125, 125, 134, 38, 134, 38, 38, 38, 116, 116, 116, 116, 116, 116, 93, 93, 93, 93, 93, 93, 125, 125, 130, 93, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 35, 35, 79, 106, 106, 106, 106, 4, 106, 4, 4, 38, 38, 93, 51, 51, 51, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 134, 134, 134, 134, 134, 134, 52, 52, 38, 52, 5, 93, 93, 134, 134, 33, 93, 93, 114, 16, 16, 114, 72, 114, 96, 
+#> 96, 96, 96, 96, 96, 96, 93, 93, 93, 93, 116, 116, 38, 38, 38, 38, 38, 4, 114, 116, 116, 116, 116, 79, 116, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 72, 131, 33, 93, 93, 93, 93, 93, 93, 116, 114, 114, 114, 114, 93, 114, 93, 93, 125, 114, 66, 66, 66, 66, 66, 66, 66, 66, 16, 16, 16, 16, 35, 35, 58, 33, 93, 93, 102, 102, 102, 3, 96, 96, 96, 96, 130, 130, 130, 35, 78, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 45, 45, 93, 35, 35, 30, 30, 30, 30, 30, 52, 52, 52, 52, 52, 52, 52, 130, 55, 55, 3, 94, 94, 131, 
+#> 131, 131, 131, 131, 131, 131, 66, 131, 66, 52, 52, 52, 52, 52, 83, 83, 83, 83, 83, 83, 83, 83, 114, 114, 114, 38, 130, 130, 130, 51, 131, 131, 131, 131, 131, 131, 131, 131, 5, 55, 55, 114, 72, 72, 72, 72, 72, 93, 93, 93, 93, 93, 93, 93, 93, 33, 3, 94, 94, 134, 134, 134, 134, 134, 134, 134, 72, 72, 72, 72, 72, 3, 3, 94, 94, 38, 38, 38, 38, 38, 106, 106, 16, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 72, 45, 38, 38, 38, 38, 38, 38, 38, 38, 52, 106, 52, 16, 4, 4, 4, 4, 4, 4, 4, 
+#> 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 45, 78, 4, 4, 58, 58, 58, 58, 58, 58, 58, 58, 58, 102, 102, 94, 94, 94, 16, 94, 4, 66, 66, 66, 66, 66, 66, 58, 66, 94, 94, 94, 94, 94, 94, 94, 117, 125, 125, 93, 93, 38, 38, 38, 38, 16, 38, 16, 35, 35, 114, 5, 134, 134, 134, 134, 134, 134, 134, 134, 134, 134, 134, 134, 55, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 117, 117, 117, 71, 134, 86, 86, 86, 86, 86, 86, 86, 86, 2, 71, 71, 71, 71, 71, 131, 5, 116, 58, 58, 58, 58, 58, 58, 94, 51, 
+#> 51, 4, 4, 4, 4, 58, 3, 35, 35, 35, 131, 131, 125, 5, 5, 5, 16, 116, 116, 116, 116, 116, 116, 116, 116, 116, 116, 102, 116, 102, 102, 102, 102, 51, 52, 52, 52, 58, 58, 58, 58, 52, 58, 52, 66, 72, 66, 94, 86, 86, 86, 86, 86, 86, 16, 86, 16, 55, 131, 52, 52, 102, 134, 134, 134, 134, 134, 134, 134, 96, 125, 125, 125, 131, 3, 3, 3, 4, 66, 66, 66, 66, 66, 96, 96, 96, 96, 33, 33, 33, 33, 33, 30, 2, 2, 2, 2, 2, 2, 2, 2, 71, 71, 33, 58, 58, 131, 131, 131, 131, 131, 131, 131, 93, 93, 96, 94, 96, 131, 131, 
+#> 131, 79, 131, 131, 52, 52, 52, 83, 83, 83, 83, 78, 134, 125, 125, 125, 125, 125, 117, 117, 51, 51, 51, 51, 51, 51, 66, 66, 117, 35, 117, 35, 35, 52, 52, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 96, 96, 96, 96, 96, 96, 96, 93, 93, 93, 93, 93, 93, 93, 51, 96, 51, 51, 51, 45, 45, 94, 134, 94, 94, 94, 45, 94, 117, 117, 117, 117, 117, 117, 58, 58, 72, 72, 72, 72, 58, 58, 58, 58, 52, 52, 52, 52, 52, 79, 51, 16, 51, 38, 102, 55, 52, 52, 52, 55, 55, 55, 55, 55, 35, 35, 4, 55, 131, 
+#> 102, 116, 116, 116, 116, 4, 4, 4, 4, 4, 4, 72, 72, 72, 72, 72, 72, 125, 125, 76, 2, 2, 2, 2, 2, 2, 2, 3, 134, 134, 125, 125, 4, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 33, 33, 33, 33, 33, 33, 33, 33, 52, 52, 52, 52, 52, 52, 52, 55, 55, 55, 125, 125, 125, 125, 125, 125, 16, 4, 4, 52, 117, 117, 38, 79, 79, 79, 79, 79, 79, 16, 79, 94, 66, 93, 106, 72, 96, 96, 96, 96, 96, 96, 96, 96, 96, 96, 96, 96, 96, 93, 93, 3, 3, 33, 33, 33, 33, 38, 116, 116, 116, 116, 94, 94, 114, 114, 
+#> 78, 78, 16, 16, 55, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 71, 71, 71, 71, 71, 52, 52, 79, 116, 116, 116, 116, 116, 116, 116, 116, 116, 116, 116, 93, 116, 93, 93, 76, 116, 94, 83, 83, 83, 78, 78, 125, 125, 125, 125, 52, 114, 114, 114, 52, 114, 58, 58, 52, 52, 58, 58, 58, 58, 58, 58, 58, 58, 72, 72, 86, 86, 86, 86, 86, 86, 86, 16, 86, 71, 71, 71, 33, 79, 96, 38, 45, 117, 51, 51, 55, 55, 55, 72, 3, 3, 3, 3, 78, 3, 3, 78, 78, 78, 78, 78, 5, 5, 5, 5, 5, 94, 94, 94, 94, 93, 94, 116, 55, 117, 117, 
+#> 55, 117, 134, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 71, 71, 71, 71, 58, 58, 58, 58, 58, 35, 58, 35, 58, 52, 3, 3, 3, 3, 3, 3, 3, 3, 72, 55, 117, 117, 117, 117, 117, 117, 117, 117, 117, 114, 116, 38, 38, 117, 117, 117, 96, 96, 96, 96, 96, 125, 125, 125, 125, 55, 131, 55, 55, 55, 55, 117, 117, 117, 117, 117, 125, 2, 2, 2, 2, 2, 71, 71, 125, 125, 96, 137, 116, 72, 72, 72, 72, 30, 30, 30, 114, 114, 94, 114, 94, 116, 96, 96, 96, 96, 96, 96, 96, 117, 117, 117, 117, 117, 117, 117, 96, 2, 
+#> 2, 2, 2, 2, 2, 2, 71, 134, 117, 117, 117, 117, 131, 45, 38, 45, 38, 38, 38, 38, 38, 38, 38, 38, 94, 45, 96, 96, 96, 96, 96, 96, 96, 5, 5, 5, 5, 58, 58, 5, 114, 117, 66, 134, 134, 134, 96, 33, 33, 55, 134, 134, 134, 134, 16, 134, 16, 130, 93, 106, 4, 4, 4, 3, 51, 51, 51, 51, 51, 51, 58, 131, 131, 93, 93, 93, 93, 93, 131, 131, 137, 35, 35, 35, 35, 35, 35, 35, 93, 93, 30, 30, 30, 2, 2, 2, 2, 2, 2, 2, 2, 71, 71, 71, 71, 4, 72, 16, 116, 16, 16, 16, 16, 16, 16, 16, 72, 72, 72, 72, 4, 4, 4, 45, 93, 131, 
+#> 55, 55, 55, 55, 55, 16, 16, 16, 16, 16, 16, 16, 72, 72, 72, 134, 134, 134, 134, 134, 134, 134, 134, 134, 134, 134, 134, 102, 102, 102, 102, 72, 72, 72, 72, 72, 72, 72, 72, 16, 131, 78, 114, 55, 55, 55, 55, 55, 55, 35, 35, 35, 35, 35, 35, 4, 35, 5, 106, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 79, 79, 94, 94, 94, 94, 116, 134, 134, 134, 134, 134, 134, 117, 130, 3, 16, 72, 72, 114, 58, 33, 117, 33, 33, 33, 33, 33, 96, 16, 16, 16, 96, 66, 66, 66, 66, 66, 66, 66, 72, 93, 94, 55, 55, 55, 55, 55, 52, 52, 
+#> 3, 52, 38, 117, 117, 117, 117, 117, 35, 35, 117, 16, 16, 16, 72, 134, 134, 134, 134, 134, 134, 134, 134, 134, 134, 134, 134, 71, 71, 93, 86, 86, 86, 86, 86, 86, 86, 86, 137, 137, 116, 116, 93, 55, 55, 55, 55, 55, 55, 55, 16, 16, 16, 16, 16, 4, 4, 4, 4, 4, 4, 114, 102, 102, 102, 102, 102, 102, 102, 102, 72, 58, 114, 72, 78, 78, 5, 78, 76, 52, 79, 79, 79, 79, 79, 79, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 79, 79, 79, 79, 79, 79, 79, 79, 94, 94, 94, 94, 134, 72, 72, 72, 72, 35, 72, 35, 
+#> 106, 125, 5, 5, 5, 78, 137, 38, 96, 96, 96, 96, 96, 96, 96, 3, 106, 106, 114, 106, 106, 106, 106, 16, 106, 16, 94, 94, 94, 116, 131, 131, 131, 131, 4, 131, 4, 71, 93, 93, 93, 93, 93, 93, 93, 94, 5, 94, 5, 5, 5, 5, 5, 5, 5, 5, 5, 51, 3, 45, 45, 45, 45, 45, 45, 45, 16, 45, 16, 52, 52, 52, 52, 83, 83, 83, 78, 78, 78, 78, 58, 78, 114, 114, 114, 16, 58, 58, 72, 72, 72, 72, 72, 72, 72, 72, 116, 116, 116, 116, 116, 16, 131, 131, 131, 131, 131, 102, 102, 4, 4, 4, 3, 78, 137, 58, 58, 102, 102, 102, 102, 102, 
+#> 102, 102, 102, 93, 102, 93, 93, 71, 71, 71, 71, 72, 94, 106, 106, 106, 106, 106, 106, 106, 106, 106, 116, 116, 4, 116, 4, 72, 38, 72, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 125, 125, 125, 125, 125, 125, 4, 72, 72, 16, 16, 16, 16, 16, 4, 4, 106, 106, 106, 106, 106, 106, 117, 117, 117, 117, 117, 117, 72, 72, 117, 117, 117, 117, 79, 79, 79, 79, 79, 79, 79, 131, 131, 52, 52, 45, 45, 45, 45, 45, 45, 86, 33, 2, 71, 71, 71, 16, 33, 93, 96, 96, 94, 94, 134, 134, 134, 134, 134, 134, 
+#> 125, 125, 125, 125, 125, 125, 125, 125, 125, 134, 134, 134, 134, 3, 3, 3, 72, 79, 114, 33, 114, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 102, 102, 131, 51, 86, 86, 137, 137, 137, 137, 116, 96, 96, 96, 96, 51, 51, 51, 114, 114, 71, 114, 71, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 58, 58, 58, 58, 58, 58, 58, 114, 93, 86, 86, 86, 86, 86, 86, 35, 35, 35, 35, 114, 114, 134, 55, 55, 55, 55, 55, 52, 52, 52, 52, 52, 52, 52, 52, 
+#> 33, 33, 33, 33, 33, 33, 78, 78, 131, 58, 58, 58, 58, 58, 58, 76, 4, 4, 4, 4, 125, 125, 125, 35, 35, 51, 137, 3, 137, 79, 114, 114, 38, 134, 134, 38, 38, 38, 38, 137, 137, 125, 137, 3, 78, 16, 125, 78, 130, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 93, 66, 66, 66, 66, 66, 66, 96, 16, 16, 16, 16, 93, 93, 93, 93, 52, 130, 45, 131, 131, 131, 131, 131, 131, 131, 131, 131, 131, 131, 131, 131, 72, 102, 72, 72, 72, 72, 72, 72, 55, 72, 55, 94, 94, 55, 137, 125, 125, 125, 125, 102, 125, 102, 102, 52, 102, 52, 
+#> 52, 52, 52, 102, 102, 102, 76, 2, 2, 2, 2, 125, 125, 125, 3, 134, 114, 114, 22, 22, 64, 5, 5, 5, 5, 5, 5, 5, 5, 52, 96, 4, 72, 3, 3, 3, 3, 3, 3, 3, 86, 86, 86, 72, 86, 72, 72, 72, 72, 35, 35, 125, 66, 66, 66, 45, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 106, 51, 51, 16, 16, 16, 3, 66, 66, 66, 66, 66, 16, 106, 125, 125, 125, 78, 78, 78, 78, 125, 114, 2, 2, 2, 71, 71, 71, 71, 94, 94, 78, 94, 78, 5, 78, 78, 78, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 16, 55, 55, 55, 55, 55, 55, 72, 76, 72, 72, 
+#> 16, 93, 93, 93, 93, 93, 93, 93, 93, 93, 116, 116, 33, 33, 33, 33, 33, 33, 33, 33, 33, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 72, 102, 4, 4, 4, 4, 4, 4, 4, 4, 4, 93, 93, 51, 51, 51, 51, 51, 96, 125, 125, 125, 125, 125, 125, 125, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 76, 94, 94, 94, 94, 94, 94, 94, 94, 94, 76, 134, 134, 51, 134, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 
+#> 93, 125, 125, 131, 16, 16, 16, 16, 16, 16, 16, 102, 102, 102, 102, 137, 131, 52, 96, 52, 52, 52, 16, 130, 130, 130, 130, 35, 130, 58, 66, 131, 125, 125, 38, 38, 38, 38, 52, 52, 52, 52, 52, 137, 137, 45, 45, 45, 45, 45, 45, 45, 45, 78, 93, 93, 93, 93, 93, 93, 93, 114, 114, 114, 114, 114, 114, 114, 33, 114, 33, 33, 33, 16, 33, 16, 117, 117, 16, 16, 16, 16, 16, 16, 16, 16, 16, 33, 93, 45, 45, 45, 45, 45, 45, 45, 45, 16, 102, 102, 130, 72, 72, 72, 72, 72, 93, 93, 106, 106, 134, 4, 4, 4, 4, 4, 94, 94, 
+#> 131, 66, 66, 66, 117, 114, 102, 33, 33, 33, 33, 33, 102, 102, 117, 117, 117, 117, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 72, 78, 78, 78, 78, 78, 78, 78, 52, 52, 131, 131, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 96, 116, 102, 116, 134, 134, 134, 134, 134, 134, 116, 134, 116, 5, 5, 125, 125, 102, 125, 16, 16, 16, 16, 16, 16, 116, 116, 116, 116, 116, 116, 94, 33, 3, 3, 3, 3, 3, 3, 3, 3, 3, 58, 58, 52, 52, 52, 52, 94, 16, 16, 16, 16, 16, 16, 16, 16, 16, 
+#> 16, 78, 78, 78, 78, 78, 78, 78, 78, 78, 3, 3, 38, 38, 38, 3, 114, 5, 4, 4, 93, 93, 35, 35, 35, 35, 35, 130, 55, 45, 45, 79, 79, 130, 130, 130, 35, 35, 35, 131, 78, 78, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 131, 45, 45, 45, 45, 45, 45, 45, 45, 102, 116, 131, 102, 102, 102, 102, 58, 58, 58, 58, 58, 58, 102, 102, 102, 102, 137, 117, 117, 117, 117, 117, 117, 117, 117, 117, 131, 131, 114, 114, 114, 114, 114, 16, 16, 72, 72, 72, 72, 45, 45, 45, 45, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 125, 
+#> 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 106, 106, 106, 106, 4, 106, 4, 4, 5, 106, 5, 137, 114, 102, 102, 102, 102, 102, 102, 102, 72, 102, 16, 16, 16, 71, 106, 106, 106, 106, 106, 35, 106, 35, 35, 35, 35, 35, 35, 35, 35, 78, 78, 78, 78, 106, 16, 16, 16, 16, 16, 16, 16, 16, 16, 96, 35, 130, 130, 130, 130, 130, 130, 130, 130, 35, 35, 35, 35, 35, 35, 35, 35, 131, 131, 96, 131, 33, 130, 130, 130, 130, 130, 130, 58, 130, 5, 5, 5, 52, 117, 117, 117, 38, 131, 131, 131, 131, 131, 71, 71, 131, 
+#> 3, 3, 33, 33, 33, 33, 114, 114, 114, 131, 45, 131, 45, 45, 125, 125, 125, 114, 125, 106, 114, 38, 38, 38, 130, 130, 130, 130, 130, 130, 130, 130, 130, 16, 16, 72, 72, 72, 134, 134, 134, 134, 134, 134, 3, 134, 3, 3, 3, 3, 35, 16, 66, 66, 66, 66, 66, 66, 66, 78, 71, 78, 72, 72, 72, 116, 116, 5, 5, 5, 5, 5, 5, 5, 5, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 76, 134, 134, 134, 137, 137, 137, 137, 137, 137, 137, 137, 137, 137, 137, 102, 102, 58, 58, 58, 4, 58, 4, 45, 45, 4, 45, 72, 72, 72, 72, 72, 
+#> 72, 72, 72, 72, 114, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 66, 66, 66, 66, 66, 33, 33, 134, 94, 94, 94, 114, 114, 114, 114, 114, 76, 3, 130, 96, 96, 96, 16, 16, 93, 55, 55, 55, 76, 76, 35, 35, 134, 134, 134, 134, 134, 134, 134, 134, 134, 78, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 116, 116, 116, 116, 116, 116, 38, 102, 125, 125, 125, 125, 125, 93, 93, 93, 93, 93, 93, 93, 71, 96, 130, 79, 79, 79, 79, 79, 79, 33, 79, 106, 106, 106, 96, 96, 96, 96, 96, 96, 4, 4, 4, 4, 4, 4, 4, 4, 4, 117, 
+#> 117, 116, 116, 116, 116, 116, 116, 116, 116, 116, 116, 116, 45, 45, 45, 45, 116, 116, 116, 116, 116, 116, 96, 51, 51, 51, 51, 51, 51, 51, 106, 106, 106, 16, 16, 16, 38, 38, 38, 38, 38, 38, 38, 38, 3, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 134, 5, 66, 106, 130, 106, 106, 106, 106, 134, 134, 134, 134, 134, 134, 134, 134, 38, 38, 38, 38, 38, 38, 38, 38, 38, 52, 72, 38, 55, 72, 55, 55, 55, 55, 117, 117, 16, 3, 3, 96, 106, 106, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 116, 
+#> 116, 116, 116, 116, 4, 4, 4, 130, 93, 93, 137, 137, 35, 131, 131, 131, 131, 131, 131, 52, 131, 117, 117, 117, 117, 117, 117, 117, 33, 33, 33, 33, 33, 33, 33, 33, 55, 55, 55, 55, 55, 4, 4, 4, 4, 117, 137, 78, 78, 78, 78, 78, 78, 78, 78, 131, 78, 131, 131, 131, 131, 131, 131, 131, 131, 5, 116, 125, 125, 125, 125, 125, 71, 71, 16, 16, 16, 16, 16, 16, 16, 93, 93, 72, 72, 72, 72, 72, 72, 72, 72, 5, 5, 5, 5, 5, 5, 5, 66, 66, 66, 66, 66, 66, 66, 66, 66, 5, 5, 5, 5, 5, 5, 5, 5, 5, 4, 71, 71, 71, 71, 71, 
+#> 71, 71, 71, 71, 71, 3, 3, 3, 3, 3, 3, 78, 5, 78, 66, 66, 66, 66, 66, 66, 66, 66, 96, 78, 78, 78, 78, 78, 125, 45, 106, 51, 130, 130, 130, 130, 130, 3, 4, 4, 4, 4, 4, 114, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 93, 93, 93, 93, 94, 94, 45, 45, 45, 45, 45, 45, 45, 45, 137, 130, 3, 3, 3, 3, 3, 3, 4, 4, 114, 33, 3, 33, 3, 3, 3, 3, 130, 130, 79, 79, 79, 52, 79, 52, 102, 130, 5, 5, 93, 93, 93, 93, 93, 4, 66, 117, 134, 134, 33, 117, 117, 117, 117, 117, 117, 117, 16, 131, 131, 131, 131, 131, 
+#> 116, 79, 94, 94, 94, 134, 134, 134, 52, 52, 52, 52, 52, 52, 52, 71, 71, 130, 130, 116, 35, 116, 130, 130, 130, 130, 130, 130, 52, 130, 52, 134, 16, 16, 16, 96, 96, 96, 96, 78, 78, 78, 78, 78, 79, 5, 5, 5, 5, 5, 4, 4, 4, 106, 106, 4, 16, 106, 3, 137, 137, 137, 137, 33, 35, 35, 35, 35, 35, 72, 72, 134, 114, 114, 114, 114, 114, 114, 114, 93, 114, 93, 106, 106, 106, 106, 106, 106, 106, 4, 4, 4, 4, 4, 125, 94, 94, 96, 96, 96, 96, 134, 134, 16, 16, 51, 117, 117, 117, 71, 71, 71, 71, 71, 137, 137, 137, 
+#> 137, 79, 79, 79, 79, 79, 79, 117, 33, 33, 33, 33, 33, 33, 33, 33, 131, 16, 125, 4, 55, 55, 55, 55, 55, 137, 137, 96, 79, 79, 66, 79, 66, 66, 38, 38, 38, 38, 38, 38, 38, 38, 137, 137, 137, 137, 137, 137, 137, 137, 137, 137, 137, 137, 137, 5, 5, 5, 131, 131, 16, 16, 16, 3, 3, 52, 52, 52, 52, 52, 137, 66, 66, 66, 66, 66, 5, 5, 5, 5, 66, 66, 66, 66, 66, 3, 3, 3, 3, 3, 51, 51, 51, 94, 79, 79, 78, 78, 78, 78, 78, 58, 78, 4, 4, 4, 4, 125, 125, 125, 130, 130, 114, 76, 76, 76, 131, 131, 131, 5, 131, 5, 5, 
+#> 5, 5, 125, 125, 125, 125, 125, 106, 106, 106, 106, 106, 106, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 51, 51, 51, 94, 78, 66, 66, 66, 66, 66, 114, 35, 35, 35, 35, 131, 131, 114, 114, 114, 114, 114, 94, 94, 116, 66, 35, 78, 78, 78, 93, 106, 76, 76, 117, 45, 45, 45, 45, 45, 116, 116, 116, 116, 116, 58, 58, 58, 58, 35, 51, 51, 51, 51, 94, 94, 94, 76, 76, 76, 55, 55, 76, 76, 76, 76, 117, 117, 117, 117, 117, 117, 117, 33, 33, 94, 94, 58, 58, 58, 58, 58, 134, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 
+#> 106, 106, 106, 106, 106, 106, 106, 137, 137, 137, 78, 78, 78, 66, 66, 66, 66, 66, 94, 94, 94, 5, 5, 5, 5, 35, 35, 35, 130, 130, 130, 96, 96, 16, 96, 52, 94, 71, 71, 71, 71, 72, 72, 72, 72, 76, 3, 3, 3, 3, 106, 106, 106, 106, 117, 117, 117, 117, 117, 96, 96, 96, 96, 134, 94, 94, 94, 94, 94, 94, 94, 58, 35, 71, 71, 71, 71, 71, 71, 116, 79, 116, 66, 58, 58, 58, 52, 52, 16, 16, 16) x c(55, 72, 45, 61, 59, 65, 76, 3, 8, 37, 7, 11, 39, 59, 69, 64, 60, 62, 85, 85, 80, 84, 97, 114, 98, 121, 123, 133, 121, 69, 31, 54, 78, 81, 78, 70, 84, 91, 56, 81, 86, 6, 72, 83, 89, 87, 66, 66, 51, 24, 35, 45, 29, 23, 78, 52, 138, 124, 130, 134, 137, 129, 109, 12, 46, 53, 70, 62, 47, 64, 56, 51, 47, 30, 8, 11, 39, 22, 3, 21, 72, 55, 63, 55, 73, 45, 55, 16, 29, 37, 22, 33, 73, 62, 70, 56, 56, 53, 40, 41, 3, 71, 136, 138, 127, 147, 131, 125, 130, 131, 134, 152, 147, 55, 79, 18, 15, 1, 17, 55, 53, 
+#> 53, 52, 47, 53, 48, 47, 44, 41, 45, 45, 41, 43, 38, 40, 46, 36, 35, 21, 11, 7, 39, 127, 147, 77, 102, 131, 86, 1, 125, 140, 65, 152, 137, 157, 128, 159, 90, 117, 137, 121, 129, 113, 2, 10, 30, 30, 2, 34, 39, 46, 46, 43, 44, 43, 31, 10, 6, 42, 42, 45, 48, 44, 38, 41, 56, 37, 38, 45, 43, 40, 41, 27, 1, 12, 128, 151, 125, 106, 118, 130, 133, 131, 102, 39, 75, 58, 145, 142, 152, 74, 110, 10, 145, 136, 77, 44, 141, 151, 150, 21, 97, 2, 39, 84, 77, 80, 76, 83, 96, 98, 109, 7, 75, 84, 74, 27, 1, 22, 72, 
+#> 98, 76, 32, 108, 98, 118, 112, 137, 97, 45, 89, 41, 1, 1, 31, 101, 131, 140, 137, 150, 154, 145, 144, 152, 156, 154, 146, 149, 153, 157, 156, 100, 61, 2, 155, 154, 155, 148, 83, 152, 18, 29, 42, 57, 66, 32, 52, 63, 62, 17, 10, 5, 2, 4, 33, 34, 28, 35, 36, 42, 42, 33, 13, 39, 5, 5, 46, 48, 40, 46, 44, 28, 37, 30, 22, 26, 24, 6, 10, 1, 2, 41, 98, 150, 150, 156, 140, 146, 140, 122, 98, 156, 145, 152, 111, 124, 112, 128, 137, 145, 155, 121, 79, 134, 95, 4, 30, 45, 130, 154, 151, 126, 134, 133, 135, 139, 
+#> 156, 139, 147, 137, 116, 138, 125, 100, 55, 26, 9, 14, 8, 32, 130, 153, 148, 143, 157, 143, 147, 95, 124, 73, 6, 2, 86, 65, 51, 113, 109, 104, 124, 110, 140, 72, 88, 81, 48, 69, 101, 77, 15, 74, 114, 132, 123, 111, 107, 104, 126, 91, 75, 27, 81, 80, 66, 78, 121, 34, 126, 60, 42, 150, 37, 155, 56, 12, 77, 35, 75, 132, 131, 128, 149, 148, 106, 129, 113, 104, 72, 141, 118, 148, 151, 152, 123, 110, 9, 2, 1, 26, 31, 31, 36, 36, 46, 50, 46, 53, 16, 39, 9, 26, 36, 12, 37, 42, 38, 41, 48, 45, 41, 16, 19, 
+#> 9, 61, 151, 147, 135, 140, 136, 129, 132, 147, 142, 142, 151, 137, 150, 130, 145, 114, 150, 156, 123, 74, 27, 49, 88, 132, 117, 150, 112, 115, 134, 122, 147, 149, 143, 150, 156, 101, 102, 26, 124, 152, 99, 154, 151, 126, 127, 125, 46, 143, 136, 139, 83, 71, 24, 56, 1, 1, 41, 41, 32, 38, 52, 39, 52, 43, 41, 39, 41, 39, 33, 35, 34, 27, 46, 35, 24, 33, 39, 15, 10, 44, 33, 21, 5, 20, 123, 146, 97, 102, 140, 151, 154, 139, 132, 137, 151, 72, 55, 64, 30, 93, 6, 14, 102, 153, 153, 132, 153, 148, 152, 155, 
+#> 155, 156, 97, 140, 153, 139, 154, 145, 152, 118, 106, 95, 36, 9, 3, 37, 57, 94, 114, 72, 87, 87, 82, 46, 33, 11, 3, 2, 29, 131, 137, 89, 72, 29, 1, 7, 31, 143, 141, 141, 153, 141, 158, 150, 151, 142, 127, 134, 150, 132, 131, 150, 135, 117, 150, 141, 64, 33, 36, 45, 46, 41, 26, 43, 36, 35, 38, 40, 37, 41, 34, 42, 37, 20, 14, 36, 40, 45, 42, 55, 54, 55, 64, 58, 57, 65, 56, 33, 38, 43, 42, 39, 36, 35, 26, 40, 46, 53, 47, 50, 70, 55, 53, 50, 40, 38, 12, 11, 43, 6, 6, 24, 35, 44, 43, 24, 21, 29, 10, 119, 
+#> 72, 61, 66, 142, 20, 157, 142, 150, 144, 153, 157, 155, 145, 147, 128, 129, 141, 104, 23, 41, 10, 46, 81, 113, 143, 150, 143, 100, 95, 48, 102, 120, 33, 35, 4, 1, 4, 25, 34, 40, 28, 43, 40, 40, 16, 3, 34, 35, 25, 27, 26, 9, 33, 19, 53, 64, 56, 69, 75, 125, 124, 118, 136, 111, 129, 93, 88, 31, 2, 12, 1, 3, 106, 51, 98, 135, 127, 146, 131, 133, 149, 152, 151, 135, 108, 82, 28, 131, 153, 107, 30, 10, 2, 31, 38, 41, 38, 40, 41, 9, 36, 36, 4, 3, 7, 86, 64, 134, 120, 153, 136, 143, 36, 17, 28, 147, 109, 
+#> 5, 6, 44, 80, 40, 84, 60, 103, 48, 22, 2, 1, 32, 67, 78, 83, 110, 117, 87, 53, 17, 24, 24, 78, 37, 46, 52, 56, 2, 5, 29, 27, 32, 46, 2, 43, 31, 38, 44, 45, 20, 40, 36, 32, 27, 48, 28, 26, 28, 20, 1, 7, 18, 80, 98, 116, 120, 111, 79, 97, 77, 2, 9, 9, 24, 95, 155, 154, 140, 143, 143, 154, 121, 132, 138, 146, 156, 122, 72, 45, 115, 56, 1, 34, 32, 8, 12, 33, 10, 9, 148, 146, 148, 149, 149, 150, 100, 146, 126, 141, 94, 69, 1, 77, 88, 141, 121, 80, 122, 100, 94, 99, 54, 38, 78, 3, 34, 37, 44, 12, 17, 18, 
+#> 21, 30, 26, 5, 5, 20, 147, 154, 148, 122, 45, 83, 155, 146, 17, 139, 146, 94, 62, 108, 113, 113, 101, 133, 141, 103, 74, 69, 55, 53, 10, 46, 15, 90, 127, 133, 126, 120, 134, 110, 80, 47, 25, 50, 46, 47, 48, 49, 49, 47, 3, 30, 46, 31, 33, 39, 21, 32, 7, 23, 37, 34, 22, 9, 144, 149, 145, 139, 126, 150, 127, 125, 108, 140, 142, 136, 156, 125, 102, 69, 104, 147, 151, 143, 143, 132, 145, 150, 9, 113, 135, 75, 113, 137, 5, 14, 79, 148, 155, 122, 93, 147, 65, 150, 135, 106, 48, 50, 1, 29, 13, 45, 43, 42, 
+#> 39, 6, 27, 36, 37, 34, 8, 28, 39, 39, 38, 6, 26, 19, 38, 126, 153, 148, 149, 119, 140, 150, 117, 120, 148, 152, 142, 154, 146, 59, 47, 1, 3, 19, 113, 138, 143, 131, 155, 127, 148, 146, 127, 139, 154, 153, 137, 52, 38, 33, 61, 61, 84, 62, 47, 51, 125, 96, 114, 69, 35, 27, 119, 2, 82, 10, 17, 9, 111, 153, 124, 142, 80, 144, 110, 84, 6, 3, 5, 46, 65, 99, 143, 145, 127, 146, 139, 107, 40, 150, 121, 123, 16, 118, 104, 144, 153, 145, 124, 132, 109, 149, 141, 127, 88, 139, 27, 144, 154, 146, 148, 152, 155, 
+#> 154, 107, 120, 36, 41, 42, 43, 41, 33, 12, 79, 107, 116, 110, 118, 88, 113, 122, 134, 124, 84, 114, 73, 103, 97, 91, 94, 45, 30, 10, 12, 40, 33, 8, 17, 24, 37, 16, 39, 49, 7, 25, 15, 40, 124, 145, 127, 140, 134, 140, 78, 54, 94, 116, 31, 33, 137, 143, 150, 43, 94, 19, 4, 130, 147, 149, 150, 137, 140, 121, 83, 46, 26, 156, 140, 123, 138, 145, 146, 149, 109, 105, 137, 148, 148, 152, 98, 141, 150, 111, 88, 23, 129, 136, 135, 129, 140, 108, 131, 151, 128, 142, 123, 57, 125, 82, 16, 2, 5, 42, 36, 32, 
+#> 48, 37, 16, 29, 28, 36, 9, 18, 26, 143, 156, 149, 155, 142, 11, 131, 134, 153, 155, 141, 152, 75, 78, 9, 112, 146, 142, 145, 149, 143, 23, 25, 100, 112, 80, 119, 119, 121, 100, 76, 108, 97, 80, 61, 66, 55, 7, 1, 6, 29, 150, 154, 155, 155, 152, 119, 139, 154, 149, 156, 154, 93, 88, 24, 49, 14, 1, 51, 150, 135, 53, 113, 90, 36, 41, 39, 6, 48, 43, 48, 32, 24, 27, 117, 4, 139, 160, 149, 156, 126, 122, 145, 97, 115, 123, 145, 25, 12, 14, 11, 7, 100, 144, 132, 115, 39, 32, 50, 87, 108, 104, 120, 118, 107, 
+#> 55, 63, 153, 142, 127, 125, 92, 108, 42, 153, 156, 107, 79, 128, 127, 111, 149, 104, 10, 86, 122, 149, 153, 144, 147, 6, 58, 28, 49, 55, 151, 118, 138, 94, 109, 148, 146, 151, 136, 148, 107, 107, 131, 99, 66, 21, 1, 13, 38, 45, 16, 2, 30, 41, 12, 37, 5, 14, 81, 151, 135, 114, 132, 154, 138, 142, 151, 150, 150, 149, 118, 20, 154, 116, 5, 42, 67, 52, 95, 130, 142, 152, 110, 152, 153, 98, 152, 151, 154, 135, 145, 145, 133, 137, 125, 28, 64, 42, 106, 79, 69, 140, 96, 138, 155, 79, 77, 114, 118, 73, 52, 
+#> 91, 18, 139, 145, 115, 138, 149, 154, 154, 107, 143, 138, 134, 155, 140, 156, 42, 100, 19, 11, 46, 24, 10, 2, 20, 7, 29, 4, 44, 3, 128, 118, 118, 49, 78, 80, 64, 92, 23, 53, 87, 47, 10, 16, 3, 82, 141, 150, 142, 27, 1, 134, 22, 60, 42, 147, 151, 136, 148, 151, 118, 112, 140, 151, 121, 146, 152, 53, 135, 142, 3, 40, 27, 36, 35, 9, 20, 41, 45, 40, 44, 49, 38, 40, 37, 31, 141, 106, 154, 109, 156, 128, 115, 111, 11, 74, 6, 85, 120, 98, 105, 97, 125, 104, 103, 62, 45, 9, 74, 145, 69, 39, 136, 113, 133, 
+#> 149, 112, 49, 138, 121, 134, 144, 140, 46, 115, 101, 2, 129, 150, 154, 156, 140, 154, 155, 126, 66, 130, 140, 155, 153, 149, 133, 27, 86, 144, 108, 19, 6, 30, 40, 38, 44, 41, 38, 36, 44, 38, 41, 39, 38, 32, 8, 8, 9, 69, 80, 87, 121, 130, 129, 114, 125, 149, 106, 133, 113, 106, 35, 74, 10, 81, 155, 130, 147, 148, 142, 149, 151, 151, 126, 128, 139, 108, 152, 145, 130, 127, 2, 30, 26, 15, 12, 7, 42, 43, 44, 41, 35, 38, 40, 17, 131, 115, 80, 140, 152, 66, 76, 102, 147, 153, 154, 154, 135, 126, 139, 131, 
+#> 98, 132, 45, 6, 42, 41, 26, 43, 37, 36, 40, 40, 34, 31, 39, 48, 33, 11, 23, 29, 30, 17, 4, 10, 8, 4, 15, 70, 1, 95, 157, 142, 145, 148, 122, 122, 139, 149, 147, 154, 155, 126, 57, 68, 7, 115, 69, 132, 150, 123, 135, 155, 149, 151, 151, 142, 146, 3, 6, 13, 70, 153, 113, 120, 107, 133, 154, 144, 153, 96, 43, 3, 1, 1, 9, 33, 53, 9, 46, 45, 42, 37, 31, 12, 37, 32, 31, 18, 4, 58, 155, 7, 141, 153, 143, 154, 148, 154, 152, 152, 142, 148, 150, 147, 120, 106, 73, 97, 5, 51, 49, 47, 37, 49, 41, 25, 21, 5, 
+#> 45, 46, 38, 43, 41, 43, 35, 33, 37, 32, 36, 5, 12, 12, 26, 14, 30, 38, 47, 48, 43, 40, 41, 41, 31, 1, 144, 100, 123, 157, 126, 138, 154, 154, 154, 152, 153, 22, 33, 40, 4, 64, 72, 105, 85, 94, 114, 40, 97, 58, 37, 7, 121, 130, 153, 141, 149, 152, 133, 130, 95, 40, 50, 35, 41, 11, 25, 40, 43, 43, 33, 21, 34, 27, 18, 27, 31, 29, 44, 42, 36, 38, 48, 35, 38, 22, 13, 45, 51, 35, 23, 38, 12, 39, 14, 14, 37, 54, 110, 153, 132, 151, 145, 120, 135, 153, 141, 138, 133, 131, 115, 147, 140, 103, 93, 17, 17, 
+#> 49, 11, 8, 32, 155, 149, 151, 145, 144, 147, 136, 61, 116, 147, 39, 51, 64, 43, 133, 92, 125, 137, 147, 150, 123, 89, 66, 42, 12, 23, 38, 35, 23, 13, 40, 42, 37, 34, 33, 33, 7, 2, 8, 21, 31, 32, 43, 121, 104, 123, 119, 84, 60, 146, 148, 102, 123, 112, 94, 60, 8, 1, 39, 38, 25, 41, 37, 36, 5, 45, 50, 39, 38, 60, 57, 28, 17, 3, 7, 15, 34, 46, 51, 56, 45, 52, 37, 30, 43, 32, 35, 29, 17, 23, 35, 24, 29, 38, 39, 23, 43, 40, 40, 42, 35, 39, 37, 34, 43, 35, 32, 22, 25, 16, 31, 19, 2, 42, 45, 49, 67, 49, 
+#> 34, 55, 13, 47, 35, 12, 136, 151, 155, 91, 138, 153, 153, 152, 144, 153, 62, 155, 122, 95, 7, 6, 68, 101, 148, 141, 148, 143, 128, 65, 63, 59, 19, 38, 20, 16, 1, 69, 136, 150, 79, 140, 145, 149, 118, 144, 153, 150, 141, 141, 151, 125, 142, 15, 26, 27, 48, 56, 58, 59, 55, 50, 43, 55, 40, 59, 53, 38, 1, 8, 12, 10, 24, 18, 5, 35, 33, 38, 30, 45, 43, 46, 34, 14, 21, 30, 23, 11, 3, 22, 154, 153, 153, 153, 155, 154, 153, 155, 152, 109, 130, 125, 135, 12, 50, 14, 148, 151, 154, 152, 151, 141, 147, 147, 
+#> 147, 120, 114, 146, 149, 107, 75, 2, 39, 2, 1, 3, 52, 49, 94, 96, 128, 131, 71, 17, 94, 147, 61, 75, 16, 91, 94, 85, 50, 55, 22, 44, 14, 2, 3, 13, 31, 37, 42, 39, 43, 33, 37, 34, 29, 33, 32, 31, 19, 38, 35, 26, 2, 2, 21, 45, 42, 41, 44, 26, 21, 39, 16, 8, 1, 2, 36, 37, 35, 31, 24, 34, 38, 31, 35, 30, 27, 28, 6, 19, 20, 12, 103, 102, 130, 135, 126, 153, 148, 113, 140, 112, 134, 137, 153, 143, 126, 35, 82, 35, 42, 10, 1, 43, 119, 121, 135, 124, 121, 66, 81, 17, 64, 85, 20, 110, 26, 108, 140, 145, 152, 
+#> 143, 138, 143, 127, 112, 102, 103, 28, 16, 45, 2, 51, 44, 38, 42, 36, 24, 29, 32, 17, 14, 28, 5, 11, 11, 24, 32, 38, 32, 32, 35, 40, 47, 40, 34, 28, 27, 25, 25, 22, 23, 30, 3, 96, 151, 112, 111, 127, 150, 149, 116, 145, 52, 53, 137, 128, 126, 17, 7, 142, 153, 142, 150, 152, 149, 144, 130, 130, 155, 135, 154, 119, 57, 5, 31, 85, 111, 117, 93, 127, 120, 25, 141, 116, 121, 140, 130, 116, 121, 110, 88, 97, 37, 64, 19, 109, 117, 145, 139, 146, 146, 64, 134, 152, 149, 140, 99, 100, 90, 42, 58, 18, 10, 
+#> 6, 3, 79, 82, 113, 116, 136, 149, 127, 117, 131, 108, 69, 66, 33, 14, 51, 36, 22, 134, 120, 126, 131, 135, 130, 122, 139, 130, 129, 115, 44, 27, 152, 153, 147, 106, 119, 143, 138, 128, 154, 146, 138, 128, 143, 103, 125, 93, 9, 37, 9, 40, 4, 14, 101, 150, 154, 150, 147, 148, 135, 145, 101, 47, 151, 150, 132, 151, 147, 147, 79, 38, 9, 41, 43, 41, 41, 49, 40, 57, 42, 49, 51, 50, 29, 26, 23, 24, 21, 22, 22, 20, 5, 1, 1, 11, 117, 153, 157, 85, 133, 139, 156, 154, 110, 70, 142, 45, 62, 144, 117, 82, 153, 
+#> 153, 119, 143, 108, 24, 135, 77, 127, 71, 9, 37, 134, 137, 153, 154, 152, 149, 146, 131, 108, 91, 145, 142, 107, 140, 65, 21, 91, 89, 90, 72, 24, 33, 39, 109, 105, 66, 32, 24, 57, 8, 21, 33, 42, 36, 43, 47, 33, 23, 32, 8, 18, 2, 4, 4, 137, 105, 135, 119, 130, 126, 44, 22, 84, 147, 146, 129, 127, 151, 140, 82, 4, 9, 29, 149, 147, 152, 143, 148, 155, 147, 112, 18, 114, 148, 133, 121, 6, 109, 120, 99, 136, 151, 154, 142, 49, 88, 146, 149, 153, 137, 119, 82, 132, 17, 15, 10, 10, 100, 132, 153, 118, 153, 
+#> 148, 13, 133, 12, 45, 45, 51, 39, 42, 50, 41, 44, 45, 22, 35, 35, 32, 24, 25, 23, 21, 42, 40, 37, 35, 34, 34, 39, 30, 11, 7, 3, 107, 62, 142, 146, 145, 150, 155, 112, 135, 117, 67, 7, 34, 3, 22, 39, 31, 39, 4, 39, 38, 38, 27, 12, 20, 31, 8, 4, 28, 38, 42, 40, 36, 9, 10, 13, 10, 126, 155, 155, 154, 154, 154, 155, 156, 152, 154, 149, 155, 157, 157, 8, 155, 153, 116, 147, 143, 135, 142, 139, 123, 130, 150, 126, 54, 14, 13, 1, 13, 22, 43, 37, 37, 46, 46, 40, 36, 42, 30, 26, 8, 16, 16, 8, 18, 36, 48, 
+#> 39, 22, 27, 11, 6, 44, 40, 36, 37, 34, 43, 12, 18, 35, 33, 4, 1, 36, 9, 17, 27, 42, 48, 40, 43, 37, 39, 39, 35, 34, 38, 33, 43, 44, 35, 36, 19, 1, 48, 39, 30, 37, 35, 29, 33, 38, 33, 28, 29, 19, 20, 33, 37, 30, 25, 16, 144, 155, 152, 151, 145, 150, 154, 154, 146, 139, 148, 154, 148, 125, 89, 11, 95, 114, 82, 83, 9, 1, 3, 77, 133, 98, 150, 149, 150, 154, 153, 154, 123, 153, 145, 79, 85, 95, 108, 90, 128, 21, 120, 120, 107, 115, 92, 113, 91, 93, 85, 39, 3, 4, 16, 150, 152, 151, 68, 154, 134, 121, 140, 
+#> 122, 106, 129, 147, 112, 72, 19, 55, 3, 101, 15, 19, 23, 19, 21, 15, 41, 40, 13, 27, 44, 51, 52, 9, 29, 33, 9, 5, 47, 33, 18, 37, 35, 30, 32, 45, 11, 31, 42, 41, 35, 8, 38, 35, 34, 16, 29, 24, 93, 78, 103, 138, 134, 120, 122, 83, 144, 140, 15, 89, 35, 40, 49, 39, 48, 45, 49, 33, 36, 39, 38, 33, 21, 13, 27, 1, 3, 52, 104, 140, 138, 153, 130, 148, 78, 144, 138, 97, 90, 26, 82, 81, 65, 20, 126, 112, 75, 148, 40, 121, 26, 18, 23, 5, 8, 123, 133, 154, 155, 154, 101, 152, 155, 154, 150, 154, 144, 152, 
+#> 118, 139, 127, 45, 59, 17, 142, 155, 145, 124, 110, 122, 124, 121, 85, 119, 125, 101, 153, 151, 127, 117, 127, 30, 26, 2, 24, 150, 145, 152, 149, 142, 137, 138, 144, 122, 63, 89, 26, 44, 49, 43, 36, 21, 33, 25, 3, 19, 20, 34, 32, 38, 37, 35, 43, 27, 43, 52, 38, 1, 2, 47, 53, 48, 55, 61, 34, 75, 61, 18, 53, 5, 26, 3, 2, 4, 7, 150, 147, 154, 150, 135, 14, 129, 8, 56, 84, 109, 150, 51, 13, 33, 1, 42, 40, 45, 36, 37, 31, 34, 29, 35, 28, 3, 33, 6, 66, 80, 39, 76, 80, 97, 76, 75, 68, 47, 69, 59, 33, 20, 
+#> 39, 37, 36, 40, 45, 49, 42, 42, 39, 24, 29, 31, 26, 24, 12, 19, 13, 8, 36, 114, 154, 140, 134, 148, 43, 78, 83, 10, 26, 61, 118, 149, 153, 139, 154, 149, 150, 147, 155, 150, 149, 124, 144, 135, 30, 70, 15, 89, 151, 139, 155, 153, 151, 154, 140, 152, 156, 134, 24, 87, 64, 8, 38, 12, 63, 145, 154, 156, 143, 152, 127, 144, 81, 148, 143, 143, 149, 143, 45, 59, 76, 3, 6, 19, 20, 35, 37, 28, 37, 32, 40, 23, 9, 21, 21, 99, 107, 51, 141, 149, 151, 154, 132, 144, 106, 19, 98, 26, 2, 26, 6, 53, 40, 47, 38, 
+#> 40, 38, 45, 41, 41, 30, 44, 24, 32, 39, 29, 41, 34, 35, 47, 48, 31, 43, 33, 24, 35, 39, 33, 3, 47, 45, 51, 43, 41, 38, 37, 29, 29, 32, 42, 35, 10, 37, 42, 40, 37, 41, 35, 35, 36, 38, 18, 28, 13, 6, 27, 27, 20, 13, 1, 9, 64, 149, 156, 148, 154, 152, 115, 119, 29, 117, 115, 129, 25, 85, 116, 50, 14, 12, 4, 15, 40, 37, 35, 38, 34, 31, 34, 32, 26, 9, 23, 13, 1, 1, 20, 35, 39, 52, 44, 40, 36, 31, 34, 33, 37, 15, 12, 21, 9, 25, 154, 153, 113, 154, 153, 138, 152, 156, 135, 133, 11, 155, 153, 47, 75, 15, 
+#> 12, 27, 40, 42, 44, 34, 40, 11, 16, 17, 5, 34, 33, 2, 1, 47, 51, 51, 53, 51, 27, 13, 19, 10, 1, 1, 1, 72, 143, 129, 135, 154, 152, 146, 137, 145, 128, 127, 105, 139, 5, 104, 90, 99, 5, 10, 130, 109, 130, 108, 130, 104, 120, 112, 140, 132, 128, 106, 109, 82, 85, 54, 14, 152, 144, 133, 146, 153, 139, 132, 131, 147, 143, 138, 148, 64, 18, 38, 125, 142, 120, 132, 146, 133, 122, 138, 152, 122, 44, 92, 115, 57, 26, 49, 8, 37, 36, 36, 41, 31, 38, 34, 34, 33, 40, 35, 34, 28, 33, 26, 24, 8, 35, 34, 33, 36, 
+#> 36, 39, 34, 25, 29, 29, 25, 23, 25, 4, 9, 151, 156, 145, 137, 150, 150, 138, 30, 59, 99, 16, 97, 2, 20, 3, 128, 111, 126, 126, 140, 128, 128, 105, 71, 131, 36, 59, 114, 103, 118, 115, 91, 56, 61, 26, 148, 149, 154, 155, 156, 146, 150, 106, 37, 133, 142, 48, 78, 128, 66, 26, 41, 75, 20, 5, 22, 7, 27, 34, 40, 37, 49, 29, 41, 35, 13, 1, 129, 152, 149, 137, 156, 126, 148, 152, 156, 106, 128, 149, 64, 65, 4, 108, 3, 152, 124, 145, 128, 134, 147, 143, 109, 98, 21, 51, 45, 45, 10, 4, 31, 27, 32, 14, 2, 
+#> 82, 30, 43, 31, 23, 23, 11, 36, 40, 39, 44, 44, 42, 36, 38, 39, 29, 31, 15, 29, 19, 30, 11, 13, 15, 80, 146, 132, 155, 121, 46, 6, 45, 89, 87, 35, 82, 124, 150, 148, 138, 154, 152, 153, 152, 150, 151, 150, 125, 151, 148, 152, 125, 120, 135, 31, 4, 3, 4, 86, 132, 139, 155, 152, 142, 125, 138, 138, 121, 8, 30, 39, 44, 38, 46, 45, 36, 30, 35, 38, 37, 24, 1, 117, 153, 152, 12, 154, 155, 138, 148, 19, 78, 142, 125, 2, 30, 65, 92, 152, 153, 149, 154, 133, 148, 137, 150, 154, 151, 140, 143, 141, 68, 73, 
+#> 4, 9, 149, 153, 119, 104, 152, 138, 144, 146, 145, 116, 25, 14, 128, 128, 131, 73, 148, 155, 141, 93, 73, 77, 127, 121, 66, 39, 6, 123, 85, 145, 110, 135, 143, 98, 91, 88, 86, 40, 105, 138, 154, 134, 154, 107, 141, 58, 20, 138, 151, 145, 120, 132, 139, 154, 132, 141, 153, 76, 139, 116, 3, 31, 36, 32, 37, 4, 34, 35, 6, 18, 33, 38, 15, 14, 24, 13, 33, 25, 13, 23, 37, 24, 30, 34, 32, 11, 20, 27, 17, 15, 24, 85, 146, 154, 142, 115, 142, 116, 146, 150, 136, 140, 48, 56, 90, 78, 110, 88, 70, 6, 96, 139, 
+#> 151, 118, 153, 138, 154, 81, 148, 150, 154, 142, 155, 18, 149, 139, 139, 142, 50, 72, 20, 111, 124, 149, 154, 152, 156, 149, 151, 140, 144, 98, 150, 92, 76, 151, 87, 154, 154, 151, 153, 156, 151, 145, 60, 63, 10, 30, 42, 39, 47, 47, 49, 42, 43, 42, 43, 36, 40, 6, 26, 38, 3, 37, 35, 32, 36, 35, 12, 17, 25, 22, 28, 7, 37, 32, 29, 33, 35, 5, 10, 7, 17, 4, 7, 41, 37, 27, 2, 37, 30, 151, 154, 149, 130, 154, 100, 31, 146, 126, 10, 114, 138, 102, 34, 36, 33, 27, 2, 7, 5, 126, 145, 149, 153, 155, 126, 142, 
+#> 101, 154, 152, 106, 13, 90, 113, 78, 81, 23, 134, 107, 154, 154, 129, 150, 121, 48, 16, 64, 39, 16, 39, 35, 25, 25, 23, 3, 5, 18, 35, 30, 1, 89, 149, 135, 154, 151, 152, 139, 136, 69, 8, 37, 37, 29, 60, 60, 6, 52, 48, 55, 55, 45, 50, 53, 54, 45, 44, 33, 38, 30, 21, 8, 14, 50, 88, 104, 66, 10, 60, 49, 32, 123, 144, 116, 100, 66, 107, 119, 98, 36, 31, 62, 81, 49, 2, 12, 20, 126, 121, 100, 151, 147, 118, 60, 102, 86, 48, 141, 115, 36, 3, 2, 1, 50, 7, 28, 44, 31, 13, 46, 35, 6, 36, 43, 6, 30, 22, 10, 
+#> 6, 37, 36, 10, 24, 17, 14, 11, 14, 10, 17, 21, 33, 30, 12, 35, 37, 40, 33, 31, 41, 33, 35, 1, 12, 24, 151, 156, 155, 154, 145, 126, 153, 152, 135, 81, 15, 75, 73, 118, 107, 132, 120, 121, 120, 129, 130, 109, 117, 105, 104, 117, 115, 88, 48, 3, 53, 65, 32, 93, 120, 135, 140, 130, 119, 40, 39, 43, 42, 44, 37, 37, 28, 32, 13, 13, 31, 16, 13, 25, 14, 148, 136, 147, 145, 124, 136, 42, 87, 80, 62, 127, 151, 155, 156, 147, 152, 112, 155, 144, 148, 119, 142, 141, 147, 153, 138, 152, 150, 138, 149, 149, 117, 
+#> 144, 143, 14, 26, 39, 39, 43, 44, 9, 48, 42, 44, 36, 35, 33, 30, 25, 19, 25, 19, 10, 44, 43, 16, 33, 34, 35, 34, 6, 31, 32, 31, 26, 32, 34, 33, 35, 41, 45, 45, 149, 144, 143, 150, 150, 156, 137, 155, 89, 148, 6, 37, 117, 98, 136, 132, 129, 103, 113, 9, 22, 52, 23, 83, 49, 64, 56, 36, 15, 40, 37, 39, 40, 37, 37, 24, 24, 20, 7, 1, 51, 46, 24, 11, 28, 40, 63, 22, 14, 31, 32, 31, 31, 24, 1, 34, 125, 131, 148, 78, 124, 125, 150, 146, 141, 144, 111, 24, 24, 29, 1, 87, 78, 60, 149, 137, 153, 118, 132, 88, 
+#> 41, 6, 63, 154, 101, 51, 98, 112, 117, 53, 58, 147, 137, 152, 155, 149, 151, 150, 154, 143, 105, 8, 12, 119, 3, 92, 144, 60, 99, 124, 136, 126, 21, 56, 88, 155, 119, 32, 53, 51, 5, 111, 138, 140, 152, 141, 44, 150, 45, 83, 60, 50, 54, 2, 11, 58, 135, 147, 152, 154, 156, 151, 105, 148, 143, 98, 41, 85, 55, 38, 5, 36, 77, 151, 154, 142, 154, 155, 115, 91, 151, 130, 85, 64, 19, 149, 120, 126, 139, 137, 116, 124, 75, 3, 24, 32, 43, 30, 34, 33, 28, 35, 11, 19, 15, 29, 7, 21, 11, 36, 24, 27, 18, 109, 138, 
+#> 138, 135, 146, 130, 136, 152, 15, 137, 74, 16, 32, 102, 156, 151, 131, 146, 157, 142, 149, 150, 95, 63, 138, 108, 147, 107, 132, 145, 34, 79, 4, 22, 4, 43, 26, 10, 23, 30, 3, 29, 16, 37, 40, 31, 27, 11, 10, 9, 33, 27, 21, 14, 1, 16, 1, 15, 33, 29, 36, 4, 12, 16, 29, 16, 7, 15, 3, 146, 93, 58, 137, 125, 122, 110, 64, 84, 53, 74, 34, 1, 2, 9, 34, 41, 48, 38, 35, 42, 4, 46, 56, 37, 7, 18, 112, 149, 140, 113, 152, 156, 147, 146, 151, 148, 123, 140, 143, 69, 108, 10, 91, 24, 96, 77, 11, 74, 88, 115, 143, 
+#> 100, 146, 118, 129, 137, 138, 63, 134, 127, 136, 85, 61, 82, 14, 156, 137, 115, 147, 124, 118, 132, 1, 149, 154, 149, 149, 152, 110, 149, 116, 151, 153, 80, 13, 12, 38, 35, 28, 39, 29, 15, 29, 12, 23, 28, 28, 26, 23, 18, 33, 22, 18, 45, 21, 44, 35, 39, 41, 14, 25, 21, 37, 2, 30, 38, 3, 36, 35, 33, 7, 1, 12, 23, 11, 27, 28, 24, 30, 1, 4, 34, 17, 51, 86, 149, 149, 153, 152, 147, 114, 7, 104, 3, 145, 137, 145, 149, 115, 150, 155, 155, 149, 109, 92, 44, 46, 101, 3, 22, 4, 47, 38, 29, 37, 37, 34, 20, 
+#> 4, 28, 10, 8, 1, 37, 42, 29, 32, 12, 1, 43, 19, 9, 3, 1, 125, 155, 147, 129, 144, 123, 146, 149, 144, 134, 106, 67, 3, 80, 122, 131, 117, 128, 133, 106, 130, 24, 62, 86, 58, 32, 147, 153, 155, 143, 148, 127, 131, 25, 69, 103, 20, 49, 3, 104, 135, 102, 155, 155, 153, 155, 151, 155, 154, 48, 102, 31, 155, 85, 132, 127, 113, 108, 15, 124, 94, 11, 35, 33, 40, 36, 45, 51, 42, 40, 34, 32, 33, 34, 42, 26, 10, 2, 30, 40, 43, 33, 37, 5, 31, 30, 30, 30, 28, 22, 7, 155, 78, 111, 112, 110, 59, 3, 3, 12, 140, 
+#> 157, 146, 156, 149, 155, 157, 146, 152, 154, 157, 153, 154, 156, 134, 135, 115, 116, 123, 135, 124, 5, 17, 52, 47, 42, 41, 41, 44, 35, 26, 24, 21, 28, 6, 68, 125, 122, 112, 4, 87, 140, 91, 82, 42, 102, 15, 109, 102, 53, 57, 14, 54, 40, 48, 132, 150, 8, 2, 110, 151, 143, 157, 109, 127, 15, 6, 83, 154, 152, 129, 148, 141, 70, 7, 93, 50, 1, 1, 28, 33, 39, 37, 47, 40, 37, 40, 39, 38, 35, 17, 26, 7, 26, 2, 32, 148, 141, 143, 156, 143, 144, 140, 150, 151, 139, 142, 136, 98, 67, 48, 95, 144, 154, 143, 80, 
+#> 5, 9, 146, 155, 138, 1, 155, 56, 55, 98, 4, 45, 2, 4, 44, 41, 36, 22, 11, 37, 30, 19, 55, 145, 127, 151, 132, 144, 155, 125, 151, 146, 140, 139, 149, 106, 2, 98, 17, 8, 26, 6, 154, 127, 61, 43, 143, 148, 118, 138, 147, 154, 150, 148, 129, 88, 22, 43, 151, 139, 154, 154, 152, 108, 14, 125, 154, 154, 134, 140, 102, 150, 152, 147, 81, 34, 88, 40, 13, 34, 38, 118, 3, 51, 42, 7, 85, 100, 95, 83, 57, 61, 45, 52, 31, 4, 1, 9, 14, 3, 44, 37, 37, 30, 38, 27, 31, 27, 30, 5, 19, 36, 28, 40, 15, 2, 32, 41, 33, 
+#> 33, 21, 7, 13, 25, 75, 22, 86, 149, 21, 38, 64, 138, 154, 8, 146, 113, 142, 7, 146, 124, 106, 92, 22, 65, 107, 136, 143, 152, 132, 139, 127, 111, 105, 82, 89, 41, 27, 71, 6, 5, 115, 139, 149, 133, 142, 146, 77, 10, 13, 128, 144, 65, 129, 142, 144, 146, 84, 49, 150, 140, 138, 86, 45, 83, 95, 71, 3, 29, 31, 24, 37, 29, 33, 32, 27, 24, 25, 27, 25, 29, 35, 15, 18, 33, 41, 39, 28, 13, 3, 11, 26, 141, 152, 155, 154, 149, 150, 139, 117, 105, 27, 31, 1, 6, 2, 3, 38, 42, 9, 36, 23, 36, 34, 23, 4, 40, 41, 
+#> 38, 40, 37, 41, 9, 3, 22, 138, 54, 89, 145, 3, 100, 46, 65, 8, 128, 154, 134, 51, 142, 106, 76, 5, 138, 151, 145, 148, 154, 150, 153, 28, 90, 141, 154, 152, 151, 150, 119, 102, 119, 74, 9, 1, 139, 147, 105, 26, 152, 92, 134, 157, 147, 75, 39, 134, 26, 71, 128, 102, 21, 99, 1, 50, 100, 82, 98, 110, 107, 26, 36, 1, 53, 155, 148, 147, 152, 150, 97, 140, 150, 152, 134, 81, 82, 4, 9, 27, 16, 40, 37, 38, 39, 38, 21, 6, 31, 25, 5, 20, 24, 12, 19, 142, 89, 13, 153, 144, 146, 67, 138, 152, 145, 53, 17, 9, 
+#> 125, 109, 87, 95, 86, 69, 91, 103, 92, 66, 77, 31, 44, 14, 141, 139, 152, 154, 153, 144, 151, 152, 145, 146, 153, 136, 106, 26, 5, 40, 40, 40, 43, 39, 37, 26, 7, 47, 41, 45, 25, 3, 84, 152, 151, 152, 142, 151, 155, 141, 154, 149, 140, 141, 145, 147, 103, 59, 108, 144, 151, 142, 136, 155, 145, 141, 146, 128, 3, 38, 148, 154, 151, 130, 145, 125, 146, 139, 136, 144, 94, 7, 83, 125, 116, 151, 141, 142, 137, 151, 147, 140, 134, 122, 131, 120, 119, 86, 64, 4, 2, 39, 41, 44, 35, 38, 41, 37, 36, 43, 41, 
+#> 42, 36, 67, 131, 99, 90, 144, 127, 150, 142, 146, 115, 73, 92, 130, 96, 64, 50, 17, 51, 50, 4, 30, 7, 2, 33, 33, 22, 30, 40, 39, 23, 5, 8, 2, 144, 152, 156, 152, 150, 151, 149, 117, 41, 147, 113, 21, 16, 24, 43, 36, 34, 43, 42, 16, 7, 17, 17, 5, 1, 4, 24, 41, 37, 40, 41, 42, 52, 38, 41, 40, 39, 39, 41, 40, 40, 39, 36, 33, 39, 21, 16, 116, 131, 155, 143, 141, 105, 136, 21, 107, 122, 47, 22, 151, 147, 156, 144, 153, 149, 136, 124, 105, 117, 136, 145, 150, 151, 117, 145, 128, 65, 56, 58, 10, 50, 53, 
+#> 106, 111, 110, 99, 87, 90, 20, 128, 122, 79, 55, 42, 5, 5, 55, 47, 52, 46, 72, 56, 54, 51, 40, 49, 43, 25, 15, 2, 15, 36, 38, 33, 35, 31, 28, 30, 20, 1, 46, 63, 87, 57, 80, 89, 114, 133, 126, 113, 37, 48, 122, 84, 30, 6, 23, 42, 38, 34, 36, 39, 16, 8, 10, 3, 5, 3, 24, 29, 32, 18, 2, 15, 137, 130, 154, 156, 151, 155, 154, 115, 48, 100, 140, 114, 18, 136, 50, 55, 19, 20, 32, 56, 55, 60, 37, 7, 2, 27, 129, 91, 110, 145, 154, 36, 106, 138, 55, 55, 22, 117, 101, 15, 35, 39, 40, 37, 35, 38, 19, 14, 21, 
+#> 102, 119, 155, 149, 138, 85, 37, 128, 29, 94, 74, 136, 144, 25, 94, 131, 99, 8, 74, 6, 35, 1, 28, 134, 156, 153, 158, 153, 141, 154, 150, 153, 150, 141, 124, 101, 109, 54, 11, 9, 6, 131, 135, 130, 142, 141, 134, 150, 144, 140, 131, 66, 16, 83, 130, 126, 143, 128, 144, 111, 123, 124, 103, 39, 40, 40, 31, 57, 52, 34, 39, 11, 61, 24, 24, 140, 113, 31, 11, 92, 145, 144, 152, 152, 148, 115, 127, 141, 144, 138, 49, 33, 12, 33, 34, 28, 43, 48, 63, 23, 69, 48, 43, 29, 22, 1, 133, 144, 126, 153, 128, 153, 
+#> 155, 144, 152, 134, 127, 81, 31, 128, 153, 121, 11, 8, 107, 43, 80, 72, 11, 136, 99, 37, 115, 152, 107, 141, 125, 93, 28, 63, 62, 26, 79, 14, 13, 1, 23, 43, 36, 41, 36, 23, 16, 32, 35, 23, 5, 3, 20, 10, 6, 53, 74, 58, 42, 48, 9, 33, 45, 8, 27, 117, 124, 108, 142, 153, 158, 134, 132, 150, 140, 149, 119, 122, 50, 8, 40, 53, 146, 152, 150, 144, 153, 149, 148, 151, 139, 106, 126, 101, 85, 80, 129, 91, 42, 42, 37, 40, 39, 34, 36, 13, 8, 21, 14, 2, 2, 129, 154, 157, 150, 151, 154, 152, 104, 122, 133, 35, 
+#> 27, 21, 3, 141, 148, 151, 2, 29, 121, 147, 142, 134, 140, 149, 153, 131, 140, 119, 89, 21, 18, 131, 152, 141, 126, 141, 120, 141, 138, 127, 119, 121, 34, 151, 152, 152, 152, 152, 151, 153, 154, 162, 157, 157, 157, 152, 141, 148, 117, 139, 136, 69, 19, 66, 14, 47, 42, 35, 27, 34, 10, 23, 28, 2, 19, 6, 7, 10, 1, 39, 33, 21, 38, 34, 30, 36, 34, 27, 25, 15, 33, 37, 36, 34, 21, 7, 26, 51, 33, 33, 40, 43, 44, 7, 28, 55, 20, 14, 16, 9, 7, 31, 145, 96, 42, 145, 141, 151, 108, 142, 79, 75, 127, 88, 13, 6, 
+#> 37, 40, 25, 14, 25, 3, 37, 57, 34, 5, 6, 32, 34, 7, 96, 142, 127, 146, 147, 150, 144, 150, 144, 153, 153, 123, 65, 143, 122, 108, 144, 144, 21, 43, 40, 44, 39, 44, 45, 51, 43, 39, 36, 35, 35, 26, 27, 35, 31, 20, 10, 11, 13, 21, 141, 128, 127, 68, 6, 34, 51, 109, 149, 20, 121, 73, 43, 131, 73, 103, 108, 6, 7, 5, 23, 155, 154, 148, 155, 137, 139, 121, 19, 155, 155, 145, 146, 151, 139, 139, 126, 131, 130, 120, 111, 54, 23, 3, 86, 151, 146, 147, 153, 149, 147, 145, 151, 144, 160, 148, 116, 111, 88, 137, 
+#> 142, 151, 119, 151, 153, 135, 152, 146, 148, 145, 92, 40, 93, 57, 106, 5, 68, 72, 98, 6, 16, 12, 11, 2, 19, 31, 37, 32, 30, 25, 28, 2, 37, 4, 6, 30, 67, 76, 82, 94, 111, 92, 54, 37, 26, 26, 46, 26, 11, 40, 26, 3, 15, 12, 151, 152, 149, 142, 108, 145, 138, 134, 95, 122, 68, 53, 9, 113, 136, 134, 154, 135, 149, 149, 153, 138, 69, 100, 31, 60, 81, 107, 31, 80, 141, 150, 141, 143, 141, 138, 129, 113, 20, 22, 51, 4, 22, 20, 31, 39, 38, 49, 47, 47, 43, 42, 12, 9, 5, 43, 46, 63, 50, 71, 62, 13, 53, 34, 
+#> 38, 32, 35, 42, 34, 34, 32, 40, 37, 2, 27, 36, 1, 21, 17, 33, 35, 5, 12, 30, 23, 8, 4, 144, 133, 24, 144, 144, 144, 120, 146, 156, 142, 145, 135, 6, 7, 3, 88, 130, 147, 152, 154, 155, 154, 154, 155, 155, 156, 150, 159, 157, 137, 133, 21, 145, 157, 138, 141, 151, 148, 149, 148, 153, 152, 152, 158, 141, 156, 134, 36, 101, 31, 30, 138, 152, 153, 149, 146, 136, 147, 153, 100, 145, 146, 125, 142, 131, 102, 131, 131, 133, 106, 91, 147, 20, 33, 34, 39, 31, 24, 30, 35, 33, 39, 38, 38, 39, 38, 22, 7, 10, 
+#> 154, 154, 139, 156, 154, 155, 156, 138, 154, 130, 157, 163, 141, 151, 150, 155, 72, 39, 50, 44, 21, 45, 31, 28, 29, 23, 25, 18, 52, 46, 31, 6, 27, 1, 3, 152, 143, 145, 152, 153, 156, 153, 146, 146, 144, 151, 134, 157, 156, 146, 125, 110, 132, 152, 150, 148, 146, 139, 153, 162, 140, 156, 156, 155, 129, 130, 148, 132, 133, 103, 147, 129, 15, 49, 36, 147, 150, 142, 150, 149, 151, 153, 160, 159, 162, 144, 136, 57, 56, 10, 83, 25, 122, 153, 153, 151, 153, 154, 153, 155, 156, 161, 145, 150, 158, 155, 160, 
+#> 147, 150, 139, 129, 120, 112, 137, 85, 5, 22, 39, 40, 39, 35, 42, 38, 34, 39, 41, 35, 34, 32, 39, 30, 38, 34, 2, 3, 45, 46, 39, 45, 45, 41, 47, 52, 46, 42, 39, 17, 21, 28, 8, 8, 19, 54, 19, 6, 27, 153, 155, 154, 152, 151, 156, 151, 148, 106, 82, 28, 11, 22, 109, 126, 98, 132, 113, 107, 138, 136, 101, 127, 140, 129, 116, 84, 35, 9, 138, 8, 147, 151, 153, 139, 151, 153, 149, 148, 154, 152, 39, 109, 30, 3, 2, 85, 154, 155, 154, 151, 150, 151, 145, 79, 124, 154, 137, 100, 8, 113, 157, 76, 127, 138, 132, 
+#> 147, 153, 45, 135, 106, 109, 3, 33, 38, 36, 37, 39, 39, 45, 19, 9, 23, 50, 12, 10, 15, 15, 45, 36, 40, 38, 38, 43, 41, 41, 39, 43, 40, 27, 9, 25, 35, 31, 97, 98, 110, 103, 125, 107, 129, 136, 135, 150, 110, 126, 42, 66, 71, 1, 10, 35, 36, 27, 32, 33, 33, 34, 15, 24, 11, 19, 127, 147, 127, 129, 93, 52, 147, 147, 147, 144, 138, 68, 19, 18, 124, 117, 102, 146, 154, 127, 139, 148, 122, 142, 120, 148, 75, 6, 56, 151, 133, 149, 155, 151, 130, 100, 138, 121, 135, 20, 40, 29, 87, 53, 75, 5, 54, 134, 120, 
+#> 144, 153, 162, 152, 150, 106, 125, 33, 46, 27, 81, 148, 152, 135, 151, 152, 159, 142, 162, 130, 162, 163, 143, 67, 112, 70, 34, 67, 79, 116, 138, 133, 112, 118, 131, 150, 142, 15, 107, 86, 69, 60, 50, 9, 48, 61, 37, 46, 5, 41, 42, 31, 29, 31, 28, 50, 49, 24, 45, 56, 7, 144, 147, 152, 152, 151, 145, 154, 148, 137, 146, 80, 25, 48, 144, 160, 154, 107, 122, 2, 148, 151, 151, 152, 162, 156, 142, 33, 19, 123, 151, 157, 154, 148, 71, 28, 3, 142, 33, 39, 6, 128, 153, 142, 157, 151, 149, 108, 135, 15, 124, 
+#> 156, 126, 60, 39, 23, 15, 35, 5, 34, 35, 32, 35, 44, 49, 40, 38, 35, 38, 41, 39, 39, 35, 34, 12, 22, 5, 23, 57, 53, 58, 36, 38, 39, 55, 20, 29, 3, 3, 5, 30, 38, 43, 25, 54, 73, 35, 39, 41, 44, 37, 40, 34, 38, 40, 40, 37, 36, 17, 27, 20, 62, 128, 140, 151, 139, 108, 136, 34, 72, 98, 27, 18, 137, 145, 139, 143, 142, 137, 96, 82, 41, 16, 11, 150, 144, 159, 149, 148, 149, 135, 70, 153, 145, 81, 47, 52, 101, 106, 91, 152, 130, 160, 150, 135, 148, 149, 152, 105, 81, 130, 128, 122, 11, 71, 141, 108, 117, 
+#> 48, 2, 14, 36, 33, 28, 35, 50, 39, 37, 30, 11, 7, 27, 28, 50, 44, 39, 34, 36, 38, 35, 11, 23, 21, 36, 34, 34, 26, 6, 15, 50, 145, 88, 152, 163, 162, 161, 163, 144, 157, 158, 162, 156, 158, 156, 153, 155, 153, 144, 71, 24, 5, 4, 48, 68, 26, 137, 133, 148, 147, 131, 131, 115, 48, 96, 142, 149, 148, 140, 149, 133, 106, 118, 85, 5, 25, 50, 116, 51, 99, 122, 136, 161, 157, 90, 141, 46, 119, 125, 100, 138, 26, 138, 144, 153, 159, 162, 160, 148, 159, 110, 127, 49, 95, 151, 142, 125, 151, 147, 138, 148, 
+#> 161, 158, 161, 153, 155, 10, 34, 12, 2, 153, 155, 71, 144, 158, 162, 23, 157, 40, 86, 85, 59, 61, 16, 8, 9, 117, 92, 141, 123, 134, 149, 146, 149, 158, 161, 161, 153, 14, 95, 85, 87, 108, 134, 122, 126, 74, 146, 150, 140, 89, 73, 73, 146, 120, 62, 8, 35, 52, 29, 34, 39, 18, 11, 26, 15, 4, 39, 16, 28, 33, 6, 16, 26, 37, 46, 70, 57, 42, 9, 11, 4, 39, 31, 26, 62, 65, 55, 55, 57, 63, 71, 64, 41, 24, 12, 51, 62, 44, 37, 47, 38, 40, 36, 33, 38, 8, 18, 9, 9, 11, 5, 97, 73, 134, 150, 162, 161, 151, 159, 
+#> 160, 149, 3, 36, 41, 40, 39, 32, 39, 42, 22, 16, 6, 5, 13, 14, 14, 35, 114, 118, 103, 128, 128, 135, 134, 136, 142, 116, 135, 115, 46, 124, 147, 111, 140, 105, 144, 146, 144, 152, 155, 152, 154, 147, 132, 138, 108, 132, 102, 27, 154, 154, 154, 155, 162, 156, 159, 156, 158, 130, 132, 148, 146, 136, 124, 115, 103, 83, 148, 148, 165, 134, 158, 158, 143, 149, 153, 104, 47, 132, 149, 71, 27, 34, 33, 16, 43, 11, 11, 1, 18, 12, 146, 159, 161, 162, 164, 162, 162, 163, 163, 161, 157, 150, 156, 117, 155, 120, 
+#> 13, 58, 121, 159, 148, 147, 144, 142, 160, 152, 127, 142, 130, 135, 137, 121, 53, 5, 101, 134, 143, 154, 145, 163, 161, 160, 160, 162, 151, 60, 63, 40, 39, 46, 94, 110, 102, 108, 116, 7, 90, 90, 99, 114, 110, 100, 103, 91, 7, 68, 80, 79, 77, 3, 15, 12, 1, 18, 34, 32, 34, 39, 30, 34, 37, 9, 12, 35, 18, 56, 10, 29, 65, 27, 6, 12, 42, 20, 29, 4, 38, 42, 59, 47, 64, 60, 71, 66, 67, 51, 42, 2, 74, 87, 39, 133, 160, 149, 163, 144, 150, 135, 69, 38, 11, 3, 22, 7, 40, 9, 24, 35, 31, 43, 40, 27, 30, 15, 11, 
+#> 2, 26, 37, 47, 46, 41, 40, 43, 42, 40, 58, 46, 38, 31, 12, 3, 13, 47, 48, 36, 46, 56, 47, 45, 36, 43, 56, 54, 24, 7, 31, 42, 43, 42, 36, 26, 40, 3, 4, 49, 41, 62, 24, 10, 160, 154, 134, 123, 112, 137, 144, 147, 116, 106, 111, 124, 113, 112, 22, 9, 157, 145, 153, 156, 151, 130, 152, 94, 45, 10, 8, 7, 2, 40, 44, 30, 34, 31, 33, 24, 34, 31, 31, 12, 1, 110, 132, 163, 146, 152, 17, 100, 154, 132, 24, 123, 11, 57, 66, 79, 26, 15, 137, 158, 116, 72, 8, 36, 14, 2, 48, 37, 38, 41, 36, 37, 21, 34, 32, 11, 
+#> 62, 66, 79, 63, 16, 39, 20, 3, 11, 22, 43, 43, 69, 59, 57, 58, 68, 62, 63, 56, 55, 16, 54, 61, 2, 43, 44, 12, 16, 34, 40, 35, 37, 42, 28, 40, 29, 43, 41, 148, 160, 151, 151, 133, 160, 161, 157, 162, 161, 148, 125, 152, 148, 149, 155, 150, 144, 147, 105, 91, 131, 119, 29, 15, 129, 160, 159, 160, 160, 137, 160, 122, 72, 31, 66, 52, 133, 148, 126, 114, 98, 80, 85, 151, 140, 106, 108, 79, 50, 5, 3, 121, 121, 140, 132, 151, 158, 162, 156, 160, 134, 150, 153, 13, 4, 112, 142, 126, 139, 46, 135, 27, 121, 
+#> 159, 119, 34, 2, 2, 3, 5, 50, 54, 42, 38, 48, 46, 37, 37, 53, 33, 157, 136, 162, 156, 148, 149, 156, 159, 160, 154, 160, 163, 162, 162, 162, 159, 163, 162, 107, 162, 151, 26, 95, 119, 72, 63, 157, 160, 143, 152, 133, 108, 135, 56, 75, 115, 66, 3, 31, 11, 30, 38, 42, 33, 39, 37, 26, 38, 38, 34, 37, 25, 34, 11, 2, 18, 49, 99, 138, 157, 157, 162, 160, 155, 149, 121, 134, 147, 103, 92, 45, 21, 40, 40, 42, 41, 40, 42, 46, 27, 35, 37, 40, 31, 34, 25, 33, 22, 5, 50, 45, 46, 36, 41, 41, 43, 20, 45, 3, 31, 
+#> 90, 150, 142, 121, 139, 93, 51, 33, 63, 111, 99, 117, 38, 59, 17, 24, 75, 29, 7, 95, 154, 162, 162, 161, 164, 155, 161, 162, 160, 154, 154, 133, 149, 117, 40, 92, 135, 79, 115, 129, 118, 14, 130, 47, 41, 9, 7, 161, 149, 159, 146, 128, 153, 157, 126, 10, 146, 127, 131, 67, 10, 162, 161, 141, 122, 152, 118, 122, 155, 148, 72, 128, 119, 85, 54, 67, 118, 122, 138, 114, 157, 156, 149, 38, 31, 22, 9, 38, 44, 9, 13, 153, 124, 150, 155, 142, 158, 113, 162, 163, 100, 162, 157, 147, 139, 69, 122, 106, 11, 
+#> 58, 154, 147, 161, 162, 151, 159, 161, 158, 107, 101, 45, 45, 78, 77, 58, 36, 13, 20, 143, 127, 57, 132, 110, 148, 128, 117, 152, 129, 113, 115, 12, 2, 113, 80, 142, 154, 148, 148, 135, 115, 159, 161, 161, 149, 141, 147, 114, 114, 26, 28, 34, 59, 58, 62, 50, 51, 43, 31, 1, 1, 7, 4, 100, 144, 130, 136, 155, 155, 143, 117, 148, 111, 110, 130, 120, 71, 48, 74, 153, 158, 163, 156, 160, 108, 137, 160, 160, 153, 150, 72, 34, 55, 144, 131, 155, 137, 155, 99, 21, 50, 8, 74, 157, 152, 136, 84, 95, 109, 119, 
+#> 70, 73, 109, 101, 132, 137, 100, 87, 74, 4, 156, 149, 148, 120, 129, 46, 53, 11, 4, 80, 39, 28, 54, 42, 47, 48, 30, 53, 20, 39, 50, 35, 27, 43, 11, 31, 72, 8, 15, 42, 14, 37, 37, 36, 36, 39, 38, 35, 37, 38, 19, 6, 83, 13, 17, 140, 159, 142, 108, 127, 138, 159, 158, 96, 131, 12, 11, 49, 50, 3, 148, 15, 10, 108, 117, 144, 140, 134, 128, 145, 136, 141, 138, 148, 140, 124, 117, 63, 122, 126, 67, 38, 74, 17, 3, 15, 57, 33, 59, 82, 44, 23, 46, 54, 52, 67, 57, 43, 6, 26, 6, 40, 5, 26, 2, 43, 53, 84, 38, 
+#> 20, 70, 78, 56, 11, 36, 11, 63, 45, 162, 142, 161, 159, 152, 27, 104, 130, 72, 44, 5, 13, 13, 10, 160, 158, 132, 149, 153, 113, 114, 83, 26, 17, 81, 153, 147, 152, 133, 82, 121, 114, 119, 76, 2, 21, 138, 137, 127, 126, 150, 150, 139, 146, 137, 64, 62, 21, 15, 4, 124, 140, 134, 144, 140, 125, 154, 152, 154, 128, 140, 114, 110, 134, 95, 50, 5, 122, 141, 96, 124, 104, 94, 49, 82, 42, 9, 15, 35, 38, 54, 47, 18, 27, 52, 40, 37, 18, 15, 75, 95, 106, 132, 154, 157, 121, 143, 154, 140, 160, 123, 154, 131, 
+#> 2, 120, 19, 93, 3, 10, 34, 66, 57, 54, 38, 15, 41, 41, 48, 4, 47, 17, 24, 17, 33, 35, 38, 33, 16, 65, 55, 68, 5, 71, 54, 48, 10, 5, 12, 104, 99, 156, 160, 160, 158, 158, 136, 151, 158, 137, 139, 154, 148, 132, 151, 84, 69, 91, 71, 72, 77, 4, 123, 148, 52, 103, 155, 156, 159, 159, 157, 155, 157, 153, 160, 153, 136, 133, 141, 92, 120, 32, 46, 39, 23, 29, 9, 27, 33, 38, 39, 27, 33, 25, 22, 4, 3, 24, 42, 47, 40, 40, 29, 25, 4, 45, 41, 41, 38, 32, 9, 23, 4, 162, 159, 124, 152, 127, 146, 152, 158, 158, 
+#> 158, 156, 157, 120, 45, 44, 16, 8, 119, 133, 151, 141, 150, 133, 141, 142, 146, 151, 140, 145, 83, 75, 75, 2, 12, 124, 154, 156, 139, 135, 132, 161, 157, 130, 2, 6, 149, 152, 160, 151, 73, 9, 114, 124, 32, 74, 13, 2, 137, 127, 123, 51, 147, 142, 149, 153, 143, 156, 155, 152, 110, 144, 93, 138, 129, 93, 127, 36, 38, 39, 42, 39, 36, 39, 32, 37, 35, 20, 13, 36, 33, 26, 23, 22, 34, 34, 35, 16, 12, 8, 10, 22, 127, 143, 113, 150, 138, 128, 138, 44, 134, 77, 45, 130, 11, 74, 12, 47, 90, 93, 90, 79, 6, 70, 
+#> 67, 157, 105, 158, 156, 149, 157, 123, 145, 139, 150, 130, 148, 36, 30, 7, 60, 1, 39, 40, 43, 40, 39, 36, 38, 41, 37, 30, 28, 34, 37, 29, 19, 34, 33, 47, 72, 38, 33, 44, 43, 40, 32, 41, 38, 42, 45, 41, 42, 41, 32, 31, 20, 27, 3, 20, 33, 38, 38, 44, 42, 14, 33, 15, 5, 6, 158, 155, 143, 147, 159, 131, 115, 143, 135, 65, 47, 148, 128, 68, 92, 41, 106, 4, 30, 92, 145, 153, 149, 142, 139, 142, 157, 99, 52, 84, 75, 53, 154, 153, 146, 155, 131, 143, 131, 120, 114, 64, 9, 26, 154, 148, 158, 149, 147, 152, 
+#> 160, 142, 135, 142, 120, 130, 114, 52, 119, 110, 79, 53, 37, 68, 134, 152, 151, 132, 152, 142, 27, 105, 29, 74, 60, 8, 20, 4, 37, 40, 36, 36, 44, 42, 38, 12, 21, 35, 23, 11, 44, 55, 57, 25, 7, 8, 79, 49, 150, 63, 71, 23, 61, 26, 150, 10, 149, 17, 52, 15, 25, 143, 146, 122, 143, 141, 96, 119, 108, 111, 72, 159, 114, 1, 139, 50, 32, 33, 162, 97, 1, 29, 30, 35, 34, 24, 35, 41, 41, 30, 36, 38, 39, 12, 4, 106, 150, 145, 160, 158, 154, 155, 149, 160, 153, 154, 145, 39, 59, 131, 56, 6, 1, 25, 4, 3, 34, 
+#> 51, 88, 76, 77, 44, 49, 49, 42, 43, 7, 24, 28, 7, 99, 133, 103, 129, 50, 90, 103, 75, 11, 2, 32, 25, 38, 38, 28, 39, 41, 38, 35, 38, 38, 36, 26, 2, 20, 131, 148, 145, 142, 149, 142, 118, 157, 136, 1, 78, 24, 44, 11, 8, 69, 145, 150, 145, 150, 113, 154, 155, 152, 153, 144, 135, 101, 113, 64, 54, 37, 41, 149, 162, 142, 143, 125, 153, 136, 162, 139, 91, 47, 67, 10, 47, 124, 148, 158, 152, 147, 148, 144, 154, 71, 144, 134, 30, 4, 6, 135, 144, 126, 151, 144, 140, 74, 100, 103, 130, 130, 116, 60, 102, 
+#> 53, 29, 159, 96, 135, 120, 142, 129, 153, 84, 152, 108, 26, 98, 9, 35, 154, 152, 149, 150, 135, 151, 148, 157, 134, 146, 139, 131, 143, 94, 153, 116, 143, 143, 132, 115, 1, 103, 139, 142, 123, 154, 157, 158, 147, 100, 129, 115, 85, 15, 9, 30, 35, 32, 34, 37, 41, 40, 39, 37, 35, 36, 34, 36, 38, 24, 38, 37, 34, 16, 10, 16, 6, 23, 9, 4, 4, 81, 78, 63, 110, 117, 141, 139, 146, 162, 155, 149, 32, 108, 123, 11, 48, 6, 30, 139, 129, 147, 137, 134, 136, 106, 92, 124, 21, 12, 53, 70, 69, 72, 59, 55, 70, 66, 
+#> 75, 67, 11, 36, 17, 9, 8, 34, 90, 67, 70, 63, 7, 33, 5, 55, 27, 9, 80, 154, 133, 162, 155, 131, 158, 38, 72, 121, 88, 61, 44, 42, 35, 35, 5, 35, 42, 36, 33, 39, 32, 47, 41, 40, 35, 35, 36, 8, 15, 19, 113, 146, 148, 82, 29, 102, 118, 132, 150, 128, 71, 106, 97, 25, 54, 33, 7, 1, 37, 120, 133, 134, 143, 69, 82, 90, 78, 11, 19, 3, 4, 12, 157, 147, 147, 153, 130, 141, 111, 119, 137, 98, 25, 47, 98, 155, 156, 135, 152, 154, 152, 129, 139, 52, 96, 111, 138, 150, 95, 141, 146, 74, 21, 26, 132, 125, 140, 
+#> 147, 144, 157, 152, 149, 154, 97, 8, 43, 36, 35, 40, 38, 39, 27, 1, 25, 15, 31, 43, 36, 37, 38, 39, 40, 35, 28, 16, 18, 13, 14, 16, 31, 37, 38, 42, 35, 29, 4, 35, 26, 5, 17, 43, 110, 92, 152, 152, 149, 129, 95, 147, 110, 15, 49, 22, 12, 6, 39, 27, 38, 40, 39, 37, 38, 35, 37, 31, 18, 31, 19, 33, 28, 19, 48, 159, 147, 143, 148, 146, 132, 153, 142, 141, 151, 107, 99, 125, 98, 40, 81, 158, 157, 155, 153, 160, 150, 145, 99, 158, 26, 130, 146, 86, 45, 22, 128, 157, 156, 157, 142, 153, 143, 160, 129, 146, 
+#> 158, 149, 152, 153, 98, 42, 141, 43, 19, 33, 151, 111, 123, 157, 142, 115, 106, 106, 34, 118, 107, 71, 53, 87, 111, 121, 155, 17, 110, 150, 156, 157, 162, 149, 158, 107, 157, 131, 135, 101, 97, 1, 10, 145, 151, 132, 118, 111, 61, 61, 100, 39, 64, 109, 142, 156, 147, 152, 110, 98, 23, 115, 137, 139, 144, 120, 63, 64, 11, 21, 152, 159, 146, 153, 160, 156, 147, 147, 154, 146, 58, 74, 100, 50, 65, 9, 31, 95, 106, 141, 102, 95, 80, 93, 86, 107, 50, 35, 2, 29, 36, 9, 27, 44, 38, 36, 38, 26, 39, 40, 39, 
+#> 38, 23, 37, 22, 36, 14, 5, 5, 25, 127, 146, 158, 153, 147, 148, 148, 152, 146, 148, 150, 148, 124, 78, 26, 42, 30, 129, 128, 138, 136, 149, 151, 133, 114, 152, 85, 56, 47, 21, 24, 38, 7, 50, 83, 62, 15, 27, 9, 9, 30, 3, 31, 26, 8, 38, 41, 43, 38, 22, 66, 58, 54, 67, 64, 61, 40, 20, 40, 8, 10, 157, 122, 133, 10, 147, 144, 160, 149, 157, 149, 146, 141, 153, 132, 127, 141, 90, 134, 123, 116, 16, 38, 65, 82, 160, 158, 158, 128, 147, 142, 151, 133, 58, 66, 53, 13, 32, 46, 49, 36, 42, 39, 40, 41, 38, 41, 
+#> 41, 37, 15, 22, 32, 34, 37, 32, 10, 24, 24, 32, 14, 16, 18, 125, 129, 113, 93, 100, 49, 5, 2, 14, 131, 135, 52, 79, 134, 152, 157, 91, 131, 96, 135, 138, 102, 153, 125, 135, 76, 103, 137, 134, 62, 25, 4, 54, 145, 132, 154, 158, 109, 77, 151, 158, 159, 156, 162, 153, 45, 28, 1, 90, 161, 139, 139, 160, 131, 150, 141, 50, 132, 137, 82, 138, 98, 110, 83, 28, 37, 145, 159, 152, 122, 162, 136, 156, 154, 156, 147, 147, 103, 142, 147, 133, 72, 14, 7, 34, 35, 34, 33, 35, 26, 35, 13, 35, 17, 33, 25, 19, 68, 
+#> 35, 106, 127, 147, 120, 158, 126, 130, 64, 133, 90, 104, 49, 71, 4, 18, 19, 102, 27, 134, 77, 29, 10, 36, 6, 157, 150, 153, 141, 141, 145, 139, 6, 150, 113, 128, 96, 156, 88, 12, 25, 38, 106, 95, 111, 82, 28, 27, 49, 71, 63, 50, 59, 51, 66, 49, 64, 72, 59, 67, 10, 49, 48, 11, 34, 11, 19, 73, 42, 10, 58, 71, 65, 61, 65, 53, 57, 56, 29, 8, 51, 2, 67, 144, 142, 147, 159, 135, 147, 134, 149, 151, 134, 137, 149, 150, 98, 85, 8, 77, 55, 60, 30, 7, 133, 162, 160, 150, 144, 52, 144, 153, 150, 100, 145, 120, 
+#> 116, 144, 98, 8, 76, 45, 113, 138, 131, 144, 125, 19, 66, 96, 90, 119, 86, 120, 57, 38, 31, 59, 72, 1, 150, 153, 154, 143, 127, 152, 97, 45, 75, 94, 28, 5, 1, 23, 39, 41, 47, 24, 65, 59, 36, 56, 45, 51, 43, 11, 9, 110, 94, 114, 133, 133, 33, 148, 160, 101, 150, 124, 119, 68, 20, 148, 154, 116, 156, 148, 129, 156, 155, 101, 162, 132, 147, 97, 123, 44, 45, 4, 5, 50, 46, 149, 152, 126, 156, 161, 153, 152, 137, 149, 94, 69, 17, 11, 47, 162, 162, 155, 153, 152, 162, 146, 160, 158, 159, 152, 130, 78, 32, 
+#> 3, 34, 12, 35, 39, 40, 30, 40, 41, 39, 39, 13, 21, 18, 23, 5, 24, 12, 12, 89, 125, 161, 160, 156, 44, 92, 144, 159, 160, 154, 102, 141, 142, 131, 151, 151, 150, 144, 107, 1, 16, 34, 27, 35, 42, 41, 10, 98, 81, 91, 129, 162, 160, 84, 149, 153, 155, 153, 130, 82, 153, 131, 89, 76, 105, 37, 21, 4, 24, 66, 65, 92, 106, 58, 24, 30, 4, 12, 54, 90, 18, 20, 3, 34, 81, 96, 114, 156, 160, 162, 162, 162, 162, 163, 110, 162, 100, 161, 162, 155, 27, 13, 130, 133, 140, 122, 76, 136, 135, 144, 26, 133, 100, 32, 
+#> 30, 37, 39, 42, 43, 38, 39, 37, 41, 39, 36, 22, 21, 19, 28, 47, 94, 120, 139, 150, 148, 149, 149, 122, 123, 103, 59, 53, 38, 29, 42, 38, 39, 26, 34, 39, 44, 29, 16, 6, 11, 101, 130, 119, 89, 160, 140, 152, 156, 153, 149, 156, 106, 147, 143, 154, 155, 90, 104, 84, 96, 48, 144, 99, 97, 112, 34, 64, 6, 59, 22, 151, 152, 152, 158, 154, 153, 116, 99, 89, 113, 121, 58, 86, 131, 145, 151, 153, 146, 100, 52, 160, 94, 160, 134, 133, 107, 40, 150, 116, 72, 85, 43, 122, 151, 137, 58, 27, 70, 13, 132, 162, 158, 
+#> 160, 154, 145, 160, 150, 102, 148, 154, 151, 158, 160, 147, 108, 42, 44, 40, 31, 53, 39, 22, 25, 22, 8, 7, 17, 103, 149, 147, 155, 141, 140, 144, 135, 94, 131, 90, 45, 63, 53, 59, 17, 29, 36, 47, 17, 9, 21, 56, 56, 25, 46, 41, 1, 60, 45, 48, 65, 62, 76, 76, 70, 78, 67, 54, 66, 47, 50, 33, 47, 21, 128, 130, 142, 140, 122, 85, 69, 137, 82, 154, 130, 103, 34, 110, 111, 87, 21, 19, 41, 46, 33, 34, 38, 18, 21, 43, 35, 38, 35, 38, 32, 32, 30, 25, 9, 6, 15, 145, 132, 129, 150, 147, 110, 76, 138, 117, 142, 
+#> 124, 112, 111, 87, 27, 117, 90, 21, 147, 154, 161, 155, 157, 150, 159, 151, 82, 7, 125, 144, 135, 99, 17, 146, 139, 155, 148, 143, 94, 119, 97, 77, 105, 6, 33, 23, 17, 37, 35, 25, 2, 32, 34, 6, 8, 7, 35, 38, 26, 37, 24, 22, 26, 32, 6, 31, 11, 3, 4, 3, 22, 96, 157, 158, 150, 160, 155, 157, 158, 158, 159, 145, 89, 103, 122, 129, 124, 137, 126, 112, 80, 24, 144, 153, 160, 163, 158, 124, 108, 145, 155, 159, 140, 157, 108, 135, 56, 8, 127, 116, 118, 161, 151, 155, 159, 139, 149, 160, 103, 162, 138, 88, 
+#> 126, 95, 20, 46, 40, 40, 28, 38, 41, 25, 13, 28, 8, 28, 150, 161, 85, 161, 149, 149, 155, 137, 106, 104, 159, 144, 125, 4, 129, 151, 143, 140, 158, 147, 155, 121, 154, 133, 136, 163, 102, 160, 157, 28, 91, 35, 61, 54, 73, 148, 138, 159, 148, 158, 139, 67, 73, 144, 156, 160, 162, 153, 101, 144, 157, 119, 13, 36, 21, 39, 62, 31, 72, 63, 36, 64, 32, 56, 57, 62, 50, 45, 40, 46, 11, 31, 44, 30, 39, 36, 16, 1, 5, 44, 66, 65, 68, 65, 58, 58, 45, 24, 31, 9, 9, 104, 36, 59, 17, 106, 134, 144, 158, 158, 121, 
+#> 144, 108, 151, 157, 146, 129, 15, 72, 29, 76, 159, 17, 142, 154, 153, 160, 159, 151, 128, 96, 134, 106, 52, 89, 27, 118, 45, 22, 132, 155, 140, 149, 149, 150, 151, 102, 139, 131, 110, 115, 140, 61, 24, 38, 76, 18, 119, 133, 128, 146, 73, 147, 152, 148, 108, 162, 126, 162, 159, 152, 154, 149, 146, 123, 101, 120, 138, 68, 148, 144, 140, 103, 152, 50, 108, 119, 79, 89, 97, 6, 25, 39, 34, 31, 25, 33, 38, 38, 29, 36, 22, 31, 31, 33, 37, 36, 20, 7, 30, 34, 32, 12, 11, 13, 33, 35, 10, 38, 43, 36, 41, 40, 
+#> 39, 33, 33, 40, 35, 35, 33, 34, 33, 32, 23, 27, 7, 31, 33, 5, 29, 34, 35, 16, 28, 63, 47, 78, 69, 29, 41, 23, 30, 62, 82, 57, 50, 34, 7, 8, 58, 71, 23, 41, 8, 22, 51, 14, 30, 31, 11, 3, 4, 10, 10, 4, 77, 17, 58, 25, 38, 12, 19, 21, 7, 28, 24, 36, 40, 58, 10, 13, 133, 159, 159, 139, 128, 154, 117, 89, 144, 123, 104, 155, 124, 115, 157, 124, 142, 131, 152, 145, 17, 70, 99, 61, 106, 148, 126, 149, 162, 156, 101, 124, 101, 159, 157, 106, 112, 112, 18, 4, 39, 34, 35, 31, 33, 18, 32, 24, 30, 29, 35, 20, 
+#> 13, 32, 34, 32, 33, 34, 33, 32, 3, 29, 17, 79, 58, 30, 118, 155, 137, 138, 141, 74, 58, 147, 99, 19, 96, 102, 8, 18, 158, 147, 146, 143, 21, 135, 103, 60, 136, 159, 109, 38, 14, 128, 26, 29, 18, 36, 16, 145, 146, 97, 121, 132, 132, 119, 141, 76, 143, 142, 139, 150, 144, 128, 122, 131, 40, 25, 88, 132, 148, 154, 158, 95, 146, 101, 127, 118, 120, 127, 80, 59, 122, 69, 25, 106, 46, 21, 30, 51, 99, 111, 152, 152, 143, 127, 154, 94, 145, 146, 129, 149, 151, 154, 150, 135, 82, 16, 33, 106, 78, 145, 123, 
+#> 127, 62, 70, 58, 112, 92, 110, 132, 113, 57, 39, 27, 110, 120, 152, 162, 132, 136, 34, 108, 85, 146, 110, 139, 122, 28, 6, 3, 13, 29, 127, 159, 149, 142, 112, 153, 149, 151, 153, 103, 147, 149, 100, 111, 83, 160, 161, 159, 158, 99, 151, 156, 162, 156, 137, 160, 161, 160, 155, 153, 156, 154, 108, 113, 64, 88, 46, 9, 24, 139, 157, 155, 151, 103, 148, 159, 138, 139, 130, 153, 157, 118, 147, 149, 143, 121, 75, 79, 42, 30, 125, 147, 134, 153, 138, 93, 144, 104, 142, 143, 141, 120, 110, 145, 26, 93, 124, 
+#> 90, 7, 145, 126, 36, 143, 143, 80, 155, 141, 142, 26, 17, 27, 9, 2, 21, 25, 27, 30, 39, 41, 42, 28, 39, 37, 31, 34, 35, 21, 35, 29, 30, 35, 30, 34, 33, 32, 30, 27, 27, 13, 114, 158, 152, 154, 145, 153, 155, 109, 11, 33, 7, 93, 62, 2, 5, 82, 133, 152, 161, 152, 157, 150, 150, 152, 123, 145, 100, 137, 153, 132, 143, 76, 73, 78, 21, 36, 41, 38, 38, 41, 35, 38, 44, 16, 12, 4, 20, 31, 43, 25, 9, 36, 32, 15, 4, 53, 153, 155, 154, 118, 80, 141, 126, 148, 148, 147, 148, 110, 142, 144, 80, 32, 40, 154, 157, 
+#> 158, 158, 123, 141, 141, 73, 59, 46, 131, 11, 11, 7, 36, 37, 34, 37, 23, 34, 32, 30, 34, 30, 22, 13, 15, 89, 143, 114, 77, 105, 86, 132, 120, 129, 97, 135, 104, 95, 41, 14, 64, 129, 161, 159, 161, 159, 103, 160, 95, 55, 154, 158, 149, 154, 95, 75, 43, 11, 142, 145, 155, 117, 134, 151, 153, 141, 58, 128, 147, 16, 72, 99, 59, 37, 47, 12, 94, 127, 151, 146, 86, 22, 48, 111, 86, 11, 10, 42, 28, 46, 37, 40, 34, 42, 38, 42, 41, 39, 38, 44, 45, 44, 40, 22, 35, 34, 32, 33, 34, 1, 22, 3, 11, 139, 127, 145, 
+#> 109, 152, 161, 143, 152, 144, 149, 115, 148, 132, 138, 130, 119, 92, 84, 89, 121, 124, 79, 140, 104, 32, 130, 141, 60, 150, 89, 131, 153, 149, 161, 158, 160, 162, 66, 152, 151, 155, 161, 158, 162, 68, 38, 109, 70, 112, 104, 78, 54, 107, 147, 161, 154, 127, 149, 143, 96, 156, 149, 160, 122, 140, 158, 162, 160, 158, 130, 150, 127, 8, 26, 136, 156, 143, 127, 99, 157, 135, 57, 126, 65, 131, 150, 142, 115, 140, 81, 2, 20, 36, 40, 39, 40, 20, 36, 20, 34, 15, 29, 16, 7, 34, 30, 5, 64, 42, 52, 62, 64, 62, 
+#> 60, 48, 70, 60, 71, 58, 16, 38, 14, 12, 30, 121, 106, 123, 160, 107, 150, 153, 106, 155, 160, 148, 154, 134, 63, 132, 156, 116, 153, 159, 129, 142, 162, 129, 97, 148, 156, 148, 67, 84, 155, 143, 21, 74, 34, 15, 134, 145, 109, 132, 138, 112, 72, 138, 18, 97, 109, 72, 17, 21, 154, 158, 152, 152, 118, 141, 94, 149, 88, 31, 98, 125, 81, 108, 76, 17, 56, 145, 143, 137, 157, 158, 159, 162, 105, 140, 152, 141, 155, 154, 156, 149, 112, 20, 150, 156, 143, 77, 46, 8, 1, 102, 118, 137, 145, 157, 154, 158, 162, 
+#> 90, 103, 157, 144, 134, 142, 160, 108, 20, 92, 17, 107, 120, 27, 69, 131, 145, 143, 69, 161, 141, 155, 124, 120, 36, 4, 13, 50, 60, 58, 71, 38, 23, 13, 50, 1, 6, 8, 5, 16, 148, 150, 101, 117, 142, 8, 12, 14, 5, 153, 155, 101, 162, 162, 140, 162, 162, 144, 95, 136, 141, 109, 63, 46, 1, 2, 40, 44, 14, 34, 36, 20, 15, 20, 29, 35, 33, 37, 5, 20, 36, 29, 16, 22, 18, 117, 131, 130, 119, 130, 150, 157, 118, 61, 120, 145, 127, 84, 68, 85, 69, 115, 142, 162, 148, 155, 154, 152, 149, 159, 156, 103, 156, 151, 
+#> 111, 78, 103, 41, 150, 158, 162, 133, 56, 4, 142, 130, 47, 67, 129, 143, 110, 41, 135, 112, 121, 134, 123, 10, 8, 58, 56, 119, 145, 81, 100, 149, 100, 147, 158, 144, 6, 48, 150, 155, 162, 162, 103, 158, 97, 48, 117, 24, 34, 118, 36, 34, 4, 38, 39, 32, 18, 20, 27, 40, 36, 44, 36, 38, 37, 24, 35, 38, 38, 32, 3, 25, 19, 8, 5, 38, 15, 4, 43, 57, 51, 54, 60, 41, 56, 58, 45, 55, 65, 57, 34, 34, 34, 25, 24, 27, 39, 42, 34, 17, 31, 30, 32, 49, 15, 60, 121, 159, 107, 151, 130, 153, 152, 98, 82, 49, 98, 12, 
+#> 13, 127, 154, 161, 102, 136, 137, 128, 141, 156, 146, 147, 112, 115, 113, 132, 105, 17, 4, 24, 17, 15, 29, 33, 23, 29, 16, 14, 19, 139, 142, 146, 105, 157, 142, 139, 149, 151, 151, 128, 121, 146, 101, 29, 112, 76, 74, 66, 90, 93, 36, 90, 156, 157, 128, 105, 58, 88, 143, 124, 32, 9, 9, 144, 91, 154, 157, 140, 154, 100, 154, 145, 159, 149, 132, 139, 130, 50, 92, 101, 95, 159, 156, 158, 110, 140, 159, 124, 158, 153, 158, 153, 155, 143, 150, 132, 141, 98, 44, 82, 32, 75, 40, 72, 69, 72, 84, 62, 47, 20, 
+#> 33, 63, 5, 131, 48, 22, 59, 41, 66, 46, 19, 13, 24, 37, 20, 51, 40, 56, 25, 12, 85, 143, 144, 96, 133, 155, 147, 140, 91, 130, 123, 124, 133, 119, 24, 69, 10, 40, 70, 14, 94, 58, 92, 100, 115, 132, 128, 139, 156, 107, 159, 125, 131, 101, 103, 42, 58, 113, 139, 145, 149, 152, 36, 102, 140, 150, 101, 136, 144, 120, 16, 69, 102, 65, 69, 20, 35, 35, 35, 34, 33, 32, 20, 36, 37, 16, 34, 34, 34, 6, 31, 37, 7, 7, 31, 88, 136, 147, 71, 89, 80, 38, 96, 68, 113, 84, 102, 49, 90, 33, 6, 6, 27, 41, 24, 12, 34, 
+#> 37, 34, 34, 35, 14, 29, 8, 14, 43, 57, 78, 51, 46, 48, 54, 56, 48, 11, 38, 2, 11, 152, 159, 158, 145, 153, 159, 150, 157, 85, 150, 159, 146, 145, 97, 45, 10, 25, 38, 36, 35, 35, 39, 38, 23, 34, 35, 2, 32, 8, 29, 36, 14, 5, 20, 3, 46, 122, 131, 92, 116, 143, 104, 2, 89, 158, 108, 149, 145, 142, 143, 153, 95, 140, 65, 85, 136, 134, 117, 90, 44, 87, 112, 148, 32, 88, 152, 121, 31, 92, 123, 72, 30, 3, 33, 42, 48, 3, 31, 33, 32, 32, 30, 34, 23, 21, 33, 54, 29, 3, 15, 33, 31, 64, 74, 74, 60, 60, 55, 53, 
+#> 61, 54, 51, 7, 13, 10, 121, 157, 151, 102, 128, 80, 151, 98, 151, 151, 150, 148, 134, 5, 135, 4, 118, 91, 80, 158, 109, 138, 145, 157, 103, 121, 28, 120, 60, 7, 28, 28, 44, 25, 37, 44, 35, 36, 35, 36, 34, 24, 36, 35, 34, 27, 23, 5, 25, 75, 98, 150, 160, 144, 137, 31, 152, 59, 44, 162, 136, 115, 43, 35, 54, 94, 135, 117, 125, 94, 105, 96, 42, 82, 113, 74, 53, 50, 4, 33, 53, 45, 34, 32, 24, 30, 3, 22, 6, 19, 18, 151, 104, 156, 104, 162, 162, 162, 162, 160, 159, 156, 154, 97, 57, 153, 18, 26, 23, 160, 
+#> 162, 162, 161, 162, 162, 161, 162, 161, 162, 162, 162, 112, 144, 163, 162, 161, 86, 83, 128, 31, 150, 155, 145, 136, 157, 157, 160, 158, 155, 158, 143, 57, 7, 18, 11, 140, 64, 147, 131, 152, 146, 122, 21, 80, 10, 1, 61, 129, 150, 142, 120, 145, 100, 153, 95, 146, 120, 140, 133, 4, 96, 87, 148, 100, 137, 153, 141, 131, 24, 21, 29, 35, 29, 30, 17, 43, 10, 53, 44, 50, 44, 25, 52, 40, 31, 35, 3, 10, 6, 21, 16, 2, 3, 34, 35, 26, 38, 25, 34, 29, 28, 7, 60, 17, 121, 99, 137, 156, 162, 103, 158, 106, 46, 
+#> 35, 135, 44, 57, 20, 36, 29, 38, 36, 35, 36, 38, 34, 33, 33, 33, 9, 21, 4, 19, 17, 17, 100, 62, 156, 130, 145, 120, 28, 134, 48, 43, 134, 135, 122, 84, 9, 94, 35, 17, 38, 35, 35, 40, 30, 40, 38, 23, 35, 36, 31, 8, 1, 2, 7, 28, 35, 34, 33, 34, 21, 15, 34, 34, 30, 29, 10, 5, 5, 6, 25, 6, 43, 71, 59, 21, 91, 136, 124, 119, 92, 125, 128, 109, 132, 122, 60, 77, 79, 62, 61, 8, 2, 25, 43, 39, 36, 35, 31, 35, 2, 26, 30, 26, 33, 31, 16, 19, 21, 4, 36, 22, 33, 27, 13, 156, 158, 156, 153, 154, 132, 155, 157, 
+#> 155, 158, 158, 117, 57, 150, 135, 8, 66, 138, 151, 147, 147, 144, 116, 149, 141, 143, 141, 133, 126, 40, 91, 67, 31, 9, 123, 147, 145, 152, 124, 153, 137, 58, 29, 125, 131, 138, 130, 45, 67, 123, 122, 120, 132, 14, 80, 83, 150, 162, 106, 158, 145, 88, 27, 90, 137, 150, 105, 2, 3, 54, 47, 58, 68, 68, 15, 3, 38, 25, 3, 20, 145, 139, 116, 86, 30, 59, 75, 51, 22, 83, 17, 122, 147, 111, 136, 154, 153, 134, 152, 139, 43, 32, 29, 32, 63, 11, 101, 24, 104, 153, 158, 161, 149, 147, 155, 156, 155, 144, 143, 
+#> 143, 97, 126, 132, 104, 123, 90, 114, 100, 147, 151, 158, 152, 152, 155, 128, 135, 122, 74, 31, 162, 151, 155, 154, 155, 30, 123, 153, 134, 105, 10, 33, 84, 101, 153, 149, 148, 143, 141, 143, 85, 125, 107, 69, 6, 83, 117, 132, 107, 120, 133, 157, 153, 157, 160, 107, 155, 160, 160, 141, 141, 126, 38, 35, 80, 49, 136, 154, 5, 84, 106, 32, 95, 136, 149, 146, 95, 85, 44, 97, 117, 99, 145, 148, 120, 142, 143, 141, 105, 53, 15, 13, 30, 6, 27, 20, 35, 36, 32, 50, 9, 45, 8, 41, 13, 6, 15, 88, 156, 156, 160, 
+#> 150, 151, 139, 109, 145, 130, 155, 144, 115, 101, 133, 59, 74, 109, 58, 4, 47, 98, 18, 40, 72, 66, 69, 65, 66, 63, 64, 64, 11, 53, 67, 70, 8, 55, 41, 52, 11, 43, 25, 12, 51, 83, 69, 128, 149, 154, 119, 128, 150, 71, 89, 132, 16, 116, 98, 70, 67, 55, 52, 53, 13, 75, 11, 63, 80, 74, 64, 45, 63, 32, 10, 10, 122, 122, 143, 121, 108, 93, 68, 107, 28, 26, 36, 46, 35, 9, 12, 38, 39, 36, 38, 28, 13, 23, 152, 155, 135, 157, 140, 142, 140, 145, 40, 31, 35, 33, 25, 34, 19, 35, 27, 33, 30, 7, 29, 20, 23, 26, 
+#> 1, 18, 8, 54, 86, 158, 154, 160, 157, 133, 158, 141, 134, 128, 122, 110, 135, 116, 149, 127, 111, 36, 71, 4, 26, 27, 32, 30, 1, 20, 21, 36, 36, 35, 37, 41, 30, 31, 20, 7, 91, 153, 159, 162, 141, 144, 158, 102, 152, 157, 134, 97, 128, 21, 32, 36, 25, 18, 48, 43, 49, 43, 39, 32, 30, 33, 35, 39, 20, 28, 17, 19, 24, 9, 16, 6, 31, 22, 3, 10, 22, 140, 125, 154, 133, 129, 119, 136, 137, 48, 30, 5, 71, 158, 156, 160, 155, 134, 153, 159, 154, 161, 151, 150, 133, 113, 97, 57, 45, 18, 61, 25, 18, 75, 66, 68, 
+#> 63, 62, 63, 63, 65, 47, 57, 14, 46, 58, 11, 150, 159, 149, 156, 155, 160, 154, 12, 134, 100, 122, 150, 142, 83, 12, 92, 63, 151, 154, 151, 153, 145, 124, 72, 71, 92, 104, 75, 40, 33, 6, 60, 39, 159, 157, 159, 156, 156, 153, 142, 149, 155, 102, 24, 98, 126, 150, 153, 156, 80, 112, 151, 148, 153, 103, 82, 75, 34, 141, 82, 161, 156, 147, 160, 145, 132, 158, 96, 50, 32, 103, 141, 140, 118, 94, 127, 143, 44, 93, 104, 107, 28, 72, 24, 32, 23, 124, 159, 143, 158, 154, 144, 72, 45, 14, 76, 103, 135, 89, 
+#> 145, 159, 152, 141, 86, 15, 151, 27, 119, 70, 32, 6, 16, 18, 32, 34, 36, 37, 30, 17, 9, 23, 6, 25, 8, 33, 139, 156, 158, 137, 150, 86, 62, 12, 21, 15, 33, 36, 35, 35, 31, 35, 32, 29, 24, 23, 34, 34, 33, 30, 32, 33, 29, 33, 33, 32, 19, 18, 18, 6, 23, 37, 24, 31, 36, 38, 36, 32, 33, 32, 2, 9, 145, 157, 162, 160, 157, 154, 133, 130, 154, 152, 130, 20, 82, 90, 137, 141, 148, 37, 91, 113, 5, 25, 139, 128, 110, 155, 158, 159, 137, 129, 21, 153, 84, 30, 128, 161, 161, 157, 158, 159, 146, 152, 160, 156, 
+#> 108, 137, 15, 88, 161, 163, 146, 154, 140, 161, 145, 155, 48, 94, 104, 108, 120, 138, 142, 28, 48, 56, 130, 151, 150, 142, 148, 125, 2, 88, 78, 12, 5, 32, 35, 39, 40, 32, 38, 26, 21, 10, 2, 33, 17, 74, 75, 68, 47, 67, 35, 38, 59, 72, 65, 29, 157, 159, 158, 65, 131, 154, 97, 22, 60, 111, 102, 96, 108, 151, 113, 37, 61, 76, 18, 100, 158, 151, 152, 158, 93, 49, 106, 30, 22, 82, 106, 137, 59, 80, 140, 153, 146, 79, 61, 6, 9, 62, 92, 81, 133, 144, 135, 52, 95, 93, 10, 40, 46, 41, 32, 34, 35, 31, 22, 27, 
+#> 7, 8, 17, 22, 35, 35, 36, 37, 36, 35, 24, 12, 35, 35, 35, 29, 6, 3, 6, 15, 64, 70, 40, 37, 68, 65, 57, 28, 40, 68, 56, 49, 46, 29, 35, 24, 37, 35, 35, 24, 10, 33, 34, 33, 35, 18, 31, 18, 9, 23, 25, 67, 149, 159, 159, 110, 162, 121, 153, 160, 161, 77, 133, 42, 111, 50, 79, 6, 12, 110, 121, 120, 68, 96, 108, 95, 37, 1, 59, 46, 57, 56, 132, 129, 135, 131, 127, 89, 76, 23, 108, 37, 129, 42, 131, 58, 92, 74, 125, 140, 111, 64, 160, 152, 13, 140, 105, 118, 154, 155, 103, 158, 158, 160, 115, 130, 161, 135, 
+#> 126, 11, 8, 134, 88, 7, 37, 80, 139, 136, 133, 89, 131, 94, 44, 150, 134, 18, 151, 155, 143, 156, 154, 139, 27, 47, 104, 130, 105, 51, 155, 153, 89, 97, 17, 146, 139, 129, 100, 152, 106, 139, 101, 81, 136, 97, 15, 109, 89, 133, 126, 108, 49, 6, 19, 7, 135, 122, 87, 44, 92, 135, 121, 76, 28, 26, 10, 18, 160, 161, 145, 160, 157, 86, 51, 143, 153, 29, 47, 103, 59, 76, 15, 69, 45, 43, 63, 36, 36, 36, 21, 33, 27, 33, 33, 34, 25, 5, 30, 34, 25, 3, 43, 43, 41, 27, 21, 32, 23, 11, 36, 26, 14, 26, 24, 16, 
+#> 34, 36, 34, 35, 33, 30, 23, 33, 28, 9, 24, 26, 33, 54, 60, 51, 63, 67, 69, 64, 45, 52, 63, 57, 50, 6, 122, 104, 130, 114, 129, 128, 104, 103, 114, 145, 122, 124, 101, 8, 45, 37, 37, 40, 36, 35, 4, 21, 35, 34, 21, 26, 33, 32, 34, 32, 10, 20, 10, 67, 126, 160, 158, 153, 160, 161, 140, 145, 74, 21, 29, 159, 122, 156, 125, 156, 153, 146, 100, 101, 146, 74, 146, 134, 47, 126, 101, 137, 146, 137, 157, 154, 130, 136, 138, 154, 83, 105, 17, 63, 6, 6, 100, 105, 151, 157, 150, 152, 153, 69, 54, 109, 64, 54, 
+#> 67, 74, 68, 70, 60, 55, 52, 31, 35, 47, 48, 51, 59, 61, 46, 62, 58, 38, 52, 31, 16, 147, 84, 138, 40, 103, 158, 110, 137, 155, 121, 96, 110, 80, 137, 82, 148, 153, 96, 148, 68, 20, 5, 54, 16, 149, 160, 160, 149, 128, 152, 150, 157, 146, 35, 144, 112, 112, 78, 42, 1, 25, 125, 103, 125, 108, 95, 15, 40, 17, 31, 125, 158, 145, 159, 147, 49, 146, 95, 120, 77, 24, 105, 147, 157, 152, 155, 107, 95, 120, 103, 143, 159, 154, 153, 141, 49, 72, 104, 110, 7, 75, 63, 141, 159, 163, 160, 157, 128, 139, 108, 61, 
+#> 80, 159, 153, 28, 72, 60, 114, 93, 1, 2, 20, 5, 33, 39, 36, 14, 19, 31, 28, 18, 8, 33, 6, 41, 125, 151, 97, 158, 123, 140, 100, 110, 131, 152, 73, 145, 161, 102, 45, 145, 70, 111, 8, 23, 2, 106, 74, 105, 123, 124, 139, 131, 135, 127, 129, 67, 35, 1, 32, 45, 46, 8, 32, 4, 42, 29, 8, 37, 37, 36, 36, 35, 31, 26, 22, 16, 111, 150, 162, 159, 154, 148, 144, 132, 110, 123, 117, 110, 149, 77, 79, 51, 4, 15, 32, 32, 36, 35, 21, 22, 17, 19, 15, 32, 26, 19, 13, 13, 4, 39, 147, 152, 158, 151, 147, 148, 147, 
+#> 143, 109, 110, 51, 25, 116, 124, 135, 111, 23, 85, 75, 2, 9, 20, 46, 77, 67, 43, 21, 62, 70, 53, 29, 14, 13, 25, 35, 20, 19, 5, 39, 42, 34, 32, 34, 35, 34, 3, 17, 12, 34, 32, 27, 22, 32, 28, 50, 34, 35, 31, 18, 7, 2, 7, 108, 62, 69, 148, 154, 140, 113, 99, 93, 95, 27, 37, 20, 51, 10, 34, 13, 37, 52, 35, 71, 27, 68, 8, 51, 51, 29, 13, 37, 55, 10, 64, 64, 72, 60, 50, 16, 3, 20, 43, 9, 34, 11, 64, 61, 13, 28, 116, 101, 123, 30, 5, 46, 102, 37, 26, 12, 3, 107, 154, 161, 153, 153, 152, 68, 83, 113, 144, 
+#> 159, 152, 151, 144, 158, 49, 97, 146, 86, 27, 33, 78, 90, 82, 86, 117, 135, 154, 157, 152, 107, 134, 143, 17, 113, 158, 156, 162, 159, 161, 27, 124, 158, 110, 56, 70, 46, 96, 25, 14, 27, 20, 94, 122, 63, 43, 107, 61, 14, 54, 27, 116, 126, 88, 157, 148, 153, 154, 156, 100, 72, 93, 87, 50, 134, 150, 149, 162, 155, 114, 141, 162, 162, 160, 160, 101, 155, 145, 153, 156, 155, 145, 141, 25, 35, 31, 29, 32, 34, 31, 35, 25, 32, 35, 25, 34, 33, 34, 22, 18, 14, 74, 150, 95, 155, 138, 146, 142, 18, 7, 88, 127, 
+#> 82, 114, 18, 62, 36, 42, 62, 98, 88, 72, 8, 53, 127, 141, 145, 108, 27, 139, 138, 75, 43, 136, 44, 43, 6, 23, 25, 34, 23, 38, 31, 32, 25, 35, 38, 36, 33, 35, 36, 20, 30, 26, 27, 30, 33, 40, 33, 36, 35, 34, 24, 33, 32, 32, 23, 15, 5, 87, 138, 158, 135, 150, 113, 120, 18, 1, 7, 132, 51, 89, 64, 80, 66, 127, 125, 117, 37, 97, 70, 51, 38, 75, 50, 46, 19, 27, 8, 133, 144, 97, 152, 130, 66, 146, 42, 103, 156, 119, 100, 42, 120, 122, 124, 138, 55, 11, 127, 155, 154, 142, 156, 111, 72, 140, 157, 161, 160, 
+#> 145, 111, 70, 53, 83, 128, 109, 144, 41, 102, 117, 33, 113, 150, 144, 159, 151, 153, 140, 159, 112, 144, 158, 159, 156, 102, 143, 153, 143, 130, 147, 14, 130, 126, 6, 34, 37, 35, 35, 39, 35, 36, 25, 28, 35, 33, 34, 33, 35, 35, 35, 37, 34, 35, 22, 12, 35, 7, 27, 15, 27, 24, 26, 154, 149, 148, 19, 147, 91, 125, 117, 46, 37, 74, 68, 67, 63, 45, 16, 15, 1, 10, 54, 55, 65, 66, 58, 66, 74, 38, 57, 62, 61, 21, 41, 20, 51, 68, 61, 77, 67, 55, 25, 17, 7, 16, 127, 109, 144, 157, 104, 120, 40, 139, 146, 133, 
+#> 68, 78, 111, 118, 30, 34, 82, 74, 159, 162, 155, 154, 109, 136, 107, 53, 98, 103, 14, 84, 52, 84, 159, 157, 146, 145, 112, 76, 105, 151, 135, 154, 96, 106, 60, 44, 54, 93, 129, 12, 114, 141, 122, 142, 130, 133, 135, 119, 117, 24, 12, 39, 21, 49, 19, 29, 31, 33, 36, 26, 14, 13, 31, 9, 42, 30, 34, 36, 35, 36, 26, 29, 39, 33, 33, 36, 37, 35, 37, 33, 35, 33, 32, 35, 14, 143, 158, 147, 161, 152, 153, 107, 130, 153, 112, 147, 159, 155, 157, 149, 67, 73, 38, 18, 16, 150, 157, 157, 157, 109, 135, 158, 54, 
+#> 161, 161, 141, 142, 141, 49, 89, 102, 27, 81, 52, 69, 140, 139, 92, 70, 62, 119, 25, 51, 3, 37, 34, 33, 11, 8, 28, 35, 20, 19, 38, 24, 140, 141, 149, 158, 149, 143, 143, 109, 143, 132, 112, 123, 81, 21, 37, 35, 35, 24, 29, 24, 24, 39, 19, 19, 3, 50, 51, 54, 67, 25, 59, 12, 1, 151, 155, 153, 109, 136, 153, 156, 150, 150, 102, 137, 80, 156, 162, 142, 110, 114, 162, 162, 147, 162, 159, 161, 158, 160, 156, 39, 60, 158, 160, 153, 113, 145, 141, 146, 160, 135, 159, 20, 148, 153, 74, 34, 137, 155, 55, 16, 
+#> 23, 66, 143, 162, 149, 157, 162, 162, 162, 158, 155, 111, 139, 157, 157, 85, 41, 21, 146, 75, 152, 154, 153, 157, 119, 122, 139, 121, 138, 34, 89, 59, 34, 102, 17, 29, 33, 34, 29, 32, 24, 13, 17, 27, 5, 20, 88, 123, 137, 99, 130, 153, 150, 145, 144, 91, 111, 108, 144, 135, 129, 136, 129, 82, 33, 93, 28, 111, 44, 134, 142, 157, 160, 158, 155, 106, 143, 142, 151, 158, 161, 143, 145, 124, 66, 35, 154, 153, 152, 150, 135, 136, 85, 15, 29, 20, 133, 137, 143, 138, 103, 131, 83, 153, 130, 127, 87, 142, 
+#> 136, 143, 38, 44, 100, 12, 33, 38, 38, 36, 35, 21, 29, 35, 36, 26, 29, 36, 75, 62, 73, 33, 35, 32, 6, 8, 7, 149, 98, 16, 101, 87, 52, 14, 149, 158, 111, 143, 154, 162, 139, 153, 155, 121, 142, 114, 40, 13, 14, 65, 144, 150, 135, 42, 89, 145, 139, 155, 154, 142, 153, 132, 97, 145, 141, 24, 25, 142, 155, 140, 107, 90, 134, 133, 154, 144, 115, 140, 70, 82, 33, 1, 66, 149, 161, 151, 114, 144, 157, 154, 146, 85, 155, 98, 118, 24, 95, 125, 50, 146, 72, 68, 87, 63, 161, 135, 40, 90, 152, 141, 143, 135, 
+#> 155, 154, 154, 39, 133, 114, 100, 2, 36, 49, 53, 58, 131, 143, 89, 145, 147, 69, 98, 5, 52, 84, 9, 33, 26, 23, 9, 16, 19, 30, 122, 108, 149, 156, 131, 85, 29, 92, 127, 29, 9, 4, 26, 33, 35, 34, 34, 25, 30, 30, 8, 14, 4, 4, 11, 49, 51, 59, 66, 36, 80, 71, 47, 52, 28, 24, 75, 23, 46, 70, 54, 56, 94, 125, 105, 138, 138, 85, 11, 52, 19, 31, 26, 55, 54, 6, 6, 5, 4, 12, 19, 19, 39, 20, 148, 148, 112, 118, 154, 122, 154, 120, 137, 133, 93, 46, 56, 84, 83, 110, 129, 52, 84, 143, 81, 142, 136, 158, 69, 136, 
+#> 151, 153, 151, 144, 156, 155, 151, 64, 148, 152, 153, 145, 92, 62, 108, 58, 60, 149, 132, 138, 148, 144, 144, 128, 128, 35, 95, 63, 6, 40, 85, 8, 67, 109, 130, 97, 118, 37, 49, 104, 110, 48, 26, 98, 148, 159, 157, 110, 139, 158, 144, 142, 154, 146, 135, 111, 149, 145, 44, 5, 38, 73, 78, 159, 157, 159, 154, 110, 138, 151, 153, 155, 151, 149, 129, 32, 72, 6, 111, 139, 138, 158, 108, 135, 125, 154, 160, 162, 159, 159, 154, 152, 49, 78, 87, 4, 5, 35, 56, 42, 34, 13, 17, 28, 35, 35, 24, 13, 16, 35, 36, 
+#> 24, 32, 32, 31, 24, 14, 45, 63, 73, 67, 65, 69, 42, 54, 48, 55, 56, 49, 23, 142, 100, 143, 156, 157, 136, 98, 158, 137, 138, 148, 60, 76, 21, 149, 107, 112, 148, 152, 5, 37, 109, 141, 136, 141, 135, 68, 129, 113, 126, 83, 108, 158, 161, 154, 103, 135, 100, 26, 133, 147, 22, 33, 73, 105, 79, 93, 15, 78, 94, 67, 103, 95, 68, 130, 82, 118, 121, 97, 28, 47, 98, 136, 58, 32, 62, 9, 123, 153, 159, 106, 143, 158, 161, 163, 161, 141, 83, 147, 132, 126, 56, 90, 149, 63, 85, 161, 84, 62, 40, 11, 21, 35, 34, 
+#> 32, 34, 27, 8, 34, 23, 13, 17, 11, 29, 31, 31, 30, 25, 5, 25, 72, 100, 136, 114, 58, 74, 141, 81, 26, 155, 135, 97, 82, 58, 31, 65, 76, 48, 60, 63, 73, 81, 12, 31, 34, 68, 36, 26, 16, 101, 72, 89, 110, 109, 42, 112, 139, 157, 159, 148, 159, 96, 149, 71, 75, 45, 98, 8, 26, 41, 14, 2, 115, 136, 107, 93, 143, 150, 159, 126, 136, 132, 151, 155, 123, 98, 87, 15, 6, 27, 13, 26, 20, 32, 33, 18, 33, 21, 14, 17, 28, 3, 26, 31, 45, 138, 110, 131, 59, 140, 96, 54, 38, 89, 89, 6, 66, 130, 27, 29, 9, 28, 162, 
+#> 115, 133, 157, 151, 93, 139, 119, 139, 116, 124, 25, 140, 131, 114, 28, 80, 21, 4, 7, 22, 33, 33, 31, 36, 23, 30, 14, 30, 11, 23, 35, 35, 35, 35, 18, 35, 34, 33, 10, 30, 22, 7, 129, 61, 143, 155, 157, 138, 161, 155, 101, 143, 103, 107, 117, 38, 1, 63, 30, 161, 153, 152, 135, 143, 111, 143, 146, 137, 131, 78, 59, 64, 54, 4, 97, 120, 124, 31, 102, 135, 84, 44, 128, 83, 108, 109, 19, 81, 142, 159, 162, 142, 94, 139, 161, 143, 159, 156, 152, 140, 150, 147, 104, 58, 112, 139, 43, 74, 113, 152, 111, 140, 
+#> 161, 141, 154, 139, 161, 139, 27, 6, 7, 24, 13, 15, 34, 51, 62, 69, 66, 44, 32, 68, 66, 71, 74, 61, 70, 55, 79, 16, 40, 8, 8, 25, 28, 63, 72, 52, 64, 61, 49, 57, 66, 37, 52, 137, 145, 103, 119, 124, 62, 122, 131, 9, 28, 33, 33, 12, 17, 29, 32, 33, 34, 33, 18, 19, 3, 22, 91, 137, 152, 150, 150, 147, 118, 142, 120, 154, 152, 152, 130, 133, 100, 53, 104, 24, 66, 5, 58, 144, 84, 135, 131, 143, 153, 113, 10, 20, 114, 12, 9, 105, 52, 139, 160, 159, 162, 158, 85, 122, 24, 143, 147, 148, 142, 15, 72, 21, 
+#> 48, 109, 134, 112, 141, 116, 139, 159, 151, 161, 151, 30, 125, 107, 33, 25, 153, 116, 67, 159, 105, 144, 124, 162, 159, 162, 156, 160, 150, 137, 126, 102, 114, 27, 40, 47, 98, 137, 151, 147, 123, 146, 158, 156, 147, 159, 143, 59, 143, 130, 149, 107, 17, 108, 22, 71, 28, 30, 18, 94, 141, 114, 133, 154, 55, 152, 150, 144, 137, 153, 142, 110, 117, 85, 26, 13, 73, 12, 32, 25, 24, 32, 36, 33, 29, 31, 34, 34, 33, 31, 27, 30, 32, 28, 34, 35, 23, 41, 22, 29, 13, 19, 10, 15, 30, 22, 33, 9, 116, 138, 107, 
+#> 133, 81, 86, 135, 133, 103, 126, 140, 130, 135, 93, 88, 24, 85, 62, 139, 108, 144, 143, 129, 128, 158, 141, 146, 154, 119, 148, 141, 131, 40, 89, 151, 159, 152, 161, 137, 157, 154, 160, 161, 157, 156, 111, 39, 90, 34, 105, 3, 28, 34, 24, 30, 35, 35, 29, 34, 33, 9, 4, 28, 18, 7, 25, 60, 58, 51, 137, 152, 158, 101, 126, 150, 157, 72, 87, 112, 19, 9, 8, 80, 100, 138, 123, 133, 65, 134, 128, 109, 129, 150, 103, 76, 18, 31, 22, 6, 67, 70, 52, 60, 62, 61, 63, 62, 62, 9, 59, 55, 67, 56, 53, 50, 56, 66, 
+#> 13, 48, 10, 55, 18, 15, 157, 159, 149, 158, 148, 150, 157, 119, 154, 159, 154, 156, 150, 153, 157, 131, 159, 17, 145, 41, 149, 106, 55, 92, 56, 81, 33, 95, 39, 93, 57, 24, 107, 34, 56, 17, 48, 146, 141, 161, 129, 148, 162, 162, 161, 155, 162, 154, 158, 138, 124, 137, 99, 122, 44, 151, 49, 144, 90, 120, 141, 118, 37, 117, 119, 153, 149, 138, 109, 26, 104, 56, 56, 4, 31, 35, 35, 33, 31, 32, 31, 22, 33, 15, 33, 38, 36, 33, 32, 21, 12, 30, 4, 14, 4, 1, 4, 3, 1, 34, 20, 28, 33, 27, 28, 32, 31, 29, 33, 
+#> 30, 30, 17, 16, 28, 39, 47, 55, 70, 70, 66, 64, 70, 62, 61, 9, 55, 60, 65, 61, 48, 55, 50, 2, 66, 24, 30, 33, 31, 33, 31, 29, 18, 30, 29, 33, 31, 23, 5, 20, 9, 22, 84, 152, 156, 154, 159, 159, 160, 111, 143, 162, 158, 162, 158, 158, 160, 155, 154, 154, 110, 151, 120, 153, 154, 45, 149, 144, 34, 23, 1, 17, 35, 20, 11, 34, 35, 36, 33, 36, 35, 11, 26, 34, 8, 23, 24, 8, 35, 31, 18, 26, 12, 29, 2, 55, 46, 9, 50, 78, 78, 39, 34, 64, 60, 77, 24, 153, 143, 135, 140, 21, 156, 156, 38, 43, 62, 122, 121, 55, 
+#> 65, 37, 156, 160, 112, 128, 151, 100, 55, 154, 142, 56, 142, 112, 115, 40, 88, 133, 65, 92, 24, 36, 136, 109, 97, 141, 155, 158, 142, 159, 155, 154, 150, 138, 138, 131, 51, 18, 142, 115, 129, 123, 161, 96, 115, 83, 151, 119, 104, 7, 56, 50, 24, 32, 6, 30, 34, 32, 20, 19, 16, 30, 35, 7, 19, 61, 66, 54, 66, 66, 71, 45, 64, 74, 71, 63, 67, 64, 66, 61, 64, 9, 64, 18, 41, 54, 43, 40, 41, 32, 16, 11, 18, 34, 32, 30, 34, 35, 16, 31, 31, 31, 30, 8, 5, 7, 22, 36, 38, 70, 96, 123, 114, 129, 152, 133, 135, 
+#> 120, 33, 76, 108, 138, 142, 139, 157, 152, 127, 158, 155, 159, 148, 14, 74, 31, 153, 159, 162, 161, 161, 154, 156, 154, 160, 156, 154, 75, 82, 107, 77, 94, 3, 6, 23, 27, 35, 32, 39, 33, 11, 10, 3, 20, 27, 8, 4, 5, 49, 33, 46, 40, 48, 24, 32, 34, 42, 73, 21, 47, 19, 15, 66, 80, 79, 59, 44, 34, 3, 24, 155, 148, 158, 154, 136, 55, 15, 108, 23, 26, 25, 29, 33, 32, 22, 21, 4, 22, 65, 58, 23, 24, 55, 10, 47, 73, 88, 114, 28, 21, 151, 153, 151, 126, 154, 85, 36, 98, 102, 90, 76, 113, 16, 81, 152, 148, 93, 
+#> 36, 154, 49, 94, 152, 150, 145, 57, 4, 26, 38, 120, 145, 141, 154, 95, 108, 102, 43, 120, 158, 153, 127, 136, 69, 22, 1, 4, 28, 27, 33, 35, 35, 26, 26, 34, 33, 36, 35, 33, 20, 17, 32, 22, 13, 21, 33, 29, 17, 24, 15, 24, 9, 20, 28, 3, 14, 121, 132, 135, 158, 153, 162, 161, 158, 160, 157, 158, 115, 34, 130, 128, 59, 149, 135, 133, 119, 37, 96, 24, 16, 50, 134, 86, 145, 108, 34, 130, 131, 131, 118, 67, 38, 6, 96, 151, 133, 145, 120, 147, 146, 137, 53, 59, 143, 69, 8, 140, 157, 157, 160, 157, 156, 159, 
+#> 158, 153, 137, 109, 110, 134, 128, 143, 95, 126, 112, 7, 68, 73, 61, 104, 7, 5, 42, 107, 74, 16, 1, 37, 62, 58, 66, 28, 64, 70, 78, 46, 75, 70, 66, 45, 15, 2, 71, 14, 156, 98, 155, 162, 141, 90, 69, 151, 140, 144, 161, 81, 64, 98, 44, 151, 145, 109, 133, 62, 48, 2, 63, 24, 42, 28, 17, 31, 11, 16, 2, 43, 37, 138, 153, 142, 152, 162, 162, 143, 161, 128, 144, 144, 139, 159, 26, 101, 123, 151, 144, 158, 150, 124, 135, 142, 139, 109, 18, 12, 9, 90, 159, 160, 154, 159, 161, 112, 156, 141, 156, 150, 143, 
+#> 100, 152, 145, 13, 44, 24, 29, 34, 32, 34, 35, 43, 36, 32, 36, 12, 13, 21, 10, 16, 39, 34, 15, 33, 8, 25, 23, 27, 23, 11, 30, 34, 32, 26, 33, 34, 33, 34, 32, 8, 25, 34, 33, 30, 19, 10, 3, 15, 39, 52, 33, 36, 33, 18, 14, 20, 14, 38, 32, 4, 7, 33, 63, 64, 71, 13, 19, 45, 61, 33, 39, 54, 25, 56, 28, 27, 33, 34, 28, 30, 26, 31, 34, 29, 23, 10, 17, 18, 5, 98, 75, 60, 158, 157, 97, 61, 131, 65, 137, 145, 146, 138, 154, 141, 57, 139, 133, 142, 157, 157, 150, 67, 125, 153, 40, 87, 140, 107, 73, 69, 63, 81, 
+#> 35, 24, 31, 30, 31, 34, 12, 19, 34, 20, 34, 33, 35, 30, 34, 11, 30, 28, 80, 106, 123, 108, 57, 128, 121, 110, 141, 122, 134, 47, 17, 83, 162, 157, 162, 87, 49, 145, 120, 23, 103, 154, 87, 21, 33, 35, 152, 159, 160, 159, 156, 160, 154, 144, 145, 154, 83, 151, 118, 124, 69, 124, 54, 140, 142, 153, 158, 152, 154, 155, 156, 80, 139, 139, 83, 145, 19, 83, 87, 64, 60, 71, 26, 37, 65, 140, 107, 125, 39, 89, 155, 137, 138, 159, 159, 152, 130, 145, 149, 115, 136, 121, 27, 48, 68, 51, 68, 65, 65, 67, 45, 24, 
+#> 79, 26, 33, 51, 27, 68, 62, 63, 45, 17, 58, 73, 68, 58, 66, 60, 79, 33, 19, 61, 63, 69, 61, 35, 131, 79, 154, 156, 143, 154, 159, 138, 36, 150, 97, 37, 50, 121, 9, 48, 154, 159, 161, 156, 91, 58, 149, 153, 115, 151, 14, 128, 1, 8, 60, 111, 112, 151, 138, 143, 142, 137, 142, 143, 144, 51, 111, 120, 115, 21, 145, 157, 153, 160, 153, 160, 52, 82, 155, 157, 146, 131, 84, 92, 106, 154, 133, 154, 150, 141, 152, 157, 149, 153, 149, 124, 138, 124, 72, 96, 8, 118, 3, 151, 143, 142, 49, 78, 87, 91, 72, 125, 
+#> 20, 16, 115, 153, 151, 153, 156, 125, 160, 137, 90, 23, 8, 33, 58, 113, 80, 44, 28, 11, 116, 141, 146, 155, 150, 158, 147, 140, 76, 141, 151, 120, 149, 48, 33, 45, 1, 6, 135, 99, 148, 148, 154, 138, 98, 147, 160, 146, 119, 152, 156, 140, 144, 142, 139, 157, 157, 159, 161, 162, 161, 161, 162, 146, 162, 161, 67, 95, 150, 143, 153, 24, 79, 113, 140, 79, 159, 37, 123, 154, 150, 61, 29, 49, 101, 103, 75, 50, 130, 128, 127, 150, 128, 130, 143, 129, 134, 139, 117, 81, 36, 21, 16, 79, 104, 125, 162, 153, 
+#> 162, 58, 103, 141, 153, 155, 161, 59, 101, 123, 91, 39, 3, 1, 51, 107, 37, 50, 67, 141, 112, 89, 140, 150, 105, 122, 110, 130, 102, 107, 3, 44, 18, 71, 71, 77, 76, 73, 62, 9, 45, 15, 64, 30, 41, 36, 19, 8, 161, 157, 157, 154, 161, 143, 158, 148, 160, 159, 147, 154, 99, 159, 157, 12, 137, 122, 154, 112, 77, 56, 146, 152, 154, 153, 162, 162, 148, 156, 105, 155, 153, 139, 136, 9, 105, 46, 122, 152, 141, 156, 133, 129, 51, 73, 114, 122, 99, 140, 60, 27, 34, 30, 26, 33, 32, 17, 3, 3, 15, 9, 44, 62, 75, 
+#> 73, 78, 72, 68, 79, 68, 33, 156, 137, 144, 143, 144, 129, 139, 87, 115, 129, 135, 114, 86, 5, 101, 119, 32, 117, 26, 7, 15, 42, 44, 69, 62, 14, 35, 35, 35, 34, 35, 34, 34, 32, 34, 34, 13, 32, 30, 3, 2, 31, 130, 96, 122, 119, 97, 119, 117, 134, 145, 132, 61, 57, 15, 10, 5, 62, 75, 66, 66, 69, 31, 68, 20, 20, 13, 26, 105, 159, 160, 162, 162, 162, 162, 162, 162, 133, 158, 158, 97, 59, 91, 53, 56, 68, 69, 84, 55, 24, 23, 151, 124, 155, 147, 31, 78, 84, 133, 39, 54, 131, 117, 91, 52, 7, 32, 33, 37, 22, 
+#> 32, 21, 6, 44, 9, 22, 158, 156, 156, 145, 156, 159, 135, 109, 117, 147, 137, 151, 93, 58, 67, 5, 106, 150, 154, 156, 157, 159, 161, 158, 159, 112, 142, 141, 108, 145, 135, 80, 8, 12, 63, 74, 74, 67, 32, 33, 33, 35, 35, 33, 34, 34, 34, 34, 21, 17, 9, 4, 23, 24, 26, 29, 33, 30, 27, 32, 21, 30, 21, 7, 8, 20, 2, 36, 19, 17, 34, 36, 21, 19, 32, 31, 34, 32, 33, 32, 25, 13, 5, 20, 33, 77, 77, 70, 14, 2, 20, 34, 50, 22, 141, 70, 158, 158, 162, 155, 161, 158, 50, 150, 155, 141, 39, 109, 85, 28, 41, 75, 44, 
+#> 128, 136, 134, 146, 152, 150, 122, 142, 85, 50, 87, 142, 86, 49, 55, 105, 106, 162, 146, 124, 158, 153, 64, 4, 47, 86, 91, 38, 16, 11, 54, 67, 72, 72, 65, 72, 72, 43, 44, 31, 15, 20, 158, 134, 159, 132, 9, 84, 21, 14, 27, 42, 40, 35, 38, 8, 7, 6, 10, 16, 55, 128, 145, 116, 153, 70, 103, 8, 146, 110, 150, 32, 24, 3, 30, 159, 161, 134, 156, 154, 149, 108, 158, 157, 131, 77, 130, 67, 83, 140, 153, 124, 152, 144, 110, 87, 126, 147, 85, 8, 97, 140, 146, 160, 130, 158, 150, 153, 154, 113, 119, 73, 68, 
+#> 68, 145, 102, 152, 141, 116, 22, 32, 28, 32, 33, 25, 15, 13, 20, 12, 24, 35, 36, 33, 5, 26, 6, 8, 15, 86, 10, 130, 89, 125, 128, 150, 159, 151, 149, 109, 150, 145, 146, 90, 137, 142, 146, 30, 15, 27, 45, 34, 33, 34, 33, 34, 25, 29, 21, 46, 135, 158, 159, 106, 22, 32, 65, 45, 135, 114, 150, 18, 57, 5, 63, 11, 151, 84, 96, 93, 145, 97, 9, 61, 27, 3, 120, 162, 159, 145, 49, 106, 151, 95, 123, 70, 68, 146, 145, 162, 162, 54, 78, 103, 54, 156, 158, 156, 123, 15, 123, 111, 66, 53, 79, 128, 149, 96, 140, 
+#> 149, 155, 126, 135, 125, 113, 42, 12, 49, 141, 147, 153, 147, 73, 56, 99, 127, 145, 159, 151, 120, 19, 73, 132, 140, 153, 91, 102, 21, 86, 154, 154, 105, 155, 133, 101, 107, 77, 152, 138, 126, 159, 158, 156, 156, 156, 149, 143, 111, 154, 124, 156, 161, 148, 143, 89, 10, 16, 134, 105, 115, 120, 23, 15, 59, 151, 152, 154, 162, 157, 158, 159, 162, 58, 98, 158, 156, 152, 154, 142, 8, 92, 78, 108, 147, 150, 157, 158, 142, 135, 87, 75, 31, 61, 17, 62, 40, 6, 26, 49, 142, 143, 156, 151, 137, 155, 158, 152, 
+#> 151, 122, 152, 149, 149, 144, 126, 81, 14, 104, 135, 109, 135, 100, 145, 72, 146, 140, 109, 137, 139, 81, 9, 13, 6, 32, 33, 33, 11, 14, 11, 29, 29, 32, 29, 32, 6, 5, 19, 20, 4, 78, 73, 69, 64, 68, 68, 70, 48, 66, 67, 62, 1, 19, 31, 32, 30, 34, 16, 17, 34, 34, 33, 10, 19, 7, 12, 29, 24, 30, 31, 33, 14, 33, 24, 34, 34, 13, 28, 33, 32, 1, 4, 28, 35, 34, 3, 54, 142, 135, 131, 157, 139, 107, 149, 126, 119, 51, 35, 1, 86, 144, 139, 51, 132, 142, 137, 133, 103, 131, 131, 109, 39, 68, 28, 35, 21, 36, 35, 
+#> 35, 33, 32, 30, 20, 15, 24, 17, 9, 12, 69, 74, 68, 76, 6, 9, 67, 69, 48, 63, 64, 44, 62, 40, 58, 28, 33, 62, 19, 88, 159, 144, 162, 160, 143, 152, 71, 80, 153, 129, 4, 49, 127, 131, 150, 127, 85, 30, 28, 8, 126, 89, 132, 117, 70, 134, 133, 107, 57, 44, 30, 7, 87, 160, 158, 158, 157, 160, 160, 150, 161, 161, 148, 159, 119, 127, 152, 150, 140, 158, 153, 162, 102, 59, 162, 115, 160, 157, 155, 66, 81, 15, 40, 30, 21, 35, 44, 46, 40, 39, 38, 17, 3, 25, 7, 17, 21, 10, 49, 85, 59, 79, 148, 85, 71, 154, 
+#> 43, 100, 85, 66, 4, 109, 16, 32, 75, 38, 112, 159, 143, 138, 156, 155, 159, 59, 39, 17, 77, 91, 47, 145, 146, 161, 145, 159, 155, 154, 145, 150, 148, 149, 141, 143, 143, 145, 150, 64, 2, 106, 156, 160, 160, 159, 162, 156, 155, 135, 157, 159, 156, 21, 126, 6, 36, 34, 125, 149, 147, 52, 91, 132, 124, 119, 21, 46, 45, 88, 118, 144, 53, 94, 122, 126, 86, 43, 110, 142, 141, 153, 132, 122, 90, 118, 153, 152, 120, 142, 158, 123, 117, 18, 76, 136, 116, 4, 4, 19, 1, 1, 54, 64, 26, 69, 71, 74, 16, 38, 49, 
+#> 23, 29, 35, 33, 33, 34, 34, 1, 78, 153, 156, 51, 105, 123, 148, 133, 150, 121, 81, 137, 134, 116, 86, 30, 40, 74, 141, 157, 157, 163, 135, 81, 69, 134, 127, 25, 135, 49, 8, 8, 23, 13, 4, 32, 35, 34, 33, 11, 21, 31, 32, 32, 35, 33, 30, 15, 15, 8, 5, 59, 69, 66, 69, 64, 76, 70, 53, 31, 42, 78, 23, 25, 69, 60, 2, 30, 32, 33, 35, 33, 34, 33, 34, 32, 20, 2, 158, 154, 153, 151, 142, 92, 64, 93, 86, 128, 105, 132, 122, 160, 159, 161, 160, 159, 161, 160, 157, 156, 7, 17, 53, 151, 144, 132, 150, 47, 97, 90, 
+#> 35, 131, 140, 109, 146, 138, 137, 82, 147, 113, 120, 158, 43, 94, 147, 160, 132, 159, 156, 115, 103, 83, 131, 155, 34, 73, 59, 130, 139, 145, 138, 143, 128, 121, 102, 140, 135, 121, 125, 155, 158, 139, 93, 63, 158, 124, 157, 141, 156, 73, 6, 32, 32, 31, 34, 37, 37, 38, 35, 42, 25, 35, 69, 53, 161, 153, 160, 159, 36, 133, 126, 160, 93, 143, 47, 69, 69, 160, 154, 160, 160, 144, 157, 102, 156, 112, 134, 38, 34, 114, 156, 158, 153, 160, 132, 152, 153, 159, 136, 85, 37, 145, 32, 73, 17, 59, 59, 67, 66, 
+#> 65, 63, 70, 61, 66, 37, 22, 22, 75, 40, 131, 142, 79, 18, 148, 139, 135, 144, 153, 160, 85, 4, 18, 16, 110, 144, 127, 152, 142, 54, 155, 104, 126, 48, 136, 50, 33, 33, 31, 30, 31, 28, 34, 18, 17, 34, 34, 33, 28, 32, 8, 29, 17, 32, 27, 30, 32, 37, 29, 3, 13, 17, 19, 32, 10, 13, 20, 12, 19, 72, 44, 147, 145, 145, 136, 102, 120, 42, 80, 28, 43, 158, 162, 162, 157, 106, 33, 71, 52, 60, 39, 58, 121, 151, 155, 143, 97, 125, 133, 127, 111, 129, 70, 162, 162, 155, 82, 75, 124, 15, 153, 148, 59, 22, 10, 119, 
+#> 63, 126, 93, 140, 157, 109, 161, 152, 144, 105, 108, 14, 158, 154, 156, 154, 158, 158, 162, 137, 155, 88, 142, 156, 160, 138, 144, 39, 157, 158, 159, 162, 161, 162, 162, 162, 42, 158, 4, 50, 84, 92, 150, 159, 147, 126, 108, 106, 122, 60, 74, 42, 74, 26, 30, 63, 26, 54, 34, 31, 59, 26, 38, 70, 62, 37, 25, 68, 30, 42, 72, 76, 81, 68, 50, 47, 3, 54, 64, 72, 68, 47, 29, 60, 60, 57, 40, 18, 54, 29, 61, 44, 65, 74, 52, 60, 75, 71, 20, 21, 31, 139, 157, 154, 75, 159, 141, 160, 135, 93, 113, 151, 158, 157, 
+#> 150, 154, 61, 135, 140, 35, 36, 4, 41, 27, 34, 6, 6, 22, 20, 1, 8, 1, 73, 68, 22, 11, 32, 72, 69, 18, 10, 16, 30, 32, 33, 31, 18, 11, 13, 27, 26, 23, 30, 36, 32, 34, 33, 31, 33, 30, 20, 12, 2, 9, 33, 32, 33, 20, 31, 22, 12, 13, 15, 35, 33, 34, 13, 6, 78, 80, 70, 78, 66, 72, 67, 50, 25, 11, 24, 34, 33, 33, 33, 33, 32, 34, 16, 16, 43, 156, 161, 162, 160, 160, 159, 123, 36, 157, 159, 156, 11, 112, 6, 6, 149, 158, 141, 153, 155, 150, 147, 151, 121, 148, 51, 114, 129, 111, 124, 140, 136, 139, 138, 136, 
+#> 110, 136, 41, 106, 137, 152, 84, 45, 85, 81, 55, 34, 146, 79, 36, 21, 153, 131, 146, 156, 147, 132, 53, 101, 122, 30, 33, 38, 72, 18, 73, 158, 142, 63, 96, 145, 123, 157, 132, 149, 82, 124, 149, 149, 92, 133, 81, 56, 15, 12, 33, 32, 32, 31, 33, 33, 21, 11, 32, 122, 157, 151, 133, 74, 160, 162, 160, 1, 11, 18, 141, 102, 105, 125, 52, 47, 54, 14, 10, 78, 39, 111, 113, 162, 157, 154, 68, 63, 151, 154, 110, 40, 157, 150, 52, 90, 156, 89, 133, 121, 148, 151, 89, 50, 57, 81, 130, 99, 131, 118, 86, 82, 
+#> 50, 23, 39, 8, 15, 19, 120, 152, 139, 59, 77, 38, 101, 125, 38, 112, 63, 151, 152, 156, 151, 143, 109, 156, 154, 130, 31, 116, 105, 69, 105, 155, 160, 55, 158, 138, 33, 104, 156, 87, 133, 116, 10, 8, 24, 33, 3, 52, 32, 33, 33, 29, 13, 24, 29, 32, 32, 32, 41, 132, 119, 149, 151, 162, 160, 159, 137, 28, 32, 34, 35, 35, 33, 32, 30, 34, 33, 33, 31, 31, 33, 32, 32, 20, 157, 162, 106, 157, 142, 101, 145, 147, 61, 95, 17, 105, 138, 157, 141, 53, 105, 155, 130, 106, 46, 95, 52, 98, 155, 159, 162, 161, 106, 
+#> 73, 150, 154, 3, 61, 37, 25, 40, 37, 33, 35, 32, 7, 130, 109, 144, 149, 144, 77, 51, 27, 17, 42, 22, 81, 74, 68, 67, 64, 73, 69, 13, 68, 47, 42, 19, 30, 10, 128, 91, 65, 39, 70, 125, 148, 18, 89, 88, 151, 150, 125, 93, 143, 96, 149, 126, 153, 141, 160, 139, 135, 149, 142, 130, 142, 6, 38, 41, 32, 32, 32, 20, 46, 69, 74, 62, 59, 21, 163, 162, 162, 51, 143, 93, 142, 145, 141, 34, 6, 28, 14, 29, 31, 26, 12, 22, 26, 29, 31, 24, 33, 36, 34, 34, 27, 29, 35, 34, 23, 7, 35, 33, 29, 21, 31, 24, 12, 31, 30, 
+#> 31, 34, 34, 33, 33, 31, 34, 31, 7, 43, 100, 134, 153, 152, 92, 40, 41, 59, 85, 89, 145, 127, 135, 110, 70, 153, 21, 24, 9, 6, 32, 35, 35, 34, 40, 36, 34, 36, 32, 32, 15, 25, 155, 101, 151, 122, 143, 47, 126, 91, 87, 41, 16, 13, 23, 12, 11, 117, 142, 107, 21, 113, 161, 149, 92, 118, 155, 153, 24, 151, 131, 150, 161, 111, 162, 62, 158, 6, 14, 2, 91, 8, 66, 145, 151, 120, 33, 121, 130, 94, 83, 9, 14, 24, 27, 32, 35, 37, 49, 52, 45, 45, 35, 32, 33, 23, 31, 30, 21, 32, 33, 11, 40, 6, 7, 53, 71, 14, 77, 
+#> 64, 42, 69, 68, 64, 6, 20, 70, 64, 8, 6, 30, 30, 18, 7, 108, 45, 148, 148, 147, 150, 136, 148, 156, 158, 158, 158, 158, 154, 154, 159, 146, 158, 159, 161, 154, 136, 48, 4, 67, 20, 4, 31, 33, 33, 33, 33, 33, 33, 8, 41, 96, 31, 128, 108, 124, 159, 109, 159, 152, 17, 70, 97, 144, 138, 134, 121, 33, 145, 153, 18, 158, 74, 134, 149, 111, 22, 31, 32, 33, 34, 35, 27, 34, 96, 130, 139, 144, 148, 26, 75, 151, 134, 49, 74, 151, 161, 156, 156, 104, 147, 161, 157, 161, 160, 160, 104, 160, 155, 156, 34, 79, 98, 
+#> 137, 138, 143, 141, 138, 156, 156, 120, 133, 141, 133, 156, 104, 46, 55, 100, 92, 124, 159, 158, 159, 161, 162, 151, 151, 7, 50, 74, 75, 62, 13, 49, 13, 60, 10, 29, 31, 32, 13, 29, 21, 79, 63, 68, 63, 61, 29, 104, 141, 116, 102, 124, 67, 9, 47, 159, 158, 141, 160, 136, 156, 160, 61, 155, 157, 45, 114, 131, 97, 151, 143, 136, 97, 49, 143, 43, 108, 138, 133, 159, 150, 149, 154, 150, 6, 11, 3, 33, 9, 3, 64, 30, 162, 152, 108, 153, 40, 84, 151, 80, 23, 83, 52, 6, 130, 150, 129, 154, 147, 155, 113, 88, 
+#> 139, 158, 41, 153, 152, 117, 108, 141, 157, 126, 4, 38, 25, 9, 1, 32, 35, 27, 33, 34, 34, 35, 33, 20, 27, 39, 63, 48, 38, 73, 72, 39, 76, 68, 69, 14, 54, 5, 23, 32, 34, 31, 27, 11, 23, 21, 11, 27, 29, 87, 156, 114, 109, 149, 124, 35, 151, 146, 115, 101, 129, 158, 159, 141, 114, 110, 141, 149, 152, 136, 57, 6, 87, 151, 43, 154, 152, 140, 127, 30, 143, 156, 141, 72, 22, 2, 15, 8, 91, 156, 161, 113, 161, 141, 58, 77, 156, 108, 154, 158, 157, 157, 146, 157, 142, 128, 158, 104, 149, 154, 27, 48, 137, 
+#> 118, 117, 104, 145, 144, 150, 113, 95, 61, 127, 5, 40, 139, 157, 157, 159, 139, 118, 100, 153, 7, 9, 33, 114, 130, 137, 131, 128, 140, 136, 134, 138, 128, 129, 135, 134, 72, 30, 113, 12, 16, 142, 144, 102, 133, 114, 136, 145, 111, 24, 68, 9, 26, 108, 101, 148, 157, 155, 160, 137, 157, 12, 5, 28, 30, 34, 23, 21, 154, 154, 130, 158, 154, 156, 12, 43, 43, 22, 37, 73, 64, 43, 17, 31, 31, 33, 32, 32, 33, 34, 128, 152, 159, 131, 158, 51, 156, 82, 162, 39, 76, 138, 150, 142, 48, 145, 160, 109, 159, 133, 
+#> 111, 157, 58, 153, 137, 97, 94, 137, 147, 148, 41, 74, 49, 157, 146, 147, 15, 19, 30, 88, 87, 60, 28, 8, 11, 80, 113, 45, 31, 28, 139, 160, 127, 160, 7, 114, 157, 158, 154, 95, 74, 149, 152, 122, 150, 8, 41, 35, 115, 126, 150, 144, 71, 153, 157, 139, 101, 130, 49, 117, 43, 6, 61, 115, 133, 140, 49, 87, 160, 140, 160, 7, 31, 31, 30, 18, 14, 4, 4, 20, 30, 34, 9, 116, 157, 155, 22, 92, 160, 60, 49, 3, 12, 26, 36, 32, 53, 155, 160, 159, 161, 17, 33, 30, 33, 37, 81, 109, 149, 150, 121, 116, 143, 62, 144, 
+#> 126, 100, 150, 123, 116, 145, 74, 4, 20, 35, 32, 31, 34, 36, 145, 154, 23, 31, 57, 147, 152, 158, 154, 43, 88, 135, 95, 28, 72, 114, 149, 151, 156, 137, 17, 110, 159, 129, 133, 137, 151, 98, 153, 80, 9, 38, 145, 158, 155, 158, 162, 148, 10, 27, 29, 18, 22, 24, 5, 9, 26, 33, 1, 108, 151, 129, 135, 51, 101, 102, 57, 21, 58, 127, 159, 56, 87, 38, 148, 145, 31, 137, 75, 157, 47, 135, 135, 153, 66, 143, 149, 153, 143, 14, 75, 158, 158, 158, 49, 155, 109, 156, 161, 143, 130, 99, 151, 57, 43, 27, 152, 51, 
+#> 134, 156, 39, 59, 158, 53, 113, 86, 123, 158, 18, 144, 156) x c(245, 289, 182, 259, 236, 257, 282, 10, 30, 162, 23, 49, 181, 271, 308, 305, 261, 257, 409, 374, 361, 379, 442, 490, 411, 487, 478, 513, 486, 273, 121, 206, 340, 332, 316, 297, 343, 370, 211, 327, 340, 21, 270, 326, 381, 361, 249, 253, 175, 79, 122, 154, 96, 76, 297, 206, 579, 517, 529, 534, 577, 521, 419, 43, 152, 189, 259, 210, 166, 205, 191, 181, 149, 92, 21, 29, 117, 79, 11, 84, 283, 210, 215, 205, 262, 173, 187, 57, 101, 131, 55, 103, 284, 220, 256, 212, 186, 179, 144, 138, 8, 298, 584, 596, 
+#> 536, 612, 560, 539, 531, 527, 550, 568, 588, 181, 285, 46, 40, 1, 65, 174, 196, 187, 186, 140, 180, 153, 154, 148, 124, 153, 148, 137, 148, 120, 104, 125, 115, 107, 55, 25, 16, 175, 545, 608, 312, 451, 544, 348, 4, 485, 553, 249, 602, 509, 581, 469, 591, 315, 448, 465, 419, 490, 426, 6, 34, 81, 98, 3, 112, 115, 139, 116, 86, 101, 91, 75, 9, 11, 130, 127, 124, 133, 127, 91, 107, 129, 95, 107, 112, 110, 103, 105, 51, 5, 17, 465, 597, 498, 405, 474, 524, 527, 522, 384, 146, 291, 206, 567, 542, 602, 
+#> 259, 408, 38, 560, 534, 288, 165, 561, 570, 547, 69, 359, 5, 138, 287, 258, 288, 268, 266, 317, 299, 313, 17, 226, 237, 212, 69, 2, 74, 238, 367, 263, 111, 371, 323, 387, 329, 430, 265, 142, 256, 91, 0, 0, 127, 389, 515, 555, 550, 562, 575, 563, 582, 591, 589, 588, 574, 581, 609, 582, 612, 322, 104, 2, 635, 581, 596, 588, 310, 562, 41, 58, 99, 154, 157, 84, 138, 158, 136, 32, 16, 11, 0, 4, 103, 114, 76, 97, 100, 114, 97, 80, 36, 103, 13, 13, 135, 161, 124, 140, 130, 91, 109, 82, 45, 69, 60, 13, 12, 
+#> 0, 2, 150, 358, 605, 581, 573, 506, 591, 553, 428, 345, 563, 542, 588, 421, 497, 428, 507, 526, 556, 625, 415, 233, 490, 353, 13, 98, 149, 516, 593, 577, 485, 550, 494, 511, 541, 587, 476, 538, 487, 403, 508, 410, 323, 147, 73, 13, 18, 10, 98, 474, 525, 498, 491, 534, 491, 493, 260, 436, 210, 16, 2, 295, 235, 178, 406, 402, 331, 405, 328, 449, 234, 234, 227, 108, 162, 248, 221, 51, 256, 431, 491, 452, 380, 343, 334, 424, 297, 241, 80, 252, 209, 266, 276, 476, 143, 496, 236, 132, 606, 121, 593, 222, 
+#> 12, 244, 31, 310, 550, 517, 518, 599, 602, 399, 527, 459, 427, 278, 525, 417, 501, 551, 550, 429, 392, 13, 2, 2, 77, 89, 93, 98, 85, 121, 125, 103, 91, 31, 54, 19, 59, 82, 16, 97, 117, 101, 110, 104, 102, 87, 34, 42, 11, 237, 588, 571, 527, 549, 534, 512, 490, 548, 516, 515, 568, 495, 556, 473, 558, 413, 552, 566, 432, 230, 86, 173, 348, 566, 488, 603, 437, 451, 489, 447, 533, 549, 544, 554, 583, 375, 369, 90, 464, 532, 340, 533, 508, 416, 463, 433, 155, 478, 446, 491, 278, 241, 83, 183, 3, 0, 117, 
+#> 134, 88, 107, 150, 128, 148, 131, 115, 103, 103, 103, 66, 110, 83, 63, 99, 86, 56, 67, 55, 29, 12, 74, 92, 33, 3, 84, 493, 563, 342, 386, 538, 559, 577, 553, 497, 465, 550, 230, 177, 149, 103, 267, 15, 23, 330, 571, 581, 493, 543, 534, 526, 521, 545, 564, 330, 518, 602, 526, 598, 505, 556, 425, 375, 226, 33, 7, 2, 109, 149, 280, 342, 232, 266, 256, 178, 95, 63, 33, 12, 2, 91, 394, 407, 257, 216, 88, 1, 19, 116, 544, 538, 500, 580, 520, 571, 547, 546, 523, 471, 494, 552, 506, 426, 574, 486, 429, 539, 
+#> 523, 191, 99, 120, 134, 129, 126, 73, 123, 89, 96, 86, 94, 90, 76, 60, 93, 81, 38, 36, 79, 101, 137, 128, 144, 134, 136, 147, 142, 130, 150, 125, 64, 111, 108, 93, 113, 97, 103, 46, 120, 126, 155, 135, 142, 157, 125, 126, 129, 98, 90, 20, 21, 77, 10, 7, 55, 69, 88, 124, 56, 43, 54, 6, 422, 192, 137, 194, 505, 68, 532, 496, 561, 511, 597, 596, 561, 550, 581, 500, 509, 506, 402, 84, 134, 22, 135, 259, 382, 486, 510, 482, 311, 300, 118, 274, 351, 84, 82, 2, 1, 7, 39, 83, 103, 53, 114, 97, 85, 22, 9, 
+#> 92, 89, 63, 56, 55, 11, 31, 9, 147, 192, 149, 241, 240, 441, 451, 392, 474, 382, 452, 324, 295, 88, 5, 24, 0, 10, 406, 160, 374, 514, 507, 579, 499, 476, 547, 583, 587, 529, 386, 265, 97, 456, 577, 335, 72, 16, 3, 60, 72, 87, 88, 84, 98, 16, 59, 87, 7, 2, 26, 287, 195, 470, 411, 527, 477, 512, 125, 53, 83, 515, 346, 16, 27, 115, 208, 101, 256, 180, 297, 139, 53, 3, 0, 82, 176, 215, 229, 351, 351, 258, 137, 42, 67, 48, 220, 83, 132, 141, 110, 3, 11, 75, 61, 44, 113, 2, 120, 79, 92, 99, 100, 50, 93, 
+#> 93, 79, 60, 78, 62, 60, 43, 39, 0, 20, 42, 261, 313, 387, 385, 368, 248, 309, 205, 2, 22, 26, 58, 364, 603, 563, 503, 508, 522, 519, 445, 464, 470, 544, 571, 419, 246, 137, 400, 163, 4, 91, 79, 5, 15, 42, 13, 31, 541, 561, 592, 577, 564, 570, 360, 553, 504, 567, 330, 234, 1, 252, 275, 503, 394, 241, 400, 300, 291, 297, 186, 120, 238, 5, 85, 97, 99, 19, 34, 20, 18, 71, 14, 23, 17, 75, 571, 572, 528, 453, 158, 303, 592, 538, 65, 516, 570, 333, 188, 355, 380, 351, 313, 435, 468, 331, 247, 184, 129, 
+#> 118, 31, 124, 17, 220, 365, 391, 371, 378, 381, 289, 239, 132, 68, 138, 102, 103, 137, 130, 138, 139, 10, 70, 118, 95, 85, 111, 65, 79, 15, 50, 94, 86, 41, 4, 552, 573, 559, 508, 474, 544, 478, 468, 396, 537, 553, 516, 610, 500, 405, 227, 377, 570, 575, 526, 558, 482, 539, 591, 38, 441, 476, 257, 381, 471, 13, 46, 268, 537, 570, 425, 314, 541, 257, 573, 505, 386, 76, 52, 1, 54, 27, 104, 96, 105, 84, 8, 55, 63, 75, 76, 23, 59, 95, 63, 86, 11, 22, 46, 73, 468, 568, 543, 576, 456, 512, 567, 423, 440, 
+#> 559, 584, 537, 607, 581, 155, 127, 0, 10, 37, 413, 492, 517, 473, 553, 430, 493, 501, 463, 524, 597, 586, 470, 79, 50, 104, 149, 186, 229, 151, 120, 100, 350, 292, 364, 186, 98, 62, 379, 10, 263, 5, 56, 32, 385, 526, 430, 491, 261, 504, 365, 267, 8, 8, 9, 113, 183, 335, 535, 557, 447, 564, 520, 398, 151, 585, 463, 444, 50, 395, 322, 506, 560, 540, 454, 451, 328, 555, 546, 461, 270, 487, 92, 529, 569, 536, 544, 583, 580, 580, 348, 355, 82, 95, 117, 103, 94, 61, 22, 207, 307, 359, 338, 316, 225, 330, 
+#> 387, 424, 408, 272, 356, 167, 285, 264, 245, 249, 92, 76, 21, 32, 106, 86, 17, 27, 52, 82, 40, 84, 125, 15, 57, 27, 135, 409, 487, 442, 483, 455, 467, 248, 194, 330, 388, 108, 70, 492, 506, 503, 132, 277, 50, 6, 436, 525, 499, 522, 448, 503, 426, 214, 45, 102, 606, 534, 453, 535, 533, 528, 568, 362, 409, 536, 583, 568, 600, 349, 566, 616, 411, 247, 63, 401, 392, 413, 410, 424, 333, 394, 485, 416, 442, 382, 153, 343, 226, 26, 1, 2, 83, 68, 53, 85, 104, 43, 71, 57, 82, 19, 50, 86, 571, 586, 509, 604, 
+#> 561, 38, 480, 493, 612, 672, 581, 594, 266, 234, 29, 366, 560, 558, 562, 571, 478, 67, 57, 310, 307, 237, 339, 347, 399, 323, 245, 364, 295, 260, 171, 192, 146, 10, 1, 17, 51, 605, 561, 622, 623, 597, 465, 534, 631, 605, 631, 614, 336, 349, 47, 129, 21, 2, 187, 548, 530, 158, 404, 284, 85, 74, 71, 12, 97, 86, 95, 52, 42, 48, 397, 2, 455, 587, 553, 599, 493, 448, 550, 357, 426, 465, 559, 65, 35, 35, 18, 21, 326, 473, 406, 313, 112, 92, 154, 264, 309, 318, 402, 354, 325, 148, 194, 563, 477, 478, 499, 
+#> 335, 442, 171, 606, 651, 444, 319, 479, 453, 375, 515, 358, 17, 259, 451, 519, 537, 497, 498, 21, 166, 62, 156, 94, 518, 405, 468, 351, 435, 590, 562, 584, 535, 558, 314, 336, 492, 238, 65, 17, 1, 20, 92, 110, 31, 2, 63, 60, 11, 17, 2, 13, 274, 580, 539, 452, 511, 631, 582, 586, 636, 649, 613, 614, 491, 49, 629, 431, 10, 92, 136, 123, 317, 432, 457, 540, 406, 522, 529, 359, 495, 540, 536, 499, 518, 534, 457, 459, 365, 72, 160, 130, 380, 294, 247, 482, 290, 498, 579, 281, 280, 417, 473, 275, 193, 
+#> 305, 57, 495, 523, 416, 512, 589, 592, 623, 424, 536, 504, 527, 568, 486, 602, 104, 357, 58, 9, 83, 23, 24, 5, 56, 14, 97, 4, 96, 5, 366, 316, 349, 154, 219, 214, 164, 221, 48, 122, 191, 114, 16, 25, 2, 256, 544, 587, 532, 96, 0, 500, 36, 230, 47, 523, 533, 541, 563, 582, 447, 420, 571, 629, 427, 546, 575, 206, 502, 556, 7, 72, 51, 85, 71, 13, 53, 91, 86, 67, 57, 112, 86, 99, 112, 109, 508, 375, 570, 346, 563, 446, 433, 435, 29, 193, 16, 268, 360, 299, 320, 286, 409, 331, 315, 191, 133, 10, 166, 
+#> 551, 272, 69, 522, 435, 504, 579, 418, 165, 527, 483, 540, 563, 570, 163, 450, 376, 6, 427, 587, 620, 593, 564, 599, 588, 468, 244, 485, 521, 629, 610, 599, 542, 100, 324, 538, 296, 23, 13, 26, 92, 60, 79, 103, 95, 101, 113, 122, 108, 107, 104, 82, 18, 4, 27, 215, 234, 269, 386, 378, 370, 359, 398, 489, 335, 392, 330, 307, 91, 191, 24, 255, 584, 524, 590, 586, 530, 566, 575, 559, 474, 491, 536, 419, 602, 576, 476, 442, 1, 75, 49, 21, 30, 21, 97, 86, 104, 100, 96, 98, 102, 41, 509, 430, 301, 558, 
+#> 592, 260, 286, 357, 592, 583, 566, 581, 487, 463, 512, 488, 350, 499, 143, 17, 69, 90, 69, 111, 114, 93, 126, 124, 96, 81, 96, 131, 91, 16, 57, 76, 44, 20, 5, 2, 7, 0, 45, 236, 0, 340, 570, 540, 552, 543, 446, 453, 534, 577, 520, 568, 523, 422, 147, 217, 17, 365, 227, 509, 564, 481, 492, 639, 587, 581, 603, 561, 615, 8, 22, 43, 227, 605, 412, 471, 407, 512, 582, 549, 618, 330, 124, 6, 1, 1, 17, 48, 101, 18, 120, 108, 92, 77, 68, 11, 90, 81, 59, 23, 8, 197, 586, 23, 557, 624, 561, 633, 595, 646, 649, 
+#> 641, 603, 616, 616, 593, 413, 288, 85, 335, 5, 90, 108, 99, 89, 131, 76, 42, 20, 7, 75, 97, 110, 94, 111, 116, 99, 79, 82, 81, 82, 6, 19, 21, 45, 34, 58, 80, 104, 115, 80, 67, 64, 76, 54, 0, 539, 359, 366, 528, 443, 507, 569, 576, 557, 533, 548, 60, 103, 143, 6, 184, 183, 323, 267, 310, 393, 152, 335, 177, 87, 26, 474, 489, 581, 504, 559, 596, 526, 500, 372, 55, 84, 63, 69, 24, 54, 104, 108, 125, 69, 54, 77, 60, 37, 70, 78, 49, 53, 18, 18, 38, 77, 107, 104, 53, 45, 109, 143, 92, 27, 83, 16, 98, 32, 
+#> 27, 34, 190, 440, 618, 514, 641, 603, 502, 545, 617, 547, 527, 540, 518, 486, 585, 550, 354, 303, 32, 38, 76, 7, 23, 107, 590, 587, 592, 560, 571, 586, 499, 222, 402, 577, 166, 188, 202, 164, 469, 310, 478, 550, 632, 614, 499, 282, 126, 68, 28, 40, 70, 95, 63, 35, 97, 89, 98, 63, 57, 51, 5, 1, 7, 13, 58, 45, 134, 411, 387, 491, 461, 341, 252, 644, 610, 404, 434, 387, 312, 125, 17, 4, 70, 74, 49, 100, 80, 98, 5, 102, 120, 95, 113, 124, 102, 49, 30, 4, 5, 15, 51, 94, 94, 101, 95, 81, 61, 51, 47, 39, 
+#> 38, 54, 20, 53, 47, 26, 55, 97, 94, 47, 101, 101, 109, 107, 84, 103, 84, 81, 104, 65, 55, 40, 34, 35, 44, 24, 3, 92, 104, 97, 125, 117, 62, 108, 21, 92, 80, 31, 479, 545, 587, 349, 523, 610, 588, 577, 569, 589, 178, 574, 443, 272, 20, 18, 218, 305, 492, 538, 505, 500, 392, 140, 148, 137, 29, 76, 38, 47, 1, 182, 451, 556, 286, 537, 543, 602, 455, 524, 570, 573, 502, 505, 558, 453, 459, 31, 43, 32, 94, 109, 144, 107, 101, 132, 79, 98, 108, 117, 90, 55, 0, 5, 20, 5, 21, 12, 14, 69, 91, 105, 74, 102, 
+#> 112, 126, 88, 34, 46, 68, 46, 19, 3, 70, 572, 558, 553, 594, 608, 578, 569, 588, 578, 353, 484, 503, 524, 22, 141, 44, 533, 562, 593, 563, 542, 519, 524, 543, 547, 463, 429, 531, 570, 384, 267, 8, 132, 3, 0, 8, 113, 125, 270, 260, 392, 452, 183, 22, 317, 492, 178, 133, 52, 248, 249, 174, 67, 163, 67, 123, 10, 2, 2, 28, 32, 64, 111, 86, 104, 73, 102, 78, 83, 67, 54, 75, 30, 25, 19, 7, 1, 3, 42, 101, 115, 77, 73, 39, 13, 43, 5, 3, 1, 0, 89, 83, 106, 98, 55, 90, 96, 74, 89, 67, 56, 28, 4, 15, 17, 41, 
+#> 336, 393, 502, 521, 493, 622, 591, 405, 516, 376, 453, 522, 542, 543, 442, 74, 291, 108, 112, 15, 2, 77, 388, 372, 383, 379, 344, 174, 200, 68, 145, 345, 35, 416, 17, 370, 536, 567, 644, 594, 557, 555, 489, 433, 364, 366, 43, 16, 79, 0, 122, 84, 61, 92, 50, 60, 56, 44, 15, 9, 56, 6, 18, 8, 24, 75, 77, 85, 65, 83, 101, 99, 85, 69, 74, 51, 60, 66, 53, 21, 14, 8, 327, 596, 411, 385, 469, 537, 551, 431, 555, 195, 122, 523, 511, 465, 52, 19, 571, 616, 545, 591, 574, 573, 569, 540, 497, 615, 513, 624, 
+#> 444, 204, 12, 72, 231, 354, 398, 284, 449, 388, 22, 508, 380, 406, 490, 438, 413, 424, 356, 299, 306, 64, 150, 61, 379, 402, 522, 487, 503, 518, 220, 476, 570, 507, 501, 285, 320, 319, 127, 184, 59, 14, 17, 6, 233, 261, 358, 361, 449, 501, 393, 368, 428, 350, 188, 198, 83, 50, 136, 63, 57, 420, 370, 432, 468, 514, 487, 459, 518, 429, 437, 411, 126, 98, 594, 654, 583, 406, 464, 581, 554, 513, 670, 605, 558, 525, 568, 419, 470, 330, 21, 81, 24, 133, 6, 50, 358, 600, 579, 601, 568, 581, 456, 553, 396, 
+#> 188, 591, 572, 549, 614, 590, 572, 181, 57, 5, 77, 97, 104, 110, 91, 91, 122, 33, 73, 91, 97, 82, 70, 57, 72, 61, 75, 74, 67, 14, 3, 0, 40, 466, 617, 614, 285, 499, 509, 642, 613, 446, 262, 559, 157, 223, 567, 406, 253, 616, 614, 458, 570, 407, 25, 532, 268, 446, 192, 25, 151, 523, 528, 619, 603, 574, 576, 560, 487, 382, 311, 549, 556, 399, 544, 109, 36, 262, 229, 234, 191, 34, 59, 111, 329, 292, 189, 85, 58, 145, 10, 38, 88, 96, 73, 109, 106, 64, 48, 60, 10, 33, 2, 2, 3, 478, 392, 479, 407, 505, 
+#> 470, 56, 60, 244, 558, 551, 462, 488, 603, 549, 209, 4, 9, 49, 544, 528, 509, 480, 540, 552, 523, 331, 59, 410, 524, 447, 386, 18, 308, 422, 278, 498, 593, 638, 574, 198, 356, 616, 625, 658, 556, 479, 313, 466, 51, 13, 12, 33, 326, 458, 546, 385, 605, 600, 16, 503, 35, 65, 81, 80, 88, 102, 110, 115, 107, 105, 37, 89, 80, 91, 54, 67, 53, 45, 86, 71, 83, 83, 78, 86, 102, 75, 19, 4, 10, 383, 180, 529, 551, 520, 574, 585, 395, 481, 360, 172, 20, 49, 5, 43, 85, 34, 56, 5, 76, 93, 96, 67, 25, 19, 39, 20, 
+#> 2, 50, 97, 91, 81, 67, 13, 12, 26, 12, 437, 572, 584, 562, 553, 581, 619, 596, 593, 579, 535, 579, 569, 576, 28, 589, 570, 404, 545, 571, 484, 510, 523, 438, 477, 537, 446, 120, 39, 44, 1, 38, 43, 99, 92, 84, 75, 79, 76, 99, 109, 76, 46, 16, 30, 43, 6, 31, 32, 56, 54, 39, 48, 12, 3, 86, 95, 96, 98, 56, 87, 13, 42, 42, 38, 3, 0, 58, 4, 4, 13, 91, 122, 73, 96, 80, 90, 76, 85, 40, 69, 15, 67, 48, 57, 31, 33, 1, 108, 94, 72, 99, 74, 74, 61, 114, 87, 69, 65, 45, 27, 30, 19, 33, 30, 22, 536, 623, 602, 
+#> 596, 589, 559, 630, 618, 599, 549, 585, 619, 625, 461, 238, 35, 294, 333, 225, 136, 7, 0, 7, 163, 489, 225, 580, 568, 607, 633, 611, 643, 475, 602, 596, 229, 252, 280, 335, 279, 443, 70, 411, 394, 362, 383, 274, 369, 277, 290, 230, 87, 2, 3, 37, 629, 659, 662, 260, 681, 565, 500, 611, 537, 414, 537, 619, 379, 166, 51, 164, 4, 287, 14, 14, 19, 38, 23, 22, 80, 96, 25, 76, 88, 122, 102, 30, 32, 93, 20, 4, 91, 69, 19, 38, 31, 33, 58, 78, 18, 50, 112, 86, 62, 10, 66, 54, 53, 7, 20, 91, 358, 225, 346, 
+#> 520, 517, 446, 450, 253, 568, 535, 59, 257, 62, 48, 63, 44, 88, 83, 75, 73, 90, 72, 84, 70, 42, 19, 46, 0, 1, 79, 356, 543, 562, 646, 549, 609, 303, 595, 538, 383, 342, 106, 297, 291, 237, 57, 467, 428, 263, 566, 129, 465, 108, 37, 59, 13, 18, 459, 508, 603, 634, 610, 383, 618, 628, 601, 610, 641, 564, 568, 406, 515, 436, 45, 186, 49, 546, 613, 501, 416, 410, 465, 429, 417, 242, 401, 435, 355, 558, 554, 456, 403, 435, 85, 89, 1, 35, 593, 606, 648, 626, 586, 532, 563, 591, 417, 251, 298, 57, 87, 114, 
+#> 114, 91, 44, 79, 60, 7, 33, 18, 57, 67, 51, 42, 101, 103, 54, 79, 62, 32, 0, 4, 93, 118, 116, 128, 140, 78, 150, 135, 33, 106, 12, 49, 8, 2, 4, 23, 560, 557, 614, 605, 515, 52, 467, 14, 171, 252, 391, 566, 157, 43, 99, 1, 95, 105, 105, 79, 78, 63, 64, 15, 51, 33, 2, 33, 20, 76, 150, 73, 140, 113, 153, 150, 122, 105, 66, 108, 82, 46, 47, 93, 86, 83, 108, 109, 117, 109, 110, 97, 58, 53, 81, 57, 60, 20, 16, 12, 9, 35, 354, 638, 528, 512, 595, 159, 229, 177, 9, 32, 130, 400, 517, 562, 515, 585, 573, 
+#> 539, 535, 585, 569, 565, 467, 515, 487, 100, 205, 20, 224, 597, 534, 627, 631, 599, 598, 563, 614, 609, 482, 55, 309, 118, 17, 83, 22, 227, 494, 587, 611, 557, 602, 504, 556, 295, 570, 530, 520, 548, 518, 79, 77, 191, 8, 3, 16, 26, 81, 81, 56, 80, 55, 56, 47, 9, 21, 26, 385, 356, 132, 494, 574, 617, 612, 496, 552, 400, 62, 327, 56, 1, 41, 2, 64, 46, 87, 86, 103, 73, 105, 94, 68, 32, 37, 32, 34, 70, 64, 50, 82, 92, 97, 96, 62, 84, 59, 37, 72, 73, 76, 5, 92, 93, 90, 80, 119, 110, 108, 84, 68, 58, 57, 
+#> 75, 29, 86, 87, 94, 82, 83, 92, 86, 95, 95, 31, 47, 30, 10, 70, 47, 47, 28, 2, 14, 253, 616, 648, 594, 650, 606, 435, 434, 109, 492, 406, 458, 47, 270, 354, 73, 14, 20, 7, 20, 83, 104, 80, 99, 83, 69, 105, 86, 73, 9, 59, 33, 1, 0, 19, 99, 100, 113, 91, 84, 80, 71, 52, 86, 77, 32, 30, 26, 2, 98, 656, 619, 456, 666, 632, 564, 624, 623, 558, 536, 36, 571, 585, 184, 252, 47, 9, 21, 66, 97, 68, 84, 97, 13, 11, 8, 6, 79, 39, 0, 3, 97, 105, 118, 128, 121, 66, 26, 34, 18, 0, 1, 2, 233, 610, 475, 554, 614, 
+#> 587, 604, 539, 510, 516, 481, 336, 528, 12, 373, 316, 337, 2, 15, 447, 366, 477, 423, 478, 395, 448, 423, 530, 454, 480, 372, 348, 268, 242, 134, 24, 567, 543, 524, 550, 570, 524, 489, 480, 540, 499, 523, 543, 200, 60, 67, 378, 510, 411, 526, 554, 517, 482, 527, 533, 457, 165, 344, 390, 99, 37, 151, 11, 89, 87, 91, 78, 67, 90, 83, 97, 90, 108, 85, 104, 77, 49, 56, 29, 10, 54, 67, 78, 98, 109, 118, 96, 54, 71, 68, 47, 63, 64, 3, 3, 555, 617, 602, 528, 615, 589, 534, 113, 199, 407, 32, 329, 2, 41, 
+#> 12, 421, 360, 404, 372, 439, 379, 426, 334, 236, 412, 119, 174, 317, 289, 372, 331, 243, 150, 126, 106, 595, 620, 634, 636, 633, 590, 606, 423, 158, 538, 553, 173, 324, 490, 218, 92, 77, 150, 19, 8, 29, 4, 50, 63, 57, 50, 85, 43, 67, 41, 6, 0, 497, 573, 558, 499, 568, 469, 541, 595, 594, 374, 495, 610, 126, 123, 14, 425, 2, 623, 462, 535, 493, 499, 599, 584, 418, 370, 50, 109, 109, 90, 10, 6, 61, 67, 55, 19, 4, 120, 61, 79, 52, 17, 8, 1, 63, 75, 94, 84, 87, 102, 80, 86, 88, 72, 62, 25, 67, 47, 74, 
+#> 25, 35, 28, 279, 593, 540, 618, 491, 128, 13, 124, 343, 289, 60, 163, 435, 545, 521, 497, 566, 580, 582, 593, 534, 545, 527, 396, 536, 525, 549, 380, 399, 451, 68, 4, 5, 8, 361, 524, 580, 681, 649, 580, 506, 562, 543, 428, 7, 31, 98, 117, 107, 74, 81, 67, 69, 78, 66, 75, 26, 1, 449, 593, 619, 46, 594, 556, 500, 573, 67, 270, 523, 402, 6, 82, 223, 384, 661, 649, 644, 643, 560, 658, 589, 661, 660, 630, 606, 578, 541, 204, 157, 4, 26, 591, 621, 438, 405, 620, 506, 594, 621, 554, 404, 56, 36, 535, 516, 
+#> 517, 220, 628, 634, 519, 350, 268, 256, 489, 496, 208, 13, 1, 413, 323, 599, 454, 539, 572, 339, 269, 281, 228, 86, 377, 550, 565, 483, 583, 396, 577, 194, 57, 637, 621, 599, 462, 508, 541, 610, 503, 534, 594, 272, 525, 415, 7, 73, 113, 87, 79, 7, 67, 84, 15, 21, 30, 52, 23, 21, 53, 11, 73, 72, 26, 67, 87, 67, 79, 71, 48, 20, 22, 39, 7, 14, 24, 345, 585, 649, 589, 437, 537, 438, 577, 599, 535, 569, 175, 168, 255, 189, 308, 265, 136, 26, 297, 489, 612, 452, 525, 526, 574, 294, 516, 566, 592, 543, 
+#> 585, 57, 582, 503, 497, 492, 128, 178, 60, 402, 427, 561, 582, 609, 641, 603, 586, 553, 533, 383, 597, 323, 240, 542, 270, 581, 566, 573, 529, 583, 575, 530, 198, 204, 25, 42, 91, 95, 92, 101, 84, 85, 85, 71, 62, 73, 85, 4, 47, 40, 3, 46, 63, 74, 92, 81, 25, 49, 34, 39, 51, 11, 83, 83, 77, 67, 28, 0, 4, 11, 14, 5, 13, 45, 81, 45, 4, 43, 22, 585, 612, 606, 501, 624, 382, 121, 563, 458, 40, 411, 487, 300, 75, 92, 85, 49, 0, 8, 2, 414, 560, 531, 564, 579, 473, 541, 377, 586, 560, 388, 23, 274, 332, 
+#> 137, 104, 56, 515, 385, 605, 615, 476, 560, 460, 113, 35, 187, 86, 51, 96, 96, 55, 75, 41, 1, 1, 13, 10, 11, 0, 279, 639, 568, 648, 631, 648, 588, 561, 265, 7, 79, 51, 55, 121, 114, 11, 99, 109, 124, 115, 113, 109, 127, 129, 107, 114, 89, 89, 80, 46, 25, 24, 133, 235, 324, 204, 35, 151, 116, 95, 431, 504, 377, 334, 203, 395, 416, 288, 115, 85, 180, 284, 139, 3, 41, 61, 502, 431, 356, 585, 568, 424, 151, 370, 316, 166, 491, 364, 111, 2, 0, 0, 93, 11, 73, 108, 75, 25, 124, 97, 18, 107, 88, 11, 75, 
+#> 44, 15, 15, 88, 86, 19, 62, 42, 29, 7, 15, 2, 6, 23, 83, 36, 20, 76, 75, 95, 73, 57, 78, 52, 16, 1, 16, 83, 640, 630, 618, 603, 564, 472, 581, 580, 504, 212, 40, 180, 182, 413, 350, 417, 332, 387, 368, 489, 450, 376, 398, 309, 295, 373, 368, 238, 110, 2, 97, 152, 69, 292, 448, 520, 524, 459, 408, 76, 102, 87, 87, 101, 103, 76, 59, 69, 26, 17, 72, 31, 24, 47, 3, 592, 489, 549, 568, 470, 519, 149, 226, 225, 141, 458, 567, 616, 588, 538, 543, 376, 562, 550, 541, 368, 535, 547, 582, 566, 477, 563, 544, 
+#> 512, 552, 550, 438, 525, 529, 22, 53, 94, 99, 115, 120, 25, 124, 98, 95, 72, 83, 81, 60, 56, 48, 21, 16, 11, 67, 39, 5, 82, 95, 101, 88, 10, 67, 79, 78, 53, 80, 83, 59, 16, 21, 10, 10, 565, 561, 456, 522, 514, 528, 509, 566, 334, 531, 10, 91, 386, 320, 400, 420, 411, 272, 310, 38, 75, 195, 88, 300, 96, 121, 137, 64, 35, 120, 117, 106, 99, 90, 107, 61, 55, 45, 15, 2, 95, 75, 53, 26, 40, 57, 105, 47, 19, 59, 68, 55, 63, 51, 0, 135, 490, 515, 524, 198, 501, 484, 563, 543, 523, 586, 333, 43, 28, 51, 
+#> 0, 304, 231, 197, 503, 487, 587, 448, 441, 242, 69, 10, 187, 613, 337, 184, 360, 365, 440, 162, 147, 572, 475, 576, 571, 534, 526, 523, 584, 541, 379, 30, 44, 375, 5, 248, 505, 188, 316, 431, 465, 439, 63, 159, 250, 581, 385, 110, 179, 156, 13, 398, 500, 507, 544, 512, 163, 538, 151, 247, 116, 51, 62, 1, 12, 220, 491, 532, 588, 608, 582, 559, 296, 487, 494, 299, 58, 170, 88, 62, 10, 60, 296, 569, 585, 534, 576, 536, 421, 299, 545, 468, 266, 172, 57, 577, 459, 498, 508, 537, 438, 463, 251, 8, 21, 
+#> 61, 41, 71, 97, 91, 84, 114, 30, 42, 42, 78, 15, 29, 11, 78, 55, 48, 43, 392, 534, 517, 526, 567, 476, 528, 608, 54, 465, 204, 58, 120, 378, 602, 530, 475, 509, 565, 512, 529, 524, 353, 198, 525, 382, 645, 454, 549, 606, 110, 241, 10, 34, 7, 78, 28, 2, 26, 13, 0, 18, 36, 80, 109, 77, 60, 13, 16, 7, 79, 41, 28, 4, 1, 3, 0, 7, 71, 58, 93, 8, 11, 5, 64, 22, 19, 29, 11, 560, 292, 225, 536, 480, 423, 388, 127, 221, 78, 140, 44, 3, 3, 7, 66, 103, 112, 77, 65, 77, 5, 72, 48, 15, 3, 4, 395, 604, 516, 425, 
+#> 591, 609, 551, 549, 568, 556, 409, 510, 492, 125, 267, 9, 223, 83, 209, 138, 18, 99, 293, 396, 487, 358, 519, 429, 450, 465, 543, 214, 471, 464, 481, 246, 176, 221, 40, 635, 556, 335, 590, 458, 405, 538, 1, 576, 587, 543, 581, 624, 427, 573, 398, 541, 558, 246, 28, 17, 102, 86, 66, 91, 61, 2, 22, 37, 50, 74, 76, 75, 63, 31, 45, 49, 22, 68, 34, 74, 74, 95, 112, 31, 58, 42, 32, 2, 66, 84, 2, 75, 98, 72, 6, 0, 30, 69, 5, 60, 60, 71, 97, 1, 12, 94, 49, 68, 203, 629, 570, 592, 578, 506, 391, 20, 314, 
+#> 2, 575, 512, 559, 571, 450, 562, 635, 610, 628, 377, 295, 129, 165, 365, 6, 56, 9, 69, 83, 70, 103, 100, 94, 26, 6, 67, 13, 14, 0, 55, 80, 31, 40, 7, 3, 73, 33, 7, 4, 0, 435, 547, 485, 418, 506, 430, 498, 540, 567, 515, 372, 186, 7, 234, 397, 344, 307, 386, 421, 365, 461, 84, 198, 259, 125, 68, 620, 621, 638, 565, 604, 490, 480, 67, 177, 308, 17, 158, 6, 375, 463, 329, 588, 590, 577, 571, 583, 595, 579, 184, 400, 51, 592, 296, 494, 446, 329, 327, 40, 442, 282, 5, 57, 31, 50, 75, 91, 133, 102, 103, 
+#> 68, 69, 14, 63, 52, 44, 9, 0, 14, 34, 73, 25, 21, 2, 62, 71, 60, 68, 64, 41, 7, 633, 276, 396, 368, 322, 126, 2, 2, 47, 467, 617, 568, 624, 587, 611, 612, 555, 578, 578, 593, 591, 562, 594, 502, 472, 341, 331, 372, 433, 337, 2, 12, 55, 73, 92, 87, 105, 112, 64, 50, 40, 42, 16, 19, 200, 438, 449, 397, 18, 280, 515, 290, 307, 147, 337, 47, 342, 349, 137, 158, 15, 111, 68, 78, 493, 540, 14, 4, 356, 528, 496, 580, 342, 452, 25, 19, 274, 643, 632, 487, 571, 515, 157, 2, 326, 88, 0, 1, 40, 60, 52, 65, 
+#> 120, 109, 103, 96, 92, 91, 74, 29, 46, 8, 13, 0, 129, 551, 527, 560, 581, 538, 541, 486, 555, 540, 482, 531, 480, 272, 208, 160, 282, 478, 601, 537, 259, 4, 21, 498, 597, 473, 1, 540, 248, 169, 343, 5, 37, 2, 9, 105, 79, 55, 53, 15, 72, 61, 13, 147, 509, 525, 595, 500, 545, 604, 468, 583, 561, 527, 541, 586, 402, 10, 328, 17, 13, 70, 20, 593, 454, 225, 154, 556, 531, 393, 540, 535, 607, 576, 529, 408, 181, 81, 155, 540, 459, 583, 573, 565, 323, 41, 443, 575, 597, 485, 528, 360, 565, 575, 555, 310, 
+#> 126, 307, 104, 19, 103, 130, 402, 8, 87, 75, 4, 257, 313, 300, 234, 139, 120, 115, 99, 37, 1, 0, 6, 15, 2, 73, 91, 56, 22, 41, 24, 38, 27, 30, 2, 41, 79, 54, 27, 2, 5, 68, 74, 55, 84, 39, 3, 9, 67, 179, 61, 257, 501, 77, 109, 241, 488, 571, 13, 523, 328, 464, 21, 589, 458, 329, 268, 55, 193, 346, 482, 530, 614, 498, 510, 459, 334, 360, 256, 206, 63, 21, 158, 4, 9, 366, 522, 555, 511, 519, 513, 220, 14, 58, 469, 534, 234, 513, 548, 519, 514, 277, 178, 551, 516, 510, 252, 93, 220, 164, 142, 0, 42, 
+#> 68, 57, 83, 83, 82, 77, 58, 55, 29, 39, 70, 74, 90, 41, 50, 72, 56, 36, 61, 7, 0, 6, 8, 558, 629, 631, 636, 568, 618, 585, 380, 322, 29, 36, 3, 7, 1, 0, 81, 75, 9, 89, 17, 72, 39, 5, 8, 50, 90, 101, 74, 45, 59, 4, 4, 77, 473, 183, 264, 606, 3, 310, 141, 172, 14, 471, 607, 501, 202, 535, 370, 276, 19, 531, 621, 553, 587, 600, 558, 584, 90, 327, 546, 569, 608, 597, 538, 403, 270, 355, 91, 8, 5, 514, 567, 434, 87, 588, 368, 522, 641, 598, 276, 152, 460, 93, 233, 429, 345, 80, 310, 1, 160, 330, 252, 
+#> 326, 331, 283, 74, 82, 1, 225, 627, 579, 506, 539, 584, 345, 515, 538, 560, 475, 260, 273, 2, 28, 31, 43, 87, 65, 68, 82, 84, 36, 1, 68, 31, 3, 47, 15, 8, 1, 510, 261, 25, 555, 483, 559, 247, 506, 527, 515, 83, 30, 26, 418, 337, 266, 307, 234, 172, 241, 279, 259, 172, 229, 81, 81, 19, 540, 541, 589, 610, 595, 532, 592, 578, 556, 564, 630, 490, 329, 96, 12, 27, 94, 107, 115, 97, 102, 52, 14, 71, 68, 17, 8, 2, 312, 595, 564, 542, 476, 566, 617, 531, 616, 559, 524, 554, 553, 572, 330, 147, 418, 584, 
+#> 622, 534, 513, 648, 605, 588, 639, 486, 3, 134, 602, 617, 594, 495, 554, 449, 516, 483, 484, 517, 302, 22, 293, 469, 415, 597, 547, 534, 503, 584, 541, 521, 482, 433, 472, 359, 395, 232, 147, 9, 2, 67, 57, 85, 63, 89, 83, 78, 81, 76, 85, 41, 50, 206, 471, 347, 293, 538, 483, 565, 550, 588, 411, 151, 292, 471, 286, 148, 142, 36, 141, 94, 3, 57, 5, 1, 56, 106, 48, 19, 89, 82, 32, 5, 5, 0, 502, 565, 555, 549, 547, 531, 516, 414, 148, 557, 321, 6, 40, 18, 97, 74, 62, 34, 63, 19, 0, 34, 13, 4, 0, 6, 43, 
+#> 98, 90, 111, 106, 116, 112, 105, 101, 81, 105, 94, 108, 104, 95, 94, 98, 90, 59, 35, 21, 401, 510, 587, 537, 499, 298, 469, 66, 397, 357, 71, 41, 590, 574, 593, 518, 548, 510, 484, 386, 317, 357, 461, 520, 525, 522, 425, 538, 446, 235, 118, 140, 33, 162, 143, 341, 379, 359, 308, 280, 291, 53, 446, 403, 268, 137, 101, 4, 5, 89, 56, 119, 108, 136, 102, 124, 112, 98, 78, 93, 46, 13, 4, 40, 81, 83, 86, 85, 69, 63, 64, 33, 0, 114, 138, 180, 87, 238, 251, 371, 397, 411, 376, 105, 135, 377, 225, 63, 7, 
+#> 26, 70, 68, 84, 70, 67, 18, 6, 8, 0, 5, 0, 34, 60, 54, 9, 1, 13, 543, 529, 587, 646, 589, 647, 644, 475, 206, 413, 583, 464, 64, 477, 141, 198, 32, 36, 43, 46, 24, 40, 8, 0, 7, 68, 445, 291, 355, 484, 561, 138, 388, 485, 200, 166, 86, 411, 282, 18, 80, 114, 98, 81, 84, 94, 34, 19, 46, 333, 391, 608, 559, 501, 285, 130, 440, 94, 295, 257, 481, 515, 43, 247, 443, 317, 6, 105, 5, 44, 2, 77, 481, 596, 561, 582, 508, 520, 579, 546, 550, 579, 475, 413, 197, 215, 127, 22, 31, 19, 474, 450, 437, 521, 489, 
+#> 481, 550, 522, 464, 363, 144, 47, 279, 436, 437, 505, 468, 519, 397, 446, 388, 330, 96, 97, 103, 47, 117, 111, 74, 60, 12, 105, 36, 20, 471, 370, 89, 30, 285, 514, 509, 550, 572, 550, 385, 444, 492, 477, 450, 120, 58, 21, 19, 62, 62, 92, 71, 34, 32, 29, 27, 12, 2, 2, 0, 515, 553, 471, 549, 464, 614, 617, 540, 578, 413, 307, 143, 52, 447, 522, 362, 42, 10, 300, 96, 183, 157, 41, 559, 360, 132, 459, 606, 320, 453, 361, 223, 52, 162, 151, 39, 179, 27, 5, 2, 40, 56, 78, 93, 69, 34, 19, 65, 38, 12, 2, 
+#> 0, 34, 2, 3, 17, 37, 19, 14, 50, 3, 13, 8, 2, 0, 335, 437, 364, 549, 620, 667, 425, 479, 547, 523, 523, 395, 411, 93, 10, 83, 160, 552, 620, 606, 534, 590, 584, 538, 542, 508, 327, 370, 235, 233, 158, 354, 167, 86, 95, 97, 96, 96, 45, 60, 14, 11, 77, 41, 7, 7, 446, 662, 637, 589, 596, 609, 596, 405, 401, 502, 133, 67, 64, 0, 582, 572, 608, 1, 32, 439, 547, 503, 447, 519, 513, 577, 491, 504, 416, 247, 58, 55, 402, 555, 541, 394, 533, 438, 539, 503, 434, 337, 464, 127, 565, 580, 578, 585, 600, 575, 
+#> 595, 572, 621, 596, 578, 558, 552, 486, 498, 403, 478, 417, 195, 49, 209, 30, 66, 112, 69, 48, 63, 5, 40, 70, 0, 29, 8, 7, 16, 1, 53, 75, 15, 40, 51, 70, 91, 89, 57, 57, 21, 37, 66, 72, 96, 38, 3, 41, 22, 56, 35, 23, 10, 16, 8, 13, 7, 0, 5, 0, 33, 20, 116, 530, 357, 152, 540, 525, 567, 395, 520, 261, 151, 378, 236, 15, 2, 75, 81, 46, 19, 30, 1, 8, 36, 17, 0, 3, 30, 10, 0, 341, 549, 461, 543, 517, 533, 474, 519, 541, 527, 514, 377, 172, 465, 361, 333, 440, 435, 44, 67, 102, 87, 112, 123, 122, 107, 
+#> 100, 80, 99, 89, 79, 33, 52, 79, 68, 35, 21, 10, 16, 45, 540, 486, 437, 211, 6, 36, 58, 363, 587, 70, 458, 265, 145, 498, 242, 317, 374, 6, 9, 5, 44, 554, 573, 567, 599, 466, 492, 416, 80, 679, 656, 620, 591, 624, 561, 561, 474, 471, 487, 417, 351, 120, 59, 3, 159, 605, 607, 538, 594, 617, 555, 553, 557, 439, 588, 525, 334, 372, 235, 565, 606, 659, 408, 640, 642, 553, 620, 564, 610, 553, 334, 153, 394, 254, 427, 3, 226, 120, 143, 5, 24, 19, 3, 0, 46, 79, 98, 88, 63, 43, 29, 0, 20, 1, 0, 3, 176, 163, 
+#> 164, 187, 244, 190, 48, 70, 25, 16, 9, 32, 1, 32, 1, 0, 1, 2, 635, 593, 540, 516, 290, 543, 469, 463, 244, 343, 118, 89, 10, 379, 531, 538, 607, 497, 570, 573, 612, 517, 127, 301, 101, 122, 181, 263, 14, 201, 542, 597, 559, 555, 537, 513, 463, 375, 47, 45, 172, 0, 25, 16, 62, 98, 82, 89, 72, 84, 101, 34, 15, 1, 9, 21, 0, NA, 0, 0, 0, 0, 1, 36, 60, 60, 72, 71, 65, 66, 69, 88, 64, 0, 45, 30, 0, 20, 16, 84, 87, 11, 11, 52, 30, 6, 0, 534, 509, 71, 561, 604, 519, 409, 599, 663, 554, 473, 481, 3, 3, 13, 
+#> 247, 457, 604, 648, 624, 631, 636, 649, 619, 623, 624, 605, 606, 621, 539, 442, 41, 528, 579, 476, 499, 552, 572, 546, 594, 548, 572, 536, 547, 502, 546, 452, 108, 328, 52, 28, 504, 588, 617, 577, 543, 511, 551, 586, 398, 551, 525, 399, 479, 458, 327, 456, 467, 405, 278, 310, 558, 36, 75, 62, 86, 78, 42, 73, 65, 53, 96, 85, 92, 67, 82, 18, 13, 35, 593, 596, 538, 594, 617, 589, 597, 511, 610, 432, 591, 612, 511, 573, 552, 565, 222, 83, 81, 88, 41, 79, 56, 49, 47, 29, 25, 20, 25, 11, 31, 1, 11, 2, 
+#> 0, 533, 575, 557, 612, 600, 625, 581, 601, 578, 564, 659, 546, 622, 599, 552, 491, 436, 499, 572, 611, 554, 540, 464, 545, 609, 482, 568, 582, 576, 479, 421, 539, 471, 455, 342, 534, 427, 50, 118, 67, 530, 595, 544, 570, 563, 552, 589, 611, 617, 628, 535, 496, 180, 166, 24, 221, 34, 468, 602, 609, 615, 601, 629, 590, 603, 592, 631, 570, 570, 603, 600, 606, 547, 516, 495, 449, 392, 340, 465, 271, 2, 17, 51, 77, 79, 91, 87, 57, 70, 102, 99, 83, 68, 67, 56, 56, 31, 9, 0, 1, 35, 53, 79, 86, 86, 88, 99, 
+#> 104, 91, 103, 51, 26, 31, 43, 1, 6, 20, 8, 0, 20, 103, 634, 627, 604, 595, 590, 619, 580, 537, 364, 155, 62, 32, 38, 284, 396, 310, 375, 334, 316, 426, 450, 351, 421, 505, 421, 337, 220, 73, 16, 516, 14, 569, 556, 568, 517, 545, 568, 556, 570, 591, 540, 97, 315, 31, 8, 2, 199, 540, 557, 588, 470, 479, 448, 393, 246, 399, 505, 468, 320, 13, 379, 528, 220, 431, 559, 512, 568, 617, 169, 557, 415, 339, 3, 89, 59, 72, 74, 74, 98, 94, 30, 7, 25, 22, 15, 3, 15, 18, 94, 75, 89, 81, 100, 95, 84, 99, 103, 
+#> 106, 104, 51, 18, 47, 71, 25, 279, 290, 356, 376, 443, 323, 446, 494, 487, 550, 391, 410, 116, 199, 203, 2, 18, 81, 82, 46, 57, 88, 46, 55, 21, 12, 14, 25, 462, 596, 530, 467, 385, 205, 595, 580, 563, 611, 541, 221, 45, 48, 197, 368, 366, 576, 610, 459, 536, 585, 406, 542, 352, 535, 227, 7, 161, 585, 474, 515, 601, 609, 417, 317, 486, 484, 471, 52, 124, 94, 255, 112, 123, 3, 162, 460, 380, 520, 560, 600, 556, 478, 297, 336, 44, 58, 30, 255, 526, 567, 493, 538, 558, 572, 534, 601, 494, 621, 639, 506, 
+#> 227, 367, 193, 64, 228, 255, 382, 463, 440, 311, 383, 427, 518, 537, 30, 350, 259, 195, 140, 108, 14, 97, 93, 73, 93, 9, 68, 61, 83, 67, 56, 52, 11, 19, 2, 70, 168, 19, 570, 552, 580, 574, 578, 544, 548, 535, 498, 530, 138, 80, 82, 427, 614, 578, 265, 360, 3, 603, 605, 569, 585, 625, 579, 529, 34, 49, 452, 563, 600, 573, 567, 250, 84, 3, 550, 107, 148, 21, 455, 577, 510, 588, 594, 562, 374, 479, 50, 423, 571, 420, 197, 143, 58, 33, 77, 5, 44, 52, 52, 51, 61, 97, 87, 94, 73, 88, 79, 91, 86, 71, 71, 
+#> 11, 29, 0, 32, 37, 13, 17, 9, 14, 10, 10, 1, 5, 0, 6, 15, 69, 98, 92, 47, 120, 106, 70, 77, 108, 99, 91, 93, 84, 101, 86, 75, 90, 75, 37, 54, 11, 136, 448, 473, 616, 477, 341, 508, 64, 253, 351, 42, 52, 429, 511, 516, 505, 451, 523, 243, 164, 89, 19, 35, 570, 501, 556, 519, 527, 492, 438, 168, 496, 469, 189, 72, 192, 260, 328, 229, 564, 364, 540, 502, 456, 523, 491, 495, 329, 263, 383, 344, 413, 24, 202, 478, 351, 353, 113, 2, 10, 77, 57, 63, 90, 85, 80, 36, 21, 1, 0, 41, 32, 52, 63, 57, 63, 62, 
+#> 96, 94, 19, 45, 23, 61, 82, 66, 27, 22, 44, 117, 463, 313, 595, 668, 634, 589, 612, 559, 620, 610, 608, 598, 608, 589, 556, 549, 553, 482, 218, 47, 7, 4, 115, 168, 64, 466, 460, 522, 508, 405, 394, 364, 109, 274, 523, 515, 494, 534, 534, 396, 298, 364, 158, 7, 48, 143, 358, 182, 401, 433, 499, 590, 590, 312, 513, 155, 348, 410, 310, 508, 29, 517, 554, 591, 614, 658, 631, 543, 577, 308, 385, 57, 384, 521, 520, 501, 584, 593, 573, 596, 678, 631, 636, 587, 584, 26, 70, 19, 4, 530, 533, 196, 482, 575, 
+#> 587, 74, 498, 87, 275, 185, 91, 145, 30, 29, 21, 448, 267, 493, 417, 433, 516, 493, 519, 598, 592, 566, 549, 33, 287, 227, 215, 288, 464, 457, 465, 282, 538, 561, 478, 237, 273, 262, 559, 337, 123, 8, 61, 68, 62, 72, 89, 35, 21, 4, 19, 10, 41, 11, 29, 30, 5, 18, 44, 29, 19, 15, 32, 16, 3, 6, 5, 32, 74, 30, 29, 26, 17, 21, 22, 16, 8, 22, 11, 13, 2, 8, 24, 9, 7, 2, NA, 0, 64, 70, 66, 10, 14, 3, 5, 26, 7, 305, 182, 469, 460, 662, 692, 630, 679, 664, 610, 0, 82, 103, 73, 88, 80, 93, 108, 24, 35, 7, 3, 
+#> 17, 2, 19, 69, 384, 397, 287, 394, 389, 470, 414, 437, 445, 334, 380, 361, 86, 474, 543, 451, 519, 432, 570, 572, 538, 600, 622, 589, 638, 585, 502, 507, 412, 522, 378, 96, 648, 652, 607, 619, 652, 625, 669, 618, 650, 499, 495, 574, 566, 484, 466, 406, 319, 242, 516, 613, 695, 527, 630, 650, 594, 616, 627, 434, 189, 522, 601, 132, 61, 66, 50, 19, 15, 13, 10, 0, 33, 47, 529, 618, 612, 645, 645, 648, 634, 642, 642, 636, 594, 574, 576, 404, 520, 351, 8, 104, 353, 535, 507, 493, 479, 467, 603, 488, 411, 
+#> 483, 370, 452, 440, 363, 149, 9, 322, 461, 489, 588, 555, 583, 601, 597, 588, 592, 533, 190, 191, 113, 91, 56, 219, 371, 312, 345, 421, 21, 229, 205, 251, 377, 337, 323, 360, 264, 5, 171, 77, 67, 60, 3, 0, 3, 0, 32, 35, 45, 89, 90, 50, 53, 49, 8, 26, 56, 4, 32, 2, 5, 25, 4, 0, 25, 43, 13, 25, 1, 35, 50, 45, 25, 20, 16, 16, 9, 16, 19, 11, 0, 221, 129, 98, 453, 612, 550, 641, 517, 549, 433, 162, 49, 12, 6, 42, 4, 71, 17, 41, 49, 66, 106, 87, 35, 49, 14, 6, 0, 26, 73, 66, 91, 83, 83, 111, 96, 110, 130, 
+#> 106, 93, 79, 22, 1, 14, 63, 100, 61, 83, 93, 118, 99, 77, 87, 76, 93, 45, NA, 0, 1, NA, 79, 53, 48, NA, 1, NA, 35, 8, 12, 4, 28, 661, 566, 434, 469, 363, 436, 485, 460, 297, 271, 305, 295, 272, 303, 37, 8, 622, 520, 533, 602, 537, 448, 507, 331, 143, 6, 3, 3, 1, 76, 90, 83, 80, 61, 23, 56, 89, 69, 48, 6, 1, 352, 460, 665, 556, 592, 60, 313, 577, 456, 79, 454, 42, 213, 200, 219, 82, 26, 552, 626, 460, 219, 19, 26, 19, 0, 45, 81, 66, 83, 80, 107, 41, 58, 35, 4, 31, 29, 37, 27, 2, 9, 4, 0, 2, 4, 30, 
+#> 26, 26, 16, 7, 13, 17, 11, 12, 8, 4, 1, 11, 6, 0, 4, 2, 12, 17, 26, 49, 54, 57, 77, 69, 110, 74, 113, 118, 583, 646, 570, 567, 494, 594, 579, 539, 603, 566, 508, 455, 540, 515, 543, 546, 558, 523, 518, 364, 338, 459, 380, 59, 45, 510, 568, 621, 659, 666, 543, 581, 403, 217, 75, 194, 145, 452, 495, 423, 371, 282, 209, 230, 496, 458, 317, 332, 250, 117, 1, 3, 422, 208, 396, 335, 635, 662, 679, 617, 626, 514, 618, 606, 35, 14, 311, 418, 283, 394, 89, 363, 71, 370, 501, 340, 18, 0, 0, 3, 0, 81, 120, 
+#> 72, 81, 99, 72, 71, 82, 96, 30, 623, 516, 670, 654, 585, 626, 627, 649, 632, 645, 680, 652, 662, 665, 655, 655, 628, 655, 431, 634, 493, 96, 278, 405, 237, 138, 580, 613, 531, 585, 501, 380, 513, 213, 279, 427, 214, 11, 112, 31, 59, 89, 112, 97, 98, 112, 79, 123, 109, 85, 105, 51, 69, NA, 2, 64, 104, 288, 455, 603, 626, 654, 619, 612, 556, 398, 495, 477, 290, 275, 136, 26, 28, 66, 76, 87, 96, 104, 100, 60, 94, 118, 109, 87, 103, 65, 81, 28, 5, 65, 80, 89, 75, 76, 92, 93, 24, 42, 0, 21, 370, 577, 
+#> 505, 344, 359, 339, 180, 71, 98, 183, 295, 368, 64, 83, 23, 48, 77, 27, 6, 347, 578, 604, 630, 592, 608, 561, 586, 577, 575, 555, 555, 464, 536, 375, 76, 264, 381, 226, 217, 299, 184, 23, 417, 41, 27, 9, 7, 672, 576, 622, 557, 470, 637, 628, 487, 28, 571, 459, 455, 123, 24, 632, 619, 524, 463, 521, 438, 459, 549, 506, 250, 462, 416, 298, 171, 254, 397, 438, 532, 394, 612, 603, 538, 91, 87, 51, 13, 80, 99, 31, 31, 546, 442, 541, 552, 515, 577, 401, 569, 547, 295, 555, 527, 500, 433, 248, 333, 312, 
+#> 27, 175, 592, 505, 602, 611, 590, 614, 580, 601, 347, 340, 124, 157, 230, 191, 133, 56, 28, 20, 533, 475, 196, 479, 388, 529, 478, 367, 520, 443, 401, 403, 23, 2, 406, 220, 501, 601, 523, 546, 477, 424, 602, 624, 634, 544, 519, 529, 361, 310, 51, 15, 67, 31, 12, 27, 10, 29, 67, 3, 2, 0, 1, 10, 300, 520, 431, 492, 517, 540, 489, 395, 516, 374, 380, 445, 427, 237, 142, 198, 589, 565, 597, 557, 568, 379, 452, 578, 588, 554, 551, 195, 92, 102, 462, 419, 554, 451, 542, 269, 36, 101, 11, 102, 544, 544, 
+#> 494, 286, 275, 314, 388, 169, 158, 346, 293, 468, 502, 257, 171, 74, 15, 497, 510, 522, 356, 401, 126, 111, 24, 10, 212, 47, 32, 66, 55, 57, 88, 53, 69, 22, 60, 97, 78, 28, 31, 16, 17, 9, 2, 3, 8, 37, 99, 80, 82, 91, 101, 85, 94, 80, NA, 0, 4, 283, 19, 19, 477, 616, 505, 361, 342, 475, 574, 582, 230, 464, 36, 25, 152, 174, 10, 555, 38, 31, 304, 421, 533, 485, 462, 435, 522, 474, 511, 495, 522, 508, 461, 428, 186, 390, 424, 202, 60, 73, 8, 5, 7, 46, 36, 18, 29, 13, 2, 5, 12, 13, 11, 16, 17, 7, NA, 
+#> 1, 26, 11, 24, 1, 5, 6, 18, 8, 4, 17, 17, 8, 0, 14, 3, 13, 6, 486, 465, 590, 511, 494, 71, 345, 402, 161, 97, 14, 27, 12, 19, 629, 529, 368, 565, 636, 425, 422, 204, 62, 51, 209, 500, 579, 550, 474, 285, 426, 348, 347, 158, 1, 42, 542, 497, 507, 480, 575, 547, 518, 543, 452, 135, 87, 59, 12, 13, 400, 491, 424, 472, 491, 415, 550, 533, 526, 418, 465, 370, 344, 435, 293, 41, 13, 429, 528, 322, 379, 328, 311, 136, 236, 104, 8, 23, 69, 72, 73, 79, 32, 64, 108, 88, 76, 31, 17, 182, 247, 322, 415, 561, 
+#> 565, 415, 555, 666, 574, 662, 476, 575, 461, 8, 324, 48, 280, 3, 3, 8, 21, 8, 7, 9, 1, 16, 3, 6, 0, 7, 1, 2, 17, 40, 63, 63, 41, 12, 21, 10, 20, 1, 15, 9, 8, 1, 0, 25, 281, 257, 600, 625, 629, 587, 609, 515, 564, 596, 511, 527, 559, 544, 489, 585, 306, 196, 253, 137, 183, 200, 11, 434, 547, 215, 419, 631, 643, 689, 660, 655, 664, 640, 621, 650, 635, 528, 498, 489, 298, 405, 59, 54, 99, 39, 41, 9, 53, 69, 59, 94, 44, 67, 48, 34, 1, 1, 22, 54, 66, 88, 80, 28, 46, 6, 41, 66, 84, 58, 66, 5, 25, 2, 601, 
+#> 565, 350, 549, 480, 537, 578, 604, 604, 617, 606, 584, 412, 156, 146, 44, 1, 364, 303, 552, 421, 625, 480, 516, 477, 500, 552, 440, 375, 164, 125, 140, 5, 2, 214, 542, 475, 413, 468, 471, 614, 533, 427, 1, 15, 526, 539, 553, 522, 250, 21, 357, 368, 88, 180, 18, 4, 514, 461, 458, 191, 577, 535, 580, 599, 535, 605, 616, 564, 409, 540, 364, 523, 472, 329, 443, 77, 95, 91, 95, 92, 89, 93, 71, 95, 82, 55, 31, 74, 76, 46, 55, 34, 64, 0, 0, NA, NA, 24, 10, 67, 405, 465, 409, 543, 471, 434, 515, 164, 474, 
+#> 239, 152, 331, 28, 106, 21, 59, 155, 169, 146, 137, 5, 250, 219, 564, 418, 594, 542, 495, 554, 404, 542, 481, 535, 412, 449, 117, 77, 1, 51, 0, 93, 100, 108, 113, 115, 109, 84, 2, NA, NA, NA, 0, 0, NA, NA, 67, 53, 14, 17, 10, 36, 64, 86, 64, 61, 70, 91, 82, 115, 89, NA, NA, NA, 54, 3, 6, 5, 37, 74, 93, 85, 111, 106, 31, 58, 12, 4, 26, 565, 558, 543, 580, 618, 467, 423, 517, 477, 225, 170, 488, 447, 234, 311, 35, 349, 11, 117, 235, 333, 583, 592, 568, 401, 435, 602, 394, 164, 214, 222, 151, 614, 656, 
+#> 597, 643, 543, 591, 530, 474, 372, 172, 16, 86, 564, 532, 605, 562, 538, 557, 621, 530, 465, 494, 393, 464, 360, 178, 399, 310, 189, 51, 26, 89, 394, 476, 459, 372, 399, 356, 36, 276, 19, 217, 52, 22, 10, 7, 81, 60, 74, 79, 92, 0, NA, 0, 1, 0, 42, NA, 11, 14, 9, 9, NA, 0, 226, 139, 483, 210, 250, 80, 174, 79, 535, 46, 519, 39, 161, 43, 80, 512, 526, 401, 512, 508, 371, 450, 333, 411, 238, 615, 401, 4, 519, 169, 102, 122, 646, 335, 3, 38, 51, 65, 77, 38, 86, 94, 105, 74, 79, NA, NA, 21, 12, 309, 533, 
+#> 580, 655, 664, 631, 617, 577, 577, 599, 601, 502, 119, 134, 431, 110, 3, 3, 12, 1, 5, 6, 16, 22, 15, 18, 96, 125, NA, 0, 0, NA, NA, NA, 12, 210, 328, 135, 187, 53, 274, 247, 121, 11, 1, 18, 12, 71, 93, 57, 103, 112, 107, 87, NA, NA, NA, NA, NA, 47, 501, 510, 504, 511, 530, 510, 376, 559, 454, 1, 156, 49, 89, 3, 19, 184, 472, 530, 459, 500, 285, 470, 493, 442, 522, 402, 348, 198, 268, 139, 50, 91, 136, 570, 652, 590, 577, 498, 638, 518, 676, 531, 314, 79, 129, 0, 114, 393, 504, 566, 557, 510, 514, 
+#> 500, 572, 273, 496, 475, 98, 1, 5, 493, 542, 448, 574, 513, 518, 199, 327, 339, 472, 461, 321, 159, 261, 148, 86, 590, 340, 478, 439, 521, 504, 562, 266, 519, 351, 88, 330, 23, 118, 553, 549, 426, 567, 499, 539, 506, 593, 498, 525, 511, 465, 514, 334, 530, 397, 525, 460, 419, 336, 4, 323, 522, 491, 406, 535, 583, 553, 521, 356, 454, 402, 240, 2, 15, 72, 73, 80, 80, 96, 117, 100, 102, 90, 92, 97, 86, 94, 101, 67, 101, 97, 84, 28, NA, 34, 11, NA, NA, NA, 3, 200, 195, 76, 250, 324, 535, 550, 558, 698, 
+#> 677, 609, 121, 404, 497, 11, 81, 15, 74, 495, 411, 509, 483, 506, 505, 375, 339, 461, 50, 40, 12, 14, 24, 19, 19, 8, 10, 7, 24, 24, 2, 3, 1, 0, 0, 5, 21, 10, 7, 10, NA, 3, NA, 9, 3, 35, 222, 563, 457, 612, 571, 478, 584, 129, 202, 396, 263, 136, 50, 91, 73, 60, 2, 51, 13, 53, 59, 42, 42, 93, 97, 92, 71, NA, NA, NA, 0, 68, 386, 511, 510, 212, 87, 352, 352, 403, 518, 470, 150, 295, 259, 63, 171, 101, 16, 0, 116, 450, 486, 457, 492, 204, 136, 276, 238, 34, 52, 6, 5, 32, 472, 443, 485, 504, 297, 463, 
+#> 298, 409, 415, 267, 40, 162, 333, 569, 576, 484, 553, 574, 533, 448, 471, 170, 313, 404, 521, 558, 349, 506, 560, 266, 57, 86, 453, 451, 511, 519, 517, 597, 616, 595, 617, 382, 7, 93, 77, 52, 94, 89, 94, 45, 2, 26, 19, 56, 95, 60, 82, 85, 92, 105, 73, 59, NA, 12, NA, 8, 22, 39, 74, 71, 77, 83, 29, 2, NA, NA, NA, 69, 93, 265, 278, 637, 589, 604, 457, 357, 506, 272, 16, 74, 21, 10, 15, 102, 45, 1, 0, NA, NA, 1, 79, 83, 68, 35, NA, NA, 30, 43, 59, 93, 620, 555, 540, 583, 552, 470, 592, 478, 486, 577, 
+#> 394, 372, 475, 356, 97, 307, 622, 663, 619, 626, 643, 567, 529, 378, 592, 90, 475, 538, 231, 163, 88, 339, 600, 515, 613, 558, 624, 569, 643, 498, 593, 641, 615, 599, 611, 350, 169, 493, 56, 37, 99, 540, 402, 395, 564, 547, 418, 356, 331, 73, 359, 269, 103, 71, 180, 415, 466, 572, 67, 400, 562, 641, 600, 625, 554, 602, 404, 534, 447, 389, 170, 122, 1, 19, 497, 565, 459, 413, 383, 184, 190, 348, 86, 77, 340, 521, 626, 528, 621, 391, 384, 47, 414, 487, 551, 542, 406, 132, 156, 37, 69, 564, 581, 529, 
+#> 585, 616, 606, 526, 533, 554, 499, 190, 264, 297, 117, 141, 22, 64, 190, 338, 491, 301, 321, 208, 188, 140, 126, 108, 76, 4, 26, 73, 13, 64, 113, 102, 98, NA, NA, NA, NA, NA, NA, NA, 0, NA, NA, NA, NA, 4, 75, 438, 559, 607, 605, 553, 592, 545, 556, 580, 530, 585, 556, 456, 222, 55, 91, 96, 459, 486, 533, 520, 589, 596, 481, 389, 571, 220, 74, 48, 0, 6, 8, 0, 13, 14, 7, NA, NA, NA, NA, 2, NA, 2, 24, 7, 35, 74, 84, 82, 25, 16, 17, 10, 13, 9, 10, 4, 2, 0, 25, 37, 601, 425, 494, 20, 535, 548, 583, 552, 
+#> 576, 512, 498, 472, 521, 441, 436, 461, 308, 463, 404, 365, 38, 105, 179, 227, 510, 484, 498, 417, 437, 401, 463, 316, 129, 124, 62, 13, 18, 56, 64, 86, 91, 97, 117, 120, 98, 110, NA, NA, 0, NA, NA, NA, 87, 71, NA, NA, 48, NA, NA, 0, 55, 483, 470, 396, 312, 287, 127, 6, 5, 48, 457, 508, 187, 263, 487, 536, 571, 320, 478, 338, 476, 488, 359, 543, 457, 454, 253, 375, 452, 460, 188, 53, 11, 133, 514, 447, 444, 582, 320, 193, 576, 625, 527, 516, 515, 502, 63, 75, 2, 355, 611, 559, 525, 610, 500, 575, 
+#> 530, 192, 470, 499, 306, 492, 332, 380, 220, 76, 78, 547, 650, 579, 446, 669, 583, 624, 624, 654, 539, 540, 360, 499, 499, 391, 195, 19, 11, 78, 65, 79, 70, 88, 50, NA, NA, NA, NA, NA, NA, 43, 181, 122, 350, 513, 593, 437, 593, 468, 500, 242, 497, 330, 372, 122, 193, 1, 66, 55, 199, 49, 450, 229, 54, 26, 83, 6, 601, 562, 542, 501, 487, 495, 531, 17, 501, 344, 388, 307, 530, 261, 33, 40, 118, 218, 155, 317, 171, 37, 8, 8, 17, 13, 3, 21, NA, 1, NA, 0, 0, NA, 0, 0, NA, 5, NA, 2, 2, 5, 30, 16, 5, 24, 
+#> 29, 14, 10, 11, 14, 18, 19, NA, NA, 11, 0, 269, 578, 573, 601, 642, 547, 603, 569, 625, 601, 527, 509, 536, 552, 269, 239, 9, 210, 82, 143, 95, 30, 460, 581, 582, 524, 518, 181, 487, 534, 498, 352, 506, 387, 363, 479, 313, 14, 87, 118, 372, 413, 287, 445, 343, 20, 203, 97, 157, 321, 122, 114, 48, 24, 26, 98, 112, 2, 562, 641, 580, 572, 450, 481, 269, 123, 235, 259, 27, 0, 0, 15, 37, 21, 23, 4, NA, NA, NA, 1, NA, NA, NA, NA, 11, 356, 270, 349, 450, 518, 114, 569, 645, 392, 562, 378, 344, 95, 62, 540, 
+#> 561, 425, 587, 555, 474, 631, 571, 359, 616, 446, 491, 298, 370, 42, 119, 9, 4, 148, 137, 503, 510, 427, 554, 594, 543, 515, 464, 501, 290, 215, 33, 24, 130, 605, 609, 502, 538, 535, 592, 498, 562, 550, 580, 540, 476, 254, 65, 0, 73, 35, 80, 100, 105, 69, 90, 0, 0, 2, NA, NA, NA, 10, NA, 43, 26, 44, 260, 418, 595, 571, 567, 139, 257, 461, 547, 562, 556, 357, 465, 523, 401, 505, 507, 499, 437, 276, 1, 16, 27, 50, 70, 95, 31, 1, 212, 278, 211, 434, 615, 553, 252, 554, 634, 625, 627, 466, 262, 497, 
+#> 451, 262, 169, 216, 9, 27, 0, 11, 16, 22, 33, 34, 15, 6, 5, 1, NA, 0, 0, 0, 0, 3, 93, 225, 294, 349, 642, 659, 631, 646, 639, 648, 658, 431, 625, 388, 617, 654, 557, 76, 37, 435, 474, 507, 349, 202, 483, 384, 475, 42, 332, 287, 40, 59, 92, 82, 85, 90, 103, 105, 1, 0, NA, 1, NA, NA, NA, 8, 37, 82, 255, 324, 474, 501, 486, 492, 296, 356, 145, 118, 119, 87, 20, 77, 70, 93, 53, 89, 96, 108, 67, 34, NA, 22, 265, 327, 378, 328, 594, 507, 576, 572, 565, 590, 622, 421, 572, 528, 531, 560, 311, 279, 197, 
+#> 302, 57, 573, 347, 264, 355, 124, 196, 12, 181, 65, 526, 554, 585, 604, 579, 488, 397, 278, 319, 285, 401, 71, 191, 415, 519, 541, 525, 494, 338, 125, 589, 322, 591, 469, 352, 284, 63, 559, 413, 272, 280, 122, 472, 582, 554, 221, 85, 230, 34, 367, 568, 562, 584, 544, 513, 541, 548, 354, 514, 534, 528, 549, 552, 522, 390, 148, 19, 75, 38, 64, 80, 62, 44, NA, NA, 15, 37, 333, 536, 504, 581, 531, 511, 503, 448, 357, 503, 285, 5, 19, 1, 0, NA, NA, 26, 8, 0, 0, 2, 2, 8, 3, 4, 0, 0, 25, 39, 33, 19, 1, 
+#> 0, 1, 0, 20, 12, 12, 18, 0, 0, NA, NA, 77, 453, 514, 514, 533, 447, 311, 249, 494, 279, 568, 473, 403, 114, 399, 379, 326, 61, 45, 68, 36, 71, 87, 81, 32, 19, 56, NA, 0, 1, 1, NA, NA, NA, NA, 16, NA, 43, 528, 507, 497, 541, 531, 415, 256, 472, 437, 517, 448, 397, 396, 301, 90, 353, 196, 78, 426, 579, 592, 577, 587, 540, 605, 523, 260, 10, 458, 587, 538, 374, 52, 531, 571, 598, 548, 549, 323, 412, 324, 241, 218, 7, 67, 46, 35, 82, 75, 60, 2, 68, 79, 0, 15, 14, 80, 78, 49, 70, 42, 30, 15, 58, NA, 19, 
+#> NA, NA, NA, 3, 76, 225, 549, 598, 557, 552, 566, 581, 583, 589, 587, 521, 324, 349, 405, 462, 395, 440, 354, 177, 93, 67, 564, 581, 644, 677, 619, 504, 451, 573, 626, 657, 546, 618, 404, 485, 209, 1, 383, 374, 461, 573, 522, 584, 539, 450, 527, 561, 361, 602, 526, 253, 396, 289, 48, 65, 83, 103, 43, 82, 86, 45, 17, 27, 12, 100, 563, 610, 302, 596, 533, 554, 540, 452, 368, 378, 583, 502, 412, 8, 463, 551, 529, 565, 654, 617, 628, 443, 568, 525, 492, 656, 421, 617, 614, 93, 339, 79, 187, 139, 220, 
+#> 558, 537, 637, 581, 622, 518, 240, 244, 552, 607, 635, 637, 589, 377, 553, 610, 466, 36, 16, 0, NA, NA, NA, 23, NA, NA, 0, NA, NA, NA, 22, 11, 7, 4, 1, NA, 1, NA, NA, 0, 0, 3, 0, 1, 4, 13, 15, 7, 8, NA, NA, 1, 1, 3, 5, 19, 368, 105, 145, 39, 276, 463, 562, 615, 604, 440, 528, 414, 550, 601, 553, 452, 51, 233, 130, 223, 561, 63, 547, 604, 601, 555, 571, 507, 480, 306, 385, 343, 164, 175, 52, 257, 67, 20, 368, 472, 448, 453, 518, 495, 505, 339, 470, 378, 348, 367, 429, 139, 54, 91, 147, 57, 282, 463, 
+#> 412, 501, 230, 497, 489, 463, 412, 609, 470, 630, 617, 529, 541, 559, 520, 445, 270, 480, 552, 252, 566, 560, 471, 360, 562, 194, 375, 341, 216, 205, 114, 6, 24, 59, 69, 51, 62, 79, 84, 69, 63, 74, 51, 64, 79, 66, 0, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 82, 75, 62, 98, 84, 88, 91, 84, 98, 80, 84, 73, 72, 77, 64, 51, 68, NA, NA, NA, NA, NA, NA, NA, 23, NA, NA, 1, 0, NA, NA, NA, NA, NA, 7, 10, 1, 6, 0, 1, 1, 15, 17, 6, 5, NA, 3, 7, NA, 2, NA, NA, NA, NA, 0, 0, 0, 8, 3, 4, 0, 62, 22, 42, 
+#> 43, 16, 46, 38, 38, 4, 6, 1, 40, 457, 634, 645, 564, 510, 645, 449, 347, 552, 464, 377, 550, 441, 427, 589, 457, 544, 505, 592, 560, 51, 165, 337, 97, 338, 539, 480, 527, 641, 623, 393, 489, 389, 613, 589, 317, 320, 278, 32, NA, NA, 0, 0, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, 0, NA, 58, 25, 268, 159, 129, 466, 616, 590, 565, 559, 286, 247, 630, 399, 68, 309, 313, 2, 25, 599, 531, 552, 527, 84, 518, 420, 230, 544, 609, 410, 144, 19, 481, 62, 38, 16, 32, 51, 521, 488, 289, 
+#> 361, 440, 435, 398, 480, 227, 472, 468, 450, 460, 442, 389, 352, 405, 117, 86, 227, 463, 562, 585, 614, 380, 544, 396, 484, 458, 399, 438, 292, 198, 399, 193, 50, 236, 63, 77, 85, 139, 204, 304, 446, 474, 461, 467, 560, 364, 524, 549, 479, 563, 566, 563, 537, 418, 241, 57, 99, 389, 254, 478, 424, 473, 142, 237, 166, 196, 315, 354, 411, 343, 174, 81, 58, 269, 328, 581, 606, 485, 516, 119, 403, 253, 560, 356, 524, 452, 82, 5, 7, 24, 62, 446, 604, 574, 494, 384, 533, 522, 554, 579, 400, 570, 531, 243, 
+#> 343, 242, 611, 610, 606, 621, 378, 550, 582, 588, 583, 495, 618, 603, 594, 558, 576, 551, 610, 433, 436, 230, 336, 160, 7, 85, 525, 609, 639, 577, 394, 608, 633, 533, 529, 496, 621, 591, 416, 529, 563, 542, 461, 292, 226, 58, 61, 430, 551, 499, 574, 513, 357, 553, 420, 564, 497, 492, 449, 404, 549, 96, 292, 431, 286, 11, 482, 405, 76, 545, 510, 255, 581, 546, 520, 96, 60, 87, 31, 0, 44, 29, 45, 47, 96, 0, NA, NA, NA, NA, NA, NA, 70, 51, 83, 69, 61, 63, 59, 65, 70, NA, NA, NA, NA, NA, 384, 580, 540, 
+#> 663, 626, 627, 644, 430, 45, 119, 4, 271, 206, 3, 14, 284, 510, 594, 619, 599, 581, 546, 516, 516, 448, 495, 380, 539, 600, 497, 528, 127, 177, 107, 44, 73, 86, 77, 83, 87, 73, 79, 82, 25, NA, 7, 29, 59, 70, 60, 19, 73, 61, 26, 2, 213, 621, 647, 672, 504, 333, 563, 460, 493, 546, 510, 510, 362, 506, 505, 219, 57, 117, 496, 602, 562, 477, 379, 431, 489, 227, 160, 146, 417, 9, 0, 0, 0, 0, 0, 0, NA, NA, 0, 0, NA, NA, NA, 0, 33, 98, 441, 280, 108, 269, 189, 475, 427, 412, 316, 409, 262, 123, 45, 34, 
+#> 188, 374, 560, 542, 610, 595, 376, 579, 320, 218, 550, 593, 551, 587, 348, 215, 130, 42, 535, 530, 618, 427, 502, 587, 582, 553, 214, 450, 494, 17, 230, 275, 157, 98, 43, 33, 305, 508, 570, 548, 311, 76, 169, 337, 271, 38, 0, 10, 8, 57, 77, 95, 79, 92, 93, 82, 104, 99, 94, 109, 120, 123, 90, 52, 87, 65, NA, NA, NA, 1, NA, NA, 32, 484, 423, 477, 335, 560, 643, 558, 609, 584, 604, 403, 509, 472, 470, 453, 383, 322, 249, 323, 487, 463, 300, 499, 386, 113, 483, 517, 206, 513, 292, 410, 554, 546, 591, 
+#> 549, 569, 599, 239, 585, 561, 574, 589, 623, 642, 246, 86, 340, 161, 219, 115, 72, 45, 344, 558, 638, 605, 502, 577, 611, 377, 635, 578, 624, 466, 522, 635, 621, 614, 587, 503, 557, 454, 17, 102, 413, 592, 527, 437, 385, 563, 492, 203, 442, 232, 419, 496, 455, 334, 481, 257, NA, NA, NA, NA, NA, 0, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0, NA, 8, 20, 13, 12, 9, 9, 8, 7, 10, 4, 1, 1, 42, 17, 101, 414, 305, 451, 643, 407, 590, 622, 416, 654, 661, 603, 631, 542, 250, 466, 631, 423, 553, 604, 479, 
+#> 556, 670, 490, 360, 537, 618, 553, 247, 313, 568, 522, 54, 269, 82, 54, 429, 513, 400, 442, 473, 411, 214, 470, 39, 317, 256, 116, 12, 33, 545, 582, 504, 552, 431, 531, 349, 549, 320, 121, 401, 451, 152, 214, 164, 39, 141, 498, 509, 492, 615, 587, 597, 558, 388, 539, 598, 567, 633, 565, 575, 559, 414, 61, 568, 583, 547, 294, 115, 17, 2, 320, 405, 489, 524, 595, 561, 591, 628, 340, 377, 608, 534, 493, 477, 585, 339, 49, 264, 35, 303, 372, 85, 183, 433, 508, 515, 226, 589, 508, 587, 461, 401, 85, NA, 
+#> NA, NA, NA, 1, 0, NA, NA, NA, 7, NA, NA, 1, NA, NA, 393, 546, 381, 410, 563, 27, 4, 41, 4, 624, 653, 388, 539, 528, 419, 614, 594, 494, 316, 506, 461, 350, 150, 95, 1, 0, 85, 27, 11, NA, NA, 56, NA, 43, 53, 81, 75, 70, 5, 32, NA, NA, 23, 70, 56, 350, 432, 409, 389, 425, 520, 533, 418, 174, 373, 443, 422, 240, 155, 130, 198, 298, 507, 560, 511, 586, 544, 536, 502, 570, 583, 363, 561, 507, 363, 250, 384, 129, 584, 586, 621, 486, 167, 13, 486, 451, 135, 209, 388, 459, 309, 115, 472, 305, 350, 502, 474, 
+#> 36, 24, 211, 168, 395, 532, 255, 353, 535, 248, 549, 592, 561, 6, 122, 492, 515, 695, 676, 434, 645, 405, 152, 355, 70, 66, 359, 46, 60, 5, 51, 66, 30, 12, 3, 5, 14, 27, 50, 65, 83, 80, 51, 89, 85, 83, 68, NA, NA, NA, NA, NA, 23, 17, 4, 24, 13, 18, 20, 24, 14, 13, 7, 10, 4, 6, 8, 1, 2, 3, 3, 34, 34, 0, 58, 72, 21, NA, NA, NA, 0, NA, 52, 388, 573, 390, 543, 471, 559, 523, 329, 219, 144, 156, 6, 34, 198, 588, 705, 439, 585, 576, 541, 605, 631, 610, 591, 383, 307, 294, 396, 221, 21, 0, NA, 1, 0, NA, 
+#> NA, NA, 0, NA, 0, 43, 448, 460, 560, 392, 489, 505, 555, 605, 574, 597, 466, 449, 559, 375, 102, 401, 292, 223, 193, 127, 219, 32, 282, 532, 555, 443, 325, 193, 270, 452, 366, 51, 6, 27, 503, 311, 522, 533, 505, 549, 374, 557, 541, 596, 555, 490, 523, 455, 153, 244, 248, 285, 590, 587, 609, 450, 488, 552, 412, 537, 514, 600, 575, 593, 512, 550, 518, 545, 381, 156, 227, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, 4, 1, 453, 138, 56, 11, 1, 7, 8, 0, NA, NA, NA, NA, 0, NA, NA, NA, 46, 288, 493, 553, 
+#> 348, 486, 605, 578, 549, 327, 466, 424, 433, 470, 402, 83, 192, 20, 126, 178, 38, 253, 147, 252, 332, 305, 450, 469, 514, 592, 400, 602, 411, 461, 341, 346, 114, 121, 440, 495, 561, 551, 541, 111, 382, 493, 572, 394, 515, 529, 441, 41, 256, 283, 162, 127, 29, 78, 62, 72, 83, 73, 78, 41, 73, 54, 16, 45, 76, 57, 7, 25, 24, 12, 16, 100, 282, 469, 519, 234, 300, 246, 120, 282, 216, 284, 264, 296, 139, 227, 63, 8, 2, 0, NA, NA, NA, NA, NA, 31, 45, 77, 28, 18, NA, 10, 45, 46, 16, 4, 5, 5, 22, 5, 11, 0, 
+#> 15, 2, 37, 507, 577, 566, 502, 564, 555, 487, 551, 312, 556, 581, 505, 500, 256, 104, 1, 64, 95, 91, 79, 97, 109, 92, 44, 66, 69, NA, NA, 12, 32, 63, 17, 5, 65, 3, 150, 295, 343, 294, 195, 153, 82, 0, 351, 591, 423, 536, 513, 502, 547, 608, 358, 554, 235, 306, 489, 470, 396, 318, 163, 296, 407, 465, 115, 288, 542, 438, 96, 324, 379, 179, 72, 7, 72, 70, 50, 3, 70, 62, 67, 67, 75, 64, 42, 35, 50, 14, NA, NA, NA, NA, NA, NA, NA, NA, 0, NA, 0, NA, 3, 7, 1, NA, NA, NA, 453, 654, 602, 399, 482, 299, 597, 
+#> 401, 591, 554, 556, 551, 507, 16, 496, 6, 363, 239, 278, 628, 440, 536, 574, 639, 385, 425, 81, 368, 202, NA, NA, 0, 0, NA, NA, 0, NA, 0, NA, 1, 0, NA, NA, NA, NA, NA, NA, 8, 62, 183, 347, 575, 584, 535, 487, 61, 545, 215, 149, 570, 498, 427, 146, 106, 134, 316, 452, 359, 387, 228, 310, 227, 86, 196, 335, 197, 121, 130, NA, NA, NA, 58, 79, 71, NA, NA, NA, NA, NA, 65, 76, 530, 384, 569, 369, 598, 589, 607, 616, 614, 566, 592, 574, 349, 214, 544, 62, 42, 39, 598, 663, 641, 642, 627, 624, 575, 646, 
+#> 600, 650, 637, 641, 444, 550, 640, 615, 601, 332, 309, 477, 119, 638, 623, 569, 488, 633, 610, 632, 651, 615, 652, 567, 119, 24, 41, 38, 543, 250, 597, 525, 633, 600, 424, 60, 203, 18, 1, 167, 440, 522, 511, 422, 489, 346, 575, 370, 547, 427, 512, 453, 9, 303, 328, 539, 337, 473, 542, 484, 439, 73, 51, 18, 85, 49, 57, 12, 85, 13, 31, 21, 6, 7, 11, 52, 81, 63, 40, NA, 18, 2, 23, 15, 0, 3, NA, NA, NA, NA, NA, NA, NA, NA, NA, 155, 46, 240, 227, 452, 557, 628, 363, 567, 371, 164, 108, 484, 145, 170, 
+#> 0, 1, 0, 0, NA, NA, NA, 0, 0, 0, NA, NA, NA, NA, NA, 1, 4, 30, 298, 176, 592, 492, 504, 448, 96, 508, 167, 114, 482, 466, 353, 158, 24, 199, 59, 41, 79, 77, 74, 96, 71, 77, 81, 55, 85, 82, 49, 14, NA, NA, NA, 0, 0, 0, NA, 0, NA, NA, NA, NA, NA, NA, NA, 6, 7, 13, 40, 11, 109, 145, 174, 42, 270, 441, 368, 362, 251, 344, 347, 330, 362, 327, 141, 167, 151, 128, 147, 9, NA, 0, NA, NA, 0, 0, 64, 46, 0, 44, 67, 51, 73, 70, NA, NA, NA, 6, 77, 47, 81, 54, 6, 635, 633, 636, 609, 627, 523, 618, 606, 615, 585, 
+#> 612, 456, 223, 554, 447, 21, 210, 497, 542, 546, 546, 510, 384, 505, 424, 491, 464, 410, 304, 112, 263, 174, 67, 19, 422, 601, 571, 612, 497, 620, 562, 199, 113, 501, 497, 474, 475, 156, 200, 309, 300, 269, 271, 11, 92, 65, 551, 618, 386, 609, 507, 278, 93, 271, 486, 563, 299, 0, 0, 5, 16, 34, 7, 5, NA, 0, 5, NA, NA, 29, 520, 466, 379, 296, 80, 159, 225, 169, 61, 277, 47, 420, 522, 393, 475, 532, 543, 476, 542, 505, 156, 100, 92, 87, 202, 29, 295, 49, 338, 582, 625, 653, 580, 551, 584, 621, 619, 
+#> 546, 514, 560, 366, 460, 501, 353, 435, 292, 389, 378, 487, 539, 592, 584, 589, 592, 472, 502, 431, 260, 102, 647, 576, 555, 594, 579, 127, 472, 602, 530, 404, 29, 109, 248, 382, 562, 549, 530, 532, 432, 512, 265, 355, 303, 171, 17, 292, 332, 406, 161, 315, 439, 579, 565, 558, 612, 409, 570, 594, 600, 544, 479, 365, 80, 56, 267, 95, 496, 619, 17, 251, 278, 66, 258, 435, 552, 539, 275, 245, 163, 325, 431, 361, 532, 517, 397, 439, 408, 443, 294, 131, 32, 24, 51, 10, 6, 32, 79, 74, 40, 29, 5, 37, NA, 
+#> 27, NA, 0, 20, 313, 647, 615, 622, 575, 580, 530, 429, 517, 457, 609, 551, 415, 384, 502, 201, 271, 321, 135, 11, 78, 89, 0, 9, 16, 9, 13, 6, 5, 2, NA, NA, NA, 2, 0, 0, NA, 2, NA, NA, NA, 0, 0, 38, 175, 290, 266, 401, 531, 581, 441, 487, 542, 253, 315, 462, 56, 403, 330, 227, 16, 1, 8, 19, 0, 3, 2, 13, 0, 1, 0, 0, NA, NA, 7, 4, 370, 221, 536, 469, 324, 199, 166, 187, 57, 53, 23, 57, 29, 4, 19, 95, 73, 84, 94, NA, NA, 19, 567, 578, 479, 580, 478, 498, 494, 462, 104, 70, 93, 81, 64, 90, 40, 75, 63, 
+#> 72, 70, 12, NA, 4, 2, 2, 1, 2, 0, 190, 304, 606, 622, 642, 589, 521, 604, 573, 530, 520, 489, 419, 535, 451, 592, 461, 411, 127, 102, 2, 28, 65, 78, 52, 1, 40, 48, 83, 86, 84, 74, 90, NA, 1, 29, 12, 279, 603, 652, 677, 569, 599, 631, 394, 587, 640, 530, 372, 458, 37, 58, 34, NA, 24, 0, NA, NA, 5, 0, NA, NA, NA, NA, 0, NA, NA, 28, 45, 58, 14, 35, 1, 5, 4, 0, 5, 85, 397, 443, 539, 394, 458, 444, 423, 282, 129, 30, 11, 212, 596, 581, 582, 569, 480, 593, 592, 573, 626, 577, 537, 477, 414, 327, 190, 162, 
+#> 0, 8, 4, 1, 10, 8, 9, 7, 8, 0, NA, 0, NA, 0, 0, NA, 2, NA, 491, 547, 560, 566, 597, 516, 524, 40, 457, 365, 415, 499, 490, 264, 16, 232, 107, 636, 600, 623, 616, 563, 497, 278, 229, 373, 438, 293, 162, 84, 14, 163, 112, 606, 607, 641, 610, 614, 613, 562, 558, 627, 410, 81, 358, 457, 586, 561, 605, 306, 430, 588, 542, 568, 357, 306, 168, 61, 491, 280, 608, 596, 569, 640, 570, 505, 599, 333, 172, 94, 321, 488, 478, 416, 326, 385, 495, 134, 318, 293, 345, 85, 222, 61, 84, 67, 322, 641, 526, 603, 569, 
+#> 545, 289, 133, 10, 222, 411, 493, 313, 558, 596, 559, 510, 304, 50, 561, 100, 447, 155, 60, NA, NA, NA, NA, NA, 76, 94, 72, 35, 13, 46, 2, 46, 18, 44, 475, 534, 625, 559, 612, 336, 159, 16, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, 2, 4, 4, 3, 2, 3, 1, 72, 58, 27, 2, 12, 9, 41, 48, 48, 47, 72, 95, 80, 71, 75, 54, 1, 26, 508, 584, 588, 560, 596, 584, 468, 498, 577, 586, 456, 50, 281, 327, 514, 522, 502, 128, 306, 280, 10, 95, 394, 388, 320, 539, 589, 590, 468, 441, 80, 476, 284, 95, 557, 
+#> 691, 680, 624, 657, 635, 551, 611, 639, 622, 439, 538, 34, 233, 564, 687, 578, 648, 573, 635, 558, 622, 173, 353, 366, 384, 409, 486, 485, 64, 59, 180, 418, 510, 523, 482, 528, 428, 8, 249, 231, 28, NA, NA, 0, 0, NA, NA, NA, NA, NA, NA, NA, NA, 1, 7, 10, 6, 1, 0, 0, 0, 2, 0, 0, 96, 600, 630, 610, 227, 481, 572, 366, 73, 231, 429, 396, 360, 388, 583, 430, 111, 218, 256, 61, 350, 574, 578, 561, 581, 327, 176, 398, 113, 40, 183, 384, 540, 233, 300, 439, 500, 562, 293, 214, 12, 24, 205, 289, 204, 449, 
+#> 498, 462, 151, 299, 260, 15, 104, 94, 105, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0, 0, 23, 85, 71, NA, NA, NA, 6, NA, 2, 26, 19, 17, 64, 5, 4, 2, 0, 6, 4, NA, 2, 2, 0, NA, NA, NA, NA, NA, 64, NA, NA, NA, 2, NA, NA, NA, NA, NA, 24, 2, 262, 559, 578, 583, 391, 613, 447, 586, 640, 633, 309, 513, 162, 406, 113, 237, 7, 34, 303, 340, 352, 190, 279, 336, 293, 97, 5, 139, 98, 174, 122, 415, 474, 472, 462, 453, 285, 267, 75, 376, 120, 415, 158, 452, 191, 254, 156, 521, 584, 450, 251, 
+#> 666, 608, 46, 576, 437, 465, 609, 615, 418, 665, 609, 636, 454, 525, 660, 538, 502, 10, 26, 411, 216, 18, 127, 278, 516, 514, 507, 341, 503, 374, 160, 566, 478, 53, 557, 550, 490, 523, 483, 467, 84, 135, 317, 423, 366, 174, 509, 521, 236, 299, 62, 546, 492, 462, 344, 580, 386, 469, 337, 266, 481, 341, 29, 350, 252, 477, 478, 401, 175, 23, 53, 24, 461, 382, 268, 111, 240, 456, 384, 217, 79, 49, 11, 65, 701, 663, 591, 655, 629, 333, 199, 492, 594, 102, 122, 261, 136, 171, 34, 188, 95, 50, NA, 0, NA, 
+#> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2, NA, 9, 37, 59, 76, 42, 28, 4, 40, 28, 71, 49, 25, 57, NA, 26, NA, NA, 0, NA, NA, NA, NA, NA, NA, NA, 55, 56, 69, 0, NA, 0, 0, 0, NA, 0, 0, 0, 1, 0, NA, 15, 391, 351, 454, 379, 456, 438, 389, 369, 406, 514, 447, 422, 338, 0, 50, 76, 71, 90, 85, 77, 7, 31, 68, 73, 44, NA, NA, 3, 66, 62, 7, 59, 10, 104, 445, 530, 598, 613, 642, 631, 458, 485, 207, 7, 51, 639, 455, 636, 443, 642, 641, 598, 403, 427, 552, 265, 563, 474, 158, 390, 309, 361, 424, 418, 564, 587, 
+#> 476, 493, 491, 614, 323, 374, 63, 214, 8, 3, 303, 354, 549, 549, 553, 526, 523, 237, 150, 305, 154, 3, 6, 4, 2, 1, 3, 5, 1, 1, 1, 3, 0, 1, 0, 2, 0, 1, 0, 0, 0, 0, 26, 452, 236, 445, 133, 316, 500, 423, 427, 517, 393, 347, 279, 192, 538, 304, 567, 582, 344, 552, 258, 71, 13, 125, 29, 560, 658, 636, 599, 495, 613, 548, 582, 589, 107, 532, 433, 432, 289, 141, 1, 90, 338, 197, 320, 233, 165, 40, 50, 31, 35, 412, 590, 578, 610, 544, 180, 540, 327, 481, 295, 75, 321, 551, 609, 572, 579, 375, 325, 470, 
+#> 417, 554, 626, 600, 555, 494, 156, 243, 292, 272, 10, 234, 192, 466, 584, 616, 625, 577, 438, 502, 403, 237, 317, 595, 562, 97, 236, 119, 239, 174, 1, 3, 10, NA, NA, 23, 67, 26, 33, 0, NA, NA, NA, 0, NA, 159, 439, 588, 325, 614, 464, 533, 384, 427, 496, 517, 224, 538, 583, 396, 156, 507, 241, 346, 18, 41, 4, 295, 195, 284, 344, 315, 412, 395, 446, 398, 385, 180, 62, 0, 5, 39, 7, NA, NA, 0, NA, NA, 0, NA, 0, NA, 0, NA, NA, NA, NA, NA, 408, 529, 575, 588, 600, 565, 513, 491, 389, 454, 436, 393, 554, 
+#> 251, 256, 171, NA, NA, NA, NA, NA, 90, 36, 37, 23, 36, 24, 65, 57, 31, 9, 13, 7, 140, 525, 564, 560, 590, 552, 545, 521, 522, 373, 351, 180, 82, 396, 439, 515, 405, 71, 284, 201, 2, 11, 30, 46, 12, 8, 7, 23, 10, 13, NA, NA, 1, NA, 3, 1, 0, NA, 10, 67, 76, 81, 65, 82, 73, 31, 6, 34, NA, 0, 0, 1, 0, 23, 61, 41, 69, 50, 18, 38, 10, 3, 14, 328, 196, 268, 505, 543, 524, 371, 360, 323, 310, 92, 114, 59, 127, 21, 57, NA, NA, NA, 1, NA, NA, 0, NA, 0, NA, NA, NA, NA, NA, NA, 0, NA, 0, 0, 1, 1, NA, 0, NA, 
+#> 0, 0, NA, 2, 0, 0, 0, 475, 392, 270, 55, 2, 68, 162, 47, 68, 34, 5, 295, 536, 551, 557, 528, 531, 255, 302, 424, 528, 617, 564, 564, 529, 566, 170, 343, 523, 297, 72, 76, 211, 211, 211, 283, 411, 444, 501, 525, 522, 339, 429, 491, 44, 382, 643, 615, 634, 608, 661, 101, 500, 630, 426, 215, 264, 158, 360, 90, 48, 74, 60, 344, 419, 174, 133, 307, 170, 28, 155, 66, 355, 389, 220, 554, 495, 571, 590, 564, 350, 235, 227, 169, 123, 443, 555, 546, 613, 610, 437, 553, 605, 619, 646, 639, 377, 617, 577, 628, 
+#> 633, 590, 548, 517, 0, NA, 0, NA, NA, NA, NA, NA, NA, NA, NA, 6, 4, 4, 7, 0, 4, 28, 250, 581, 346, 575, 471, 545, 492, 73, 10, 331, 477, 287, 419, 71, 156, 51, 93, 150, 216, 186, 147, 9, 163, 419, 564, 530, 395, 86, 504, 442, 315, 94, 508, 164, 134, 12, 29, 19, 70, 45, 85, 73, 51, 50, 76, 83, NA, NA, NA, 0, NA, NA, 1, NA, 59, 76, 77, 84, 84, 89, 71, 58, 60, 56, 1, 1, 16, 13, 143, 341, 569, 545, 592, 429, 446, 65, 1, 19, 445, 184, 299, 215, 292, 203, 418, 451, 409, 137, 356, 220, 167, 116, 194, 146, 
+#> 128, 46, 62, 22, 558, 540, 399, 588, 474, 235, 499, 149, 278, 613, 424, 357, 147, 390, 393, 439, 518, 198, 33, 455, 597, 548, 565, 582, 433, 260, 545, 608, 633, 606, 520, 364, 197, 166, 300, 491, 428, 528, 131, 359, 387, 98, 413, 551, 538, 580, 519, 510, 473, 539, 391, 506, 517, 532, 552, 355, 480, 476, 403, 390, 373, 42, 367, 340, 12, 42, 96, 81, 83, 88, 88, 91, 63, 72, 68, 67, 75, 64, 80, 64, 59, 68, 69, 76, 43, 25, 62, 13, 42, 11, 49, 53, 95, 522, 516, 462, 36, 389, 265, 372, 277, 61, 2, 8, 7, 
+#> 2, 5, 1, NA, NA, 0, 0, 7, 4, 5, 4, 29, 7, 2, 1, 0, 0, 0, 0, 1, NA, 0, NA, NA, NA, NA, NA, NA, 1, NA, 51, 439, 396, 484, 585, 352, 411, 140, 495, 540, 429, 249, 275, 381, 398, 74, 83, 175, 174, 573, 624, 594, 573, 425, 494, 391, 200, 361, 381, 35, 245, 156, 292, 617, 589, 529, 579, 445, 283, 404, 596, 510, 627, 371, 408, 215, 134, 134, 290, 365, 35, 341, 429, 374, 461, 408, 408, 435, 345, 348, NA, NA, NA, NA, 37, 38, 62, 67, 72, 82, 49, 22, 0, 16, 16, 60, 67, 62, 74, 77, 81, 56, 63, 76, 63, 71, 65, 
+#> 68, 57, 68, 53, 54, 64, 53, 56, 19, 545, 623, 586, 637, 571, 589, 392, 517, 588, 412, 588, 563, 610, 575, 590, 253, 263, 110, 61, 45, 493, 606, 592, 554, 401, 492, 586, 183, 590, 588, 469, 456, 465, 109, 283, 152, 48, 195, 80, 220, 459, 485, 330, 243, 219, 407, 50, 160, NA, 0, NA, 0, NA, NA, NA, NA, NA, NA, 0, 67, 532, 515, 559, 593, 550, 477, 510, 375, 492, 462, 394, 392, 274, 30, 79, 76, 75, 49, 53, 46, 1, 1, 26, 1, NA, 0, NA, NA, 0, NA, 0, 0, 0, 565, 600, 602, 445, 538, 578, 611, 603, 603, 400, 
+#> 521, 300, 554, 586, 535, 400, 448, 568, 566, 540, 562, 590, 600, 571, 605, 572, 100, 191, 559, 573, 549, 399, 493, 527, 530, 585, 486, 582, 68, 523, 546, 240, 105, 466, 531, 186, 60, 51, 244, 489, 663, 588, 621, 651, 634, 638, 622, 603, 435, 558, 625, 612, 283, 105, 83, 563, 260, 575, 561, 544, 606, 410, 419, 502, 383, 516, 82, 343, 171, 81, 309, 41, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 21, 280, 420, 473, 363, 492, 639, 597, 579, 600, 363, 442, 408, 511, 527, 504, 547, 502, 302, 96, 327, 98, 398, 
+#> 124, 486, 510, 589, 619, 603, 594, 403, 552, 547, 555, 595, 593, 510, 476, 298, 135, 143, 611, 578, 514, 502, 468, 431, 290, 43, 97, 47, 419, 487, 528, 490, 395, 494, 272, 568, 454, 438, 314, 497, 477, 454, 108, 150, 315, 17, 62, 74, 65, 75, 71, 37, 56, 78, 79, 51, 62, 7, 2, 1, 2, 68, 64, 54, 8, 2, 13, 579, 356, 54, 334, 317, 132, 14, 545, 619, 406, 551, 608, 628, 507, 578, 584, 438, 524, 336, 103, 43, 32, 171, 487, 544, 528, 135, 326, 511, 499, 542, 556, 502, 556, 470, 328, 497, 486, 60, 90, 545, 
+#> 584, 536, 422, 352, 541, 533, 606, 562, 461, 532, 277, 327, 127, 1, 232, 557, 659, 607, 464, 567, 616, 595, 557, 322, 574, 334, 397, 80, 368, 487, 175, 557, 236, 258, 322, 213, 519, 444, 136, 301, 549, 501, 515, 492, 576, 573, 584, 151, 494, 418, 268, 3, 103, 138, 129, 144, 368, 459, 285, 485, 510, 257, 342, 12, 126, 269, NA, NA, NA, NA, NA, NA, 54, 43, 391, 367, 608, 653, 527, 301, 55, 333, 323, 72, 13, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0, NA, NA, NA, 4, 0, 1, NA, 0, NA, 
+#> 0, NA, 2, 0, 0, 154, 241, 346, 291, 480, 488, 295, 35, 143, 57, 94, 69, 159, 160, 20, 14, 6, 4, 14, 42, 53, 117, 74, 576, 569, 459, 481, 662, 493, 600, 465, 543, 517, 352, 180, 208, 339, 276, 367, 469, 173, 317, 387, 255, 426, 483, 560, 286, 542, 542, 565, 576, 574, 613, 611, 582, 250, 567, 568, 579, 513, 266, 177, 344, 167, 153, 549, 420, 477, 547, 498, 492, 443, 494, 129, 336, 227, 7, 116, 200, 13, 178, 349, 432, 316, 379, 82, 145, 337, 291, 137, 74, 288, 558, 653, 630, 475, 551, 671, 558, 542, 
+#> 603, 595, 448, 343, 587, 562, 137, 14, 125, 211, 271, 583, 608, 632, 604, 424, 530, 527, 573, 549, 589, 565, 428, 49, 116, 8, 358, 454, 458, 551, 384, 492, 398, 524, 557, 581, 565, 572, 553, 539, 164, 261, 173, NA, NA, NA, 3, 64, 75, 28, 40, 63, 81, 76, 50, 31, 30, 83, 86, 52, 7, 0, 2, 2, 2, 0, 0, NA, NA, NA, NA, NA, 0, 0, 0, 0, 0, 79, 515, 373, 537, 581, 582, 463, 353, 568, 475, 483, 528, 186, 211, 69, 547, 405, 434, 547, 556, 18, 149, 394, 534, 482, 503, 478, 234, 455, 398, 399, 309, 312, 593, 
+#> 657, 624, 442, 557, 424, 83, 467, 511, 57, 80, 182, 207, 85, 158, 30, 216, 249, 122, 189, 181, 173, 423, 290, 399, 397, 260, 87, 156, 341, 427, 185, 97, 218, 23, 461, 585, 594, 412, 546, 602, 634, 609, 610, 559, 236, 431, 431, 429, 159, 352, 590, 246, 345, 637, 315, 254, 134, NA, 31, 80, 77, 70, 72, 65, NA, NA, NA, NA, NA, NA, 3, 3, 3, 3, 1, 4, 35, 222, 320, 522, 451, 163, 309, 337, 77, 77, 585, 470, 270, 164, 79, 2, 2, 4, 3, 3, 3, 0, 1, 0, 0, 0, 1, 0, 0, 49, 312, 208, 239, 318, 146, 86, 434, 536, 
+#> 634, 616, 580, 601, 388, 572, 270, 299, 162, 361, 34, 99, 142, 15, 5, 341, 482, 422, 344, 540, 538, 584, 454, 513, 484, 565, 601, 427, 345, 328, 49, NA, NA, NA, NA, 34, 66, 46, 28, 65, 48, 29, 29, 48, 4, 50, 3, 126, 475, 415, 514, 198, 570, 341, 194, 148, 348, 268, 18, 143, 436, 66, 51, 20, 91, 595, 451, 483, 597, 405, 309, 444, 409, 524, 451, 493, 84, 521, 335, 389, 100, 215, 41, 9, 7, NA, NA, NA, NA, 0, NA, NA, NA, NA, 32, 7, 97, 83, 80, 89, 36, 80, 8, 6, 15, 50, 26, 14, 419, 223, 544, 575, 531, 
+#> 435, 570, 536, 285, 422, 330, 346, 367, 44, 0, 203, 83, 585, 541, 574, 506, 543, 406, 526, 546, 486, 452, 273, 208, 171, 185, 11, 315, 386, 416, 113, 346, 426, 286, 135, 451, 244, 356, 305, 46, 217, 464, 596, 607, 545, 373, 562, 655, 560, 619, 590, 539, 495, 505, 516, 404, 224, 406, 426, 94, 219, 355, 539, 394, 550, 635, 527, 609, 524, 614, 487, 79, NA, NA, 0, NA, NA, NA, NA, 0, NA, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, NA, NA, NA, NA, 0, 0, NA, 0, NA, NA, NA, 0, NA, 1, 512, 569, 378, 438, 425, 
+#> 200, 409, 458, 30, 66, 75, 69, 20, 30, 56, 6, 5, 63, 65, 26, 4, 0, 53, 290, 484, 550, 561, 571, 522, 439, 529, 436, 569, 568, 554, 449, 483, 365, 187, 352, 69, 196, 17, 185, 468, 301, 520, 527, 575, 588, 450, 35, 60, 208, 5, 16, 337, 130, 527, 629, 612, 645, 615, 331, 445, 93, 543, 542, 583, 494, 21, 254, 46, 138, 349, 445, 387, 538, 484, 579, 633, 561, 662, 593, 114, 461, 391, 99, 84, 532, 316, 262, 598, 426, 564, 498, 642, 643, 625, 604, 577, 556, 517, 478, 380, 412, 98, 117, 154, 321, 452, 505, 
+#> 496, 440, 494, 557, 526, 480, 578, 508, 193, 490, 432, 503, 345, 17, 276, 71, 206, 101, 62, 61, 289, 558, 431, 502, 599, 204, 525, 500, 476, 447, 498, 467, 350, 365, 250, 90, 29, 217, NA, NA, NA, NA, NA, NA, 4, 2, 11, 6, 7, 5, 2, 1, 3, 4, 2, 5, 22, 42, 32, 23, 59, 19, 24, NA, 19, 25, 4, 0, 40, 385, 496, 400, 484, 287, 312, 481, 478, 340, 441, 505, 453, 446, 295, 325, 73, 320, 261, 567, 408, 563, 551, 509, 499, 591, 537, 540, 612, 445, 561, 485, 420, 126, 240, 549, 602, 591, 587, 522, 568, 594, 622, 
+#> 615, 553, 607, 417, 146, 367, 131, 343, NA, NA, NA, NA, NA, NA, 7, 5, 6, 60, 0, 0, 5, 1, 22, 69, 192, 204, 163, 406, 543, 563, 358, 470, 564, 540, 244, 266, 364, 45, 16, 16, 277, 333, 489, 414, 489, 246, 481, 438, 347, 457, 579, 395, 279, 63, 21, 7, 0, 5, 4, 4, NA, 0, 1, 0, 0, 0, 2, 12, 7, 3, 9, 28, 3, 3, 1, 0, 0, 0, 0, 0, 48, 582, 654, 626, 627, 593, 614, 644, 482, 643, 654, 623, 639, 596, 634, 663, 546, 683, 63, 581, 103, 478, 296, 175, 261, 167, 261, 117, 298, 132, 228, 148, 35, 268, 68, 156, 
+#> 54, 142, 601, 587, 686, 502, 554, 632, 624, 607, 601, 605, 572, 583, 510, 444, 522, 373, 463, 156, 523, 132, 490, 228, 366, 568, 468, 154, 452, 456, 607, 603, 496, 404, 71, 344, 142, 128, 10, NA, NA, NA, 4, 5, 5, 4, 3, 7, 23, 62, 62, 4, 2, 5, 4, 4, 2, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 70, 48, 57, 57, 58, 62, 53, 53, 54, 18, 0, 2, 5, 3, 2, 8, 3, 3, 3, 0, 4, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 4, 44, 63, 64, 69, 7, 2, 0, 0, 5, 3, 2, 69, 38, 9, 39, 14, 73, 221, 580, 559, 598, 631, 608, 597, 436, 554, 
+#> 626, 614, 619, 565, 565, 600, 546, 561, 550, 369, 502, 356, 505, 520, 133, 461, 460, 117, 61, 1, 29, 82, 45, 18, 89, 81, 64, 74, 81, 82, 23, 45, 75, 17, 2, 40, 14, 61, 46, 1, 3, NA, NA, NA, 15, 7, NA, 6, 5, 3, 2, 0, 0, 0, 0, 87, 684, 604, 532, 529, 83, 635, 658, 156, 165, 230, 469, 431, 163, 160, 130, 561, 601, 421, 483, 554, 375, 205, 559, 500, 196, 521, 392, 408, 137, 338, 471, 252, 294, 68, 112, 460, 408, 329, 519, 595, 594, 531, 589, 569, 589, 511, 476, 458, 303, 165, 67, 456, 386, 352, 343, 
+#> 597, 380, 431, 265, 519, 361, 200, NA, 11, 14, 42, 74, 14, 55, 72, 63, 37, 37, 0, 56, 45, 11, NA, NA, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 0, 0, 0, NA, NA, NA, NA, NA, NA, NA, NA, 28, NA, NA, NA, 4, 6, 6, 2, 4, 6, 57, 7, 0, 5, 15, 38, 68, 87, 213, 324, 389, 428, 479, 530, 473, 470, 428, 129, 271, 381, 513, 520, 443, 583, 608, 463, 623, 608, 622, 593, 53, 273, 106, 399, 582, 592, 656, 625, 560, 595, 570, 586, 565, 572, 209, 281, 278, 190, 233, NA, NA, NA, NA, NA, 50, 50, 61, 22, 0, 8, 0, 0, 12, 
+#> 7, NA, NA, 0, 0, NA, NA, NA, 0, NA, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 93, 583, 486, 594, 542, 482, 165, 16, 234, 20, 54, 40, 48, 72, 61, 45, 18, 6, 1, 0, 0, 0, 0, 0, 1, 151, 230, 316, 357, 45, 67, 527, 594, 549, 464, 585, 304, 107, 223, 267, 189, 193, 316, 19, 268, 541, 519, 342, 119, 582, 187, 355, 572, 560, 524, 216, 12, 86, 113, 382, 542, 501, 569, 370, 392, 375, 141, 361, 573, 550, 461, 485, 251, 37, NA, NA, NA, 1, NA, NA, 0, NA, NA, 75, 72, 82, 78, 66, 36, 20, 63, 0, 2, 7, 3, 9, 0, 0, 0, 
+#> 3, 11, 35, 48, 6, 33, 379, 422, 429, 630, 614, 610, 619, 582, 611, 590, 581, 417, 113, 446, 397, 133, 585, 518, 428, 421, 107, 244, 79, 47, 166, 455, 313, 510, 389, 121, 476, 508, 476, 392, 209, 77, 10, 302, 594, 480, 533, 425, 573, 571, 529, 184, 213, 453, 199, 3, 524, 598, 597, 601, 567, 579, 572, 548, 555, 472, 358, 411, 513, 439, 488, 317, 455, 387, 13, 156, 191, 149, 309, 22, 10, 117, 350, 170, 38, 0, 5, 1, 3, 0, 2, 0, 2, 2, 2, 3, 0, 0, 0, 0, 0, 0, 58, 663, 372, 617, 637, 521, 333, 266, 582, 
+#> 510, 554, 606, 308, 220, 353, 167, 547, 554, 403, 478, 7, 16, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 130, 91, 488, 519, 530, 573, 569, 574, 505, 570, 458, 521, 524, 538, 598, 94, 335, 368, 518, 557, 628, 544, 457, 490, 514, 519, 368, 50, 37, 27, 325, 623, 610, 571, 599, 614, 394, 612, 520, 607, 574, 541, 383, 593, 562, 0, 1, 48, 42, 73, 61, 74, 73, 79, 64, 60, 64, 25, 24, 37, 0, 22, 61, 60, NA, NA, 8, NA, NA, NA, NA, NA, 3, 2, 2, 2, 1, 5, 5, 2, 1, 18, 3, 73, 51, 42, 26, 13, NA, NA, NA, 3, 79, 75, 60, 1, 16, 
+#> 0, 2, 48, 3, 5, 6, 29, 5, 6, 5, 1, 0, 1, 0, 0, 0, 0, 0, 0, NA, NA, NA, NA, NA, NA, NA, 1, 66, 55, 53, NA, 32, 31, 4, 292, 263, 214, 608, 601, 367, 232, 488, 221, 532, 529, 539, 508, 590, 503, 208, 539, 537, 585, 676, 631, 625, 258, 495, 609, 95, 310, 322, 134, NA, 0, 0, NA, NA, NA, NA, NA, 3, 4, 25, 3, 4, 2, 3, 4, 5, 3, 7, 2, 1, 53, 166, 313, 320, 320, 163, 417, 381, 315, 441, 385, 443, 160, 45, 313, 647, 690, 651, 382, 199, 554, 328, 62, 319, 572, 236, 65, 64, 93, 530, 578, 580, 587, 553, 583, 547, 
+#> 509, 546, 557, 299, 544, 398, 421, 240, 397, 176, 536, 519, 562, 575, 510, 520, 560, 535, 264, 417, 446, 254, 458, 24, 269, 176, 131, 89, 186, 60, 113, 192, 496, 415, 472, 102, 335, 580, 526, 511, 587, 607, 623, 505, 540, 553, 407, 494, 440, 0, 5, 5, 1, 0, 0, 0, 0, 0, 0, 3, 0, 2, 0, 0, 3, 0, 0, 0, 3, 4, 2, 0, 0, 3, 0, 1, 0, 0, 1, 0, 0, 0, 0, 455, 324, 636, 664, 563, 616, 654, 581, 143, 613, 383, 137, 196, 477, 35, 165, 551, 563, 588, 569, 319, 207, 538, 540, 385, 544, 29, 412, 0, 14, 188, 358, 379, 
+#> 505, 484, 511, 481, 449, 474, 465, 506, 168, 383, 383, 344, 69, 535, 624, 588, 593, 590, 606, 202, 305, 593, 595, 561, 465, 323, 329, 431, 617, 517, 585, 562, 493, 544, 587, 586, 623, 598, 494, 503, 460, 243, 299, 25, 327, 14, 543, 467, 487, 107, 284, 275, 314, 166, 285, 18, 45, 356, 501, 552, 585, 588, 475, 625, 485, 341, 89, 30, 111, 160, 278, 228, 69, 38, 11, 379, 396, 542, 543, 540, 545, 534, 493, 308, 552, 571, 444, 544, 162, 94, 143, 0, 17, 384, 336, 564, 561, 581, 520, 372, 557, 600, 551, 
+#> 451, 573, 580, 534, 606, 549, 521, 692, 647, 679, 704, 679, 695, 678, 686, 639, 680, 677, 227, 402, 520, 359, 398, 45, 124, 288, 554, 324, 637, 154, 487, 631, 622, 259, 115, 160, 327, 328, 226, 149, 425, 412, 458, 523, 422, 447, 450, 403, 387, 439, 349, 216, 95, 63, 18, 261, 382, 422, 626, 563, 626, 228, 390, 540, 607, 638, 661, 242, 414, 494, 324, 126, 1, 0, 164, 335, 66, 108, 152, 458, 436, 303, 473, 578, 372, 282, 248, 404, 204, 157, NA, NA, NA, 0, 0, 5, 0, 1, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 590, 
+#> 590, 591, 592, 591, 535, 565, 524, 568, 587, 579, 607, 391, 633, 602, 21, 473, 387, 540, 392, 262, 209, 483, 550, 547, 614, 618, 609, 524, 579, 379, 579, 586, 464, 341, 19, 318, 102, 413, 558, 509, 636, 538, 505, 138, 261, 426, 440, 329, 407, 122, 4, 5, 5, 4, 4, 62, 25, 2, 0, 4, NA, 3, 0, 2, 0, 3, 0, 0, 1, 2, 102, 598, 478, 474, 449, 468, 416, 451, 279, 339, 529, 342, 380, 168, 0, 281, 391, 126, 371, 57, 15, 49, 83, 67, 160, 98, 0, 5, 4, 6, 4, 7, 3, 62, 51, 51, 51, 13, 53, 34, 0, 1, 101, 473, 325, 
+#> 428, 409, 337, 410, 433, 497, 530, 491, 202, 175, NA, 1, NA, 4, 5, 2, 4, 6, 54, 0, 0, 0, 0, 99, 365, 593, 607, 622, 662, 636, 653, 654, 648, 514, 632, 635, 401, 235, 322, 156, 1, 1, 0, 0, 0, 0, 0, 566, 449, 570, 477, 80, 197, 186, 381, 84, 106, 281, 236, 132, 52, 15, 62, 54, 71, 38, 62, 26, 0, 1, 8, 50, 574, 696, 682, 608, 637, 647, 579, 453, 477, 496, 475, 561, 362, 219, 226, 13, 374, 607, 624, 622, 620, 647, 672, 638, 638, 442, 575, 543, 417, 557, 496, 155, 1, 2, 4, 0, 1, 1, 3, 4, 4, 65, 64, 59, 
+#> 65, 54, 53, 52, 4, 0, 0, 7, 31, 46, 44, 59, 7, 11, 6, 5, 0, 5, 5, 16, 8, 39, NA, 2, 0, 1, 6, 9, 6, 2, 3, 4, 4, 1, 92, 74, 53, 18, 10, 28, 44, 1, 0, 3, 0, 0, 0, 0, 0, 54, 454, 218, 477, 561, 581, 539, 605, 594, 175, 567, 623, 532, 129, 418, 334, 101, 164, 263, 153, 487, 539, 537, 606, 595, 564, 439, 584, 349, 199, 298, 486, 247, 183, 212, 352, 349, 603, 577, 466, 539, 545, 202, 12, 156, 223, 256, 49, 0, 13, 0, 2, 0, 0, 1, 0, 0, 0, 0, 0, 53, 75, 567, 512, 608, 474, 11, 226, 22, 27, 58, 74, 92, 64, 
+#> 63, 0, 1, 4, 2, 31, 200, 390, 534, 414, 560, 210, 353, 13, 524, 399, 519, 107, 88, 2, 96, 608, 678, 536, 620, 611, 584, 427, 630, 590, 505, 243, 424, 169, 205, 494, 606, 486, 604, 509, 412, 309, 463, 548, 308, 15, 308, 508, 551, 597, 492, 598, 500, 573, 589, 419, 445, 218, 244, 213, 551, 379, 577, 550, 420, 30, 57, 45, 59, 70, 45, 26, 21, 30, 23, 35, 68, 77, 61, 0, 40, 7, 0, 49, 278, 20, 415, 303, 412, 448, 582, 601, 558, 549, 416, 541, 518, 525, 324, 518, 518, 528, 1, 0, 4, 3, 8, 6, 2, 7, 78, 42, 
+#> 62, 35, 134, 439, 558, 670, 444, 73, 119, 191, 123, 414, 387, 473, 30, 162, 4, 129, 12, 545, 333, 358, 349, 556, 238, 12, 156, 79, 8, 411, 599, 570, 538, 184, 393, 531, 348, 444, 194, 206, 529, 545, 644, 628, 208, 286, 381, 193, 609, 601, 589, 451, 53, 440, 392, 31, 199, 215, 436, 557, 344, 550, 593, 624, 467, 513, 450, 316, 127, 32, 159, 520, 547, 572, 562, 266, 211, 377, 493, 540, 605, 561, 440, 50, 154, 418, 434, 587, 352, 384, 66, 217, 589, 620, 404, 635, 460, 261, 181, 195, 538, 510, 475, 587, 
+#> 559, 598, 603, 620, 595, 556, 449, 589, 487, 604, 631, 549, 567, 298, 17, 36, 462, 357, 414, 442, 53, 22, 188, 497, 546, 576, 588, 572, 577, 574, 588, 209, 339, 605, 609, 563, 573, 502, 24, 195, 133, 390, 527, 558, 652, 587, 543, 477, 305, 266, 107, 193, 41, 173, 71, 7, 73, 144, 513, 524, 582, 570, 444, 563, 575, 566, 549, 438, 546, 548, 543, 533, 467, 208, 36, 368, 407, 375, 424, 287, 518, 252, 494, 466, 368, 452, 478, 248, 5, 19, 12, 56, 62, 60, 19, 23, 26, 56, 61, 66, 53, 66, 7, 6, 28, 32, 0, 
+#> 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 7, 5, 7, 6, 39, 6, 3, 3, 1, 3, 2, 0, 1, 4, 6, 62, 58, NA, 1, 1, 2, 6, 1, 62, 77, 71, 1, 5, 63, 72, 71, 6, 192, 474, 489, 461, 579, 517, 407, 551, 497, 398, 137, 123, 1, 221, 483, 448, 174, 467, 451, 463, 470, 365, 435, 423, 364, 112, 222, 47, 77, 39, 71, 73, 66, 64, 70, 49, 28, 29, 38, 0, 6, 0, 2, 0, 2, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 39, 312, 581, 529, 610, 616, 550, 557, 260, 286, 569, 467, 7, 132, 385, 411, 526, 387, 224, 58, 74, 23, 433, 
+#> 271, 472, 376, 226, 456, 424, 375, 211, 133, 94, 18, 314, 603, 613, 576, 588, 616, 611, 548, 572, 622, 555, 611, 429, 492, 572, 558, 492, 623, 591, 618, 388, 236, 627, 436, 610, 605, 585, 258, 292, 2, 31, 38, 2, 72, 87, 78, 72, 59, 64, 22, 4, 42, 0, 32, 42, 16, 177, 282, 197, 264, 580, 343, 274, 603, 156, 325, 345, 259, 15, 376, 44, 97, 273, 128, 460, 641, 561, 563, 621, 611, 632, 230, 163, 66, 265, 317, 188, 517, 472, 642, 583, 655, 644, 623, 608, 621, 624, 593, 533, 555, 550, 539, 582, 207, 2, 
+#> 386, 573, 666, 690, 668, 691, 639, 645, 541, 656, 631, 611, 51, 468, 14, 95, 65, 460, 580, 568, 186, 349, 445, 512, 445, 34, 139, 114, 220, 323, 564, 206, 342, 492, 503, 343, 158, 461, 587, 580, 618, 554, 469, 303, 377, 582, 608, 452, 566, 630, 500, 434, 64, 260, 503, 442, 1, 0, 13, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 50, 64, 62, 73, 73, 67, 2, 269, 657, 649, 193, 396, 488, 617, 539, 536, 481, 257, 528, 548, 453, 331, 110, 106, 280, 490, 592, 590, 623, 508, 296, 264, 505, 495, 77, 502, 168, NA, NA, 
+#> 2, 22, NA, 5, 3, 5, 1, 2, 41, 57, 58, 55, 61, 50, 42, 5, 21, 10, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 1, 4, 5, 2, 4, 4, 4, 2, 6, 0, 2, 633, 639, 589, 576, 543, 338, 251, 353, 304, 449, 401, 522, 482, 617, 597, 637, 626, 623, 627, 605, 595, 624, 14, 50, 200, 536, 490, 432, 544, 167, 335, 333, 107, 489, 521, 406, 536, 523, 510, 296, 545, 445, 455, 592, 134, 267, 543, 658, 530, 607, 571, 425, 398, 301, 476, 589, 124, 249, 180, 442, 504, 509, 488, 479, 466, 439, 356, 495, 465, 400, 479, 
+#> 602, 636, 539, 346, 235, 596, 446, 599, 520, 574, 229, 2, 30, 75, 70, 80, 73, 81, 83, 69, 52, 44, 34, 274, 220, 696, 647, 681, 688, 147, 563, 537, 642, 382, 610, 193, 288, 263, 575, 582, 604, 626, 535, 587, 389, 581, 430, 535, 152, 93, 353, 577, 578, 538, 544, 468, 536, 561, 554, 460, 298, 106, 488, 81, 256, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 62, 273, 124, 452, 481, 260, 33, 490, 490, 471, 484, 493, 497, 277, 3, 59, 29, 333, 536, 373, 548, 540, 201, 562, 389, 469, 172, 460, 150, 4, 5, 6, 4, 6, 9, 
+#> 3, 3, 48, 4, 5, 3, 5, 4, 2, 3, 33, 55, 59, 53, 60, 73, 49, 0, 23, 7, 1, 5, 9, 6, 0, 23, 36, 208, 79, 569, 528, 538, 491, 362, 431, 146, 292, 105, 138, 640, 655, 628, 634, 436, 128, 268, 185, 162, 98, 175, 415, 540, 553, 505, 331, 417, 422, 438, 379, 441, 257, 651, 642, 599, 304, 289, 401, 53, 601, 561, 183, 62, 24, 326, 123, 302, 157, 487, 578, 405, 612, 549, 499, 331, 331, 53, 656, 637, 628, 657, 677, 689, 716, 556, 672, 350, 567, 632, 600, 538, 517, 59, 569, 573, 588, 591, 578, 569, 581, 624, 150, 
+#> 613, 4, 165, 240, 282, 575, 618, 559, 471, 392, 411, 470, 217, 265, 126, 242, 52, 99, NA, NA, NA, NA, NA, NA, 0, NA, 0, 0, 0, 0, 1, 0, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 89, 520, 653, 626, 302, 635, 563, 641, 551, 381, 451, 611, 635, 619, 563, 598, 225, 530, 506, 60, 52, 4, 54, 14, 19, 2, NA, 2, 0, NA, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 2, 4, 2, 3, 64, 30, 18, 0, 49, 39, 44, 64, 76, 61, 67, 69, 69, 56, 62, 39, 3, 0, 0, 3, 8, 6, 5, 5, 5, 33, 
+#> 3, 0, 75, 64, 60, 24, 2, 4, 1, 0, 0, 0, 0, 0, 0, 0, 0, 43, 70, 66, 67, 61, 45, 57, 44, 21, 42, 150, 570, 646, 616, 552, 591, 630, 484, 145, 583, 591, 571, 31, 370, 22, 9, 536, 650, 559, 584, 626, 610, 580, 606, 462, 588, 135, 385, 417, 353, 444, 481, 465, 475, 505, 505, 404, 488, 109, 270, 329, 597, 339, 168, 242, 267, 209, 57, 531, 139, 73, 17, 415, 456, 570, 620, 587, 519, 208, 387, 477, 123, 94, 84, 251, 56, 254, 603, 522, 232, 375, 547, 463, 594, 506, 554, 306, 465, 565, 570, 304, 494, 279, 196, 
+#> 4, 0, 5, 3, 3, 5, 5, 6, 3, 2, 62, 448, 584, 574, 483, 273, 614, 624, 604, 1, 25, 54, 494, 331, 322, 421, 176, 148, 163, 42, 38, 187, 122, 411, 454, 636, 600, 575, 224, 230, 550, 598, 430, 106, 569, 521, 78, 298, 624, 336, 518, 487, 562, 576, 338, 170, 166, 229, 480, 351, 453, 421, 284, 276, 130, 81, 136, 26, 50, 41, 303, 538, 486, 209, 281, 112, 378, 422, 129, 357, 259, 630, 626, 644, 600, 584, 443, 606, 600, 506, 117, 435, 343, 181, 361, 546, 608, 205, 682, 528, 124, 396, 609, 327, 501, 313, 0, 
+#> 0, 2, 2, 0, 1, 7, 6, 6, 49, 0, 33, 58, 60, 67, 74, 65, 477, 473, 581, 567, 648, 653, 644, 546, 0, 3, 6, 6, 3, 3, 4, 5, 6, 4, 5, 2, 67, 4, 0, 7, 58, 614, 653, 428, 610, 525, 395, 578, 568, 214, 346, 8, 119, 467, 606, 535, 227, 429, 624, 525, 444, 136, 289, 154, 292, 606, 606, 602, 602, 403, 263, 541, 596, 0, 6, 62, 60, 89, 84, 66, 71, 72, 10, 447, 393, 544, 572, 524, 233, 118, 42, 1, 3, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 504, 358, 269, 93, 195, 385, 440, 60, 290, 326, 587, 569, 499, 321, 
+#> 465, 290, 502, 396, 447, 525, 596, 517, 487, 556, 482, 341, 395, NA, 0, 0, 4, 3, 4, 2, 2, 2, 0, 0, 3, 2, 623, 584, 629, 172, 547, 337, 456, 482, 517, 95, 0, 5, 0, 5, 2, 2, 0, 3, 47, 45, 65, 4, 3, 8, 5, 3, 3, 65, 63, 76, 41, 12, 77, 69, 55, 38, 53, 38, 0, 4, 4, 1, 6, 2, 7, 3, 5, 2, 3, 1, 136, 271, 399, 565, 568, 322, 150, 145, 171, 302, 278, 587, 481, 518, 391, 260, 554, 21, 21, 6, 0, 6, 1, 81, 70, 61, 62, 68, 57, 63, 59, 27, 96, 609, 377, 543, 470, 537, 181, 446, 315, 323, 163, 11, 25, 40, 12, 28, 
+#> 400, 532, 314, 56, 336, 569, 513, 332, 452, 553, 543, 84, 526, 469, 547, 599, 374, 581, 220, 545, 19, 25, 5, 250, 14, 173, 461, 559, 452, 73, 405, 476, 317, 202, 22, 28, 43, NA, NA, 1, 2, 3, 2, 3, 0, 0, 2, 8, 4, 2, 3, 2, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 17, 406, 162, 530, 520, 547, 557, 480, 542, 585, 614, 593, 637, 622, 583, 611, 632, 531, 564, 589, 600, 523, 448, 130, 11, 120, 40, 9, 58, 63, 68, 67, 57, 54, 4, 5, 130, 307, 115, 462, 399, 475, 585, 413, 613, 
+#> 590, 31, 240, 333, 501, 462, 462, 424, 116, 554, 624, 78, 660, 303, 577, 575, 452, 29, 48, 55, 71, 58, 77, 63, 71, 354, 446, 500, 526, 523, 104, 258, 543, 493, 164, 242, 611, 642, 633, 563, 354, 491, 637, 595, 642, 629, 641, 420, 634, 642, 612, 40, 194, 346, 504, 534, 556, 517, 550, 589, 597, 455, 364, 445, 385, 601, 406, 123, 224, 323, 329, 443, 608, 595, 597, 614, 582, 549, 538, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 2, 1, 3, 0, 41, 0, 0, 0, 0, 0, 1, 61, 294, 464, 367, 330, 390, 178, 25, 162, 596, 612, 
+#> 553, 631, 466, 583, 596, 214, 564, 580, 159, 352, 523, 381, 604, 555, 508, 378, 175, 505, 140, 356, 526, 495, 592, 554, 558, 566, 542, 0, 27, 0, 65, 13, 0, 1, 126, 645, 575, 395, 570, 168, 305, 574, 272, 62, 242, 174, 19, 460, 545, 414, 485, 458, 658, 459, 344, 568, 629, 145, 572, 563, 426, 396, 525, 588, 470, 0, 1, 0, 0, 0, 4, 0, 51, 59, 72, 6, 9, 3, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 7, 4, 4, 6, 0, 4, 5, 4, 59, 62, 254, 611, 385, 363, 526, 372, 128, 592, 569, 414, 340, 527, 663, 601, 
+#> 529, 411, 324, 451, 492, 563, 492, 212, 19, 324, 560, 151, 571, 511, 494, 429, 79, 529, 548, 501, 204, 33, 4, 23, 18, 331, 543, 610, 381, 604, 520, 191, 279, 580, 433, 570, 572, 593, 583, 548, 566, 520, 396, 587, 382, 573, 547, 36, 75, 455, 381, 365, 338, 517, 574, 632, 395, 377, 243, 488, 11, 123, 559, 589, 602, 575, 533, 424, 352, 521, 10, 22, 88, 381, 440, 487, 471, 460, 509, 472, 534, 504, 474, 464, 479, 503, 256, 82, 407, 25, 23, 502, 521, 351, 427, 370, 488, 519, 389, 73, 224, 0, 0, 413, 345, 
+#> 509, 585, 560, 626, 493, 580, 20, 6, 47, 49, 60, 38, 82, 525, 584, 513, 600, 593, 583, 2, 0, 0, 0, 0, 0, 0, 0, 13, 53, 2, 4, 2, 3, 2, 69, 523, 535, 623, 503, 599, 191, 667, 327, 633, 148, 289, 496, 578, 531, 156, 514, 602, 406, 567, 486, 432, 616, 125, 577, 315, 291, 231, 415, 536, 574, 149, 286, 166, 606, 540, 535, 21, 29, 52, 335, 325, 225, 50, 16, 18, 295, 391, 120, 123, 76, 515, 584, 450, 573, 15, 296, 626, 595, 574, 347, 235, 525, 558, 398, 437, 18, 112, 102, 339, 422, 557, 547, 249, 588, 609, 
+#> 529, 358, 489, 190, 379, 147, 22, 222, 399, 471, 551, 128, 337, 606, 524, 586, 0, 5, 54, 46, 28, 23, 5, 9, 31, 1, 4, 24, 355, 610, 546, 53, 265, 616, 110, 127, 0, 0, 2, 5, 6, 182, 594, 615, 590, 623, 20, 2, 3, 5, 60, 229, 404, 494, 564, 392, 416, 441, 240, 582, 476, 359, 516, 449, 425, 539, 279, 2, 39, 59, 68, 56, 66, 77, 556, 613, 46, 59, 221, 576, 626, 660, 638, 98, 293, 485, 363, 112, 297, 451, 552, 556, 611, 529, 36, 426, 596, 472, 478, 512, 543, 351, 613, 311, 4, 125, 506, 548, 605, 607, 579, 
+#> 612, 18, 58, 65, 3, 4, 3, 0, 15, 39, 79, 0, 331, 505, 487, 529, 201, 399, 403, 230, 23, 195, 493, 630, 224, 303, 94, 609, 615, 81, 443, 265, 609, 167, 510, 495, 579, 196, 435, 499, 491, 507, 32, 274, 579, 608, 620, 131, 508, 391, 571, 658, 596, 499, 387, 559, 197, 119, 61, 566, 193, 484, 602, 154, 213, 569, 208, 395, 296, 441, 596, 44, 538, 613) x c(25, 32, 18, 32, 22, 35, 27, 0, 1, 21, 0, 9, 33, 47, 45, 62, 44, 42, 81, 64, 65, 73, 94, 94, 63, 80, 83, 84, 77, 41, 11, 25, 62, 59, 53, 48, 76, 89, 32, 42, 43, 1, 27, 30, 59, 48, 34, 30, 25, 6, 17, 20, 11, 8, 49, 44, 106, 167, 96, 123, 112, 112, 63, 4, 18, 24, 39, 27, 20, 26, 27, 10, 17, 18, 2, 0, 6, 10, 0, 16, 34, 21, 40, 20, 36, 18, 28, 7, 8, 18, 8, 15, 31, 30, 19, 32, 20, 14, 25, 23, 0, 60, 144, 161, 134, 125, 147, 160, 110, 97, 130, 97, 103, 27, 40, 10, 7, 0, 6, 23, 14, 23, 24, 20, 31, 14, 
+#> 20, 22, 13, 20, 17, 21, 14, 8, 9, 10, 9, 6, 0, 0, 1, 36, 107, 113, 70, 95, 145, 81, 0, 90, 92, 29, 88, 53, 77, 56, 94, 36, 66, 66, 37, 40, 33, 0, 2, 6, 16, 0, 8, 4, 6, 4, 5, 4, 4, 2, 0, 1, 10, 10, 13, 15, 13, 6, 8, 11, 9, 9, 12, 14, 7, 8, 3, 1, 1, 60, 84, 72, 50, 60, 67, 82, 61, 49, 15, 43, 27, 85, 66, 71, 30, 58, 4, 61, 86, 25, 26, 103, 81, 62, 8, 50, 0, 15, 43, 39, 31, 26, 32, 41, 34, 33, 0, 12, 12, 15, 3, 1, 10, 36, 54, 36, 10, 29, 25, 37, 30, 40, 11, 10, 26, 9, 0, 0, 25, 68, 91, 92, 88, 49, 73, 
+#> 65, 102, 102, 83, 83, 109, 81, 78, 74, 81, 41, 6, 0, 78, 91, 77, 89, 33, 60, 5, 5, 12, 7, 10, 5, 12, 23, 12, 1, 0, 0, 0, 1, 8, 8, 3, 6, 4, 6, 6, 3, 2, 11, 2, 0, 16, 16, 11, 12, 16, 5, 20, 5, 6, 6, 11, 3, 1, 0, 1, 19, 45, 97, 88, 116, 106, 147, 120, 70, 69, 144, 113, 107, 83, 92, 86, 124, 99, 103, 115, 97, 48, 104, 54, 0, 16, 19, 99, 81, 91, 70, 69, 71, 63, 57, 67, 64, 56, 59, 36, 47, 35, 39, 11, 3, 1, 0, 0, 3, 81, 74, 76, 61, 59, 61, 71, 42, 59, 19, 1, 0, 40, 30, 16, 87, 81, 58, 69, 57, 70, 27, 35, 
+#> 22, 8, 20, 42, 19, 8, 26, 49, 67, 41, 26, 45, 44, 51, 31, 32, 8, 26, 20, 49, 40, 107, 30, 110, 42, 17, 124, 15, 71, 33, 3, 27, 1, 54, 96, 96, 120, 116, 122, 84, 118, 103, 88, 51, 95, 69, 97, 83, 97, 57, 73, 0, 0, 0, 4, 8, 6, 11, 6, 5, 13, 9, 8, 3, 2, 2, 4, 10, 2, 6, 3, 3, 6, 6, 8, 3, 6, 2, 1, 37, 80, 98, 107, 101, 105, 97, 97, 114, 103, 98, 100, 92, 90, 87, 91, 51, 60, 68, 45, 15, 23, 35, 64, 125, 106, 115, 77, 66, 88, 79, 76, 84, 61, 83, 101, 43, 52, 7, 70, 49, 44, 65, 66, 83, 88, 87, 29, 73, 81, 
+#> 81, 38, 33, 5, 20, 0, 0, 9, 14, 8, 8, 10, 9, 9, 12, 5, 3, 9, 6, 5, 6, 4, 4, 10, 3, 4, 6, 3, 1, 1, 3, 3, 3, 1, 16, 67, 77, 44, 42, 57, 93, 105, 90, 85, 54, 66, 31, 12, 21, 11, 35, 2, 0, 39, 104, 81, 92, 137, 125, 122, 118, 87, 91, 51, 87, 117, 79, 92, 89, 108, 80, 66, 50, 3, 0, 1, 5, 13, 25, 36, 29, 34, 17, 18, 10, 7, 1, 0, 0, 8, 31, 25, 13, 16, 4, 0, 0, 12, 73, 92, 88, 136, 94, 101, 108, 102, 90, 73, 83, 137, 107, 85, 133, 94, 79, 96, 71, 28, 10, 15, 18, 9, 12, 6, 9, 4, 5, 6, 7, 5, 8, 6, 7, 3, 0, 
+#> 3, 7, 6, 14, 18, 16, 12, 23, 14, 13, 15, 10, 13, 6, 10, 8, 11, 18, 12, 6, 6, 20, 11, 14, 15, 13, 16, 13, 13, 15, 4, 13, 1, 4, 11, 0, 1, 4, 9, 15, 16, 10, 2, 6, 1, 41, 30, 25, 32, 74, 13, 114, 90, 126, 107, 98, 97, 99, 73, 112, 74, 82, 85, 72, 15, 17, 6, 14, 8, 28, 37, 42, 53, 32, 23, 6, 19, 28, 4, 1, 0, 0, 1, 0, 9, 9, 5, 13, 8, 4, 1, 0, 2, 4, 7, 6, 5, 1, 3, 1, 32, 37, 26, 38, 39, 83, 89, 92, 103, 58, 65, 53, 54, 23, 2, 3, 0, 0, 75, 20, 64, 97, 97, 92, 71, 66, 102, 93, 126, 83, 60, 50, 24, 99, 80, 
+#> 42, 14, 1, 0, 2, 4, 8, 6, 5, 7, 0, 4, 5, 0, 1, 7, 43, 30, 67, 55, 60, 83, 66, 28, 7, 11, 65, 29, 2, 0, 12, 20, 6, 22, 14, 33, 14, 3, 0, 0, 4, 19, 25, 17, 37, 35, 25, 12, 0, 9, 4, 24, 4, 20, 31, 10, 1, 0, 8, 2, 4, 6, 0, 10, 8, 11, 9, 10, 5, 6, 6, 9, 5, 7, 4, 7, 2, 3, 0, 1, 6, 31, 36, 41, 35, 38, 17, 21, 11, 0, 3, 2, 4, 51, 100, 77, 75, 79, 60, 110, 79, 79, 92, 96, 72, 44, 24, 17, 46, 11, 1, 7, 7, 0, 2, 0, 0, 5, 73, 83, 96, 116, 116, 84, 46, 57, 65, 70, 46, 30, 0, 17, 24, 45, 35, 19, 16, 27, 16, 19, 
+#> 9, 9, 12, 0, 5, 3, 3, 0, 5, 2, 0, 3, 1, 0, 3, 15, 126, 121, 109, 61, 21, 42, 91, 91, 9, 79, 105, 20, 18, 41, 45, 25, 18, 28, 42, 30, 18, 20, 6, 10, 2, 9, 1, 15, 25, 48, 60, 37, 33, 24, 21, 8, 5, 12, 7, 9, 18, 9, 10, 17, 1, 6, 9, 8, 4, 10, 3, 7, 1, 1, 7, 13, 2, 0, 67, 89, 81, 76, 89, 62, 75, 59, 50, 79, 97, 69, 114, 63, 47, 16, 65, 86, 97, 102, 98, 67, 87, 86, 6, 55, 48, 38, 61, 48, 1, 7, 39, 61, 71, 50, 43, 94, 37, 98, 83, 46, 6, 4, 0, 3, 1, 9, 14, 5, 3, 0, 3, 3, 6, 0, 1, 2, 3, 3, 4, 0, 3, 4, 10, 
+#> 76, 83, 79, 74, 44, 42, 50, 40, 32, 50, 72, 58, 70, 57, 19, 12, 0, 0, 7, 55, 80, 88, 64, 50, 51, 47, 53, 50, 67, 72, 101, 74, 4, 3, 4, 12, 22, 26, 11, 13, 11, 38, 22, 42, 19, 6, 5, 46, 0, 22, 0, 4, 1, 29, 62, 53, 61, 34, 75, 43, 38, 2, 0, 0, 17, 23, 35, 80, 95, 69, 75, 65, 54, 22, 61, 43, 56, 10, 40, 49, 63, 96, 102, 83, 59, 51, 82, 78, 69, 21, 57, 8, 47, 64, 59, 72, 80, 71, 64, 33, 30, 1, 7, 9, 9, 8, 4, 2, 32, 44, 64, 41, 41, 36, 43, 58, 77, 46, 39, 46, 17, 36, 40, 41, 43, 16, 9, 3, 4, 10, 7, 3, 
+#> 3, 2, 6, 1, 0, 5, 1, 2, 1, 13, 56, 64, 73, 75, 62, 57, 30, 16, 28, 45, 13, 8, 86, 52, 56, 12, 43, 7, 0, 63, 78, 76, 89, 70, 70, 43, 34, 2, 15, 78, 55, 70, 64, 66, 64, 76, 38, 39, 70, 89, 91, 92, 63, 92, 125, 68, 34, 7, 38, 30, 46, 36, 48, 35, 57, 64, 32, 57, 42, 15, 44, 26, 2, 0, 0, 9, 3, 8, 2, 5, 2, 2, 2, 6, 2, 6, 8, 68, 74, 51, 79, 69, 3, 44, 48, 90, 115, 78, 62, 37, 32, 0, 40, 87, 85, 69, 67, 46, 3, 4, 38, 25, 24, 26, 30, 37, 35, 30, 32, 20, 24, 10, 21, 6, 0, 0, 2, 11, 81, 100, 83, 105, 103, 80, 
+#> 86, 115, 111, 104, 99, 43, 65, 5, 9, 4, 0, 33, 78, 77, 18, 46, 43, 7, 6, 5, 0, 3, 3, 3, 2, 1, 8, 51, 0, 59, 72, 85, 91, 86, 79, 86, 54, 63, 91, 82, 7, 2, 2, 2, 1, 19, 41, 23, 18, 5, 7, 7, 26, 36, 34, 37, 37, 21, 10, 7, 85, 53, 56, 69, 45, 79, 23, 121, 117, 80, 49, 75, 70, 44, 47, 35, 0, 42, 74, 94, 87, 74, 60, 5, 19, 3, 17, 12, 59, 55, 53, 49, 54, 88, 67, 98, 98, 101, 78, 63, 86, 31, 11, 1, 0, 4, 3, 13, 3, 0, 5, 5, 2, 2, 0, 2, 28, 83, 60, 69, 96, 137, 125, 134, 94, 100, 78, 87, 71, 1, 67, 54, 1, 
+#> 16, 18, 14, 50, 103, 158, 177, 94, 151, 143, 61, 139, 158, 163, 121, 150, 149, 120, 97, 78, 13, 38, 16, 51, 53, 37, 72, 46, 54, 61, 30, 40, 69, 57, 27, 15, 39, 5, 63, 86, 51, 68, 96, 131, 141, 89, 121, 133, 96, 133, 99, 156, 15, 64, 10, 2, 9, 2, 1, 1, 7, 1, 9, 1, 16, 0, 42, 27, 32, 12, 18, 14, 17, 23, 5, 13, 25, 14, 1, 0, 0, 25, 72, 88, 64, 8, 0, 68, 7, 29, 5, 55, 51, 64, 83, 78, 64, 37, 89, 102, 65, 73, 75, 16, 68, 88, 1, 10, 4, 9, 7, 1, 10, 7, 5, 10, 6, 6, 6, 5, 10, 29, 78, 59, 101, 50, 98, 84, 
+#> 75, 97, 0, 14, 3, 18, 25, 27, 26, 22, 28, 30, 17, 16, 11, 2, 26, 73, 34, 4, 82, 61, 73, 81, 68, 29, 88, 67, 91, 95, 83, 20, 76, 46, 2, 77, 114, 99, 76, 76, 90, 82, 70, 41, 74, 85, 140, 120, 113, 109, 18, 46, 70, 41, 2, 0, 2, 5, 1, 4, 8, 8, 9, 11, 11, 18, 9, 11, 12, 2, 0, 1, 17, 19, 28, 32, 30, 21, 34, 46, 63, 39, 33, 31, 29, 7, 14, 4, 29, 81, 93, 98, 100, 85, 90, 75, 89, 81, 76, 91, 74, 111, 87, 107, 62, 0, 6, 4, 3, 2, 3, 10, 8, 4, 7, 13, 5, 14, 2, 72, 51, 53, 71, 90, 46, 28, 41, 72, 69, 68, 58, 
+#> 42, 56, 49, 56, 46, 57, 15, 1, 7, 5, 8, 9, 10, 15, 15, 11, 12, 4, 10, 17, 11, 3, 9, 4, 4, 1, 1, 0, 0, 0, 1, 18, 1, 35, 55, 67, 65, 63, 59, 89, 109, 128, 62, 73, 72, 67, 19, 23, 2, 52, 37, 61, 76, 62, 56, 85, 96, 85, 63, 66, 98, 0, 1, 2, 35, 69, 54, 37, 36, 62, 83, 51, 82, 29, 12, 1, 0, 1, 1, 1, 4, 1, 14, 10, 8, 9, 2, 0, 6, 11, 3, 1, 0, 26, 77, 3, 80, 83, 83, 91, 117, 106, 111, 98, 98, 95, 119, 121, 81, 58, 19, 48, 0, 12, 12, 5, 8, 17, 8, 4, 3, 0, 8, 1, 6, 10, 13, 3, 4, 9, 3, 3, 8, 1, 1, 2, 0, 1, 
+#> 2, 8, 18, 14, 9, 11, 12, 6, 6, 0, 66, 25, 37, 40, 40, 41, 41, 65, 64, 48, 56, 3, 10, 15, 1, 16, 9, 31, 23, 22, 30, 21, 39, 16, 9, 5, 70, 73, 92, 90, 105, 121, 112, 82, 62, 3, 11, 4, 1, 1, 8, 10, 8, 8, 7, 6, 3, 7, 2, 3, 8, 4, 4, 0, 0, 3, 8, 9, 10, 3, 6, 10, 18, 7, 2, 9, 3, 12, 5, 5, 3, 21, 57, 121, 101, 116, 121, 89, 75, 112, 107, 93, 121, 96, 59, 74, 74, 52, 40, 3, 2, 4, 0, 2, 12, 69, 95, 96, 82, 91, 87, 70, 27, 46, 73, 22, 18, 23, 17, 46, 47, 61, 78, 100, 113, 79, 42, 31, 15, 1, 4, 8, 8, 6, 5, 11, 
+#> 9, 9, 5, 11, 5, 0, 0, 0, 1, 4, 3, 9, 26, 25, 65, 54, 45, 44, 111, 105, 50, 39, 44, 33, 14, 1, 1, 8, 6, 2, 4, 9, 8, 1, 14, 19, 15, 12, 13, 10, 5, 1, 0, 0, 0, 8, 9, 3, 13, 4, 7, 6, 4, 5, 2, 8, 6, 5, 3, 3, 2, 3, 6, 3, 3, 6, 7, 8, 7, 10, 8, 6, 4, 4, 2, 6, 0, 2, 2, 3, 1, 0, 8, 3, 12, 12, 6, 5, 18, 2, 6, 7, 3, 59, 70, 82, 48, 74, 109, 96, 96, 79, 88, 19, 72, 49, 30, 2, 1, 9, 22, 40, 58, 58, 53, 31, 21, 14, 11, 1, 4, 1, 3, 0, 25, 57, 57, 34, 74, 66, 114, 92, 121, 107, 97, 90, 106, 83, 86, 79, 3, 7, 4, 21, 
+#> 21, 23, 10, 10, 16, 4, 9, 18, 15, 8, 2, 0, 1, 1, 1, 1, 0, 1, 3, 6, 4, 9, 6, 4, 14, 6, 4, 2, 5, 6, 0, 1, 14, 101, 80, 98, 99, 78, 91, 83, 79, 90, 44, 102, 95, 87, 0, 11, 6, 38, 62, 64, 78, 53, 73, 58, 68, 67, 66, 58, 65, 66, 38, 24, 0, 13, 0, 0, 1, 9, 11, 29, 32, 68, 73, 25, 2, 37, 63, 19, 23, 6, 35, 37, 11, 7, 16, 3, 10, 0, 0, 0, 5, 3, 6, 7, 9, 8, 7, 7, 8, 8, 8, 10, 8, 1, 1, 0, 0, 0, 1, 6, 7, 9, 3, 4, 1, 0, 5, 1, 0, 0, 0, 9, 5, 7, 8, 2, 10, 7, 4, 4, 6, 2, 1, 1, 1, 1, 7, 42, 62, 56, 83, 103, 87, 84, 
+#> 56, 71, 65, 70, 68, 78, 83, 83, 11, 45, 20, 7, 3, 0, 5, 37, 41, 45, 43, 40, 20, 19, 9, 16, 41, 4, 50, 3, 69, 94, 87, 130, 98, 109, 89, 73, 63, 56, 64, 7, 0, 10, 0, 15, 2, 5, 11, 3, 8, 7, 4, 1, 0, 7, 1, 1, 0, 2, 7, 7, 9, 5, 11, 13, 6, 8, 6, 1, 4, 5, 8, 4, 0, 2, 1, 45, 81, 51, 64, 67, 73, 92, 70, 65, 23, 11, 75, 74, 41, 6, 0, 89, 108, 86, 114, 83, 93, 91, 94, 90, 81, 74, 85, 62, 24, 3, 4, 28, 56, 61, 35, 56, 61, 2, 84, 53, 52, 55, 58, 67, 49, 47, 40, 36, 3, 20, 5, 48, 59, 77, 69, 71, 78, 35, 64, 82, 
+#> 64, 63, 39, 44, 43, 12, 25, 5, 0, 1, 0, 18, 30, 41, 34, 63, 50, 55, 42, 61, 31, 16, 18, 6, 1, 10, 13, 4, 69, 50, 80, 92, 113, 110, 87, 118, 104, 74, 93, 24, 27, 69, 122, 90, 86, 78, 114, 152, 105, 144, 85, 102, 68, 96, 60, 79, 39, 0, 7, 1, 9, 1, 8, 44, 86, 100, 116, 105, 96, 80, 82, 81, 34, 114, 88, 97, 106, 88, 122, 30, 6, 0, 10, 6, 7, 16, 10, 7, 20, 6, 11, 11, 9, 5, 2, 6, 9, 5, 4, 8, 10, 0, 0, 0, 4, 94, 144, 113, 60, 92, 111, 155, 110, 58, 37, 80, 22, 36, 96, 48, 45, 80, 97, 73, 78, 63, 4, 83, 
+#> 36, 50, 19, 1, 29, 79, 87, 92, 98, 95, 123, 108, 92, 73, 45, 57, 72, 44, 72, 11, 5, 20, 35, 29, 22, 2, 1, 12, 34, 29, 16, 8, 3, 9, 0, 3, 4, 5, 4, 13, 8, 1, 3, 1, 0, 2, 0, 0, 0, 55, 49, 60, 42, 61, 63, 7, 1, 52, 71, 91, 64, 69, 97, 84, 29, 1, 0, 5, 57, 58, 82, 63, 85, 70, 72, 49, 9, 68, 76, 59, 52, 2, 59, 83, 46, 95, 102, 104, 85, 26, 74, 110, 121, 115, 88, 68, 43, 57, 9, 2, 0, 4, 43, 74, 91, 75, 135, 120, 3, 69, 4, 3, 6, 8, 10, 13, 11, 8, 10, 9, 4, 5, 5, 6, 8, 3, 4, 6, 6, 9, 14, 3, 4, 4, 8, 8, 1, 
+#> 0, 0, 62, 28, 97, 119, 89, 135, 146, 66, 77, 41, 24, 0, 0, 0, 3, 3, 3, 10, 0, 6, 9, 13, 1, 4, 1, 4, 1, 0, 5, 6, 3, 5, 2, 1, 1, 6, 2, 73, 135, 149, 139, 127, 143, 163, 138, 138, 128, 125, 167, 138, 115, 2, 79, 92, 62, 101, 109, 67, 79, 94, 59, 72, 82, 56, 21, 6, 7, 0, 1, 3, 8, 4, 7, 8, 5, 4, 10, 15, 9, 2, 0, 1, 5, 0, 1, 1, 2, 4, 4, 1, 1, 0, 5, 5, 9, 9, 3, 9, 2, 4, 5, 2, 0, 0, 4, 0, 0, 1, 8, 15, 5, 8, 4, 7, 4, 1, 3, 8, 1, 7, 2, 4, 4, 4, 0, 6, 9, 6, 8, 3, 8, 4, 6, 4, 5, 3, 3, 1, 1, 1, 2, 3, 3, 101, 
+#> 114, 142, 131, 117, 88, 107, 101, 122, 98, 107, 94, 77, 62, 32, 5, 40, 43, 29, 16, 1, 0, 1, 26, 75, 26, 101, 100, 103, 139, 121, 124, 68, 109, 91, 36, 27, 32, 42, 40, 50, 11, 45, 59, 54, 45, 36, 34, 25, 38, 25, 15, 0, 0, 2, 133, 121, 134, 32, 90, 90, 59, 95, 83, 67, 80, 79, 49, 30, 7, 17, 2, 23, 3, 2, 5, 5, 3, 1, 11, 6, 2, 6, 5, 11, 7, 1, 1, 6, 1, 0, 8, 6, 2, 5, 4, 4, 6, 3, 1, 4, 12, 2, 1, 2, 2, 8, 4, 0, 1, 10, 36, 30, 62, 101, 101, 108, 94, 34, 77, 75, 10, 39, 7, 1, 4, 2, 11, 13, 4, 12, 9, 9, 10, 
+#> 5, 3, 3, 2, 0, 1, 19, 43, 90, 107, 99, 99, 127, 38, 83, 70, 59, 49, 12, 38, 55, 33, 5, 78, 60, 38, 97, 20, 65, 21, 0, 8, 2, 3, 62, 110, 108, 131, 144, 67, 112, 103, 134, 123, 144, 133, 133, 86, 108, 65, 6, 13, 4, 81, 88, 66, 50, 68, 93, 54, 61, 39, 76, 69, 48, 71, 49, 52, 45, 62, 10, 9, 0, 10, 117, 113, 137, 118, 119, 129, 120, 143, 86, 47, 47, 3, 6, 11, 12, 10, 5, 5, 4, 1, 4, 0, 1, 4, 6, 6, 6, 8, 3, 9, 2, 4, 0, 0, 12, 19, 24, 14, 26, 12, 25, 20, 7, 7, 1, 6, 0, 0, 2, 3, 78, 82, 94, 87, 83, 2, 47, 
+#> 3, 18, 32, 51, 74, 19, 5, 13, 0, 8, 8, 12, 12, 7, 5, 2, 0, 4, 0, 0, 5, 1, 15, 14, 8, 15, 18, 15, 13, 14, 11, 6, 11, 8, 1, 3, 6, 5, 9, 11, 6, 9, 15, 9, 4, 3, 3, 5, 5, 2, 0, 2, 2, 0, 2, 67, 152, 122, 85, 120, 14, 31, 27, 2, 8, 23, 85, 123, 127, 93, 151, 125, 120, 118, 130, 111, 139, 130, 106, 87, 18, 25, 0, 30, 110, 102, 140, 116, 83, 128, 109, 136, 121, 101, 8, 58, 10, 2, 9, 2, 23, 72, 127, 103, 95, 89, 68, 70, 36, 102, 98, 97, 104, 98, 7, 8, 24, 1, 0, 0, 2, 8, 5, 3, 6, 3, 8, 3, 2, 0, 3, 54, 45, 9, 
+#> 57, 62, 88, 71, 50, 54, 45, 8, 39, 8, 0, 1, 0, 6, 0, 14, 10, 11, 5, 6, 8, 4, 2, 3, 1, 7, 5, 7, 3, 11, 9, 9, 14, 5, 7, 5, 5, 2, 8, 5, 0, 6, 3, 7, 2, 8, 10, 4, 2, 4, 4, 2, 3, 3, 3, 6, 7, 5, 15, 16, 10, 3, 12, 2, 4, 2, 2, 8, 7, 6, 1, 0, 0, 41, 126, 158, 121, 152, 101, 78, 71, 19, 83, 74, 53, 8, 37, 39, 6, 0, 0, 1, 1, 8, 9, 3, 8, 4, 1, 8, 5, 3, 0, 5, 4, 0, 0, 3, 8, 9, 12, 9, 9, 10, 5, 4, 6, 6, 1, 2, 2, 1, 14, 102, 82, 79, 113, 101, 106, 86, 111, 77, 77, 4, 76, 76, 24, 32, 3, 2, 0, 4, 10, 5, 8, 9, 1, 
+#> 1, 1, 1, 5, 2, 0, 1, 10, 8, 15, 18, 7, 8, 3, 4, 2, 0, 0, 0, 27, 101, 69, 88, 118, 78, 102, 60, 71, 91, 67, 37, 76, 0, 44, 53, 48, 0, 1, 60, 55, 65, 66, 58, 56, 54, 99, 87, 84, 98, 45, 35, 28, 29, 10, 1, 85, 89, 69, 89, 88, 77, 57, 70, 79, 65, 62, 79, 18, 2, 9, 59, 60, 75, 77, 88, 93, 90, 93, 78, 68, 17, 51, 52, 7, 3, 14, 2, 11, 7, 6, 4, 4, 10, 3, 7, 9, 7, 12, 10, 8, 6, 0, 1, 1, 4, 5, 5, 7, 9, 10, 9, 5, 11, 5, 2, 5, 4, 0, 1, 98, 94, 90, 84, 92, 91, 88, 14, 40, 74, 5, 36, 0, 3, 0, 60, 38, 44, 39, 58, 
+#> 50, 46, 31, 19, 32, 20, 15, 33, 17, 40, 27, 22, 13, 9, 13, 92, 110, 132, 115, 111, 100, 98, 62, 21, 100, 69, 13, 41, 64, 17, 14, 7, 19, 0, 1, 3, 2, 5, 4, 7, 3, 9, 5, 4, 3, 0, 0, 71, 85, 115, 108, 122, 71, 88, 94, 113, 69, 82, 112, 24, 19, 5, 64, 0, 129, 84, 89, 85, 92, 115, 105, 56, 51, 6, 15, 19, 16, 2, 1, 7, 7, 10, 2, 0, 14, 4, 9, 3, 1, 0, 0, 8, 7, 11, 2, 9, 11, 3, 5, 3, 8, 4, 1, 3, 2, 9, 0, 1, 2, 20, 82, 77, 81, 53, 15, 2, 17, 51, 25, 7, 23, 69, 138, 122, 104, 119, 98, 119, 113, 120, 99, 116, 
+#> 85, 89, 89, 118, 65, 91, 73, 2, 0, 1, 0, 53, 56, 106, 108, 110, 89, 76, 80, 83, 47, 1, 3, 8, 19, 8, 9, 9, 12, 4, 11, 6, 10, 0, 0, 59, 118, 121, 10, 137, 144, 112, 129, 12, 47, 91, 71, 0, 12, 37, 73, 109, 99, 96, 99, 90, 116, 110, 94, 93, 71, 79, 69, 62, 26, 21, 1, 1, 80, 106, 53, 71, 93, 76, 81, 121, 89, 45, 0, 2, 82, 101, 116, 46, 116, 91, 69, 49, 38, 42, 54, 70, 21, 11, 5, 68, 47, 122, 74, 121, 121, 60, 34, 48, 28, 15, 35, 77, 79, 52, 72, 48, 84, 22, 4, 132, 151, 129, 108, 93, 122, 123, 81, 97, 
+#> 110, 58, 114, 72, 0, 5, 12, 12, 10, 0, 9, 12, 2, 1, 3, 8, 1, 3, 1, 1, 5, 7, 2, 12, 12, 5, 12, 10, 3, 0, 6, 3, 2, 1, 2, 60, 98, 113, 86, 68, 91, 78, 73, 82, 82, 79, 23, 20, 32, 26, 49, 47, 17, 2, 36, 66, 90, 75, 94, 111, 98, 41, 82, 96, 93, 78, 63, 12, 59, 67, 63, 82, 11, 32, 10, 54, 75, 102, 106, 109, 112, 101, 111, 91, 78, 65, 110, 55, 28, 93, 26, 78, 72, 67, 68, 111, 69, 82, 21, 23, 4, 4, 11, 8, 7, 7, 8, 4, 5, 1, 7, 6, 5, 0, 5, 5, 0, 3, 5, 6, 11, 4, 0, 7, 2, 2, 2, 0, 7, 7, 2, 6, 2, 0, 0, 3, 0, 
+#> 1, 1, 2, 11, 1, 0, 6, 1, 73, 89, 87, 64, 93, 42, 12, 58, 41, 1, 44, 56, 27, 9, 6, 4, 0, 0, 0, 0, 76, 103, 85, 104, 111, 67, 97, 70, 137, 110, 59, 4, 43, 37, 9, 6, 4, 68, 60, 93, 104, 63, 68, 68, 20, 3, 18, 5, 4, 10, 5, 5, 7, 2, 0, 0, 2, 1, 0, 0, 54, 108, 116, 143, 132, 139, 102, 106, 42, 0, 6, 8, 5, 12, 9, 2, 15, 14, 20, 10, 11, 13, 14, 11, 12, 12, 8, 10, 8, 4, 1, 2, 14, 31, 45, 28, 3, 27, 9, 7, 47, 57, 43, 30, 27, 58, 46, 29, 7, 12, 12, 23, 7, 0, 6, 8, 104, 64, 55, 89, 82, 58, 20, 60, 46, 23, 81, 
+#> 64, 17, 0, 0, 0, 6, 0, 6, 11, 9, 2, 9, 6, 0, 9, 3, 0, 5, 4, 0, 0, 4, 3, 0, 5, 0, 1, 2, 0, 0, 1, 2, 6, 1, 6, 6, 7, 9, 6, 3, 6, 5, 1, 0, 1, 5, 89, 99, 93, 77, 58, 56, 85, 68, 46, 24, 7, 14, 20, 43, 30, 42, 36, 42, 41, 60, 43, 50, 33, 32, 19, 37, 46, 19, 8, 0, 8, 16, 3, 30, 59, 79, 65, 58, 45, 6, 8, 5, 4, 10, 3, 4, 8, 2, 3, 0, 5, 0, 1, 0, 0, 86, 81, 86, 103, 85, 78, 14, 21, 31, 24, 83, 92, 112, 104, 88, 82, 35, 89, 96, 74, 59, 103, 111, 103, 91, 91, 114, 115, 93, 98, 78, 65, 106, 71, 2, 1, 6, 14, 7, 
+#> 11, 2, 9, 8, 1, 7, 7, 10, 5, 3, 6, 0, 0, 1, 3, 1, 1, 10, 2, 6, 1, 1, 0, 6, 9, 2, 4, 1, 4, 0, 1, 0, 0, 131, 134, 135, 141, 142, 125, 124, 150, 82, 109, 2, 17, 93, 77, 71, 96, 81, 32, 56, 2, 8, 27, 10, 36, 14, 12, 15, 10, 6, 16, 11, 6, 13, 11, 9, 11, 6, 3, 1, 0, 9, 4, 6, 4, 6, 8, 10, 3, 0, 5, 4, 5, 3, 3, 0, 25, 77, 88, 63, 33, 76, 95, 102, 78, 66, 78, 46, 4, 10, 6, 1, 41, 27, 21, 64, 68, 93, 56, 75, 36, 6, 1, 17, 110, 44, 24, 50, 65, 68, 20, 11, 104, 101, 145, 103, 119, 90, 92, 108, 108, 43, 4, 4, 
+#> 49, 0, 24, 59, 24, 56, 66, 73, 66, 8, 14, 16, 62, 39, 12, 15, 11, 0, 87, 102, 102, 106, 97, 26, 98, 36, 41, 17, 7, 6, 0, 2, 37, 78, 74, 83, 95, 116, 82, 36, 69, 68, 42, 3, 23, 17, 12, 0, 3, 32, 78, 54, 47, 49, 48, 46, 30, 69, 45, 21, 17, 8, 76, 73, 65, 56, 57, 58, 53, 27, 2, 1, 6, 3, 5, 14, 8, 7, 7, 0, 1, 2, 6, 0, 0, 1, 3, 3, 2, 7, 48, 85, 77, 72, 96, 55, 60, 106, 4, 45, 10, 8, 17, 52, 88, 106, 101, 106, 105, 92, 92, 89, 56, 24, 86, 50, 88, 56, 81, 75, 6, 23, 0, 3, 0, 7, 5, 0, 1, 2, 0, 2, 1, 8, 10, 
+#> 5, 7, 1, 1, 1, 6, 5, 5, 2, 0, 0, 0, 0, 10, 4, 6, 1, 1, 2, 6, 0, 2, 3, 2, 85, 33, 34, 117, 89, 75, 68, 17, 32, 12, 22, 7, 0, 0, 0, 5, 5, 6, 2, 2, 5, 0, 6, 4, 0, 0, 0, 59, 95, 96, 71, 100, 100, 100, 91, 92, 82, 48, 73, 64, 19, 49, 1, 37, 15, 24, 21, 0, 10, 34, 40, 49, 43, 69, 51, 53, 53, 84, 23, 50, 45, 46, 28, 22, 26, 5, 79, 71, 49, 72, 59, 59, 80, 0, 86, 84, 67, 83, 72, 47, 74, 47, 49, 91, 35, 2, 1, 8, 5, 6, 5, 3, 0, 1, 3, 1, 4, 5, 5, 6, 4, 4, 2, 0, 10, 10, 8, 5, 6, 7, 2, 6, 2, 3, 0, 4, 3, 0, 3, 
+#> 8, 3, 0, 0, 2, 10, 2, 5, 4, 6, 9, 0, 1, 9, 5, 5, 22, 94, 72, 83, 83, 62, 71, 3, 46, 0, 84, 75, 91, 90, 67, 74, 114, 113, 125, 62, 35, 14, 16, 31, 0, 10, 0, 4, 5, 4, 6, 7, 9, 5, 2, 5, 0, 3, 0, 5, 1, 2, 1, 0, 0, 6, 2, 1, 0, 0, 44, 50, 66, 38, 50, 63, 51, 57, 70, 61, 36, 16, 0, 17, 45, 32, 27, 32, 53, 31, 43, 5, 15, 22, 10, 6, 105, 115, 106, 124, 111, 112, 93, 10, 26, 43, 5, 17, 0, 72, 85, 66, 105, 91, 81, 90, 77, 71, 78, 16, 40, 4, 70, 51, 67, 59, 48, 44, 5, 52, 23, 0, 7, 4, 5, 9, 9, 18, 11, 7, 5, 
+#> 6, 2, 6, 6, 3, 1, 0, 0, 4, 11, 1, 2, 0, 12, 8, 4, 3, 1, 2, 0, 91, 53, 64, 59, 50, 17, 0, 0, 8, 87, 108, 112, 124, 113, 135, 128, 105, 124, 105, 127, 120, 97, 87, 82, 64, 37, 49, 46, 57, 34, 0, 0, 5, 14, 12, 9, 9, 10, 10, 4, 2, 5, 1, 3, 19, 58, 52, 56, 3, 29, 79, 40, 34, 14, 52, 3, 42, 33, 12, 21, 0, 11, 5, 7, 56, 71, 1, 2, 59, 73, 57, 64, 41, 64, 2, 1, 34, 125, 107, 75, 102, 90, 29, 0, 32, 10, 0, 0, 3, 3, 1, 4, 10, 9, 6, 5, 6, 8, 6, 4, 5, 1, 0, 0, 18, 88, 74, 75, 82, 85, 80, 50, 93, 99, 77, 94, 73, 
+#> 33, 24, 19, 37, 69, 87, 85, 43, 0, 0, 51, 59, 44, 0, 50, 37, 14, 38, 1, 7, 0, 0, 8, 4, 3, 3, 0, 2, 1, 0, 22, 70, 75, 87, 74, 71, 78, 95, 95, 79, 94, 91, 103, 60, 1, 68, 2, 1, 12, 3, 105, 84, 27, 30, 75, 88, 57, 83, 77, 102, 80, 77, 39, 26, 6, 20, 78, 37, 78, 88, 77, 37, 5, 64, 67, 76, 58, 59, 49, 68, 77, 62, 42, 14, 26, 8, 0, 5, 5, 50, 0, 4, 10, 0, 31, 32, 24, 26, 13, 16, 12, 11, 4, 1, 0, 1, 2, 2, 11, 8, 4, 1, 3, 2, 1, 2, 2, 0, 0, 6, 10, 3, 0, 0, 4, 4, 6, 2, 2, 0, 0, 12, 31, 8, 41, 82, 16, 15, 30, 
+#> 66, 98, 3, 80, 63, 82, 5, 85, 55, 43, 29, 4, 34, 46, 59, 93, 106, 94, 89, 56, 41, 46, 49, 24, 7, 3, 21, 1, 1, 51, 69, 95, 84, 76, 108, 34, 0, 7, 47, 64, 18, 68, 82, 79, 95, 42, 26, 76, 70, 61, 29, 15, 31, 17, 17, 0, 4, 8, 1, 2, 5, 4, 8, 8, 4, 3, 1, 4, 2, 5, 5, 5, 9, 5, 4, 2, 1, 0, 1, 0, 56, 75, 93, 125, 80, 90, 85, 47, 44, 1, 2, 0, 1, 0, 0, 2, 5, 1, 1, 1, 6, 0, 0, 1, 3, 11, 6, 4, 3, 4, 1, 0, 10, 75, 22, 38, 126, 0, 39, 11, 19, 2, 49, 76, 71, 21, 66, 35, 23, 0, 73, 76, 89, 88, 77, 78, 72, 8, 47, 69, 
+#> 71, 101, 90, 74, 67, 36, 49, 8, 0, 1, 51, 50, 67, 3, 75, 47, 97, 114, 92, 41, 11, 68, 15, 25, 44, 45, 7, 28, 0, 19, 32, 23, 47, 38, 37, 9, 3, 0, 42, 97, 95, 57, 69, 91, 50, 51, 79, 116, 53, 23, 37, 1, 0, 2, 3, 2, 5, 6, 10, 7, 3, 1, 4, 2, 1, 6, 0, 1, 1, 92, 32, 4, 128, 98, 97, 49, 90, 115, 88, 13, 5, 4, 41, 39, 20, 38, 25, 10, 30, 28, 26, 10, 21, 9, 7, 0, 70, 71, 86, 92, 92, 76, 90, 79, 73, 82, 80, 61, 22, 10, 1, 0, 6, 13, 11, 10, 9, 4, 3, 4, 8, 1, 0, 0, 58, 76, 87, 79, 81, 96, 132, 97, 94, 94, 108, 
+#> 98, 99, 85, 33, 21, 81, 117, 110, 85, 75, 127, 126, 131, 113, 81, 0, 5, 100, 101, 78, 93, 86, 53, 83, 69, 47, 84, 33, 3, 41, 70, 59, 116, 92, 97, 80, 88, 84, 93, 74, 60, 64, 46, 62, 25, 20, 1, 0, 6, 2, 1, 1, 7, 6, 8, 5, 8, 6, 3, 3, 39, 109, 64, 57, 106, 77, 92, 109, 138, 90, 20, 24, 53, 36, 24, 16, 6, 19, 7, 1, 5, 0, 0, 2, 5, 3, 3, 7, 10, 1, 0, 0, 0, 63, 118, 104, 116, 112, 124, 90, 73, 27, 88, 56, 0, 1, 3, 8, 3, 5, 3, 6, 0, 0, 3, 2, 1, 0, 1, 3, 6, 10, 11, 7, 8, 10, 6, 4, 7, 8, 3, 10, 11, 10, 13, 
+#> 3, 7, 2, 0, 1, 41, 63, 102, 72, 81, 38, 65, 5, 52, 51, 7, 6, 125, 108, 122, 99, 106, 104, 109, 62, 51, 61, 70, 81, 81, 83, 63, 82, 73, 30, 9, 23, 7, 15, 16, 37, 46, 28, 24, 20, 22, 1, 54, 42, 33, 8, 4, 0, 0, 9, 11, 20, 17, 21, 11, 14, 12, 11, 11, 8, 2, 1, 1, 5, 10, 7, 6, 5, 4, 4, 3, 0, 0, 14, 11, 17, 14, 27, 33, 55, 52, 54, 43, 13, 16, 38, 24, 9, 1, 1, 3, 3, 3, 4, 3, 1, 0, 0, 0, 1, 0, 0, 6, 5, 1, 0, 0, 85, 74, 79, 114, 92, 126, 98, 77, 19, 54, 80, 54, 7, 60, 16, 29, 3, 5, 5, 1, 3, 2, 1, 0, 0, 4, 
+#> 47, 37, 31, 47, 73, 21, 48, 59, 22, 21, 10, 53, 35, 1, 6, 9, 7, 12, 4, 7, 1, 1, 4, 60, 49, 96, 99, 86, 46, 22, 61, 5, 33, 30, 65, 84, 5, 38, 45, 33, 0, 7, 0, 3, 0, 9, 48, 94, 98, 118, 87, 101, 106, 75, 86, 94, 68, 57, 22, 25, 15, 2, 4, 4, 50, 64, 57, 100, 87, 78, 96, 69, 67, 38, 19, 2, 32, 65, 70, 90, 73, 103, 43, 81, 39, 31, 8, 8, 11, 6, 18, 13, 8, 9, 2, 10, 0, 1, 84, 46, 10, 3, 37, 75, 74, 92, 99, 85, 55, 87, 76, 61, 46, 7, 5, 3, 1, 4, 8, 11, 5, 1, 0, 3, 0, 1, 0, 0, 0, 65, 79, 53, 78, 65, 110, 
+#> 125, 87, 89, 54, 47, 19, 6, 54, 69, 48, 6, 1, 39, 12, 15, 23, 3, 101, 37, 13, 56, 61, 27, 55, 42, 24, 3, 18, 17, 4, 16, 1, 0, 0, 2, 2, 8, 5, 2, 3, 4, 6, 5, 0, 0, 0, 2, 0, 1, 0, 0, 0, 1, 3, 0, 0, 0, 0, 0, 29, 61, 55, 95, 99, 93, 52, 82, 56, 83, 66, 61, 54, 8, 1, 6, 22, 100, 109, 96, 80, 132, 120, 126, 112, 91, 45, 59, 38, 35, 28, 44, 16, 6, 4, 2, 6, 5, 7, 5, 1, 1, 6, 3, 0, 1, 42, 83, 78, 61, 74, 90, 83, 57, 42, 59, 18, 4, 10, 0, 100, 101, 79, 0, 3, 83, 106, 110, 84, 104, 92, 94, 91, 89, 57, 41, 1, 
+#> 5, 72, 65, 82, 66, 79, 79, 87, 69, 44, 54, 59, 17, 119, 123, 101, 112, 121, 125, 107, 129, 130, 115, 121, 118, 99, 83, 84, 64, 94, 82, 27, 8, 24, 0, 3, 9, 5, 6, 3, 0, 1, 1, 0, 0, 0, 1, 0, 0, 4, 3, 2, 1, 4, 5, 8, 3, 2, 4, 1, 2, 4, 11, 13, 6, 2, 5, 2, 6, 1, 4, 1, 3, 0, 0, 0, 0, 0, 0, 4, 4, 18, 78, 59, 22, 85, 77, 89, 61, 98, 29, 11, 46, 27, 1, 0, 4, 9, 1, 0, 2, 0, 0, 1, 1, 0, 0, 3, 0, 0, 61, 94, 105, 129, 121, 132, 121, 127, 104, 119, 132, 96, 40, 92, 44, 40, 63, 57, 1, 2, 1, 8, 3, 14, 11, 12, 8, 5, 
+#> 12, 6, 6, 1, 3, 7, 3, 1, 1, 1, 1, 6, 96, 65, 63, 26, 0, 10, 10, 32, 72, 8, 76, 33, 12, 56, 37, 34, 44, 1, 1, 0, 3, 100, 82, 101, 115, 76, 61, 64, 2, 94, 81, 101, 96, 74, 73, 99, 65, 60, 73, 61, 42, 11, 4, 0, 15, 125, 107, 110, 102, 89, 81, 91, 96, 74, 83, 77, 44, 54, 30, 89, 94, 91, 64, 102, 81, 88, 91, 107, 98, 68, 39, 22, 56, 35, 47, 0, 21, 9, 21, 0, 4, 0, 0, 0, 3, 5, 8, 3, 3, 4, 2, 0, 1, 1, 0, 0, 34, 18, 31, 22, 20, 20, 1, 3, 2, 2, 1, 2, 0, 2, 0, 0, 0, 0, 106, 86, 86, 86, 36, 93, 74, 79, 36, 41, 
+#> 8, 6, 1, 49, 63, 76, 74, 62, 97, 104, 116, 91, 12, 29, 11, 11, 20, 32, 3, 39, 76, 102, 85, 112, 83, 74, 60, 54, 1, 7, 29, 0, 0, 1, 7, 6, 8, 7, 8, 9, 4, 2, 4, 0, 1, 1, 0, NA, 0, 0, 0, 0, 0, 5, 7, 9, 6, 5, 4, 3, 3, 6, 6, 0, 1, 5, 0, 1, 0, 5, 11, 1, 1, 1, 2, 0, 0, 58, 67, 10, 59, 75, 67, 60, 81, 82, 58, 59, 58, 1, 2, 0, 42, 45, 93, 76, 92, 111, 100, 109, 110, 82, 84, 85, 67, 79, 54, 45, 3, 80, 110, 96, 108, 103, 109, 97, 118, 108, 103, 106, 82, 83, 77, 72, 14, 39, 4, 9, 42, 121, 96, 83, 84, 86, 77, 
+#> 116, 78, 89, 77, 72, 85, 94, 49, 74, 64, 69, 46, 40, 71, 2, 10, 7, 9, 9, 4, 10, 6, 4, 11, 5, 5, 5, 4, 0, 0, 3, 70, 98, 82, 113, 119, 97, 94, 75, 87, 41, 67, 79, 52, 68, 71, 60, 25, 4, 11, 6, 4, 10, 6, 9, 8, 3, 2, 2, 3, 1, 0, 0, 0, 0, 0, 69, 82, 76, 98, 86, 90, 72, 73, 93, 67, 97, 55, 55, 77, 86, 56, 47, 56, 122, 97, 90, 106, 86, 117, 134, 79, 103, 109, 122, 83, 69, 111, 88, 82, 41, 85, 75, 6, 19, 5, 78, 91, 79, 101, 86, 95, 109, 92, 86, 100, 71, 62, 17, 17, 0, 20, 0, 58, 105, 106, 118, 109, 116, 
+#> 102, 115, 127, 121, 103, 109, 117, 113, 84, 100, 103, 95, 75, 84, 47, 45, 22, 0, 5, 7, 10, 10, 11, 4, 4, 5, 6, 7, 10, 3, 4, 3, 3, 2, 0, 0, 0, 1, 4, 3, 10, 9, 11, 11, 14, 11, 10, 6, 2, 0, 6, 0, 0, 3, 0, 0, 2, 15, 82, 76, 90, 60, 74, 74, 66, 62, 40, 6, 7, 4, 0, 28, 55, 44, 35, 46, 31, 67, 55, 33, 53, 63, 43, 38, 17, 4, 2, 109, 3, 96, 104, 119, 79, 106, 96, 94, 92, 89, 91, 14, 38, 4, 0, 0, 21, 60, 51, 86, 50, 51, 50, 48, 38, 42, 42, 66, 35, 1, 30, 44, 24, 56, 66, 67, 77, 84, 28, 72, 46, 26, 0, 3, 3, 
+#> 6, 8, 13, 5, 9, 3, 0, 0, 1, 0, 0, 0, 4, 10, 7, 7, 2, 6, 9, 4, 4, 6, 10, 8, 0, 0, 3, 1, 1, 33, 35, 33, 45, 59, 29, 64, 63, 75, 63, 38, 38, 9, 13, 22, 0, 2, 8, 7, 5, 4, 8, 3, 4, 1, 0, 0, 2, 36, 91, 77, 48, 63, 35, 102, 69, 64, 80, 65, 17, 6, 1, 11, 46, 53, 72, 91, 56, 64, 86, 45, 73, 35, 55, 16, 4, 28, 76, 77, 68, 91, 103, 55, 42, 70, 81, 38, 4, 13, 9, 28, 10, 14, 0, 27, 79, 52, 69, 68, 114, 80, 92, 44, 29, 2, 6, 0, 30, 59, 69, 50, 58, 71, 55, 43, 66, 52, 56, 62, 36, 13, 29, 17, 3, 21, 21, 55, 60, 
+#> 61, 37, 45, 50, 65, 81, 3, 35, 18, 12, 11, 10, 3, 21, 16, 10, 6, 1, 6, 11, 3, 7, 2, 9, 0, 0, 0, 13, 30, 3, 80, 87, 92, 95, 80, 82, 83, 101, 64, 63, 22, 9, 17, 92, 115, 92, 34, 41, 0, 88, 92, 81, 105, 105, 100, 75, 1, 5, 65, 91, 71, 74, 87, 31, 6, 0, 51, 3, 21, 1, 68, 81, 72, 69, 72, 89, 41, 54, 7, 58, 69, 34, 19, 20, 7, 3, 7, 0, 1, 2, 4, 6, 3, 7, 5, 3, 4, 5, 6, 3, 2, 2, 2, 0, 1, 0, 3, 1, 2, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 4, 6, 4, 4, 6, 9, 3, 12, 8, 5, 11, 10, 8, 5, 4, 7, 11, 8, 4, 5, 1, 22, 62, 87, 
+#> 103, 60, 40, 59, 2, 26, 45, 9, 7, 63, 73, 93, 76, 49, 66, 35, 16, 7, 1, 1, 83, 79, 83, 102, 99, 90, 71, 34, 73, 63, 18, 15, 32, 37, 59, 41, 103, 55, 93, 85, 73, 81, 101, 98, 45, 30, 52, 53, 43, 0, 20, 54, 32, 34, 8, 0, 0, 2, 3, 2, 2, 3, 3, 0, 1, 0, 0, 0, 5, 10, 8, 3, 3, 11, 6, 10, 0, 6, 2, 9, 9, 11, 3, 0, 5, 13, 31, 29, 74, 89, 77, 67, 82, 81, 91, 88, 65, 73, 84, 67, 48, 53, 46, 50, 16, 3, 1, 1, 12, 24, 9, 49, 70, 58, 64, 33, 36, 30, 6, 38, 72, 78, 89, 87, 82, 56, 30, 46, 23, 1, 4, 19, 61, 26, 61, 
+#> 69, 98, 132, 92, 53, 86, 22, 37, 64, 25, 63, 5, 77, 81, 89, 93, 106, 92, 82, 85, 29, 34, 7, 38, 45, 40, 58, 67, 74, 85, 71, 76, 85, 70, 55, 58, 3, 4, 1, 0, 72, 51, 12, 55, 85, 61, 3, 35, 7, 28, 15, 13, 6, 2, 3, 2, 54, 36, 80, 58, 60, 53, 52, 71, 79, 111, 90, 60, 1, 28, 26, 37, 46, 78, 54, 61, 39, 63, 76, 63, 19, 19, 28, 63, 27, 8, 0, 3, 7, 3, 5, 6, 2, 1, 0, 2, 1, 2, 2, 6, 2, 0, 1, 3, 2, 0, 2, 2, 1, 0, 1, 0, 1, 7, 0, 2, 0, 1, 1, 1, 0, 0, 1, 0, 1, 0, 1, 2, 0, 1, 0, NA, 0, 2, 4, 3, 0, 0, 0, 0, 2, 1, 
+#> 36, 18, 53, 45, 80, 99, 72, 90, 76, 71, 0, 4, 14, 4, 6, 7, 11, 13, 3, 2, 0, 0, 1, 0, 3, 6, 52, 39, 22, 59, 45, 50, 42, 42, 47, 37, 31, 33, 7, 48, 66, 42, 69, 60, 89, 100, 95, 77, 95, 91, 105, 103, 74, 87, 65, 82, 68, 20, 131, 107, 101, 107, 96, 99, 97, 70, 90, 60, 58, 74, 60, 56, 56, 46, 38, 27, 75, 105, 130, 83, 81, 92, 60, 92, 76, 57, 23, 77, 73, 16, 5, 5, 3, 1, 1, 0, 1, 0, 0, 4, 75, 94, 87, 100, 115, 100, 92, 91, 103, 137, 86, 95, 72, 55, 68, 36, 2, 16, 64, 119, 94, 67, 63, 79, 98, 64, 50, 81, 
+#> 58, 72, 51, 51, 17, 3, 55, 66, 80, 90, 67, 129, 90, 91, 89, 92, 68, 20, 10, 8, 13, 4, 21, 49, 31, 41, 67, 4, 28, 29, 28, 41, 33, 37, 38, 20, 1, 9, 2, 0, 2, 0, 0, 0, 0, 0, 0, 2, 3, 7, 0, 0, 3, 0, 2, 2, 0, 1, 0, 0, 2, 0, 0, 0, 4, 1, 7, 0, 2, 4, 1, 1, 2, 2, 1, 0, 1, 2, 0, 0, 31, 20, 12, 74, 96, 73, 94, 91, 70, 56, 14, 5, 0, 0, 1, 0, 3, 0, 0, 1, 3, 6, 2, 2, 2, 2, 0, 0, 4, 7, 9, 9, 3, 9, 9, 5, 10, 18, 6, 2, 4, 1, 0, 0, 10, 9, 2, 11, 6, 12, 7, 7, 8, 17, 6, 3, NA, 1, 0, NA, 4, 4, 4, NA, 0, NA, 4, 2, 0, 
+#> 0, 4, 90, 54, 70, 65, 43, 64, 83, 40, 24, 29, 42, 42, 27, 20, 3, 1, 94, 91, 75, 94, 76, 45, 60, 46, 13, 1, 1, 0, 0, 10, 10, 8, 5, 4, 3, 6, 8, 4, 7, 0, 0, 43, 60, 120, 69, 70, 3, 27, 72, 30, 2, 52, 4, 24, 17, 26, 9, 3, 53, 67, 43, 16, 1, 2, 1, 0, 3, 9, 8, 6, 6, 9, 3, 3, 3, 0, 0, 0, 2, 4, 0, 0, 0, 0, 0, 0, 1, 1, 2, 1, 0, 0, 3, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 3, 1, 3, 1, 3, 3, 4, 5, 71, 99, 91, 77, 78, 81, 112, 90, 96, 125, 75, 70, 82, 93, 91, 71, 99, 70, 69, 49, 36, 53, 38, 4, 2, 65, 69, 
+#> 74, 94, 126, 73, 63, 29, 21, 9, 21, 14, 47, 46, 47, 47, 24, 10, 14, 52, 46, 18, 33, 24, 8, 0, 2, 50, 24, 37, 53, 99, 112, 97, 90, 64, 68, 71, 80, 4, 1, 30, 29, 28, 31, 8, 27, 5, 23, 40, 25, 2, 0, 0, 1, 0, 12, 9, 2, 12, 10, 10, 9, 12, 7, 2, 101, 64, 117, 97, 86, 94, 120, 120, 86, 107, 115, 110, 112, 130, 95, 103, 90, 95, 73, 80, 52, 9, 34, 60, 15, 14, 79, 71, 51, 85, 45, 41, 49, 38, 44, 50, 23, 0, 16, 3, 3, 13, 6, 4, 2, 10, 5, 8, 3, 5, 4, 3, 4, NA, 0, 10, 12, 36, 74, 107, 96, 101, 93, 93, 62, 46, 
+#> 66, 65, 27, 28, 10, 1, 4, 4, 11, 12, 8, 14, 11, 7, 3, 11, 14, 5, 12, 8, 6, 1, 0, 1, 5, 3, 3, 1, 2, 0, 1, 1, 0, 0, 44, 64, 67, 42, 47, 34, 15, 10, 15, 29, 48, 59, 5, 9, 0, 3, 15, 2, 1, 44, 84, 44, 79, 94, 88, 93, 107, 86, 97, 83, 77, 68, 65, 29, 8, 25, 34, 24, 25, 31, 26, 0, 31, 3, 4, 3, 0, 109, 107, 99, 76, 54, 97, 96, 73, 1, 63, 43, 46, 3, 6, 125, 93, 112, 89, 87, 79, 88, 82, 90, 39, 84, 54, 52, 19, 38, 64, 48, 83, 52, 81, 73, 53, 4, 7, 3, 1, 12, 10, 4, 2, 98, 84, 94, 85, 88, 95, 78, 89, 105, 40, 
+#> 106, 96, 61, 53, 29, 28, 25, 7, 15, 83, 86, 66, 78, 75, 77, 78, 95, 31, 31, 7, 25, 31, 25, 17, 10, 4, 3, 64, 59, 21, 63, 44, 79, 72, 70, 89, 56, 61, 66, 1, 0, 40, 23, 57, 87, 68, 83, 67, 45, 72, 89, 97, 71, 67, 59, 33, 36, 2, 2, 4, 4, 1, 2, 3, 0, 5, 0, 0, 0, 0, 1, 37, 69, 45, 47, 66, 73, 61, 44, 57, 51, 33, 58, 42, 22, 13, 23, 77, 42, 61, 65, 59, 30, 45, 67, 67, 59, 25, 9, 5, 15, 72, 73, 69, 50, 66, 34, 4, 15, 1, 10, 57, 69, 51, 23, 29, 33, 40, 11, 20, 44, 29, 49, 59, 24, 15, 2, 0, 88, 61, 81, 52, 
+#> 54, 15, 4, 1, 1, 21, 7, 2, 4, 5, 8, 8, 4, 11, 3, 8, 13, 5, 6, 1, 1, 1, 0, 0, 1, 1, 2, 8, 8, 5, 4, 9, 8, 6, 3, NA, 1, 0, 31, 1, 1, 63, 92, 75, 39, 29, 51, 66, 74, 19, 61, 3, 0, 14, 16, 2, 66, 3, 1, 34, 53, 68, 84, 54, 57, 89, 70, 104, 75, 106, 90, 71, 54, 29, 60, 60, 28, 2, 6, 0, 1, 0, 2, 2, 0, 3, 0, 0, 1, 0, 0, 1, 0, 1, 0, NA, 0, 1, 1, 3, 1, 1, 0, 1, 0, 0, 0, 2, 1, 0, 1, 0, 0, 0, 42, 47, 54, 51, 48, 5, 34, 34, 14, 8, 0, 3, 0, 2, 98, 73, 30, 97, 107, 58, 52, 30, 8, 3, 30, 47, 88, 59, 48, 28, 46, 38, 
+#> 30, 25, 0, 4, 72, 40, 35, 38, 42, 40, 45, 44, 32, 7, 10, 5, 0, 0, 44, 67, 74, 54, 78, 53, 60, 83, 82, 59, 53, 52, 37, 64, 29, 0, 2, 45, 47, 19, 26, 25, 19, 8, 18, 5, 0, 3, 8, 5, 19, 13, 7, 13, 8, 9, 6, 2, 2, 21, 38, 48, 59, 96, 75, 60, 80, 122, 76, 72, 54, 70, 52, 0, 33, 4, 25, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 4, 4, 5, 3, 1, 2, 0, 3, 0, 0, 1, 0, 0, 0, 1, 40, 25, 78, 93, 103, 107, 72, 64, 73, 81, 74, 77, 71, 63, 58, 73, 35, 18, 18, 9, 25, 14, 1, 73, 79, 30, 81, 107, 94, 113, 92, 97, 
+#> 114, 126, 81, 110, 105, 78, 73, 69, 31, 56, 4, 5, 7, 4, 1, 2, 2, 1, 2, 3, 2, 5, 1, 2, 0, 0, 1, 4, 3, 4, 3, 3, 5, 0, 2, 5, 8, 4, 6, 1, 5, 0, 73, 74, 23, 63, 50, 72, 71, 98, 74, 86, 73, 103, 51, 18, 19, 9, 0, 49, 35, 72, 48, 102, 79, 75, 47, 73, 77, 51, 29, 20, 10, 7, 0, 2, 29, 80, 67, 56, 42, 76, 84, 69, 45, 1, 0, 50, 68, 41, 67, 13, 1, 23, 35, 2, 7, 3, 0, 66, 46, 79, 27, 88, 61, 98, 86, 89, 97, 128, 85, 78, 74, 57, 88, 66, 42, 69, 5, 5, 7, 9, 8, 5, 9, 3, 7, 5, 10, 1, 5, 3, 5, 3, 3, 6, 0, 0, NA, NA, 
+#> 3, 3, 5, 39, 53, 48, 50, 68, 35, 46, 16, 51, 19, 14, 30, 3, 13, 1, 6, 26, 28, 18, 13, 2, 31, 19, 90, 62, 102, 85, 113, 82, 38, 117, 90, 104, 80, 75, 10, 7, 0, 6, 0, 5, 4, 6, 4, 13, 8, 2, 1, NA, NA, NA, 0, 0, NA, NA, 2, 3, 0, 0, 0, 3, 9, 3, 12, 4, 5, 6, 4, 9, 3, NA, NA, NA, 5, 0, 0, 1, 2, 2, 10, 3, 7, 5, 2, 0, 0, 0, 1, 78, 78, 87, 109, 85, 75, 79, 79, 67, 35, 20, 104, 82, 41, 47, 5, 51, 3, 14, 28, 38, 88, 73, 83, 43, 45, 81, 40, 26, 34, 30, 15, 73, 73, 91, 98, 69, 99, 80, 51, 38, 11, 2, 7, 67, 83, 
+#> 97, 80, 87, 83, 108, 83, 62, 67, 52, 73, 52, 14, 44, 32, 20, 12, 4, 10, 25, 37, 51, 27, 35, 31, 2, 22, 0, 19, 3, 3, 1, 0, 4, 1, 3, 6, 5, 0, NA, 0, 0, 0, 0, NA, 0, 2, 1, 0, NA, 0, 16, 15, 61, 24, 25, 9, 23, 10, 79, 6, 83, 3, 20, 6, 6, 69, 72, 47, 68, 66, 53, 64, 44, 42, 32, 62, 40, 0, 55, 15, 11, 12, 77, 32, 0, 1, 4, 1, 6, 1, 10, 4, 14, 3, 4, NA, NA, 1, 1, 19, 50, 61, 63, 109, 100, 77, 77, 52, 83, 77, 55, 12, 14, 35, 14, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 1, 8, NA, 0, 0, NA, NA, NA, 2, 41, 36, 29, 20, 
+#> 9, 15, 20, 20, 3, 0, 0, 0, 4, 6, 3, 6, 6, 7, 5, NA, NA, NA, NA, NA, 5, 47, 62, 50, 52, 68, 67, 31, 84, 56, 0, 23, 5, 14, 1, 2, 19, 40, 76, 53, 67, 36, 60, 54, 44, 66, 39, 39, 28, 37, 9, 6, 20, 13, 49, 98, 100, 65, 46, 82, 50, 81, 55, 40, 3, 15, 0, 4, 54, 61, 85, 59, 43, 69, 59, 63, 19, 57, 44, 10, 0, 1, 43, 54, 43, 65, 53, 71, 7, 36, 47, 67, 49, 39, 16, 33, 19, 8, 69, 40, 53, 53, 69, 68, 56, 18, 64, 38, 12, 36, 1, 13, 82, 123, 57, 87, 72, 99, 90, 91, 84, 93, 82, 78, 94, 33, 92, 43, 67, 64, 65, 42, 
+#> 0, 38, 58, 53, 41, 92, 82, 82, 62, 44, 53, 31, 17, 0, 0, 5, 6, 5, 4, 5, 6, 6, 7, 8, 5, 7, 7, 9, 7, 5, 8, 9, 8, 2, NA, 3, 1, NA, NA, NA, 1, 38, 28, 4, 28, 37, 86, 87, 59, 105, 97, 85, 11, 46, 59, 1, 8, 1, 2, 74, 46, 63, 92, 71, 63, 39, 48, 62, 2, 2, 2, 0, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, NA, 0, NA, 0, 0, 7, 39, 65, 53, 89, 80, 46, 63, 14, 31, 65, 29, 13, 5, 7, 4, 8, 0, 5, 0, 3, 5, 2, 4, 8, 9, 10, 3, NA, NA, NA, 0, 2, 39, 61, 50, 13, 10, 35, 36, 50, 53, 56, 12, 60, 38, 6, 14, 6, 
+#> 0, 0, 11, 62, 53, 42, 37, 20, 14, 26, 25, 3, 6, 2, 2, 4, 51, 50, 49, 49, 25, 45, 29, 41, 48, 21, 6, 24, 42, 62, 90, 51, 70, 79, 61, 41, 45, 19, 47, 69, 82, 77, 59, 57, 89, 23, 8, 6, 59, 71, 54, 80, 64, 83, 79, 85, 73, 42, 0, 6, 7, 5, 7, 8, 9, 2, 0, 1, 1, 2, 5, 2, 5, 5, 3, 5, 1, 3, NA, 1, NA, 0, 1, 2, 4, 1, 6, 7, 0, 0, NA, NA, NA, 8, 10, 35, 28, 104, 112, 88, 42, 45, 58, 32, 1, 7, 2, 1, 1, 6, 4, 0, 0, NA, NA, 0, 8, 7, 3, 4, NA, NA, 0, 3, 6, 6, 91, 80, 75, 89, 87, 87, 93, 85, 74, 100, 56, 49, 73, 35, 
+#> 6, 55, 120, 134, 110, 118, 131, 97, 93, 48, 103, 8, 85, 93, 37, 26, 12, 56, 103, 60, 91, 52, 74, 65, 86, 66, 92, 84, 81, 82, 86, 41, 16, 61, 9, 3, 20, 59, 38, 42, 72, 55, 54, 35, 48, 5, 34, 25, 16, 7, 26, 49, 51, 70, 8, 38, 66, 79, 90, 81, 61, 83, 44, 57, 59, 47, 16, 13, 0, 4, 64, 72, 58, 47, 42, 18, 17, 39, 9, 18, 58, 78, 77, 60, 53, 35, 36, 2, 56, 49, 78, 52, 34, 11, 8, 2, 3, 82, 95, 94, 102, 83, 69, 80, 73, 90, 66, 22, 42, 41, 14, 12, 2, 10, 27, 60, 81, 40, 59, 30, 24, 16, 23, 16, 7, 0, 2, 11, 
+#> 2, 5, 13, 7, 12, NA, NA, NA, NA, NA, NA, NA, 0, NA, NA, NA, NA, 1, 14, 54, 78, 85, 78, 85, 87, 65, 59, 67, 61, 75, 56, 59, 20, 3, 12, 6, 62, 63, 60, 55, 64, 77, 60, 52, 42, 15, 8, 2, 0, 2, 0, 0, 3, 1, 0, NA, NA, NA, NA, 0, NA, 0, 3, 1, 2, 5, 8, 4, 1, 1, 1, 0, 1, 0, 2, 0, 0, 0, 5, 4, 100, 60, 73, 6, 94, 102, 87, 122, 116, 107, 107, 113, 113, 68, 70, 66, 47, 68, 72, 50, 1, 19, 26, 22, 83, 71, 83, 64, 66, 60, 61, 46, 26, 18, 7, 0, 1, 0, 4, 4, 2, 3, 5, 7, 5, 5, NA, NA, 0, NA, NA, NA, 5, 2, NA, NA, 5, 
+#> NA, NA, 0, 2, 51, 43, 43, 35, 21, 14, 0, 0, 7, 74, 65, 36, 47, 76, 106, 94, 49, 73, 44, 66, 85, 54, 85, 42, 68, 37, 47, 65, 42, 12, 2, 0, 8, 44, 54, 35, 42, 21, 12, 71, 63, 40, 42, 55, 55, 2, 6, 0, 46, 85, 103, 86, 95, 93, 89, 92, 31, 57, 71, 42, 52, 40, 59, 24, 14, 5, 50, 74, 67, 42, 97, 79, 71, 93, 78, 74, 57, 34, 50, 73, 33, 13, 2, 1, 6, 5, 3, 6, 10, 1, NA, NA, NA, NA, NA, NA, 4, 10, 10, 40, 62, 94, 53, 73, 66, 54, 48, 58, 35, 42, 14, 21, 1, 8, 3, 13, 5, 60, 28, 5, 1, 7, 0, 74, 74, 58, 55, 60, 
+#> 51, 58, 1, 47, 31, 35, 33, 41, 31, 2, 1, 9, 16, 21, 39, 26, 7, 1, 0, 0, 2, 1, 2, NA, 0, NA, 0, 0, NA, 0, 0, NA, 2, NA, 0, 0, 0, 2, 0, 0, 2, 6, 1, 0, 2, 2, 1, 1, NA, NA, 0, 0, 27, 67, 82, 85, 87, 71, 97, 80, 85, 89, 77, 69, 67, 77, 30, 27, 2, 32, 11, 19, 11, 7, 66, 82, 92, 81, 93, 24, 68, 78, 60, 56, 74, 65, 60, 74, 42, 0, 15, 16, 48, 49, 45, 58, 36, 3, 18, 20, 21, 43, 8, 16, 5, 5, 4, 5, 14, 0, 64, 84, 67, 66, 54, 37, 24, 11, 17, 24, 5, 0, 0, 0, 1, 1, 0, 0, NA, NA, NA, 0, NA, NA, NA, NA, 5, 73, 35, 
+#> 47, 71, 74, 21, 80, 118, 61, 77, 63, 47, 6, 11, 74, 87, 67, 79, 89, 75, 97, 79, 62, 89, 66, 101, 45, 49, 3, 10, 0, 0, 23, 16, 65, 87, 63, 95, 76, 73, 51, 61, 62, 34, 20, 7, 1, 11, 67, 106, 93, 75, 64, 97, 84, 64, 75, 65, 85, 57, 28, 10, 0, 2, 4, 4, 5, 6, 4, 6, 0, 0, 0, NA, NA, NA, 2, NA, 2, 3, 4, 42, 67, 114, 99, 82, 11, 42, 64, 82, 68, 69, 51, 64, 94, 60, 81, 78, 90, 48, 31, 0, 3, 0, 7, 5, 11, 1, 0, 35, 30, 29, 47, 55, 61, 24, 53, 84, 72, 72, 38, 20, 64, 47, 25, 19, 21, 2, 2, 0, 0, 3, 0, 1, 2, 0, 
+#> 0, 1, 0, NA, 0, 0, 0, 0, 0, 8, 27, 36, 37, 95, 85, 85, 91, 89, 92, 78, 63, 66, 76, 72, 80, 58, 5, 5, 48, 64, 58, 26, 19, 61, 34, 58, 1, 33, 20, 3, 5, 9, 9, 5, 10, 14, 5, 0, 0, NA, 0, NA, NA, NA, 8, 5, 13, 32, 35, 73, 69, 59, 54, 28, 38, 16, 14, 14, 2, 1, 5, 4, 8, 2, 3, 12, 8, 3, 2, NA, 1, 38, 24, 40, 39, 70, 62, 74, 59, 75, 91, 72, 57, 48, 54, 46, 59, 42, 32, 11, 25, 10, 54, 29, 25, 25, 9, 12, 1, 20, 4, 71, 84, 81, 71, 91, 72, 49, 35, 32, 42, 43, 5, 19, 57, 82, 80, 98, 63, 60, 15, 86, 43, 67, 57, 
+#> 44, 31, 8, 81, 70, 40, 55, 21, 68, 82, 68, 26, 8, 21, 2, 43, 108, 93, 112, 114, 93, 109, 104, 78, 108, 104, 93, 89, 97, 88, 52, 19, 3, 3, 7, 6, 8, 5, 2, NA, NA, 2, 4, 44, 75, 69, 91, 78, 68, 69, 48, 42, 61, 30, 1, 1, 0, 0, NA, NA, 2, 1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 2, 1, 4, 2, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, NA, NA, 16, 65, 77, 68, 70, 76, 48, 37, 62, 35, 92, 68, 38, 20, 49, 38, 56, 5, 3, 2, 0, 9, 4, 8, 7, 0, 3, NA, 0, 0, 0, NA, NA, NA, NA, 0, NA, 5, 103, 76, 81, 75, 116, 67, 28, 89, 56, 84, 59, 67, 
+#> 49, 37, 9, 44, 18, 5, 40, 48, 43, 40, 58, 41, 42, 39, 10, 0, 62, 81, 74, 50, 4, 75, 85, 62, 70, 59, 37, 39, 27, 29, 22, 1, 1, 5, 5, 4, 3, 5, 0, 10, 1, 1, 1, 5, 4, 3, 1, 2, 3, 1, 1, 2, NA, 1, NA, NA, NA, 0, 13, 27, 81, 78, 65, 65, 74, 71, 88, 99, 81, 71, 52, 46, 47, 56, 56, 66, 36, 16, 5, 6, 92, 75, 104, 121, 117, 81, 51, 86, 90, 98, 85, 98, 66, 57, 22, 4, 45, 47, 64, 79, 81, 64, 90, 56, 99, 100, 64, 100, 81, 40, 65, 36, 2, 4, 7, 6, 2, 6, 8, 1, 0, 1, 0, 13, 66, 76, 29, 85, 74, 99, 85, 47, 44, 55, 
+#> 87, 73, 47, 1, 55, 63, 69, 88, 90, 96, 90, 62, 75, 65, 69, 96, 53, 90, 70, 9, 27, 1, 20, 17, 27, 75, 82, 107, 102, 109, 71, 29, 41, 68, 73, 88, 89, 77, 43, 56, 71, 45, 2, 0, 0, NA, NA, NA, 0, NA, NA, 0, NA, NA, NA, 0, 1, 0, 0, 0, NA, 0, NA, NA, 0, 0, 0, 0, 0, 0, 2, 2, 0, 0, NA, NA, 0, 0, 0, 1, 2, 39, 11, 15, 6, 31, 71, 86, 124, 97, 68, 79, 64, 64, 74, 67, 57, 2, 28, 14, 14, 47, 6, 64, 68, 65, 46, 54, 47, 40, 30, 40, 27, 14, 7, 4, 24, 0, 1, 45, 45, 33, 61, 54, 50, 59, 42, 37, 30, 43, 38, 41, 9, 8, 
+#> 13, 13, 2, 46, 60, 61, 61, 39, 75, 69, 72, 84, 122, 74, 121, 110, 86, 109, 96, 82, 66, 35, 69, 73, 33, 65, 67, 55, 47, 71, 20, 40, 53, 19, 31, 21, 0, 3, 4, 6, 0, 3, 6, 4, 3, 3, 3, 0, 3, 3, 2, 0, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 4, 4, 3, 6, 6, 4, 4, 6, 7, 4, 2, 3, 1, 2, 3, 1, 3, NA, NA, NA, NA, NA, NA, NA, 1, NA, NA, 0, 0, NA, NA, NA, NA, NA, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, NA, 0, 0, NA, 0, NA, NA, NA, NA, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 4, 0, 0, 1, 3, 0, 0, 0, 2, 49, 84, 94, 105, 79, 
+#> 119, 87, 42, 101, 90, 42, 108, 70, 71, 90, 67, 82, 77, 55, 69, 1, 18, 39, 9, 36, 71, 58, 75, 104, 90, 55, 73, 38, 91, 84, 30, 41, 22, 5, NA, NA, 0, 0, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0, 0, NA, 3, 6, 31, 18, 26, 69, 70, 95, 79, 78, 37, 35, 96, 62, 6, 37, 40, 2, 3, 78, 60, 69, 55, 9, 52, 52, 22, 70, 66, 36, 19, 1, 39, 6, 2, 0, 4, 4, 42, 41, 28, 40, 55, 48, 38, 34, 19, 42, 46, 33, 37, 48, 42, 38, 33, 11, 19, 24, 95, 111, 117, 90, 62, 89, 65, 70, 60, 44, 68, 36, 33, 65, 21, 
+#> 5, 26, 6, 13, 10, 20, 19, 43, 39, 59, 66, 73, 70, 35, 71, 52, 58, 62, 76, 67, 48, 34, 20, 8, 10, 60, 43, 49, 56, 61, 19, 26, 18, 25, 44, 60, 54, 48, 14, 6, 9, 28, 44, 71, 98, 63, 69, 11, 58, 27, 72, 39, 60, 59, 5, 0, 0, 3, 2, 62, 101, 80, 63, 36, 86, 62, 86, 80, 48, 80, 71, 31, 48, 25, 81, 85, 90, 100, 57, 87, 115, 97, 111, 61, 89, 75, 66, 96, 69, 64, 77, 57, 68, 36, 33, 13, 0, 9, 64, 84, 90, 96, 71, 107, 104, 73, 65, 65, 90, 78, 62, 72, 69, 60, 44, 34, 30, 6, 9, 59, 91, 87, 98, 99, 59, 85, 73, 86, 
+#> 75, 76, 96, 43, 62, 15, 37, 60, 29, 1, 75, 52, 7, 88, 68, 37, 81, 95, 96, 18, 16, 11, 7, 0, 2, 3, 2, 4, 4, 0, NA, NA, NA, NA, NA, NA, 5, 3, 5, 3, 3, 2, 1, 2, 1, NA, NA, NA, NA, NA, 36, 66, 75, 80, 75, 93, 89, 53, 4, 22, 2, 35, 26, 0, 0, 29, 64, 70, 62, 66, 80, 60, 82, 71, 68, 84, 45, 73, 76, 44, 60, 14, 20, 6, 3, 3, 4, 3, 9, 9, 5, 8, 4, 1, NA, 0, 2, 8, 7, 7, 1, 4, 2, 2, 0, 32, 94, 82, 105, 83, 47, 76, 39, 40, 63, 42, 42, 35, 43, 45, 20, 5, 17, 55, 52, 44, 54, 40, 47, 57, 20, 11, 16, 36, 2, 0, 0, 
+#> 3, 1, 0, 0, NA, NA, 0, 0, NA, NA, NA, 0, 9, 13, 65, 41, 21, 40, 34, 66, 60, 52, 38, 50, 41, 17, 5, 3, 20, 54, 90, 90, 116, 111, 65, 79, 43, 34, 83, 87, 94, 87, 43, 18, 7, 6, 77, 95, 108, 72, 85, 93, 109, 79, 35, 58, 64, 5, 32, 52, 38, 11, 4, 2, 36, 63, 75, 73, 40, 8, 15, 33, 30, 5, 0, 0, 0, 4, 3, 11, 5, 3, 7, 3, 5, 5, 5, 2, 5, 10, 2, 1, 6, 3, NA, NA, NA, 0, NA, NA, 5, 71, 75, 68, 48, 76, 94, 90, 102, 95, 110, 54, 77, 75, 94, 77, 72, 67, 36, 50, 66, 81, 42, 85, 75, 15, 61, 70, 15, 43, 26, 43, 60, 
+#> 71, 54, 89, 98, 94, 32, 77, 65, 93, 73, 84, 75, 32, 9, 42, 9, 11, 5, 2, 2, 48, 67, 59, 66, 66, 72, 121, 50, 129, 102, 105, 76, 82, 99, 92, 101, 98, 66, 71, 62, 3, 14, 64, 90, 84, 77, 60, 90, 82, 33, 71, 34, 93, 81, 76, 59, 75, 32, NA, NA, NA, NA, NA, 0, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0, NA, 0, 4, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 9, 0, 12, 55, 49, 66, 86, 60, 83, 96, 70, 104, 106, 63, 82, 46, 25, 49, 86, 51, 66, 75, 64, 71, 89, 76, 44, 62, 75, 88, 28, 33, 89, 74, 3, 24, 4, 5, 55, 53, 50, 
+#> 62, 84, 51, 26, 73, 8, 41, 36, 16, 0, 3, 55, 42, 51, 53, 40, 68, 37, 52, 33, 16, 45, 36, 22, 27, 15, 3, 9, 57, 74, 81, 104, 88, 97, 89, 52, 84, 99, 106, 105, 90, 83, 96, 63, 7, 75, 92, 72, 35, 11, 4, 0, 33, 64, 66, 79, 85, 87, 103, 120, 39, 52, 80, 82, 84, 70, 93, 64, 3, 28, 3, 41, 70, 8, 20, 77, 97, 89, 22, 90, 78, 91, 49, 49, 8, NA, NA, NA, NA, 0, 0, NA, NA, NA, 0, NA, NA, 0, NA, NA, 49, 67, 41, 48, 83, 5, 0, 5, 1, 81, 63, 30, 57, 62, 53, 75, 74, 69, 39, 49, 38, 27, 21, 15, 0, 0, 6, 1, 2, NA, NA, 
+#> 3, NA, 4, 3, 8, 8, 5, 0, 2, NA, NA, 0, 4, 2, 50, 59, 66, 43, 61, 77, 101, 51, 22, 46, 57, 56, 30, 21, 19, 22, 34, 77, 100, 68, 88, 62, 90, 67, 93, 85, 48, 71, 52, 28, 22, 46, 15, 93, 80, 94, 64, 24, 2, 55, 70, 15, 17, 57, 59, 32, 17, 65, 54, 41, 65, 70, 4, 5, 22, 16, 65, 97, 31, 40, 80, 25, 68, 66, 70, 1, 24, 69, 95, 110, 87, 62, 82, 48, 17, 37, 9, 12, 46, 5, 2, 0, 1, 8, 5, 2, 0, 0, 1, 1, 2, 6, 1, 7, 1, 2, 1, 4, 6, NA, NA, NA, NA, NA, 0, 3, 1, 1, 1, 3, 1, 0, 2, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 2, 
+#> 0, 2, 3, 1, NA, NA, NA, 0, NA, 15, 57, 86, 58, 84, 55, 93, 77, 50, 39, 14, 20, 0, 10, 43, 113, 133, 54, 87, 90, 81, 87, 77, 97, 81, 58, 49, 38, 38, 29, 4, 0, NA, 0, 0, NA, NA, NA, 1, NA, 0, 6, 49, 68, 107, 52, 66, 83, 85, 79, 107, 109, 73, 54, 71, 57, 11, 72, 38, 28, 16, 17, 20, 0, 14, 37, 35, 46, 24, 13, 13, 44, 23, 2, 0, 5, 58, 31, 86, 76, 74, 76, 48, 91, 63, 75, 83, 81, 55, 39, 14, 24, 22, 24, 69, 77, 67, 53, 58, 69, 53, 70, 67, 104, 80, 82, 61, 96, 73, 75, 51, 16, 36, NA, NA, NA, NA, NA, NA, 
+#> NA, NA, NA, NA, 0, 0, 0, 76, 14, 7, 1, 0, 0, 1, 0, NA, NA, NA, NA, 0, NA, NA, NA, 10, 37, 65, 79, 39, 75, 80, 75, 64, 53, 42, 44, 48, 54, 38, 7, 19, 2, 10, 15, 2, 27, 16, 28, 45, 36, 63, 71, 88, 94, 53, 92, 49, 49, 40, 31, 8, 10, 64, 65, 82, 72, 75, 9, 55, 67, 73, 67, 65, 73, 57, 5, 23, 45, 14, 12, 1, 9, 6, 6, 2, 7, 11, 0, 7, 4, 1, 3, 7, 9, 0, 3, 1, 1, 1, 7, 25, 47, 70, 23, 29, 18, 8, 15, 22, 28, 31, 28, 12, 18, 10, 0, 1, 0, NA, NA, NA, NA, NA, 1, 3, 6, 4, 0, NA, 1, 2, 1, 2, 0, 0, 0, 1, 0, 0, 0, 
+#> 1, 0, 3, 60, 88, 72, 69, 77, 84, 77, 81, 42, 62, 73, 71, 64, 42, 12, 0, 3, 6, 5, 5, 7, 5, 4, 2, 3, 8, NA, NA, 0, 3, 4, 0, 1, 5, 0, 25, 44, 38, 35, 33, 21, 9, 1, 49, 111, 89, 119, 105, 113, 146, 130, 78, 118, 41, 72, 119, 105, 77, 77, 37, 66, 67, 110, 21, 63, 101, 89, 17, 58, 70, 40, 7, 0, 4, 4, 1, 0, 6, 2, 1, 4, 5, 4, 3, 3, 5, 0, NA, NA, NA, NA, NA, NA, NA, NA, 0, NA, 0, NA, 0, 0, 0, NA, NA, NA, 63, 114, 87, 61, 65, 43, 70, 51, 80, 89, 80, 81, 58, 0, 65, 0, 26, 17, 29, 87, 51, 58, 77, 107, 50, 40, 
+#> 8, 42, 22, NA, NA, 1, 0, NA, NA, 3, NA, 0, NA, 0, 0, NA, NA, NA, NA, NA, NA, 3, 7, 27, 46, 87, 87, 85, 99, 7, 89, 24, 16, 60, 42, 41, 10, 18, 18, 41, 34, 42, 53, 19, 33, 20, 5, 13, 31, 16, 4, 10, NA, NA, NA, 4, 7, 4, NA, NA, NA, NA, NA, 3, 5, 66, 53, 98, 43, 113, 131, 94, 118, 89, 115, 77, 60, 38, 22, 66, 5, 1, 1, 90, 121, 103, 116, 98, 97, 87, 80, 78, 99, 73, 87, 71, 71, 94, 79, 65, 51, 43, 43, 15, 88, 94, 70, 62, 91, 84, 70, 88, 70, 85, 74, 20, 2, 5, 3, 50, 24, 89, 84, 79, 70, 57, 3, 26, 2, 0, 
+#> 20, 36, 63, 72, 67, 64, 49, 94, 49, 77, 50, 69, 65, 1, 42, 42, 84, 58, 86, 58, 66, 70, 10, 4, 2, 2, 4, 4, 1, 10, 1, 6, 2, 1, 0, 2, 2, 7, 4, 1, NA, 0, 0, 2, 1, 0, 0, NA, NA, NA, NA, NA, NA, NA, NA, NA, 16, 10, 34, 27, 70, 97, 78, 54, 96, 51, 21, 6, 76, 21, 24, 0, 0, 1, 0, NA, NA, NA, 1, 0, 0, NA, NA, NA, NA, NA, 0, 6, 4, 69, 40, 120, 83, 77, 77, 15, 80, 26, 14, 89, 72, 58, 23, 8, 35, 13, 2, 5, 4, 2, 1, 2, 8, 7, 5, 3, 5, 2, 1, NA, NA, NA, 0, 1, 1, NA, 0, NA, NA, NA, NA, NA, NA, NA, 1, 1, 2, 0, 0, 12, 
+#> 18, 11, 1, 27, 41, 48, 51, 24, 35, 33, 37, 54, 42, 16, 25, 16, 13, 15, 2, NA, 0, NA, NA, 0, 0, 4, 3, 0, 4, 3, 4, 10, 5, NA, NA, NA, 0, 7, 3, 2, 6, 2, 103, 94, 114, 113, 68, 81, 77, 104, 116, 104, 100, 67, 36, 85, 54, 1, 16, 53, 51, 77, 53, 56, 40, 55, 36, 62, 45, 39, 20, 18, 25, 14, 4, 2, 43, 75, 82, 114, 65, 76, 73, 23, 23, 76, 67, 56, 53, 19, 32, 52, 29, 27, 25, 1, 8, 7, 64, 71, 43, 72, 43, 15, 13, 22, 51, 46, 34, 0, 0, 2, 1, 0, 0, 0, NA, 0, 1, NA, NA, 3, 75, 67, 51, 34, 8, 21, 31, 26, 4, 29, 7, 
+#> 63, 75, 78, 76, 108, 101, 69, 92, 86, 20, 12, 13, 15, 35, 1, 44, 10, 51, 100, 109, 107, 107, 108, 128, 113, 89, 93, 62, 83, 61, 76, 80, 55, 51, 40, 44, 36, 51, 104, 97, 92, 89, 106, 77, 72, 64, 37, 10, 79, 68, 75, 67, 67, 16, 48, 75, 52, 47, 0, 11, 28, 32, 75, 47, 54, 54, 46, 51, 20, 19, 25, 12, 2, 46, 33, 51, 24, 44, 49, 87, 79, 73, 79, 53, 62, 85, 96, 69, 48, 47, 9, 6, 32, 13, 73, 81, 3, 26, 24, 6, 36, 45, 54, 44, 30, 23, 15, 34, 55, 39, 75, 65, 53, 51, 42, 69, 35, 12, 1, 4, 3, 0, 0, 1, 5, 1, 2, 
+#> 2, 0, 6, NA, 1, NA, 3, 5, 61, 90, 133, 106, 115, 91, 123, 66, 76, 65, 102, 102, 75, 80, 81, 45, 56, 53, 20, 1, 13, 9, 0, 0, 2, 0, 0, 0, 0, 0, NA, NA, NA, 0, 0, 0, NA, 0, NA, NA, NA, 0, 0, 3, 23, 41, 34, 60, 92, 96, 84, 95, 106, 35, 59, 81, 6, 62, 71, 37, 0, 1, 0, 0, 0, 1, 0, 2, 0, 0, 0, 0, NA, NA, 5, 0, 56, 41, 94, 63, 32, 38, 19, 26, 4, 6, 0, 3, 3, 0, 0, 3, 2, 8, 2, NA, NA, 0, 80, 78, 66, 86, 67, 84, 63, 39, 5, 5, 11, 5, 4, 8, 1, 4, 7, 8, 5, 1, NA, 0, 0, 1, 0, 0, 0, 33, 34, 88, 90, 107, 119, 64, 
+#> 82, 79, 69, 77, 70, 79, 82, 67, 97, 65, 59, 17, 5, 0, 0, 6, 8, 5, 0, 3, 4, 10, 2, 9, 2, 9, NA, 0, 0, 0, 34, 91, 107, 117, 93, 94, 79, 40, 64, 89, 78, 62, 59, 1, 1, 2, NA, 0, 0, NA, NA, 0, 0, NA, NA, NA, NA, 1, NA, NA, 0, 2, 7, 1, 2, 0, 0, 0, 0, 5, 19, 63, 67, 93, 49, 65, 77, 66, 37, 27, 0, 1, 19, 89, 54, 55, 70, 50, 89, 52, 76, 69, 60, 53, 42, 68, 24, 23, 14, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, NA, 0, NA, 0, 0, NA, 0, NA, 71, 58, 64, 58, 63, 61, 52, 5, 44, 46, 50, 62, 59, 35, 2, 21, 22, 107, 94, 121, 77, 
+#> 94, 73, 45, 37, 64, 61, 39, 27, 10, 0, 19, 5, 85, 87, 101, 111, 78, 88, 67, 63, 74, 36, 8, 34, 40, 53, 61, 67, 50, 57, 61, 56, 74, 48, 28, 14, 5, 55, 42, 89, 76, 72, 86, 72, 59, 55, 55, 18, 11, 41, 76, 58, 64, 44, 60, 80, 15, 40, 40, 57, 5, 24, 2, 3, 8, 49, 100, 88, 101, 77, 83, 39, 20, 4, 29, 50, 83, 43, 67, 97, 48, 73, 42, 4, 65, 9, 39, 17, 6, NA, NA, NA, NA, NA, 3, 9, 6, 1, 0, 0, 0, 3, 0, 7, 56, 59, 94, 72, 83, 31, 15, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0, 1, 0, 0, 0, 0, 1, 0, 
+#> 1, 2, 0, 0, 1, 0, 4, 2, 2, 3, 7, 7, 4, 1, 2, 0, 0, 4, 59, 81, 55, 71, 91, 95, 66, 63, 61, 58, 41, 3, 37, 53, 76, 71, 63, 21, 39, 22, 0, 7, 54, 58, 51, 94, 107, 89, 62, 71, 8, 69, 37, 8, 63, 80, 119, 96, 109, 75, 82, 92, 104, 89, 79, 83, 5, 29, 71, 91, 90, 76, 64, 84, 81, 84, 20, 45, 50, 57, 55, 71, 73, 6, 5, 14, 41, 56, 55, 47, 61, 57, 2, 19, 12, 0, NA, NA, 0, 0, NA, NA, NA, NA, NA, NA, NA, NA, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 16, 85, 81, 120, 40, 83, 115, 66, 8, 30, 88, 64, 68, 56, 98, 75, 16, 31, 
+#> 46, 6, 51, 91, 70, 78, 87, 44, 29, 46, 8, 11, 26, 53, 90, 30, 35, 44, 73, 88, 39, 34, 0, 2, 22, 30, 21, 54, 66, 49, 11, 33, 24, 3, 4, 7, 5, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0, 0, 2, 4, 2, NA, NA, NA, 0, NA, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, NA, 0, 0, 0, NA, NA, NA, NA, NA, 4, NA, NA, NA, 1, NA, NA, NA, NA, NA, 0, 0, 37, 56, 56, 82, 44, 83, 46, 94, 98, 81, 25, 70, 21, 30, 11, 17, 0, 2, 18, 33, 24, 15, 27, 25, 22, 6, 0, 6, 7, 33, 26, 97, 120, 81, 74, 84, 39, 21, 14, 57, 19, 
+#> 81, 29, 81, 27, 38, 17, 73, 88, 81, 45, 136, 95, 3, 93, 62, 114, 115, 84, 64, 133, 89, 121, 86, 63, 99, 63, 75, 1, 2, 47, 29, 1, 20, 32, 74, 76, 49, 48, 70, 45, 12, 69, 39, 10, 97, 87, 74, 87, 62, 87, 16, 26, 75, 104, 48, 38, 130, 118, 60, 48, 10, 64, 49, 50, 42, 60, 37, 49, 35, 40, 71, 31, 3, 28, 22, 39, 56, 53, 15, 1, 3, 2, 69, 53, 15, 12, 21, 52, 42, 25, 11, 4, 1, 14, 105, 101, 90, 113, 68, 37, 32, 62, 74, 15, 7, 31, 32, 28, 3, 34, 13, 14, NA, 0, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0, 
+#> NA, 1, 1, 2, 6, 3, 3, 1, 1, 0, 3, 2, 0, 2, NA, 2, NA, NA, 0, NA, NA, NA, NA, NA, NA, NA, 1, 1, 7, 0, NA, 0, 0, 0, NA, 0, 0, 0, 0, 0, NA, 3, 66, 42, 37, 32, 50, 48, 47, 51, 43, 79, 60, 45, 35, 0, 4, 5, 4, 10, 1, 4, 0, 6, 6, 11, 4, NA, NA, 0, 7, 3, 0, 8, 3, 15, 46, 73, 61, 87, 100, 95, 55, 64, 33, 7, 8, 103, 76, 86, 57, 110, 98, 116, 67, 61, 77, 37, 84, 60, 26, 52, 51, 45, 61, 48, 93, 101, 64, 67, 87, 103, 42, 41, 6, 26, 1, 0, 40, 45, 63, 63, 54, 59, 52, 28, 20, 23, 10, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 
+#> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 44, 30, 50, 15, 36, 50, 58, 65, 89, 52, 64, 38, 29, 74, 40, 95, 91, 42, 86, 41, 10, 0, 15, 3, 68, 82, 97, 80, 86, 88, 80, 96, 108, 19, 85, 72, 72, 46, 22, 0, 13, 51, 28, 37, 30, 14, 1, 7, 7, 4, 71, 86, 87, 71, 76, 16, 77, 60, 67, 35, 9, 39, 72, 99, 76, 65, 34, 38, 71, 77, 89, 119, 120, 103, 67, 17, 33, 30, 36, 1, 27, 28, 58, 87, 96, 112, 102, 62, 81, 60, 47, 49, 107, 77, 11, 28, 12, 23, 17, 0, 0, 2, NA, NA, 1, 4, 1, 1, 0, NA, NA, NA, 0, NA, 27, 64, 91, 47, 85, 
+#> 88, 76, 57, 78, 98, 117, 34, 93, 108, 71, 29, 72, 39, 55, 4, 4, 0, 23, 16, 28, 53, 35, 55, 48, 57, 63, 42, 14, 5, 0, 2, 3, 0, NA, NA, 0, NA, NA, 0, NA, 0, NA, 0, NA, NA, NA, NA, NA, 66, 89, 102, 104, 91, 84, 69, 82, 73, 85, 69, 56, 98, 40, 49, 29, NA, NA, NA, NA, NA, 11, 4, 1, 1, 0, 2, 3, 3, 1, 1, 0, 1, 15, 68, 61, 89, 86, 82, 74, 75, 65, 45, 44, 23, 9, 46, 63, 86, 74, 8, 32, 23, 1, 2, 3, 4, 0, 0, 0, 3, 2, 0, NA, NA, 0, NA, 1, 0, 0, NA, 0, 7, 9, 4, 5, 4, 8, 2, 0, 0, NA, 0, 0, 0, 0, 0, 4, 3, 5, 3, 
+#> 0, 3, 2, 0, 0, 51, 19, 49, 60, 100, 90, 52, 48, 56, 57, 9, 18, 7, 14, 1, 2, NA, NA, NA, 0, NA, NA, 0, NA, 0, NA, NA, NA, NA, NA, NA, 0, NA, 0, 0, 0, 0, NA, 0, NA, 0, 0, NA, 1, 0, 0, 0, 64, 63, 42, 7, 2, 10, 32, 9, 8, 4, 1, 58, 100, 98, 91, 84, 79, 59, 52, 81, 85, 81, 77, 73, 75, 82, 27, 40, 67, 32, 7, 10, 23, 26, 19, 31, 72, 68, 85, 82, 79, 57, 76, 78, 5, 50, 97, 77, 101, 70, 110, 17, 66, 77, 71, 33, 40, 22, 39, 6, 4, 7, 5, 55, 47, 19, 14, 40, 14, 3, 23, 11, 43, 38, 30, 93, 85, 104, 89, 108, 48, 
+#> 32, 30, 26, 14, 64, 53, 79, 96, 98, 88, 123, 113, 146, 123, 123, 67, 118, 96, 102, 100, 94, 79, 68, 0, NA, 0, NA, NA, NA, NA, NA, NA, NA, NA, 1, 0, 0, 0, 0, 0, 2, 40, 66, 40, 69, 52, 73, 59, 8, 3, 38, 58, 27, 57, 14, 26, 10, 12, 23, 28, 26, 7, 1, 24, 55, 96, 79, 49, 10, 68, 45, 37, 10, 71, 24, 15, 2, 3, 1, 1, 3, 5, 2, 0, 4, 2, 5, NA, NA, NA, 0, NA, NA, 0, NA, 2, 4, 1, 8, 6, 5, 2, 4, 4, 5, 1, 0, 1, 0, 20, 50, 75, 83, 92, 58, 42, 10, 0, 1, 60, 10, 22, 24, 44, 32, 53, 63, 45, 19, 44, 17, 21, 8, 22, 
+#> 15, 11, 5, 3, 1, 94, 93, 73, 89, 56, 35, 75, 33, 41, 142, 91, 54, 22, 73, 74, 83, 92, 27, 6, 61, 91, 76, 83, 113, 94, 52, 125, 125, 120, 123, 100, 57, 17, 34, 49, 85, 62, 78, 16, 51, 44, 6, 72, 99, 97, 96, 104, 95, 109, 129, 89, 109, 122, 123, 120, 91, 129, 129, 117, 111, 129, 8, 74, 75, 0, 3, 13, 6, 1, 8, 6, 5, 5, 8, 6, 3, 4, 7, 2, 3, 6, 2, 5, 4, 2, 1, 2, 0, 1, 0, 2, 4, 14, 73, 64, 50, 3, 39, 32, 30, 33, 7, 0, 0, 0, 0, 0, 0, NA, NA, 0, 0, 1, 1, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, NA, 0, NA, NA, NA, 
+#> NA, NA, NA, 0, NA, 7, 76, 67, 78, 90, 61, 73, 23, 84, 94, 75, 46, 43, 58, 54, 6, 7, 30, 24, 104, 102, 80, 80, 67, 70, 55, 30, 40, 48, 1, 28, 17, 31, 87, 72, 58, 105, 74, 53, 69, 86, 72, 98, 43, 58, 29, 17, 8, 27, 31, 3, 29, 47, 36, 44, 29, 40, 46, 39, 19, NA, NA, NA, NA, 2, 0, 3, 7, 3, 5, 4, 1, 0, 0, 0, 6, 6, 5, 1, 11, 3, 4, 6, 8, 6, 3, 3, 5, 4, 0, 4, 5, 2, 6, 3, 2, 84, 82, 80, 88, 105, 109, 78, 71, 132, 64, 86, 138, 111, 113, 73, 42, 34, 14, 4, 5, 48, 92, 85, 85, 57, 79, 96, 27, 84, 88, 61, 70, 
+#> 68, 11, 31, 19, 8, 17, 3, 20, 38, 33, 31, 21, 17, 48, 4, 7, NA, 1, NA, 0, NA, NA, NA, NA, NA, NA, 0, 5, 82, 75, 80, 78, 85, 85, 75, 59, 61, 72, 52, 60, 34, 1, 4, 8, 4, 4, 4, 5, 1, 2, 1, 1, NA, 0, NA, NA, 0, NA, 0, 0, 0, 78, 104, 82, 85, 107, 140, 117, 117, 120, 75, 66, 41, 79, 87, 76, 104, 88, 111, 109, 124, 143, 152, 126, 94, 109, 104, 11, 39, 104, 108, 106, 106, 102, 110, 110, 109, 74, 115, 8, 77, 87, 53, 19, 77, 63, 20, 7, 6, 32, 64, 108, 83, 85, 84, 79, 89, 97, 92, 70, 70, 84, 76, 36, 15, 9, 
+#> 85, 26, 107, 101, 74, 113, 79, 74, 68, 60, 107, 15, 54, 31, 15, 58, 4, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0, 24, 39, 56, 56, 56, 116, 98, 88, 116, 66, 70, 67, 90, 72, 71, 74, 50, 33, 11, 41, 14, 32, 14, 65, 74, 72, 87, 72, 86, 55, 97, 88, 87, 92, 107, 75, 66, 43, 13, 21, 82, 52, 46, 53, 38, 33, 34, 5, 4, 4, 59, 59, 85, 85, 76, 96, 58, 143, 113, 108, 64, 107, 95, 86, 22, 29, 66, 1, 6, 7, 7, 7, 2, 6, 5, 3, 10, 4, 11, 0, 0, 0, 0, 1, 5, 1, 0, 0, 1, 93, 50, 8, 35, 51, 13, 0, 63, 74, 51, 83, 84, 86, 
+#> 59, 74, 84, 42, 52, 37, 8, 6, 0, 20, 71, 98, 100, 20, 47, 121, 121, 104, 86, 86, 100, 80, 42, 72, 45, 6, 11, 78, 77, 105, 57, 57, 89, 87, 110, 114, 69, 97, 38, 49, 17, 0, 32, 65, 87, 98, 66, 79, 90, 90, 74, 45, 93, 34, 42, 12, 34, 67, 25, 87, 33, 34, 61, 46, 118, 86, 21, 52, 103, 105, 98, 82, 126, 117, 104, 22, 107, 52, 44, 1, 14, 18, 10, 13, 29, 62, 36, 80, 90, 43, 44, 3, 22, 46, NA, NA, NA, NA, NA, NA, 7, 4, 55, 48, 82, 76, 72, 35, 7, 48, 49, 8, 0, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
+#> NA, NA, NA, 0, NA, NA, NA, 0, 0, 0, NA, 0, NA, 0, NA, 0, 0, 0, 15, 22, 36, 22, 47, 38, 24, 1, 14, 6, 6, 3, 17, 12, 2, 1, 1, 0, 1, 3, 6, 12, 9, 96, 116, 105, 93, 132, 90, 101, 110, 107, 91, 68, 30, 39, 58, 51, 67, 79, 24, 62, 45, 19, 42, 49, 68, 39, 87, 98, 89, 86, 112, 101, 84, 85, 43, 82, 66, 88, 54, 24, 17, 36, 18, 13, 73, 62, 66, 91, 67, 74, 54, 85, 13, 51, 35, 0, 12, 14, 0, 16, 24, 48, 30, 21, 5, 9, 22, 30, 17, 16, 42, 73, 99, 104, 96, 80, 106, 74, 57, 92, 67, 56, 57, 82, 78, 8, 3, 14, 23, 33, 
+#> 93, 96, 87, 102, 68, 79, 65, 89, 79, 132, 87, 59, 3, 11, 2, 43, 64, 68, 109, 47, 72, 59, 90, 91, 107, 84, 91, 85, 64, 16, 29, 18, NA, NA, NA, 0, 3, 3, 0, 3, 1, 4, 3, 5, 2, 0, 4, 7, 4, 0, 0, 0, 0, 0, 0, 0, NA, NA, NA, NA, NA, 0, 0, 0, 0, 0, 8, 93, 67, 111, 90, 95, 84, 60, 108, 63, 84, 78, 15, 30, 5, 81, 64, 82, 87, 104, 1, 20, 67, 100, 90, 81, 69, 37, 47, 41, 39, 33, 46, 80, 92, 105, 81, 87, 54, 5, 53, 46, 4, 6, 17, 31, 6, 18, 4, 34, 21, 9, 21, 25, 24, 70, 54, 63, 73, 45, 16, 25, 49, 59, 22, 11, 22, 
+#> 1, 60, 81, 93, 90, 121, 124, 90, 113, 108, 71, 40, 77, 86, 57, 27, 39, 106, 48, 53, 143, 68, 37, 21, NA, 0, 2, 9, 7, 3, 5, NA, NA, NA, NA, NA, NA, 0, 1, 1, 0, 0, 0, 4, 41, 38, 84, 70, 19, 47, 55, 15, 7, 95, 63, 44, 18, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 64, 20, 31, 47, 15, 13, 63, 91, 98, 95, 85, 98, 78, 88, 39, 51, 27, 56, 2, 8, 17, 4, 0, 53, 70, 81, 48, 87, 88, 104, 82, 79, 50, 83, 106, 67, 52, 51, 4, NA, NA, NA, NA, 3, 2, 4, 1, 4, 4, 4, 1, 4, 0, 6, 0, 17, 56, 65, 64, 29, 82, 58, 35, 
+#> 18, 46, 30, 1, 21, 57, 6, 2, 3, 10, 75, 60, 72, 84, 46, 30, 54, 53, 75, 44, 75, 13, 55, 42, 43, 11, 23, 2, 1, 0, NA, NA, NA, NA, 0, NA, NA, NA, NA, 1, 1, 1, 4, 2, 4, 2, 1, 0, 0, 0, 2, 1, 1, 60, 22, 80, 69, 81, 65, 93, 82, 43, 47, 48, 62, 40, 5, 0, 10, 5, 71, 52, 65, 68, 75, 63, 74, 109, 92, 87, 45, 42, 12, 24, 5, 40, 34, 43, 13, 31, 58, 52, 24, 51, 18, 49, 42, 5, 35, 46, 84, 84, 69, 64, 104, 126, 101, 92, 100, 100, 66, 82, 82, 61, 31, 41, 66, 9, 21, 42, 86, 65, 98, 118, 91, 107, 63, 93, 67, 10, NA, 
+#> NA, 0, NA, NA, NA, NA, 0, NA, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, NA, NA, NA, NA, 0, 0, NA, 0, NA, NA, NA, 0, NA, 0, 81, 97, 44, 52, 62, 23, 61, 55, 5, 2, 1, 3, 1, 3, 3, 0, 0, 3, 4, 2, 0, 0, 5, 51, 85, 94, 99, 108, 131, 92, 93, 84, 117, 108, 112, 79, 84, 66, 36, 62, 6, 32, 0, 21, 50, 53, 108, 84, 95, 113, 58, 6, 8, 18, 1, 1, 36, 16, 82, 97, 94, 108, 83, 22, 62, 7, 56, 65, 93, 53, 2, 24, 1, 13, 40, 53, 37, 93, 74, 102, 114, 81, 97, 104, 13, 67, 45, 19, 8, 72, 39, 41, 92, 59, 89, 84, 90, 134, 114, 
+#> 106, 146, 122, 99, 69, 39, 53, 7, 8, 28, 58, 92, 122, 104, 89, 101, 106, 101, 101, 111, 97, 26, 108, 79, 93, 55, 0, 48, 11, 21, 8, 9, 5, 35, 120, 73, 82, 115, 34, 129, 95, 96, 89, 102, 88, 52, 39, 47, 6, 6, 38, NA, NA, NA, NA, NA, NA, 0, 0, 1, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 2, 1, 7, 1, 1, NA, 2, 1, 0, 0, 6, 62, 90, 66, 91, 49, 52, 83, 92, 43, 84, 75, 74, 64, 49, 45, 12, 43, 39, 67, 80, 93, 108, 107, 101, 116, 108, 102, 102, 77, 105, 53, 65, 17, 35, 84, 108, 106, 92, 91, 109, 100, 108, 112, 86, 
+#> 80, 79, 24, 54, 22, 52, NA, NA, NA, NA, NA, NA, 0, 0, 0, 4, 0, 0, 0, 0, 0, 8, 28, 27, 16, 64, 69, 91, 74, 86, 107, 104, 33, 37, 50, 4, 3, 1, 27, 37, 56, 52, 73, 34, 60, 45, 31, 89, 83, 47, 30, 6, 1, 2, 0, 0, 0, 0, NA, 0, 1, 0, 0, 0, 0, 1, 1, 0, 2, 1, 0, 0, 0, 0, 0, 0, 0, 0, 5, 104, 116, 127, 134, 119, 110, 124, 87, 111, 122, 118, 102, 88, 107, 111, 84, 99, 8, 47, 16, 64, 39, 23, 39, 39, 42, 21, 39, 16, 32, 28, 3, 23, 6, 21, 4, 15, 141, 100, 123, 110, 134, 133, 125, 124, 112, 124, 113, 143, 104, 78, 
+#> 74, 67, 74, 21, 83, 9, 82, 37, 68, 113, 78, 28, 78, 73, 98, 98, 57, 71, 9, 55, 22, 19, 1, NA, NA, NA, 0, 0, 0, 0, 0, 0, 0, 1, 4, 0, 0, 1, 0, 0, 0, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 3, 2, 1, 1, 1, 2, 3, 2, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 5, 5, 0, 0, 0, 0, 1, 0, 0, 2, 2, 1, 3, 0, 9, 32, 75, 76, 72, 115, 84, 124, 82, 89, 110, 95, 98, 96, 102, 98, 99, 92, 68, 47, 51, 35, 46, 49, 10, 31, 53, 14, 2, 1, 2, 3, 5, 1, 6, 7, 6, 2, 2, 7, 0, 6, 9, 1, 0, 0, 1, 
+#> 2, 3, 0, 0, NA, NA, NA, 1, 1, NA, 2, 0, 0, 0, 0, 0, 0, 0, 11, 122, 111, 103, 104, 13, 101, 120, 24, 28, 28, 82, 39, 24, 17, 10, 93, 120, 74, 88, 96, 52, 37, 98, 109, 28, 94, 55, 58, 24, 52, 66, 31, 26, 4, 11, 53, 48, 42, 92, 82, 96, 92, 95, 69, 89, 63, 66, 63, 43, 11, 7, 63, 46, 49, 61, 110, 56, 60, 48, 90, 49, 41, NA, 0, 0, 2, 5, 0, 3, 6, 2, 1, 1, 0, 6, 5, 0, NA, NA, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, NA, NA, NA, NA, NA, NA, NA, NA, 2, NA, NA, NA, 0, 0, 0, 0, 0, 0, 2, 1, 0, 0, 2, 
+#> 1, 9, 13, 26, 31, 69, 73, 59, 86, 64, 57, 57, 15, 31, 59, 63, 56, 40, 76, 102, 61, 118, 88, 111, 74, 3, 30, 11, 60, 89, 97, 122, 104, 91, 101, 85, 95, 107, 83, 21, 43, 41, 27, 27, NA, NA, NA, NA, NA, 4, 5, 4, 0, 0, 1, 0, 0, 0, 0, NA, NA, 0, 0, NA, NA, NA, 0, NA, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 12, 94, 80, 92, 72, 62, 28, 2, 28, 1, 3, 6, 3, 5, 4, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 14, 33, 41, 35, 4, 10, 97, 84, 83, 76, 77, 29, 8, 26, 37, 24, 24, 33, 0, 38, 74, 88, 50, 30, 98, 23, 47, 84, 92, 73, 
+#> 34, 0, 3, 18, 51, 81, 77, 97, 59, 67, 78, 20, 60, 112, 104, 83, 74, 28, 8, NA, NA, NA, 0, NA, NA, 0, NA, NA, 1, 4, 4, 1, 2, 2, 2, 4, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 4, 1, 0, 1, 52, 52, 57, 106, 134, 98, 121, 110, 84, 92, 87, 59, 14, 62, 48, 20, 85, 76, 50, 46, 9, 32, 6, 1, 21, 59, 39, 84, 55, 21, 46, 68, 58, 48, 22, 6, 1, 44, 103, 69, 69, 56, 71, 101, 75, 17, 30, 40, 14, 2, 87, 114, 100, 123, 116, 118, 113, 90, 103, 69, 66, 87, 108, 82, 80, 47, 56, 58, 1, 19, 20, 18, 30, 0, 0, 6, 26, 14, 3, 0, 0, 0, 
+#> 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 12, 112, 49, 106, 114, 102, 70, 51, 83, 127, 93, 116, 50, 21, 61, 17, 83, 79, 46, 57, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 17, 7, 68, 79, 94, 113, 115, 102, 103, 117, 74, 81, 89, 71, 96, 15, 26, 36, 84, 94, 123, 109, 64, 78, 56, 66, 36, 1, 4, 2, 44, 108, 102, 101, 107, 106, 71, 124, 95, 92, 89, 85, 59, 83, 60, 0, 0, 7, 9, 6, 3, 10, 7, 20, 9, 6, 7, 4, 3, 6, 0, 3, 3, 4, NA, NA, 0, NA, NA, NA, NA, NA, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 4, 4, 2, 1, 1, NA, NA, NA, 
+#> 0, 6, 4, 6, 0, 0, 0, 1, 1, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, NA, NA, NA, NA, NA, NA, NA, 0, 8, 6, 3, NA, 0, 6, 0, 32, 26, 24, 96, 107, 50, 41, 74, 28, 87, 74, 103, 68, 96, 78, 34, 99, 84, 84, 121, 89, 99, 35, 79, 86, 8, 33, 49, 13, NA, 0, 0, NA, NA, NA, NA, NA, 0, 1, 2, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 3, 13, 31, 29, 24, 16, 43, 40, 31, 43, 28, 42, 10, 4, 46, 80, 108, 92, 65, 18, 65, 27, 12, 28, 59, 27, 4, 5, 13, 78, 114, 138, 132, 107, 135, 115, 92, 94, 86, 39, 79, 48, 59, 31, 41, 27, 
+#> 84, 66, 92, 115, 108, 109, 120, 97, 33, 74, 92, 31, 68, 4, 39, 17, 20, 7, 21, 3, 16, 36, 65, 53, 65, 16, 45, 90, 94, 86, 114, 84, 102, 77, 96, 100, 61, 78, 42, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 87, 39, 95, 130, 103, 100, 113, 87, 34, 92, 66, 15, 29, 69, 4, 19, 85, 120, 100, 99, 53, 47, 78, 105, 60, 69, 2, 52, 0, 1, 29, 56, 50, 92, 59, 79, 83, 72, 67, 65, 91, 18, 55, 49, 34, 12, 70, 100, 102, 97, 116, 95, 32, 38, 82, 117, 72, 54, 
+#> 56, 33, 68, 90, 79, 92, 94, 54, 77, 96, 84, 100, 100, 87, 69, 50, 26, 34, 1, 34, 0, 77, 60, 67, 13, 34, 36, 37, 26, 37, 0, 6, 47, 89, 91, 87, 94, 87, 92, 74, 43, 10, 0, 10, 16, 36, 28, 6, 4, 1, 63, 53, 93, 96, 99, 84, 74, 76, 47, 88, 88, 69, 78, 24, 9, 18, 0, 0, 52, 44, 82, 89, 83, 79, 63, 86, 94, 85, 74, 76, 80, 81, 90, 71, 67, 127, 111, 111, 101, 111, 110, 111, 103, 88, 74, 80, 28, 49, 57, 42, 45, 5, 20, 46, 94, 37, 101, 17, 81, 95, 75, 35, 21, 18, 45, 44, 30, 16, 45, 62, 62, 75, 45, 57, 43, 38, 
+#> 35, 37, 38, 15, 9, 4, 4, 44, 48, 47, 64, 64, 95, 33, 41, 70, 95, 101, 93, 42, 41, 64, 35, 4, 0, 0, 20, 43, 4, 20, 23, 76, 63, 40, 59, 85, 56, 31, 31, 61, 16, 19, NA, NA, NA, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 112, 118, 137, 133, 129, 119, 99, 100, 124, 115, 105, 85, 49, 89, 85, 1, 51, 40, 82, 57, 34, 35, 70, 78, 84, 112, 106, 128, 90, 92, 69, 90, 93, 70, 30, 4, 27, 16, 54, 68, 67, 114, 76, 65, 22, 27, 61, 61, 40, 33, 10, 0, 0, 0, 0, 2, 3, 5, 0, 0, 0, NA, 0, 0, 0, 0, 0, 0, 0, 0, 0, 12, 82, 
+#> 48, 65, 71, 70, 49, 50, 27, 42, 65, 43, 36, 22, 3, 32, 42, 12, 39, 5, 1, 3, 8, 5, 17, 9, 0, 0, 0, 0, 0, 0, 0, 2, 1, 2, 1, 0, 3, 3, 0, 0, 8, 59, 31, 34, 37, 36, 45, 44, 38, 46, 52, 17, 10, NA, 0, NA, 0, 0, 1, 1, 1, 2, 0, 0, 0, 0, 10, 53, 93, 105, 107, 108, 98, 107, 89, 99, 72, 92, 83, 40, 31, 28, 15, 0, 0, 0, 0, 0, 0, 0, 99, 74, 66, 79, 8, 35, 25, 59, 13, 18, 38, 24, 9, 2, 2, 6, 3, 3, 0, 3, 1, 0, 0, 2, 5, 77, 128, 114, 77, 102, 119, 97, 76, 64, 67, 50, 68, 47, 37, 22, 0, 50, 79, 76, 62, 88, 92, 83, 
+#> 93, 80, 57, 68, 63, 67, 66, 52, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 5, 2, 4, 6, 6, 4, 0, 0, 0, 1, 0, 3, 2, 5, 2, 1, 0, 1, 0, 0, 0, 0, 0, 4, NA, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 6, 3, 4, 0, 1, 1, 3, 0, 0, 0, 0, 0, 0, 0, 0, 9, 62, 21, 70, 83, 95, 91, 90, 120, 30, 91, 93, 91, 17, 63, 39, 16, 26, 27, 21, 76, 101, 76, 86, 99, 91, 72, 84, 54, 37, 46, 77, 28, 28, 31, 55, 63, 91, 92, 64, 90, 76, 23, 0, 23, 34, 37, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 8, 8, 92, 72, 68, 45, 0, 26, 6, 4, 2, 5, 14, 8, 11, 0, 
+#> 0, 1, 0, 2, 31, 51, 93, 61, 97, 38, 51, 0, 85, 75, 69, 12, 8, 0, 14, 87, 118, 82, 78, 91, 85, 63, 84, 79, 60, 36, 45, 19, 24, 67, 101, 82, 103, 77, 51, 38, 52, 78, 28, 1, 32, 73, 65, 88, 76, 87, 56, 79, 79, 58, 54, 23, 36, 27, 101, 61, 104, 87, 52, 2, 5, 2, 6, 9, 6, 2, 2, 1, 1, 5, 5, 11, 2, 0, 3, 0, 0, 10, 47, 1, 59, 46, 52, 79, 94, 119, 115, 116, 74, 77, 86, 84, 65, 84, 59, 73, 0, 0, 0, 0, 0, 1, 0, 2, 5, 1, 2, 0, 19, 43, 47, 90, 48, 4, 10, 15, 16, 50, 34, 42, 4, 9, 4, 6, 1, 70, 66, 42, 40, 66, 35, 
+#> 0, 9, 13, 2, 61, 110, 101, 78, 39, 72, 103, 48, 59, 21, 30, 66, 101, 112, 99, 38, 48, 63, 39, 103, 113, 90, 66, 5, 56, 57, 6, 25, 35, 49, 86, 68, 111, 86, 96, 67, 77, 44, 39, 5, 2, 15, 77, 73, 82, 78, 30, 32, 56, 64, 76, 68, 87, 39, 13, 20, 56, 55, 93, 49, 40, 10, 23, 74, 108, 54, 75, 52, 27, 19, 18, 84, 71, 59, 70, 50, 104, 69, 88, 87, 74, 54, 84, 82, 95, 88, 79, 83, 26, 0, 2, 56, 31, 43, 40, 0, 1, 22, 68, 118, 103, 118, 102, 99, 118, 104, 37, 61, 123, 100, 96, 88, 54, 1, 28, 12, 44, 77, 58, 82, 
+#> 60, 70, 67, 24, 26, 11, 17, 3, 22, 4, 0, 7, 14, 71, 84, 92, 81, 49, 84, 98, 97, 71, 59, 75, 89, 69, 66, 41, 15, 9, 72, 73, 80, 61, 60, 118, 48, 84, 84, 79, 84, 69, 23, 0, 1, 0, 2, 1, 2, 1, 2, 3, 3, 2, 4, 2, 4, 1, 1, 1, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 2, NA, 0, 0, 0, 0, 1, 1, 7, 2, 0, 0, 3, 2, 2, 0, 20, 54, 73, 62, 87, 69, 54, 74, 80, 54, 10, 11, 0, 31, 70, 55, 19, 58, 63, 67, 70, 46, 57, 37, 41, 18, 32, 3, 5, 4, 1, 1, 3, 2, 3, 4, 1, 
+#> 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 52, 104, 94, 105, 105, 87, 81, 28, 34, 65, 53, 0, 14, 69, 51, 86, 67, 36, 11, 6, 3, 53, 28, 42, 41, 33, 55, 48, 54, 23, 6, 9, 3, 39, 101, 106, 112, 91, 85, 96, 111, 111, 109, 103, 101, 64, 66, 107, 75, 82, 100, 103, 85, 60, 42, 93, 61, 65, 67, 66, 24, 29, 0, 3, 6, 0, 6, 10, 8, 9, 8, 7, 1, 0, 3, 0, 3, 0, 2, 21, 35, 28, 35, 97, 55, 43, 70, 30, 34, 44, 44, 2, 50, 4, 8, 42, 18, 65, 107, 92, 85, 103, 107, 110, 28, 18, 2, 33, 40, 32, 
+#> 61, 70, 104, 101, 136, 108, 118, 103, 123, 117, 115, 93, 95, 107, 81, 79, 25, 0, 57, 77, 106, 114, 114, 93, 80, 102, 76, 99, 88, 79, 3, 49, 2, 11, 6, 71, 74, 64, 27, 41, 45, 80, 46, 3, 13, 10, 24, 50, 87, 28, 47, 87, 74, 58, 26, 58, 105, 90, 82, 76, 46, 28, 33, 82, 107, 59, 92, 90, 68, 58, 5, 27, 64, 49, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 3, 0, 4, 1, 2, 0, 27, 99, 76, 11, 51, 72, 101, 83, 56, 73, 32, 64, 85, 70, 36, 10, 14, 39, 62, 97, 84, 97, 85, 53, 19, 63, 56, 6, 62, 19, NA, NA, 0, 
+#> 1, NA, 0, 0, 0, 0, 0, 3, 3, 5, 4, 4, 2, 4, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 119, 125, 125, 101, 92, 55, 30, 49, 62, 64, 59, 78, 62, 93, 70, 103, 103, 104, 105, 81, 77, 82, 2, 1, 28, 68, 67, 54, 76, 13, 41, 42, 18, 61, 86, 62, 98, 94, 88, 38, 81, 62, 60, 69, 13, 36, 93, 131, 104, 113, 112, 75, 54, 48, 73, 74, 14, 23, 20, 61, 51, 68, 63, 63, 51, 44, 43, 57, 68, 65, 68, 119, 120, 107, 52, 42, 95, 83, 95, 103, 83, 24, 0, 0, 9, 8, 8, 9, 9, 9, 
+#> 7, 5, 8, 3, 47, 33, 99, 122, 119, 113, 18, 83, 101, 86, 58, 94, 21, 36, 41, 99, 96, 113, 115, 88, 87, 60, 91, 63, 54, 24, 10, 76, 110, 106, 110, 104, 76, 95, 95, 114, 73, 39, 9, 90, 12, 27, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 31, 12, 51, 89, 37, 3, 99, 76, 91, 64, 72, 72, 38, 0, 4, 3, 38, 81, 63, 68, 68, 25, 78, 72, 61, 19, 57, 15, 0, 0, 1, 0, 1, 0, 0, 1, 3, 1, 0, 0, 0, 0, 0, 0, 4, 4, 5, 5, 6, 8, 4, 0, 2, 0, 0, 1, 1, 0, 0, 1, 5, 38, 11, 100, 85, 91, 99, 77, 68, 25, 47, 12, 15, 111, 134, 118, 101, 
+#> 73, 15, 34, 14, 21, 4, 20, 65, 87, 87, 63, 45, 57, 50, 51, 45, 76, 41, 83, 84, 70, 32, 40, 43, 9, 77, 58, 19, 1, 2, 34, 21, 41, 22, 94, 77, 59, 105, 57, 61, 42, 34, 5, 97, 82, 85, 119, 115, 127, 139, 76, 100, 48, 87, 102, 65, 78, 71, 2, 82, 109, 86, 103, 94, 95, 83, 82, 19, 78, 1, 23, 30, 32, 101, 105, 97, 81, 62, 56, 63, 23, 26, 13, 25, 10, 11, NA, NA, NA, NA, NA, NA, 0, NA, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 86, 118, 
+#> 115, 53, 102, 81, 91, 72, 46, 91, 92, 113, 101, 109, 108, 30, 68, 87, 9, 7, 0, 7, 2, 2, 0, NA, 0, 0, NA, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 1, 0, 2, 0, 4, 7, 3, 6, 4, 2, 5, 4, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 6, 3, 5, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 7, 8, 2, 0, 2, 3, 2, 0, 7, 17, 83, 101, 103, 90, 87, 108, 63, 12, 69, 83, 76, 5, 36, 1, 1, 65, 107, 80, 78, 100, 94, 86, 80, 44, 69, 12, 36, 29, 30, 37, 45, 34, 55, 65, 68, 40, 34, 20, 50, 62, 113, 59, 27, 30, 35, 35, 4, 
+#> 76, 10, 8, 5, 70, 78, 102, 102, 84, 95, 26, 46, 82, 14, 10, 9, 23, 2, 19, 83, 51, 31, 44, 99, 72, 93, 72, 97, 46, 61, 80, 92, 43, 47, 25, 18, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 67, 100, 96, 78, 39, 91, 83, 74, 0, 1, 12, 66, 27, 47, 46, 26, 19, 20, 3, 5, 20, 12, 42, 67, 91, 92, 70, 31, 26, 68, 96, 51, 8, 100, 45, 7, 52, 98, 43, 95, 80, 103, 73, 43, 22, 23, 29, 96, 47, 73, 53, 44, 42, 9, 10, 14, 3, 3, 8, 42, 104, 63, 19, 44, 14, 42, 53, 7, 28, 23, 80, 104, 101, 89, 93, 69, 96, 110, 65, 23, 62, 56, 19, 
+#> 49, 70, 87, 19, 103, 70, 23, 38, 93, 45, 52, 32, 0, 0, 0, 1, 0, 0, 0, 0, 0, 6, 0, 3, 5, 5, 8, 6, 16, 61, 83, 76, 68, 103, 100, 88, 74, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 2, 0, 0, 0, 6, 84, 99, 51, 110, 85, 52, 93, 84, 26, 43, 2, 29, 57, 97, 84, 30, 64, 96, 75, 57, 10, 29, 30, 47, 93, 97, 82, 115, 74, 35, 77, 80, 0, 2, 4, 5, 7, 4, 5, 4, 4, 0, 60, 70, 78, 66, 69, 31, 11, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 84, 60, 33, 10, 10, 50, 64, 8, 34, 48, 93, 57, 56, 28, 67, 38, 72, 50, 50, 
+#> 90, 92, 71, 67, 79, 54, 29, 54, NA, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 82, 109, 108, 32, 100, 43, 62, 55, 58, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 4, 0, 0, 1, 1, 0, 0, 2, 4, 6, 2, 2, 4, 4, 4, 2, 0, 3, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 2, 21, 41, 54, 85, 61, 26, 18, 18, 27, 31, 53, 111, 92, 89, 72, 35, 87, 2, 0, 0, 0, 0, 0, 5, 5, 4, 4, 5, 1, 4, 0, 5, 15, 104, 48, 101, 89, 81, 33, 72, 71, 46, 31, 3, 1, 1, 1, 3, 58, 75, 38, 7, 54, 109, 105, 64, 82, 101, 108, 11, 69, 82, 106, 101, 59, 101, 32, 95, 1, 1, 
+#> 0, 30, 4, 35, 59, 73, 60, 11, 54, 70, 33, 15, 3, 0, 3, NA, NA, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 58, 17, 78, 61, 72, 74, 65, 71, 83, 81, 59, 68, 82, 54, 105, 113, 97, 84, 100, 88, 86, 60, 13, 1, 12, 5, 0, 6, 7, 10, 3, 4, 1, 0, 1, 15, 35, 19, 75, 60, 64, 86, 49, 87, 90, 3, 28, 41, 70, 53, 53, 53, 20, 98, 94, 10, 119, 43, 92, 71, 66, 1, 2, 4, 10, 2, 8, 5, 2, 35, 37, 72, 67, 59, 13, 24, 60, 72, 28, 34, 101, 93, 90, 87, 40, 
+#> 72, 97, 106, 94, 79, 72, 59, 89, 81, 73, 5, 18, 53, 70, 69, 71, 67, 68, 77, 74, 59, 31, 55, 58, 79, 51, 13, 30, 53, 38, 44, 78, 77, 74, 72, 62, 57, 63, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 9, 28, 63, 42, 39, 44, 21, 2, 18, 90, 122, 112, 91, 76, 136, 102, 31, 73, 98, 30, 48, 81, 39, 87, 70, 66, 54, 20, 66, 17, 52, 84, 73, 105, 107, 94, 77, 85, 0, 1, 0, 5, 1, 0, 0, 16, 65, 80, 50, 77, 28, 26, 54, 22, 8, 27, 20, 1, 75, 66, 42, 66, 50, 102, 84, 39, 81, 70, 24, 79, 61, 55, 59, 
+#> 52, 68, 43, 0, 0, 0, 0, 0, 1, 0, 7, 0, 3, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 5, 41, 85, 54, 53, 67, 46, 13, 89, 78, 53, 44, 76, 85, 66, 56, 45, 45, 53, 89, 71, 66, 30, 2, 46, 75, 15, 76, 70, 73, 41, 12, 66, 73, 49, 18, 6, 0, 4, 1, 34, 62, 77, 43, 95, 59, 28, 27, 74, 74, 94, 87, 107, 97, 89, 91, 83, 50, 93, 67, 74, 79, 2, 10, 50, 48, 52, 49, 76, 100, 92, 59, 47, 40, 57, 1, 20, 129, 109, 115, 104, 98, 71, 41, 118, 1, 3, 12, 51, 54, 63, 45, 61, 65, 54, 
+#> 66, 57, 43, 38, 68, 48, 19, 6, 38, 2, 3, 62, 75, 54, 70, 54, 69, 85, 42, 14, 34, 0, 0, 63, 47, 80, 84, 89, 89, 71, 72, 0, 1, 4, 2, 3, 1, 9, 59, 65, 72, 77, 73, 69, 0, 0, 0, 0, 0, 0, 0, 0, 1, 4, 0, 0, 0, 0, 0, 4, 66, 65, 86, 54, 98, 24, 88, 38, 102, 20, 38, 48, 57, 52, 28, 82, 103, 75, 103, 49, 58, 97, 14, 79, 51, 38, 37, 72, 80, 95, 19, 42, 17, 76, 44, 60, 0, 1, 5, 50, 37, 40, 5, 1, 2, 51, 48, 7, 16, 9, 75, 103, 65, 100, 0, 44, 126, 99, 101, 42, 18, 64, 70, 46, 60, 1, 12, 14, 49, 55, 102, 87, 30, 
+#> 93, 93, 70, 53, 74, 32, 44, 17, 4, 27, 54, 55, 101, 9, 44, 71, 89, 94, 0, 0, 2, 2, 3, 2, 0, 1, 0, 0, 0, 1, 58, 70, 46, 9, 27, 56, 7, 7, 0, 0, 1, 0, 0, 22, 62, 79, 71, 85, 1, 0, 1, 0, 3, 26, 39, 59, 85, 35, 46, 47, 34, 94, 63, 45, 79, 75, 62, 89, 47, 0, 2, 5, 4, 3, 10, 9, 80, 88, 3, 3, 26, 80, 64, 85, 86, 9, 45, 61, 38, 10, 38, 63, 63, 66, 94, 68, 5, 57, 76, 62, 62, 74, 69, 40, 111, 43, 2, 20, 57, 69, 68, 57, 74, 76, 0, 2, 1, 0, 0, 0, 0, 0, 3, 5, 0, 35, 62, 70, 74, 27, 62, 62, 39, 2, 29, 90, 78, 34, 
+#> 38, 9, 92, 88, 8, 64, 41, 111, 18, 83, 73, 84, 22, 44, 52, 54, 65, 1, 34, 89, 93, 122, 24, 60, 49, 62, 92, 79, 56, 52, 87, 21, 12, 7, 86, 29, 61, 64, 12, 16, 81, 29, 34, 24, 57, 93, 7, 60, 84) x c(54, 77, 50, 59, 50, 62, 62, 2, 4, 48, 3, 12, 60, 80, 101, 101, 73, 92, 146, 115, 103, 117, 132, 148, 111, 152, 147, 144, 148, 72, 22, 58, 94, 90, 94, 81, 117, 118, 48, 93, 77, 3, 59, 78, 108, 83, 58, 60, 40, 17, 23, 39, 17, 15, 82, 72, 190, 225, 177, 179, 174, 167, 105, 10, 35, 43, 57, 50, 27, 35, 42, 23, 23, 10, 2, 5, 10, 18, 4, 22, 61, 49, 52, 40, 54, 43, 42, 13, 14, 27, 11, 18, 79, 54, 54, 57, 52, 44, 40, 29, 1, 84, 172, 191, 180, 184, 203, 237, 187, 158, 187, 169, 164, 55, 86, 13, 12, 0, 8, 
+#> 29, 31, 44, 40, 30, 52, 34, 39, 32, 22, 32, 34, 44, 33, 18, 16, 27, 26, 21, 8, 2, 1, 57, 197, 197, 118, 152, 232, 132, 1, 167, 208, 82, 214, 152, 168, 152, 227, 115, 165, 156, 108, 137, 105, 0, 8, 14, 25, 0, 32, 14, 17, 20, 14, 12, 10, 5, 1, 2, 28, 26, 28, 30, 30, 24, 20, 20, 25, 25, 22, 29, 19, 23, 8, 3, 0, 116, 193, 143, 104, 134, 152, 166, 143, 110, 31, 101, 55, 165, 184, 167, 78, 116, 6, 145, 166, 72, 49, 180, 152, 144, 13, 97, 0, 31, 80, 66, 78, 62, 68, 61, 63, 62, 3, 41, 45, 36, 13, 0, 20, 
+#> 65, 90, 64, 21, 85, 65, 83, 59, 82, 43, 26, 55, 19, 0, 0, 39, 101, 170, 185, 184, 143, 171, 166, 188, 184, 185, 170, 217, 189, 193, 183, 183, 92, 18, 0, 189, 208, 191, 165, 89, 144, 9, 9, 14, 25, 27, 18, 30, 34, 33, 5, 1, 4, 0, 1, 12, 22, 10, 13, 21, 13, 15, 8, 4, 17, 3, 0, 23, 28, 30, 38, 25, 11, 29, 13, 9, 10, 12, 1, 1, 0, 1, 36, 113, 212, 188, 216, 194, 248, 226, 167, 127, 208, 201, 225, 161, 191, 143, 197, 211, 189, 211, 157, 79, 175, 114, 2, 21, 35, 173, 160, 170, 130, 178, 141, 136, 149, 159, 
+#> 123, 138, 123, 96, 131, 95, 78, 31, 16, 3, 5, 1, 15, 133, 129, 149, 136, 135, 130, 128, 71, 126, 48, 6, 0, 79, 64, 51, 142, 114, 100, 114, 83, 127, 57, 65, 63, 36, 37, 69, 45, 15, 70, 123, 146, 110, 83, 107, 95, 117, 80, 54, 14, 80, 57, 86, 90, 162, 41, 174, 84, 37, 216, 38, 198, 70, 4, 77, 5, 83, 191, 168, 202, 184, 206, 110, 171, 145, 150, 85, 157, 129, 145, 146, 158, 113, 127, 1, 0, 1, 15, 19, 13, 20, 13, 25, 22, 18, 23, 9, 11, 4, 15, 24, 4, 15, 21, 12, 23, 21, 25, 21, 9, 9, 1, 80, 176, 192, 201, 
+#> 194, 176, 182, 171, 199, 175, 180, 201, 168, 178, 158, 181, 124, 139, 155, 124, 61, 34, 47, 117, 180, 160, 209, 122, 127, 154, 140, 144, 158, 154, 151, 149, 88, 97, 20, 136, 141, 94, 136, 127, 125, 122, 114, 35, 163, 127, 137, 73, 52, 16, 41, 0, 0, 17, 29, 12, 20, 23, 24, 27, 20, 20, 14, 17, 14, 11, 14, 13, 11, 23, 12, 6, 6, 6, 3, 3, 9, 18, 3, 0, 24, 135, 158, 98, 91, 142, 168, 173, 146, 138, 112, 137, 68, 45, 32, 22, 77, 3, 8, 90, 198, 188, 180, 189, 184, 181, 173, 168, 163, 91, 165, 224, 177, 194, 
+#> 182, 194, 147, 129, 76, 10, 0, 1, 23, 35, 83, 85, 67, 70, 62, 45, 19, 17, 4, 2, 0, 23, 81, 86, 52, 48, 16, 0, 3, 26, 168, 183, 167, 222, 189, 193, 176, 211, 184, 150, 146, 214, 183, 161, 218, 167, 167, 164, 171, 51, 18, 35, 25, 31, 29, 17, 26, 16, 21, 11, 18, 24, 8, 9, 24, 15, 4, 4, 13, 13, 24, 30, 38, 35, 30, 34, 32, 33, 40, 24, 17, 30, 22, 18, 32, 42, 20, 16, 39, 35, 45, 35, 32, 34, 32, 27, 33, 28, 25, 7, 4, 24, 1, 0, 9, 18, 23, 36, 15, 6, 14, 0, 125, 49, 37, 71, 150, 20, 145, 130, 130, 118, 150, 
+#> 150, 128, 124, 163, 117, 124, 133, 113, 18, 32, 9, 24, 46, 84, 111, 135, 125, 65, 72, 33, 78, 88, 17, 14, 1, 0, 2, 2, 16, 26, 12, 33, 16, 12, 6, 3, 17, 13, 16, 16, 15, 2, 7, 2, 41, 55, 44, 67, 69, 144, 140, 124, 151, 112, 123, 88, 88, 21, 1, 5, 0, 1, 117, 34, 114, 143, 151, 149, 128, 136, 166, 151, 153, 143, 92, 64, 29, 131, 152, 75, 14, 1, 0, 3, 6, 12, 11, 12, 23, 1, 9, 14, 0, 0, 7, 68, 50, 126, 100, 150, 155, 129, 34, 15, 19, 148, 81, 5, 8, 23, 40, 31, 57, 50, 81, 30, 15, 0, 0, 12, 47, 43, 53, 
+#> 94, 93, 55, 26, 4, 16, 8, 56, 14, 29, 45, 28, 1, 3, 21, 11, 10, 19, 0, 22, 18, 20, 25, 23, 11, 20, 25, 13, 9, 12, 9, 16, 12, 8, 0, 3, 5, 60, 81, 98, 109, 98, 64, 75, 45, 0, 6, 7, 9, 101, 180, 159, 165, 144, 141, 172, 128, 142, 144, 171, 160, 101, 63, 44, 119, 35, 3, 21, 12, 2, 2, 2, 1, 9, 165, 159, 198, 200, 190, 182, 97, 156, 154, 166, 97, 65, 0, 66, 57, 133, 103, 54, 77, 67, 69, 61, 47, 29, 55, 1, 14, 17, 13, 4, 6, 7, 2, 12, 3, 3, 3, 29, 233, 226, 197, 153, 43, 99, 202, 162, 23, 181, 218, 77, 41, 
+#> 86, 95, 86, 66, 108, 105, 80, 81, 43, 33, 21, 10, 27, 2, 61, 104, 130, 133, 118, 109, 67, 59, 28, 17, 24, 19, 13, 32, 22, 33, 30, 1, 12, 27, 29, 15, 24, 15, 19, 7, 6, 23, 25, 2, 0, 146, 176, 172, 178, 156, 164, 151, 122, 122, 148, 168, 158, 205, 146, 114, 59, 116, 172, 164, 163, 184, 135, 140, 189, 15, 118, 121, 67, 110, 134, 1, 9, 83, 132, 167, 90, 97, 154, 84, 172, 139, 97, 17, 10, 0, 8, 3, 17, 21, 23, 15, 1, 6, 9, 15, 13, 6, 10, 19, 14, 12, 3, 3, 11, 22, 150, 186, 176, 181, 143, 151, 172, 115, 
+#> 134, 166, 179, 164, 191, 169, 57, 38, 0, 3, 11, 117, 140, 163, 133, 143, 111, 152, 133, 132, 157, 185, 187, 134, 20, 10, 20, 33, 42, 49, 34, 24, 17, 67, 62, 99, 43, 27, 18, 111, 2, 56, 3, 12, 9, 82, 130, 110, 134, 67, 138, 83, 64, 4, 1, 2, 33, 50, 95, 164, 207, 140, 167, 138, 116, 41, 174, 126, 113, 14, 96, 81, 152, 153, 170, 119, 119, 80, 155, 137, 132, 53, 136, 16, 120, 155, 148, 163, 175, 154, 150, 96, 85, 12, 21, 28, 24, 18, 14, 7, 55, 88, 89, 90, 90, 55, 101, 118, 134, 130, 75, 104, 40, 94, 
+#> 84, 70, 59, 16, 14, 4, 4, 18, 12, 2, 6, 9, 15, 7, 10, 21, 1, 3, 5, 30, 88, 126, 117, 126, 125, 113, 65, 43, 67, 83, 26, 13, 156, 134, 129, 33, 71, 9, 0, 124, 179, 149, 149, 127, 141, 99, 73, 13, 31, 172, 153, 138, 161, 170, 136, 177, 113, 137, 159, 191, 182, 201, 131, 212, 221, 119, 80, 18, 98, 106, 110, 95, 96, 73, 111, 131, 105, 124, 87, 30, 94, 60, 6, 1, 0, 15, 10, 14, 17, 9, 8, 11, 12, 14, 4, 10, 18, 141, 144, 124, 142, 146, 12, 128, 131, 180, 198, 161, 158, 62, 55, 7, 88, 159, 157, 146, 134, 
+#> 104, 10, 12, 82, 78, 71, 75, 85, 106, 82, 67, 96, 79, 74, 45, 55, 30, 2, 0, 1, 15, 173, 170, 169, 174, 180, 135, 162, 181, 181, 180, 168, 86, 102, 12, 33, 1, 0, 48, 131, 149, 36, 80, 66, 9, 15, 11, 0, 7, 14, 12, 6, 5, 13, 112, 0, 131, 170, 149, 182, 158, 139, 164, 118, 113, 135, 157, 15, 8, 10, 2, 4, 75, 141, 105, 74, 28, 21, 28, 66, 99, 109, 103, 107, 78, 32, 50, 143, 101, 116, 132, 91, 132, 51, 193, 209, 135, 89, 153, 141, 91, 127, 99, 1, 67, 130, 150, 129, 131, 126, 5, 37, 15, 35, 19, 133, 113, 
+#> 113, 97, 121, 192, 180, 180, 157, 183, 104, 116, 135, 61, 19, 8, 0, 5, 15, 21, 7, 0, 11, 10, 2, 4, 1, 1, 78, 177, 190, 154, 180, 257, 216, 246, 194, 224, 178, 201, 167, 12, 205, 133, 2, 29, 37, 40, 95, 139, 172, 204, 128, 205, 200, 104, 184, 192, 173, 172, 186, 199, 156, 138, 105, 13, 48, 24, 95, 91, 66, 127, 83, 140, 153, 75, 73, 98, 108, 77, 53, 59, 14, 155, 171, 117, 163, 218, 235, 250, 163, 227, 203, 167, 205, 188, 229, 32, 118, 13, 3, 27, 7, 5, 2, 18, 3, 28, 1, 26, 3, 89, 78, 88, 33, 61, 52, 
+#> 49, 70, 6, 40, 62, 37, 7, 5, 1, 68, 160, 180, 138, 20, 0, 150, 8, 74, 13, 117, 145, 133, 151, 132, 127, 126, 169, 208, 106, 164, 177, 52, 138, 188, 3, 17, 12, 12, 10, 2, 13, 13, 14, 14, 12, 20, 14, 20, 22, 34, 131, 103, 154, 80, 170, 119, 130, 132, 4, 24, 3, 60, 88, 70, 76, 62, 112, 77, 90, 42, 43, 1, 54, 164, 78, 13, 178, 145, 162, 196, 147, 58, 185, 168, 183, 182, 173, 41, 146, 102, 3, 110, 177, 172, 144, 143, 158, 174, 128, 75, 140, 161, 207, 188, 178, 186, 26, 72, 143, 73, 7, 2, 2, 19, 7, 17, 
+#> 21, 23, 29, 25, 31, 29, 28, 36, 17, 7, 0, 4, 49, 69, 68, 91, 89, 68, 87, 115, 157, 108, 122, 82, 73, 26, 44, 7, 72, 156, 163, 143, 169, 137, 133, 156, 143, 137, 131, 167, 137, 183, 166, 156, 117, 0, 10, 7, 2, 6, 4, 14, 14, 14, 16, 23, 17, 22, 10, 161, 116, 96, 161, 201, 89, 70, 100, 158, 150, 139, 151, 126, 132, 124, 123, 119, 133, 32, 3, 16, 18, 17, 34, 27, 22, 30, 37, 24, 18, 18, 42, 26, 3, 15, 14, 11, 3, 1, 0, 1, 0, 9, 50, 0, 91, 127, 119, 141, 141, 103, 138, 144, 166, 132, 150, 142, 124, 35, 
+#> 64, 3, 96, 59, 143, 149, 132, 151, 204, 180, 177, 174, 136, 202, 0, 5, 7, 65, 150, 108, 126, 104, 157, 177, 158, 196, 99, 26, 1, 0, 1, 3, 9, 24, 4, 32, 22, 19, 14, 10, 3, 20, 16, 14, 5, 3, 59, 177, 8, 179, 211, 185, 187, 188, 216, 227, 216, 179, 202, 199, 207, 128, 93, 25, 98, 0, 15, 25, 21, 23, 33, 15, 11, 1, 1, 13, 13, 21, 20, 25, 18, 10, 7, 11, 9, 17, 2, 1, 4, 8, 11, 8, 18, 27, 22, 16, 16, 11, 13, 13, 0, 129, 72, 85, 127, 98, 141, 153, 151, 150, 131, 137, 13, 28, 36, 4, 35, 45, 77, 67, 86, 111, 
+#> 50, 83, 43, 22, 9, 143, 152, 204, 165, 185, 200, 187, 132, 114, 8, 11, 6, 4, 1, 10, 11, 16, 25, 15, 8, 8, 9, 10, 8, 10, 2, 4, 4, 0, 9, 18, 27, 30, 8, 14, 26, 49, 23, 4, 24, 4, 22, 13, 8, 12, 43, 123, 211, 168, 223, 198, 166, 171, 208, 164, 176, 187, 161, 142, 177, 168, 104, 83, 7, 6, 12, 0, 2, 31, 157, 181, 194, 172, 185, 181, 151, 60, 119, 169, 55, 54, 49, 41, 112, 79, 132, 154, 204, 215, 149, 74, 30, 15, 4, 5, 12, 16, 13, 8, 26, 18, 25, 12, 13, 11, 1, 0, 3, 1, 11, 13, 26, 80, 105, 158, 136, 98, 
+#> 72, 182, 184, 118, 125, 104, 86, 38, 4, 2, 11, 14, 7, 14, 16, 27, 2, 25, 39, 31, 31, 42, 26, 13, 7, 2, 3, 1, 11, 18, 17, 24, 15, 15, 6, 8, 12, 8, 10, 14, 6, 9, 9, 1, 9, 15, 18, 7, 25, 13, 21, 17, 18, 22, 19, 20, 18, 15, 11, 6, 9, 9, 12, 5, 0, 24, 20, 34, 26, 32, 15, 36, 2, 23, 21, 5, 118, 143, 143, 106, 144, 171, 174, 190, 173, 174, 41, 167, 115, 77, 4, 3, 41, 77, 128, 155, 135, 135, 95, 43, 43, 35, 5, 16, 6, 12, 0, 41, 127, 156, 79, 172, 168, 237, 162, 211, 197, 225, 184, 201, 183, 156, 153, 8, 
+#> 13, 11, 23, 29, 52, 33, 29, 30, 21, 28, 37, 36, 22, 10, 0, 0, 8, 3, 8, 0, 2, 17, 23, 25, 21, 16, 25, 28, 13, 5, 7, 14, 11, 2, 1, 23, 182, 167, 195, 188, 204, 187, 180, 190, 182, 102, 146, 137, 143, 2, 31, 14, 121, 154, 173, 194, 156, 159, 145, 169, 161, 138, 124, 176, 175, 95, 79, 0, 33, 1, 0, 3, 32, 27, 67, 65, 127, 144, 44, 4, 88, 144, 47, 26, 11, 76, 75, 39, 16, 39, 15, 30, 0, 0, 0, 9, 4, 17, 30, 18, 21, 13, 26, 27, 18, 8, 15, 18, 4, 1, 5, 2, 1, 0, 5, 20, 21, 13, 13, 3, 2, 7, 0, 2, 0, 0, 20, 7, 
+#> 16, 14, 10, 15, 17, 10, 12, 9, 5, 5, 1, 2, 1, 17, 74, 112, 131, 150, 164, 187, 174, 127, 167, 118, 132, 161, 166, 171, 144, 21, 75, 32, 24, 5, 0, 14, 119, 120, 114, 131, 96, 53, 57, 19, 36, 92, 6, 84, 6, 118, 166, 183, 222, 213, 165, 166, 151, 133, 106, 110, 13, 1, 25, 0, 31, 24, 19, 29, 10, 13, 17, 7, 2, 1, 12, 1, 5, 1, 4, 13, 20, 18, 9, 16, 16, 20, 18, 15, 15, 9, 11, 10, 8, 5, 3, 0, 90, 180, 117, 126, 149, 145, 162, 146, 172, 50, 30, 140, 154, 107, 11, 5, 161, 208, 160, 189, 182, 196, 192, 192, 
+#> 182, 183, 169, 190, 137, 57, 2, 14, 62, 106, 115, 78, 132, 117, 6, 172, 107, 110, 135, 131, 142, 130, 126, 82, 85, 17, 45, 12, 93, 113, 150, 132, 138, 154, 65, 138, 155, 131, 131, 70, 84, 92, 36, 48, 9, 0, 2, 2, 56, 70, 99, 92, 142, 142, 122, 110, 132, 90, 46, 50, 25, 6, 32, 12, 12, 139, 101, 146, 137, 170, 174, 160, 152, 138, 140, 131, 34, 30, 183, 253, 199, 159, 163, 212, 211, 200, 216, 200, 192, 140, 186, 117, 142, 93, 3, 25, 3, 27, 3, 13, 116, 180, 199, 201, 201, 194, 173, 159, 129, 51, 194, 
+#> 171, 163, 187, 172, 180, 43, 9, 1, 17, 18, 22, 28, 23, 20, 38, 5, 19, 26, 20, 18, 11, 12, 14, 18, 18, 20, 16, 0, 0, 0, 10, 165, 220, 197, 88, 142, 183, 228, 202, 130, 83, 189, 42, 56, 185, 110, 69, 177, 189, 141, 160, 126, 5, 171, 76, 122, 49, 3, 49, 194, 167, 227, 180, 174, 187, 176, 148, 133, 92, 137, 158, 103, 162, 26, 9, 77, 77, 65, 55, 7, 16, 41, 103, 101, 51, 21, 13, 50, 0, 8, 16, 24, 14, 32, 33, 16, 7, 20, 1, 9, 0, 0, 0, 139, 99, 137, 92, 178, 139, 15, 14, 88, 171, 181, 143, 164, 216, 175, 
+#> 52, 2, 0, 13, 159, 134, 142, 141, 146, 170, 140, 89, 15, 121, 150, 126, 104, 6, 103, 122, 84, 188, 177, 241, 204, 65, 129, 189, 214, 221, 194, 131, 91, 155, 12, 4, 0, 9, 98, 139, 159, 125, 181, 197, 2, 136, 8, 8, 8, 10, 15, 22, 22, 23, 18, 9, 6, 7, 11, 13, 8, 9, 8, 5, 13, 14, 21, 14, 14, 11, 16, 17, 2, 0, 2, 113, 43, 170, 175, 163, 198, 208, 103, 143, 96, 45, 2, 6, 1, 7, 23, 10, 15, 0, 21, 17, 23, 11, 6, 5, 9, 5, 0, 7, 17, 9, 9, 7, 3, 1, 11, 6, 129, 179, 218, 210, 166, 220, 211, 208, 198, 210, 176, 
+#> 205, 200, 170, 4, 162, 176, 134, 193, 173, 129, 153, 154, 117, 130, 154, 109, 32, 11, 13, 0, 5, 5, 22, 20, 16, 10, 24, 16, 22, 28, 17, 9, 1, 4, 13, 0, 3, 5, 10, 14, 6, 4, 1, 0, 16, 14, 21, 25, 7, 21, 1, 10, 10, 7, 0, 0, 8, 1, 0, 1, 13, 27, 13, 15, 21, 20, 13, 8, 7, 14, 5, 12, 8, 10, 4, 5, 1, 19, 17, 12, 20, 14, 13, 13, 23, 16, 11, 16, 6, 5, 2, 3, 9, 5, 4, 180, 237, 223, 200, 217, 180, 215, 191, 217, 176, 218, 219, 175, 151, 69, 6, 82, 86, 70, 39, 1, 0, 1, 39, 156, 65, 189, 185, 226, 254, 213, 225, 
+#> 153, 213, 203, 71, 66, 78, 110, 85, 122, 21, 106, 128, 115, 105, 68, 94, 81, 81, 64, 24, 0, 1, 9, 223, 221, 234, 94, 214, 188, 138, 173, 166, 133, 177, 194, 108, 43, 21, 42, 1, 75, 4, 5, 5, 9, 6, 3, 15, 18, 4, 13, 19, 27, 19, 4, 7, 17, 3, 1, 14, 16, 6, 6, 5, 3, 14, 12, 4, 8, 16, 9, 11, 3, 11, 11, 9, 2, 4, 23, 108, 61, 114, 175, 175, 150, 157, 87, 172, 157, 20, 67, 15, 13, 14, 5, 17, 28, 15, 15, 22, 14, 19, 16, 4, 2, 14, 0, 1, 20, 102, 164, 172, 231, 175, 231, 91, 161, 167, 111, 94, 28, 82, 105, 66, 
+#> 13, 149, 133, 86, 209, 36, 139, 40, 5, 12, 6, 3, 127, 161, 193, 215, 201, 119, 184, 204, 214, 201, 227, 209, 174, 132, 161, 96, 12, 35, 9, 140, 168, 138, 105, 128, 150, 123, 135, 67, 131, 131, 97, 148, 144, 122, 116, 116, 26, 27, 0, 14, 203, 181, 231, 194, 202, 183, 179, 190, 125, 80, 84, 14, 15, 26, 30, 26, 8, 16, 13, 2, 8, 4, 10, 12, 11, 8, 19, 19, 11, 14, 13, 7, 0, 1, 22, 35, 37, 31, 38, 22, 52, 36, 12, 27, 2, 11, 1, 0, 2, 7, 153, 170, 192, 188, 147, 9, 116, 4, 39, 75, 111, 171, 38, 12, 22, 0, 
+#> 18, 22, 26, 17, 14, 10, 11, 0, 10, 1, 0, 11, 3, 23, 47, 23, 41, 38, 43, 43, 35, 23, 21, 26, 22, 5, 5, 12, 13, 20, 26, 20, 23, 26, 25, 21, 9, 8, 15, 8, 11, 4, 4, 2, 3, 5, 113, 254, 202, 172, 219, 40, 70, 56, 6, 10, 42, 131, 183, 188, 150, 213, 204, 180, 185, 198, 162, 197, 168, 153, 146, 27, 42, 1, 60, 198, 181, 209, 198, 180, 187, 162, 232, 182, 159, 15, 81, 33, 2, 22, 5, 55, 139, 203, 187, 177, 186, 143, 164, 83, 175, 172, 160, 156, 161, 24, 24, 46, 3, 1, 4, 4, 10, 8, 12, 12, 10, 8, 9, 5, 2, 5, 
+#> 98, 80, 25, 146, 147, 189, 148, 145, 133, 104, 13, 74, 14, 0, 13, 1, 10, 7, 18, 18, 23, 12, 13, 16, 9, 6, 6, 5, 5, 17, 15, 12, 21, 19, 30, 23, 13, 16, 10, 11, 7, 13, 14, 0, 18, 13, 18, 16, 21, 23, 18, 13, 9, 13, 9, 15, 9, 11, 18, 18, 15, 22, 21, 19, 19, 22, 8, 7, 5, 3, 12, 11, 5, 4, 1, 1, 91, 219, 250, 200, 226, 223, 131, 127, 32, 152, 132, 113, 9, 81, 77, 9, 1, 2, 1, 3, 11, 18, 9, 13, 10, 10, 21, 13, 11, 0, 9, 5, 0, 0, 5, 19, 30, 22, 20, 17, 21, 23, 10, 18, 9, 6, 10, 5, 0, 32, 206, 173, 138, 227, 
+#> 211, 189, 173, 191, 163, 156, 7, 146, 193, 53, 77, 10, 2, 3, 10, 16, 14, 21, 21, 2, 3, 1, 1, 14, 9, 0, 1, 25, 19, 29, 30, 27, 15, 5, 5, 4, 0, 1, 0, 71, 184, 152, 160, 189, 159, 187, 141, 152, 158, 126, 80, 123, 2, 113, 77, 91, 0, 3, 145, 124, 156, 131, 152, 127, 125, 153, 176, 142, 145, 92, 99, 79, 85, 35, 6, 178, 179, 155, 159, 172, 159, 135, 130, 161, 133, 145, 161, 55, 13, 16, 114, 136, 135, 175, 159, 155, 157, 158, 148, 150, 51, 104, 110, 25, 10, 35, 4, 19, 19, 23, 16, 13, 23, 16, 15, 22, 24, 
+#> 17, 19, 13, 11, 7, 3, 3, 8, 11, 16, 12, 26, 25, 23, 7, 14, 12, 4, 6, 14, 0, 0, 172, 199, 185, 165, 183, 174, 154, 31, 58, 125, 6, 85, 0, 13, 0, 130, 97, 111, 112, 120, 95, 103, 68, 63, 104, 35, 45, 84, 74, 98, 76, 53, 46, 33, 37, 182, 198, 224, 223, 237, 190, 201, 127, 48, 171, 166, 47, 91, 165, 62, 28, 24, 46, 4, 2, 5, 2, 9, 19, 13, 14, 12, 12, 19, 8, 1, 0, 158, 180, 186, 192, 190, 151, 174, 182, 178, 118, 137, 186, 41, 30, 4, 110, 0, 200, 118, 147, 144, 129, 173, 162, 100, 76, 11, 33, 34, 23, 2, 
+#> 1, 15, 18, 15, 4, 0, 36, 11, 22, 10, 4, 0, 0, 9, 19, 17, 16, 14, 21, 11, 15, 10, 10, 11, 2, 8, 10, 16, 2, 3, 5, 63, 188, 161, 182, 128, 32, 2, 30, 84, 73, 23, 46, 140, 179, 182, 145, 180, 164, 190, 191, 175, 160, 164, 122, 155, 150, 162, 89, 115, 139, 5, 0, 1, 2, 110, 153, 192, 201, 205, 180, 153, 151, 150, 117, 1, 7, 21, 28, 21, 16, 18, 16, 14, 15, 10, 13, 1, 0, 135, 201, 203, 16, 200, 175, 156, 195, 18, 84, 145, 100, 0, 19, 58, 129, 195, 202, 214, 188, 171, 198, 183, 200, 180, 166, 182, 169, 149, 
+#> 60, 42, 0, 6, 189, 194, 115, 138, 216, 145, 193, 201, 153, 114, 11, 7, 154, 147, 166, 67, 208, 186, 153, 101, 81, 67, 141, 156, 51, 4, 0, 124, 77, 189, 131, 161, 177, 103, 79, 86, 72, 24, 84, 144, 179, 127, 172, 114, 162, 46, 12, 206, 215, 194, 176, 179, 193, 186, 146, 168, 190, 94, 158, 109, 2, 18, 32, 20, 23, 2, 10, 25, 6, 3, 6, 12, 2, 6, 12, 2, 9, 13, 5, 15, 14, 6, 20, 16, 10, 1, 3, 7, 3, 0, 2, 112, 202, 208, 181, 134, 166, 132, 156, 147, 150, 168, 36, 46, 70, 49, 85, 70, 26, 8, 69, 134, 197, 
+#> 137, 161, 204, 182, 89, 162, 197, 186, 142, 192, 21, 180, 154, 156, 148, 30, 42, 21, 116, 133, 167, 173, 195, 191, 191, 186, 166, 154, 108, 193, 92, 65, 155, 57, 153, 151, 162, 144, 182, 160, 156, 63, 59, 4, 8, 22, 17, 19, 15, 16, 12, 18, 9, 13, 14, 14, 1, 9, 12, 1, 13, 9, 13, 13, 10, 3, 5, 1, 4, 8, 1, 8, 13, 9, 12, 5, 0, 1, 1, 2, 0, 4, 10, 21, 2, 0, 8, 1, 176, 200, 207, 144, 186, 94, 32, 146, 125, 7, 121, 166, 83, 14, 22, 16, 3, 0, 3, 0, 136, 204, 179, 197, 182, 150, 165, 127, 177, 162, 102, 6, 
+#> 76, 86, 36, 26, 14, 140, 125, 212, 199, 130, 170, 139, 26, 6, 42, 25, 13, 24, 22, 13, 18, 6, 0, 0, 1, 2, 1, 0, 80, 192, 181, 179, 196, 213, 147, 148, 58, 1, 17, 10, 14, 38, 35, 3, 37, 36, 38, 29, 28, 37, 37, 26, 24, 35, 11, 27, 20, 10, 3, 5, 36, 68, 82, 63, 6, 36, 22, 23, 133, 146, 99, 74, 60, 104, 111, 69, 13, 25, 43, 76, 31, 1, 14, 14, 172, 126, 78, 199, 158, 116, 50, 113, 87, 47, 123, 116, 34, 0, 0, 0, 17, 1, 22, 23, 19, 3, 31, 18, 4, 23, 9, 0, 12, 11, 5, 2, 10, 14, 2, 10, 4, 7, 3, 2, 0, 1, 5, 
+#> 15, 4, 6, 10, 11, 13, 18, 5, 11, 4, 2, 0, 5, 27, 209, 209, 191, 162, 156, 143, 177, 160, 143, 75, 9, 45, 54, 125, 99, 127, 114, 129, 123, 167, 129, 120, 105, 102, 90, 95, 113, 69, 31, 0, 32, 37, 11, 84, 137, 163, 157, 112, 114, 10, 24, 12, 15, 20, 13, 10, 11, 11, 7, 1, 14, 4, 4, 8, 1, 159, 139, 150, 166, 152, 134, 40, 55, 72, 37, 117, 161, 173, 162, 173, 135, 79, 153, 154, 136, 87, 155, 168, 174, 165, 146, 176, 184, 137, 152, 160, 116, 170, 148, 3, 9, 17, 21, 18, 18, 4, 16, 18, 9, 17, 10, 10, 7, 
+#> 6, 9, 1, 0, 0, 12, 1, 2, 19, 21, 16, 9, 1, 7, 18, 18, 9, 14, 12, 12, 1, 0, 2, 3, 185, 193, 185, 186, 176, 181, 188, 194, 106, 169, 4, 37, 133, 114, 138, 163, 135, 69, 98, 8, 14, 50, 19, 78, 24, 29, 38, 9, 10, 39, 24, 20, 24, 24, 30, 14, 7, 12, 4, 0, 20, 13, 8, 4, 12, 13, 40, 6, 0, 11, 12, 9, 10, 7, 0, 43, 139, 135, 146, 55, 133, 141, 150, 138, 139, 154, 82, 9, 5, 13, 0, 67, 67, 48, 142, 133, 176, 115, 122, 57, 18, 2, 45, 203, 94, 54, 97, 113, 133, 35, 32, 149, 140, 174, 175, 155, 142, 143, 149, 148, 
+#> 88, 9, 7, 79, 0, 56, 137, 49, 92, 122, 143, 123, 15, 40, 47, 144, 91, 25, 38, 40, 2, 133, 143, 151, 159, 139, 49, 148, 36, 66, 29, 16, 16, 0, 0, 65, 146, 135, 173, 188, 167, 136, 65, 119, 129, 70, 13, 41, 24, 13, 1, 9, 79, 157, 140, 130, 129, 112, 100, 58, 146, 115, 55, 39, 18, 167, 131, 139, 128, 130, 125, 124, 59, 3, 2, 12, 5, 15, 25, 15, 23, 29, 6, 3, 4, 14, 4, 6, 1, 19, 13, 7, 13, 125, 170, 164, 181, 190, 139, 170, 218, 13, 117, 44, 13, 33, 100, 157, 167, 161, 128, 164, 147, 151, 132, 87, 42, 
+#> 145, 115, 192, 127, 168, 155, 20, 58, 1, 12, 2, 15, 6, 0, 6, 3, 0, 7, 6, 14, 26, 14, 17, 2, 2, 3, 15, 8, 6, 1, 1, 0, 0, 1, 16, 15, 18, 1, 3, 0, 12, 3, 5, 5, 3, 156, 71, 66, 184, 149, 117, 120, 30, 60, 16, 38, 6, 0, 0, 2, 11, 17, 21, 8, 9, 10, 1, 10, 10, 1, 0, 1, 109, 193, 158, 132, 188, 183, 162, 176, 191, 161, 115, 153, 143, 31, 86, 1, 62, 24, 53, 42, 3, 17, 59, 100, 131, 88, 125, 120, 134, 114, 155, 54, 138, 119, 110, 52, 57, 49, 8, 197, 169, 98, 182, 107, 120, 153, 0, 159, 191, 138, 156, 179, 
+#> 111, 169, 96, 139, 166, 57, 9, 1, 18, 9, 10, 12, 2, 0, 1, 7, 8, 9, 15, 10, 15, 4, 7, 8, 1, 13, 10, 15, 18, 18, 30, 7, 17, 5, 7, 0, 11, 20, 1, 5, 15, 5, 1, 0, 4, 14, 2, 9, 11, 15, 25, 0, 4, 14, 12, 19, 47, 203, 152, 187, 169, 141, 92, 3, 77, 1, 169, 148, 164, 165, 138, 157, 171, 177, 185, 113, 75, 24, 53, 104, 1, 14, 2, 16, 13, 13, 19, 17, 19, 6, 2, 14, 0, 6, 0, 11, 8, 3, 2, 1, 0, 10, 8, 0, 0, 0, 121, 138, 134, 117, 135, 119, 116, 147, 143, 140, 92, 46, 0, 54, 106, 89, 81, 89, 109, 95, 126, 24, 54, 
+#> 63, 23, 16, 205, 208, 207, 159, 185, 153, 150, 10, 45, 90, 3, 40, 1, 115, 138, 101, 186, 153, 150, 155, 161, 157, 160, 39, 97, 8, 166, 77, 141, 131, 82, 85, 12, 116, 71, 1, 12, 4, 9, 16, 20, 36, 25, 20, 11, 15, 2, 12, 14, 6, 3, 0, 4, 4, 10, 3, 0, 0, 19, 11, 15, 14, 10, 12, 1, 200, 98, 106, 104, 89, 26, 1, 0, 20, 147, 220, 197, 228, 183, 230, 207, 192, 205, 194, 200, 195, 179, 184, 176, 159, 87, 91, 107, 143, 86, 1, 1, 11, 14, 16, 13, 30, 25, 20, 9, 5, 6, 1, 6, 49, 123, 143, 126, 7, 75, 157, 77, 86, 
+#> 31, 111, 9, 107, 82, 30, 49, 3, 31, 18, 21, 126, 123, 1, 1, 103, 141, 118, 144, 82, 116, 0, 4, 60, 205, 195, 122, 146, 130, 41, 0, 71, 19, 0, 0, 8, 9, 8, 12, 29, 28, 13, 19, 19, 18, 13, 9, 10, 4, 2, 0, 43, 161, 144, 166, 183, 160, 157, 128, 176, 153, 135, 162, 137, 62, 54, 40, 71, 134, 177, 148, 63, 1, 3, 128, 166, 130, 0, 154, 73, 39, 99, 0, 4, 0, 1, 22, 10, 9, 9, 2, 7, 7, 1, 33, 147, 167, 173, 141, 158, 163, 152, 158, 145, 150, 167, 172, 116, 3, 90, 2, 2, 19, 7, 179, 140, 63, 47, 171, 165, 114, 
+#> 163, 191, 182, 184, 162, 129, 51, 21, 39, 168, 121, 158, 168, 161, 75, 10, 138, 181, 168, 122, 138, 105, 174, 156, 147, 95, 34, 64, 21, 0, 28, 34, 124, 0, 17, 12, 1, 63, 69, 71, 60, 28, 32, 24, 27, 9, 1, 0, 1, 5, 2, 19, 21, 11, 7, 6, 4, 6, 8, 3, 0, 3, 15, 9, 4, 0, 1, 6, 9, 12, 9, 4, 0, 0, 19, 43, 11, 59, 159, 28, 21, 69, 141, 162, 1, 145, 110, 104, 8, 162, 125, 94, 64, 15, 54, 99, 130, 154, 197, 177, 150, 144, 93, 106, 70, 64, 15, 6, 50, 0, 3, 93, 150, 150, 165, 156, 159, 47, 2, 22, 126, 159, 66, 
+#> 155, 171, 146, 156, 69, 47, 158, 153, 146, 67, 24, 61, 39, 31, 0, 8, 11, 7, 11, 20, 12, 21, 14, 12, 6, 7, 11, 15, 12, 7, 11, 13, 7, 8, 13, 1, 0, 1, 0, 155, 170, 195, 224, 176, 191, 190, 101, 96, 5, 4, 0, 1, 0, 0, 11, 13, 2, 10, 1, 8, 7, 1, 1, 4, 16, 17, 18, 5, 9, 1, 0, 24, 133, 46, 69, 197, 1, 87, 28, 39, 3, 103, 151, 143, 51, 149, 92, 71, 3, 159, 168, 148, 207, 159, 135, 170, 17, 100, 160, 143, 205, 173, 162, 125, 65, 104, 20, 1, 1, 138, 154, 142, 26, 188, 112, 179, 218, 191, 88, 45, 141, 24, 66, 
+#> 134, 90, 25, 92, 0, 45, 98, 68, 82, 89, 64, 15, 17, 0, 58, 185, 149, 143, 154, 191, 106, 151, 165, 199, 135, 70, 73, 0, 5, 7, 7, 14, 15, 8, 16, 12, 5, 0, 13, 4, 1, 13, 6, 3, 0, 125, 72, 6, 143, 132, 141, 79, 144, 158, 127, 19, 8, 4, 95, 95, 63, 88, 59, 36, 57, 71, 77, 40, 59, 21, 16, 4, 169, 149, 171, 184, 185, 142, 171, 165, 145, 167, 164, 140, 86, 21, 4, 2, 28, 37, 25, 20, 21, 11, 4, 19, 17, 6, 0, 0, 85, 136, 144, 154, 135, 155, 172, 138, 176, 152, 142, 171, 156, 147, 74, 33, 126, 165, 178, 169, 
+#> 145, 185, 186, 193, 189, 143, 1, 27, 195, 195, 166, 147, 145, 109, 129, 134, 109, 157, 75, 8, 82, 143, 115, 192, 161, 146, 149, 179, 147, 155, 121, 115, 134, 99, 107, 52, 43, 2, 0, 10, 7, 8, 14, 13, 16, 17, 15, 14, 13, 5, 8, 66, 127, 96, 90, 149, 129, 142, 158, 181, 118, 41, 78, 139, 79, 31, 26, 9, 33, 23, 0, 10, 1, 0, 6, 13, 11, 4, 13, 24, 5, 1, 0, 0, 124, 177, 147, 170, 149, 164, 126, 117, 40, 159, 78, 0, 4, 2, 12, 15, 5, 4, 11, 3, 0, 4, 4, 2, 0, 1, 7, 16, 15, 18, 23, 22, 18, 23, 21, 17, 22, 13, 
+#> 36, 24, 14, 21, 18, 16, 11, 4, 3, 103, 144, 171, 146, 153, 70, 132, 15, 106, 95, 18, 7, 175, 170, 203, 170, 185, 157, 159, 120, 81, 98, 134, 146, 138, 147, 146, 176, 114, 71, 30, 37, 10, 31, 42, 89, 112, 102, 76, 68, 87, 5, 125, 109, 83, 36, 25, 1, 0, 16, 18, 34, 29, 37, 21, 28, 26, 21, 19, 18, 3, 3, 1, 10, 19, 13, 17, 15, 13, 9, 9, 6, 0, 29, 27, 40, 19, 65, 69, 101, 106, 125, 95, 22, 37, 105, 61, 16, 4, 4, 9, 9, 11, 10, 8, 4, 1, 1, 0, 3, 0, 2, 7, 10, 0, 0, 3, 175, 146, 164, 196, 177, 194, 189, 134, 
+#> 52, 118, 169, 137, 19, 126, 42, 48, 5, 9, 7, 10, 7, 7, 2, 0, 0, 12, 109, 75, 97, 120, 173, 43, 97, 125, 50, 44, 20, 103, 74, 1, 13, 29, 19, 25, 8, 21, 3, 6, 7, 96, 97, 185, 172, 143, 70, 45, 118, 19, 81, 65, 127, 145, 12, 68, 125, 83, 1, 34, 0, 6, 0, 12, 120, 170, 159, 156, 129, 157, 176, 158, 146, 173, 123, 114, 39, 52, 32, 5, 8, 6, 119, 132, 119, 156, 139, 146, 158, 151, 127, 111, 35, 8, 72, 125, 123, 164, 126, 162, 82, 142, 85, 80, 22, 24, 23, 15, 42, 26, 17, 21, 5, 32, 5, 6, 144, 88, 20, 6, 77, 
+#> 119, 138, 139, 172, 162, 93, 131, 145, 125, 108, 22, 10, 4, 1, 8, 6, 12, 13, 4, 0, 11, 5, 3, 0, 0, 0, 158, 157, 121, 150, 117, 169, 200, 148, 147, 112, 60, 37, 12, 123, 150, 90, 17, 2, 65, 22, 47, 42, 6, 180, 86, 35, 128, 150, 90, 127, 96, 57, 10, 47, 42, 4, 48, 7, 0, 1, 12, 11, 19, 14, 7, 5, 3, 18, 6, 2, 1, 0, 10, 0, 0, 3, 4, 3, 1, 11, 0, 0, 1, 0, 0, 95, 129, 108, 177, 189, 197, 105, 165, 161, 164, 151, 121, 119, 27, 2, 20, 39, 161, 199, 168, 162, 198, 199, 166, 158, 139, 102, 114, 57, 69, 44, 86, 
+#> 35, 16, 13, 16, 16, 9, 8, 8, 4, 0, 19, 7, 1, 2, 116, 174, 172, 150, 164, 168, 178, 104, 90, 114, 40, 11, 19, 0, 159, 160, 141, 0, 5, 132, 153, 164, 132, 143, 135, 157, 143, 135, 120, 70, 14, 12, 123, 146, 154, 102, 152, 136, 156, 126, 109, 87, 127, 30, 195, 185, 171, 195, 208, 180, 190, 176, 189, 187, 171, 177, 159, 128, 144, 114, 139, 113, 52, 9, 44, 5, 8, 17, 5, 13, 8, 0, 5, 9, 0, 1, 2, 1, 2, 0, 7, 8, 1, 5, 5, 8, 14, 10, 4, 3, 3, 7, 11, 18, 19, 9, 1, 6, 2, 10, 8, 5, 1, 7, 0, 2, 1, 0, 0, 0, 10, 
+#> 5, 34, 138, 104, 36, 148, 138, 153, 104, 150, 55, 45, 98, 59, 1, 0, 10, 18, 9, 3, 2, 0, 0, 5, 4, 0, 1, 3, 0, 0, 91, 171, 136, 163, 158, 188, 173, 158, 154, 145, 163, 121, 54, 141, 92, 96, 108, 103, 11, 5, 12, 15, 14, 22, 15, 27, 20, 13, 20, 17, 12, 3, 10, 16, 9, 6, 5, 2, 1, 10, 151, 131, 115, 64, 1, 9, 15, 97, 151, 21, 121, 68, 35, 127, 63, 78, 92, 0, 1, 1, 7, 159, 152, 171, 201, 140, 120, 111, 26, 209, 201, 190, 196, 173, 179, 198, 146, 125, 148, 121, 92, 26, 14, 1, 47, 168, 171, 134, 178, 154, 
+#> 145, 156, 138, 107, 159, 148, 76, 104, 51, 157, 170, 167, 111, 190, 177, 160, 188, 193, 192, 148, 99, 48, 122, 78, 112, 0, 58, 36, 43, 0, 6, 1, 1, 0, 6, 15, 25, 9, 12, 14, 5, 0, 1, 0, 0, 0, 44, 38, 56, 57, 53, 39, 9, 10, 3, 1, 1, 6, 0, 3, 0, 0, 0, 0, 193, 175, 161, 152, 69, 164, 140, 152, 59, 90, 26, 18, 1, 104, 164, 165, 157, 159, 180, 187, 192, 156, 34, 88, 30, 32, 53, 64, 3, 60, 165, 179, 160, 189, 146, 115, 124, 95, 8, 11, 41, 0, 3, 2, 11, 16, 17, 14, 11, 19, 16, 8, 4, 0, 0, 2, 0, NA, 0, 0, 0, 
+#> 0, 0, 11, 17, 11, 15, 9, 16, 9, 16, 14, 9, 0, 8, 7, 0, 2, 1, 10, 16, 1, 1, 5, 3, 0, 0, 150, 170, 15, 141, 161, 132, 108, 156, 164, 149, 115, 134, 1, 0, 2, 63, 113, 189, 192, 178, 201, 198, 192, 196, 187, 191, 175, 152, 166, 140, 117, 11, 128, 175, 138, 144, 150, 167, 137, 182, 152, 175, 142, 144, 117, 137, 113, 25, 78, 11, 7, 139, 200, 194, 170, 170, 167, 153, 190, 121, 172, 154, 112, 138, 141, 94, 124, 130, 119, 87, 79, 146, 7, 20, 10, 14, 17, 6, 15, 15, 8, 17, 10, 13, 8, 15, 0, 2, 11, 163, 176, 
+#> 160, 169, 193, 179, 162, 142, 164, 98, 156, 162, 139, 158, 136, 143, 56, 16, 23, 22, 6, 19, 14, 15, 12, 6, 8, 6, 5, 2, 3, 0, 3, 0, 0, 142, 148, 148, 157, 166, 170, 140, 150, 154, 127, 182, 127, 164, 168, 173, 114, 112, 135, 166, 197, 149, 168, 138, 176, 208, 125, 174, 172, 182, 149, 113, 166, 144, 128, 86, 142, 107, 10, 28, 15, 140, 182, 144, 175, 174, 168, 194, 178, 176, 185, 139, 132, 47, 39, 3, 60, 7, 131, 189, 200, 198, 196, 223, 172, 197, 191, 201, 187, 181, 168, 184, 174, 164, 154, 162, 119, 
+#> 118, 91, 109, 62, 0, 5, 9, 20, 16, 17, 11, 11, 12, 16, 17, 17, 13, 12, 8, 12, 4, 3, 0, 0, 4, 9, 7, 20, 16, 13, 24, 21, 16, 21, 9, 1, 3, 12, 0, 2, 6, 1, 0, 7, 17, 185, 185, 169, 161, 157, 175, 169, 142, 87, 32, 15, 7, 8, 74, 111, 78, 90, 96, 77, 111, 132, 90, 115, 134, 106, 95, 59, 17, 3, 167, 6, 160, 174, 182, 149, 172, 176, 168, 172, 184, 151, 19, 72, 7, 1, 0, 42, 132, 130, 147, 126, 126, 122, 90, 65, 94, 111, 115, 80, 4, 80, 128, 47, 128, 148, 143, 155, 170, 53, 143, 95, 74, 1, 15, 10, 8, 13, 16, 
+#> 15, 13, 4, 1, 3, 3, 3, 0, 3, 6, 20, 14, 17, 13, 13, 23, 13, 12, 22, 19, 17, 5, 2, 2, 9, 3, 81, 76, 90, 118, 121, 79, 155, 138, 140, 172, 91, 105, 17, 39, 49, 0, 5, 11, 11, 8, 5, 12, 4, 4, 2, 0, 3, 4, 118, 190, 164, 121, 122, 62, 172, 167, 151, 177, 146, 55, 10, 10, 51, 87, 103, 149, 164, 122, 136, 153, 110, 132, 70, 141, 48, 2, 43, 159, 135, 146, 176, 159, 99, 78, 137, 156, 115, 16, 24, 23, 80, 30, 26, 0, 33, 138, 103, 145, 166, 185, 151, 117, 76, 83, 9, 9, 2, 62, 149, 156, 119, 147, 148, 155, 131, 
+#> 161, 134, 163, 167, 127, 52, 84, 49, 12, 60, 56, 104, 112, 104, 74, 97, 116, 133, 158, 6, 104, 52, 45, 30, 25, 3, 28, 18, 12, 22, 2, 21, 11, 12, 17, 8, 13, 2, 0, 0, 12, 50, 2, 163, 147, 160, 158, 182, 153, 157, 148, 131, 146, 32, 15, 20, 123, 160, 176, 59, 100, 0, 188, 192, 169, 182, 191, 183, 161, 6, 14, 137, 183, 149, 147, 173, 69, 25, 0, 159, 23, 39, 2, 116, 172, 125, 166, 172, 158, 84, 114, 13, 120, 152, 109, 50, 42, 10, 7, 20, 0, 4, 3, 7, 14, 10, 16, 16, 10, 12, 6, 11, 11, 9, 5, 3, 0, 1, 0, 
+#> 7, 6, 2, 2, 1, 0, 3, 4, 0, 0, 0, 1, 2, 15, 29, 19, 15, 33, 23, 10, 18, 20, 22, 25, 17, 15, 23, 10, 15, 22, 15, 6, 7, 3, 39, 121, 120, 177, 122, 80, 132, 10, 57, 105, 12, 13, 116, 130, 153, 129, 112, 127, 59, 41, 21, 2, 7, 149, 126, 136, 138, 143, 141, 102, 37, 128, 116, 43, 15, 68, 62, 89, 67, 158, 80, 149, 148, 126, 153, 157, 143, 91, 56, 102, 87, 104, 5, 41, 134, 80, 88, 23, 0, 1, 14, 10, 10, 9, 11, 16, 5, 2, 0, 0, 3, 11, 12, 16, 10, 12, 12, 16, 17, 5, 14, 5, 19, 20, 16, 3, 2, 10, 28, 110, 89, 
+#> 175, 192, 192, 148, 194, 166, 167, 164, 154, 140, 168, 160, 139, 141, 159, 97, 46, 7, 2, 1, 20, 38, 14, 126, 139, 146, 145, 110, 117, 93, 18, 58, 145, 140, 125, 151, 122, 89, 62, 87, 35, 1, 10, 36, 84, 41, 99, 118, 141, 159, 151, 84, 144, 37, 81, 107, 79, 130, 7, 156, 157, 169, 199, 200, 191, 157, 159, 77, 92, 12, 109, 139, 142, 158, 175, 163, 186, 164, 199, 201, 186, 149, 152, 3, 12, 0, 0, 135, 132, 34, 109, 150, 138, 13, 116, 20, 51, 48, 27, 30, 4, 7, 3, 120, 79, 146, 114, 98, 149, 137, 133, 164, 
+#> 175, 160, 153, 8, 70, 58, 73, 92, 143, 139, 127, 84, 166, 150, 129, 48, 80, 71, 153, 84, 27, 0, 6, 14, 9, 10, 10, 10, 2, 0, 7, 0, 4, 3, 3, 5, 1, 5, 6, 6, 3, 6, 5, 3, 1, 1, 1, 7, 19, 2, 1, 6, 4, 2, 2, 2, 0, 2, 1, 0, 0, 0, 4, 1, 2, 0, NA, 0, 9, 8, 10, 1, 2, 0, 0, 4, 1, 78, 45, 141, 116, 173, 209, 167, 181, 164, 153, 0, 16, 19, 9, 15, 10, 17, 25, 4, 8, 0, 0, 2, 1, 4, 10, 104, 92, 61, 99, 97, 111, 119, 102, 123, 91, 82, 95, 20, 121, 169, 114, 150, 128, 179, 201, 168, 192, 211, 194, 202, 209, 146, 175, 
+#> 145, 178, 118, 26, 205, 187, 208, 181, 204, 166, 204, 178, 187, 135, 126, 164, 149, 133, 121, 112, 71, 63, 152, 173, 208, 159, 173, 186, 162, 186, 174, 129, 42, 141, 169, 17, 11, 9, 8, 5, 0, 0, 1, 0, 5, 13, 147, 184, 175, 201, 203, 179, 176, 185, 188, 205, 179, 191, 166, 113, 127, 74, 2, 25, 101, 193, 123, 133, 123, 124, 168, 118, 108, 135, 96, 128, 114, 95, 34, 4, 89, 116, 148, 151, 138, 169, 164, 162, 161, 170, 127, 42, 46, 23, 20, 15, 55, 110, 91, 127, 129, 4, 63, 58, 71, 112, 99, 98, 118, 74, 
+#> 1, 42, 22, 21, 8, 0, 0, 2, 0, 3, 3, 7, 8, 15, 8, 3, 2, 1, 3, 13, 2, 5, 0, 0, 7, 2, 0, 3, 8, 4, 4, 0, 2, 6, 2, 5, 4, 2, 5, 1, 1, 2, 0, 0, 70, 29, 21, 127, 164, 160, 162, 152, 153, 105, 46, 9, 4, 1, 6, 1, 14, 3, 4, 6, 15, 20, 7, 7, 7, 3, 1, 0, 5, 9, 15, 15, 13, 16, 22, 16, 19, 39, 20, 12, 14, 3, 0, 2, 15, 18, 8, 14, 23, 23, 17, 12, 18, 15, 15, 13, NA, 0, 0, NA, 14, 10, 7, NA, 0, NA, 5, 3, 0, 0, 5, 172, 133, 111, 121, 91, 121, 144, 116, 70, 68, 76, 81, 61, 73, 9, 2, 178, 140, 131, 168, 125, 98, 99, 
+#> 74, 26, 1, 1, 0, 0, 17, 20, 12, 9, 8, 3, 10, 16, 9, 7, 0, 0, 97, 128, 230, 181, 163, 15, 98, 174, 122, 19, 123, 11, 60, 58, 71, 21, 7, 169, 181, 130, 58, 5, 2, 6, 0, 5, 9, 11, 11, 8, 11, 4, 3, 1, 0, 3, 2, 6, 5, 0, 1, 1, 0, 0, 1, 4, 3, 5, 2, 0, 3, 7, 3, 1, 2, 0, 0, 0, 0, 0, 0, 1, 0, 2, 0, 6, 6, 7, 5, 6, 7, 7, 20, 9, 155, 191, 183, 164, 154, 165, 189, 162, 154, 186, 129, 120, 160, 155, 146, 146, 165, 145, 140, 100, 83, 126, 101, 9, 6, 143, 137, 162, 171, 182, 135, 116, 79, 49, 20, 37, 27, 115, 128, 
+#> 119, 99, 54, 43, 55, 115, 101, 74, 89, 61, 26, 0, 1, 110, 53, 94, 108, 188, 200, 211, 191, 167, 172, 186, 173, 7, 2, 76, 90, 60, 90, 21, 69, 12, 74, 116, 68, 4, 0, 0, 1, 0, 21, 25, 13, 19, 21, 15, 12, 20, 26, 6, 170, 139, 209, 205, 176, 210, 218, 205, 192, 198, 230, 185, 210, 215, 204, 198, 208, 185, 140, 172, 121, 35, 72, 107, 52, 33, 157, 154, 131, 149, 126, 93, 124, 57, 70, 131, 56, 4, 30, 4, 7, 21, 20, 14, 17, 28, 14, 20, 15, 5, 14, 10, 13, NA, 0, 19, 18, 75, 121, 181, 178, 179, 162, 169, 145, 
+#> 97, 131, 126, 61, 71, 24, 3, 5, 13, 20, 18, 15, 25, 20, 8, 16, 29, 33, 15, 20, 12, 17, 5, 0, 4, 12, 7, 7, 2, 3, 5, 1, 3, 0, 0, 108, 156, 152, 86, 103, 101, 43, 11, 26, 57, 84, 117, 12, 15, 4, 15, 24, 7, 1, 87, 164, 137, 187, 185, 173, 175, 176, 142, 166, 148, 148, 140, 143, 83, 17, 61, 98, 55, 47, 79, 39, 5, 93, 5, 6, 4, 3, 217, 185, 191, 161, 136, 197, 204, 164, 9, 166, 131, 123, 26, 7, 201, 187, 166, 142, 137, 126, 128, 162, 156, 79, 139, 97, 80, 41, 68, 118, 114, 160, 90, 160, 168, 126, 24, 19, 
+#> 8, 4, 16, 22, 9, 6, 132, 122, 156, 134, 133, 156, 108, 160, 147, 62, 153, 143, 127, 100, 60, 74, 62, 6, 51, 170, 140, 167, 154, 171, 150, 151, 167, 81, 79, 29, 42, 60, 50, 31, 16, 7, 4, 145, 144, 47, 138, 102, 132, 125, 103, 145, 112, 124, 108, 4, 1, 113, 62, 147, 193, 152, 172, 132, 115, 174, 203, 230, 157, 149, 149, 89, 95, 9, 4, 14, 6, 1, 6, 1, 6, 13, 0, 1, 0, 0, 4, 73, 156, 101, 115, 146, 142, 128, 95, 143, 98, 89, 132, 105, 64, 33, 61, 173, 133, 150, 160, 145, 97, 106, 162, 145, 146, 123, 42, 
+#> 25, 24, 120, 107, 134, 90, 137, 57, 7, 22, 5, 20, 136, 149, 129, 69, 65, 79, 95, 34, 42, 87, 79, 137, 121, 56, 44, 11, 1, 129, 144, 149, 85, 100, 27, 22, 5, 0, 50, 10, 3, 5, 11, 16, 15, 8, 13, 6, 10, 15, 15, 5, 4, 2, 5, 2, 0, 1, 2, 9, 13, 11, 8, 13, 18, 16, 16, 16, NA, 0, 2, 61, 2, 2, 130, 177, 130, 81, 71, 121, 147, 154, 49, 114, 6, 3, 23, 34, 6, 129, 5, 9, 74, 115, 145, 153, 125, 103, 160, 125, 151, 145, 156, 153, 136, 110, 51, 115, 119, 53, 17, 17, 0, 3, 1, 6, 5, 3, 4, 2, 0, 1, 0, 0, 1, 1, 2, 
+#> 0, NA, 1, 4, 2, 4, 1, 2, 0, 3, 2, 0, 1, 0, 2, 0, 3, 0, 1, 0, 105, 125, 137, 125, 123, 14, 79, 92, 33, 23, 3, 4, 2, 3, 172, 124, 80, 153, 182, 121, 96, 48, 11, 11, 44, 126, 173, 158, 116, 70, 104, 79, 86, 32, 0, 16, 154, 136, 146, 129, 136, 141, 134, 156, 126, 28, 24, 16, 0, 1, 97, 130, 123, 117, 141, 97, 137, 162, 156, 107, 117, 98, 91, 129, 63, 10, 4, 109, 131, 63, 82, 75, 63, 28, 51, 21, 4, 4, 12, 15, 15, 14, 8, 15, 20, 20, 10, 6, 1, 46, 68, 85, 120, 177, 159, 105, 165, 218, 157, 210, 134, 156, 
+#> 133, 2, 90, 10, 66, 0, 0, 0, 2, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 1, 1, 3, 13, 9, 13, 1, 3, 1, 3, 0, 1, 0, 0, 1, 0, 2, 73, 68, 174, 176, 185, 186, 164, 146, 177, 158, 144, 137, 158, 158, 132, 161, 77, 51, 61, 33, 60, 51, 1, 114, 141, 54, 146, 182, 183, 206, 184, 195, 202, 200, 193, 193, 194, 163, 150, 133, 66, 123, 8, 5, 14, 11, 4, 4, 9, 10, 8, 9, 1, 11, 5, 6, 0, 0, 6, 12, 7, 16, 15, 3, 8, 1, 3, 14, 10, 6, 9, 1, 4, 0, 147, 171, 60, 139, 142, 141, 154, 185, 170, 176, 166, 157, 96, 35, 39, 14, 0, 85, 84, 
+#> 162, 89, 178, 128, 135, 111, 140, 144, 96, 74, 43, 22, 21, 1, 0, 55, 129, 120, 102, 112, 131, 196, 146, 119, 0, 1, 124, 144, 125, 133, 61, 7, 78, 83, 17, 37, 3, 0, 150, 126, 152, 70, 177, 170, 203, 218, 192, 200, 239, 188, 130, 179, 111, 167, 160, 97, 124, 11, 15, 11, 17, 18, 13, 15, 7, 17, 7, 12, 5, 9, 12, 6, 11, 6, 10, 0, 0, NA, NA, 4, 2, 16, 117, 134, 113, 149, 139, 110, 134, 47, 132, 60, 36, 88, 7, 23, 8, 15, 43, 54, 36, 33, 1, 61, 49, 155, 107, 148, 146, 133, 156, 82, 148, 106, 145, 102, 93, 
+#> 23, 11, 0, 7, 0, 14, 16, 15, 14, 28, 20, 10, 1, NA, NA, NA, 0, 0, NA, NA, 10, 13, 1, 1, 1, 2, 7, 5, 9, 12, 8, 8, 11, 15, 6, NA, NA, NA, 7, 0, 0, 1, 5, 4, 17, 10, 18, 17, 2, 6, 2, 0, 4, 139, 148, 168, 176, 175, 126, 128, 160, 144, 63, 37, 150, 132, 64, 100, 7, 99, 3, 28, 68, 70, 151, 139, 143, 117, 102, 147, 87, 42, 55, 51, 40, 147, 188, 167, 189, 158, 170, 181, 128, 95, 44, 6, 14, 155, 156, 177, 134, 145, 141, 174, 150, 109, 136, 102, 128, 90, 55, 103, 79, 42, 12, 6, 12, 96, 108, 116, 65, 80, 80, 
+#> 9, 61, 4, 41, 10, 4, 2, 1, 4, 5, 11, 12, 14, 0, NA, 0, 0, 0, 5, NA, 1, 1, 1, 1, NA, 0, 52, 27, 115, 47, 62, 16, 53, 16, 147, 10, 115, 11, 32, 14, 13, 140, 138, 110, 146, 133, 113, 130, 77, 130, 71, 169, 105, 1, 150, 42, 32, 25, 180, 74, 0, 2, 7, 6, 15, 6, 11, 8, 14, 12, 12, NA, NA, 4, 2, 62, 146, 134, 157, 181, 168, 159, 158, 151, 155, 146, 120, 28, 32, 110, 22, 0, 0, 0, 0, 0, 0, 1, 2, 0, 2, 5, 17, NA, 0, 0, NA, NA, NA, 1, 57, 81, 40, 29, 13, 47, 53, 25, 0, 0, 0, 0, 8, 13, 11, 12, 10, 11, 11, NA, 
+#> NA, NA, NA, NA, 8, 129, 126, 122, 143, 149, 144, 83, 151, 114, 1, 50, 15, 17, 1, 3, 32, 98, 152, 100, 133, 53, 106, 111, 100, 141, 83, 74, 33, 61, 23, 12, 25, 32, 165, 174, 183, 167, 128, 185, 139, 191, 150, 78, 19, 28, 0, 20, 95, 113, 154, 140, 111, 129, 120, 140, 62, 124, 117, 24, 0, 0, 139, 163, 125, 179, 128, 158, 39, 92, 112, 148, 137, 92, 44, 80, 43, 26, 160, 104, 126, 116, 147, 126, 135, 64, 146, 77, 23, 82, 5, 21, 138, 151, 101, 157, 132, 158, 146, 150, 138, 150, 140, 138, 154, 79, 146, 77, 
+#> 117, 116, 101, 74, 1, 75, 124, 127, 95, 159, 152, 139, 125, 87, 121, 96, 51, 0, 4, 11, 12, 17, 16, 17, 23, 16, 25, 14, 20, 26, 25, 21, 19, 9, 22, 19, 16, 5, NA, 7, 2, NA, NA, NA, 1, 62, 57, 11, 66, 75, 183, 186, 185, 231, 201, 192, 34, 127, 147, 3, 16, 2, 11, 136, 101, 151, 164, 140, 161, 92, 88, 130, 12, 8, 1, 1, 3, 2, 3, 2, 1, 0, 2, 1, 0, 0, 0, 0, 0, 1, 2, 1, 1, 2, NA, 0, NA, 0, 0, 11, 67, 155, 129, 184, 171, 119, 150, 31, 51, 114, 65, 26, 15, 22, 12, 11, 0, 11, 2, 9, 13, 8, 6, 16, 24, 17, 11, 
+#> NA, NA, NA, 0, 13, 98, 140, 121, 47, 21, 94, 98, 107, 131, 116, 34, 85, 61, 9, 35, 17, 1, 0, 20, 138, 134, 110, 126, 40, 19, 83, 63, 12, 12, 2, 1, 12, 103, 120, 117, 127, 69, 128, 66, 118, 118, 64, 8, 54, 89, 140, 145, 118, 131, 146, 137, 100, 121, 46, 75, 117, 140, 148, 100, 129, 149, 59, 7, 22, 137, 113, 143, 156, 135, 190, 186, 183, 183, 110, 0, 15, 14, 7, 17, 10, 15, 8, 0, 4, 4, 8, 12, 12, 15, 13, 16, 13, 13, 7, NA, 2, NA, 0, 3, 4, 10, 10, 11, 14, 4, 0, NA, NA, NA, 13, 16, 67, 64, 194, 186, 171, 
+#> 94, 95, 129, 71, 2, 15, 4, 0, 3, 12, 2, 0, 0, NA, NA, 0, 6, 10, 5, 7, NA, NA, 4, 4, 13, 14, 176, 167, 158, 175, 157, 116, 165, 120, 145, 170, 99, 100, 136, 93, 16, 78, 161, 200, 178, 162, 182, 145, 143, 100, 156, 25, 126, 148, 47, 35, 28, 86, 171, 126, 180, 133, 177, 146, 161, 155, 181, 198, 178, 171, 180, 102, 42, 132, 14, 4, 22, 137, 88, 98, 137, 138, 90, 92, 75, 16, 84, 48, 22, 20, 49, 114, 136, 156, 22, 97, 171, 188, 172, 171, 155, 170, 110, 144, 125, 100, 40, 38, 0, 7, 129, 146, 109, 105, 92, 
+#> 39, 45, 84, 19, 17, 99, 158, 168, 137, 144, 89, 100, 5, 124, 127, 152, 147, 103, 32, 39, 9, 12, 146, 146, 175, 171, 187, 166, 157, 138, 147, 140, 49, 72, 80, 31, 32, 4, 19, 47, 109, 156, 70, 84, 45, 45, 32, 36, 29, 20, 1, 5, 7, 1, 13, 17, 20, 22, NA, NA, NA, NA, NA, NA, NA, 0, NA, NA, NA, NA, 0, 25, 116, 162, 169, 153, 154, 168, 147, 149, 152, 137, 148, 137, 116, 54, 16, 28, 26, 139, 158, 170, 155, 166, 171, 158, 113, 157, 58, 17, 12, 0, 0, 2, 0, 3, 0, 1, NA, NA, NA, NA, 0, NA, 0, 7, 2, 6, 17, 13, 
+#> 15, 5, 3, 1, 0, 4, 1, 3, 0, 0, 0, 6, 7, 163, 121, 136, 5, 126, 147, 149, 161, 167, 150, 163, 151, 150, 104, 109, 112, 74, 134, 93, 89, 6, 32, 49, 51, 132, 102, 127, 104, 102, 90, 122, 70, 30, 32, 11, 3, 4, 3, 10, 16, 13, 11, 14, 14, 10, 17, NA, NA, 0, NA, NA, NA, 8, 6, NA, NA, 12, NA, NA, 0, 7, 118, 122, 101, 83, 69, 24, 0, 0, 15, 134, 125, 56, 87, 124, 169, 162, 87, 138, 89, 127, 141, 83, 129, 101, 116, 70, 110, 129, 111, 43, 10, 1, 22, 117, 100, 82, 133, 60, 36, 153, 164, 120, 105, 122, 111, 11, 
+#> 18, 0, 110, 161, 179, 168, 164, 144, 171, 148, 54, 123, 154, 83, 142, 77, 105, 53, 33, 18, 137, 162, 145, 94, 184, 178, 155, 175, 192, 130, 144, 102, 123, 133, 87, 48, 2, 3, 10, 9, 8, 7, 17, 3, NA, NA, NA, NA, NA, NA, 8, 32, 23, 108, 137, 181, 118, 174, 130, 135, 64, 127, 80, 88, 22, 41, 0, 21, 12, 37, 7, 135, 75, 12, 4, 15, 2, 141, 151, 135, 125, 132, 112, 125, 3, 126, 78, 103, 69, 136, 67, 7, 6, 21, 53, 44, 79, 37, 9, 2, 1, 2, 0, 3, 4, NA, 0, NA, 0, 0, NA, 0, 0, NA, 2, NA, 1, 0, 0, 3, 1, 0, 6, 
+#> 6, 1, 1, 2, 3, 3, 0, NA, NA, 1, 0, 69, 156, 153, 149, 177, 142, 168, 143, 150, 150, 153, 135, 137, 140, 50, 56, 1, 53, 21, 46, 20, 9, 128, 146, 153, 136, 138, 44, 122, 157, 135, 107, 132, 113, 93, 116, 84, 2, 17, 26, 86, 95, 89, 116, 87, 4, 50, 19, 35, 82, 25, 29, 12, 6, 7, 24, 22, 0, 132, 142, 145, 145, 102, 101, 50, 27, 61, 65, 2, 0, 0, 2, 3, 6, 0, 0, NA, NA, NA, 0, NA, NA, NA, NA, 4, 120, 63, 94, 113, 164, 27, 162, 205, 107, 147, 104, 93, 19, 18, 162, 161, 119, 164, 157, 135, 192, 159, 108, 173, 
+#> 115, 143, 70, 96, 11, 28, 0, 0, 32, 25, 150, 142, 100, 161, 138, 125, 129, 127, 124, 72, 45, 9, 7, 25, 152, 171, 132, 146, 126, 170, 121, 129, 132, 145, 154, 117, 50, 13, 0, 9, 7, 10, 15, 21, 9, 16, 0, 0, 0, NA, NA, NA, 2, NA, 10, 6, 14, 63, 106, 167, 137, 138, 24, 57, 117, 133, 142, 147, 92, 119, 145, 93, 125, 122, 128, 91, 57, 0, 3, 3, 10, 12, 16, 4, 0, 48, 72, 48, 118, 163, 149, 52, 152, 176, 179, 170, 123, 61, 136, 111, 70, 44, 54, 2, 7, 0, 1, 3, 3, 8, 8, 1, 1, 0, 1, NA, 0, 0, 0, 0, 1, 25, 51, 
+#> 79, 106, 200, 210, 200, 192, 202, 204, 200, 122, 176, 114, 175, 184, 142, 16, 10, 115, 110, 127, 69, 47, 133, 73, 116, 12, 87, 61, 6, 9, 18, 19, 19, 18, 36, 23, 1, 0, NA, 0, NA, NA, NA, 2, 9, 18, 70, 68, 133, 129, 149, 131, 67, 85, 37, 29, 32, 18, 2, 12, 11, 16, 10, 15, 23, 17, 12, 4, NA, 2, 69, 67, 79, 94, 167, 139, 162, 155, 170, 166, 162, 129, 164, 123, 130, 141, 81, 89, 39, 66, 15, 158, 78, 66, 96, 29, 42, 2, 42, 12, 147, 167, 132, 143, 157, 147, 89, 73, 81, 79, 108, 15, 49, 134, 157, 155, 160, 
+#> 124, 110, 24, 179, 102, 160, 134, 94, 81, 19, 173, 124, 91, 95, 32, 127, 163, 171, 60, 31, 67, 7, 72, 160, 140, 153, 149, 129, 137, 157, 112, 144, 136, 146, 152, 160, 153, 97, 30, 4, 9, 8, 12, 19, 14, 8, NA, NA, 3, 7, 108, 168, 146, 168, 154, 134, 132, 130, 111, 147, 69, 2, 10, 0, 0, NA, NA, 9, 4, 0, 0, 0, 0, 4, 2, 0, 0, 0, 5, 4, 7, 6, 0, 0, 0, 0, 1, 2, 1, 5, 0, 0, NA, NA, 27, 142, 182, 174, 161, 138, 102, 65, 137, 95, 181, 153, 102, 41, 100, 106, 91, 11, 5, 6, 4, 18, 7, 19, 13, 3, 6, NA, 0, 0, 0, 
+#> NA, NA, NA, NA, 3, NA, 18, 175, 159, 129, 161, 177, 125, 56, 141, 119, 140, 118, 114, 100, 76, 20, 85, 47, 28, 100, 157, 159, 154, 153, 133, 162, 141, 56, 0, 122, 187, 153, 109, 7, 175, 167, 172, 154, 142, 85, 117, 89, 68, 52, 3, 7, 6, 8, 13, 11, 7, 0, 12, 8, 0, 1, 4, 7, 8, 6, 4, 7, 1, 1, 5, NA, 1, NA, NA, NA, 1, 17, 50, 129, 156, 141, 129, 139, 155, 148, 150, 162, 132, 79, 85, 94, 123, 90, 115, 77, 37, 16, 18, 174, 164, 206, 213, 201, 148, 128, 177, 191, 184, 159, 200, 112, 128, 49, 0, 88, 97, 120, 
+#> 149, 153, 152, 142, 103, 147, 150, 105, 183, 140, 55, 107, 63, 8, 10, 11, 6, 5, 15, 15, 3, 2, 4, 2, 30, 158, 174, 82, 179, 162, 171, 143, 114, 84, 100, 170, 128, 98, 1, 132, 149, 149, 176, 191, 198, 176, 143, 175, 170, 159, 209, 130, 204, 184, 29, 101, 20, 47, 40, 62, 172, 168, 215, 194, 193, 153, 62, 66, 154, 173, 198, 174, 149, 97, 146, 176, 108, 12, 0, 0, NA, NA, NA, 5, NA, NA, 0, NA, NA, NA, 4, 0, 0, 0, 0, NA, 0, NA, NA, 0, 0, 0, 0, 0, 0, 4, 3, 0, 0, NA, NA, 0, 0, 1, 2, 6, 86, 28, 29, 11, 73, 
+#> 139, 172, 197, 170, 133, 144, 122, 136, 145, 149, 119, 11, 53, 31, 54, 130, 17, 135, 153, 142, 123, 127, 124, 115, 67, 102, 87, 36, 35, 18, 62, 8, 4, 91, 94, 102, 132, 144, 136, 138, 94, 118, 76, 91, 90, 91, 28, 13, 26, 29, 15, 63, 130, 113, 121, 66, 123, 134, 123, 122, 178, 112, 186, 162, 137, 165, 164, 148, 111, 73, 137, 161, 57, 149, 145, 110, 88, 152, 54, 86, 85, 47, 52, 26, 0, 5, 10, 10, 8, 12, 9, 17, 10, 10, 15, 6, 7, 14, 8, 0, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 15, 10, 11, 15, 
+#> 13, 19, 13, 10, 18, 11, 7, 11, 6, 11, 5, 7, 11, NA, NA, NA, NA, NA, NA, NA, 2, NA, NA, 0, 0, NA, NA, NA, NA, NA, 1, 1, 0, 2, 0, 0, 0, 1, 0, 1, 2, NA, 0, 0, NA, 0, NA, NA, NA, NA, 0, 0, 0, 0, 0, 0, 0, 7, 3, 6, 3, 2, 2, 6, 3, 2, 2, 0, 5, 129, 195, 215, 176, 150, 212, 175, 109, 166, 144, 107, 184, 128, 124, 180, 129, 179, 129, 169, 149, 10, 41, 89, 27, 79, 167, 147, 175, 191, 170, 113, 145, 106, 189, 183, 96, 83, 70, 10, NA, NA, 0, 0, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0, 0, 
+#> NA, 9, 8, 71, 34, 45, 133, 175, 184, 184, 148, 82, 74, 210, 114, 16, 88, 94, 0, 6, 153, 131, 145, 160, 24, 158, 135, 71, 156, 156, 96, 46, 4, 132, 11, 10, 1, 9, 14, 136, 118, 71, 98, 125, 123, 114, 110, 48, 121, 120, 91, 114, 98, 94, 104, 111, 28, 33, 57, 141, 189, 186, 177, 120, 160, 123, 134, 140, 109, 120, 90, 60, 114, 48, 14, 62, 13, 29, 24, 31, 45, 76, 102, 116, 127, 124, 148, 91, 156, 143, 130, 140, 154, 138, 126, 107, 52, 17, 24, 104, 74, 122, 114, 123, 36, 54, 30, 52, 96, 119, 125, 103, 41, 
+#> 23, 17, 65, 91, 154, 189, 133, 152, 27, 113, 66, 151, 73, 145, 120, 15, 2, 0, 7, 14, 143, 174, 147, 129, 93, 155, 137, 152, 170, 128, 171, 138, 71, 92, 58, 173, 174, 179, 186, 111, 174, 178, 180, 173, 151, 171, 171, 147, 184, 150, 144, 174, 110, 141, 59, 88, 35, 2, 20, 148, 154, 176, 178, 119, 183, 189, 132, 135, 141, 178, 179, 105, 164, 153, 150, 126, 70, 58, 16, 10, 115, 151, 139, 155, 151, 83, 155, 117, 162, 137, 136, 137, 93, 155, 26, 75, 141, 72, 4, 128, 83, 15, 148, 146, 80, 158, 165, 151, 
+#> 27, 17, 20, 4, 0, 5, 3, 8, 6, 13, 0, NA, NA, NA, NA, NA, NA, 6, 11, 10, 5, 6, 7, 6, 4, 4, NA, NA, NA, NA, NA, 109, 146, 157, 194, 155, 174, 179, 126, 7, 34, 0, 77, 43, 1, 3, 69, 155, 180, 192, 163, 193, 159, 164, 148, 127, 150, 82, 145, 185, 110, 144, 32, 49, 21, 6, 9, 19, 16, 19, 18, 10, 13, 13, 2, NA, 1, 7, 10, 11, 9, 2, 8, 10, 4, 0, 62, 200, 181, 211, 161, 96, 139, 121, 127, 154, 126, 113, 90, 129, 125, 50, 11, 29, 136, 159, 138, 118, 92, 99, 128, 54, 27, 32, 99, 3, 0, 0, 0, 0, 0, 0, NA, NA, 0, 
+#> 0, NA, NA, NA, 0, 11, 21, 115, 73, 21, 76, 48, 125, 125, 113, 92, 104, 75, 32, 15, 10, 47, 108, 163, 138, 210, 191, 115, 173, 98, 62, 171, 183, 171, 170, 96, 50, 26, 9, 147, 141, 162, 103, 142, 163, 154, 139, 44, 109, 137, 4, 59, 78, 47, 23, 10, 12, 85, 149, 165, 151, 98, 16, 35, 97, 65, 8, 0, 1, 0, 7, 8, 20, 12, 14, 18, 10, 20, 17, 18, 19, 27, 24, 12, 4, 17, 12, NA, NA, NA, 0, NA, NA, 8, 138, 121, 111, 88, 160, 206, 161, 170, 157, 160, 111, 128, 112, 131, 126, 111, 97, 73, 86, 153, 124, 83, 130, 
+#> 117, 31, 129, 141, 53, 115, 63, 105, 155, 182, 172, 166, 156, 186, 70, 163, 145, 162, 176, 173, 175, 58, 23, 102, 51, 53, 34, 19, 12, 86, 149, 161, 174, 147, 154, 179, 103, 210, 178, 186, 129, 163, 198, 190, 195, 145, 131, 147, 117, 4, 23, 104, 181, 144, 124, 103, 154, 132, 65, 124, 55, 120, 120, 110, 89, 120, 54, NA, NA, NA, NA, NA, 0, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0, NA, 0, 3, 1, 3, 1, 0, 1, 0, 0, 0, 0, 0, 13, 4, 24, 114, 95, 127, 193, 127, 182, 219, 133, 205, 203, 166, 185, 140, 
+#> 62, 119, 169, 111, 150, 170, 140, 157, 200, 161, 106, 159, 171, 174, 54, 74, 158, 148, 10, 68, 15, 13, 106, 146, 109, 129, 152, 94, 57, 136, 11, 74, 71, 24, 3, 5, 135, 139, 141, 144, 112, 155, 100, 149, 87, 32, 102, 101, 45, 63, 41, 8, 39, 132, 136, 139, 169, 181, 184, 154, 114, 151, 169, 193, 174, 148, 158, 180, 114, 13, 149, 169, 148, 74, 22, 4, 0, 81, 116, 133, 148, 147, 141, 151, 186, 85, 90, 160, 162, 129, 110, 139, 81, 14, 58, 7, 79, 109, 17, 35, 114, 133, 120, 54, 161, 143, 159, 109, 92, 10, 
+#> NA, NA, NA, NA, 0, 0, NA, NA, NA, 0, NA, NA, 0, NA, NA, 112, 165, 102, 99, 156, 12, 1, 6, 2, 179, 166, 81, 130, 132, 101, 166, 169, 130, 63, 125, 97, 85, 35, 20, 0, 0, 21, 4, 2, NA, NA, 14, NA, 10, 11, 12, 12, 10, 0, 3, NA, NA, 3, 15, 7, 89, 104, 95, 81, 117, 138, 155, 104, 39, 86, 116, 98, 53, 41, 31, 52, 73, 139, 169, 141, 176, 151, 176, 147, 168, 177, 101, 141, 140, 78, 57, 104, 29, 135, 160, 168, 135, 44, 2, 125, 124, 23, 50, 100, 113, 85, 32, 106, 62, 78, 116, 113, 7, 6, 44, 40, 105, 153, 71, 
+#> 78, 109, 49, 147, 141, 118, 1, 33, 118, 121, 196, 168, 120, 158, 98, 38, 92, 17, 13, 84, 9, 6, 1, 6, 13, 4, 3, 1, 0, 3, 5, 7, 9, 10, 22, 9, 8, 8, 11, 17, NA, NA, NA, NA, NA, 3, 4, 1, 4, 4, 4, 2, 4, 1, 2, 1, 4, 0, 1, 2, 0, 0, 1, 1, 0, 4, 0, 7, 8, 3, NA, NA, NA, 0, NA, 10, 99, 157, 98, 129, 107, 143, 122, 83, 51, 36, 34, 1, 11, 43, 185, 230, 133, 194, 159, 163, 168, 170, 170, 155, 97, 89, 70, 107, 57, 5, 0, NA, 0, 0, NA, NA, NA, 0, NA, 0, 8, 120, 127, 168, 101, 126, 161, 174, 156, 159, 205, 145, 109, 
+#> 170, 93, 28, 132, 78, 60, 45, 34, 62, 8, 54, 126, 135, 113, 72, 47, 57, 107, 89, 13, 1, 11, 136, 68, 148, 136, 143, 145, 94, 163, 146, 175, 156, 125, 123, 110, 28, 62, 61, 62, 152, 124, 140, 100, 121, 134, 106, 148, 144, 182, 155, 162, 130, 157, 153, 157, 100, 31, 64, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0, 1, 0, 131, 29, 12, 1, 0, 0, 1, 0, NA, NA, NA, NA, 0, NA, NA, NA, 9, 63, 136, 158, 85, 138, 163, 137, 150, 84, 114, 91, 103, 126, 87, 19, 45, 4, 34, 36, 10, 61, 32, 68, 95, 87, 118, 142, 145, 
+#> 180, 97, 147, 115, 121, 99, 98, 27, 22, 118, 138, 145, 146, 168, 27, 110, 148, 173, 112, 145, 168, 122, 5, 59, 77, 39, 31, 7, 24, 11, 12, 15, 8, 23, 5, 15, 13, 4, 11, 13, 17, 1, 7, 4, 3, 2, 20, 63, 112, 144, 57, 68, 54, 25, 61, 56, 69, 71, 72, 42, 62, 17, 1, 0, 0, NA, NA, NA, NA, NA, 4, 8, 12, 4, 2, NA, 2, 3, 8, 3, 0, 0, 0, 3, 0, 0, 0, 3, 0, 10, 124, 151, 160, 139, 136, 150, 137, 140, 90, 141, 160, 121, 116, 70, 23, 0, 16, 16, 17, 15, 21, 24, 13, 8, 12, 21, NA, NA, 3, 8, 9, 3, 1, 15, 0, 42, 78, 97, 
+#> 78, 52, 34, 15, 0, 96, 179, 135, 143, 150, 147, 172, 160, 104, 169, 58, 90, 159, 126, 112, 104, 35, 77, 122, 112, 21, 79, 128, 138, 21, 77, 86, 40, 15, 0, 9, 9, 3, 0, 9, 6, 11, 10, 11, 4, 8, 3, 8, 1, NA, NA, NA, NA, NA, NA, NA, NA, 0, NA, 0, NA, 0, 1, 1, NA, NA, NA, 133, 188, 157, 134, 145, 92, 179, 111, 168, 160, 155, 185, 136, 1, 130, 2, 87, 51, 69, 175, 115, 125, 125, 171, 102, 112, 16, 100, 52, NA, NA, 0, 0, NA, NA, 0, NA, 0, NA, 0, 0, NA, NA, NA, NA, NA, NA, 5, 15, 59, 104, 175, 174, 162, 156, 
+#> 15, 184, 64, 40, 177, 140, 116, 32, 29, 34, 84, 103, 77, 99, 44, 67, 48, 18, 48, 68, 45, 25, 27, NA, NA, NA, 8, 12, 13, NA, NA, NA, NA, NA, 17, 24, 120, 106, 160, 91, 168, 178, 176, 185, 163, 167, 134, 131, 81, 57, 137, 10, 6, 5, 158, 211, 195, 181, 177, 157, 152, 166, 150, 210, 160, 165, 140, 144, 178, 166, 163, 113, 79, 114, 33, 180, 175, 138, 136, 210, 171, 175, 205, 160, 198, 134, 28, 6, 8, 10, 151, 63, 185, 161, 180, 169, 119, 7, 55, 2, 0, 42, 103, 135, 146, 97, 122, 91, 173, 104, 147, 104, 
+#> 131, 106, 2, 82, 95, 168, 87, 132, 153, 127, 120, 16, 11, 1, 20, 10, 19, 3, 24, 2, 9, 5, 4, 1, 3, 9, 15, 9, 6, NA, 7, 0, 4, 2, 0, 0, NA, NA, NA, NA, NA, NA, NA, NA, NA, 29, 12, 43, 45, 111, 136, 150, 94, 139, 82, 30, 17, 104, 26, 33, 0, 0, 0, 0, NA, NA, NA, 0, 0, 0, NA, NA, NA, NA, NA, 0, 0, 5, 101, 57, 182, 158, 126, 115, 25, 146, 42, 27, 152, 142, 97, 39, 5, 57, 12, 4, 11, 13, 11, 10, 8, 12, 13, 8, 11, 12, 7, 2, NA, NA, NA, 0, 0, 0, NA, 0, NA, NA, NA, NA, NA, NA, NA, 3, 0, 4, 8, 2, 26, 38, 37, 
+#> 5, 61, 114, 88, 95, 54, 88, 80, 76, 92, 68, 25, 42, 27, 25, 34, 1, NA, 0, NA, NA, 0, 0, 4, 6, 0, 10, 15, 5, 13, 9, NA, NA, NA, 1, 13, 9, 10, 12, 1, 172, 165, 200, 186, 178, 154, 163, 176, 188, 170, 186, 141, 53, 135, 118, 9, 63, 147, 163, 156, 136, 147, 82, 133, 110, 129, 107, 99, 55, 33, 69, 34, 11, 4, 125, 172, 166, 216, 127, 177, 164, 47, 31, 168, 155, 141, 143, 44, 57, 95, 90, 68, 68, 2, 24, 13, 175, 163, 100, 179, 154, 62, 26, 59, 145, 144, 65, 0, 0, 1, 1, 2, 0, 0, NA, 0, 2, NA, NA, 7, 132, 
+#> 100, 87, 63, 19, 44, 58, 51, 10, 68, 9, 108, 131, 109, 123, 151, 146, 107, 150, 134, 37, 14, 22, 24, 53, 3, 73, 16, 118, 210, 203, 240, 207, 200, 214, 205, 187, 181, 133, 169, 125, 149, 156, 103, 122, 88, 89, 88, 115, 170, 166, 151, 149, 167, 113, 111, 107, 68, 25, 182, 163, 173, 163, 174, 44, 129, 184, 153, 112, 5, 31, 63, 115, 166, 156, 127, 139, 114, 128, 60, 85, 84, 40, 6, 80, 78, 92, 42, 81, 133, 173, 178, 161, 185, 109, 157, 189, 187, 163, 133, 88, 16, 19, 68, 26, 137, 177, 6, 63, 69, 14, 68, 
+#> 118, 141, 136, 68, 66, 42, 75, 107, 85, 132, 136, 93, 102, 94, 117, 75, 26, 2, 5, 8, 1, 1, 6, 9, 9, 5, 4, 1, 6, NA, 3, NA, 0, 1, 95, 179, 183, 192, 184, 194, 175, 116, 148, 131, 163, 162, 127, 102, 143, 57, 87, 93, 29, 3, 24, 17, 0, 0, 1, 1, 1, 0, 0, 0, NA, NA, NA, 0, 0, 0, NA, 0, NA, NA, NA, 0, 0, 9, 46, 95, 74, 91, 150, 167, 118, 135, 157, 54, 82, 109, 11, 105, 91, 59, 1, 0, 2, 4, 0, 0, 1, 5, 0, 0, 0, 0, NA, NA, 4, 3, 92, 51, 149, 119, 73, 63, 48, 32, 8, 10, 3, 5, 5, 0, 0, 15, 6, 11, 10, NA, NA, 
+#> 4, 161, 166, 130, 171, 141, 152, 140, 102, 26, 14, 21, 7, 14, 16, 8, 14, 15, 19, 14, 2, NA, 0, 0, 1, 0, 0, 0, 55, 94, 213, 197, 211, 218, 163, 203, 177, 168, 165, 175, 165, 197, 159, 220, 148, 139, 41, 33, 1, 2, 20, 18, 7, 1, 15, 9, 22, 13, 28, 14, 25, NA, 0, 6, 2, 79, 207, 211, 238, 186, 186, 191, 101, 169, 184, 154, 113, 132, 2, 11, 3, NA, 6, 0, NA, NA, 0, 0, NA, NA, NA, NA, 0, NA, NA, 3, 5, 10, 1, 4, 0, 0, 0, 0, 1, 25, 90, 114, 139, 82, 96, 114, 101, 61, 26, 6, 2, 50, 160, 156, 143, 148, 112, 
+#> 177, 152, 159, 185, 130, 120, 106, 116, 87, 45, 37, 0, 0, 0, 0, 1, 1, 0, 2, 1, 0, NA, 0, NA, 0, 0, NA, 0, NA, 134, 137, 156, 148, 151, 144, 143, 8, 128, 105, 103, 131, 120, 73, 1, 56, 26, 170, 139, 180, 160, 143, 145, 71, 63, 104, 105, 84, 47, 13, 1, 38, 30, 177, 167, 198, 188, 165, 182, 149, 159, 160, 89, 25, 110, 114, 147, 159, 163, 104, 113, 164, 145, 151, 85, 66, 48, 14, 125, 80, 165, 167, 173, 198, 169, 148, 166, 107, 49, 25, 93, 144, 121, 130, 96, 115, 154, 39, 97, 88, 111, 23, 59, 13, 11, 
+#> 18, 97, 192, 163, 179, 150, 151, 78, 30, 2, 55, 110, 131, 101, 154, 180, 141, 134, 80, 13, 161, 25, 118, 30, 15, NA, NA, NA, NA, NA, 16, 13, 11, 7, 0, 5, 0, 7, 1, 10, 144, 142, 179, 164, 173, 86, 36, 3, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, 1, 0, 0, 0, 0, 2, 0, 12, 12, 2, 1, 0, 1, 3, 7, 8, 6, 11, 12, 10, 6, 10, 7, 0, 5, 117, 143, 154, 138, 171, 150, 141, 125, 132, 144, 103, 9, 72, 94, 134, 143, 126, 41, 81, 57, 0, 22, 97, 98, 91, 156, 170, 155, 114, 106, 16, 117, 64, 13, 165, 199, 223, 
+#> 207, 234, 215, 164, 195, 210, 184, 139, 169, 9, 63, 163, 213, 186, 186, 147, 175, 152, 171, 39, 108, 102, 94, 117, 156, 159, 18, 18, 46, 109, 138, 134, 112, 132, 106, 2, 57, 39, 2, NA, NA, 0, 0, NA, NA, NA, NA, NA, NA, NA, NA, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 29, 144, 162, 187, 61, 132, 152, 90, 17, 59, 121, 121, 104, 91, 138, 120, 27, 56, 66, 13, 95, 152, 145, 152, 156, 82, 40, 110, 20, 12, 41, 106, 138, 61, 80, 97, 137, 169, 70, 57, 2, 5, 59, 72, 60, 121, 147, 119, 31, 69, 55, 3, 21, 10, 23, NA, 
+#> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0, 0, 3, 13, 9, NA, NA, NA, 1, NA, 0, 1, 2, 2, 5, 1, 0, 0, 0, 1, 2, NA, 0, 1, 0, NA, NA, NA, NA, NA, 11, NA, NA, NA, 0, NA, NA, NA, NA, NA, 2, 1, 85, 134, 138, 167, 99, 162, 103, 187, 199, 172, 78, 149, 33, 102, 28, 61, 0, 5, 71, 102, 92, 60, 72, 97, 75, 25, 1, 39, 24, 39, 30, 115, 139, 129, 130, 118, 67, 61, 19, 88, 22, 119, 48, 148, 49, 77, 32, 142, 188, 137, 67, 201, 164, 10, 171, 123, 164, 190, 194, 119, 216, 195, 211, 155, 142, 225, 164, 
+#> 141, 3, 10, 119, 46, 3, 39, 72, 144, 155, 122, 95, 141, 88, 41, 144, 120, 10, 161, 143, 113, 123, 97, 125, 28, 34, 87, 132, 104, 44, 152, 145, 72, 56, 18, 164, 122, 109, 93, 155, 97, 108, 92, 76, 127, 83, 9, 87, 66, 125, 133, 112, 48, 6, 11, 8, 133, 96, 67, 30, 57, 122, 86, 54, 23, 6, 2, 18, 191, 175, 157, 178, 153, 76, 49, 119, 161, 29, 32, 60, 42, 48, 6, 48, 27, 9, NA, 0, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0, NA, 5, 6, 5, 10, 7, 5, 1, 7, 4, 13, 6, 2, 12, NA, 4, NA, NA, 0, NA, NA, NA, NA, 
+#> NA, NA, NA, 6, 7, 11, 0, NA, 0, 0, 0, NA, 0, 0, 0, 0, 0, NA, 5, 111, 93, 124, 95, 125, 122, 111, 105, 113, 140, 111, 102, 96, 0, 10, 15, 17, 19, 11, 14, 0, 8, 15, 26, 9, NA, NA, 0, 10, 9, 0, 12, 3, 15, 99, 146, 169, 184, 162, 160, 113, 122, 48, 1, 12, 168, 118, 156, 96, 181, 159, 163, 109, 121, 151, 65, 157, 127, 42, 108, 81, 88, 110, 113, 165, 169, 113, 140, 130, 199, 100, 92, 10, 52, 3, 0, 84, 96, 143, 145, 134, 155, 135, 60, 42, 75, 46, 0, 2, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
+#> 0, 0, 12, 113, 55, 118, 30, 67, 133, 106, 111, 146, 106, 97, 63, 50, 146, 79, 153, 175, 84, 143, 66, 18, 2, 32, 8, 153, 188, 183, 183, 158, 186, 173, 172, 201, 25, 154, 138, 139, 82, 34, 0, 27, 96, 58, 99, 64, 45, 10, 10, 10, 11, 135, 192, 178, 181, 163, 42, 170, 88, 143, 87, 14, 87, 168, 184, 147, 148, 82, 79, 174, 133, 155, 190, 191, 169, 149, 45, 57, 76, 82, 3, 63, 46, 140, 160, 173, 175, 174, 109, 133, 117, 79, 103, 171, 167, 27, 56, 19, 61, 37, 0, 1, 3, NA, NA, 7, 18, 5, 2, 0, NA, NA, NA, 0, 
+#> NA, 45, 107, 174, 111, 185, 140, 162, 121, 119, 158, 154, 71, 166, 171, 124, 40, 124, 68, 100, 4, 7, 0, 70, 46, 74, 88, 75, 101, 106, 120, 100, 101, 31, 15, 0, 2, 7, 1, NA, NA, 0, NA, NA, 0, NA, 0, NA, 0, NA, NA, NA, NA, NA, 117, 163, 162, 196, 177, 170, 154, 139, 128, 137, 124, 128, 169, 76, 77, 59, NA, NA, NA, NA, NA, 13, 8, 2, 2, 3, 2, 5, 9, 5, 3, 1, 1, 31, 146, 132, 161, 163, 159, 148, 140, 135, 92, 86, 46, 17, 93, 108, 132, 110, 16, 66, 56, 1, 1, 4, 6, 3, 1, 2, 5, 2, 0, NA, NA, 0, NA, 1, 0, 
+#> 0, NA, 1, 10, 13, 8, 8, 18, 9, 4, 1, 4, NA, 0, 0, 0, 0, 3, 6, 4, 8, 7, 3, 5, 1, 1, 3, 91, 48, 82, 127, 158, 152, 95, 103, 110, 101, 28, 37, 9, 29, 3, 8, NA, NA, NA, 0, NA, NA, 0, NA, 0, NA, NA, NA, NA, NA, NA, 0, NA, 0, 0, 0, 0, NA, 0, NA, 0, 0, NA, 1, 0, 0, 0, 139, 103, 59, 7, 0, 21, 47, 16, 20, 11, 1, 73, 151, 148, 167, 147, 152, 79, 83, 135, 148, 182, 156, 160, 164, 157, 48, 109, 143, 74, 13, 20, 53, 43, 41, 74, 106, 99, 132, 125, 128, 84, 102, 121, 4, 101, 169, 156, 194, 170, 203, 28, 139, 147, 
+#> 114, 56, 70, 35, 93, 22, 10, 16, 14, 100, 113, 48, 35, 75, 39, 5, 49, 14, 88, 94, 54, 147, 114, 164, 144, 146, 78, 56, 48, 33, 26, 114, 153, 161, 170, 175, 139, 167, 174, 191, 210, 188, 101, 180, 146, 166, 178, 156, 135, 130, 0, NA, 0, NA, NA, NA, NA, NA, NA, NA, NA, 0, 0, 0, 0, 0, 0, 3, 65, 145, 85, 143, 131, 143, 128, 23, 4, 92, 141, 86, 119, 28, 37, 9, 32, 46, 54, 52, 34, 1, 40, 108, 167, 142, 90, 21, 139, 116, 75, 27, 146, 40, 33, 1, 5, 3, 17, 10, 12, 7, 4, 9, 8, 13, NA, NA, NA, 0, NA, NA, 0, 
+#> NA, 7, 13, 8, 18, 15, 14, 6, 14, 14, 10, 0, 0, 1, 3, 28, 80, 158, 158, 162, 108, 102, 18, 0, 4, 129, 40, 75, 58, 84, 61, 110, 146, 96, 42, 103, 54, 48, 31, 52, 35, 35, 10, 20, 3, 152, 159, 121, 174, 119, 60, 137, 48, 74, 211, 123, 102, 45, 110, 135, 123, 156, 52, 6, 120, 179, 179, 174, 180, 140, 67, 165, 185, 180, 173, 141, 104, 52, 41, 76, 148, 108, 146, 34, 88, 83, 18, 92, 144, 152, 144, 156, 149, 147, 181, 122, 149, 159, 155, 167, 93, 147, 156, 149, 133, 135, 12, 99, 94, 4, 5, 19, 17, 12, 18, 
+#> 15, 15, 14, 11, 10, 7, 18, 11, 15, 12, 11, 10, 11, 13, 4, 5, 9, 1, 5, 2, 9, 7, 27, 140, 142, 122, 8, 105, 67, 97, 72, 21, 0, 0, 0, 0, 2, 1, NA, NA, 0, 0, 2, 1, 0, 1, 5, 1, 1, 0, 0, 0, 0, 0, 0, NA, 0, NA, NA, NA, NA, NA, NA, 0, NA, 12, 124, 109, 124, 158, 110, 104, 45, 163, 151, 123, 66, 84, 92, 106, 23, 13, 47, 40, 159, 163, 145, 153, 110, 120, 97, 52, 94, 92, 5, 46, 32, 59, 171, 158, 120, 170, 119, 95, 122, 157, 136, 190, 102, 112, 56, 33, 34, 80, 80, 11, 93, 127, 94, 122, 105, 102, 115, 91, 77, 
+#> NA, NA, NA, NA, 2, 8, 10, 14, 14, 22, 10, 3, 0, 2, 2, 11, 10, 7, 17, 19, 14, 10, 14, 22, 14, 17, 9, 10, 8, 7, 8, 11, 13, 9, 12, 2, 145, 184, 168, 188, 177, 192, 120, 155, 193, 137, 166, 182, 189, 193, 157, 64, 69, 34, 11, 8, 123, 172, 167, 145, 113, 145, 168, 48, 155, 177, 109, 108, 115, 24, 71, 37, 9, 55, 12, 61, 121, 121, 85, 66, 47, 110, 11, 35, NA, 0, NA, 0, NA, NA, NA, NA, NA, NA, 0, 16, 160, 153, 174, 165, 147, 136, 159, 102, 141, 131, 96, 95, 74, 4, 17, 13, 12, 5, 11, 11, 0, 0, 2, 1, NA, 0, 
+#> NA, NA, 0, NA, 0, 0, 0, 159, 178, 167, 139, 179, 197, 178, 160, 176, 113, 130, 63, 163, 160, 171, 147, 130, 179, 162, 164, 171, 183, 173, 166, 168, 152, 25, 63, 178, 185, 174, 141, 152, 184, 184, 155, 148, 191, 15, 132, 146, 65, 23, 126, 147, 49, 10, 9, 67, 128, 200, 155, 168, 158, 147, 174, 164, 153, 118, 141, 158, 143, 70, 31, 22, 146, 46, 174, 141, 141, 166, 113, 103, 115, 92, 134, 19, 87, 44, 21, 81, 6, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2, 74, 109, 129, 108, 149, 192, 187, 186, 199, 126, 
+#> 136, 128, 152, 176, 139, 164, 141, 89, 21, 82, 24, 106, 27, 144, 160, 182, 169, 185, 193, 120, 180, 181, 177, 184, 183, 143, 142, 75, 27, 46, 160, 134, 134, 133, 110, 107, 78, 7, 26, 8, 101, 141, 159, 130, 127, 151, 75, 208, 165, 166, 97, 174, 161, 129, 35, 42, 91, 2, 7, 12, 7, 12, 13, 6, 6, 17, 18, 10, 17, 0, 0, 0, 0, 10, 8, 5, 0, 0, 1, 168, 87, 16, 73, 76, 24, 1, 140, 153, 108, 164, 158, 167, 150, 176, 146, 103, 142, 96, 20, 16, 9, 41, 147, 167, 181, 32, 93, 182, 163, 179, 179, 169, 180, 144, 91, 
+#> 146, 128, 9, 26, 144, 152, 166, 116, 104, 170, 158, 193, 183, 133, 173, 78, 96, 35, 0, 69, 144, 175, 182, 122, 156, 165, 163, 160, 82, 184, 88, 86, 19, 91, 143, 34, 184, 69, 76, 89, 69, 163, 111, 37, 95, 165, 163, 160, 151, 190, 166, 170, 45, 131, 94, 74, 1, 21, 31, 25, 30, 74, 123, 56, 131, 131, 77, 85, 2, 33, 71, NA, NA, NA, NA, NA, NA, 12, 5, 104, 88, 158, 180, 132, 61, 14, 102, 74, 15, 4, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0, NA, NA, NA, 0, 0, 1, NA, 0, NA, 0, NA, 0, 
+#> 0, 0, 42, 62, 99, 71, 116, 124, 73, 4, 33, 13, 26, 22, 47, 38, 6, 3, 3, 2, 2, 12, 10, 23, 15, 164, 185, 160, 149, 210, 164, 169, 140, 151, 135, 91, 48, 68, 94, 76, 123, 141, 49, 96, 85, 63, 98, 142, 143, 78, 144, 161, 158, 166, 191, 176, 156, 160, 61, 165, 154, 171, 126, 59, 47, 95, 42, 36, 149, 110, 126, 132, 122, 129, 115, 154, 27, 75, 48, 1, 29, 42, 2, 40, 85, 119, 79, 95, 18, 34, 76, 72, 41, 19, 74, 149, 180, 188, 137, 142, 207, 146, 147, 161, 145, 99, 95, 176, 157, 29, 5, 27, 46, 70, 148, 164, 
+#> 167, 187, 117, 139, 132, 167, 138, 170, 151, 106, 8, 21, 3, 95, 116, 130, 200, 114, 143, 109, 154, 197, 173, 161, 173, 166, 145, 46, 64, 50, NA, NA, NA, 1, 10, 11, 3, 7, 11, 14, 10, 5, 8, 5, 11, 15, 3, 1, 0, 1, 1, 0, 0, 0, NA, NA, NA, NA, NA, 0, 0, 0, 0, 0, 14, 146, 107, 177, 166, 172, 139, 94, 165, 108, 138, 145, 47, 56, 16, 174, 129, 150, 184, 201, 5, 42, 137, 162, 156, 151, 134, 67, 121, 100, 113, 85, 81, 171, 205, 200, 139, 175, 113, 16, 131, 136, 13, 20, 52, 71, 20, 40, 10, 59, 57, 30, 47, 45, 
+#> 43, 129, 87, 107, 107, 78, 25, 45, 82, 120, 41, 26, 49, 4, 130, 152, 172, 147, 173, 187, 174, 200, 181, 157, 60, 127, 123, 116, 43, 78, 192, 73, 104, 194, 86, 67, 35, NA, 2, 12, 18, 14, 9, 6, NA, NA, NA, NA, NA, NA, 0, 0, 1, 1, 0, 1, 8, 55, 74, 132, 116, 40, 78, 77, 18, 23, 157, 113, 65, 46, 19, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 11, 88, 35, 61, 86, 32, 25, 133, 153, 188, 191, 162, 152, 105, 144, 65, 67, 49, 93, 4, 28, 30, 3, 1, 96, 138, 143, 94, 152, 157, 182, 161, 170, 133, 158, 176, 137, 
+#> 104, 112, 17, NA, NA, NA, NA, 7, 9, 9, 3, 15, 17, 5, 3, 8, 0, 13, 0, 38, 118, 122, 147, 57, 160, 91, 58, 39, 98, 67, 4, 39, 121, 13, 6, 5, 23, 174, 144, 146, 175, 98, 79, 129, 116, 163, 123, 143, 20, 146, 102, 103, 28, 57, 8, 1, 1, NA, NA, NA, NA, 0, NA, NA, NA, NA, 2, 1, 12, 13, 8, 12, 7, 10, 0, 1, 1, 7, 2, 2, 101, 49, 157, 148, 149, 108, 156, 152, 70, 104, 90, 113, 101, 9, 0, 50, 15, 149, 131, 145, 149, 142, 115, 159, 178, 141, 114, 78, 63, 38, 43, 5, 79, 84, 104, 25, 75, 107, 84, 44, 117, 53, 
+#> 82, 72, 9, 54, 119, 170, 177, 145, 103, 167, 195, 146, 154, 156, 151, 136, 145, 148, 111, 59, 90, 105, 17, 57, 83, 160, 122, 165, 207, 166, 205, 147, 167, 126, 15, NA, NA, 0, NA, NA, NA, NA, 0, NA, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, NA, NA, NA, NA, 0, 0, NA, 0, NA, NA, NA, 0, NA, 0, 142, 176, 93, 111, 121, 49, 123, 116, 7, 6, 10, 11, 1, 8, 12, 0, 1, 4, 9, 3, 0, 0, 9, 78, 149, 170, 184, 168, 174, 154, 162, 152, 185, 175, 162, 144, 143, 109, 74, 102, 18, 61, 1, 51, 130, 95, 155, 156, 176, 145, 
+#> 114, 9, 12, 50, 1, 4, 86, 43, 163, 191, 186, 206, 169, 73, 120, 20, 126, 150, 158, 125, 4, 59, 12, 29, 89, 106, 111, 167, 147, 197, 198, 173, 219, 177, 33, 136, 112, 27, 20, 124, 64, 68, 156, 128, 151, 136, 161, 198, 180, 193, 189, 160, 144, 121, 84, 104, 25, 24, 41, 86, 142, 157, 142, 129, 137, 150, 153, 146, 154, 139, 40, 141, 119, 123, 86, 4, 78, 21, 50, 26, 15, 15, 79, 162, 131, 146, 184, 51, 155, 152, 148, 123, 150, 123, 90, 92, 64, 16, 6, 62, NA, NA, NA, NA, NA, NA, 1, 0, 3, 0, 1, 3, 0, 0, 
+#> 0, 0, 0, 1, 3, 2, 7, 4, 13, 5, 4, NA, 4, 0, 2, 0, 8, 104, 136, 105, 148, 72, 79, 129, 136, 79, 116, 126, 129, 116, 80, 80, 23, 76, 73, 152, 118, 173, 168, 167, 169, 202, 165, 166, 204, 117, 147, 121, 118, 32, 52, 154, 162, 184, 163, 154, 163, 168, 192, 182, 171, 181, 131, 40, 114, 35, 97, NA, NA, NA, NA, NA, NA, 0, 0, 1, 8, 0, 0, 0, 0, 5, 13, 43, 56, 45, 99, 132, 153, 100, 123, 153, 131, 59, 59, 92, 10, 6, 6, 68, 105, 138, 122, 139, 78, 138, 117, 81, 150, 183, 110, 74, 12, 3, 1, 0, 1, 0, 1, NA, 0, 
+#> 1, 0, 0, 0, 1, 1, 2, 0, 1, 3, 0, 0, 0, 0, 0, 0, 0, 0, 12, 183, 190, 203, 219, 201, 191, 191, 156, 188, 202, 214, 206, 179, 212, 179, 162, 216, 12, 149, 24, 139, 73, 47, 74, 54, 61, 43, 88, 34, 58, 47, 6, 68, 18, 37, 11, 33, 215, 176, 213, 143, 175, 201, 187, 181, 172, 194, 166, 183, 154, 127, 141, 103, 126, 38, 131, 34, 132, 62, 116, 184, 132, 42, 129, 128, 180, 168, 139, 105, 14, 99, 39, 26, 2, NA, NA, NA, 0, 1, 0, 0, 1, 1, 4, 5, 12, 0, 0, 1, 1, 1, 0, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 7, 5, 
+#> 6, 6, 3, 4, 8, 1, 5, 0, 0, 0, 1, 0, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 7, 6, 8, 0, 0, 0, 0, 0, 0, 0, 6, 4, 1, 6, 1, 18, 61, 178, 154, 191, 203, 163, 176, 139, 172, 181, 156, 183, 183, 163, 164, 149, 146, 142, 98, 129, 77, 124, 134, 25, 114, 117, 37, 10, 1, 5, 16, 13, 4, 21, 24, 15, 14, 20, 20, 2, 12, 16, 4, 1, 5, 3, 9, 10, 0, 0, NA, NA, NA, 1, 2, NA, 0, 0, 0, 0, 0, 0, 0, 0, 21, 209, 195, 190, 197, 24, 197, 198, 50, 49, 65, 142, 122, 43, 45, 33, 159, 174, 113, 144, 160, 97, 57, 
+#> 160, 157, 46, 154, 104, 107, 37, 108, 134, 61, 72, 15, 23, 118, 108, 86, 152, 174, 176, 149, 155, 147, 165, 134, 130, 120, 73, 40, 16, 123, 104, 91, 90, 182, 98, 91, 65, 160, 79, 48, NA, 0, 0, 8, 9, 2, 10, 11, 11, 6, 7, 0, 11, 12, 0, NA, NA, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, NA, NA, NA, NA, NA, NA, NA, NA, 4, NA, NA, NA, 1, 0, 1, 0, 0, 1, 6, 1, 0, 1, 4, 4, 16, 19, 53, 77, 102, 130, 97, 159, 117, 108, 123, 25, 68, 122, 137, 121, 99, 155, 153, 116, 206, 169, 183, 149, 9, 63, 23, 92, 
+#> 158, 163, 199, 157, 148, 165, 149, 154, 148, 127, 33, 60, 64, 47, 46, NA, NA, NA, NA, NA, 5, 7, 5, 0, 0, 1, 0, 0, 1, 0, NA, NA, 0, 0, NA, NA, NA, 0, NA, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 29, 168, 129, 166, 143, 121, 38, 4, 61, 5, 7, 10, 9, 12, 10, 6, 2, 3, 0, 0, 0, 0, 0, 0, 0, 39, 72, 68, 77, 7, 23, 139, 161, 146, 120, 146, 68, 20, 53, 64, 44, 54, 85, 2, 50, 124, 127, 84, 40, 163, 52, 87, 159, 147, 134, 48, 0, 12, 30, 84, 132, 114, 152, 94, 88, 105, 29, 78, 156, 135, 117, 113, 41, 7, NA, NA, 
+#> NA, 0, NA, NA, 0, NA, NA, 9, 9, 17, 5, 5, 3, 5, 10, 0, 1, 0, 1, 0, 0, 0, 0, 1, 3, 5, 8, 0, 3, 109, 118, 123, 175, 190, 164, 184, 166, 171, 157, 166, 118, 29, 130, 87, 34, 167, 132, 96, 111, 23, 54, 21, 12, 42, 112, 80, 153, 108, 28, 133, 159, 129, 103, 57, 18, 2, 82, 197, 151, 165, 111, 167, 185, 165, 45, 63, 134, 64, 2, 139, 185, 176, 188, 181, 180, 189, 179, 169, 117, 106, 133, 173, 160, 129, 84, 125, 111, 4, 40, 41, 50, 77, 4, 3, 25, 95, 39, 8, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 
+#> 16, 194, 92, 189, 174, 160, 86, 74, 155, 140, 153, 172, 100, 56, 102, 54, 147, 164, 94, 132, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 28, 15, 132, 136, 155, 156, 196, 160, 140, 172, 123, 157, 139, 139, 162, 28, 93, 96, 163, 155, 191, 176, 111, 151, 133, 150, 102, 5, 6, 5, 98, 202, 193, 197, 184, 206, 130, 206, 165, 200, 186, 164, 113, 178, 163, 0, 0, 7, 10, 10, 16, 23, 20, 23, 22, 11, 11, 8, 5, 12, 0, 2, 14, 5, NA, NA, 0, NA, NA, NA, NA, NA, 1, 0, 1, 0, 0, 1, 2, 1, 0, 1, 1, 9, 4, 5, 2, 2, NA, NA, NA, 
+#> 0, 11, 6, 10, 0, 0, 0, 1, 9, 1, 0, 2, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, NA, NA, NA, NA, NA, NA, NA, 0, 15, 13, 12, NA, 4, 6, 0, 82, 62, 50, 179, 193, 100, 69, 123, 38, 141, 145, 170, 129, 172, 126, 59, 161, 159, 148, 240, 163, 177, 65, 146, 166, 21, 77, 89, 26, NA, 0, 0, NA, NA, NA, NA, NA, 0, 0, 3, 0, 2, 0, 2, 0, 0, 1, 1, 0, 0, 12, 41, 64, 78, 76, 35, 109, 83, 77, 111, 95, 107, 37, 7, 91, 177, 193, 187, 114, 48, 131, 84, 23, 74, 157, 60, 13, 11, 26, 167, 185, 216, 197, 182, 209, 190, 163, 165, 
+#> 178, 79, 177, 102, 127, 57, 99, 45, 156, 152, 166, 181, 170, 178, 176, 134, 55, 113, 113, 60, 113, 7, 52, 43, 34, 20, 34, 8, 27, 46, 134, 121, 131, 27, 97, 145, 156, 148, 196, 181, 195, 150, 156, 160, 119, 149, 123, 0, 2, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 134, 89, 175, 194, 157, 175, 196, 157, 51, 165, 115, 27, 50, 126, 6, 36, 132, 160, 147, 142, 79, 52, 139, 136, 101, 147, 5, 99, 0, 1, 47, 96, 93, 145, 134, 137, 135, 122, 124, 129, 171, 
+#> 45, 109, 95, 81, 22, 151, 188, 185, 181, 189, 192, 59, 92, 177, 216, 178, 144, 98, 84, 133, 171, 146, 161, 156, 128, 166, 194, 168, 172, 175, 164, 136, 115, 67, 75, 5, 75, 6, 166, 122, 146, 23, 70, 66, 89, 46, 79, 6, 14, 88, 139, 159, 161, 166, 131, 168, 117, 82, 22, 3, 26, 42, 78, 64, 17, 7, 1, 98, 83, 139, 145, 144, 130, 135, 114, 84, 148, 138, 108, 136, 42, 14, 34, 0, 4, 98, 94, 147, 162, 145, 141, 100, 155, 172, 153, 135, 161, 152, 167, 184, 157, 125, 242, 208, 212, 262, 206, 224, 238, 213, 225, 
+#> 214, 184, 73, 105, 136, 102, 91, 10, 31, 74, 157, 89, 198, 41, 146, 191, 168, 65, 26, 41, 82, 96, 56, 27, 113, 111, 126, 139, 98, 115, 103, 100, 100, 101, 82, 47, 28, 14, 4, 73, 97, 100, 173, 148, 186, 67, 96, 139, 171, 192, 186, 70, 116, 130, 79, 28, 0, 0, 49, 84, 10, 28, 48, 126, 123, 71, 114, 148, 95, 62, 56, 115, 51, 28, NA, NA, NA, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 194, 185, 212, 196, 195, 177, 185, 187, 186, 183, 173, 173, 101, 172, 147, 4, 120, 94, 162, 107, 76, 54, 131, 142, 146, 
+#> 206, 192, 198, 151, 176, 98, 157, 159, 129, 89, 9, 76, 28, 110, 157, 138, 206, 138, 140, 35, 63, 120, 132, 83, 115, 26, 0, 1, 0, 0, 0, 9, 7, 1, 0, 0, NA, 0, 0, 0, 0, 0, 0, 0, 0, 1, 26, 159, 129, 148, 121, 130, 125, 123, 61, 95, 153, 85, 89, 44, 0, 70, 107, 38, 97, 16, 2, 18, 11, 12, 43, 27, 0, 0, 0, 0, 0, 1, 0, 7, 6, 6, 6, 0, 4, 5, 0, 0, 26, 133, 85, 105, 115, 93, 121, 123, 137, 155, 130, 52, 42, NA, 0, NA, 0, 0, 1, 1, 0, 6, 0, 0, 0, 0, 20, 85, 149, 167, 166, 204, 177, 203, 199, 214, 152, 179, 199, 
+#> 108, 63, 77, 45, 0, 0, 0, 0, 0, 0, 0, 158, 109, 140, 125, 23, 52, 38, 94, 19, 27, 72, 55, 26, 9, 4, 19, 12, 17, 6, 8, 2, 0, 0, 1, 9, 154, 209, 198, 170, 171, 179, 173, 127, 115, 128, 116, 147, 92, 56, 50, 5, 120, 173, 189, 183, 188, 185, 194, 195, 201, 133, 163, 152, 124, 163, 133, 28, 0, 0, 0, 0, 0, 0, 1, 0, 1, 10, 6, 7, 9, 12, 8, 9, 2, 0, 0, 2, 1, 7, 7, 9, 3, 2, 0, 1, 0, 0, 1, 0, 1, 7, NA, 0, 0, 0, 0, 1, 0, 0, 0, 2, 0, 0, 13, 9, 9, 0, 2, 4, 6, 0, 0, 0, 0, 0, 0, 0, 0, 14, 106, 45, 134, 158, 157, 
+#> 146, 168, 199, 50, 180, 181, 163, 37, 105, 82, 34, 43, 63, 31, 147, 180, 141, 185, 187, 164, 132, 173, 106, 59, 73, 147, 58, 49, 49, 89, 84, 146, 158, 114, 135, 132, 43, 3, 47, 52, 60, 6, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 16, 17, 163, 134, 164, 111, 1, 52, 3, 4, 14, 15, 24, 11, 18, 0, 0, 1, 0, 12, 66, 114, 157, 120, 150, 62, 94, 2, 171, 113, 153, 27, 23, 0, 30, 167, 215, 146, 167, 185, 143, 128, 164, 161, 110, 56, 99, 42, 45, 150, 200, 155, 190, 158, 121, 85, 134, 172, 72, 4, 78, 137, 156, 165, 
+#> 136, 175, 118, 163, 191, 115, 129, 52, 64, 49, 174, 118, 168, 144, 96, 7, 11, 8, 8, 14, 12, 4, 4, 5, 3, 5, 11, 19, 10, 0, 6, 1, 0, 16, 77, 0, 117, 71, 112, 129, 175, 180, 160, 182, 110, 129, 140, 162, 103, 160, 136, 144, 0, 0, 1, 1, 3, 1, 0, 2, 11, 7, 11, 3, 36, 102, 140, 193, 114, 17, 30, 47, 34, 109, 99, 109, 6, 38, 2, 27, 0, 130, 92, 82, 79, 132, 53, 2, 35, 23, 2, 116, 183, 163, 133, 54, 111, 142, 90, 109, 32, 42, 137, 153, 194, 177, 66, 85, 108, 69, 178, 154, 146, 113, 8, 95, 100, 5, 58, 56, 
+#> 109, 130, 109, 187, 168, 171, 128, 146, 117, 90, 29, 9, 46, 147, 167, 181, 169, 74, 71, 107, 149, 178, 182, 188, 108, 13, 43, 120, 137, 170, 99, 111, 28, 58, 185, 208, 113, 181, 132, 73, 42, 42, 148, 148, 126, 151, 134, 200, 154, 166, 164, 148, 119, 189, 144, 194, 199, 178, 163, 68, 2, 11, 145, 93, 125, 123, 9, 5, 47, 155, 183, 182, 170, 176, 173, 173, 168, 69, 94, 171, 180, 165, 146, 127, 5, 48, 33, 87, 133, 143, 201, 151, 148, 141, 83, 71, 24, 48, 9, 43, 12, 1, 16, 31, 151, 156, 164, 173, 104, 
+#> 156, 163, 177, 142, 105, 151, 171, 163, 159, 114, 43, 15, 89, 120, 121, 107, 83, 158, 72, 140, 126, 103, 126, 122, 55, 1, 0, 1, 6, 6, 5, 0, 4, 4, 7, 4, 9, 5, 9, 1, 1, 5, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 1, 1, 5, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 2, 8, NA, 0, 0, 0, 1, 1, 5, 5, 9, 0, 0, 11, 8, 11, 1, 53, 127, 132, 125, 166, 152, 124, 156, 133, 98, 27, 26, 1, 56, 130, 111, 51, 124, 123, 137, 132, 87, 111, 93, 76, 26, 49, 9, 10, 7, 10, 13, 10, 8, 15, 6, 4, 4, 3, 0, 2, 0, 0, 0, 0, 0, 
+#> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 11, 90, 182, 142, 153, 172, 152, 141, 57, 76, 127, 107, 2, 32, 112, 113, 149, 91, 52, 13, 15, 7, 127, 58, 118, 99, 47, 131, 117, 115, 54, 30, 19, 3, 84, 177, 198, 195, 188, 180, 198, 180, 197, 205, 193, 191, 145, 144, 172, 150, 130, 181, 180, 164, 111, 76, 190, 137, 183, 149, 161, 74, 71, 0, 1, 5, 1, 21, 27, 14, 10, 12, 11, 3, 0, 8, 0, 9, 5, 3, 46, 64, 42, 64, 169, 92, 77, 148, 60, 76, 104, 83, 4, 87, 8, 21, 69, 29, 124, 175, 176, 161, 180, 181, 179, 64, 
+#> 36, 12, 66, 75, 53, 140, 130, 178, 179, 214, 165, 178, 166, 189, 197, 169, 144, 168, 155, 146, 152, 46, 0, 96, 150, 204, 216, 221, 217, 201, 183, 174, 186, 213, 169, 16, 129, 4, 22, 16, 147, 163, 155, 48, 105, 126, 163, 121, 10, 32, 29, 61, 102, 173, 61, 97, 142, 150, 116, 50, 136, 200, 178, 176, 165, 130, 78, 98, 166, 178, 114, 156, 185, 146, 134, 14, 72, 131, 118, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 11, 6, 10, 0, 66, 201, 177, 51, 109, 159, 172, 146, 145, 151, 79, 155, 163, 137, 
+#> 99, 30, 24, 76, 117, 190, 160, 187, 139, 102, 60, 135, 128, 20, 160, 52, NA, NA, 0, 6, NA, 1, 0, 2, 0, 0, 12, 4, 12, 12, 8, 7, 6, 1, 4, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 185, 212, 177, 197, 163, 82, 68, 87, 105, 127, 100, 155, 165, 189, 162, 204, 200, 188, 196, 190, 187, 179, 5, 11, 57, 140, 117, 109, 154, 36, 83, 75, 33, 144, 181, 119, 176, 191, 167, 85, 174, 144, 126, 157, 32, 71, 158, 203, 176, 177, 161, 117, 103, 77, 135, 159, 25, 54, 50, 147, 
+#> 136, 153, 137, 129, 126, 101, 91, 115, 108, 116, 147, 196, 216, 173, 99, 83, 186, 132, 177, 156, 156, 64, 0, 1, 18, 16, 24, 11, 20, 28, 15, 12, 14, 6, 84, 56, 190, 194, 191, 204, 41, 159, 181, 184, 113, 175, 50, 82, 77, 176, 181, 196, 189, 164, 166, 99, 178, 132, 144, 44, 22, 105, 191, 169, 155, 172, 137, 169, 156, 173, 126, 73, 27, 147, 21, 62, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 16, 69, 27, 112, 116, 61, 9, 138, 121, 107, 95, 111, 98, 58, 0, 8, 7, 86, 166, 112, 166, 163, 57, 167, 106, 127, 43, 
+#> 147, 42, 0, 1, 3, 1, 2, 2, 2, 1, 11, 1, 1, 0, 0, 0, 0, 0, 7, 4, 10, 10, 10, 17, 13, 0, 2, 1, 0, 0, 1, 0, 0, 0, 7, 54, 22, 159, 152, 168, 150, 111, 111, 34, 69, 23, 34, 185, 190, 174, 170, 108, 27, 60, 40, 41, 24, 45, 117, 158, 155, 126, 82, 99, 89, 99, 110, 106, 77, 169, 188, 143, 76, 90, 95, 18, 171, 132, 38, 12, 2, 84, 36, 78, 45, 151, 156, 106, 189, 149, 130, 76, 77, 17, 180, 156, 165, 190, 196, 191, 212, 154, 168, 85, 152, 158, 151, 131, 116, 17, 154, 165, 162, 177, 151, 170, 182, 174, 37, 187, 
+#> 1, 46, 58, 73, 185, 206, 170, 160, 115, 118, 141, 56, 69, 36, 68, 12, 26, NA, NA, NA, NA, NA, NA, 0, NA, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 17, 165, 213, 185, 87, 195, 163, 193, 153, 111, 146, 174, 203, 188, 187, 191, 67, 141, 144, 20, 15, 2, 14, 3, 4, 0, NA, 0, 0, NA, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 2, 4, 0, 3, 3, 5, 9, 17, 9, 10, 11, 15, 10, 13, 6, 1, 0, 0, 1, 0, 1, 0, 0, 0, 7, 0, 0, 15, 10, 11, 6, 2, 0, 
+#> 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 11, 10, 7, 5, 4, 6, 3, 3, 10, 34, 173, 182, 172, 153, 176, 213, 145, 43, 171, 163, 157, 8, 77, 4, 0, 148, 187, 146, 161, 172, 183, 163, 158, 123, 173, 36, 97, 90, 97, 135, 141, 122, 145, 159, 161, 114, 132, 28, 63, 85, 165, 87, 43, 46, 61, 56, 8, 137, 24, 11, 5, 119, 128, 167, 181, 152, 145, 51, 101, 140, 33, 23, 18, 59, 10, 65, 181, 122, 60, 105, 174, 140, 173, 157, 160, 97, 112, 173, 171, 86, 141, 69, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 122, 164, 169, 118, 79, 165, 
+#> 158, 163, 0, 5, 21, 141, 72, 90, 96, 35, 29, 40, 11, 9, 41, 35, 102, 142, 198, 178, 150, 56, 65, 154, 182, 109, 20, 165, 128, 15, 87, 190, 90, 186, 145, 160, 144, 89, 43, 42, 49, 138, 83, 110, 107, 74, 76, 23, 19, 36, 4, 11, 9, 81, 161, 129, 44, 79, 26, 90, 116, 31, 87, 67, 177, 185, 194, 183, 184, 121, 185, 184, 129, 33, 123, 103, 48, 99, 159, 177, 54, 195, 108, 39, 89, 184, 95, 122, 72, 0, 0, 0, 1, 0, 0, 2, 1, 0, 7, 0, 7, 19, 12, 15, 16, 16, 129, 131, 165, 159, 186, 186, 181, 147, 0, 0, 1, 1, 0, 
+#> 0, 0, 0, 1, 1, 0, 1, 3, 0, 0, 1, 23, 176, 174, 121, 178, 161, 114, 163, 156, 60, 86, 1, 33, 107, 173, 142, 63, 130, 171, 138, 114, 30, 71, 39, 100, 176, 180, 150, 195, 122, 71, 155, 158, 0, 3, 18, 16, 16, 14, 8, 15, 13, 0, 110, 114, 155, 146, 142, 60, 24, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 162, 96, 62, 13, 50, 109, 110, 22, 69, 92, 179, 135, 125, 82, 134, 93, 139, 122, 127, 160, 162, 151, 142, 158, 131, 85, 116, NA, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 179, 174, 192, 52, 156, 99, 
+#> 125, 132, 130, 14, 0, 1, 0, 0, 0, 1, 0, 0, 3, 5, 11, 1, 0, 0, 1, 1, 0, 9, 6, 20, 6, 4, 15, 8, 12, 6, 2, 7, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 37, 72, 99, 160, 139, 72, 39, 36, 50, 73, 79, 197, 142, 157, 118, 62, 150, 3, 1, 0, 0, 0, 0, 9, 10, 12, 7, 10, 6, 9, 4, 6, 23, 177, 99, 161, 148, 162, 52, 139, 107, 97, 39, 3, 5, 8, 2, 4, 94, 135, 76, 12, 79, 148, 155, 80, 117, 158, 136, 27, 156, 151, 177, 185, 126, 177, 56, 171, 4, 4, 1, 53, 7, 58, 120, 151, 120, 21, 97, 127, 88, 51, 2, 2, 7, NA, NA, 0, 0, 
+#> 0, 0, 1, 0, 0, 0, 2, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 124, 46, 178, 153, 170, 177, 139, 150, 165, 165, 157, 181, 170, 145, 172, 155, 138, 137, 169, 140, 115, 80, 21, 0, 22, 10, 1, 10, 16, 15, 11, 12, 6, 2, 1, 29, 72, 38, 120, 127, 125, 152, 110, 166, 178, 10, 71, 99, 147, 121, 120, 109, 41, 155, 188, 15, 212, 82, 172, 156, 116, 2, 5, 3, 16, 12, 14, 11, 9, 102, 111, 131, 131, 123, 32, 69, 134, 128, 38, 52, 185, 189, 168, 150, 96, 143, 191, 182, 
+#> 188, 187, 182, 125, 172, 177, 181, 10, 46, 96, 157, 135, 155, 150, 149, 164, 161, 132, 95, 130, 105, 161, 105, 33, 53, 106, 96, 122, 183, 189, 174, 192, 168, 149, 135, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 9, 0, 0, 0, 0, 0, 0, 17, 67, 137, 89, 75, 85, 34, 6, 44, 155, 185, 155, 157, 115, 153, 138, 49, 128, 150, 45, 91, 161, 105, 165, 150, 123, 93, 40, 134, 31, 89, 158, 135, 171, 155, 147, 153, 136, 0, 4, 0, 18, 2, 0, 0, 40, 186, 167, 112, 170, 46, 81, 153, 71, 16, 73, 47, 4, 129, 149, 103, 133, 
+#> 117, 201, 159, 96, 171, 172, 50, 189, 151, 134, 112, 146, 164, 115, 0, 1, 0, 0, 0, 1, 0, 13, 8, 11, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 10, 12, 71, 148, 87, 96, 143, 92, 31, 164, 161, 95, 91, 142, 158, 158, 142, 90, 90, 117, 140, 153, 133, 69, 5, 80, 146, 26, 155, 121, 128, 89, 19, 146, 139, 104, 47, 10, 0, 7, 4, 89, 142, 161, 110, 173, 130, 50, 64, 150, 124, 163, 148, 194, 185, 172, 165, 144, 90, 158, 97, 155, 160, 8, 16, 124, 94, 97, 88, 138, 162, 174, 
+#> 118, 102, 88, 145, 1, 27, 182, 190, 173, 172, 144, 116, 96, 172, 3, 6, 27, 110, 132, 152, 128, 118, 150, 124, 150, 151, 128, 133, 133, 137, 65, 20, 122, 5, 7, 139, 138, 89, 111, 99, 120, 135, 81, 17, 47, 0, 0, 105, 77, 143, 150, 141, 164, 107, 131, 1, 0, 13, 7, 6, 5, 23, 141, 148, 150, 168, 151, 136, 0, 0, 0, 0, 0, 0, 0, 0, 0, 12, 0, 0, 0, 1, 0, 15, 153, 124, 188, 136, 178, 50, 189, 91, 181, 49, 87, 145, 150, 138, 39, 147, 182, 122, 182, 130, 124, 177, 29, 149, 72, 72, 52, 108, 152, 163, 36, 75, 
+#> 48, 150, 132, 142, 3, 1, 8, 98, 72, 57, 11, 2, 3, 84, 93, 23, 34, 19, 139, 167, 88, 150, 1, 87, 199, 162, 156, 89, 45, 128, 130, 92, 106, 4, 29, 25, 89, 111, 158, 151, 62, 162, 165, 150, 93, 162, 63, 98, 45, 6, 59, 100, 142, 169, 18, 96, 141, 150, 163, 0, 0, 7, 6, 3, 6, 0, 3, 4, 0, 2, 4, 107, 174, 122, 8, 61, 177, 20, 27, 0, 0, 0, 1, 0, 47, 154, 160, 158, 166, 2, 0, 0, 1, 15, 68, 113, 132, 170, 95, 117, 114, 69, 165, 143, 93, 135, 130, 106, 155, 74, 0, 7, 7, 11, 6, 17, 19, 176, 178, 10, 11, 61, 167, 
+#> 177, 225, 200, 20, 86, 135, 84, 35, 73, 120, 159, 158, 200, 164, 7, 126, 163, 132, 120, 139, 146, 93, 176, 82, 2, 38, 119, 139, 177, 142, 165, 157, 6, 5, 7, 0, 1, 0, 0, 2, 7, 12, 0, 87, 133, 142, 127, 54, 102, 118, 66, 4, 55, 134, 161, 68, 69, 22, 176, 205, 20, 119, 80, 192, 43, 143, 144, 166, 40, 108, 124, 121, 130, 5, 66, 174, 155, 184, 41, 135, 125, 166, 188, 172, 140, 108, 154, 46, 35, 13, 173, 56, 132, 167, 36, 44, 165, 57, 95, 74, 139, 168, 11, 129, 196) x c(1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 11, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 12, 13, 14, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 9, 10, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 17, 18, 19, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 22, 1, 2, 3, 4, 5, 6, 7, 7, 
+#> 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 1, 3, 4, 5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 10, 10, 11, 12, 13, 14, 15, 1, 2, 3, 4, 4, 5, 6, 7, 8, 9, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 1, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 1, 2, 
+#> 3, 4, 5, 6, 7, 8, 9, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 18, 19, 21, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 1, 4, 5, 6, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 12, 13, 14, 1, 2, 3, 4, 5, 6, 6, 7, 8, 10, 13, 13, 14, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 
+#> 16, 17, 18, 20, 21, 22, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 16, 21, 28, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 13, 14, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 
+#> 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 1, 2, 2, 2, 5, 6, 7, 8, 9, 28, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 14, 15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 
+#> 9, 10, 11, 12, 13, 14, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 17, 18, 19, 20, 21, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 15, 16, 17, 18, 21, 1, 3, 4, 5, 6, 7, 8, 9, 10, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 11, 12, 13, 14, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 1, 2, 3, 4, 5, 6, 7, 8, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 23, 1, 4, 6, 7, 8, 9, 10, 11, 
+#> 12, 13, 14, 15, 15, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 14, 15, 16, 1, 2, 3, 4, 4, 6, 7, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12, 14, 15, 1, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 20, 1, 2, 3, 4, 4, 5, 6, 8, 15, 1, 2, 3, 4, 5, 6, 7, 8, 8, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 1, 2, 3, 4, 5, 6, 7, 
+#> 8, 9, 10, 10, 11, 12, 13, 14, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 12, 13, 14, 14, 15, 1, 5, 6, 7, 8, 9, 10, 11, 12, 14, 15, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 2, 
+#> 3, 4, 5, 6, 7, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 1, 3, 4, 5, 6, 6, 7, 8, 9, 11, 12, 13, 13, 15, 1, 2, 3, 4, 5, 6, 7, 8, 8, 9, 10, 12, 1, 2, 3, 4, 5, 1, 2, 2, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 24, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 
+#> 11, 12, 13, 14, 15, 16, 19, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 1, 2, 3, 7, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 2, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 8, 9, 10, 11, 12, 13, 14, 15, 16, 1, 2, 3, 4, 5, 6, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 1, 2, 3, 4, 5, 6, 7, 9, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 14, 14, 15, 16, 1, 2, 
+#> 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 1, 2, 3, 4, 4, 5, 6, 7, 8, 9, 9, 10, 11, 12, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 19, 20, 21, 22, 23, 1, 2, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 14, 14, 15, 16, 20, 21, 1, 3, 4, 5, 6, 8, 8, 9, 10, 10, 11, 1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 2, 3, 4, 5, 6, 1, 4, 5, 6, 7, 8, 8, 9, 10, 11, 12, 13, 14, 15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1, 2, 3, 4, 4, 5, 
+#> 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 19, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 1, 3, 4, 5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 15, 16, 17, 18, 18, 19, 19, 19, 1, 3, 4, 4, 5, 
+#> 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 1, 3, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 17, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 5, 6, 7, 8, 9, 10, 11, 12, 1, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 12, 13, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 
+#> 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 1, 2, 3, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 16, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 1, 2, 3, 4, 5, 5, 6, 7, 8, 9, 10, 11, 12, 12, 13, 13, 14, 15, 1, 2, 3, 4, 5, 6, 6, 7, 8, 9, 10, 11, 12, 13, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 15, 16, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 
+#> 11, 12, 13, 1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 1, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 11, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 20, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 19, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 15, 15, 16, 18, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 12, 13, 14, 15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 
+#> 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 11, 12, 13, 14, 14, 15, 16, 17, 18, 19, 20, 20, 21, 1, 2, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 1, 1, 4, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 20, 21, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 19, 20, 1, 2, 9, 10, 11, 12, 13, 14, 15, 1, 2, 3, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 1, 1, 2, 3, 4, 5, 8, 9, 10, 
+#> 11, 1, 2, 3, 4, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 
+#> 16, 17, 18, 20, 21, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 11, 12, 13, 14, 15, 16, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 24, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 15, 16, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 1, 2, 3, 4, 5, 5, 6, 6, 7, 8, 9, 10, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 11, 11, 12, 1, 2, 3, 4, 5, 6, 7, 7, 8, 9, 10, 11, 12, 13, 14, 15, 15, 16, 16, 1, 2, 3, 4, 5, 6, 7, 
+#> 8, 9, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 8, 9, 10, 11, 12, 13, 14, 15, 16, 16, 17, 1, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 11, 12, 13, 14, 1, 5, 6, 7, 8, 9, 10, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 13, 14, 14, 15, 
+#> 15, 16, 17, 18, 19, 20, 20, 21, 1, 2, 3, 4, 5, 6, 7, 7, 8, 9, 10, 10, 11, 12, 12, 1, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 16, 17, 18, 19, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 1, 2, 3, 4, 5, 6, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 15, 15, 16, 18, 18, 19, 1, 2, 2, 3, 4, 5, 5, 6, 
+#> 7, 8, 9, 9, 10, 11, 1, 7, 8, 9, 10, 1, 2, 3, 4, 5, 5, 6, 7, 8, 8, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 13, 14, 15, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 7, 8, 9, 10, 11, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 8, 9, 9, 1, 2, 3, 
+#> 4, 5, 6, 7, 8, 9, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 11, 12, 12, 13, 14, 15, 1, 2, 3, 4, 5, 6, 6, 7, 8, 8, 9, 10, 12, 13, 13, 14, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 1, 2, 4, 5, 10, 11, 12, 13, 14, 15, 15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 18, 20, 21, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 
+#> 18, 19, 20, 1, 2, 5, 6, 7, 8, 9, 10, 11, 12, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 11, 12, 1, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 1, 2, 3, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 13, 14, 15, 16, 17, 18, 19, 1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 10, 11, 12, 12, 13, 14, 15, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 13, 14, 16, 1, 2, 3, 4, 5, 6, 7, 
+#> 8, 9, 10, 11, 11, 12, 13, 16, 16, 17, 1, 4, 5, 6, 7, 8, 9, 10, 10, 11, 11, 12, 13, 14, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 15, 16, 17, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 19, 1, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 12, 13, 14, 15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 
+#> 8, 9, 9, 10, 11, 11, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 10, 11, 12, 12, 13, 14, 14, 15, 16, 17, 1, 2, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 11, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 16, 17, 1, 4, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 11, 14, 15, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 
+#> 17, 18, 19, 20, 21, 22, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 16, 1, 4, 5, 6, 7, 8, 9, 10, 11, 12, 16, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 17, 1, 3, 4, 5, 6, 7, 8, 9, 10, 1, 2, 3, 4, 5, 6, 7, 11, 12, 13, 14, 15, 16, 1, 2, 3, 4, 5, 6, 6, 7, 8, 8, 9, 10, 11, 11, 12, 12, 1, 2, 3, 4, 5, 6, 7, 8, 
+#> 9, 10, 10, 11, 12, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 12, 13, 14, 15, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 18, 19, 20, 21, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 11, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 13, 14, 1, 2, 3, 4, 5, 6, 7, 7, 8, 9, 10, 10, 11, 12, 13, 14, 15, 16, 18, 1, 2, 4, 6, 7, 8, 9, 10, 10, 11, 1, 2, 3, 4, 5, 6, 6, 7, 8, 9, 9, 10, 11, 12, 1, 2, 3, 4, 4, 9, 1, 2, 3, 4, 5, 6, 7, 11, 12, 13, 
+#> 14, 14, 15, 16, 17, 18, 1, 2, 4, 5, 6, 7, 8, 9, 10, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 6, 7, 8, 9, 1, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 22, 23, 24, 1, 2, 3, 4, 4, 5, 6, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 15, 16, 17, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 11, 12, 13, 14, 1, 2, 4, 6, 7, 7, 8, 9, 9, 10, 11, 11, 12, 13, 14, 14, 15, 15, 15, 16, 17, 18, 18, 19, 19, 20, 24, 24, 25, 1, 2, 3, 4, 5, 6, 7, 10, 11, 12, 13, 14, 15, 1, 4, 5, 
+#> 6, 7, 8, 9, 10, 11, 12, 13, 14, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 11, 12, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 1, 2, 3, 4, 5, 6, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 1, 2, 3, 4, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 
+#> 1, 2, 3, 4, 4, 5, 6, 7, 8, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 1, 2, 3, 3, 4, 5, 6, 7, 7, 8, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 14, 15, 15, 16, 16, 1, 2, 3, 4, 5, 6, 7, 8, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 11, 12, 1, 2, 4, 5, 6, 7, 8, 9, 10, 10, 11, 12, 13, 13, 14, 14, 15, 1, 2, 3, 4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 1, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 1, 2, 3, 
+#> 4, 5, 6, 7, 9, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 1, 2, 3, 1, 2, 3, 4, 5, 6, 7, 8, 9, 13, 14, 15, 1, 2, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 1, 2, 3, 4, 5, 6, 7, 10, 1, 2, 3, 4, 5, 5, 6, 7, 8, 9, 11, 12, 13, 14, 15, 16, 17, 1, 2, 3, 4, 7, 8, 9, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 1, 2, 3, 4, 5, 1, 2, 3, 7, 8, 9, 10, 11, 12, 13, 1, 2, 3, 3, 4, 5, 6, 7, 10, 11, 11, 12, 13, 13, 14, 1, 2, 3, 4, 5, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 18, 19, 19, 20, 21, 22, 22, 1, 2, 3, 4, 5, 6, 
+#> 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 1, 2, 3, 4, 5, 6, 7, 1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 14, 1, 2, 3, 4, 6, 7, 8, 9, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 1, 2, 3, 6, 7, 8, 9, 10, 11, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 1, 2, 3, 4, 5, 7, 8, 9, 10, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 13, 14, 15, 15, 1, 2, 3, 4, 5, 6, 7, 8, 8, 9, 10, 10, 12, 1, 2, 6, 7, 8, 1, 2, 6, 7, 8, 9, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 13, 14, 15, 
+#> 18, 1, 5, 6, 7, 8, 9, 10, 11, 11, 12, 13, 13, 1, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 14, 15, 1, 4, 5, 6, 7, 8, 9, 9, 10, 11, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 14, 19, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1, 3, 4, 6, 7, 8, 9, 10, 12, 1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 1, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 11, 11, 12, 13, 14, 15, 15, 16, 17, 18, 1, 2, 3, 4, 4, 5, 6, 7, 8, 9, 10, 10, 1, 2, 3, 4, 
+#> 5, 6, 7, 8, 8, 9, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 15, 1, 2, 3, 4, 5, 7, 8, 1, 2, 3, 3, 4, 5, 5, 6, 7, 7, 1, 2, 3, 4, 5, 6, 6, 7, 8, 9, 1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 14, 15, 1, 3, 4, 5, 6, 6, 7, 8, 9, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 1, 2, 4, 5, 6, 7, 8, 9, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 11, 13, 14, 14, 15, 16, 1, 2, 3, 4, 4, 12, 13, 14, 15, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 
+#> 11, 12, 13, 13, 14, 15, 16, 17, 1, 2, 3, 4, 5, 6, 7, 7, 1, 2, 3, 3, 4, 5, 5, 5, 6, 7, 8, 8, 9, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 10, 11, 12, 13, 14, 15, 16, 17, 1, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 1, 2, 3, 4, 4, 5, 6, 7, 8, 9, 9, 9, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 1, 2, 3, 4, 7, 8, 9, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 9, 10, 10, 1, 2, 3, 8, 9, 10, 10, 1, 2, 3, 8, 9, 10, 11, 12, 
+#> 13, 1, 2, 3, 4, 5, 8, 9, 10, 11, 12, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 1, 2, 3, 4, 4, 5, 6, 7, 8, 9, 10, 10, 11, 12, 12, 13, 14, 14, 15, 1, 3, 4, 5, 6, 7, 8, 9, 9, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 1, 2, 3, 6, 7, 8, 9, 10, 11, 11, 12, 13, 13, 14, 15, 16, 16, 1, 2, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 1, 2, 3, 4, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 14, 1, 5, 6, 7, 8, 9, 10, 10, 11, 12, 13, 14, 14, 1, 2, 3, 7, 8, 9, 10, 11, 12, 
+#> 13, 14, 15, 16, 17, 18, 19, 1, 2, 3, 7, 8, 9, 10, 11, 12, 13, 14, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 10, 11, 12, 13, 14, 1, 2, 3, 4, 5, 6, 6, 7, 9, 10, 11, 1, 5, 6, 7, 8, 9, 10, 11, 11, 12, 14, 1, 2, 3, 4, 5, 6, 7, 8, 8, 9, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 11, 11, 13, 1, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 24, 1, 5, 6, 7, 
+#> 8, 9, 10, 11, 11, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 1, 2, 3, 4, 5, 6, 7, 11, 12, 12, 13, 14, 15, 16, 17, 1, 2, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 11, 12, 13, 14, 1, 2, 6, 7, 8, 9, 10, 11, 11, 12, 12, 12, 13, 13, 14, 15, 16, 16, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 11, 12, 13, 13, 14, 15, 15, 1, 2, 3, 4, 5, 6, 7, 11, 1, 2, 3, 4, 5, 6, 7, 8, 8, 9, 10, 10, 10, 11, 12, 1, 2, 3, 4, 5, 6, 
+#> 7, 8, 9, 10, 1, 2, 3, 4, 5, 6, 6, 7, 8, 8, 9, 10, 11, 12, 13, 14, 15, 15, 16, 17, 17, 1, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 1, 2, 3, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 1, 2, 3, 6, 7, 8, 9, 10, 10, 11, 12, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 11, 12, 1, 2, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 2, 3, 4, 4, 5, 6, 7, 8, 9, 10, 10, 11, 11, 12, 
+#> 13, 1, 2, 3, 4, 5, 6, 8, 9, 9, 10, 11, 12, 13, 13, 1, 3, 5, 6, 7, 8, 9, 10, 11, 11, 12, 13, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 16, 19, 1, 2, 3, 5, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 22, 23, 1, 6, 7, 8, 9, 10, 11, 11, 
+#> 12, 12, 13, 13, 14, 14, 1, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 14, 15, 16, 16, 16, 1, 2, 5, 8, 9, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 1, 3, 4, 5, 6, 6, 7, 8, 1, 2, 3, 4, 4, 5, 6, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 18, 19, 19, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 6, 7, 8, 8, 9, 10, 11, 12, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 
+#> 12, 13, 14, 14, 15, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 12, 13, 13, 14, 15, 16, 17, 18, 19, 1, 2, 3, 4, 4, 5, 6, 7, 8, 9, 10, 11, 11, 12, 12, 12, 1, 2, 3, 4, 5, 6, 8, 1, 2, 3, 4, 5, 5, 6, 7, 7, 7, 9, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 13, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 11, 11, 1, 2, 3, 6, 7, 8, 9, 10, 11, 12, 13, 14, 14, 1, 2, 3, 4, 5, 6, 7, 8, 8, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 
+#> 14, 14, 15, 17, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 1, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 10, 11, 12, 12, 13, 13, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 
+#> 11, 12, 13, 14, 15, 16, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 19, 20, 21, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 13, 14, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 1, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 14, 15, 15, 16, 16, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 1, 3, 
+#> 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 28, 32, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 14, 15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 11, 12, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 15, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 13, 14, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 13, 1, 2, 3, 4, 5, 5, 6, 7, 8, 9, 10, 11, 11, 11, 12, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 14, 14, 15, 16, 17, 
+#> 18, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 1, 2, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 1, 2, 3, 4, 5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 1, 2, 3, 3, 4, 5, 6, 7, 8, 9, 10, 12, 1, 2, 2, 3, 4, 5, 6, 7, 8, 9, 1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 10, 11, 12, 13, 14, 15, 15, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 11, 12, 13, 14, 14, 15, 15, 15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 16, 1, 2, 3, 4, 5, 6, 7, 8, 
+#> 9, 10, 10, 11, 1, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 1, 2, 3, 4, 5, 6, 7, 8, 8, 1, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 18, 19, 20, 21, 22, 1, 2, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 1, 2, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 1, 2, 3, 4, 5, 6, 7, 8, 
+#> 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 11, 11, 1, 2, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 1, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 11, 12, 13, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 11, 12, 13, 14, 14, 1, 2, 3, 4, 5, 6, 6, 7, 8, 1, 2, 3, 4, 5, 5, 6, 6, 7, 8, 9, 10, 11, 12, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 14, 15, 
+#> 16, 17, 18, 19, 20, 21, 1, 2, 3, 4, 5, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 11, 11, 12, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 11, 12, 13, 14, 1, 2, 3, 4, 5, 6, 6, 7, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 
+#> 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 13, 14, 14, 1, 3, 4, 5, 6, 7, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 16, 17, 18, 19, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 14, 1, 2, 3, 5, 6, 7, 8, 9, 1, 2, 3, 5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 11, 12, 1, 2, 2, 3, 4, 4, 5, 6, 7, 8, 9, 10, 11, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 15, 16, 17, 18, 19, 20, 21, 21, 22, 22, 23, 24, 25, 
+#> 1, 2, 3, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 11, 12, 12, 12, 13, 14, 14, 15, 16, 17, 18, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 5, 6, 6, 8, 8, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 
+#> 11, 11, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 22, 23, 24, 1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 10, 11, 12, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 
+#> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 11, 1, 2, 3, 4, 5, 6, 6, 7, 7, 8, 9, 10, 11, 11, 12, 15, 16, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 13, 14, 15, 16, 17, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 
+#> 9, 10, 11, 12, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 10, 10, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 1, 2, 3, 4, 5, 6, 7, 7, 8, 8, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 2, 3, 4, 5, 6, 6, 7, 7, 7, 8, 8, 1, 2, 3, 4, 5, 6, 7, 7, 8, 9, 10, 11, 12, 12, 13, 13, 14, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 1, 2, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 14, 15, 15, 15, 
+#> 16, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 1, 2, 3, 4, 5, 6, 7, 8, 8, 9, 10, 11, 12, 13, 14, 14, 15, 15, 1, 2, 3, 6, 9, 10, 11, 12, 12, 13, 14, 15, 16, 16, 16, 17, 18, 1, 2, 3, 4, 5, 6, 6, 7, 8, 9, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 1, 2, 4, 5, 6, 7, 8, 8, 9, 10, 11, 12, 12, 
+#> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 14, 15, 16, 16, 17, 1, 2, 3, 4, 5, 6, 6, 7, 8, 9, 9, 10, 11, 11, 1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 10, 11, 12, 13, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 1, 2, 3, 4, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 14, 14, 1, 2, 3, 4, 5, 6, 7, 
+#> 8, 9, 10, 11, 12, 13, 14, 15, 16, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 20, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 14, 15, 16, 16, 17, 17, 18, 19, 20, 21, 22, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 15, 1, 2, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 1, 2, 3, 1, 2, 3, 4, 5, 6, 
+#> 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 11, 12, 13, 14, 15, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 11, 12, 12, 13, 13, 14, 1, 3, 4, 5, 6, 7, 8, 9, 10, 10, 11, 12, 12, 13, 14, 15, 16, 17, 17, 1, 2, 3, 4, 4, 5, 5, 5, 6, 7, 7, 8, 9, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 15, 
+#> 16, 16, 16, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 14, 15, 16, 1, 2, 3, 4, 4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 1, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 1, 5, 6, 7, 8, 9, 10, 
+#> 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 22, 22, 23, 23, 24, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 13, 14, 14, 15, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 11, 12, 12, 13, 1, 2, 3, 4, 5, 6, 6, 7, 8, 9, 1, 2, 3, 4, 
+#> 5, 6, 7, 8, 9, 9, 10, 11, 12, 1, 2, 3, 4, 5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 17, 1, 2, 3, 4, 5, 6, 6, 7, 8, 9, 10, 11, 12, 13, 14, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 11, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 11, 1, 2, 3, 4, 6, 7, 8, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 13, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 13, 
+#> 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 11, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 16, 17, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 1, 2, 3, 4, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 1, 2, 3, 4, 5, 6, 7, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 10, 11, 12, 13, 14, 15, 16, 1, 2, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 15, 16, 17, 18, 
+#> 19, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 1, 3, 3, 5, 7, 8, 9, 10, 10, 11, 11, 12, 13, 13, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 
+#> 14, 15, 16, 17, 18, 19, 19, 20, 21, 22, 22, 1, 2, 3, 4, 5, 6, 7, 8, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 15, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 1, 3, 4, 5, 7, 8, 9, 9, 10, 10, 10, 1, 2, 3, 4, 5, 6, 7, 7, 8, 9, 
+#> 10, 11, 12, 13, 14, 14, 14, 15, 16, 17, 18, 19, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 14, 15, 16, 16, 1, 2, 3, 4, 5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 16, 17, 18, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 1, 3, 4, 5, 6, 7, 8, 9, 10, 10, 11, 12, 13, 14, 15, 16, 16, 17, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 10, 11, 1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 
+#> 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 12, 13, 14, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 1, 3, 4, 5, 6, 7, 8, 9, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 1, 3, 4, 4, 5, 6, 7, 8, 9, 10, 10, 11, 11, 12, 13, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 
+#> 15, 16, 17, 18, 19, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 1, 2, 3, 4, 5, 6, 7, 7, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 1, 2, 3, 4, 5, 6, 6, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 5, 6, 7, 8, 9, 10, 11, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 1, 2, 3, 4, 
+#> 5, 6, 7, 8, 9, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 1, 2, 3, 4, 5, 6, 7, 7, 8, 9, 10, 11, 12, 13, 13, 14, 15, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 15, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 1, 2, 3, 4, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 11, 1, 2, 3, 4, 
+#> 5, 6, 7, 8, 9, 10, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 17, 18, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 19, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 
+#> 16, 17, 18, 18, 20, 21, 22, 23, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1, 2, 3, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 18, 1, 2, 3, 4, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 14, 15, 16, 17, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14, 15, 16, 17, 18, 19, 20, 20, 21, 22, 23, 23, 24, 25, 26, 27, 1, 2, 3, 
+#> 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 17, 18, 19, 20, 20, 21, 22, 23, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 1, 2, 3, 4, 4, 5, 5, 6, 7, 8, 1, 2, 3, 4, 5, 1, 2, 3, 4, 4, 5, 1, 2, 2, 3, 4, 5, 6, 7, 8, 9, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 13, 14, 15, 16, 17, 18, 19, 20, 21, 21, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 11, 12, 13, 
+#> 14, 15, 1, 5, 6, 7, 8, 9, 10, 10, 11, 11, 12, 13, 14, 14, 15, 15, 16, 16, 17, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 14, 15, 16, 16, 17, 18, 18, 19, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 17, 18, 1, 2, 3, 4, 5, 6, 7, 7, 8, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 
+#> 12, 13, 14, 15, 16, 17, 18, 19, 20, 20, 21, 21, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 16, 17, 18, 1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 12, 13, 14, 
+#> 15, 16, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 11, 12, 13, 14, 15, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 13, 14, 15, 15, 16, 1, 2, 3, 4, 5, 6, 7, 7, 8, 9, 11, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 24, 24, 1, 2, 3, 4, 5, 6, 
+#> 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 17, 18, 19, 20, 21, 22, 23, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 13, 14, 15, 16, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 
+#> 12, 13, 14, 14, 15, 16, 17, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 11, 12, 13, 14, 15, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 18, 19, 20, 21, 22, 23, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 18, 19, 1, 2, 3, 4, 4, 5, 6, 7, 9, 10, 11, 12, 13, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 10, 11, 11, 12, 13, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 1, 3, 4, 5, 6, 7, 8, 9, 
+#> 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 1, 2, 2, 3, 4, 5, 6, 7, 8, 8, 9, 10, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 7, 7, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 10, 11, 11, 12, 1, 2, 3, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 19, 20, 21, 21, 22, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 
+#> 10, 11, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 1, 2, 3, 4, 5, 6, 7, 8, 9, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 3, 4, 5, 6, 7, 8, 8, 9, 10, 11, 11, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 11, 12, 1, 2, 3, 1, 2, 3, 4, 6, 6, 8, 12, 13, 14, 15, 16, 17, 1, 2, 3, 
+#> 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 16, 17, 18, 19, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 8, 9, 10, 11, 12, 13, 14, 15, 15, 16, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 1, 2, 2, 3, 4, 4, 5, 6, 7, 8, 9, 10, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 11, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14, 15, 16, 
+#> 17, 18, 18, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 11, 12, 13, 14, 15, 15, 16, 17, 18, 19, 19, 20, 21, 22, 22, 23, 24, 25, 1, 2, 3, 4, 5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 11, 12, 13, 14, 15, 1, 2, 3, 4, 5, 6, 7, 
+#> 8, 9, 10, 11, 12, 13, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 15, 16, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 11, 12, 13, 14, 15, 15, 1, 2, 3, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1, 2, 3, 4, 6, 7, 
+#> 8, 9, 10, 11, 11, 12, 13, 14, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 20, 1, 2, 3, 4, 5, 6, 7, 8, 8, 9, 10, 11, 12, 13, 14, 15, 16, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 10, 11, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 
+#> 13, 14, 15, 16, 17, 18, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 1, 4, 5, 6, 7, 8, 9, 10, 11, 11, 12, 13, 14, 15, 1, 3, 4, 5, 6, 7, 8, 9, 9, 9, 10, 11, 1, 2, 3, 4, 5, 5, 6, 7, 8, 9, 9, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 7, 8, 9, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 
+#> 14, 15, 16, 17, 18, 19, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 5, 6, 7, 8, 9, 10, 11, 12, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 23, 23, 24, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 11, 12, 13, 14, 14, 15, 16, 17, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 1, 2, 3, 4, 5, 6, 7, 7, 8, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 1, 2, 3, 4, 5, 6, 6, 7, 8, 9, 10, 11, 12, 
+#> 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 17, 17, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 1, 2, 3, 4, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 12, 14, 15, 16, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 11, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 17, 1, 2, 3, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 
+#> 14, 14, 15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 14, 15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 11, 12, 13, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 11, 11, 12, 13, 14, 15, 16, 17, 18, 18, 19, 20, 20, 21, 21, 22, 1, 2, 3, 4, 5, 6, 7, 8, 8, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 11, 12, 12, 13, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 
+#> 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 13, 14, 15, 16, 17, 18, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 11, 12, 13, 15, 16, 17, 19, 19, 1, 2, 3, 4, 5, 6, 7, 8, 8, 9, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 1, 2, 3, 4, 5, 8, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 8, 9, 10, 11, 12, 13, 14, 15, 16, 16, 17, 1, 
+#> 2, 3, 4, 5, 6, 7, 8, 9, 10, 1, 2, 3, 4, 5, 5, 6, 7, 8, 9, 9, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 9, 10, 1, 2, 3, 4, 5, 6, 7, 8, 8, 9, 10, 11, 12, 13, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 10, 11, 13, 14, 15, 1, 2, 3, 4, 5, 6, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 13, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 11, 13, 14, 15, 16, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 
+#> 13, 14, 15, 16, 17, 18, 19, 20, 21, 1, 2, 3, 4, 5, 5, 6, 7, 8, 9, 10, 11, 12, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 12, 13, 14, 15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 6, 7, 8, 9, 10, 11, 11, 1, 2, 3, 4, 5, 6, 7, 7, 8, 9, 10, 10, 11, 12, 13, 13, 14, 15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 1, 2, 3, 4, 5, 6, 6, 7, 7, 8, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 
+#> 21, 22, 23, 24, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 21, 22, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 8, 9, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 
+#> 12, 13, 15, 16, 16, 18, 20, 21, 22, 23, 24, 25, 26, 26, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 17, 18, 19, 20, 1, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 11, 12, 13, 13, 14, 15, 16, 1, 3, 4, 5, 6, 7, 8, 9, 9, 10, 11, 12, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 1, 4, 5, 6, 6, 7, 8, 8, 9, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 
+#> 12, 13, 14, 15, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 11, 12, 13, 14, 15, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 8, 9, 1, 2, 4, 5, 6, 7, 8, 8, 9, 10, 11, 12, 13, 13, 14, 14, 15, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 6, 7, 8, 1, 3, 4, 4, 5, 6, 7, 8, 9, 10, 11, 13, 13, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 11, 12, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 8, 9, 9, 10, 10, 11, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 1, 2, 3, 4, 5, 6, 7, 8, 8, 
+#> 9, 10, 11, 12, 13, 14, 15, 16, 16, 17, 18, 19, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 7, 8, 9, 10, 10, 11, 11, 12, 12, 13, 15, 16, 17, 18, 18, 19, 20, 21, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 13, 14, 14, 15, 15, 16, 17, 18, 1, 2, 3, 4, 5, 6, 6, 7, 8, 9, 9, 10, 11, 11, 12, 1, 2, 3, 4, 
+#> 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 15, 16, 17, 18, 19, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 12, 13, 14, 15, 16, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 20, 21, 22, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 
+#> 21, 22, 23, 23, 1, 2, 3, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 8, 8, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 14, 1, 2, 3, 4, 5, 6, 7, 8, 8, 9, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 12, 13, 14, 1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12, 12, 13, 14, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 18, 19, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 1, 2, 3, 
+#> 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 16, 17, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 19, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 
+#> 14, 15, 16, 16, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12, 13, 14, 14, 15, 15, 16, 17, 1, 2, 3, 4, 5, 6, 7, 7, 8, 10, 11, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 18, 19, 19, 20, 21, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14, 15, 16, 17, 18, 19, 20, 21, 22, 22, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 1, 2, 3, 4, 
+#> 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 6, 7, 8, 9, 10, 11, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 15, 1, 2, 3, 4, 5, 5, 1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 10, 11, 12, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 15, 16, 17, 17, 18, 19, 1, 2, 3, 4, 5, 6, 7, 8, 8, 9, 9, 9, 10, 11, 
+#> 12, 12, 14, 15, 16, 17, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 12, 13, 13, 14, 15, 16, 17, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 13, 
+#> 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 1, 2, 3, 4, 5, 6, 7, 7, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 1, 2, 3, 4, 5, 6, 7, 7, 8, 9, 10, 10, 13, 14, 15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 12, 13, 13, 14, 15, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 5, 6, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 7, 8, 9, 10, 10, 11, 12, 13, 14, 15, 16, 18, 1, 2, 3, 4, 5, 6, 6, 7, 8, 8, 9, 10, 11, 12, 13, 1, 2, 3, 
+#> 4, 5, 6, 7, 8, 9, 9, 10, 11, 13, 14, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 11, 11, 12, 12, 13, 1, 1, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 11, 12, 13, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 10, 11, 11, 12, 13, 14, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 14, 15, 16, 17, 17, 18, 18, 1, 2, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 1, 2, 
+#> 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 15, 1, 2, 3, 4, 5, 5, 6, 7, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 16, 17, 18, 19, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 1, 4, 5, 6, 6, 7, 8, 9, 10, 11, 12, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 21, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 2, 3, 4, 4, 5, 6, 7, 8, 9, 10, 11, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 16, 17, 18, 18, 19, 1, 2, 3, 4, 5, 6, 7, 8, 9, 
+#> 10, 11, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 11, 12, 13, 14, 15, 16, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 13, 14, 1, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 19, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 19, 20, 21, 21, 22, 22, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 16, 18, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 8, 9, 10, 11, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 
+#> 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 15, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 1, 2, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 6, 7, 8, 8, 9, 10, 11, 11, 12, 12, 1, 2, 3, 4, 5, 
+#> 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 22, 1, 2, 3, 4, 5, 6, 6, 7, 8, 9, 10, 11, 12, 12, 13, 14, 15, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 19, 1, 2, 3, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 19, 1, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 2, 3, 4, 4, 
+#> 5, 6, 7, 8, 9, 10, 11, 11, 12, 13, 13, 14, 14, 15, 16, 17, 17, 1, 2, 3, 4, 5, 6, 6, 7, 8, 9, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 10, 11, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 7, 8, 9, 10, 11, 12, 13, 14, 14, 15, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 6, 7, 8, 9, 10, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 10, 11, 12, 13, 14, 15, 16, 17, 
+#> 18, 19, 20, 20, 21, 21, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 11, 12, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14, 15, 15, 16, 17, 18, 19, 20, 21, 22, 1, 2, 3, 4, 5, 6, 7, 8, 8, 9, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 13, 14, 15, 1, 2, 3, 4, 5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 1, 3, 4, 5, 6, 7, 8, 9, 9, 10, 11, 12, 13, 14, 15, 1, 2, 3, 
+#> 4, 5, 6, 7, 8, 8, 9, 10, 11, 12, 13, 14, 15, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 7, 8, 9, 9, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 11, 12, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 15, 16, 1, 2, 3, 4, 5, 6, 7, 7, 8, 
+#> 9, 10, 11, 12, 13, 14, 14, 15, 16, 17, 18, 1, 2, 3, 4, 5, 5, 6, 7, 8, 8, 9, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 16, 17, 18, 1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 21, 22, 23, 24, 25, 27, 1, 2, 3, 4, 5, 6, 7, 8, 8, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 7, 8, 9, 9, 10, 11, 11, 1, 2, 3, 4, 5, 6, 7, 8, 
+#> 9, 10, 11, 11, 12, 13, 15, 1, 2, 3, 4, 5, 6, 6, 7, 8, 9, 10, 11, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 6, 7, 8, 9, 9, 10, 11, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 15, 16, 17, 18, 19, 20, 1, 1, 2, 3, 4, 5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 1, 2, 3, 4, 
+#> 5, 6, 7, 8, 9, 9, 10, 11, 11, 12, 12, 13, 14, 15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 1, 2, 3, 4, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 12, 13, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 1, 2, 3, 4, 5, 6, 7, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 
+#> 14, 15, 16, 17, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 12, 13, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 8, 9, 10, 11, 12, 13, 13, 14, 15, 15, 1, 3, 3, 4, 5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 10, 11, 12, 13, 14, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 1, 2, 3, 4, 5, 6, 
+#> 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 11, 12, 13, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 1, 3, 4, 5, 6, 7, 7, 8, 9, 9, 10, 11, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 13, 1, 2, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 11, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 14, 15, 17, 1, 2, 3, 4, 5, 6, 6, 1, 2, 3, 4, 5, 5, 6, 7, 8, 8, 
+#> 9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 1, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 14, 15, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 12, 13, 14, 15, 1, 1, 2, 3, 4, 5, 6, 
+#> 7, 8, 9, 9, 9, 10, 11, 12, 1, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 1, 2, 3, 4, 5, 6, 7, 8, 8, 9, 1, 2, 3, 4, 5, 6, 7, 7, 8, 9, 10, 11, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 11, 12, 13, 14, 14, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 1, 2, 3, 4, 5, 
+#> 6, 6, 7, 7, 8, 9, 10, 11, 12, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 8, 1, 1, 2, 3, 4, 5, 6, 6, 7, 8, 9, 10, 11, 1, 2, 3, 4, 5, 5, 6, 6, 7, 8, 9, 10, 11, 12, 13, 1, 2, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 8, 9, 10, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 8, 9, 10, 11, 12, 13, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 11, 12, 13, 14, 15, 16, 17, 17, 19, 1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 10, 11, 11, 
+#> 12, 1, 2, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 1, 2, 2, 3, 4, 5, 6, 7, 7, 8, 9, 10, 11, 12, 13, 15, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 17, 1, 2, 3, 4, 5, 6, 6, 7, 8, 9, 10, 11, 12, 13, 15, 16, 17, 18, 19, 1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 11, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 8, 1, 
+#> 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 11, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1, 3, 4, 5, 6, 7, 8, 8, 9, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 8, 9, 10, 11, 12, 13, 14, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 12, 13, 13, 14, 16, 1, 2, 3, 4, 5, 6, 6, 7, 8, 8, 9, 9, 10, 10, 11, 11, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 
+#> 13, 14, 14, 1, 2, 3, 4, 5, 6, 7, 7, 8, 9, 10, 11, 11, 1, 2, 3, 4, 5, 5, 6, 7, 8, 8, 9, 10, 11, 12, 13, 14, 15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 8, 9, 10, 1, 2, 3, 1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 10, 10, 1, 2, 3, 4, 5, 6, 7, 1, 2, 3, 4, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 11, 12, 13, 1, 2, 3, 4, 4, 5, 6, 7, 8, 9, 9, 10, 11, 12, 13, 14, 15, 16, 16, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 11, 12, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 1, 2, 3, 4, 5, 6, 7, 8, 
+#> 8, 9, 10, 11, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 1, 2, 3, 4, 5, 6, 6, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 12, 13, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 11, 1, 2, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 
+#> 13, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 8, 9, 10, 11, 12, 13, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 8, 9, 10, 11, 12, 12, 13, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 10, 1, 2, 3, 4, 5, 6, 7, 8, 11, 11, 12, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 1, 2, 3, 4, 5, 5, 6, 6, 7, 8, 9, 9, 10, 11, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 16, 1, 
+#> 2, 3, 4, 5, 6, 7, 7, 8, 9, 10, 10, 11, 12, 12, 13, 14, 15, 16, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 2, 2, 3, 4, 5, 6, 1, 2, 3, 3, 4, 7, 8, 9, 10, 11, 11, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 8, 9, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 1, 2, 3, 4, 5, 6, 7, 8, 8, 9, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 10, 11, 12, 1, 
+#> 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 5, 6, 7, 8, 8, 9, 10, 1, 3, 4, 5, 6, 7, 8, 9, 10, 10, 11, 12, 13, 13, 1, 2, 3, 4, 5, 6, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 10, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 8, 9, 10, 10, 11, 1, 2, 3, 4, 5, 6, 7, 7, 8, 9, 10, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 2, 2, 3, 4, 6, 7, 8, 9, 9, 10, 10, 11, 12, 13, 1, 2, 3, 
+#> 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 7, 8, 9, 10, 11, 1, 2, 1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 1, 2, 3, 4, 5, 6, 6, 7, 8, 9, 10, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 1, 2, 3, 4, 5, 6, 7, 7, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 1, 2, 3, 4, 5, 7, 1, 2, 3, 4, 5, 6, 7, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 
+#> 10, 1, 3, 4, 5, 6, 7, 8, 8, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 1, 2, 4, 5, 6, 7, 8, 8, 9, 10, 11, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10, 1, 1, 1, 1, 2, 3, 4, 5, 5, 6, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 3, 4, 4, 4, 5, 6, 7, 8, 8, 9, 10, 11, 12, 13, 1, 2, 4, 5, 6, 7, 8, 9, 10, 
+#> 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 1, 2, 3, 4, 5, 6, 7, 7, 1, 2, 3, 4, 5, 6, 7, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 1, 2, 3, 4, 5, 6, 7, 1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 1, 2, 3, 4, 5, 6, 6, 7, 7, 1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 2, 3, 4, 5, 
+#> 5, 6, 6, 7, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 7, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 8, 9, 1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 2, 2, 3, 4, 6, 7, 1, 2, 3, 4, 5, 6, 6, 7, 8, 8, 9, 10, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 1, 2, 3, 4, 5, 6, 7, 8, 1, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 15, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 14, 1, 2, 3, 4, 5, 6, 7, 7, 8, 8, 1, 2, 3, 4, 5, 6, 7, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 1, 2, 3, 4, 5, 6, 6, 6, 7, 8, 9, 10, 11, 
+#> 12, 1, 2, 3, 4, 5, 5, 6, 6, 1, 2, 3, 4, 5, 6, 7, 8, 8, 9, 1, 2, 3, 4, 5, 6, 7, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 11, 12, 13, 1, 2, 3, 4, 5, 1, 2, 3, 4, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 11, 1, 2, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 7, 1, 2, 3, 3, 4, 5, 6, 7, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 1, 2, 3, 4, 1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 2, 3, 1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 1, 2, 3, 4, 
+#> 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 4, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 1, 2, 3, 4, 5, 5, 7, 8, 8, 1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 2, 3, 4, 1, 2, 3, 4, 5, 1, 2, 3, 1, 2, 3, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 7, 1, 2, 1, 2, 1, 2, 3, 4, 5, 1, 2, 3, 4, 1, 2, 3, 4, 5, 6, 7, 1, 2, 3, 4, 5, 6, 7, 1, 2, 3, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 4, 1, 2, 3, 4, 4, 5, 6, 1, 2, 3, 1, 
+#> 2, 3, 3, 4, 4, 1, 2, 3, 4, 1, 2, 3, 4, 5, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4, 5, 1, 3, 4, 5, 6, 1, 2, 4, 5, 6, 7, 8, 1, 1, 1, 2, 3, 4, 5, 7, 8, 9, 9, 10, 1, 2, 3, 4, 5, 1, 2, 3)]
+#> Groups: playerID [1,322]
+#> 
+#>   playerID yearID teamID     G    AB     R     H career_year
+#>      <chr>  <int> <fctr> <int> <int> <int> <int>       <dbl>
+#> 1 bondto01   1874    BR2    55   245    25    54           1
+#> 2 bondto01   1875    HR1    72   289    32    77           2
+#> 3 bondto01   1876    HAR    45   182    18    50           3
+#> 4 bondto01   1877    BSN    61   259    32    59           4
+#> # ... with 19,109 more rows
+

Or, as in the introductory example, we could compute a z-score:

+
mutate(players, G_z = (G - mean(G)) / sd(G))
+#> Source: local data frame [c("bondto01", "bondto01", "bondto01", "bondto01", "bondto01", "bondto01", "bondto01", "bondto01", "bondto01", "bondto01", "bondto01", "hinespa01", "hinespa01", "hinespa01", "hinespa01", "hinespa01", "hinespa01", "hinespa01", "hinespa01", "hinespa01", "hinespa01", "hinespa01", "hinespa01", "hinespa01", "hinespa01", "hinespa01", "hinespa01", "hinespa01", "hinespa01", "hinespa01", "hinespa01", "hinespa01", "heckegu01", "heckegu01", "heckegu01", "heckegu01", "heckegu01", "heckegu01", "heckegu01", "heckegu01", 
+#> "heckegu01", "radboch01", "radboch01", "radboch01", "radboch01", "radboch01", "radboch01", "radboch01", "radboch01", "radboch01", "radboch01", "radboch01", "radboch01", "oneilti01", "oneilti01", "oneilti01", "oneilti01", "oneilti01", "oneilti01", "oneilti01", "oneilti01", "oneilti01", "oneilti01", "keefeti01", "keefeti01", "keefeti01", "keefeti01", "keefeti01", "keefeti01", "keefeti01", "keefeti01", "keefeti01", "keefeti01", "keefeti01", "keefeti01", "keefeti01", "keefeti01", "keefeti01", "clarkjo01", 
+#> "clarkjo01", "clarkjo01", "clarkjo01", "clarkjo01", "clarkjo01", "clarkjo01", "clarkjo01", "clarkjo01", "clarkjo01", "clarkjo01", "clarkjo01", "clarkjo01", "rusieam01", "rusieam01", "rusieam01", "rusieam01", "rusieam01", "rusieam01", "rusieam01", "rusieam01", "rusieam01", "rusieam01", "duffyhu01", "duffyhu01", "duffyhu01", "duffyhu01", "duffyhu01", "duffyhu01", "duffyhu01", "duffyhu01", "duffyhu01", "duffyhu01", "duffyhu01", "duffyhu01", "duffyhu01", "duffyhu01", "duffyhu01", "duffyhu01", "duffyhu01", 
+#> "youngcy01", "youngcy01", "youngcy01", "youngcy01", "youngcy01", "youngcy01", "youngcy01", "youngcy01", "youngcy01", "youngcy01", "youngcy01", "youngcy01", "youngcy01", "youngcy01", "youngcy01", "youngcy01", "youngcy01", "youngcy01", "youngcy01", "youngcy01", "youngcy01", "youngcy01", "youngcy01", "lajoina01", "lajoina01", "lajoina01", "lajoina01", "lajoina01", "lajoina01", "lajoina01", "lajoina01", "lajoina01", "lajoina01", "lajoina01", "lajoina01", "lajoina01", "lajoina01", "lajoina01", "lajoina01", 
+#> "lajoina01", "lajoina01", "lajoina01", "lajoina01", "lajoina01", "lajoina01", "wadderu01", "wadderu01", "wadderu01", "wadderu01", "wadderu01", "wadderu01", "wadderu01", "wadderu01", "wadderu01", "wadderu01", "wadderu01", "wadderu01", "wadderu01", "wadderu01", "mathech01", "mathech01", "mathech01", "mathech01", "mathech01", "mathech01", "mathech01", "mathech01", "mathech01", "mathech01", "mathech01", "mathech01", "mathech01", "mathech01", "mathech01", "mathech01", "mathech01", "mathech01", "chaseha01", 
+#> "chaseha01", "chaseha01", "chaseha01", "chaseha01", "chaseha01", "chaseha01", "chaseha01", "chaseha01", "chaseha01", "chaseha01", "chaseha01", "chaseha01", "chaseha01", "chaseha01", "chaseha01", "chaseha01", "lordha01", "lordha01", "lordha01", "lordha01", "lordha01", "lordha01", "lordha01", "lordha01", "lordha01", "lordha01", "crigelo01", "crigelo01", "crigelo01", "crigelo01", "crigelo01", "crigelo01", "crigelo01", "crigelo01", "crigelo01", "crigelo01", "crigelo01", "crigelo01", "crigelo01", "crigelo01", 
+#> "crigelo01", "crigelo01", "sullibi03", "sullibi03", "sullibi03", "sullibi03", "sullibi03", "sullibi03", "sullibi03", "sullibi03", "sullibi03", "sullibi03", "sullibi03", "sullibi03", "sullibi03", "sullibi03", "sullibi03", "sullibi03", "crawfsa01", "crawfsa01", "crawfsa01", "crawfsa01", "crawfsa01", "crawfsa01", "crawfsa01", "crawfsa01", "crawfsa01", "crawfsa01", "crawfsa01", "crawfsa01", "crawfsa01", "crawfsa01", "crawfsa01", "crawfsa01", "crawfsa01", "crawfsa01", "crawfsa01", "stonege01", "stonege01", 
+#> "stonege01", "stonege01", "stonege01", "stonege01", "stonege01", "walshed01", "walshed01", "walshed01", "walshed01", "walshed01", "walshed01", "walshed01", "walshed01", "walshed01", "walshed01", "walshed01", "walshed01", "walshed01", "walshed01", "jossad01", "jossad01", "jossad01", "jossad01", "jossad01", "jossad01", "jossad01", "jossad01", "jossad01", "donovbi01", "donovbi01", "donovbi01", "donovbi01", "donovbi01", "donovbi01", "donovbi01", "donovbi01", "donovbi01", "donovbi01", "donovbi01", "donovbi01", 
+#> "donovbi01", "donovbi01", "donovbi01", "donovbi01", "donovbi01", "donovbi01", "cobbty01", "cobbty01", "cobbty01", "cobbty01", "cobbty01", "cobbty01", "cobbty01", "cobbty01", "cobbty01", "cobbty01", "cobbty01", "cobbty01", "cobbty01", "cobbty01", "cobbty01", "cobbty01", "cobbty01", "cobbty01", "cobbty01", "cobbty01", "cobbty01", "cobbty01", "cobbty01", "cobbty01", "wallabo01", "wallabo01", "wallabo01", "wallabo01", "wallabo01", "wallabo01", "wallabo01", "wallabo01", "wallabo01", "wallabo01", "wallabo01", 
+#> "wallabo01", "wallabo01", "wallabo01", "wallabo01", "wallabo01", "wallabo01", "wallabo01", "wallabo01", "wallabo01", "wallabo01", "wallabo01", "wallabo01", "wallabo01", "wallabo01", "devliar01", "devliar01", "devliar01", "devliar01", "devliar01", "devliar01", "devliar01", "devliar01", "devliar01", "devliar01", "bresnro01", "bresnro01", "bresnro01", "bresnro01", "bresnro01", "bresnro01", "bresnro01", "bresnro01", "bresnro01", "bresnro01", "bresnro01", "bresnro01", "bresnro01", "bresnro01", "bresnro01", 
+#> "bresnro01", "bresnro01", "bresnro01", "klingjo01", "klingjo01", "klingjo01", "klingjo01", "klingjo01", "klingjo01", "klingjo01", "klingjo01", "klingjo01", "klingjo01", "klingjo01", "klingjo01", "klingjo01", "klingjo01", "donlimi01", "donlimi01", "donlimi01", "donlimi01", "donlimi01", "donlimi01", "donlimi01", "donlimi01", "donlimi01", "donlimi01", "donlimi01", "donlimi01", "donlimi01", "donlimi01", "clarkfr01", "clarkfr01", "clarkfr01", "clarkfr01", "clarkfr01", "clarkfr01", "clarkfr01", "clarkfr01", 
+#> "clarkfr01", "clarkfr01", "clarkfr01", "clarkfr01", "clarkfr01", "clarkfr01", "clarkfr01", "clarkfr01", "clarkfr01", "clarkfr01", "clarkfr01", "clarkfr01", "clarkfr01", "brownmo01", "brownmo01", "brownmo01", "brownmo01", "brownmo01", "brownmo01", "brownmo01", "brownmo01", "brownmo01", "brownmo01", "brownmo01", "brownmo01", "brownmo01", "brownmo01", "brownmo01", "ruckena01", "ruckena01", "ruckena01", "ruckena01", "ruckena01", "ruckena01", "ruckena01", "ruckena01", "ruckena01", "ruckena01", "wagneho01", 
+#> "wagneho01", "wagneho01", "wagneho01", "wagneho01", "wagneho01", "wagneho01", "wagneho01", "wagneho01", "wagneho01", "wagneho01", "wagneho01", "wagneho01", "wagneho01", "wagneho01", "wagneho01", "wagneho01", "wagneho01", "wagneho01", "wagneho01", "wagneho01", "tennefr02", "tennefr02", "tennefr02", "tennefr02", "tennefr02", "tennefr02", "tennefr02", "tennefr02", "tennefr02", "tennefr02", "tennefr02", "tennefr02", "tennefr02", "tennefr02", "tennefr02", "tennefr02", "tennefr02", "eversjo01", "eversjo01", 
+#> "eversjo01", "eversjo01", "eversjo01", "eversjo01", "eversjo01", "eversjo01", "eversjo01", "eversjo01", "eversjo01", "eversjo01", "eversjo01", "eversjo01", "eversjo01", "eversjo01", "eversjo01", "eversjo01", "eversjo01", "willivi01", "willivi01", "willivi01", "willivi01", "willivi01", "willivi01", "willivi01", "willivi01", "willivi01", "willivi01", "willivi01", "willivi01", "willivi01", "reulbed01", "reulbed01", "reulbed01", "reulbed01", "reulbed01", "reulbed01", "reulbed01", "reulbed01", "reulbed01", 
+#> "reulbed01", "reulbed01", "reulbed01", "reulbed01", "reulbed01", "schulfr01", "schulfr01", "schulfr01", "schulfr01", "schulfr01", "schulfr01", "schulfr01", "schulfr01", "schulfr01", "schulfr01", "schulfr01", "schulfr01", "schulfr01", "schulfr01", "schulfr01", "schulfr01", "schulfr01", "collied01", "collied01", "collied01", "collied01", "collied01", "collied01", "collied01", "collied01", "collied01", "collied01", "collied01", "collied01", "collied01", "collied01", "collied01", "collied01", "collied01", 
+#> "collied01", "collied01", "collied01", "collied01", "collied01", "collied01", "collied01", "collied01", "carribi02", "carribi02", "carribi02", "carribi02", "carribi02", "carribi02", "carribi02", "carribi02", "carribi02", "carribi02", "streega01", "streega01", "streega01", "streega01", "streega01", "streega01", "streega01", "streega01", "streega01", "streega01", "speaktr01", "speaktr01", "speaktr01", "speaktr01", "speaktr01", "speaktr01", "speaktr01", "speaktr01", "speaktr01", "speaktr01", "speaktr01", 
+#> "speaktr01", "speaktr01", "speaktr01", "speaktr01", "speaktr01", "speaktr01", "speaktr01", "speaktr01", "speaktr01", "speaktr01", "speaktr01", "planked01", "planked01", "planked01", "planked01", "planked01", "planked01", "planked01", "planked01", "planked01", "planked01", "planked01", "planked01", "planked01", "planked01", "planked01", "planked01", "planked01", "johnswa01", "johnswa01", "johnswa01", "johnswa01", "johnswa01", "johnswa01", "johnswa01", "johnswa01", "johnswa01", "johnswa01", "johnswa01", 
+#> "johnswa01", "johnswa01", "johnswa01", "johnswa01", "johnswa01", "johnswa01", "johnswa01", "johnswa01", "johnswa01", "johnswa01", "mullige01", "mullige01", "mullige01", "mullige01", "mullige01", "mullige01", "mullige01", "mullige01", "mullige01", "mullige01", "mullige01", "mullige01", "mullige01", "mullige01", "mullige01", "woodjo02", "woodjo02", "woodjo02", "woodjo02", "woodjo02", "woodjo02", "woodjo02", "woodjo02", "woodjo02", "woodjo02", "woodjo02", "woodjo02", "woodjo02", "woodjo02", "bushdo01", 
+#> "bushdo01", "bushdo01", "bushdo01", "bushdo01", "bushdo01", "bushdo01", "bushdo01", "bushdo01", "bushdo01", "bushdo01", "bushdo01", "bushdo01", "bushdo01", "bushdo01", "bushdo01", "bushdo01", "gibsoge01", "gibsoge01", "gibsoge01", "gibsoge01", "gibsoge01", "gibsoge01", "gibsoge01", "gibsoge01", "gibsoge01", "gibsoge01", "gibsoge01", "gibsoge01", "gibsoge01", "gibsoge01", "adamsba01", "adamsba01", "adamsba01", "adamsba01", "adamsba01", "adamsba01", "adamsba01", "adamsba01", "adamsba01", "adamsba01", 
+#> "adamsba01", "adamsba01", "adamsba01", "adamsba01", "adamsba01", "adamsba01", "adamsba01", "adamsba01", "adamsba01", "chancfr01", "chancfr01", "chancfr01", "chancfr01", "chancfr01", "chancfr01", "chancfr01", "chancfr01", "chancfr01", "chancfr01", "chancfr01", "chancfr01", "chancfr01", "chancfr01", "chancfr01", "chancfr01", "chancfr01", "leachto01", "leachto01", "leachto01", "leachto01", "leachto01", "leachto01", "leachto01", "leachto01", "leachto01", "leachto01", "leachto01", "leachto01", "leachto01", 
+#> "leachto01", "leachto01", "leachto01", "leachto01", "leachto01", "leachto01", "leachto01", "camniho01", "camniho01", "camniho01", "camniho01", "camniho01", "camniho01", "camniho01", "camniho01", "camniho01", "camniho01", "camniho01", "camniho01", "hofmaso01", "hofmaso01", "hofmaso01", "hofmaso01", "hofmaso01", "hofmaso01", "hofmaso01", "hofmaso01", "hofmaso01", "hofmaso01", "hofmaso01", "hofmaso01", "hofmaso01", "hofmaso01", "hofmaso01", "hofmaso01", "thomair01", "thomair01", "thomair01", "thomair01", 
+#> "thomair01", "thomair01", "thomair01", "thomair01", "thomair01", "thomair01", "sweened01", "sweened01", "sweened01", "sweened01", "sweened01", "sweened01", "sweened01", "sweened01", "sweened01", "coombja01", "coombja01", "coombja01", "coombja01", "coombja01", "coombja01", "coombja01", "coombja01", "coombja01", "coombja01", "coombja01", "coombja01", "coombja01", "coombja01", "bendech01", "bendech01", "bendech01", "bendech01", "bendech01", "bendech01", "bendech01", "bendech01", "bendech01", "bendech01", 
+#> "bendech01", "bendech01", "bendech01", "bendech01", "bendech01", "bendech01", "archeji01", "archeji01", "archeji01", "archeji01", "archeji01", "archeji01", "archeji01", "archeji01", "archeji01", "archeji01", "archeji01", "archeji01", "archeji01", "archeji01", "mageesh01", "mageesh01", "mageesh01", "mageesh01", "mageesh01", "mageesh01", "mageesh01", "mageesh01", "mageesh01", "mageesh01", "mageesh01", "mageesh01", "mageesh01", "mageesh01", "mageesh01", "mageesh01", "mageesh01", "coleki01", "coleki01", 
+#> "coleki01", "coleki01", "coleki01", "coleki01", "coleki01", "bakerfr01", "bakerfr01", "bakerfr01", "bakerfr01", "bakerfr01", "bakerfr01", "bakerfr01", "bakerfr01", "bakerfr01", "bakerfr01", "bakerfr01", "bakerfr01", "bakerfr01", "stanaos01", "stanaos01", "stanaos01", "stanaos01", "stanaos01", "stanaos01", "stanaos01", "stanaos01", "stanaos01", "stanaos01", "stanaos01", "stanaos01", "stanaos01", "stanaos01", "greggve01", "greggve01", "greggve01", "greggve01", "greggve01", "greggve01", "greggve01", 
+#> "greggve01", "greggve01", "jacksjo01", "jacksjo01", "jacksjo01", "jacksjo01", "jacksjo01", "jacksjo01", "jacksjo01", "jacksjo01", "jacksjo01", "jacksjo01", "jacksjo01", "jacksjo01", "jacksjo01", "jacksjo01", "dooinre01", "dooinre01", "dooinre01", "dooinre01", "dooinre01", "dooinre01", "dooinre01", "dooinre01", "dooinre01", "dooinre01", "dooinre01", "dooinre01", "dooinre01", "dooinre01", "dooinre01", "dooinre01", "meyerch01", "meyerch01", "meyerch01", "meyerch01", "meyerch01", "meyerch01", "meyerch01", 
+#> "meyerch01", "meyerch01", "meyerch01", "alexape01", "alexape01", "alexape01", "alexape01", "alexape01", "alexape01", "alexape01", "alexape01", "alexape01", "alexape01", "alexape01", "alexape01", "alexape01", "alexape01", "alexape01", "alexape01", "alexape01", "alexape01", "alexape01", "alexape01", "alexape01", "daubeja01", "daubeja01", "daubeja01", "daubeja01", "daubeja01", "daubeja01", "daubeja01", "daubeja01", "daubeja01", "daubeja01", "daubeja01", "daubeja01", "daubeja01", "daubeja01", "daubeja01", 
+#> "doylela01", "doylela01", "doylela01", "doylela01", "doylela01", "doylela01", "doylela01", "doylela01", "doylela01", "doylela01", "doylela01", "doylela01", "doylela01", "doylela01", "doylela01", "loberha01", "loberha01", "loberha01", "loberha01", "loberha01", "loberha01", "loberha01", "loberha01", "loberha01", "loberha01", "loberha01", "loberha01", "loberha01", "loberha01", "marquru01", "marquru01", "marquru01", "marquru01", "marquru01", "marquru01", "marquru01", "marquru01", "marquru01", "marquru01", 
+#> "marquru01", "marquru01", "marquru01", "marquru01", "marquru01", "marquru01", "marquru01", "marquru01", "marquru01", "mcinnst01", "mcinnst01", "mcinnst01", "mcinnst01", "mcinnst01", "mcinnst01", "mcinnst01", "mcinnst01", "mcinnst01", "mcinnst01", "mcinnst01", "mcinnst01", "mcinnst01", "mcinnst01", "mcinnst01", "mcinnst01", "mcinnst01", "mcinnst01", "mcinnst01", "gardnla01", "gardnla01", "gardnla01", "gardnla01", "gardnla01", "gardnla01", "gardnla01", "gardnla01", "gardnla01", "gardnla01", "gardnla01", 
+#> "gardnla01", "gardnla01", "gardnla01", "gardnla01", "gardnla01", "gardnla01", "ainsmed01", "ainsmed01", "ainsmed01", "ainsmed01", "ainsmed01", "ainsmed01", "ainsmed01", "ainsmed01", "ainsmed01", "ainsmed01", "ainsmed01", "ainsmed01", "ainsmed01", "ainsmed01", "ainsmed01", "ainsmed01", "ainsmed01", "wagnehe01", "wagnehe01", "wagnehe01", "wagnehe01", "wagnehe01", "wagnehe01", "wagnehe01", "wagnehe01", "wagnehe01", "wagnehe01", "wagnehe01", "wagnehe01", "zimmehe01", "zimmehe01", "zimmehe01", "zimmehe01", 
+#> "zimmehe01", "zimmehe01", "zimmehe01", "zimmehe01", "zimmehe01", "zimmehe01", "zimmehe01", "zimmehe01", "zimmehe01", "zimmehe01", "paskedo01", "paskedo01", "paskedo01", "paskedo01", "paskedo01", "paskedo01", "paskedo01", "paskedo01", "paskedo01", "paskedo01", "paskedo01", "paskedo01", "paskedo01", "paskedo01", "paskedo01", "wilsoch01", "wilsoch01", "wilsoch01", "wilsoch01", "wilsoch01", "wilsoch01", "wilsoch01", "wilsoch01", "wilsoch01", "tesreje01", "tesreje01", "tesreje01", "tesreje01", "tesreje01", 
+#> "tesreje01", "tesreje01", "schanwa01", "schanwa01", "schanwa01", "schanwa01", "schanwa01", "schanwa01", "schanwa01", "schanwa01", "schanwa01", "schanwa01", "schanwa01", "schanwa01", "schanwa01", "schanwa01", "schanwa01", "schanwa01", "schanwa01", "schanwa01", "schanwa01", "falkecy01", "falkecy01", "falkecy01", "falkecy01", "falkecy01", "falkecy01", "falkecy01", "falkecy01", "falkecy01", "falkecy01", "falkecy01", "falkecy01", "falkecy01", "falkecy01", "barryja01", "barryja01", "barryja01", "barryja01", 
+#> "barryja01", "barryja01", "barryja01", "barryja01", "barryja01", "barryja01", "barryja01", "barryja01", "vioxji01", "vioxji01", "vioxji01", "vioxji01", "vioxji01", "cravaga01", "cravaga01", "cravaga01", "cravaga01", "cravaga01", "cravaga01", "cravaga01", "cravaga01", "cravaga01", "cravaga01", "cravaga01", "cravaga01", "wheatza01", "wheatza01", "wheatza01", "wheatza01", "wheatza01", "wheatza01", "wheatza01", "wheatza01", "wheatza01", "wheatza01", "wheatza01", "wheatza01", "wheatza01", "wheatza01", 
+#> "wheatza01", "wheatza01", "wheatza01", "wheatza01", "wheatza01", "schalra01", "schalra01", "schalra01", "schalra01", "schalra01", "schalra01", "schalra01", "schalra01", "schalra01", "schalra01", "schalra01", "schalra01", "schalra01", "schalra01", "schalra01", "schalra01", "schalra01", "schalra01", "leonadu01", "leonadu01", "leonadu01", "leonadu01", "leonadu01", "leonadu01", "leonadu01", "leonadu01", "leonadu01", "leonadu01", "leonadu01", "maranra01", "maranra01", "maranra01", "maranra01", "maranra01", 
+#> "maranra01", "maranra01", "maranra01", "maranra01", "maranra01", "maranra01", "maranra01", "maranra01", "maranra01", "maranra01", "maranra01", "maranra01", "maranra01", "maranra01", "maranra01", "maranra01", "maranra01", "maranra01", "wingoiv01", "wingoiv01", "wingoiv01", "wingoiv01", "wingoiv01", "wingoiv01", "wingoiv01", "wingoiv01", "wingoiv01", "wingoiv01", "wingoiv01", "wingoiv01", "wingoiv01", "wingoiv01", "wingoiv01", "wingoiv01", "wingoiv01", "burnsge01", "burnsge01", "burnsge01", "burnsge01", 
+#> "burnsge01", "burnsge01", "burnsge01", "burnsge01", "burnsge01", "burnsge01", "burnsge01", "burnsge01", "burnsge01", "burnsge01", "burnsge01", "jamesbi02", "jamesbi02", "jamesbi02", "jamesbi02", "maisefr01", "maisefr01", "maisefr01", "maisefr01", "maisefr01", "maisefr01", "scottji01", "scottji01", "scottji01", "scottji01", "scottji01", "scottji01", "scottji01", "scottji01", "scottji01", "grohhe01", "grohhe01", "grohhe01", "grohhe01", "grohhe01", "grohhe01", "grohhe01", "grohhe01", "grohhe01", "grohhe01", 
+#> "grohhe01", "grohhe01", "grohhe01", "grohhe01", "grohhe01", "grohhe01", "grohhe01", "snydefr01", "snydefr01", "snydefr01", "snydefr01", "snydefr01", "snydefr01", "snydefr01", "snydefr01", "snydefr01", "snydefr01", "snydefr01", "snydefr01", "snydefr01", "snydefr01", "snydefr01", "snydefr01", "snydefr01", "bancrda01", "bancrda01", "bancrda01", "bancrda01", "bancrda01", "bancrda01", "bancrda01", "bancrda01", "bancrda01", "bancrda01", "bancrda01", "bancrda01", "bancrda01", "bancrda01", "bancrda01", "bancrda01", 
+#> "bancrda01", "saiervi01", "saiervi01", "saiervi01", "saiervi01", "saiervi01", "saiervi01", "saiervi01", "saiervi01", "willicy01", "willicy01", "willicy01", "willicy01", "willicy01", "willicy01", "willicy01", "willicy01", "willicy01", "willicy01", "willicy01", "willicy01", "willicy01", "willicy01", "willicy01", "willicy01", "willicy01", "willicy01", "willicy01", "mamaual01", "mamaual01", "mamaual01", "mamaual01", "mamaual01", "mamaual01", "mamaual01", "mamaual01", "mamaual01", "mamaual01", "mamaual01", 
+#> "mamaual01", "sislege01", "sislege01", "sislege01", "sislege01", "sislege01", "sislege01", "sislege01", "sislege01", "sislege01", "sislege01", "sislege01", "sislege01", "sislege01", "sislege01", "sislege01", "sislege01", "ruthba01", "ruthba01", "ruthba01", "ruthba01", "ruthba01", "ruthba01", "ruthba01", "ruthba01", "ruthba01", "ruthba01", "ruthba01", "ruthba01", "ruthba01", "ruthba01", "ruthba01", "ruthba01", "ruthba01", "ruthba01", "ruthba01", "ruthba01", "ruthba01", "ruthba01", "herzobu01", "herzobu01", 
+#> "herzobu01", "herzobu01", "herzobu01", "herzobu01", "herzobu01", "herzobu01", "herzobu01", "herzobu01", "herzobu01", "herzobu01", "herzobu01", "herzobu01", "herzobu01", "herzobu01", "hornsro01", "hornsro01", "hornsro01", "hornsro01", "hornsro01", "hornsro01", "hornsro01", "hornsro01", "hornsro01", "hornsro01", "hornsro01", "hornsro01", "hornsro01", "hornsro01", "hornsro01", "hornsro01", "hornsro01", "hornsro01", "hornsro01", "hornsro01", "hornsro01", "hornsro01", "hornsro01", "hornsro01", "gowdyha01", 
+#> "gowdyha01", "gowdyha01", "gowdyha01", "gowdyha01", "gowdyha01", "gowdyha01", "gowdyha01", "gowdyha01", "gowdyha01", "gowdyha01", "gowdyha01", "gowdyha01", "gowdyha01", "gowdyha01", "gowdyha01", "gowdyha01", "gowdyha01", "gowdyha01", "roberda01", "roberda01", "roberda01", "roberda01", "roberda01", "roberda01", "roberda01", "roberda01", "roberda01", "roberda01", "roberda01", "weavebu01", "weavebu01", "weavebu01", "weavebu01", "weavebu01", "weavebu01", "weavebu01", "weavebu01", "weavebu01", "felscha01", 
+#> "felscha01", "felscha01", "felscha01", "felscha01", "felscha01", "cicoted01", "cicoted01", "cicoted01", "cicoted01", "cicoted01", "cicoted01", "cicoted01", "cicoted01", "cicoted01", "cicoted01", "cicoted01", "cicoted01", "cicoted01", "cicoted01", "cicoted01", "chapmra01", "chapmra01", "chapmra01", "chapmra01", "chapmra01", "chapmra01", "chapmra01", "chapmra01", "chapmra01", "killebi01", "killebi01", "killebi01", "killebi01", "killebi01", "killebi01", "killebi01", "killebi01", "killebi01", "killebi01", 
+#> "killebi01", "killebi01", "killebi01", "roushed01", "roushed01", "roushed01", "roushed01", "roushed01", "roushed01", "roushed01", "roushed01", "roushed01", "roushed01", "roushed01", "roushed01", "roushed01", "roushed01", "roushed01", "roushed01", "roushed01", "roushed01", "roushed01", "careyma01", "careyma01", "careyma01", "careyma01", "careyma01", "careyma01", "careyma01", "careyma01", "careyma01", "careyma01", "careyma01", "careyma01", "careyma01", "careyma01", "careyma01", "careyma01", "careyma01", 
+#> "careyma01", "careyma01", "careyma01", "careyma01", "coopewi01", "coopewi01", "coopewi01", "coopewi01", "coopewi01", "coopewi01", "coopewi01", "coopewi01", "coopewi01", "coopewi01", "coopewi01", "coopewi01", "coopewi01", "coopewi01", "coopewi01", "coopewi01", "oneilst01", "oneilst01", "oneilst01", "oneilst01", "oneilst01", "oneilst01", "oneilst01", "oneilst01", "oneilst01", "oneilst01", "oneilst01", "oneilst01", "oneilst01", "oneilst01", "oneilst01", "oneilst01", "oneilst01", "hoopeha01", "hoopeha01", 
+#> "hoopeha01", "hoopeha01", "hoopeha01", "hoopeha01", "hoopeha01", "hoopeha01", "hoopeha01", "hoopeha01", "hoopeha01", "hoopeha01", "hoopeha01", "hoopeha01", "hoopeha01", "hoopeha01", "hoopeha01", "vaughhi01", "vaughhi01", "vaughhi01", "vaughhi01", "vaughhi01", "vaughhi01", "vaughhi01", "vaughhi01", "vaughhi01", "vaughhi01", "vaughhi01", "vaughhi01", "vaughhi01", "vaughhi01", "holloch01", "holloch01", "holloch01", "holloch01", "holloch01", "holloch01", "holloch01", "cutshge01", "cutshge01", "cutshge01", 
+#> "cutshge01", "cutshge01", "cutshge01", "cutshge01", "cutshge01", "cutshge01", "cutshge01", "cutshge01", "cutshge01", "grimebu01", "grimebu01", "grimebu01", "grimebu01", "grimebu01", "grimebu01", "grimebu01", "grimebu01", "grimebu01", "grimebu01", "grimebu01", "grimebu01", "grimebu01", "grimebu01", "grimebu01", "grimebu01", "grimebu01", "grimebu01", "grimebu01", "grimebu01", "grimebu01", "grimebu01", "grimebu01", "peckiro01", "peckiro01", "peckiro01", "peckiro01", "peckiro01", "peckiro01", "peckiro01", 
+#> "peckiro01", "peckiro01", "peckiro01", "peckiro01", "peckiro01", "peckiro01", "peckiro01", "peckiro01", "peckiro01", "peckiro01", "peckiro01", "stockmi01", "stockmi01", "stockmi01", "stockmi01", "stockmi01", "stockmi01", "stockmi01", "stockmi01", "stockmi01", "stockmi01", "stockmi01", "stockmi01", "stockmi01", "stockmi01", "myershy01", "myershy01", "myershy01", "myershy01", "myershy01", "myershy01", "myershy01", "myershy01", "myershy01", "myershy01", "myershy01", "myershy01", "myershy01", "myershy01", 
+#> "myershy01", "myershy01", "barneje01", "barneje01", "barneje01", "barneje01", "barneje01", "barneje01", "barneje01", "barneje01", "barneje01", "barneje01", "barneje01", "barneje01", "barneje01", "barneje01", "ricesa01", "ricesa01", "ricesa01", "ricesa01", "ricesa01", "ricesa01", "ricesa01", "ricesa01", "ricesa01", "ricesa01", "ricesa01", "ricesa01", "ricesa01", "ricesa01", "ricesa01", "ricesa01", "ricesa01", "ricesa01", "ricesa01", "ricesa01", "bagbyji01", "bagbyji01", "bagbyji01", "bagbyji01", "bagbyji01", 
+#> "bagbyji01", "bagbyji01", "bagbyji01", "bagbyji01", "covelst01", "covelst01", "covelst01", "covelst01", "covelst01", "covelst01", "covelst01", "covelst01", "covelst01", "covelst01", "covelst01", "covelst01", "covelst01", "covelst01", "shockur01", "shockur01", "shockur01", "shockur01", "shockur01", "shockur01", "shockur01", "shockur01", "shockur01", "shockur01", "shockur01", "shockur01", "shockur01", "scottev01", "scottev01", "scottev01", "scottev01", "scottev01", "scottev01", "scottev01", "scottev01", 
+#> "scottev01", "scottev01", "scottev01", "scottev01", "scottev01", "scottev01", "scottev01", "schmiwa01", "schmiwa01", "schmiwa01", "schmiwa01", "schmiwa01", "schmiwa01", "schmiwa01", "schmiwa01", "schmiwa01", "schmiwa01", "youngro01", "youngro01", "youngro01", "youngro01", "youngro01", "youngro01", "youngro01", "youngro01", "youngro01", "youngro01", "faberre01", "faberre01", "faberre01", "faberre01", "faberre01", "faberre01", "faberre01", "faberre01", "faberre01", "faberre01", "faberre01", "faberre01", 
+#> "faberre01", "faberre01", "faberre01", "faberre01", "faberre01", "faberre01", "faberre01", "faberre01", "maysca01", "maysca01", "maysca01", "maysca01", "maysca01", "maysca01", "maysca01", "maysca01", "maysca01", "maysca01", "maysca01", "maysca01", "maysca01", "maysca01", "maysca01", "maysca01", "friscfr01", "friscfr01", "friscfr01", "friscfr01", "friscfr01", "friscfr01", "friscfr01", "friscfr01", "friscfr01", "friscfr01", "friscfr01", "friscfr01", "friscfr01", "friscfr01", "friscfr01", "friscfr01", 
+#> "friscfr01", "friscfr01", "friscfr01", "kellyge01", "kellyge01", "kellyge01", "kellyge01", "kellyge01", "kellyge01", "kellyge01", "kellyge01", "kellyge01", "kellyge01", "kellyge01", "kellyge01", "kellyge01", "kellyge01", "kellyge01", "kellyge01", "kellyge01", "kellyge01", "bigbeca01", "bigbeca01", "bigbeca01", "bigbeca01", "bigbeca01", "bigbeca01", "bigbeca01", "bigbeca01", "bigbeca01", "bigbeca01", "bigbeca01", "nehfar01", "nehfar01", "nehfar01", "nehfar01", "nehfar01", "nehfar01", "nehfar01", "nehfar01", 
+#> "nehfar01", "nehfar01", "nehfar01", "nehfar01", "nehfar01", "nehfar01", "nehfar01", "nehfar01", "nehfar01", "nehfar01", "duganjo01", "duganjo01", "duganjo01", "duganjo01", "duganjo01", "duganjo01", "duganjo01", "duganjo01", "duganjo01", "duganjo01", "duganjo01", "duganjo01", "duganjo01", "duganjo01", "duganjo01", "bushjo01", "bushjo01", "bushjo01", "bushjo01", "bushjo01", "bushjo01", "bushjo01", "bushjo01", "bushjo01", "bushjo01", "bushjo01", "bushjo01", "bushjo01", "bushjo01", "bushjo01", "bushjo01", 
+#> "bushjo01", "bushjo01", "bushjo01", "rommeed01", "rommeed01", "rommeed01", "rommeed01", "rommeed01", "rommeed01", "rommeed01", "rommeed01", "rommeed01", "rommeed01", "rommeed01", "rommeed01", "rommeed01", "rixeyep01", "rixeyep01", "rixeyep01", "rixeyep01", "rixeyep01", "rixeyep01", "rixeyep01", "rixeyep01", "rixeyep01", "rixeyep01", "rixeyep01", "rixeyep01", "rixeyep01", "rixeyep01", "rixeyep01", "rixeyep01", "rixeyep01", "rixeyep01", "rixeyep01", "rixeyep01", "rixeyep01", "ruethdu01", "ruethdu01", 
+#> "ruethdu01", "ruethdu01", "ruethdu01", "ruethdu01", "ruethdu01", "ruethdu01", "ruethdu01", "ruethdu01", "ruethdu01", "ruethdu01", "ruethdu01", "pippwa01", "pippwa01", "pippwa01", "pippwa01", "pippwa01", "pippwa01", "pippwa01", "pippwa01", "pippwa01", "pippwa01", "pippwa01", "pippwa01", "pippwa01", "pippwa01", "pippwa01", "perkicy01", "perkicy01", "perkicy01", "perkicy01", "perkicy01", "perkicy01", "perkicy01", "perkicy01", "perkicy01", "perkicy01", "perkicy01", "perkicy01", "perkicy01", "perkicy01", 
+#> "perkicy01", "perkicy01", "perkicy01", "heilmha01", "heilmha01", "heilmha01", "heilmha01", "heilmha01", "heilmha01", "heilmha01", "heilmha01", "heilmha01", "heilmha01", "heilmha01", "heilmha01", "heilmha01", "heilmha01", "heilmha01", "heilmha01", "heilmha01", "uhlege01", "uhlege01", "uhlege01", "uhlege01", "uhlege01", "uhlege01", "uhlege01", "uhlege01", "uhlege01", "uhlege01", "uhlege01", "uhlege01", "uhlege01", "uhlege01", "uhlege01", "uhlege01", "uhlege01", "uhlege01", "uhlege01", "ehmkeho01", 
+#> "ehmkeho01", "ehmkeho01", "ehmkeho01", "ehmkeho01", "ehmkeho01", "ehmkeho01", "ehmkeho01", "ehmkeho01", "ehmkeho01", "ehmkeho01", "ehmkeho01", "ehmkeho01", "ehmkeho01", "ehmkeho01", "ehmkeho01", "seweljo01", "seweljo01", "seweljo01", "seweljo01", "seweljo01", "seweljo01", "seweljo01", "seweljo01", "seweljo01", "seweljo01", "seweljo01", "seweljo01", "seweljo01", "seweljo01", "grimmch01", "grimmch01", "grimmch01", "grimmch01", "grimmch01", "grimmch01", "grimmch01", "grimmch01", "grimmch01", "grimmch01", 
+#> "grimmch01", "grimmch01", "grimmch01", "grimmch01", "grimmch01", "grimmch01", "grimmch01", "grimmch01", "grimmch01", "grimmch01", "ofarrbo01", "ofarrbo01", "ofarrbo01", "ofarrbo01", "ofarrbo01", "ofarrbo01", "ofarrbo01", "ofarrbo01", "ofarrbo01", "ofarrbo01", "ofarrbo01", "ofarrbo01", "ofarrbo01", "ofarrbo01", "ofarrbo01", "ofarrbo01", "ofarrbo01", "ofarrbo01", "ofarrbo01", "ofarrbo01", "ofarrbo01", "ofarrbo01", "ofarrbo01", "ofarrbo01", "luquedo01", "luquedo01", "luquedo01", "luquedo01", "luquedo01", 
+#> "luquedo01", "luquedo01", "luquedo01", "luquedo01", "luquedo01", "luquedo01", "luquedo01", "luquedo01", "luquedo01", "luquedo01", "luquedo01", "luquedo01", "luquedo01", "luquedo01", "luquedo01", "morrijo04", "morrijo04", "morrijo04", "morrijo04", "morrijo04", "morrijo04", "morrijo04", "morrijo04", "morrijo04", "morrijo04", "vanceda01", "vanceda01", "vanceda01", "vanceda01", "vanceda01", "vanceda01", "vanceda01", "vanceda01", "vanceda01", "vanceda01", "vanceda01", "vanceda01", "vanceda01", "vanceda01", 
+#> "vanceda01", "vanceda01", "vanceda01", "vanceda01", "judgejo01", "judgejo01", "judgejo01", "judgejo01", "judgejo01", "judgejo01", "judgejo01", "judgejo01", "judgejo01", "judgejo01", "judgejo01", "judgejo01", "judgejo01", "judgejo01", "judgejo01", "judgejo01", "judgejo01", "judgejo01", "judgejo01", "judgejo01", "judgejo01", "bassljo01", "bassljo01", "bassljo01", "bassljo01", "bassljo01", "bassljo01", "bassljo01", "bassljo01", "bassljo01", "jamiech01", "jamiech01", "jamiech01", "jamiech01", "jamiech01", 
+#> "jamiech01", "jamiech01", "jamiech01", "jamiech01", "jamiech01", "jamiech01", "jamiech01", "jamiech01", "jamiech01", "jamiech01", "jamiech01", "jamiech01", "jamiech01", "jamiech01", "thurssl01", "thurssl01", "thurssl01", "thurssl01", "thurssl01", "thurssl01", "thurssl01", "thurssl01", "thurssl01", "thurssl01", "pennohe01", "pennohe01", "pennohe01", "pennohe01", "pennohe01", "pennohe01", "pennohe01", "pennohe01", "pennohe01", "pennohe01", "pennohe01", "pennohe01", "pennohe01", "pennohe01", "pennohe01", 
+#> "pennohe01", "pennohe01", "pennohe01", "pennohe01", "pennohe01", "pennohe01", "pennohe01", "pennohe01", "jackstr01", "jackstr01", "jackstr01", "jackstr01", "jackstr01", "jackstr01", "jackstr01", "jackstr01", "jackstr01", "jackstr01", "jackstr01", "jackstr01", "jackstr01", "jackstr01", "jackstr01", "traynpi01", "traynpi01", "traynpi01", "traynpi01", "traynpi01", "traynpi01", "traynpi01", "traynpi01", "traynpi01", "traynpi01", "traynpi01", "traynpi01", "traynpi01", "traynpi01", "traynpi01", "traynpi01", 
+#> "traynpi01", "hartnga01", "hartnga01", "hartnga01", "hartnga01", "hartnga01", "hartnga01", "hartnga01", "hartnga01", "hartnga01", "hartnga01", "hartnga01", "hartnga01", "hartnga01", "hartnga01", "hartnga01", "hartnga01", "hartnga01", "hartnga01", "hartnga01", "hartnga01", "bluegos01", "bluegos01", "bluegos01", "bluegos01", "bluegos01", "bluegos01", "bluegos01", "bluegos01", "bluegos01", "bluegos01", "bluegos01", "bluegos01", "bluegos01", "bluegos01", "bluegos01", "bluegos01", "bluegos01", "bluegos01", 
+#> "ruelmu01", "ruelmu01", "ruelmu01", "ruelmu01", "ruelmu01", "ruelmu01", "ruelmu01", "ruelmu01", "ruelmu01", "ruelmu01", "ruelmu01", "ruelmu01", "ruelmu01", "ruelmu01", "ruelmu01", "ruelmu01", "ruelmu01", "ruelmu01", "ruelmu01", "ruelmu01", "cochrmi01", "cochrmi01", "cochrmi01", "cochrmi01", "cochrmi01", "cochrmi01", "cochrmi01", "cochrmi01", "cochrmi01", "cochrmi01", "cochrmi01", "cochrmi01", "cochrmi01", "simmoal01", "simmoal01", "simmoal01", "simmoal01", "simmoal01", "simmoal01", "simmoal01", "simmoal01", 
+#> "simmoal01", "simmoal01", "simmoal01", "simmoal01", "simmoal01", "simmoal01", "simmoal01", "simmoal01", "simmoal01", "simmoal01", "simmoal01", "simmoal01", "simmoal01", "gosligo01", "gosligo01", "gosligo01", "gosligo01", "gosligo01", "gosligo01", "gosligo01", "gosligo01", "gosligo01", "gosligo01", "gosligo01", "gosligo01", "gosligo01", "gosligo01", "gosligo01", "gosligo01", "gosligo01", "gosligo01", "gosligo01", "lyonste01", "lyonste01", "lyonste01", "lyonste01", "lyonste01", "lyonste01", "lyonste01", 
+#> "lyonste01", "lyonste01", "lyonste01", "lyonste01", "lyonste01", "lyonste01", "lyonste01", "lyonste01", "lyonste01", "lyonste01", "lyonste01", "lyonste01", "lyonste01", "lyonste01", "cuyleki01", "cuyleki01", "cuyleki01", "cuyleki01", "cuyleki01", "cuyleki01", "cuyleki01", "cuyleki01", "cuyleki01", "cuyleki01", "cuyleki01", "cuyleki01", "cuyleki01", "cuyleki01", "cuyleki01", "cuyleki01", "cuyleki01", "cuyleki01", "cuyleki01", "wrighgl01", "wrighgl01", "wrighgl01", "wrighgl01", "wrighgl01", "wrighgl01", 
+#> "wrighgl01", "wrighgl01", "wrighgl01", "wrighgl01", "wrighgl01", "bottoji01", "bottoji01", "bottoji01", "bottoji01", "bottoji01", "bottoji01", "bottoji01", "bottoji01", "bottoji01", "bottoji01", "bottoji01", "bottoji01", "bottoji01", "bottoji01", "bottoji01", "bottoji01", "smithea02", "smithea02", "smithea02", "smithea02", "smithea02", "smithea02", "smithea02", "smithea02", "smithea02", "smithea02", "smithea02", "smithea02", "smithea02", "smithea02", "smithea02", "donohpe01", "donohpe01", "donohpe01", 
+#> "donohpe01", "donohpe01", "donohpe01", "donohpe01", "donohpe01", "donohpe01", "donohpe01", "donohpe01", "donohpe01", "donohpe01", "donohpe01", "burnsge02", "burnsge02", "burnsge02", "burnsge02", "burnsge02", "burnsge02", "burnsge02", "burnsge02", "burnsge02", "burnsge02", "burnsge02", "burnsge02", "burnsge02", "burnsge02", "burnsge02", "burnsge02", "burnsge02", "burnsge02", "burnsge02", "kammwi01", "kammwi01", "kammwi01", "kammwi01", "kammwi01", "kammwi01", "kammwi01", "kammwi01", "kammwi01", "kammwi01", 
+#> "kammwi01", "kammwi01", "kammwi01", "kammwi01", "manushe01", "manushe01", "manushe01", "manushe01", "manushe01", "manushe01", "manushe01", "manushe01", "manushe01", "manushe01", "manushe01", "manushe01", "manushe01", "manushe01", "manushe01", "manushe01", "manushe01", "manushe01", "manushe01", "mostijo01", "mostijo01", "mostijo01", "mostijo01", "mostijo01", "mostijo01", "mostijo01", "mostijo01", "mostijo01", "mostijo01", "grovele01", "grovele01", "grovele01", "grovele01", "grovele01", "grovele01", 
+#> "grovele01", "grovele01", "grovele01", "grovele01", "grovele01", "grovele01", "grovele01", "grovele01", "grovele01", "grovele01", "grovele01", "kremera01", "kremera01", "kremera01", "kremera01", "kremera01", "kremera01", "kremera01", "kremera01", "kremera01", "kremera01", "wilsoha01", "wilsoha01", "wilsoha01", "wilsoha01", "wilsoha01", "wilsoha01", "wilsoha01", "wilsoha01", "wilsoha01", "wilsoha01", "wilsoha01", "wilsoha01", "wilsoha01", "carlsha01", "carlsha01", "carlsha01", "carlsha01", "carlsha01", 
+#> "carlsha01", "carlsha01", "carlsha01", "carlsha01", "carlsha01", "carlsha01", "carlsha01", "carlsha01", "carlsha01", "carlsha01", "pettyje01", "pettyje01", "pettyje01", "pettyje01", "pettyje01", "pettyje01", "pettyje01", "pettyje01", "gehrilo01", "gehrilo01", "gehrilo01", "gehrilo01", "gehrilo01", "gehrilo01", "gehrilo01", "gehrilo01", "gehrilo01", "gehrilo01", "gehrilo01", "gehrilo01", "gehrilo01", "gehrilo01", "gehrilo01", "gehrilo01", "gehrilo01", "lazzeto01", "lazzeto01", "lazzeto01", "lazzeto01", 
+#> "lazzeto01", "lazzeto01", "lazzeto01", "lazzeto01", "lazzeto01", "lazzeto01", "lazzeto01", "lazzeto01", "lazzeto01", "lazzeto01", "lazzeto01", "hoytwa01", "hoytwa01", "hoytwa01", "hoytwa01", "hoytwa01", "hoytwa01", "hoytwa01", "hoytwa01", "hoytwa01", "hoytwa01", "hoytwa01", "hoytwa01", "hoytwa01", "hoytwa01", "hoytwa01", "hoytwa01", "hoytwa01", "hoytwa01", "hoytwa01", "hoytwa01", "hoytwa01", "hoytwa01", "hoytwa01", "hoytwa01", "hoytwa01", "thomato02", "thomato02", "thomato02", "thomato02", "thomato02", 
+#> "thomato02", "thomato02", "thomato02", "thomato02", "thomato02", "thomato02", "thomato02", "thomato02", "thomato02", "thomato02", "rootch01", "rootch01", "rootch01", "rootch01", "rootch01", "rootch01", "rootch01", "rootch01", "rootch01", "rootch01", "rootch01", "rootch01", "rootch01", "rootch01", "rootch01", "rootch01", "rootch01", "haineje01", "haineje01", "haineje01", "haineje01", "haineje01", "haineje01", "haineje01", "haineje01", "haineje01", "haineje01", "haineje01", "haineje01", "haineje01", 
+#> "haineje01", "haineje01", "haineje01", "haineje01", "haineje01", "haineje01", "wanerpa01", "wanerpa01", "wanerpa01", "wanerpa01", "wanerpa01", "wanerpa01", "wanerpa01", "wanerpa01", "wanerpa01", "wanerpa01", "wanerpa01", "wanerpa01", "wanerpa01", "wanerpa01", "wanerpa01", "wanerpa01", "wanerpa01", "wanerpa01", "wanerpa01", "wanerpa01", "wanerpa01", "wanerpa01", "terrybi01", "terrybi01", "terrybi01", "terrybi01", "terrybi01", "terrybi01", "terrybi01", "terrybi01", "terrybi01", "terrybi01", "terrybi01", 
+#> "terrybi01", "terrybi01", "terrybi01", "wilsoji01", "wilsoji01", "wilsoji01", "wilsoji01", "wilsoji01", "wilsoji01", "wilsoji01", "wilsoji01", "wilsoji01", "wilsoji01", "wilsoji01", "wilsoji01", "wilsoji01", "wilsoji01", "wilsoji01", "wilsoji01", "wilsoji01", "wilsoji01", "wilsoji01", "wanerll01", "wanerll01", "wanerll01", "wanerll01", "wanerll01", "wanerll01", "wanerll01", "wanerll01", "wanerll01", "wanerll01", "wanerll01", "wanerll01", "wanerll01", "wanerll01", "wanerll01", "wanerll01", "wanerll01", 
+#> "wanerll01", "wanerll01", "wanerll01", "wanerll01", "crowdal01", "crowdal01", "crowdal01", "crowdal01", "crowdal01", "crowdal01", "crowdal01", "crowdal01", "crowdal01", "crowdal01", "crowdal01", "crowdal01", "crowdal01", "crowdal01", "morried02", "morried02", "morried02", "morried02", "morried02", "bentola01", "bentola01", "bentola01", "bentola01", "bentola01", "bentola01", "bentola01", "bentola01", "bentola01", "bentola01", "bentola01", "bentola01", "bentola01", "bentola01", "bentola01", "hafeych01", 
+#> "hafeych01", "hafeych01", "hafeych01", "hafeych01", "hafeych01", "hafeych01", "hafeych01", "hafeych01", "hafeych01", "hafeych01", "hafeych01", "hafeych01", "sherdbi01", "sherdbi01", "sherdbi01", "sherdbi01", "sherdbi01", "sherdbi01", "sherdbi01", "sherdbi01", "sherdbi01", "sherdbi01", "sherdbi01", "sherdbi01", "sherdbi01", "sherdbi01", "sherdbi01", "sherdbi01", "sherdbi01", "lindsfr01", "lindsfr01", "lindsfr01", "lindsfr01", "lindsfr01", "lindsfr01", "lindsfr01", "lindsfr01", "lindsfr01", "lindsfr01", 
+#> "lindsfr01", "lindsfr01", "lindsfr01", "fonsele01", "fonsele01", "fonsele01", "fonsele01", "fonsele01", "fonsele01", "fonsele01", "fonsele01", "fonsele01", "fonsele01", "fonsele01", "fonsele01", "fonsele01", "gehrich01", "gehrich01", "gehrich01", "gehrich01", "gehrich01", "gehrich01", "gehrich01", "gehrich01", "gehrich01", "gehrich01", "gehrich01", "gehrich01", "gehrich01", "gehrich01", "gehrich01", "gehrich01", "gehrich01", "gehrich01", "gehrich01", "dykesji01", "dykesji01", "dykesji01", "dykesji01", 
+#> "dykesji01", "dykesji01", "dykesji01", "dykesji01", "dykesji01", "dykesji01", "dykesji01", "dykesji01", "dykesji01", "dykesji01", "dykesji01", "dykesji01", "dykesji01", "dykesji01", "dykesji01", "dykesji01", "dykesji01", "dykesji01", "combsea01", "combsea01", "combsea01", "combsea01", "combsea01", "combsea01", "combsea01", "combsea01", "combsea01", "combsea01", "combsea01", "combsea01", "earnsge01", "earnsge01", "earnsge01", "earnsge01", "earnsge01", "earnsge01", "earnsge01", "earnsge01", "earnsge01", 
+#> "earnsge01", "earnsge01", "graydo02", "graydo02", "graydo02", "graydo02", "graydo02", "graydo02", "graydo02", "graydo02", "graydo02", "graydo02", "ferrewe01", "ferrewe01", "ferrewe01", "ferrewe01", "ferrewe01", "ferrewe01", "ferrewe01", "ferrewe01", "ferrewe01", "ferrewe01", "ferrewe01", "ferrewe01", "ferrewe01", "ferrewe01", "ferrewe01", "ferrewe01", "ferrewe01", "kressre01", "kressre01", "kressre01", "kressre01", "kressre01", "kressre01", "kressre01", "kressre01", "kressre01", "kressre01", "kressre01", 
+#> "kressre01", "kressre01", "kressre01", "kressre01", "kressre01", "kressre01", "malonpa02", "malonpa02", "malonpa02", "malonpa02", "malonpa02", "malonpa02", "malonpa02", "malonpa02", "malonpa02", "malonpa02", "lucasre01", "lucasre01", "lucasre01", "lucasre01", "lucasre01", "lucasre01", "lucasre01", "lucasre01", "lucasre01", "lucasre01", "lucasre01", "lucasre01", "lucasre01", "lucasre01", "lucasre01", "lucasre01", "hubbeca01", "hubbeca01", "hubbeca01", "hubbeca01", "hubbeca01", "hubbeca01", "hubbeca01", 
+#> "hubbeca01", "hubbeca01", "hubbeca01", "hubbeca01", "hubbeca01", "hubbeca01", "hubbeca01", "hubbeca01", "hubbeca01", "odoulle01", "odoulle01", "odoulle01", "odoulle01", "odoulle01", "odoulle01", "odoulle01", "odoulle01", "odoulle01", "odoulle01", "odoulle01", "odoulle01", "foxxji01", "foxxji01", "foxxji01", "foxxji01", "foxxji01", "foxxji01", "foxxji01", "foxxji01", "foxxji01", "foxxji01", "foxxji01", "foxxji01", "foxxji01", "foxxji01", "foxxji01", "foxxji01", "foxxji01", "foxxji01", "foxxji01", 
+#> "foxxji01", "foxxji01", "averiea01", "averiea01", "averiea01", "averiea01", "averiea01", "averiea01", "averiea01", "averiea01", "averiea01", "averiea01", "averiea01", "averiea01", "averiea01", "averiea01", "cronijo01", "cronijo01", "cronijo01", "cronijo01", "cronijo01", "cronijo01", "cronijo01", "cronijo01", "cronijo01", "cronijo01", "cronijo01", "cronijo01", "cronijo01", "cronijo01", "cronijo01", "cronijo01", "cronijo01", "cronijo01", "cronijo01", "cronijo01", "hallabi01", "hallabi01", "hallabi01", 
+#> "hallabi01", "hallabi01", "hallabi01", "hallabi01", "hallabi01", "hallabi01", "hallabi01", "hallabi01", "hallabi01", "hallabi01", "melilsk01", "melilsk01", "melilsk01", "melilsk01", "melilsk01", "melilsk01", "melilsk01", "melilsk01", "melilsk01", "melilsk01", "melilsk01", "melilsk01", "melilsk01", "walberu01", "walberu01", "walberu01", "walberu01", "walberu01", "walberu01", "walberu01", "walberu01", "walberu01", "walberu01", "walberu01", "walberu01", "walberu01", "walberu01", "walberu01", "walberu01", 
+#> "branded01", "branded01", "branded01", "branded01", "branded01", "branded01", "branded01", "branded01", "branded01", "branded01", "branded01", "derripa01", "derripa01", "derripa01", "derripa01", "derripa01", "derripa01", "derripa01", "derripa01", "derripa01", "derripa01", "derripa01", "derripa01", "derripa01", "derripa01", "derripa01", "derripa01", "fitzsfr01", "fitzsfr01", "fitzsfr01", "fitzsfr01", "fitzsfr01", "fitzsfr01", "fitzsfr01", "fitzsfr01", "fitzsfr01", "fitzsfr01", "fitzsfr01", "fitzsfr01", 
+#> "fitzsfr01", "fitzsfr01", "fitzsfr01", "fitzsfr01", "fitzsfr01", "fitzsfr01", "fitzsfr01", "fitzsfr01", "kleinch01", "kleinch01", "kleinch01", "kleinch01", "kleinch01", "kleinch01", "kleinch01", "kleinch01", "kleinch01", "kleinch01", "kleinch01", "kleinch01", "kleinch01", "kleinch01", "kleinch01", "kleinch01", "kleinch01", "kleinch01", "kleinch01", "gomezle01", "gomezle01", "gomezle01", "gomezle01", "gomezle01", "gomezle01", "gomezle01", "gomezle01", "gomezle01", "gomezle01", "gomezle01", "gomezle01", 
+#> "gomezle01", "gomezle01", "warnelo01", "warnelo01", "warnelo01", "warnelo01", "warnelo01", "warnelo01", "warnelo01", "warnelo01", "warnelo01", "warnelo01", "warnelo01", "warnelo01", "warnelo01", "warnelo01", "warnelo01", "warnelo01", "hermabi01", "hermabi01", "hermabi01", "hermabi01", "hermabi01", "hermabi01", "hermabi01", "hermabi01", "hermabi01", "hermabi01", "hermabi01", "hermabi01", "hermabi01", "hermabi01", "hermabi01", "hermabi01", "hermabi01", "clarkwa02", "clarkwa02", "clarkwa02", "clarkwa02", 
+#> "clarkwa02", "clarkwa02", "clarkwa02", "clarkwa02", "clarkwa02", "clarkwa02", "clarkwa02", "clarkwa02", "clarkwa02", "clarkwa02", "deandi01", "deandi01", "deandi01", "deandi01", "deandi01", "deandi01", "deandi01", "deandi01", "deandi01", "deandi01", "deandi01", "deandi01", "bartedi01", "bartedi01", "bartedi01", "bartedi01", "bartedi01", "bartedi01", "bartedi01", "bartedi01", "bartedi01", "bartedi01", "bartedi01", "bartedi01", "bartedi01", "bartedi01", "bartedi01", "bartedi01", "bartedi01", "bartedi01", 
+#> "bartedi01", "dickebi01", "dickebi01", "dickebi01", "dickebi01", "dickebi01", "dickebi01", "dickebi01", "dickebi01", "dickebi01", "dickebi01", "dickebi01", "dickebi01", "dickebi01", "dickebi01", "dickebi01", "dickebi01", "dickebi01", "higgipi01", "higgipi01", "higgipi01", "higgipi01", "higgipi01", "higgipi01", "higgipi01", "higgipi01", "higgipi01", "higgipi01", "higgipi01", "higgipi01", "higgipi01", "higgipi01", "higgipi01", "westsa01", "westsa01", "westsa01", "westsa01", "westsa01", "westsa01", 
+#> "westsa01", "westsa01", "westsa01", "westsa01", "westsa01", "westsa01", "westsa01", "westsa01", "westsa01", "westsa01", "westsa01", "whiteea01", "whiteea01", "whiteea01", "whiteea01", "whiteea01", "whiteea01", "whiteea01", "whiteea01", "whiteea01", "whiteea01", "whiteea01", "whiteea01", "whiteea01", "whiteea01", "whiteea01", "whiteea01", "whiteea01", "bridgto01", "bridgto01", "bridgto01", "bridgto01", "bridgto01", "bridgto01", "bridgto01", "bridgto01", "bridgto01", "bridgto01", "bridgto01", "bridgto01", 
+#> "bridgto01", "bridgto01", "bridgto01", "bridgto01", "bergewa01", "bergewa01", "bergewa01", "bergewa01", "bergewa01", "bergewa01", "bergewa01", "bergewa01", "bergewa01", "bergewa01", "bergewa01", "bergewa01", "bergewa01", "bergewa01", "lopezal01", "lopezal01", "lopezal01", "lopezal01", "lopezal01", "lopezal01", "lopezal01", "lopezal01", "lopezal01", "lopezal01", "lopezal01", "lopezal01", "lopezal01", "lopezal01", "lopezal01", "lopezal01", "lopezal01", "lopezal01", "lopezal01", "lopezal01", "medwijo01", 
+#> "medwijo01", "medwijo01", "medwijo01", "medwijo01", "medwijo01", "medwijo01", "medwijo01", "medwijo01", "medwijo01", "medwijo01", "medwijo01", "medwijo01", "medwijo01", "medwijo01", "medwijo01", "medwijo01", "medwijo01", "medwijo01", "medwijo01", "cantwbe01", "cantwbe01", "cantwbe01", "cantwbe01", "cantwbe01", "cantwbe01", "cantwbe01", "cantwbe01", "cantwbe01", "cantwbe01", "cantwbe01", "cantwbe01", "cantwbe01", "vaughar01", "vaughar01", "vaughar01", "vaughar01", "vaughar01", "vaughar01", "vaughar01", 
+#> "vaughar01", "vaughar01", "vaughar01", "vaughar01", "vaughar01", "vaughar01", "vaughar01", "werbebi01", "werbebi01", "werbebi01", "werbebi01", "werbebi01", "werbebi01", "werbebi01", "werbebi01", "werbebi01", "werbebi01", "werbebi01", "werbebi01", "rowesc01", "rowesc01", "rowesc01", "rowesc01", "rowesc01", "rowesc01", "rowesc01", "rowesc01", "rowesc01", "rowesc01", "rowesc01", "rowesc01", "rowesc01", "rowesc01", "rowesc01", "rowesc01", "hardeme01", "hardeme01", "hardeme01", "hardeme01", "hardeme01", 
+#> "hardeme01", "hardeme01", "hardeme01", "hardeme01", "hardeme01", "hardeme01", "hardeme01", "hardeme01", "hardeme01", "hardeme01", "hardeme01", "hardeme01", "hardeme01", "hardeme01", "hardeme01", "knickbi01", "knickbi01", "knickbi01", "knickbi01", "knickbi01", "knickbi01", "knickbi01", "knickbi01", "knickbi01", "knickbi01", "ottme01", "ottme01", "ottme01", "ottme01", "ottme01", "ottme01", "ottme01", "ottme01", "ottme01", "ottme01", "ottme01", "ottme01", "ottme01", "ottme01", "ottme01", "ottme01", 
+#> "ottme01", "ottme01", "ottme01", "ottme01", "ottme01", "ottme01", "moorejo02", "moorejo02", "moorejo02", "moorejo02", "moorejo02", "moorejo02", "moorejo02", "moorejo02", "moorejo02", "moorejo02", "moorejo02", "moorejo02", "schumha02", "schumha02", "schumha02", "schumha02", "schumha02", "schumha02", "schumha02", "schumha02", "schumha02", "schumha02", "schumha02", "schumha02", "schumha02", "greenha01", "greenha01", "greenha01", "greenha01", "greenha01", "greenha01", "greenha01", "greenha01", "greenha01", 
+#> "greenha01", "greenha01", "greenha01", "greenha01", "cramedo01", "cramedo01", "cramedo01", "cramedo01", "cramedo01", "cramedo01", "cramedo01", "cramedo01", "cramedo01", "cramedo01", "cramedo01", "cramedo01", "cramedo01", "cramedo01", "cramedo01", "cramedo01", "cramedo01", "cramedo01", "cramedo01", "cramedo01", "vosmijo01", "vosmijo01", "vosmijo01", "vosmijo01", "vosmijo01", "vosmijo01", "vosmijo01", "vosmijo01", "vosmijo01", "vosmijo01", "vosmijo01", "vosmijo01", "vosmijo01", "foxpe01", "foxpe01", 
+#> "foxpe01", "foxpe01", "foxpe01", "foxpe01", "foxpe01", "foxpe01", "foxpe01", "foxpe01", "foxpe01", "foxpe01", "foxpe01", "martipe01", "martipe01", "martipe01", "martipe01", "martipe01", "martipe01", "martipe01", "martipe01", "martipe01", "martipe01", "martipe01", "martipe01", "martipe01", "owenma01", "owenma01", "owenma01", "owenma01", "owenma01", "owenma01", "owenma01", "owenma01", "owenma01", "dimagjo01", "dimagjo01", "dimagjo01", "dimagjo01", "dimagjo01", "dimagjo01", "dimagjo01", "dimagjo01", 
+#> "dimagjo01", "dimagjo01", "dimagjo01", "dimagjo01", "dimagjo01", "kenneve01", "kenneve01", "kenneve01", "kenneve01", "kenneve01", "kenneve01", "kenneve01", "kenneve01", "kenneve01", "kenneve01", "kenneve01", "kenneve01", "kenneve01", "kenneve01", "kenneve01", "kenneve01", "allenjo02", "allenjo02", "allenjo02", "allenjo02", "allenjo02", "allenjo02", "allenjo02", "allenjo02", "allenjo02", "allenjo02", "allenjo02", "allenjo02", "allenjo02", "allenjo02", "allenjo02", "moseswa01", "moseswa01", "moseswa01", 
+#> "moseswa01", "moseswa01", "moseswa01", "moseswa01", "moseswa01", "moseswa01", "moseswa01", "moseswa01", "moseswa01", "moseswa01", "moseswa01", "moseswa01", "moseswa01", "moseswa01", "moseswa01", "applilu01", "applilu01", "applilu01", "applilu01", "applilu01", "applilu01", "applilu01", "applilu01", "applilu01", "applilu01", "applilu01", "applilu01", "applilu01", "applilu01", "applilu01", "applilu01", "applilu01", "applilu01", "applilu01", "applilu01", "hackst01", "hackst01", "hackst01", "hackst01", 
+#> "hackst01", "hackst01", "hackst01", "hackst01", "hackst01", "hackst01", "hackst01", "hackst01", "hackst01", "hackst01", "hackst01", "hackst01", "suhrgu01", "suhrgu01", "suhrgu01", "suhrgu01", "suhrgu01", "suhrgu01", "suhrgu01", "suhrgu01", "suhrgu01", "suhrgu01", "suhrgu01", "suhrgu01", "frencla01", "frencla01", "frencla01", "frencla01", "frencla01", "frencla01", "frencla01", "frencla01", "frencla01", "frencla01", "frencla01", "frencla01", "frencla01", "frencla01", "frencla01", "macfada01", "macfada01", 
+#> "macfada01", "macfada01", "macfada01", "macfada01", "macfada01", "macfada01", "macfada01", "macfada01", "macfada01", "macfada01", "macfada01", "macfada01", "macfada01", "macfada01", "macfada01", "macfada01", "macfada01", "lawsoro01", "lawsoro01", "lawsoro01", "lawsoro01", "lawsoro01", "lawsoro01", "lawsoro01", "lawsoro01", "lawsoro01", "lawsoro01", "whitnpi01", "whitnpi01", "whitnpi01", "whitnpi01", "whitnpi01", "whitnpi01", "whitnpi01", "whitnpi01", "whitnpi01", "whitnpi01", "whitnpi01", "whitnpi01", 
+#> "whitnpi01", "whitnpi01", "fettelo01", "fettelo01", "fettelo01", "fettelo01", "fettelo01", "fettelo01", "mizejo01", "mizejo01", "mizejo01", "mizejo01", "mizejo01", "mizejo01", "mizejo01", "mizejo01", "mizejo01", "mizejo01", "mizejo01", "mizejo01", "mizejo01", "mizejo01", "mizejo01", "mizejo01", "demarfr02", "demarfr02", "demarfr02", "demarfr02", "demarfr02", "demarfr02", "demarfr02", "demarfr02", "demarfr02", "demarfr02", "demarfr02", "demarfr02", "demarfr02", "turneji01", "turneji01", "turneji01", 
+#> "turneji01", "turneji01", "turneji01", "turneji01", "turneji01", "turneji01", "turneji01", "rolfere01", "rolfere01", "rolfere01", "rolfere01", "rolfere01", "rolfere01", "rolfere01", "rolfere01", "rolfere01", "rolfere01", "ruffire01", "ruffire01", "ruffire01", "ruffire01", "ruffire01", "ruffire01", "ruffire01", "ruffire01", "ruffire01", "ruffire01", "ruffire01", "ruffire01", "ruffire01", "ruffire01", "ruffire01", "ruffire01", "ruffire01", "ruffire01", "ruffire01", "ruffire01", "ruffire01", "ruffire01", 
+#> "ruffire01", "hemslro01", "hemslro01", "hemslro01", "hemslro01", "hemslro01", "hemslro01", "hemslro01", "hemslro01", "hemslro01", "hemslro01", "hemslro01", "hemslro01", "hemslro01", "hemslro01", "hemslro01", "hemslro01", "hemslro01", "hemslro01", "hemslro01", "hemslro01", "hemslro01", "hemslro01", "heathje01", "heathje01", "heathje01", "heathje01", "heathje01", "heathje01", "heathje01", "heathje01", "heathje01", "heathje01", "heathje01", "heathje01", "heathje01", "heathje01", "heathje01", "newsobo01", 
+#> "newsobo01", "newsobo01", "newsobo01", "newsobo01", "newsobo01", "newsobo01", "newsobo01", "newsobo01", "newsobo01", "newsobo01", "newsobo01", "newsobo01", "newsobo01", "newsobo01", "newsobo01", "newsobo01", "newsobo01", "newsobo01", "newsobo01", "newsobo01", "newsobo01", "newsobo01", "newsobo01", "newsobo01", "newsobo01", "newsobo01", "newsobo01", "newsobo01", "vandejo01", "vandejo01", "vandejo01", "vandejo01", "vandejo01", "vandejo01", "vandejo01", "vandejo01", "vandejo01", "vandejo01", "vandejo01", 
+#> "vandejo01", "vandejo01", "mccorfr01", "mccorfr01", "mccorfr01", "mccorfr01", "mccorfr01", "mccorfr01", "mccorfr01", "mccorfr01", "mccorfr01", "mccorfr01", "mccorfr01", "mccorfr01", "mccorfr01", "mccorfr01", "lombaer01", "lombaer01", "lombaer01", "lombaer01", "lombaer01", "lombaer01", "lombaer01", "lombaer01", "lombaer01", "lombaer01", "lombaer01", "lombaer01", "lombaer01", "lombaer01", "lombaer01", "lombaer01", "lombaer01", "danniha01", "danniha01", "danniha01", "danniha01", "danniha01", "danniha01", 
+#> "danniha01", "danniha01", "danniha01", "danniha01", "leebi02", "leebi02", "leebi02", "leebi02", "leebi02", "leebi02", "leebi02", "leebi02", "leebi02", "leebi02", "leebi02", "leebi02", "leebi02", "leebi02", "leebi02", "leebi02", "goodmiv01", "goodmiv01", "goodmiv01", "goodmiv01", "goodmiv01", "goodmiv01", "goodmiv01", "goodmiv01", "goodmiv01", "goodmiv01", "gordojo01", "gordojo01", "gordojo01", "gordojo01", "gordojo01", "gordojo01", "gordojo01", "gordojo01", "gordojo01", "gordojo01", "gordojo01", 
+#> "johnsbo01", "johnsbo01", "johnsbo01", "johnsbo01", "johnsbo01", "johnsbo01", "johnsbo01", "johnsbo01", "johnsbo01", "johnsbo01", "johnsbo01", "johnsbo01", "johnsbo01", "fellebo01", "fellebo01", "fellebo01", "fellebo01", "fellebo01", "fellebo01", "fellebo01", "fellebo01", "fellebo01", "fellebo01", "fellebo01", "fellebo01", "fellebo01", "fellebo01", "fellebo01", "fellebo01", "fellebo01", "fellebo01", "leonadu02", "leonadu02", "leonadu02", "leonadu02", "leonadu02", "leonadu02", "leonadu02", "leonadu02", 
+#> "leonadu02", "leonadu02", "leonadu02", "leonadu02", "leonadu02", "leonadu02", "leonadu02", "leonadu02", "leonadu02", "leonadu02", "leonadu02", "leonadu02", "willite01", "willite01", "willite01", "willite01", "willite01", "willite01", "willite01", "willite01", "willite01", "willite01", "willite01", "willite01", "willite01", "willite01", "willite01", "willite01", "willite01", "willite01", "willite01", "waltebu01", "waltebu01", "waltebu01", "waltebu01", "waltebu01", "waltebu01", "waltebu01", "waltebu01", 
+#> "waltebu01", "waltebu01", "waltebu01", "waltebu01", "waltebu01", "waltebu01", "waltebu01", "waltebu01", "waltebu01", "waltebu01", "waltebu01", "waltebu01", "waltebu01", "daviscu01", "daviscu01", "daviscu01", "daviscu01", "daviscu01", "daviscu01", "daviscu01", "daviscu01", "daviscu01", "daviscu01", "daviscu01", "daviscu01", "daviscu01", "daviscu01", "daviscu01", "freylo01", "freylo01", "freylo01", "freylo01", "freylo01", "freylo01", "freylo01", "freylo01", "freylo01", "freylo01", "freylo01", "freylo01", 
+#> "freylo01", "freylo01", "freylo01", "freylo01", "lavagco01", "lavagco01", "lavagco01", "lavagco01", "lavagco01", "lavagco01", "lavagco01", "lavagco01", "lavagco01", "lavagco01", "leibeha01", "leibeha01", "leibeha01", "leibeha01", "leibeha01", "leibeha01", "leibeha01", "leibeha01", "leibeha01", "leibeha01", "cliftha01", "cliftha01", "cliftha01", "cliftha01", "cliftha01", "cliftha01", "cliftha01", "cliftha01", "cliftha01", "cliftha01", "cliftha01", "cliftha01", "cliftha01", "hayesfr01", "hayesfr01", 
+#> "hayesfr01", "hayesfr01", "hayesfr01", "hayesfr01", "hayesfr01", "hayesfr01", "hayesfr01", "hayesfr01", "hayesfr01", "hayesfr01", "hayesfr01", "hayesfr01", "hayesfr01", "hayesfr01", "hayesfr01", "kellech01", "kellech01", "kellech01", "kellech01", "kellech01", "kellech01", "kellech01", "kellech01", "kellech01", "kellech01", "kellech01", "kellech01", "kellech01", "nichobi01", "nichobi01", "nichobi01", "nichobi01", "nichobi01", "nichobi01", "nichobi01", "nichobi01", "nichobi01", "nichobi01", "nichobi01", 
+#> "nichobi01", "nichobi01", "nichobi01", "nichobi01", "nichobi01", "milleed03", "milleed03", "milleed03", "milleed03", "milleed03", "milleed03", "milleed03", "milleed03", "milleed03", "milleed03", "milleed03", "milleed03", "milleed03", "milleed03", "taborji01", "taborji01", "taborji01", "taborji01", "taborji01", "taborji01", "taborji01", "taborji01", "taborji01", "leeth01", "leeth01", "leeth01", "leeth01", "leeth01", "leeth01", "leeth01", "leeth01", "leeth01", "leeth01", "leeth01", "leeth01", "leeth01", 
+#> "leeth01", "leeth01", "leeth01", "newsodi01", "newsodi01", "newsodi01", "travice01", "travice01", "travice01", "travice01", "travice01", "travice01", "travice01", "travice01", "travice01", "travice01", "travice01", "travice01", "camildo01", "camildo01", "camildo01", "camildo01", "camildo01", "camildo01", "camildo01", "camildo01", "camildo01", "camildo01", "camildo01", "camildo01", "camildo01", "brownji03", "brownji03", "brownji03", "brownji03", "brownji03", "brownji03", "brownji03", "brownji03", 
+#> "wyattwh01", "wyattwh01", "wyattwh01", "wyattwh01", "wyattwh01", "wyattwh01", "wyattwh01", "wyattwh01", "wyattwh01", "wyattwh01", "wyattwh01", "wyattwh01", "wyattwh01", "wyattwh01", "wyattwh01", "wyattwh01", "wyattwh01", "whiteer01", "whiteer01", "whiteer01", "whiteer01", "whiteer01", "whiteer01", "whiteer01", "riddlel01", "riddlel01", "riddlel01", "riddlel01", "riddlel01", "riddlel01", "riddlel01", "riddlel01", "riddlel01", "riddlel01", "crespcr01", "crespcr01", "crespcr01", "crespcr01", "crespcr01", 
+#> "reisepe01", "reisepe01", "reisepe01", "reisepe01", "reisepe01", "reisepe01", "reisepe01", "reisepe01", "reisepe01", "reisepe01", "higbeki01", "higbeki01", "higbeki01", "higbeki01", "higbeki01", "higbeki01", "higbeki01", "higbeki01", "higbeki01", "higbeki01", "higbeki01", "higbeki01", "higbeki01", "higbeki01", "higbeki01", "slaugen01", "slaugen01", "slaugen01", "slaugen01", "slaugen01", "slaugen01", "slaugen01", "slaugen01", "slaugen01", "slaugen01", "slaugen01", "slaugen01", "slaugen01", "slaugen01", 
+#> "slaugen01", "slaugen01", "slaugen01", "slaugen01", "slaugen01", "slaugen01", "slaugen01", "slaugen01", "jurgebi01", "jurgebi01", "jurgebi01", "jurgebi01", "jurgebi01", "jurgebi01", "jurgebi01", "jurgebi01", "jurgebi01", "jurgebi01", "jurgebi01", "jurgebi01", "jurgebi01", "jurgebi01", "jurgebi01", "jurgebi01", "jurgebi01", "hassebu01", "hassebu01", "hassebu01", "hassebu01", "hassebu01", "hassebu01", "hassebu01", "keltnke01", "keltnke01", "keltnke01", "keltnke01", "keltnke01", "keltnke01", "keltnke01", 
+#> "keltnke01", "keltnke01", "keltnke01", "keltnke01", "keltnke01", "keltnke01", "hughste01", "hughste01", "hughste01", "hughste01", "hughste01", "hughste01", "hughste01", "hughste01", "bonhati01", "bonhati01", "bonhati01", "bonhati01", "bonhati01", "bonhati01", "bonhati01", "bonhati01", "bonhati01", "bonhati01", "bagbyji02", "bagbyji02", "bagbyji02", "bagbyji02", "bagbyji02", "bagbyji02", "bagbyji02", "bagbyji02", "bagbyji02", "bagbyji02", "marchph01", "marchph01", "marchph01", "marchph01", "marchph01", 
+#> "marchph01", "marchph01", "marchph01", "marchph01", "chandsp01", "chandsp01", "chandsp01", "chandsp01", "chandsp01", "chandsp01", "chandsp01", "chandsp01", "chandsp01", "chandsp01", "chandsp01", "spencst01", "spencst01", "spencst01", "spencst01", "spencst01", "spencst01", "spencst01", "spencst01", "spencst01", "spencst01", "stephve01", "stephve01", "stephve01", "stephve01", "stephve01", "stephve01", "stephve01", "stephve01", "stephve01", "stephve01", "stephve01", "stephve01", "stephve01", "stephve01", 
+#> "stephve01", "stephve01", "stephve01", "coopemo01", "coopemo01", "coopemo01", "coopemo01", "coopemo01", "coopemo01", "coopemo01", "coopemo01", "coopemo01", "coopemo01", "coopemo01", "coopemo01", "coopemo01", "hugheto04", "hugheto04", "hugheto04", "hugheto04", "hugheto04", "beazljo01", "beazljo01", "beazljo01", "beazljo01", "beazljo01", "beazljo01", "marioma01", "marioma01", "marioma01", "marioma01", "marioma01", "marioma01", "marioma01", "marioma01", "marioma01", "marioma01", "marioma01", "marioma01", 
+#> "marioma01", "owenmi01", "owenmi01", "owenmi01", "owenmi01", "owenmi01", "owenmi01", "owenmi01", "owenmi01", "owenmi01", "owenmi01", "owenmi01", "owenmi01", "owenmi01", "peskyjo01", "peskyjo01", "peskyjo01", "peskyjo01", "peskyjo01", "peskyjo01", "peskyjo01", "peskyjo01", "peskyjo01", "peskyjo01", "peskyjo01", "peskyjo01", "yorkru01", "yorkru01", "yorkru01", "yorkru01", "yorkru01", "yorkru01", "yorkru01", "yorkru01", "yorkru01", "yorkru01", "yorkru01", "yorkru01", "yorkru01", "yorkru01", "johnsbi03", 
+#> "johnsbi03", "johnsbi03", "johnsbi03", "johnsbi03", "johnsbi03", "johnsbi03", "johnsbi03", "johnsbi03", "johnsbi03", "troutdi01", "troutdi01", "troutdi01", "troutdi01", "troutdi01", "troutdi01", "troutdi01", "troutdi01", "troutdi01", "troutdi01", "troutdi01", "troutdi01", "troutdi01", "troutdi01", "troutdi01", "troutdi01", "smithal03", "smithal03", "smithal03", "smithal03", "smithal03", "smithal03", "smithal03", "smithal03", "smithal03", "smithal03", "smithal03", "smithal03", "wakefdi01", "wakefdi01", 
+#> "wakefdi01", "wakefdi01", "wakefdi01", "wakefdi01", "wakefdi01", "wakefdi01", "wakefdi01", "musiast01", "musiast01", "musiast01", "musiast01", "musiast01", "musiast01", "musiast01", "musiast01", "musiast01", "musiast01", "musiast01", "musiast01", "musiast01", "musiast01", "musiast01", "musiast01", "musiast01", "musiast01", "musiast01", "musiast01", "musiast01", "musiast01", "sewelri01", "sewelri01", "sewelri01", "sewelri01", "sewelri01", "sewelri01", "sewelri01", "sewelri01", "sewelri01", "sewelri01", 
+#> "sewelri01", "sewelri01", "sewelri01", "coopewa01", "coopewa01", "coopewa01", "coopewa01", "coopewa01", "coopewa01", "coopewa01", "coopewa01", "coopewa01", "coopewa01", "coopewa01", "coopewa01", "coopewa01", "coopewa01", "coopewa01", "coopewa01", "coopewa01", "coopewa01", "coopewa01", "coopewa01", "coopewa01", "dimagvi01", "dimagvi01", "dimagvi01", "dimagvi01", "dimagvi01", "dimagvi01", "dimagvi01", "dimagvi01", "dimagvi01", "dimagvi01", "dimagvi01", "dimagvi01", "stirnsn01", "stirnsn01", "stirnsn01", 
+#> "stirnsn01", "stirnsn01", "stirnsn01", "stirnsn01", "stirnsn01", "stirnsn01", "stirnsn01", "stirnsn01", "newhoha01", "newhoha01", "newhoha01", "newhoha01", "newhoha01", "newhoha01", "newhoha01", "newhoha01", "newhoha01", "newhoha01", "newhoha01", "newhoha01", "newhoha01", "newhoha01", "newhoha01", "newhoha01", "newhoha01", "elliobo01", "elliobo01", "elliobo01", "elliobo01", "elliobo01", "elliobo01", "elliobo01", "elliobo01", "elliobo01", "elliobo01", "elliobo01", "elliobo01", "elliobo01", "elliobo01", 
+#> "elliobo01", "elliobo01", "sandera01", "sandera01", "sandera01", "sandera01", "sandera01", "sandera01", "sandera01", "verbaem01", "verbaem01", "verbaem01", "verbaem01", "verbaem01", "verbaem01", "verbaem01", "verbaem01", "verbaem01", "verbaem01", "voisebi01", "voisebi01", "voisebi01", "voisebi01", "voisebi01", "voisebi01", "voisebi01", "voisebi01", "voisebi01", "voisebi01", "doerrbo01", "doerrbo01", "doerrbo01", "doerrbo01", "doerrbo01", "doerrbo01", "doerrbo01", "doerrbo01", "doerrbo01", "doerrbo01", 
+#> "doerrbo01", "doerrbo01", "doerrbo01", "doerrbo01", "walkedi02", "walkedi02", "walkedi02", "walkedi02", "walkedi02", "walkedi02", "walkedi02", "walkedi02", "walkedi02", "walkedi02", "walkedi02", "walkedi02", "walkedi02", "walkedi02", "walkedi02", "walkedi02", "walkedi02", "walkedi02", "walkedi02", "walkedi02", "ettenni01", "ettenni01", "ettenni01", "ettenni01", "ettenni01", "ettenni01", "ettenni01", "ettenni01", "ettenni01", "cuccito01", "cuccito01", "cuccito01", "cuccito01", "cuccito01", "cuccito01", 
+#> "cuccito01", "cuccito01", "cuccito01", "cuccito01", "cuccito01", "cuccito01", "cuccito01", "cuccito01", "cuccito01", "cuccito01", "cuccito01", "richapa01", "richapa01", "richapa01", "richapa01", "richapa01", "richapa01", "richapa01", "richapa01", "richapa01", "ferrida01", "ferrida01", "ferrida01", "ferrida01", "ferrida01", "ferrida01", "gromest01", "gromest01", "gromest01", "gromest01", "gromest01", "gromest01", "gromest01", "gromest01", "gromest01", "gromest01", "gromest01", "gromest01", "gromest01", 
+#> "gromest01", "gromest01", "gromest01", "gromest01", "gromest01", "wolffro01", "wolffro01", "wolffro01", "wolffro01", "wolffro01", "wolffro01", "wolffro01", "wolffro01", "cullero01", "cullero01", "cullero01", "cullero01", "cullero01", "cullero01", "cullero01", "cullero01", "cullero01", "cullero01", "cullero01", "cullero01", "cullero01", "cullero01", "cavarph01", "cavarph01", "cavarph01", "cavarph01", "cavarph01", "cavarph01", "cavarph01", "cavarph01", "cavarph01", "cavarph01", "cavarph01", "cavarph01", 
+#> "cavarph01", "cavarph01", "cavarph01", "cavarph01", "cavarph01", "cavarph01", "cavarph01", "cavarph01", "cavarph01", "cavarph01", "kurowwh01", "kurowwh01", "kurowwh01", "kurowwh01", "kurowwh01", "kurowwh01", "kurowwh01", "kurowwh01", "kurowwh01", "pafkoan01", "pafkoan01", "pafkoan01", "pafkoan01", "pafkoan01", "pafkoan01", "pafkoan01", "pafkoan01", "pafkoan01", "pafkoan01", "pafkoan01", "pafkoan01", "pafkoan01", "pafkoan01", "pafkoan01", "pafkoan01", "pafkoan01", "pafkoan01", "brechha01", "brechha01", 
+#> "brechha01", "brechha01", "brechha01", "brechha01", "brechha01", "brechha01", "brechha01", "brechha01", "brechha01", "brechha01", "borowha01", "borowha01", "borowha01", "borowha01", "borowha01", "borowha01", "borowha01", "borowha01", "borowha01", "borowha01", "borowha01", "borowha01", "borowha01", "holmeto01", "holmeto01", "holmeto01", "holmeto01", "holmeto01", "holmeto01", "holmeto01", "holmeto01", "holmeto01", "holmeto01", "holmeto01", "barrere01", "barrere01", "barrere01", "barrere01", "barrere01", 
+#> "barrere01", "barrere01", "barrere01", "barrere01", "barrere01", "barrere01", "barrere01", "wyseha01", "wyseha01", "wyseha01", "wyseha01", "wyseha01", "wyseha01", "wyseha01", "wyseha01", "wyseha01", "rosengo01", "rosengo01", "rosengo01", "rosengo01", "rosengo01", "rosengo01", "rosengo01", "mayoed01", "mayoed01", "mayoed01", "mayoed01", "mayoed01", "mayoed01", "mayoed01", "mayoed01", "mayoed01", "vernomi01", "vernomi01", "vernomi01", "vernomi01", "vernomi01", "vernomi01", "vernomi01", "vernomi01", 
+#> "vernomi01", "vernomi01", "vernomi01", "vernomi01", "vernomi01", "vernomi01", "vernomi01", "vernomi01", "vernomi01", "vernomi01", "vernomi01", "vernomi01", "vernomi01", "kellge01", "kellge01", "kellge01", "kellge01", "kellge01", "kellge01", "kellge01", "kellge01", "kellge01", "kellge01", "kellge01", "kellge01", "kellge01", "kellge01", "kellge01", "kellge01", "kellge01", "kellge01", "kellge01", "robinaa01", "robinaa01", "robinaa01", "robinaa01", "robinaa01", "robinaa01", "robinaa01", "robinaa01", 
+#> "robinaa01", "boudrlo01", "boudrlo01", "boudrlo01", "boudrlo01", "boudrlo01", "boudrlo01", "boudrlo01", "boudrlo01", "boudrlo01", "boudrlo01", "boudrlo01", "boudrlo01", "boudrlo01", "boudrlo01", "boudrlo01", "polleho01", "polleho01", "polleho01", "polleho01", "polleho01", "polleho01", "polleho01", "polleho01", "polleho01", "polleho01", "polleho01", "polleho01", "polleho01", "polleho01", "polleho01", "polleho01", "polleho01", "stanked01", "stanked01", "stanked01", "stanked01", "stanked01", "stanked01", 
+#> "stanked01", "stanked01", "stanked01", "stanked01", "stanked01", "stanked01", "mcculcl01", "mcculcl01", "mcculcl01", "mcculcl01", "mcculcl01", "mcculcl01", "mcculcl01", "mcculcl01", "mcculcl01", "mcculcl01", "mcculcl01", "mcculcl01", "mcculcl01", "mcculcl01", "mcculcl01", "ennisde01", "ennisde01", "ennisde01", "ennisde01", "ennisde01", "ennisde01", "ennisde01", "ennisde01", "ennisde01", "ennisde01", "ennisde01", "ennisde01", "ennisde01", "ennisde01", "ennisde01", "sainjo01", "sainjo01", "sainjo01", 
+#> "sainjo01", "sainjo01", "sainjo01", "sainjo01", "sainjo01", "sainjo01", "sainjo01", "sainjo01", "sainjo01", "sainjo01", "reesepe01", "reesepe01", "reesepe01", "reesepe01", "reesepe01", "reesepe01", "reesepe01", "reesepe01", "reesepe01", "reesepe01", "reesepe01", "reesepe01", "reesepe01", "reesepe01", "reesepe01", "reesepe01", "dimagdo01", "dimagdo01", "dimagdo01", "dimagdo01", "dimagdo01", "dimagdo01", "dimagdo01", "dimagdo01", "dimagdo01", "dimagdo01", "dimagdo01", "mcquige02", "mcquige02", "mcquige02", 
+#> "mcquige02", "mcquige02", "mcquige02", "mcquige02", "mcquige02", "mcquige02", "mcquige02", "mcquige02", "mcquige02", "berrayo01", "berrayo01", "berrayo01", "berrayo01", "berrayo01", "berrayo01", "berrayo01", "berrayo01", "berrayo01", "berrayo01", "berrayo01", "berrayo01", "berrayo01", "berrayo01", "berrayo01", "berrayo01", "berrayo01", "berrayo01", "berrayo01", "reynoal01", "reynoal01", "reynoal01", "reynoal01", "reynoal01", "reynoal01", "reynoal01", "reynoal01", "reynoal01", "reynoal01", "reynoal01", 
+#> "reynoal01", "reynoal01", "henrito01", "henrito01", "henrito01", "henrito01", "henrito01", "henrito01", "henrito01", "henrito01", "henrito01", "henrito01", "henrito01", "edwarbr01", "edwarbr01", "edwarbr01", "edwarbr01", "edwarbr01", "edwarbr01", "edwarbr01", "edwarbr01", "edwarbr01", "edwarbr01", "edwarbr01", "blackew01", "blackew01", "blackew01", "blackew01", "blackew01", "blackew01", "blackew01", "blackew01", "blackew01", "blackew01", "blackew01", "kinerra01", "kinerra01", "kinerra01", "kinerra01", 
+#> "kinerra01", "kinerra01", "kinerra01", "kinerra01", "kinerra01", "kinerra01", "kinerra01", "brancra01", "brancra01", "brancra01", "brancra01", "brancra01", "brancra01", "brancra01", "brancra01", "brancra01", "brancra01", "brancra01", "brancra01", "brancra01", "brancra01", "spahnwa01", "spahnwa01", "spahnwa01", "spahnwa01", "spahnwa01", "spahnwa01", "spahnwa01", "spahnwa01", "spahnwa01", "spahnwa01", "spahnwa01", "spahnwa01", "spahnwa01", "spahnwa01", "spahnwa01", "spahnwa01", "spahnwa01", "spahnwa01", 
+#> "spahnwa01", "spahnwa01", "spahnwa01", "spahnwa01", "marshwi01", "marshwi01", "marshwi01", "marshwi01", "marshwi01", "marshwi01", "marshwi01", "marshwi01", "marshwi01", "marshwi01", "marshwi01", "marshwi01", "robinja02", "robinja02", "robinja02", "robinja02", "robinja02", "robinja02", "robinja02", "robinja02", "robinja02", "robinja02", "fainfe01", "fainfe01", "fainfe01", "fainfe01", "fainfe01", "fainfe01", "fainfe01", "fainfe01", "fainfe01", "fainfe01", "tebbebi01", "tebbebi01", "tebbebi01", "tebbebi01", 
+#> "tebbebi01", "tebbebi01", "tebbebi01", "tebbebi01", "tebbebi01", "tebbebi01", "tebbebi01", "tebbebi01", "tebbebi01", "tebbebi01", "tebbebi01", "lemonbo01", "lemonbo01", "lemonbo01", "lemonbo01", "lemonbo01", "lemonbo01", "lemonbo01", "lemonbo01", "lemonbo01", "lemonbo01", "lemonbo01", "lemonbo01", "lemonbo01", "lemonbo01", "lemonbo01", "raschvi01", "raschvi01", "raschvi01", "raschvi01", "raschvi01", "raschvi01", "raschvi01", "raschvi01", "raschvi01", "raschvi01", "raschvi01", "masiph01", "masiph01", 
+#> "masiph01", "masiph01", "masiph01", "masiph01", "masiph01", "masiph01", "masiph01", "masiph01", "masiph01", "masiph01", "masiph01", "masiph01", "masiph01", "schmijo01", "schmijo01", "schmijo01", "schmijo01", "schmijo01", "schmijo01", "schmijo01", "schmijo01", "schmijo01", "schmijo01", "schmijo01", "schmijo01", "schmijo01", "schmijo01", "schmijo01", "schmijo01", "schmijo01", "schmijo01", "darkal01", "darkal01", "darkal01", "darkal01", "darkal01", "darkal01", "darkal01", "darkal01", "darkal01", "darkal01", 
+#> "darkal01", "darkal01", "darkal01", "darkal01", "darkal01", "darkal01", "darkal01", "pagejo01", "pagejo01", "pagejo01", "pagejo01", "pagejo01", "pagejo01", "pagejo01", "pagejo01", "michaca01", "michaca01", "michaca01", "michaca01", "michaca01", "michaca01", "michaca01", "michaca01", "michaca01", "michaca01", "michaca01", "michaca01", "michaca01", "michaca01", "michaca01", "parneme01", "parneme01", "parneme01", "parneme01", "parneme01", "parneme01", "parneme01", "parneme01", "parneme01", "parneme01", 
+#> "wertzvi01", "wertzvi01", "wertzvi01", "wertzvi01", "wertzvi01", "wertzvi01", "wertzvi01", "wertzvi01", "wertzvi01", "wertzvi01", "wertzvi01", "wertzvi01", "wertzvi01", "wertzvi01", "wertzvi01", "wertzvi01", "wertzvi01", "wertzvi01", "wertzvi01", "wertzvi01", "wertzvi01", "hodgegi01", "hodgegi01", "hodgegi01", "hodgegi01", "hodgegi01", "hodgegi01", "hodgegi01", "hodgegi01", "hodgegi01", "hodgegi01", "hodgegi01", "hodgegi01", "hodgegi01", "hodgegi01", "hodgegi01", "hodgegi01", "hodgegi01", "hodgegi01", 
+#> "gordosi01", "gordosi01", "gordosi01", "gordosi01", "gordosi01", "gordosi01", "gordosi01", "gordosi01", "gordosi01", "gordosi01", "gordosi01", "gordosi01", "gordosi01", "gordosi01", "camparo01", "camparo01", "camparo01", "camparo01", "camparo01", "camparo01", "camparo01", "camparo01", "camparo01", "camparo01", "newcodo01", "newcodo01", "newcodo01", "newcodo01", "newcodo01", "newcodo01", "newcodo01", "newcodo01", "newcodo01", "newcodo01", "newcodo01", "newcodo01", "sievero01", "sievero01", "sievero01", 
+#> "sievero01", "sievero01", "sievero01", "sievero01", "sievero01", "sievero01", "sievero01", "sievero01", "sievero01", "sievero01", "sievero01", "sievero01", "sievero01", "sievero01", "sievero01", "kindeel01", "kindeel01", "kindeel01", "kindeel01", "kindeel01", "kindeel01", "kindeel01", "kindeel01", "kindeel01", "kindeel01", "kindeel01", "kindeel01", "kindeel01", "rizzuph01", "rizzuph01", "rizzuph01", "rizzuph01", "rizzuph01", "rizzuph01", "rizzuph01", "rizzuph01", "rizzuph01", "rizzuph01", "rizzuph01", 
+#> "rizzuph01", "rizzuph01", "colemje01", "colemje01", "colemje01", "colemje01", "colemje01", "colemje01", "colemje01", "colemje01", "colemje01", "dropowa01", "dropowa01", "dropowa01", "dropowa01", "dropowa01", "dropowa01", "dropowa01", "dropowa01", "dropowa01", "dropowa01", "dropowa01", "dropowa01", "dropowa01", "dropowa01", "dropowa01", "dropowa01", "houttar01", "houttar01", "houttar01", "houttar01", "houttar01", "houttar01", "houttar01", "houttar01", "houttar01", "houttar01", "houttar01", "houttar01", 
+#> "houttar01", "houttar01", "konstji01", "konstji01", "konstji01", "konstji01", "konstji01", "konstji01", "konstji01", "konstji01", "konstji01", "konstji01", "konstji01", "konstji01", "konstji01", "furilca01", "furilca01", "furilca01", "furilca01", "furilca01", "furilca01", "furilca01", "furilca01", "furilca01", "furilca01", "furilca01", "furilca01", "furilca01", "furilca01", "furilca01", "snidedu01", "snidedu01", "snidedu01", "snidedu01", "snidedu01", "snidedu01", "snidedu01", "snidedu01", "snidedu01", 
+#> "snidedu01", "snidedu01", "snidedu01", "snidedu01", "snidedu01", "snidedu01", "snidedu01", "snidedu01", "snidedu01", "jansela01", "jansela01", "jansela01", "jansela01", "jansela01", "jansela01", "jansela01", "jansela01", "jansela01", "hamnegr01", "hamnegr01", "hamnegr01", "hamnegr01", "hamnegr01", "hamnegr01", "hamnegr01", "hamnegr01", "hamnegr01", "hamnegr01", "hamnegr01", "hamnegr01", "hamnegr01", "hamnegr01", "hamnegr01", "hamnegr01", "hamnegr01", "hamnegr01", "jethrsa01", "jethrsa01", "jethrsa01", 
+#> "jethrsa01", "dobyla01", "dobyla01", "dobyla01", "dobyla01", "dobyla01", "dobyla01", "dobyla01", "dobyla01", "dobyla01", "dobyla01", "dobyla01", "dobyla01", "dobyla01", "dobyla01", "mcdougi01", "mcdougi01", "mcdougi01", "mcdougi01", "mcdougi01", "mcdougi01", "mcdougi01", "mcdougi01", "mcdougi01", "mcdougi01", "mayswi01", "mayswi01", "mayswi01", "mayswi01", "mayswi01", "mayswi01", "mayswi01", "mayswi01", "mayswi01", "mayswi01", "mayswi01", "mayswi01", "mayswi01", "mayswi01", "mayswi01", "mayswi01", 
+#> "mayswi01", "mayswi01", "mayswi01", "mayswi01", "mayswi01", "mayswi01", "mayswi01", "maglisa01", "maglisa01", "maglisa01", "maglisa01", "maglisa01", "maglisa01", "maglisa01", "maglisa01", "maglisa01", "maglisa01", "maglisa01", "maglisa01", "maglisa01", "maglisa01", "roepr01", "roepr01", "roepr01", "roepr01", "roepr01", "roepr01", "roepr01", "roepr01", "roepr01", "roepr01", "roepr01", "roepr01", "shantbo01", "shantbo01", "shantbo01", "shantbo01", "shantbo01", "shantbo01", "shantbo01", "shantbo01", 
+#> "shantbo01", "shantbo01", "shantbo01", "shantbo01", "shantbo01", "shantbo01", "shantbo01", "shantbo01", "shantbo01", "shantbo01", "shantbo01", "sauerha01", "sauerha01", "sauerha01", "sauerha01", "sauerha01", "sauerha01", "sauerha01", "sauerha01", "sauerha01", "sauerha01", "sauerha01", "sauerha01", "sauerha01", "sauerha01", "sauerha01", "sauerha01", "byrdha01", "byrdha01", "byrdha01", "byrdha01", "byrdha01", "byrdha01", "byrdha01", "byrdha01", "blackjo02", "blackjo02", "blackjo02", "blackjo02", "blackjo02", 
+#> "blackjo02", "blackjo02", "mantlmi01", "mantlmi01", "mantlmi01", "mantlmi01", "mantlmi01", "mantlmi01", "mantlmi01", "mantlmi01", "mantlmi01", "mantlmi01", "mantlmi01", "mantlmi01", "mantlmi01", "mantlmi01", "mantlmi01", "mantlmi01", "mantlmi01", "mantlmi01", "roberro01", "roberro01", "roberro01", "roberro01", "roberro01", "roberro01", "roberro01", "roberro01", "roberro01", "roberro01", "roberro01", "roberro01", "roberro01", "roberro01", "roberro01", "roberro01", "roberro01", "roberro01", "roberro01", 
+#> "roberro01", "roberro01", "eastelu01", "eastelu01", "eastelu01", "eastelu01", "eastelu01", "eastelu01", "martibi02", "martibi02", "martibi02", "martibi02", "martibi02", "martibi02", "martibi02", "martibi02", "martibi02", "martibi02", "martibi02", "martibi02", "martibi02", "rosenal01", "rosenal01", "rosenal01", "rosenal01", "rosenal01", "rosenal01", "rosenal01", "rosenal01", "rosenal01", "rosenal01", "kuennha01", "kuennha01", "kuennha01", "kuennha01", "kuennha01", "kuennha01", "kuennha01", "kuennha01", 
+#> "kuennha01", "kuennha01", "kuennha01", "kuennha01", "kuennha01", "kuennha01", "kuennha01", "kuennha01", "kuennha01", "gilliji01", "gilliji01", "gilliji01", "gilliji01", "gilliji01", "gilliji01", "gilliji01", "gilliji01", "gilliji01", "gilliji01", "gilliji01", "gilliji01", "gilliji01", "gilliji01", "schoere01", "schoere01", "schoere01", "schoere01", "schoere01", "schoere01", "schoere01", "schoere01", "schoere01", "schoere01", "schoere01", "schoere01", "schoere01", "schoere01", "schoere01", "schoere01", 
+#> "schoere01", "schoere01", "schoere01", "schoere01", "schoere01", "portebo01", "portebo01", "portebo01", "portebo01", "portebo01", "portebo01", "portebo01", "portebo01", "portebo01", "portebo01", "portebo01", "portebo01", "portebo01", "portebo01", "portebo01", "portebo01", "rhodedu01", "rhodedu01", "rhodedu01", "rhodedu01", "rhodedu01", "rhodedu01", "rhodedu01", "grimbo01", "grimbo01", "grimbo01", "grimbo01", "grimbo01", "grimbo01", "grimbo01", "grimbo01", "grimbo01", "grimbo01", "grimbo01", "moonwa01", 
+#> "moonwa01", "moonwa01", "moonwa01", "moonwa01", "moonwa01", "moonwa01", "moonwa01", "moonwa01", "moonwa01", "moonwa01", "moonwa01", "kluszte01", "kluszte01", "kluszte01", "kluszte01", "kluszte01", "kluszte01", "kluszte01", "kluszte01", "kluszte01", "kluszte01", "kluszte01", "kluszte01", "kluszte01", "kluszte01", "kluszte01", "kluszte01", "avilabo01", "avilabo01", "avilabo01", "avilabo01", "avilabo01", "avilabo01", "avilabo01", "avilabo01", "avilabo01", "avilabo01", "avilabo01", "avilabo01", "avilabo01", 
+#> "antonjo02", "antonjo02", "antonjo02", "antonjo02", "antonjo02", "antonjo02", "antonjo02", "antonjo02", "antonjo02", "antonjo02", "antonjo02", "antonjo02", "antonjo02", "ayalabo01", "ayalabo01", "ayalabo01", "ayalabo01", "ayalabo01", "ayalabo01", "ayalabo01", "ayalabo01", "ayalabo01", "podrejo01", "podrejo01", "podrejo01", "podrejo01", "podrejo01", "podrejo01", "podrejo01", "podrejo01", "podrejo01", "podrejo01", "podrejo01", "podrejo01", "podrejo01", "podrejo01", "podrejo01", "podrejo01", "scorehe01", 
+#> "scorehe01", "scorehe01", "scorehe01", "scorehe01", "scorehe01", "scorehe01", "scorehe01", "virdobi01", "virdobi01", "virdobi01", "virdobi01", "virdobi01", "virdobi01", "virdobi01", "virdobi01", "virdobi01", "virdobi01", "virdobi01", "virdobi01", "virdobi01", "foxne01", "foxne01", "foxne01", "foxne01", "foxne01", "foxne01", "foxne01", "foxne01", "foxne01", "foxne01", "foxne01", "foxne01", "foxne01", "foxne01", "foxne01", "foxne01", "foxne01", "foxne01", "foxne01", "matheed01", "matheed01", "matheed01", 
+#> "matheed01", "matheed01", "matheed01", "matheed01", "matheed01", "matheed01", "matheed01", "matheed01", "matheed01", "matheed01", "matheed01", "matheed01", "matheed01", "matheed01", "matheed01", "kalinal01", "kalinal01", "kalinal01", "kalinal01", "kalinal01", "kalinal01", "kalinal01", "kalinal01", "kalinal01", "kalinal01", "kalinal01", "kalinal01", "kalinal01", "kalinal01", "kalinal01", "kalinal01", "kalinal01", "kalinal01", "kalinal01", "kalinal01", "kalinal01", "kalinal01", "fordwh01", "fordwh01", 
+#> "fordwh01", "fordwh01", "fordwh01", "fordwh01", "fordwh01", "fordwh01", "fordwh01", "fordwh01", "fordwh01", "fordwh01", "fordwh01", "fordwh01", "fordwh01", "fordwh01", "bankser01", "bankser01", "bankser01", "bankser01", "bankser01", "bankser01", "bankser01", "bankser01", "bankser01", "bankser01", "bankser01", "bankser01", "bankser01", "bankser01", "bankser01", "bankser01", "bankser01", "bankser01", "bankser01", "larsedo01", "larsedo01", "larsedo01", "larsedo01", "larsedo01", "larsedo01", "larsedo01", 
+#> "larsedo01", "larsedo01", "larsedo01", "larsedo01", "larsedo01", "larsedo01", "larsedo01", "larsedo01", "larsedo01", "larsedo01", "aparilu01", "aparilu01", "aparilu01", "aparilu01", "aparilu01", "aparilu01", "aparilu01", "aparilu01", "aparilu01", "aparilu01", "aparilu01", "aparilu01", "aparilu01", "aparilu01", "aparilu01", "aparilu01", "aparilu01", "aparilu01", "robinfr02", "robinfr02", "robinfr02", "robinfr02", "robinfr02", "robinfr02", "robinfr02", "robinfr02", "robinfr02", "robinfr02", "robinfr02", 
+#> "robinfr02", "robinfr02", "robinfr02", "robinfr02", "robinfr02", "robinfr02", "robinfr02", "robinfr02", "robinfr02", "robinfr02", "robinfr02", "boyerke01", "boyerke01", "boyerke01", "boyerke01", "boyerke01", "boyerke01", "boyerke01", "boyerke01", "boyerke01", "boyerke01", "boyerke01", "boyerke01", "boyerke01", "boyerke01", "boyerke01", "boyerke01", "boyerke01", "aaronha01", "aaronha01", "aaronha01", "aaronha01", "aaronha01", "aaronha01", "aaronha01", "aaronha01", "aaronha01", "aaronha01", "aaronha01", 
+#> "aaronha01", "aaronha01", "aaronha01", "aaronha01", "aaronha01", "aaronha01", "aaronha01", "aaronha01", "aaronha01", "aaronha01", "aaronha01", "aaronha01", "piercbi02", "piercbi02", "piercbi02", "piercbi02", "piercbi02", "piercbi02", "piercbi02", "piercbi02", "piercbi02", "piercbi02", "piercbi02", "piercbi02", "piercbi02", "piercbi02", "piercbi02", "piercbi02", "piercbi02", "piercbi02", "burdele01", "burdele01", "burdele01", "burdele01", "burdele01", "burdele01", "burdele01", "burdele01", "burdele01", 
+#> "burdele01", "burdele01", "burdele01", "burdele01", "burdele01", "burdele01", "burdele01", "burdele01", "burdele01", "burdele01", "burdele01", "burdele01", "malzofr01", "malzofr01", "malzofr01", "malzofr01", "malzofr01", "malzofr01", "malzofr01", "malzofr01", "malzofr01", "malzofr01", "malzofr01", "malzofr01", "lollash01", "lollash01", "lollash01", "lollash01", "lollash01", "lollash01", "lollash01", "lollash01", "lollash01", "lollash01", "lollash01", "lollash01", "lollash01", "lollash01", "lollash01", 
+#> "lollash01", "lollash01", "lollash01", "minosmi01", "minosmi01", "minosmi01", "minosmi01", "minosmi01", "minosmi01", "minosmi01", "minosmi01", "minosmi01", "minosmi01", "minosmi01", "minosmi01", "minosmi01", "minosmi01", "minosmi01", "minosmi01", "minosmi01", "minosmi01", "mcmilro01", "mcmilro01", "mcmilro01", "mcmilro01", "mcmilro01", "mcmilro01", "mcmilro01", "mcmilro01", "mcmilro01", "mcmilro01", "mcmilro01", "mcmilro01", "mcmilro01", "mcmilro01", "mcmilro01", "mcmilro01", "mcmilro01", "kubekto01", 
+#> "kubekto01", "kubekto01", "kubekto01", "kubekto01", "kubekto01", "kubekto01", "kubekto01", "kubekto01", "sanfoja02", "sanfoja02", "sanfoja02", "sanfoja02", "sanfoja02", "sanfoja02", "sanfoja02", "sanfoja02", "sanfoja02", "sanfoja02", "sanfoja02", "sanfoja02", "sanfoja02", "sanfoja02", "bunniji01", "bunniji01", "bunniji01", "bunniji01", "bunniji01", "bunniji01", "bunniji01", "bunniji01", "bunniji01", "bunniji01", "bunniji01", "bunniji01", "bunniji01", "bunniji01", "bunniji01", "bunniji01", "bunniji01", 
+#> "bunniji01", "howarel01", "howarel01", "howarel01", "howarel01", "howarel01", "howarel01", "howarel01", "howarel01", "howarel01", "howarel01", "howarel01", "howarel01", "howarel01", "howarel01", "howarel01", "turlebo01", "turlebo01", "turlebo01", "turlebo01", "turlebo01", "turlebo01", "turlebo01", "turlebo01", "turlebo01", "turlebo01", "turlebo01", "turlebo01", "turlebo01", "powervi01", "powervi01", "powervi01", "powervi01", "powervi01", "powervi01", "powervi01", "powervi01", "powervi01", "powervi01", 
+#> "powervi01", "powervi01", "powervi01", "powervi01", "powervi01", "bollifr01", "bollifr01", "bollifr01", "bollifr01", "bollifr01", "bollifr01", "bollifr01", "bollifr01", "bollifr01", "bollifr01", "bollifr01", "bollifr01", "piersji01", "piersji01", "piersji01", "piersji01", "piersji01", "piersji01", "piersji01", "piersji01", "piersji01", "piersji01", "piersji01", "piersji01", "piersji01", "piersji01", "piersji01", "piersji01", "piersji01", "piersji01", "piersji01", "siebeno01", "siebeno01", "siebeno01", 
+#> "siebeno01", "siebeno01", "siebeno01", "siebeno01", "siebeno01", "siebeno01", "siebeno01", "siebeno01", "siebeno01", "siebeno01", "mazerbi01", "mazerbi01", "mazerbi01", "mazerbi01", "mazerbi01", "mazerbi01", "mazerbi01", "mazerbi01", "mazerbi01", "mazerbi01", "mazerbi01", "mazerbi01", "mazerbi01", "mazerbi01", "mazerbi01", "mazerbi01", "mazerbi01", "crandde01", "crandde01", "crandde01", "crandde01", "crandde01", "crandde01", "crandde01", "crandde01", "crandde01", "crandde01", "crandde01", "crandde01", 
+#> "crandde01", "crandde01", "crandde01", "crandde01", "haddiha01", "haddiha01", "haddiha01", "haddiha01", "haddiha01", "haddiha01", "haddiha01", "haddiha01", "haddiha01", "haddiha01", "haddiha01", "haddiha01", "haddiha01", "haddiha01", "haddiha01", "jenseja01", "jenseja01", "jenseja01", "jenseja01", "jenseja01", "jenseja01", "jenseja01", "jenseja01", "jenseja01", "jenseja01", "jenseja01", "jenseja01", "pearsal02", "pearsal02", "pearsal02", "pearsal02", "pearsal02", "pearsal02", "pearsal02", "pearsal02", 
+#> "pearsal02", "pearsal02", "cepedor01", "cepedor01", "cepedor01", "cepedor01", "cepedor01", "cepedor01", "cepedor01", "cepedor01", "cepedor01", "cepedor01", "cepedor01", "cepedor01", "cepedor01", "cepedor01", "cepedor01", "cepedor01", "cepedor01", "cepedor01", "cepedor01", "thomafr03", "thomafr03", "thomafr03", "thomafr03", "thomafr03", "thomafr03", "thomafr03", "thomafr03", "thomafr03", "thomafr03", "thomafr03", "thomafr03", "thomafr03", "thomafr03", "thomafr03", "thomafr03", "thomafr03", "thomafr03", 
+#> "thomafr03", "thomafr03", "frienbo01", "frienbo01", "frienbo01", "frienbo01", "frienbo01", "frienbo01", "frienbo01", "frienbo01", "frienbo01", "frienbo01", "frienbo01", "frienbo01", "frienbo01", "frienbo01", "frienbo01", "frienbo01", "frienbo01", "sherrla01", "sherrla01", "sherrla01", "sherrla01", "sherrla01", "sherrla01", "sherrla01", "sherrla01", "sherrla01", "sherrla01", "sherrla01", "sherrla01", "wynnea01", "wynnea01", "wynnea01", "wynnea01", "wynnea01", "wynnea01", "wynnea01", "wynnea01", "wynnea01", 
+#> "wynnea01", "wynnea01", "wynnea01", "wynnea01", "wynnea01", "wynnea01", "wynnea01", "wynnea01", "wynnea01", "wynnea01", "wynnea01", "wynnea01", "wynnea01", "wynnea01", "nealch01", "nealch01", "nealch01", "nealch01", "nealch01", "nealch01", "nealch01", "nealch01", "nealch01", "brandja01", "brandja01", "brandja01", "brandja01", "brandja01", "brandja01", "brandja01", "brandja01", "brandja01", "brandja01", "brandja01", "brandja01", "brandja01", "allisbo01", "allisbo01", "allisbo01", "allisbo01", "allisbo01", 
+#> "allisbo01", "allisbo01", "allisbo01", "allisbo01", "allisbo01", "allisbo01", "allisbo01", "allisbo01", "mccovwi01", "mccovwi01", "mccovwi01", "mccovwi01", "mccovwi01", "mccovwi01", "mccovwi01", "mccovwi01", "mccovwi01", "mccovwi01", "mccovwi01", "mccovwi01", "mccovwi01", "mccovwi01", "mccovwi01", "mccovwi01", "mccovwi01", "mccovwi01", "mccovwi01", "mccovwi01", "mccovwi01", "mccovwi01", "mccovwi01", "jonessa02", "jonessa02", "jonessa02", "jonessa02", "jonessa02", "jonessa02", "jonessa02", "jonessa02", 
+#> "jonessa02", "jonessa02", "jonessa02", "jonessa02", "lawve01", "lawve01", "lawve01", "lawve01", "lawve01", "lawve01", "lawve01", "lawve01", "lawve01", "lawve01", "lawve01", "lawve01", "lawve01", "lawve01", "lawve01", "lawve01", "robinbr01", "robinbr01", "robinbr01", "robinbr01", "robinbr01", "robinbr01", "robinbr01", "robinbr01", "robinbr01", "robinbr01", "robinbr01", "robinbr01", "robinbr01", "robinbr01", "robinbr01", "robinbr01", "robinbr01", "robinbr01", "robinbr01", "robinbr01", "robinbr01", 
+#> "robinbr01", "robinbr01", "batteea01", "batteea01", "batteea01", "batteea01", "batteea01", "batteea01", "batteea01", "batteea01", "batteea01", "batteea01", "batteea01", "batteea01", "batteea01", "landiji01", "landiji01", "landiji01", "landiji01", "landiji01", "landiji01", "landiji01", "landiji01", "landiji01", "landiji01", "landiji01", "landiji01", "landiji01", "marisro01", "marisro01", "marisro01", "marisro01", "marisro01", "marisro01", "marisro01", "marisro01", "marisro01", "marisro01", "marisro01", 
+#> "marisro01", "marisro01", "whitebi03", "whitebi03", "whitebi03", "whitebi03", "whitebi03", "whitebi03", "whitebi03", "whitebi03", "whitebi03", "whitebi03", "whitebi03", "whitebi03", "whitebi03", "groatdi01", "groatdi01", "groatdi01", "groatdi01", "groatdi01", "groatdi01", "groatdi01", "groatdi01", "groatdi01", "groatdi01", "groatdi01", "groatdi01", "groatdi01", "groatdi01", "groatdi01", "hansero02", "hansero02", "hansero02", "hansero02", "hansero02", "hansero02", "hansero02", "hansero02", "hansero02", 
+#> "hansero02", "hansero02", "hansero02", "hansero02", "hansero02", "hansero02", "hansero02", "howarfr01", "howarfr01", "howarfr01", "howarfr01", "howarfr01", "howarfr01", "howarfr01", "howarfr01", "howarfr01", "howarfr01", "howarfr01", "howarfr01", "howarfr01", "howarfr01", "howarfr01", "howarfr01", "howarfr01", "skowrbi01", "skowrbi01", "skowrbi01", "skowrbi01", "skowrbi01", "skowrbi01", "skowrbi01", "skowrbi01", "skowrbi01", "skowrbi01", "skowrbi01", "skowrbi01", "skowrbi01", "skowrbi01", "skowrbi01", 
+#> "skowrbi01", "brogler01", "brogler01", "brogler01", "brogler01", "brogler01", "brogler01", "brogler01", "brogler01", "brogler01", "fornimi01", "fornimi01", "fornimi01", "fornimi01", "fornimi01", "fornimi01", "fornimi01", "fornimi01", "fornimi01", "fornimi01", "fornimi01", "fornimi01", "fornimi01", "fornimi01", "fornimi01", "mcdanli01", "mcdanli01", "mcdanli01", "mcdanli01", "mcdanli01", "mcdanli01", "mcdanli01", "mcdanli01", "mcdanli01", "mcdanli01", "mcdanli01", "mcdanli01", "mcdanli01", "mcdanli01", 
+#> "mcdanli01", "mcdanli01", "mcdanli01", "mcdanli01", "mcdanli01", "mcdanli01", "mcdanli01", "mcdanli01", "estrach01", "estrach01", "estrach01", "estrach01", "estrach01", "estrach01", "estrach01", "richabo01", "richabo01", "richabo01", "richabo01", "richabo01", "richabo01", "richabo01", "richabo01", "richabo01", "richabo01", "richabo01", "richabo01", "laryfr01", "laryfr01", "laryfr01", "laryfr01", "laryfr01", "laryfr01", "laryfr01", "laryfr01", "laryfr01", "laryfr01", "laryfr01", "laryfr01", "laryfr01", 
+#> "laryfr01", "laryfr01", "rosebjo01", "rosebjo01", "rosebjo01", "rosebjo01", "rosebjo01", "rosebjo01", "rosebjo01", "rosebjo01", "rosebjo01", "rosebjo01", "rosebjo01", "rosebjo01", "rosebjo01", "rosebjo01", "clemero01", "clemero01", "clemero01", "clemero01", "clemero01", "clemero01", "clemero01", "clemero01", "clemero01", "clemero01", "clemero01", "clemero01", "clemero01", "clemero01", "clemero01", "clemero01", "clemero01", "clemero01", "pinsova01", "pinsova01", "pinsova01", "pinsova01", "pinsova01", 
+#> "pinsova01", "pinsova01", "pinsova01", "pinsova01", "pinsova01", "pinsova01", "pinsova01", "pinsova01", "pinsova01", "pinsova01", "pinsova01", "pinsova01", "pinsova01", "willsma01", "willsma01", "willsma01", "willsma01", "willsma01", "willsma01", "willsma01", "willsma01", "willsma01", "willsma01", "willsma01", "willsma01", "willsma01", "willsma01", "willsma01", "schwado01", "schwado01", "schwado01", "schwado01", "schwado01", "schwado01", "schwado01", "schwado01", "willibi01", "willibi01", "willibi01", 
+#> "willibi01", "willibi01", "willibi01", "willibi01", "willibi01", "willibi01", "willibi01", "willibi01", "willibi01", "willibi01", "willibi01", "willibi01", "willibi01", "willibi01", "willibi01", "cashno01", "cashno01", "cashno01", "cashno01", "cashno01", "cashno01", "cashno01", "cashno01", "cashno01", "cashno01", "cashno01", "cashno01", "cashno01", "cashno01", "cashno01", "cashno01", "cashno01", "colavro01", "colavro01", "colavro01", "colavro01", "colavro01", "colavro01", "colavro01", "colavro01", 
+#> "colavro01", "colavro01", "colavro01", "colavro01", "colavro01", "colavro01", "colavro01", "colavro01", "burgesm01", "burgesm01", "burgesm01", "burgesm01", "burgesm01", "burgesm01", "burgesm01", "burgesm01", "burgesm01", "burgesm01", "burgesm01", "burgesm01", "burgesm01", "burgesm01", "burgesm01", "burgesm01", "burgesm01", "burgesm01", "burgesm01", "burgesm01", "jayjo01", "jayjo01", "jayjo01", "jayjo01", "jayjo01", "jayjo01", "jayjo01", "jayjo01", "jayjo01", "jayjo01", "jayjo01", "jayjo01", "jayjo01", 
+#> "jayjo01", "arroylu01", "arroylu01", "arroylu01", "arroylu01", "arroylu01", "arroylu01", "arroylu01", "arroylu01", "millest01", "millest01", "millest01", "millest01", "millest01", "millest01", "millest01", "millest01", "millest01", "millest01", "millest01", "millest01", "millest01", "millest01", "millest01", "millest01", "millest01", "wagnele01", "wagnele01", "wagnele01", "wagnele01", "wagnele01", "wagnele01", "wagnele01", "wagnele01", "wagnele01", "wagnele01", "wagnele01", "wagnele01", "wagnele01", 
+#> "terryra01", "terryra01", "terryra01", "terryra01", "terryra01", "terryra01", "terryra01", "terryra01", "terryra01", "terryra01", "terryra01", "terryra01", "terryra01", "terryra01", "terryra01", "drysddo01", "drysddo01", "drysddo01", "drysddo01", "drysddo01", "drysddo01", "drysddo01", "drysddo01", "drysddo01", "drysddo01", "drysddo01", "drysddo01", "drysddo01", "drysddo01", "kaatji01", "kaatji01", "kaatji01", "kaatji01", "kaatji01", "kaatji01", "kaatji01", "kaatji01", "kaatji01", "kaatji01", "kaatji01", 
+#> "kaatji01", "kaatji01", "kaatji01", "kaatji01", "kaatji01", "kaatji01", "kaatji01", "kaatji01", "kaatji01", "kaatji01", "kaatji01", "kaatji01", "kaatji01", "kaatji01", "kaatji01", "kaatji01", "kaatji01", "hubbske01", "hubbske01", "hubbske01", "davenji01", "davenji01", "davenji01", "davenji01", "davenji01", "davenji01", "davenji01", "davenji01", "davenji01", "davenji01", "davenji01", "davenji01", "davenji01", "treshto01", "treshto01", "treshto01", "treshto01", "treshto01", "treshto01", "treshto01", 
+#> "treshto01", "treshto01", "treshto01", "donovdi01", "donovdi01", "donovdi01", "donovdi01", "donovdi01", "donovdi01", "donovdi01", "donovdi01", "donovdi01", "donovdi01", "donovdi01", "donovdi01", "donovdi01", "donovdi01", "donovdi01", "davisto02", "davisto02", "davisto02", "davisto02", "davisto02", "davisto02", "davisto02", "davisto02", "davisto02", "davisto02", "davisto02", "davisto02", "davisto02", "davisto02", "davisto02", "davisto02", "davisto02", "davisto02", "davisto02", "davisto02", "davisto02", 
+#> "davisto02", "davisto02", "purkebo01", "purkebo01", "purkebo01", "purkebo01", "purkebo01", "purkebo01", "purkebo01", "purkebo01", "purkebo01", "purkebo01", "purkebo01", "purkebo01", "purkebo01", "radatdi01", "radatdi01", "radatdi01", "radatdi01", "radatdi01", "radatdi01", "radatdi01", "radatdi01", "radatdi01", "radatdi01", "facero01", "facero01", "facero01", "facero01", "facero01", "facero01", "facero01", "facero01", "facero01", "facero01", "facero01", "facero01", "facero01", "facero01", "facero01", 
+#> "facero01", "facero01", "koufasa01", "koufasa01", "koufasa01", "koufasa01", "koufasa01", "koufasa01", "koufasa01", "koufasa01", "koufasa01", "koufasa01", "koufasa01", "koufasa01", "yastrca01", "yastrca01", "yastrca01", "yastrca01", "yastrca01", "yastrca01", "yastrca01", "yastrca01", "yastrca01", "yastrca01", "yastrca01", "yastrca01", "yastrca01", "yastrca01", "yastrca01", "yastrca01", "yastrca01", "yastrca01", "yastrca01", "yastrca01", "yastrca01", "yastrca01", "yastrca01", "versazo01", "versazo01", 
+#> "versazo01", "versazo01", "versazo01", "versazo01", "versazo01", "versazo01", "versazo01", "versazo01", "versazo01", "versazo01", "versazo01", "edwarjo01", "edwarjo01", "edwarjo01", "edwarjo01", "edwarjo01", "edwarjo01", "edwarjo01", "edwarjo01", "edwarjo01", "edwarjo01", "edwarjo01", "edwarjo01", "edwarjo01", "edwarjo01", "floodcu01", "floodcu01", "floodcu01", "floodcu01", "floodcu01", "floodcu01", "floodcu01", "floodcu01", "floodcu01", "floodcu01", "floodcu01", "floodcu01", "floodcu01", "floodcu01", 
+#> "floodcu01", "winebo01", "winebo01", "winebo01", "winebo01", "winebo01", "winebo01", "winebo01", "winebo01", "winebo01", "winebo01", "winebo01", "winebo01", "peterga01", "peterga01", "peterga01", "peterga01", "peterga01", "peterga01", "peterga01", "peterga01", "peterga01", "peterga01", "peterga01", "peterga01", "peterga01", "peterga01", "rosepe01", "rosepe01", "rosepe01", "rosepe01", "rosepe01", "rosepe01", "rosepe01", "rosepe01", "rosepe01", "rosepe01", "rosepe01", "rosepe01", "rosepe01", "rosepe01", 
+#> "rosepe01", "rosepe01", "rosepe01", "rosepe01", "rosepe01", "rosepe01", "rosepe01", "rosepe01", "rosepe01", "rosepe01", "rosepe01", "pepitjo01", "pepitjo01", "pepitjo01", "pepitjo01", "pepitjo01", "pepitjo01", "pepitjo01", "pepitjo01", "pepitjo01", "pepitjo01", "pepitjo01", "pepitjo01", "pepitjo01", "pepitjo01", "maricju01", "maricju01", "maricju01", "maricju01", "maricju01", "maricju01", "maricju01", "maricju01", "maricju01", "maricju01", "maricju01", "maricju01", "maricju01", "maricju01", "maricju01", 
+#> "maricju01", "callijo01", "callijo01", "callijo01", "callijo01", "callijo01", "callijo01", "callijo01", "callijo01", "callijo01", "callijo01", "callijo01", "callijo01", "callijo01", "callijo01", "callijo01", "callijo01", "gibsobo01", "gibsobo01", "gibsobo01", "gibsobo01", "gibsobo01", "gibsobo01", "gibsobo01", "gibsobo01", "gibsobo01", "gibsobo01", "gibsobo01", "gibsobo01", "gibsobo01", "gibsobo01", "gibsobo01", "gibsobo01", "gibsobo01", "chancde01", "chancde01", "chancde01", "chancde01", "chancde01", 
+#> "chancde01", "chancde01", "chancde01", "chancde01", "chancde01", "chancde01", "chancde01", "davalvi01", "davalvi01", "davalvi01", "davalvi01", "davalvi01", "davalvi01", "davalvi01", "davalvi01", "davalvi01", "davalvi01", "davalvi01", "davalvi01", "davalvi01", "davalvi01", "davalvi01", "davalvi01", "davalvi01", "davalvi01", "davalvi01", "santoro01", "santoro01", "santoro01", "santoro01", "santoro01", "santoro01", "santoro01", "santoro01", "santoro01", "santoro01", "santoro01", "santoro01", "santoro01", 
+#> "santoro01", "santoro01", "amaroru01", "amaroru01", "amaroru01", "amaroru01", "amaroru01", "amaroru01", "amaroru01", "amaroru01", "amaroru01", "amaroru01", "amaroru01", "olivato01", "olivato01", "olivato01", "olivato01", "olivato01", "olivato01", "olivato01", "olivato01", "olivato01", "olivato01", "olivato01", "olivato01", "olivato01", "olivato01", "olivato01", "allendi01", "allendi01", "allendi01", "allendi01", "allendi01", "allendi01", "allendi01", "allendi01", "allendi01", "allendi01", "allendi01", 
+#> "allendi01", "allendi01", "allendi01", "allendi01", "stuardi01", "stuardi01", "stuardi01", "stuardi01", "stuardi01", "stuardi01", "stuardi01", "stuardi01", "stuardi01", "stuardi01", "stuardi01", "killeha01", "killeha01", "killeha01", "killeha01", "killeha01", "killeha01", "killeha01", "killeha01", "killeha01", "killeha01", "killeha01", "killeha01", "killeha01", "killeha01", "killeha01", "killeha01", "killeha01", "killeha01", "killeha01", "killeha01", "killeha01", "killeha01", "fregoji01", "fregoji01", 
+#> "fregoji01", "fregoji01", "fregoji01", "fregoji01", "fregoji01", "fregoji01", "fregoji01", "fregoji01", "fregoji01", "fregoji01", "fregoji01", "fregoji01", "fregoji01", "fregoji01", "fregoji01", "fregoji01", "fregoji01", "fregoji01", "huntro01", "huntro01", "huntro01", "huntro01", "huntro01", "huntro01", "huntro01", "huntro01", "huntro01", "huntro01", "huntro01", "huntro01", "huntro01", "torrejo01", "torrejo01", "torrejo01", "torrejo01", "torrejo01", "torrejo01", "torrejo01", "torrejo01", "torrejo01", 
+#> "torrejo01", "torrejo01", "torrejo01", "torrejo01", "torrejo01", "torrejo01", "torrejo01", "torrejo01", "torrejo01", "mcbeaal01", "mcbeaal01", "mcbeaal01", "mcbeaal01", "mcbeaal01", "mcbeaal01", "mcbeaal01", "mcbeaal01", "mcbeaal01", "mcbeaal01", "mcbeaal01", "mcbeaal01", "freehbi01", "freehbi01", "freehbi01", "freehbi01", "freehbi01", "freehbi01", "freehbi01", "freehbi01", "freehbi01", "freehbi01", "freehbi01", "freehbi01", "freehbi01", "freehbi01", "freehbi01", "cardele01", "cardele01", "cardele01", 
+#> "cardele01", "cardele01", "cardele01", "cardele01", "cardele01", "cardele01", "cardele01", "cardele01", "cardele01", "cardele01", "cardele01", "cardele01", "cardele01", "blefacu01", "blefacu01", "blefacu01", "blefacu01", "blefacu01", "blefacu01", "blefacu01", "blefacu01", "blefacu01", "blefacu01", "lefebji01", "lefebji01", "lefebji01", "lefebji01", "lefebji01", "lefebji01", "lefebji01", "lefebji01", "whitffr01", "whitffr01", "whitffr01", "whitffr01", "whitffr01", "whitffr01", "whitffr01", "whitffr01", 
+#> "whitffr01", "hallji02", "hallji02", "hallji02", "hallji02", "hallji02", "hallji02", "hallji02", "hallji02", "hallji02", "hallji02", "hallji02", "hallji02", "grantmu01", "grantmu01", "grantmu01", "grantmu01", "grantmu01", "grantmu01", "grantmu01", "grantmu01", "grantmu01", "grantmu01", "grantmu01", "grantmu01", "grantmu01", "grantmu01", "grantmu01", "grantmu01", "grantmu01", "grantmu01", "stottme01", "stottme01", "stottme01", "stottme01", "stottme01", "stottme01", "stottme01", "stottme01", "stottme01", 
+#> "stottme01", "stottme01", "johnsde01", "johnsde01", "johnsde01", "johnsde01", "johnsde01", "johnsde01", "johnsde01", "johnsde01", "johnsde01", "johnsde01", "johnsde01", "johnsde01", "johnsde01", "johnsde01", "johnsde01", "johnsde01", "johnsde01", "johnsde01", "johnsde01", "johnsde01", "johnsde01", "stargwi01", "stargwi01", "stargwi01", "stargwi01", "stargwi01", "stargwi01", "stargwi01", "stargwi01", "stargwi01", "stargwi01", "stargwi01", "stargwi01", "stargwi01", "stargwi01", "stargwi01", "stargwi01", 
+#> "stargwi01", "stargwi01", "stargwi01", "stargwi01", "stargwi01", "fisheed02", "fisheed02", "fisheed02", "fisheed02", "fisheed02", "fisheed02", "fisheed02", "fisheed02", "fisheed02", "fisheed02", "fisheed02", "fisheed02", "fisheed02", "fisheed02", "fisheed02", "fisheed02", "fisheed02", "fisheed02", "abernte02", "abernte02", "abernte02", "abernte02", "abernte02", "abernte02", "abernte02", "abernte02", "abernte02", "abernte02", "abernte02", "abernte02", "abernte02", "abernte02", "abernte02", "abernte02", 
+#> "abernte02", "knoopbo01", "knoopbo01", "knoopbo01", "knoopbo01", "knoopbo01", "knoopbo01", "knoopbo01", "knoopbo01", "knoopbo01", "knoopbo01", "ageeto01", "ageeto01", "ageeto01", "ageeto01", "ageeto01", "ageeto01", "ageeto01", "ageeto01", "ageeto01", "ageeto01", "ageeto01", "ageeto01", "ageeto01", "alleyge01", "alleyge01", "alleyge01", "alleyge01", "alleyge01", "alleyge01", "alleyge01", "alleyge01", "alleyge01", "alleyge01", "alleyge01", "helmsto01", "helmsto01", "helmsto01", "helmsto01", "helmsto01", 
+#> "helmsto01", "helmsto01", "helmsto01", "helmsto01", "helmsto01", "helmsto01", "helmsto01", "helmsto01", "helmsto01", "helmsto01", "powelbo01", "powelbo01", "powelbo01", "powelbo01", "powelbo01", "powelbo01", "powelbo01", "powelbo01", "powelbo01", "powelbo01", "powelbo01", "powelbo01", "powelbo01", "powelbo01", "powelbo01", "powelbo01", "powelbo01", "casanpa01", "casanpa01", "casanpa01", "casanpa01", "casanpa01", "casanpa01", "casanpa01", "casanpa01", "casanpa01", "casanpa01", "wilsoea01", "wilsoea01", 
+#> "wilsoea01", "wilsoea01", "wilsoea01", "wilsoea01", "wilsoea01", "wilsoea01", "wilsoea01", "wilsoea01", "wilsoea01", "wilsoea01", "wilsoea01", "aloufe01", "aloufe01", "aloufe01", "aloufe01", "aloufe01", "aloufe01", "aloufe01", "aloufe01", "aloufe01", "aloufe01", "aloufe01", "aloufe01", "aloufe01", "aloufe01", "aloufe01", "aloufe01", "aloufe01", "aloufe01", "aloufe01", "akerja01", "akerja01", "akerja01", "akerja01", "akerja01", "akerja01", "akerja01", "akerja01", "akerja01", "akerja01", "akerja01", 
+#> "akerja01", "akerja01", "akerja01", "reganph01", "reganph01", "reganph01", "reganph01", "reganph01", "reganph01", "reganph01", "reganph01", "reganph01", "reganph01", "reganph01", "reganph01", "reganph01", "reganph01", "reganph01", "perezto01", "perezto01", "perezto01", "perezto01", "perezto01", "perezto01", "perezto01", "perezto01", "perezto01", "perezto01", "perezto01", "perezto01", "perezto01", "perezto01", "perezto01", "perezto01", "perezto01", "perezto01", "perezto01", "perezto01", "perezto01", 
+#> "perezto01", "perezto01", "brocklo01", "brocklo01", "brocklo01", "brocklo01", "brocklo01", "brocklo01", "brocklo01", "brocklo01", "brocklo01", "brocklo01", "brocklo01", "brocklo01", "brocklo01", "brocklo01", "brocklo01", "brocklo01", "brocklo01", "brocklo01", "brocklo01", "brocklo01", "lonboji01", "lonboji01", "lonboji01", "lonboji01", "lonboji01", "lonboji01", "lonboji01", "lonboji01", "lonboji01", "lonboji01", "lonboji01", "lonboji01", "lonboji01", "lonboji01", "lonboji01", "mccormi03", "mccormi03", 
+#> "mccormi03", "mccormi03", "mccormi03", "mccormi03", "mccormi03", "mccormi03", "mccormi03", "mccormi03", "mccormi03", "mccormi03", "mccormi03", "mccormi03", "mccormi03", "mccormi03", "mccormi03", "scottge02", "scottge02", "scottge02", "scottge02", "scottge02", "scottge02", "scottge02", "scottge02", "scottge02", "scottge02", "scottge02", "scottge02", "scottge02", "scottge02", "scottge02", "scottge02", "blairpa01", "blairpa01", "blairpa01", "blairpa01", "blairpa01", "blairpa01", "blairpa01", "blairpa01", 
+#> "blairpa01", "blairpa01", "blairpa01", "blairpa01", "blairpa01", "blairpa01", "blairpa01", "blairpa01", "blairpa01", "blairpa01", "parkewe01", "parkewe01", "parkewe01", "parkewe01", "parkewe01", "parkewe01", "parkewe01", "parkewe01", "parkewe01", "hundlra01", "hundlra01", "hundlra01", "hundlra01", "hundlra01", "hundlra01", "hundlra01", "hundlra01", "hundlra01", "hundlra01", "hundlra01", "hundlra01", "hundlra01", "hundlra01", "carewro01", "carewro01", "carewro01", "carewro01", "carewro01", "carewro01", 
+#> "carewro01", "carewro01", "carewro01", "carewro01", "carewro01", "carewro01", "carewro01", "carewro01", "carewro01", "carewro01", "carewro01", "carewro01", "carewro01", "seaveto01", "seaveto01", "seaveto01", "seaveto01", "seaveto01", "seaveto01", "seaveto01", "seaveto01", "seaveto01", "seaveto01", "seaveto01", "seaveto01", "seaveto01", "seaveto01", "seaveto01", "seaveto01", "seaveto01", "seaveto01", "seaveto01", "seaveto01", "seaveto01", "seaveto01", "mccarti01", "mccarti01", "mccarti01", "mccarti01", 
+#> "mccarti01", "mccarti01", "mccarti01", "mccarti01", "mccarti01", "mccarti01", "mccarti01", "mccarti01", "mccarti01", "mccarti01", "mccarti01", "mccarti01", "mccarti01", "mccarti01", "mccarti01", "mccarti01", "mccarti01", "mccarti01", "mccarti01", "mccarti01", "wynnji01", "wynnji01", "wynnji01", "wynnji01", "wynnji01", "wynnji01", "wynnji01", "wynnji01", "wynnji01", "wynnji01", "wynnji01", "wynnji01", "wynnji01", "wynnji01", "wynnji01", "wynnji01", "jenkife01", "jenkife01", "jenkife01", "jenkife01", 
+#> "jenkife01", "jenkife01", "jenkife01", "jenkife01", "jenkife01", "jenkife01", "jenkife01", "jenkife01", "jenkife01", "jenkife01", "jenkife01", "jenkife01", "jenkife01", "jenkife01", "jenkife01", "jenkife01", "rojasmi01", "rojasmi01", "rojasmi01", "lolicmi01", "lolicmi01", "lolicmi01", "lolicmi01", "lolicmi01", "lolicmi01", "lolicmi01", "lolicmi01", "lolicmi01", "lolicmi01", "lolicmi01", "lolicmi01", "lolicmi01", "lolicmi01", "lolicmi01", "lolicmi01", "mclaide01", "mclaide01", "mclaide01", "mclaide01", 
+#> "mclaide01", "mclaide01", "mclaide01", "mclaide01", "mclaide01", "mclaide01", "mclaide01", "smithre06", "smithre06", "smithre06", "smithre06", "smithre06", "smithre06", "smithre06", "smithre06", "smithre06", "smithre06", "smithre06", "smithre06", "smithre06", "smithre06", "smithre06", "smithre06", "smithre06", "smithre06", "stanlmi01", "stanlmi01", "stanlmi01", "stanlmi01", "stanlmi01", "stanlmi01", "stanlmi01", "stanlmi01", "stanlmi01", "stanlmi01", "stanlmi01", "stanlmi01", "stanlmi01", "stanlmi01", 
+#> "stanlmi01", "beckegl01", "beckegl01", "beckegl01", "beckegl01", "beckegl01", "beckegl01", "beckegl01", "beckegl01", "beckegl01", "beckegl01", "beckegl01", "benchjo01", "benchjo01", "benchjo01", "benchjo01", "benchjo01", "benchjo01", "benchjo01", "benchjo01", "benchjo01", "benchjo01", "benchjo01", "benchjo01", "benchjo01", "benchjo01", "benchjo01", "benchjo01", "benchjo01", "maxvida01", "maxvida01", "maxvida01", "maxvida01", "maxvida01", "maxvida01", "maxvida01", "maxvida01", "maxvida01", "maxvida01", 
+#> "maxvida01", "maxvida01", "maxvida01", "maxvida01", "maxvida01", "maxvida01", "maxvida01", "bahnsst01", "bahnsst01", "bahnsst01", "bahnsst01", "bahnsst01", "bahnsst01", "bahnsst01", "bahnsst01", "bahnsst01", "bahnsst01", "bahnsst01", "bahnsst01", "bahnsst01", "bahnsst01", "bahnsst01", "bahnsst01", "bahnsst01", "bahnsst01", "bahnsst01", "harreke01", "harreke01", "harreke01", "harreke01", "harreke01", "harreke01", "harreke01", "harreke01", "harreke01", "harreke01", "harreke01", "harreke01", "harreke01", 
+#> "hortowi01", "hortowi01", "hortowi01", "hortowi01", "hortowi01", "hortowi01", "hortowi01", "hortowi01", "hortowi01", "hortowi01", "hortowi01", "hortowi01", "hortowi01", "hortowi01", "hortowi01", "hortowi01", "hortowi01", "hortowi01", "hortowi01", "hortowi01", "hortowi01", "mcnalda01", "mcnalda01", "mcnalda01", "mcnalda01", "mcnalda01", "mcnalda01", "mcnalda01", "mcnalda01", "mcnalda01", "mcnalda01", "mcnalda01", "mcnalda01", "mcnalda01", "mcnalda01", "kessido01", "kessido01", "kessido01", "kessido01", 
+#> "kessido01", "kessido01", "kessido01", "kessido01", "kessido01", "kessido01", "kessido01", "kessido01", "kessido01", "kessido01", "kessido01", "kessido01", "kessido01", "woodwi01", "woodwi01", "woodwi01", "woodwi01", "woodwi01", "woodwi01", "woodwi01", "woodwi01", "woodwi01", "woodwi01", "woodwi01", "woodwi01", "woodwi01", "woodwi01", "woodwi01", "woodwi01", "woodwi01", "woodwi01", "weisal01", "weisal01", "weisal01", "weisal01", "weisal01", "weisal01", "weisal01", "weisal01", "weisal01", "weisal01", 
+#> "cuellmi01", "cuellmi01", "cuellmi01", "cuellmi01", "cuellmi01", "cuellmi01", "cuellmi01", "cuellmi01", "cuellmi01", "cuellmi01", "cuellmi01", "cuellmi01", "cuellmi01", "cuellmi01", "cuellmi01", "johnsda02", "johnsda02", "johnsda02", "johnsda02", "johnsda02", "johnsda02", "johnsda02", "johnsda02", "johnsda02", "johnsda02", "johnsda02", "johnsda02", "johnsda02", "johnsda02", "belanma01", "belanma01", "belanma01", "belanma01", "belanma01", "belanma01", "belanma01", "belanma01", "belanma01", "belanma01", 
+#> "belanma01", "belanma01", "belanma01", "belanma01", "belanma01", "belanma01", "belanma01", "belanma01", "millafe01", "millafe01", "millafe01", "millafe01", "millafe01", "millafe01", "millafe01", "millafe01", "millafe01", "millafe01", "millafe01", "millafe01", "boyercl02", "boyercl02", "boyercl02", "boyercl02", "boyercl02", "boyercl02", "boyercl02", "boyercl02", "boyercl02", "boyercl02", "boyercl02", "boyercl02", "boyercl02", "boyercl02", "boyercl02", "boyercl02", "pinielo01", "pinielo01", "pinielo01", 
+#> "pinielo01", "pinielo01", "pinielo01", "pinielo01", "pinielo01", "pinielo01", "pinielo01", "pinielo01", "pinielo01", "pinielo01", "pinielo01", "pinielo01", "pinielo01", "pinielo01", "pinielo01", "sizemte01", "sizemte01", "sizemte01", "sizemte01", "sizemte01", "sizemte01", "sizemte01", "sizemte01", "sizemte01", "sizemte01", "sizemte01", "sizemte01", "sizemte01", "jacksre01", "jacksre01", "jacksre01", "jacksre01", "jacksre01", "jacksre01", "jacksre01", "jacksre01", "jacksre01", "jacksre01", "jacksre01", 
+#> "jacksre01", "jacksre01", "jacksre01", "jacksre01", "jacksre01", "jacksre01", "jacksre01", "jacksre01", "jacksre01", "jacksre01", "petrori01", "petrori01", "petrori01", "petrori01", "petrori01", "petrori01", "petrori01", "petrori01", "petrori01", "petrori01", "petrori01", "petrori01", "petrori01", "carltst01", "carltst01", "carltst01", "carltst01", "carltst01", "carltst01", "carltst01", "carltst01", "carltst01", "carltst01", "carltst01", "carltst01", "carltst01", "carltst01", "carltst01", "carltst01", 
+#> "carltst01", "carltst01", "carltst01", "carltst01", "carltst01", "carltst01", "carltst01", "carltst01", "carltst01", "carltst01", "carltst01", "alouma01", "alouma01", "alouma01", "alouma01", "alouma01", "alouma01", "alouma01", "alouma01", "alouma01", "alouma01", "alouma01", "alouma01", "alouma01", "alouma01", "alouma01", "alouma01", "alouma01", "jonescl01", "jonescl01", "jonescl01", "jonescl01", "jonescl01", "jonescl01", "jonescl01", "jonescl01", "jonescl01", "jonescl01", "jonescl01", "jonescl01", 
+#> "jonescl01", "perraro01", "perraro01", "perraro01", "perraro01", "perraro01", "perraro01", "perraro01", "perraro01", "perraro01", "perraro01", "perraro01", "perraro01", "perraro01", "perraro01", "perraro01", "grangwa01", "grangwa01", "grangwa01", "grangwa01", "grangwa01", "grangwa01", "grangwa01", "grangwa01", "grangwa01", "grangwa01", "clenddo01", "clenddo01", "clenddo01", "clenddo01", "clenddo01", "clenddo01", "clenddo01", "clenddo01", "clenddo01", "clenddo01", "clenddo01", "clenddo01", "clenddo01", 
+#> "perryji01", "perryji01", "perryji01", "perryji01", "perryji01", "perryji01", "perryji01", "perryji01", "perryji01", "perryji01", "perryji01", "perryji01", "perryji01", "perryji01", "perryji01", "perryji01", "perryji01", "perryji01", "perryji01", "spencji01", "spencji01", "spencji01", "spencji01", "spencji01", "spencji01", "spencji01", "spencji01", "spencji01", "spencji01", "spencji01", "spencji01", "spencji01", "spencji01", "spencji01", "spencji01", "spencji01", "fossera01", "fossera01", "fossera01", 
+#> "fossera01", "fossera01", "fossera01", "fossera01", "fossera01", "fossera01", "fossera01", "fossera01", "fossera01", "fossera01", "berryke01", "berryke01", "berryke01", "berryke01", "berryke01", "berryke01", "berryke01", "berryke01", "berryke01", "berryke01", "berryke01", "berryke01", "berryke01", "berryke01", "raderdo02", "raderdo02", "raderdo02", "raderdo02", "raderdo02", "raderdo02", "raderdo02", "raderdo02", "raderdo02", "raderdo02", "raderdo02", "raderdo02", "conigto01", "conigto01", "conigto01", 
+#> "conigto01", "conigto01", "conigto01", "conigto01", "conigto01", "munsoth01", "munsoth01", "munsoth01", "munsoth01", "munsoth01", "munsoth01", "munsoth01", "munsoth01", "munsoth01", "munsoth01", "munsoth01", "mortoca01", "mortoca01", "mortoca01", "mortoca01", "mortoca01", "mortoca01", "mortoca01", "mortoca01", "mcdowsa01", "mcdowsa01", "mcdowsa01", "mcdowsa01", "mcdowsa01", "mcdowsa01", "mcdowsa01", "mcdowsa01", "mcdowsa01", "mcdowsa01", "mcdowsa01", "mcdowsa01", "mcdowsa01", "mcdowsa01", "mcdowsa01", 
+#> "mcdowsa01", "merriji01", "merriji01", "merriji01", "merriji01", "merriji01", "merriji01", "merriji01", "merriji01", "merriji01", "merriji01", "merriji01", "tolanbo01", "tolanbo01", "tolanbo01", "tolanbo01", "tolanbo01", "tolanbo01", "tolanbo01", "tolanbo01", "tolanbo01", "tolanbo01", "tolanbo01", "tolanbo01", "tolanbo01", "tolanbo01", "bluevi01", "bluevi01", "bluevi01", "bluevi01", "bluevi01", "bluevi01", "bluevi01", "bluevi01", "bluevi01", "bluevi01", "bluevi01", "bluevi01", "bluevi01", "bluevi01", 
+#> "bluevi01", "bluevi01", "bluevi01", "otisam01", "otisam01", "otisam01", "otisam01", "otisam01", "otisam01", "otisam01", "otisam01", "otisam01", "otisam01", "otisam01", "otisam01", "otisam01", "otisam01", "otisam01", "otisam01", "otisam01", "bondsbo01", "bondsbo01", "bondsbo01", "bondsbo01", "bondsbo01", "bondsbo01", "bondsbo01", "bondsbo01", "bondsbo01", "bondsbo01", "bondsbo01", "bondsbo01", "bondsbo01", "bondsbo01", "bondsbo01", "daviswi02", "daviswi02", "daviswi02", "daviswi02", "daviswi02", "daviswi02", 
+#> "daviswi02", "daviswi02", "daviswi02", "daviswi02", "daviswi02", "daviswi02", "daviswi02", "daviswi02", "daviswi02", "daviswi02", "daviswi02", "daviswi02", "daviswi02", "harrebu01", "harrebu01", "harrebu01", "harrebu01", "harrebu01", "harrebu01", "harrebu01", "harrebu01", "harrebu01", "harrebu01", "harrebu01", "harrebu01", "harrebu01", "harrebu01", "harrebu01", "harrebu01", "chambch01", "chambch01", "chambch01", "chambch01", "chambch01", "chambch01", "chambch01", "chambch01", "chambch01", "chambch01", 
+#> "chambch01", "chambch01", "chambch01", "chambch01", "chambch01", "chambch01", "chambch01", "chambch01", "williea02", "williea02", "williea02", "williea02", "williea02", "williea02", "williea02", "williea02", "williea02", "rojasco01", "rojasco01", "rojasco01", "rojasco01", "rojasco01", "rojasco01", "rojasco01", "rojasco01", "rojasco01", "rojasco01", "rojasco01", "rojasco01", "rojasco01", "rojasco01", "rojasco01", "rojasco01", "rojasco01", "murcebo01", "murcebo01", "murcebo01", "murcebo01", "murcebo01", 
+#> "murcebo01", "murcebo01", "murcebo01", "murcebo01", "murcebo01", "murcebo01", "murcebo01", "murcebo01", "murcebo01", "murcebo01", "murcebo01", "murcebo01", "murcebo01", "retteme01", "retteme01", "retteme01", "retteme01", "retteme01", "retteme01", "retteme01", "retteme01", "retteme01", "retteme01", "retteme01", "retteme01", "retteme01", "palmeji01", "palmeji01", "palmeji01", "palmeji01", "palmeji01", "palmeji01", "palmeji01", "palmeji01", "palmeji01", "palmeji01", "palmeji01", "palmeji01", "palmeji01", 
+#> "palmeji01", "palmeji01", "palmeji01", "palmeji01", "palmeji01", "palmeji01", "mayle01", "mayle01", "mayle01", "mayle01", "mayle01", "mayle01", "mayle01", "mayle01", "mayle01", "mayle01", "mayle01", "mayle01", "mayle01", "mayle01", "mayle01", "mayle01", "mayle01", "mayle01", "sanguma01", "sanguma01", "sanguma01", "sanguma01", "sanguma01", "sanguma01", "sanguma01", "sanguma01", "sanguma01", "sanguma01", "sanguma01", "sanguma01", "sanguma01", "sandeke01", "sandeke01", "sandeke01", "sandeke01", "sandeke01", 
+#> "sandeke01", "sandeke01", "sandeke01", "sandeke01", "sandeke01", "sandeke01", "sandeke01", "sandeke01", "sandeke01", "giustda01", "giustda01", "giustda01", "giustda01", "giustda01", "giustda01", "giustda01", "giustda01", "giustda01", "giustda01", "giustda01", "giustda01", "giustda01", "giustda01", "giustda01", "giustda01", "morgajo02", "morgajo02", "morgajo02", "morgajo02", "morgajo02", "morgajo02", "morgajo02", "morgajo02", "morgajo02", "morgajo02", "morgajo02", "morgajo02", "morgajo02", "morgajo02", 
+#> "morgajo02", "morgajo02", "morgajo02", "morgajo02", "morgajo02", "morgajo02", "morgajo02", "morgajo02", "tenacge01", "tenacge01", "tenacge01", "tenacge01", "tenacge01", "tenacge01", "tenacge01", "tenacge01", "tenacge01", "tenacge01", "tenacge01", "tenacge01", "tenacge01", "tenacge01", "tenacge01", "perryga01", "perryga01", "perryga01", "perryga01", "perryga01", "perryga01", "perryga01", "perryga01", "perryga01", "perryga01", "perryga01", "perryga01", "perryga01", "perryga01", "perryga01", "perryga01", 
+#> "perryga01", "perryga01", "perryga01", "perryga01", "perryga01", "perryga01", "perryga01", "perryga01", "perryga01", "griffdo01", "griffdo01", "griffdo01", "griffdo01", "griffdo01", "griffdo01", "griffdo01", "griffdo01", "fiskca01", "fiskca01", "fiskca01", "fiskca01", "fiskca01", "fiskca01", "fiskca01", "fiskca01", "fiskca01", "fiskca01", "fiskca01", "fiskca01", "fiskca01", "fiskca01", "fiskca01", "fiskca01", "fiskca01", "fiskca01", "fiskca01", "fiskca01", "fiskca01", "fiskca01", "fiskca01", "fiskca01", 
+#> "brinked01", "brinked01", "brinked01", "brinked01", "brinked01", "brinked01", "brinked01", "brinked01", "brinked01", "brinked01", "brinked01", "brinked01", "brinked01", "brinked01", "brinked01", "brinked01", "brinked01", "cedence01", "cedence01", "cedence01", "cedence01", "cedence01", "cedence01", "cedence01", "cedence01", "cedence01", "cedence01", "cedence01", "cedence01", "cedence01", "cedence01", "cedence01", "cedence01", "cedence01", "cedence01", "bowala01", "bowala01", "bowala01", "bowala01", 
+#> "bowala01", "bowala01", "bowala01", "bowala01", "bowala01", "bowala01", "bowala01", "bowala01", "bowala01", "bowala01", "bowala01", "bowala01", "bowala01", "matlajo01", "matlajo01", "matlajo01", "matlajo01", "matlajo01", "matlajo01", "matlajo01", "matlajo01", "matlajo01", "matlajo01", "matlajo01", "matlajo01", "matlajo01", "rudijo01", "rudijo01", "rudijo01", "rudijo01", "rudijo01", "rudijo01", "rudijo01", "rudijo01", "rudijo01", "rudijo01", "rudijo01", "rudijo01", "rudijo01", "rudijo01", "rudijo01", 
+#> "rudijo01", "scheiri01", "scheiri01", "scheiri01", "scheiri01", "scheiri01", "scheiri01", "scheiri01", "scheiri01", "scheiri01", "scheiri01", "scheiri01", "speiech01", "speiech01", "speiech01", "speiech01", "speiech01", "speiech01", "speiech01", "speiech01", "speiech01", "speiech01", "speiech01", "speiech01", "speiech01", "speiech01", "speiech01", "speiech01", "speiech01", "speiech01", "speiech01", "speiech01", "speiech01", "speiech01", "lylesp01", "lylesp01", "lylesp01", "lylesp01", "lylesp01", 
+#> "lylesp01", "lylesp01", "lylesp01", "lylesp01", "lylesp01", "lylesp01", "lylesp01", "lylesp01", "lylesp01", "lylesp01", "lylesp01", "lylesp01", "lylesp01", "carrocl02", "carrocl02", "carrocl02", "carrocl02", "carrocl02", "carrocl02", "carrocl02", "carrocl02", "carrocl02", "carrocl02", "carrocl02", "carrocl02", "carrocl02", "carrocl02", "carrocl02", "carrocl02", "carrocl02", "campabe01", "campabe01", "campabe01", "campabe01", "campabe01", "campabe01", "campabe01", "campabe01", "campabe01", "campabe01", 
+#> "campabe01", "campabe01", "campabe01", "campabe01", "campabe01", "campabe01", "campabe01", "campabe01", "campabe01", "campabe01", "grichbo01", "grichbo01", "grichbo01", "grichbo01", "grichbo01", "grichbo01", "grichbo01", "grichbo01", "grichbo01", "grichbo01", "grichbo01", "grichbo01", "grichbo01", "grichbo01", "grichbo01", "grichbo01", "grichbo01", "jorgemi01", "jorgemi01", "jorgemi01", "jorgemi01", "jorgemi01", "jorgemi01", "jorgemi01", "jorgemi01", "jorgemi01", "jorgemi01", "jorgemi01", "jorgemi01", 
+#> "jorgemi01", "jorgemi01", "jorgemi01", "jorgemi01", "jorgemi01", "jorgemi01", "jorgemi01", "jorgemi01", "metzgro01", "metzgro01", "metzgro01", "metzgro01", "metzgro01", "metzgro01", "metzgro01", "metzgro01", "metzgro01", "metzgro01", "metzgro01", "metzgro01", "hillejo01", "hillejo01", "hillejo01", "hillejo01", "hillejo01", "hillejo01", "hillejo01", "hillejo01", "hillejo01", "hillejo01", "hillejo01", "hillejo01", "hillejo01", "hillejo01", "hillejo01", "bumbral01", "bumbral01", "bumbral01", "bumbral01", 
+#> "bumbral01", "bumbral01", "bumbral01", "bumbral01", "bumbral01", "bumbral01", "bumbral01", "bumbral01", "bumbral01", "bumbral01", "matthga01", "matthga01", "matthga01", "matthga01", "matthga01", "matthga01", "matthga01", "matthga01", "matthga01", "matthga01", "matthga01", "matthga01", "matthga01", "matthga01", "matthga01", "matthga01", "matthga01", "maybejo01", "maybejo01", "maybejo01", "maybejo01", "maybejo01", "maybejo01", "maybejo01", "maybejo01", "maybejo01", "maybejo01", "maybejo01", "maybejo01", 
+#> "maybejo01", "maybejo01", "maybejo01", "maybejo01", "bandosa01", "bandosa01", "bandosa01", "bandosa01", "bandosa01", "bandosa01", "bandosa01", "bandosa01", "bandosa01", "bandosa01", "bandosa01", "bandosa01", "bandosa01", "bandosa01", "bandosa01", "bandosa01", "holtzke01", "holtzke01", "holtzke01", "holtzke01", "holtzke01", "holtzke01", "holtzke01", "holtzke01", "holtzke01", "holtzke01", "holtzke01", "holtzke01", "holtzke01", "holtzke01", "holtzke01", "holtzke01", "holtzke01", "evansda01", "evansda01", 
+#> "evansda01", "evansda01", "evansda01", "evansda01", "evansda01", "evansda01", "evansda01", "evansda01", "evansda01", "evansda01", "evansda01", "evansda01", "evansda01", "evansda01", "evansda01", "evansda01", "evansda01", "evansda01", "evansda01", "evansda01", "bryanro01", "bryanro01", "bryanro01", "bryanro01", "bryanro01", "bryanro01", "bryanro01", "bryanro01", "russebi01", "russebi01", "russebi01", "russebi01", "russebi01", "russebi01", "russebi01", "russebi01", "russebi01", "russebi01", "russebi01", 
+#> "russebi01", "russebi01", "russebi01", "russebi01", "russebi01", "russebi01", "russebi01", "marshmi01", "marshmi01", "marshmi01", "marshmi01", "marshmi01", "marshmi01", "marshmi01", "marshmi01", "marshmi01", "marshmi01", "marshmi01", "marshmi01", "marshmi01", "marshmi01", "marshmi01", "marshmi01", "marshmi01", "garvest01", "garvest01", "garvest01", "garvest01", "garvest01", "garvest01", "garvest01", "garvest01", "garvest01", "garvest01", "garvest01", "garvest01", "garvest01", "garvest01", "garvest01", 
+#> "garvest01", "garvest01", "garvest01", "garvest01", "greendi01", "greendi01", "greendi01", "greendi01", "greendi01", "greendi01", "greendi01", "greendi01", "greendi01", "greendi01", "greendi01", "greendi01", "hunteca01", "hunteca01", "hunteca01", "hunteca01", "hunteca01", "hunteca01", "hunteca01", "hunteca01", "hunteca01", "hunteca01", "hunteca01", "hunteca01", "hunteca01", "hunteca01", "hunteca01", "geronce01", "geronce01", "geronce01", "geronce01", "geronce01", "geronce01", "geronce01", "geronce01", 
+#> "geronce01", "geronce01", "geronce01", "geronce01", "geronce01", "geronce01", "geronce01", "messean01", "messean01", "messean01", "messean01", "messean01", "messean01", "messean01", "messean01", "messean01", "messean01", "messean01", "messean01", "conceda01", "conceda01", "conceda01", "conceda01", "conceda01", "conceda01", "conceda01", "conceda01", "conceda01", "conceda01", "conceda01", "conceda01", "conceda01", "conceda01", "conceda01", "conceda01", "conceda01", "conceda01", "conceda01", "thompda01", 
+#> "thompda01", "thompda01", "thompda01", "thompda01", "thompda01", "thompda01", "thompda01", "burroje01", "burroje01", "burroje01", "burroje01", "burroje01", "burroje01", "burroje01", "burroje01", "burroje01", "burroje01", "burroje01", "burroje01", "burroje01", "burroje01", "burroje01", "burroje01", "hargrmi01", "hargrmi01", "hargrmi01", "hargrmi01", "hargrmi01", "hargrmi01", "hargrmi01", "hargrmi01", "hargrmi01", "hargrmi01", "hargrmi01", "hargrmi01", "hargrmi01", "mcbriba01", "mcbriba01", "mcbriba01", 
+#> "mcbriba01", "mcbriba01", "mcbriba01", "mcbriba01", "mcbriba01", "mcbriba01", "mcbriba01", "mcbriba01", "mcbriba01", "schmimi01", "schmimi01", "schmimi01", "schmimi01", "schmimi01", "schmimi01", "schmimi01", "schmimi01", "schmimi01", "schmimi01", "schmimi01", "schmimi01", "schmimi01", "schmimi01", "schmimi01", "schmimi01", "schmimi01", "schmimi01", "gulledo01", "gulledo01", "gulledo01", "gulledo01", "gulledo01", "gulledo01", "gulledo01", "gulledo01", "gulledo01", "ziskri01", "ziskri01", "ziskri01", 
+#> "ziskri01", "ziskri01", "ziskri01", "ziskri01", "ziskri01", "ziskri01", "ziskri01", "ziskri01", "ziskri01", "ziskri01", "forstte01", "forstte01", "forstte01", "forstte01", "forstte01", "forstte01", "forstte01", "forstte01", "forstte01", "forstte01", "forstte01", "forstte01", "forstte01", "forstte01", "forstte01", "forstte01", "fingero01", "fingero01", "fingero01", "fingero01", "fingero01", "fingero01", "fingero01", "fingero01", "fingero01", "fingero01", "fingero01", "fingero01", "fingero01", "fingero01", 
+#> "fingero01", "fingero01", "fingero01", "madlobi01", "madlobi01", "madlobi01", "madlobi01", "madlobi01", "madlobi01", "madlobi01", "madlobi01", "madlobi01", "madlobi01", "madlobi01", "madlobi01", "madlobi01", "madlobi01", "madlobi01", "madlobi01", "madlobi01", "madlobi01", "tiantlu01", "tiantlu01", "tiantlu01", "tiantlu01", "tiantlu01", "tiantlu01", "tiantlu01", "tiantlu01", "tiantlu01", "tiantlu01", "tiantlu01", "tiantlu01", "tiantlu01", "tiantlu01", "tiantlu01", "tiantlu01", "tiantlu01", "tiantlu01", 
+#> "tiantlu01", "lynnfr01", "lynnfr01", "lynnfr01", "lynnfr01", "lynnfr01", "lynnfr01", "lynnfr01", "lynnfr01", "lynnfr01", "lynnfr01", "lynnfr01", "lynnfr01", "lynnfr01", "lynnfr01", "lynnfr01", "lynnfr01", "lynnfr01", "lynnfr01", "reitzke01", "reitzke01", "reitzke01", "reitzke01", "reitzke01", "reitzke01", "reitzke01", "reitzke01", "reitzke01", "reitzke01", "reitzke01", "maddoga01", "maddoga01", "maddoga01", "maddoga01", "maddoga01", "maddoga01", "maddoga01", "maddoga01", "maddoga01", "maddoga01", 
+#> "maddoga01", "maddoga01", "maddoga01", "maddoga01", "maddoga01", "maddoga01", "nolanga01", "nolanga01", "nolanga01", "nolanga01", "nolanga01", "nolanga01", "nolanga01", "nolanga01", "nolanga01", "nolanga01", "nolanga01", "montejo01", "montejo01", "montejo01", "montejo01", "montejo01", "montejo01", "montejo01", "montejo01", "montejo01", "montejo01", "montejo01", "montejo01", "montejo01", "montejo01", "nettlgr01", "nettlgr01", "nettlgr01", "nettlgr01", "nettlgr01", "nettlgr01", "nettlgr01", "nettlgr01", 
+#> "nettlgr01", "nettlgr01", "nettlgr01", "nettlgr01", "nettlgr01", "nettlgr01", "nettlgr01", "nettlgr01", "nettlgr01", "nettlgr01", "nettlgr01", "nettlgr01", "nettlgr01", "nettlgr01", "riceji01", "riceji01", "riceji01", "riceji01", "riceji01", "riceji01", "riceji01", "riceji01", "riceji01", "riceji01", "riceji01", "riceji01", "riceji01", "riceji01", "riceji01", "riceji01", "harrato01", "harrato01", "harrato01", "harrato01", "harrato01", "harrato01", "harrato01", "harrato01", "harrato01", "harrato01", 
+#> "harrato01", "harrato01", "harrato01", "harrato01", "harrato01", "harrato01", "harrato01", "jonesra01", "jonesra01", "jonesra01", "jonesra01", "jonesra01", "jonesra01", "jonesra01", "jonesra01", "jonesra01", "jonesra01", "luzingr01", "luzingr01", "luzingr01", "luzingr01", "luzingr01", "luzingr01", "luzingr01", "luzingr01", "luzingr01", "luzingr01", "luzingr01", "luzingr01", "luzingr01", "luzingr01", "luzingr01", "oliveal01", "oliveal01", "oliveal01", "oliveal01", "oliveal01", "oliveal01", "oliveal01", 
+#> "oliveal01", "oliveal01", "oliveal01", "oliveal01", "oliveal01", "oliveal01", "oliveal01", "oliveal01", "oliveal01", "oliveal01", "oliveal01", "oliveal01", "oliveal01", "parkeda01", "parkeda01", "parkeda01", "parkeda01", "parkeda01", "parkeda01", "parkeda01", "parkeda01", "parkeda01", "parkeda01", "parkeda01", "parkeda01", "parkeda01", "parkeda01", "parkeda01", "parkeda01", "parkeda01", "parkeda01", "parkeda01", "parkeda01", "gossari01", "gossari01", "gossari01", "gossari01", "gossari01", "gossari01", 
+#> "gossari01", "gossari01", "gossari01", "gossari01", "gossari01", "gossari01", "gossari01", "gossari01", "gossari01", "gossari01", "gossari01", "gossari01", "gossari01", "gossari01", "gossari01", "gossari01", "gossari01", "hraboal01", "hraboal01", "hraboal01", "hraboal01", "hraboal01", "hraboal01", "hraboal01", "hraboal01", "hraboal01", "hraboal01", "hraboal01", "hraboal01", "hraboal01", "fostege01", "fostege01", "fostege01", "fostege01", "fostege01", "fostege01", "fostege01", "fostege01", "fostege01", 
+#> "fostege01", "fostege01", "fostege01", "fostege01", "fostege01", "fostege01", "fostege01", "fostege01", "fostege01", "fostege01", "fostege01", "rodriau01", "rodriau01", "rodriau01", "rodriau01", "rodriau01", "rodriau01", "rodriau01", "rodriau01", "rodriau01", "rodriau01", "rodriau01", "rodriau01", "rodriau01", "rodriau01", "rodriau01", "rodriau01", "rodriau01", "rodriau01", "rodriau01", "rodriau01", "sundbji01", "sundbji01", "sundbji01", "sundbji01", "sundbji01", "sundbji01", "sundbji01", "sundbji01", 
+#> "sundbji01", "sundbji01", "sundbji01", "sundbji01", "sundbji01", "sundbji01", "sundbji01", "sundbji01", "sundbji01", "evansdw01", "evansdw01", "evansdw01", "evansdw01", "evansdw01", "evansdw01", "evansdw01", "evansdw01", "evansdw01", "evansdw01", "evansdw01", "evansdw01", "evansdw01", "evansdw01", "evansdw01", "evansdw01", "evansdw01", "evansdw01", "evansdw01", "evansdw01", "manniri01", "manniri01", "manniri01", "manniri01", "manniri01", "manniri01", "manniri01", "manniri01", "manniri01", "manniri01", 
+#> "manniri01", "manniri01", "manniri01", "manniri01", "johnto01", "johnto01", "johnto01", "johnto01", "johnto01", "johnto01", "johnto01", "johnto01", "johnto01", "johnto01", "johnto01", "johnto01", "johnto01", "johnto01", "johnto01", "johnto01", "johnto01", "johnto01", "johnto01", "johnto01", "johnto01", "johnto01", "johnto01", "johnto01", "johnto01", "johnto01", "johnto01", "johnto01", "suttodo01", "suttodo01", "suttodo01", "suttodo01", "suttodo01", "suttodo01", "suttodo01", "suttodo01", "suttodo01", 
+#> "suttodo01", "suttodo01", "suttodo01", "suttodo01", "suttodo01", "suttodo01", "suttodo01", "suttodo01", "suttodo01", "suttodo01", "suttodo01", "suttodo01", "suttodo01", "suttodo01", "suttodo01", "suttodo01", "campbbi02", "campbbi02", "campbbi02", "campbbi02", "campbbi02", "campbbi02", "campbbi02", "campbbi02", "campbbi02", "campbbi02", "campbbi02", "campbbi02", "campbbi02", "campbbi02", "campbbi02", "eastwra01", "eastwra01", "eastwra01", "eastwra01", "eastwra01", "eastwra01", "eastwra01", "eastwra01", 
+#> "eastwra01", "eastwra01", "fidryma01", "fidryma01", "fidryma01", "fidryma01", "fidryma01", "metzgbu01", "metzgbu01", "metzgbu01", "metzgbu01", "metzgbu01", "metzgbu01", "zachrpa01", "zachrpa01", "zachrpa01", "zachrpa01", "zachrpa01", "zachrpa01", "zachrpa01", "zachrpa01", "zachrpa01", "zachrpa01", "zachrpa01", "brettge01", "brettge01", "brettge01", "brettge01", "brettge01", "brettge01", "brettge01", "brettge01", "brettge01", "brettge01", "brettge01", "brettge01", "brettge01", "brettge01", "brettge01", 
+#> "brettge01", "brettge01", "brettge01", "brettge01", "brettge01", "brettge01", "mcraeha01", "mcraeha01", "mcraeha01", "mcraeha01", "mcraeha01", "mcraeha01", "mcraeha01", "mcraeha01", "mcraeha01", "mcraeha01", "mcraeha01", "mcraeha01", "mcraeha01", "mcraeha01", "mcraeha01", "mcraeha01", "mcraeha01", "mcraeha01", "mcraeha01", "tananfr01", "tananfr01", "tananfr01", "tananfr01", "tananfr01", "tananfr01", "tananfr01", "tananfr01", "tananfr01", "tananfr01", "tananfr01", "tananfr01", "tananfr01", "tananfr01", 
+#> "tananfr01", "tananfr01", "tananfr01", "tananfr01", "tananfr01", "tananfr01", "tananfr01", "tananfr01", "tananfr01", "rivermi01", "rivermi01", "rivermi01", "rivermi01", "rivermi01", "rivermi01", "rivermi01", "rivermi01", "rivermi01", "rivermi01", "rivermi01", "rivermi01", "rivermi01", "rivermi01", "rivermi01", "rivermi01", "montawi01", "montawi01", "montawi01", "montawi01", "montawi01", "montawi01", "montawi01", "montawi01", "montawi01", "montawi01", "montawi01", "montawi01", "montawi01", "montawi01", 
+#> "montawi01", "montawi01", "montawi01", "montawi01", "montawi01", "montawi01", "boonebo01", "boonebo01", "boonebo01", "boonebo01", "boonebo01", "boonebo01", "boonebo01", "boonebo01", "boonebo01", "boonebo01", "boonebo01", "boonebo01", "boonebo01", "boonebo01", "boonebo01", "boonebo01", "boonebo01", "boonebo01", "boonebo01", "griffke01", "griffke01", "griffke01", "griffke01", "griffke01", "griffke01", "griffke01", "griffke01", "griffke01", "griffke01", "griffke01", "griffke01", "griffke01", "griffke01", 
+#> "griffke01", "griffke01", "griffke01", "griffke01", "griffke01", "griffke01", "griffke01", "griffke01", "whitefr01", "whitefr01", "whitefr01", "whitefr01", "whitefr01", "whitefr01", "whitefr01", "whitefr01", "whitefr01", "whitefr01", "whitefr01", "whitefr01", "whitefr01", "whitefr01", "whitefr01", "whitefr01", "whitefr01", "whitefr01", "beniqju01", "beniqju01", "beniqju01", "beniqju01", "beniqju01", "beniqju01", "beniqju01", "beniqju01", "beniqju01", "beniqju01", "beniqju01", "beniqju01", "beniqju01", 
+#> "beniqju01", "beniqju01", "beniqju01", "beniqju01", "beniqju01", "cowenal01", "cowenal01", "cowenal01", "cowenal01", "cowenal01", "cowenal01", "cowenal01", "cowenal01", "cowenal01", "cowenal01", "cowenal01", "cowenal01", "cowenal01", "cowenal01", "bakerdu01", "bakerdu01", "bakerdu01", "bakerdu01", "bakerdu01", "bakerdu01", "bakerdu01", "bakerdu01", "bakerdu01", "bakerdu01", "bakerdu01", "bakerdu01", "bakerdu01", "bakerdu01", "bakerdu01", "bakerdu01", "bakerdu01", "bakerdu01", "bakerdu01", "murraed02", 
+#> "murraed02", "murraed02", "murraed02", "murraed02", "murraed02", "murraed02", "murraed02", "murraed02", "murraed02", "murraed02", "murraed02", "murraed02", "murraed02", "murraed02", "murraed02", "murraed02", "murraed02", "murraed02", "murraed02", "murraed02", "murraed02", "murraed02", "dawsoan01", "dawsoan01", "dawsoan01", "dawsoan01", "dawsoan01", "dawsoan01", "dawsoan01", "dawsoan01", "dawsoan01", "dawsoan01", "dawsoan01", "dawsoan01", "dawsoan01", "dawsoan01", "dawsoan01", "dawsoan01", "dawsoan01", 
+#> "dawsoan01", "dawsoan01", "dawsoan01", "dawsoan01", "randowi01", "randowi01", "randowi01", "randowi01", "randowi01", "randowi01", "randowi01", "randowi01", "randowi01", "randowi01", "randowi01", "randowi01", "randowi01", "randowi01", "randowi01", "randowi01", "randowi01", "randowi01", "randowi01", "hislela01", "hislela01", "hislela01", "hislela01", "hislela01", "hislela01", "hislela01", "hislela01", "hislela01", "hislela01", "hislela01", "hislela01", "hislela01", "hislela01", "ryanno01", "ryanno01", 
+#> "ryanno01", "ryanno01", "ryanno01", "ryanno01", "ryanno01", "ryanno01", "ryanno01", "ryanno01", "ryanno01", "ryanno01", "ryanno01", "ryanno01", "ryanno01", "ryanno01", "ryanno01", "ryanno01", "ryanno01", "ryanno01", "ryanno01", "ryanno01", "ryanno01", "ryanno01", "ryanno01", "ryanno01", "ryanno01", "burleri01", "burleri01", "burleri01", "burleri01", "burleri01", "burleri01", "burleri01", "burleri01", "burleri01", "burleri01", "burleri01", "burleri01", "burleri01", "simmote01", "simmote01", "simmote01", 
+#> "simmote01", "simmote01", "simmote01", "simmote01", "simmote01", "simmote01", "simmote01", "simmote01", "simmote01", "simmote01", "simmote01", "simmote01", "simmote01", "simmote01", "simmote01", "simmote01", "simmote01", "simmote01", "reuscri01", "reuscri01", "reuscri01", "reuscri01", "reuscri01", "reuscri01", "reuscri01", "reuscri01", "reuscri01", "reuscri01", "reuscri01", "reuscri01", "reuscri01", "reuscri01", "reuscri01", "reuscri01", "reuscri01", "reuscri01", "reuscri01", "reuscri01", "reuscri01", 
+#> "templga01", "templga01", "templga01", "templga01", "templga01", "templga01", "templga01", "templga01", "templga01", "templga01", "templga01", "templga01", "templga01", "templga01", "templga01", "templga01", "templga01", "dentbu01", "dentbu01", "dentbu01", "dentbu01", "dentbu01", "dentbu01", "dentbu01", "dentbu01", "dentbu01", "dentbu01", "dentbu01", "dentbu01", "dentbu01", "guidrro01", "guidrro01", "guidrro01", "guidrro01", "guidrro01", "guidrro01", "guidrro01", "guidrro01", "guidrro01", "guidrro01", 
+#> "guidrro01", "guidrro01", "guidrro01", "guidrro01", "milleri01", "milleri01", "milleri01", "milleri01", "milleri01", "milleri01", "milleri01", "milleri01", "milleri01", "milleri01", "milleri01", "milleri01", "milleri01", "milleri01", "milleri01", "hernake01", "hernake01", "hernake01", "hernake01", "hernake01", "hernake01", "hernake01", "hernake01", "hernake01", "hernake01", "hernake01", "hernake01", "hernake01", "hernake01", "hernake01", "hernake01", "hernake01", "hernake01", "lopesda01", "lopesda01", 
+#> "lopesda01", "lopesda01", "lopesda01", "lopesda01", "lopesda01", "lopesda01", "lopesda01", "lopesda01", "lopesda01", "lopesda01", "lopesda01", "lopesda01", "lopesda01", "lopesda01", "lopesda01", "lopesda01", "valenel01", "valenel01", "valenel01", "valenel01", "valenel01", "valenel01", "valenel01", "valenel01", "valenel01", "valenel01", "valenel01", "niekrph01", "niekrph01", "niekrph01", "niekrph01", "niekrph01", "niekrph01", "niekrph01", "niekrph01", "niekrph01", "niekrph01", "niekrph01", "niekrph01", 
+#> "niekrph01", "niekrph01", "niekrph01", "niekrph01", "niekrph01", "niekrph01", "niekrph01", "niekrph01", "niekrph01", "niekrph01", "niekrph01", "niekrph01", "niekrph01", "niekrph01", "whitalo01", "whitalo01", "whitalo01", "whitalo01", "whitalo01", "whitalo01", "whitalo01", "whitalo01", "whitalo01", "whitalo01", "whitalo01", "whitalo01", "whitalo01", "whitalo01", "whitalo01", "whitalo01", "whitalo01", "whitalo01", "whitalo01", "hornebo01", "hornebo01", "hornebo01", "hornebo01", "hornebo01", "hornebo01", 
+#> "hornebo01", "hornebo01", "hornebo01", "hornebo01", "staubru01", "staubru01", "staubru01", "staubru01", "staubru01", "staubru01", "staubru01", "staubru01", "staubru01", "staubru01", "staubru01", "staubru01", "staubru01", "staubru01", "staubru01", "staubru01", "staubru01", "staubru01", "staubru01", "staubru01", "staubru01", "staubru01", "staubru01", "staubru01", "yountro01", "yountro01", "yountro01", "yountro01", "yountro01", "yountro01", "yountro01", "yountro01", "yountro01", "yountro01", "yountro01", 
+#> "yountro01", "yountro01", "yountro01", "yountro01", "yountro01", "yountro01", "yountro01", "yountro01", "yountro01", "clarkja01", "clarkja01", "clarkja01", "clarkja01", "clarkja01", "clarkja01", "clarkja01", "clarkja01", "clarkja01", "clarkja01", "clarkja01", "clarkja01", "clarkja01", "clarkja01", "clarkja01", "clarkja01", "clarkja01", "clarkja01", "flanami01", "flanami01", "flanami01", "flanami01", "flanami01", "flanami01", "flanami01", "flanami01", "flanami01", "flanami01", "flanami01", "flanami01", 
+#> "flanami01", "flanami01", "flanami01", "flanami01", "flanami01", "flanami01", "flanami01", "suttebr01", "suttebr01", "suttebr01", "suttebr01", "suttebr01", "suttebr01", "suttebr01", "suttebr01", "suttebr01", "suttebr01", "suttebr01", "suttebr01", "coopece01", "coopece01", "coopece01", "coopece01", "coopece01", "coopece01", "coopece01", "coopece01", "coopece01", "coopece01", "coopece01", "coopece01", "coopece01", "coopece01", "coopece01", "coopece01", "coopece01", "bellbu01", "bellbu01", "bellbu01", 
+#> "bellbu01", "bellbu01", "bellbu01", "bellbu01", "bellbu01", "bellbu01", "bellbu01", "bellbu01", "bellbu01", "bellbu01", "bellbu01", "bellbu01", "bellbu01", "bellbu01", "bellbu01", "bellbu01", "bellbu01", "lezcasi01", "lezcasi01", "lezcasi01", "lezcasi01", "lezcasi01", "lezcasi01", "lezcasi01", "lezcasi01", "lezcasi01", "lezcasi01", "lezcasi01", "lezcasi01", "lezcasi01", "trillma01", "trillma01", "trillma01", "trillma01", "trillma01", "trillma01", "trillma01", "trillma01", "trillma01", "trillma01", 
+#> "trillma01", "trillma01", "trillma01", "trillma01", "trillma01", "trillma01", "trillma01", "trillma01", "winfida01", "winfida01", "winfida01", "winfida01", "winfida01", "winfida01", "winfida01", "winfida01", "winfida01", "winfida01", "winfida01", "winfida01", "winfida01", "winfida01", "winfida01", "winfida01", "winfida01", "winfida01", "winfida01", "winfida01", "winfida01", "winfida01", "winfida01", "baylodo01", "baylodo01", "baylodo01", "baylodo01", "baylodo01", "baylodo01", "baylodo01", "baylodo01", 
+#> "baylodo01", "baylodo01", "baylodo01", "baylodo01", "baylodo01", "baylodo01", "baylodo01", "baylodo01", "baylodo01", "baylodo01", "baylodo01", "baylodo01", "thornan01", "thornan01", "thornan01", "thornan01", "thornan01", "thornan01", "thornan01", "thornan01", "thornan01", "thornan01", "thornan01", "thornan01", "thornan01", "thornan01", "thornan01", "kernji01", "kernji01", "kernji01", "kernji01", "kernji01", "kernji01", "kernji01", "kernji01", "kernji01", "kernji01", "kernji01", "kernji01", "kernji01", 
+#> "kernji01", "kernji01", "castijo01", "castijo01", "castijo01", "castijo01", "castijo01", "castijo01", "griffal01", "griffal01", "griffal01", "griffal01", "griffal01", "griffal01", "griffal01", "griffal01", "griffal01", "griffal01", "griffal01", "griffal01", "griffal01", "griffal01", "griffal01", "griffal01", "griffal01", "griffal01", "sutclri01", "sutclri01", "sutclri01", "sutclri01", "sutclri01", "sutclri01", "sutclri01", "sutclri01", "sutclri01", "sutclri01", "sutclri01", "sutclri01", "sutclri01", 
+#> "sutclri01", "sutclri01", "sutclri01", "sutclri01", "sutclri01", "sutclri01", "porteda02", "porteda02", "porteda02", "porteda02", "porteda02", "porteda02", "porteda02", "porteda02", "porteda02", "porteda02", "porteda02", "porteda02", "porteda02", "porteda02", "porteda02", "porteda02", "porteda02", "singlke01", "singlke01", "singlke01", "singlke01", "singlke01", "singlke01", "singlke01", "singlke01", "singlke01", "singlke01", "singlke01", "singlke01", "singlke01", "singlke01", "singlke01", "smallro02", 
+#> "smallro02", "smallro02", "smallro02", "smallro02", "smallro02", "smallro02", "smallro02", "smallro02", "smallro02", "smallro02", "smallro02", "smallro02", "smallro02", "smallro02", "smallro02", "kingmda01", "kingmda01", "kingmda01", "kingmda01", "kingmda01", "kingmda01", "kingmda01", "kingmda01", "kingmda01", "kingmda01", "kingmda01", "kingmda01", "kingmda01", "kingmda01", "kingmda01", "kingmda01", "kingmda01", "kingmda01", "kingmda01", "morenom01", "morenom01", "morenom01", "morenom01", "morenom01", 
+#> "morenom01", "morenom01", "morenom01", "morenom01", "morenom01", "morenom01", "morenom01", "morenom01", "morenom01", "niekrjo01", "niekrjo01", "niekrjo01", "niekrjo01", "niekrjo01", "niekrjo01", "niekrjo01", "niekrjo01", "niekrjo01", "niekrjo01", "niekrjo01", "niekrjo01", "niekrjo01", "niekrjo01", "niekrjo01", "niekrjo01", "niekrjo01", "niekrjo01", "niekrjo01", "niekrjo01", "niekrjo01", "niekrjo01", "niekrjo01", "niekrjo01", "niekrjo01", "mcgratu01", "mcgratu01", "mcgratu01", "mcgratu01", "mcgratu01", 
+#> "mcgratu01", "mcgratu01", "mcgratu01", "mcgratu01", "mcgratu01", "mcgratu01", "mcgratu01", "mcgratu01", "mcgratu01", "mcgratu01", "mcgratu01", "mcgratu01", "mcgratu01", "mcgratu01", "stonest01", "stonest01", "stonest01", "stonest01", "stonest01", "stonest01", "stonest01", "stonest01", "stonest01", "stonest01", "stonest01", "murphdw01", "murphdw01", "murphdw01", "murphdw01", "murphdw01", "murphdw01", "murphdw01", "murphdw01", "murphdw01", "murphdw01", "murphdw01", "murphdw01", "wilsowi02", "wilsowi02", 
+#> "wilsowi02", "wilsowi02", "wilsowi02", "wilsowi02", "wilsowi02", "wilsowi02", "wilsowi02", "wilsowi02", "wilsowi02", "wilsowi02", "wilsowi02", "wilsowi02", "wilsowi02", "wilsowi02", "wilsowi02", "wilsowi02", "wilsowi02", "norrimi01", "norrimi01", "norrimi01", "norrimi01", "norrimi01", "norrimi01", "norrimi01", "norrimi01", "norrimi01", "norrimi01", "trammal01", "trammal01", "trammal01", "trammal01", "trammal01", "trammal01", "trammal01", "trammal01", "trammal01", "trammal01", "trammal01", "trammal01", 
+#> "trammal01", "trammal01", "trammal01", "trammal01", "trammal01", "trammal01", "trammal01", "trammal01", "flynndo01", "flynndo01", "flynndo01", "flynndo01", "flynndo01", "flynndo01", "flynndo01", "flynndo01", "flynndo01", "flynndo01", "flynndo01", "flynndo01", "flynndo01", "flynndo01", "cartega01", "cartega01", "cartega01", "cartega01", "cartega01", "cartega01", "cartega01", "cartega01", "cartega01", "cartega01", "cartega01", "cartega01", "cartega01", "cartega01", "cartega01", "cartega01", "cartega01", 
+#> "cartega01", "cartega01", "smithoz01", "smithoz01", "smithoz01", "smithoz01", "smithoz01", "smithoz01", "smithoz01", "smithoz01", "smithoz01", "smithoz01", "smithoz01", "smithoz01", "smithoz01", "smithoz01", "smithoz01", "smithoz01", "smithoz01", "smithoz01", "smithoz01", "quiseda01", "quiseda01", "quiseda01", "quiseda01", "quiseda01", "quiseda01", "quiseda01", "quiseda01", "quiseda01", "quiseda01", "quiseda01", "quiseda01", "quiseda01", "charbjo01", "charbjo01", "charbjo01", "howest01", "howest01", 
+#> "howest01", "howest01", "howest01", "howest01", "howest01", "howest01", "howest01", "howest01", "howest01", "howest01", "howest01", "parrila02", "parrila02", "parrila02", "parrila02", "parrila02", "parrila02", "parrila02", "parrila02", "parrila02", "parrila02", "parrila02", "parrila02", "parrila02", "parrila02", "parrila02", "parrila02", "parrila02", "parrila02", "parrila02", "parrila02", "oglivbe01", "oglivbe01", "oglivbe01", "oglivbe01", "oglivbe01", "oglivbe01", "oglivbe01", "oglivbe01", "oglivbe01", 
+#> "oglivbe01", "oglivbe01", "oglivbe01", "oglivbe01", "oglivbe01", "oglivbe01", "oglivbe01", "hendrge01", "hendrge01", "hendrge01", "hendrge01", "hendrge01", "hendrge01", "hendrge01", "hendrge01", "hendrge01", "hendrge01", "hendrge01", "hendrge01", "hendrge01", "hendrge01", "hendrge01", "hendrge01", "hendrge01", "hendrge01", "hendrge01", "hendrge01", "forscbo01", "forscbo01", "forscbo01", "forscbo01", "forscbo01", "forscbo01", "forscbo01", "forscbo01", "forscbo01", "forscbo01", "forscbo01", "forscbo01", 
+#> "forscbo01", "forscbo01", "forscbo01", "forscbo01", "forscbo01", "ceronri01", "ceronri01", "ceronri01", "ceronri01", "ceronri01", "ceronri01", "ceronri01", "ceronri01", "ceronri01", "ceronri01", "ceronri01", "ceronri01", "ceronri01", "ceronri01", "ceronri01", "ceronri01", "ceronri01", "ceronri01", "bibbyji01", "bibbyji01", "bibbyji01", "bibbyji01", "bibbyji01", "bibbyji01", "bibbyji01", "bibbyji01", "bibbyji01", "bibbyji01", "bibbyji01", "bibbyji01", "bibbyji01", "bibbyji01", "humeto01", "humeto01", 
+#> "humeto01", "humeto01", "humeto01", "humeto01", "humeto01", "humeto01", "humeto01", "humeto01", "humeto01", "humeto01", "ceyro01", "ceyro01", "ceyro01", "ceyro01", "ceyro01", "ceyro01", "ceyro01", "ceyro01", "ceyro01", "ceyro01", "ceyro01", "ceyro01", "ceyro01", "ceyro01", "ceyro01", "ceyro01", "ceyro01", "valenfe01", "valenfe01", "valenfe01", "valenfe01", "valenfe01", "valenfe01", "valenfe01", "valenfe01", "valenfe01", "valenfe01", "valenfe01", "valenfe01", "valenfe01", "valenfe01", "valenfe01", 
+#> "valenfe01", "valenfe01", "valenfe01", "squirmi01", "squirmi01", "squirmi01", "squirmi01", "squirmi01", "squirmi01", "squirmi01", "squirmi01", "squirmi01", "squirmi01", "henderi01", "henderi01", "henderi01", "henderi01", "henderi01", "henderi01", "henderi01", "henderi01", "henderi01", "henderi01", "henderi01", "henderi01", "henderi01", "henderi01", "henderi01", "henderi01", "henderi01", "henderi01", "henderi01", "henderi01", "henderi01", "henderi01", "henderi01", "henderi01", "henderi01", "henderi01", 
+#> "henderi01", "henderi01", "henderi01", "hootobu01", "hootobu01", "hootobu01", "hootobu01", "hootobu01", "hootobu01", "hootobu01", "hootobu01", "hootobu01", "hootobu01", "hootobu01", "hootobu01", "hootobu01", "hootobu01", "hootobu01", "hootobu01", "righeda01", "righeda01", "righeda01", "righeda01", "righeda01", "righeda01", "righeda01", "righeda01", "righeda01", "righeda01", "righeda01", "righeda01", "righeda01", "righeda01", "righeda01", "righeda01", "righeda01", "lansfca01", "lansfca01", "lansfca01", 
+#> "lansfca01", "lansfca01", "lansfca01", "lansfca01", "lansfca01", "lansfca01", "lansfca01", "lansfca01", "lansfca01", "lansfca01", "lansfca01", "lansfca01", "armasto01", "armasto01", "armasto01", "armasto01", "armasto01", "armasto01", "armasto01", "armasto01", "armasto01", "armasto01", "armasto01", "armasto01", "armasto01", "armasto01", "morrija02", "morrija02", "morrija02", "morrija02", "morrija02", "morrija02", "morrija02", "morrija02", "morrija02", "morrija02", "morrija02", "morrija02", "morrija02", 
+#> "morrija02", "morrija02", "morrija02", "morrija02", "morrija02", "guerrpe01", "guerrpe01", "guerrpe01", "guerrpe01", "guerrpe01", "guerrpe01", "guerrpe01", "guerrpe01", "guerrpe01", "guerrpe01", "guerrpe01", "guerrpe01", "guerrpe01", "guerrpe01", "guerrpe01", "guerrpe01", "yeagest01", "yeagest01", "yeagest01", "yeagest01", "yeagest01", "yeagest01", "yeagest01", "yeagest01", "yeagest01", "yeagest01", "yeagest01", "yeagest01", "yeagest01", "yeagest01", "yeagest01", "vuckope01", "vuckope01", "vuckope01", 
+#> "vuckope01", "vuckope01", "vuckope01", "vuckope01", "vuckope01", "vuckope01", "vuckope01", "vuckope01", "murphda05", "murphda05", "murphda05", "murphda05", "murphda05", "murphda05", "murphda05", "murphda05", "murphda05", "murphda05", "murphda05", "murphda05", "murphda05", "murphda05", "murphda05", "murphda05", "murphda05", "murphda05", "murphda05", "ripkeca01", "ripkeca01", "ripkeca01", "ripkeca01", "ripkeca01", "ripkeca01", "ripkeca01", "ripkeca01", "ripkeca01", "ripkeca01", "ripkeca01", "ripkeca01", 
+#> "ripkeca01", "ripkeca01", "ripkeca01", "ripkeca01", "ripkeca01", "ripkeca01", "ripkeca01", "ripkeca01", "ripkeca01", "saxst01", "saxst01", "saxst01", "saxst01", "saxst01", "saxst01", "saxst01", "saxst01", "saxst01", "saxst01", "saxst01", "saxst01", "saxst01", "saxst01", "garcida01", "garcida01", "garcida01", "garcida01", "garcida01", "garcida01", "garcida01", "garcida01", "garcida01", "garcida01", "garcida01", "decindo01", "decindo01", "decindo01", "decindo01", "decindo01", "decindo01", "decindo01", 
+#> "decindo01", "decindo01", "decindo01", "decindo01", "decindo01", "decindo01", "decindo01", "decindo01", "decindo01", "durhale01", "durhale01", "durhale01", "durhale01", "durhale01", "durhale01", "durhale01", "durhale01", "durhale01", "durhale01", "durhale01", "robindo01", "robindo01", "robindo01", "robindo01", "robindo01", "robindo01", "robindo01", "robindo01", "robindo01", "robindo01", "robindo01", "robindo01", "robindo01", "robindo01", "robindo01", "robindo01", "robindo01", "zahnge01", "zahnge01", 
+#> "zahnge01", "zahnge01", "zahnge01", "zahnge01", "zahnge01", "zahnge01", "zahnge01", "zahnge01", "zahnge01", "zahnge01", "zahnge01", "zahnge01", "thomago01", "thomago01", "thomago01", "thomago01", "thomago01", "thomago01", "thomago01", "thomago01", "thomago01", "thomago01", "thomago01", "thomago01", "thomago01", "thomago01", "thomago01", "stiebda01", "stiebda01", "stiebda01", "stiebda01", "stiebda01", "stiebda01", "stiebda01", "stiebda01", "stiebda01", "stiebda01", "stiebda01", "stiebda01", "stiebda01", 
+#> "stiebda01", "stiebda01", "stiebda01", "smithlo01", "smithlo01", "smithlo01", "smithlo01", "smithlo01", "smithlo01", "smithlo01", "smithlo01", "smithlo01", "smithlo01", "smithlo01", "smithlo01", "smithlo01", "smithlo01", "smithlo01", "smithlo01", "smithlo01", "smithlo01", "smithlo01", "rogerst01", "rogerst01", "rogerst01", "rogerst01", "rogerst01", "rogerst01", "rogerst01", "rogerst01", "rogerst01", "rogerst01", "rogerst01", "rogerst01", "rogerst01", "boddimi01", "boddimi01", "boddimi01", "boddimi01", 
+#> "boddimi01", "boddimi01", "boddimi01", "boddimi01", "boddimi01", "boddimi01", "boddimi01", "boddimi01", "boddimi01", "boddimi01", "boddimi01", "dempsri01", "dempsri01", "dempsri01", "dempsri01", "dempsri01", "dempsri01", "dempsri01", "dempsri01", "dempsri01", "dempsri01", "dempsri01", "dempsri01", "dempsri01", "dempsri01", "dempsri01", "dempsri01", "dempsri01", "dempsri01", "dempsri01", "dempsri01", "dempsri01", "dempsri01", "dempsri01", "dempsri01", "dempsri01", "hoytla01", "hoytla01", "hoytla01", 
+#> "hoytla01", "hoytla01", "hoytla01", "hoytla01", "hoytla01", "dennyjo01", "dennyjo01", "dennyjo01", "dennyjo01", "dennyjo01", "dennyjo01", "dennyjo01", "dennyjo01", "dennyjo01", "dennyjo01", "dennyjo01", "dennyjo01", "dennyjo01", "dennyjo01", "sandbry01", "sandbry01", "sandbry01", "sandbry01", "sandbry01", "sandbry01", "sandbry01", "sandbry01", "sandbry01", "sandbry01", "sandbry01", "sandbry01", "sandbry01", "sandbry01", "sandbry01", "sandbry01", "penato01", "penato01", "penato01", "penato01", "penato01", 
+#> "penato01", "penato01", "penato01", "penato01", "penato01", "penato01", "penato01", "penato01", "penato01", "penato01", "penato01", "penato01", "penato01", "penato01", "mcgeewi01", "mcgeewi01", "mcgeewi01", "mcgeewi01", "mcgeewi01", "mcgeewi01", "mcgeewi01", "mcgeewi01", "mcgeewi01", "mcgeewi01", "mcgeewi01", "mcgeewi01", "mcgeewi01", "mcgeewi01", "mcgeewi01", "mcgeewi01", "mcgeewi01", "mcgeewi01", "mcgeewi01", "knighra01", "knighra01", "knighra01", "knighra01", "knighra01", "knighra01", "knighra01", 
+#> "knighra01", "knighra01", "knighra01", "knighra01", "knighra01", "knighra01", "knighra01", "hollaal01", "hollaal01", "hollaal01", "hollaal01", "hollaal01", "hollaal01", "hollaal01", "hollaal01", "hollaal01", "hollaal01", "hollaal01", "hollaal01", "kittlro01", "kittlro01", "kittlro01", "kittlro01", "kittlro01", "kittlro01", "kittlro01", "kittlro01", "kittlro01", "kittlro01", "kittlro01", "kittlro01", "strawda01", "strawda01", "strawda01", "strawda01", "strawda01", "strawda01", "strawda01", "strawda01", 
+#> "strawda01", "strawda01", "strawda01", "strawda01", "strawda01", "strawda01", "strawda01", "strawda01", "strawda01", "boggswa01", "boggswa01", "boggswa01", "boggswa01", "boggswa01", "boggswa01", "boggswa01", "boggswa01", "boggswa01", "boggswa01", "boggswa01", "boggswa01", "boggswa01", "boggswa01", "boggswa01", "boggswa01", "boggswa01", "boggswa01", "mosebll01", "mosebll01", "mosebll01", "mosebll01", "mosebll01", "mosebll01", "mosebll01", "mosebll01", "mosebll01", "mosebll01", "mosebll01", "mosebll01", 
+#> "rayjo01", "rayjo01", "rayjo01", "rayjo01", "rayjo01", "rayjo01", "rayjo01", "rayjo01", "rayjo01", "rayjo01", "rayjo01", "kennete02", "kennete02", "kennete02", "kennete02", "kennete02", "kennete02", "kennete02", "kennete02", "kennete02", "kennete02", "kennete02", "kennete02", "kennete02", "kennete02", "cruzjo01", "cruzjo01", "cruzjo01", "cruzjo01", "cruzjo01", "cruzjo01", "cruzjo01", "cruzjo01", "cruzjo01", "cruzjo01", "cruzjo01", "cruzjo01", "cruzjo01", "cruzjo01", "cruzjo01", "cruzjo01", "cruzjo01", 
+#> "cruzjo01", "cruzjo01", "thondi01", "thondi01", "thondi01", "thondi01", "thondi01", "thondi01", "thondi01", "thondi01", "thondi01", "thondi01", "thondi01", "thondi01", "thondi01", "thondi01", "thondi01", "hubbagl01", "hubbagl01", "hubbagl01", "hubbagl01", "hubbagl01", "hubbagl01", "hubbagl01", "hubbagl01", "hubbagl01", "hubbagl01", "hubbagl01", "hubbagl01", "mcwilla01", "mcwilla01", "mcwilla01", "mcwilla01", "mcwilla01", "mcwilla01", "mcwilla01", "mcwilla01", "mcwilla01", "mcwilla01", "mcwilla01", 
+#> "mcwilla01", "mcwilla01", "mcwilla01", "mcwilla01", "raineti01", "raineti01", "raineti01", "raineti01", "raineti01", "raineti01", "raineti01", "raineti01", "raineti01", "raineti01", "raineti01", "raineti01", "raineti01", "raineti01", "raineti01", "raineti01", "raineti01", "raineti01", "raineti01", "raineti01", "raineti01", "raineti01", "raineti01", "raineti01", "smithle02", "smithle02", "smithle02", "smithle02", "smithle02", "smithle02", "smithle02", "smithle02", "smithle02", "smithle02", "smithle02", 
+#> "smithle02", "smithle02", "smithle02", "smithle02", "smithle02", "smithle02", "smithle02", "smithle02", "smithle02", "smithle02", "gibsoki01", "gibsoki01", "gibsoki01", "gibsoki01", "gibsoki01", "gibsoki01", "gibsoki01", "gibsoki01", "gibsoki01", "gibsoki01", "gibsoki01", "gibsoki01", "gibsoki01", "gibsoki01", "gibsoki01", "gibsoki01", "gibsoki01", "hernawi01", "hernawi01", "hernawi01", "hernawi01", "hernawi01", "hernawi01", "hernawi01", "hernawi01", "hernawi01", "hernawi01", "hernawi01", "hernawi01", 
+#> "hernawi01", "hernawi01", "dernibo01", "dernibo01", "dernibo01", "dernibo01", "dernibo01", "dernibo01", "dernibo01", "dernibo01", "dernibo01", "dernibo01", "andujjo01", "andujjo01", "andujjo01", "andujjo01", "andujjo01", "andujjo01", "andujjo01", "andujjo01", "andujjo01", "andujjo01", "andujjo01", "andujjo01", "andujjo01", "andujjo01", "davisal01", "davisal01", "davisal01", "davisal01", "davisal01", "davisal01", "davisal01", "davisal01", "davisal01", "goodedw01", "goodedw01", "goodedw01", "goodedw01", 
+#> "goodedw01", "goodedw01", "goodedw01", "goodedw01", "goodedw01", "goodedw01", "goodedw01", "goodedw01", "goodedw01", "goodedw01", "goodedw01", "goodedw01", "goodedw01", "goodedw01", "gwynnto01", "gwynnto01", "gwynnto01", "gwynnto01", "gwynnto01", "gwynnto01", "gwynnto01", "gwynnto01", "gwynnto01", "gwynnto01", "gwynnto01", "gwynnto01", "gwynnto01", "gwynnto01", "gwynnto01", "gwynnto01", "gwynnto01", "gwynnto01", "gwynnto01", "gwynnto01", "rhoderi01", "rhoderi01", "rhoderi01", "rhoderi01", "rhoderi01", 
+#> "rhoderi01", "rhoderi01", "rhoderi01", "rhoderi01", "rhoderi01", "rhoderi01", "rhoderi01", "rhoderi01", "rhoderi01", "rhoderi01", "rhoderi01", "mattido01", "mattido01", "mattido01", "mattido01", "mattido01", "mattido01", "mattido01", "mattido01", "mattido01", "mattido01", "mattido01", "mattido01", "mattido01", "mattido01", "thurmma01", "thurmma01", "thurmma01", "thurmma01", "thurmma01", "thurmma01", "thurmma01", "thurmma01", "thurmma01", "saberbr01", "saberbr01", "saberbr01", "saberbr01", "saberbr01", 
+#> "saberbr01", "saberbr01", "saberbr01", "saberbr01", "saberbr01", "saberbr01", "saberbr01", "saberbr01", "saberbr01", "saberbr01", "saberbr01", "saberbr01", "pettiga01", "pettiga01", "pettiga01", "pettiga01", "pettiga01", "pettiga01", "pettiga01", "pettiga01", "pettiga01", "pettiga01", "pettiga01", "pettiga01", "wallati01", "wallati01", "wallati01", "wallati01", "wallati01", "wallati01", "wallati01", "wallati01", "wallati01", "wallati01", "wallati01", "wallati01", "wallati01", "wallati01", "wallati01", 
+#> "wallati01", "wallati01", "wallati01", "reardje01", "reardje01", "reardje01", "reardje01", "reardje01", "reardje01", "reardje01", "reardje01", "reardje01", "reardje01", "reardje01", "reardje01", "reardje01", "reardje01", "reardje01", "reardje01", "reardje01", "reardje01", "guilloz01", "guilloz01", "guilloz01", "guilloz01", "guilloz01", "guilloz01", "guilloz01", "guilloz01", "guilloz01", "guilloz01", "guilloz01", "guilloz01", "guilloz01", "guilloz01", "guilloz01", "guilloz01", "guilloz01", "colemvi01", 
+#> "colemvi01", "colemvi01", "colemvi01", "colemvi01", "colemvi01", "colemvi01", "colemvi01", "colemvi01", "colemvi01", "colemvi01", "colemvi01", "colemvi01", "colemvi01", "bellge02", "bellge02", "bellge02", "bellge02", "bellge02", "bellge02", "bellge02", "bellge02", "bellge02", "bellge02", "bellge02", "bellge02", "brookhu01", "brookhu01", "brookhu01", "brookhu01", "brookhu01", "brookhu01", "brookhu01", "brookhu01", "brookhu01", "brookhu01", "brookhu01", "brookhu01", "brookhu01", "brookhu01", "brookhu01", 
+#> "baineha01", "baineha01", "baineha01", "baineha01", "baineha01", "baineha01", "baineha01", "baineha01", "baineha01", "baineha01", "baineha01", "baineha01", "baineha01", "baineha01", "baineha01", "baineha01", "baineha01", "baineha01", "baineha01", "baineha01", "baineha01", "baineha01", "baineha01", "baineha01", "baineha01", "baineha01", "baineha01", "bradlph01", "bradlph01", "bradlph01", "bradlph01", "bradlph01", "bradlph01", "bradlph01", "bradlph01", "bradlph01", "herrto01", "herrto01", "herrto01", 
+#> "herrto01", "herrto01", "herrto01", "herrto01", "herrto01", "herrto01", "herrto01", "herrto01", "herrto01", "herrto01", "herrto01", "herrto01", "herrto01", "tudorjo01", "tudorjo01", "tudorjo01", "tudorjo01", "tudorjo01", "tudorjo01", "tudorjo01", "tudorjo01", "tudorjo01", "tudorjo01", "tudorjo01", "tudorjo01", "tudorjo01", "barrema02", "barrema02", "barrema02", "barrema02", "barrema02", "barrema02", "barrema02", "barrema02", "barrema02", "barrema02", "clemero02", "clemero02", "clemero02", "clemero02", 
+#> "clemero02", "clemero02", "clemero02", "clemero02", "clemero02", "clemero02", "clemero02", "clemero02", "clemero02", "clemero02", "clemero02", "clemero02", "clemero02", "clemero02", "clemero02", "clemero02", "clemero02", "clemero02", "clemero02", "clemero02", "scottmi03", "scottmi03", "scottmi03", "scottmi03", "scottmi03", "scottmi03", "scottmi03", "scottmi03", "scottmi03", "scottmi03", "scottmi03", "scottmi03", "scottmi03", "gaettga01", "gaettga01", "gaettga01", "gaettga01", "gaettga01", "gaettga01", 
+#> "gaettga01", "gaettga01", "gaettga01", "gaettga01", "gaettga01", "gaettga01", "gaettga01", "gaettga01", "gaettga01", "gaettga01", "gaettga01", "gaettga01", "gaettga01", "gaettga01", "gaettga01", "gaettga01", "barfije01", "barfije01", "barfije01", "barfije01", "barfije01", "barfije01", "barfije01", "barfije01", "barfije01", "barfije01", "barfije01", "barfije01", "barfije01", "puckeki01", "puckeki01", "puckeki01", "puckeki01", "puckeki01", "puckeki01", "puckeki01", "puckeki01", "puckeki01", "puckeki01", 
+#> "puckeki01", "puckeki01", "fernato01", "fernato01", "fernato01", "fernato01", "fernato01", "fernato01", "fernato01", "fernato01", "fernato01", "fernato01", "fernato01", "fernato01", "fernato01", "fernato01", "fernato01", "fernato01", "fernato01", "fernato01", "fernato01", "davisjo02", "davisjo02", "davisjo02", "davisjo02", "davisjo02", "davisjo02", "davisjo02", "davisjo02", "davisjo02", "davisjo02", "davisjo02", "leonade01", "leonade01", "leonade01", "leonade01", "leonade01", "leonade01", "leonade01", 
+#> "leonade01", "leonade01", "leonade01", "leonade01", "leonade01", "worreto01", "worreto01", "worreto01", "worreto01", "worreto01", "worreto01", "worreto01", "worreto01", "worreto01", "worreto01", "worreto01", "cansejo01", "cansejo01", "cansejo01", "cansejo01", "cansejo01", "cansejo01", "cansejo01", "cansejo01", "cansejo01", "cansejo01", "cansejo01", "cansejo01", "cansejo01", "cansejo01", "cansejo01", "cansejo01", "cansejo01", "cansejo01", "cansejo01", "davisgl01", "davisgl01", "davisgl01", "davisgl01", 
+#> "davisgl01", "davisgl01", "davisgl01", "davisgl01", "davisgl01", "davisgl01", "bernato01", "bernato01", "bernato01", "bernato01", "bernato01", "bernato01", "bernato01", "bernato01", "bernato01", "bernato01", "bernato01", "bernato01", "gedmari01", "gedmari01", "gedmari01", "gedmari01", "gedmari01", "gedmari01", "gedmari01", "gedmari01", "gedmari01", "gedmari01", "gedmari01", "gedmari01", "gedmari01", "gedmari01", "higuete01", "higuete01", "higuete01", "higuete01", "higuete01", "higuete01", "higuete01", 
+#> "higuete01", "higuete01", "violafr01", "violafr01", "violafr01", "violafr01", "violafr01", "violafr01", "violafr01", "violafr01", "violafr01", "violafr01", "violafr01", "violafr01", "violafr01", "violafr01", "violafr01", "violafr01", "bedrost01", "bedrost01", "bedrost01", "bedrost01", "bedrost01", "bedrost01", "bedrost01", "bedrost01", "bedrost01", "bedrost01", "bedrost01", "bedrost01", "bedrost01", "bedrost01", "bedrost01", "langsma01", "langsma01", "langsma01", "langsma01", "langsma01", "langsma01", 
+#> "langsma01", "langsma01", "langsma01", "langsma01", "langsma01", "langsma01", "langsma01", "langsma01", "langsma01", "langsma01", "langsma01", "pendlte01", "pendlte01", "pendlte01", "pendlte01", "pendlte01", "pendlte01", "pendlte01", "pendlte01", "pendlte01", "pendlte01", "pendlte01", "pendlte01", "pendlte01", "pendlte01", "pendlte01", "pendlte01", "lavalmi01", "lavalmi01", "lavalmi01", "lavalmi01", "lavalmi01", "lavalmi01", "lavalmi01", "lavalmi01", "lavalmi01", "lavalmi01", "lavalmi01", "lavalmi01", 
+#> "lavalmi01", "daviser01", "daviser01", "daviser01", "daviser01", "daviser01", "daviser01", "daviser01", "daviser01", "daviser01", "daviser01", "daviser01", "daviser01", "daviser01", "daviser01", "daviser01", "daviser01", "daviser01", "daviser01", "molitpa01", "molitpa01", "molitpa01", "molitpa01", "molitpa01", "molitpa01", "molitpa01", "molitpa01", "molitpa01", "molitpa01", "molitpa01", "molitpa01", "molitpa01", "molitpa01", "molitpa01", "molitpa01", "molitpa01", "molitpa01", "molitpa01", "molitpa01", 
+#> "molitpa01", "leonaje01", "leonaje01", "leonaje01", "leonaje01", "leonaje01", "leonaje01", "leonaje01", "leonaje01", "leonaje01", "leonaje01", "leonaje01", "leonaje01", "leonaje01", "leonaje01", "leonaje01", "leonaje01", "mcgwima01", "mcgwima01", "mcgwima01", "mcgwima01", "mcgwima01", "mcgwima01", "mcgwima01", "mcgwima01", "mcgwima01", "mcgwima01", "mcgwima01", "mcgwima01", "mcgwima01", "mcgwima01", "mcgwima01", "mcgwima01", "mcgwima01", "santibe01", "santibe01", "santibe01", "santibe01", "santibe01", 
+#> "santibe01", "santibe01", "santibe01", "santibe01", "santibe01", "santibe01", "santibe01", "santibe01", "santibe01", "santibe01", "santibe01", "santibe01", "santibe01", "santibe01", "santibe01", "nokesma01", "nokesma01", "nokesma01", "nokesma01", "nokesma01", "nokesma01", "nokesma01", "nokesma01", "nokesma01", "nokesma01", "nokesma01", "nokesma01", "nokesma01", "samueju01", "samueju01", "samueju01", "samueju01", "samueju01", "samueju01", "samueju01", "samueju01", "samueju01", "samueju01", "samueju01", 
+#> "samueju01", "samueju01", "samueju01", "samueju01", "samueju01", "samueju01", "samueju01", "samueju01", "keyji01", "keyji01", "keyji01", "keyji01", "keyji01", "keyji01", "keyji01", "keyji01", "keyji01", "keyji01", "keyji01", "keyji01", "keyji01", "keyji01", "keyji01", "smithza01", "smithza01", "smithza01", "smithza01", "smithza01", "smithza01", "smithza01", "smithza01", "smithza01", "smithza01", "smithza01", "smithza01", "smithza01", "smithza01", "smithza01", "eckerde01", "eckerde01", "eckerde01", 
+#> "eckerde01", "eckerde01", "eckerde01", "eckerde01", "eckerde01", "eckerde01", "eckerde01", "eckerde01", "eckerde01", "eckerde01", "eckerde01", "eckerde01", "eckerde01", "eckerde01", "eckerde01", "eckerde01", "eckerde01", "eckerde01", "eckerde01", "eckerde01", "eckerde01", "eckerde01", "steinte01", "steinte01", "steinte01", "steinte01", "steinte01", "steinte01", "steinte01", "steinte01", "steinte01", "steinte01", "steinte01", "steinte01", "steinte01", "steinte01", "hershor01", "hershor01", "hershor01", 
+#> "hershor01", "hershor01", "hershor01", "hershor01", "hershor01", "hershor01", "hershor01", "hershor01", "hershor01", "hershor01", "hershor01", "hershor01", "hershor01", "hershor01", "hershor01", "reynoha01", "reynoha01", "reynoha01", "reynoha01", "reynoha01", "reynoha01", "reynoha01", "reynoha01", "reynoha01", "reynoha01", "reynoha01", "reynoha01", "whitede03", "whitede03", "whitede03", "whitede03", "whitede03", "whitede03", "whitede03", "whitede03", "whitede03", "whitede03", "whitede03", "whitede03", 
+#> "whitede03", "whitede03", "whitede03", "whitede03", "whitede03", "vanslan01", "vanslan01", "vanslan01", "vanslan01", "vanslan01", "vanslan01", "vanslan01", "vanslan01", "vanslan01", "vanslan01", "vanslan01", "vanslan01", "vanslan01", "vanslan01", "oestero01", "oestero01", "oestero01", "oestero01", "oestero01", "oestero01", "oestero01", "oestero01", "oestero01", "oestero01", "oestero01", "oestero01", "oestero01", "francjo01", "francjo01", "francjo01", "francjo01", "francjo01", "francjo01", "francjo01", 
+#> "francjo01", "francjo01", "francjo01", "francjo01", "francjo01", "francjo01", "francjo01", "francjo01", "francjo01", "francjo01", "francjo01", "francjo01", "francjo01", "francjo01", "weisswa01", "weisswa01", "weisswa01", "weisswa01", "weisswa01", "weisswa01", "weisswa01", "weisswa01", "weisswa01", "weisswa01", "weisswa01", "weisswa01", "weisswa01", "weisswa01", "saboch01", "saboch01", "saboch01", "saboch01", "saboch01", "saboch01", "saboch01", "saboch01", "saboch01", "saboch01", "francju01", "francju01", 
+#> "francju01", "francju01", "francju01", "francju01", "francju01", "francju01", "francju01", "francju01", "francju01", "francju01", "francju01", "francju01", "francju01", "francju01", "francju01", "francju01", "francju01", "francju01", "francju01", "francju01", "francju01", "francju01", "francju01", "greenmi01", "greenmi01", "greenmi01", "greenmi01", "greenmi01", "greenmi01", "greenmi01", "greenmi01", "greenmi01", "greenmi01", "greenmi01", "greenmi01", "galaran01", "galaran01", "galaran01", "galaran01", 
+#> "galaran01", "galaran01", "galaran01", "galaran01", "galaran01", "galaran01", "galaran01", "galaran01", "galaran01", "galaran01", "galaran01", "galaran01", "galaran01", "galaran01", "galaran01", "galaran01", "bonilbo01", "bonilbo01", "bonilbo01", "bonilbo01", "bonilbo01", "bonilbo01", "bonilbo01", "bonilbo01", "bonilbo01", "bonilbo01", "bonilbo01", "bonilbo01", "bonilbo01", "bonilbo01", "bonilbo01", "bonilbo01", "bonilbo01", "bonilbo01", "bonilbo01", "learyti01", "learyti01", "learyti01", "learyti01", 
+#> "learyti01", "learyti01", "learyti01", "learyti01", "learyti01", "learyti01", "learyti01", "learyti01", "learyti01", "learyti01", "learyti01", "larkiba01", "larkiba01", "larkiba01", "larkiba01", "larkiba01", "larkiba01", "larkiba01", "larkiba01", "larkiba01", "larkiba01", "larkiba01", "larkiba01", "larkiba01", "larkiba01", "larkiba01", "larkiba01", "larkiba01", "larkiba01", "larkiba01", "whitter01", "whitter01", "whitter01", "whitter01", "whitter01", "whitter01", "whitter01", "whitter01", "whitter01", 
+#> "whitter01", "whitter01", "whitter01", "whitter01", "whitter01", "whitter01", "stewada01", "stewada01", "stewada01", "stewada01", "stewada01", "stewada01", "stewada01", "stewada01", "stewada01", "stewada01", "stewada01", "stewada01", "stewada01", "stewada01", "stewada01", "stewada01", "stewada01", "stewada01", "stewada01", "clarkwi02", "clarkwi02", "clarkwi02", "clarkwi02", "clarkwi02", "clarkwi02", "clarkwi02", "clarkwi02", "clarkwi02", "clarkwi02", "clarkwi02", "clarkwi02", "clarkwi02", "clarkwi02", 
+#> "clarkwi02", "clarkwi02", "jacksda02", "jacksda02", "jacksda02", "jacksda02", "jacksda02", "jacksda02", "jacksda02", "jacksda02", "jacksda02", "jacksda02", "jacksda02", "jacksda02", "jacksda02", "jacksda02", "jacksda02", "jacksda02", "jacksda02", "mcreyke01", "mcreyke01", "mcreyke01", "mcreyke01", "mcreyke01", "mcreyke01", "mcreyke01", "mcreyke01", "mcreyke01", "mcreyke01", "mcreyke01", "mcreyke01", "jacksbo01", "jacksbo01", "jacksbo01", "jacksbo01", "jacksbo01", "jacksbo01", "jacksbo01", "jacksbo01", 
+#> "davisma01", "davisma01", "davisma01", "davisma01", "davisma01", "davisma01", "davisma01", "davisma01", "davisma01", "davisma01", "davisma01", "davisma01", "davisma01", "davisma01", "davisma01", "davisma01", "davisma01", "davisma01", "darliro01", "darliro01", "darliro01", "darliro01", "darliro01", "darliro01", "darliro01", "darliro01", "darliro01", "darliro01", "darliro01", "darliro01", "darliro01", "darliro01", "darliro01", "draveda01", "draveda01", "draveda01", "draveda01", "draveda01", "draveda01", 
+#> "draveda01", "draveda01", "draveda01", "mitchke01", "mitchke01", "mitchke01", "mitchke01", "mitchke01", "mitchke01", "mitchke01", "mitchke01", "mitchke01", "mitchke01", "mitchke01", "mitchke01", "mitchke01", "mitchke01", "mitchke01", "russeje01", "russeje01", "russeje01", "russeje01", "russeje01", "russeje01", "russeje01", "russeje01", "russeje01", "russeje01", "russeje01", "russeje01", "russeje01", "russeje01", "russeje01", "russeje01", "olsongr01", "olsongr01", "olsongr01", "olsongr01", "olsongr01", 
+#> "olsongr01", "olsongr01", "olsongr01", "olsongr01", "olsongr01", "olsongr01", "olsongr01", "olsongr01", "olsongr01", "olsongr01", "olsongr01", "olsongr01", "waltoje01", "waltoje01", "waltoje01", "waltoje01", "waltoje01", "waltoje01", "waltoje01", "waltoje01", "waltoje01", "waltoje01", "mcgrifr01", "mcgrifr01", "mcgrifr01", "mcgrifr01", "mcgrifr01", "mcgrifr01", "mcgrifr01", "mcgrifr01", "mcgrifr01", "mcgrifr01", "mcgrifr01", "mcgrifr01", "mcgrifr01", "mcgrifr01", "mcgrifr01", "mcgrifr01", "mcgrifr01", 
+#> "mcgrifr01", "mcgrifr01", "mcgrifr01", "mcgrifr01", "tettlmi01", "tettlmi01", "tettlmi01", "tettlmi01", "tettlmi01", "tettlmi01", "tettlmi01", "tettlmi01", "tettlmi01", "tettlmi01", "tettlmi01", "tettlmi01", "tettlmi01", "tettlmi01", "sierrru01", "sierrru01", "sierrru01", "sierrru01", "sierrru01", "sierrru01", "sierrru01", "sierrru01", "sierrru01", "sierrru01", "sierrru01", "sierrru01", "sierrru01", "sierrru01", "sierrru01", "sierrru01", "sierrru01", "sierrru01", "sierrru01", "sierrru01", "sierrru01", 
+#> "sierrru01", "sierrru01", "sierrru01", "sierrru01", "johnsho01", "johnsho01", "johnsho01", "johnsho01", "johnsho01", "johnsho01", "johnsho01", "johnsho01", "johnsho01", "johnsho01", "johnsho01", "johnsho01", "johnsho01", "johnsho01", "biggicr01", "biggicr01", "biggicr01", "biggicr01", "biggicr01", "biggicr01", "biggicr01", "biggicr01", "biggicr01", "biggicr01", "biggicr01", "biggicr01", "biggicr01", "biggicr01", "biggicr01", "biggicr01", "biggicr01", "biggicr01", "biggicr01", "biggicr01", "finlech01", 
+#> "finlech01", "finlech01", "finlech01", "finlech01", "finlech01", "finlech01", "finlech01", "finlech01", "finlech01", "finlech01", "finlech01", "finlech01", "finlech01", "finlech01", "finlech01", "finlech01", "finlech01", "dunstsh01", "dunstsh01", "dunstsh01", "dunstsh01", "dunstsh01", "dunstsh01", "dunstsh01", "dunstsh01", "dunstsh01", "dunstsh01", "dunstsh01", "dunstsh01", "dunstsh01", "dunstsh01", "dunstsh01", "dunstsh01", "dunstsh01", "dunstsh01", "dunstsh01", "dunstsh01", "dunstsh01", "hatchbi01", 
+#> "hatchbi01", "hatchbi01", "hatchbi01", "hatchbi01", "hatchbi01", "hatchbi01", "hatchbi01", "hatchbi01", "hatchbi01", "hatchbi01", "hatchbi01", "hatchbi01", "hatchbi01", "hatchbi01", "welchbo01", "welchbo01", "welchbo01", "welchbo01", "welchbo01", "welchbo01", "welchbo01", "welchbo01", "welchbo01", "welchbo01", "welchbo01", "welchbo01", "welchbo01", "welchbo01", "welchbo01", "welchbo01", "welchbo01", "drabedo01", "drabedo01", "drabedo01", "drabedo01", "drabedo01", "drabedo01", "drabedo01", "drabedo01", 
+#> "drabedo01", "drabedo01", "drabedo01", "drabedo01", "drabedo01", "grubeke01", "grubeke01", "grubeke01", "grubeke01", "grubeke01", "grubeke01", "grubeke01", "grubeke01", "grubeke01", "grubeke01", "alomasa02", "alomasa02", "alomasa02", "alomasa02", "alomasa02", "alomasa02", "alomasa02", "alomasa02", "alomasa02", "alomasa02", "alomasa02", "alomasa02", "alomasa02", "alomasa02", "alomasa02", "alomasa02", "alomasa02", "alomasa02", "alomasa02", "alomasa02", "alomasa02", "alomasa02", "burksel01", "burksel01", 
+#> "burksel01", "burksel01", "burksel01", "burksel01", "burksel01", "burksel01", "burksel01", "burksel01", "burksel01", "burksel01", "burksel01", "burksel01", "burksel01", "burksel01", "burksel01", "burksel01", "burksel01", "griffke02", "griffke02", "griffke02", "griffke02", "griffke02", "griffke02", "griffke02", "griffke02", "griffke02", "griffke02", "griffke02", "griffke02", "griffke02", "griffke02", "griffke02", "griffke02", "griffke02", "griffke02", "griffke02", "griffke02", "griffke02", "griffke02", 
+#> "griffke02", "bondsba01", "bondsba01", "bondsba01", "bondsba01", "bondsba01", "bondsba01", "bondsba01", "bondsba01", "bondsba01", "bondsba01", "bondsba01", "bondsba01", "bondsba01", "bondsba01", "bondsba01", "bondsba01", "bondsba01", "bondsba01", "bondsba01", "bondsba01", "bondsba01", "bondsba01", "maddugr01", "maddugr01", "maddugr01", "maddugr01", "maddugr01", "maddugr01", "maddugr01", "maddugr01", "maddugr01", "maddugr01", "maddugr01", "maddugr01", "maddugr01", "maddugr01", "maddugr01", "maddugr01", 
+#> "maddugr01", "maddugr01", "maddugr01", "maddugr01", "maddugr01", "maddugr01", "maddugr01", "maddugr01", "maddugr01", "breamsi01", "breamsi01", "breamsi01", "breamsi01", "breamsi01", "breamsi01", "breamsi01", "breamsi01", "breamsi01", "breamsi01", "breamsi01", "breamsi01", "breamsi01", "dibblro01", "dibblro01", "dibblro01", "dibblro01", "dibblro01", "dibblro01", "dibblro01", "dibblro01", "myersra01", "myersra01", "myersra01", "myersra01", "myersra01", "myersra01", "myersra01", "myersra01", "myersra01", 
+#> "myersra01", "myersra01", "myersra01", "myersra01", "myersra01", "myersra01", "thigpbo01", "thigpbo01", "thigpbo01", "thigpbo01", "thigpbo01", "thigpbo01", "thigpbo01", "thigpbo01", "thigpbo01", "thigpbo01", "justida01", "justida01", "justida01", "justida01", "justida01", "justida01", "justida01", "justida01", "justida01", "justida01", "justida01", "justida01", "justida01", "justida01", "justida01", "fieldce01", "fieldce01", "fieldce01", "fieldce01", "fieldce01", "fieldce01", "fieldce01", "fieldce01", 
+#> "fieldce01", "fieldce01", "fieldce01", "fieldce01", "fieldce01", "fieldce01", "fieldce01", "willima04", "willima04", "willima04", "willima04", "willima04", "willima04", "willima04", "willima04", "willima04", "willima04", "willima04", "willima04", "willima04", "willima04", "willima04", "willima04", "willima04", "sciosmi01", "sciosmi01", "sciosmi01", "sciosmi01", "sciosmi01", "sciosmi01", "sciosmi01", "sciosmi01", "sciosmi01", "sciosmi01", "sciosmi01", "sciosmi01", "sciosmi01", "rijojo01", "rijojo01", 
+#> "rijojo01", "rijojo01", "rijojo01", "rijojo01", "rijojo01", "rijojo01", "rijojo01", "rijojo01", "rijojo01", "rijojo01", "rijojo01", "rijojo01", "glavito02", "glavito02", "glavito02", "glavito02", "glavito02", "glavito02", "glavito02", "glavito02", "glavito02", "glavito02", "glavito02", "glavito02", "glavito02", "glavito02", "glavito02", "glavito02", "glavito02", "glavito02", "glavito02", "glavito02", "glavito02", "glavito02", "alomaro01", "alomaro01", "alomaro01", "alomaro01", "alomaro01", "alomaro01", 
+#> "alomaro01", "alomaro01", "alomaro01", "alomaro01", "alomaro01", "alomaro01", "alomaro01", "alomaro01", "alomaro01", "alomaro01", "alomaro01", "alomaro01", "alomaro01", "venturo01", "venturo01", "venturo01", "venturo01", "venturo01", "venturo01", "venturo01", "venturo01", "venturo01", "venturo01", "venturo01", "venturo01", "venturo01", "venturo01", "venturo01", "venturo01", "venturo01", "pagnoto01", "pagnoto01", "pagnoto01", "pagnoto01", "pagnoto01", "pagnoto01", "pagnoto01", "pagnoto01", "pagnoto01", 
+#> "pagnoto01", "pagnoto01", "pagnoto01", "wegmabi01", "wegmabi01", "wegmabi01", "wegmabi01", "wegmabi01", "wegmabi01", "wegmabi01", "wegmabi01", "wegmabi01", "wegmabi01", "wegmabi01", "hrbekke01", "hrbekke01", "hrbekke01", "hrbekke01", "hrbekke01", "hrbekke01", "hrbekke01", "hrbekke01", "hrbekke01", "hrbekke01", "hrbekke01", "hrbekke01", "hrbekke01", "hrbekke01", "averyst01", "averyst01", "averyst01", "averyst01", "averyst01", "averyst01", "averyst01", "averyst01", "averyst01", "averyst01", "averyst01", 
+#> "harvebr01", "harvebr01", "harvebr01", "harvebr01", "harvebr01", "harvebr01", "harvebr01", "harvebr01", "harvebr01", "knoblch01", "knoblch01", "knoblch01", "knoblch01", "knoblch01", "knoblch01", "knoblch01", "knoblch01", "knoblch01", "knoblch01", "knoblch01", "knoblch01", "bagweje01", "bagweje01", "bagweje01", "bagweje01", "bagweje01", "bagweje01", "bagweje01", "bagweje01", "bagweje01", "bagweje01", "bagweje01", "bagweje01", "bagweje01", "bagweje01", "bagweje01", "thomafr04", "thomafr04", "thomafr04", 
+#> "thomafr04", "thomafr04", "thomafr04", "thomafr04", "thomafr04", "thomafr04", "thomafr04", "thomafr04", "thomafr04", "thomafr04", "thomafr04", "thomafr04", "thomafr04", "thomafr04", "thomafr04", "thomafr04", "thomafr04", "cartejo01", "cartejo01", "cartejo01", "cartejo01", "cartejo01", "cartejo01", "cartejo01", "cartejo01", "cartejo01", "cartejo01", "cartejo01", "cartejo01", "cartejo01", "cartejo01", "cartejo01", "cartejo01", "cartejo01", "gantro01", "gantro01", "gantro01", "gantro01", "gantro01", 
+#> "gantro01", "gantro01", "gantro01", "gantro01", "gantro01", "gantro01", "gantro01", "gantro01", "gantro01", "gantro01", "gantro01", "gantro01", "gantro01", "abbotji01", "abbotji01", "abbotji01", "abbotji01", "abbotji01", "abbotji01", "abbotji01", "abbotji01", "abbotji01", "abbotji01", "abbotji01", "rodriiv01", "rodriiv01", "rodriiv01", "rodriiv01", "rodriiv01", "rodriiv01", "rodriiv01", "rodriiv01", "rodriiv01", "rodriiv01", "rodriiv01", "rodriiv01", "rodriiv01", "rodriiv01", "rodriiv01", "rodriiv01", 
+#> "rodriiv01", "rodriiv01", "rodriiv01", "rodriiv01", "rodriiv01", "rodriiv01", "rodriiv01", "gracema01", "gracema01", "gracema01", "gracema01", "gracema01", "gracema01", "gracema01", "gracema01", "gracema01", "gracema01", "gracema01", "gracema01", "gracema01", "gracema01", "gracema01", "gracema01", "lindjo01", "lindjo01", "lindjo01", "lindjo01", "lindjo01", "lindjo01", "lindjo01", "lindjo01", "lindjo01", "lindjo01", "walkela01", "walkela01", "walkela01", "walkela01", "walkela01", "walkela01", "walkela01", 
+#> "walkela01", "walkela01", "walkela01", "walkela01", "walkela01", "walkela01", "walkela01", "walkela01", "walkela01", "walkela01", "walkela01", "smoltjo01", "smoltjo01", "smoltjo01", "smoltjo01", "smoltjo01", "smoltjo01", "smoltjo01", "smoltjo01", "smoltjo01", "smoltjo01", "smoltjo01", "smoltjo01", "smoltjo01", "smoltjo01", "smoltjo01", "smoltjo01", "smoltjo01", "smoltjo01", "smoltjo01", "smoltjo01", "smoltjo01", "smoltjo01", "listapa01", "listapa01", "listapa01", "listapa01", "listapa01", "listapa01", 
+#> "karroer01", "karroer01", "karroer01", "karroer01", "karroer01", "karroer01", "karroer01", "karroer01", "karroer01", "karroer01", "karroer01", "karroer01", "karroer01", "karroer01", "martied01", "martied01", "martied01", "martied01", "martied01", "martied01", "martied01", "martied01", "martied01", "martied01", "martied01", "martied01", "martied01", "martied01", "martied01", "martied01", "martied01", "martied01", "gonzaju03", "gonzaju03", "gonzaju03", "gonzaju03", "gonzaju03", "gonzaju03", "gonzaju03", 
+#> "gonzaju03", "gonzaju03", "gonzaju03", "gonzaju03", "gonzaju03", "gonzaju03", "gonzaju03", "gonzaju03", "gonzaju03", "gonzaju03", "frymatr01", "frymatr01", "frymatr01", "frymatr01", "frymatr01", "frymatr01", "frymatr01", "frymatr01", "frymatr01", "frymatr01", "frymatr01", "frymatr01", "frymatr01", "sheffga01", "sheffga01", "sheffga01", "sheffga01", "sheffga01", "sheffga01", "sheffga01", "sheffga01", "sheffga01", "sheffga01", "sheffga01", "sheffga01", "sheffga01", "sheffga01", "sheffga01", "sheffga01", 
+#> "sheffga01", "sheffga01", "sheffga01", "sheffga01", "sheffga01", "sheffga01", "sheffga01", "sheffga01", "daultda01", "daultda01", "daultda01", "daultda01", "daultda01", "daultda01", "daultda01", "daultda01", "daultda01", "daultda01", "daultda01", "daultda01", "daultda01", "daultda01", "daultda01", "flemida01", "flemida01", "flemida01", "flemida01", "flemida01", "flemida01", "devermi01", "devermi01", "devermi01", "devermi01", "devermi01", "devermi01", "devermi01", "devermi01", "devermi01", "devermi01", 
+#> "devermi01", "devermi01", "devermi01", "mcdowja01", "mcdowja01", "mcdowja01", "mcdowja01", "mcdowja01", "mcdowja01", "mcdowja01", "mcdowja01", "mcdowja01", "mcdowja01", "mcdowja01", "mcdowja01", "jonesdo01", "jonesdo01", "jonesdo01", "jonesdo01", "jonesdo01", "jonesdo01", "jonesdo01", "jonesdo01", "jonesdo01", "jonesdo01", "jonesdo01", "jonesdo01", "jonesdo01", "jonesdo01", "jonesdo01", "jonesdo01", "jonesdo01", "jonesdo01", "bordepa01", "bordepa01", "bordepa01", "bordepa01", "bordepa01", "bordepa01", 
+#> "bordepa01", "bordepa01", "bordepa01", "bordepa01", "bordepa01", "bordepa01", "bordepa01", "bordepa01", "bordepa01", "bordepa01", "bordepa01", "bordepa01", "bordepa01", "bordepa01", "bordepa01", "bordepa01", "loftoke01", "loftoke01", "loftoke01", "loftoke01", "loftoke01", "loftoke01", "loftoke01", "loftoke01", "loftoke01", "loftoke01", "loftoke01", "loftoke01", "loftoke01", "loftoke01", "loftoke01", "loftoke01", "loftoke01", "loftoke01", "loftoke01", "loftoke01", "vizquom01", "vizquom01", "vizquom01", 
+#> "vizquom01", "vizquom01", "vizquom01", "vizquom01", "vizquom01", "vizquom01", "vizquom01", "vizquom01", "vizquom01", "vizquom01", "vizquom01", "vizquom01", "vizquom01", "vizquom01", "vizquom01", "vizquom01", "vizquom01", "vizquom01", "vizquom01", "vizquom01", "vizquom01", "thompro01", "thompro01", "thompro01", "thompro01", "thompro01", "thompro01", "thompro01", "thompro01", "thompro01", "thompro01", "thompro01", "manwaki01", "manwaki01", "manwaki01", "manwaki01", "manwaki01", "manwaki01", "manwaki01", 
+#> "manwaki01", "manwaki01", "manwaki01", "manwaki01", "manwaki01", "manwaki01", "manwaki01", "grissma02", "grissma02", "grissma02", "grissma02", "grissma02", "grissma02", "grissma02", "grissma02", "grissma02", "grissma02", "grissma02", "grissma02", "grissma02", "grissma02", "grissma02", "grissma02", "grissma02", "bellja01", "bellja01", "bellja01", "bellja01", "bellja01", "bellja01", "bellja01", "bellja01", "bellja01", "bellja01", "bellja01", "bellja01", "bellja01", "bellja01", "bellja01", "bellja01", 
+#> "bellja01", "bellja01", "olerujo01", "olerujo01", "olerujo01", "olerujo01", "olerujo01", "olerujo01", "olerujo01", "olerujo01", "olerujo01", "olerujo01", "olerujo01", "olerujo01", "olerujo01", "olerujo01", "olerujo01", "olerujo01", "olerujo01", "olerujo01", "schilcu01", "schilcu01", "schilcu01", "schilcu01", "schilcu01", "schilcu01", "schilcu01", "schilcu01", "schilcu01", "schilcu01", "schilcu01", "schilcu01", "schilcu01", "schilcu01", "schilcu01", "schilcu01", "schilcu01", "schilcu01", "schilcu01", 
+#> "schilcu01", "schilcu01", "montgje01", "montgje01", "montgje01", "montgje01", "montgje01", "montgje01", "montgje01", "montgje01", "montgje01", "montgje01", "montgje01", "montgje01", "montgje01", "salmoti01", "salmoti01", "salmoti01", "salmoti01", "salmoti01", "salmoti01", "salmoti01", "salmoti01", "salmoti01", "salmoti01", "salmoti01", "salmoti01", "salmoti01", "salmoti01", "piazzmi01", "piazzmi01", "piazzmi01", "piazzmi01", "piazzmi01", "piazzmi01", "piazzmi01", "piazzmi01", "piazzmi01", "piazzmi01", 
+#> "piazzmi01", "piazzmi01", "piazzmi01", "piazzmi01", "piazzmi01", "piazzmi01", "piazzmi01", "piazzmi01", "baergca01", "baergca01", "baergca01", "baergca01", "baergca01", "baergca01", "baergca01", "baergca01", "baergca01", "baergca01", "baergca01", "baergca01", "baergca01", "baergca01", "baergca01", "baergca01", "stanlmi02", "stanlmi02", "stanlmi02", "stanlmi02", "stanlmi02", "stanlmi02", "stanlmi02", "stanlmi02", "stanlmi02", "stanlmi02", "stanlmi02", "stanlmi02", "stanlmi02", "stanlmi02", "stanlmi02", 
+#> "stanlmi02", "stanlmi02", "stanlmi02", "belleal01", "belleal01", "belleal01", "belleal01", "belleal01", "belleal01", "belleal01", "belleal01", "belleal01", "belleal01", "belleal01", "belleal01", "dykstle01", "dykstle01", "dykstle01", "dykstle01", "dykstle01", "dykstle01", "dykstle01", "dykstle01", "dykstle01", "dykstle01", "dykstle01", "dykstle01", "dykstle01", "coneda01", "coneda01", "coneda01", "coneda01", "coneda01", "coneda01", "coneda01", "coneda01", "coneda01", "coneda01", "coneda01", "coneda01", 
+#> "coneda01", "coneda01", "coneda01", "coneda01", "coneda01", "coneda01", "coneda01", "lewisda01", "lewisda01", "lewisda01", "lewisda01", "lewisda01", "lewisda01", "lewisda01", "lewisda01", "lewisda01", "lewisda01", "lewisda01", "lewisda01", "lewisda01", "lewisda01", "lewisda01", "beckro01", "beckro01", "beckro01", "beckro01", "beckro01", "beckro01", "beckro01", "beckro01", "beckro01", "beckro01", "beckro01", "beckro01", "beckro01", "beckro01", "hamelbo01", "hamelbo01", "hamelbo01", "hamelbo01", "hamelbo01", 
+#> "hamelbo01", "mondera01", "mondera01", "mondera01", "mondera01", "mondera01", "mondera01", "mondera01", "mondera01", "mondera01", "mondera01", "mondera01", "mondera01", "mondera01", "mondera01", "mondera01", "mondera01", "aloumo01", "aloumo01", "aloumo01", "aloumo01", "aloumo01", "aloumo01", "aloumo01", "aloumo01", "aloumo01", "aloumo01", "aloumo01", "aloumo01", "aloumo01", "aloumo01", "aloumo01", "aloumo01", "aloumo01", "aloumo01", "portuma01", "portuma01", "portuma01", "portuma01", "portuma01", 
+#> "portuma01", "portuma01", "portuma01", "portuma01", "portuma01", "portuma01", "portuma01", "portuma01", "portuma01", "portuma01", "portuma01", "cordewi01", "cordewi01", "cordewi01", "cordewi01", "cordewi01", "cordewi01", "cordewi01", "cordewi01", "cordewi01", "cordewi01", "cordewi01", "cordewi01", "cordewi01", "cordewi01", "cordewi01", "cordewi01", "coninje01", "coninje01", "coninje01", "coninje01", "coninje01", "coninje01", "coninje01", "coninje01", "coninje01", "coninje01", "coninje01", "coninje01", 
+#> "coninje01", "coninje01", "coninje01", "coninje01", "coninje01", "coninje01", "coninje01", "coninje01", "johnsra05", "johnsra05", "johnsra05", "johnsra05", "johnsra05", "johnsra05", "johnsra05", "johnsra05", "johnsra05", "johnsra05", "johnsra05", "johnsra05", "johnsra05", "johnsra05", "johnsra05", "johnsra05", "johnsra05", "johnsra05", "johnsra05", "johnsra05", "johnsra05", "johnsra05", "johnsra05", "johnsra05", "snowjt01", "snowjt01", "snowjt01", "snowjt01", "snowjt01", "snowjt01", "snowjt01", "snowjt01", 
+#> "snowjt01", "snowjt01", "snowjt01", "snowjt01", "snowjt01", "snowjt01", "snowjt01", "snowjt01", "caminke01", "caminke01", "caminke01", "caminke01", "caminke01", "caminke01", "caminke01", "caminke01", "caminke01", "caminke01", "caminke01", "caminke01", "caminke01", "caminke01", "caminke01", "caminke01", "johnsch04", "johnsch04", "johnsch04", "johnsch04", "johnsch04", "johnsch04", "johnsch04", "johnsch04", "johnsch04", "johnsch04", "johnsch04", "johnsch04", "johnsch04", "johnsch04", "finlest01", "finlest01", 
+#> "finlest01", "finlest01", "finlest01", "finlest01", "finlest01", "finlest01", "finlest01", "finlest01", "finlest01", "finlest01", "finlest01", "finlest01", "finlest01", "finlest01", "finlest01", "finlest01", "finlest01", "finlest01", "vaughmo01", "vaughmo01", "vaughmo01", "vaughmo01", "vaughmo01", "vaughmo01", "vaughmo01", "vaughmo01", "vaughmo01", "vaughmo01", "vaughmo01", "vaughmo01", "mesajo01", "mesajo01", "mesajo01", "mesajo01", "mesajo01", "mesajo01", "mesajo01", "mesajo01", "mesajo01", "mesajo01", 
+#> "mesajo01", "mesajo01", "mesajo01", "mesajo01", "mesajo01", "mesajo01", "mesajo01", "mesajo01", "mesajo01", "mesajo01", "mesajo01", "mesajo01", "henketo01", "henketo01", "henketo01", "henketo01", "henketo01", "henketo01", "henketo01", "henketo01", "henketo01", "henketo01", "henketo01", "henketo01", "henketo01", "henketo01", "cordoma01", "cordoma01", "cordoma01", "cordoma01", "cordoma01", "cordoma01", "cordoma01", "cordoma01", "cordoma01", "nomohi01", "nomohi01", "nomohi01", "nomohi01", "nomohi01", 
+#> "nomohi01", "nomohi01", "nomohi01", "nomohi01", "nomohi01", "nomohi01", "nomohi01", "nomohi01", "ramirma02", "ramirma02", "ramirma02", "ramirma02", "ramirma02", "ramirma02", "ramirma02", "ramirma02", "ramirma02", "ramirma02", "ramirma02", "ramirma02", "ramirma02", "ramirma02", "ramirma02", "ramirma02", "ramirma02", "ramirma02", "ramirma02", "ramirma02", "ramirma02", "valenjo02", "valenjo02", "valenjo02", "valenjo02", "valenjo02", "valenjo02", "valenjo02", "valenjo02", "valenjo02", "valenjo02", "valenjo02", 
+#> "castivi02", "castivi02", "castivi02", "castivi02", "castivi02", "castivi02", "castivi02", "castivi02", "castivi02", "castivi02", "castivi02", "castivi02", "castivi02", "castivi02", "castivi02", "castivi02", "castivi02", "castivi02", "bicheda01", "bicheda01", "bicheda01", "bicheda01", "bicheda01", "bicheda01", "bicheda01", "bicheda01", "bicheda01", "bicheda01", "bicheda01", "bicheda01", "bicheda01", "bicheda01", "bicheda01", "sosasa01", "sosasa01", "sosasa01", "sosasa01", "sosasa01", "sosasa01", 
+#> "sosasa01", "sosasa01", "sosasa01", "sosasa01", "sosasa01", "sosasa01", "sosasa01", "sosasa01", "sosasa01", "sosasa01", "sosasa01", "sosasa01", "sosasa01", "thomeji01", "thomeji01", "thomeji01", "thomeji01", "thomeji01", "thomeji01", "thomeji01", "thomeji01", "thomeji01", "thomeji01", "thomeji01", "thomeji01", "thomeji01", "thomeji01", "thomeji01", "thomeji01", "thomeji01", "thomeji01", "thomeji01", "thomeji01", "thomeji01", "thomeji01", "thomeji01", "thomeji01", "thomeji01", "edmonji01", "edmonji01", 
+#> "edmonji01", "edmonji01", "edmonji01", "edmonji01", "edmonji01", "edmonji01", "edmonji01", "edmonji01", "edmonji01", "edmonji01", "edmonji01", "edmonji01", "edmonji01", "edmonji01", "edmonji01", "edmonji01", "edmonji01", "mussimi01", "mussimi01", "mussimi01", "mussimi01", "mussimi01", "mussimi01", "mussimi01", "mussimi01", "mussimi01", "mussimi01", "mussimi01", "mussimi01", "mussimi01", "mussimi01", "mussimi01", "mussimi01", "mussimi01", "mussimi01", "schoupe01", "schoupe01", "schoupe01", "schoupe01", 
+#> "schoupe01", "schoupe01", "schoupe01", "schoupe01", "schoupe01", "schoupe01", "schoupe01", "schoupe01", "sandere02", "sandere02", "sandere02", "sandere02", "sandere02", "sandere02", "sandere02", "sandere02", "sandere02", "sandere02", "sandere02", "sandere02", "sandere02", "sandere02", "sandere02", "sandere02", "sandere02", "willibe02", "willibe02", "willibe02", "willibe02", "willibe02", "willibe02", "willibe02", "willibe02", "willibe02", "willibe02", "willibe02", "willibe02", "willibe02", "willibe02", 
+#> "willibe02", "willibe02", "butlebr01", "butlebr01", "butlebr01", "butlebr01", "butlebr01", "butlebr01", "butlebr01", "butlebr01", "butlebr01", "butlebr01", "butlebr01", "butlebr01", "butlebr01", "butlebr01", "butlebr01", "butlebr01", "butlebr01", "butlebr01", "hentgpa01", "hentgpa01", "hentgpa01", "hentgpa01", "hentgpa01", "hentgpa01", "hentgpa01", "hentgpa01", "hentgpa01", "hentgpa01", "hentgpa01", "hentgpa01", "hentgpa01", "hentgpa01", "buhneja01", "buhneja01", "buhneja01", "buhneja01", "buhneja01", 
+#> "buhneja01", "buhneja01", "buhneja01", "buhneja01", "buhneja01", "buhneja01", "buhneja01", "buhneja01", "buhneja01", "buhneja01", "buhneja01", "lopezja01", "lopezja01", "lopezja01", "lopezja01", "lopezja01", "lopezja01", "lopezja01", "lopezja01", "lopezja01", "lopezja01", "lopezja01", "lopezja01", "lopezja01", "lopezja01", "lopezja01", "lopezja01", "wettejo01", "wettejo01", "wettejo01", "wettejo01", "wettejo01", "wettejo01", "wettejo01", "wettejo01", "wettejo01", "wettejo01", "wettejo01", "wettejo01", 
+#> "brantje01", "brantje01", "brantje01", "brantje01", "brantje01", "brantje01", "brantje01", "brantje01", "brantje01", "brantje01", "brantje01", "brantje01", "brantje01", "brantje01", "jeterde01", "jeterde01", "jeterde01", "jeterde01", "jeterde01", "jeterde01", "jeterde01", "jeterde01", "jeterde01", "jeterde01", "jeterde01", "jeterde01", "jeterde01", "jeterde01", "jeterde01", "jeterde01", "jeterde01", "jeterde01", "jeterde01", "jeterde01", "hollato01", "hollato01", "hollato01", "hollato01", "hollato01", 
+#> "hollato01", "hollato01", "hollato01", "hollato01", "hollato01", "hollato01", "hollato01", "hollato01", "hollato01", "hollato01", "hollato01", "rodrial01", "rodrial01", "rodrial01", "rodrial01", "rodrial01", "rodrial01", "rodrial01", "rodrial01", "rodrial01", "rodrial01", "rodrial01", "rodrial01", "rodrial01", "rodrial01", "rodrial01", "rodrial01", "rodrial01", "rodrial01", "rodrial01", "rodrial01", "rodrial01", "younger01", "younger01", "younger01", "younger01", "younger01", "younger01", "younger01", 
+#> "younger01", "younger01", "younger01", "younger01", "younger01", "younger01", "younger01", "younger01", "younger01", "younger01", "younger01", "pettian01", "pettian01", "pettian01", "pettian01", "pettian01", "pettian01", "pettian01", "pettian01", "pettian01", "pettian01", "pettian01", "pettian01", "pettian01", "pettian01", "pettian01", "pettian01", "pettian01", "pettian01", "leiteal01", "leiteal01", "leiteal01", "leiteal01", "leiteal01", "leiteal01", "leiteal01", "leiteal01", "leiteal01", "leiteal01", 
+#> "leiteal01", "leiteal01", "leiteal01", "leiteal01", "leiteal01", "leiteal01", "leiteal01", "leiteal01", "leiteal01", "leiteal01", "leiteal01", "hoffmtr01", "hoffmtr01", "hoffmtr01", "hoffmtr01", "hoffmtr01", "hoffmtr01", "hoffmtr01", "hoffmtr01", "hoffmtr01", "hoffmtr01", "hoffmtr01", "hoffmtr01", "hoffmtr01", "hoffmtr01", "hoffmtr01", "hoffmtr01", "hoffmtr01", "hoffmtr01", "hoffmtr01", "martipe02", "martipe02", "martipe02", "martipe02", "martipe02", "martipe02", "martipe02", "martipe02", "martipe02", 
+#> "martipe02", "martipe02", "martipe02", "martipe02", "martipe02", "martipe02", "martipe02", "martipe02", "martipe02", "palmera01", "palmera01", "palmera01", "palmera01", "palmera01", "palmera01", "palmera01", "palmera01", "palmera01", "palmera01", "palmera01", "palmera01", "palmera01", "palmera01", "palmera01", "palmera01", "palmera01", "palmera01", "palmera01", "palmera01", "ordonre01", "ordonre01", "ordonre01", "ordonre01", "ordonre01", "ordonre01", "ordonre01", "ordonre01", "ordonre01", "hernali01", 
+#> "hernali01", "hernali01", "hernali01", "hernali01", "hernali01", "hernali01", "hernali01", "hernali01", "hernali01", "hernali01", "hernali01", "hernali01", "hernali01", "hernali01", "hernali01", "hernali01", "hernali01", "hernali01", "hernali01", "hernali01", "hernali01", "shawje01", "shawje01", "shawje01", "shawje01", "shawje01", "shawje01", "shawje01", "shawje01", "shawje01", "shawje01", "shawje01", "shawje01", "shawje01", "shawje01", "garcino01", "garcino01", "garcino01", "garcino01", "garcino01", 
+#> "garcino01", "garcino01", "garcino01", "garcino01", "garcino01", "garcino01", "garcino01", "garcino01", "garcino01", "garcino01", "rolensc01", "rolensc01", "rolensc01", "rolensc01", "rolensc01", "rolensc01", "rolensc01", "rolensc01", "rolensc01", "rolensc01", "rolensc01", "rolensc01", "rolensc01", "rolensc01", "rolensc01", "rolensc01", "rolensc01", "rolensc01", "rolensc01", "martiti02", "martiti02", "martiti02", "martiti02", "martiti02", "martiti02", "martiti02", "martiti02", "martiti02", "martiti02", 
+#> "martiti02", "martiti02", "martiti02", "martiti02", "martiti02", "martiti02", "blausje01", "blausje01", "blausje01", "blausje01", "blausje01", "blausje01", "blausje01", "blausje01", "blausje01", "blausje01", "blausje01", "blausje01", "blausje01", "neaglde01", "neaglde01", "neaglde01", "neaglde01", "neaglde01", "neaglde01", "neaglde01", "neaglde01", "neaglde01", "neaglde01", "neaglde01", "neaglde01", "neaglde01", "neaglde01", "neaglde01", "riverma01", "riverma01", "riverma01", "riverma01", "riverma01", 
+#> "riverma01", "riverma01", "riverma01", "riverma01", "riverma01", "riverma01", "riverma01", "riverma01", "riverma01", "riverma01", "riverma01", "riverma01", "riverma01", "riverma01", "wellsda01", "wellsda01", "wellsda01", "wellsda01", "wellsda01", "wellsda01", "wellsda01", "wellsda01", "wellsda01", "wellsda01", "wellsda01", "wellsda01", "wellsda01", "wellsda01", "wellsda01", "wellsda01", "wellsda01", "wellsda01", "wellsda01", "wellsda01", "wellsda01", "wellsda01", "wellsda01", "wellsda01", "brosisc01", 
+#> "brosisc01", "brosisc01", "brosisc01", "brosisc01", "brosisc01", "brosisc01", "brosisc01", "brosisc01", "brosisc01", "brosisc01", "boonebr01", "boonebr01", "boonebr01", "boonebr01", "boonebr01", "boonebr01", "boonebr01", "boonebr01", "boonebr01", "boonebr01", "boonebr01", "boonebr01", "boonebr01", "boonebr01", "boonebr01", "jonesan01", "jonesan01", "jonesan01", "jonesan01", "jonesan01", "jonesan01", "jonesan01", "jonesan01", "jonesan01", "jonesan01", "jonesan01", "jonesan01", "jonesan01", "jonesan01", 
+#> "jonesan01", "jonesan01", "jonesan01", "hitchst01", "hitchst01", "hitchst01", "hitchst01", "hitchst01", "hitchst01", "hitchst01", "hitchst01", "hitchst01", "hitchst01", "hitchst01", "hitchst01", "hitchst01", "hitchst01", "hitchst01", "gordoto01", "gordoto01", "gordoto01", "gordoto01", "gordoto01", "gordoto01", "gordoto01", "gordoto01", "gordoto01", "gordoto01", "gordoto01", "gordoto01", "gordoto01", "gordoto01", "gordoto01", "gordoto01", "gordoto01", "gordoto01", "gordoto01", "gordoto01", "gordoto01", 
+#> "gordoto01", "grievbe01", "grievbe01", "grievbe01", "grievbe01", "grievbe01", "grievbe01", "grievbe01", "grievbe01", "grievbe01", "grievbe01", "woodke02", "woodke02", "woodke02", "woodke02", "woodke02", "woodke02", "woodke02", "woodke02", "woodke02", "woodke02", "woodke02", "woodke02", "woodke02", "woodke02", "woodke02", "easleda01", "easleda01", "easleda01", "easleda01", "easleda01", "easleda01", "easleda01", "easleda01", "easleda01", "easleda01", "easleda01", "easleda01", "easleda01", "easleda01", 
+#> "easleda01", "easleda01", "easleda01", "easleda01", "palmede01", "palmede01", "palmede01", "palmede01", "palmede01", "palmede01", "palmede01", "palmede01", "palmede01", "palmede01", "palmede01", "palmede01", "palmede01", "palmede01", "palmede01", "vaughgr01", "vaughgr01", "vaughgr01", "vaughgr01", "vaughgr01", "vaughgr01", "vaughgr01", "vaughgr01", "vaughgr01", "vaughgr01", "vaughgr01", "vaughgr01", "vaughgr01", "vaughgr01", "vaughgr01", "vaughgr01", "brownke01", "brownke01", "brownke01", "brownke01", 
+#> "brownke01", "brownke01", "brownke01", "brownke01", "brownke01", "brownke01", "brownke01", "brownke01", "brownke01", "brownke01", "brownke01", "brownke01", "brownke01", "brownke01", "brownke01", "hernaor01", "hernaor01", "hernaor01", "hernaor01", "hernaor01", "hernaor01", "hernaor01", "hernaor01", "hernaor01", "hernaor01", "greensh01", "greensh01", "greensh01", "greensh01", "greensh01", "greensh01", "greensh01", "greensh01", "greensh01", "greensh01", "greensh01", "greensh01", "greensh01", "greensh01", 
+#> "greensh01", "greensh01", "reesepo01", "reesepo01", "reesepo01", "reesepo01", "reesepo01", "reesepo01", "reesepo01", "reesepo01", "liebemi01", "liebemi01", "liebemi01", "liebemi01", "liebemi01", "liebemi01", "liebemi01", "liebemi01", "liebemi01", "liebemi01", "liebemi01", "liebemi01", "liebemi01", "liebemi01", "caseyse01", "caseyse01", "caseyse01", "caseyse01", "caseyse01", "caseyse01", "caseyse01", "caseyse01", "caseyse01", "caseyse01", "caseyse01", "caseyse01", "caseyse01", "jonesch06", "jonesch06", 
+#> "jonesch06", "jonesch06", "jonesch06", "jonesch06", "jonesch06", "jonesch06", "jonesch06", "jonesch06", "jonesch06", "jonesch06", "jonesch06", "jonesch06", "jonesch06", "jonesch06", "jonesch06", "jonesch06", "jonesch06", "perezed02", "perezed02", "perezed02", "perezed02", "perezed02", "perezed02", "perezed02", "perezed02", "perezed02", "perezed02", "perezed02", "wagnebi02", "wagnebi02", "wagnebi02", "wagnebi02", "wagnebi02", "wagnebi02", "wagnebi02", "wagnebi02", "wagnebi02", "wagnebi02", "wagnebi02", 
+#> "wagnebi02", "wagnebi02", "wagnebi02", "wagnebi02", "wagnebi02", "wagnebi02", "beltrca01", "beltrca01", "beltrca01", "beltrca01", "beltrca01", "beltrca01", "beltrca01", "beltrca01", "beltrca01", "beltrca01", "beltrca01", "beltrca01", "beltrca01", "beltrca01", "beltrca01", "beltrca01", "beltrca01", "beltrca01", "beltrca01", "beltrca01", "willisc01", "willisc01", "willisc01", "willisc01", "willisc01", "willisc01", "willisc01", "willisc01", "willisc01", "willisc01", "willisc01", "delgaca01", "delgaca01", 
+#> "delgaca01", "delgaca01", "delgaca01", "delgaca01", "delgaca01", "delgaca01", "delgaca01", "delgaca01", "delgaca01", "delgaca01", "delgaca01", "delgaca01", "delgaca01", "delgaca01", "delgaca01", "alfoned01", "alfoned01", "alfoned01", "alfoned01", "alfoned01", "alfoned01", "alfoned01", "alfoned01", "alfoned01", "alfoned01", "alfoned01", "alfoned01", "alfoned01", "guerrvl01", "guerrvl01", "guerrvl01", "guerrvl01", "guerrvl01", "guerrvl01", "guerrvl01", "guerrvl01", "guerrvl01", "guerrvl01", "guerrvl01", 
+#> "guerrvl01", "guerrvl01", "guerrvl01", "guerrvl01", "guerrvl01", "hamptmi01", "hamptmi01", "hamptmi01", "hamptmi01", "hamptmi01", "hamptmi01", "hamptmi01", "hamptmi01", "hamptmi01", "hamptmi01", "hamptmi01", "hamptmi01", "hamptmi01", "hamptmi01", "hamptmi01", "hamptmi01", "moyerja01", "moyerja01", "moyerja01", "moyerja01", "moyerja01", "moyerja01", "moyerja01", "moyerja01", "moyerja01", "moyerja01", "moyerja01", "moyerja01", "moyerja01", "moyerja01", "moyerja01", "moyerja01", "moyerja01", "moyerja01", 
+#> "moyerja01", "moyerja01", "moyerja01", "moyerja01", "moyerja01", "moyerja01", "moyerja01", "moyerja01", "moyerja01", "limajo01", "limajo01", "limajo01", "limajo01", "limajo01", "limajo01", "limajo01", "limajo01", "limajo01", "limajo01", "limajo01", "limajo01", "limajo01", "limajo01", "urbinug01", "urbinug01", "urbinug01", "urbinug01", "urbinug01", "urbinug01", "urbinug01", "urbinug01", "urbinug01", "urbinug01", "urbinug01", "urbinug01", "urbinug01", "urbinug01", "stottto01", "stottto01", "stottto01", 
+#> "stottto01", "stottto01", "stottto01", "stottto01", "stottto01", "stottto01", "stottto01", "stottto01", "stottto01", "stottto01", "stottto01", "stottto01", "dyeje01", "dyeje01", "dyeje01", "dyeje01", "dyeje01", "dyeje01", "dyeje01", "dyeje01", "dyeje01", "dyeje01", "dyeje01", "dyeje01", "dyeje01", "dyeje01", "dyeje01", "erstada01", "erstada01", "erstada01", "erstada01", "erstada01", "erstada01", "erstada01", "erstada01", "erstada01", "erstada01", "erstada01", "erstada01", "erstada01", "erstada01", 
+#> "rogerke01", "rogerke01", "rogerke01", "rogerke01", "rogerke01", "rogerke01", "rogerke01", "rogerke01", "rogerke01", "rogerke01", "rogerke01", "rogerke01", "rogerke01", "rogerke01", "rogerke01", "rogerke01", "rogerke01", "rogerke01", "rogerke01", "rogerke01", "rogerke01", "mathemi01", "mathemi01", "mathemi01", "mathemi01", "mathemi01", "mathemi01", "mathemi01", "mathemi01", "mathemi01", "mathemi01", "mathemi01", "mathemi01", "mathemi01", "perezne01", "perezne01", "perezne01", "perezne01", "perezne01", 
+#> "perezne01", "perezne01", "perezne01", "perezne01", "perezne01", "perezne01", "perezne01", "perezne01", "perezne01", "perezne01", "heltoto01", "heltoto01", "heltoto01", "heltoto01", "heltoto01", "heltoto01", "heltoto01", "heltoto01", "heltoto01", "heltoto01", "heltoto01", "heltoto01", "heltoto01", "heltoto01", "heltoto01", "heltoto01", "heltoto01", "giambja01", "giambja01", "giambja01", "giambja01", "giambja01", "giambja01", "giambja01", "giambja01", "giambja01", "giambja01", "giambja01", "giambja01", 
+#> "giambja01", "giambja01", "giambja01", "giambja01", "giambja01", "giambja01", "giambja01", "giambja01", "giambja01", "kentje01", "kentje01", "kentje01", "kentje01", "kentje01", "kentje01", "kentje01", "kentje01", "kentje01", "kentje01", "kentje01", "kentje01", "kentje01", "kentje01", "kentje01", "kentje01", "kentje01", "kentje01", "kentje01", "jonesto02", "jonesto02", "jonesto02", "jonesto02", "jonesto02", "jonesto02", "jonesto02", "jonesto02", "jonesto02", "jonesto02", "jonesto02", "jonesto02", 
+#> "jonesto02", "jonesto02", "jonesto02", "jonesto02", "jonesto02", "jonesto02", "jonesto02", "alfonan01", "alfonan01", "alfonan01", "alfonan01", "alfonan01", "alfonan01", "alfonan01", "alfonan01", "alfonan01", "alfonan01", "alfonan01", "sasakka01", "sasakka01", "sasakka01", "sasakka01", "furcara01", "furcara01", "furcara01", "furcara01", "furcara01", "furcara01", "furcara01", "furcara01", "furcara01", "furcara01", "furcara01", "furcara01", "furcara01", "furcara01", "furcara01", "glaustr01", "glaustr01", 
+#> "glaustr01", "glaustr01", "glaustr01", "glaustr01", "glaustr01", "glaustr01", "glaustr01", "glaustr01", "glaustr01", "glaustr01", "glaustr01", "posadjo01", "posadjo01", "posadjo01", "posadjo01", "posadjo01", "posadjo01", "posadjo01", "posadjo01", "posadjo01", "posadjo01", "posadjo01", "posadjo01", "posadjo01", "posadjo01", "posadjo01", "posadjo01", "posadjo01", "ordonma01", "ordonma01", "ordonma01", "ordonma01", "ordonma01", "ordonma01", "ordonma01", "ordonma01", "ordonma01", "ordonma01", "ordonma01", 
+#> "ordonma01", "ordonma01", "ordonma01", "ordonma01", "renteed01", "renteed01", "renteed01", "renteed01", "renteed01", "renteed01", "renteed01", "renteed01", "renteed01", "renteed01", "renteed01", "renteed01", "renteed01", "renteed01", "renteed01", "renteed01", "mientdo01", "mientdo01", "mientdo01", "mientdo01", "mientdo01", "mientdo01", "mientdo01", "mientdo01", "mientdo01", "mientdo01", "mientdo01", "mientdo01", "mientdo01", "chaveer01", "chaveer01", "chaveer01", "chaveer01", "chaveer01", "chaveer01", 
+#> "chaveer01", "chaveer01", "chaveer01", "chaveer01", "chaveer01", "chaveer01", "chaveer01", "chaveer01", "chaveer01", "chaveer01", "chaveer01", "camermi01", "camermi01", "camermi01", "camermi01", "camermi01", "camermi01", "camermi01", "camermi01", "camermi01", "camermi01", "camermi01", "camermi01", "camermi01", "camermi01", "camermi01", "camermi01", "camermi01", "camermi01", "hunteto01", "hunteto01", "hunteto01", "hunteto01", "hunteto01", "hunteto01", "hunteto01", "hunteto01", "hunteto01", "hunteto01", 
+#> "hunteto01", "hunteto01", "hunteto01", "hunteto01", "hunteto01", "hunteto01", "hunteto01", "hunteto01", "hunteto01", "suzukic01", "suzukic01", "suzukic01", "suzukic01", "suzukic01", "suzukic01", "suzukic01", "suzukic01", "suzukic01", "suzukic01", "suzukic01", "suzukic01", "suzukic01", "suzukic01", "suzukic01", "suzukic01", "vinafe01", "vinafe01", "vinafe01", "vinafe01", "vinafe01", "vinafe01", "vinafe01", "vinafe01", "vinafe01", "vinafe01", "vinafe01", "vinafe01", "ausmubr01", "ausmubr01", "ausmubr01", 
+#> "ausmubr01", "ausmubr01", "ausmubr01", "ausmubr01", "ausmubr01", "ausmubr01", "ausmubr01", "ausmubr01", "ausmubr01", "ausmubr01", "ausmubr01", "ausmubr01", "ausmubr01", "ausmubr01", "ausmubr01", "ausmubr01", "cabreor01", "cabreor01", "cabreor01", "cabreor01", "cabreor01", "cabreor01", "cabreor01", "cabreor01", "cabreor01", "cabreor01", "cabreor01", "cabreor01", "cabreor01", "cabreor01", "cabreor01", "cabreor01", "cabreor01", "cabreor01", "counscr01", "counscr01", "counscr01", "counscr01", "counscr01", 
+#> "counscr01", "counscr01", "counscr01", "counscr01", "counscr01", "counscr01", "counscr01", "counscr01", "counscr01", "counscr01", "counscr01", "counscr01", "counscr01", "benitar01", "benitar01", "benitar01", "benitar01", "benitar01", "benitar01", "benitar01", "benitar01", "benitar01", "benitar01", "benitar01", "benitar01", "benitar01", "benitar01", "benitar01", "benitar01", "benitar01", "benitar01", "pujolal01", "pujolal01", "pujolal01", "pujolal01", "pujolal01", "pujolal01", "pujolal01", "pujolal01", 
+#> "pujolal01", "pujolal01", "pujolal01", "pujolal01", "pujolal01", "pujolal01", "pujolal01", "gonzalu01", "gonzalu01", "gonzalu01", "gonzalu01", "gonzalu01", "gonzalu01", "gonzalu01", "gonzalu01", "gonzalu01", "gonzalu01", "gonzalu01", "gonzalu01", "gonzalu01", "gonzalu01", "gonzalu01", "gonzalu01", "gonzalu01", "gonzalu01", "gonzalu01", "gonzalu01", "aurilri01", "aurilri01", "aurilri01", "aurilri01", "aurilri01", "aurilri01", "aurilri01", "aurilri01", "aurilri01", "aurilri01", "aurilri01", "aurilri01", 
+#> "aurilri01", "aurilri01", "aurilri01", "aurilri01", "muldema01", "muldema01", "muldema01", "muldema01", "muldema01", "muldema01", "muldema01", "muldema01", "muldema01", "nenro01", "nenro01", "nenro01", "nenro01", "nenro01", "nenro01", "nenro01", "nenro01", "nenro01", "nenro01", "nenro01", "kennead01", "kennead01", "kennead01", "kennead01", "kennead01", "kennead01", "kennead01", "kennead01", "kennead01", "kennead01", "kennead01", "kennead01", "kennead01", "kennead01", "valenbo02", "valenbo02", "valenbo02", 
+#> "valenbo02", "valenbo02", "valenbo02", "valenbo02", "valenbo02", "valenbo02", "valenbo02", "valenbo02", "valenbo02", "zitoba01", "zitoba01", "zitoba01", "zitoba01", "zitoba01", "zitoba01", "zitoba01", "zitoba01", "zitoba01", "zitoba01", "zitoba01", "zitoba01", "zitoba01", "zitoba01", "zitoba01", "molinbe01", "molinbe01", "molinbe01", "molinbe01", "molinbe01", "molinbe01", "molinbe01", "molinbe01", "molinbe01", "molinbe01", "molinbe01", "molinbe01", "molinbe01", "molinbe01", "graveda01", "graveda01", 
+#> "graveda01", "graveda01", "graveda01", "graveda01", "graveda01", "graveda01", "graveda01", "graveda01", "graveda01", "graveda01", "graveda01", "tejadmi01", "tejadmi01", "tejadmi01", "tejadmi01", "tejadmi01", "tejadmi01", "tejadmi01", "tejadmi01", "tejadmi01", "tejadmi01", "tejadmi01", "tejadmi01", "tejadmi01", "tejadmi01", "tejadmi01", "tejadmi01", "tejadmi01", "kochbi01", "kochbi01", "kochbi01", "kochbi01", "kochbi01", "kochbi01", "kochbi01", "hinsker01", "hinsker01", "hinsker01", "hinsker01", "hinsker01", 
+#> "hinsker01", "hinsker01", "hinsker01", "hinsker01", "hinsker01", "hinsker01", "hinsker01", "hinsker01", "hinsker01", "jennija01", "jennija01", "jennija01", "jennija01", "jennija01", "jennija01", "jennija01", "jennija01", "jennija01", "soriaal01", "soriaal01", "soriaal01", "soriaal01", "soriaal01", "soriaal01", "soriaal01", "soriaal01", "soriaal01", "soriaal01", "soriaal01", "soriaal01", "soriaal01", "soriaal01", "soriaal01", "soriaal01", "soriaal01", "anderga01", "anderga01", "anderga01", "anderga01", 
+#> "anderga01", "anderga01", "anderga01", "anderga01", "anderga01", "anderga01", "anderga01", "anderga01", "anderga01", "anderga01", "anderga01", "anderga01", "anderga01", "lowede01", "lowede01", "lowede01", "lowede01", "lowede01", "lowede01", "lowede01", "lowede01", "lowede01", "lowede01", "lowede01", "lowede01", "lowede01", "lowede01", "lowede01", "lowede01", "lowede01", "lowede01", "lowede01", "beckejo02", "beckejo02", "beckejo02", "beckejo02", "beckejo02", "beckejo02", "beckejo02", "beckejo02", 
+#> "beckejo02", "beckejo02", "beckejo02", "beckejo02", "beckejo02", "beckejo02", "beckejo02", "hallaro01", "hallaro01", "hallaro01", "hallaro01", "hallaro01", "hallaro01", "hallaro01", "hallaro01", "hallaro01", "hallaro01", "hallaro01", "hallaro01", "hallaro01", "hallaro01", "hallaro01", "hallaro01", "gagneer01", "gagneer01", "gagneer01", "gagneer01", "gagneer01", "gagneer01", "gagneer01", "gagneer01", "gagneer01", "gagneer01", "gagneer01", "leede02", "leede02", "leede02", "leede02", "leede02", "leede02", 
+#> "leede02", "leede02", "leede02", "leede02", "leede02", "leede02", "leede02", "leede02", "leede02", "leede02", "leede02", "castilu01", "castilu01", "castilu01", "castilu01", "castilu01", "castilu01", "castilu01", "castilu01", "castilu01", "castilu01", "castilu01", "castilu01", "castilu01", "castilu01", "castilu01", "castilu01", "cruzjo02", "cruzjo02", "cruzjo02", "cruzjo02", "cruzjo02", "cruzjo02", "cruzjo02", "cruzjo02", "cruzjo02", "cruzjo02", "cruzjo02", "cruzjo02", "cruzjo02", "cruzjo02", "cruzjo02", 
+#> "foulkke01", "foulkke01", "foulkke01", "foulkke01", "foulkke01", "foulkke01", "foulkke01", "foulkke01", "foulkke01", "foulkke01", "foulkke01", "foulkke01", "berroan01", "berroan01", "berroan01", "berroan01", "berroan01", "berroan01", "berroan01", "berroan01", "berroan01", "berroan01", "willido03", "willido03", "willido03", "willido03", "willido03", "willido03", "willido03", "willido03", "willido03", "willido03", "muellbi02", "muellbi02", "muellbi02", "muellbi02", "muellbi02", "muellbi02", "muellbi02", 
+#> "muellbi02", "muellbi02", "muellbi02", "muellbi02", "muellbi02", "wellsve01", "wellsve01", "wellsve01", "wellsve01", "wellsve01", "wellsve01", "wellsve01", "wellsve01", "wellsve01", "wellsve01", "wellsve01", "wellsve01", "wellsve01", "wellsve01", "wellsve01", "vidrojo01", "vidrojo01", "vidrojo01", "vidrojo01", "vidrojo01", "vidrojo01", "vidrojo01", "vidrojo01", "vidrojo01", "vidrojo01", "vidrojo01", "vidrojo01", "lowelmi01", "lowelmi01", "lowelmi01", "lowelmi01", "lowelmi01", "lowelmi01", "lowelmi01", 
+#> "lowelmi01", "lowelmi01", "lowelmi01", "lowelmi01", "lowelmi01", "lowelmi01", "gilesma01", "gilesma01", "gilesma01", "gilesma01", "gilesma01", "gilesma01", "gilesma01", "wolfra02", "wolfra02", "wolfra02", "wolfra02", "wolfra02", "wolfra02", "wolfra02", "wolfra02", "wolfra02", "wolfra02", "wolfra02", "wolfra02", "wolfra02", "wolfra02", "wolfra02", "wolfra02", "wolfra02", "wolfra02", "ortizda01", "ortizda01", "ortizda01", "ortizda01", "ortizda01", "ortizda01", "ortizda01", "ortizda01", "ortizda01", 
+#> "ortizda01", "ortizda01", "ortizda01", "ortizda01", "ortizda01", "ortizda01", "ortizda01", "ortizda01", "ortizda01", "ortizda01", "santajo01", "santajo01", "santajo01", "santajo01", "santajo01", "santajo01", "santajo01", "santajo01", "santajo01", "santajo01", "santajo01", "santajo01", "izturce01", "izturce01", "izturce01", "izturce01", "izturce01", "izturce01", "izturce01", "izturce01", "izturce01", "izturce01", "izturce01", "izturce01", "izturce01", "izturce01", "izturce01", "izturce01", "crosbbo01", 
+#> "crosbbo01", "crosbbo01", "crosbbo01", "crosbbo01", "crosbbo01", "crosbbo01", "crosbbo01", "crosbbo01", "bayja01", "bayja01", "bayja01", "bayja01", "bayja01", "bayja01", "bayja01", "bayja01", "bayja01", "bayja01", "bayja01", "bayja01", "bayja01", "teixema01", "teixema01", "teixema01", "teixema01", "teixema01", "teixema01", "teixema01", "teixema01", "teixema01", "teixema01", "teixema01", "teixema01", "teixema01", "teixema01", "teixema01", "morame01", "morame01", "morame01", "morame01", "morame01", 
+#> "morame01", "morame01", "morame01", "morame01", "morame01", "morame01", "morame01", "morame01", "morame01", "martivi01", "martivi01", "martivi01", "martivi01", "martivi01", "martivi01", "martivi01", "martivi01", "martivi01", "martivi01", "martivi01", "martivi01", "martivi01", "martivi01", "loretma01", "loretma01", "loretma01", "loretma01", "loretma01", "loretma01", "loretma01", "loretma01", "loretma01", "loretma01", "loretma01", "loretma01", "loretma01", "loretma01", "loretma01", "loretma01", "beltrad01", 
+#> "beltrad01", "beltrad01", "beltrad01", "beltrad01", "beltrad01", "beltrad01", "beltrad01", "beltrad01", "beltrad01", "beltrad01", "beltrad01", "beltrad01", "beltrad01", "beltrad01", "beltrad01", "beltrad01", "beltrad01", "estrajo01", "estrajo01", "estrajo01", "estrajo01", "estrajo01", "estrajo01", "estrajo01", "estrajo01", "abreubo01", "abreubo01", "abreubo01", "abreubo01", "abreubo01", "abreubo01", "abreubo01", "abreubo01", "abreubo01", "abreubo01", "abreubo01", "abreubo01", "abreubo01", "abreubo01", 
+#> "abreubo01", "abreubo01", "abreubo01", "abreubo01", "abreubo01", "abreubo01", "wilsoja02", "wilsoja02", "wilsoja02", "wilsoja02", "wilsoja02", "wilsoja02", "wilsoja02", "wilsoja02", "wilsoja02", "wilsoja02", "wilsoja02", "wilsoja02", "wilsoja02", "wilsoja02", "konerpa01", "konerpa01", "konerpa01", "konerpa01", "konerpa01", "konerpa01", "konerpa01", "konerpa01", "konerpa01", "konerpa01", "konerpa01", "konerpa01", "konerpa01", "konerpa01", "konerpa01", "konerpa01", "konerpa01", "konerpa01", "konerpa01", 
+#> "drewjd01", "drewjd01", "drewjd01", "drewjd01", "drewjd01", "drewjd01", "drewjd01", "drewjd01", "drewjd01", "drewjd01", "drewjd01", "drewjd01", "drewjd01", "drewjd01", "schmija01", "schmija01", "schmija01", "schmija01", "schmija01", "schmija01", "schmija01", "schmija01", "schmija01", "schmija01", "schmija01", "schmija01", "schmija01", "schmija01", "schmija01", "schmija01", "nathajo01", "nathajo01", "nathajo01", "nathajo01", "nathajo01", "nathajo01", "nathajo01", "nathajo01", "nathajo01", "nathajo01", 
+#> "nathajo01", "nathajo01", "nathajo01", "nathajo01", "nathajo01", "colonba01", "colonba01", "colonba01", "colonba01", "colonba01", "colonba01", "colonba01", "colonba01", "colonba01", "colonba01", "colonba01", "colonba01", "colonba01", "colonba01", "colonba01", "colonba01", "colonba01", "colonba01", "colonba01", "carpech01", "carpech01", "carpech01", "carpech01", "carpech01", "carpech01", "carpech01", "carpech01", "carpech01", "carpech01", "carpech01", "carpech01", "carpech01", "carpech01", "carpech01", 
+#> "hudsoor01", "hudsoor01", "hudsoor01", "hudsoor01", "hudsoor01", "hudsoor01", "hudsoor01", "hudsoor01", "hudsoor01", "hudsoor01", "hudsoor01", "hudsoor01", "varitja01", "varitja01", "varitja01", "varitja01", "varitja01", "varitja01", "varitja01", "varitja01", "varitja01", "varitja01", "varitja01", "varitja01", "varitja01", "varitja01", "varitja01", "oswalro01", "oswalro01", "oswalro01", "oswalro01", "oswalro01", "oswalro01", "oswalro01", "oswalro01", "oswalro01", "oswalro01", "oswalro01", "oswalro01", 
+#> "oswalro01", "oswalro01", "cordech01", "cordech01", "cordech01", "cordech01", "cordech01", "cordech01", "cordech01", "streehu01", "streehu01", "streehu01", "streehu01", "streehu01", "streehu01", "streehu01", "streehu01", "streehu01", "streehu01", "streehu01", "streehu01", "howarry01", "howarry01", "howarry01", "howarry01", "howarry01", "howarry01", "howarry01", "howarry01", "howarry01", "howarry01", "howarry01", "howarry01", "ensbemo01", "ensbemo01", "ensbemo01", "ensbemo01", "ensbemo01", "ensbemo01", 
+#> "ensbemo01", "ensbemo01", "ensbemo01", "barremi01", "barremi01", "barremi01", "barremi01", "barremi01", "barremi01", "barremi01", "barremi01", "barremi01", "barremi01", "barremi01", "barremi01", "barremi01", "cabremi01", "cabremi01", "cabremi01", "cabremi01", "cabremi01", "cabremi01", "cabremi01", "cabremi01", "cabremi01", "cabremi01", "cabremi01", "cabremi01", "cabremi01", "leeca01", "leeca01", "leeca01", "leeca01", "leeca01", "leeca01", "leeca01", "leeca01", "leeca01", "leeca01", "leeca01", "leeca01", 
+#> "leeca01", "leeca01", "leeca01", "leeca01", "marquja01", "marquja01", "marquja01", "marquja01", "marquja01", "marquja01", "marquja01", "marquja01", "marquja01", "marquja01", "marquja01", "marquja01", "marquja01", "marquja01", "marquja01", "marquja01", "marquja01", "lopezfe01", "lopezfe01", "lopezfe01", "lopezfe01", "lopezfe01", "lopezfe01", "lopezfe01", "lopezfe01", "lopezfe01", "lopezfe01", "lopezfe01", "lopezfe01", "lopezfe01", "lopezfe01", "lopezfe01", "lopezfe01", "roberbr01", "roberbr01", "roberbr01", 
+#> "roberbr01", "roberbr01", "roberbr01", "roberbr01", "roberbr01", "roberbr01", "roberbr01", "roberbr01", "roberbr01", "roberbr01", "roberbr01", "damonjo01", "damonjo01", "damonjo01", "damonjo01", "damonjo01", "damonjo01", "damonjo01", "damonjo01", "damonjo01", "damonjo01", "damonjo01", "damonjo01", "damonjo01", "damonjo01", "damonjo01", "damonjo01", "damonjo01", "damonjo01", "youngmi02", "youngmi02", "youngmi02", "youngmi02", "youngmi02", "youngmi02", "youngmi02", "youngmi02", "youngmi02", "youngmi02", 
+#> "youngmi02", "youngmi02", "youngmi02", "youngmi02", "youngmi02", "loducpa01", "loducpa01", "loducpa01", "loducpa01", "loducpa01", "loducpa01", "loducpa01", "loducpa01", "loducpa01", "loducpa01", "loducpa01", "loducpa01", "loducpa01", "polanpl01", "polanpl01", "polanpl01", "polanpl01", "polanpl01", "polanpl01", "polanpl01", "polanpl01", "polanpl01", "polanpl01", "polanpl01", "polanpl01", "polanpl01", "polanpl01", "polanpl01", "polanpl01", "polanpl01", "polanpl01", "eckstda01", "eckstda01", "eckstda01", 
+#> "eckstda01", "eckstda01", "eckstda01", "eckstda01", "eckstda01", "eckstda01", "eckstda01", "eckstda01", "lasorto01", "lasorto01", "lasorto01", "johnsji04", "johnsji04", "johnsji04", "johnsji04", "johnsji04", "johnsji04", "johnsji04", "johnsji04", "johnsji04", "johnsji04", "johnsji04", "johnsji04", "webbbr01", "webbbr01", "webbbr01", "webbbr01", "webbbr01", "webbbr01", "webbbr01", "grudzma01", "grudzma01", "grudzma01", "grudzma01", "grudzma01", "grudzma01", "grudzma01", "grudzma01", "grudzma01", "grudzma01", 
+#> "grudzma01", "grudzma01", "grudzma01", "grudzma01", "grudzma01", "grudzma01", "morneju01", "morneju01", "morneju01", "morneju01", "morneju01", "morneju01", "morneju01", "morneju01", "morneju01", "morneju01", "morneju01", "morneju01", "morneju01", "morneju01", "suppaje01", "suppaje01", "suppaje01", "suppaje01", "suppaje01", "suppaje01", "suppaje01", "suppaje01", "suppaje01", "suppaje01", "suppaje01", "suppaje01", "suppaje01", "suppaje01", "suppaje01", "suppaje01", "suppaje01", "suppaje01", "suppaje01", 
+#> "suppaje01", "rodrifr03", "rodrifr03", "rodrifr03", "rodrifr03", "rodrifr03", "rodrifr03", "rodrifr03", "rodrifr03", "rodrifr03", "rodrifr03", "rodrifr03", "rodrifr03", "rodrifr03", "rodrifr03", "rodrifr03", "rodrifr03", "verlaju01", "verlaju01", "verlaju01", "verlaju01", "verlaju01", "verlaju01", "verlaju01", "verlaju01", "verlaju01", "verlaju01", "verlaju01", "ramirha01", "ramirha01", "ramirha01", "ramirha01", "ramirha01", "ramirha01", "ramirha01", "ramirha01", "ramirha01", "ramirha01", "ramirha01", 
+#> "ramirha01", "canoro01", "canoro01", "canoro01", "canoro01", "canoro01", "canoro01", "canoro01", "canoro01", "canoro01", "canoro01", "canoro01", "credejo01", "credejo01", "credejo01", "credejo01", "credejo01", "credejo01", "credejo01", "credejo01", "credejo01", "credejo01", "mauerjo01", "mauerjo01", "mauerjo01", "mauerjo01", "mauerjo01", "mauerjo01", "mauerjo01", "mauerjo01", "mauerjo01", "mauerjo01", "mauerjo01", "mauerjo01", "utleych01", "utleych01", "utleych01", "utleych01", "utleych01", "utleych01", 
+#> "utleych01", "utleych01", "utleych01", "utleych01", "utleych01", "utleych01", "utleych01", "utleych01", "mccanbr01", "mccanbr01", "mccanbr01", "mccanbr01", "mccanbr01", "mccanbr01", "mccanbr01", "mccanbr01", "mccanbr01", "mccanbr01", "mccanbr01", "hollima01", "hollima01", "hollima01", "hollima01", "hollima01", "hollima01", "hollima01", "hollima01", "hollima01", "hollima01", "hollima01", "hollima01", "hollima01", "zambrca01", "zambrca01", "zambrca01", "zambrca01", "zambrca01", "zambrca01", "zambrca01", 
+#> "zambrca01", "zambrca01", "zambrca01", "zambrca01", "zambrca01", "reyesjo01", "reyesjo01", "reyesjo01", "reyesjo01", "reyesjo01", "reyesjo01", "reyesjo01", "reyesjo01", "reyesjo01", "reyesjo01", "reyesjo01", "reyesjo01", "reyesjo01", "reyesjo01", "wrighda03", "wrighda03", "wrighda03", "wrighda03", "wrighda03", "wrighda03", "wrighda03", "wrighda03", "wrighda03", "wrighda03", "wrighda03", "wrighda03", "berkmla01", "berkmla01", "berkmla01", "berkmla01", "berkmla01", "berkmla01", "berkmla01", "berkmla01", 
+#> "berkmla01", "berkmla01", "berkmla01", "berkmla01", "berkmla01", "berkmla01", "berkmla01", "berkmla01", "papeljo01", "papeljo01", "papeljo01", "papeljo01", "papeljo01", "papeljo01", "papeljo01", "papeljo01", "papeljo01", "papeljo01", "papeljo01", "papeljo01", "penaca01", "penaca01", "penaca01", "penaca01", "penaca01", "penaca01", "penaca01", "penaca01", "penaca01", "penaca01", "penaca01", "penaca01", "penaca01", "penaca01", "penaca01", "penaca01", "youngdm01", "youngdm01", "youngdm01", "youngdm01", 
+#> "youngdm01", "youngdm01", "youngdm01", "youngdm01", "youngdm01", "youngdm01", "youngdm01", "youngdm01", "youngdm01", "sabatcc01", "sabatcc01", "sabatcc01", "sabatcc01", "sabatcc01", "sabatcc01", "sabatcc01", "sabatcc01", "sabatcc01", "sabatcc01", "sabatcc01", "sabatcc01", "sabatcc01", "sabatcc01", "sabatcc01", "sabatcc01", "peavyja01", "peavyja01", "peavyja01", "peavyja01", "peavyja01", "peavyja01", "peavyja01", "peavyja01", "peavyja01", "peavyja01", "peavyja01", "peavyja01", "peavyja01", "peavyja01", 
+#> "peavyja01", "peavyja01", "peavyja01", "youklke01", "youklke01", "youklke01", "youklke01", "youklke01", "youklke01", "youklke01", "youklke01", "youklke01", "youklke01", "youklke01", "sizemgr01", "sizemgr01", "sizemgr01", "sizemgr01", "sizemgr01", "sizemgr01", "sizemgr01", "sizemgr01", "sizemgr01", "sizemgr01", "sizemgr01", "sizemgr01", "martiru01", "martiru01", "martiru01", "martiru01", "martiru01", "martiru01", "martiru01", "martiru01", "martiru01", "martiru01", "francje02", "francje02", "francje02", 
+#> "francje02", "francje02", "francje02", "francje02", "francje02", "francje02", "francje02", "francje02", "francje02", "francje02", "francje02", "rowanaa01", "rowanaa01", "rowanaa01", "rowanaa01", "rowanaa01", "rowanaa01", "rowanaa01", "rowanaa01", "rowanaa01", "rowanaa01", "rowanaa01", "rolliji01", "rolliji01", "rolliji01", "rolliji01", "rolliji01", "rolliji01", "rolliji01", "rolliji01", "rolliji01", "rolliji01", "rolliji01", "rolliji01", "rolliji01", "rolliji01", "rolliji01", "rolliji01", "fieldpr01", 
+#> "fieldpr01", "fieldpr01", "fieldpr01", "fieldpr01", "fieldpr01", "fieldpr01", "fieldpr01", "fieldpr01", "fieldpr01", "fieldpr01", "sweenmi01", "sweenmi01", "sweenmi01", "sweenmi01", "sweenmi01", "sweenmi01", "sweenmi01", "sweenmi01", "sweenmi01", "sweenmi01", "sweenmi01", "sweenmi01", "sweenmi01", "sweenmi01", "sweenmi01", "sweenmi01", "sweenmi01", "timlimi01", "timlimi01", "timlimi01", "timlimi01", "timlimi01", "timlimi01", "timlimi01", "timlimi01", "timlimi01", "timlimi01", "timlimi01", "timlimi01", 
+#> "timlimi01", "timlimi01", "timlimi01", "timlimi01", "timlimi01", "timlimi01", "timlimi01", "timlimi01", "timlimi01", "putzjj01", "putzjj01", "putzjj01", "putzjj01", "putzjj01", "putzjj01", "putzjj01", "putzjj01", "putzjj01", "putzjj01", "putzjj01", "putzjj01", "valvejo01", "valvejo01", "valvejo01", "valvejo01", "valvejo01", "valvejo01", "valvejo01", "valvejo01", "valvejo01", "valvejo01", "valvejo01", "valvejo01", "pedrodu01", "pedrodu01", "pedrodu01", "pedrodu01", "pedrodu01", "pedrodu01", "pedrodu01", 
+#> "pedrodu01", "pedrodu01", "pedrodu01", "braunry02", "braunry02", "braunry02", "braunry02", "braunry02", "braunry02", "braunry02", "braunry02", "braunry02", "owingmi01", "owingmi01", "owingmi01", "owingmi01", "owingmi01", "owingmi01", "owingmi01", "borowjo01", "borowjo01", "borowjo01", "borowjo01", "borowjo01", "borowjo01", "borowjo01", "borowjo01", "borowjo01", "borowjo01", "borowjo01", "borowjo01", "borowjo01", "borowjo01", "garzama01", "garzama01", "garzama01", "garzama01", "garzama01", "garzama01", 
+#> "garzama01", "garzama01", "garzama01", "garzama01", "garzama01", "hamelco01", "hamelco01", "hamelco01", "hamelco01", "hamelco01", "hamelco01", "hamelco01", "hamelco01", "hamelco01", "hamelco01", "hamelco01", "leecl02", "leecl02", "leecl02", "leecl02", "leecl02", "leecl02", "leecl02", "leecl02", "leecl02", "leecl02", "leecl02", "leecl02", "leecl02", "leecl02", "leecl02", "lidgebr01", "lidgebr01", "lidgebr01", "lidgebr01", "lidgebr01", "lidgebr01", "lidgebr01", "lidgebr01", "lidgebr01", "lidgebr01", 
+#> "lidgebr01", "linceti01", "linceti01", "linceti01", "linceti01", "linceti01", "linceti01", "linceti01", "linceti01", "linceti01", "gonzaad01", "gonzaad01", "gonzaad01", "gonzaad01", "gonzaad01", "gonzaad01", "gonzaad01", "gonzaad01", "gonzaad01", "gonzaad01", "gonzaad01", "gonzaad01", "gonzaad01", "phillbr01", "phillbr01", "phillbr01", "phillbr01", "phillbr01", "phillbr01", "phillbr01", "phillbr01", "phillbr01", "phillbr01", "phillbr01", "phillbr01", "phillbr01", "phillbr01", "molinya01", "molinya01", 
+#> "molinya01", "molinya01", "molinya01", "molinya01", "molinya01", "molinya01", "molinya01", "molinya01", "molinya01", "molinya01", "mclouna01", "mclouna01", "mclouna01", "mclouna01", "mclouna01", "mclouna01", "mclouna01", "mclouna01", "mclouna01", "mclouna01", "mclouna01", "mclouna01", "victosh01", "victosh01", "victosh01", "victosh01", "victosh01", "victosh01", "victosh01", "victosh01", "victosh01", "victosh01", "victosh01", "victosh01", "victosh01", "victosh01", "ramirar01", "ramirar01", "ramirar01", 
+#> "ramirar01", "ramirar01", "ramirar01", "ramirar01", "ramirar01", "ramirar01", "ramirar01", "ramirar01", "ramirar01", "ramirar01", "ramirar01", "ramirar01", "ramirar01", "ramirar01", "ramirar01", "ramirar01", "ramirar01", "lestejo01", "lestejo01", "lestejo01", "lestejo01", "lestejo01", "lestejo01", "lestejo01", "lestejo01", "lestejo01", "lestejo01", "lestejo01", "longoev01", "longoev01", "longoev01", "longoev01", "longoev01", "longoev01", "longoev01", "longoev01", "sotoge01", "sotoge01", "sotoge01", 
+#> "sotoge01", "sotoge01", "sotoge01", "sotoge01", "sotoge01", "sotoge01", "sotoge01", "sotoge01", "sotoge01", "sotoge01", "huffau01", "huffau01", "huffau01", "huffau01", "huffau01", "huffau01", "huffau01", "huffau01", "huffau01", "huffau01", "huffau01", "huffau01", "huffau01", "huffau01", "huffau01", "hamiljo03", "hamiljo03", "hamiljo03", "hamiljo03", "hamiljo03", "hamiljo03", "hamiljo03", "hamiljo03", "hamiljo03", "quentca01", "quentca01", "quentca01", "quentca01", "quentca01", "quentca01", "quentca01", 
+#> "quentca01", "quentca01", "ludwiry01", "ludwiry01", "ludwiry01", "ludwiry01", "ludwiry01", "ludwiry01", "ludwiry01", "ludwiry01", "ludwiry01", "ludwiry01", "ludwiry01", "ludwiry01", "ludwiry01", "ludwiry01", "ludwiry01", "crawfca02", "crawfca02", "crawfca02", "crawfca02", "crawfca02", "crawfca02", "crawfca02", "crawfca02", "crawfca02", "crawfca02", "crawfca02", "crawfca02", "crawfca02", "crawfca02", "hillaa01", "hillaa01", "hillaa01", "hillaa01", "hillaa01", "hillaa01", "hillaa01", "hillaa01", "hillaa01", 
+#> "hillaa01", "hillaa01", "hillaa01", "carpech02", "carpech02", "greinza01", "greinza01", "greinza01", "greinza01", "greinza01", "greinza01", "greinza01", "greinza01", "greinza01", "greinza01", "greinza01", "greinza01", "greinza01", "jonesad01", "jonesad01", "jonesad01", "jonesad01", "jonesad01", "jonesad01", "jonesad01", "jonesad01", "jonesad01", "jonesad01", "buehrma01", "buehrma01", "buehrma01", "buehrma01", "buehrma01", "buehrma01", "buehrma01", "buehrma01", "buehrma01", "buehrma01", "buehrma01", 
+#> "buehrma01", "buehrma01", "buehrma01", "buehrma01", "buehrma01", "zimmery01", "zimmery01", "zimmery01", "zimmery01", "zimmery01", "zimmery01", "zimmery01", "zimmery01", "zimmery01", "zimmery01", "zimmery01", "bournmi01", "bournmi01", "bournmi01", "bournmi01", "bournmi01", "bournmi01", "bournmi01", "bournmi01", "bournmi01", "bournmi01", "bournmi01", "bournmi01", "kempma01", "kempma01", "kempma01", "kempma01", "kempma01", "kempma01", "kempma01", "kempma01", "kempma01", "kempma01", "wainwad01", "wainwad01", 
+#> "wainwad01", "wainwad01", "wainwad01", "wainwad01", "wainwad01", "wainwad01", "wainwad01", "wainwad01", "teahema01", "teahema01", "teahema01", "teahema01", "teahema01", "teahema01", "teahema01", "teahema01", "bellhe01", "bellhe01", "bellhe01", "bellhe01", "bellhe01", "bellhe01", "bellhe01", "bellhe01", "bellhe01", "bellhe01", "bellhe01", "bailean01", "bailean01", "bailean01", "bailean01", "bailean01", "bailean01", "coghlch01", "coghlch01", "coghlch01", "coghlch01", "coghlch01", "coghlch01", "coghlch01", 
+#> "lindad01", "lindad01", "lindad01", "lindad01", "lindad01", "lindad01", "lindad01", "lindad01", "lindad01", "lindad01", "ethiean01", "ethiean01", "ethiean01", "ethiean01", "ethiean01", "ethiean01", "ethiean01", "ethiean01", "ethiean01", "ethiean01", "frankry01", "frankry01", "frankry01", "frankry01", "frankry01", "frankry01", "frankry01", "frankry01", "frankry01", "frankry01", "frankry01", "frankry01", "frankry01", "matsuhi01", "matsuhi01", "matsuhi01", "matsuhi01", "matsuhi01", "matsuhi01", "matsuhi01", 
+#> "matsuhi01", "matsuhi01", "matsuhi01", "liriafr01", "liriafr01", "liriafr01", "liriafr01", "liriafr01", "liriafr01", "liriafr01", "liriafr01", "liriafr01", "liriafr01", "liriafr01", "hudsoti01", "hudsoti01", "hudsoti01", "hudsoti01", "hudsoti01", "hudsoti01", "hudsoti01", "hudsoti01", "hudsoti01", "hudsoti01", "hudsoti01", "hudsoti01", "hudsoti01", "hudsoti01", "hudsoti01", "hudsoti01", "hudsoti01", "hernafe02", "hernafe02", "hernafe02", "hernafe02", "hernafe02", "hernafe02", "hernafe02", "hernafe02", 
+#> "hernafe02", "hernafe02", "hernafe02", "gutiefr01", "gutiefr01", "gutiefr01", "gutiefr01", "gutiefr01", "gutiefr01", "gutiefr01", "gutiefr01", "gutiefr01", "gutiefr01", "gonzaca01", "gonzaca01", "gonzaca01", "gonzaca01", "gonzaca01", "gonzaca01", "gonzaca01", "gonzaca01", "arroybr01", "arroybr01", "arroybr01", "arroybr01", "arroybr01", "arroybr01", "arroybr01", "arroybr01", "arroybr01", "arroybr01", "arroybr01", "arroybr01", "arroybr01", "arroybr01", "arroybr01", "tulowtr01", "tulowtr01", "tulowtr01", 
+#> "tulowtr01", "tulowtr01", "tulowtr01", "tulowtr01", "tulowtr01", "tulowtr01", "tulowtr01", "tulowtr01", "bautijo02", "bautijo02", "bautijo02", "bautijo02", "bautijo02", "bautijo02", "bautijo02", "bautijo02", "bautijo02", "bautijo02", "bautijo02", "bautijo02", "bautijo02", "bautijo02", "bautijo02", "bautijo02", "vottojo01", "vottojo01", "vottojo01", "vottojo01", "vottojo01", "vottojo01", "vottojo01", "vottojo01", "vottojo01", "rossco01", "rossco01", "rossco01", "rossco01", "rossco01", "rossco01", 
+#> "rossco01", "rossco01", "rossco01", "rossco01", "rossco01", "rossco01", "rossco01", "rossco01", "rossco01", "wakefti01", "wakefti01", "wakefti01", "wakefti01", "wakefti01", "wakefti01", "wakefti01", "wakefti01", "wakefti01", "wakefti01", "wakefti01", "wakefti01", "wakefti01", "wakefti01", "wakefti01", "wakefti01", "wakefti01", "wakefti01", "wakefti01", "soriara01", "soriara01", "soriara01", "soriara01", "soriara01", "soriara01", "soriara01", "soriara01", "soriara01", "soriara01", "soriara01", "soriara01", 
+#> "soriara01", "soriara01", "felizne01", "felizne01", "felizne01", "felizne01", "felizne01", "felizne01", "felizne01", "felizne01", "poseybu01", "poseybu01", "poseybu01", "poseybu01", "poseybu01", "poseybu01", "poseybu01", "ramiral03", "ramiral03", "ramiral03", "ramiral03", "ramiral03", "ramiral03", "ramiral03", "ramiral03", "ugglada01", "ugglada01", "ugglada01", "ugglada01", "ugglada01", "ugglada01", "ugglada01", "ugglada01", "ugglada01", "ugglada01", "ugglada01", "gallayo01", "gallayo01", "gallayo01", 
+#> "gallayo01", "gallayo01", "gallayo01", "gallayo01", "gallayo01", "gallayo01", "cruzne02", "cruzne02", "cruzne02", "cruzne02", "cruzne02", "cruzne02", "cruzne02", "cruzne02", "cruzne02", "cruzne02", "cruzne02", "freesda01", "freesda01", "freesda01", "freesda01", "freesda01", "freesda01", "freesda01", "ellsbja01", "ellsbja01", "ellsbja01", "ellsbja01", "ellsbja01", "ellsbja01", "ellsbja01", "ellsbja01", "ellsbja01", "kershcl01", "kershcl01", "kershcl01", "kershcl01", "kershcl01", "kershcl01", "kershcl01", 
+#> "kershcl01", "wietema01", "wietema01", "wietema01", "wietema01", "wietema01", "wietema01", "wietema01", "gordoal01", "gordoal01", "gordoal01", "gordoal01", "gordoal01", "gordoal01", "gordoal01", "gordoal01", "gordoal01", "markani01", "markani01", "markani01", "markani01", "markani01", "markani01", "markani01", "markani01", "markani01", "markani01", "aybarer01", "aybarer01", "aybarer01", "aybarer01", "aybarer01", "aybarer01", "aybarer01", "aybarer01", "aybarer01", "aybarer01", "parrage01", "parrage01", 
+#> "parrage01", "parrage01", "parrage01", "parrage01", "parrage01", "parrage01", "parrage01", "butlebi03", "butlebi03", "butlebi03", "butlebi03", "butlebi03", "butlebi03", "butlebi03", "butlebi03", "butlebi03", "axforjo01", "axforjo01", "axforjo01", "axforjo01", "axforjo01", "axforjo01", "axforjo01", "axforjo01", "axforjo01", "hellije01", "hellije01", "hellije01", "hellije01", "hellije01", "hellije01", "kimbrcr01", "kimbrcr01", "kimbrcr01", "kimbrcr01", "kimbrcr01", "kimbrcr01", "avilaal01", "avilaal01", 
+#> "avilaal01", "avilaal01", "avilaal01", "avilaal01", "avilaal01", "grandcu01", "grandcu01", "grandcu01", "grandcu01", "grandcu01", "grandcu01", "grandcu01", "grandcu01", "grandcu01", "grandcu01", "grandcu01", "grandcu01", "cabreas01", "cabreas01", "cabreas01", "cabreas01", "cabreas01", "cabreas01", "cabreas01", "cabreas01", "cabreas01", "cabreas01", "uptonju01", "uptonju01", "uptonju01", "uptonju01", "uptonju01", "uptonju01", "uptonju01", "uptonju01", "uptonju01", "hudsoda01", "hudsoda01", "hudsoda01", 
+#> "hudsoda01", "hudsoda01", "hudsoda01", "hudsoda01", "youngde03", "youngde03", "youngde03", "youngde03", "youngde03", "youngde03", "youngde03", "youngde03", "youngde03", "youngde03", "youngde03", "youngde03", "cabreme01", "cabreme01", "cabreme01", "cabreme01", "cabreme01", "cabreme01", "cabreme01", "cabreme01", "cabreme01", "cabreme01", "cabreme01", "sandopa01", "sandopa01", "sandopa01", "sandopa01", "sandopa01", "sandopa01", "sandopa01", "sandopa01", "dickera01", "dickera01", "dickera01", "dickera01", 
+#> "dickera01", "dickera01", "dickera01", "dickera01", "dickera01", "dickera01", "dickera01", "dickera01", "dickera01", "rodnefe01", "rodnefe01", "rodnefe01", "rodnefe01", "rodnefe01", "rodnefe01", "rodnefe01", "rodnefe01", "rodnefe01", "rodnefe01", "rodnefe01", "rodnefe01", "rodnefe01", "rodnefe01", "priceda01", "priceda01", "priceda01", "priceda01", "priceda01", "priceda01", "priceda01", "priceda01", "priceda01", "priceda01", "reddijo01", "reddijo01", "reddijo01", "reddijo01", "reddijo01", "reddijo01", 
+#> "reddijo01", "hardyjj01", "hardyjj01", "hardyjj01", "hardyjj01", "hardyjj01", "hardyjj01", "hardyjj01", "hardyjj01", "hardyjj01", "hardyjj01", "hardyjj01", "larocad01", "larocad01", "larocad01", "larocad01", "larocad01", "larocad01", "larocad01", "larocad01", "larocad01", "larocad01", "larocad01", "larocad01", "larocad01", "larocad01", "barneda01", "barneda01", "barneda01", "barneda01", "barneda01", "barneda01", "barneda01", "barneda01", "headlch01", "headlch01", "headlch01", "headlch01", "headlch01", 
+#> "headlch01", "headlch01", "headlch01", "headlch01", "headlch01", "mccutan01", "mccutan01", "mccutan01", "mccutan01", "mccutan01", "mccutan01", "mccutan01", "heywaja01", "heywaja01", "heywaja01", "heywaja01", "heywaja01", "heywaja01", "scutama01", "scutama01", "scutama01", "scutama01", "scutama01", "scutama01", "scutama01", "scutama01", "scutama01", "scutama01", "scutama01", "scutama01", "scutama01", "scutama01", "troutmi01", "troutmi01", "troutmi01", "troutmi01", "troutmi01", "harpebr03", "harpebr03", 
+#> "harpebr03", "harpebr03", "pierzaj01", "pierzaj01", "pierzaj01", "pierzaj01", "pierzaj01", "pierzaj01", "pierzaj01", "pierzaj01", "pierzaj01", "pierzaj01", "pierzaj01", "pierzaj01", "pierzaj01", "pierzaj01", "pierzaj01", "pierzaj01", "pierzaj01", "pierzaj01", "pierzaj01", "willijo03", "willijo03", "willijo03", "willijo03", "willijo03", "willijo03", "willijo03", "willijo03", "willijo03", "willijo03", "willijo03", "willijo03", "braunry01", "braunry01", "bruceja01", "bruceja01", "bruceja01", "bruceja01", 
+#> "bruceja01", "bruceja01", "bruceja01", "bruceja01", "strasst01", "strasst01", "strasst01", "strasst01", "strasst01", "strasst01", "desmoia01", "desmoia01", "desmoia01", "desmoia01", "desmoia01", "desmoia01", "desmoia01", "ueharko01", "ueharko01", "ueharko01", "ueharko01", "ueharko01", "ueharko01", "ueharko01", "ueharko01", "scherma01", "scherma01", "scherma01", "scherma01", "scherma01", "scherma01", "scherma01", "scherma01", "hosmeer01", "hosmeer01", "hosmeer01", "hosmeer01", "hosmeer01", "machama01", 
+#> "machama01", "machama01", "machama01", "perezsa02", "perezsa02", "perezsa02", "perezsa02", "perezsa02", "goldspa01", "goldspa01", "goldspa01", "goldspa01", "goldspa01", "arenano01", "arenano01", "arenano01", "gomezca01", "gomezca01", "gomezca01", "gomezca01", "gomezca01", "gomezca01", "gomezca01", "gomezca01", "gomezca01", "gomezca01", "simmoan01", "simmoan01", "simmoan01", "simmoan01", "wachami01", "wachami01", "wachami01", "myerswi01", "myerswi01", "myerswi01", "fernajo02", "fernajo02", "fernajo02", 
+#> "davisch02", "davisch02", "davisch02", "davisch02", "davisch02", "davisch02", "davisch02", "davisch02", "davisch02", "carpema01", "carpema01", "carpema01", "carpema01", "carpema01", "alvarpe01", "alvarpe01", "alvarpe01", "alvarpe01", "alvarpe01", "alvarpe01", "cuddymi01", "cuddymi01", "cuddymi01", "cuddymi01", "cuddymi01", "cuddymi01", "cuddymi01", "cuddymi01", "cuddymi01", "cuddymi01", "cuddymi01", "cuddymi01", "cuddymi01", "cuddymi01", "cuddymi01", "cainlo01", "cainlo01", "cainlo01", "cainlo01", 
+#> "cainlo01", "cainlo01", "rizzoan01", "rizzoan01", "rizzoan01", "rizzoan01", "rizzoan01", "youngch03", "youngch03", "youngch03", "youngch03", "youngch03", "youngch03", "youngch03", "youngch03", "youngch03", "youngch03", "youngch03", "mcgehca01", "mcgehca01", "mcgehca01", "mcgehca01", "mcgehca01", "mcgehca01", "mcgehca01", "mcgehca01", "mcgehca01", "klubeco01", "klubeco01", "klubeco01", "klubeco01", "klubeco01", "seageky01", "seageky01", "seageky01", "seageky01", "seageky01", "keuchda01", "keuchda01", 
+#> "keuchda01", "keuchda01", "lemahdj01", "lemahdj01", "lemahdj01", "lemahdj01", "lemahdj01", "lagarju01", "lagarju01", "lagarju01", "yelicch01", "yelicch01", "yelicch01", "stantmi03", "stantmi03", "stantmi03", "stantmi03", "stantmi03", "stantmi03", "bumgama01", "bumgama01", "bumgama01", "bumgama01", "bumgama01", "bumgama01", "bumgama01", "abreujo02", "abreujo02", "degroja01", "degroja01", "altuvjo01", "altuvjo01", "altuvjo01", "altuvjo01", "altuvjo01", "gomesya01", "gomesya01", "gomesya01", "gomesya01", 
+#> "brantmi02", "brantmi02", "brantmi02", "brantmi02", "brantmi02", "brantmi02", "brantmi02", "walkene01", "walkene01", "walkene01", "walkene01", "walkene01", "walkene01", "walkene01", "rendoan01", "rendoan01", "rendoan01", "escobal02", "escobal02", "escobal02", "escobal02", "escobal02", "escobal02", "escobal02", "escobal02", "harvema01", "harvema01", "harvema01", "arrieja01", "arrieja01", "arrieja01", "arrieja01", "arrieja01", "arrieja01", "arrieja01", "kiermke01", "kiermke01", "kiermke01", "cespeyo01", 
+#> "cespeyo01", "cespeyo01", "cespeyo01", "cespeyo01", "cespeyo01", "calhoko01", "calhoko01", "calhoko01", "calhoko01", "gordode01", "gordode01", "gordode01", "gordode01", "gordode01", "polloaj01", "polloaj01", "polloaj01", "polloaj01", "martest01", "martest01", "martest01", "martest01", "crawfbr01", "crawfbr01", "crawfbr01", "crawfbr01", "crawfbr01", "donaljo02", "donaljo02", "donaljo02", "donaljo02", "donaljo02", "murphda08", "murphda08", "murphda08", "murphda08", "murphda08", "murphda08", "murphda08", 
+#> "correca01", "bryankr01", "moralke01", "moralke01", "moralke01", "moralke01", "moralke01", "moralke01", "moralke01", "moralke01", "moralke01", "moralke01", "martijd02", "martijd02", "martijd02", "martijd02", "martijd02", "bogaexa01", "bogaexa01", "bogaexa01") x c(1874, 1875, 1876, 1877, 1878, 1879, 1880, 1881, 1882, 1884, 1884, 1872, 1873, 1874, 1875, 1876, 1877, 1878, 1879, 1880, 1881, 1882, 1883, 1884, 1885, 1886, 1887, 1888, 1889, 1890, 1890, 1891, 1882, 1883, 1884, 1885, 1886, 1887, 1888, 1889, 1890, 1880, 1881, 1882, 1883, 1884, 1885, 1886, 1887, 1888, 1889, 1890, 1891, 1883, 1884, 1885, 1886, 1887, 1888, 1889, 1890, 1891, 1892, 1880, 1881, 1882, 1883, 1884, 1885, 1886, 1887, 1888, 1889, 1890, 1891, 1891, 1892, 1893, 1882, 1884, 1885, 1886, 1887, 1888, 
+#> 1889, 1890, 1891, 1892, 1892, 1893, 1894, 1889, 1890, 1891, 1892, 1893, 1894, 1895, 1897, 1898, 1901, 1888, 1889, 1890, 1891, 1892, 1893, 1894, 1895, 1896, 1897, 1898, 1899, 1900, 1901, 1904, 1905, 1906, 1890, 1891, 1892, 1893, 1894, 1895, 1896, 1897, 1898, 1899, 1900, 1901, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1911, 1896, 1897, 1898, 1899, 1900, 1901, 1902, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1897, 1899, 1900, 1901, 1901, 
+#> 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1900, 1901, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1916, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1913, 1914, 1914, 1915, 1916, 1917, 1918, 1919, 1907, 1908, 1909, 1910, 1910, 1911, 1912, 1913, 1914, 1915, 1896, 1897, 1898, 1899, 1900, 1901, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1912, 1899, 1900, 1901, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 
+#> 1914, 1916, 1899, 1900, 1901, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1903, 1905, 1906, 1907, 1908, 1909, 1910, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1898, 1899, 1900, 1901, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1915, 1916, 1918, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 
+#> 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1894, 1895, 1896, 1897, 1898, 1899, 1900, 1901, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1897, 1900, 1901, 1902, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1900, 1901, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1910, 1911, 1911, 1912, 1913, 1899, 1900, 1901, 1902, 1903, 1904, 1904, 1905, 
+#> 1906, 1908, 1911, 1911, 1912, 1914, 1894, 1895, 1896, 1897, 1898, 1899, 1900, 1901, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1913, 1914, 1915, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1914, 1915, 1916, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1897, 1898, 1899, 1900, 1901, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1894, 1895, 1896, 1897, 1898, 1899, 1900, 1901, 1902, 1903, 1904, 
+#> 1905, 1906, 1907, 1908, 1909, 1911, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1917, 1922, 1929, 1898, 1899, 1900, 1901, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1913, 1914, 1915, 1916, 1917, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1916, 1917, 1917, 1918, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 
+#> 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1906, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1904, 1905, 1905, 1905, 1908, 1909, 1910, 1911, 1912, 1931, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1901, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 
+#> 1922, 1923, 1924, 1925, 1926, 1927, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1913, 1914, 1915, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1917, 1918, 1919, 1920, 1921, 1922, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1921, 1922, 1923, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1906, 1907, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 
+#> 1926, 1898, 1899, 1900, 1901, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1898, 1899, 1900, 1901, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1912, 1913, 1914, 1915, 1918, 1904, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1913, 1914, 1915, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1912, 1913, 1914, 1915, 1916, 1916, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 
+#> 1919, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1920, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1925, 1904, 1907, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1918, 1918, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1917, 1918, 1919, 1909, 1910, 1911, 1912, 1912, 1914, 1915, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1916, 1917, 1918, 1919, 1921, 1922, 1906, 1909, 
+#> 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1925, 1911, 1912, 1913, 1914, 1914, 1915, 1916, 1918, 1925, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1915, 1916, 1917, 1918, 1919, 1920, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1915, 1916, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1917, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1926, 1927, 1928, 1929, 1930, 1910, 1911, 
+#> 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1916, 1917, 1918, 1919, 1920, 1903, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1908, 1909, 1910, 1911, 
+#> 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1921, 1922, 1923, 1923, 1924, 1902, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1915, 1916, 1918, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1916, 1917, 1918, 1919, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1912, 1913, 1914, 1915, 
+#> 1916, 1917, 1918, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1903, 1905, 1906, 1907, 1908, 1908, 1909, 1910, 1911, 1913, 1914, 1915, 1915, 1917, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1915, 1916, 1917, 1919, 1912, 1913, 1914, 1915, 1916, 1908, 1909, 1909, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 
+#> 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1924, 1925, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1935, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1929, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 
+#> 1913, 1914, 1915, 1919, 1913, 1914, 1915, 1916, 1917, 1918, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1912, 1913, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1915, 1916, 1917, 1918, 1919, 1920, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1919, 1912, 1913, 1914, 1915, 1916, 1917, 
+#> 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1924, 1925, 1926, 1927, 1928, 1928, 1929, 1930, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1908, 1909, 1910, 1911, 1911, 1912, 1913, 1914, 1915, 1916, 1916, 1917, 1918, 1919, 1919, 1920, 1915, 1916, 1917, 1918, 1919, 
+#> 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1933, 1934, 1935, 1936, 1937, 1910, 1911, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1919, 1920, 1921, 1922, 1923, 1923, 1924, 1925, 1929, 1930, 1912, 1914, 1915, 1916, 1917, 1919, 1919, 1920, 1921, 1921, 1922, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1915, 1916, 1917, 1918, 1919, 1920, 1905, 1908, 1909, 1910, 1911, 1912, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1912, 1913, 1914, 1915, 1916, 
+#> 1917, 1918, 1919, 1920, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1913, 1914, 1915, 1916, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1931, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1926, 1927, 1928, 1929, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1926, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 
+#> 1922, 1923, 1924, 1925, 1927, 1928, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1908, 1910, 1911, 1912, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1930, 1931, 1932, 1933, 1933, 1934, 1934, 1934, 1910, 1912, 1913, 1913, 1914, 
+#> 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1909, 1911, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1925, 1925, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1923, 1924, 1925, 1926, 1927, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1912, 1916, 1917, 1918, 1919, 1920, 1921, 
+#> 1922, 1923, 1912, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1925, 1926, 1926, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 
+#> 1915, 1916, 1917, 1918, 1919, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1915, 1916, 1917, 1917, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1930, 1932, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1915, 1916, 1917, 1918, 1919, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1926, 1927, 1927, 1928, 1929, 1917, 1918, 
+#> 1919, 1920, 1921, 1922, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1931, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1926, 1927, 1927, 1928, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1912, 1913, 1914, 1915, 1916, 1917, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1917, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1926, 1927, 1913, 1915, 1916, 1917, 1918, 
+#> 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1915, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1934, 1914, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1932, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1933, 1933, 1934, 1936, 1915, 1916, 1917, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1926, 1927, 1928, 1929, 1930, 1920, 1921, 1922, 1923, 1924, 
+#> 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1916, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1925, 1926, 1927, 1928, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1934, 1935, 1914, 1915, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1929, 1930, 1915, 
+#> 1915, 1918, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1934, 1935, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1933, 1934, 1913, 1914, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1915, 1916, 1917, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1923, 1923, 1924, 1925, 1926, 1927, 1930, 1931, 1932, 1933, 1912, 1913, 1914, 1915, 1915, 1916, 1917, 1919, 
+#> 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1937, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 
+#> 1939, 1915, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1931, 1932, 1933, 1934, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1939, 1940, 1941, 1943, 1944, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 
+#> 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1946, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1935, 1936, 1937, 1938, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1935, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1919, 1920, 1921, 1922, 1923, 1923, 1924, 1924, 1925, 1926, 1927, 1928, 1928, 1929, 1930, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1930, 1931, 
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+#> 1927, 1928, 1929, 1930, 1930, 1931, 1931, 1932, 1932, 1933, 1934, 1935, 1936, 1937, 1937, 1938, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1932, 1933, 1934, 1935, 1935, 1936, 1937, 1937, 1923, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1918, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1941, 
+#> 1942, 1943, 1944, 1944, 1945, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1923, 1924, 1925, 1926, 1927, 1928, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1941, 1941, 1942, 1944, 1944, 1945, 1926, 1927, 1927, 1928, 1929, 1930, 1930, 1931, 1932, 1933, 1934, 1934, 1935, 1936, 1922, 1928, 1929, 1930, 1931, 1923, 1924, 1925, 1926, 1927, 1927, 
+#> 1928, 1929, 1930, 1930, 1931, 1932, 1933, 1934, 1935, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1937, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1930, 1931, 1932, 1932, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1921, 1922, 1923, 1924, 1925, 1927, 1928, 1929, 1930, 1931, 1931, 1932, 1933, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 
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+#> 1938, 1939, 1939, 1940, 1946, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1919, 1920, 1922, 1923, 1928, 1929, 1930, 1931, 1932, 1933, 1933, 1934, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1942, 1944, 1945, 1929, 1930, 1931, 1932, 
+#> 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1939, 1940, 1941, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1925, 1926, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1936, 1937, 1938, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1935, 1936, 1937, 1923, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1931, 
+#> 1932, 1933, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1936, 1937, 1938, 1939, 1939, 1940, 1941, 1942, 1943, 1944, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1942, 1943, 1945, 
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+#> 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1946, 1946, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1938, 1939, 1940, 1941, 1942, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1945, 1946, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1937, 1938, 1938, 1939, 1940, 1940, 1928, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 
+#> 1939, 1940, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1940, 1941, 1942, 1943, 1943, 1944, 1945, 1945, 1946, 1947, 1948, 1927, 1928, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1937, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1947, 1948, 1930, 1933, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1942, 1943, 1946, 1947, 1948, 
+#> 1949, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1946, 1930, 1933, 1934, 1935, 1936, 1937, 
+#> 1938, 1939, 1940, 1941, 1945, 1946, 1947, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1944, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1928, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1944, 1931, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1946, 1947, 
+#> 1948, 1949, 1950, 1951, 1934, 1935, 1936, 1937, 1938, 1939, 1939, 1940, 1941, 1941, 1942, 1943, 1944, 1944, 1945, 1945, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1941, 1942, 1943, 1943, 1944, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1946, 1947, 1948, 1949, 1950, 1951, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1945, 1946, 1947, 1948, 1949, 1950, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 
+#> 1943, 1944, 1945, 1946, 1947, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1939, 1940, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1941, 1942, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1932, 1933, 1934, 1935, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1943, 1930, 1931, 1933, 1935, 1936, 1937, 1938, 1939, 1939, 1940, 1928, 1929, 1930, 1931, 1932, 1933, 1933, 1934, 1935, 1936, 1936, 1937, 1938, 1939, 1937, 1938, 1939, 1940, 1940, 1945, 1936, 1937, 1938, 
+#> 1939, 1940, 1941, 1942, 1946, 1947, 1948, 1949, 1949, 1950, 1951, 1952, 1953, 1932, 1933, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1941, 1942, 1943, 1944, 1937, 1938, 1939, 1940, 1941, 1942, 1942, 1943, 1944, 1945, 1931, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1945, 1946, 1947, 1928, 1929, 1930, 1931, 1931, 1932, 1933, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 
+#> 1941, 1942, 1942, 1943, 1944, 1946, 1947, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1946, 1947, 1948, 1949, 1929, 1930, 1932, 1934, 1935, 1935, 1936, 1937, 1937, 1938, 1939, 1939, 1940, 1941, 1942, 1942, 1943, 1943, 1943, 1944, 1945, 1946, 1946, 1947, 1947, 1948, 1952, 1952, 1953, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1946, 1947, 1948, 1949, 1950, 1951, 1934, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1947, 1948, 1931, 1932, 1933, 1934, 1935, 1936, 
+#> 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1943, 1944, 1945, 1945, 1946, 1947, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1938, 1939, 1940, 1941, 1942, 1943, 1946, 1947, 1948, 1949, 1950, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1936, 1937, 1938, 1939, 1940, 1941, 1945, 1946, 1947, 1948, 1949, 1950, 1951, 
+#> 1952, 1953, 1954, 1955, 1956, 1933, 1934, 1935, 1936, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1939, 1940, 1941, 1942, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1931, 1932, 1933, 1934, 1934, 1935, 1936, 1937, 1938, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1950, 1934, 1935, 1936, 1936, 1937, 1938, 1939, 1940, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1933, 1934, 1935, 1936, 
+#> 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1946, 1947, 1947, 1948, 1948, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1946, 1947, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1943, 1944, 1945, 1933, 1934, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1942, 1943, 1944, 1945, 1945, 1946, 1946, 1947, 1939, 1940, 1941, 1942, 1943, 1945, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1936, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 
+#> 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1936, 1937, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1950, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1946, 1947, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1941, 1942, 1943, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1945, 1946, 1947, 1933, 1934, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1945, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1946, 1929, 1930, 
+#> 1931, 1932, 1933, 1933, 1934, 1935, 1936, 1937, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1940, 1941, 1942, 1943, 1946, 1947, 1948, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1947, 1948, 1949, 1938, 1939, 1940, 1941, 1942, 1940, 1941, 1942, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1937, 1938, 1939, 1939, 1940, 1941, 1942, 1943, 1946, 1947, 1947, 1948, 1949, 1949, 1950, 1938, 1939, 1940, 1941, 1942, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1955, 1956, 1956, 1957, 1958, 1959, 1959, 
+#> 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1946, 1947, 1948, 1949, 1950, 1941, 1942, 1943, 1944, 1946, 1947, 1948, 1949, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1940, 1941, 1942, 1945, 1946, 1947, 1948, 1949, 1950, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 
+#> 1947, 1940, 1941, 1942, 1943, 1944, 1946, 1947, 1948, 1949, 1949, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1953, 1954, 1955, 1955, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1945, 1946, 1947, 1947, 1949, 1941, 1942, 1946, 1947, 1948, 1941, 1942, 1946, 1947, 1948, 1949, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1950, 1952, 1953, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1949, 1950, 1951, 1954, 1942, 1946, 1947, 1948, 1949, 1950, 
+#> 1951, 1952, 1952, 1953, 1954, 1954, 1934, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1947, 1948, 1943, 1946, 1947, 1948, 1949, 1950, 1951, 1951, 1952, 1953, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1952, 1957, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1941, 1943, 1944, 1946, 1947, 1948, 1949, 1950, 1952, 1941, 1942, 1943, 1944, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 
+#> 1959, 1960, 1961, 1962, 1963, 1932, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1949, 1950, 1950, 1951, 1952, 1953, 1954, 1954, 1955, 1956, 1957, 1937, 1938, 1939, 1940, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1946, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1950, 1950, 1951, 1952, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1939, 1940, 1941, 1942, 1943, 
+#> 1944, 1945, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1953, 1942, 1943, 1944, 1945, 1946, 1948, 1949, 1944, 1945, 1946, 1946, 1947, 1948, 1948, 1949, 1950, 1950, 1942, 1943, 1944, 1945, 1946, 1947, 1947, 1948, 1949, 1950, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1946, 1947, 1948, 1949, 1950, 1951, 1931, 1933, 1934, 1935, 1936, 1936, 1937, 1938, 1939, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1938, 1939, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1930, 1931, 1932, 
+#> 1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1940, 1942, 1943, 1943, 1944, 1945, 1932, 1933, 1934, 1935, 1935, 1943, 1944, 1945, 1946, 1945, 1946, 1947, 1948, 1949, 1950, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1953, 1954, 1955, 1956, 1957, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1947, 1938, 1939, 1940, 1940, 1941, 1942, 1942, 1942, 1943, 1944, 1945, 1945, 1946, 1947, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 
+#> 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1950, 1951, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1940, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1942, 1943, 1944, 1945, 1945, 1946, 1947, 1948, 1949, 1950, 1950, 1950, 1951, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1937, 1938, 1939, 1940, 1943, 1944, 1945, 1945, 1946, 1947, 1948, 1949, 1942, 1943, 
+#> 1944, 1945, 1946, 1947, 1950, 1951, 1951, 1937, 1938, 1939, 1944, 1945, 1946, 1946, 1936, 1937, 1938, 1943, 1944, 1945, 1946, 1947, 1948, 1939, 1940, 1941, 1942, 1943, 1946, 1947, 1948, 1949, 1950, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1943, 1944, 1945, 1946, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1952, 1953, 1954, 1954, 1955, 1956, 1956, 1957, 1943, 1945, 1946, 1947, 1948, 1949, 1950, 1951, 1951, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 
+#> 1950, 1951, 1952, 1941, 1942, 1943, 1946, 1947, 1948, 1949, 1950, 1951, 1951, 1952, 1953, 1953, 1954, 1955, 1956, 1956, 1943, 1944, 1944, 1945, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1940, 1941, 1942, 1943, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1959, 1942, 1946, 1947, 1948, 1949, 1950, 1951, 1951, 1952, 1953, 1954, 1955, 1955, 1940, 1941, 1942, 1946, 1947, 1948, 1949, 1950, 1951, 
+#> 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1940, 1941, 1942, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1936, 1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1965, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1937, 1938, 1939, 1940, 1941, 1942, 1946, 1947, 1948, 1949, 1950, 1946, 1947, 1948, 1949, 1950, 1951, 1951, 1952, 1954, 1955, 1956, 
+#> 1942, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1952, 1953, 1955, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1953, 1954, 1955, 1944, 1945, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1953, 1954, 1954, 1956, 1942, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1965, 1942, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1952, 1953, 1954, 1955, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1947, 1948, 1949, 1950, 
+#> 1951, 1952, 1953, 1954, 1955, 1955, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1946, 1947, 1947, 1948, 1949, 1950, 1951, 1952, 1941, 1942, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1955, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1949, 1950, 1951, 1952, 1941, 1942, 1946, 1947, 1948, 1949, 1950, 1951, 1951, 1952, 1952, 1952, 1953, 1953, 1954, 1955, 1956, 1956, 1946, 1948, 1949, 1950, 
+#> 1951, 1952, 1953, 1954, 1955, 1956, 1956, 1957, 1958, 1958, 1959, 1960, 1960, 1944, 1945, 1946, 1947, 1948, 1949, 1950, 1954, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1950, 1950, 1951, 1952, 1952, 1952, 1953, 1954, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1947, 1948, 1949, 1950, 1951, 1952, 1952, 1953, 1954, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1961, 1962, 1963, 1963, 1943, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 
+#> 1963, 1941, 1942, 1943, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1955, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1949, 1950, 1951, 1954, 1955, 1956, 1957, 1958, 1958, 1959, 1960, 1960, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1964, 1965, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1956, 1957, 1941, 1942, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1949, 1950, 1951, 
+#> 1952, 1953, 1954, 1955, 1956, 1957, 1949, 1950, 1951, 1952, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1958, 1959, 1959, 1960, 1961, 1945, 1946, 1947, 1948, 1949, 1950, 1952, 1953, 1953, 1954, 1955, 1956, 1957, 1957, 1944, 1946, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1954, 1955, 1956, 1956, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1947, 1948, 
+#> 1949, 1950, 1951, 1952, 1953, 1954, 1956, 1944, 1945, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1959, 1962, 1950, 1951, 1952, 1954, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1959, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1951, 1952, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1972, 1973, 1945, 1950, 1951, 1952, 1953, 1954, 1955, 1955, 
+#> 1956, 1956, 1957, 1957, 1958, 1958, 1938, 1944, 1945, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1962, 1963, 1964, 1964, 1964, 1941, 1942, 1945, 1948, 1949, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1950, 1952, 1953, 1954, 1955, 1955, 1956, 1957, 1952, 1953, 1954, 1955, 1955, 1956, 1957, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 
+#> 1967, 1968, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1965, 1966, 1966, 1949, 1950, 1951, 1952, 1953, 1954, 1950, 1951, 1952, 1953, 1955, 1956, 1957, 1957, 1958, 1959, 1960, 1961, 1961, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1965, 1966, 1966, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1945, 
+#> 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1956, 1957, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1948, 1949, 1950, 1951, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1958, 1959, 1959, 1959, 1952, 1953, 1954, 1955, 1956, 1957, 1959, 1954, 1955, 1956, 1957, 1958, 1958, 1959, 1960, 1960, 1960, 1962, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1959, 1960, 1961, 1949, 1950, 
+#> 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1959, 1959, 1948, 1949, 1950, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1961, 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 1999, 1953, 1954, 1955, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1966, 1967, 1969, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1955, 1956, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1968, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 
+#> 1961, 1962, 1963, 1964, 1965, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1967, 1968, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1950, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1953, 1954, 1955, 1956, 
+#> 1957, 1958, 1959, 1960, 1961, 1961, 1962, 1963, 1964, 1964, 1965, 1965, 1967, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1974, 1975, 1976, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1967, 1968, 1968, 1969, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 
+#> 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1945, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1963, 1964, 1964, 1965, 1965, 1966, 1967, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1949, 1951, 1951, 1952, 1953, 1954, 
+#> 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1976, 1980, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1964, 1965, 1966, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1965, 1966, 1967, 1967, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1969, 1970, 1971, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1967, 
+#> 1968, 1951, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1963, 1954, 1955, 1956, 1957, 1958, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1964, 1964, 1965, 1954, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1950, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1963, 1963, 1964, 1965, 1966, 1967, 1956, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1967, 1968, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 
+#> 1967, 1968, 1969, 1970, 1971, 1972, 1949, 1950, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1952, 1953, 1954, 1955, 1956, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1950, 1951, 1952, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1961, 1958, 1959, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1972, 1973, 1974, 1951, 1952, 1953, 1954, 1955, 1956, 
+#> 1957, 1958, 1959, 1960, 1961, 1961, 1962, 1963, 1964, 1964, 1965, 1965, 1965, 1966, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1966, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1967, 1968, 1939, 1941, 1942, 1943, 1944, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1963, 1956, 1956, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 
+#> 1965, 1966, 1967, 1967, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1976, 1977, 1978, 1979, 1980, 1951, 1952, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1950, 1951, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 
+#> 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1967, 1967, 1957, 1958, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1956, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1952, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1967, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 
+#> 1968, 1968, 1969, 1970, 1971, 1972, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1972, 1973, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1964, 1965, 1966, 1967, 1967, 1959, 1960, 1961, 1962, 1963, 1964, 1964, 1965, 1966, 1952, 1953, 1954, 1955, 1956, 1956, 1957, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1963, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 
+#> 1975, 1960, 1961, 1962, 1963, 1964, 1966, 1967, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1964, 1964, 1965, 1965, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 
+#> 1975, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1969, 1970, 1971, 1972, 1961, 1962, 1963, 1964, 1965, 1966, 1966, 1967, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1967, 1968, 1968, 1949, 1951, 1952, 1953, 1954, 1955, 1955, 1956, 1957, 
+#> 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1964, 1965, 1966, 1967, 1953, 1954, 1955, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1966, 1955, 1956, 1957, 1959, 1960, 1961, 1962, 1963, 1952, 1953, 1954, 1956, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1968, 1969, 1956, 1957, 1957, 1958, 1959, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1966, 1967, 1956, 1957, 1958, 1959, 1960, 1961, 
+#> 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1979, 1980, 1980, 1981, 1982, 1983, 1961, 1962, 1963, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1969, 1950, 1951, 1952, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 
+#> 1966, 1967, 1968, 1969, 1969, 1970, 1970, 1970, 1971, 1972, 1972, 1973, 1974, 1975, 1976, 1976, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1962, 1963, 1964, 1965, 1966, 1966, 1967, 1967, 1969, 1969, 1953, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1968, 1969, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 
+#> 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1969, 1971, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1971, 1960, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 
+#> 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1984, 1985, 1986, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1970, 1971, 1972, 1973, 1973, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1961, 1962, 1963, 1964, 1965, 
+#> 1966, 1967, 1968, 1969, 1970, 1970, 1971, 1963, 1964, 1965, 1966, 1967, 1968, 1968, 1969, 1969, 1970, 1971, 1972, 1973, 1973, 1974, 1977, 1978, 1979, 1980, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1958, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1958, 1959, 
+#> 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1966, 1969, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1973, 1974, 1975, 1976, 1977, 1977, 1978, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1974, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1961, 1962, 
+#> 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1969, 1970, 1970, 1961, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1971, 1972, 1972, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1963, 1964, 1965, 1966, 1967, 1968, 1968, 1969, 1969, 1969, 1970, 1970, 1958, 1959, 1960, 1961, 
+#> 1962, 1963, 1964, 1964, 1965, 1966, 1967, 1968, 1969, 1969, 1970, 1970, 1971, 1971, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1960, 1961, 1961, 1962, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1973, 1974, 1974, 1974, 1975, 1975, 1976, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1972, 1973, 
+#> 1973, 1955, 1956, 1957, 1960, 1963, 1964, 1965, 1966, 1966, 1967, 1968, 1969, 1970, 1970, 1970, 1971, 1972, 1964, 1965, 1966, 1967, 1968, 1969, 1969, 1970, 1971, 1972, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1973, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1977, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 
+#> 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1959, 1960, 1962, 1963, 1964, 1965, 1966, 1966, 1967, 1968, 1969, 1970, 1970, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1971, 1972, 1973, 1973, 1974, 1964, 1965, 1966, 1967, 1968, 1969, 1969, 1970, 1971, 1972, 1972, 1973, 1974, 1974, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1968, 1969, 1970, 1971, 1972, 1972, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 
+#> 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986, 1961, 1962, 1963, 1964, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1970, 1971, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1979, 1979, 1964, 1965, 1966, 1967, 1968, 1969, 
+#> 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1979, 1980, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986, 1986, 1959, 1960, 1961, 1963, 1964, 1965, 1966, 1967, 
+#> 1968, 1969, 1970, 1971, 1972, 1972, 1973, 1974, 1974, 1975, 1975, 1976, 1977, 1978, 1979, 1980, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1977, 1965, 1966, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1966, 1967, 1968, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1978, 1979, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1972, 1966, 1967, 
+#> 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1972, 1973, 1973, 1974, 1974, 1975, 1966, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 
+#> 1975, 1975, 1976, 1977, 1977, 1978, 1979, 1980, 1981, 1982, 1982, 1963, 1964, 1965, 1966, 1966, 1967, 1967, 1967, 1968, 1969, 1969, 1970, 1971, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1977, 1978, 1978, 1978, 1979, 1980, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1977, 1978, 1979, 1961, 1962, 1963, 1964, 1964, 1965, 1967, 1968, 
+#> 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1959, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1977, 1978, 1978, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1955, 1956, 1957, 1959, 1960, 
+#> 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1964, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1979, 1980, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986, 1987, 1963, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 
+#> 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986, 1986, 1986, 1987, 1987, 1988, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1972, 1973, 1973, 1974, 1963, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1971, 1972, 1972, 1973, 1968, 1969, 1970, 1971, 1972, 1973, 1973, 1974, 1975, 1976, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1969, 
+#> 1970, 1971, 1972, 1959, 1960, 1961, 1962, 1963, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1975, 1968, 1969, 1970, 1971, 1972, 1973, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1981, 1982, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1977, 1979, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1977, 1964, 1965, 1966, 1967, 1969, 1970, 
+#> 1971, 1975, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1973, 1974, 1975, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1965, 1966, 1967, 1968, 1969, 1970, 1972, 1973, 1974, 1975, 1976, 1977, 1977, 1979, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1985, 1986, 1967, 1969, 1970, 1971, 1972, 
+#> 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1978, 1979, 1980, 1981, 1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1975, 1976, 1979, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1971, 1972, 1973, 1974, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986, 1988, 1970, 1971, 1972, 1973, 
+#> 1974, 1975, 1976, 1976, 1977, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1965, 1966, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1979, 1980, 1981, 1982, 1983, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1965, 1966, 1967, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 
+#> 1977, 1978, 1979, 1980, 1981, 1982, 1967, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1964, 1966, 1966, 1968, 1970, 1971, 1972, 1973, 1973, 1974, 1974, 1975, 1976, 1976, 1962, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1977, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 
+#> 1982, 1983, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1975, 1976, 1977, 1978, 1979, 1980, 1980, 1981, 1982, 1983, 1983, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1969, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986, 1987, 1988, 1989, 1990, 1991, 1992, 1993, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1975, 1975, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 
+#> 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1985, 1986, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1985, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1965, 1967, 1968, 1969, 1971, 1972, 1973, 1973, 1974, 1974, 1974, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1984, 1984, 
+#> 1985, 1986, 1987, 1988, 1989, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1980, 1981, 1982, 1982, 1964, 1965, 1966, 1967, 1968, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1977, 1978, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1979, 1980, 1981, 1983, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986, 1968, 1970, 1971, 1972, 1973, 1974, 1975, 
+#> 1976, 1977, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1983, 1984, 1984, 1985, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1978, 1979, 1980, 1965, 1966, 1967, 1968, 1969, 1970, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986, 1987, 1987, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 
+#> 1981, 1982, 1982, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1976, 1977, 1978, 1978, 1979, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986, 1987, 1988, 1989, 1967, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986, 
+#> 1967, 1969, 1970, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1976, 1977, 1977, 1978, 1979, 1980, 1981, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986, 1987, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1968, 1969, 1970, 1971, 1972, 1973, 
+#> 1974, 1975, 1976, 1977, 1978, 1979, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986, 1987, 1988, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1976, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1974, 1975, 1976, 1977, 1978, 1979, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1973, 1974, 1975, 1976, 1977, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 
+#> 1982, 1983, 1984, 1985, 1986, 1987, 1988, 1989, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1984, 1985, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1985, 1986, 1987, 1987, 1964, 1965, 1966, 
+#> 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986, 1987, 1988, 1988, 1989, 1990, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1972, 1973, 1974, 1975, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1975, 1976, 1977, 1977, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1983, 1984, 
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+#> 2013, 2013, 2014, 2015, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2010, 1991, 1992, 1993, 1994, 1995, 1996, 1997, 1997, 1998, 1999, 2000, 2000, 2001, 2002, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2003, 2004, 2005, 2006, 
+#> 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2007, 2008, 2008, 2009, 2010, 2011, 2012, 1995, 1996, 1997, 1997, 1998, 2001, 2002, 2003, 2004, 2005, 2005, 2006, 2007, 2008, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2013, 2014, 2015, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2015, 2002, 2003, 
+#> 2004, 2005, 2006, 2007, 2008, 2009, 2009, 2010, 2010, 2011, 2012, 2013, 2014, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2012, 2013, 2014, 2015, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2005, 2006, 2007, 2008, 2009, 2009, 2010, 2011, 2012, 2012, 2013, 2014, 
+#> 2003, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2012, 2013, 2014, 2015, 2015, 1998, 1999, 2000, 2001, 2002, 2003, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2015, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2014, 2015, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2012, 2013, 2014, 2014, 2015, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2006, 2007, 2008, 2009, 2009, 2010, 2011, 2012, 2007, 2008, 2009, 
+#> 2010, 2011, 2012, 2013, 2014, 2015, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2002, 2003, 2003, 2004, 2005, 2007, 2008, 2009, 2010, 2010, 2011, 2011, 2012, 2013, 2014, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2011, 2012, 2013, 2014, 2015, 2011, 2012, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2012, 2013, 2014, 2015, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2000, 2001, 2002, 
+#> 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2006, 2007, 2008, 2009, 2010, 2011, 2011, 2012, 2013, 2014, 2015, 2015, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2005, 2006, 2007, 2008, 2009, 2010, 2012, 2013, 2014, 2015, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2011, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2009, 2010, 2011, 2012, 2013, 2015, 2009, 2010, 2011, 
+#> 2012, 2013, 2014, 2015, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 1999, 2001, 2002, 2003, 2004, 2005, 2006, 2006, 2007, 2008, 2009, 2010, 2011, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2005, 2006, 2008, 2009, 2010, 2011, 2012, 2012, 2013, 2014, 2015, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 
+#> 2014, 2015, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2015, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2015, 2004, 2004, 2004, 2004, 2005, 2006, 2007, 2008, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2003, 2005, 2006, 2006, 2006, 2007, 2008, 2009, 2010, 2010, 2011, 2012, 2013, 
+#> 2014, 2015, 1992, 1993, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2015, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2014, 2015, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2005, 2006, 2007, 2008, 2009, 2010, 
+#> 2011, 2012, 2013, 2014, 2015, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2009, 2010, 2011, 2012, 2013, 2014, 2014, 2015, 2015, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2009, 
+#> 2010, 2011, 2012, 2013, 2013, 2014, 2014, 2015, 2010, 2011, 2012, 2013, 2014, 2015, 2010, 2011, 2012, 2013, 2014, 2015, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2014, 2015, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2009, 2010, 2010, 2011, 2012, 2014, 2015, 2006, 2007, 2008, 2009, 2010, 2011, 2011, 2012, 2013, 2013, 2014, 2015, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 
+#> 2012, 2013, 2014, 2015, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2001, 2003, 2004, 2005, 2006, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2002, 2003, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2015, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2014, 2015, 2015, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2004, 2005, 2006, 2007, 2008, 2009, 2009, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2010, 2011, 2012, 
+#> 2013, 2014, 2014, 2015, 2015, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2014, 2015, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2010, 2011, 2012, 2013, 2014, 2015, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2012, 2013, 2014, 2011, 2012, 2013, 2014, 2015, 2012, 2013, 2014, 2015, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2014, 2015, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2014, 2006, 2007, 
+#> 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2010, 2011, 2012, 2013, 2014, 2015, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2009, 2010, 2011, 2011, 2012, 2013, 2014, 2015, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2011, 2012, 2013, 2014, 2015, 2012, 2013, 2014, 2015, 2011, 2012, 2013, 2014, 2015, 2011, 2012, 2013, 2014, 2015, 2013, 2014, 2015, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2015, 2012, 2013, 2014, 2015, 2013, 2014, 2015, 2013, 2014, 2015, 2013, 2014, 2015, 2008, 2009, 
+#> 2010, 2011, 2011, 2012, 2013, 2014, 2015, 2011, 2012, 2013, 2014, 2015, 2010, 2011, 2012, 2013, 2014, 2015, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2010, 2011, 2012, 2013, 2014, 2015, 2011, 2012, 2013, 2014, 2015, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2014, 2015, 2008, 2009, 2010, 2011, 2012, 2012, 2014, 2015, 2015, 2011, 2012, 2013, 2014, 2015, 2011, 2012, 2013, 2014, 2015, 2012, 2013, 2014, 2015, 2011, 2012, 2013, 2014, 2015, 2013, 
+#> 2014, 2015, 2013, 2014, 2015, 2010, 2011, 2012, 2013, 2014, 2015, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2014, 2015, 2014, 2015, 2011, 2012, 2013, 2014, 2015, 2012, 2013, 2014, 2015, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2013, 2014, 2015, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2012, 2013, 2015, 2010, 2011, 2012, 2013, 2013, 2014, 2015, 2013, 2014, 2015, 2012, 2013, 2014, 2014, 2015, 2015, 2012, 2013, 2014, 2015, 2011, 2012, 2013, 2014, 2015, 
+#> 2012, 2013, 2014, 2015, 2012, 2013, 2014, 2015, 2011, 2012, 2013, 2014, 2015, 2010, 2012, 2013, 2014, 2015, 2008, 2009, 2011, 2012, 2013, 2014, 2015, 2015, 2015, 2006, 2007, 2008, 2009, 2010, 2012, 2013, 2014, 2014, 2015, 2011, 2012, 2013, 2014, 2015, 2013, 2014, 2015) x c(18, 59, 57, 26, 26, 26, 26, 26, 139, 28, 61, 143, 144, 32, 32, 35, 35, 107, 107, 107, 107, 107, 107, 107, 107, 147, 147, 62, 62, 26, 106, 148, 74, 74, 74, 74, 74, 74, 74, 74, 106, 6, 107, 107, 107, 107, 107, 26, 26, 26, 26, 27, 38, 89, 121, 121, 121, 121, 121, 121, 36, 121, 38, 135, 135, 135, 92, 92, 89, 89, 89, 89, 89, 95, 89, 102, 102, 102, 139, 35, 35, 35, 35, 26, 26, 26, 26, 26, 42, 42, 42, 62, 89, 89, 89, 89, 89, 89, 89, 89, 38, 35, 35, 36, 25, 26, 26, 26, 26, 26, 26, 26, 26, 26, 84, 102, 
+#> 102, 102, 42, 42, 42, 42, 42, 42, 42, 42, 42, 125, 125, 16, 16, 16, 16, 16, 16, 16, 16, 45, 45, 26, 45, 102, 102, 102, 102, 102, 101, 45, 101, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 101, 101, 75, 75, 106, 35, 106, 101, 101, 101, 101, 101, 101, 123, 123, 123, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 38, 89, 93, 93, 93, 93, 93, 93, 93, 93, 33, 93, 29, 33, 29, 38, 38, 38, 89, 16, 16, 16, 16, 33, 33, 33, 33, 33, 29, 42, 42, 42, 125, 125, 16, 16, 16, 16, 16, 16, 16, 16, 
+#> 123, 93, 123, 26, 26, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 52, 38, 38, 38, 38, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 16, 123, 123, 123, 123, 123, 123, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 26, 45, 45, 45, 45, 45, 45, 45, 45, 45, 137, 22, 22, 22, 22, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 93, 93, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 101, 101, 42, 42, 42, 42, 42, 125, 125, 125, 123, 123, 123, 
+#> 123, 123, 123, 123, 123, 123, 123, 123, 123, 123, 123, 123, 125, 125, 89, 89, 89, 89, 89, 89, 89, 89, 26, 26, 137, 35, 12, 12, 89, 89, 89, 89, 89, 89, 89, 125, 125, 125, 125, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 26, 35, 26, 38, 125, 125, 12, 38, 38, 38, 89, 89, 89, 89, 26, 89, 106, 89, 75, 75, 75, 75, 75, 75, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 125, 35, 35, 35, 35, 35, 35, 35, 35, 35, 38, 21, 124, 34, 35, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 
+#> 75, 75, 75, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 89, 89, 26, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 26, 26, 26, 26, 102, 33, 26, 26, 26, 26, 26, 26, 26, 26, 26, 106, 106, 106, 106, 125, 35, 35, 35, 35, 35, 35, 35, 35, 22, 35, 22, 87, 26, 26, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 106, 102, 106, 140, 101, 101, 101, 101, 101, 101, 101, 101, 101, 33, 33, 33, 33, 33, 33, 
+#> 33, 33, 33, 33, 33, 33, 101, 101, 101, 101, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 38, 26, 38, 38, 140, 140, 140, 140, 93, 125, 16, 16, 16, 16, 16, 16, 16, 16, 16, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 140, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 124, 123, 123, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 140, 63, 87, 16, 16, 16, 16, 16, 16, 16, 16, 
+#> 45, 45, 45, 45, 45, 45, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 140, 140, 140, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 89, 89, 125, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 93, 93, 75, 75, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 35, 106, 35, 35, 38, 106, 106, 106, 106, 106, 106, 106, 106, 106, 102, 106, 109, 109, 106, 35, 35, 35, 35, 
+#> 35, 35, 35, 35, 35, 106, 106, 21, 29, 35, 93, 93, 93, 52, 101, 101, 101, 101, 101, 101, 101, 93, 93, 93, 93, 93, 93, 93, 93, 106, 101, 101, 101, 101, 101, 101, 101, 101, 101, 22, 22, 22, 22, 52, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 13, 102, 102, 33, 106, 52, 35, 35, 35, 35, 35, 35, 35, 35, 35, 22, 38, 106, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 26, 26, 26, 38, 38, 38, 35, 35, 35, 35, 106, 93, 93, 101, 101, 101, 101, 101, 101, 101, 93, 93, 93, 93, 93, 93, 38, 
+#> 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 45, 45, 45, 16, 45, 16, 16, 101, 140, 101, 101, 45, 45, 45, 45, 45, 33, 45, 33, 33, 33, 33, 33, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 38, 89, 89, 89, 89, 89, 89, 89, 89, 89, 22, 22, 26, 102, 102, 102, 102, 102, 102, 102, 35, 35, 35, 35, 35, 35, 35, 35, 35, 125, 125, 125, 125, 102, 22, 22, 22, 22, 22, 22, 22, 22, 22, 38, 38, 38, 38, 38, 38, 89, 89, 89, 89, 89, 89, 89, 89, 89, 35, 89, 35, 89, 89, 89, 106, 35, 38, 38, 38, 
+#> 38, 38, 102, 102, 102, 102, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 22, 89, 22, 22, 22, 22, 22, 38, 26, 26, 26, 26, 101, 101, 101, 101, 101, 101, 101, 101, 101, 16, 16, 16, 16, 45, 26, 26, 106, 106, 102, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 101, 45, 45, 45, 45, 45, 45, 140, 140, 140, 140, 140, 140, 140, 140, 140, 52, 52, 52, 125, 125, 22, 125, 89, 89, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 89, 89, 89, 89, 38, 38, 38, 38, 102, 102, 102, 102, 102, 102, 
+#> 102, 35, 35, 35, 38, 106, 106, 106, 106, 106, 106, 125, 125, 125, 89, 89, 89, 89, 89, 89, 89, 101, 101, 101, 101, 101, 16, 16, 16, 93, 93, 93, 93, 93, 123, 123, 123, 123, 101, 52, 106, 140, 140, 140, 45, 140, 45, 45, 45, 45, 63, 21, 87, 101, 101, 101, 101, 101, 101, 101, 101, 16, 101, 16, 16, 16, 106, 106, 106, 106, 106, 16, 33, 140, 102, 102, 102, 102, 102, 102, 102, 102, 102, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 101, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 
+#> 33, 33, 33, 33, 33, 33, 89, 16, 16, 16, 16, 16, 16, 52, 52, 52, 52, 52, 26, 26, 26, 26, 26, 26, 26, 26, 26, 106, 106, 106, 106, 35, 22, 125, 125, 26, 26, 26, 26, 26, 26, 125, 125, 125, 125, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 38, 38, 38, 102, 26, 26, 26, 26, 93, 93, 93, 93, 93, 123, 33, 33, 33, 33, 33, 33, 33, 33, 33, 89, 38, 89, 38, 38, 38, 38, 38, 38, 38, 38, 89, 89, 89, 89, 89, 106, 125, 125, 125, 125, 125, 125, 125, 89, 125, 89, 89, 
+#> 89, 89, 89, 89, 89, 125, 102, 102, 102, 102, 102, 89, 102, 89, 89, 89, 26, 26, 26, 26, 22, 22, 89, 35, 35, 35, 35, 35, 35, 35, 106, 35, 35, 35, 35, 35, 35, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 106, 106, 106, 106, 106, 22, 22, 22, 22, 22, 22, 93, 123, 123, 123, 123, 123, 123, 123, 123, 123, 123, 123, 123, 26, 140, 26, 26, 16, 16, 16, 16, 16, 16, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 26, 89, 89, 26, 26, 89, 89, 89, 38, 38, 38, 89, 89, 26, 26, 35, 35, 
+#> 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 89, 26, 35, 35, 35, 35, 123, 125, 123, 123, 123, 123, 89, 26, 89, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 89, 89, 89, 26, 26, 89, 89, 89, 89, 89, 35, 89, 35, 35, 106, 89, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 52, 16, 16, 16, 16, 16, 33, 33, 33, 33, 33, 33, 33, 33, 33, 45, 45, 45, 45, 45, 45, 45, 45, 45, 123, 123, 102, 102, 102, 102, 102, 102, 102, 35, 35, 35, 35, 33, 63, 87, 38, 89, 38, 38, 38, 38, 38, 38, 38, 38, 
+#> 38, 38, 89, 89, 89, 38, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 22, 106, 22, 22, 22, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 35, 35, 52, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 16, 93, 123, 123, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 33, 33, 33, 33, 33, 93, 93, 93, 93, 140, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 22, 22, 22, 22, 22, 22, 106, 106, 106, 106, 52, 52, 106, 106, 22, 22, 22, 22, 
+#> 22, 22, 22, 22, 22, 89, 106, 106, 26, 125, 125, 35, 35, 125, 93, 106, 125, 45, 45, 45, 93, 93, 93, 93, 93, 93, 93, 93, 93, 140, 140, 140, 140, 140, 33, 89, 89, 102, 102, 102, 102, 125, 125, 125, 125, 125, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 125, 125, 38, 125, 125, 26, 26, 26, 89, 89, 89, 89, 89, 26, 89, 26, 26, 22, 22, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 45, 38, 45, 45, 45, 45, 45, 45, 45, 106, 101, 45, 45, 45, 45, 45, 
+#> 45, 45, 45, 45, 140, 140, 140, 93, 93, 93, 123, 123, 123, 123, 123, 123, 123, 93, 93, 93, 93, 16, 16, 16, 16, 16, 16, 16, 16, 93, 93, 93, 93, 140, 33, 38, 106, 106, 106, 106, 106, 106, 106, 106, 106, 125, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 16, 16, 16, 16, 16, 93, 93, 93, 93, 93, 38, 38, 38, 38, 38, 89, 89, 89, 89, 89, 89, 89, 89, 89, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 89, 89, 89, 106, 89, 89, 
+#> 89, 89, 89, 89, 89, 89, 38, 38, 38, 35, 38, 22, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 26, 26, 26, 26, 26, 89, 89, 89, 89, 89, 89, 89, 38, 89, 35, 38, 35, 35, 101, 101, 101, 101, 101, 16, 93, 93, 93, 93, 93, 93, 93, 26, 52, 101, 101, 101, 101, 101, 101, 16, 16, 16, 16, 93, 93, 93, 123, 106, 140, 89, 106, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 102, 102, 102, 102, 102, 102, 102, 102, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 35, 38, 38, 38, 38, 
+#> 22, 22, 22, 22, 140, 93, 140, 93, 52, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 38, 38, 38, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 93, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 38, 38, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 52, 52, 52, 52, 52, 89, 93, 93, 45, 29, 52, 52, 52, 52, 52, 52, 16, 16, 16, 16, 101, 101, 101, 101, 101, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 93, 93, 93, 101, 125, 106, 106, 106, 106, 106, 106, 35, 35, 35, 35, 
+#> 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 125, 125, 125, 89, 125, 89, 89, 89, 89, 125, 35, 38, 125, 26, 26, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 22, 22, 89, 89, 89, 89, 106, 106, 106, 106, 106, 106, 106, 106, 22, 22, 93, 106, 93, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 125, 38, 125, 22, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 16, 22, 16, 45, 45, 52, 52, 52, 52, 52, 52, 52, 140, 140, 101, 140, 101, 45, 
+#> 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 33, 123, 33, 33, 33, 140, 22, 22, 22, 22, 101, 101, 101, 16, 101, 16, 16, 16, 16, 16, 16, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 16, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 89, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 
+#> 123, 93, 93, 93, 93, 16, 16, 140, 140, 140, 140, 140, 140, 140, 140, 16, 52, 52, 123, 33, 101, 101, 101, 101, 101, 101, 101, 101, 101, 52, 52, 52, 52, 101, 101, 101, 101, 101, 101, 101, 101, 101, 33, 33, 33, 52, 140, 140, 26, 38, 101, 101, 16, 101, 140, 140, 140, 140, 140, 140, 140, 140, 140, 123, 140, 123, 123, 140, 52, 52, 52, 52, 140, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 106, 106, 106, 106, 106, 106, 106, 35, 35, 35, 35, 35, 35, 35, 35, 38, 38, 38, 
+#> 22, 106, 106, 106, 106, 106, 22, 22, 22, 22, 22, 33, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 38, 38, 38, 123, 123, 89, 89, 89, 89, 26, 89, 26, 106, 106, 106, 106, 106, 125, 125, 125, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 89, 45, 89, 16, 52, 52, 52, 52, 101, 101, 45, 101, 45, 16, 16, 45, 45, 45, 45, 45, 93, 93, 101, 33, 33, 33, 33, 33, 33, 33, 33, 33, 45, 45, 45, 45, 45, 52, 52, 52, 52, 52, 123, 123, 123, 140, 140, 140, 140, 140, 140, 16, 22, 22, 106, 106, 33, 33, 33, 33, 33, 33, 
+#> 33, 33, 33, 33, 101, 101, 101, 101, 101, 101, 101, 101, 101, 16, 16, 16, 16, 16, 16, 16, 16, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 89, 89, 89, 35, 35, 35, 35, 35, 35, 22, 22, 22, 102, 106, 106, 106, 106, 106, 106, 106, 102, 102, 102, 35, 102, 35, 35, 35, 45, 22, 22, 22, 22, 106, 35, 106, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 35, 22, 89, 89, 16, 16, 93, 93, 93, 93, 93, 93, 93, 93, 93, 52, 93, 52, 101, 22, 89, 
+#> 106, 106, 106, 106, 22, 106, 22, 33, 33, 33, 33, 33, 33, 33, 140, 140, 140, 102, 140, 123, 16, 123, 123, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 38, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 22, 26, 26, 22, 22, 93, 93, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 102, 102, 102, 102, 102, 102, 125, 125, 125, 125, 125, 125, 102, 102, 102, 102, 
+#> 102, 38, 38, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 26, 38, 106, 102, 22, 106, 106, 140, 123, 140, 123, 123, 123, 140, 140, 140, 140, 52, 140, 52, 52, 35, 16, 16, 16, 16, 26, 26, 26, 26, 26, 89, 89, 89, 38, 89, 38, 38, 38, 38, 26, 125, 125, 125, 125, 125, 125, 125, 125, 38, 38, 38, 38, 38, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 26, 125, 26, 26, 125, 89, 89, 89, 89, 89, 89, 89, 89, 89, 106, 106, 35, 22, 38, 38, 38, 38, 102, 45, 45, 45, 45, 33, 45, 
+#> 33, 33, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 33, 33, 33, 33, 33, 33, 33, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 101, 101, 101, 101, 101, 101, 33, 22, 33, 22, 125, 101, 101, 101, 101, 123, 123, 123, 123, 123, 123, 45, 45, 45, 45, 45, 45, 45, 16, 16, 16, 16, 140, 93, 140, 93, 22, 26, 123, 123, 123, 123, 123, 33, 123, 33, 33, 140, 140, 140, 123, 52, 123, 52, 89, 35, 35, 35, 35, 
+#> 35, 35, 35, 93, 93, 93, 89, 26, 26, 38, 38, 38, 38, 38, 38, 38, 38, 106, 106, 106, 106, 106, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 93, 93, 93, 16, 89, 102, 102, 22, 22, 22, 89, 89, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 16, 16, 16, 16, 16, 16, 16, 35, 35, 102, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 52, 52, 26, 106, 106, 140, 140, 140, 140, 140, 140, 140, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 125, 125, 125, 125, 125, 125, 125, 125, 125, 38, 125, 
+#> 38, 102, 123, 123, 123, 123, 123, 123, 123, 123, 123, 16, 123, 16, 16, 89, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 101, 16, 16, 16, 16, 26, 26, 26, 26, 26, 26, 26, 26, 22, 106, 106, 125, 125, 38, 125, 38, 38, 38, 38, 38, 38, 38, 38, 38, 35, 35, 35, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 22, 89, 22, 22, 22, 22, 22, 22, 102, 102, 102, 102, 102, 102, 35, 35, 35, 102, 102, 102, 102, 106, 102, 102, 102, 102, 102, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 140, 35, 35, 35, 35, 
+#> 35, 35, 35, 125, 125, 125, 125, 125, 35, 125, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 22, 35, 22, 22, 22, 26, 106, 45, 22, 22, 22, 22, 22, 22, 22, 89, 22, 89, 22, 22, 22, 125, 125, 125, 125, 125, 125, 125, 35, 35, 35, 35, 123, 106, 106, 106, 106, 102, 102, 102, 102, 89, 89, 89, 89, 35, 52, 52, 89, 89, 89, 89, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 101, 101, 101, 101, 101, 16, 16, 52, 52, 52, 52, 52, 52, 16, 52, 140, 140, 140, 140, 140, 140, 123, 123, 123, 123, 
+#> 123, 123, 140, 140, 140, 140, 33, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 140, 140, 140, 140, 45, 45, 35, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 26, 26, 26, 26, 26, 26, 26, 26, 89, 38, 89, 38, 38, 102, 22, 22, 22, 22, 22, 22, 22, 26, 26, 26, 26, 26, 106, 106, 106, 106, 106, 106, 106, 45, 125, 125, 125, 125, 125, 125, 125, 125, 22, 125, 22, 22, 22, 89, 89, 26, 89, 22, 125, 125, 89, 26, 89, 26, 26, 26, 26, 26, 26, 26, 26, 22, 89, 106, 106, 106, 106, 106, 106, 106, 106, 106, 
+#> 106, 22, 22, 22, 22, 93, 16, 93, 16, 16, 16, 101, 101, 38, 38, 38, 89, 52, 52, 52, 52, 52, 52, 52, 52, 52, 22, 52, 102, 102, 102, 102, 102, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 123, 93, 93, 93, 33, 101, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 106, 
+#> 101, 101, 101, 101, 101, 101, 101, 16, 16, 16, 16, 16, 140, 52, 52, 52, 52, 52, 52, 52, 45, 45, 45, 45, 45, 45, 45, 123, 16, 16, 22, 22, 140, 52, 52, 52, 52, 52, 52, 52, 52, 16, 16, 16, 16, 16, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 52, 52, 52, 52, 52, 52, 33, 33, 16, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 33, 33, 33, 33, 52, 52, 123, 123, 123, 140, 45, 45, 45, 102, 38, 102, 93, 93, 93, 93, 45, 45, 45, 45, 45, 22, 123, 22, 22, 89, 89, 101, 101, 101, 101, 101, 
+#> 101, 101, 33, 33, 33, 33, 16, 33, 16, 16, 101, 101, 101, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 106, 106, 106, 106, 106, 106, 106, 106, 106, 102, 106, 102, 106, 106, 106, 106, 106, 106, 35, 35, 35, 35, 35, 35, 22, 35, 22, 16, 16, 16, 16, 16, 16, 16, 93, 93, 93, 26, 38, 26, 26, 26, 26, 106, 140, 26, 45, 45, 52, 52, 52, 52, 52, 52, 123, 123, 102, 102, 102, 102, 102, 26, 102, 26, 26, 26, 102, 102, 
+#> 102, 102, 26, 26, 26, 22, 26, 26, 125, 125, 125, 125, 125, 125, 89, 89, 89, 89, 89, 93, 93, 93, 93, 93, 35, 35, 35, 35, 35, 35, 89, 89, 26, 89, 26, 125, 123, 26, 26, 26, 38, 38, 38, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 16, 16, 16, 16, 16, 16, 16, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 33, 106, 106, 106, 35, 106, 35, 38, 123, 123, 123, 123, 123, 45, 45, 45, 45, 38, 93, 93, 93, 102, 102, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 123, 140, 123, 26, 26, 22, 22, 35, 
+#> 123, 123, 140, 140, 16, 140, 123, 52, 123, 52, 52, 22, 140, 22, 123, 140, 101, 101, 101, 140, 93, 140, 89, 101, 140, 101, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 35, 45, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 102, 26, 102, 26, 22, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 26, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 102, 102, 26, 102, 26, 35, 38, 38, 38, 38, 38, 38, 38, 38, 35, 35, 93, 93, 93, 93, 93, 93, 93, 45, 45, 45, 45, 101, 101, 
+#> 101, 101, 101, 101, 101, 101, 101, 101, 140, 16, 16, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 22, 22, 22, 22, 140, 140, 140, 140, 140, 140, 140, 140, 140, 102, 102, 35, 35, 35, 35, 35, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 26, 26, 16, 16, 102, 102, 102, 102, 38, 102, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 26, 102, 102, 35, 102, 35, 125, 125, 22, 125, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 35, 38, 38, 38, 38, 38, 38, 38, 35, 93, 
+#> 89, 93, 106, 106, 106, 22, 22, 22, 22, 22, 22, 22, 89, 89, 89, 89, 89, 89, 35, 35, 35, 89, 123, 123, 123, 123, 123, 123, 123, 123, 123, 123, 140, 140, 140, 101, 101, 101, 101, 101, 101, 101, 101, 101, 123, 123, 101, 45, 101, 33, 45, 16, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 52, 52, 93, 101, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 102, 102, 102, 102, 102, 38, 38, 26, 26, 26, 26, 38, 38, 38, 38, 38, 102, 102, 125, 16, 16, 16, 16, 16, 16, 16, 102, 102, 45, 45, 45, 45, 33, 33, 33, 33, 33, 33, 33, 33, 
+#> 33, 33, 33, 89, 16, 16, 16, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 35, 35, 102, 102, 102, 102, 22, 22, 22, 22, 22, 22, 16, 125, 125, 125, 125, 125, 125, 125, 106, 52, 52, 52, 52, 33, 52, 33, 33, 33, 45, 22, 22, 22, 22, 22, 22, 102, 125, 125, 125, 125, 26, 26, 26, 38, 38, 38, 38, 38, 38, 38, 38, 106, 106, 125, 125, 125, 125, 125, 22, 22, 22, 22, 22, 22, 26, 26, 106, 45, 35, 35, 35, 102, 102, 22, 22, 22, 22, 22, 106, 106, 89, 106, 89, 125, 125, 125, 125, 125, 125, 125, 125, 125, 
+#> 125, 125, 125, 125, 93, 64, 93, 64, 93, 93, 93, 80, 93, 35, 35, 35, 35, 35, 35, 35, 35, 89, 89, 89, 89, 89, 89, 89, 35, 35, 22, 22, 22, 26, 26, 26, 93, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 16, 16, 16, 16, 16, 16, 16, 16, 16, 93, 93, 93, 93, 93, 93, 93, 106, 106, 106, 16, 16, 16, 45, 45, 45, 45, 45, 16, 106, 101, 101, 101, 101, 101, 101, 101, 101, 16, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 16, 16, 140, 140, 140, 140, 140, 16, 16, 123, 123, 123, 123, 123, 123, 123, 123, 16, 16, 16, 
+#> 16, 16, 33, 123, 5, 5, 33, 125, 125, 125, 125, 125, 125, 125, 26, 125, 26, 26, 89, 35, 102, 102, 102, 102, 38, 125, 125, 125, 26, 26, 26, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 123, 123, 125, 125, 125, 125, 22, 22, 22, 22, 22, 35, 35, 35, 16, 16, 16, 16, 16, 16, 16, 16, 16, 52, 52, 52, 140, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 16, 16, 33, 101, 93, 93, 93, 93, 93, 93, 93, 125, 125, 125, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 16, 52, 5, 89, 89, 89, 89, 102, 102, 45, 
+#> 45, 45, 45, 45, 45, 52, 52, 52, 52, 52, 52, 52, 93, 89, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 52, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 125, 125, 125, 125, 125, 125, 89, 89, 89, 38, 89, 26, 38, 26, 26, 80, 35, 106, 35, 125, 125, 26, 26, 38, 38, 106, 106, 106, 106, 106, 102, 89, 102, 93, 93, 93, 93, 93, 93, 93, 93, 123, 45, 45, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 45, 45, 106, 106, 
+#> 106, 106, 106, 106, 106, 106, 26, 26, 26, 26, 26, 89, 33, 123, 125, 125, 125, 125, 26, 26, 26, 125, 125, 102, 125, 102, 35, 102, 35, 26, 35, 89, 89, 89, 89, 89, 26, 89, 26, 26, 35, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 93, 93, 93, 93, 33, 93, 33, 52, 22, 52, 22, 22, 22, 22, 22, 22, 22, 22, 106, 106, 101, 101, 102, 102, 93, 93, 93, 93, 102, 38, 38, 22, 22, 22, 22, 26, 26, 26, 26, 26, 89, 26, 26, 33, 33, 33, 22, 89, 89, 89, 101, 52, 52, 52, 52, 16, 16, 16, 16, 16, 16, 45, 45, 45, 
+#> 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 52, 52, 52, 52, 52, 101, 101, 101, 140, 140, 140, 45, 106, 52, 52, 22, 123, 123, 93, 123, 140, 45, 45, 45, 52, 52, 52, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 33, 33, 125, 125, 125, 125, 125, 125, 125, 125, 125, 35, 35, 35, 35, 35, 35, 35, 35, 22, 35, 22, 80, 80, 80, 80, 80, 80, 80, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 123, 93, 93, 93, 35, 93, 35, 35, 35, 102, 52, 102, 106, 52, 26, 26, 26, 26, 26, 26, 
+#> 26, 26, 26, 26, 22, 38, 38, 38, 38, 26, 26, 26, 125, 125, 26, 26, 26, 35, 35, 35, 35, 35, 35, 101, 101, 140, 22, 22, 22, 22, 22, 22, 89, 89, 26, 26, 101, 52, 52, 52, 52, 52, 140, 140, 140, 140, 140, 140, 140, 140, 45, 45, 140, 140, 140, 140, 140, 140, 16, 16, 45, 80, 106, 101, 101, 101, 52, 101, 52, 52, 52, 52, 52, 16, 52, 16, 16, 33, 33, 5, 33, 5, 93, 93, 93, 93, 33, 52, 52, 16, 52, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 16, 16, 125, 125, 125, 125, 125, 125, 125, 125, 106, 125, 106, 
+#> 35, 106, 35, 35, 33, 106, 35, 22, 35, 22, 22, 22, 26, 26, 89, 89, 125, 125, 35, 35, 35, 35, 35, 35, 35, 106, 106, 106, 106, 35, 35, 35, 35, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 125, 125, 33, 38, 26, 26, 26, 26, 26, 26, 26, 93, 93, 93, 93, 64, 93, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 72, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 38, 123, 123, 123, 123, 123, 123, 123, 123, 101, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 
+#> 94, 45, 45, 45, 45, 45, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 22, 22, 22, 22, 22, 22, 35, 35, 35, 140, 38, 38, 38, 38, 38, 38, 38, 38, 38, 93, 93, 64, 106, 106, 106, 106, 106, 106, 106, 35, 106, 35, 45, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 52, 52, 93, 22, 26, 26, 26, 26, 26, 26, 26, 26, 80, 80, 80, 80, 80, 80, 80, 80, 80, 80, 80, 80, 94, 117, 89, 89, 89, 89, 89, 26, 26, 26, 38, 38, 33, 33, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 101, 101, 101, 101, 101, 101, 
+#> 33, 33, 45, 52, 52, 52, 52, 52, 52, 52, 52, 52, 16, 52, 16, 16, 16, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 93, 93, 93, 93, 93, 93, 93, 93, 125, 64, 125, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 106, 33, 33, 33, 35, 35, 35, 35, 35, 35, 35, 22, 35, 22, 38, 93, 93, 140, 140, 140, 5, 16, 26, 26, 26, 89, 89, 89, 89, 89, 89, 89, 125, 125, 35, 125, 35, 80, 102, 93, 93, 93, 93, 93, 93, 93, 106, 33, 33, 33, 33, 33, 33, 33, 33, 140, 140, 101, 123, 140, 101, 33, 16, 16, 16, 16, 
+#> 16, 16, 16, 16, 16, 16, 52, 52, 52, 52, 52, 52, 123, 123, 5, 45, 45, 45, 45, 45, 16, 16, 16, 52, 52, 52, 79, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 72, 72, 72, 72, 94, 94, 89, 89, 89, 89, 89, 89, 89, 26, 26, 26, 80, 106, 89, 106, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 38, 72, 38, 38, 45, 123, 123, 123, 123, 123, 140, 140, 140, 140, 140, 140, 33, 33, 102, 102, 102, 141, 141, 123, 123, 16, 16, 16, 16, 16, 16, 16, 16, 33, 125, 33, 93, 93, 93, 93, 93, 93, 93, 93, 
+#> 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 16, 16, 16, 16, 52, 52, 52, 33, 33, 33, 33, 38, 5, 38, 5, 5, 52, 52, 52, 52, 52, 52, 52, 45, 52, 45, 45, 45, 5, 45, 38, 26, 102, 102, 102, 102, 102, 102, 93, 102, 93, 93, 125, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 72, 72, 72, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 72, 72, 72, 72, 72, 94, 117, 89, 89, 89, 89, 89, 89, 89, 89, 38, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 45, 102, 64, 26, 26, 26, 
+#> 106, 45, 45, 45, 45, 45, 45, 45, 45, 45, 33, 33, 45, 33, 52, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 89, 89, 89, 89, 89, 89, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 94, 117, 94, 89, 89, 89, 89, 89, 89, 45, 89, 22, 45, 22, 93, 93, 125, 125, 106, 106, 106, 106, 22, 22, 22, 22, 22, 22, 22, 101, 101, 101, 101, 101, 101, 64, 64, 93, 93, 93, 93, 106, 58, 125, 125, 35, 102, 125, 38, 38, 38, 38, 35, 38, 35, 35, 35, 35, 35, 35, 125, 89, 117, 117, 101, 101, 101, 93, 5, 33, 33, 
+#> 52, 22, 22, 22, 22, 38, 38, 140, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 5, 5, 5, 5, 58, 35, 58, 45, 45, 45, 45, 45, 45, 93, 93, 93, 93, 93, 93, 64, 93, 52, 45, 38, 79, 80, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 52, 52, 52, 52, 52, 52, 52, 52, 45, 117, 117, 117, 117, 35, 117, 35, 102, 22, 22, 22, 22, 22, 72, 72, 72, 72, 72, 72, 72, 72, 72, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 89, 
+#> 125, 80, 89, 80, 80, 80, 125, 125, 125, 93, 93, 93, 93, 140, 140, 140, 140, 140, 16, 16, 16, 106, 35, 106, 106, 89, 89, 89, 89, 89, 89, 117, 93, 93, 93, 93, 64, 93, 64, 38, 45, 125, 64, 125, 125, 125, 125, 125, 72, 72, 72, 72, 72, 72, 72, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 106, 33, 106, 33, 71, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 5, 16, 80, 26, 26, 26, 80, 89, 89, 89, 89, 117, 117, 117, 45, 80, 38, 38, 116, 116, 116, 116, 116, 35, 86, 22, 22, 22, 22, 72, 72, 72, 72, 72, 72, 72, 72, 52, 
+#> 72, 52, 114, 45, 45, 45, 45, 45, 33, 33, 33, 125, 106, 125, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 101, 101, 101, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 58, 58, 26, 80, 80, 80, 80, 80, 80, 80, 80, 80, 80, 80, 80, 80, 4, 52, 58, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 123, 5, 93, 93, 
+#> 93, 93, 93, 64, 33, 64, 117, 117, 58, 117, 5, 58, 35, 33, 33, 33, 33, 33, 33, 33, 5, 5, 5, 5, 5, 33, 33, 33, 16, 16, 16, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 5, 5, 5, 5, 5, 5, 72, 30, 30, 45, 45, 45, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 94, 33, 94, 33, 72, 72, 80, 80, 80, 80, 80, 80, 80, 80, 80, 80, 80, 80, 4, 4, 4, 4, 4, 4, 4, 4, 4, 83, 83, 52, 52, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 117, 117, 117, 93, 26, 26, 80, 80, 80, 80, 80, 80, 80, 80, 80, 80, 80, 125, 
+#> 35, 125, 35, 102, 30, 30, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 30, 45, 93, 93, 123, 123, 123, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 45, 33, 45, 33, 33, 33, 33, 33, 33, 45, 45, 33, 33, 125, 141, 33, 33, 33, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 80, 80, 80, 80, 94, 94, 94, 93, 93, 93, 93, 93, 93, 93, 93, 93, 102, 102, 102, 117, 117, 117, 117, 117, 117, 30, 117, 30, 30, 64, 52, 52, 52, 52, 52, 52, 52, 52, 52, 102, 102, 102, 102, 106, 72, 106, 102, 102, 93, 93, 93, 93, 93, 93, 93, 
+#> 93, 93, 93, 93, 93, 16, 93, 16, 123, 123, 5, 93, 93, 93, 93, 93, 93, 93, 93, 16, 71, 101, 64, 64, 64, 45, 64, 45, 45, 45, 79, 79, 71, 79, 102, 30, 52, 52, 52, 52, 52, 52, 80, 80, 80, 80, 80, 4, 16, 16, 16, 16, 16, 16, 16, 16, 45, 45, 45, 141, 71, 94, 141, 71, 30, 30, 30, 93, 93, 93, 64, 64, 64, 64, 5, 5, 30, 16, 117, 16, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 26, 26, 80, 80, 80, 80, 80, 80, 80, 80, 80, 80, 80, 117, 106, 45, 125, 125, 125, 125, 102, 125, 
+#> 102, 38, 106, 106, 106, 106, 106, 5, 5, 93, 93, 93, 140, 140, 16, 16, 16, 16, 16, 16, 16, 140, 5, 140, 5, 71, 71, 71, 71, 30, 30, 117, 117, 117, 117, 117, 117, 117, 117, 117, 125, 125, 125, 4, 4, 4, 4, 96, 16, 66, 106, 106, 106, 106, 106, 106, 106, 106, 38, 35, 35, 80, 94, 94, 94, 102, 58, 80, 102, 35, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 93, 94, 72, 72, 72, 72, 72, 72, 52, 52, 52, 52, 58, 30, 140, 140, 140, 140, 140, 140, 140, 140, 45, 45, 45, 45, 45, 45, 45, 
+#> 45, 45, 33, 33, 33, 33, 33, 45, 22, 22, 72, 72, 72, 72, 94, 38, 94, 89, 125, 117, 117, 5, 5, 5, 5, 5, 5, 102, 58, 102, 140, 140, 140, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 114, 114, 96, 114, 117, 117, 117, 117, 45, 45, 35, 35, 125, 125, 117, 117, 117, 52, 125, 5, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 33, 33, 33, 
+#> 33, 33, 140, 79, 79, 79, 79, 79, 79, 79, 33, 33, 33, 33, 33, 33, 33, 33, 64, 45, 16, 52, 58, 45, 45, 64, 64, 93, 93, 93, 93, 93, 93, 93, 125, 125, 89, 117, 125, 125, 125, 125, 125, 125, 125, 102, 102, 102, 125, 106, 106, 106, 106, 106, 106, 106, 106, 106, 125, 125, 125, 102, 102, 117, 5, 5, 5, 5, 5, 33, 33, 33, 33, 33, 33, 141, 33, 93, 93, 66, 72, 72, 72, 72, 72, 72, 72, 141, 141, 141, 141, 141, 141, 141, 52, 131, 52, 93, 93, 93, 93, 93, 93, 93, 93, 93, 72, 33, 141, 33, 33, 30, 33, 125, 125, 125, 
+#> 125, 125, 35, 125, 35, 35, 140, 33, 33, 33, 5, 33, 5, 16, 16, 16, 16, 16, 16, 16, 79, 125, 125, 125, 125, 125, 125, 125, 125, 35, 35, 35, 117, 117, 93, 117, 93, 93, 93, 93, 93, 66, 66, 5, 5, 5, 5, 5, 35, 94, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 80, 94, 33, 94, 22, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 79, 79, 141, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 
+#> 38, 125, 45, 45, 30, 30, 66, 66, 72, 72, 72, 72, 72, 72, 72, 72, 106, 106, 72, 86, 72, 72, 72, 16, 16, 106, 106, 106, 4, 106, 4, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 96, 96, 33, 33, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 45, 45, 45, 45, 45, 52, 52, 52, 52, 64, 45, 45, 33, 45, 72, 93, 35, 35, 102, 102, 102, 38, 102, 38, 38, 38, 106, 106, 106, 106, 106, 33, 106, 33, 33, 33, 80, 80, 80, 80, 80, 80, 80, 38, 38, 38, 38, 38, 4, 38, 125, 106, 106, 38, 93, 
+#> 93, 93, 93, 125, 125, 125, 102, 125, 89, 117, 117, 117, 117, 117, 5, 5, 5, 5, 5, 4, 117, 117, 125, 71, 71, 71, 45, 45, 45, 45, 33, 45, 117, 93, 64, 93, 64, 64, 93, 93, 93, 93, 93, 93, 45, 64, 94, 94, 22, 22, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 140, 140, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 33, 79, 33, 33, 102, 102, 102, 93, 102, 93, 125, 125, 125, 125, 35, 35, 35, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 93, 93, 93, 93, 93, 93, 93, 93, 52, 93, 26, 26, 
+#> 26, 52, 33, 33, 33, 33, 33, 33, 141, 45, 45, 45, 45, 72, 72, 72, 72, 72, 72, 72, 72, 94, 33, 58, 115, 35, 58, 96, 96, 5, 35, 5, 5, 5, 30, 66, 106, 106, 106, 106, 38, 38, 38, 38, 38, 38, 38, 125, 106, 16, 16, 16, 16, 16, 45, 35, 45, 52, 86, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 52, 106, 86, 22, 22, 22, 72, 72, 72, 72, 72, 72, 72, 72, 72, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 140, 140, 79, 79, 79, 79, 79, 79, 79, 
+#> 72, 45, 141, 4, 38, 38, 38, 38, 38, 38, 38, 125, 58, 58, 58, 58, 58, 58, 38, 38, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 141, 102, 102, 102, 102, 102, 102, 102, 102, 86, 86, 86, 86, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 16, 16, 16, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 102, 102, 102, 102, 102, 38, 86, 38, 38, 93, 93, 93, 93, 93, 93, 93, 93, 35, 58, 35, 35, 4, 35, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 16, 72, 33, 33, 
+#> 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 35, 35, 93, 93, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 71, 71, 71, 71, 30, 30, 79, 79, 79, 45, 94, 52, 45, 45, 45, 45, 45, 30, 45, 30, 125, 125, 106, 106, 96, 106, 96, 72, 72, 72, 72, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 33, 125, 102, 102, 102, 102, 102, 102, 93, 93, 93, 30, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 102, 102, 102, 102, 102, 102, 102, 125, 72, 33, 33, 
+#> 33, 102, 102, 96, 106, 106, 106, 106, 106, 16, 16, 102, 72, 94, 30, 140, 140, 140, 140, 140, 140, 140, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 66, 71, 71, 71, 71, 30, 30, 30, 30, 30, 30, 30, 94, 94, 131, 131, 131, 131, 106, 131, 106, 94, 94, 94, 94, 72, 117, 117, 117, 86, 86, 86, 86, 125, 80, 80, 80, 80, 80, 80, 4, 4, 4, 125, 125, 125, 125, 125, 125, 94, 94, 94, 106, 106, 106, 106, 106, 106, 106, 106, 72, 114, 72, 106, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 38, 
+#> 38, 38, 38, 38, 38, 38, 38, 38, 79, 79, 79, 30, 45, 131, 131, 5, 5, 5, 5, 58, 93, 93, 96, 96, 114, 72, 72, 72, 72, 72, 72, 72, 72, 125, 45, 45, 45, 45, 45, 38, 38, 86, 79, 79, 79, 79, 30, 30, 45, 35, 45, 93, 4, 35, 45, 45, 45, 45, 45, 45, 45, 79, 79, 79, 79, 72, 86, 125, 96, 106, 96, 106, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 64, 93, 64, 38, 38, 38, 38, 4, 102, 102, 102, 102, 96, 102, 16, 83, 96, 16, 33, 16, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 
+#> 106, 106, 106, 106, 106, 117, 117, 117, 33, 33, 33, 33, 5, 33, 5, 45, 30, 30, 30, 30, 33, 33, 125, 140, 140, 140, 140, 45, 45, 35, 4, 35, 38, 38, 35, 35, 66, 125, 66, 66, 71, 30, 30, 30, 30, 30, 33, 33, 66, 66, 45, 45, 45, 33, 33, 33, 94, 94, 94, 94, 94, 58, 125, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 38, 38, 38, 38, 38, 38, 38, 38, 58, 58, 58, 58, 106, 16, 106, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 45, 45, 72, 141, 141, 141, 141, 141, 141, 141, 4, 4, 4, 16, 16, 16, 16, 16, 16, 
+#> 16, 52, 52, 52, 52, 52, 114, 117, 117, 117, 117, 117, 117, 80, 80, 4, 4, 4, 4, 96, 93, 96, 93, 86, 93, 83, 64, 64, 64, 64, 96, 93, 115, 93, 93, 35, 93, 35, 4, 94, 52, 52, 52, 52, 52, 52, 72, 72, 35, 72, 35, 35, 35, 33, 35, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 86, 86, 86, 16, 16, 16, 102, 38, 38, 38, 35, 35, 35, 35, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 16, 16, 16, 16, 16, 16, 16, 83, 102, 102, 102, 102, 102, 102, 102, 89, 89, 117, 117, 117, 
+#> 117, 117, 5, 5, 141, 141, 117, 117, 117, 93, 117, 66, 16, 16, 16, 16, 16, 16, 83, 83, 83, 83, 83, 16, 16, 16, 66, 93, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 93, 93, 38, 93, 93, 72, 72, 72, 72, 72, 72, 72, 72, 72, 117, 117, 35, 35, 35, 35, 35, 35, 35, 35, 79, 114, 35, 35, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 30, 30, 30, 30, 30, 30, 30, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 38, 94, 38, 38, 38, 38, 38, 94, 33, 33, 16, 33, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 102, 102, 86, 102, 
+#> 125, 16, 125, 16, 102, 102, 102, 102, 102, 102, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 72, 72, 4, 83, 93, 102, 35, 102, 35, 35, 35, 35, 35, 35, 35, 131, 131, 16, 16, 131, 131, 131, 131, 35, 35, 30, 30, 30, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 94, 114, 114, 52, 52, 52, 52, 52, 52, 52, 52, 141, 4, 96, 16, 16, 16, 16, 16, 16, 16, 16, 125, 125, 72, 125, 72, 72, 72, 72, 72, 117, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 35, 35, 35, 35, 35, 35, 35, 35, 35, 114, 114, 
+#> 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 96, 125, 96, 106, 96, 106, 96, 93, 93, 93, 93, 93, 33, 33, 33, 33, 96, 96, 86, 96, 86, 86, 86, 86, 30, 102, 64, 64, 64, 64, 141, 16, 64, 141, 16, 16, 45, 45, 45, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 131, 45, 96, 134, 116, 116, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 86, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 125, 33, 125, 33, 33, 16, 16, 16, 16, 106, 
+#> 106, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 94, 94, 94, 94, 38, 125, 58, 58, 58, 58, 5, 5, 5, 5, 5, 5, 5, 5, 30, 5, 5, 5, 5, 5, 5, 5, 5, 4, 4, 4, 102, 35, 102, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 72, 4, 4, 4, 4, 4, 4, 4, 94, 94, 94, 94, 94, 64, 64, 64, 93, 93, 93, 93, 93, 93, 93, 93, 4, 4, 4, 4, 4, 5, 45, 66, 66, 66, 66, 66, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 72, 72, 125, 125, 125, 125, 125, 72, 102, 102, 16, 35, 16, 64, 96, 96, 96, 96, 96, 
+#> 96, 96, 96, 5, 93, 93, 93, 93, 93, 30, 30, 30, 30, 30, 96, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 125, 125, 125, 125, 125, 125, 125, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 33, 102, 117, 45, 79, 79, 117, 117, 117, 117, 117, 117, 106, 106, 106, 106, 106, 125, 96, 125, 93, 125, 114, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 33, 72, 72, 72, 72, 72, 72, 72, 79, 79, 79, 52, 79, 52, 72, 30, 125, 38, 38, 38, 79, 93, 125, 33, 58, 86, 106, 106, 106, 106, 106, 
+#> 106, 106, 106, 86, 94, 94, 94, 125, 45, 45, 45, 45, 45, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 52, 45, 45, 96, 30, 30, 30, 30, 30, 30, 131, 131, 131, 33, 33, 93, 93, 93, 93, 96, 96, 45, 45, 45, 45, 45, 45, 96, 96, 96, 45, 45, 116, 83, 33, 33, 33, 33, 33, 33, 33, 33, 33, 30, 30, 30, 83, 45, 58, 58, 58, 58, 58, 58, 58, 58, 58, 114, 114, 134, 16, 16, 16, 16, 16, 16, 30, 16, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 86, 86, 86, 86, 4, 4, 4, 4, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 117, 93, 117, 
+#> 93, 106, 79, 79, 79, 79, 38, 38, 38, 38, 131, 131, 131, 125, 125, 125, 125, 38, 38, 38, 38, 114, 114, 102, 102, 106, 114, 96, 96, 96, 96, 96, 96, 96, 96, 96, 117, 117, 117, 117, 66, 66, 117, 117, 94, 94, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 106, 117, 117, 117, 117, 117, 117, 117, 93, 30, 30, 33, 131, 45, 125, 35, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 86, 125, 131, 114, 30, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 102, 102, 131, 45, 45, 45, 45, 93, 93, 
+#> 93, 93, 93, 93, 4, 4, 4, 4, 4, 4, 4, 93, 4, 4, 4, 5, 5, 4, 4, 86, 96, 38, 102, 102, 102, 102, 102, 102, 102, 66, 125, 66, 66, 66, 66, 66, 66, 66, 93, 93, 93, 93, 93, 93, 93, 93, 117, 117, 35, 35, 35, 93, 93, 93, 93, 93, 5, 5, 5, 5, 5, 5, 38, 38, 114, 114, 30, 30, 30, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 38, 38, 38, 38, 38, 38, 38, 58, 58, 58, 5, 5, 5, 5, 5, 5, 66, 66, 106, 106, 106, 106, 106, 106, 106, 106, 106, 96, 106, 106, 106, 64, 16, 64, 96, 83, 83, 83, 45, 79, 30, 45, 94, 
+#> 66, 94, 58, 58, 58, 58, 58, 58, 125, 106, 106, 106, 106, 106, 106, 106, 35, 96, 58, 58, 58, 58, 58, 58, 58, 58, 58, 38, 38, 38, 38, 38, 38, 38, 38, 58, 117, 117, 102, 96, 96, 96, 96, 96, 96, 96, 96, 96, 114, 114, 114, 114, 125, 125, 106, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 45, 45, 45, 45, 131, 131, 131, 114, 114, 93, 131, 4, 116, 66, 116, 30, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 141, 141, 141, 141, 
+#> 141, 141, 141, 141, 141, 141, 52, 52, 52, 52, 93, 125, 131, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 38, 38, 38, 38, 125, 72, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 35, 35, 35, 35, 94, 94, 94, 94, 94, 94, 94, 94, 131, 131, 131, 131, 131, 131, 64, 96, 96, 96, 96, 96, 96, 96, 96, 96, 30, 30, 30, 30, 16, 96, 45, 45, 45, 45, 141, 66, 30, 38, 30, 66, 125, 117, 117, 117, 117, 117, 117, 86, 117, 86, 86, 86, 86, 86, 86, 79, 86, 125, 35, 35, 117, 117, 117, 16, 16, 16, 16, 16, 93, 
+#> 93, 93, 93, 93, 93, 93, 131, 102, 131, 102, 33, 102, 80, 80, 4, 4, 4, 38, 38, 38, 38, 38, 38, 38, 38, 33, 33, 125, 106, 64, 64, 64, 64, 96, 96, 96, 96, 96, 96, 96, 96, 96, 131, 131, 30, 131, 30, 30, 93, 5, 5, 5, 5, 5, 5, 5, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 94, 94, 94, 86, 86, 86, 86, 86, 86, 96, 131, 131, 94, 94, 94, 4, 94, 4, 125, 125, 35, 58, 58, 58, 58, 58, 58, 58, 58, 117, 117, 117, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 114, 
+#> 117, 117, 117, 117, 117, 4, 4, 4, 4, 102, 102, 102, 35, 35, 35, 35, 116, 58, 58, 58, 58, 66, 66, 66, 66, 66, 66, 134, 134, 134, 134, 93, 134, 64, 64, 96, 96, 96, 96, 96, 96, 96, 96, 96, 83, 83, 83, 83, 83, 35, 35, 35, 35, 35, 35, 35, 96, 96, 96, 96, 5, 93, 93, 35, 93, 35, 4, 4, 4, 4, 4, 4, 4, 4, 117, 117, 117, 117, 117, 117, 117, 117, 52, 52, 52, 52, 52, 4, 117, 117, 117, 117, 117, 117, 117, 125, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 52, 115, 58, 86, 86, 86, 86, 
+#> 72, 72, 4, 72, 4, 131, 79, 79, 79, 94, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 114, 114, 114, 114, 114, 64, 64, 64, 64, 64, 96, 96, 96, 96, 96, 96, 96, 64, 64, 64, 96, 96, 96, 96, 96, 96, 96, 93, 93, 93, 93, 93, 58, 58, 58, 38, 38, 38, 38, 38, 38, 38, 38, 38, 66, 66, 66, 30, 30, 30, 30, 30, 72, 72, 72, 4, 4, 93, 72, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 79, 79, 79, 79, 79, 79, 79, 131, 141, 141, 131, 131, 131, 131, 131, 4, 4, 4, 4, 116, 96, 96, 
+#> 96, 134, 131, 131, 131, 131, 131, 45, 114, 45, 45, 45, 45, 45, 45, 125, 125, 125, 125, 102, 125, 102, 102, 102, 102, 45, 45, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 38, 38, 38, 38, 38, 38, 38, 93, 93, 106, 106, 106, 106, 106, 106, 33, 131, 131, 131, 116, 116, 116, 33, 33, 33, 33, 33, 33, 106, 72, 72, 72, 72, 72, 4, 4, 4, 30, 96, 96, 96, 96, 96, 96, 96, 96, 96, 114, 114, 114, 114, 83, 83, 83, 83, 131, 35, 35, 35, 117, 117, 106, 117, 106, 106, 106, 
+#> 106, 106, 72, 106, 72, 52, 72, 45, 45, 45, 45, 45, 45, 79, 16, 16, 16, 16, 16, 16, 16, 16, 93, 93, 106, 30, 16, 16, 16, 16, 16, 16, 16, 30, 30, 30, 30, 5, 5, 5, 5, 52, 52, 114, 125, 125, 125, 125, 117, 125, 125, 125, 125, 35, 106, 117, 117, 117, 102, 117, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 38, 38, 38, 38, 38, 38, 38, 38, 38, 30, 38, 117, 117, 117, 117, 117, 117, 117, 4, 114, 93, 114, 93, 93, 93, 79, 79, 79, 45, 45, 45, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 114, 114, 114, 
+#> 4, 86, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 141, 141, 131, 131, 131, 131, 131, 131, 131, 45, 45, 45, 45, 45, 93, 131, 131, 114, 114, 114, 114, 114, 114, 114, 114, 94, 94, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 33, 33, 33, 33, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 131, 131, 131, 131, 86, 86, 102, 117, 72, 134, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 106, 38, 38, 38, 38, 96, 96, 83, 30, 134, 33, 33, 33, 33, 33, 106, 93, 93, 93, 93, 93, 
+#> 93, 114, 114, 114, 114, 35, 93, 117, 131, 96, 96, 116, 125, 125, 125, 125, 125, 125, 125, 125, 66, 66, 4, 4, 4, 117, 117, 38, 117, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 94, 94, 94, 94, 33, 94, 30, 30, 30, 30, 141, 52, 52, 52, 52, 52, 52, 52, 52, 52, 93, 114, 93, 33, 5, 33, 131, 131, 131, 131, 131, 131, 131, 131, 131, 131, 83, 66, 66, 35, 35, 131, 131, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 5, 45, 45, 45, 45, 45, 45, 45, 45, 45, 83, 83, 83, 83, 83, 45, 45, 33, 
+#> 33, 33, 33, 33, 33, 33, 72, 72, 72, 72, 72, 72, 93, 93, 93, 30, 93, 30, 30, 30, 96, 93, 93, 93, 93, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 58, 58, 83, 83, 83, 30, 96, 30, 30, 72, 79, 79, 79, 79, 16, 16, 16, 16, 16, 35, 35, 102, 125, 52, 86, 38, 38, 38, 38, 125, 93, 102, 102, 66, 35, 52, 52, 52, 52, 52, 117, 114, 114, 114, 125, 94, 38, 38, 94, 94, 94, 94, 94, 94, 72, 72, 102, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 38, 38, 38, 38, 66, 
+#> 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 30, 30, 30, 30, 30, 30, 30, 30, 16, 131, 131, 131, 52, 131, 52, 52, 52, 52, 52, 52, 52, 93, 94, 30, 30, 30, 30, 30, 30, 93, 93, 93, 93, 131, 131, 131, 131, 131, 131, 30, 102, 102, 102, 102, 102, 102, 117, 4, 117, 4, 94, 94, 131, 86, 114, 86, 106, 102, 106, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 30, 30, 30, 30, 30, 30, 30, 66, 66, 38, 38, 38, 38, 38, 38, 38, 38, 38, 93, 93, 93, 93, 4, 93, 4, 4, 38, 38, 38, 116, 116, 66, 66, 66, 66, 
+#> 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 16, 16, 16, 16, 131, 131, 131, 93, 116, 30, 30, 30, 30, 30, 5, 66, 134, 134, 66, 66, 66, 66, 66, 66, 30, 52, 52, 116, 116, 116, 116, 116, 4, 4, 4, 4, 4, 4, 4, 4, 72, 72, 72, 72, 72, 72, 72, 72, 117, 96, 96, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 72, 72, 72, 94, 94, 45, 45, 5, 45, 2, 72, 86, 86, 86, 86, 86, 86, 86, 86, 86, 86, 86, 35, 35, 35, 35, 35, 35, 16, 16, 55, 55, 106, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 72, 72, 96, 83, 94, 
+#> 102, 102, 102, 102, 79, 79, 79, 79, 79, 83, 83, 83, 83, 83, 94, 94, 94, 94, 94, 30, 30, 30, 30, 30, 30, 30, 30, 58, 58, 58, 58, 58, 58, 58, 58, 58, 131, 131, 131, 131, 131, 16, 16, 16, 16, 16, 16, 16, 30, 30, 30, 30, 30, 5, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 83, 83, 83, 83, 83, 4, 4, 4, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 93, 35, 35, 106, 106, 106, 117, 117, 117, 117, 117, 125, 125, 125, 125, 125, 125, 114, 114, 114, 114, 114, 114, 114, 114, 114, 94, 114, 33, 33, 
+#> 33, 33, 93, 93, 93, 93, 93, 93, 131, 131, 66, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 16, 16, 16, 16, 16, 16, 16, 30, 30, 30, 16, 16, 16, 16, 16, 125, 125, 125, 125, 125, 125, 125, 125, 125, 94, 125, 94, 94, 94, 94, 94, 94, 45, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 96, 96, 35, 96, 35, 35, 58, 58, 86, 86, 86, 86, 86, 86, 86, 94, 94, 30, 131, 80, 80, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 93, 93, 45, 4, 45, 134, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 
+#> 52, 52, 52, 52, 52, 4, 4, 4, 4, 4, 4, 4, 4, 4, 125, 58, 58, 58, 58, 58, 58, 86, 86, 86, 94, 94, 94, 94, 52, 52, 52, 52, 86, 131, 94, 94, 94, 94, 94, 83, 83, 83, 83, 83, 83, 83, 83, 83, 83, 83, 83, 83, 83, 83, 83, 83, 83, 83, 83, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 125, 125, 125, 93, 114, 114, 16, 16, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 134, 134, 134, 134, 5, 5, 35, 35, 35, 35, 35, 125, 125, 125, 125, 4, 4, 4, 16, 16, 16, 16, 16, 16, 83, 83, 83, 83, 83, 83, 83, 83, 83, 83, 83, 45, 
+#> 45, 45, 45, 45, 45, 45, 131, 131, 131, 131, 131, 131, 38, 131, 38, 38, 38, 58, 131, 83, 83, 83, 83, 83, 83, 83, 125, 114, 102, 114, 102, 106, 96, 96, 35, 35, 35, 35, 102, 102, 102, 102, 45, 86, 117, 117, 35, 35, 35, 38, 114, 114, 114, 114, 114, 114, 114, 114, 93, 93, 93, 93, 93, 93, 93, 93, 30, 93, 30, 134, 79, 79, 45, 5, 5, 5, 5, 5, 5, 96, 30, 30, 30, 30, 30, 30, 93, 93, 93, 16, 16, 79, 96, 35, 35, 35, 35, 86, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 131, 131, 131, 33, 38, 33, 
+#> 83, 102, 83, 45, 79, 79, 79, 79, 79, 79, 45, 45, 45, 134, 134, 134, 134, 134, 134, 96, 96, 96, 72, 72, 72, 72, 134, 134, 72, 72, 72, 72, 72, 45, 45, 35, 45, 35, 35, 35, 35, 35, 35, 35, 5, 5, 125, 83, 83, 83, 83, 83, 83, 66, 66, 66, 66, 125, 125, 125, 125, 125, 131, 131, 94, 94, 86, 86, 86, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 131, 79, 131, 79, 79, 79, 79, 79, 79, 93, 93, 33, 93, 79, 79, 79, 117, 117, 117, 117, 94, 94, 30, 93, 94, 114, 35, 35, 35, 94, 94, 94, 96, 96, 96, 106, 106, 106, 106, 106, 106, 106, 
+#> 106, 58, 93, 93, 66, 93, 4, 35, 35, 35, 114, 52, 52, 52, 4, 4, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 93, 93, 79, 93, 79, 94, 94, 94, 94, 94, 94, 94, 94, 94, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 117, 117, 33, 35, 35, 35, 33, 33, 5, 5, 5, 96, 96, 96, 96, 96, 96, 96, 96, 96, 96, 52, 102, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 96, 96, 35, 35, 96, 96, 96, 96, 96, 96, 96, 96, 96, 96, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 
+#> 38, 38, 38, 94, 94, 94, 94, 94, 86, 131, 86, 86, 52, 86, 86, 86, 86, 86, 86, 86, 86, 86, 86, 86, 86, 94, 94, 94, 94, 94, 117, 72, 86, 114, 114, 114, 114, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 125, 125, 117, 45, 45, 45, 72, 72, 72, 72, 72, 79, 131, 93, 93, 93, 93, 93, 93, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 102, 102, 30, 30, 30, 30, 116, 45, 106, 134, 16, 16, 16, 52, 52, 52, 52, 83, 83, 83, 83, 83, 83, 83, 83, 83, 96, 
+#> 96, 45, 45, 45, 45, 114, 114, 125, 125, 125, 125, 125, 125, 125, 30, 106, 30, 30, 30, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 58, 125, 58, 45, 45, 134, 134, 134, 93, 93, 93, 93, 93, 4, 83, 93, 16, 16, 93, 94, 86, 125, 125, 131, 131, 45, 131, 45, 45, 106, 106, 106, 106, 106, 131, 38, 38, 38, 38, 38, 38, 38, 38, 38, 102, 38, 102, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 35, 35, 35, 35, 96, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 30, 5, 102, 114, 114, 114, 125, 
+#> 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 96, 96, 96, 96, 96, 96, 93, 93, 93, 93, 93, 96, 96, 96, 96, 96, 134, 96, 96, 114, 2, 114, 96, 94, 94, 116, 114, 16, 72, 35, 35, 35, 35, 35, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 131, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 117, 117, 117, 96, 134, 33, 30, 30, 30, 16, 16, 96, 96, 96, 96, 96, 96, 96, 96, 96, 96, 106, 96, 96, 96, 96, 96, 96, 16, 16, 16, 16, 30, 30, 30, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 79, 134, 134, 45, 72, 72, 72, 72, 
+#> 72, 72, 72, 72, 72, 72, 72, 125, 125, 125, 125, 125, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 116, 33, 33, 134, 125, 125, 125, 83, 83, 83, 83, 83, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 102, 102, 102, 51, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 72, 72, 72, 72, 72, 72, 72, 72, 93, 93, 93, 33, 33, 96, 93, 93, 134, 134, 134, 134, 134, 134, 134, 4, 86, 5, 5, 5, 5, 5, 5, 5, 5, 5, 30, 30, 30, 30, 30, 30, 125, 125, 35, 35, 35, 35, 35, 35, 35, 35, 38, 125, 106, 
+#> 106, 106, 106, 106, 106, 106, 106, 106, 106, 117, 117, 117, 117, 117, 30, 102, 72, 72, 35, 72, 35, 79, 79, 79, 79, 30, 30, 30, 30, 30, 83, 83, 83, 83, 83, 83, 83, 83, 83, 45, 83, 116, 116, 83, 116, 134, 134, 134, 134, 134, 134, 134, 134, 134, 134, 134, 134, 134, 134, 33, 134, 102, 102, 102, 102, 125, 125, 125, 66, 125, 66, 66, 4, 4, 4, 4, 4, 5, 106, 5, 86, 86, 86, 86, 86, 86, 86, 86, 86, 86, 86, 86, 86, 5, 5, 5, 5, 5, 5, 5, 5, 5, 16, 16, 16, 66, 66, 83, 79, 79, 79, 79, 93, 93, 93, 5, 93, 5, 5, 5, 
+#> 5, 5, 5, 5, 5, 5, 5, 45, 72, 72, 72, 83, 5, 33, 33, 33, 33, 33, 33, 114, 114, 125, 125, 125, 125, 125, 125, 45, 45, 45, 102, 102, 102, 102, 38, 102, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 106, 106, 106, 106, 106, 106, 106, 125, 125, 125, 16, 16, 16, 16, 45, 45, 45, 33, 58, 125, 125, 125, 125, 125, 125, 125, 125, 96, 125, 117, 117, 117, 117, 16, 125, 125, 125, 125, 38, 38, 38, 38, 38, 38, 58, 58, 58, 94, 94, 94, 5, 52, 106, 117, 117, 117, 117, 102, 102, 30, 102, 106, 93, 93, 33, 
+#> 33, 33, 33, 33, 93, 93, 45, 33, 5, 33, 33, 94, 94, 94, 94, 94, 94, 94, 94, 72, 72, 72, 117, 93, 93, 93, 93, 93, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 93, 93, 93, 93, 93, 130, 130, 134, 134, 134, 134, 134, 134, 134, 134, 134, 134, 52, 52, 106, 106, 106, 106, 106, 106, 30, 106, 30, 30, 30, 125, 125, 125, 114, 114, 114, 114, 114, 114, 5, 5, 117, 117, 117, 125, 125, 125, 125, 125, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 93, 30, 30, 58, 58, 58, 58, 58, 58, 58, 114, 102, 102, 102, 131, 
+#> 83, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 96, 96, 4, 4, 4, 4, 4, 106, 106, 106, 106, 106, 4, 125, 66, 102, 66, 86, 86, 86, 86, 86, 86, 86, 86, 86, 86, 86, 86, 33, 33, 33, 33, 33, 93, 93, 93, 96, 5, 86, 55, 35, 35, 35, 35, 35, 35, 35, 35, 16, 16, 16, 125, 125, 125, 93, 125, 5, 30, 30, 38, 86, 52, 52, 52, 52, 52, 52, 52, 52, 52, 72, 72, 72, 66, 106, 52, 52, 52, 35, 35, 35, 35, 35, 35, 35, 102, 52, 52, 52, 52, 52, 52, 102, 102, 102, 102, 35, 35, 35, 35, 102, 102, 58, 58, 58, 58, 58, 58, 125, 125, 125, 125, 
+#> 125, 96, 96, 58, 116, 116, 116, 116, 116, 116, 116, 116, 30, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 93, 93, 45, 45, 58, 93, 130, 114, 114, 114, 114, 114, 114, 114, 114, 114, 114, 114, 114, 114, 114, 114, 114, 114, 114, 114, 114, 72, 72, 72, 72, 72, 106, 106, 106, 106, 106, 106, 106, 106, 93, 93, 58, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 114, 114, 114, 52, 114, 52, 5, 5, 117, 66, 66, 66, 66, 66, 66, 66, 66, 94, 94, 94, 51, 94, 16, 16, 16, 16, 30, 30, 30, 30, 30, 30, 52, 52, 
+#> 131, 131, 52, 114, 86, 86, 86, 86, 86, 86, 86, 86, 86, 86, 86, 86, 86, 72, 72, 72, 30, 72, 94, 94, 86, 94, 86, 86, 86, 86, 86, 79, 79, 79, 16, 16, 4, 16, 38, 93, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 4, 5, 4, 130, 125, 125, 125, 125, 125, 125, 94, 94, 94, 66, 66, 116, 38, 52, 134, 134, 134, 134, 134, 134, 134, 134, 134, 35, 33, 33, 94, 94, 94, 94, 94, 86, 86, 86, 86, 86, 72, 94, 30, 66, 66, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 131, 96, 131, 96, 96, 5, 5, 5, 33, 5, 33, 5, 5, 45, 5, 
+#> 33, 33, 116, 116, 116, 116, 116, 102, 5, 5, 33, 125, 125, 125, 125, 125, 125, 125, 125, 125, 79, 125, 102, 94, 102, 94, 117, 16, 16, 16, 16, 16, 106, 125, 125, 125, 72, 125, 72, 125, 16, 16, 16, 16, 16, 16, 16, 16, 16, 114, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 134, 134, 93, 93, 93, 93, 93, 58, 58, 58, 93, 94, 94, 94, 94, 58, 58, 58, 58, 58, 58, 58, 58, 58, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 30, 30, 30, 66, 66, 66, 125, 125, 35, 125, 35, 16, 134, 134, 134, 134, 134, 134, 134, 134, 
+#> 93, 134, 93, 93, 93, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 134, 134, 134, 134, 134, 134, 134, 134, 114, 114, 94, 134, 38, 93, 45, 134, 134, 78, 134, 35, 35, 35, 35, 35, 35, 35, 4, 35, 4, 4, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 125, 125, 125, 125, 125, 125, 72, 72, 72, 72, 72, 96, 96, 96, 96, 96, 96, 96, 96, 131, 131, 131, 16, 16, 96, 134, 130, 93, 130, 33, 58, 58, 58, 58, 58, 58, 58, 5, 5, 5, 86, 86, 33, 33, 33, 116, 45, 45, 45, 45, 96, 52, 16, 16, 16, 16, 16, 16, 16, 16, 16, 
+#> 16, 16, 58, 125, 125, 83, 83, 83, 83, 83, 83, 83, 83, 83, 79, 79, 79, 79, 79, 79, 79, 79, 94, 94, 94, 16, 16, 16, 38, 134, 4, 4, 4, 4, 4, 102, 102, 102, 102, 117, 117, 79, 4, 4, 4, 116, 116, 116, 116, 116, 86, 116, 30, 30, 30, 30, 30, 30, 30, 2, 114, 45, 125, 125, 125, 125, 125, 125, 125, 4, 4, 4, 4, 55, 4, 55, 38, 66, 102, 125, 125, 106, 106, 106, 106, 106, 106, 33, 106, 33, 33, 38, 38, 38, 38, 38, 38, 38, 38, 72, 52, 72, 52, 38, 5, 5, 125, 125, 117, 83, 83, 83, 83, 83, 83, 83, 83, 83, 83, 83, 83, 
+#> 83, 83, 83, 134, 134, 134, 79, 79, 79, 72, 58, 58, 58, 58, 117, 117, 117, 117, 117, 117, 117, 83, 117, 116, 116, 96, 96, 96, 96, 96, 96, 96, 96, 96, 96, 96, 96, 125, 125, 125, 125, 125, 114, 114, 114, 114, 114, 114, 114, 55, 55, 38, 102, 134, 134, 35, 38, 117, 117, 117, 66, 106, 117, 52, 52, 52, 52, 52, 93, 93, 93, 93, 93, 5, 51, 102, 102, 102, 102, 102, 102, 94, 102, 72, 72, 66, 72, 38, 52, 52, 66, 134, 134, 134, 134, 134, 134, 134, 134, 134, 134, 134, 134, 93, 93, 93, 93, 5, 5, 4, 4, 4, 4, 4, 4, 
+#> 86, 86, 106, 106, 106, 106, 106, 16, 106, 45, 45, 45, 16, 16, 16, 16, 16, 16, 16, 35, 35, 35, 96, 96, 96, 96, 96, 96, 96, 96, 96, 125, 125, 16, 96, 96, 96, 96, 96, 96, 96, 96, 96, 96, 96, 79, 79, 79, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 45, 45, 45, 117, 94, 72, 116, 116, 116, 116, 116, 116, 116, 116, 116, 116, 5, 30, 30, 30, 30, 30, 30, 30, 134, 134, 134, 134, 134, 55, 55, 3, 72, 72, 78, 125, 125, 125, 125, 106, 106, 106, 106, 106, 106, 106, 106, 5, 102, 38, 38, 38, 38, 38, 38, 38, 38, 
+#> 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 58, 96, 96, 96, 96, 96, 96, 55, 51, 51, 51, 51, 4, 4, 4, 38, 38, 38, 38, 38, 38, 5, 33, 125, 38, 102, 45, 45, 45, 45, 45, 45, 131, 131, 131, 131, 131, 33, 45, 45, 83, 130, 4, 4, 4, 4, 4, 94, 4, 94, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 86, 86, 86, 86, 86, 86, 86, 125, 51, 51, 51, 51, 51, 4, 4, 117, 131, 86, 117, 2, 33, 106, 106, 106, 106, 106, 106, 94, 94, 94, 5, 94, 5, 55, 55, 72, 94, 4, 
+#> 125, 94, 94, 94, 83, 83, 72, 72, 38, 72, 93, 93, 93, 116, 116, 131, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 16, 134, 134, 134, 134, 134, 134, 134, 134, 134, 134, 134, 134, 4, 5, 72, 72, 72, 72, 131, 131, 102, 131, 96, 102, 96, 96, 96, 96, 96, 96, 134, 134, 96, 117, 117, 117, 117, 117, 117, 117, 117, 131, 131, 131, 131, 131, 5, 5, 125, 66, 66, 66, 66, 66, 38, 38, 38, 35, 35, 106, 102, 102, 125, 125, 114, 125, 114, 114, 114, 114, 94, 94, 94, 94, 94, 66, 66, 94, 66, 
+#> 66, 66, 66, 66, 33, 33, 30, 102, 102, 117, 117, 117, 117, 114, 117, 114, 114, 66, 66, 4, 66, 102, 114, 114, 83, 94, 94, 94, 94, 94, 94, 94, 94, 86, 94, 96, 96, 96, 96, 96, 114, 114, 114, 114, 114, 114, 117, 117, 117, 94, 94, 114, 117, 117, 117, 117, 117, 116, 38, 38, 16, 38, 45, 96, 38, 38, 131, 131, 131, 131, 131, 131, 131, 96, 131, 16, 16, 45, 131, 131, 5, 5, 5, 5, 5, 5, 4, 45, 66, 52, 58, 66, 79, 3, 3, 72, 72, 35, 35, 35, 35, 30, 38, 38, 4, 5, 130, 134, 134, 134, 134, 134, 114, 114, 4, 114, 4, 
+#> 4, 4, 4, 130, 130, 130, 35, 130, 35, 72, 130, 96, 96, 96, 96, 5, 5, 5, 52, 52, 52, 52, 131, 131, 131, 131, 131, 131, 131, 131, 131, 96, 131, 96, 96, 93, 96, 52, 93, 38, 134, 33, 131, 131, 116, 93, 131, 93, 93, 79, 52, 52, 52, 94, 94, 94, 94, 94, 94, 94, 94, 94, 51, 35, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 2, 2, 2, 45, 45, 45, 125, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 117, 35, 106, 45, 117, 94, 125, 125, 
+#> 117, 117, 35, 35, 58, 58, 58, 58, 106, 38, 38, 16, 38, 16, 16, 102, 131, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 96, 96, 96, 96, 96, 96, 96, 93, 106, 106, 106, 106, 106, 106, 58, 58, 58, 58, 33, 5, 134, 134, 134, 134, 134, 134, 134, 134, 134, 30, 114, 114, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 33, 33, 51, 33, 33, 131, 33, 72, 94, 16, 16, 16, 16, 16, 16, 33, 51, 51, 51, 51, 51, 117, 117, 117, 45, 45, 45, 16, 116, 116, 116, 116, 116, 116, 116, 116, 116, 116, 116, 38, 38, 38, 38, 38, 38, 38, 38, 
+#> 33, 38, 116, 116, 106, 106, 106, 106, 106, 106, 106, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 35, 35, 35, 35, 35, 35, 35, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 35, 35, 35, 72, 114, 72, 114, 72, 72, 72, 106, 106, 106, 106, 106, 106, 4, 4, 4, 58, 38, 38, 38, 38, 38, 38, 33, 83, 94, 94, 94, 94, 94, 38, 38, 114, 35, 35, 35, 5, 5, 114, 134, 33, 33, 33, 33, 33, 33, 33, 33, 102, 116, 4, 4, 4, 4, 4, 4, 4, 4, 45, 45, 45, 45, 93, 93, 96, 134, 134, 134, 134, 52, 52, 52, 52, 52, 
+#> 52, 52, 93, 93, 2, 45, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 45, 3, 3, 3, 3, 3, 3, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 93, 96, 96, 96, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 94, 94, 94, 94, 94, 4, 114, 114, 114, 134, 134, 134, 134, 134, 5, 5, 5, 45, 45, 45, 94, 33, 94, 3, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 94, 94, 94, 93, 72, 93, 72, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 83, 83, 83, 83, 83, 
+#> 83, 83, 83, 83, 83, 83, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 4, 4, 4, 4, 4, 4, 4, 16, 16, 38, 52, 30, 30, 30, 30, 30, 30, 55, 55, 55, 79, 79, 79, 79, 79, 79, 79, 93, 93, 93, 93, 66, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 96, 134, 96, 134, 35, 45, 45, 45, 45, 45, 45, 114, 134, 134, 134, 134, 134, 134, 134, 5, 117, 4, 4, 4, 4, 4, 4, 4, 38, 125, 125, 125, 102, 2, 102, 51, 96, 114, 96, 30, 30, 30, 
+#> 30, 93, 93, 30, 33, 30, 33, 78, 131, 131, 131, 131, 131, 131, 131, 131, 131, 131, 131, 131, 55, 52, 52, 52, 52, 52, 93, 58, 131, 137, 137, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 3, 3, 3, 106, 106, 106, 106, 106, 106, 66, 66, 30, 66, 86, 86, 86, 86, 86, 86, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 125, 125, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 16, 125, 83, 83, 83, 83, 83, 58, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 35, 96, 116, 116, 116, 116, 116, 116, 116, 
+#> 116, 116, 116, 116, 116, 116, 116, 116, 116, 116, 116, 131, 131, 131, 131, 131, 131, 131, 131, 131, 131, 131, 52, 45, 131, 131, 66, 45, 52, 52, 52, 52, 52, 52, 52, 52, 45, 45, 45, 45, 45, 83, 83, 83, 83, 114, 55, 114, 55, 55, 55, 55, 55, 72, 72, 72, 72, 4, 4, 93, 93, 93, 52, 52, 94, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 55, 102, 116, 116, 116, 116, 66, 116, 72, 72, 5, 5, 5, 5, 5, 5, 4, 33, 5, 131, 72, 33, 33, 33, 33, 33, 33, 33, 93, 45, 45, 2, 2, 83, 45, 45, 45, 45, 45, 
+#> 45, 58, 58, 102, 5, 35, 83, 83, 45, 78, 96, 96, 134, 134, 134, 134, 134, 134, 134, 58, 66, 30, 33, 125, 45, 45, 45, 134, 116, 116, 116, 79, 116, 116, 58, 45, 45, 45, 45, 45, 4, 45, 45, 45, 45, 33, 117, 35, 106, 93, 102, 72, 45, 131, 116, 116, 116, 116, 116, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 117, 117, 117, 117, 131, 33, 33, 134, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 117, 58, 117, 51, 51, 51, 86, 86, 86, 86, 86, 86, 4, 4, 45, 78, 78, 
+#> 78, 72, 72, 117, 117, 117, 45, 45, 45, 106, 106, 106, 106, 106, 106, 106, 106, 66, 3, 3, 3, 3, 3, 94, 134, 134, 134, 134, 134, 134, 134, 134, 94, 94, 94, 116, 116, 116, 116, 93, 116, 16, 5, 5, 5, 58, 102, 102, 102, 102, 102, 102, 102, 102, 3, 102, 3, 3, 3, 16, 16, 16, 16, 38, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 30, 30, 30, 30, 30, 2, 2, 2, 2, 2, 2, 2, 2, 71, 72, 72, 72, 72, 72, 72, 55, 72, 94, 94, 94, 94, 94, 94, 94, 94, 114, 96, 45, 45, 45, 45, 45, 45, 45, 94, 94, 94, 45, 114, 16, 3, 
+#> 3, 137, 131, 131, 131, 131, 131, 131, 93, 93, 93, 93, 16, 16, 93, 16, 134, 16, 16, 96, 45, 45, 45, 45, 45, 45, 45, 45, 33, 33, 5, 5, 94, 94, 94, 94, 94, 102, 102, 102, 102, 102, 102, 102, 102, 66, 94, 94, 94, 94, 94, 94, 134, 66, 66, 93, 134, 93, 93, 93, 93, 93, 16, 94, 96, 117, 117, 117, 117, 38, 117, 33, 33, 72, 16, 16, 16, 16, 35, 117, 117, 117, 117, 117, 117, 117, 35, 16, 35, 16, 16, 114, 114, 66, 66, 66, 66, 52, 78, 72, 72, 72, 72, 72, 72, 72, 134, 134, 93, 134, 3, 93, 2, 106, 4, 86, 106, 86, 
+#> 86, 86, 86, 86, 55, 58, 58, 58, 35, 35, 35, 117, 117, 94, 94, 79, 79, 79, 79, 58, 58, 58, 58, 58, 117, 38, 117, 38, 102, 102, 16, 86, 86, 86, 86, 16, 16, 33, 45, 45, 106, 45, 45, 86, 86, 55, 137, 66, 66, 55, 55, 55, 55, 55, 66, 5, 5, 5, 5, 5, 55, 55, 55, 5, 102, 38, 94, 86, 86, 116, 116, 116, 116, 116, 116, 116, 116, 116, 58, 116, 3, 3, 3, 3, 3, 3, 93, 93, 3, 3, 117, 93, 30, 30, 30, 30, 117, 117, 117, 117, 117, 117, 117, 117, 117, 16, 117, 58, 58, 58, 58, 58, 58, 58, 58, 114, 114, 114, 114, 58, 58, 
+#> 4, 131, 55, 55, 55, 55, 55, 72, 5, 5, 33, 55, 55, 51, 51, 130, 5, 5, 58, 58, 58, 58, 114, 114, 114, 114, 3, 3, 3, 3, 3, 3, 72, 71, 117, 51, 16, 16, 16, 16, 16, 16, 16, 16, 2, 2, 94, 94, 5, 5, 5, 5, 45, 45, 45, 45, 45, 45, 45, 117, 116, 116, 102, 102, 102, 106, 106, 51, 52, 102, 131, 131, 131, 134, 134, 134, 134, 134, 134, 134, 134, 131, 131, 125, 79, 79, 79, 79, 79, 134, 45, 5, 5, 72, 72, 72, 72, 94, 78, 52, 16, 72, 72, 72, 130, 66, 45, 45, 45, 45, 45, 45, 45, 45, 16, 16, 16, 16, 16, 16, 16, 16, 
+#> 72, 72, 33, 72, 130, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 94, 4, 4, 51, 51, 51, 51, 51, 51, 51, 130, 58, 130, 4, 4, 51, 137, 51, 114, 30, 30, 30, 83, 83, 51, 51, 51, 51, 51, 51, 51, 16, 38, 16, 33, 131, 33, 33, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 5, 131, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 102, 102, 102, 33, 33, 33, 33, 72, 79, 45, 79, 5, 102, 30, 30, 30, 30, 2, 2, 2, 125, 125, 125, 125, 125, 125, 125, 125, 35, 114, 38, 78, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 93, 93, 93, 
+#> 93, 93, 93, 93, 93, 94, 94, 94, 38, 38, 38, 38, 16, 58, 106, 16, 16, 38, 38, 38, 38, 38, 38, 38, 38, 114, 4, 3, 117, 106, 125, 125, 66, 66, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 4, 4, 4, 45, 45, 45, 45, 117, 117, 117, 72, 72, 72, 72, 72, 94, 72, 72, 134, 134, 134, 134, 134, 134, 134, 134, 134, 125, 5, 5, 5, 134, 93, 93, 116, 116, 116, 116, 116, 116, 116, 116, 116, 116, 116, 116, 116, 116, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 5, 5, 5, 16, 72, 72, 72, 86, 86, 86, 93, 93, 131, 
+#> 131, 131, 131, 117, 117, 117, 117, 117, 117, 38, 38, 38, 38, 125, 102, 102, 131, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 72, 72, 72, 72, 72, 51, 72, 51, 51, 131, 55, 35, 4, 35, 38, 45, 116, 116, 116, 116, 116, 116, 116, 131, 131, 131, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 72, 51, 51, 51, 51, 51, 72, 72, 72, 35, 35, 78, 78, 117, 131, 114, 114, 131, 93, 93, 93, 93, 93, 93, 93, 93, 93, 58, 58, 58, 93, 93, 93, 93, 93, 93, 93, 93, 93, 134, 134, 134, 134, 134, 
+#> 134, 134, 55, 55, 94, 94, 94, 94, 94, 94, 94, 55, 93, 55, 114, 114, 114, 114, 114, 114, 114, 114, 114, 114, 114, 114, 114, 114, 114, 114, 78, 78, 72, 72, 86, 86, 86, 86, 16, 16, 16, 16, 16, 16, 16, 94, 94, 94, 94, 102, 35, 35, 35, 131, 131, 131, 131, 131, 5, 5, 5, 5, 5, 131, 131, 131, 131, 131, 5, 5, 94, 94, 94, 94, 94, 94, 94, 130, 35, 55, 55, 55, 55, 117, 117, 117, 117, 86, 86, 137, 3, 137, 3, 51, 79, 94, 137, 137, 137, 4, 78, 45, 45, 45, 86, 86, 33, 86, 38, 38, 38, 72, 72, 72, 72, 16, 16, 16, 
+#> 16, 16, 16, 16, 16, 16, 35, 35, 72, 72, 72, 96, 102, 102, 102, 102, 102, 102, 102, 125, 125, 125, 125, 125, 125, 134, 38, 134, 38, 38, 38, 116, 116, 116, 116, 116, 116, 93, 93, 93, 93, 93, 93, 125, 125, 130, 93, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 35, 35, 79, 106, 106, 106, 106, 4, 106, 4, 4, 38, 38, 93, 51, 51, 51, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 134, 134, 134, 134, 134, 134, 52, 52, 38, 52, 5, 93, 93, 134, 134, 33, 93, 93, 114, 16, 16, 114, 72, 114, 96, 
+#> 96, 96, 96, 96, 96, 96, 93, 93, 93, 93, 116, 116, 38, 38, 38, 38, 38, 4, 114, 116, 116, 116, 116, 79, 116, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 72, 131, 33, 93, 93, 93, 93, 93, 93, 116, 114, 114, 114, 114, 93, 114, 93, 93, 125, 114, 66, 66, 66, 66, 66, 66, 66, 66, 16, 16, 16, 16, 35, 35, 58, 33, 93, 93, 102, 102, 102, 3, 96, 96, 96, 96, 130, 130, 130, 35, 78, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 45, 45, 93, 35, 35, 30, 30, 30, 30, 30, 52, 52, 52, 52, 52, 52, 52, 130, 55, 55, 3, 94, 94, 131, 
+#> 131, 131, 131, 131, 131, 131, 66, 131, 66, 52, 52, 52, 52, 52, 83, 83, 83, 83, 83, 83, 83, 83, 114, 114, 114, 38, 130, 130, 130, 51, 131, 131, 131, 131, 131, 131, 131, 131, 5, 55, 55, 114, 72, 72, 72, 72, 72, 93, 93, 93, 93, 93, 93, 93, 93, 33, 3, 94, 94, 134, 134, 134, 134, 134, 134, 134, 72, 72, 72, 72, 72, 3, 3, 94, 94, 38, 38, 38, 38, 38, 106, 106, 16, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 72, 45, 38, 38, 38, 38, 38, 38, 38, 38, 52, 106, 52, 16, 4, 4, 4, 4, 4, 4, 4, 
+#> 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 45, 78, 4, 4, 58, 58, 58, 58, 58, 58, 58, 58, 58, 102, 102, 94, 94, 94, 16, 94, 4, 66, 66, 66, 66, 66, 66, 58, 66, 94, 94, 94, 94, 94, 94, 94, 117, 125, 125, 93, 93, 38, 38, 38, 38, 16, 38, 16, 35, 35, 114, 5, 134, 134, 134, 134, 134, 134, 134, 134, 134, 134, 134, 134, 55, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 117, 117, 117, 71, 134, 86, 86, 86, 86, 86, 86, 86, 86, 2, 71, 71, 71, 71, 71, 131, 5, 116, 58, 58, 58, 58, 58, 58, 94, 51, 
+#> 51, 4, 4, 4, 4, 58, 3, 35, 35, 35, 131, 131, 125, 5, 5, 5, 16, 116, 116, 116, 116, 116, 116, 116, 116, 116, 116, 102, 116, 102, 102, 102, 102, 51, 52, 52, 52, 58, 58, 58, 58, 52, 58, 52, 66, 72, 66, 94, 86, 86, 86, 86, 86, 86, 16, 86, 16, 55, 131, 52, 52, 102, 134, 134, 134, 134, 134, 134, 134, 96, 125, 125, 125, 131, 3, 3, 3, 4, 66, 66, 66, 66, 66, 96, 96, 96, 96, 33, 33, 33, 33, 33, 30, 2, 2, 2, 2, 2, 2, 2, 2, 71, 71, 33, 58, 58, 131, 131, 131, 131, 131, 131, 131, 93, 93, 96, 94, 96, 131, 131, 
+#> 131, 79, 131, 131, 52, 52, 52, 83, 83, 83, 83, 78, 134, 125, 125, 125, 125, 125, 117, 117, 51, 51, 51, 51, 51, 51, 66, 66, 117, 35, 117, 35, 35, 52, 52, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 96, 96, 96, 96, 96, 96, 96, 93, 93, 93, 93, 93, 93, 93, 51, 96, 51, 51, 51, 45, 45, 94, 134, 94, 94, 94, 45, 94, 117, 117, 117, 117, 117, 117, 58, 58, 72, 72, 72, 72, 58, 58, 58, 58, 52, 52, 52, 52, 52, 79, 51, 16, 51, 38, 102, 55, 52, 52, 52, 55, 55, 55, 55, 55, 35, 35, 4, 55, 131, 
+#> 102, 116, 116, 116, 116, 4, 4, 4, 4, 4, 4, 72, 72, 72, 72, 72, 72, 125, 125, 76, 2, 2, 2, 2, 2, 2, 2, 3, 134, 134, 125, 125, 4, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 93, 33, 33, 33, 33, 33, 33, 33, 33, 52, 52, 52, 52, 52, 52, 52, 55, 55, 55, 125, 125, 125, 125, 125, 125, 16, 4, 4, 52, 117, 117, 38, 79, 79, 79, 79, 79, 79, 16, 79, 94, 66, 93, 106, 72, 96, 96, 96, 96, 96, 96, 96, 96, 96, 96, 96, 96, 96, 93, 93, 3, 3, 33, 33, 33, 33, 38, 116, 116, 116, 116, 94, 94, 114, 114, 
+#> 78, 78, 16, 16, 55, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 71, 71, 71, 71, 71, 52, 52, 79, 116, 116, 116, 116, 116, 116, 116, 116, 116, 116, 116, 93, 116, 93, 93, 76, 116, 94, 83, 83, 83, 78, 78, 125, 125, 125, 125, 52, 114, 114, 114, 52, 114, 58, 58, 52, 52, 58, 58, 58, 58, 58, 58, 58, 58, 72, 72, 86, 86, 86, 86, 86, 86, 86, 16, 86, 71, 71, 71, 33, 79, 96, 38, 45, 117, 51, 51, 55, 55, 55, 72, 3, 3, 3, 3, 78, 3, 3, 78, 78, 78, 78, 78, 5, 5, 5, 5, 5, 94, 94, 94, 94, 93, 94, 116, 55, 117, 117, 
+#> 55, 117, 134, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 71, 71, 71, 71, 58, 58, 58, 58, 58, 35, 58, 35, 58, 52, 3, 3, 3, 3, 3, 3, 3, 3, 72, 55, 117, 117, 117, 117, 117, 117, 117, 117, 117, 114, 116, 38, 38, 117, 117, 117, 96, 96, 96, 96, 96, 125, 125, 125, 125, 55, 131, 55, 55, 55, 55, 117, 117, 117, 117, 117, 125, 2, 2, 2, 2, 2, 71, 71, 125, 125, 96, 137, 116, 72, 72, 72, 72, 30, 30, 30, 114, 114, 94, 114, 94, 116, 96, 96, 96, 96, 96, 96, 96, 117, 117, 117, 117, 117, 117, 117, 96, 2, 
+#> 2, 2, 2, 2, 2, 2, 71, 134, 117, 117, 117, 117, 131, 45, 38, 45, 38, 38, 38, 38, 38, 38, 38, 38, 94, 45, 96, 96, 96, 96, 96, 96, 96, 5, 5, 5, 5, 58, 58, 5, 114, 117, 66, 134, 134, 134, 96, 33, 33, 55, 134, 134, 134, 134, 16, 134, 16, 130, 93, 106, 4, 4, 4, 3, 51, 51, 51, 51, 51, 51, 58, 131, 131, 93, 93, 93, 93, 93, 131, 131, 137, 35, 35, 35, 35, 35, 35, 35, 93, 93, 30, 30, 30, 2, 2, 2, 2, 2, 2, 2, 2, 71, 71, 71, 71, 4, 72, 16, 116, 16, 16, 16, 16, 16, 16, 16, 72, 72, 72, 72, 4, 4, 4, 45, 93, 131, 
+#> 55, 55, 55, 55, 55, 16, 16, 16, 16, 16, 16, 16, 72, 72, 72, 134, 134, 134, 134, 134, 134, 134, 134, 134, 134, 134, 134, 102, 102, 102, 102, 72, 72, 72, 72, 72, 72, 72, 72, 16, 131, 78, 114, 55, 55, 55, 55, 55, 55, 35, 35, 35, 35, 35, 35, 4, 35, 5, 106, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 79, 79, 94, 94, 94, 94, 116, 134, 134, 134, 134, 134, 134, 117, 130, 3, 16, 72, 72, 114, 58, 33, 117, 33, 33, 33, 33, 33, 96, 16, 16, 16, 96, 66, 66, 66, 66, 66, 66, 66, 72, 93, 94, 55, 55, 55, 55, 55, 52, 52, 
+#> 3, 52, 38, 117, 117, 117, 117, 117, 35, 35, 117, 16, 16, 16, 72, 134, 134, 134, 134, 134, 134, 134, 134, 134, 134, 134, 134, 71, 71, 93, 86, 86, 86, 86, 86, 86, 86, 86, 137, 137, 116, 116, 93, 55, 55, 55, 55, 55, 55, 55, 16, 16, 16, 16, 16, 4, 4, 4, 4, 4, 4, 114, 102, 102, 102, 102, 102, 102, 102, 102, 72, 58, 114, 72, 78, 78, 5, 78, 76, 52, 79, 79, 79, 79, 79, 79, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 79, 79, 79, 79, 79, 79, 79, 79, 94, 94, 94, 94, 134, 72, 72, 72, 72, 35, 72, 35, 
+#> 106, 125, 5, 5, 5, 78, 137, 38, 96, 96, 96, 96, 96, 96, 96, 3, 106, 106, 114, 106, 106, 106, 106, 16, 106, 16, 94, 94, 94, 116, 131, 131, 131, 131, 4, 131, 4, 71, 93, 93, 93, 93, 93, 93, 93, 94, 5, 94, 5, 5, 5, 5, 5, 5, 5, 5, 5, 51, 3, 45, 45, 45, 45, 45, 45, 45, 16, 45, 16, 52, 52, 52, 52, 83, 83, 83, 78, 78, 78, 78, 58, 78, 114, 114, 114, 16, 58, 58, 72, 72, 72, 72, 72, 72, 72, 72, 116, 116, 116, 116, 116, 16, 131, 131, 131, 131, 131, 102, 102, 4, 4, 4, 3, 78, 137, 58, 58, 102, 102, 102, 102, 102, 
+#> 102, 102, 102, 93, 102, 93, 93, 71, 71, 71, 71, 72, 94, 106, 106, 106, 106, 106, 106, 106, 106, 106, 116, 116, 4, 116, 4, 72, 38, 72, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 125, 125, 125, 125, 125, 125, 4, 72, 72, 16, 16, 16, 16, 16, 4, 4, 106, 106, 106, 106, 106, 106, 117, 117, 117, 117, 117, 117, 72, 72, 117, 117, 117, 117, 79, 79, 79, 79, 79, 79, 79, 131, 131, 52, 52, 45, 45, 45, 45, 45, 45, 86, 33, 2, 71, 71, 71, 16, 33, 93, 96, 96, 94, 94, 134, 134, 134, 134, 134, 134, 
+#> 125, 125, 125, 125, 125, 125, 125, 125, 125, 134, 134, 134, 134, 3, 3, 3, 72, 79, 114, 33, 114, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 102, 102, 131, 51, 86, 86, 137, 137, 137, 137, 116, 96, 96, 96, 96, 51, 51, 51, 114, 114, 71, 114, 71, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 58, 58, 58, 58, 58, 58, 58, 114, 93, 86, 86, 86, 86, 86, 86, 35, 35, 35, 35, 114, 114, 134, 55, 55, 55, 55, 55, 52, 52, 52, 52, 52, 52, 52, 52, 
+#> 33, 33, 33, 33, 33, 33, 78, 78, 131, 58, 58, 58, 58, 58, 58, 76, 4, 4, 4, 4, 125, 125, 125, 35, 35, 51, 137, 3, 137, 79, 114, 114, 38, 134, 134, 38, 38, 38, 38, 137, 137, 125, 137, 3, 78, 16, 125, 78, 130, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 93, 66, 66, 66, 66, 66, 66, 96, 16, 16, 16, 16, 93, 93, 93, 93, 52, 130, 45, 131, 131, 131, 131, 131, 131, 131, 131, 131, 131, 131, 131, 131, 72, 102, 72, 72, 72, 72, 72, 72, 55, 72, 55, 94, 94, 55, 137, 125, 125, 125, 125, 102, 125, 102, 102, 52, 102, 52, 
+#> 52, 52, 52, 102, 102, 102, 76, 2, 2, 2, 2, 125, 125, 125, 3, 134, 114, 114, 22, 22, 64, 5, 5, 5, 5, 5, 5, 5, 5, 52, 96, 4, 72, 3, 3, 3, 3, 3, 3, 3, 86, 86, 86, 72, 86, 72, 72, 72, 72, 35, 35, 125, 66, 66, 66, 45, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 106, 51, 51, 16, 16, 16, 3, 66, 66, 66, 66, 66, 16, 106, 125, 125, 125, 78, 78, 78, 78, 125, 114, 2, 2, 2, 71, 71, 71, 71, 94, 94, 78, 94, 78, 5, 78, 78, 78, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 16, 55, 55, 55, 55, 55, 55, 72, 76, 72, 72, 
+#> 16, 93, 93, 93, 93, 93, 93, 93, 93, 93, 116, 116, 33, 33, 33, 33, 33, 33, 33, 33, 33, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 72, 102, 4, 4, 4, 4, 4, 4, 4, 4, 4, 93, 93, 51, 51, 51, 51, 51, 96, 125, 125, 125, 125, 125, 125, 125, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 76, 94, 94, 94, 94, 94, 94, 94, 94, 94, 76, 134, 134, 51, 134, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 58, 
+#> 93, 125, 125, 131, 16, 16, 16, 16, 16, 16, 16, 102, 102, 102, 102, 137, 131, 52, 96, 52, 52, 52, 16, 130, 130, 130, 130, 35, 130, 58, 66, 131, 125, 125, 38, 38, 38, 38, 52, 52, 52, 52, 52, 137, 137, 45, 45, 45, 45, 45, 45, 45, 45, 78, 93, 93, 93, 93, 93, 93, 93, 114, 114, 114, 114, 114, 114, 114, 33, 114, 33, 33, 33, 16, 33, 16, 117, 117, 16, 16, 16, 16, 16, 16, 16, 16, 16, 33, 93, 45, 45, 45, 45, 45, 45, 45, 45, 16, 102, 102, 130, 72, 72, 72, 72, 72, 93, 93, 106, 106, 134, 4, 4, 4, 4, 4, 94, 94, 
+#> 131, 66, 66, 66, 117, 114, 102, 33, 33, 33, 33, 33, 102, 102, 117, 117, 117, 117, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 72, 78, 78, 78, 78, 78, 78, 78, 52, 52, 131, 131, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 66, 96, 116, 102, 116, 134, 134, 134, 134, 134, 134, 116, 134, 116, 5, 5, 125, 125, 102, 125, 16, 16, 16, 16, 16, 16, 116, 116, 116, 116, 116, 116, 94, 33, 3, 3, 3, 3, 3, 3, 3, 3, 3, 58, 58, 52, 52, 52, 52, 94, 16, 16, 16, 16, 16, 16, 16, 16, 16, 
+#> 16, 78, 78, 78, 78, 78, 78, 78, 78, 78, 3, 3, 38, 38, 38, 3, 114, 5, 4, 4, 93, 93, 35, 35, 35, 35, 35, 130, 55, 45, 45, 79, 79, 130, 130, 130, 35, 35, 35, 131, 78, 78, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 131, 45, 45, 45, 45, 45, 45, 45, 45, 102, 116, 131, 102, 102, 102, 102, 58, 58, 58, 58, 58, 58, 102, 102, 102, 102, 137, 117, 117, 117, 117, 117, 117, 117, 117, 117, 131, 131, 114, 114, 114, 114, 114, 16, 16, 72, 72, 72, 72, 45, 45, 45, 45, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 125, 
+#> 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 106, 106, 106, 106, 4, 106, 4, 4, 5, 106, 5, 137, 114, 102, 102, 102, 102, 102, 102, 102, 72, 102, 16, 16, 16, 71, 106, 106, 106, 106, 106, 35, 106, 35, 35, 35, 35, 35, 35, 35, 35, 78, 78, 78, 78, 106, 16, 16, 16, 16, 16, 16, 16, 16, 16, 96, 35, 130, 130, 130, 130, 130, 130, 130, 130, 35, 35, 35, 35, 35, 35, 35, 35, 131, 131, 96, 131, 33, 130, 130, 130, 130, 130, 130, 58, 130, 5, 5, 5, 52, 117, 117, 117, 38, 131, 131, 131, 131, 131, 71, 71, 131, 
+#> 3, 3, 33, 33, 33, 33, 114, 114, 114, 131, 45, 131, 45, 45, 125, 125, 125, 114, 125, 106, 114, 38, 38, 38, 130, 130, 130, 130, 130, 130, 130, 130, 130, 16, 16, 72, 72, 72, 134, 134, 134, 134, 134, 134, 3, 134, 3, 3, 3, 3, 35, 16, 66, 66, 66, 66, 66, 66, 66, 78, 71, 78, 72, 72, 72, 116, 116, 5, 5, 5, 5, 5, 5, 5, 5, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 76, 134, 134, 134, 137, 137, 137, 137, 137, 137, 137, 137, 137, 137, 137, 102, 102, 58, 58, 58, 4, 58, 4, 45, 45, 4, 45, 72, 72, 72, 72, 72, 
+#> 72, 72, 72, 72, 114, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 66, 66, 66, 66, 66, 33, 33, 134, 94, 94, 94, 114, 114, 114, 114, 114, 76, 3, 130, 96, 96, 96, 16, 16, 93, 55, 55, 55, 76, 76, 35, 35, 134, 134, 134, 134, 134, 134, 134, 134, 134, 78, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 116, 116, 116, 116, 116, 116, 38, 102, 125, 125, 125, 125, 125, 93, 93, 93, 93, 93, 93, 93, 71, 96, 130, 79, 79, 79, 79, 79, 79, 33, 79, 106, 106, 106, 96, 96, 96, 96, 96, 96, 4, 4, 4, 4, 4, 4, 4, 4, 4, 117, 
+#> 117, 116, 116, 116, 116, 116, 116, 116, 116, 116, 116, 116, 45, 45, 45, 45, 116, 116, 116, 116, 116, 116, 96, 51, 51, 51, 51, 51, 51, 51, 106, 106, 106, 16, 16, 16, 38, 38, 38, 38, 38, 38, 38, 38, 3, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 134, 5, 66, 106, 130, 106, 106, 106, 106, 134, 134, 134, 134, 134, 134, 134, 134, 38, 38, 38, 38, 38, 38, 38, 38, 38, 52, 72, 38, 55, 72, 55, 55, 55, 55, 117, 117, 16, 3, 3, 96, 106, 106, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 116, 
+#> 116, 116, 116, 116, 4, 4, 4, 130, 93, 93, 137, 137, 35, 131, 131, 131, 131, 131, 131, 52, 131, 117, 117, 117, 117, 117, 117, 117, 33, 33, 33, 33, 33, 33, 33, 33, 55, 55, 55, 55, 55, 4, 4, 4, 4, 117, 137, 78, 78, 78, 78, 78, 78, 78, 78, 131, 78, 131, 131, 131, 131, 131, 131, 131, 131, 5, 116, 125, 125, 125, 125, 125, 71, 71, 16, 16, 16, 16, 16, 16, 16, 93, 93, 72, 72, 72, 72, 72, 72, 72, 72, 5, 5, 5, 5, 5, 5, 5, 66, 66, 66, 66, 66, 66, 66, 66, 66, 5, 5, 5, 5, 5, 5, 5, 5, 5, 4, 71, 71, 71, 71, 71, 
+#> 71, 71, 71, 71, 71, 3, 3, 3, 3, 3, 3, 78, 5, 78, 66, 66, 66, 66, 66, 66, 66, 66, 96, 78, 78, 78, 78, 78, 125, 45, 106, 51, 130, 130, 130, 130, 130, 3, 4, 4, 4, 4, 4, 114, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 93, 93, 93, 93, 94, 94, 45, 45, 45, 45, 45, 45, 45, 45, 137, 130, 3, 3, 3, 3, 3, 3, 4, 4, 114, 33, 3, 33, 3, 3, 3, 3, 130, 130, 79, 79, 79, 52, 79, 52, 102, 130, 5, 5, 93, 93, 93, 93, 93, 4, 66, 117, 134, 134, 33, 117, 117, 117, 117, 117, 117, 117, 16, 131, 131, 131, 131, 131, 
+#> 116, 79, 94, 94, 94, 134, 134, 134, 52, 52, 52, 52, 52, 52, 52, 71, 71, 130, 130, 116, 35, 116, 130, 130, 130, 130, 130, 130, 52, 130, 52, 134, 16, 16, 16, 96, 96, 96, 96, 78, 78, 78, 78, 78, 79, 5, 5, 5, 5, 5, 4, 4, 4, 106, 106, 4, 16, 106, 3, 137, 137, 137, 137, 33, 35, 35, 35, 35, 35, 72, 72, 134, 114, 114, 114, 114, 114, 114, 114, 93, 114, 93, 106, 106, 106, 106, 106, 106, 106, 4, 4, 4, 4, 4, 125, 94, 94, 96, 96, 96, 96, 134, 134, 16, 16, 51, 117, 117, 117, 71, 71, 71, 71, 71, 137, 137, 137, 
+#> 137, 79, 79, 79, 79, 79, 79, 117, 33, 33, 33, 33, 33, 33, 33, 33, 131, 16, 125, 4, 55, 55, 55, 55, 55, 137, 137, 96, 79, 79, 66, 79, 66, 66, 38, 38, 38, 38, 38, 38, 38, 38, 137, 137, 137, 137, 137, 137, 137, 137, 137, 137, 137, 137, 137, 5, 5, 5, 131, 131, 16, 16, 16, 3, 3, 52, 52, 52, 52, 52, 137, 66, 66, 66, 66, 66, 5, 5, 5, 5, 66, 66, 66, 66, 66, 3, 3, 3, 3, 3, 51, 51, 51, 94, 79, 79, 78, 78, 78, 78, 78, 58, 78, 4, 4, 4, 4, 125, 125, 125, 130, 130, 114, 76, 76, 76, 131, 131, 131, 5, 131, 5, 5, 
+#> 5, 5, 125, 125, 125, 125, 125, 106, 106, 106, 106, 106, 106, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 79, 51, 51, 51, 94, 78, 66, 66, 66, 66, 66, 114, 35, 35, 35, 35, 131, 131, 114, 114, 114, 114, 114, 94, 94, 116, 66, 35, 78, 78, 78, 93, 106, 76, 76, 117, 45, 45, 45, 45, 45, 116, 116, 116, 116, 116, 58, 58, 58, 58, 35, 51, 51, 51, 51, 94, 94, 94, 76, 76, 76, 55, 55, 76, 76, 76, 76, 117, 117, 117, 117, 117, 117, 117, 33, 33, 94, 94, 58, 58, 58, 58, 58, 134, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 
+#> 106, 106, 106, 106, 106, 106, 106, 137, 137, 137, 78, 78, 78, 66, 66, 66, 66, 66, 94, 94, 94, 5, 5, 5, 5, 35, 35, 35, 130, 130, 130, 96, 96, 16, 96, 52, 94, 71, 71, 71, 71, 72, 72, 72, 72, 76, 3, 3, 3, 3, 106, 106, 106, 106, 117, 117, 117, 117, 117, 96, 96, 96, 96, 134, 94, 94, 94, 94, 94, 94, 94, 58, 35, 71, 71, 71, 71, 71, 71, 116, 79, 116, 66, 58, 58, 58, 52, 52, 16, 16, 16) x c(55, 72, 45, 61, 59, 65, 76, 3, 8, 37, 7, 11, 39, 59, 69, 64, 60, 62, 85, 85, 80, 84, 97, 114, 98, 121, 123, 133, 121, 69, 31, 54, 78, 81, 78, 70, 84, 91, 56, 81, 86, 6, 72, 83, 89, 87, 66, 66, 51, 24, 35, 45, 29, 23, 78, 52, 138, 124, 130, 134, 137, 129, 109, 12, 46, 53, 70, 62, 47, 64, 56, 51, 47, 30, 8, 11, 39, 22, 3, 21, 72, 55, 63, 55, 73, 45, 55, 16, 29, 37, 22, 33, 73, 62, 70, 56, 56, 53, 40, 41, 3, 71, 136, 138, 127, 147, 131, 125, 130, 131, 134, 152, 147, 55, 79, 18, 15, 1, 17, 55, 53, 
+#> 53, 52, 47, 53, 48, 47, 44, 41, 45, 45, 41, 43, 38, 40, 46, 36, 35, 21, 11, 7, 39, 127, 147, 77, 102, 131, 86, 1, 125, 140, 65, 152, 137, 157, 128, 159, 90, 117, 137, 121, 129, 113, 2, 10, 30, 30, 2, 34, 39, 46, 46, 43, 44, 43, 31, 10, 6, 42, 42, 45, 48, 44, 38, 41, 56, 37, 38, 45, 43, 40, 41, 27, 1, 12, 128, 151, 125, 106, 118, 130, 133, 131, 102, 39, 75, 58, 145, 142, 152, 74, 110, 10, 145, 136, 77, 44, 141, 151, 150, 21, 97, 2, 39, 84, 77, 80, 76, 83, 96, 98, 109, 7, 75, 84, 74, 27, 1, 22, 72, 
+#> 98, 76, 32, 108, 98, 118, 112, 137, 97, 45, 89, 41, 1, 1, 31, 101, 131, 140, 137, 150, 154, 145, 144, 152, 156, 154, 146, 149, 153, 157, 156, 100, 61, 2, 155, 154, 155, 148, 83, 152, 18, 29, 42, 57, 66, 32, 52, 63, 62, 17, 10, 5, 2, 4, 33, 34, 28, 35, 36, 42, 42, 33, 13, 39, 5, 5, 46, 48, 40, 46, 44, 28, 37, 30, 22, 26, 24, 6, 10, 1, 2, 41, 98, 150, 150, 156, 140, 146, 140, 122, 98, 156, 145, 152, 111, 124, 112, 128, 137, 145, 155, 121, 79, 134, 95, 4, 30, 45, 130, 154, 151, 126, 134, 133, 135, 139, 
+#> 156, 139, 147, 137, 116, 138, 125, 100, 55, 26, 9, 14, 8, 32, 130, 153, 148, 143, 157, 143, 147, 95, 124, 73, 6, 2, 86, 65, 51, 113, 109, 104, 124, 110, 140, 72, 88, 81, 48, 69, 101, 77, 15, 74, 114, 132, 123, 111, 107, 104, 126, 91, 75, 27, 81, 80, 66, 78, 121, 34, 126, 60, 42, 150, 37, 155, 56, 12, 77, 35, 75, 132, 131, 128, 149, 148, 106, 129, 113, 104, 72, 141, 118, 148, 151, 152, 123, 110, 9, 2, 1, 26, 31, 31, 36, 36, 46, 50, 46, 53, 16, 39, 9, 26, 36, 12, 37, 42, 38, 41, 48, 45, 41, 16, 19, 
+#> 9, 61, 151, 147, 135, 140, 136, 129, 132, 147, 142, 142, 151, 137, 150, 130, 145, 114, 150, 156, 123, 74, 27, 49, 88, 132, 117, 150, 112, 115, 134, 122, 147, 149, 143, 150, 156, 101, 102, 26, 124, 152, 99, 154, 151, 126, 127, 125, 46, 143, 136, 139, 83, 71, 24, 56, 1, 1, 41, 41, 32, 38, 52, 39, 52, 43, 41, 39, 41, 39, 33, 35, 34, 27, 46, 35, 24, 33, 39, 15, 10, 44, 33, 21, 5, 20, 123, 146, 97, 102, 140, 151, 154, 139, 132, 137, 151, 72, 55, 64, 30, 93, 6, 14, 102, 153, 153, 132, 153, 148, 152, 155, 
+#> 155, 156, 97, 140, 153, 139, 154, 145, 152, 118, 106, 95, 36, 9, 3, 37, 57, 94, 114, 72, 87, 87, 82, 46, 33, 11, 3, 2, 29, 131, 137, 89, 72, 29, 1, 7, 31, 143, 141, 141, 153, 141, 158, 150, 151, 142, 127, 134, 150, 132, 131, 150, 135, 117, 150, 141, 64, 33, 36, 45, 46, 41, 26, 43, 36, 35, 38, 40, 37, 41, 34, 42, 37, 20, 14, 36, 40, 45, 42, 55, 54, 55, 64, 58, 57, 65, 56, 33, 38, 43, 42, 39, 36, 35, 26, 40, 46, 53, 47, 50, 70, 55, 53, 50, 40, 38, 12, 11, 43, 6, 6, 24, 35, 44, 43, 24, 21, 29, 10, 119, 
+#> 72, 61, 66, 142, 20, 157, 142, 150, 144, 153, 157, 155, 145, 147, 128, 129, 141, 104, 23, 41, 10, 46, 81, 113, 143, 150, 143, 100, 95, 48, 102, 120, 33, 35, 4, 1, 4, 25, 34, 40, 28, 43, 40, 40, 16, 3, 34, 35, 25, 27, 26, 9, 33, 19, 53, 64, 56, 69, 75, 125, 124, 118, 136, 111, 129, 93, 88, 31, 2, 12, 1, 3, 106, 51, 98, 135, 127, 146, 131, 133, 149, 152, 151, 135, 108, 82, 28, 131, 153, 107, 30, 10, 2, 31, 38, 41, 38, 40, 41, 9, 36, 36, 4, 3, 7, 86, 64, 134, 120, 153, 136, 143, 36, 17, 28, 147, 109, 
+#> 5, 6, 44, 80, 40, 84, 60, 103, 48, 22, 2, 1, 32, 67, 78, 83, 110, 117, 87, 53, 17, 24, 24, 78, 37, 46, 52, 56, 2, 5, 29, 27, 32, 46, 2, 43, 31, 38, 44, 45, 20, 40, 36, 32, 27, 48, 28, 26, 28, 20, 1, 7, 18, 80, 98, 116, 120, 111, 79, 97, 77, 2, 9, 9, 24, 95, 155, 154, 140, 143, 143, 154, 121, 132, 138, 146, 156, 122, 72, 45, 115, 56, 1, 34, 32, 8, 12, 33, 10, 9, 148, 146, 148, 149, 149, 150, 100, 146, 126, 141, 94, 69, 1, 77, 88, 141, 121, 80, 122, 100, 94, 99, 54, 38, 78, 3, 34, 37, 44, 12, 17, 18, 
+#> 21, 30, 26, 5, 5, 20, 147, 154, 148, 122, 45, 83, 155, 146, 17, 139, 146, 94, 62, 108, 113, 113, 101, 133, 141, 103, 74, 69, 55, 53, 10, 46, 15, 90, 127, 133, 126, 120, 134, 110, 80, 47, 25, 50, 46, 47, 48, 49, 49, 47, 3, 30, 46, 31, 33, 39, 21, 32, 7, 23, 37, 34, 22, 9, 144, 149, 145, 139, 126, 150, 127, 125, 108, 140, 142, 136, 156, 125, 102, 69, 104, 147, 151, 143, 143, 132, 145, 150, 9, 113, 135, 75, 113, 137, 5, 14, 79, 148, 155, 122, 93, 147, 65, 150, 135, 106, 48, 50, 1, 29, 13, 45, 43, 42, 
+#> 39, 6, 27, 36, 37, 34, 8, 28, 39, 39, 38, 6, 26, 19, 38, 126, 153, 148, 149, 119, 140, 150, 117, 120, 148, 152, 142, 154, 146, 59, 47, 1, 3, 19, 113, 138, 143, 131, 155, 127, 148, 146, 127, 139, 154, 153, 137, 52, 38, 33, 61, 61, 84, 62, 47, 51, 125, 96, 114, 69, 35, 27, 119, 2, 82, 10, 17, 9, 111, 153, 124, 142, 80, 144, 110, 84, 6, 3, 5, 46, 65, 99, 143, 145, 127, 146, 139, 107, 40, 150, 121, 123, 16, 118, 104, 144, 153, 145, 124, 132, 109, 149, 141, 127, 88, 139, 27, 144, 154, 146, 148, 152, 155, 
+#> 154, 107, 120, 36, 41, 42, 43, 41, 33, 12, 79, 107, 116, 110, 118, 88, 113, 122, 134, 124, 84, 114, 73, 103, 97, 91, 94, 45, 30, 10, 12, 40, 33, 8, 17, 24, 37, 16, 39, 49, 7, 25, 15, 40, 124, 145, 127, 140, 134, 140, 78, 54, 94, 116, 31, 33, 137, 143, 150, 43, 94, 19, 4, 130, 147, 149, 150, 137, 140, 121, 83, 46, 26, 156, 140, 123, 138, 145, 146, 149, 109, 105, 137, 148, 148, 152, 98, 141, 150, 111, 88, 23, 129, 136, 135, 129, 140, 108, 131, 151, 128, 142, 123, 57, 125, 82, 16, 2, 5, 42, 36, 32, 
+#> 48, 37, 16, 29, 28, 36, 9, 18, 26, 143, 156, 149, 155, 142, 11, 131, 134, 153, 155, 141, 152, 75, 78, 9, 112, 146, 142, 145, 149, 143, 23, 25, 100, 112, 80, 119, 119, 121, 100, 76, 108, 97, 80, 61, 66, 55, 7, 1, 6, 29, 150, 154, 155, 155, 152, 119, 139, 154, 149, 156, 154, 93, 88, 24, 49, 14, 1, 51, 150, 135, 53, 113, 90, 36, 41, 39, 6, 48, 43, 48, 32, 24, 27, 117, 4, 139, 160, 149, 156, 126, 122, 145, 97, 115, 123, 145, 25, 12, 14, 11, 7, 100, 144, 132, 115, 39, 32, 50, 87, 108, 104, 120, 118, 107, 
+#> 55, 63, 153, 142, 127, 125, 92, 108, 42, 153, 156, 107, 79, 128, 127, 111, 149, 104, 10, 86, 122, 149, 153, 144, 147, 6, 58, 28, 49, 55, 151, 118, 138, 94, 109, 148, 146, 151, 136, 148, 107, 107, 131, 99, 66, 21, 1, 13, 38, 45, 16, 2, 30, 41, 12, 37, 5, 14, 81, 151, 135, 114, 132, 154, 138, 142, 151, 150, 150, 149, 118, 20, 154, 116, 5, 42, 67, 52, 95, 130, 142, 152, 110, 152, 153, 98, 152, 151, 154, 135, 145, 145, 133, 137, 125, 28, 64, 42, 106, 79, 69, 140, 96, 138, 155, 79, 77, 114, 118, 73, 52, 
+#> 91, 18, 139, 145, 115, 138, 149, 154, 154, 107, 143, 138, 134, 155, 140, 156, 42, 100, 19, 11, 46, 24, 10, 2, 20, 7, 29, 4, 44, 3, 128, 118, 118, 49, 78, 80, 64, 92, 23, 53, 87, 47, 10, 16, 3, 82, 141, 150, 142, 27, 1, 134, 22, 60, 42, 147, 151, 136, 148, 151, 118, 112, 140, 151, 121, 146, 152, 53, 135, 142, 3, 40, 27, 36, 35, 9, 20, 41, 45, 40, 44, 49, 38, 40, 37, 31, 141, 106, 154, 109, 156, 128, 115, 111, 11, 74, 6, 85, 120, 98, 105, 97, 125, 104, 103, 62, 45, 9, 74, 145, 69, 39, 136, 113, 133, 
+#> 149, 112, 49, 138, 121, 134, 144, 140, 46, 115, 101, 2, 129, 150, 154, 156, 140, 154, 155, 126, 66, 130, 140, 155, 153, 149, 133, 27, 86, 144, 108, 19, 6, 30, 40, 38, 44, 41, 38, 36, 44, 38, 41, 39, 38, 32, 8, 8, 9, 69, 80, 87, 121, 130, 129, 114, 125, 149, 106, 133, 113, 106, 35, 74, 10, 81, 155, 130, 147, 148, 142, 149, 151, 151, 126, 128, 139, 108, 152, 145, 130, 127, 2, 30, 26, 15, 12, 7, 42, 43, 44, 41, 35, 38, 40, 17, 131, 115, 80, 140, 152, 66, 76, 102, 147, 153, 154, 154, 135, 126, 139, 131, 
+#> 98, 132, 45, 6, 42, 41, 26, 43, 37, 36, 40, 40, 34, 31, 39, 48, 33, 11, 23, 29, 30, 17, 4, 10, 8, 4, 15, 70, 1, 95, 157, 142, 145, 148, 122, 122, 139, 149, 147, 154, 155, 126, 57, 68, 7, 115, 69, 132, 150, 123, 135, 155, 149, 151, 151, 142, 146, 3, 6, 13, 70, 153, 113, 120, 107, 133, 154, 144, 153, 96, 43, 3, 1, 1, 9, 33, 53, 9, 46, 45, 42, 37, 31, 12, 37, 32, 31, 18, 4, 58, 155, 7, 141, 153, 143, 154, 148, 154, 152, 152, 142, 148, 150, 147, 120, 106, 73, 97, 5, 51, 49, 47, 37, 49, 41, 25, 21, 5, 
+#> 45, 46, 38, 43, 41, 43, 35, 33, 37, 32, 36, 5, 12, 12, 26, 14, 30, 38, 47, 48, 43, 40, 41, 41, 31, 1, 144, 100, 123, 157, 126, 138, 154, 154, 154, 152, 153, 22, 33, 40, 4, 64, 72, 105, 85, 94, 114, 40, 97, 58, 37, 7, 121, 130, 153, 141, 149, 152, 133, 130, 95, 40, 50, 35, 41, 11, 25, 40, 43, 43, 33, 21, 34, 27, 18, 27, 31, 29, 44, 42, 36, 38, 48, 35, 38, 22, 13, 45, 51, 35, 23, 38, 12, 39, 14, 14, 37, 54, 110, 153, 132, 151, 145, 120, 135, 153, 141, 138, 133, 131, 115, 147, 140, 103, 93, 17, 17, 
+#> 49, 11, 8, 32, 155, 149, 151, 145, 144, 147, 136, 61, 116, 147, 39, 51, 64, 43, 133, 92, 125, 137, 147, 150, 123, 89, 66, 42, 12, 23, 38, 35, 23, 13, 40, 42, 37, 34, 33, 33, 7, 2, 8, 21, 31, 32, 43, 121, 104, 123, 119, 84, 60, 146, 148, 102, 123, 112, 94, 60, 8, 1, 39, 38, 25, 41, 37, 36, 5, 45, 50, 39, 38, 60, 57, 28, 17, 3, 7, 15, 34, 46, 51, 56, 45, 52, 37, 30, 43, 32, 35, 29, 17, 23, 35, 24, 29, 38, 39, 23, 43, 40, 40, 42, 35, 39, 37, 34, 43, 35, 32, 22, 25, 16, 31, 19, 2, 42, 45, 49, 67, 49, 
+#> 34, 55, 13, 47, 35, 12, 136, 151, 155, 91, 138, 153, 153, 152, 144, 153, 62, 155, 122, 95, 7, 6, 68, 101, 148, 141, 148, 143, 128, 65, 63, 59, 19, 38, 20, 16, 1, 69, 136, 150, 79, 140, 145, 149, 118, 144, 153, 150, 141, 141, 151, 125, 142, 15, 26, 27, 48, 56, 58, 59, 55, 50, 43, 55, 40, 59, 53, 38, 1, 8, 12, 10, 24, 18, 5, 35, 33, 38, 30, 45, 43, 46, 34, 14, 21, 30, 23, 11, 3, 22, 154, 153, 153, 153, 155, 154, 153, 155, 152, 109, 130, 125, 135, 12, 50, 14, 148, 151, 154, 152, 151, 141, 147, 147, 
+#> 147, 120, 114, 146, 149, 107, 75, 2, 39, 2, 1, 3, 52, 49, 94, 96, 128, 131, 71, 17, 94, 147, 61, 75, 16, 91, 94, 85, 50, 55, 22, 44, 14, 2, 3, 13, 31, 37, 42, 39, 43, 33, 37, 34, 29, 33, 32, 31, 19, 38, 35, 26, 2, 2, 21, 45, 42, 41, 44, 26, 21, 39, 16, 8, 1, 2, 36, 37, 35, 31, 24, 34, 38, 31, 35, 30, 27, 28, 6, 19, 20, 12, 103, 102, 130, 135, 126, 153, 148, 113, 140, 112, 134, 137, 153, 143, 126, 35, 82, 35, 42, 10, 1, 43, 119, 121, 135, 124, 121, 66, 81, 17, 64, 85, 20, 110, 26, 108, 140, 145, 152, 
+#> 143, 138, 143, 127, 112, 102, 103, 28, 16, 45, 2, 51, 44, 38, 42, 36, 24, 29, 32, 17, 14, 28, 5, 11, 11, 24, 32, 38, 32, 32, 35, 40, 47, 40, 34, 28, 27, 25, 25, 22, 23, 30, 3, 96, 151, 112, 111, 127, 150, 149, 116, 145, 52, 53, 137, 128, 126, 17, 7, 142, 153, 142, 150, 152, 149, 144, 130, 130, 155, 135, 154, 119, 57, 5, 31, 85, 111, 117, 93, 127, 120, 25, 141, 116, 121, 140, 130, 116, 121, 110, 88, 97, 37, 64, 19, 109, 117, 145, 139, 146, 146, 64, 134, 152, 149, 140, 99, 100, 90, 42, 58, 18, 10, 
+#> 6, 3, 79, 82, 113, 116, 136, 149, 127, 117, 131, 108, 69, 66, 33, 14, 51, 36, 22, 134, 120, 126, 131, 135, 130, 122, 139, 130, 129, 115, 44, 27, 152, 153, 147, 106, 119, 143, 138, 128, 154, 146, 138, 128, 143, 103, 125, 93, 9, 37, 9, 40, 4, 14, 101, 150, 154, 150, 147, 148, 135, 145, 101, 47, 151, 150, 132, 151, 147, 147, 79, 38, 9, 41, 43, 41, 41, 49, 40, 57, 42, 49, 51, 50, 29, 26, 23, 24, 21, 22, 22, 20, 5, 1, 1, 11, 117, 153, 157, 85, 133, 139, 156, 154, 110, 70, 142, 45, 62, 144, 117, 82, 153, 
+#> 153, 119, 143, 108, 24, 135, 77, 127, 71, 9, 37, 134, 137, 153, 154, 152, 149, 146, 131, 108, 91, 145, 142, 107, 140, 65, 21, 91, 89, 90, 72, 24, 33, 39, 109, 105, 66, 32, 24, 57, 8, 21, 33, 42, 36, 43, 47, 33, 23, 32, 8, 18, 2, 4, 4, 137, 105, 135, 119, 130, 126, 44, 22, 84, 147, 146, 129, 127, 151, 140, 82, 4, 9, 29, 149, 147, 152, 143, 148, 155, 147, 112, 18, 114, 148, 133, 121, 6, 109, 120, 99, 136, 151, 154, 142, 49, 88, 146, 149, 153, 137, 119, 82, 132, 17, 15, 10, 10, 100, 132, 153, 118, 153, 
+#> 148, 13, 133, 12, 45, 45, 51, 39, 42, 50, 41, 44, 45, 22, 35, 35, 32, 24, 25, 23, 21, 42, 40, 37, 35, 34, 34, 39, 30, 11, 7, 3, 107, 62, 142, 146, 145, 150, 155, 112, 135, 117, 67, 7, 34, 3, 22, 39, 31, 39, 4, 39, 38, 38, 27, 12, 20, 31, 8, 4, 28, 38, 42, 40, 36, 9, 10, 13, 10, 126, 155, 155, 154, 154, 154, 155, 156, 152, 154, 149, 155, 157, 157, 8, 155, 153, 116, 147, 143, 135, 142, 139, 123, 130, 150, 126, 54, 14, 13, 1, 13, 22, 43, 37, 37, 46, 46, 40, 36, 42, 30, 26, 8, 16, 16, 8, 18, 36, 48, 
+#> 39, 22, 27, 11, 6, 44, 40, 36, 37, 34, 43, 12, 18, 35, 33, 4, 1, 36, 9, 17, 27, 42, 48, 40, 43, 37, 39, 39, 35, 34, 38, 33, 43, 44, 35, 36, 19, 1, 48, 39, 30, 37, 35, 29, 33, 38, 33, 28, 29, 19, 20, 33, 37, 30, 25, 16, 144, 155, 152, 151, 145, 150, 154, 154, 146, 139, 148, 154, 148, 125, 89, 11, 95, 114, 82, 83, 9, 1, 3, 77, 133, 98, 150, 149, 150, 154, 153, 154, 123, 153, 145, 79, 85, 95, 108, 90, 128, 21, 120, 120, 107, 115, 92, 113, 91, 93, 85, 39, 3, 4, 16, 150, 152, 151, 68, 154, 134, 121, 140, 
+#> 122, 106, 129, 147, 112, 72, 19, 55, 3, 101, 15, 19, 23, 19, 21, 15, 41, 40, 13, 27, 44, 51, 52, 9, 29, 33, 9, 5, 47, 33, 18, 37, 35, 30, 32, 45, 11, 31, 42, 41, 35, 8, 38, 35, 34, 16, 29, 24, 93, 78, 103, 138, 134, 120, 122, 83, 144, 140, 15, 89, 35, 40, 49, 39, 48, 45, 49, 33, 36, 39, 38, 33, 21, 13, 27, 1, 3, 52, 104, 140, 138, 153, 130, 148, 78, 144, 138, 97, 90, 26, 82, 81, 65, 20, 126, 112, 75, 148, 40, 121, 26, 18, 23, 5, 8, 123, 133, 154, 155, 154, 101, 152, 155, 154, 150, 154, 144, 152, 
+#> 118, 139, 127, 45, 59, 17, 142, 155, 145, 124, 110, 122, 124, 121, 85, 119, 125, 101, 153, 151, 127, 117, 127, 30, 26, 2, 24, 150, 145, 152, 149, 142, 137, 138, 144, 122, 63, 89, 26, 44, 49, 43, 36, 21, 33, 25, 3, 19, 20, 34, 32, 38, 37, 35, 43, 27, 43, 52, 38, 1, 2, 47, 53, 48, 55, 61, 34, 75, 61, 18, 53, 5, 26, 3, 2, 4, 7, 150, 147, 154, 150, 135, 14, 129, 8, 56, 84, 109, 150, 51, 13, 33, 1, 42, 40, 45, 36, 37, 31, 34, 29, 35, 28, 3, 33, 6, 66, 80, 39, 76, 80, 97, 76, 75, 68, 47, 69, 59, 33, 20, 
+#> 39, 37, 36, 40, 45, 49, 42, 42, 39, 24, 29, 31, 26, 24, 12, 19, 13, 8, 36, 114, 154, 140, 134, 148, 43, 78, 83, 10, 26, 61, 118, 149, 153, 139, 154, 149, 150, 147, 155, 150, 149, 124, 144, 135, 30, 70, 15, 89, 151, 139, 155, 153, 151, 154, 140, 152, 156, 134, 24, 87, 64, 8, 38, 12, 63, 145, 154, 156, 143, 152, 127, 144, 81, 148, 143, 143, 149, 143, 45, 59, 76, 3, 6, 19, 20, 35, 37, 28, 37, 32, 40, 23, 9, 21, 21, 99, 107, 51, 141, 149, 151, 154, 132, 144, 106, 19, 98, 26, 2, 26, 6, 53, 40, 47, 38, 
+#> 40, 38, 45, 41, 41, 30, 44, 24, 32, 39, 29, 41, 34, 35, 47, 48, 31, 43, 33, 24, 35, 39, 33, 3, 47, 45, 51, 43, 41, 38, 37, 29, 29, 32, 42, 35, 10, 37, 42, 40, 37, 41, 35, 35, 36, 38, 18, 28, 13, 6, 27, 27, 20, 13, 1, 9, 64, 149, 156, 148, 154, 152, 115, 119, 29, 117, 115, 129, 25, 85, 116, 50, 14, 12, 4, 15, 40, 37, 35, 38, 34, 31, 34, 32, 26, 9, 23, 13, 1, 1, 20, 35, 39, 52, 44, 40, 36, 31, 34, 33, 37, 15, 12, 21, 9, 25, 154, 153, 113, 154, 153, 138, 152, 156, 135, 133, 11, 155, 153, 47, 75, 15, 
+#> 12, 27, 40, 42, 44, 34, 40, 11, 16, 17, 5, 34, 33, 2, 1, 47, 51, 51, 53, 51, 27, 13, 19, 10, 1, 1, 1, 72, 143, 129, 135, 154, 152, 146, 137, 145, 128, 127, 105, 139, 5, 104, 90, 99, 5, 10, 130, 109, 130, 108, 130, 104, 120, 112, 140, 132, 128, 106, 109, 82, 85, 54, 14, 152, 144, 133, 146, 153, 139, 132, 131, 147, 143, 138, 148, 64, 18, 38, 125, 142, 120, 132, 146, 133, 122, 138, 152, 122, 44, 92, 115, 57, 26, 49, 8, 37, 36, 36, 41, 31, 38, 34, 34, 33, 40, 35, 34, 28, 33, 26, 24, 8, 35, 34, 33, 36, 
+#> 36, 39, 34, 25, 29, 29, 25, 23, 25, 4, 9, 151, 156, 145, 137, 150, 150, 138, 30, 59, 99, 16, 97, 2, 20, 3, 128, 111, 126, 126, 140, 128, 128, 105, 71, 131, 36, 59, 114, 103, 118, 115, 91, 56, 61, 26, 148, 149, 154, 155, 156, 146, 150, 106, 37, 133, 142, 48, 78, 128, 66, 26, 41, 75, 20, 5, 22, 7, 27, 34, 40, 37, 49, 29, 41, 35, 13, 1, 129, 152, 149, 137, 156, 126, 148, 152, 156, 106, 128, 149, 64, 65, 4, 108, 3, 152, 124, 145, 128, 134, 147, 143, 109, 98, 21, 51, 45, 45, 10, 4, 31, 27, 32, 14, 2, 
+#> 82, 30, 43, 31, 23, 23, 11, 36, 40, 39, 44, 44, 42, 36, 38, 39, 29, 31, 15, 29, 19, 30, 11, 13, 15, 80, 146, 132, 155, 121, 46, 6, 45, 89, 87, 35, 82, 124, 150, 148, 138, 154, 152, 153, 152, 150, 151, 150, 125, 151, 148, 152, 125, 120, 135, 31, 4, 3, 4, 86, 132, 139, 155, 152, 142, 125, 138, 138, 121, 8, 30, 39, 44, 38, 46, 45, 36, 30, 35, 38, 37, 24, 1, 117, 153, 152, 12, 154, 155, 138, 148, 19, 78, 142, 125, 2, 30, 65, 92, 152, 153, 149, 154, 133, 148, 137, 150, 154, 151, 140, 143, 141, 68, 73, 
+#> 4, 9, 149, 153, 119, 104, 152, 138, 144, 146, 145, 116, 25, 14, 128, 128, 131, 73, 148, 155, 141, 93, 73, 77, 127, 121, 66, 39, 6, 123, 85, 145, 110, 135, 143, 98, 91, 88, 86, 40, 105, 138, 154, 134, 154, 107, 141, 58, 20, 138, 151, 145, 120, 132, 139, 154, 132, 141, 153, 76, 139, 116, 3, 31, 36, 32, 37, 4, 34, 35, 6, 18, 33, 38, 15, 14, 24, 13, 33, 25, 13, 23, 37, 24, 30, 34, 32, 11, 20, 27, 17, 15, 24, 85, 146, 154, 142, 115, 142, 116, 146, 150, 136, 140, 48, 56, 90, 78, 110, 88, 70, 6, 96, 139, 
+#> 151, 118, 153, 138, 154, 81, 148, 150, 154, 142, 155, 18, 149, 139, 139, 142, 50, 72, 20, 111, 124, 149, 154, 152, 156, 149, 151, 140, 144, 98, 150, 92, 76, 151, 87, 154, 154, 151, 153, 156, 151, 145, 60, 63, 10, 30, 42, 39, 47, 47, 49, 42, 43, 42, 43, 36, 40, 6, 26, 38, 3, 37, 35, 32, 36, 35, 12, 17, 25, 22, 28, 7, 37, 32, 29, 33, 35, 5, 10, 7, 17, 4, 7, 41, 37, 27, 2, 37, 30, 151, 154, 149, 130, 154, 100, 31, 146, 126, 10, 114, 138, 102, 34, 36, 33, 27, 2, 7, 5, 126, 145, 149, 153, 155, 126, 142, 
+#> 101, 154, 152, 106, 13, 90, 113, 78, 81, 23, 134, 107, 154, 154, 129, 150, 121, 48, 16, 64, 39, 16, 39, 35, 25, 25, 23, 3, 5, 18, 35, 30, 1, 89, 149, 135, 154, 151, 152, 139, 136, 69, 8, 37, 37, 29, 60, 60, 6, 52, 48, 55, 55, 45, 50, 53, 54, 45, 44, 33, 38, 30, 21, 8, 14, 50, 88, 104, 66, 10, 60, 49, 32, 123, 144, 116, 100, 66, 107, 119, 98, 36, 31, 62, 81, 49, 2, 12, 20, 126, 121, 100, 151, 147, 118, 60, 102, 86, 48, 141, 115, 36, 3, 2, 1, 50, 7, 28, 44, 31, 13, 46, 35, 6, 36, 43, 6, 30, 22, 10, 
+#> 6, 37, 36, 10, 24, 17, 14, 11, 14, 10, 17, 21, 33, 30, 12, 35, 37, 40, 33, 31, 41, 33, 35, 1, 12, 24, 151, 156, 155, 154, 145, 126, 153, 152, 135, 81, 15, 75, 73, 118, 107, 132, 120, 121, 120, 129, 130, 109, 117, 105, 104, 117, 115, 88, 48, 3, 53, 65, 32, 93, 120, 135, 140, 130, 119, 40, 39, 43, 42, 44, 37, 37, 28, 32, 13, 13, 31, 16, 13, 25, 14, 148, 136, 147, 145, 124, 136, 42, 87, 80, 62, 127, 151, 155, 156, 147, 152, 112, 155, 144, 148, 119, 142, 141, 147, 153, 138, 152, 150, 138, 149, 149, 117, 
+#> 144, 143, 14, 26, 39, 39, 43, 44, 9, 48, 42, 44, 36, 35, 33, 30, 25, 19, 25, 19, 10, 44, 43, 16, 33, 34, 35, 34, 6, 31, 32, 31, 26, 32, 34, 33, 35, 41, 45, 45, 149, 144, 143, 150, 150, 156, 137, 155, 89, 148, 6, 37, 117, 98, 136, 132, 129, 103, 113, 9, 22, 52, 23, 83, 49, 64, 56, 36, 15, 40, 37, 39, 40, 37, 37, 24, 24, 20, 7, 1, 51, 46, 24, 11, 28, 40, 63, 22, 14, 31, 32, 31, 31, 24, 1, 34, 125, 131, 148, 78, 124, 125, 150, 146, 141, 144, 111, 24, 24, 29, 1, 87, 78, 60, 149, 137, 153, 118, 132, 88, 
+#> 41, 6, 63, 154, 101, 51, 98, 112, 117, 53, 58, 147, 137, 152, 155, 149, 151, 150, 154, 143, 105, 8, 12, 119, 3, 92, 144, 60, 99, 124, 136, 126, 21, 56, 88, 155, 119, 32, 53, 51, 5, 111, 138, 140, 152, 141, 44, 150, 45, 83, 60, 50, 54, 2, 11, 58, 135, 147, 152, 154, 156, 151, 105, 148, 143, 98, 41, 85, 55, 38, 5, 36, 77, 151, 154, 142, 154, 155, 115, 91, 151, 130, 85, 64, 19, 149, 120, 126, 139, 137, 116, 124, 75, 3, 24, 32, 43, 30, 34, 33, 28, 35, 11, 19, 15, 29, 7, 21, 11, 36, 24, 27, 18, 109, 138, 
+#> 138, 135, 146, 130, 136, 152, 15, 137, 74, 16, 32, 102, 156, 151, 131, 146, 157, 142, 149, 150, 95, 63, 138, 108, 147, 107, 132, 145, 34, 79, 4, 22, 4, 43, 26, 10, 23, 30, 3, 29, 16, 37, 40, 31, 27, 11, 10, 9, 33, 27, 21, 14, 1, 16, 1, 15, 33, 29, 36, 4, 12, 16, 29, 16, 7, 15, 3, 146, 93, 58, 137, 125, 122, 110, 64, 84, 53, 74, 34, 1, 2, 9, 34, 41, 48, 38, 35, 42, 4, 46, 56, 37, 7, 18, 112, 149, 140, 113, 152, 156, 147, 146, 151, 148, 123, 140, 143, 69, 108, 10, 91, 24, 96, 77, 11, 74, 88, 115, 143, 
+#> 100, 146, 118, 129, 137, 138, 63, 134, 127, 136, 85, 61, 82, 14, 156, 137, 115, 147, 124, 118, 132, 1, 149, 154, 149, 149, 152, 110, 149, 116, 151, 153, 80, 13, 12, 38, 35, 28, 39, 29, 15, 29, 12, 23, 28, 28, 26, 23, 18, 33, 22, 18, 45, 21, 44, 35, 39, 41, 14, 25, 21, 37, 2, 30, 38, 3, 36, 35, 33, 7, 1, 12, 23, 11, 27, 28, 24, 30, 1, 4, 34, 17, 51, 86, 149, 149, 153, 152, 147, 114, 7, 104, 3, 145, 137, 145, 149, 115, 150, 155, 155, 149, 109, 92, 44, 46, 101, 3, 22, 4, 47, 38, 29, 37, 37, 34, 20, 
+#> 4, 28, 10, 8, 1, 37, 42, 29, 32, 12, 1, 43, 19, 9, 3, 1, 125, 155, 147, 129, 144, 123, 146, 149, 144, 134, 106, 67, 3, 80, 122, 131, 117, 128, 133, 106, 130, 24, 62, 86, 58, 32, 147, 153, 155, 143, 148, 127, 131, 25, 69, 103, 20, 49, 3, 104, 135, 102, 155, 155, 153, 155, 151, 155, 154, 48, 102, 31, 155, 85, 132, 127, 113, 108, 15, 124, 94, 11, 35, 33, 40, 36, 45, 51, 42, 40, 34, 32, 33, 34, 42, 26, 10, 2, 30, 40, 43, 33, 37, 5, 31, 30, 30, 30, 28, 22, 7, 155, 78, 111, 112, 110, 59, 3, 3, 12, 140, 
+#> 157, 146, 156, 149, 155, 157, 146, 152, 154, 157, 153, 154, 156, 134, 135, 115, 116, 123, 135, 124, 5, 17, 52, 47, 42, 41, 41, 44, 35, 26, 24, 21, 28, 6, 68, 125, 122, 112, 4, 87, 140, 91, 82, 42, 102, 15, 109, 102, 53, 57, 14, 54, 40, 48, 132, 150, 8, 2, 110, 151, 143, 157, 109, 127, 15, 6, 83, 154, 152, 129, 148, 141, 70, 7, 93, 50, 1, 1, 28, 33, 39, 37, 47, 40, 37, 40, 39, 38, 35, 17, 26, 7, 26, 2, 32, 148, 141, 143, 156, 143, 144, 140, 150, 151, 139, 142, 136, 98, 67, 48, 95, 144, 154, 143, 80, 
+#> 5, 9, 146, 155, 138, 1, 155, 56, 55, 98, 4, 45, 2, 4, 44, 41, 36, 22, 11, 37, 30, 19, 55, 145, 127, 151, 132, 144, 155, 125, 151, 146, 140, 139, 149, 106, 2, 98, 17, 8, 26, 6, 154, 127, 61, 43, 143, 148, 118, 138, 147, 154, 150, 148, 129, 88, 22, 43, 151, 139, 154, 154, 152, 108, 14, 125, 154, 154, 134, 140, 102, 150, 152, 147, 81, 34, 88, 40, 13, 34, 38, 118, 3, 51, 42, 7, 85, 100, 95, 83, 57, 61, 45, 52, 31, 4, 1, 9, 14, 3, 44, 37, 37, 30, 38, 27, 31, 27, 30, 5, 19, 36, 28, 40, 15, 2, 32, 41, 33, 
+#> 33, 21, 7, 13, 25, 75, 22, 86, 149, 21, 38, 64, 138, 154, 8, 146, 113, 142, 7, 146, 124, 106, 92, 22, 65, 107, 136, 143, 152, 132, 139, 127, 111, 105, 82, 89, 41, 27, 71, 6, 5, 115, 139, 149, 133, 142, 146, 77, 10, 13, 128, 144, 65, 129, 142, 144, 146, 84, 49, 150, 140, 138, 86, 45, 83, 95, 71, 3, 29, 31, 24, 37, 29, 33, 32, 27, 24, 25, 27, 25, 29, 35, 15, 18, 33, 41, 39, 28, 13, 3, 11, 26, 141, 152, 155, 154, 149, 150, 139, 117, 105, 27, 31, 1, 6, 2, 3, 38, 42, 9, 36, 23, 36, 34, 23, 4, 40, 41, 
+#> 38, 40, 37, 41, 9, 3, 22, 138, 54, 89, 145, 3, 100, 46, 65, 8, 128, 154, 134, 51, 142, 106, 76, 5, 138, 151, 145, 148, 154, 150, 153, 28, 90, 141, 154, 152, 151, 150, 119, 102, 119, 74, 9, 1, 139, 147, 105, 26, 152, 92, 134, 157, 147, 75, 39, 134, 26, 71, 128, 102, 21, 99, 1, 50, 100, 82, 98, 110, 107, 26, 36, 1, 53, 155, 148, 147, 152, 150, 97, 140, 150, 152, 134, 81, 82, 4, 9, 27, 16, 40, 37, 38, 39, 38, 21, 6, 31, 25, 5, 20, 24, 12, 19, 142, 89, 13, 153, 144, 146, 67, 138, 152, 145, 53, 17, 9, 
+#> 125, 109, 87, 95, 86, 69, 91, 103, 92, 66, 77, 31, 44, 14, 141, 139, 152, 154, 153, 144, 151, 152, 145, 146, 153, 136, 106, 26, 5, 40, 40, 40, 43, 39, 37, 26, 7, 47, 41, 45, 25, 3, 84, 152, 151, 152, 142, 151, 155, 141, 154, 149, 140, 141, 145, 147, 103, 59, 108, 144, 151, 142, 136, 155, 145, 141, 146, 128, 3, 38, 148, 154, 151, 130, 145, 125, 146, 139, 136, 144, 94, 7, 83, 125, 116, 151, 141, 142, 137, 151, 147, 140, 134, 122, 131, 120, 119, 86, 64, 4, 2, 39, 41, 44, 35, 38, 41, 37, 36, 43, 41, 
+#> 42, 36, 67, 131, 99, 90, 144, 127, 150, 142, 146, 115, 73, 92, 130, 96, 64, 50, 17, 51, 50, 4, 30, 7, 2, 33, 33, 22, 30, 40, 39, 23, 5, 8, 2, 144, 152, 156, 152, 150, 151, 149, 117, 41, 147, 113, 21, 16, 24, 43, 36, 34, 43, 42, 16, 7, 17, 17, 5, 1, 4, 24, 41, 37, 40, 41, 42, 52, 38, 41, 40, 39, 39, 41, 40, 40, 39, 36, 33, 39, 21, 16, 116, 131, 155, 143, 141, 105, 136, 21, 107, 122, 47, 22, 151, 147, 156, 144, 153, 149, 136, 124, 105, 117, 136, 145, 150, 151, 117, 145, 128, 65, 56, 58, 10, 50, 53, 
+#> 106, 111, 110, 99, 87, 90, 20, 128, 122, 79, 55, 42, 5, 5, 55, 47, 52, 46, 72, 56, 54, 51, 40, 49, 43, 25, 15, 2, 15, 36, 38, 33, 35, 31, 28, 30, 20, 1, 46, 63, 87, 57, 80, 89, 114, 133, 126, 113, 37, 48, 122, 84, 30, 6, 23, 42, 38, 34, 36, 39, 16, 8, 10, 3, 5, 3, 24, 29, 32, 18, 2, 15, 137, 130, 154, 156, 151, 155, 154, 115, 48, 100, 140, 114, 18, 136, 50, 55, 19, 20, 32, 56, 55, 60, 37, 7, 2, 27, 129, 91, 110, 145, 154, 36, 106, 138, 55, 55, 22, 117, 101, 15, 35, 39, 40, 37, 35, 38, 19, 14, 21, 
+#> 102, 119, 155, 149, 138, 85, 37, 128, 29, 94, 74, 136, 144, 25, 94, 131, 99, 8, 74, 6, 35, 1, 28, 134, 156, 153, 158, 153, 141, 154, 150, 153, 150, 141, 124, 101, 109, 54, 11, 9, 6, 131, 135, 130, 142, 141, 134, 150, 144, 140, 131, 66, 16, 83, 130, 126, 143, 128, 144, 111, 123, 124, 103, 39, 40, 40, 31, 57, 52, 34, 39, 11, 61, 24, 24, 140, 113, 31, 11, 92, 145, 144, 152, 152, 148, 115, 127, 141, 144, 138, 49, 33, 12, 33, 34, 28, 43, 48, 63, 23, 69, 48, 43, 29, 22, 1, 133, 144, 126, 153, 128, 153, 
+#> 155, 144, 152, 134, 127, 81, 31, 128, 153, 121, 11, 8, 107, 43, 80, 72, 11, 136, 99, 37, 115, 152, 107, 141, 125, 93, 28, 63, 62, 26, 79, 14, 13, 1, 23, 43, 36, 41, 36, 23, 16, 32, 35, 23, 5, 3, 20, 10, 6, 53, 74, 58, 42, 48, 9, 33, 45, 8, 27, 117, 124, 108, 142, 153, 158, 134, 132, 150, 140, 149, 119, 122, 50, 8, 40, 53, 146, 152, 150, 144, 153, 149, 148, 151, 139, 106, 126, 101, 85, 80, 129, 91, 42, 42, 37, 40, 39, 34, 36, 13, 8, 21, 14, 2, 2, 129, 154, 157, 150, 151, 154, 152, 104, 122, 133, 35, 
+#> 27, 21, 3, 141, 148, 151, 2, 29, 121, 147, 142, 134, 140, 149, 153, 131, 140, 119, 89, 21, 18, 131, 152, 141, 126, 141, 120, 141, 138, 127, 119, 121, 34, 151, 152, 152, 152, 152, 151, 153, 154, 162, 157, 157, 157, 152, 141, 148, 117, 139, 136, 69, 19, 66, 14, 47, 42, 35, 27, 34, 10, 23, 28, 2, 19, 6, 7, 10, 1, 39, 33, 21, 38, 34, 30, 36, 34, 27, 25, 15, 33, 37, 36, 34, 21, 7, 26, 51, 33, 33, 40, 43, 44, 7, 28, 55, 20, 14, 16, 9, 7, 31, 145, 96, 42, 145, 141, 151, 108, 142, 79, 75, 127, 88, 13, 6, 
+#> 37, 40, 25, 14, 25, 3, 37, 57, 34, 5, 6, 32, 34, 7, 96, 142, 127, 146, 147, 150, 144, 150, 144, 153, 153, 123, 65, 143, 122, 108, 144, 144, 21, 43, 40, 44, 39, 44, 45, 51, 43, 39, 36, 35, 35, 26, 27, 35, 31, 20, 10, 11, 13, 21, 141, 128, 127, 68, 6, 34, 51, 109, 149, 20, 121, 73, 43, 131, 73, 103, 108, 6, 7, 5, 23, 155, 154, 148, 155, 137, 139, 121, 19, 155, 155, 145, 146, 151, 139, 139, 126, 131, 130, 120, 111, 54, 23, 3, 86, 151, 146, 147, 153, 149, 147, 145, 151, 144, 160, 148, 116, 111, 88, 137, 
+#> 142, 151, 119, 151, 153, 135, 152, 146, 148, 145, 92, 40, 93, 57, 106, 5, 68, 72, 98, 6, 16, 12, 11, 2, 19, 31, 37, 32, 30, 25, 28, 2, 37, 4, 6, 30, 67, 76, 82, 94, 111, 92, 54, 37, 26, 26, 46, 26, 11, 40, 26, 3, 15, 12, 151, 152, 149, 142, 108, 145, 138, 134, 95, 122, 68, 53, 9, 113, 136, 134, 154, 135, 149, 149, 153, 138, 69, 100, 31, 60, 81, 107, 31, 80, 141, 150, 141, 143, 141, 138, 129, 113, 20, 22, 51, 4, 22, 20, 31, 39, 38, 49, 47, 47, 43, 42, 12, 9, 5, 43, 46, 63, 50, 71, 62, 13, 53, 34, 
+#> 38, 32, 35, 42, 34, 34, 32, 40, 37, 2, 27, 36, 1, 21, 17, 33, 35, 5, 12, 30, 23, 8, 4, 144, 133, 24, 144, 144, 144, 120, 146, 156, 142, 145, 135, 6, 7, 3, 88, 130, 147, 152, 154, 155, 154, 154, 155, 155, 156, 150, 159, 157, 137, 133, 21, 145, 157, 138, 141, 151, 148, 149, 148, 153, 152, 152, 158, 141, 156, 134, 36, 101, 31, 30, 138, 152, 153, 149, 146, 136, 147, 153, 100, 145, 146, 125, 142, 131, 102, 131, 131, 133, 106, 91, 147, 20, 33, 34, 39, 31, 24, 30, 35, 33, 39, 38, 38, 39, 38, 22, 7, 10, 
+#> 154, 154, 139, 156, 154, 155, 156, 138, 154, 130, 157, 163, 141, 151, 150, 155, 72, 39, 50, 44, 21, 45, 31, 28, 29, 23, 25, 18, 52, 46, 31, 6, 27, 1, 3, 152, 143, 145, 152, 153, 156, 153, 146, 146, 144, 151, 134, 157, 156, 146, 125, 110, 132, 152, 150, 148, 146, 139, 153, 162, 140, 156, 156, 155, 129, 130, 148, 132, 133, 103, 147, 129, 15, 49, 36, 147, 150, 142, 150, 149, 151, 153, 160, 159, 162, 144, 136, 57, 56, 10, 83, 25, 122, 153, 153, 151, 153, 154, 153, 155, 156, 161, 145, 150, 158, 155, 160, 
+#> 147, 150, 139, 129, 120, 112, 137, 85, 5, 22, 39, 40, 39, 35, 42, 38, 34, 39, 41, 35, 34, 32, 39, 30, 38, 34, 2, 3, 45, 46, 39, 45, 45, 41, 47, 52, 46, 42, 39, 17, 21, 28, 8, 8, 19, 54, 19, 6, 27, 153, 155, 154, 152, 151, 156, 151, 148, 106, 82, 28, 11, 22, 109, 126, 98, 132, 113, 107, 138, 136, 101, 127, 140, 129, 116, 84, 35, 9, 138, 8, 147, 151, 153, 139, 151, 153, 149, 148, 154, 152, 39, 109, 30, 3, 2, 85, 154, 155, 154, 151, 150, 151, 145, 79, 124, 154, 137, 100, 8, 113, 157, 76, 127, 138, 132, 
+#> 147, 153, 45, 135, 106, 109, 3, 33, 38, 36, 37, 39, 39, 45, 19, 9, 23, 50, 12, 10, 15, 15, 45, 36, 40, 38, 38, 43, 41, 41, 39, 43, 40, 27, 9, 25, 35, 31, 97, 98, 110, 103, 125, 107, 129, 136, 135, 150, 110, 126, 42, 66, 71, 1, 10, 35, 36, 27, 32, 33, 33, 34, 15, 24, 11, 19, 127, 147, 127, 129, 93, 52, 147, 147, 147, 144, 138, 68, 19, 18, 124, 117, 102, 146, 154, 127, 139, 148, 122, 142, 120, 148, 75, 6, 56, 151, 133, 149, 155, 151, 130, 100, 138, 121, 135, 20, 40, 29, 87, 53, 75, 5, 54, 134, 120, 
+#> 144, 153, 162, 152, 150, 106, 125, 33, 46, 27, 81, 148, 152, 135, 151, 152, 159, 142, 162, 130, 162, 163, 143, 67, 112, 70, 34, 67, 79, 116, 138, 133, 112, 118, 131, 150, 142, 15, 107, 86, 69, 60, 50, 9, 48, 61, 37, 46, 5, 41, 42, 31, 29, 31, 28, 50, 49, 24, 45, 56, 7, 144, 147, 152, 152, 151, 145, 154, 148, 137, 146, 80, 25, 48, 144, 160, 154, 107, 122, 2, 148, 151, 151, 152, 162, 156, 142, 33, 19, 123, 151, 157, 154, 148, 71, 28, 3, 142, 33, 39, 6, 128, 153, 142, 157, 151, 149, 108, 135, 15, 124, 
+#> 156, 126, 60, 39, 23, 15, 35, 5, 34, 35, 32, 35, 44, 49, 40, 38, 35, 38, 41, 39, 39, 35, 34, 12, 22, 5, 23, 57, 53, 58, 36, 38, 39, 55, 20, 29, 3, 3, 5, 30, 38, 43, 25, 54, 73, 35, 39, 41, 44, 37, 40, 34, 38, 40, 40, 37, 36, 17, 27, 20, 62, 128, 140, 151, 139, 108, 136, 34, 72, 98, 27, 18, 137, 145, 139, 143, 142, 137, 96, 82, 41, 16, 11, 150, 144, 159, 149, 148, 149, 135, 70, 153, 145, 81, 47, 52, 101, 106, 91, 152, 130, 160, 150, 135, 148, 149, 152, 105, 81, 130, 128, 122, 11, 71, 141, 108, 117, 
+#> 48, 2, 14, 36, 33, 28, 35, 50, 39, 37, 30, 11, 7, 27, 28, 50, 44, 39, 34, 36, 38, 35, 11, 23, 21, 36, 34, 34, 26, 6, 15, 50, 145, 88, 152, 163, 162, 161, 163, 144, 157, 158, 162, 156, 158, 156, 153, 155, 153, 144, 71, 24, 5, 4, 48, 68, 26, 137, 133, 148, 147, 131, 131, 115, 48, 96, 142, 149, 148, 140, 149, 133, 106, 118, 85, 5, 25, 50, 116, 51, 99, 122, 136, 161, 157, 90, 141, 46, 119, 125, 100, 138, 26, 138, 144, 153, 159, 162, 160, 148, 159, 110, 127, 49, 95, 151, 142, 125, 151, 147, 138, 148, 
+#> 161, 158, 161, 153, 155, 10, 34, 12, 2, 153, 155, 71, 144, 158, 162, 23, 157, 40, 86, 85, 59, 61, 16, 8, 9, 117, 92, 141, 123, 134, 149, 146, 149, 158, 161, 161, 153, 14, 95, 85, 87, 108, 134, 122, 126, 74, 146, 150, 140, 89, 73, 73, 146, 120, 62, 8, 35, 52, 29, 34, 39, 18, 11, 26, 15, 4, 39, 16, 28, 33, 6, 16, 26, 37, 46, 70, 57, 42, 9, 11, 4, 39, 31, 26, 62, 65, 55, 55, 57, 63, 71, 64, 41, 24, 12, 51, 62, 44, 37, 47, 38, 40, 36, 33, 38, 8, 18, 9, 9, 11, 5, 97, 73, 134, 150, 162, 161, 151, 159, 
+#> 160, 149, 3, 36, 41, 40, 39, 32, 39, 42, 22, 16, 6, 5, 13, 14, 14, 35, 114, 118, 103, 128, 128, 135, 134, 136, 142, 116, 135, 115, 46, 124, 147, 111, 140, 105, 144, 146, 144, 152, 155, 152, 154, 147, 132, 138, 108, 132, 102, 27, 154, 154, 154, 155, 162, 156, 159, 156, 158, 130, 132, 148, 146, 136, 124, 115, 103, 83, 148, 148, 165, 134, 158, 158, 143, 149, 153, 104, 47, 132, 149, 71, 27, 34, 33, 16, 43, 11, 11, 1, 18, 12, 146, 159, 161, 162, 164, 162, 162, 163, 163, 161, 157, 150, 156, 117, 155, 120, 
+#> 13, 58, 121, 159, 148, 147, 144, 142, 160, 152, 127, 142, 130, 135, 137, 121, 53, 5, 101, 134, 143, 154, 145, 163, 161, 160, 160, 162, 151, 60, 63, 40, 39, 46, 94, 110, 102, 108, 116, 7, 90, 90, 99, 114, 110, 100, 103, 91, 7, 68, 80, 79, 77, 3, 15, 12, 1, 18, 34, 32, 34, 39, 30, 34, 37, 9, 12, 35, 18, 56, 10, 29, 65, 27, 6, 12, 42, 20, 29, 4, 38, 42, 59, 47, 64, 60, 71, 66, 67, 51, 42, 2, 74, 87, 39, 133, 160, 149, 163, 144, 150, 135, 69, 38, 11, 3, 22, 7, 40, 9, 24, 35, 31, 43, 40, 27, 30, 15, 11, 
+#> 2, 26, 37, 47, 46, 41, 40, 43, 42, 40, 58, 46, 38, 31, 12, 3, 13, 47, 48, 36, 46, 56, 47, 45, 36, 43, 56, 54, 24, 7, 31, 42, 43, 42, 36, 26, 40, 3, 4, 49, 41, 62, 24, 10, 160, 154, 134, 123, 112, 137, 144, 147, 116, 106, 111, 124, 113, 112, 22, 9, 157, 145, 153, 156, 151, 130, 152, 94, 45, 10, 8, 7, 2, 40, 44, 30, 34, 31, 33, 24, 34, 31, 31, 12, 1, 110, 132, 163, 146, 152, 17, 100, 154, 132, 24, 123, 11, 57, 66, 79, 26, 15, 137, 158, 116, 72, 8, 36, 14, 2, 48, 37, 38, 41, 36, 37, 21, 34, 32, 11, 
+#> 62, 66, 79, 63, 16, 39, 20, 3, 11, 22, 43, 43, 69, 59, 57, 58, 68, 62, 63, 56, 55, 16, 54, 61, 2, 43, 44, 12, 16, 34, 40, 35, 37, 42, 28, 40, 29, 43, 41, 148, 160, 151, 151, 133, 160, 161, 157, 162, 161, 148, 125, 152, 148, 149, 155, 150, 144, 147, 105, 91, 131, 119, 29, 15, 129, 160, 159, 160, 160, 137, 160, 122, 72, 31, 66, 52, 133, 148, 126, 114, 98, 80, 85, 151, 140, 106, 108, 79, 50, 5, 3, 121, 121, 140, 132, 151, 158, 162, 156, 160, 134, 150, 153, 13, 4, 112, 142, 126, 139, 46, 135, 27, 121, 
+#> 159, 119, 34, 2, 2, 3, 5, 50, 54, 42, 38, 48, 46, 37, 37, 53, 33, 157, 136, 162, 156, 148, 149, 156, 159, 160, 154, 160, 163, 162, 162, 162, 159, 163, 162, 107, 162, 151, 26, 95, 119, 72, 63, 157, 160, 143, 152, 133, 108, 135, 56, 75, 115, 66, 3, 31, 11, 30, 38, 42, 33, 39, 37, 26, 38, 38, 34, 37, 25, 34, 11, 2, 18, 49, 99, 138, 157, 157, 162, 160, 155, 149, 121, 134, 147, 103, 92, 45, 21, 40, 40, 42, 41, 40, 42, 46, 27, 35, 37, 40, 31, 34, 25, 33, 22, 5, 50, 45, 46, 36, 41, 41, 43, 20, 45, 3, 31, 
+#> 90, 150, 142, 121, 139, 93, 51, 33, 63, 111, 99, 117, 38, 59, 17, 24, 75, 29, 7, 95, 154, 162, 162, 161, 164, 155, 161, 162, 160, 154, 154, 133, 149, 117, 40, 92, 135, 79, 115, 129, 118, 14, 130, 47, 41, 9, 7, 161, 149, 159, 146, 128, 153, 157, 126, 10, 146, 127, 131, 67, 10, 162, 161, 141, 122, 152, 118, 122, 155, 148, 72, 128, 119, 85, 54, 67, 118, 122, 138, 114, 157, 156, 149, 38, 31, 22, 9, 38, 44, 9, 13, 153, 124, 150, 155, 142, 158, 113, 162, 163, 100, 162, 157, 147, 139, 69, 122, 106, 11, 
+#> 58, 154, 147, 161, 162, 151, 159, 161, 158, 107, 101, 45, 45, 78, 77, 58, 36, 13, 20, 143, 127, 57, 132, 110, 148, 128, 117, 152, 129, 113, 115, 12, 2, 113, 80, 142, 154, 148, 148, 135, 115, 159, 161, 161, 149, 141, 147, 114, 114, 26, 28, 34, 59, 58, 62, 50, 51, 43, 31, 1, 1, 7, 4, 100, 144, 130, 136, 155, 155, 143, 117, 148, 111, 110, 130, 120, 71, 48, 74, 153, 158, 163, 156, 160, 108, 137, 160, 160, 153, 150, 72, 34, 55, 144, 131, 155, 137, 155, 99, 21, 50, 8, 74, 157, 152, 136, 84, 95, 109, 119, 
+#> 70, 73, 109, 101, 132, 137, 100, 87, 74, 4, 156, 149, 148, 120, 129, 46, 53, 11, 4, 80, 39, 28, 54, 42, 47, 48, 30, 53, 20, 39, 50, 35, 27, 43, 11, 31, 72, 8, 15, 42, 14, 37, 37, 36, 36, 39, 38, 35, 37, 38, 19, 6, 83, 13, 17, 140, 159, 142, 108, 127, 138, 159, 158, 96, 131, 12, 11, 49, 50, 3, 148, 15, 10, 108, 117, 144, 140, 134, 128, 145, 136, 141, 138, 148, 140, 124, 117, 63, 122, 126, 67, 38, 74, 17, 3, 15, 57, 33, 59, 82, 44, 23, 46, 54, 52, 67, 57, 43, 6, 26, 6, 40, 5, 26, 2, 43, 53, 84, 38, 
+#> 20, 70, 78, 56, 11, 36, 11, 63, 45, 162, 142, 161, 159, 152, 27, 104, 130, 72, 44, 5, 13, 13, 10, 160, 158, 132, 149, 153, 113, 114, 83, 26, 17, 81, 153, 147, 152, 133, 82, 121, 114, 119, 76, 2, 21, 138, 137, 127, 126, 150, 150, 139, 146, 137, 64, 62, 21, 15, 4, 124, 140, 134, 144, 140, 125, 154, 152, 154, 128, 140, 114, 110, 134, 95, 50, 5, 122, 141, 96, 124, 104, 94, 49, 82, 42, 9, 15, 35, 38, 54, 47, 18, 27, 52, 40, 37, 18, 15, 75, 95, 106, 132, 154, 157, 121, 143, 154, 140, 160, 123, 154, 131, 
+#> 2, 120, 19, 93, 3, 10, 34, 66, 57, 54, 38, 15, 41, 41, 48, 4, 47, 17, 24, 17, 33, 35, 38, 33, 16, 65, 55, 68, 5, 71, 54, 48, 10, 5, 12, 104, 99, 156, 160, 160, 158, 158, 136, 151, 158, 137, 139, 154, 148, 132, 151, 84, 69, 91, 71, 72, 77, 4, 123, 148, 52, 103, 155, 156, 159, 159, 157, 155, 157, 153, 160, 153, 136, 133, 141, 92, 120, 32, 46, 39, 23, 29, 9, 27, 33, 38, 39, 27, 33, 25, 22, 4, 3, 24, 42, 47, 40, 40, 29, 25, 4, 45, 41, 41, 38, 32, 9, 23, 4, 162, 159, 124, 152, 127, 146, 152, 158, 158, 
+#> 158, 156, 157, 120, 45, 44, 16, 8, 119, 133, 151, 141, 150, 133, 141, 142, 146, 151, 140, 145, 83, 75, 75, 2, 12, 124, 154, 156, 139, 135, 132, 161, 157, 130, 2, 6, 149, 152, 160, 151, 73, 9, 114, 124, 32, 74, 13, 2, 137, 127, 123, 51, 147, 142, 149, 153, 143, 156, 155, 152, 110, 144, 93, 138, 129, 93, 127, 36, 38, 39, 42, 39, 36, 39, 32, 37, 35, 20, 13, 36, 33, 26, 23, 22, 34, 34, 35, 16, 12, 8, 10, 22, 127, 143, 113, 150, 138, 128, 138, 44, 134, 77, 45, 130, 11, 74, 12, 47, 90, 93, 90, 79, 6, 70, 
+#> 67, 157, 105, 158, 156, 149, 157, 123, 145, 139, 150, 130, 148, 36, 30, 7, 60, 1, 39, 40, 43, 40, 39, 36, 38, 41, 37, 30, 28, 34, 37, 29, 19, 34, 33, 47, 72, 38, 33, 44, 43, 40, 32, 41, 38, 42, 45, 41, 42, 41, 32, 31, 20, 27, 3, 20, 33, 38, 38, 44, 42, 14, 33, 15, 5, 6, 158, 155, 143, 147, 159, 131, 115, 143, 135, 65, 47, 148, 128, 68, 92, 41, 106, 4, 30, 92, 145, 153, 149, 142, 139, 142, 157, 99, 52, 84, 75, 53, 154, 153, 146, 155, 131, 143, 131, 120, 114, 64, 9, 26, 154, 148, 158, 149, 147, 152, 
+#> 160, 142, 135, 142, 120, 130, 114, 52, 119, 110, 79, 53, 37, 68, 134, 152, 151, 132, 152, 142, 27, 105, 29, 74, 60, 8, 20, 4, 37, 40, 36, 36, 44, 42, 38, 12, 21, 35, 23, 11, 44, 55, 57, 25, 7, 8, 79, 49, 150, 63, 71, 23, 61, 26, 150, 10, 149, 17, 52, 15, 25, 143, 146, 122, 143, 141, 96, 119, 108, 111, 72, 159, 114, 1, 139, 50, 32, 33, 162, 97, 1, 29, 30, 35, 34, 24, 35, 41, 41, 30, 36, 38, 39, 12, 4, 106, 150, 145, 160, 158, 154, 155, 149, 160, 153, 154, 145, 39, 59, 131, 56, 6, 1, 25, 4, 3, 34, 
+#> 51, 88, 76, 77, 44, 49, 49, 42, 43, 7, 24, 28, 7, 99, 133, 103, 129, 50, 90, 103, 75, 11, 2, 32, 25, 38, 38, 28, 39, 41, 38, 35, 38, 38, 36, 26, 2, 20, 131, 148, 145, 142, 149, 142, 118, 157, 136, 1, 78, 24, 44, 11, 8, 69, 145, 150, 145, 150, 113, 154, 155, 152, 153, 144, 135, 101, 113, 64, 54, 37, 41, 149, 162, 142, 143, 125, 153, 136, 162, 139, 91, 47, 67, 10, 47, 124, 148, 158, 152, 147, 148, 144, 154, 71, 144, 134, 30, 4, 6, 135, 144, 126, 151, 144, 140, 74, 100, 103, 130, 130, 116, 60, 102, 
+#> 53, 29, 159, 96, 135, 120, 142, 129, 153, 84, 152, 108, 26, 98, 9, 35, 154, 152, 149, 150, 135, 151, 148, 157, 134, 146, 139, 131, 143, 94, 153, 116, 143, 143, 132, 115, 1, 103, 139, 142, 123, 154, 157, 158, 147, 100, 129, 115, 85, 15, 9, 30, 35, 32, 34, 37, 41, 40, 39, 37, 35, 36, 34, 36, 38, 24, 38, 37, 34, 16, 10, 16, 6, 23, 9, 4, 4, 81, 78, 63, 110, 117, 141, 139, 146, 162, 155, 149, 32, 108, 123, 11, 48, 6, 30, 139, 129, 147, 137, 134, 136, 106, 92, 124, 21, 12, 53, 70, 69, 72, 59, 55, 70, 66, 
+#> 75, 67, 11, 36, 17, 9, 8, 34, 90, 67, 70, 63, 7, 33, 5, 55, 27, 9, 80, 154, 133, 162, 155, 131, 158, 38, 72, 121, 88, 61, 44, 42, 35, 35, 5, 35, 42, 36, 33, 39, 32, 47, 41, 40, 35, 35, 36, 8, 15, 19, 113, 146, 148, 82, 29, 102, 118, 132, 150, 128, 71, 106, 97, 25, 54, 33, 7, 1, 37, 120, 133, 134, 143, 69, 82, 90, 78, 11, 19, 3, 4, 12, 157, 147, 147, 153, 130, 141, 111, 119, 137, 98, 25, 47, 98, 155, 156, 135, 152, 154, 152, 129, 139, 52, 96, 111, 138, 150, 95, 141, 146, 74, 21, 26, 132, 125, 140, 
+#> 147, 144, 157, 152, 149, 154, 97, 8, 43, 36, 35, 40, 38, 39, 27, 1, 25, 15, 31, 43, 36, 37, 38, 39, 40, 35, 28, 16, 18, 13, 14, 16, 31, 37, 38, 42, 35, 29, 4, 35, 26, 5, 17, 43, 110, 92, 152, 152, 149, 129, 95, 147, 110, 15, 49, 22, 12, 6, 39, 27, 38, 40, 39, 37, 38, 35, 37, 31, 18, 31, 19, 33, 28, 19, 48, 159, 147, 143, 148, 146, 132, 153, 142, 141, 151, 107, 99, 125, 98, 40, 81, 158, 157, 155, 153, 160, 150, 145, 99, 158, 26, 130, 146, 86, 45, 22, 128, 157, 156, 157, 142, 153, 143, 160, 129, 146, 
+#> 158, 149, 152, 153, 98, 42, 141, 43, 19, 33, 151, 111, 123, 157, 142, 115, 106, 106, 34, 118, 107, 71, 53, 87, 111, 121, 155, 17, 110, 150, 156, 157, 162, 149, 158, 107, 157, 131, 135, 101, 97, 1, 10, 145, 151, 132, 118, 111, 61, 61, 100, 39, 64, 109, 142, 156, 147, 152, 110, 98, 23, 115, 137, 139, 144, 120, 63, 64, 11, 21, 152, 159, 146, 153, 160, 156, 147, 147, 154, 146, 58, 74, 100, 50, 65, 9, 31, 95, 106, 141, 102, 95, 80, 93, 86, 107, 50, 35, 2, 29, 36, 9, 27, 44, 38, 36, 38, 26, 39, 40, 39, 
+#> 38, 23, 37, 22, 36, 14, 5, 5, 25, 127, 146, 158, 153, 147, 148, 148, 152, 146, 148, 150, 148, 124, 78, 26, 42, 30, 129, 128, 138, 136, 149, 151, 133, 114, 152, 85, 56, 47, 21, 24, 38, 7, 50, 83, 62, 15, 27, 9, 9, 30, 3, 31, 26, 8, 38, 41, 43, 38, 22, 66, 58, 54, 67, 64, 61, 40, 20, 40, 8, 10, 157, 122, 133, 10, 147, 144, 160, 149, 157, 149, 146, 141, 153, 132, 127, 141, 90, 134, 123, 116, 16, 38, 65, 82, 160, 158, 158, 128, 147, 142, 151, 133, 58, 66, 53, 13, 32, 46, 49, 36, 42, 39, 40, 41, 38, 41, 
+#> 41, 37, 15, 22, 32, 34, 37, 32, 10, 24, 24, 32, 14, 16, 18, 125, 129, 113, 93, 100, 49, 5, 2, 14, 131, 135, 52, 79, 134, 152, 157, 91, 131, 96, 135, 138, 102, 153, 125, 135, 76, 103, 137, 134, 62, 25, 4, 54, 145, 132, 154, 158, 109, 77, 151, 158, 159, 156, 162, 153, 45, 28, 1, 90, 161, 139, 139, 160, 131, 150, 141, 50, 132, 137, 82, 138, 98, 110, 83, 28, 37, 145, 159, 152, 122, 162, 136, 156, 154, 156, 147, 147, 103, 142, 147, 133, 72, 14, 7, 34, 35, 34, 33, 35, 26, 35, 13, 35, 17, 33, 25, 19, 68, 
+#> 35, 106, 127, 147, 120, 158, 126, 130, 64, 133, 90, 104, 49, 71, 4, 18, 19, 102, 27, 134, 77, 29, 10, 36, 6, 157, 150, 153, 141, 141, 145, 139, 6, 150, 113, 128, 96, 156, 88, 12, 25, 38, 106, 95, 111, 82, 28, 27, 49, 71, 63, 50, 59, 51, 66, 49, 64, 72, 59, 67, 10, 49, 48, 11, 34, 11, 19, 73, 42, 10, 58, 71, 65, 61, 65, 53, 57, 56, 29, 8, 51, 2, 67, 144, 142, 147, 159, 135, 147, 134, 149, 151, 134, 137, 149, 150, 98, 85, 8, 77, 55, 60, 30, 7, 133, 162, 160, 150, 144, 52, 144, 153, 150, 100, 145, 120, 
+#> 116, 144, 98, 8, 76, 45, 113, 138, 131, 144, 125, 19, 66, 96, 90, 119, 86, 120, 57, 38, 31, 59, 72, 1, 150, 153, 154, 143, 127, 152, 97, 45, 75, 94, 28, 5, 1, 23, 39, 41, 47, 24, 65, 59, 36, 56, 45, 51, 43, 11, 9, 110, 94, 114, 133, 133, 33, 148, 160, 101, 150, 124, 119, 68, 20, 148, 154, 116, 156, 148, 129, 156, 155, 101, 162, 132, 147, 97, 123, 44, 45, 4, 5, 50, 46, 149, 152, 126, 156, 161, 153, 152, 137, 149, 94, 69, 17, 11, 47, 162, 162, 155, 153, 152, 162, 146, 160, 158, 159, 152, 130, 78, 32, 
+#> 3, 34, 12, 35, 39, 40, 30, 40, 41, 39, 39, 13, 21, 18, 23, 5, 24, 12, 12, 89, 125, 161, 160, 156, 44, 92, 144, 159, 160, 154, 102, 141, 142, 131, 151, 151, 150, 144, 107, 1, 16, 34, 27, 35, 42, 41, 10, 98, 81, 91, 129, 162, 160, 84, 149, 153, 155, 153, 130, 82, 153, 131, 89, 76, 105, 37, 21, 4, 24, 66, 65, 92, 106, 58, 24, 30, 4, 12, 54, 90, 18, 20, 3, 34, 81, 96, 114, 156, 160, 162, 162, 162, 162, 163, 110, 162, 100, 161, 162, 155, 27, 13, 130, 133, 140, 122, 76, 136, 135, 144, 26, 133, 100, 32, 
+#> 30, 37, 39, 42, 43, 38, 39, 37, 41, 39, 36, 22, 21, 19, 28, 47, 94, 120, 139, 150, 148, 149, 149, 122, 123, 103, 59, 53, 38, 29, 42, 38, 39, 26, 34, 39, 44, 29, 16, 6, 11, 101, 130, 119, 89, 160, 140, 152, 156, 153, 149, 156, 106, 147, 143, 154, 155, 90, 104, 84, 96, 48, 144, 99, 97, 112, 34, 64, 6, 59, 22, 151, 152, 152, 158, 154, 153, 116, 99, 89, 113, 121, 58, 86, 131, 145, 151, 153, 146, 100, 52, 160, 94, 160, 134, 133, 107, 40, 150, 116, 72, 85, 43, 122, 151, 137, 58, 27, 70, 13, 132, 162, 158, 
+#> 160, 154, 145, 160, 150, 102, 148, 154, 151, 158, 160, 147, 108, 42, 44, 40, 31, 53, 39, 22, 25, 22, 8, 7, 17, 103, 149, 147, 155, 141, 140, 144, 135, 94, 131, 90, 45, 63, 53, 59, 17, 29, 36, 47, 17, 9, 21, 56, 56, 25, 46, 41, 1, 60, 45, 48, 65, 62, 76, 76, 70, 78, 67, 54, 66, 47, 50, 33, 47, 21, 128, 130, 142, 140, 122, 85, 69, 137, 82, 154, 130, 103, 34, 110, 111, 87, 21, 19, 41, 46, 33, 34, 38, 18, 21, 43, 35, 38, 35, 38, 32, 32, 30, 25, 9, 6, 15, 145, 132, 129, 150, 147, 110, 76, 138, 117, 142, 
+#> 124, 112, 111, 87, 27, 117, 90, 21, 147, 154, 161, 155, 157, 150, 159, 151, 82, 7, 125, 144, 135, 99, 17, 146, 139, 155, 148, 143, 94, 119, 97, 77, 105, 6, 33, 23, 17, 37, 35, 25, 2, 32, 34, 6, 8, 7, 35, 38, 26, 37, 24, 22, 26, 32, 6, 31, 11, 3, 4, 3, 22, 96, 157, 158, 150, 160, 155, 157, 158, 158, 159, 145, 89, 103, 122, 129, 124, 137, 126, 112, 80, 24, 144, 153, 160, 163, 158, 124, 108, 145, 155, 159, 140, 157, 108, 135, 56, 8, 127, 116, 118, 161, 151, 155, 159, 139, 149, 160, 103, 162, 138, 88, 
+#> 126, 95, 20, 46, 40, 40, 28, 38, 41, 25, 13, 28, 8, 28, 150, 161, 85, 161, 149, 149, 155, 137, 106, 104, 159, 144, 125, 4, 129, 151, 143, 140, 158, 147, 155, 121, 154, 133, 136, 163, 102, 160, 157, 28, 91, 35, 61, 54, 73, 148, 138, 159, 148, 158, 139, 67, 73, 144, 156, 160, 162, 153, 101, 144, 157, 119, 13, 36, 21, 39, 62, 31, 72, 63, 36, 64, 32, 56, 57, 62, 50, 45, 40, 46, 11, 31, 44, 30, 39, 36, 16, 1, 5, 44, 66, 65, 68, 65, 58, 58, 45, 24, 31, 9, 9, 104, 36, 59, 17, 106, 134, 144, 158, 158, 121, 
+#> 144, 108, 151, 157, 146, 129, 15, 72, 29, 76, 159, 17, 142, 154, 153, 160, 159, 151, 128, 96, 134, 106, 52, 89, 27, 118, 45, 22, 132, 155, 140, 149, 149, 150, 151, 102, 139, 131, 110, 115, 140, 61, 24, 38, 76, 18, 119, 133, 128, 146, 73, 147, 152, 148, 108, 162, 126, 162, 159, 152, 154, 149, 146, 123, 101, 120, 138, 68, 148, 144, 140, 103, 152, 50, 108, 119, 79, 89, 97, 6, 25, 39, 34, 31, 25, 33, 38, 38, 29, 36, 22, 31, 31, 33, 37, 36, 20, 7, 30, 34, 32, 12, 11, 13, 33, 35, 10, 38, 43, 36, 41, 40, 
+#> 39, 33, 33, 40, 35, 35, 33, 34, 33, 32, 23, 27, 7, 31, 33, 5, 29, 34, 35, 16, 28, 63, 47, 78, 69, 29, 41, 23, 30, 62, 82, 57, 50, 34, 7, 8, 58, 71, 23, 41, 8, 22, 51, 14, 30, 31, 11, 3, 4, 10, 10, 4, 77, 17, 58, 25, 38, 12, 19, 21, 7, 28, 24, 36, 40, 58, 10, 13, 133, 159, 159, 139, 128, 154, 117, 89, 144, 123, 104, 155, 124, 115, 157, 124, 142, 131, 152, 145, 17, 70, 99, 61, 106, 148, 126, 149, 162, 156, 101, 124, 101, 159, 157, 106, 112, 112, 18, 4, 39, 34, 35, 31, 33, 18, 32, 24, 30, 29, 35, 20, 
+#> 13, 32, 34, 32, 33, 34, 33, 32, 3, 29, 17, 79, 58, 30, 118, 155, 137, 138, 141, 74, 58, 147, 99, 19, 96, 102, 8, 18, 158, 147, 146, 143, 21, 135, 103, 60, 136, 159, 109, 38, 14, 128, 26, 29, 18, 36, 16, 145, 146, 97, 121, 132, 132, 119, 141, 76, 143, 142, 139, 150, 144, 128, 122, 131, 40, 25, 88, 132, 148, 154, 158, 95, 146, 101, 127, 118, 120, 127, 80, 59, 122, 69, 25, 106, 46, 21, 30, 51, 99, 111, 152, 152, 143, 127, 154, 94, 145, 146, 129, 149, 151, 154, 150, 135, 82, 16, 33, 106, 78, 145, 123, 
+#> 127, 62, 70, 58, 112, 92, 110, 132, 113, 57, 39, 27, 110, 120, 152, 162, 132, 136, 34, 108, 85, 146, 110, 139, 122, 28, 6, 3, 13, 29, 127, 159, 149, 142, 112, 153, 149, 151, 153, 103, 147, 149, 100, 111, 83, 160, 161, 159, 158, 99, 151, 156, 162, 156, 137, 160, 161, 160, 155, 153, 156, 154, 108, 113, 64, 88, 46, 9, 24, 139, 157, 155, 151, 103, 148, 159, 138, 139, 130, 153, 157, 118, 147, 149, 143, 121, 75, 79, 42, 30, 125, 147, 134, 153, 138, 93, 144, 104, 142, 143, 141, 120, 110, 145, 26, 93, 124, 
+#> 90, 7, 145, 126, 36, 143, 143, 80, 155, 141, 142, 26, 17, 27, 9, 2, 21, 25, 27, 30, 39, 41, 42, 28, 39, 37, 31, 34, 35, 21, 35, 29, 30, 35, 30, 34, 33, 32, 30, 27, 27, 13, 114, 158, 152, 154, 145, 153, 155, 109, 11, 33, 7, 93, 62, 2, 5, 82, 133, 152, 161, 152, 157, 150, 150, 152, 123, 145, 100, 137, 153, 132, 143, 76, 73, 78, 21, 36, 41, 38, 38, 41, 35, 38, 44, 16, 12, 4, 20, 31, 43, 25, 9, 36, 32, 15, 4, 53, 153, 155, 154, 118, 80, 141, 126, 148, 148, 147, 148, 110, 142, 144, 80, 32, 40, 154, 157, 
+#> 158, 158, 123, 141, 141, 73, 59, 46, 131, 11, 11, 7, 36, 37, 34, 37, 23, 34, 32, 30, 34, 30, 22, 13, 15, 89, 143, 114, 77, 105, 86, 132, 120, 129, 97, 135, 104, 95, 41, 14, 64, 129, 161, 159, 161, 159, 103, 160, 95, 55, 154, 158, 149, 154, 95, 75, 43, 11, 142, 145, 155, 117, 134, 151, 153, 141, 58, 128, 147, 16, 72, 99, 59, 37, 47, 12, 94, 127, 151, 146, 86, 22, 48, 111, 86, 11, 10, 42, 28, 46, 37, 40, 34, 42, 38, 42, 41, 39, 38, 44, 45, 44, 40, 22, 35, 34, 32, 33, 34, 1, 22, 3, 11, 139, 127, 145, 
+#> 109, 152, 161, 143, 152, 144, 149, 115, 148, 132, 138, 130, 119, 92, 84, 89, 121, 124, 79, 140, 104, 32, 130, 141, 60, 150, 89, 131, 153, 149, 161, 158, 160, 162, 66, 152, 151, 155, 161, 158, 162, 68, 38, 109, 70, 112, 104, 78, 54, 107, 147, 161, 154, 127, 149, 143, 96, 156, 149, 160, 122, 140, 158, 162, 160, 158, 130, 150, 127, 8, 26, 136, 156, 143, 127, 99, 157, 135, 57, 126, 65, 131, 150, 142, 115, 140, 81, 2, 20, 36, 40, 39, 40, 20, 36, 20, 34, 15, 29, 16, 7, 34, 30, 5, 64, 42, 52, 62, 64, 62, 
+#> 60, 48, 70, 60, 71, 58, 16, 38, 14, 12, 30, 121, 106, 123, 160, 107, 150, 153, 106, 155, 160, 148, 154, 134, 63, 132, 156, 116, 153, 159, 129, 142, 162, 129, 97, 148, 156, 148, 67, 84, 155, 143, 21, 74, 34, 15, 134, 145, 109, 132, 138, 112, 72, 138, 18, 97, 109, 72, 17, 21, 154, 158, 152, 152, 118, 141, 94, 149, 88, 31, 98, 125, 81, 108, 76, 17, 56, 145, 143, 137, 157, 158, 159, 162, 105, 140, 152, 141, 155, 154, 156, 149, 112, 20, 150, 156, 143, 77, 46, 8, 1, 102, 118, 137, 145, 157, 154, 158, 162, 
+#> 90, 103, 157, 144, 134, 142, 160, 108, 20, 92, 17, 107, 120, 27, 69, 131, 145, 143, 69, 161, 141, 155, 124, 120, 36, 4, 13, 50, 60, 58, 71, 38, 23, 13, 50, 1, 6, 8, 5, 16, 148, 150, 101, 117, 142, 8, 12, 14, 5, 153, 155, 101, 162, 162, 140, 162, 162, 144, 95, 136, 141, 109, 63, 46, 1, 2, 40, 44, 14, 34, 36, 20, 15, 20, 29, 35, 33, 37, 5, 20, 36, 29, 16, 22, 18, 117, 131, 130, 119, 130, 150, 157, 118, 61, 120, 145, 127, 84, 68, 85, 69, 115, 142, 162, 148, 155, 154, 152, 149, 159, 156, 103, 156, 151, 
+#> 111, 78, 103, 41, 150, 158, 162, 133, 56, 4, 142, 130, 47, 67, 129, 143, 110, 41, 135, 112, 121, 134, 123, 10, 8, 58, 56, 119, 145, 81, 100, 149, 100, 147, 158, 144, 6, 48, 150, 155, 162, 162, 103, 158, 97, 48, 117, 24, 34, 118, 36, 34, 4, 38, 39, 32, 18, 20, 27, 40, 36, 44, 36, 38, 37, 24, 35, 38, 38, 32, 3, 25, 19, 8, 5, 38, 15, 4, 43, 57, 51, 54, 60, 41, 56, 58, 45, 55, 65, 57, 34, 34, 34, 25, 24, 27, 39, 42, 34, 17, 31, 30, 32, 49, 15, 60, 121, 159, 107, 151, 130, 153, 152, 98, 82, 49, 98, 12, 
+#> 13, 127, 154, 161, 102, 136, 137, 128, 141, 156, 146, 147, 112, 115, 113, 132, 105, 17, 4, 24, 17, 15, 29, 33, 23, 29, 16, 14, 19, 139, 142, 146, 105, 157, 142, 139, 149, 151, 151, 128, 121, 146, 101, 29, 112, 76, 74, 66, 90, 93, 36, 90, 156, 157, 128, 105, 58, 88, 143, 124, 32, 9, 9, 144, 91, 154, 157, 140, 154, 100, 154, 145, 159, 149, 132, 139, 130, 50, 92, 101, 95, 159, 156, 158, 110, 140, 159, 124, 158, 153, 158, 153, 155, 143, 150, 132, 141, 98, 44, 82, 32, 75, 40, 72, 69, 72, 84, 62, 47, 20, 
+#> 33, 63, 5, 131, 48, 22, 59, 41, 66, 46, 19, 13, 24, 37, 20, 51, 40, 56, 25, 12, 85, 143, 144, 96, 133, 155, 147, 140, 91, 130, 123, 124, 133, 119, 24, 69, 10, 40, 70, 14, 94, 58, 92, 100, 115, 132, 128, 139, 156, 107, 159, 125, 131, 101, 103, 42, 58, 113, 139, 145, 149, 152, 36, 102, 140, 150, 101, 136, 144, 120, 16, 69, 102, 65, 69, 20, 35, 35, 35, 34, 33, 32, 20, 36, 37, 16, 34, 34, 34, 6, 31, 37, 7, 7, 31, 88, 136, 147, 71, 89, 80, 38, 96, 68, 113, 84, 102, 49, 90, 33, 6, 6, 27, 41, 24, 12, 34, 
+#> 37, 34, 34, 35, 14, 29, 8, 14, 43, 57, 78, 51, 46, 48, 54, 56, 48, 11, 38, 2, 11, 152, 159, 158, 145, 153, 159, 150, 157, 85, 150, 159, 146, 145, 97, 45, 10, 25, 38, 36, 35, 35, 39, 38, 23, 34, 35, 2, 32, 8, 29, 36, 14, 5, 20, 3, 46, 122, 131, 92, 116, 143, 104, 2, 89, 158, 108, 149, 145, 142, 143, 153, 95, 140, 65, 85, 136, 134, 117, 90, 44, 87, 112, 148, 32, 88, 152, 121, 31, 92, 123, 72, 30, 3, 33, 42, 48, 3, 31, 33, 32, 32, 30, 34, 23, 21, 33, 54, 29, 3, 15, 33, 31, 64, 74, 74, 60, 60, 55, 53, 
+#> 61, 54, 51, 7, 13, 10, 121, 157, 151, 102, 128, 80, 151, 98, 151, 151, 150, 148, 134, 5, 135, 4, 118, 91, 80, 158, 109, 138, 145, 157, 103, 121, 28, 120, 60, 7, 28, 28, 44, 25, 37, 44, 35, 36, 35, 36, 34, 24, 36, 35, 34, 27, 23, 5, 25, 75, 98, 150, 160, 144, 137, 31, 152, 59, 44, 162, 136, 115, 43, 35, 54, 94, 135, 117, 125, 94, 105, 96, 42, 82, 113, 74, 53, 50, 4, 33, 53, 45, 34, 32, 24, 30, 3, 22, 6, 19, 18, 151, 104, 156, 104, 162, 162, 162, 162, 160, 159, 156, 154, 97, 57, 153, 18, 26, 23, 160, 
+#> 162, 162, 161, 162, 162, 161, 162, 161, 162, 162, 162, 112, 144, 163, 162, 161, 86, 83, 128, 31, 150, 155, 145, 136, 157, 157, 160, 158, 155, 158, 143, 57, 7, 18, 11, 140, 64, 147, 131, 152, 146, 122, 21, 80, 10, 1, 61, 129, 150, 142, 120, 145, 100, 153, 95, 146, 120, 140, 133, 4, 96, 87, 148, 100, 137, 153, 141, 131, 24, 21, 29, 35, 29, 30, 17, 43, 10, 53, 44, 50, 44, 25, 52, 40, 31, 35, 3, 10, 6, 21, 16, 2, 3, 34, 35, 26, 38, 25, 34, 29, 28, 7, 60, 17, 121, 99, 137, 156, 162, 103, 158, 106, 46, 
+#> 35, 135, 44, 57, 20, 36, 29, 38, 36, 35, 36, 38, 34, 33, 33, 33, 9, 21, 4, 19, 17, 17, 100, 62, 156, 130, 145, 120, 28, 134, 48, 43, 134, 135, 122, 84, 9, 94, 35, 17, 38, 35, 35, 40, 30, 40, 38, 23, 35, 36, 31, 8, 1, 2, 7, 28, 35, 34, 33, 34, 21, 15, 34, 34, 30, 29, 10, 5, 5, 6, 25, 6, 43, 71, 59, 21, 91, 136, 124, 119, 92, 125, 128, 109, 132, 122, 60, 77, 79, 62, 61, 8, 2, 25, 43, 39, 36, 35, 31, 35, 2, 26, 30, 26, 33, 31, 16, 19, 21, 4, 36, 22, 33, 27, 13, 156, 158, 156, 153, 154, 132, 155, 157, 
+#> 155, 158, 158, 117, 57, 150, 135, 8, 66, 138, 151, 147, 147, 144, 116, 149, 141, 143, 141, 133, 126, 40, 91, 67, 31, 9, 123, 147, 145, 152, 124, 153, 137, 58, 29, 125, 131, 138, 130, 45, 67, 123, 122, 120, 132, 14, 80, 83, 150, 162, 106, 158, 145, 88, 27, 90, 137, 150, 105, 2, 3, 54, 47, 58, 68, 68, 15, 3, 38, 25, 3, 20, 145, 139, 116, 86, 30, 59, 75, 51, 22, 83, 17, 122, 147, 111, 136, 154, 153, 134, 152, 139, 43, 32, 29, 32, 63, 11, 101, 24, 104, 153, 158, 161, 149, 147, 155, 156, 155, 144, 143, 
+#> 143, 97, 126, 132, 104, 123, 90, 114, 100, 147, 151, 158, 152, 152, 155, 128, 135, 122, 74, 31, 162, 151, 155, 154, 155, 30, 123, 153, 134, 105, 10, 33, 84, 101, 153, 149, 148, 143, 141, 143, 85, 125, 107, 69, 6, 83, 117, 132, 107, 120, 133, 157, 153, 157, 160, 107, 155, 160, 160, 141, 141, 126, 38, 35, 80, 49, 136, 154, 5, 84, 106, 32, 95, 136, 149, 146, 95, 85, 44, 97, 117, 99, 145, 148, 120, 142, 143, 141, 105, 53, 15, 13, 30, 6, 27, 20, 35, 36, 32, 50, 9, 45, 8, 41, 13, 6, 15, 88, 156, 156, 160, 
+#> 150, 151, 139, 109, 145, 130, 155, 144, 115, 101, 133, 59, 74, 109, 58, 4, 47, 98, 18, 40, 72, 66, 69, 65, 66, 63, 64, 64, 11, 53, 67, 70, 8, 55, 41, 52, 11, 43, 25, 12, 51, 83, 69, 128, 149, 154, 119, 128, 150, 71, 89, 132, 16, 116, 98, 70, 67, 55, 52, 53, 13, 75, 11, 63, 80, 74, 64, 45, 63, 32, 10, 10, 122, 122, 143, 121, 108, 93, 68, 107, 28, 26, 36, 46, 35, 9, 12, 38, 39, 36, 38, 28, 13, 23, 152, 155, 135, 157, 140, 142, 140, 145, 40, 31, 35, 33, 25, 34, 19, 35, 27, 33, 30, 7, 29, 20, 23, 26, 
+#> 1, 18, 8, 54, 86, 158, 154, 160, 157, 133, 158, 141, 134, 128, 122, 110, 135, 116, 149, 127, 111, 36, 71, 4, 26, 27, 32, 30, 1, 20, 21, 36, 36, 35, 37, 41, 30, 31, 20, 7, 91, 153, 159, 162, 141, 144, 158, 102, 152, 157, 134, 97, 128, 21, 32, 36, 25, 18, 48, 43, 49, 43, 39, 32, 30, 33, 35, 39, 20, 28, 17, 19, 24, 9, 16, 6, 31, 22, 3, 10, 22, 140, 125, 154, 133, 129, 119, 136, 137, 48, 30, 5, 71, 158, 156, 160, 155, 134, 153, 159, 154, 161, 151, 150, 133, 113, 97, 57, 45, 18, 61, 25, 18, 75, 66, 68, 
+#> 63, 62, 63, 63, 65, 47, 57, 14, 46, 58, 11, 150, 159, 149, 156, 155, 160, 154, 12, 134, 100, 122, 150, 142, 83, 12, 92, 63, 151, 154, 151, 153, 145, 124, 72, 71, 92, 104, 75, 40, 33, 6, 60, 39, 159, 157, 159, 156, 156, 153, 142, 149, 155, 102, 24, 98, 126, 150, 153, 156, 80, 112, 151, 148, 153, 103, 82, 75, 34, 141, 82, 161, 156, 147, 160, 145, 132, 158, 96, 50, 32, 103, 141, 140, 118, 94, 127, 143, 44, 93, 104, 107, 28, 72, 24, 32, 23, 124, 159, 143, 158, 154, 144, 72, 45, 14, 76, 103, 135, 89, 
+#> 145, 159, 152, 141, 86, 15, 151, 27, 119, 70, 32, 6, 16, 18, 32, 34, 36, 37, 30, 17, 9, 23, 6, 25, 8, 33, 139, 156, 158, 137, 150, 86, 62, 12, 21, 15, 33, 36, 35, 35, 31, 35, 32, 29, 24, 23, 34, 34, 33, 30, 32, 33, 29, 33, 33, 32, 19, 18, 18, 6, 23, 37, 24, 31, 36, 38, 36, 32, 33, 32, 2, 9, 145, 157, 162, 160, 157, 154, 133, 130, 154, 152, 130, 20, 82, 90, 137, 141, 148, 37, 91, 113, 5, 25, 139, 128, 110, 155, 158, 159, 137, 129, 21, 153, 84, 30, 128, 161, 161, 157, 158, 159, 146, 152, 160, 156, 
+#> 108, 137, 15, 88, 161, 163, 146, 154, 140, 161, 145, 155, 48, 94, 104, 108, 120, 138, 142, 28, 48, 56, 130, 151, 150, 142, 148, 125, 2, 88, 78, 12, 5, 32, 35, 39, 40, 32, 38, 26, 21, 10, 2, 33, 17, 74, 75, 68, 47, 67, 35, 38, 59, 72, 65, 29, 157, 159, 158, 65, 131, 154, 97, 22, 60, 111, 102, 96, 108, 151, 113, 37, 61, 76, 18, 100, 158, 151, 152, 158, 93, 49, 106, 30, 22, 82, 106, 137, 59, 80, 140, 153, 146, 79, 61, 6, 9, 62, 92, 81, 133, 144, 135, 52, 95, 93, 10, 40, 46, 41, 32, 34, 35, 31, 22, 27, 
+#> 7, 8, 17, 22, 35, 35, 36, 37, 36, 35, 24, 12, 35, 35, 35, 29, 6, 3, 6, 15, 64, 70, 40, 37, 68, 65, 57, 28, 40, 68, 56, 49, 46, 29, 35, 24, 37, 35, 35, 24, 10, 33, 34, 33, 35, 18, 31, 18, 9, 23, 25, 67, 149, 159, 159, 110, 162, 121, 153, 160, 161, 77, 133, 42, 111, 50, 79, 6, 12, 110, 121, 120, 68, 96, 108, 95, 37, 1, 59, 46, 57, 56, 132, 129, 135, 131, 127, 89, 76, 23, 108, 37, 129, 42, 131, 58, 92, 74, 125, 140, 111, 64, 160, 152, 13, 140, 105, 118, 154, 155, 103, 158, 158, 160, 115, 130, 161, 135, 
+#> 126, 11, 8, 134, 88, 7, 37, 80, 139, 136, 133, 89, 131, 94, 44, 150, 134, 18, 151, 155, 143, 156, 154, 139, 27, 47, 104, 130, 105, 51, 155, 153, 89, 97, 17, 146, 139, 129, 100, 152, 106, 139, 101, 81, 136, 97, 15, 109, 89, 133, 126, 108, 49, 6, 19, 7, 135, 122, 87, 44, 92, 135, 121, 76, 28, 26, 10, 18, 160, 161, 145, 160, 157, 86, 51, 143, 153, 29, 47, 103, 59, 76, 15, 69, 45, 43, 63, 36, 36, 36, 21, 33, 27, 33, 33, 34, 25, 5, 30, 34, 25, 3, 43, 43, 41, 27, 21, 32, 23, 11, 36, 26, 14, 26, 24, 16, 
+#> 34, 36, 34, 35, 33, 30, 23, 33, 28, 9, 24, 26, 33, 54, 60, 51, 63, 67, 69, 64, 45, 52, 63, 57, 50, 6, 122, 104, 130, 114, 129, 128, 104, 103, 114, 145, 122, 124, 101, 8, 45, 37, 37, 40, 36, 35, 4, 21, 35, 34, 21, 26, 33, 32, 34, 32, 10, 20, 10, 67, 126, 160, 158, 153, 160, 161, 140, 145, 74, 21, 29, 159, 122, 156, 125, 156, 153, 146, 100, 101, 146, 74, 146, 134, 47, 126, 101, 137, 146, 137, 157, 154, 130, 136, 138, 154, 83, 105, 17, 63, 6, 6, 100, 105, 151, 157, 150, 152, 153, 69, 54, 109, 64, 54, 
+#> 67, 74, 68, 70, 60, 55, 52, 31, 35, 47, 48, 51, 59, 61, 46, 62, 58, 38, 52, 31, 16, 147, 84, 138, 40, 103, 158, 110, 137, 155, 121, 96, 110, 80, 137, 82, 148, 153, 96, 148, 68, 20, 5, 54, 16, 149, 160, 160, 149, 128, 152, 150, 157, 146, 35, 144, 112, 112, 78, 42, 1, 25, 125, 103, 125, 108, 95, 15, 40, 17, 31, 125, 158, 145, 159, 147, 49, 146, 95, 120, 77, 24, 105, 147, 157, 152, 155, 107, 95, 120, 103, 143, 159, 154, 153, 141, 49, 72, 104, 110, 7, 75, 63, 141, 159, 163, 160, 157, 128, 139, 108, 61, 
+#> 80, 159, 153, 28, 72, 60, 114, 93, 1, 2, 20, 5, 33, 39, 36, 14, 19, 31, 28, 18, 8, 33, 6, 41, 125, 151, 97, 158, 123, 140, 100, 110, 131, 152, 73, 145, 161, 102, 45, 145, 70, 111, 8, 23, 2, 106, 74, 105, 123, 124, 139, 131, 135, 127, 129, 67, 35, 1, 32, 45, 46, 8, 32, 4, 42, 29, 8, 37, 37, 36, 36, 35, 31, 26, 22, 16, 111, 150, 162, 159, 154, 148, 144, 132, 110, 123, 117, 110, 149, 77, 79, 51, 4, 15, 32, 32, 36, 35, 21, 22, 17, 19, 15, 32, 26, 19, 13, 13, 4, 39, 147, 152, 158, 151, 147, 148, 147, 
+#> 143, 109, 110, 51, 25, 116, 124, 135, 111, 23, 85, 75, 2, 9, 20, 46, 77, 67, 43, 21, 62, 70, 53, 29, 14, 13, 25, 35, 20, 19, 5, 39, 42, 34, 32, 34, 35, 34, 3, 17, 12, 34, 32, 27, 22, 32, 28, 50, 34, 35, 31, 18, 7, 2, 7, 108, 62, 69, 148, 154, 140, 113, 99, 93, 95, 27, 37, 20, 51, 10, 34, 13, 37, 52, 35, 71, 27, 68, 8, 51, 51, 29, 13, 37, 55, 10, 64, 64, 72, 60, 50, 16, 3, 20, 43, 9, 34, 11, 64, 61, 13, 28, 116, 101, 123, 30, 5, 46, 102, 37, 26, 12, 3, 107, 154, 161, 153, 153, 152, 68, 83, 113, 144, 
+#> 159, 152, 151, 144, 158, 49, 97, 146, 86, 27, 33, 78, 90, 82, 86, 117, 135, 154, 157, 152, 107, 134, 143, 17, 113, 158, 156, 162, 159, 161, 27, 124, 158, 110, 56, 70, 46, 96, 25, 14, 27, 20, 94, 122, 63, 43, 107, 61, 14, 54, 27, 116, 126, 88, 157, 148, 153, 154, 156, 100, 72, 93, 87, 50, 134, 150, 149, 162, 155, 114, 141, 162, 162, 160, 160, 101, 155, 145, 153, 156, 155, 145, 141, 25, 35, 31, 29, 32, 34, 31, 35, 25, 32, 35, 25, 34, 33, 34, 22, 18, 14, 74, 150, 95, 155, 138, 146, 142, 18, 7, 88, 127, 
+#> 82, 114, 18, 62, 36, 42, 62, 98, 88, 72, 8, 53, 127, 141, 145, 108, 27, 139, 138, 75, 43, 136, 44, 43, 6, 23, 25, 34, 23, 38, 31, 32, 25, 35, 38, 36, 33, 35, 36, 20, 30, 26, 27, 30, 33, 40, 33, 36, 35, 34, 24, 33, 32, 32, 23, 15, 5, 87, 138, 158, 135, 150, 113, 120, 18, 1, 7, 132, 51, 89, 64, 80, 66, 127, 125, 117, 37, 97, 70, 51, 38, 75, 50, 46, 19, 27, 8, 133, 144, 97, 152, 130, 66, 146, 42, 103, 156, 119, 100, 42, 120, 122, 124, 138, 55, 11, 127, 155, 154, 142, 156, 111, 72, 140, 157, 161, 160, 
+#> 145, 111, 70, 53, 83, 128, 109, 144, 41, 102, 117, 33, 113, 150, 144, 159, 151, 153, 140, 159, 112, 144, 158, 159, 156, 102, 143, 153, 143, 130, 147, 14, 130, 126, 6, 34, 37, 35, 35, 39, 35, 36, 25, 28, 35, 33, 34, 33, 35, 35, 35, 37, 34, 35, 22, 12, 35, 7, 27, 15, 27, 24, 26, 154, 149, 148, 19, 147, 91, 125, 117, 46, 37, 74, 68, 67, 63, 45, 16, 15, 1, 10, 54, 55, 65, 66, 58, 66, 74, 38, 57, 62, 61, 21, 41, 20, 51, 68, 61, 77, 67, 55, 25, 17, 7, 16, 127, 109, 144, 157, 104, 120, 40, 139, 146, 133, 
+#> 68, 78, 111, 118, 30, 34, 82, 74, 159, 162, 155, 154, 109, 136, 107, 53, 98, 103, 14, 84, 52, 84, 159, 157, 146, 145, 112, 76, 105, 151, 135, 154, 96, 106, 60, 44, 54, 93, 129, 12, 114, 141, 122, 142, 130, 133, 135, 119, 117, 24, 12, 39, 21, 49, 19, 29, 31, 33, 36, 26, 14, 13, 31, 9, 42, 30, 34, 36, 35, 36, 26, 29, 39, 33, 33, 36, 37, 35, 37, 33, 35, 33, 32, 35, 14, 143, 158, 147, 161, 152, 153, 107, 130, 153, 112, 147, 159, 155, 157, 149, 67, 73, 38, 18, 16, 150, 157, 157, 157, 109, 135, 158, 54, 
+#> 161, 161, 141, 142, 141, 49, 89, 102, 27, 81, 52, 69, 140, 139, 92, 70, 62, 119, 25, 51, 3, 37, 34, 33, 11, 8, 28, 35, 20, 19, 38, 24, 140, 141, 149, 158, 149, 143, 143, 109, 143, 132, 112, 123, 81, 21, 37, 35, 35, 24, 29, 24, 24, 39, 19, 19, 3, 50, 51, 54, 67, 25, 59, 12, 1, 151, 155, 153, 109, 136, 153, 156, 150, 150, 102, 137, 80, 156, 162, 142, 110, 114, 162, 162, 147, 162, 159, 161, 158, 160, 156, 39, 60, 158, 160, 153, 113, 145, 141, 146, 160, 135, 159, 20, 148, 153, 74, 34, 137, 155, 55, 16, 
+#> 23, 66, 143, 162, 149, 157, 162, 162, 162, 158, 155, 111, 139, 157, 157, 85, 41, 21, 146, 75, 152, 154, 153, 157, 119, 122, 139, 121, 138, 34, 89, 59, 34, 102, 17, 29, 33, 34, 29, 32, 24, 13, 17, 27, 5, 20, 88, 123, 137, 99, 130, 153, 150, 145, 144, 91, 111, 108, 144, 135, 129, 136, 129, 82, 33, 93, 28, 111, 44, 134, 142, 157, 160, 158, 155, 106, 143, 142, 151, 158, 161, 143, 145, 124, 66, 35, 154, 153, 152, 150, 135, 136, 85, 15, 29, 20, 133, 137, 143, 138, 103, 131, 83, 153, 130, 127, 87, 142, 
+#> 136, 143, 38, 44, 100, 12, 33, 38, 38, 36, 35, 21, 29, 35, 36, 26, 29, 36, 75, 62, 73, 33, 35, 32, 6, 8, 7, 149, 98, 16, 101, 87, 52, 14, 149, 158, 111, 143, 154, 162, 139, 153, 155, 121, 142, 114, 40, 13, 14, 65, 144, 150, 135, 42, 89, 145, 139, 155, 154, 142, 153, 132, 97, 145, 141, 24, 25, 142, 155, 140, 107, 90, 134, 133, 154, 144, 115, 140, 70, 82, 33, 1, 66, 149, 161, 151, 114, 144, 157, 154, 146, 85, 155, 98, 118, 24, 95, 125, 50, 146, 72, 68, 87, 63, 161, 135, 40, 90, 152, 141, 143, 135, 
+#> 155, 154, 154, 39, 133, 114, 100, 2, 36, 49, 53, 58, 131, 143, 89, 145, 147, 69, 98, 5, 52, 84, 9, 33, 26, 23, 9, 16, 19, 30, 122, 108, 149, 156, 131, 85, 29, 92, 127, 29, 9, 4, 26, 33, 35, 34, 34, 25, 30, 30, 8, 14, 4, 4, 11, 49, 51, 59, 66, 36, 80, 71, 47, 52, 28, 24, 75, 23, 46, 70, 54, 56, 94, 125, 105, 138, 138, 85, 11, 52, 19, 31, 26, 55, 54, 6, 6, 5, 4, 12, 19, 19, 39, 20, 148, 148, 112, 118, 154, 122, 154, 120, 137, 133, 93, 46, 56, 84, 83, 110, 129, 52, 84, 143, 81, 142, 136, 158, 69, 136, 
+#> 151, 153, 151, 144, 156, 155, 151, 64, 148, 152, 153, 145, 92, 62, 108, 58, 60, 149, 132, 138, 148, 144, 144, 128, 128, 35, 95, 63, 6, 40, 85, 8, 67, 109, 130, 97, 118, 37, 49, 104, 110, 48, 26, 98, 148, 159, 157, 110, 139, 158, 144, 142, 154, 146, 135, 111, 149, 145, 44, 5, 38, 73, 78, 159, 157, 159, 154, 110, 138, 151, 153, 155, 151, 149, 129, 32, 72, 6, 111, 139, 138, 158, 108, 135, 125, 154, 160, 162, 159, 159, 154, 152, 49, 78, 87, 4, 5, 35, 56, 42, 34, 13, 17, 28, 35, 35, 24, 13, 16, 35, 36, 
+#> 24, 32, 32, 31, 24, 14, 45, 63, 73, 67, 65, 69, 42, 54, 48, 55, 56, 49, 23, 142, 100, 143, 156, 157, 136, 98, 158, 137, 138, 148, 60, 76, 21, 149, 107, 112, 148, 152, 5, 37, 109, 141, 136, 141, 135, 68, 129, 113, 126, 83, 108, 158, 161, 154, 103, 135, 100, 26, 133, 147, 22, 33, 73, 105, 79, 93, 15, 78, 94, 67, 103, 95, 68, 130, 82, 118, 121, 97, 28, 47, 98, 136, 58, 32, 62, 9, 123, 153, 159, 106, 143, 158, 161, 163, 161, 141, 83, 147, 132, 126, 56, 90, 149, 63, 85, 161, 84, 62, 40, 11, 21, 35, 34, 
+#> 32, 34, 27, 8, 34, 23, 13, 17, 11, 29, 31, 31, 30, 25, 5, 25, 72, 100, 136, 114, 58, 74, 141, 81, 26, 155, 135, 97, 82, 58, 31, 65, 76, 48, 60, 63, 73, 81, 12, 31, 34, 68, 36, 26, 16, 101, 72, 89, 110, 109, 42, 112, 139, 157, 159, 148, 159, 96, 149, 71, 75, 45, 98, 8, 26, 41, 14, 2, 115, 136, 107, 93, 143, 150, 159, 126, 136, 132, 151, 155, 123, 98, 87, 15, 6, 27, 13, 26, 20, 32, 33, 18, 33, 21, 14, 17, 28, 3, 26, 31, 45, 138, 110, 131, 59, 140, 96, 54, 38, 89, 89, 6, 66, 130, 27, 29, 9, 28, 162, 
+#> 115, 133, 157, 151, 93, 139, 119, 139, 116, 124, 25, 140, 131, 114, 28, 80, 21, 4, 7, 22, 33, 33, 31, 36, 23, 30, 14, 30, 11, 23, 35, 35, 35, 35, 18, 35, 34, 33, 10, 30, 22, 7, 129, 61, 143, 155, 157, 138, 161, 155, 101, 143, 103, 107, 117, 38, 1, 63, 30, 161, 153, 152, 135, 143, 111, 143, 146, 137, 131, 78, 59, 64, 54, 4, 97, 120, 124, 31, 102, 135, 84, 44, 128, 83, 108, 109, 19, 81, 142, 159, 162, 142, 94, 139, 161, 143, 159, 156, 152, 140, 150, 147, 104, 58, 112, 139, 43, 74, 113, 152, 111, 140, 
+#> 161, 141, 154, 139, 161, 139, 27, 6, 7, 24, 13, 15, 34, 51, 62, 69, 66, 44, 32, 68, 66, 71, 74, 61, 70, 55, 79, 16, 40, 8, 8, 25, 28, 63, 72, 52, 64, 61, 49, 57, 66, 37, 52, 137, 145, 103, 119, 124, 62, 122, 131, 9, 28, 33, 33, 12, 17, 29, 32, 33, 34, 33, 18, 19, 3, 22, 91, 137, 152, 150, 150, 147, 118, 142, 120, 154, 152, 152, 130, 133, 100, 53, 104, 24, 66, 5, 58, 144, 84, 135, 131, 143, 153, 113, 10, 20, 114, 12, 9, 105, 52, 139, 160, 159, 162, 158, 85, 122, 24, 143, 147, 148, 142, 15, 72, 21, 
+#> 48, 109, 134, 112, 141, 116, 139, 159, 151, 161, 151, 30, 125, 107, 33, 25, 153, 116, 67, 159, 105, 144, 124, 162, 159, 162, 156, 160, 150, 137, 126, 102, 114, 27, 40, 47, 98, 137, 151, 147, 123, 146, 158, 156, 147, 159, 143, 59, 143, 130, 149, 107, 17, 108, 22, 71, 28, 30, 18, 94, 141, 114, 133, 154, 55, 152, 150, 144, 137, 153, 142, 110, 117, 85, 26, 13, 73, 12, 32, 25, 24, 32, 36, 33, 29, 31, 34, 34, 33, 31, 27, 30, 32, 28, 34, 35, 23, 41, 22, 29, 13, 19, 10, 15, 30, 22, 33, 9, 116, 138, 107, 
+#> 133, 81, 86, 135, 133, 103, 126, 140, 130, 135, 93, 88, 24, 85, 62, 139, 108, 144, 143, 129, 128, 158, 141, 146, 154, 119, 148, 141, 131, 40, 89, 151, 159, 152, 161, 137, 157, 154, 160, 161, 157, 156, 111, 39, 90, 34, 105, 3, 28, 34, 24, 30, 35, 35, 29, 34, 33, 9, 4, 28, 18, 7, 25, 60, 58, 51, 137, 152, 158, 101, 126, 150, 157, 72, 87, 112, 19, 9, 8, 80, 100, 138, 123, 133, 65, 134, 128, 109, 129, 150, 103, 76, 18, 31, 22, 6, 67, 70, 52, 60, 62, 61, 63, 62, 62, 9, 59, 55, 67, 56, 53, 50, 56, 66, 
+#> 13, 48, 10, 55, 18, 15, 157, 159, 149, 158, 148, 150, 157, 119, 154, 159, 154, 156, 150, 153, 157, 131, 159, 17, 145, 41, 149, 106, 55, 92, 56, 81, 33, 95, 39, 93, 57, 24, 107, 34, 56, 17, 48, 146, 141, 161, 129, 148, 162, 162, 161, 155, 162, 154, 158, 138, 124, 137, 99, 122, 44, 151, 49, 144, 90, 120, 141, 118, 37, 117, 119, 153, 149, 138, 109, 26, 104, 56, 56, 4, 31, 35, 35, 33, 31, 32, 31, 22, 33, 15, 33, 38, 36, 33, 32, 21, 12, 30, 4, 14, 4, 1, 4, 3, 1, 34, 20, 28, 33, 27, 28, 32, 31, 29, 33, 
+#> 30, 30, 17, 16, 28, 39, 47, 55, 70, 70, 66, 64, 70, 62, 61, 9, 55, 60, 65, 61, 48, 55, 50, 2, 66, 24, 30, 33, 31, 33, 31, 29, 18, 30, 29, 33, 31, 23, 5, 20, 9, 22, 84, 152, 156, 154, 159, 159, 160, 111, 143, 162, 158, 162, 158, 158, 160, 155, 154, 154, 110, 151, 120, 153, 154, 45, 149, 144, 34, 23, 1, 17, 35, 20, 11, 34, 35, 36, 33, 36, 35, 11, 26, 34, 8, 23, 24, 8, 35, 31, 18, 26, 12, 29, 2, 55, 46, 9, 50, 78, 78, 39, 34, 64, 60, 77, 24, 153, 143, 135, 140, 21, 156, 156, 38, 43, 62, 122, 121, 55, 
+#> 65, 37, 156, 160, 112, 128, 151, 100, 55, 154, 142, 56, 142, 112, 115, 40, 88, 133, 65, 92, 24, 36, 136, 109, 97, 141, 155, 158, 142, 159, 155, 154, 150, 138, 138, 131, 51, 18, 142, 115, 129, 123, 161, 96, 115, 83, 151, 119, 104, 7, 56, 50, 24, 32, 6, 30, 34, 32, 20, 19, 16, 30, 35, 7, 19, 61, 66, 54, 66, 66, 71, 45, 64, 74, 71, 63, 67, 64, 66, 61, 64, 9, 64, 18, 41, 54, 43, 40, 41, 32, 16, 11, 18, 34, 32, 30, 34, 35, 16, 31, 31, 31, 30, 8, 5, 7, 22, 36, 38, 70, 96, 123, 114, 129, 152, 133, 135, 
+#> 120, 33, 76, 108, 138, 142, 139, 157, 152, 127, 158, 155, 159, 148, 14, 74, 31, 153, 159, 162, 161, 161, 154, 156, 154, 160, 156, 154, 75, 82, 107, 77, 94, 3, 6, 23, 27, 35, 32, 39, 33, 11, 10, 3, 20, 27, 8, 4, 5, 49, 33, 46, 40, 48, 24, 32, 34, 42, 73, 21, 47, 19, 15, 66, 80, 79, 59, 44, 34, 3, 24, 155, 148, 158, 154, 136, 55, 15, 108, 23, 26, 25, 29, 33, 32, 22, 21, 4, 22, 65, 58, 23, 24, 55, 10, 47, 73, 88, 114, 28, 21, 151, 153, 151, 126, 154, 85, 36, 98, 102, 90, 76, 113, 16, 81, 152, 148, 93, 
+#> 36, 154, 49, 94, 152, 150, 145, 57, 4, 26, 38, 120, 145, 141, 154, 95, 108, 102, 43, 120, 158, 153, 127, 136, 69, 22, 1, 4, 28, 27, 33, 35, 35, 26, 26, 34, 33, 36, 35, 33, 20, 17, 32, 22, 13, 21, 33, 29, 17, 24, 15, 24, 9, 20, 28, 3, 14, 121, 132, 135, 158, 153, 162, 161, 158, 160, 157, 158, 115, 34, 130, 128, 59, 149, 135, 133, 119, 37, 96, 24, 16, 50, 134, 86, 145, 108, 34, 130, 131, 131, 118, 67, 38, 6, 96, 151, 133, 145, 120, 147, 146, 137, 53, 59, 143, 69, 8, 140, 157, 157, 160, 157, 156, 159, 
+#> 158, 153, 137, 109, 110, 134, 128, 143, 95, 126, 112, 7, 68, 73, 61, 104, 7, 5, 42, 107, 74, 16, 1, 37, 62, 58, 66, 28, 64, 70, 78, 46, 75, 70, 66, 45, 15, 2, 71, 14, 156, 98, 155, 162, 141, 90, 69, 151, 140, 144, 161, 81, 64, 98, 44, 151, 145, 109, 133, 62, 48, 2, 63, 24, 42, 28, 17, 31, 11, 16, 2, 43, 37, 138, 153, 142, 152, 162, 162, 143, 161, 128, 144, 144, 139, 159, 26, 101, 123, 151, 144, 158, 150, 124, 135, 142, 139, 109, 18, 12, 9, 90, 159, 160, 154, 159, 161, 112, 156, 141, 156, 150, 143, 
+#> 100, 152, 145, 13, 44, 24, 29, 34, 32, 34, 35, 43, 36, 32, 36, 12, 13, 21, 10, 16, 39, 34, 15, 33, 8, 25, 23, 27, 23, 11, 30, 34, 32, 26, 33, 34, 33, 34, 32, 8, 25, 34, 33, 30, 19, 10, 3, 15, 39, 52, 33, 36, 33, 18, 14, 20, 14, 38, 32, 4, 7, 33, 63, 64, 71, 13, 19, 45, 61, 33, 39, 54, 25, 56, 28, 27, 33, 34, 28, 30, 26, 31, 34, 29, 23, 10, 17, 18, 5, 98, 75, 60, 158, 157, 97, 61, 131, 65, 137, 145, 146, 138, 154, 141, 57, 139, 133, 142, 157, 157, 150, 67, 125, 153, 40, 87, 140, 107, 73, 69, 63, 81, 
+#> 35, 24, 31, 30, 31, 34, 12, 19, 34, 20, 34, 33, 35, 30, 34, 11, 30, 28, 80, 106, 123, 108, 57, 128, 121, 110, 141, 122, 134, 47, 17, 83, 162, 157, 162, 87, 49, 145, 120, 23, 103, 154, 87, 21, 33, 35, 152, 159, 160, 159, 156, 160, 154, 144, 145, 154, 83, 151, 118, 124, 69, 124, 54, 140, 142, 153, 158, 152, 154, 155, 156, 80, 139, 139, 83, 145, 19, 83, 87, 64, 60, 71, 26, 37, 65, 140, 107, 125, 39, 89, 155, 137, 138, 159, 159, 152, 130, 145, 149, 115, 136, 121, 27, 48, 68, 51, 68, 65, 65, 67, 45, 24, 
+#> 79, 26, 33, 51, 27, 68, 62, 63, 45, 17, 58, 73, 68, 58, 66, 60, 79, 33, 19, 61, 63, 69, 61, 35, 131, 79, 154, 156, 143, 154, 159, 138, 36, 150, 97, 37, 50, 121, 9, 48, 154, 159, 161, 156, 91, 58, 149, 153, 115, 151, 14, 128, 1, 8, 60, 111, 112, 151, 138, 143, 142, 137, 142, 143, 144, 51, 111, 120, 115, 21, 145, 157, 153, 160, 153, 160, 52, 82, 155, 157, 146, 131, 84, 92, 106, 154, 133, 154, 150, 141, 152, 157, 149, 153, 149, 124, 138, 124, 72, 96, 8, 118, 3, 151, 143, 142, 49, 78, 87, 91, 72, 125, 
+#> 20, 16, 115, 153, 151, 153, 156, 125, 160, 137, 90, 23, 8, 33, 58, 113, 80, 44, 28, 11, 116, 141, 146, 155, 150, 158, 147, 140, 76, 141, 151, 120, 149, 48, 33, 45, 1, 6, 135, 99, 148, 148, 154, 138, 98, 147, 160, 146, 119, 152, 156, 140, 144, 142, 139, 157, 157, 159, 161, 162, 161, 161, 162, 146, 162, 161, 67, 95, 150, 143, 153, 24, 79, 113, 140, 79, 159, 37, 123, 154, 150, 61, 29, 49, 101, 103, 75, 50, 130, 128, 127, 150, 128, 130, 143, 129, 134, 139, 117, 81, 36, 21, 16, 79, 104, 125, 162, 153, 
+#> 162, 58, 103, 141, 153, 155, 161, 59, 101, 123, 91, 39, 3, 1, 51, 107, 37, 50, 67, 141, 112, 89, 140, 150, 105, 122, 110, 130, 102, 107, 3, 44, 18, 71, 71, 77, 76, 73, 62, 9, 45, 15, 64, 30, 41, 36, 19, 8, 161, 157, 157, 154, 161, 143, 158, 148, 160, 159, 147, 154, 99, 159, 157, 12, 137, 122, 154, 112, 77, 56, 146, 152, 154, 153, 162, 162, 148, 156, 105, 155, 153, 139, 136, 9, 105, 46, 122, 152, 141, 156, 133, 129, 51, 73, 114, 122, 99, 140, 60, 27, 34, 30, 26, 33, 32, 17, 3, 3, 15, 9, 44, 62, 75, 
+#> 73, 78, 72, 68, 79, 68, 33, 156, 137, 144, 143, 144, 129, 139, 87, 115, 129, 135, 114, 86, 5, 101, 119, 32, 117, 26, 7, 15, 42, 44, 69, 62, 14, 35, 35, 35, 34, 35, 34, 34, 32, 34, 34, 13, 32, 30, 3, 2, 31, 130, 96, 122, 119, 97, 119, 117, 134, 145, 132, 61, 57, 15, 10, 5, 62, 75, 66, 66, 69, 31, 68, 20, 20, 13, 26, 105, 159, 160, 162, 162, 162, 162, 162, 162, 133, 158, 158, 97, 59, 91, 53, 56, 68, 69, 84, 55, 24, 23, 151, 124, 155, 147, 31, 78, 84, 133, 39, 54, 131, 117, 91, 52, 7, 32, 33, 37, 22, 
+#> 32, 21, 6, 44, 9, 22, 158, 156, 156, 145, 156, 159, 135, 109, 117, 147, 137, 151, 93, 58, 67, 5, 106, 150, 154, 156, 157, 159, 161, 158, 159, 112, 142, 141, 108, 145, 135, 80, 8, 12, 63, 74, 74, 67, 32, 33, 33, 35, 35, 33, 34, 34, 34, 34, 21, 17, 9, 4, 23, 24, 26, 29, 33, 30, 27, 32, 21, 30, 21, 7, 8, 20, 2, 36, 19, 17, 34, 36, 21, 19, 32, 31, 34, 32, 33, 32, 25, 13, 5, 20, 33, 77, 77, 70, 14, 2, 20, 34, 50, 22, 141, 70, 158, 158, 162, 155, 161, 158, 50, 150, 155, 141, 39, 109, 85, 28, 41, 75, 44, 
+#> 128, 136, 134, 146, 152, 150, 122, 142, 85, 50, 87, 142, 86, 49, 55, 105, 106, 162, 146, 124, 158, 153, 64, 4, 47, 86, 91, 38, 16, 11, 54, 67, 72, 72, 65, 72, 72, 43, 44, 31, 15, 20, 158, 134, 159, 132, 9, 84, 21, 14, 27, 42, 40, 35, 38, 8, 7, 6, 10, 16, 55, 128, 145, 116, 153, 70, 103, 8, 146, 110, 150, 32, 24, 3, 30, 159, 161, 134, 156, 154, 149, 108, 158, 157, 131, 77, 130, 67, 83, 140, 153, 124, 152, 144, 110, 87, 126, 147, 85, 8, 97, 140, 146, 160, 130, 158, 150, 153, 154, 113, 119, 73, 68, 
+#> 68, 145, 102, 152, 141, 116, 22, 32, 28, 32, 33, 25, 15, 13, 20, 12, 24, 35, 36, 33, 5, 26, 6, 8, 15, 86, 10, 130, 89, 125, 128, 150, 159, 151, 149, 109, 150, 145, 146, 90, 137, 142, 146, 30, 15, 27, 45, 34, 33, 34, 33, 34, 25, 29, 21, 46, 135, 158, 159, 106, 22, 32, 65, 45, 135, 114, 150, 18, 57, 5, 63, 11, 151, 84, 96, 93, 145, 97, 9, 61, 27, 3, 120, 162, 159, 145, 49, 106, 151, 95, 123, 70, 68, 146, 145, 162, 162, 54, 78, 103, 54, 156, 158, 156, 123, 15, 123, 111, 66, 53, 79, 128, 149, 96, 140, 
+#> 149, 155, 126, 135, 125, 113, 42, 12, 49, 141, 147, 153, 147, 73, 56, 99, 127, 145, 159, 151, 120, 19, 73, 132, 140, 153, 91, 102, 21, 86, 154, 154, 105, 155, 133, 101, 107, 77, 152, 138, 126, 159, 158, 156, 156, 156, 149, 143, 111, 154, 124, 156, 161, 148, 143, 89, 10, 16, 134, 105, 115, 120, 23, 15, 59, 151, 152, 154, 162, 157, 158, 159, 162, 58, 98, 158, 156, 152, 154, 142, 8, 92, 78, 108, 147, 150, 157, 158, 142, 135, 87, 75, 31, 61, 17, 62, 40, 6, 26, 49, 142, 143, 156, 151, 137, 155, 158, 152, 
+#> 151, 122, 152, 149, 149, 144, 126, 81, 14, 104, 135, 109, 135, 100, 145, 72, 146, 140, 109, 137, 139, 81, 9, 13, 6, 32, 33, 33, 11, 14, 11, 29, 29, 32, 29, 32, 6, 5, 19, 20, 4, 78, 73, 69, 64, 68, 68, 70, 48, 66, 67, 62, 1, 19, 31, 32, 30, 34, 16, 17, 34, 34, 33, 10, 19, 7, 12, 29, 24, 30, 31, 33, 14, 33, 24, 34, 34, 13, 28, 33, 32, 1, 4, 28, 35, 34, 3, 54, 142, 135, 131, 157, 139, 107, 149, 126, 119, 51, 35, 1, 86, 144, 139, 51, 132, 142, 137, 133, 103, 131, 131, 109, 39, 68, 28, 35, 21, 36, 35, 
+#> 35, 33, 32, 30, 20, 15, 24, 17, 9, 12, 69, 74, 68, 76, 6, 9, 67, 69, 48, 63, 64, 44, 62, 40, 58, 28, 33, 62, 19, 88, 159, 144, 162, 160, 143, 152, 71, 80, 153, 129, 4, 49, 127, 131, 150, 127, 85, 30, 28, 8, 126, 89, 132, 117, 70, 134, 133, 107, 57, 44, 30, 7, 87, 160, 158, 158, 157, 160, 160, 150, 161, 161, 148, 159, 119, 127, 152, 150, 140, 158, 153, 162, 102, 59, 162, 115, 160, 157, 155, 66, 81, 15, 40, 30, 21, 35, 44, 46, 40, 39, 38, 17, 3, 25, 7, 17, 21, 10, 49, 85, 59, 79, 148, 85, 71, 154, 
+#> 43, 100, 85, 66, 4, 109, 16, 32, 75, 38, 112, 159, 143, 138, 156, 155, 159, 59, 39, 17, 77, 91, 47, 145, 146, 161, 145, 159, 155, 154, 145, 150, 148, 149, 141, 143, 143, 145, 150, 64, 2, 106, 156, 160, 160, 159, 162, 156, 155, 135, 157, 159, 156, 21, 126, 6, 36, 34, 125, 149, 147, 52, 91, 132, 124, 119, 21, 46, 45, 88, 118, 144, 53, 94, 122, 126, 86, 43, 110, 142, 141, 153, 132, 122, 90, 118, 153, 152, 120, 142, 158, 123, 117, 18, 76, 136, 116, 4, 4, 19, 1, 1, 54, 64, 26, 69, 71, 74, 16, 38, 49, 
+#> 23, 29, 35, 33, 33, 34, 34, 1, 78, 153, 156, 51, 105, 123, 148, 133, 150, 121, 81, 137, 134, 116, 86, 30, 40, 74, 141, 157, 157, 163, 135, 81, 69, 134, 127, 25, 135, 49, 8, 8, 23, 13, 4, 32, 35, 34, 33, 11, 21, 31, 32, 32, 35, 33, 30, 15, 15, 8, 5, 59, 69, 66, 69, 64, 76, 70, 53, 31, 42, 78, 23, 25, 69, 60, 2, 30, 32, 33, 35, 33, 34, 33, 34, 32, 20, 2, 158, 154, 153, 151, 142, 92, 64, 93, 86, 128, 105, 132, 122, 160, 159, 161, 160, 159, 161, 160, 157, 156, 7, 17, 53, 151, 144, 132, 150, 47, 97, 90, 
+#> 35, 131, 140, 109, 146, 138, 137, 82, 147, 113, 120, 158, 43, 94, 147, 160, 132, 159, 156, 115, 103, 83, 131, 155, 34, 73, 59, 130, 139, 145, 138, 143, 128, 121, 102, 140, 135, 121, 125, 155, 158, 139, 93, 63, 158, 124, 157, 141, 156, 73, 6, 32, 32, 31, 34, 37, 37, 38, 35, 42, 25, 35, 69, 53, 161, 153, 160, 159, 36, 133, 126, 160, 93, 143, 47, 69, 69, 160, 154, 160, 160, 144, 157, 102, 156, 112, 134, 38, 34, 114, 156, 158, 153, 160, 132, 152, 153, 159, 136, 85, 37, 145, 32, 73, 17, 59, 59, 67, 66, 
+#> 65, 63, 70, 61, 66, 37, 22, 22, 75, 40, 131, 142, 79, 18, 148, 139, 135, 144, 153, 160, 85, 4, 18, 16, 110, 144, 127, 152, 142, 54, 155, 104, 126, 48, 136, 50, 33, 33, 31, 30, 31, 28, 34, 18, 17, 34, 34, 33, 28, 32, 8, 29, 17, 32, 27, 30, 32, 37, 29, 3, 13, 17, 19, 32, 10, 13, 20, 12, 19, 72, 44, 147, 145, 145, 136, 102, 120, 42, 80, 28, 43, 158, 162, 162, 157, 106, 33, 71, 52, 60, 39, 58, 121, 151, 155, 143, 97, 125, 133, 127, 111, 129, 70, 162, 162, 155, 82, 75, 124, 15, 153, 148, 59, 22, 10, 119, 
+#> 63, 126, 93, 140, 157, 109, 161, 152, 144, 105, 108, 14, 158, 154, 156, 154, 158, 158, 162, 137, 155, 88, 142, 156, 160, 138, 144, 39, 157, 158, 159, 162, 161, 162, 162, 162, 42, 158, 4, 50, 84, 92, 150, 159, 147, 126, 108, 106, 122, 60, 74, 42, 74, 26, 30, 63, 26, 54, 34, 31, 59, 26, 38, 70, 62, 37, 25, 68, 30, 42, 72, 76, 81, 68, 50, 47, 3, 54, 64, 72, 68, 47, 29, 60, 60, 57, 40, 18, 54, 29, 61, 44, 65, 74, 52, 60, 75, 71, 20, 21, 31, 139, 157, 154, 75, 159, 141, 160, 135, 93, 113, 151, 158, 157, 
+#> 150, 154, 61, 135, 140, 35, 36, 4, 41, 27, 34, 6, 6, 22, 20, 1, 8, 1, 73, 68, 22, 11, 32, 72, 69, 18, 10, 16, 30, 32, 33, 31, 18, 11, 13, 27, 26, 23, 30, 36, 32, 34, 33, 31, 33, 30, 20, 12, 2, 9, 33, 32, 33, 20, 31, 22, 12, 13, 15, 35, 33, 34, 13, 6, 78, 80, 70, 78, 66, 72, 67, 50, 25, 11, 24, 34, 33, 33, 33, 33, 32, 34, 16, 16, 43, 156, 161, 162, 160, 160, 159, 123, 36, 157, 159, 156, 11, 112, 6, 6, 149, 158, 141, 153, 155, 150, 147, 151, 121, 148, 51, 114, 129, 111, 124, 140, 136, 139, 138, 136, 
+#> 110, 136, 41, 106, 137, 152, 84, 45, 85, 81, 55, 34, 146, 79, 36, 21, 153, 131, 146, 156, 147, 132, 53, 101, 122, 30, 33, 38, 72, 18, 73, 158, 142, 63, 96, 145, 123, 157, 132, 149, 82, 124, 149, 149, 92, 133, 81, 56, 15, 12, 33, 32, 32, 31, 33, 33, 21, 11, 32, 122, 157, 151, 133, 74, 160, 162, 160, 1, 11, 18, 141, 102, 105, 125, 52, 47, 54, 14, 10, 78, 39, 111, 113, 162, 157, 154, 68, 63, 151, 154, 110, 40, 157, 150, 52, 90, 156, 89, 133, 121, 148, 151, 89, 50, 57, 81, 130, 99, 131, 118, 86, 82, 
+#> 50, 23, 39, 8, 15, 19, 120, 152, 139, 59, 77, 38, 101, 125, 38, 112, 63, 151, 152, 156, 151, 143, 109, 156, 154, 130, 31, 116, 105, 69, 105, 155, 160, 55, 158, 138, 33, 104, 156, 87, 133, 116, 10, 8, 24, 33, 3, 52, 32, 33, 33, 29, 13, 24, 29, 32, 32, 32, 41, 132, 119, 149, 151, 162, 160, 159, 137, 28, 32, 34, 35, 35, 33, 32, 30, 34, 33, 33, 31, 31, 33, 32, 32, 20, 157, 162, 106, 157, 142, 101, 145, 147, 61, 95, 17, 105, 138, 157, 141, 53, 105, 155, 130, 106, 46, 95, 52, 98, 155, 159, 162, 161, 106, 
+#> 73, 150, 154, 3, 61, 37, 25, 40, 37, 33, 35, 32, 7, 130, 109, 144, 149, 144, 77, 51, 27, 17, 42, 22, 81, 74, 68, 67, 64, 73, 69, 13, 68, 47, 42, 19, 30, 10, 128, 91, 65, 39, 70, 125, 148, 18, 89, 88, 151, 150, 125, 93, 143, 96, 149, 126, 153, 141, 160, 139, 135, 149, 142, 130, 142, 6, 38, 41, 32, 32, 32, 20, 46, 69, 74, 62, 59, 21, 163, 162, 162, 51, 143, 93, 142, 145, 141, 34, 6, 28, 14, 29, 31, 26, 12, 22, 26, 29, 31, 24, 33, 36, 34, 34, 27, 29, 35, 34, 23, 7, 35, 33, 29, 21, 31, 24, 12, 31, 30, 
+#> 31, 34, 34, 33, 33, 31, 34, 31, 7, 43, 100, 134, 153, 152, 92, 40, 41, 59, 85, 89, 145, 127, 135, 110, 70, 153, 21, 24, 9, 6, 32, 35, 35, 34, 40, 36, 34, 36, 32, 32, 15, 25, 155, 101, 151, 122, 143, 47, 126, 91, 87, 41, 16, 13, 23, 12, 11, 117, 142, 107, 21, 113, 161, 149, 92, 118, 155, 153, 24, 151, 131, 150, 161, 111, 162, 62, 158, 6, 14, 2, 91, 8, 66, 145, 151, 120, 33, 121, 130, 94, 83, 9, 14, 24, 27, 32, 35, 37, 49, 52, 45, 45, 35, 32, 33, 23, 31, 30, 21, 32, 33, 11, 40, 6, 7, 53, 71, 14, 77, 
+#> 64, 42, 69, 68, 64, 6, 20, 70, 64, 8, 6, 30, 30, 18, 7, 108, 45, 148, 148, 147, 150, 136, 148, 156, 158, 158, 158, 158, 154, 154, 159, 146, 158, 159, 161, 154, 136, 48, 4, 67, 20, 4, 31, 33, 33, 33, 33, 33, 33, 8, 41, 96, 31, 128, 108, 124, 159, 109, 159, 152, 17, 70, 97, 144, 138, 134, 121, 33, 145, 153, 18, 158, 74, 134, 149, 111, 22, 31, 32, 33, 34, 35, 27, 34, 96, 130, 139, 144, 148, 26, 75, 151, 134, 49, 74, 151, 161, 156, 156, 104, 147, 161, 157, 161, 160, 160, 104, 160, 155, 156, 34, 79, 98, 
+#> 137, 138, 143, 141, 138, 156, 156, 120, 133, 141, 133, 156, 104, 46, 55, 100, 92, 124, 159, 158, 159, 161, 162, 151, 151, 7, 50, 74, 75, 62, 13, 49, 13, 60, 10, 29, 31, 32, 13, 29, 21, 79, 63, 68, 63, 61, 29, 104, 141, 116, 102, 124, 67, 9, 47, 159, 158, 141, 160, 136, 156, 160, 61, 155, 157, 45, 114, 131, 97, 151, 143, 136, 97, 49, 143, 43, 108, 138, 133, 159, 150, 149, 154, 150, 6, 11, 3, 33, 9, 3, 64, 30, 162, 152, 108, 153, 40, 84, 151, 80, 23, 83, 52, 6, 130, 150, 129, 154, 147, 155, 113, 88, 
+#> 139, 158, 41, 153, 152, 117, 108, 141, 157, 126, 4, 38, 25, 9, 1, 32, 35, 27, 33, 34, 34, 35, 33, 20, 27, 39, 63, 48, 38, 73, 72, 39, 76, 68, 69, 14, 54, 5, 23, 32, 34, 31, 27, 11, 23, 21, 11, 27, 29, 87, 156, 114, 109, 149, 124, 35, 151, 146, 115, 101, 129, 158, 159, 141, 114, 110, 141, 149, 152, 136, 57, 6, 87, 151, 43, 154, 152, 140, 127, 30, 143, 156, 141, 72, 22, 2, 15, 8, 91, 156, 161, 113, 161, 141, 58, 77, 156, 108, 154, 158, 157, 157, 146, 157, 142, 128, 158, 104, 149, 154, 27, 48, 137, 
+#> 118, 117, 104, 145, 144, 150, 113, 95, 61, 127, 5, 40, 139, 157, 157, 159, 139, 118, 100, 153, 7, 9, 33, 114, 130, 137, 131, 128, 140, 136, 134, 138, 128, 129, 135, 134, 72, 30, 113, 12, 16, 142, 144, 102, 133, 114, 136, 145, 111, 24, 68, 9, 26, 108, 101, 148, 157, 155, 160, 137, 157, 12, 5, 28, 30, 34, 23, 21, 154, 154, 130, 158, 154, 156, 12, 43, 43, 22, 37, 73, 64, 43, 17, 31, 31, 33, 32, 32, 33, 34, 128, 152, 159, 131, 158, 51, 156, 82, 162, 39, 76, 138, 150, 142, 48, 145, 160, 109, 159, 133, 
+#> 111, 157, 58, 153, 137, 97, 94, 137, 147, 148, 41, 74, 49, 157, 146, 147, 15, 19, 30, 88, 87, 60, 28, 8, 11, 80, 113, 45, 31, 28, 139, 160, 127, 160, 7, 114, 157, 158, 154, 95, 74, 149, 152, 122, 150, 8, 41, 35, 115, 126, 150, 144, 71, 153, 157, 139, 101, 130, 49, 117, 43, 6, 61, 115, 133, 140, 49, 87, 160, 140, 160, 7, 31, 31, 30, 18, 14, 4, 4, 20, 30, 34, 9, 116, 157, 155, 22, 92, 160, 60, 49, 3, 12, 26, 36, 32, 53, 155, 160, 159, 161, 17, 33, 30, 33, 37, 81, 109, 149, 150, 121, 116, 143, 62, 144, 
+#> 126, 100, 150, 123, 116, 145, 74, 4, 20, 35, 32, 31, 34, 36, 145, 154, 23, 31, 57, 147, 152, 158, 154, 43, 88, 135, 95, 28, 72, 114, 149, 151, 156, 137, 17, 110, 159, 129, 133, 137, 151, 98, 153, 80, 9, 38, 145, 158, 155, 158, 162, 148, 10, 27, 29, 18, 22, 24, 5, 9, 26, 33, 1, 108, 151, 129, 135, 51, 101, 102, 57, 21, 58, 127, 159, 56, 87, 38, 148, 145, 31, 137, 75, 157, 47, 135, 135, 153, 66, 143, 149, 153, 143, 14, 75, 158, 158, 158, 49, 155, 109, 156, 161, 143, 130, 99, 151, 57, 43, 27, 152, 51, 
+#> 134, 156, 39, 59, 158, 53, 113, 86, 123, 158, 18, 144, 156) x c(245, 289, 182, 259, 236, 257, 282, 10, 30, 162, 23, 49, 181, 271, 308, 305, 261, 257, 409, 374, 361, 379, 442, 490, 411, 487, 478, 513, 486, 273, 121, 206, 340, 332, 316, 297, 343, 370, 211, 327, 340, 21, 270, 326, 381, 361, 249, 253, 175, 79, 122, 154, 96, 76, 297, 206, 579, 517, 529, 534, 577, 521, 419, 43, 152, 189, 259, 210, 166, 205, 191, 181, 149, 92, 21, 29, 117, 79, 11, 84, 283, 210, 215, 205, 262, 173, 187, 57, 101, 131, 55, 103, 284, 220, 256, 212, 186, 179, 144, 138, 8, 298, 584, 596, 
+#> 536, 612, 560, 539, 531, 527, 550, 568, 588, 181, 285, 46, 40, 1, 65, 174, 196, 187, 186, 140, 180, 153, 154, 148, 124, 153, 148, 137, 148, 120, 104, 125, 115, 107, 55, 25, 16, 175, 545, 608, 312, 451, 544, 348, 4, 485, 553, 249, 602, 509, 581, 469, 591, 315, 448, 465, 419, 490, 426, 6, 34, 81, 98, 3, 112, 115, 139, 116, 86, 101, 91, 75, 9, 11, 130, 127, 124, 133, 127, 91, 107, 129, 95, 107, 112, 110, 103, 105, 51, 5, 17, 465, 597, 498, 405, 474, 524, 527, 522, 384, 146, 291, 206, 567, 542, 602, 
+#> 259, 408, 38, 560, 534, 288, 165, 561, 570, 547, 69, 359, 5, 138, 287, 258, 288, 268, 266, 317, 299, 313, 17, 226, 237, 212, 69, 2, 74, 238, 367, 263, 111, 371, 323, 387, 329, 430, 265, 142, 256, 91, 0, 0, 127, 389, 515, 555, 550, 562, 575, 563, 582, 591, 589, 588, 574, 581, 609, 582, 612, 322, 104, 2, 635, 581, 596, 588, 310, 562, 41, 58, 99, 154, 157, 84, 138, 158, 136, 32, 16, 11, 0, 4, 103, 114, 76, 97, 100, 114, 97, 80, 36, 103, 13, 13, 135, 161, 124, 140, 130, 91, 109, 82, 45, 69, 60, 13, 12, 
+#> 0, 2, 150, 358, 605, 581, 573, 506, 591, 553, 428, 345, 563, 542, 588, 421, 497, 428, 507, 526, 556, 625, 415, 233, 490, 353, 13, 98, 149, 516, 593, 577, 485, 550, 494, 511, 541, 587, 476, 538, 487, 403, 508, 410, 323, 147, 73, 13, 18, 10, 98, 474, 525, 498, 491, 534, 491, 493, 260, 436, 210, 16, 2, 295, 235, 178, 406, 402, 331, 405, 328, 449, 234, 234, 227, 108, 162, 248, 221, 51, 256, 431, 491, 452, 380, 343, 334, 424, 297, 241, 80, 252, 209, 266, 276, 476, 143, 496, 236, 132, 606, 121, 593, 222, 
+#> 12, 244, 31, 310, 550, 517, 518, 599, 602, 399, 527, 459, 427, 278, 525, 417, 501, 551, 550, 429, 392, 13, 2, 2, 77, 89, 93, 98, 85, 121, 125, 103, 91, 31, 54, 19, 59, 82, 16, 97, 117, 101, 110, 104, 102, 87, 34, 42, 11, 237, 588, 571, 527, 549, 534, 512, 490, 548, 516, 515, 568, 495, 556, 473, 558, 413, 552, 566, 432, 230, 86, 173, 348, 566, 488, 603, 437, 451, 489, 447, 533, 549, 544, 554, 583, 375, 369, 90, 464, 532, 340, 533, 508, 416, 463, 433, 155, 478, 446, 491, 278, 241, 83, 183, 3, 0, 117, 
+#> 134, 88, 107, 150, 128, 148, 131, 115, 103, 103, 103, 66, 110, 83, 63, 99, 86, 56, 67, 55, 29, 12, 74, 92, 33, 3, 84, 493, 563, 342, 386, 538, 559, 577, 553, 497, 465, 550, 230, 177, 149, 103, 267, 15, 23, 330, 571, 581, 493, 543, 534, 526, 521, 545, 564, 330, 518, 602, 526, 598, 505, 556, 425, 375, 226, 33, 7, 2, 109, 149, 280, 342, 232, 266, 256, 178, 95, 63, 33, 12, 2, 91, 394, 407, 257, 216, 88, 1, 19, 116, 544, 538, 500, 580, 520, 571, 547, 546, 523, 471, 494, 552, 506, 426, 574, 486, 429, 539, 
+#> 523, 191, 99, 120, 134, 129, 126, 73, 123, 89, 96, 86, 94, 90, 76, 60, 93, 81, 38, 36, 79, 101, 137, 128, 144, 134, 136, 147, 142, 130, 150, 125, 64, 111, 108, 93, 113, 97, 103, 46, 120, 126, 155, 135, 142, 157, 125, 126, 129, 98, 90, 20, 21, 77, 10, 7, 55, 69, 88, 124, 56, 43, 54, 6, 422, 192, 137, 194, 505, 68, 532, 496, 561, 511, 597, 596, 561, 550, 581, 500, 509, 506, 402, 84, 134, 22, 135, 259, 382, 486, 510, 482, 311, 300, 118, 274, 351, 84, 82, 2, 1, 7, 39, 83, 103, 53, 114, 97, 85, 22, 9, 
+#> 92, 89, 63, 56, 55, 11, 31, 9, 147, 192, 149, 241, 240, 441, 451, 392, 474, 382, 452, 324, 295, 88, 5, 24, 0, 10, 406, 160, 374, 514, 507, 579, 499, 476, 547, 583, 587, 529, 386, 265, 97, 456, 577, 335, 72, 16, 3, 60, 72, 87, 88, 84, 98, 16, 59, 87, 7, 2, 26, 287, 195, 470, 411, 527, 477, 512, 125, 53, 83, 515, 346, 16, 27, 115, 208, 101, 256, 180, 297, 139, 53, 3, 0, 82, 176, 215, 229, 351, 351, 258, 137, 42, 67, 48, 220, 83, 132, 141, 110, 3, 11, 75, 61, 44, 113, 2, 120, 79, 92, 99, 100, 50, 93, 
+#> 93, 79, 60, 78, 62, 60, 43, 39, 0, 20, 42, 261, 313, 387, 385, 368, 248, 309, 205, 2, 22, 26, 58, 364, 603, 563, 503, 508, 522, 519, 445, 464, 470, 544, 571, 419, 246, 137, 400, 163, 4, 91, 79, 5, 15, 42, 13, 31, 541, 561, 592, 577, 564, 570, 360, 553, 504, 567, 330, 234, 1, 252, 275, 503, 394, 241, 400, 300, 291, 297, 186, 120, 238, 5, 85, 97, 99, 19, 34, 20, 18, 71, 14, 23, 17, 75, 571, 572, 528, 453, 158, 303, 592, 538, 65, 516, 570, 333, 188, 355, 380, 351, 313, 435, 468, 331, 247, 184, 129, 
+#> 118, 31, 124, 17, 220, 365, 391, 371, 378, 381, 289, 239, 132, 68, 138, 102, 103, 137, 130, 138, 139, 10, 70, 118, 95, 85, 111, 65, 79, 15, 50, 94, 86, 41, 4, 552, 573, 559, 508, 474, 544, 478, 468, 396, 537, 553, 516, 610, 500, 405, 227, 377, 570, 575, 526, 558, 482, 539, 591, 38, 441, 476, 257, 381, 471, 13, 46, 268, 537, 570, 425, 314, 541, 257, 573, 505, 386, 76, 52, 1, 54, 27, 104, 96, 105, 84, 8, 55, 63, 75, 76, 23, 59, 95, 63, 86, 11, 22, 46, 73, 468, 568, 543, 576, 456, 512, 567, 423, 440, 
+#> 559, 584, 537, 607, 581, 155, 127, 0, 10, 37, 413, 492, 517, 473, 553, 430, 493, 501, 463, 524, 597, 586, 470, 79, 50, 104, 149, 186, 229, 151, 120, 100, 350, 292, 364, 186, 98, 62, 379, 10, 263, 5, 56, 32, 385, 526, 430, 491, 261, 504, 365, 267, 8, 8, 9, 113, 183, 335, 535, 557, 447, 564, 520, 398, 151, 585, 463, 444, 50, 395, 322, 506, 560, 540, 454, 451, 328, 555, 546, 461, 270, 487, 92, 529, 569, 536, 544, 583, 580, 580, 348, 355, 82, 95, 117, 103, 94, 61, 22, 207, 307, 359, 338, 316, 225, 330, 
+#> 387, 424, 408, 272, 356, 167, 285, 264, 245, 249, 92, 76, 21, 32, 106, 86, 17, 27, 52, 82, 40, 84, 125, 15, 57, 27, 135, 409, 487, 442, 483, 455, 467, 248, 194, 330, 388, 108, 70, 492, 506, 503, 132, 277, 50, 6, 436, 525, 499, 522, 448, 503, 426, 214, 45, 102, 606, 534, 453, 535, 533, 528, 568, 362, 409, 536, 583, 568, 600, 349, 566, 616, 411, 247, 63, 401, 392, 413, 410, 424, 333, 394, 485, 416, 442, 382, 153, 343, 226, 26, 1, 2, 83, 68, 53, 85, 104, 43, 71, 57, 82, 19, 50, 86, 571, 586, 509, 604, 
+#> 561, 38, 480, 493, 612, 672, 581, 594, 266, 234, 29, 366, 560, 558, 562, 571, 478, 67, 57, 310, 307, 237, 339, 347, 399, 323, 245, 364, 295, 260, 171, 192, 146, 10, 1, 17, 51, 605, 561, 622, 623, 597, 465, 534, 631, 605, 631, 614, 336, 349, 47, 129, 21, 2, 187, 548, 530, 158, 404, 284, 85, 74, 71, 12, 97, 86, 95, 52, 42, 48, 397, 2, 455, 587, 553, 599, 493, 448, 550, 357, 426, 465, 559, 65, 35, 35, 18, 21, 326, 473, 406, 313, 112, 92, 154, 264, 309, 318, 402, 354, 325, 148, 194, 563, 477, 478, 499, 
+#> 335, 442, 171, 606, 651, 444, 319, 479, 453, 375, 515, 358, 17, 259, 451, 519, 537, 497, 498, 21, 166, 62, 156, 94, 518, 405, 468, 351, 435, 590, 562, 584, 535, 558, 314, 336, 492, 238, 65, 17, 1, 20, 92, 110, 31, 2, 63, 60, 11, 17, 2, 13, 274, 580, 539, 452, 511, 631, 582, 586, 636, 649, 613, 614, 491, 49, 629, 431, 10, 92, 136, 123, 317, 432, 457, 540, 406, 522, 529, 359, 495, 540, 536, 499, 518, 534, 457, 459, 365, 72, 160, 130, 380, 294, 247, 482, 290, 498, 579, 281, 280, 417, 473, 275, 193, 
+#> 305, 57, 495, 523, 416, 512, 589, 592, 623, 424, 536, 504, 527, 568, 486, 602, 104, 357, 58, 9, 83, 23, 24, 5, 56, 14, 97, 4, 96, 5, 366, 316, 349, 154, 219, 214, 164, 221, 48, 122, 191, 114, 16, 25, 2, 256, 544, 587, 532, 96, 0, 500, 36, 230, 47, 523, 533, 541, 563, 582, 447, 420, 571, 629, 427, 546, 575, 206, 502, 556, 7, 72, 51, 85, 71, 13, 53, 91, 86, 67, 57, 112, 86, 99, 112, 109, 508, 375, 570, 346, 563, 446, 433, 435, 29, 193, 16, 268, 360, 299, 320, 286, 409, 331, 315, 191, 133, 10, 166, 
+#> 551, 272, 69, 522, 435, 504, 579, 418, 165, 527, 483, 540, 563, 570, 163, 450, 376, 6, 427, 587, 620, 593, 564, 599, 588, 468, 244, 485, 521, 629, 610, 599, 542, 100, 324, 538, 296, 23, 13, 26, 92, 60, 79, 103, 95, 101, 113, 122, 108, 107, 104, 82, 18, 4, 27, 215, 234, 269, 386, 378, 370, 359, 398, 489, 335, 392, 330, 307, 91, 191, 24, 255, 584, 524, 590, 586, 530, 566, 575, 559, 474, 491, 536, 419, 602, 576, 476, 442, 1, 75, 49, 21, 30, 21, 97, 86, 104, 100, 96, 98, 102, 41, 509, 430, 301, 558, 
+#> 592, 260, 286, 357, 592, 583, 566, 581, 487, 463, 512, 488, 350, 499, 143, 17, 69, 90, 69, 111, 114, 93, 126, 124, 96, 81, 96, 131, 91, 16, 57, 76, 44, 20, 5, 2, 7, 0, 45, 236, 0, 340, 570, 540, 552, 543, 446, 453, 534, 577, 520, 568, 523, 422, 147, 217, 17, 365, 227, 509, 564, 481, 492, 639, 587, 581, 603, 561, 615, 8, 22, 43, 227, 605, 412, 471, 407, 512, 582, 549, 618, 330, 124, 6, 1, 1, 17, 48, 101, 18, 120, 108, 92, 77, 68, 11, 90, 81, 59, 23, 8, 197, 586, 23, 557, 624, 561, 633, 595, 646, 649, 
+#> 641, 603, 616, 616, 593, 413, 288, 85, 335, 5, 90, 108, 99, 89, 131, 76, 42, 20, 7, 75, 97, 110, 94, 111, 116, 99, 79, 82, 81, 82, 6, 19, 21, 45, 34, 58, 80, 104, 115, 80, 67, 64, 76, 54, 0, 539, 359, 366, 528, 443, 507, 569, 576, 557, 533, 548, 60, 103, 143, 6, 184, 183, 323, 267, 310, 393, 152, 335, 177, 87, 26, 474, 489, 581, 504, 559, 596, 526, 500, 372, 55, 84, 63, 69, 24, 54, 104, 108, 125, 69, 54, 77, 60, 37, 70, 78, 49, 53, 18, 18, 38, 77, 107, 104, 53, 45, 109, 143, 92, 27, 83, 16, 98, 32, 
+#> 27, 34, 190, 440, 618, 514, 641, 603, 502, 545, 617, 547, 527, 540, 518, 486, 585, 550, 354, 303, 32, 38, 76, 7, 23, 107, 590, 587, 592, 560, 571, 586, 499, 222, 402, 577, 166, 188, 202, 164, 469, 310, 478, 550, 632, 614, 499, 282, 126, 68, 28, 40, 70, 95, 63, 35, 97, 89, 98, 63, 57, 51, 5, 1, 7, 13, 58, 45, 134, 411, 387, 491, 461, 341, 252, 644, 610, 404, 434, 387, 312, 125, 17, 4, 70, 74, 49, 100, 80, 98, 5, 102, 120, 95, 113, 124, 102, 49, 30, 4, 5, 15, 51, 94, 94, 101, 95, 81, 61, 51, 47, 39, 
+#> 38, 54, 20, 53, 47, 26, 55, 97, 94, 47, 101, 101, 109, 107, 84, 103, 84, 81, 104, 65, 55, 40, 34, 35, 44, 24, 3, 92, 104, 97, 125, 117, 62, 108, 21, 92, 80, 31, 479, 545, 587, 349, 523, 610, 588, 577, 569, 589, 178, 574, 443, 272, 20, 18, 218, 305, 492, 538, 505, 500, 392, 140, 148, 137, 29, 76, 38, 47, 1, 182, 451, 556, 286, 537, 543, 602, 455, 524, 570, 573, 502, 505, 558, 453, 459, 31, 43, 32, 94, 109, 144, 107, 101, 132, 79, 98, 108, 117, 90, 55, 0, 5, 20, 5, 21, 12, 14, 69, 91, 105, 74, 102, 
+#> 112, 126, 88, 34, 46, 68, 46, 19, 3, 70, 572, 558, 553, 594, 608, 578, 569, 588, 578, 353, 484, 503, 524, 22, 141, 44, 533, 562, 593, 563, 542, 519, 524, 543, 547, 463, 429, 531, 570, 384, 267, 8, 132, 3, 0, 8, 113, 125, 270, 260, 392, 452, 183, 22, 317, 492, 178, 133, 52, 248, 249, 174, 67, 163, 67, 123, 10, 2, 2, 28, 32, 64, 111, 86, 104, 73, 102, 78, 83, 67, 54, 75, 30, 25, 19, 7, 1, 3, 42, 101, 115, 77, 73, 39, 13, 43, 5, 3, 1, 0, 89, 83, 106, 98, 55, 90, 96, 74, 89, 67, 56, 28, 4, 15, 17, 41, 
+#> 336, 393, 502, 521, 493, 622, 591, 405, 516, 376, 453, 522, 542, 543, 442, 74, 291, 108, 112, 15, 2, 77, 388, 372, 383, 379, 344, 174, 200, 68, 145, 345, 35, 416, 17, 370, 536, 567, 644, 594, 557, 555, 489, 433, 364, 366, 43, 16, 79, 0, 122, 84, 61, 92, 50, 60, 56, 44, 15, 9, 56, 6, 18, 8, 24, 75, 77, 85, 65, 83, 101, 99, 85, 69, 74, 51, 60, 66, 53, 21, 14, 8, 327, 596, 411, 385, 469, 537, 551, 431, 555, 195, 122, 523, 511, 465, 52, 19, 571, 616, 545, 591, 574, 573, 569, 540, 497, 615, 513, 624, 
+#> 444, 204, 12, 72, 231, 354, 398, 284, 449, 388, 22, 508, 380, 406, 490, 438, 413, 424, 356, 299, 306, 64, 150, 61, 379, 402, 522, 487, 503, 518, 220, 476, 570, 507, 501, 285, 320, 319, 127, 184, 59, 14, 17, 6, 233, 261, 358, 361, 449, 501, 393, 368, 428, 350, 188, 198, 83, 50, 136, 63, 57, 420, 370, 432, 468, 514, 487, 459, 518, 429, 437, 411, 126, 98, 594, 654, 583, 406, 464, 581, 554, 513, 670, 605, 558, 525, 568, 419, 470, 330, 21, 81, 24, 133, 6, 50, 358, 600, 579, 601, 568, 581, 456, 553, 396, 
+#> 188, 591, 572, 549, 614, 590, 572, 181, 57, 5, 77, 97, 104, 110, 91, 91, 122, 33, 73, 91, 97, 82, 70, 57, 72, 61, 75, 74, 67, 14, 3, 0, 40, 466, 617, 614, 285, 499, 509, 642, 613, 446, 262, 559, 157, 223, 567, 406, 253, 616, 614, 458, 570, 407, 25, 532, 268, 446, 192, 25, 151, 523, 528, 619, 603, 574, 576, 560, 487, 382, 311, 549, 556, 399, 544, 109, 36, 262, 229, 234, 191, 34, 59, 111, 329, 292, 189, 85, 58, 145, 10, 38, 88, 96, 73, 109, 106, 64, 48, 60, 10, 33, 2, 2, 3, 478, 392, 479, 407, 505, 
+#> 470, 56, 60, 244, 558, 551, 462, 488, 603, 549, 209, 4, 9, 49, 544, 528, 509, 480, 540, 552, 523, 331, 59, 410, 524, 447, 386, 18, 308, 422, 278, 498, 593, 638, 574, 198, 356, 616, 625, 658, 556, 479, 313, 466, 51, 13, 12, 33, 326, 458, 546, 385, 605, 600, 16, 503, 35, 65, 81, 80, 88, 102, 110, 115, 107, 105, 37, 89, 80, 91, 54, 67, 53, 45, 86, 71, 83, 83, 78, 86, 102, 75, 19, 4, 10, 383, 180, 529, 551, 520, 574, 585, 395, 481, 360, 172, 20, 49, 5, 43, 85, 34, 56, 5, 76, 93, 96, 67, 25, 19, 39, 20, 
+#> 2, 50, 97, 91, 81, 67, 13, 12, 26, 12, 437, 572, 584, 562, 553, 581, 619, 596, 593, 579, 535, 579, 569, 576, 28, 589, 570, 404, 545, 571, 484, 510, 523, 438, 477, 537, 446, 120, 39, 44, 1, 38, 43, 99, 92, 84, 75, 79, 76, 99, 109, 76, 46, 16, 30, 43, 6, 31, 32, 56, 54, 39, 48, 12, 3, 86, 95, 96, 98, 56, 87, 13, 42, 42, 38, 3, 0, 58, 4, 4, 13, 91, 122, 73, 96, 80, 90, 76, 85, 40, 69, 15, 67, 48, 57, 31, 33, 1, 108, 94, 72, 99, 74, 74, 61, 114, 87, 69, 65, 45, 27, 30, 19, 33, 30, 22, 536, 623, 602, 
+#> 596, 589, 559, 630, 618, 599, 549, 585, 619, 625, 461, 238, 35, 294, 333, 225, 136, 7, 0, 7, 163, 489, 225, 580, 568, 607, 633, 611, 643, 475, 602, 596, 229, 252, 280, 335, 279, 443, 70, 411, 394, 362, 383, 274, 369, 277, 290, 230, 87, 2, 3, 37, 629, 659, 662, 260, 681, 565, 500, 611, 537, 414, 537, 619, 379, 166, 51, 164, 4, 287, 14, 14, 19, 38, 23, 22, 80, 96, 25, 76, 88, 122, 102, 30, 32, 93, 20, 4, 91, 69, 19, 38, 31, 33, 58, 78, 18, 50, 112, 86, 62, 10, 66, 54, 53, 7, 20, 91, 358, 225, 346, 
+#> 520, 517, 446, 450, 253, 568, 535, 59, 257, 62, 48, 63, 44, 88, 83, 75, 73, 90, 72, 84, 70, 42, 19, 46, 0, 1, 79, 356, 543, 562, 646, 549, 609, 303, 595, 538, 383, 342, 106, 297, 291, 237, 57, 467, 428, 263, 566, 129, 465, 108, 37, 59, 13, 18, 459, 508, 603, 634, 610, 383, 618, 628, 601, 610, 641, 564, 568, 406, 515, 436, 45, 186, 49, 546, 613, 501, 416, 410, 465, 429, 417, 242, 401, 435, 355, 558, 554, 456, 403, 435, 85, 89, 1, 35, 593, 606, 648, 626, 586, 532, 563, 591, 417, 251, 298, 57, 87, 114, 
+#> 114, 91, 44, 79, 60, 7, 33, 18, 57, 67, 51, 42, 101, 103, 54, 79, 62, 32, 0, 4, 93, 118, 116, 128, 140, 78, 150, 135, 33, 106, 12, 49, 8, 2, 4, 23, 560, 557, 614, 605, 515, 52, 467, 14, 171, 252, 391, 566, 157, 43, 99, 1, 95, 105, 105, 79, 78, 63, 64, 15, 51, 33, 2, 33, 20, 76, 150, 73, 140, 113, 153, 150, 122, 105, 66, 108, 82, 46, 47, 93, 86, 83, 108, 109, 117, 109, 110, 97, 58, 53, 81, 57, 60, 20, 16, 12, 9, 35, 354, 638, 528, 512, 595, 159, 229, 177, 9, 32, 130, 400, 517, 562, 515, 585, 573, 
+#> 539, 535, 585, 569, 565, 467, 515, 487, 100, 205, 20, 224, 597, 534, 627, 631, 599, 598, 563, 614, 609, 482, 55, 309, 118, 17, 83, 22, 227, 494, 587, 611, 557, 602, 504, 556, 295, 570, 530, 520, 548, 518, 79, 77, 191, 8, 3, 16, 26, 81, 81, 56, 80, 55, 56, 47, 9, 21, 26, 385, 356, 132, 494, 574, 617, 612, 496, 552, 400, 62, 327, 56, 1, 41, 2, 64, 46, 87, 86, 103, 73, 105, 94, 68, 32, 37, 32, 34, 70, 64, 50, 82, 92, 97, 96, 62, 84, 59, 37, 72, 73, 76, 5, 92, 93, 90, 80, 119, 110, 108, 84, 68, 58, 57, 
+#> 75, 29, 86, 87, 94, 82, 83, 92, 86, 95, 95, 31, 47, 30, 10, 70, 47, 47, 28, 2, 14, 253, 616, 648, 594, 650, 606, 435, 434, 109, 492, 406, 458, 47, 270, 354, 73, 14, 20, 7, 20, 83, 104, 80, 99, 83, 69, 105, 86, 73, 9, 59, 33, 1, 0, 19, 99, 100, 113, 91, 84, 80, 71, 52, 86, 77, 32, 30, 26, 2, 98, 656, 619, 456, 666, 632, 564, 624, 623, 558, 536, 36, 571, 585, 184, 252, 47, 9, 21, 66, 97, 68, 84, 97, 13, 11, 8, 6, 79, 39, 0, 3, 97, 105, 118, 128, 121, 66, 26, 34, 18, 0, 1, 2, 233, 610, 475, 554, 614, 
+#> 587, 604, 539, 510, 516, 481, 336, 528, 12, 373, 316, 337, 2, 15, 447, 366, 477, 423, 478, 395, 448, 423, 530, 454, 480, 372, 348, 268, 242, 134, 24, 567, 543, 524, 550, 570, 524, 489, 480, 540, 499, 523, 543, 200, 60, 67, 378, 510, 411, 526, 554, 517, 482, 527, 533, 457, 165, 344, 390, 99, 37, 151, 11, 89, 87, 91, 78, 67, 90, 83, 97, 90, 108, 85, 104, 77, 49, 56, 29, 10, 54, 67, 78, 98, 109, 118, 96, 54, 71, 68, 47, 63, 64, 3, 3, 555, 617, 602, 528, 615, 589, 534, 113, 199, 407, 32, 329, 2, 41, 
+#> 12, 421, 360, 404, 372, 439, 379, 426, 334, 236, 412, 119, 174, 317, 289, 372, 331, 243, 150, 126, 106, 595, 620, 634, 636, 633, 590, 606, 423, 158, 538, 553, 173, 324, 490, 218, 92, 77, 150, 19, 8, 29, 4, 50, 63, 57, 50, 85, 43, 67, 41, 6, 0, 497, 573, 558, 499, 568, 469, 541, 595, 594, 374, 495, 610, 126, 123, 14, 425, 2, 623, 462, 535, 493, 499, 599, 584, 418, 370, 50, 109, 109, 90, 10, 6, 61, 67, 55, 19, 4, 120, 61, 79, 52, 17, 8, 1, 63, 75, 94, 84, 87, 102, 80, 86, 88, 72, 62, 25, 67, 47, 74, 
+#> 25, 35, 28, 279, 593, 540, 618, 491, 128, 13, 124, 343, 289, 60, 163, 435, 545, 521, 497, 566, 580, 582, 593, 534, 545, 527, 396, 536, 525, 549, 380, 399, 451, 68, 4, 5, 8, 361, 524, 580, 681, 649, 580, 506, 562, 543, 428, 7, 31, 98, 117, 107, 74, 81, 67, 69, 78, 66, 75, 26, 1, 449, 593, 619, 46, 594, 556, 500, 573, 67, 270, 523, 402, 6, 82, 223, 384, 661, 649, 644, 643, 560, 658, 589, 661, 660, 630, 606, 578, 541, 204, 157, 4, 26, 591, 621, 438, 405, 620, 506, 594, 621, 554, 404, 56, 36, 535, 516, 
+#> 517, 220, 628, 634, 519, 350, 268, 256, 489, 496, 208, 13, 1, 413, 323, 599, 454, 539, 572, 339, 269, 281, 228, 86, 377, 550, 565, 483, 583, 396, 577, 194, 57, 637, 621, 599, 462, 508, 541, 610, 503, 534, 594, 272, 525, 415, 7, 73, 113, 87, 79, 7, 67, 84, 15, 21, 30, 52, 23, 21, 53, 11, 73, 72, 26, 67, 87, 67, 79, 71, 48, 20, 22, 39, 7, 14, 24, 345, 585, 649, 589, 437, 537, 438, 577, 599, 535, 569, 175, 168, 255, 189, 308, 265, 136, 26, 297, 489, 612, 452, 525, 526, 574, 294, 516, 566, 592, 543, 
+#> 585, 57, 582, 503, 497, 492, 128, 178, 60, 402, 427, 561, 582, 609, 641, 603, 586, 553, 533, 383, 597, 323, 240, 542, 270, 581, 566, 573, 529, 583, 575, 530, 198, 204, 25, 42, 91, 95, 92, 101, 84, 85, 85, 71, 62, 73, 85, 4, 47, 40, 3, 46, 63, 74, 92, 81, 25, 49, 34, 39, 51, 11, 83, 83, 77, 67, 28, 0, 4, 11, 14, 5, 13, 45, 81, 45, 4, 43, 22, 585, 612, 606, 501, 624, 382, 121, 563, 458, 40, 411, 487, 300, 75, 92, 85, 49, 0, 8, 2, 414, 560, 531, 564, 579, 473, 541, 377, 586, 560, 388, 23, 274, 332, 
+#> 137, 104, 56, 515, 385, 605, 615, 476, 560, 460, 113, 35, 187, 86, 51, 96, 96, 55, 75, 41, 1, 1, 13, 10, 11, 0, 279, 639, 568, 648, 631, 648, 588, 561, 265, 7, 79, 51, 55, 121, 114, 11, 99, 109, 124, 115, 113, 109, 127, 129, 107, 114, 89, 89, 80, 46, 25, 24, 133, 235, 324, 204, 35, 151, 116, 95, 431, 504, 377, 334, 203, 395, 416, 288, 115, 85, 180, 284, 139, 3, 41, 61, 502, 431, 356, 585, 568, 424, 151, 370, 316, 166, 491, 364, 111, 2, 0, 0, 93, 11, 73, 108, 75, 25, 124, 97, 18, 107, 88, 11, 75, 
+#> 44, 15, 15, 88, 86, 19, 62, 42, 29, 7, 15, 2, 6, 23, 83, 36, 20, 76, 75, 95, 73, 57, 78, 52, 16, 1, 16, 83, 640, 630, 618, 603, 564, 472, 581, 580, 504, 212, 40, 180, 182, 413, 350, 417, 332, 387, 368, 489, 450, 376, 398, 309, 295, 373, 368, 238, 110, 2, 97, 152, 69, 292, 448, 520, 524, 459, 408, 76, 102, 87, 87, 101, 103, 76, 59, 69, 26, 17, 72, 31, 24, 47, 3, 592, 489, 549, 568, 470, 519, 149, 226, 225, 141, 458, 567, 616, 588, 538, 543, 376, 562, 550, 541, 368, 535, 547, 582, 566, 477, 563, 544, 
+#> 512, 552, 550, 438, 525, 529, 22, 53, 94, 99, 115, 120, 25, 124, 98, 95, 72, 83, 81, 60, 56, 48, 21, 16, 11, 67, 39, 5, 82, 95, 101, 88, 10, 67, 79, 78, 53, 80, 83, 59, 16, 21, 10, 10, 565, 561, 456, 522, 514, 528, 509, 566, 334, 531, 10, 91, 386, 320, 400, 420, 411, 272, 310, 38, 75, 195, 88, 300, 96, 121, 137, 64, 35, 120, 117, 106, 99, 90, 107, 61, 55, 45, 15, 2, 95, 75, 53, 26, 40, 57, 105, 47, 19, 59, 68, 55, 63, 51, 0, 135, 490, 515, 524, 198, 501, 484, 563, 543, 523, 586, 333, 43, 28, 51, 
+#> 0, 304, 231, 197, 503, 487, 587, 448, 441, 242, 69, 10, 187, 613, 337, 184, 360, 365, 440, 162, 147, 572, 475, 576, 571, 534, 526, 523, 584, 541, 379, 30, 44, 375, 5, 248, 505, 188, 316, 431, 465, 439, 63, 159, 250, 581, 385, 110, 179, 156, 13, 398, 500, 507, 544, 512, 163, 538, 151, 247, 116, 51, 62, 1, 12, 220, 491, 532, 588, 608, 582, 559, 296, 487, 494, 299, 58, 170, 88, 62, 10, 60, 296, 569, 585, 534, 576, 536, 421, 299, 545, 468, 266, 172, 57, 577, 459, 498, 508, 537, 438, 463, 251, 8, 21, 
+#> 61, 41, 71, 97, 91, 84, 114, 30, 42, 42, 78, 15, 29, 11, 78, 55, 48, 43, 392, 534, 517, 526, 567, 476, 528, 608, 54, 465, 204, 58, 120, 378, 602, 530, 475, 509, 565, 512, 529, 524, 353, 198, 525, 382, 645, 454, 549, 606, 110, 241, 10, 34, 7, 78, 28, 2, 26, 13, 0, 18, 36, 80, 109, 77, 60, 13, 16, 7, 79, 41, 28, 4, 1, 3, 0, 7, 71, 58, 93, 8, 11, 5, 64, 22, 19, 29, 11, 560, 292, 225, 536, 480, 423, 388, 127, 221, 78, 140, 44, 3, 3, 7, 66, 103, 112, 77, 65, 77, 5, 72, 48, 15, 3, 4, 395, 604, 516, 425, 
+#> 591, 609, 551, 549, 568, 556, 409, 510, 492, 125, 267, 9, 223, 83, 209, 138, 18, 99, 293, 396, 487, 358, 519, 429, 450, 465, 543, 214, 471, 464, 481, 246, 176, 221, 40, 635, 556, 335, 590, 458, 405, 538, 1, 576, 587, 543, 581, 624, 427, 573, 398, 541, 558, 246, 28, 17, 102, 86, 66, 91, 61, 2, 22, 37, 50, 74, 76, 75, 63, 31, 45, 49, 22, 68, 34, 74, 74, 95, 112, 31, 58, 42, 32, 2, 66, 84, 2, 75, 98, 72, 6, 0, 30, 69, 5, 60, 60, 71, 97, 1, 12, 94, 49, 68, 203, 629, 570, 592, 578, 506, 391, 20, 314, 
+#> 2, 575, 512, 559, 571, 450, 562, 635, 610, 628, 377, 295, 129, 165, 365, 6, 56, 9, 69, 83, 70, 103, 100, 94, 26, 6, 67, 13, 14, 0, 55, 80, 31, 40, 7, 3, 73, 33, 7, 4, 0, 435, 547, 485, 418, 506, 430, 498, 540, 567, 515, 372, 186, 7, 234, 397, 344, 307, 386, 421, 365, 461, 84, 198, 259, 125, 68, 620, 621, 638, 565, 604, 490, 480, 67, 177, 308, 17, 158, 6, 375, 463, 329, 588, 590, 577, 571, 583, 595, 579, 184, 400, 51, 592, 296, 494, 446, 329, 327, 40, 442, 282, 5, 57, 31, 50, 75, 91, 133, 102, 103, 
+#> 68, 69, 14, 63, 52, 44, 9, 0, 14, 34, 73, 25, 21, 2, 62, 71, 60, 68, 64, 41, 7, 633, 276, 396, 368, 322, 126, 2, 2, 47, 467, 617, 568, 624, 587, 611, 612, 555, 578, 578, 593, 591, 562, 594, 502, 472, 341, 331, 372, 433, 337, 2, 12, 55, 73, 92, 87, 105, 112, 64, 50, 40, 42, 16, 19, 200, 438, 449, 397, 18, 280, 515, 290, 307, 147, 337, 47, 342, 349, 137, 158, 15, 111, 68, 78, 493, 540, 14, 4, 356, 528, 496, 580, 342, 452, 25, 19, 274, 643, 632, 487, 571, 515, 157, 2, 326, 88, 0, 1, 40, 60, 52, 65, 
+#> 120, 109, 103, 96, 92, 91, 74, 29, 46, 8, 13, 0, 129, 551, 527, 560, 581, 538, 541, 486, 555, 540, 482, 531, 480, 272, 208, 160, 282, 478, 601, 537, 259, 4, 21, 498, 597, 473, 1, 540, 248, 169, 343, 5, 37, 2, 9, 105, 79, 55, 53, 15, 72, 61, 13, 147, 509, 525, 595, 500, 545, 604, 468, 583, 561, 527, 541, 586, 402, 10, 328, 17, 13, 70, 20, 593, 454, 225, 154, 556, 531, 393, 540, 535, 607, 576, 529, 408, 181, 81, 155, 540, 459, 583, 573, 565, 323, 41, 443, 575, 597, 485, 528, 360, 565, 575, 555, 310, 
+#> 126, 307, 104, 19, 103, 130, 402, 8, 87, 75, 4, 257, 313, 300, 234, 139, 120, 115, 99, 37, 1, 0, 6, 15, 2, 73, 91, 56, 22, 41, 24, 38, 27, 30, 2, 41, 79, 54, 27, 2, 5, 68, 74, 55, 84, 39, 3, 9, 67, 179, 61, 257, 501, 77, 109, 241, 488, 571, 13, 523, 328, 464, 21, 589, 458, 329, 268, 55, 193, 346, 482, 530, 614, 498, 510, 459, 334, 360, 256, 206, 63, 21, 158, 4, 9, 366, 522, 555, 511, 519, 513, 220, 14, 58, 469, 534, 234, 513, 548, 519, 514, 277, 178, 551, 516, 510, 252, 93, 220, 164, 142, 0, 42, 
+#> 68, 57, 83, 83, 82, 77, 58, 55, 29, 39, 70, 74, 90, 41, 50, 72, 56, 36, 61, 7, 0, 6, 8, 558, 629, 631, 636, 568, 618, 585, 380, 322, 29, 36, 3, 7, 1, 0, 81, 75, 9, 89, 17, 72, 39, 5, 8, 50, 90, 101, 74, 45, 59, 4, 4, 77, 473, 183, 264, 606, 3, 310, 141, 172, 14, 471, 607, 501, 202, 535, 370, 276, 19, 531, 621, 553, 587, 600, 558, 584, 90, 327, 546, 569, 608, 597, 538, 403, 270, 355, 91, 8, 5, 514, 567, 434, 87, 588, 368, 522, 641, 598, 276, 152, 460, 93, 233, 429, 345, 80, 310, 1, 160, 330, 252, 
+#> 326, 331, 283, 74, 82, 1, 225, 627, 579, 506, 539, 584, 345, 515, 538, 560, 475, 260, 273, 2, 28, 31, 43, 87, 65, 68, 82, 84, 36, 1, 68, 31, 3, 47, 15, 8, 1, 510, 261, 25, 555, 483, 559, 247, 506, 527, 515, 83, 30, 26, 418, 337, 266, 307, 234, 172, 241, 279, 259, 172, 229, 81, 81, 19, 540, 541, 589, 610, 595, 532, 592, 578, 556, 564, 630, 490, 329, 96, 12, 27, 94, 107, 115, 97, 102, 52, 14, 71, 68, 17, 8, 2, 312, 595, 564, 542, 476, 566, 617, 531, 616, 559, 524, 554, 553, 572, 330, 147, 418, 584, 
+#> 622, 534, 513, 648, 605, 588, 639, 486, 3, 134, 602, 617, 594, 495, 554, 449, 516, 483, 484, 517, 302, 22, 293, 469, 415, 597, 547, 534, 503, 584, 541, 521, 482, 433, 472, 359, 395, 232, 147, 9, 2, 67, 57, 85, 63, 89, 83, 78, 81, 76, 85, 41, 50, 206, 471, 347, 293, 538, 483, 565, 550, 588, 411, 151, 292, 471, 286, 148, 142, 36, 141, 94, 3, 57, 5, 1, 56, 106, 48, 19, 89, 82, 32, 5, 5, 0, 502, 565, 555, 549, 547, 531, 516, 414, 148, 557, 321, 6, 40, 18, 97, 74, 62, 34, 63, 19, 0, 34, 13, 4, 0, 6, 43, 
+#> 98, 90, 111, 106, 116, 112, 105, 101, 81, 105, 94, 108, 104, 95, 94, 98, 90, 59, 35, 21, 401, 510, 587, 537, 499, 298, 469, 66, 397, 357, 71, 41, 590, 574, 593, 518, 548, 510, 484, 386, 317, 357, 461, 520, 525, 522, 425, 538, 446, 235, 118, 140, 33, 162, 143, 341, 379, 359, 308, 280, 291, 53, 446, 403, 268, 137, 101, 4, 5, 89, 56, 119, 108, 136, 102, 124, 112, 98, 78, 93, 46, 13, 4, 40, 81, 83, 86, 85, 69, 63, 64, 33, 0, 114, 138, 180, 87, 238, 251, 371, 397, 411, 376, 105, 135, 377, 225, 63, 7, 
+#> 26, 70, 68, 84, 70, 67, 18, 6, 8, 0, 5, 0, 34, 60, 54, 9, 1, 13, 543, 529, 587, 646, 589, 647, 644, 475, 206, 413, 583, 464, 64, 477, 141, 198, 32, 36, 43, 46, 24, 40, 8, 0, 7, 68, 445, 291, 355, 484, 561, 138, 388, 485, 200, 166, 86, 411, 282, 18, 80, 114, 98, 81, 84, 94, 34, 19, 46, 333, 391, 608, 559, 501, 285, 130, 440, 94, 295, 257, 481, 515, 43, 247, 443, 317, 6, 105, 5, 44, 2, 77, 481, 596, 561, 582, 508, 520, 579, 546, 550, 579, 475, 413, 197, 215, 127, 22, 31, 19, 474, 450, 437, 521, 489, 
+#> 481, 550, 522, 464, 363, 144, 47, 279, 436, 437, 505, 468, 519, 397, 446, 388, 330, 96, 97, 103, 47, 117, 111, 74, 60, 12, 105, 36, 20, 471, 370, 89, 30, 285, 514, 509, 550, 572, 550, 385, 444, 492, 477, 450, 120, 58, 21, 19, 62, 62, 92, 71, 34, 32, 29, 27, 12, 2, 2, 0, 515, 553, 471, 549, 464, 614, 617, 540, 578, 413, 307, 143, 52, 447, 522, 362, 42, 10, 300, 96, 183, 157, 41, 559, 360, 132, 459, 606, 320, 453, 361, 223, 52, 162, 151, 39, 179, 27, 5, 2, 40, 56, 78, 93, 69, 34, 19, 65, 38, 12, 2, 
+#> 0, 34, 2, 3, 17, 37, 19, 14, 50, 3, 13, 8, 2, 0, 335, 437, 364, 549, 620, 667, 425, 479, 547, 523, 523, 395, 411, 93, 10, 83, 160, 552, 620, 606, 534, 590, 584, 538, 542, 508, 327, 370, 235, 233, 158, 354, 167, 86, 95, 97, 96, 96, 45, 60, 14, 11, 77, 41, 7, 7, 446, 662, 637, 589, 596, 609, 596, 405, 401, 502, 133, 67, 64, 0, 582, 572, 608, 1, 32, 439, 547, 503, 447, 519, 513, 577, 491, 504, 416, 247, 58, 55, 402, 555, 541, 394, 533, 438, 539, 503, 434, 337, 464, 127, 565, 580, 578, 585, 600, 575, 
+#> 595, 572, 621, 596, 578, 558, 552, 486, 498, 403, 478, 417, 195, 49, 209, 30, 66, 112, 69, 48, 63, 5, 40, 70, 0, 29, 8, 7, 16, 1, 53, 75, 15, 40, 51, 70, 91, 89, 57, 57, 21, 37, 66, 72, 96, 38, 3, 41, 22, 56, 35, 23, 10, 16, 8, 13, 7, 0, 5, 0, 33, 20, 116, 530, 357, 152, 540, 525, 567, 395, 520, 261, 151, 378, 236, 15, 2, 75, 81, 46, 19, 30, 1, 8, 36, 17, 0, 3, 30, 10, 0, 341, 549, 461, 543, 517, 533, 474, 519, 541, 527, 514, 377, 172, 465, 361, 333, 440, 435, 44, 67, 102, 87, 112, 123, 122, 107, 
+#> 100, 80, 99, 89, 79, 33, 52, 79, 68, 35, 21, 10, 16, 45, 540, 486, 437, 211, 6, 36, 58, 363, 587, 70, 458, 265, 145, 498, 242, 317, 374, 6, 9, 5, 44, 554, 573, 567, 599, 466, 492, 416, 80, 679, 656, 620, 591, 624, 561, 561, 474, 471, 487, 417, 351, 120, 59, 3, 159, 605, 607, 538, 594, 617, 555, 553, 557, 439, 588, 525, 334, 372, 235, 565, 606, 659, 408, 640, 642, 553, 620, 564, 610, 553, 334, 153, 394, 254, 427, 3, 226, 120, 143, 5, 24, 19, 3, 0, 46, 79, 98, 88, 63, 43, 29, 0, 20, 1, 0, 3, 176, 163, 
+#> 164, 187, 244, 190, 48, 70, 25, 16, 9, 32, 1, 32, 1, 0, 1, 2, 635, 593, 540, 516, 290, 543, 469, 463, 244, 343, 118, 89, 10, 379, 531, 538, 607, 497, 570, 573, 612, 517, 127, 301, 101, 122, 181, 263, 14, 201, 542, 597, 559, 555, 537, 513, 463, 375, 47, 45, 172, 0, 25, 16, 62, 98, 82, 89, 72, 84, 101, 34, 15, 1, 9, 21, 0, NA, 0, 0, 0, 0, 1, 36, 60, 60, 72, 71, 65, 66, 69, 88, 64, 0, 45, 30, 0, 20, 16, 84, 87, 11, 11, 52, 30, 6, 0, 534, 509, 71, 561, 604, 519, 409, 599, 663, 554, 473, 481, 3, 3, 13, 
+#> 247, 457, 604, 648, 624, 631, 636, 649, 619, 623, 624, 605, 606, 621, 539, 442, 41, 528, 579, 476, 499, 552, 572, 546, 594, 548, 572, 536, 547, 502, 546, 452, 108, 328, 52, 28, 504, 588, 617, 577, 543, 511, 551, 586, 398, 551, 525, 399, 479, 458, 327, 456, 467, 405, 278, 310, 558, 36, 75, 62, 86, 78, 42, 73, 65, 53, 96, 85, 92, 67, 82, 18, 13, 35, 593, 596, 538, 594, 617, 589, 597, 511, 610, 432, 591, 612, 511, 573, 552, 565, 222, 83, 81, 88, 41, 79, 56, 49, 47, 29, 25, 20, 25, 11, 31, 1, 11, 2, 
+#> 0, 533, 575, 557, 612, 600, 625, 581, 601, 578, 564, 659, 546, 622, 599, 552, 491, 436, 499, 572, 611, 554, 540, 464, 545, 609, 482, 568, 582, 576, 479, 421, 539, 471, 455, 342, 534, 427, 50, 118, 67, 530, 595, 544, 570, 563, 552, 589, 611, 617, 628, 535, 496, 180, 166, 24, 221, 34, 468, 602, 609, 615, 601, 629, 590, 603, 592, 631, 570, 570, 603, 600, 606, 547, 516, 495, 449, 392, 340, 465, 271, 2, 17, 51, 77, 79, 91, 87, 57, 70, 102, 99, 83, 68, 67, 56, 56, 31, 9, 0, 1, 35, 53, 79, 86, 86, 88, 99, 
+#> 104, 91, 103, 51, 26, 31, 43, 1, 6, 20, 8, 0, 20, 103, 634, 627, 604, 595, 590, 619, 580, 537, 364, 155, 62, 32, 38, 284, 396, 310, 375, 334, 316, 426, 450, 351, 421, 505, 421, 337, 220, 73, 16, 516, 14, 569, 556, 568, 517, 545, 568, 556, 570, 591, 540, 97, 315, 31, 8, 2, 199, 540, 557, 588, 470, 479, 448, 393, 246, 399, 505, 468, 320, 13, 379, 528, 220, 431, 559, 512, 568, 617, 169, 557, 415, 339, 3, 89, 59, 72, 74, 74, 98, 94, 30, 7, 25, 22, 15, 3, 15, 18, 94, 75, 89, 81, 100, 95, 84, 99, 103, 
+#> 106, 104, 51, 18, 47, 71, 25, 279, 290, 356, 376, 443, 323, 446, 494, 487, 550, 391, 410, 116, 199, 203, 2, 18, 81, 82, 46, 57, 88, 46, 55, 21, 12, 14, 25, 462, 596, 530, 467, 385, 205, 595, 580, 563, 611, 541, 221, 45, 48, 197, 368, 366, 576, 610, 459, 536, 585, 406, 542, 352, 535, 227, 7, 161, 585, 474, 515, 601, 609, 417, 317, 486, 484, 471, 52, 124, 94, 255, 112, 123, 3, 162, 460, 380, 520, 560, 600, 556, 478, 297, 336, 44, 58, 30, 255, 526, 567, 493, 538, 558, 572, 534, 601, 494, 621, 639, 506, 
+#> 227, 367, 193, 64, 228, 255, 382, 463, 440, 311, 383, 427, 518, 537, 30, 350, 259, 195, 140, 108, 14, 97, 93, 73, 93, 9, 68, 61, 83, 67, 56, 52, 11, 19, 2, 70, 168, 19, 570, 552, 580, 574, 578, 544, 548, 535, 498, 530, 138, 80, 82, 427, 614, 578, 265, 360, 3, 603, 605, 569, 585, 625, 579, 529, 34, 49, 452, 563, 600, 573, 567, 250, 84, 3, 550, 107, 148, 21, 455, 577, 510, 588, 594, 562, 374, 479, 50, 423, 571, 420, 197, 143, 58, 33, 77, 5, 44, 52, 52, 51, 61, 97, 87, 94, 73, 88, 79, 91, 86, 71, 71, 
+#> 11, 29, 0, 32, 37, 13, 17, 9, 14, 10, 10, 1, 5, 0, 6, 15, 69, 98, 92, 47, 120, 106, 70, 77, 108, 99, 91, 93, 84, 101, 86, 75, 90, 75, 37, 54, 11, 136, 448, 473, 616, 477, 341, 508, 64, 253, 351, 42, 52, 429, 511, 516, 505, 451, 523, 243, 164, 89, 19, 35, 570, 501, 556, 519, 527, 492, 438, 168, 496, 469, 189, 72, 192, 260, 328, 229, 564, 364, 540, 502, 456, 523, 491, 495, 329, 263, 383, 344, 413, 24, 202, 478, 351, 353, 113, 2, 10, 77, 57, 63, 90, 85, 80, 36, 21, 1, 0, 41, 32, 52, 63, 57, 63, 62, 
+#> 96, 94, 19, 45, 23, 61, 82, 66, 27, 22, 44, 117, 463, 313, 595, 668, 634, 589, 612, 559, 620, 610, 608, 598, 608, 589, 556, 549, 553, 482, 218, 47, 7, 4, 115, 168, 64, 466, 460, 522, 508, 405, 394, 364, 109, 274, 523, 515, 494, 534, 534, 396, 298, 364, 158, 7, 48, 143, 358, 182, 401, 433, 499, 590, 590, 312, 513, 155, 348, 410, 310, 508, 29, 517, 554, 591, 614, 658, 631, 543, 577, 308, 385, 57, 384, 521, 520, 501, 584, 593, 573, 596, 678, 631, 636, 587, 584, 26, 70, 19, 4, 530, 533, 196, 482, 575, 
+#> 587, 74, 498, 87, 275, 185, 91, 145, 30, 29, 21, 448, 267, 493, 417, 433, 516, 493, 519, 598, 592, 566, 549, 33, 287, 227, 215, 288, 464, 457, 465, 282, 538, 561, 478, 237, 273, 262, 559, 337, 123, 8, 61, 68, 62, 72, 89, 35, 21, 4, 19, 10, 41, 11, 29, 30, 5, 18, 44, 29, 19, 15, 32, 16, 3, 6, 5, 32, 74, 30, 29, 26, 17, 21, 22, 16, 8, 22, 11, 13, 2, 8, 24, 9, 7, 2, NA, 0, 64, 70, 66, 10, 14, 3, 5, 26, 7, 305, 182, 469, 460, 662, 692, 630, 679, 664, 610, 0, 82, 103, 73, 88, 80, 93, 108, 24, 35, 7, 3, 
+#> 17, 2, 19, 69, 384, 397, 287, 394, 389, 470, 414, 437, 445, 334, 380, 361, 86, 474, 543, 451, 519, 432, 570, 572, 538, 600, 622, 589, 638, 585, 502, 507, 412, 522, 378, 96, 648, 652, 607, 619, 652, 625, 669, 618, 650, 499, 495, 574, 566, 484, 466, 406, 319, 242, 516, 613, 695, 527, 630, 650, 594, 616, 627, 434, 189, 522, 601, 132, 61, 66, 50, 19, 15, 13, 10, 0, 33, 47, 529, 618, 612, 645, 645, 648, 634, 642, 642, 636, 594, 574, 576, 404, 520, 351, 8, 104, 353, 535, 507, 493, 479, 467, 603, 488, 411, 
+#> 483, 370, 452, 440, 363, 149, 9, 322, 461, 489, 588, 555, 583, 601, 597, 588, 592, 533, 190, 191, 113, 91, 56, 219, 371, 312, 345, 421, 21, 229, 205, 251, 377, 337, 323, 360, 264, 5, 171, 77, 67, 60, 3, 0, 3, 0, 32, 35, 45, 89, 90, 50, 53, 49, 8, 26, 56, 4, 32, 2, 5, 25, 4, 0, 25, 43, 13, 25, 1, 35, 50, 45, 25, 20, 16, 16, 9, 16, 19, 11, 0, 221, 129, 98, 453, 612, 550, 641, 517, 549, 433, 162, 49, 12, 6, 42, 4, 71, 17, 41, 49, 66, 106, 87, 35, 49, 14, 6, 0, 26, 73, 66, 91, 83, 83, 111, 96, 110, 130, 
+#> 106, 93, 79, 22, 1, 14, 63, 100, 61, 83, 93, 118, 99, 77, 87, 76, 93, 45, NA, 0, 1, NA, 79, 53, 48, NA, 1, NA, 35, 8, 12, 4, 28, 661, 566, 434, 469, 363, 436, 485, 460, 297, 271, 305, 295, 272, 303, 37, 8, 622, 520, 533, 602, 537, 448, 507, 331, 143, 6, 3, 3, 1, 76, 90, 83, 80, 61, 23, 56, 89, 69, 48, 6, 1, 352, 460, 665, 556, 592, 60, 313, 577, 456, 79, 454, 42, 213, 200, 219, 82, 26, 552, 626, 460, 219, 19, 26, 19, 0, 45, 81, 66, 83, 80, 107, 41, 58, 35, 4, 31, 29, 37, 27, 2, 9, 4, 0, 2, 4, 30, 
+#> 26, 26, 16, 7, 13, 17, 11, 12, 8, 4, 1, 11, 6, 0, 4, 2, 12, 17, 26, 49, 54, 57, 77, 69, 110, 74, 113, 118, 583, 646, 570, 567, 494, 594, 579, 539, 603, 566, 508, 455, 540, 515, 543, 546, 558, 523, 518, 364, 338, 459, 380, 59, 45, 510, 568, 621, 659, 666, 543, 581, 403, 217, 75, 194, 145, 452, 495, 423, 371, 282, 209, 230, 496, 458, 317, 332, 250, 117, 1, 3, 422, 208, 396, 335, 635, 662, 679, 617, 626, 514, 618, 606, 35, 14, 311, 418, 283, 394, 89, 363, 71, 370, 501, 340, 18, 0, 0, 3, 0, 81, 120, 
+#> 72, 81, 99, 72, 71, 82, 96, 30, 623, 516, 670, 654, 585, 626, 627, 649, 632, 645, 680, 652, 662, 665, 655, 655, 628, 655, 431, 634, 493, 96, 278, 405, 237, 138, 580, 613, 531, 585, 501, 380, 513, 213, 279, 427, 214, 11, 112, 31, 59, 89, 112, 97, 98, 112, 79, 123, 109, 85, 105, 51, 69, NA, 2, 64, 104, 288, 455, 603, 626, 654, 619, 612, 556, 398, 495, 477, 290, 275, 136, 26, 28, 66, 76, 87, 96, 104, 100, 60, 94, 118, 109, 87, 103, 65, 81, 28, 5, 65, 80, 89, 75, 76, 92, 93, 24, 42, 0, 21, 370, 577, 
+#> 505, 344, 359, 339, 180, 71, 98, 183, 295, 368, 64, 83, 23, 48, 77, 27, 6, 347, 578, 604, 630, 592, 608, 561, 586, 577, 575, 555, 555, 464, 536, 375, 76, 264, 381, 226, 217, 299, 184, 23, 417, 41, 27, 9, 7, 672, 576, 622, 557, 470, 637, 628, 487, 28, 571, 459, 455, 123, 24, 632, 619, 524, 463, 521, 438, 459, 549, 506, 250, 462, 416, 298, 171, 254, 397, 438, 532, 394, 612, 603, 538, 91, 87, 51, 13, 80, 99, 31, 31, 546, 442, 541, 552, 515, 577, 401, 569, 547, 295, 555, 527, 500, 433, 248, 333, 312, 
+#> 27, 175, 592, 505, 602, 611, 590, 614, 580, 601, 347, 340, 124, 157, 230, 191, 133, 56, 28, 20, 533, 475, 196, 479, 388, 529, 478, 367, 520, 443, 401, 403, 23, 2, 406, 220, 501, 601, 523, 546, 477, 424, 602, 624, 634, 544, 519, 529, 361, 310, 51, 15, 67, 31, 12, 27, 10, 29, 67, 3, 2, 0, 1, 10, 300, 520, 431, 492, 517, 540, 489, 395, 516, 374, 380, 445, 427, 237, 142, 198, 589, 565, 597, 557, 568, 379, 452, 578, 588, 554, 551, 195, 92, 102, 462, 419, 554, 451, 542, 269, 36, 101, 11, 102, 544, 544, 
+#> 494, 286, 275, 314, 388, 169, 158, 346, 293, 468, 502, 257, 171, 74, 15, 497, 510, 522, 356, 401, 126, 111, 24, 10, 212, 47, 32, 66, 55, 57, 88, 53, 69, 22, 60, 97, 78, 28, 31, 16, 17, 9, 2, 3, 8, 37, 99, 80, 82, 91, 101, 85, 94, 80, NA, 0, 4, 283, 19, 19, 477, 616, 505, 361, 342, 475, 574, 582, 230, 464, 36, 25, 152, 174, 10, 555, 38, 31, 304, 421, 533, 485, 462, 435, 522, 474, 511, 495, 522, 508, 461, 428, 186, 390, 424, 202, 60, 73, 8, 5, 7, 46, 36, 18, 29, 13, 2, 5, 12, 13, 11, 16, 17, 7, NA, 
+#> 1, 26, 11, 24, 1, 5, 6, 18, 8, 4, 17, 17, 8, 0, 14, 3, 13, 6, 486, 465, 590, 511, 494, 71, 345, 402, 161, 97, 14, 27, 12, 19, 629, 529, 368, 565, 636, 425, 422, 204, 62, 51, 209, 500, 579, 550, 474, 285, 426, 348, 347, 158, 1, 42, 542, 497, 507, 480, 575, 547, 518, 543, 452, 135, 87, 59, 12, 13, 400, 491, 424, 472, 491, 415, 550, 533, 526, 418, 465, 370, 344, 435, 293, 41, 13, 429, 528, 322, 379, 328, 311, 136, 236, 104, 8, 23, 69, 72, 73, 79, 32, 64, 108, 88, 76, 31, 17, 182, 247, 322, 415, 561, 
+#> 565, 415, 555, 666, 574, 662, 476, 575, 461, 8, 324, 48, 280, 3, 3, 8, 21, 8, 7, 9, 1, 16, 3, 6, 0, 7, 1, 2, 17, 40, 63, 63, 41, 12, 21, 10, 20, 1, 15, 9, 8, 1, 0, 25, 281, 257, 600, 625, 629, 587, 609, 515, 564, 596, 511, 527, 559, 544, 489, 585, 306, 196, 253, 137, 183, 200, 11, 434, 547, 215, 419, 631, 643, 689, 660, 655, 664, 640, 621, 650, 635, 528, 498, 489, 298, 405, 59, 54, 99, 39, 41, 9, 53, 69, 59, 94, 44, 67, 48, 34, 1, 1, 22, 54, 66, 88, 80, 28, 46, 6, 41, 66, 84, 58, 66, 5, 25, 2, 601, 
+#> 565, 350, 549, 480, 537, 578, 604, 604, 617, 606, 584, 412, 156, 146, 44, 1, 364, 303, 552, 421, 625, 480, 516, 477, 500, 552, 440, 375, 164, 125, 140, 5, 2, 214, 542, 475, 413, 468, 471, 614, 533, 427, 1, 15, 526, 539, 553, 522, 250, 21, 357, 368, 88, 180, 18, 4, 514, 461, 458, 191, 577, 535, 580, 599, 535, 605, 616, 564, 409, 540, 364, 523, 472, 329, 443, 77, 95, 91, 95, 92, 89, 93, 71, 95, 82, 55, 31, 74, 76, 46, 55, 34, 64, 0, 0, NA, NA, 24, 10, 67, 405, 465, 409, 543, 471, 434, 515, 164, 474, 
+#> 239, 152, 331, 28, 106, 21, 59, 155, 169, 146, 137, 5, 250, 219, 564, 418, 594, 542, 495, 554, 404, 542, 481, 535, 412, 449, 117, 77, 1, 51, 0, 93, 100, 108, 113, 115, 109, 84, 2, NA, NA, NA, 0, 0, NA, NA, 67, 53, 14, 17, 10, 36, 64, 86, 64, 61, 70, 91, 82, 115, 89, NA, NA, NA, 54, 3, 6, 5, 37, 74, 93, 85, 111, 106, 31, 58, 12, 4, 26, 565, 558, 543, 580, 618, 467, 423, 517, 477, 225, 170, 488, 447, 234, 311, 35, 349, 11, 117, 235, 333, 583, 592, 568, 401, 435, 602, 394, 164, 214, 222, 151, 614, 656, 
+#> 597, 643, 543, 591, 530, 474, 372, 172, 16, 86, 564, 532, 605, 562, 538, 557, 621, 530, 465, 494, 393, 464, 360, 178, 399, 310, 189, 51, 26, 89, 394, 476, 459, 372, 399, 356, 36, 276, 19, 217, 52, 22, 10, 7, 81, 60, 74, 79, 92, 0, NA, 0, 1, 0, 42, NA, 11, 14, 9, 9, NA, 0, 226, 139, 483, 210, 250, 80, 174, 79, 535, 46, 519, 39, 161, 43, 80, 512, 526, 401, 512, 508, 371, 450, 333, 411, 238, 615, 401, 4, 519, 169, 102, 122, 646, 335, 3, 38, 51, 65, 77, 38, 86, 94, 105, 74, 79, NA, NA, 21, 12, 309, 533, 
+#> 580, 655, 664, 631, 617, 577, 577, 599, 601, 502, 119, 134, 431, 110, 3, 3, 12, 1, 5, 6, 16, 22, 15, 18, 96, 125, NA, 0, 0, NA, NA, NA, 12, 210, 328, 135, 187, 53, 274, 247, 121, 11, 1, 18, 12, 71, 93, 57, 103, 112, 107, 87, NA, NA, NA, NA, NA, 47, 501, 510, 504, 511, 530, 510, 376, 559, 454, 1, 156, 49, 89, 3, 19, 184, 472, 530, 459, 500, 285, 470, 493, 442, 522, 402, 348, 198, 268, 139, 50, 91, 136, 570, 652, 590, 577, 498, 638, 518, 676, 531, 314, 79, 129, 0, 114, 393, 504, 566, 557, 510, 514, 
+#> 500, 572, 273, 496, 475, 98, 1, 5, 493, 542, 448, 574, 513, 518, 199, 327, 339, 472, 461, 321, 159, 261, 148, 86, 590, 340, 478, 439, 521, 504, 562, 266, 519, 351, 88, 330, 23, 118, 553, 549, 426, 567, 499, 539, 506, 593, 498, 525, 511, 465, 514, 334, 530, 397, 525, 460, 419, 336, 4, 323, 522, 491, 406, 535, 583, 553, 521, 356, 454, 402, 240, 2, 15, 72, 73, 80, 80, 96, 117, 100, 102, 90, 92, 97, 86, 94, 101, 67, 101, 97, 84, 28, NA, 34, 11, NA, NA, NA, 3, 200, 195, 76, 250, 324, 535, 550, 558, 698, 
+#> 677, 609, 121, 404, 497, 11, 81, 15, 74, 495, 411, 509, 483, 506, 505, 375, 339, 461, 50, 40, 12, 14, 24, 19, 19, 8, 10, 7, 24, 24, 2, 3, 1, 0, 0, 5, 21, 10, 7, 10, NA, 3, NA, 9, 3, 35, 222, 563, 457, 612, 571, 478, 584, 129, 202, 396, 263, 136, 50, 91, 73, 60, 2, 51, 13, 53, 59, 42, 42, 93, 97, 92, 71, NA, NA, NA, 0, 68, 386, 511, 510, 212, 87, 352, 352, 403, 518, 470, 150, 295, 259, 63, 171, 101, 16, 0, 116, 450, 486, 457, 492, 204, 136, 276, 238, 34, 52, 6, 5, 32, 472, 443, 485, 504, 297, 463, 
+#> 298, 409, 415, 267, 40, 162, 333, 569, 576, 484, 553, 574, 533, 448, 471, 170, 313, 404, 521, 558, 349, 506, 560, 266, 57, 86, 453, 451, 511, 519, 517, 597, 616, 595, 617, 382, 7, 93, 77, 52, 94, 89, 94, 45, 2, 26, 19, 56, 95, 60, 82, 85, 92, 105, 73, 59, NA, 12, NA, 8, 22, 39, 74, 71, 77, 83, 29, 2, NA, NA, NA, 69, 93, 265, 278, 637, 589, 604, 457, 357, 506, 272, 16, 74, 21, 10, 15, 102, 45, 1, 0, NA, NA, 1, 79, 83, 68, 35, NA, NA, 30, 43, 59, 93, 620, 555, 540, 583, 552, 470, 592, 478, 486, 577, 
+#> 394, 372, 475, 356, 97, 307, 622, 663, 619, 626, 643, 567, 529, 378, 592, 90, 475, 538, 231, 163, 88, 339, 600, 515, 613, 558, 624, 569, 643, 498, 593, 641, 615, 599, 611, 350, 169, 493, 56, 37, 99, 540, 402, 395, 564, 547, 418, 356, 331, 73, 359, 269, 103, 71, 180, 415, 466, 572, 67, 400, 562, 641, 600, 625, 554, 602, 404, 534, 447, 389, 170, 122, 1, 19, 497, 565, 459, 413, 383, 184, 190, 348, 86, 77, 340, 521, 626, 528, 621, 391, 384, 47, 414, 487, 551, 542, 406, 132, 156, 37, 69, 564, 581, 529, 
+#> 585, 616, 606, 526, 533, 554, 499, 190, 264, 297, 117, 141, 22, 64, 190, 338, 491, 301, 321, 208, 188, 140, 126, 108, 76, 4, 26, 73, 13, 64, 113, 102, 98, NA, NA, NA, NA, NA, NA, NA, 0, NA, NA, NA, NA, 4, 75, 438, 559, 607, 605, 553, 592, 545, 556, 580, 530, 585, 556, 456, 222, 55, 91, 96, 459, 486, 533, 520, 589, 596, 481, 389, 571, 220, 74, 48, 0, 6, 8, 0, 13, 14, 7, NA, NA, NA, NA, 2, NA, 2, 24, 7, 35, 74, 84, 82, 25, 16, 17, 10, 13, 9, 10, 4, 2, 0, 25, 37, 601, 425, 494, 20, 535, 548, 583, 552, 
+#> 576, 512, 498, 472, 521, 441, 436, 461, 308, 463, 404, 365, 38, 105, 179, 227, 510, 484, 498, 417, 437, 401, 463, 316, 129, 124, 62, 13, 18, 56, 64, 86, 91, 97, 117, 120, 98, 110, NA, NA, 0, NA, NA, NA, 87, 71, NA, NA, 48, NA, NA, 0, 55, 483, 470, 396, 312, 287, 127, 6, 5, 48, 457, 508, 187, 263, 487, 536, 571, 320, 478, 338, 476, 488, 359, 543, 457, 454, 253, 375, 452, 460, 188, 53, 11, 133, 514, 447, 444, 582, 320, 193, 576, 625, 527, 516, 515, 502, 63, 75, 2, 355, 611, 559, 525, 610, 500, 575, 
+#> 530, 192, 470, 499, 306, 492, 332, 380, 220, 76, 78, 547, 650, 579, 446, 669, 583, 624, 624, 654, 539, 540, 360, 499, 499, 391, 195, 19, 11, 78, 65, 79, 70, 88, 50, NA, NA, NA, NA, NA, NA, 43, 181, 122, 350, 513, 593, 437, 593, 468, 500, 242, 497, 330, 372, 122, 193, 1, 66, 55, 199, 49, 450, 229, 54, 26, 83, 6, 601, 562, 542, 501, 487, 495, 531, 17, 501, 344, 388, 307, 530, 261, 33, 40, 118, 218, 155, 317, 171, 37, 8, 8, 17, 13, 3, 21, NA, 1, NA, 0, 0, NA, 0, 0, NA, 5, NA, 2, 2, 5, 30, 16, 5, 24, 
+#> 29, 14, 10, 11, 14, 18, 19, NA, NA, 11, 0, 269, 578, 573, 601, 642, 547, 603, 569, 625, 601, 527, 509, 536, 552, 269, 239, 9, 210, 82, 143, 95, 30, 460, 581, 582, 524, 518, 181, 487, 534, 498, 352, 506, 387, 363, 479, 313, 14, 87, 118, 372, 413, 287, 445, 343, 20, 203, 97, 157, 321, 122, 114, 48, 24, 26, 98, 112, 2, 562, 641, 580, 572, 450, 481, 269, 123, 235, 259, 27, 0, 0, 15, 37, 21, 23, 4, NA, NA, NA, 1, NA, NA, NA, NA, 11, 356, 270, 349, 450, 518, 114, 569, 645, 392, 562, 378, 344, 95, 62, 540, 
+#> 561, 425, 587, 555, 474, 631, 571, 359, 616, 446, 491, 298, 370, 42, 119, 9, 4, 148, 137, 503, 510, 427, 554, 594, 543, 515, 464, 501, 290, 215, 33, 24, 130, 605, 609, 502, 538, 535, 592, 498, 562, 550, 580, 540, 476, 254, 65, 0, 73, 35, 80, 100, 105, 69, 90, 0, 0, 2, NA, NA, NA, 10, NA, 43, 26, 44, 260, 418, 595, 571, 567, 139, 257, 461, 547, 562, 556, 357, 465, 523, 401, 505, 507, 499, 437, 276, 1, 16, 27, 50, 70, 95, 31, 1, 212, 278, 211, 434, 615, 553, 252, 554, 634, 625, 627, 466, 262, 497, 
+#> 451, 262, 169, 216, 9, 27, 0, 11, 16, 22, 33, 34, 15, 6, 5, 1, NA, 0, 0, 0, 0, 3, 93, 225, 294, 349, 642, 659, 631, 646, 639, 648, 658, 431, 625, 388, 617, 654, 557, 76, 37, 435, 474, 507, 349, 202, 483, 384, 475, 42, 332, 287, 40, 59, 92, 82, 85, 90, 103, 105, 1, 0, NA, 1, NA, NA, NA, 8, 37, 82, 255, 324, 474, 501, 486, 492, 296, 356, 145, 118, 119, 87, 20, 77, 70, 93, 53, 89, 96, 108, 67, 34, NA, 22, 265, 327, 378, 328, 594, 507, 576, 572, 565, 590, 622, 421, 572, 528, 531, 560, 311, 279, 197, 
+#> 302, 57, 573, 347, 264, 355, 124, 196, 12, 181, 65, 526, 554, 585, 604, 579, 488, 397, 278, 319, 285, 401, 71, 191, 415, 519, 541, 525, 494, 338, 125, 589, 322, 591, 469, 352, 284, 63, 559, 413, 272, 280, 122, 472, 582, 554, 221, 85, 230, 34, 367, 568, 562, 584, 544, 513, 541, 548, 354, 514, 534, 528, 549, 552, 522, 390, 148, 19, 75, 38, 64, 80, 62, 44, NA, NA, 15, 37, 333, 536, 504, 581, 531, 511, 503, 448, 357, 503, 285, 5, 19, 1, 0, NA, NA, 26, 8, 0, 0, 2, 2, 8, 3, 4, 0, 0, 25, 39, 33, 19, 1, 
+#> 0, 1, 0, 20, 12, 12, 18, 0, 0, NA, NA, 77, 453, 514, 514, 533, 447, 311, 249, 494, 279, 568, 473, 403, 114, 399, 379, 326, 61, 45, 68, 36, 71, 87, 81, 32, 19, 56, NA, 0, 1, 1, NA, NA, NA, NA, 16, NA, 43, 528, 507, 497, 541, 531, 415, 256, 472, 437, 517, 448, 397, 396, 301, 90, 353, 196, 78, 426, 579, 592, 577, 587, 540, 605, 523, 260, 10, 458, 587, 538, 374, 52, 531, 571, 598, 548, 549, 323, 412, 324, 241, 218, 7, 67, 46, 35, 82, 75, 60, 2, 68, 79, 0, 15, 14, 80, 78, 49, 70, 42, 30, 15, 58, NA, 19, 
+#> NA, NA, NA, 3, 76, 225, 549, 598, 557, 552, 566, 581, 583, 589, 587, 521, 324, 349, 405, 462, 395, 440, 354, 177, 93, 67, 564, 581, 644, 677, 619, 504, 451, 573, 626, 657, 546, 618, 404, 485, 209, 1, 383, 374, 461, 573, 522, 584, 539, 450, 527, 561, 361, 602, 526, 253, 396, 289, 48, 65, 83, 103, 43, 82, 86, 45, 17, 27, 12, 100, 563, 610, 302, 596, 533, 554, 540, 452, 368, 378, 583, 502, 412, 8, 463, 551, 529, 565, 654, 617, 628, 443, 568, 525, 492, 656, 421, 617, 614, 93, 339, 79, 187, 139, 220, 
+#> 558, 537, 637, 581, 622, 518, 240, 244, 552, 607, 635, 637, 589, 377, 553, 610, 466, 36, 16, 0, NA, NA, NA, 23, NA, NA, 0, NA, NA, NA, 22, 11, 7, 4, 1, NA, 1, NA, NA, 0, 0, 3, 0, 1, 4, 13, 15, 7, 8, NA, NA, 1, 1, 3, 5, 19, 368, 105, 145, 39, 276, 463, 562, 615, 604, 440, 528, 414, 550, 601, 553, 452, 51, 233, 130, 223, 561, 63, 547, 604, 601, 555, 571, 507, 480, 306, 385, 343, 164, 175, 52, 257, 67, 20, 368, 472, 448, 453, 518, 495, 505, 339, 470, 378, 348, 367, 429, 139, 54, 91, 147, 57, 282, 463, 
+#> 412, 501, 230, 497, 489, 463, 412, 609, 470, 630, 617, 529, 541, 559, 520, 445, 270, 480, 552, 252, 566, 560, 471, 360, 562, 194, 375, 341, 216, 205, 114, 6, 24, 59, 69, 51, 62, 79, 84, 69, 63, 74, 51, 64, 79, 66, 0, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 82, 75, 62, 98, 84, 88, 91, 84, 98, 80, 84, 73, 72, 77, 64, 51, 68, NA, NA, NA, NA, NA, NA, NA, 23, NA, NA, 1, 0, NA, NA, NA, NA, NA, 7, 10, 1, 6, 0, 1, 1, 15, 17, 6, 5, NA, 3, 7, NA, 2, NA, NA, NA, NA, 0, 0, 0, 8, 3, 4, 0, 62, 22, 42, 
+#> 43, 16, 46, 38, 38, 4, 6, 1, 40, 457, 634, 645, 564, 510, 645, 449, 347, 552, 464, 377, 550, 441, 427, 589, 457, 544, 505, 592, 560, 51, 165, 337, 97, 338, 539, 480, 527, 641, 623, 393, 489, 389, 613, 589, 317, 320, 278, 32, NA, NA, 0, 0, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, 0, NA, 58, 25, 268, 159, 129, 466, 616, 590, 565, 559, 286, 247, 630, 399, 68, 309, 313, 2, 25, 599, 531, 552, 527, 84, 518, 420, 230, 544, 609, 410, 144, 19, 481, 62, 38, 16, 32, 51, 521, 488, 289, 
+#> 361, 440, 435, 398, 480, 227, 472, 468, 450, 460, 442, 389, 352, 405, 117, 86, 227, 463, 562, 585, 614, 380, 544, 396, 484, 458, 399, 438, 292, 198, 399, 193, 50, 236, 63, 77, 85, 139, 204, 304, 446, 474, 461, 467, 560, 364, 524, 549, 479, 563, 566, 563, 537, 418, 241, 57, 99, 389, 254, 478, 424, 473, 142, 237, 166, 196, 315, 354, 411, 343, 174, 81, 58, 269, 328, 581, 606, 485, 516, 119, 403, 253, 560, 356, 524, 452, 82, 5, 7, 24, 62, 446, 604, 574, 494, 384, 533, 522, 554, 579, 400, 570, 531, 243, 
+#> 343, 242, 611, 610, 606, 621, 378, 550, 582, 588, 583, 495, 618, 603, 594, 558, 576, 551, 610, 433, 436, 230, 336, 160, 7, 85, 525, 609, 639, 577, 394, 608, 633, 533, 529, 496, 621, 591, 416, 529, 563, 542, 461, 292, 226, 58, 61, 430, 551, 499, 574, 513, 357, 553, 420, 564, 497, 492, 449, 404, 549, 96, 292, 431, 286, 11, 482, 405, 76, 545, 510, 255, 581, 546, 520, 96, 60, 87, 31, 0, 44, 29, 45, 47, 96, 0, NA, NA, NA, NA, NA, NA, 70, 51, 83, 69, 61, 63, 59, 65, 70, NA, NA, NA, NA, NA, 384, 580, 540, 
+#> 663, 626, 627, 644, 430, 45, 119, 4, 271, 206, 3, 14, 284, 510, 594, 619, 599, 581, 546, 516, 516, 448, 495, 380, 539, 600, 497, 528, 127, 177, 107, 44, 73, 86, 77, 83, 87, 73, 79, 82, 25, NA, 7, 29, 59, 70, 60, 19, 73, 61, 26, 2, 213, 621, 647, 672, 504, 333, 563, 460, 493, 546, 510, 510, 362, 506, 505, 219, 57, 117, 496, 602, 562, 477, 379, 431, 489, 227, 160, 146, 417, 9, 0, 0, 0, 0, 0, 0, NA, NA, 0, 0, NA, NA, NA, 0, 33, 98, 441, 280, 108, 269, 189, 475, 427, 412, 316, 409, 262, 123, 45, 34, 
+#> 188, 374, 560, 542, 610, 595, 376, 579, 320, 218, 550, 593, 551, 587, 348, 215, 130, 42, 535, 530, 618, 427, 502, 587, 582, 553, 214, 450, 494, 17, 230, 275, 157, 98, 43, 33, 305, 508, 570, 548, 311, 76, 169, 337, 271, 38, 0, 10, 8, 57, 77, 95, 79, 92, 93, 82, 104, 99, 94, 109, 120, 123, 90, 52, 87, 65, NA, NA, NA, 1, NA, NA, 32, 484, 423, 477, 335, 560, 643, 558, 609, 584, 604, 403, 509, 472, 470, 453, 383, 322, 249, 323, 487, 463, 300, 499, 386, 113, 483, 517, 206, 513, 292, 410, 554, 546, 591, 
+#> 549, 569, 599, 239, 585, 561, 574, 589, 623, 642, 246, 86, 340, 161, 219, 115, 72, 45, 344, 558, 638, 605, 502, 577, 611, 377, 635, 578, 624, 466, 522, 635, 621, 614, 587, 503, 557, 454, 17, 102, 413, 592, 527, 437, 385, 563, 492, 203, 442, 232, 419, 496, 455, 334, 481, 257, NA, NA, NA, NA, NA, 0, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0, NA, 8, 20, 13, 12, 9, 9, 8, 7, 10, 4, 1, 1, 42, 17, 101, 414, 305, 451, 643, 407, 590, 622, 416, 654, 661, 603, 631, 542, 250, 466, 631, 423, 553, 604, 479, 
+#> 556, 670, 490, 360, 537, 618, 553, 247, 313, 568, 522, 54, 269, 82, 54, 429, 513, 400, 442, 473, 411, 214, 470, 39, 317, 256, 116, 12, 33, 545, 582, 504, 552, 431, 531, 349, 549, 320, 121, 401, 451, 152, 214, 164, 39, 141, 498, 509, 492, 615, 587, 597, 558, 388, 539, 598, 567, 633, 565, 575, 559, 414, 61, 568, 583, 547, 294, 115, 17, 2, 320, 405, 489, 524, 595, 561, 591, 628, 340, 377, 608, 534, 493, 477, 585, 339, 49, 264, 35, 303, 372, 85, 183, 433, 508, 515, 226, 589, 508, 587, 461, 401, 85, NA, 
+#> NA, NA, NA, 1, 0, NA, NA, NA, 7, NA, NA, 1, NA, NA, 393, 546, 381, 410, 563, 27, 4, 41, 4, 624, 653, 388, 539, 528, 419, 614, 594, 494, 316, 506, 461, 350, 150, 95, 1, 0, 85, 27, 11, NA, NA, 56, NA, 43, 53, 81, 75, 70, 5, 32, NA, NA, 23, 70, 56, 350, 432, 409, 389, 425, 520, 533, 418, 174, 373, 443, 422, 240, 155, 130, 198, 298, 507, 560, 511, 586, 544, 536, 502, 570, 583, 363, 561, 507, 363, 250, 384, 129, 584, 586, 621, 486, 167, 13, 486, 451, 135, 209, 388, 459, 309, 115, 472, 305, 350, 502, 474, 
+#> 36, 24, 211, 168, 395, 532, 255, 353, 535, 248, 549, 592, 561, 6, 122, 492, 515, 695, 676, 434, 645, 405, 152, 355, 70, 66, 359, 46, 60, 5, 51, 66, 30, 12, 3, 5, 14, 27, 50, 65, 83, 80, 51, 89, 85, 83, 68, NA, NA, NA, NA, NA, 23, 17, 4, 24, 13, 18, 20, 24, 14, 13, 7, 10, 4, 6, 8, 1, 2, 3, 3, 34, 34, 0, 58, 72, 21, NA, NA, NA, 0, NA, 52, 388, 573, 390, 543, 471, 559, 523, 329, 219, 144, 156, 6, 34, 198, 588, 705, 439, 585, 576, 541, 605, 631, 610, 591, 383, 307, 294, 396, 221, 21, 0, NA, 1, 0, NA, 
+#> NA, NA, 0, NA, 0, 43, 448, 460, 560, 392, 489, 505, 555, 605, 574, 597, 466, 449, 559, 375, 102, 401, 292, 223, 193, 127, 219, 32, 282, 532, 555, 443, 325, 193, 270, 452, 366, 51, 6, 27, 503, 311, 522, 533, 505, 549, 374, 557, 541, 596, 555, 490, 523, 455, 153, 244, 248, 285, 590, 587, 609, 450, 488, 552, 412, 537, 514, 600, 575, 593, 512, 550, 518, 545, 381, 156, 227, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, 4, 1, 453, 138, 56, 11, 1, 7, 8, 0, NA, NA, NA, NA, 0, NA, NA, NA, 46, 288, 493, 553, 
+#> 348, 486, 605, 578, 549, 327, 466, 424, 433, 470, 402, 83, 192, 20, 126, 178, 38, 253, 147, 252, 332, 305, 450, 469, 514, 592, 400, 602, 411, 461, 341, 346, 114, 121, 440, 495, 561, 551, 541, 111, 382, 493, 572, 394, 515, 529, 441, 41, 256, 283, 162, 127, 29, 78, 62, 72, 83, 73, 78, 41, 73, 54, 16, 45, 76, 57, 7, 25, 24, 12, 16, 100, 282, 469, 519, 234, 300, 246, 120, 282, 216, 284, 264, 296, 139, 227, 63, 8, 2, 0, NA, NA, NA, NA, NA, 31, 45, 77, 28, 18, NA, 10, 45, 46, 16, 4, 5, 5, 22, 5, 11, 0, 
+#> 15, 2, 37, 507, 577, 566, 502, 564, 555, 487, 551, 312, 556, 581, 505, 500, 256, 104, 1, 64, 95, 91, 79, 97, 109, 92, 44, 66, 69, NA, NA, 12, 32, 63, 17, 5, 65, 3, 150, 295, 343, 294, 195, 153, 82, 0, 351, 591, 423, 536, 513, 502, 547, 608, 358, 554, 235, 306, 489, 470, 396, 318, 163, 296, 407, 465, 115, 288, 542, 438, 96, 324, 379, 179, 72, 7, 72, 70, 50, 3, 70, 62, 67, 67, 75, 64, 42, 35, 50, 14, NA, NA, NA, NA, NA, NA, NA, NA, 0, NA, 0, NA, 3, 7, 1, NA, NA, NA, 453, 654, 602, 399, 482, 299, 597, 
+#> 401, 591, 554, 556, 551, 507, 16, 496, 6, 363, 239, 278, 628, 440, 536, 574, 639, 385, 425, 81, 368, 202, NA, NA, 0, 0, NA, NA, 0, NA, 0, NA, 1, 0, NA, NA, NA, NA, NA, NA, 8, 62, 183, 347, 575, 584, 535, 487, 61, 545, 215, 149, 570, 498, 427, 146, 106, 134, 316, 452, 359, 387, 228, 310, 227, 86, 196, 335, 197, 121, 130, NA, NA, NA, 58, 79, 71, NA, NA, NA, NA, NA, 65, 76, 530, 384, 569, 369, 598, 589, 607, 616, 614, 566, 592, 574, 349, 214, 544, 62, 42, 39, 598, 663, 641, 642, 627, 624, 575, 646, 
+#> 600, 650, 637, 641, 444, 550, 640, 615, 601, 332, 309, 477, 119, 638, 623, 569, 488, 633, 610, 632, 651, 615, 652, 567, 119, 24, 41, 38, 543, 250, 597, 525, 633, 600, 424, 60, 203, 18, 1, 167, 440, 522, 511, 422, 489, 346, 575, 370, 547, 427, 512, 453, 9, 303, 328, 539, 337, 473, 542, 484, 439, 73, 51, 18, 85, 49, 57, 12, 85, 13, 31, 21, 6, 7, 11, 52, 81, 63, 40, NA, 18, 2, 23, 15, 0, 3, NA, NA, NA, NA, NA, NA, NA, NA, NA, 155, 46, 240, 227, 452, 557, 628, 363, 567, 371, 164, 108, 484, 145, 170, 
+#> 0, 1, 0, 0, NA, NA, NA, 0, 0, 0, NA, NA, NA, NA, NA, 1, 4, 30, 298, 176, 592, 492, 504, 448, 96, 508, 167, 114, 482, 466, 353, 158, 24, 199, 59, 41, 79, 77, 74, 96, 71, 77, 81, 55, 85, 82, 49, 14, NA, NA, NA, 0, 0, 0, NA, 0, NA, NA, NA, NA, NA, NA, NA, 6, 7, 13, 40, 11, 109, 145, 174, 42, 270, 441, 368, 362, 251, 344, 347, 330, 362, 327, 141, 167, 151, 128, 147, 9, NA, 0, NA, NA, 0, 0, 64, 46, 0, 44, 67, 51, 73, 70, NA, NA, NA, 6, 77, 47, 81, 54, 6, 635, 633, 636, 609, 627, 523, 618, 606, 615, 585, 
+#> 612, 456, 223, 554, 447, 21, 210, 497, 542, 546, 546, 510, 384, 505, 424, 491, 464, 410, 304, 112, 263, 174, 67, 19, 422, 601, 571, 612, 497, 620, 562, 199, 113, 501, 497, 474, 475, 156, 200, 309, 300, 269, 271, 11, 92, 65, 551, 618, 386, 609, 507, 278, 93, 271, 486, 563, 299, 0, 0, 5, 16, 34, 7, 5, NA, 0, 5, NA, NA, 29, 520, 466, 379, 296, 80, 159, 225, 169, 61, 277, 47, 420, 522, 393, 475, 532, 543, 476, 542, 505, 156, 100, 92, 87, 202, 29, 295, 49, 338, 582, 625, 653, 580, 551, 584, 621, 619, 
+#> 546, 514, 560, 366, 460, 501, 353, 435, 292, 389, 378, 487, 539, 592, 584, 589, 592, 472, 502, 431, 260, 102, 647, 576, 555, 594, 579, 127, 472, 602, 530, 404, 29, 109, 248, 382, 562, 549, 530, 532, 432, 512, 265, 355, 303, 171, 17, 292, 332, 406, 161, 315, 439, 579, 565, 558, 612, 409, 570, 594, 600, 544, 479, 365, 80, 56, 267, 95, 496, 619, 17, 251, 278, 66, 258, 435, 552, 539, 275, 245, 163, 325, 431, 361, 532, 517, 397, 439, 408, 443, 294, 131, 32, 24, 51, 10, 6, 32, 79, 74, 40, 29, 5, 37, NA, 
+#> 27, NA, 0, 20, 313, 647, 615, 622, 575, 580, 530, 429, 517, 457, 609, 551, 415, 384, 502, 201, 271, 321, 135, 11, 78, 89, 0, 9, 16, 9, 13, 6, 5, 2, NA, NA, NA, 2, 0, 0, NA, 2, NA, NA, NA, 0, 0, 38, 175, 290, 266, 401, 531, 581, 441, 487, 542, 253, 315, 462, 56, 403, 330, 227, 16, 1, 8, 19, 0, 3, 2, 13, 0, 1, 0, 0, NA, NA, 7, 4, 370, 221, 536, 469, 324, 199, 166, 187, 57, 53, 23, 57, 29, 4, 19, 95, 73, 84, 94, NA, NA, 19, 567, 578, 479, 580, 478, 498, 494, 462, 104, 70, 93, 81, 64, 90, 40, 75, 63, 
+#> 72, 70, 12, NA, 4, 2, 2, 1, 2, 0, 190, 304, 606, 622, 642, 589, 521, 604, 573, 530, 520, 489, 419, 535, 451, 592, 461, 411, 127, 102, 2, 28, 65, 78, 52, 1, 40, 48, 83, 86, 84, 74, 90, NA, 1, 29, 12, 279, 603, 652, 677, 569, 599, 631, 394, 587, 640, 530, 372, 458, 37, 58, 34, NA, 24, 0, NA, NA, 5, 0, NA, NA, NA, NA, 0, NA, NA, 28, 45, 58, 14, 35, 1, 5, 4, 0, 5, 85, 397, 443, 539, 394, 458, 444, 423, 282, 129, 30, 11, 212, 596, 581, 582, 569, 480, 593, 592, 573, 626, 577, 537, 477, 414, 327, 190, 162, 
+#> 0, 8, 4, 1, 10, 8, 9, 7, 8, 0, NA, 0, NA, 0, 0, NA, 2, NA, 491, 547, 560, 566, 597, 516, 524, 40, 457, 365, 415, 499, 490, 264, 16, 232, 107, 636, 600, 623, 616, 563, 497, 278, 229, 373, 438, 293, 162, 84, 14, 163, 112, 606, 607, 641, 610, 614, 613, 562, 558, 627, 410, 81, 358, 457, 586, 561, 605, 306, 430, 588, 542, 568, 357, 306, 168, 61, 491, 280, 608, 596, 569, 640, 570, 505, 599, 333, 172, 94, 321, 488, 478, 416, 326, 385, 495, 134, 318, 293, 345, 85, 222, 61, 84, 67, 322, 641, 526, 603, 569, 
+#> 545, 289, 133, 10, 222, 411, 493, 313, 558, 596, 559, 510, 304, 50, 561, 100, 447, 155, 60, NA, NA, NA, NA, NA, 76, 94, 72, 35, 13, 46, 2, 46, 18, 44, 475, 534, 625, 559, 612, 336, 159, 16, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, 2, 4, 4, 3, 2, 3, 1, 72, 58, 27, 2, 12, 9, 41, 48, 48, 47, 72, 95, 80, 71, 75, 54, 1, 26, 508, 584, 588, 560, 596, 584, 468, 498, 577, 586, 456, 50, 281, 327, 514, 522, 502, 128, 306, 280, 10, 95, 394, 388, 320, 539, 589, 590, 468, 441, 80, 476, 284, 95, 557, 
+#> 691, 680, 624, 657, 635, 551, 611, 639, 622, 439, 538, 34, 233, 564, 687, 578, 648, 573, 635, 558, 622, 173, 353, 366, 384, 409, 486, 485, 64, 59, 180, 418, 510, 523, 482, 528, 428, 8, 249, 231, 28, NA, NA, 0, 0, NA, NA, NA, NA, NA, NA, NA, NA, 1, 7, 10, 6, 1, 0, 0, 0, 2, 0, 0, 96, 600, 630, 610, 227, 481, 572, 366, 73, 231, 429, 396, 360, 388, 583, 430, 111, 218, 256, 61, 350, 574, 578, 561, 581, 327, 176, 398, 113, 40, 183, 384, 540, 233, 300, 439, 500, 562, 293, 214, 12, 24, 205, 289, 204, 449, 
+#> 498, 462, 151, 299, 260, 15, 104, 94, 105, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0, 0, 23, 85, 71, NA, NA, NA, 6, NA, 2, 26, 19, 17, 64, 5, 4, 2, 0, 6, 4, NA, 2, 2, 0, NA, NA, NA, NA, NA, 64, NA, NA, NA, 2, NA, NA, NA, NA, NA, 24, 2, 262, 559, 578, 583, 391, 613, 447, 586, 640, 633, 309, 513, 162, 406, 113, 237, 7, 34, 303, 340, 352, 190, 279, 336, 293, 97, 5, 139, 98, 174, 122, 415, 474, 472, 462, 453, 285, 267, 75, 376, 120, 415, 158, 452, 191, 254, 156, 521, 584, 450, 251, 
+#> 666, 608, 46, 576, 437, 465, 609, 615, 418, 665, 609, 636, 454, 525, 660, 538, 502, 10, 26, 411, 216, 18, 127, 278, 516, 514, 507, 341, 503, 374, 160, 566, 478, 53, 557, 550, 490, 523, 483, 467, 84, 135, 317, 423, 366, 174, 509, 521, 236, 299, 62, 546, 492, 462, 344, 580, 386, 469, 337, 266, 481, 341, 29, 350, 252, 477, 478, 401, 175, 23, 53, 24, 461, 382, 268, 111, 240, 456, 384, 217, 79, 49, 11, 65, 701, 663, 591, 655, 629, 333, 199, 492, 594, 102, 122, 261, 136, 171, 34, 188, 95, 50, NA, 0, NA, 
+#> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2, NA, 9, 37, 59, 76, 42, 28, 4, 40, 28, 71, 49, 25, 57, NA, 26, NA, NA, 0, NA, NA, NA, NA, NA, NA, NA, 55, 56, 69, 0, NA, 0, 0, 0, NA, 0, 0, 0, 1, 0, NA, 15, 391, 351, 454, 379, 456, 438, 389, 369, 406, 514, 447, 422, 338, 0, 50, 76, 71, 90, 85, 77, 7, 31, 68, 73, 44, NA, NA, 3, 66, 62, 7, 59, 10, 104, 445, 530, 598, 613, 642, 631, 458, 485, 207, 7, 51, 639, 455, 636, 443, 642, 641, 598, 403, 427, 552, 265, 563, 474, 158, 390, 309, 361, 424, 418, 564, 587, 
+#> 476, 493, 491, 614, 323, 374, 63, 214, 8, 3, 303, 354, 549, 549, 553, 526, 523, 237, 150, 305, 154, 3, 6, 4, 2, 1, 3, 5, 1, 1, 1, 3, 0, 1, 0, 2, 0, 1, 0, 0, 0, 0, 26, 452, 236, 445, 133, 316, 500, 423, 427, 517, 393, 347, 279, 192, 538, 304, 567, 582, 344, 552, 258, 71, 13, 125, 29, 560, 658, 636, 599, 495, 613, 548, 582, 589, 107, 532, 433, 432, 289, 141, 1, 90, 338, 197, 320, 233, 165, 40, 50, 31, 35, 412, 590, 578, 610, 544, 180, 540, 327, 481, 295, 75, 321, 551, 609, 572, 579, 375, 325, 470, 
+#> 417, 554, 626, 600, 555, 494, 156, 243, 292, 272, 10, 234, 192, 466, 584, 616, 625, 577, 438, 502, 403, 237, 317, 595, 562, 97, 236, 119, 239, 174, 1, 3, 10, NA, NA, 23, 67, 26, 33, 0, NA, NA, NA, 0, NA, 159, 439, 588, 325, 614, 464, 533, 384, 427, 496, 517, 224, 538, 583, 396, 156, 507, 241, 346, 18, 41, 4, 295, 195, 284, 344, 315, 412, 395, 446, 398, 385, 180, 62, 0, 5, 39, 7, NA, NA, 0, NA, NA, 0, NA, 0, NA, 0, NA, NA, NA, NA, NA, 408, 529, 575, 588, 600, 565, 513, 491, 389, 454, 436, 393, 554, 
+#> 251, 256, 171, NA, NA, NA, NA, NA, 90, 36, 37, 23, 36, 24, 65, 57, 31, 9, 13, 7, 140, 525, 564, 560, 590, 552, 545, 521, 522, 373, 351, 180, 82, 396, 439, 515, 405, 71, 284, 201, 2, 11, 30, 46, 12, 8, 7, 23, 10, 13, NA, NA, 1, NA, 3, 1, 0, NA, 10, 67, 76, 81, 65, 82, 73, 31, 6, 34, NA, 0, 0, 1, 0, 23, 61, 41, 69, 50, 18, 38, 10, 3, 14, 328, 196, 268, 505, 543, 524, 371, 360, 323, 310, 92, 114, 59, 127, 21, 57, NA, NA, NA, 1, NA, NA, 0, NA, 0, NA, NA, NA, NA, NA, NA, 0, NA, 0, 0, 1, 1, NA, 0, NA, 
+#> 0, 0, NA, 2, 0, 0, 0, 475, 392, 270, 55, 2, 68, 162, 47, 68, 34, 5, 295, 536, 551, 557, 528, 531, 255, 302, 424, 528, 617, 564, 564, 529, 566, 170, 343, 523, 297, 72, 76, 211, 211, 211, 283, 411, 444, 501, 525, 522, 339, 429, 491, 44, 382, 643, 615, 634, 608, 661, 101, 500, 630, 426, 215, 264, 158, 360, 90, 48, 74, 60, 344, 419, 174, 133, 307, 170, 28, 155, 66, 355, 389, 220, 554, 495, 571, 590, 564, 350, 235, 227, 169, 123, 443, 555, 546, 613, 610, 437, 553, 605, 619, 646, 639, 377, 617, 577, 628, 
+#> 633, 590, 548, 517, 0, NA, 0, NA, NA, NA, NA, NA, NA, NA, NA, 6, 4, 4, 7, 0, 4, 28, 250, 581, 346, 575, 471, 545, 492, 73, 10, 331, 477, 287, 419, 71, 156, 51, 93, 150, 216, 186, 147, 9, 163, 419, 564, 530, 395, 86, 504, 442, 315, 94, 508, 164, 134, 12, 29, 19, 70, 45, 85, 73, 51, 50, 76, 83, NA, NA, NA, 0, NA, NA, 1, NA, 59, 76, 77, 84, 84, 89, 71, 58, 60, 56, 1, 1, 16, 13, 143, 341, 569, 545, 592, 429, 446, 65, 1, 19, 445, 184, 299, 215, 292, 203, 418, 451, 409, 137, 356, 220, 167, 116, 194, 146, 
+#> 128, 46, 62, 22, 558, 540, 399, 588, 474, 235, 499, 149, 278, 613, 424, 357, 147, 390, 393, 439, 518, 198, 33, 455, 597, 548, 565, 582, 433, 260, 545, 608, 633, 606, 520, 364, 197, 166, 300, 491, 428, 528, 131, 359, 387, 98, 413, 551, 538, 580, 519, 510, 473, 539, 391, 506, 517, 532, 552, 355, 480, 476, 403, 390, 373, 42, 367, 340, 12, 42, 96, 81, 83, 88, 88, 91, 63, 72, 68, 67, 75, 64, 80, 64, 59, 68, 69, 76, 43, 25, 62, 13, 42, 11, 49, 53, 95, 522, 516, 462, 36, 389, 265, 372, 277, 61, 2, 8, 7, 
+#> 2, 5, 1, NA, NA, 0, 0, 7, 4, 5, 4, 29, 7, 2, 1, 0, 0, 0, 0, 1, NA, 0, NA, NA, NA, NA, NA, NA, 1, NA, 51, 439, 396, 484, 585, 352, 411, 140, 495, 540, 429, 249, 275, 381, 398, 74, 83, 175, 174, 573, 624, 594, 573, 425, 494, 391, 200, 361, 381, 35, 245, 156, 292, 617, 589, 529, 579, 445, 283, 404, 596, 510, 627, 371, 408, 215, 134, 134, 290, 365, 35, 341, 429, 374, 461, 408, 408, 435, 345, 348, NA, NA, NA, NA, 37, 38, 62, 67, 72, 82, 49, 22, 0, 16, 16, 60, 67, 62, 74, 77, 81, 56, 63, 76, 63, 71, 65, 
+#> 68, 57, 68, 53, 54, 64, 53, 56, 19, 545, 623, 586, 637, 571, 589, 392, 517, 588, 412, 588, 563, 610, 575, 590, 253, 263, 110, 61, 45, 493, 606, 592, 554, 401, 492, 586, 183, 590, 588, 469, 456, 465, 109, 283, 152, 48, 195, 80, 220, 459, 485, 330, 243, 219, 407, 50, 160, NA, 0, NA, 0, NA, NA, NA, NA, NA, NA, 0, 67, 532, 515, 559, 593, 550, 477, 510, 375, 492, 462, 394, 392, 274, 30, 79, 76, 75, 49, 53, 46, 1, 1, 26, 1, NA, 0, NA, NA, 0, NA, 0, 0, 0, 565, 600, 602, 445, 538, 578, 611, 603, 603, 400, 
+#> 521, 300, 554, 586, 535, 400, 448, 568, 566, 540, 562, 590, 600, 571, 605, 572, 100, 191, 559, 573, 549, 399, 493, 527, 530, 585, 486, 582, 68, 523, 546, 240, 105, 466, 531, 186, 60, 51, 244, 489, 663, 588, 621, 651, 634, 638, 622, 603, 435, 558, 625, 612, 283, 105, 83, 563, 260, 575, 561, 544, 606, 410, 419, 502, 383, 516, 82, 343, 171, 81, 309, 41, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 21, 280, 420, 473, 363, 492, 639, 597, 579, 600, 363, 442, 408, 511, 527, 504, 547, 502, 302, 96, 327, 98, 398, 
+#> 124, 486, 510, 589, 619, 603, 594, 403, 552, 547, 555, 595, 593, 510, 476, 298, 135, 143, 611, 578, 514, 502, 468, 431, 290, 43, 97, 47, 419, 487, 528, 490, 395, 494, 272, 568, 454, 438, 314, 497, 477, 454, 108, 150, 315, 17, 62, 74, 65, 75, 71, 37, 56, 78, 79, 51, 62, 7, 2, 1, 2, 68, 64, 54, 8, 2, 13, 579, 356, 54, 334, 317, 132, 14, 545, 619, 406, 551, 608, 628, 507, 578, 584, 438, 524, 336, 103, 43, 32, 171, 487, 544, 528, 135, 326, 511, 499, 542, 556, 502, 556, 470, 328, 497, 486, 60, 90, 545, 
+#> 584, 536, 422, 352, 541, 533, 606, 562, 461, 532, 277, 327, 127, 1, 232, 557, 659, 607, 464, 567, 616, 595, 557, 322, 574, 334, 397, 80, 368, 487, 175, 557, 236, 258, 322, 213, 519, 444, 136, 301, 549, 501, 515, 492, 576, 573, 584, 151, 494, 418, 268, 3, 103, 138, 129, 144, 368, 459, 285, 485, 510, 257, 342, 12, 126, 269, NA, NA, NA, NA, NA, NA, 54, 43, 391, 367, 608, 653, 527, 301, 55, 333, 323, 72, 13, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0, NA, NA, NA, 4, 0, 1, NA, 0, NA, 
+#> 0, NA, 2, 0, 0, 154, 241, 346, 291, 480, 488, 295, 35, 143, 57, 94, 69, 159, 160, 20, 14, 6, 4, 14, 42, 53, 117, 74, 576, 569, 459, 481, 662, 493, 600, 465, 543, 517, 352, 180, 208, 339, 276, 367, 469, 173, 317, 387, 255, 426, 483, 560, 286, 542, 542, 565, 576, 574, 613, 611, 582, 250, 567, 568, 579, 513, 266, 177, 344, 167, 153, 549, 420, 477, 547, 498, 492, 443, 494, 129, 336, 227, 7, 116, 200, 13, 178, 349, 432, 316, 379, 82, 145, 337, 291, 137, 74, 288, 558, 653, 630, 475, 551, 671, 558, 542, 
+#> 603, 595, 448, 343, 587, 562, 137, 14, 125, 211, 271, 583, 608, 632, 604, 424, 530, 527, 573, 549, 589, 565, 428, 49, 116, 8, 358, 454, 458, 551, 384, 492, 398, 524, 557, 581, 565, 572, 553, 539, 164, 261, 173, NA, NA, NA, 3, 64, 75, 28, 40, 63, 81, 76, 50, 31, 30, 83, 86, 52, 7, 0, 2, 2, 2, 0, 0, NA, NA, NA, NA, NA, 0, 0, 0, 0, 0, 79, 515, 373, 537, 581, 582, 463, 353, 568, 475, 483, 528, 186, 211, 69, 547, 405, 434, 547, 556, 18, 149, 394, 534, 482, 503, 478, 234, 455, 398, 399, 309, 312, 593, 
+#> 657, 624, 442, 557, 424, 83, 467, 511, 57, 80, 182, 207, 85, 158, 30, 216, 249, 122, 189, 181, 173, 423, 290, 399, 397, 260, 87, 156, 341, 427, 185, 97, 218, 23, 461, 585, 594, 412, 546, 602, 634, 609, 610, 559, 236, 431, 431, 429, 159, 352, 590, 246, 345, 637, 315, 254, 134, NA, 31, 80, 77, 70, 72, 65, NA, NA, NA, NA, NA, NA, 3, 3, 3, 3, 1, 4, 35, 222, 320, 522, 451, 163, 309, 337, 77, 77, 585, 470, 270, 164, 79, 2, 2, 4, 3, 3, 3, 0, 1, 0, 0, 0, 1, 0, 0, 49, 312, 208, 239, 318, 146, 86, 434, 536, 
+#> 634, 616, 580, 601, 388, 572, 270, 299, 162, 361, 34, 99, 142, 15, 5, 341, 482, 422, 344, 540, 538, 584, 454, 513, 484, 565, 601, 427, 345, 328, 49, NA, NA, NA, NA, 34, 66, 46, 28, 65, 48, 29, 29, 48, 4, 50, 3, 126, 475, 415, 514, 198, 570, 341, 194, 148, 348, 268, 18, 143, 436, 66, 51, 20, 91, 595, 451, 483, 597, 405, 309, 444, 409, 524, 451, 493, 84, 521, 335, 389, 100, 215, 41, 9, 7, NA, NA, NA, NA, 0, NA, NA, NA, NA, 32, 7, 97, 83, 80, 89, 36, 80, 8, 6, 15, 50, 26, 14, 419, 223, 544, 575, 531, 
+#> 435, 570, 536, 285, 422, 330, 346, 367, 44, 0, 203, 83, 585, 541, 574, 506, 543, 406, 526, 546, 486, 452, 273, 208, 171, 185, 11, 315, 386, 416, 113, 346, 426, 286, 135, 451, 244, 356, 305, 46, 217, 464, 596, 607, 545, 373, 562, 655, 560, 619, 590, 539, 495, 505, 516, 404, 224, 406, 426, 94, 219, 355, 539, 394, 550, 635, 527, 609, 524, 614, 487, 79, NA, NA, 0, NA, NA, NA, NA, 0, NA, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, NA, NA, NA, NA, 0, 0, NA, 0, NA, NA, NA, 0, NA, 1, 512, 569, 378, 438, 425, 
+#> 200, 409, 458, 30, 66, 75, 69, 20, 30, 56, 6, 5, 63, 65, 26, 4, 0, 53, 290, 484, 550, 561, 571, 522, 439, 529, 436, 569, 568, 554, 449, 483, 365, 187, 352, 69, 196, 17, 185, 468, 301, 520, 527, 575, 588, 450, 35, 60, 208, 5, 16, 337, 130, 527, 629, 612, 645, 615, 331, 445, 93, 543, 542, 583, 494, 21, 254, 46, 138, 349, 445, 387, 538, 484, 579, 633, 561, 662, 593, 114, 461, 391, 99, 84, 532, 316, 262, 598, 426, 564, 498, 642, 643, 625, 604, 577, 556, 517, 478, 380, 412, 98, 117, 154, 321, 452, 505, 
+#> 496, 440, 494, 557, 526, 480, 578, 508, 193, 490, 432, 503, 345, 17, 276, 71, 206, 101, 62, 61, 289, 558, 431, 502, 599, 204, 525, 500, 476, 447, 498, 467, 350, 365, 250, 90, 29, 217, NA, NA, NA, NA, NA, NA, 4, 2, 11, 6, 7, 5, 2, 1, 3, 4, 2, 5, 22, 42, 32, 23, 59, 19, 24, NA, 19, 25, 4, 0, 40, 385, 496, 400, 484, 287, 312, 481, 478, 340, 441, 505, 453, 446, 295, 325, 73, 320, 261, 567, 408, 563, 551, 509, 499, 591, 537, 540, 612, 445, 561, 485, 420, 126, 240, 549, 602, 591, 587, 522, 568, 594, 622, 
+#> 615, 553, 607, 417, 146, 367, 131, 343, NA, NA, NA, NA, NA, NA, 7, 5, 6, 60, 0, 0, 5, 1, 22, 69, 192, 204, 163, 406, 543, 563, 358, 470, 564, 540, 244, 266, 364, 45, 16, 16, 277, 333, 489, 414, 489, 246, 481, 438, 347, 457, 579, 395, 279, 63, 21, 7, 0, 5, 4, 4, NA, 0, 1, 0, 0, 0, 2, 12, 7, 3, 9, 28, 3, 3, 1, 0, 0, 0, 0, 0, 48, 582, 654, 626, 627, 593, 614, 644, 482, 643, 654, 623, 639, 596, 634, 663, 546, 683, 63, 581, 103, 478, 296, 175, 261, 167, 261, 117, 298, 132, 228, 148, 35, 268, 68, 156, 
+#> 54, 142, 601, 587, 686, 502, 554, 632, 624, 607, 601, 605, 572, 583, 510, 444, 522, 373, 463, 156, 523, 132, 490, 228, 366, 568, 468, 154, 452, 456, 607, 603, 496, 404, 71, 344, 142, 128, 10, NA, NA, NA, 4, 5, 5, 4, 3, 7, 23, 62, 62, 4, 2, 5, 4, 4, 2, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 70, 48, 57, 57, 58, 62, 53, 53, 54, 18, 0, 2, 5, 3, 2, 8, 3, 3, 3, 0, 4, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 4, 44, 63, 64, 69, 7, 2, 0, 0, 5, 3, 2, 69, 38, 9, 39, 14, 73, 221, 580, 559, 598, 631, 608, 597, 436, 554, 
+#> 626, 614, 619, 565, 565, 600, 546, 561, 550, 369, 502, 356, 505, 520, 133, 461, 460, 117, 61, 1, 29, 82, 45, 18, 89, 81, 64, 74, 81, 82, 23, 45, 75, 17, 2, 40, 14, 61, 46, 1, 3, NA, NA, NA, 15, 7, NA, 6, 5, 3, 2, 0, 0, 0, 0, 87, 684, 604, 532, 529, 83, 635, 658, 156, 165, 230, 469, 431, 163, 160, 130, 561, 601, 421, 483, 554, 375, 205, 559, 500, 196, 521, 392, 408, 137, 338, 471, 252, 294, 68, 112, 460, 408, 329, 519, 595, 594, 531, 589, 569, 589, 511, 476, 458, 303, 165, 67, 456, 386, 352, 343, 
+#> 597, 380, 431, 265, 519, 361, 200, NA, 11, 14, 42, 74, 14, 55, 72, 63, 37, 37, 0, 56, 45, 11, NA, NA, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 0, 0, 0, NA, NA, NA, NA, NA, NA, NA, NA, 28, NA, NA, NA, 4, 6, 6, 2, 4, 6, 57, 7, 0, 5, 15, 38, 68, 87, 213, 324, 389, 428, 479, 530, 473, 470, 428, 129, 271, 381, 513, 520, 443, 583, 608, 463, 623, 608, 622, 593, 53, 273, 106, 399, 582, 592, 656, 625, 560, 595, 570, 586, 565, 572, 209, 281, 278, 190, 233, NA, NA, NA, NA, NA, 50, 50, 61, 22, 0, 8, 0, 0, 12, 
+#> 7, NA, NA, 0, 0, NA, NA, NA, 0, NA, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 93, 583, 486, 594, 542, 482, 165, 16, 234, 20, 54, 40, 48, 72, 61, 45, 18, 6, 1, 0, 0, 0, 0, 0, 1, 151, 230, 316, 357, 45, 67, 527, 594, 549, 464, 585, 304, 107, 223, 267, 189, 193, 316, 19, 268, 541, 519, 342, 119, 582, 187, 355, 572, 560, 524, 216, 12, 86, 113, 382, 542, 501, 569, 370, 392, 375, 141, 361, 573, 550, 461, 485, 251, 37, NA, NA, NA, 1, NA, NA, 0, NA, NA, 75, 72, 82, 78, 66, 36, 20, 63, 0, 2, 7, 3, 9, 0, 0, 0, 
+#> 3, 11, 35, 48, 6, 33, 379, 422, 429, 630, 614, 610, 619, 582, 611, 590, 581, 417, 113, 446, 397, 133, 585, 518, 428, 421, 107, 244, 79, 47, 166, 455, 313, 510, 389, 121, 476, 508, 476, 392, 209, 77, 10, 302, 594, 480, 533, 425, 573, 571, 529, 184, 213, 453, 199, 3, 524, 598, 597, 601, 567, 579, 572, 548, 555, 472, 358, 411, 513, 439, 488, 317, 455, 387, 13, 156, 191, 149, 309, 22, 10, 117, 350, 170, 38, 0, 5, 1, 3, 0, 2, 0, 2, 2, 2, 3, 0, 0, 0, 0, 0, 0, 58, 663, 372, 617, 637, 521, 333, 266, 582, 
+#> 510, 554, 606, 308, 220, 353, 167, 547, 554, 403, 478, 7, 16, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 130, 91, 488, 519, 530, 573, 569, 574, 505, 570, 458, 521, 524, 538, 598, 94, 335, 368, 518, 557, 628, 544, 457, 490, 514, 519, 368, 50, 37, 27, 325, 623, 610, 571, 599, 614, 394, 612, 520, 607, 574, 541, 383, 593, 562, 0, 1, 48, 42, 73, 61, 74, 73, 79, 64, 60, 64, 25, 24, 37, 0, 22, 61, 60, NA, NA, 8, NA, NA, NA, NA, NA, 3, 2, 2, 2, 1, 5, 5, 2, 1, 18, 3, 73, 51, 42, 26, 13, NA, NA, NA, 3, 79, 75, 60, 1, 16, 
+#> 0, 2, 48, 3, 5, 6, 29, 5, 6, 5, 1, 0, 1, 0, 0, 0, 0, 0, 0, NA, NA, NA, NA, NA, NA, NA, 1, 66, 55, 53, NA, 32, 31, 4, 292, 263, 214, 608, 601, 367, 232, 488, 221, 532, 529, 539, 508, 590, 503, 208, 539, 537, 585, 676, 631, 625, 258, 495, 609, 95, 310, 322, 134, NA, 0, 0, NA, NA, NA, NA, NA, 3, 4, 25, 3, 4, 2, 3, 4, 5, 3, 7, 2, 1, 53, 166, 313, 320, 320, 163, 417, 381, 315, 441, 385, 443, 160, 45, 313, 647, 690, 651, 382, 199, 554, 328, 62, 319, 572, 236, 65, 64, 93, 530, 578, 580, 587, 553, 583, 547, 
+#> 509, 546, 557, 299, 544, 398, 421, 240, 397, 176, 536, 519, 562, 575, 510, 520, 560, 535, 264, 417, 446, 254, 458, 24, 269, 176, 131, 89, 186, 60, 113, 192, 496, 415, 472, 102, 335, 580, 526, 511, 587, 607, 623, 505, 540, 553, 407, 494, 440, 0, 5, 5, 1, 0, 0, 0, 0, 0, 0, 3, 0, 2, 0, 0, 3, 0, 0, 0, 3, 4, 2, 0, 0, 3, 0, 1, 0, 0, 1, 0, 0, 0, 0, 455, 324, 636, 664, 563, 616, 654, 581, 143, 613, 383, 137, 196, 477, 35, 165, 551, 563, 588, 569, 319, 207, 538, 540, 385, 544, 29, 412, 0, 14, 188, 358, 379, 
+#> 505, 484, 511, 481, 449, 474, 465, 506, 168, 383, 383, 344, 69, 535, 624, 588, 593, 590, 606, 202, 305, 593, 595, 561, 465, 323, 329, 431, 617, 517, 585, 562, 493, 544, 587, 586, 623, 598, 494, 503, 460, 243, 299, 25, 327, 14, 543, 467, 487, 107, 284, 275, 314, 166, 285, 18, 45, 356, 501, 552, 585, 588, 475, 625, 485, 341, 89, 30, 111, 160, 278, 228, 69, 38, 11, 379, 396, 542, 543, 540, 545, 534, 493, 308, 552, 571, 444, 544, 162, 94, 143, 0, 17, 384, 336, 564, 561, 581, 520, 372, 557, 600, 551, 
+#> 451, 573, 580, 534, 606, 549, 521, 692, 647, 679, 704, 679, 695, 678, 686, 639, 680, 677, 227, 402, 520, 359, 398, 45, 124, 288, 554, 324, 637, 154, 487, 631, 622, 259, 115, 160, 327, 328, 226, 149, 425, 412, 458, 523, 422, 447, 450, 403, 387, 439, 349, 216, 95, 63, 18, 261, 382, 422, 626, 563, 626, 228, 390, 540, 607, 638, 661, 242, 414, 494, 324, 126, 1, 0, 164, 335, 66, 108, 152, 458, 436, 303, 473, 578, 372, 282, 248, 404, 204, 157, NA, NA, NA, 0, 0, 5, 0, 1, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 590, 
+#> 590, 591, 592, 591, 535, 565, 524, 568, 587, 579, 607, 391, 633, 602, 21, 473, 387, 540, 392, 262, 209, 483, 550, 547, 614, 618, 609, 524, 579, 379, 579, 586, 464, 341, 19, 318, 102, 413, 558, 509, 636, 538, 505, 138, 261, 426, 440, 329, 407, 122, 4, 5, 5, 4, 4, 62, 25, 2, 0, 4, NA, 3, 0, 2, 0, 3, 0, 0, 1, 2, 102, 598, 478, 474, 449, 468, 416, 451, 279, 339, 529, 342, 380, 168, 0, 281, 391, 126, 371, 57, 15, 49, 83, 67, 160, 98, 0, 5, 4, 6, 4, 7, 3, 62, 51, 51, 51, 13, 53, 34, 0, 1, 101, 473, 325, 
+#> 428, 409, 337, 410, 433, 497, 530, 491, 202, 175, NA, 1, NA, 4, 5, 2, 4, 6, 54, 0, 0, 0, 0, 99, 365, 593, 607, 622, 662, 636, 653, 654, 648, 514, 632, 635, 401, 235, 322, 156, 1, 1, 0, 0, 0, 0, 0, 566, 449, 570, 477, 80, 197, 186, 381, 84, 106, 281, 236, 132, 52, 15, 62, 54, 71, 38, 62, 26, 0, 1, 8, 50, 574, 696, 682, 608, 637, 647, 579, 453, 477, 496, 475, 561, 362, 219, 226, 13, 374, 607, 624, 622, 620, 647, 672, 638, 638, 442, 575, 543, 417, 557, 496, 155, 1, 2, 4, 0, 1, 1, 3, 4, 4, 65, 64, 59, 
+#> 65, 54, 53, 52, 4, 0, 0, 7, 31, 46, 44, 59, 7, 11, 6, 5, 0, 5, 5, 16, 8, 39, NA, 2, 0, 1, 6, 9, 6, 2, 3, 4, 4, 1, 92, 74, 53, 18, 10, 28, 44, 1, 0, 3, 0, 0, 0, 0, 0, 54, 454, 218, 477, 561, 581, 539, 605, 594, 175, 567, 623, 532, 129, 418, 334, 101, 164, 263, 153, 487, 539, 537, 606, 595, 564, 439, 584, 349, 199, 298, 486, 247, 183, 212, 352, 349, 603, 577, 466, 539, 545, 202, 12, 156, 223, 256, 49, 0, 13, 0, 2, 0, 0, 1, 0, 0, 0, 0, 0, 53, 75, 567, 512, 608, 474, 11, 226, 22, 27, 58, 74, 92, 64, 
+#> 63, 0, 1, 4, 2, 31, 200, 390, 534, 414, 560, 210, 353, 13, 524, 399, 519, 107, 88, 2, 96, 608, 678, 536, 620, 611, 584, 427, 630, 590, 505, 243, 424, 169, 205, 494, 606, 486, 604, 509, 412, 309, 463, 548, 308, 15, 308, 508, 551, 597, 492, 598, 500, 573, 589, 419, 445, 218, 244, 213, 551, 379, 577, 550, 420, 30, 57, 45, 59, 70, 45, 26, 21, 30, 23, 35, 68, 77, 61, 0, 40, 7, 0, 49, 278, 20, 415, 303, 412, 448, 582, 601, 558, 549, 416, 541, 518, 525, 324, 518, 518, 528, 1, 0, 4, 3, 8, 6, 2, 7, 78, 42, 
+#> 62, 35, 134, 439, 558, 670, 444, 73, 119, 191, 123, 414, 387, 473, 30, 162, 4, 129, 12, 545, 333, 358, 349, 556, 238, 12, 156, 79, 8, 411, 599, 570, 538, 184, 393, 531, 348, 444, 194, 206, 529, 545, 644, 628, 208, 286, 381, 193, 609, 601, 589, 451, 53, 440, 392, 31, 199, 215, 436, 557, 344, 550, 593, 624, 467, 513, 450, 316, 127, 32, 159, 520, 547, 572, 562, 266, 211, 377, 493, 540, 605, 561, 440, 50, 154, 418, 434, 587, 352, 384, 66, 217, 589, 620, 404, 635, 460, 261, 181, 195, 538, 510, 475, 587, 
+#> 559, 598, 603, 620, 595, 556, 449, 589, 487, 604, 631, 549, 567, 298, 17, 36, 462, 357, 414, 442, 53, 22, 188, 497, 546, 576, 588, 572, 577, 574, 588, 209, 339, 605, 609, 563, 573, 502, 24, 195, 133, 390, 527, 558, 652, 587, 543, 477, 305, 266, 107, 193, 41, 173, 71, 7, 73, 144, 513, 524, 582, 570, 444, 563, 575, 566, 549, 438, 546, 548, 543, 533, 467, 208, 36, 368, 407, 375, 424, 287, 518, 252, 494, 466, 368, 452, 478, 248, 5, 19, 12, 56, 62, 60, 19, 23, 26, 56, 61, 66, 53, 66, 7, 6, 28, 32, 0, 
+#> 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 7, 5, 7, 6, 39, 6, 3, 3, 1, 3, 2, 0, 1, 4, 6, 62, 58, NA, 1, 1, 2, 6, 1, 62, 77, 71, 1, 5, 63, 72, 71, 6, 192, 474, 489, 461, 579, 517, 407, 551, 497, 398, 137, 123, 1, 221, 483, 448, 174, 467, 451, 463, 470, 365, 435, 423, 364, 112, 222, 47, 77, 39, 71, 73, 66, 64, 70, 49, 28, 29, 38, 0, 6, 0, 2, 0, 2, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 39, 312, 581, 529, 610, 616, 550, 557, 260, 286, 569, 467, 7, 132, 385, 411, 526, 387, 224, 58, 74, 23, 433, 
+#> 271, 472, 376, 226, 456, 424, 375, 211, 133, 94, 18, 314, 603, 613, 576, 588, 616, 611, 548, 572, 622, 555, 611, 429, 492, 572, 558, 492, 623, 591, 618, 388, 236, 627, 436, 610, 605, 585, 258, 292, 2, 31, 38, 2, 72, 87, 78, 72, 59, 64, 22, 4, 42, 0, 32, 42, 16, 177, 282, 197, 264, 580, 343, 274, 603, 156, 325, 345, 259, 15, 376, 44, 97, 273, 128, 460, 641, 561, 563, 621, 611, 632, 230, 163, 66, 265, 317, 188, 517, 472, 642, 583, 655, 644, 623, 608, 621, 624, 593, 533, 555, 550, 539, 582, 207, 2, 
+#> 386, 573, 666, 690, 668, 691, 639, 645, 541, 656, 631, 611, 51, 468, 14, 95, 65, 460, 580, 568, 186, 349, 445, 512, 445, 34, 139, 114, 220, 323, 564, 206, 342, 492, 503, 343, 158, 461, 587, 580, 618, 554, 469, 303, 377, 582, 608, 452, 566, 630, 500, 434, 64, 260, 503, 442, 1, 0, 13, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 50, 64, 62, 73, 73, 67, 2, 269, 657, 649, 193, 396, 488, 617, 539, 536, 481, 257, 528, 548, 453, 331, 110, 106, 280, 490, 592, 590, 623, 508, 296, 264, 505, 495, 77, 502, 168, NA, NA, 
+#> 2, 22, NA, 5, 3, 5, 1, 2, 41, 57, 58, 55, 61, 50, 42, 5, 21, 10, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 1, 4, 5, 2, 4, 4, 4, 2, 6, 0, 2, 633, 639, 589, 576, 543, 338, 251, 353, 304, 449, 401, 522, 482, 617, 597, 637, 626, 623, 627, 605, 595, 624, 14, 50, 200, 536, 490, 432, 544, 167, 335, 333, 107, 489, 521, 406, 536, 523, 510, 296, 545, 445, 455, 592, 134, 267, 543, 658, 530, 607, 571, 425, 398, 301, 476, 589, 124, 249, 180, 442, 504, 509, 488, 479, 466, 439, 356, 495, 465, 400, 479, 
+#> 602, 636, 539, 346, 235, 596, 446, 599, 520, 574, 229, 2, 30, 75, 70, 80, 73, 81, 83, 69, 52, 44, 34, 274, 220, 696, 647, 681, 688, 147, 563, 537, 642, 382, 610, 193, 288, 263, 575, 582, 604, 626, 535, 587, 389, 581, 430, 535, 152, 93, 353, 577, 578, 538, 544, 468, 536, 561, 554, 460, 298, 106, 488, 81, 256, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 62, 273, 124, 452, 481, 260, 33, 490, 490, 471, 484, 493, 497, 277, 3, 59, 29, 333, 536, 373, 548, 540, 201, 562, 389, 469, 172, 460, 150, 4, 5, 6, 4, 6, 9, 
+#> 3, 3, 48, 4, 5, 3, 5, 4, 2, 3, 33, 55, 59, 53, 60, 73, 49, 0, 23, 7, 1, 5, 9, 6, 0, 23, 36, 208, 79, 569, 528, 538, 491, 362, 431, 146, 292, 105, 138, 640, 655, 628, 634, 436, 128, 268, 185, 162, 98, 175, 415, 540, 553, 505, 331, 417, 422, 438, 379, 441, 257, 651, 642, 599, 304, 289, 401, 53, 601, 561, 183, 62, 24, 326, 123, 302, 157, 487, 578, 405, 612, 549, 499, 331, 331, 53, 656, 637, 628, 657, 677, 689, 716, 556, 672, 350, 567, 632, 600, 538, 517, 59, 569, 573, 588, 591, 578, 569, 581, 624, 150, 
+#> 613, 4, 165, 240, 282, 575, 618, 559, 471, 392, 411, 470, 217, 265, 126, 242, 52, 99, NA, NA, NA, NA, NA, NA, 0, NA, 0, 0, 0, 0, 1, 0, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 89, 520, 653, 626, 302, 635, 563, 641, 551, 381, 451, 611, 635, 619, 563, 598, 225, 530, 506, 60, 52, 4, 54, 14, 19, 2, NA, 2, 0, NA, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 2, 4, 2, 3, 64, 30, 18, 0, 49, 39, 44, 64, 76, 61, 67, 69, 69, 56, 62, 39, 3, 0, 0, 3, 8, 6, 5, 5, 5, 33, 
+#> 3, 0, 75, 64, 60, 24, 2, 4, 1, 0, 0, 0, 0, 0, 0, 0, 0, 43, 70, 66, 67, 61, 45, 57, 44, 21, 42, 150, 570, 646, 616, 552, 591, 630, 484, 145, 583, 591, 571, 31, 370, 22, 9, 536, 650, 559, 584, 626, 610, 580, 606, 462, 588, 135, 385, 417, 353, 444, 481, 465, 475, 505, 505, 404, 488, 109, 270, 329, 597, 339, 168, 242, 267, 209, 57, 531, 139, 73, 17, 415, 456, 570, 620, 587, 519, 208, 387, 477, 123, 94, 84, 251, 56, 254, 603, 522, 232, 375, 547, 463, 594, 506, 554, 306, 465, 565, 570, 304, 494, 279, 196, 
+#> 4, 0, 5, 3, 3, 5, 5, 6, 3, 2, 62, 448, 584, 574, 483, 273, 614, 624, 604, 1, 25, 54, 494, 331, 322, 421, 176, 148, 163, 42, 38, 187, 122, 411, 454, 636, 600, 575, 224, 230, 550, 598, 430, 106, 569, 521, 78, 298, 624, 336, 518, 487, 562, 576, 338, 170, 166, 229, 480, 351, 453, 421, 284, 276, 130, 81, 136, 26, 50, 41, 303, 538, 486, 209, 281, 112, 378, 422, 129, 357, 259, 630, 626, 644, 600, 584, 443, 606, 600, 506, 117, 435, 343, 181, 361, 546, 608, 205, 682, 528, 124, 396, 609, 327, 501, 313, 0, 
+#> 0, 2, 2, 0, 1, 7, 6, 6, 49, 0, 33, 58, 60, 67, 74, 65, 477, 473, 581, 567, 648, 653, 644, 546, 0, 3, 6, 6, 3, 3, 4, 5, 6, 4, 5, 2, 67, 4, 0, 7, 58, 614, 653, 428, 610, 525, 395, 578, 568, 214, 346, 8, 119, 467, 606, 535, 227, 429, 624, 525, 444, 136, 289, 154, 292, 606, 606, 602, 602, 403, 263, 541, 596, 0, 6, 62, 60, 89, 84, 66, 71, 72, 10, 447, 393, 544, 572, 524, 233, 118, 42, 1, 3, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 504, 358, 269, 93, 195, 385, 440, 60, 290, 326, 587, 569, 499, 321, 
+#> 465, 290, 502, 396, 447, 525, 596, 517, 487, 556, 482, 341, 395, NA, 0, 0, 4, 3, 4, 2, 2, 2, 0, 0, 3, 2, 623, 584, 629, 172, 547, 337, 456, 482, 517, 95, 0, 5, 0, 5, 2, 2, 0, 3, 47, 45, 65, 4, 3, 8, 5, 3, 3, 65, 63, 76, 41, 12, 77, 69, 55, 38, 53, 38, 0, 4, 4, 1, 6, 2, 7, 3, 5, 2, 3, 1, 136, 271, 399, 565, 568, 322, 150, 145, 171, 302, 278, 587, 481, 518, 391, 260, 554, 21, 21, 6, 0, 6, 1, 81, 70, 61, 62, 68, 57, 63, 59, 27, 96, 609, 377, 543, 470, 537, 181, 446, 315, 323, 163, 11, 25, 40, 12, 28, 
+#> 400, 532, 314, 56, 336, 569, 513, 332, 452, 553, 543, 84, 526, 469, 547, 599, 374, 581, 220, 545, 19, 25, 5, 250, 14, 173, 461, 559, 452, 73, 405, 476, 317, 202, 22, 28, 43, NA, NA, 1, 2, 3, 2, 3, 0, 0, 2, 8, 4, 2, 3, 2, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 17, 406, 162, 530, 520, 547, 557, 480, 542, 585, 614, 593, 637, 622, 583, 611, 632, 531, 564, 589, 600, 523, 448, 130, 11, 120, 40, 9, 58, 63, 68, 67, 57, 54, 4, 5, 130, 307, 115, 462, 399, 475, 585, 413, 613, 
+#> 590, 31, 240, 333, 501, 462, 462, 424, 116, 554, 624, 78, 660, 303, 577, 575, 452, 29, 48, 55, 71, 58, 77, 63, 71, 354, 446, 500, 526, 523, 104, 258, 543, 493, 164, 242, 611, 642, 633, 563, 354, 491, 637, 595, 642, 629, 641, 420, 634, 642, 612, 40, 194, 346, 504, 534, 556, 517, 550, 589, 597, 455, 364, 445, 385, 601, 406, 123, 224, 323, 329, 443, 608, 595, 597, 614, 582, 549, 538, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 2, 1, 3, 0, 41, 0, 0, 0, 0, 0, 1, 61, 294, 464, 367, 330, 390, 178, 25, 162, 596, 612, 
+#> 553, 631, 466, 583, 596, 214, 564, 580, 159, 352, 523, 381, 604, 555, 508, 378, 175, 505, 140, 356, 526, 495, 592, 554, 558, 566, 542, 0, 27, 0, 65, 13, 0, 1, 126, 645, 575, 395, 570, 168, 305, 574, 272, 62, 242, 174, 19, 460, 545, 414, 485, 458, 658, 459, 344, 568, 629, 145, 572, 563, 426, 396, 525, 588, 470, 0, 1, 0, 0, 0, 4, 0, 51, 59, 72, 6, 9, 3, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 7, 4, 4, 6, 0, 4, 5, 4, 59, 62, 254, 611, 385, 363, 526, 372, 128, 592, 569, 414, 340, 527, 663, 601, 
+#> 529, 411, 324, 451, 492, 563, 492, 212, 19, 324, 560, 151, 571, 511, 494, 429, 79, 529, 548, 501, 204, 33, 4, 23, 18, 331, 543, 610, 381, 604, 520, 191, 279, 580, 433, 570, 572, 593, 583, 548, 566, 520, 396, 587, 382, 573, 547, 36, 75, 455, 381, 365, 338, 517, 574, 632, 395, 377, 243, 488, 11, 123, 559, 589, 602, 575, 533, 424, 352, 521, 10, 22, 88, 381, 440, 487, 471, 460, 509, 472, 534, 504, 474, 464, 479, 503, 256, 82, 407, 25, 23, 502, 521, 351, 427, 370, 488, 519, 389, 73, 224, 0, 0, 413, 345, 
+#> 509, 585, 560, 626, 493, 580, 20, 6, 47, 49, 60, 38, 82, 525, 584, 513, 600, 593, 583, 2, 0, 0, 0, 0, 0, 0, 0, 13, 53, 2, 4, 2, 3, 2, 69, 523, 535, 623, 503, 599, 191, 667, 327, 633, 148, 289, 496, 578, 531, 156, 514, 602, 406, 567, 486, 432, 616, 125, 577, 315, 291, 231, 415, 536, 574, 149, 286, 166, 606, 540, 535, 21, 29, 52, 335, 325, 225, 50, 16, 18, 295, 391, 120, 123, 76, 515, 584, 450, 573, 15, 296, 626, 595, 574, 347, 235, 525, 558, 398, 437, 18, 112, 102, 339, 422, 557, 547, 249, 588, 609, 
+#> 529, 358, 489, 190, 379, 147, 22, 222, 399, 471, 551, 128, 337, 606, 524, 586, 0, 5, 54, 46, 28, 23, 5, 9, 31, 1, 4, 24, 355, 610, 546, 53, 265, 616, 110, 127, 0, 0, 2, 5, 6, 182, 594, 615, 590, 623, 20, 2, 3, 5, 60, 229, 404, 494, 564, 392, 416, 441, 240, 582, 476, 359, 516, 449, 425, 539, 279, 2, 39, 59, 68, 56, 66, 77, 556, 613, 46, 59, 221, 576, 626, 660, 638, 98, 293, 485, 363, 112, 297, 451, 552, 556, 611, 529, 36, 426, 596, 472, 478, 512, 543, 351, 613, 311, 4, 125, 506, 548, 605, 607, 579, 
+#> 612, 18, 58, 65, 3, 4, 3, 0, 15, 39, 79, 0, 331, 505, 487, 529, 201, 399, 403, 230, 23, 195, 493, 630, 224, 303, 94, 609, 615, 81, 443, 265, 609, 167, 510, 495, 579, 196, 435, 499, 491, 507, 32, 274, 579, 608, 620, 131, 508, 391, 571, 658, 596, 499, 387, 559, 197, 119, 61, 566, 193, 484, 602, 154, 213, 569, 208, 395, 296, 441, 596, 44, 538, 613) x c(25, 32, 18, 32, 22, 35, 27, 0, 1, 21, 0, 9, 33, 47, 45, 62, 44, 42, 81, 64, 65, 73, 94, 94, 63, 80, 83, 84, 77, 41, 11, 25, 62, 59, 53, 48, 76, 89, 32, 42, 43, 1, 27, 30, 59, 48, 34, 30, 25, 6, 17, 20, 11, 8, 49, 44, 106, 167, 96, 123, 112, 112, 63, 4, 18, 24, 39, 27, 20, 26, 27, 10, 17, 18, 2, 0, 6, 10, 0, 16, 34, 21, 40, 20, 36, 18, 28, 7, 8, 18, 8, 15, 31, 30, 19, 32, 20, 14, 25, 23, 0, 60, 144, 161, 134, 125, 147, 160, 110, 97, 130, 97, 103, 27, 40, 10, 7, 0, 6, 23, 14, 23, 24, 20, 31, 14, 
+#> 20, 22, 13, 20, 17, 21, 14, 8, 9, 10, 9, 6, 0, 0, 1, 36, 107, 113, 70, 95, 145, 81, 0, 90, 92, 29, 88, 53, 77, 56, 94, 36, 66, 66, 37, 40, 33, 0, 2, 6, 16, 0, 8, 4, 6, 4, 5, 4, 4, 2, 0, 1, 10, 10, 13, 15, 13, 6, 8, 11, 9, 9, 12, 14, 7, 8, 3, 1, 1, 60, 84, 72, 50, 60, 67, 82, 61, 49, 15, 43, 27, 85, 66, 71, 30, 58, 4, 61, 86, 25, 26, 103, 81, 62, 8, 50, 0, 15, 43, 39, 31, 26, 32, 41, 34, 33, 0, 12, 12, 15, 3, 1, 10, 36, 54, 36, 10, 29, 25, 37, 30, 40, 11, 10, 26, 9, 0, 0, 25, 68, 91, 92, 88, 49, 73, 
+#> 65, 102, 102, 83, 83, 109, 81, 78, 74, 81, 41, 6, 0, 78, 91, 77, 89, 33, 60, 5, 5, 12, 7, 10, 5, 12, 23, 12, 1, 0, 0, 0, 1, 8, 8, 3, 6, 4, 6, 6, 3, 2, 11, 2, 0, 16, 16, 11, 12, 16, 5, 20, 5, 6, 6, 11, 3, 1, 0, 1, 19, 45, 97, 88, 116, 106, 147, 120, 70, 69, 144, 113, 107, 83, 92, 86, 124, 99, 103, 115, 97, 48, 104, 54, 0, 16, 19, 99, 81, 91, 70, 69, 71, 63, 57, 67, 64, 56, 59, 36, 47, 35, 39, 11, 3, 1, 0, 0, 3, 81, 74, 76, 61, 59, 61, 71, 42, 59, 19, 1, 0, 40, 30, 16, 87, 81, 58, 69, 57, 70, 27, 35, 
+#> 22, 8, 20, 42, 19, 8, 26, 49, 67, 41, 26, 45, 44, 51, 31, 32, 8, 26, 20, 49, 40, 107, 30, 110, 42, 17, 124, 15, 71, 33, 3, 27, 1, 54, 96, 96, 120, 116, 122, 84, 118, 103, 88, 51, 95, 69, 97, 83, 97, 57, 73, 0, 0, 0, 4, 8, 6, 11, 6, 5, 13, 9, 8, 3, 2, 2, 4, 10, 2, 6, 3, 3, 6, 6, 8, 3, 6, 2, 1, 37, 80, 98, 107, 101, 105, 97, 97, 114, 103, 98, 100, 92, 90, 87, 91, 51, 60, 68, 45, 15, 23, 35, 64, 125, 106, 115, 77, 66, 88, 79, 76, 84, 61, 83, 101, 43, 52, 7, 70, 49, 44, 65, 66, 83, 88, 87, 29, 73, 81, 
+#> 81, 38, 33, 5, 20, 0, 0, 9, 14, 8, 8, 10, 9, 9, 12, 5, 3, 9, 6, 5, 6, 4, 4, 10, 3, 4, 6, 3, 1, 1, 3, 3, 3, 1, 16, 67, 77, 44, 42, 57, 93, 105, 90, 85, 54, 66, 31, 12, 21, 11, 35, 2, 0, 39, 104, 81, 92, 137, 125, 122, 118, 87, 91, 51, 87, 117, 79, 92, 89, 108, 80, 66, 50, 3, 0, 1, 5, 13, 25, 36, 29, 34, 17, 18, 10, 7, 1, 0, 0, 8, 31, 25, 13, 16, 4, 0, 0, 12, 73, 92, 88, 136, 94, 101, 108, 102, 90, 73, 83, 137, 107, 85, 133, 94, 79, 96, 71, 28, 10, 15, 18, 9, 12, 6, 9, 4, 5, 6, 7, 5, 8, 6, 7, 3, 0, 
+#> 3, 7, 6, 14, 18, 16, 12, 23, 14, 13, 15, 10, 13, 6, 10, 8, 11, 18, 12, 6, 6, 20, 11, 14, 15, 13, 16, 13, 13, 15, 4, 13, 1, 4, 11, 0, 1, 4, 9, 15, 16, 10, 2, 6, 1, 41, 30, 25, 32, 74, 13, 114, 90, 126, 107, 98, 97, 99, 73, 112, 74, 82, 85, 72, 15, 17, 6, 14, 8, 28, 37, 42, 53, 32, 23, 6, 19, 28, 4, 1, 0, 0, 1, 0, 9, 9, 5, 13, 8, 4, 1, 0, 2, 4, 7, 6, 5, 1, 3, 1, 32, 37, 26, 38, 39, 83, 89, 92, 103, 58, 65, 53, 54, 23, 2, 3, 0, 0, 75, 20, 64, 97, 97, 92, 71, 66, 102, 93, 126, 83, 60, 50, 24, 99, 80, 
+#> 42, 14, 1, 0, 2, 4, 8, 6, 5, 7, 0, 4, 5, 0, 1, 7, 43, 30, 67, 55, 60, 83, 66, 28, 7, 11, 65, 29, 2, 0, 12, 20, 6, 22, 14, 33, 14, 3, 0, 0, 4, 19, 25, 17, 37, 35, 25, 12, 0, 9, 4, 24, 4, 20, 31, 10, 1, 0, 8, 2, 4, 6, 0, 10, 8, 11, 9, 10, 5, 6, 6, 9, 5, 7, 4, 7, 2, 3, 0, 1, 6, 31, 36, 41, 35, 38, 17, 21, 11, 0, 3, 2, 4, 51, 100, 77, 75, 79, 60, 110, 79, 79, 92, 96, 72, 44, 24, 17, 46, 11, 1, 7, 7, 0, 2, 0, 0, 5, 73, 83, 96, 116, 116, 84, 46, 57, 65, 70, 46, 30, 0, 17, 24, 45, 35, 19, 16, 27, 16, 19, 
+#> 9, 9, 12, 0, 5, 3, 3, 0, 5, 2, 0, 3, 1, 0, 3, 15, 126, 121, 109, 61, 21, 42, 91, 91, 9, 79, 105, 20, 18, 41, 45, 25, 18, 28, 42, 30, 18, 20, 6, 10, 2, 9, 1, 15, 25, 48, 60, 37, 33, 24, 21, 8, 5, 12, 7, 9, 18, 9, 10, 17, 1, 6, 9, 8, 4, 10, 3, 7, 1, 1, 7, 13, 2, 0, 67, 89, 81, 76, 89, 62, 75, 59, 50, 79, 97, 69, 114, 63, 47, 16, 65, 86, 97, 102, 98, 67, 87, 86, 6, 55, 48, 38, 61, 48, 1, 7, 39, 61, 71, 50, 43, 94, 37, 98, 83, 46, 6, 4, 0, 3, 1, 9, 14, 5, 3, 0, 3, 3, 6, 0, 1, 2, 3, 3, 4, 0, 3, 4, 10, 
+#> 76, 83, 79, 74, 44, 42, 50, 40, 32, 50, 72, 58, 70, 57, 19, 12, 0, 0, 7, 55, 80, 88, 64, 50, 51, 47, 53, 50, 67, 72, 101, 74, 4, 3, 4, 12, 22, 26, 11, 13, 11, 38, 22, 42, 19, 6, 5, 46, 0, 22, 0, 4, 1, 29, 62, 53, 61, 34, 75, 43, 38, 2, 0, 0, 17, 23, 35, 80, 95, 69, 75, 65, 54, 22, 61, 43, 56, 10, 40, 49, 63, 96, 102, 83, 59, 51, 82, 78, 69, 21, 57, 8, 47, 64, 59, 72, 80, 71, 64, 33, 30, 1, 7, 9, 9, 8, 4, 2, 32, 44, 64, 41, 41, 36, 43, 58, 77, 46, 39, 46, 17, 36, 40, 41, 43, 16, 9, 3, 4, 10, 7, 3, 
+#> 3, 2, 6, 1, 0, 5, 1, 2, 1, 13, 56, 64, 73, 75, 62, 57, 30, 16, 28, 45, 13, 8, 86, 52, 56, 12, 43, 7, 0, 63, 78, 76, 89, 70, 70, 43, 34, 2, 15, 78, 55, 70, 64, 66, 64, 76, 38, 39, 70, 89, 91, 92, 63, 92, 125, 68, 34, 7, 38, 30, 46, 36, 48, 35, 57, 64, 32, 57, 42, 15, 44, 26, 2, 0, 0, 9, 3, 8, 2, 5, 2, 2, 2, 6, 2, 6, 8, 68, 74, 51, 79, 69, 3, 44, 48, 90, 115, 78, 62, 37, 32, 0, 40, 87, 85, 69, 67, 46, 3, 4, 38, 25, 24, 26, 30, 37, 35, 30, 32, 20, 24, 10, 21, 6, 0, 0, 2, 11, 81, 100, 83, 105, 103, 80, 
+#> 86, 115, 111, 104, 99, 43, 65, 5, 9, 4, 0, 33, 78, 77, 18, 46, 43, 7, 6, 5, 0, 3, 3, 3, 2, 1, 8, 51, 0, 59, 72, 85, 91, 86, 79, 86, 54, 63, 91, 82, 7, 2, 2, 2, 1, 19, 41, 23, 18, 5, 7, 7, 26, 36, 34, 37, 37, 21, 10, 7, 85, 53, 56, 69, 45, 79, 23, 121, 117, 80, 49, 75, 70, 44, 47, 35, 0, 42, 74, 94, 87, 74, 60, 5, 19, 3, 17, 12, 59, 55, 53, 49, 54, 88, 67, 98, 98, 101, 78, 63, 86, 31, 11, 1, 0, 4, 3, 13, 3, 0, 5, 5, 2, 2, 0, 2, 28, 83, 60, 69, 96, 137, 125, 134, 94, 100, 78, 87, 71, 1, 67, 54, 1, 
+#> 16, 18, 14, 50, 103, 158, 177, 94, 151, 143, 61, 139, 158, 163, 121, 150, 149, 120, 97, 78, 13, 38, 16, 51, 53, 37, 72, 46, 54, 61, 30, 40, 69, 57, 27, 15, 39, 5, 63, 86, 51, 68, 96, 131, 141, 89, 121, 133, 96, 133, 99, 156, 15, 64, 10, 2, 9, 2, 1, 1, 7, 1, 9, 1, 16, 0, 42, 27, 32, 12, 18, 14, 17, 23, 5, 13, 25, 14, 1, 0, 0, 25, 72, 88, 64, 8, 0, 68, 7, 29, 5, 55, 51, 64, 83, 78, 64, 37, 89, 102, 65, 73, 75, 16, 68, 88, 1, 10, 4, 9, 7, 1, 10, 7, 5, 10, 6, 6, 6, 5, 10, 29, 78, 59, 101, 50, 98, 84, 
+#> 75, 97, 0, 14, 3, 18, 25, 27, 26, 22, 28, 30, 17, 16, 11, 2, 26, 73, 34, 4, 82, 61, 73, 81, 68, 29, 88, 67, 91, 95, 83, 20, 76, 46, 2, 77, 114, 99, 76, 76, 90, 82, 70, 41, 74, 85, 140, 120, 113, 109, 18, 46, 70, 41, 2, 0, 2, 5, 1, 4, 8, 8, 9, 11, 11, 18, 9, 11, 12, 2, 0, 1, 17, 19, 28, 32, 30, 21, 34, 46, 63, 39, 33, 31, 29, 7, 14, 4, 29, 81, 93, 98, 100, 85, 90, 75, 89, 81, 76, 91, 74, 111, 87, 107, 62, 0, 6, 4, 3, 2, 3, 10, 8, 4, 7, 13, 5, 14, 2, 72, 51, 53, 71, 90, 46, 28, 41, 72, 69, 68, 58, 
+#> 42, 56, 49, 56, 46, 57, 15, 1, 7, 5, 8, 9, 10, 15, 15, 11, 12, 4, 10, 17, 11, 3, 9, 4, 4, 1, 1, 0, 0, 0, 1, 18, 1, 35, 55, 67, 65, 63, 59, 89, 109, 128, 62, 73, 72, 67, 19, 23, 2, 52, 37, 61, 76, 62, 56, 85, 96, 85, 63, 66, 98, 0, 1, 2, 35, 69, 54, 37, 36, 62, 83, 51, 82, 29, 12, 1, 0, 1, 1, 1, 4, 1, 14, 10, 8, 9, 2, 0, 6, 11, 3, 1, 0, 26, 77, 3, 80, 83, 83, 91, 117, 106, 111, 98, 98, 95, 119, 121, 81, 58, 19, 48, 0, 12, 12, 5, 8, 17, 8, 4, 3, 0, 8, 1, 6, 10, 13, 3, 4, 9, 3, 3, 8, 1, 1, 2, 0, 1, 
+#> 2, 8, 18, 14, 9, 11, 12, 6, 6, 0, 66, 25, 37, 40, 40, 41, 41, 65, 64, 48, 56, 3, 10, 15, 1, 16, 9, 31, 23, 22, 30, 21, 39, 16, 9, 5, 70, 73, 92, 90, 105, 121, 112, 82, 62, 3, 11, 4, 1, 1, 8, 10, 8, 8, 7, 6, 3, 7, 2, 3, 8, 4, 4, 0, 0, 3, 8, 9, 10, 3, 6, 10, 18, 7, 2, 9, 3, 12, 5, 5, 3, 21, 57, 121, 101, 116, 121, 89, 75, 112, 107, 93, 121, 96, 59, 74, 74, 52, 40, 3, 2, 4, 0, 2, 12, 69, 95, 96, 82, 91, 87, 70, 27, 46, 73, 22, 18, 23, 17, 46, 47, 61, 78, 100, 113, 79, 42, 31, 15, 1, 4, 8, 8, 6, 5, 11, 
+#> 9, 9, 5, 11, 5, 0, 0, 0, 1, 4, 3, 9, 26, 25, 65, 54, 45, 44, 111, 105, 50, 39, 44, 33, 14, 1, 1, 8, 6, 2, 4, 9, 8, 1, 14, 19, 15, 12, 13, 10, 5, 1, 0, 0, 0, 8, 9, 3, 13, 4, 7, 6, 4, 5, 2, 8, 6, 5, 3, 3, 2, 3, 6, 3, 3, 6, 7, 8, 7, 10, 8, 6, 4, 4, 2, 6, 0, 2, 2, 3, 1, 0, 8, 3, 12, 12, 6, 5, 18, 2, 6, 7, 3, 59, 70, 82, 48, 74, 109, 96, 96, 79, 88, 19, 72, 49, 30, 2, 1, 9, 22, 40, 58, 58, 53, 31, 21, 14, 11, 1, 4, 1, 3, 0, 25, 57, 57, 34, 74, 66, 114, 92, 121, 107, 97, 90, 106, 83, 86, 79, 3, 7, 4, 21, 
+#> 21, 23, 10, 10, 16, 4, 9, 18, 15, 8, 2, 0, 1, 1, 1, 1, 0, 1, 3, 6, 4, 9, 6, 4, 14, 6, 4, 2, 5, 6, 0, 1, 14, 101, 80, 98, 99, 78, 91, 83, 79, 90, 44, 102, 95, 87, 0, 11, 6, 38, 62, 64, 78, 53, 73, 58, 68, 67, 66, 58, 65, 66, 38, 24, 0, 13, 0, 0, 1, 9, 11, 29, 32, 68, 73, 25, 2, 37, 63, 19, 23, 6, 35, 37, 11, 7, 16, 3, 10, 0, 0, 0, 5, 3, 6, 7, 9, 8, 7, 7, 8, 8, 8, 10, 8, 1, 1, 0, 0, 0, 1, 6, 7, 9, 3, 4, 1, 0, 5, 1, 0, 0, 0, 9, 5, 7, 8, 2, 10, 7, 4, 4, 6, 2, 1, 1, 1, 1, 7, 42, 62, 56, 83, 103, 87, 84, 
+#> 56, 71, 65, 70, 68, 78, 83, 83, 11, 45, 20, 7, 3, 0, 5, 37, 41, 45, 43, 40, 20, 19, 9, 16, 41, 4, 50, 3, 69, 94, 87, 130, 98, 109, 89, 73, 63, 56, 64, 7, 0, 10, 0, 15, 2, 5, 11, 3, 8, 7, 4, 1, 0, 7, 1, 1, 0, 2, 7, 7, 9, 5, 11, 13, 6, 8, 6, 1, 4, 5, 8, 4, 0, 2, 1, 45, 81, 51, 64, 67, 73, 92, 70, 65, 23, 11, 75, 74, 41, 6, 0, 89, 108, 86, 114, 83, 93, 91, 94, 90, 81, 74, 85, 62, 24, 3, 4, 28, 56, 61, 35, 56, 61, 2, 84, 53, 52, 55, 58, 67, 49, 47, 40, 36, 3, 20, 5, 48, 59, 77, 69, 71, 78, 35, 64, 82, 
+#> 64, 63, 39, 44, 43, 12, 25, 5, 0, 1, 0, 18, 30, 41, 34, 63, 50, 55, 42, 61, 31, 16, 18, 6, 1, 10, 13, 4, 69, 50, 80, 92, 113, 110, 87, 118, 104, 74, 93, 24, 27, 69, 122, 90, 86, 78, 114, 152, 105, 144, 85, 102, 68, 96, 60, 79, 39, 0, 7, 1, 9, 1, 8, 44, 86, 100, 116, 105, 96, 80, 82, 81, 34, 114, 88, 97, 106, 88, 122, 30, 6, 0, 10, 6, 7, 16, 10, 7, 20, 6, 11, 11, 9, 5, 2, 6, 9, 5, 4, 8, 10, 0, 0, 0, 4, 94, 144, 113, 60, 92, 111, 155, 110, 58, 37, 80, 22, 36, 96, 48, 45, 80, 97, 73, 78, 63, 4, 83, 
+#> 36, 50, 19, 1, 29, 79, 87, 92, 98, 95, 123, 108, 92, 73, 45, 57, 72, 44, 72, 11, 5, 20, 35, 29, 22, 2, 1, 12, 34, 29, 16, 8, 3, 9, 0, 3, 4, 5, 4, 13, 8, 1, 3, 1, 0, 2, 0, 0, 0, 55, 49, 60, 42, 61, 63, 7, 1, 52, 71, 91, 64, 69, 97, 84, 29, 1, 0, 5, 57, 58, 82, 63, 85, 70, 72, 49, 9, 68, 76, 59, 52, 2, 59, 83, 46, 95, 102, 104, 85, 26, 74, 110, 121, 115, 88, 68, 43, 57, 9, 2, 0, 4, 43, 74, 91, 75, 135, 120, 3, 69, 4, 3, 6, 8, 10, 13, 11, 8, 10, 9, 4, 5, 5, 6, 8, 3, 4, 6, 6, 9, 14, 3, 4, 4, 8, 8, 1, 
+#> 0, 0, 62, 28, 97, 119, 89, 135, 146, 66, 77, 41, 24, 0, 0, 0, 3, 3, 3, 10, 0, 6, 9, 13, 1, 4, 1, 4, 1, 0, 5, 6, 3, 5, 2, 1, 1, 6, 2, 73, 135, 149, 139, 127, 143, 163, 138, 138, 128, 125, 167, 138, 115, 2, 79, 92, 62, 101, 109, 67, 79, 94, 59, 72, 82, 56, 21, 6, 7, 0, 1, 3, 8, 4, 7, 8, 5, 4, 10, 15, 9, 2, 0, 1, 5, 0, 1, 1, 2, 4, 4, 1, 1, 0, 5, 5, 9, 9, 3, 9, 2, 4, 5, 2, 0, 0, 4, 0, 0, 1, 8, 15, 5, 8, 4, 7, 4, 1, 3, 8, 1, 7, 2, 4, 4, 4, 0, 6, 9, 6, 8, 3, 8, 4, 6, 4, 5, 3, 3, 1, 1, 1, 2, 3, 3, 101, 
+#> 114, 142, 131, 117, 88, 107, 101, 122, 98, 107, 94, 77, 62, 32, 5, 40, 43, 29, 16, 1, 0, 1, 26, 75, 26, 101, 100, 103, 139, 121, 124, 68, 109, 91, 36, 27, 32, 42, 40, 50, 11, 45, 59, 54, 45, 36, 34, 25, 38, 25, 15, 0, 0, 2, 133, 121, 134, 32, 90, 90, 59, 95, 83, 67, 80, 79, 49, 30, 7, 17, 2, 23, 3, 2, 5, 5, 3, 1, 11, 6, 2, 6, 5, 11, 7, 1, 1, 6, 1, 0, 8, 6, 2, 5, 4, 4, 6, 3, 1, 4, 12, 2, 1, 2, 2, 8, 4, 0, 1, 10, 36, 30, 62, 101, 101, 108, 94, 34, 77, 75, 10, 39, 7, 1, 4, 2, 11, 13, 4, 12, 9, 9, 10, 
+#> 5, 3, 3, 2, 0, 1, 19, 43, 90, 107, 99, 99, 127, 38, 83, 70, 59, 49, 12, 38, 55, 33, 5, 78, 60, 38, 97, 20, 65, 21, 0, 8, 2, 3, 62, 110, 108, 131, 144, 67, 112, 103, 134, 123, 144, 133, 133, 86, 108, 65, 6, 13, 4, 81, 88, 66, 50, 68, 93, 54, 61, 39, 76, 69, 48, 71, 49, 52, 45, 62, 10, 9, 0, 10, 117, 113, 137, 118, 119, 129, 120, 143, 86, 47, 47, 3, 6, 11, 12, 10, 5, 5, 4, 1, 4, 0, 1, 4, 6, 6, 6, 8, 3, 9, 2, 4, 0, 0, 12, 19, 24, 14, 26, 12, 25, 20, 7, 7, 1, 6, 0, 0, 2, 3, 78, 82, 94, 87, 83, 2, 47, 
+#> 3, 18, 32, 51, 74, 19, 5, 13, 0, 8, 8, 12, 12, 7, 5, 2, 0, 4, 0, 0, 5, 1, 15, 14, 8, 15, 18, 15, 13, 14, 11, 6, 11, 8, 1, 3, 6, 5, 9, 11, 6, 9, 15, 9, 4, 3, 3, 5, 5, 2, 0, 2, 2, 0, 2, 67, 152, 122, 85, 120, 14, 31, 27, 2, 8, 23, 85, 123, 127, 93, 151, 125, 120, 118, 130, 111, 139, 130, 106, 87, 18, 25, 0, 30, 110, 102, 140, 116, 83, 128, 109, 136, 121, 101, 8, 58, 10, 2, 9, 2, 23, 72, 127, 103, 95, 89, 68, 70, 36, 102, 98, 97, 104, 98, 7, 8, 24, 1, 0, 0, 2, 8, 5, 3, 6, 3, 8, 3, 2, 0, 3, 54, 45, 9, 
+#> 57, 62, 88, 71, 50, 54, 45, 8, 39, 8, 0, 1, 0, 6, 0, 14, 10, 11, 5, 6, 8, 4, 2, 3, 1, 7, 5, 7, 3, 11, 9, 9, 14, 5, 7, 5, 5, 2, 8, 5, 0, 6, 3, 7, 2, 8, 10, 4, 2, 4, 4, 2, 3, 3, 3, 6, 7, 5, 15, 16, 10, 3, 12, 2, 4, 2, 2, 8, 7, 6, 1, 0, 0, 41, 126, 158, 121, 152, 101, 78, 71, 19, 83, 74, 53, 8, 37, 39, 6, 0, 0, 1, 1, 8, 9, 3, 8, 4, 1, 8, 5, 3, 0, 5, 4, 0, 0, 3, 8, 9, 12, 9, 9, 10, 5, 4, 6, 6, 1, 2, 2, 1, 14, 102, 82, 79, 113, 101, 106, 86, 111, 77, 77, 4, 76, 76, 24, 32, 3, 2, 0, 4, 10, 5, 8, 9, 1, 
+#> 1, 1, 1, 5, 2, 0, 1, 10, 8, 15, 18, 7, 8, 3, 4, 2, 0, 0, 0, 27, 101, 69, 88, 118, 78, 102, 60, 71, 91, 67, 37, 76, 0, 44, 53, 48, 0, 1, 60, 55, 65, 66, 58, 56, 54, 99, 87, 84, 98, 45, 35, 28, 29, 10, 1, 85, 89, 69, 89, 88, 77, 57, 70, 79, 65, 62, 79, 18, 2, 9, 59, 60, 75, 77, 88, 93, 90, 93, 78, 68, 17, 51, 52, 7, 3, 14, 2, 11, 7, 6, 4, 4, 10, 3, 7, 9, 7, 12, 10, 8, 6, 0, 1, 1, 4, 5, 5, 7, 9, 10, 9, 5, 11, 5, 2, 5, 4, 0, 1, 98, 94, 90, 84, 92, 91, 88, 14, 40, 74, 5, 36, 0, 3, 0, 60, 38, 44, 39, 58, 
+#> 50, 46, 31, 19, 32, 20, 15, 33, 17, 40, 27, 22, 13, 9, 13, 92, 110, 132, 115, 111, 100, 98, 62, 21, 100, 69, 13, 41, 64, 17, 14, 7, 19, 0, 1, 3, 2, 5, 4, 7, 3, 9, 5, 4, 3, 0, 0, 71, 85, 115, 108, 122, 71, 88, 94, 113, 69, 82, 112, 24, 19, 5, 64, 0, 129, 84, 89, 85, 92, 115, 105, 56, 51, 6, 15, 19, 16, 2, 1, 7, 7, 10, 2, 0, 14, 4, 9, 3, 1, 0, 0, 8, 7, 11, 2, 9, 11, 3, 5, 3, 8, 4, 1, 3, 2, 9, 0, 1, 2, 20, 82, 77, 81, 53, 15, 2, 17, 51, 25, 7, 23, 69, 138, 122, 104, 119, 98, 119, 113, 120, 99, 116, 
+#> 85, 89, 89, 118, 65, 91, 73, 2, 0, 1, 0, 53, 56, 106, 108, 110, 89, 76, 80, 83, 47, 1, 3, 8, 19, 8, 9, 9, 12, 4, 11, 6, 10, 0, 0, 59, 118, 121, 10, 137, 144, 112, 129, 12, 47, 91, 71, 0, 12, 37, 73, 109, 99, 96, 99, 90, 116, 110, 94, 93, 71, 79, 69, 62, 26, 21, 1, 1, 80, 106, 53, 71, 93, 76, 81, 121, 89, 45, 0, 2, 82, 101, 116, 46, 116, 91, 69, 49, 38, 42, 54, 70, 21, 11, 5, 68, 47, 122, 74, 121, 121, 60, 34, 48, 28, 15, 35, 77, 79, 52, 72, 48, 84, 22, 4, 132, 151, 129, 108, 93, 122, 123, 81, 97, 
+#> 110, 58, 114, 72, 0, 5, 12, 12, 10, 0, 9, 12, 2, 1, 3, 8, 1, 3, 1, 1, 5, 7, 2, 12, 12, 5, 12, 10, 3, 0, 6, 3, 2, 1, 2, 60, 98, 113, 86, 68, 91, 78, 73, 82, 82, 79, 23, 20, 32, 26, 49, 47, 17, 2, 36, 66, 90, 75, 94, 111, 98, 41, 82, 96, 93, 78, 63, 12, 59, 67, 63, 82, 11, 32, 10, 54, 75, 102, 106, 109, 112, 101, 111, 91, 78, 65, 110, 55, 28, 93, 26, 78, 72, 67, 68, 111, 69, 82, 21, 23, 4, 4, 11, 8, 7, 7, 8, 4, 5, 1, 7, 6, 5, 0, 5, 5, 0, 3, 5, 6, 11, 4, 0, 7, 2, 2, 2, 0, 7, 7, 2, 6, 2, 0, 0, 3, 0, 
+#> 1, 1, 2, 11, 1, 0, 6, 1, 73, 89, 87, 64, 93, 42, 12, 58, 41, 1, 44, 56, 27, 9, 6, 4, 0, 0, 0, 0, 76, 103, 85, 104, 111, 67, 97, 70, 137, 110, 59, 4, 43, 37, 9, 6, 4, 68, 60, 93, 104, 63, 68, 68, 20, 3, 18, 5, 4, 10, 5, 5, 7, 2, 0, 0, 2, 1, 0, 0, 54, 108, 116, 143, 132, 139, 102, 106, 42, 0, 6, 8, 5, 12, 9, 2, 15, 14, 20, 10, 11, 13, 14, 11, 12, 12, 8, 10, 8, 4, 1, 2, 14, 31, 45, 28, 3, 27, 9, 7, 47, 57, 43, 30, 27, 58, 46, 29, 7, 12, 12, 23, 7, 0, 6, 8, 104, 64, 55, 89, 82, 58, 20, 60, 46, 23, 81, 
+#> 64, 17, 0, 0, 0, 6, 0, 6, 11, 9, 2, 9, 6, 0, 9, 3, 0, 5, 4, 0, 0, 4, 3, 0, 5, 0, 1, 2, 0, 0, 1, 2, 6, 1, 6, 6, 7, 9, 6, 3, 6, 5, 1, 0, 1, 5, 89, 99, 93, 77, 58, 56, 85, 68, 46, 24, 7, 14, 20, 43, 30, 42, 36, 42, 41, 60, 43, 50, 33, 32, 19, 37, 46, 19, 8, 0, 8, 16, 3, 30, 59, 79, 65, 58, 45, 6, 8, 5, 4, 10, 3, 4, 8, 2, 3, 0, 5, 0, 1, 0, 0, 86, 81, 86, 103, 85, 78, 14, 21, 31, 24, 83, 92, 112, 104, 88, 82, 35, 89, 96, 74, 59, 103, 111, 103, 91, 91, 114, 115, 93, 98, 78, 65, 106, 71, 2, 1, 6, 14, 7, 
+#> 11, 2, 9, 8, 1, 7, 7, 10, 5, 3, 6, 0, 0, 1, 3, 1, 1, 10, 2, 6, 1, 1, 0, 6, 9, 2, 4, 1, 4, 0, 1, 0, 0, 131, 134, 135, 141, 142, 125, 124, 150, 82, 109, 2, 17, 93, 77, 71, 96, 81, 32, 56, 2, 8, 27, 10, 36, 14, 12, 15, 10, 6, 16, 11, 6, 13, 11, 9, 11, 6, 3, 1, 0, 9, 4, 6, 4, 6, 8, 10, 3, 0, 5, 4, 5, 3, 3, 0, 25, 77, 88, 63, 33, 76, 95, 102, 78, 66, 78, 46, 4, 10, 6, 1, 41, 27, 21, 64, 68, 93, 56, 75, 36, 6, 1, 17, 110, 44, 24, 50, 65, 68, 20, 11, 104, 101, 145, 103, 119, 90, 92, 108, 108, 43, 4, 4, 
+#> 49, 0, 24, 59, 24, 56, 66, 73, 66, 8, 14, 16, 62, 39, 12, 15, 11, 0, 87, 102, 102, 106, 97, 26, 98, 36, 41, 17, 7, 6, 0, 2, 37, 78, 74, 83, 95, 116, 82, 36, 69, 68, 42, 3, 23, 17, 12, 0, 3, 32, 78, 54, 47, 49, 48, 46, 30, 69, 45, 21, 17, 8, 76, 73, 65, 56, 57, 58, 53, 27, 2, 1, 6, 3, 5, 14, 8, 7, 7, 0, 1, 2, 6, 0, 0, 1, 3, 3, 2, 7, 48, 85, 77, 72, 96, 55, 60, 106, 4, 45, 10, 8, 17, 52, 88, 106, 101, 106, 105, 92, 92, 89, 56, 24, 86, 50, 88, 56, 81, 75, 6, 23, 0, 3, 0, 7, 5, 0, 1, 2, 0, 2, 1, 8, 10, 
+#> 5, 7, 1, 1, 1, 6, 5, 5, 2, 0, 0, 0, 0, 10, 4, 6, 1, 1, 2, 6, 0, 2, 3, 2, 85, 33, 34, 117, 89, 75, 68, 17, 32, 12, 22, 7, 0, 0, 0, 5, 5, 6, 2, 2, 5, 0, 6, 4, 0, 0, 0, 59, 95, 96, 71, 100, 100, 100, 91, 92, 82, 48, 73, 64, 19, 49, 1, 37, 15, 24, 21, 0, 10, 34, 40, 49, 43, 69, 51, 53, 53, 84, 23, 50, 45, 46, 28, 22, 26, 5, 79, 71, 49, 72, 59, 59, 80, 0, 86, 84, 67, 83, 72, 47, 74, 47, 49, 91, 35, 2, 1, 8, 5, 6, 5, 3, 0, 1, 3, 1, 4, 5, 5, 6, 4, 4, 2, 0, 10, 10, 8, 5, 6, 7, 2, 6, 2, 3, 0, 4, 3, 0, 3, 
+#> 8, 3, 0, 0, 2, 10, 2, 5, 4, 6, 9, 0, 1, 9, 5, 5, 22, 94, 72, 83, 83, 62, 71, 3, 46, 0, 84, 75, 91, 90, 67, 74, 114, 113, 125, 62, 35, 14, 16, 31, 0, 10, 0, 4, 5, 4, 6, 7, 9, 5, 2, 5, 0, 3, 0, 5, 1, 2, 1, 0, 0, 6, 2, 1, 0, 0, 44, 50, 66, 38, 50, 63, 51, 57, 70, 61, 36, 16, 0, 17, 45, 32, 27, 32, 53, 31, 43, 5, 15, 22, 10, 6, 105, 115, 106, 124, 111, 112, 93, 10, 26, 43, 5, 17, 0, 72, 85, 66, 105, 91, 81, 90, 77, 71, 78, 16, 40, 4, 70, 51, 67, 59, 48, 44, 5, 52, 23, 0, 7, 4, 5, 9, 9, 18, 11, 7, 5, 
+#> 6, 2, 6, 6, 3, 1, 0, 0, 4, 11, 1, 2, 0, 12, 8, 4, 3, 1, 2, 0, 91, 53, 64, 59, 50, 17, 0, 0, 8, 87, 108, 112, 124, 113, 135, 128, 105, 124, 105, 127, 120, 97, 87, 82, 64, 37, 49, 46, 57, 34, 0, 0, 5, 14, 12, 9, 9, 10, 10, 4, 2, 5, 1, 3, 19, 58, 52, 56, 3, 29, 79, 40, 34, 14, 52, 3, 42, 33, 12, 21, 0, 11, 5, 7, 56, 71, 1, 2, 59, 73, 57, 64, 41, 64, 2, 1, 34, 125, 107, 75, 102, 90, 29, 0, 32, 10, 0, 0, 3, 3, 1, 4, 10, 9, 6, 5, 6, 8, 6, 4, 5, 1, 0, 0, 18, 88, 74, 75, 82, 85, 80, 50, 93, 99, 77, 94, 73, 
+#> 33, 24, 19, 37, 69, 87, 85, 43, 0, 0, 51, 59, 44, 0, 50, 37, 14, 38, 1, 7, 0, 0, 8, 4, 3, 3, 0, 2, 1, 0, 22, 70, 75, 87, 74, 71, 78, 95, 95, 79, 94, 91, 103, 60, 1, 68, 2, 1, 12, 3, 105, 84, 27, 30, 75, 88, 57, 83, 77, 102, 80, 77, 39, 26, 6, 20, 78, 37, 78, 88, 77, 37, 5, 64, 67, 76, 58, 59, 49, 68, 77, 62, 42, 14, 26, 8, 0, 5, 5, 50, 0, 4, 10, 0, 31, 32, 24, 26, 13, 16, 12, 11, 4, 1, 0, 1, 2, 2, 11, 8, 4, 1, 3, 2, 1, 2, 2, 0, 0, 6, 10, 3, 0, 0, 4, 4, 6, 2, 2, 0, 0, 12, 31, 8, 41, 82, 16, 15, 30, 
+#> 66, 98, 3, 80, 63, 82, 5, 85, 55, 43, 29, 4, 34, 46, 59, 93, 106, 94, 89, 56, 41, 46, 49, 24, 7, 3, 21, 1, 1, 51, 69, 95, 84, 76, 108, 34, 0, 7, 47, 64, 18, 68, 82, 79, 95, 42, 26, 76, 70, 61, 29, 15, 31, 17, 17, 0, 4, 8, 1, 2, 5, 4, 8, 8, 4, 3, 1, 4, 2, 5, 5, 5, 9, 5, 4, 2, 1, 0, 1, 0, 56, 75, 93, 125, 80, 90, 85, 47, 44, 1, 2, 0, 1, 0, 0, 2, 5, 1, 1, 1, 6, 0, 0, 1, 3, 11, 6, 4, 3, 4, 1, 0, 10, 75, 22, 38, 126, 0, 39, 11, 19, 2, 49, 76, 71, 21, 66, 35, 23, 0, 73, 76, 89, 88, 77, 78, 72, 8, 47, 69, 
+#> 71, 101, 90, 74, 67, 36, 49, 8, 0, 1, 51, 50, 67, 3, 75, 47, 97, 114, 92, 41, 11, 68, 15, 25, 44, 45, 7, 28, 0, 19, 32, 23, 47, 38, 37, 9, 3, 0, 42, 97, 95, 57, 69, 91, 50, 51, 79, 116, 53, 23, 37, 1, 0, 2, 3, 2, 5, 6, 10, 7, 3, 1, 4, 2, 1, 6, 0, 1, 1, 92, 32, 4, 128, 98, 97, 49, 90, 115, 88, 13, 5, 4, 41, 39, 20, 38, 25, 10, 30, 28, 26, 10, 21, 9, 7, 0, 70, 71, 86, 92, 92, 76, 90, 79, 73, 82, 80, 61, 22, 10, 1, 0, 6, 13, 11, 10, 9, 4, 3, 4, 8, 1, 0, 0, 58, 76, 87, 79, 81, 96, 132, 97, 94, 94, 108, 
+#> 98, 99, 85, 33, 21, 81, 117, 110, 85, 75, 127, 126, 131, 113, 81, 0, 5, 100, 101, 78, 93, 86, 53, 83, 69, 47, 84, 33, 3, 41, 70, 59, 116, 92, 97, 80, 88, 84, 93, 74, 60, 64, 46, 62, 25, 20, 1, 0, 6, 2, 1, 1, 7, 6, 8, 5, 8, 6, 3, 3, 39, 109, 64, 57, 106, 77, 92, 109, 138, 90, 20, 24, 53, 36, 24, 16, 6, 19, 7, 1, 5, 0, 0, 2, 5, 3, 3, 7, 10, 1, 0, 0, 0, 63, 118, 104, 116, 112, 124, 90, 73, 27, 88, 56, 0, 1, 3, 8, 3, 5, 3, 6, 0, 0, 3, 2, 1, 0, 1, 3, 6, 10, 11, 7, 8, 10, 6, 4, 7, 8, 3, 10, 11, 10, 13, 
+#> 3, 7, 2, 0, 1, 41, 63, 102, 72, 81, 38, 65, 5, 52, 51, 7, 6, 125, 108, 122, 99, 106, 104, 109, 62, 51, 61, 70, 81, 81, 83, 63, 82, 73, 30, 9, 23, 7, 15, 16, 37, 46, 28, 24, 20, 22, 1, 54, 42, 33, 8, 4, 0, 0, 9, 11, 20, 17, 21, 11, 14, 12, 11, 11, 8, 2, 1, 1, 5, 10, 7, 6, 5, 4, 4, 3, 0, 0, 14, 11, 17, 14, 27, 33, 55, 52, 54, 43, 13, 16, 38, 24, 9, 1, 1, 3, 3, 3, 4, 3, 1, 0, 0, 0, 1, 0, 0, 6, 5, 1, 0, 0, 85, 74, 79, 114, 92, 126, 98, 77, 19, 54, 80, 54, 7, 60, 16, 29, 3, 5, 5, 1, 3, 2, 1, 0, 0, 4, 
+#> 47, 37, 31, 47, 73, 21, 48, 59, 22, 21, 10, 53, 35, 1, 6, 9, 7, 12, 4, 7, 1, 1, 4, 60, 49, 96, 99, 86, 46, 22, 61, 5, 33, 30, 65, 84, 5, 38, 45, 33, 0, 7, 0, 3, 0, 9, 48, 94, 98, 118, 87, 101, 106, 75, 86, 94, 68, 57, 22, 25, 15, 2, 4, 4, 50, 64, 57, 100, 87, 78, 96, 69, 67, 38, 19, 2, 32, 65, 70, 90, 73, 103, 43, 81, 39, 31, 8, 8, 11, 6, 18, 13, 8, 9, 2, 10, 0, 1, 84, 46, 10, 3, 37, 75, 74, 92, 99, 85, 55, 87, 76, 61, 46, 7, 5, 3, 1, 4, 8, 11, 5, 1, 0, 3, 0, 1, 0, 0, 0, 65, 79, 53, 78, 65, 110, 
+#> 125, 87, 89, 54, 47, 19, 6, 54, 69, 48, 6, 1, 39, 12, 15, 23, 3, 101, 37, 13, 56, 61, 27, 55, 42, 24, 3, 18, 17, 4, 16, 1, 0, 0, 2, 2, 8, 5, 2, 3, 4, 6, 5, 0, 0, 0, 2, 0, 1, 0, 0, 0, 1, 3, 0, 0, 0, 0, 0, 29, 61, 55, 95, 99, 93, 52, 82, 56, 83, 66, 61, 54, 8, 1, 6, 22, 100, 109, 96, 80, 132, 120, 126, 112, 91, 45, 59, 38, 35, 28, 44, 16, 6, 4, 2, 6, 5, 7, 5, 1, 1, 6, 3, 0, 1, 42, 83, 78, 61, 74, 90, 83, 57, 42, 59, 18, 4, 10, 0, 100, 101, 79, 0, 3, 83, 106, 110, 84, 104, 92, 94, 91, 89, 57, 41, 1, 
+#> 5, 72, 65, 82, 66, 79, 79, 87, 69, 44, 54, 59, 17, 119, 123, 101, 112, 121, 125, 107, 129, 130, 115, 121, 118, 99, 83, 84, 64, 94, 82, 27, 8, 24, 0, 3, 9, 5, 6, 3, 0, 1, 1, 0, 0, 0, 1, 0, 0, 4, 3, 2, 1, 4, 5, 8, 3, 2, 4, 1, 2, 4, 11, 13, 6, 2, 5, 2, 6, 1, 4, 1, 3, 0, 0, 0, 0, 0, 0, 4, 4, 18, 78, 59, 22, 85, 77, 89, 61, 98, 29, 11, 46, 27, 1, 0, 4, 9, 1, 0, 2, 0, 0, 1, 1, 0, 0, 3, 0, 0, 61, 94, 105, 129, 121, 132, 121, 127, 104, 119, 132, 96, 40, 92, 44, 40, 63, 57, 1, 2, 1, 8, 3, 14, 11, 12, 8, 5, 
+#> 12, 6, 6, 1, 3, 7, 3, 1, 1, 1, 1, 6, 96, 65, 63, 26, 0, 10, 10, 32, 72, 8, 76, 33, 12, 56, 37, 34, 44, 1, 1, 0, 3, 100, 82, 101, 115, 76, 61, 64, 2, 94, 81, 101, 96, 74, 73, 99, 65, 60, 73, 61, 42, 11, 4, 0, 15, 125, 107, 110, 102, 89, 81, 91, 96, 74, 83, 77, 44, 54, 30, 89, 94, 91, 64, 102, 81, 88, 91, 107, 98, 68, 39, 22, 56, 35, 47, 0, 21, 9, 21, 0, 4, 0, 0, 0, 3, 5, 8, 3, 3, 4, 2, 0, 1, 1, 0, 0, 34, 18, 31, 22, 20, 20, 1, 3, 2, 2, 1, 2, 0, 2, 0, 0, 0, 0, 106, 86, 86, 86, 36, 93, 74, 79, 36, 41, 
+#> 8, 6, 1, 49, 63, 76, 74, 62, 97, 104, 116, 91, 12, 29, 11, 11, 20, 32, 3, 39, 76, 102, 85, 112, 83, 74, 60, 54, 1, 7, 29, 0, 0, 1, 7, 6, 8, 7, 8, 9, 4, 2, 4, 0, 1, 1, 0, NA, 0, 0, 0, 0, 0, 5, 7, 9, 6, 5, 4, 3, 3, 6, 6, 0, 1, 5, 0, 1, 0, 5, 11, 1, 1, 1, 2, 0, 0, 58, 67, 10, 59, 75, 67, 60, 81, 82, 58, 59, 58, 1, 2, 0, 42, 45, 93, 76, 92, 111, 100, 109, 110, 82, 84, 85, 67, 79, 54, 45, 3, 80, 110, 96, 108, 103, 109, 97, 118, 108, 103, 106, 82, 83, 77, 72, 14, 39, 4, 9, 42, 121, 96, 83, 84, 86, 77, 
+#> 116, 78, 89, 77, 72, 85, 94, 49, 74, 64, 69, 46, 40, 71, 2, 10, 7, 9, 9, 4, 10, 6, 4, 11, 5, 5, 5, 4, 0, 0, 3, 70, 98, 82, 113, 119, 97, 94, 75, 87, 41, 67, 79, 52, 68, 71, 60, 25, 4, 11, 6, 4, 10, 6, 9, 8, 3, 2, 2, 3, 1, 0, 0, 0, 0, 0, 69, 82, 76, 98, 86, 90, 72, 73, 93, 67, 97, 55, 55, 77, 86, 56, 47, 56, 122, 97, 90, 106, 86, 117, 134, 79, 103, 109, 122, 83, 69, 111, 88, 82, 41, 85, 75, 6, 19, 5, 78, 91, 79, 101, 86, 95, 109, 92, 86, 100, 71, 62, 17, 17, 0, 20, 0, 58, 105, 106, 118, 109, 116, 
+#> 102, 115, 127, 121, 103, 109, 117, 113, 84, 100, 103, 95, 75, 84, 47, 45, 22, 0, 5, 7, 10, 10, 11, 4, 4, 5, 6, 7, 10, 3, 4, 3, 3, 2, 0, 0, 0, 1, 4, 3, 10, 9, 11, 11, 14, 11, 10, 6, 2, 0, 6, 0, 0, 3, 0, 0, 2, 15, 82, 76, 90, 60, 74, 74, 66, 62, 40, 6, 7, 4, 0, 28, 55, 44, 35, 46, 31, 67, 55, 33, 53, 63, 43, 38, 17, 4, 2, 109, 3, 96, 104, 119, 79, 106, 96, 94, 92, 89, 91, 14, 38, 4, 0, 0, 21, 60, 51, 86, 50, 51, 50, 48, 38, 42, 42, 66, 35, 1, 30, 44, 24, 56, 66, 67, 77, 84, 28, 72, 46, 26, 0, 3, 3, 
+#> 6, 8, 13, 5, 9, 3, 0, 0, 1, 0, 0, 0, 4, 10, 7, 7, 2, 6, 9, 4, 4, 6, 10, 8, 0, 0, 3, 1, 1, 33, 35, 33, 45, 59, 29, 64, 63, 75, 63, 38, 38, 9, 13, 22, 0, 2, 8, 7, 5, 4, 8, 3, 4, 1, 0, 0, 2, 36, 91, 77, 48, 63, 35, 102, 69, 64, 80, 65, 17, 6, 1, 11, 46, 53, 72, 91, 56, 64, 86, 45, 73, 35, 55, 16, 4, 28, 76, 77, 68, 91, 103, 55, 42, 70, 81, 38, 4, 13, 9, 28, 10, 14, 0, 27, 79, 52, 69, 68, 114, 80, 92, 44, 29, 2, 6, 0, 30, 59, 69, 50, 58, 71, 55, 43, 66, 52, 56, 62, 36, 13, 29, 17, 3, 21, 21, 55, 60, 
+#> 61, 37, 45, 50, 65, 81, 3, 35, 18, 12, 11, 10, 3, 21, 16, 10, 6, 1, 6, 11, 3, 7, 2, 9, 0, 0, 0, 13, 30, 3, 80, 87, 92, 95, 80, 82, 83, 101, 64, 63, 22, 9, 17, 92, 115, 92, 34, 41, 0, 88, 92, 81, 105, 105, 100, 75, 1, 5, 65, 91, 71, 74, 87, 31, 6, 0, 51, 3, 21, 1, 68, 81, 72, 69, 72, 89, 41, 54, 7, 58, 69, 34, 19, 20, 7, 3, 7, 0, 1, 2, 4, 6, 3, 7, 5, 3, 4, 5, 6, 3, 2, 2, 2, 0, 1, 0, 3, 1, 2, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 4, 6, 4, 4, 6, 9, 3, 12, 8, 5, 11, 10, 8, 5, 4, 7, 11, 8, 4, 5, 1, 22, 62, 87, 
+#> 103, 60, 40, 59, 2, 26, 45, 9, 7, 63, 73, 93, 76, 49, 66, 35, 16, 7, 1, 1, 83, 79, 83, 102, 99, 90, 71, 34, 73, 63, 18, 15, 32, 37, 59, 41, 103, 55, 93, 85, 73, 81, 101, 98, 45, 30, 52, 53, 43, 0, 20, 54, 32, 34, 8, 0, 0, 2, 3, 2, 2, 3, 3, 0, 1, 0, 0, 0, 5, 10, 8, 3, 3, 11, 6, 10, 0, 6, 2, 9, 9, 11, 3, 0, 5, 13, 31, 29, 74, 89, 77, 67, 82, 81, 91, 88, 65, 73, 84, 67, 48, 53, 46, 50, 16, 3, 1, 1, 12, 24, 9, 49, 70, 58, 64, 33, 36, 30, 6, 38, 72, 78, 89, 87, 82, 56, 30, 46, 23, 1, 4, 19, 61, 26, 61, 
+#> 69, 98, 132, 92, 53, 86, 22, 37, 64, 25, 63, 5, 77, 81, 89, 93, 106, 92, 82, 85, 29, 34, 7, 38, 45, 40, 58, 67, 74, 85, 71, 76, 85, 70, 55, 58, 3, 4, 1, 0, 72, 51, 12, 55, 85, 61, 3, 35, 7, 28, 15, 13, 6, 2, 3, 2, 54, 36, 80, 58, 60, 53, 52, 71, 79, 111, 90, 60, 1, 28, 26, 37, 46, 78, 54, 61, 39, 63, 76, 63, 19, 19, 28, 63, 27, 8, 0, 3, 7, 3, 5, 6, 2, 1, 0, 2, 1, 2, 2, 6, 2, 0, 1, 3, 2, 0, 2, 2, 1, 0, 1, 0, 1, 7, 0, 2, 0, 1, 1, 1, 0, 0, 1, 0, 1, 0, 1, 2, 0, 1, 0, NA, 0, 2, 4, 3, 0, 0, 0, 0, 2, 1, 
+#> 36, 18, 53, 45, 80, 99, 72, 90, 76, 71, 0, 4, 14, 4, 6, 7, 11, 13, 3, 2, 0, 0, 1, 0, 3, 6, 52, 39, 22, 59, 45, 50, 42, 42, 47, 37, 31, 33, 7, 48, 66, 42, 69, 60, 89, 100, 95, 77, 95, 91, 105, 103, 74, 87, 65, 82, 68, 20, 131, 107, 101, 107, 96, 99, 97, 70, 90, 60, 58, 74, 60, 56, 56, 46, 38, 27, 75, 105, 130, 83, 81, 92, 60, 92, 76, 57, 23, 77, 73, 16, 5, 5, 3, 1, 1, 0, 1, 0, 0, 4, 75, 94, 87, 100, 115, 100, 92, 91, 103, 137, 86, 95, 72, 55, 68, 36, 2, 16, 64, 119, 94, 67, 63, 79, 98, 64, 50, 81, 
+#> 58, 72, 51, 51, 17, 3, 55, 66, 80, 90, 67, 129, 90, 91, 89, 92, 68, 20, 10, 8, 13, 4, 21, 49, 31, 41, 67, 4, 28, 29, 28, 41, 33, 37, 38, 20, 1, 9, 2, 0, 2, 0, 0, 0, 0, 0, 0, 2, 3, 7, 0, 0, 3, 0, 2, 2, 0, 1, 0, 0, 2, 0, 0, 0, 4, 1, 7, 0, 2, 4, 1, 1, 2, 2, 1, 0, 1, 2, 0, 0, 31, 20, 12, 74, 96, 73, 94, 91, 70, 56, 14, 5, 0, 0, 1, 0, 3, 0, 0, 1, 3, 6, 2, 2, 2, 2, 0, 0, 4, 7, 9, 9, 3, 9, 9, 5, 10, 18, 6, 2, 4, 1, 0, 0, 10, 9, 2, 11, 6, 12, 7, 7, 8, 17, 6, 3, NA, 1, 0, NA, 4, 4, 4, NA, 0, NA, 4, 2, 0, 
+#> 0, 4, 90, 54, 70, 65, 43, 64, 83, 40, 24, 29, 42, 42, 27, 20, 3, 1, 94, 91, 75, 94, 76, 45, 60, 46, 13, 1, 1, 0, 0, 10, 10, 8, 5, 4, 3, 6, 8, 4, 7, 0, 0, 43, 60, 120, 69, 70, 3, 27, 72, 30, 2, 52, 4, 24, 17, 26, 9, 3, 53, 67, 43, 16, 1, 2, 1, 0, 3, 9, 8, 6, 6, 9, 3, 3, 3, 0, 0, 0, 2, 4, 0, 0, 0, 0, 0, 0, 1, 1, 2, 1, 0, 0, 3, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 3, 1, 3, 1, 3, 3, 4, 5, 71, 99, 91, 77, 78, 81, 112, 90, 96, 125, 75, 70, 82, 93, 91, 71, 99, 70, 69, 49, 36, 53, 38, 4, 2, 65, 69, 
+#> 74, 94, 126, 73, 63, 29, 21, 9, 21, 14, 47, 46, 47, 47, 24, 10, 14, 52, 46, 18, 33, 24, 8, 0, 2, 50, 24, 37, 53, 99, 112, 97, 90, 64, 68, 71, 80, 4, 1, 30, 29, 28, 31, 8, 27, 5, 23, 40, 25, 2, 0, 0, 1, 0, 12, 9, 2, 12, 10, 10, 9, 12, 7, 2, 101, 64, 117, 97, 86, 94, 120, 120, 86, 107, 115, 110, 112, 130, 95, 103, 90, 95, 73, 80, 52, 9, 34, 60, 15, 14, 79, 71, 51, 85, 45, 41, 49, 38, 44, 50, 23, 0, 16, 3, 3, 13, 6, 4, 2, 10, 5, 8, 3, 5, 4, 3, 4, NA, 0, 10, 12, 36, 74, 107, 96, 101, 93, 93, 62, 46, 
+#> 66, 65, 27, 28, 10, 1, 4, 4, 11, 12, 8, 14, 11, 7, 3, 11, 14, 5, 12, 8, 6, 1, 0, 1, 5, 3, 3, 1, 2, 0, 1, 1, 0, 0, 44, 64, 67, 42, 47, 34, 15, 10, 15, 29, 48, 59, 5, 9, 0, 3, 15, 2, 1, 44, 84, 44, 79, 94, 88, 93, 107, 86, 97, 83, 77, 68, 65, 29, 8, 25, 34, 24, 25, 31, 26, 0, 31, 3, 4, 3, 0, 109, 107, 99, 76, 54, 97, 96, 73, 1, 63, 43, 46, 3, 6, 125, 93, 112, 89, 87, 79, 88, 82, 90, 39, 84, 54, 52, 19, 38, 64, 48, 83, 52, 81, 73, 53, 4, 7, 3, 1, 12, 10, 4, 2, 98, 84, 94, 85, 88, 95, 78, 89, 105, 40, 
+#> 106, 96, 61, 53, 29, 28, 25, 7, 15, 83, 86, 66, 78, 75, 77, 78, 95, 31, 31, 7, 25, 31, 25, 17, 10, 4, 3, 64, 59, 21, 63, 44, 79, 72, 70, 89, 56, 61, 66, 1, 0, 40, 23, 57, 87, 68, 83, 67, 45, 72, 89, 97, 71, 67, 59, 33, 36, 2, 2, 4, 4, 1, 2, 3, 0, 5, 0, 0, 0, 0, 1, 37, 69, 45, 47, 66, 73, 61, 44, 57, 51, 33, 58, 42, 22, 13, 23, 77, 42, 61, 65, 59, 30, 45, 67, 67, 59, 25, 9, 5, 15, 72, 73, 69, 50, 66, 34, 4, 15, 1, 10, 57, 69, 51, 23, 29, 33, 40, 11, 20, 44, 29, 49, 59, 24, 15, 2, 0, 88, 61, 81, 52, 
+#> 54, 15, 4, 1, 1, 21, 7, 2, 4, 5, 8, 8, 4, 11, 3, 8, 13, 5, 6, 1, 1, 1, 0, 0, 1, 1, 2, 8, 8, 5, 4, 9, 8, 6, 3, NA, 1, 0, 31, 1, 1, 63, 92, 75, 39, 29, 51, 66, 74, 19, 61, 3, 0, 14, 16, 2, 66, 3, 1, 34, 53, 68, 84, 54, 57, 89, 70, 104, 75, 106, 90, 71, 54, 29, 60, 60, 28, 2, 6, 0, 1, 0, 2, 2, 0, 3, 0, 0, 1, 0, 0, 1, 0, 1, 0, NA, 0, 1, 1, 3, 1, 1, 0, 1, 0, 0, 0, 2, 1, 0, 1, 0, 0, 0, 42, 47, 54, 51, 48, 5, 34, 34, 14, 8, 0, 3, 0, 2, 98, 73, 30, 97, 107, 58, 52, 30, 8, 3, 30, 47, 88, 59, 48, 28, 46, 38, 
+#> 30, 25, 0, 4, 72, 40, 35, 38, 42, 40, 45, 44, 32, 7, 10, 5, 0, 0, 44, 67, 74, 54, 78, 53, 60, 83, 82, 59, 53, 52, 37, 64, 29, 0, 2, 45, 47, 19, 26, 25, 19, 8, 18, 5, 0, 3, 8, 5, 19, 13, 7, 13, 8, 9, 6, 2, 2, 21, 38, 48, 59, 96, 75, 60, 80, 122, 76, 72, 54, 70, 52, 0, 33, 4, 25, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 4, 4, 5, 3, 1, 2, 0, 3, 0, 0, 1, 0, 0, 0, 1, 40, 25, 78, 93, 103, 107, 72, 64, 73, 81, 74, 77, 71, 63, 58, 73, 35, 18, 18, 9, 25, 14, 1, 73, 79, 30, 81, 107, 94, 113, 92, 97, 
+#> 114, 126, 81, 110, 105, 78, 73, 69, 31, 56, 4, 5, 7, 4, 1, 2, 2, 1, 2, 3, 2, 5, 1, 2, 0, 0, 1, 4, 3, 4, 3, 3, 5, 0, 2, 5, 8, 4, 6, 1, 5, 0, 73, 74, 23, 63, 50, 72, 71, 98, 74, 86, 73, 103, 51, 18, 19, 9, 0, 49, 35, 72, 48, 102, 79, 75, 47, 73, 77, 51, 29, 20, 10, 7, 0, 2, 29, 80, 67, 56, 42, 76, 84, 69, 45, 1, 0, 50, 68, 41, 67, 13, 1, 23, 35, 2, 7, 3, 0, 66, 46, 79, 27, 88, 61, 98, 86, 89, 97, 128, 85, 78, 74, 57, 88, 66, 42, 69, 5, 5, 7, 9, 8, 5, 9, 3, 7, 5, 10, 1, 5, 3, 5, 3, 3, 6, 0, 0, NA, NA, 
+#> 3, 3, 5, 39, 53, 48, 50, 68, 35, 46, 16, 51, 19, 14, 30, 3, 13, 1, 6, 26, 28, 18, 13, 2, 31, 19, 90, 62, 102, 85, 113, 82, 38, 117, 90, 104, 80, 75, 10, 7, 0, 6, 0, 5, 4, 6, 4, 13, 8, 2, 1, NA, NA, NA, 0, 0, NA, NA, 2, 3, 0, 0, 0, 3, 9, 3, 12, 4, 5, 6, 4, 9, 3, NA, NA, NA, 5, 0, 0, 1, 2, 2, 10, 3, 7, 5, 2, 0, 0, 0, 1, 78, 78, 87, 109, 85, 75, 79, 79, 67, 35, 20, 104, 82, 41, 47, 5, 51, 3, 14, 28, 38, 88, 73, 83, 43, 45, 81, 40, 26, 34, 30, 15, 73, 73, 91, 98, 69, 99, 80, 51, 38, 11, 2, 7, 67, 83, 
+#> 97, 80, 87, 83, 108, 83, 62, 67, 52, 73, 52, 14, 44, 32, 20, 12, 4, 10, 25, 37, 51, 27, 35, 31, 2, 22, 0, 19, 3, 3, 1, 0, 4, 1, 3, 6, 5, 0, NA, 0, 0, 0, 0, NA, 0, 2, 1, 0, NA, 0, 16, 15, 61, 24, 25, 9, 23, 10, 79, 6, 83, 3, 20, 6, 6, 69, 72, 47, 68, 66, 53, 64, 44, 42, 32, 62, 40, 0, 55, 15, 11, 12, 77, 32, 0, 1, 4, 1, 6, 1, 10, 4, 14, 3, 4, NA, NA, 1, 1, 19, 50, 61, 63, 109, 100, 77, 77, 52, 83, 77, 55, 12, 14, 35, 14, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 1, 8, NA, 0, 0, NA, NA, NA, 2, 41, 36, 29, 20, 
+#> 9, 15, 20, 20, 3, 0, 0, 0, 4, 6, 3, 6, 6, 7, 5, NA, NA, NA, NA, NA, 5, 47, 62, 50, 52, 68, 67, 31, 84, 56, 0, 23, 5, 14, 1, 2, 19, 40, 76, 53, 67, 36, 60, 54, 44, 66, 39, 39, 28, 37, 9, 6, 20, 13, 49, 98, 100, 65, 46, 82, 50, 81, 55, 40, 3, 15, 0, 4, 54, 61, 85, 59, 43, 69, 59, 63, 19, 57, 44, 10, 0, 1, 43, 54, 43, 65, 53, 71, 7, 36, 47, 67, 49, 39, 16, 33, 19, 8, 69, 40, 53, 53, 69, 68, 56, 18, 64, 38, 12, 36, 1, 13, 82, 123, 57, 87, 72, 99, 90, 91, 84, 93, 82, 78, 94, 33, 92, 43, 67, 64, 65, 42, 
+#> 0, 38, 58, 53, 41, 92, 82, 82, 62, 44, 53, 31, 17, 0, 0, 5, 6, 5, 4, 5, 6, 6, 7, 8, 5, 7, 7, 9, 7, 5, 8, 9, 8, 2, NA, 3, 1, NA, NA, NA, 1, 38, 28, 4, 28, 37, 86, 87, 59, 105, 97, 85, 11, 46, 59, 1, 8, 1, 2, 74, 46, 63, 92, 71, 63, 39, 48, 62, 2, 2, 2, 0, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, NA, 0, NA, 0, 0, 7, 39, 65, 53, 89, 80, 46, 63, 14, 31, 65, 29, 13, 5, 7, 4, 8, 0, 5, 0, 3, 5, 2, 4, 8, 9, 10, 3, NA, NA, NA, 0, 2, 39, 61, 50, 13, 10, 35, 36, 50, 53, 56, 12, 60, 38, 6, 14, 6, 
+#> 0, 0, 11, 62, 53, 42, 37, 20, 14, 26, 25, 3, 6, 2, 2, 4, 51, 50, 49, 49, 25, 45, 29, 41, 48, 21, 6, 24, 42, 62, 90, 51, 70, 79, 61, 41, 45, 19, 47, 69, 82, 77, 59, 57, 89, 23, 8, 6, 59, 71, 54, 80, 64, 83, 79, 85, 73, 42, 0, 6, 7, 5, 7, 8, 9, 2, 0, 1, 1, 2, 5, 2, 5, 5, 3, 5, 1, 3, NA, 1, NA, 0, 1, 2, 4, 1, 6, 7, 0, 0, NA, NA, NA, 8, 10, 35, 28, 104, 112, 88, 42, 45, 58, 32, 1, 7, 2, 1, 1, 6, 4, 0, 0, NA, NA, 0, 8, 7, 3, 4, NA, NA, 0, 3, 6, 6, 91, 80, 75, 89, 87, 87, 93, 85, 74, 100, 56, 49, 73, 35, 
+#> 6, 55, 120, 134, 110, 118, 131, 97, 93, 48, 103, 8, 85, 93, 37, 26, 12, 56, 103, 60, 91, 52, 74, 65, 86, 66, 92, 84, 81, 82, 86, 41, 16, 61, 9, 3, 20, 59, 38, 42, 72, 55, 54, 35, 48, 5, 34, 25, 16, 7, 26, 49, 51, 70, 8, 38, 66, 79, 90, 81, 61, 83, 44, 57, 59, 47, 16, 13, 0, 4, 64, 72, 58, 47, 42, 18, 17, 39, 9, 18, 58, 78, 77, 60, 53, 35, 36, 2, 56, 49, 78, 52, 34, 11, 8, 2, 3, 82, 95, 94, 102, 83, 69, 80, 73, 90, 66, 22, 42, 41, 14, 12, 2, 10, 27, 60, 81, 40, 59, 30, 24, 16, 23, 16, 7, 0, 2, 11, 
+#> 2, 5, 13, 7, 12, NA, NA, NA, NA, NA, NA, NA, 0, NA, NA, NA, NA, 1, 14, 54, 78, 85, 78, 85, 87, 65, 59, 67, 61, 75, 56, 59, 20, 3, 12, 6, 62, 63, 60, 55, 64, 77, 60, 52, 42, 15, 8, 2, 0, 2, 0, 0, 3, 1, 0, NA, NA, NA, NA, 0, NA, 0, 3, 1, 2, 5, 8, 4, 1, 1, 1, 0, 1, 0, 2, 0, 0, 0, 5, 4, 100, 60, 73, 6, 94, 102, 87, 122, 116, 107, 107, 113, 113, 68, 70, 66, 47, 68, 72, 50, 1, 19, 26, 22, 83, 71, 83, 64, 66, 60, 61, 46, 26, 18, 7, 0, 1, 0, 4, 4, 2, 3, 5, 7, 5, 5, NA, NA, 0, NA, NA, NA, 5, 2, NA, NA, 5, 
+#> NA, NA, 0, 2, 51, 43, 43, 35, 21, 14, 0, 0, 7, 74, 65, 36, 47, 76, 106, 94, 49, 73, 44, 66, 85, 54, 85, 42, 68, 37, 47, 65, 42, 12, 2, 0, 8, 44, 54, 35, 42, 21, 12, 71, 63, 40, 42, 55, 55, 2, 6, 0, 46, 85, 103, 86, 95, 93, 89, 92, 31, 57, 71, 42, 52, 40, 59, 24, 14, 5, 50, 74, 67, 42, 97, 79, 71, 93, 78, 74, 57, 34, 50, 73, 33, 13, 2, 1, 6, 5, 3, 6, 10, 1, NA, NA, NA, NA, NA, NA, 4, 10, 10, 40, 62, 94, 53, 73, 66, 54, 48, 58, 35, 42, 14, 21, 1, 8, 3, 13, 5, 60, 28, 5, 1, 7, 0, 74, 74, 58, 55, 60, 
+#> 51, 58, 1, 47, 31, 35, 33, 41, 31, 2, 1, 9, 16, 21, 39, 26, 7, 1, 0, 0, 2, 1, 2, NA, 0, NA, 0, 0, NA, 0, 0, NA, 2, NA, 0, 0, 0, 2, 0, 0, 2, 6, 1, 0, 2, 2, 1, 1, NA, NA, 0, 0, 27, 67, 82, 85, 87, 71, 97, 80, 85, 89, 77, 69, 67, 77, 30, 27, 2, 32, 11, 19, 11, 7, 66, 82, 92, 81, 93, 24, 68, 78, 60, 56, 74, 65, 60, 74, 42, 0, 15, 16, 48, 49, 45, 58, 36, 3, 18, 20, 21, 43, 8, 16, 5, 5, 4, 5, 14, 0, 64, 84, 67, 66, 54, 37, 24, 11, 17, 24, 5, 0, 0, 0, 1, 1, 0, 0, NA, NA, NA, 0, NA, NA, NA, NA, 5, 73, 35, 
+#> 47, 71, 74, 21, 80, 118, 61, 77, 63, 47, 6, 11, 74, 87, 67, 79, 89, 75, 97, 79, 62, 89, 66, 101, 45, 49, 3, 10, 0, 0, 23, 16, 65, 87, 63, 95, 76, 73, 51, 61, 62, 34, 20, 7, 1, 11, 67, 106, 93, 75, 64, 97, 84, 64, 75, 65, 85, 57, 28, 10, 0, 2, 4, 4, 5, 6, 4, 6, 0, 0, 0, NA, NA, NA, 2, NA, 2, 3, 4, 42, 67, 114, 99, 82, 11, 42, 64, 82, 68, 69, 51, 64, 94, 60, 81, 78, 90, 48, 31, 0, 3, 0, 7, 5, 11, 1, 0, 35, 30, 29, 47, 55, 61, 24, 53, 84, 72, 72, 38, 20, 64, 47, 25, 19, 21, 2, 2, 0, 0, 3, 0, 1, 2, 0, 
+#> 0, 1, 0, NA, 0, 0, 0, 0, 0, 8, 27, 36, 37, 95, 85, 85, 91, 89, 92, 78, 63, 66, 76, 72, 80, 58, 5, 5, 48, 64, 58, 26, 19, 61, 34, 58, 1, 33, 20, 3, 5, 9, 9, 5, 10, 14, 5, 0, 0, NA, 0, NA, NA, NA, 8, 5, 13, 32, 35, 73, 69, 59, 54, 28, 38, 16, 14, 14, 2, 1, 5, 4, 8, 2, 3, 12, 8, 3, 2, NA, 1, 38, 24, 40, 39, 70, 62, 74, 59, 75, 91, 72, 57, 48, 54, 46, 59, 42, 32, 11, 25, 10, 54, 29, 25, 25, 9, 12, 1, 20, 4, 71, 84, 81, 71, 91, 72, 49, 35, 32, 42, 43, 5, 19, 57, 82, 80, 98, 63, 60, 15, 86, 43, 67, 57, 
+#> 44, 31, 8, 81, 70, 40, 55, 21, 68, 82, 68, 26, 8, 21, 2, 43, 108, 93, 112, 114, 93, 109, 104, 78, 108, 104, 93, 89, 97, 88, 52, 19, 3, 3, 7, 6, 8, 5, 2, NA, NA, 2, 4, 44, 75, 69, 91, 78, 68, 69, 48, 42, 61, 30, 1, 1, 0, 0, NA, NA, 2, 1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 2, 1, 4, 2, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, NA, NA, 16, 65, 77, 68, 70, 76, 48, 37, 62, 35, 92, 68, 38, 20, 49, 38, 56, 5, 3, 2, 0, 9, 4, 8, 7, 0, 3, NA, 0, 0, 0, NA, NA, NA, NA, 0, NA, 5, 103, 76, 81, 75, 116, 67, 28, 89, 56, 84, 59, 67, 
+#> 49, 37, 9, 44, 18, 5, 40, 48, 43, 40, 58, 41, 42, 39, 10, 0, 62, 81, 74, 50, 4, 75, 85, 62, 70, 59, 37, 39, 27, 29, 22, 1, 1, 5, 5, 4, 3, 5, 0, 10, 1, 1, 1, 5, 4, 3, 1, 2, 3, 1, 1, 2, NA, 1, NA, NA, NA, 0, 13, 27, 81, 78, 65, 65, 74, 71, 88, 99, 81, 71, 52, 46, 47, 56, 56, 66, 36, 16, 5, 6, 92, 75, 104, 121, 117, 81, 51, 86, 90, 98, 85, 98, 66, 57, 22, 4, 45, 47, 64, 79, 81, 64, 90, 56, 99, 100, 64, 100, 81, 40, 65, 36, 2, 4, 7, 6, 2, 6, 8, 1, 0, 1, 0, 13, 66, 76, 29, 85, 74, 99, 85, 47, 44, 55, 
+#> 87, 73, 47, 1, 55, 63, 69, 88, 90, 96, 90, 62, 75, 65, 69, 96, 53, 90, 70, 9, 27, 1, 20, 17, 27, 75, 82, 107, 102, 109, 71, 29, 41, 68, 73, 88, 89, 77, 43, 56, 71, 45, 2, 0, 0, NA, NA, NA, 0, NA, NA, 0, NA, NA, NA, 0, 1, 0, 0, 0, NA, 0, NA, NA, 0, 0, 0, 0, 0, 0, 2, 2, 0, 0, NA, NA, 0, 0, 0, 1, 2, 39, 11, 15, 6, 31, 71, 86, 124, 97, 68, 79, 64, 64, 74, 67, 57, 2, 28, 14, 14, 47, 6, 64, 68, 65, 46, 54, 47, 40, 30, 40, 27, 14, 7, 4, 24, 0, 1, 45, 45, 33, 61, 54, 50, 59, 42, 37, 30, 43, 38, 41, 9, 8, 
+#> 13, 13, 2, 46, 60, 61, 61, 39, 75, 69, 72, 84, 122, 74, 121, 110, 86, 109, 96, 82, 66, 35, 69, 73, 33, 65, 67, 55, 47, 71, 20, 40, 53, 19, 31, 21, 0, 3, 4, 6, 0, 3, 6, 4, 3, 3, 3, 0, 3, 3, 2, 0, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 4, 4, 3, 6, 6, 4, 4, 6, 7, 4, 2, 3, 1, 2, 3, 1, 3, NA, NA, NA, NA, NA, NA, NA, 1, NA, NA, 0, 0, NA, NA, NA, NA, NA, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, NA, 0, 0, NA, 0, NA, NA, NA, NA, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 4, 0, 0, 1, 3, 0, 0, 0, 2, 49, 84, 94, 105, 79, 
+#> 119, 87, 42, 101, 90, 42, 108, 70, 71, 90, 67, 82, 77, 55, 69, 1, 18, 39, 9, 36, 71, 58, 75, 104, 90, 55, 73, 38, 91, 84, 30, 41, 22, 5, NA, NA, 0, 0, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0, 0, NA, 3, 6, 31, 18, 26, 69, 70, 95, 79, 78, 37, 35, 96, 62, 6, 37, 40, 2, 3, 78, 60, 69, 55, 9, 52, 52, 22, 70, 66, 36, 19, 1, 39, 6, 2, 0, 4, 4, 42, 41, 28, 40, 55, 48, 38, 34, 19, 42, 46, 33, 37, 48, 42, 38, 33, 11, 19, 24, 95, 111, 117, 90, 62, 89, 65, 70, 60, 44, 68, 36, 33, 65, 21, 
+#> 5, 26, 6, 13, 10, 20, 19, 43, 39, 59, 66, 73, 70, 35, 71, 52, 58, 62, 76, 67, 48, 34, 20, 8, 10, 60, 43, 49, 56, 61, 19, 26, 18, 25, 44, 60, 54, 48, 14, 6, 9, 28, 44, 71, 98, 63, 69, 11, 58, 27, 72, 39, 60, 59, 5, 0, 0, 3, 2, 62, 101, 80, 63, 36, 86, 62, 86, 80, 48, 80, 71, 31, 48, 25, 81, 85, 90, 100, 57, 87, 115, 97, 111, 61, 89, 75, 66, 96, 69, 64, 77, 57, 68, 36, 33, 13, 0, 9, 64, 84, 90, 96, 71, 107, 104, 73, 65, 65, 90, 78, 62, 72, 69, 60, 44, 34, 30, 6, 9, 59, 91, 87, 98, 99, 59, 85, 73, 86, 
+#> 75, 76, 96, 43, 62, 15, 37, 60, 29, 1, 75, 52, 7, 88, 68, 37, 81, 95, 96, 18, 16, 11, 7, 0, 2, 3, 2, 4, 4, 0, NA, NA, NA, NA, NA, NA, 5, 3, 5, 3, 3, 2, 1, 2, 1, NA, NA, NA, NA, NA, 36, 66, 75, 80, 75, 93, 89, 53, 4, 22, 2, 35, 26, 0, 0, 29, 64, 70, 62, 66, 80, 60, 82, 71, 68, 84, 45, 73, 76, 44, 60, 14, 20, 6, 3, 3, 4, 3, 9, 9, 5, 8, 4, 1, NA, 0, 2, 8, 7, 7, 1, 4, 2, 2, 0, 32, 94, 82, 105, 83, 47, 76, 39, 40, 63, 42, 42, 35, 43, 45, 20, 5, 17, 55, 52, 44, 54, 40, 47, 57, 20, 11, 16, 36, 2, 0, 0, 
+#> 3, 1, 0, 0, NA, NA, 0, 0, NA, NA, NA, 0, 9, 13, 65, 41, 21, 40, 34, 66, 60, 52, 38, 50, 41, 17, 5, 3, 20, 54, 90, 90, 116, 111, 65, 79, 43, 34, 83, 87, 94, 87, 43, 18, 7, 6, 77, 95, 108, 72, 85, 93, 109, 79, 35, 58, 64, 5, 32, 52, 38, 11, 4, 2, 36, 63, 75, 73, 40, 8, 15, 33, 30, 5, 0, 0, 0, 4, 3, 11, 5, 3, 7, 3, 5, 5, 5, 2, 5, 10, 2, 1, 6, 3, NA, NA, NA, 0, NA, NA, 5, 71, 75, 68, 48, 76, 94, 90, 102, 95, 110, 54, 77, 75, 94, 77, 72, 67, 36, 50, 66, 81, 42, 85, 75, 15, 61, 70, 15, 43, 26, 43, 60, 
+#> 71, 54, 89, 98, 94, 32, 77, 65, 93, 73, 84, 75, 32, 9, 42, 9, 11, 5, 2, 2, 48, 67, 59, 66, 66, 72, 121, 50, 129, 102, 105, 76, 82, 99, 92, 101, 98, 66, 71, 62, 3, 14, 64, 90, 84, 77, 60, 90, 82, 33, 71, 34, 93, 81, 76, 59, 75, 32, NA, NA, NA, NA, NA, 0, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0, NA, 0, 4, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 9, 0, 12, 55, 49, 66, 86, 60, 83, 96, 70, 104, 106, 63, 82, 46, 25, 49, 86, 51, 66, 75, 64, 71, 89, 76, 44, 62, 75, 88, 28, 33, 89, 74, 3, 24, 4, 5, 55, 53, 50, 
+#> 62, 84, 51, 26, 73, 8, 41, 36, 16, 0, 3, 55, 42, 51, 53, 40, 68, 37, 52, 33, 16, 45, 36, 22, 27, 15, 3, 9, 57, 74, 81, 104, 88, 97, 89, 52, 84, 99, 106, 105, 90, 83, 96, 63, 7, 75, 92, 72, 35, 11, 4, 0, 33, 64, 66, 79, 85, 87, 103, 120, 39, 52, 80, 82, 84, 70, 93, 64, 3, 28, 3, 41, 70, 8, 20, 77, 97, 89, 22, 90, 78, 91, 49, 49, 8, NA, NA, NA, NA, 0, 0, NA, NA, NA, 0, NA, NA, 0, NA, NA, 49, 67, 41, 48, 83, 5, 0, 5, 1, 81, 63, 30, 57, 62, 53, 75, 74, 69, 39, 49, 38, 27, 21, 15, 0, 0, 6, 1, 2, NA, NA, 
+#> 3, NA, 4, 3, 8, 8, 5, 0, 2, NA, NA, 0, 4, 2, 50, 59, 66, 43, 61, 77, 101, 51, 22, 46, 57, 56, 30, 21, 19, 22, 34, 77, 100, 68, 88, 62, 90, 67, 93, 85, 48, 71, 52, 28, 22, 46, 15, 93, 80, 94, 64, 24, 2, 55, 70, 15, 17, 57, 59, 32, 17, 65, 54, 41, 65, 70, 4, 5, 22, 16, 65, 97, 31, 40, 80, 25, 68, 66, 70, 1, 24, 69, 95, 110, 87, 62, 82, 48, 17, 37, 9, 12, 46, 5, 2, 0, 1, 8, 5, 2, 0, 0, 1, 1, 2, 6, 1, 7, 1, 2, 1, 4, 6, NA, NA, NA, NA, NA, 0, 3, 1, 1, 1, 3, 1, 0, 2, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 2, 
+#> 0, 2, 3, 1, NA, NA, NA, 0, NA, 15, 57, 86, 58, 84, 55, 93, 77, 50, 39, 14, 20, 0, 10, 43, 113, 133, 54, 87, 90, 81, 87, 77, 97, 81, 58, 49, 38, 38, 29, 4, 0, NA, 0, 0, NA, NA, NA, 1, NA, 0, 6, 49, 68, 107, 52, 66, 83, 85, 79, 107, 109, 73, 54, 71, 57, 11, 72, 38, 28, 16, 17, 20, 0, 14, 37, 35, 46, 24, 13, 13, 44, 23, 2, 0, 5, 58, 31, 86, 76, 74, 76, 48, 91, 63, 75, 83, 81, 55, 39, 14, 24, 22, 24, 69, 77, 67, 53, 58, 69, 53, 70, 67, 104, 80, 82, 61, 96, 73, 75, 51, 16, 36, NA, NA, NA, NA, NA, NA, 
+#> NA, NA, NA, NA, 0, 0, 0, 76, 14, 7, 1, 0, 0, 1, 0, NA, NA, NA, NA, 0, NA, NA, NA, 10, 37, 65, 79, 39, 75, 80, 75, 64, 53, 42, 44, 48, 54, 38, 7, 19, 2, 10, 15, 2, 27, 16, 28, 45, 36, 63, 71, 88, 94, 53, 92, 49, 49, 40, 31, 8, 10, 64, 65, 82, 72, 75, 9, 55, 67, 73, 67, 65, 73, 57, 5, 23, 45, 14, 12, 1, 9, 6, 6, 2, 7, 11, 0, 7, 4, 1, 3, 7, 9, 0, 3, 1, 1, 1, 7, 25, 47, 70, 23, 29, 18, 8, 15, 22, 28, 31, 28, 12, 18, 10, 0, 1, 0, NA, NA, NA, NA, NA, 1, 3, 6, 4, 0, NA, 1, 2, 1, 2, 0, 0, 0, 1, 0, 0, 0, 
+#> 1, 0, 3, 60, 88, 72, 69, 77, 84, 77, 81, 42, 62, 73, 71, 64, 42, 12, 0, 3, 6, 5, 5, 7, 5, 4, 2, 3, 8, NA, NA, 0, 3, 4, 0, 1, 5, 0, 25, 44, 38, 35, 33, 21, 9, 1, 49, 111, 89, 119, 105, 113, 146, 130, 78, 118, 41, 72, 119, 105, 77, 77, 37, 66, 67, 110, 21, 63, 101, 89, 17, 58, 70, 40, 7, 0, 4, 4, 1, 0, 6, 2, 1, 4, 5, 4, 3, 3, 5, 0, NA, NA, NA, NA, NA, NA, NA, NA, 0, NA, 0, NA, 0, 0, 0, NA, NA, NA, 63, 114, 87, 61, 65, 43, 70, 51, 80, 89, 80, 81, 58, 0, 65, 0, 26, 17, 29, 87, 51, 58, 77, 107, 50, 40, 
+#> 8, 42, 22, NA, NA, 1, 0, NA, NA, 3, NA, 0, NA, 0, 0, NA, NA, NA, NA, NA, NA, 3, 7, 27, 46, 87, 87, 85, 99, 7, 89, 24, 16, 60, 42, 41, 10, 18, 18, 41, 34, 42, 53, 19, 33, 20, 5, 13, 31, 16, 4, 10, NA, NA, NA, 4, 7, 4, NA, NA, NA, NA, NA, 3, 5, 66, 53, 98, 43, 113, 131, 94, 118, 89, 115, 77, 60, 38, 22, 66, 5, 1, 1, 90, 121, 103, 116, 98, 97, 87, 80, 78, 99, 73, 87, 71, 71, 94, 79, 65, 51, 43, 43, 15, 88, 94, 70, 62, 91, 84, 70, 88, 70, 85, 74, 20, 2, 5, 3, 50, 24, 89, 84, 79, 70, 57, 3, 26, 2, 0, 
+#> 20, 36, 63, 72, 67, 64, 49, 94, 49, 77, 50, 69, 65, 1, 42, 42, 84, 58, 86, 58, 66, 70, 10, 4, 2, 2, 4, 4, 1, 10, 1, 6, 2, 1, 0, 2, 2, 7, 4, 1, NA, 0, 0, 2, 1, 0, 0, NA, NA, NA, NA, NA, NA, NA, NA, NA, 16, 10, 34, 27, 70, 97, 78, 54, 96, 51, 21, 6, 76, 21, 24, 0, 0, 1, 0, NA, NA, NA, 1, 0, 0, NA, NA, NA, NA, NA, 0, 6, 4, 69, 40, 120, 83, 77, 77, 15, 80, 26, 14, 89, 72, 58, 23, 8, 35, 13, 2, 5, 4, 2, 1, 2, 8, 7, 5, 3, 5, 2, 1, NA, NA, NA, 0, 1, 1, NA, 0, NA, NA, NA, NA, NA, NA, NA, 1, 1, 2, 0, 0, 12, 
+#> 18, 11, 1, 27, 41, 48, 51, 24, 35, 33, 37, 54, 42, 16, 25, 16, 13, 15, 2, NA, 0, NA, NA, 0, 0, 4, 3, 0, 4, 3, 4, 10, 5, NA, NA, NA, 0, 7, 3, 2, 6, 2, 103, 94, 114, 113, 68, 81, 77, 104, 116, 104, 100, 67, 36, 85, 54, 1, 16, 53, 51, 77, 53, 56, 40, 55, 36, 62, 45, 39, 20, 18, 25, 14, 4, 2, 43, 75, 82, 114, 65, 76, 73, 23, 23, 76, 67, 56, 53, 19, 32, 52, 29, 27, 25, 1, 8, 7, 64, 71, 43, 72, 43, 15, 13, 22, 51, 46, 34, 0, 0, 2, 1, 0, 0, 0, NA, 0, 1, NA, NA, 3, 75, 67, 51, 34, 8, 21, 31, 26, 4, 29, 7, 
+#> 63, 75, 78, 76, 108, 101, 69, 92, 86, 20, 12, 13, 15, 35, 1, 44, 10, 51, 100, 109, 107, 107, 108, 128, 113, 89, 93, 62, 83, 61, 76, 80, 55, 51, 40, 44, 36, 51, 104, 97, 92, 89, 106, 77, 72, 64, 37, 10, 79, 68, 75, 67, 67, 16, 48, 75, 52, 47, 0, 11, 28, 32, 75, 47, 54, 54, 46, 51, 20, 19, 25, 12, 2, 46, 33, 51, 24, 44, 49, 87, 79, 73, 79, 53, 62, 85, 96, 69, 48, 47, 9, 6, 32, 13, 73, 81, 3, 26, 24, 6, 36, 45, 54, 44, 30, 23, 15, 34, 55, 39, 75, 65, 53, 51, 42, 69, 35, 12, 1, 4, 3, 0, 0, 1, 5, 1, 2, 
+#> 2, 0, 6, NA, 1, NA, 3, 5, 61, 90, 133, 106, 115, 91, 123, 66, 76, 65, 102, 102, 75, 80, 81, 45, 56, 53, 20, 1, 13, 9, 0, 0, 2, 0, 0, 0, 0, 0, NA, NA, NA, 0, 0, 0, NA, 0, NA, NA, NA, 0, 0, 3, 23, 41, 34, 60, 92, 96, 84, 95, 106, 35, 59, 81, 6, 62, 71, 37, 0, 1, 0, 0, 0, 1, 0, 2, 0, 0, 0, 0, NA, NA, 5, 0, 56, 41, 94, 63, 32, 38, 19, 26, 4, 6, 0, 3, 3, 0, 0, 3, 2, 8, 2, NA, NA, 0, 80, 78, 66, 86, 67, 84, 63, 39, 5, 5, 11, 5, 4, 8, 1, 4, 7, 8, 5, 1, NA, 0, 0, 1, 0, 0, 0, 33, 34, 88, 90, 107, 119, 64, 
+#> 82, 79, 69, 77, 70, 79, 82, 67, 97, 65, 59, 17, 5, 0, 0, 6, 8, 5, 0, 3, 4, 10, 2, 9, 2, 9, NA, 0, 0, 0, 34, 91, 107, 117, 93, 94, 79, 40, 64, 89, 78, 62, 59, 1, 1, 2, NA, 0, 0, NA, NA, 0, 0, NA, NA, NA, NA, 1, NA, NA, 0, 2, 7, 1, 2, 0, 0, 0, 0, 5, 19, 63, 67, 93, 49, 65, 77, 66, 37, 27, 0, 1, 19, 89, 54, 55, 70, 50, 89, 52, 76, 69, 60, 53, 42, 68, 24, 23, 14, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, NA, 0, NA, 0, 0, NA, 0, NA, 71, 58, 64, 58, 63, 61, 52, 5, 44, 46, 50, 62, 59, 35, 2, 21, 22, 107, 94, 121, 77, 
+#> 94, 73, 45, 37, 64, 61, 39, 27, 10, 0, 19, 5, 85, 87, 101, 111, 78, 88, 67, 63, 74, 36, 8, 34, 40, 53, 61, 67, 50, 57, 61, 56, 74, 48, 28, 14, 5, 55, 42, 89, 76, 72, 86, 72, 59, 55, 55, 18, 11, 41, 76, 58, 64, 44, 60, 80, 15, 40, 40, 57, 5, 24, 2, 3, 8, 49, 100, 88, 101, 77, 83, 39, 20, 4, 29, 50, 83, 43, 67, 97, 48, 73, 42, 4, 65, 9, 39, 17, 6, NA, NA, NA, NA, NA, 3, 9, 6, 1, 0, 0, 0, 3, 0, 7, 56, 59, 94, 72, 83, 31, 15, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0, 1, 0, 0, 0, 0, 1, 0, 
+#> 1, 2, 0, 0, 1, 0, 4, 2, 2, 3, 7, 7, 4, 1, 2, 0, 0, 4, 59, 81, 55, 71, 91, 95, 66, 63, 61, 58, 41, 3, 37, 53, 76, 71, 63, 21, 39, 22, 0, 7, 54, 58, 51, 94, 107, 89, 62, 71, 8, 69, 37, 8, 63, 80, 119, 96, 109, 75, 82, 92, 104, 89, 79, 83, 5, 29, 71, 91, 90, 76, 64, 84, 81, 84, 20, 45, 50, 57, 55, 71, 73, 6, 5, 14, 41, 56, 55, 47, 61, 57, 2, 19, 12, 0, NA, NA, 0, 0, NA, NA, NA, NA, NA, NA, NA, NA, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 16, 85, 81, 120, 40, 83, 115, 66, 8, 30, 88, 64, 68, 56, 98, 75, 16, 31, 
+#> 46, 6, 51, 91, 70, 78, 87, 44, 29, 46, 8, 11, 26, 53, 90, 30, 35, 44, 73, 88, 39, 34, 0, 2, 22, 30, 21, 54, 66, 49, 11, 33, 24, 3, 4, 7, 5, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0, 0, 2, 4, 2, NA, NA, NA, 0, NA, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, NA, 0, 0, 0, NA, NA, NA, NA, NA, 4, NA, NA, NA, 1, NA, NA, NA, NA, NA, 0, 0, 37, 56, 56, 82, 44, 83, 46, 94, 98, 81, 25, 70, 21, 30, 11, 17, 0, 2, 18, 33, 24, 15, 27, 25, 22, 6, 0, 6, 7, 33, 26, 97, 120, 81, 74, 84, 39, 21, 14, 57, 19, 
+#> 81, 29, 81, 27, 38, 17, 73, 88, 81, 45, 136, 95, 3, 93, 62, 114, 115, 84, 64, 133, 89, 121, 86, 63, 99, 63, 75, 1, 2, 47, 29, 1, 20, 32, 74, 76, 49, 48, 70, 45, 12, 69, 39, 10, 97, 87, 74, 87, 62, 87, 16, 26, 75, 104, 48, 38, 130, 118, 60, 48, 10, 64, 49, 50, 42, 60, 37, 49, 35, 40, 71, 31, 3, 28, 22, 39, 56, 53, 15, 1, 3, 2, 69, 53, 15, 12, 21, 52, 42, 25, 11, 4, 1, 14, 105, 101, 90, 113, 68, 37, 32, 62, 74, 15, 7, 31, 32, 28, 3, 34, 13, 14, NA, 0, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0, 
+#> NA, 1, 1, 2, 6, 3, 3, 1, 1, 0, 3, 2, 0, 2, NA, 2, NA, NA, 0, NA, NA, NA, NA, NA, NA, NA, 1, 1, 7, 0, NA, 0, 0, 0, NA, 0, 0, 0, 0, 0, NA, 3, 66, 42, 37, 32, 50, 48, 47, 51, 43, 79, 60, 45, 35, 0, 4, 5, 4, 10, 1, 4, 0, 6, 6, 11, 4, NA, NA, 0, 7, 3, 0, 8, 3, 15, 46, 73, 61, 87, 100, 95, 55, 64, 33, 7, 8, 103, 76, 86, 57, 110, 98, 116, 67, 61, 77, 37, 84, 60, 26, 52, 51, 45, 61, 48, 93, 101, 64, 67, 87, 103, 42, 41, 6, 26, 1, 0, 40, 45, 63, 63, 54, 59, 52, 28, 20, 23, 10, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 
+#> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 44, 30, 50, 15, 36, 50, 58, 65, 89, 52, 64, 38, 29, 74, 40, 95, 91, 42, 86, 41, 10, 0, 15, 3, 68, 82, 97, 80, 86, 88, 80, 96, 108, 19, 85, 72, 72, 46, 22, 0, 13, 51, 28, 37, 30, 14, 1, 7, 7, 4, 71, 86, 87, 71, 76, 16, 77, 60, 67, 35, 9, 39, 72, 99, 76, 65, 34, 38, 71, 77, 89, 119, 120, 103, 67, 17, 33, 30, 36, 1, 27, 28, 58, 87, 96, 112, 102, 62, 81, 60, 47, 49, 107, 77, 11, 28, 12, 23, 17, 0, 0, 2, NA, NA, 1, 4, 1, 1, 0, NA, NA, NA, 0, NA, 27, 64, 91, 47, 85, 
+#> 88, 76, 57, 78, 98, 117, 34, 93, 108, 71, 29, 72, 39, 55, 4, 4, 0, 23, 16, 28, 53, 35, 55, 48, 57, 63, 42, 14, 5, 0, 2, 3, 0, NA, NA, 0, NA, NA, 0, NA, 0, NA, 0, NA, NA, NA, NA, NA, 66, 89, 102, 104, 91, 84, 69, 82, 73, 85, 69, 56, 98, 40, 49, 29, NA, NA, NA, NA, NA, 11, 4, 1, 1, 0, 2, 3, 3, 1, 1, 0, 1, 15, 68, 61, 89, 86, 82, 74, 75, 65, 45, 44, 23, 9, 46, 63, 86, 74, 8, 32, 23, 1, 2, 3, 4, 0, 0, 0, 3, 2, 0, NA, NA, 0, NA, 1, 0, 0, NA, 0, 7, 9, 4, 5, 4, 8, 2, 0, 0, NA, 0, 0, 0, 0, 0, 4, 3, 5, 3, 
+#> 0, 3, 2, 0, 0, 51, 19, 49, 60, 100, 90, 52, 48, 56, 57, 9, 18, 7, 14, 1, 2, NA, NA, NA, 0, NA, NA, 0, NA, 0, NA, NA, NA, NA, NA, NA, 0, NA, 0, 0, 0, 0, NA, 0, NA, 0, 0, NA, 1, 0, 0, 0, 64, 63, 42, 7, 2, 10, 32, 9, 8, 4, 1, 58, 100, 98, 91, 84, 79, 59, 52, 81, 85, 81, 77, 73, 75, 82, 27, 40, 67, 32, 7, 10, 23, 26, 19, 31, 72, 68, 85, 82, 79, 57, 76, 78, 5, 50, 97, 77, 101, 70, 110, 17, 66, 77, 71, 33, 40, 22, 39, 6, 4, 7, 5, 55, 47, 19, 14, 40, 14, 3, 23, 11, 43, 38, 30, 93, 85, 104, 89, 108, 48, 
+#> 32, 30, 26, 14, 64, 53, 79, 96, 98, 88, 123, 113, 146, 123, 123, 67, 118, 96, 102, 100, 94, 79, 68, 0, NA, 0, NA, NA, NA, NA, NA, NA, NA, NA, 1, 0, 0, 0, 0, 0, 2, 40, 66, 40, 69, 52, 73, 59, 8, 3, 38, 58, 27, 57, 14, 26, 10, 12, 23, 28, 26, 7, 1, 24, 55, 96, 79, 49, 10, 68, 45, 37, 10, 71, 24, 15, 2, 3, 1, 1, 3, 5, 2, 0, 4, 2, 5, NA, NA, NA, 0, NA, NA, 0, NA, 2, 4, 1, 8, 6, 5, 2, 4, 4, 5, 1, 0, 1, 0, 20, 50, 75, 83, 92, 58, 42, 10, 0, 1, 60, 10, 22, 24, 44, 32, 53, 63, 45, 19, 44, 17, 21, 8, 22, 
+#> 15, 11, 5, 3, 1, 94, 93, 73, 89, 56, 35, 75, 33, 41, 142, 91, 54, 22, 73, 74, 83, 92, 27, 6, 61, 91, 76, 83, 113, 94, 52, 125, 125, 120, 123, 100, 57, 17, 34, 49, 85, 62, 78, 16, 51, 44, 6, 72, 99, 97, 96, 104, 95, 109, 129, 89, 109, 122, 123, 120, 91, 129, 129, 117, 111, 129, 8, 74, 75, 0, 3, 13, 6, 1, 8, 6, 5, 5, 8, 6, 3, 4, 7, 2, 3, 6, 2, 5, 4, 2, 1, 2, 0, 1, 0, 2, 4, 14, 73, 64, 50, 3, 39, 32, 30, 33, 7, 0, 0, 0, 0, 0, 0, NA, NA, 0, 0, 1, 1, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, NA, 0, NA, NA, NA, 
+#> NA, NA, NA, 0, NA, 7, 76, 67, 78, 90, 61, 73, 23, 84, 94, 75, 46, 43, 58, 54, 6, 7, 30, 24, 104, 102, 80, 80, 67, 70, 55, 30, 40, 48, 1, 28, 17, 31, 87, 72, 58, 105, 74, 53, 69, 86, 72, 98, 43, 58, 29, 17, 8, 27, 31, 3, 29, 47, 36, 44, 29, 40, 46, 39, 19, NA, NA, NA, NA, 2, 0, 3, 7, 3, 5, 4, 1, 0, 0, 0, 6, 6, 5, 1, 11, 3, 4, 6, 8, 6, 3, 3, 5, 4, 0, 4, 5, 2, 6, 3, 2, 84, 82, 80, 88, 105, 109, 78, 71, 132, 64, 86, 138, 111, 113, 73, 42, 34, 14, 4, 5, 48, 92, 85, 85, 57, 79, 96, 27, 84, 88, 61, 70, 
+#> 68, 11, 31, 19, 8, 17, 3, 20, 38, 33, 31, 21, 17, 48, 4, 7, NA, 1, NA, 0, NA, NA, NA, NA, NA, NA, 0, 5, 82, 75, 80, 78, 85, 85, 75, 59, 61, 72, 52, 60, 34, 1, 4, 8, 4, 4, 4, 5, 1, 2, 1, 1, NA, 0, NA, NA, 0, NA, 0, 0, 0, 78, 104, 82, 85, 107, 140, 117, 117, 120, 75, 66, 41, 79, 87, 76, 104, 88, 111, 109, 124, 143, 152, 126, 94, 109, 104, 11, 39, 104, 108, 106, 106, 102, 110, 110, 109, 74, 115, 8, 77, 87, 53, 19, 77, 63, 20, 7, 6, 32, 64, 108, 83, 85, 84, 79, 89, 97, 92, 70, 70, 84, 76, 36, 15, 9, 
+#> 85, 26, 107, 101, 74, 113, 79, 74, 68, 60, 107, 15, 54, 31, 15, 58, 4, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0, 24, 39, 56, 56, 56, 116, 98, 88, 116, 66, 70, 67, 90, 72, 71, 74, 50, 33, 11, 41, 14, 32, 14, 65, 74, 72, 87, 72, 86, 55, 97, 88, 87, 92, 107, 75, 66, 43, 13, 21, 82, 52, 46, 53, 38, 33, 34, 5, 4, 4, 59, 59, 85, 85, 76, 96, 58, 143, 113, 108, 64, 107, 95, 86, 22, 29, 66, 1, 6, 7, 7, 7, 2, 6, 5, 3, 10, 4, 11, 0, 0, 0, 0, 1, 5, 1, 0, 0, 1, 93, 50, 8, 35, 51, 13, 0, 63, 74, 51, 83, 84, 86, 
+#> 59, 74, 84, 42, 52, 37, 8, 6, 0, 20, 71, 98, 100, 20, 47, 121, 121, 104, 86, 86, 100, 80, 42, 72, 45, 6, 11, 78, 77, 105, 57, 57, 89, 87, 110, 114, 69, 97, 38, 49, 17, 0, 32, 65, 87, 98, 66, 79, 90, 90, 74, 45, 93, 34, 42, 12, 34, 67, 25, 87, 33, 34, 61, 46, 118, 86, 21, 52, 103, 105, 98, 82, 126, 117, 104, 22, 107, 52, 44, 1, 14, 18, 10, 13, 29, 62, 36, 80, 90, 43, 44, 3, 22, 46, NA, NA, NA, NA, NA, NA, 7, 4, 55, 48, 82, 76, 72, 35, 7, 48, 49, 8, 0, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
+#> NA, NA, NA, 0, NA, NA, NA, 0, 0, 0, NA, 0, NA, 0, NA, 0, 0, 0, 15, 22, 36, 22, 47, 38, 24, 1, 14, 6, 6, 3, 17, 12, 2, 1, 1, 0, 1, 3, 6, 12, 9, 96, 116, 105, 93, 132, 90, 101, 110, 107, 91, 68, 30, 39, 58, 51, 67, 79, 24, 62, 45, 19, 42, 49, 68, 39, 87, 98, 89, 86, 112, 101, 84, 85, 43, 82, 66, 88, 54, 24, 17, 36, 18, 13, 73, 62, 66, 91, 67, 74, 54, 85, 13, 51, 35, 0, 12, 14, 0, 16, 24, 48, 30, 21, 5, 9, 22, 30, 17, 16, 42, 73, 99, 104, 96, 80, 106, 74, 57, 92, 67, 56, 57, 82, 78, 8, 3, 14, 23, 33, 
+#> 93, 96, 87, 102, 68, 79, 65, 89, 79, 132, 87, 59, 3, 11, 2, 43, 64, 68, 109, 47, 72, 59, 90, 91, 107, 84, 91, 85, 64, 16, 29, 18, NA, NA, NA, 0, 3, 3, 0, 3, 1, 4, 3, 5, 2, 0, 4, 7, 4, 0, 0, 0, 0, 0, 0, 0, NA, NA, NA, NA, NA, 0, 0, 0, 0, 0, 8, 93, 67, 111, 90, 95, 84, 60, 108, 63, 84, 78, 15, 30, 5, 81, 64, 82, 87, 104, 1, 20, 67, 100, 90, 81, 69, 37, 47, 41, 39, 33, 46, 80, 92, 105, 81, 87, 54, 5, 53, 46, 4, 6, 17, 31, 6, 18, 4, 34, 21, 9, 21, 25, 24, 70, 54, 63, 73, 45, 16, 25, 49, 59, 22, 11, 22, 
+#> 1, 60, 81, 93, 90, 121, 124, 90, 113, 108, 71, 40, 77, 86, 57, 27, 39, 106, 48, 53, 143, 68, 37, 21, NA, 0, 2, 9, 7, 3, 5, NA, NA, NA, NA, NA, NA, 0, 1, 1, 0, 0, 0, 4, 41, 38, 84, 70, 19, 47, 55, 15, 7, 95, 63, 44, 18, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 64, 20, 31, 47, 15, 13, 63, 91, 98, 95, 85, 98, 78, 88, 39, 51, 27, 56, 2, 8, 17, 4, 0, 53, 70, 81, 48, 87, 88, 104, 82, 79, 50, 83, 106, 67, 52, 51, 4, NA, NA, NA, NA, 3, 2, 4, 1, 4, 4, 4, 1, 4, 0, 6, 0, 17, 56, 65, 64, 29, 82, 58, 35, 
+#> 18, 46, 30, 1, 21, 57, 6, 2, 3, 10, 75, 60, 72, 84, 46, 30, 54, 53, 75, 44, 75, 13, 55, 42, 43, 11, 23, 2, 1, 0, NA, NA, NA, NA, 0, NA, NA, NA, NA, 1, 1, 1, 4, 2, 4, 2, 1, 0, 0, 0, 2, 1, 1, 60, 22, 80, 69, 81, 65, 93, 82, 43, 47, 48, 62, 40, 5, 0, 10, 5, 71, 52, 65, 68, 75, 63, 74, 109, 92, 87, 45, 42, 12, 24, 5, 40, 34, 43, 13, 31, 58, 52, 24, 51, 18, 49, 42, 5, 35, 46, 84, 84, 69, 64, 104, 126, 101, 92, 100, 100, 66, 82, 82, 61, 31, 41, 66, 9, 21, 42, 86, 65, 98, 118, 91, 107, 63, 93, 67, 10, NA, 
+#> NA, 0, NA, NA, NA, NA, 0, NA, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, NA, NA, NA, NA, 0, 0, NA, 0, NA, NA, NA, 0, NA, 0, 81, 97, 44, 52, 62, 23, 61, 55, 5, 2, 1, 3, 1, 3, 3, 0, 0, 3, 4, 2, 0, 0, 5, 51, 85, 94, 99, 108, 131, 92, 93, 84, 117, 108, 112, 79, 84, 66, 36, 62, 6, 32, 0, 21, 50, 53, 108, 84, 95, 113, 58, 6, 8, 18, 1, 1, 36, 16, 82, 97, 94, 108, 83, 22, 62, 7, 56, 65, 93, 53, 2, 24, 1, 13, 40, 53, 37, 93, 74, 102, 114, 81, 97, 104, 13, 67, 45, 19, 8, 72, 39, 41, 92, 59, 89, 84, 90, 134, 114, 
+#> 106, 146, 122, 99, 69, 39, 53, 7, 8, 28, 58, 92, 122, 104, 89, 101, 106, 101, 101, 111, 97, 26, 108, 79, 93, 55, 0, 48, 11, 21, 8, 9, 5, 35, 120, 73, 82, 115, 34, 129, 95, 96, 89, 102, 88, 52, 39, 47, 6, 6, 38, NA, NA, NA, NA, NA, NA, 0, 0, 1, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 2, 1, 7, 1, 1, NA, 2, 1, 0, 0, 6, 62, 90, 66, 91, 49, 52, 83, 92, 43, 84, 75, 74, 64, 49, 45, 12, 43, 39, 67, 80, 93, 108, 107, 101, 116, 108, 102, 102, 77, 105, 53, 65, 17, 35, 84, 108, 106, 92, 91, 109, 100, 108, 112, 86, 
+#> 80, 79, 24, 54, 22, 52, NA, NA, NA, NA, NA, NA, 0, 0, 0, 4, 0, 0, 0, 0, 0, 8, 28, 27, 16, 64, 69, 91, 74, 86, 107, 104, 33, 37, 50, 4, 3, 1, 27, 37, 56, 52, 73, 34, 60, 45, 31, 89, 83, 47, 30, 6, 1, 2, 0, 0, 0, 0, NA, 0, 1, 0, 0, 0, 0, 1, 1, 0, 2, 1, 0, 0, 0, 0, 0, 0, 0, 0, 5, 104, 116, 127, 134, 119, 110, 124, 87, 111, 122, 118, 102, 88, 107, 111, 84, 99, 8, 47, 16, 64, 39, 23, 39, 39, 42, 21, 39, 16, 32, 28, 3, 23, 6, 21, 4, 15, 141, 100, 123, 110, 134, 133, 125, 124, 112, 124, 113, 143, 104, 78, 
+#> 74, 67, 74, 21, 83, 9, 82, 37, 68, 113, 78, 28, 78, 73, 98, 98, 57, 71, 9, 55, 22, 19, 1, NA, NA, NA, 0, 0, 0, 0, 0, 0, 0, 1, 4, 0, 0, 1, 0, 0, 0, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 3, 2, 1, 1, 1, 2, 3, 2, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 5, 5, 0, 0, 0, 0, 1, 0, 0, 2, 2, 1, 3, 0, 9, 32, 75, 76, 72, 115, 84, 124, 82, 89, 110, 95, 98, 96, 102, 98, 99, 92, 68, 47, 51, 35, 46, 49, 10, 31, 53, 14, 2, 1, 2, 3, 5, 1, 6, 7, 6, 2, 2, 7, 0, 6, 9, 1, 0, 0, 1, 
+#> 2, 3, 0, 0, NA, NA, NA, 1, 1, NA, 2, 0, 0, 0, 0, 0, 0, 0, 11, 122, 111, 103, 104, 13, 101, 120, 24, 28, 28, 82, 39, 24, 17, 10, 93, 120, 74, 88, 96, 52, 37, 98, 109, 28, 94, 55, 58, 24, 52, 66, 31, 26, 4, 11, 53, 48, 42, 92, 82, 96, 92, 95, 69, 89, 63, 66, 63, 43, 11, 7, 63, 46, 49, 61, 110, 56, 60, 48, 90, 49, 41, NA, 0, 0, 2, 5, 0, 3, 6, 2, 1, 1, 0, 6, 5, 0, NA, NA, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, NA, NA, NA, NA, NA, NA, NA, NA, 2, NA, NA, NA, 0, 0, 0, 0, 0, 0, 2, 1, 0, 0, 2, 
+#> 1, 9, 13, 26, 31, 69, 73, 59, 86, 64, 57, 57, 15, 31, 59, 63, 56, 40, 76, 102, 61, 118, 88, 111, 74, 3, 30, 11, 60, 89, 97, 122, 104, 91, 101, 85, 95, 107, 83, 21, 43, 41, 27, 27, NA, NA, NA, NA, NA, 4, 5, 4, 0, 0, 1, 0, 0, 0, 0, NA, NA, 0, 0, NA, NA, NA, 0, NA, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 12, 94, 80, 92, 72, 62, 28, 2, 28, 1, 3, 6, 3, 5, 4, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 14, 33, 41, 35, 4, 10, 97, 84, 83, 76, 77, 29, 8, 26, 37, 24, 24, 33, 0, 38, 74, 88, 50, 30, 98, 23, 47, 84, 92, 73, 
+#> 34, 0, 3, 18, 51, 81, 77, 97, 59, 67, 78, 20, 60, 112, 104, 83, 74, 28, 8, NA, NA, NA, 0, NA, NA, 0, NA, NA, 1, 4, 4, 1, 2, 2, 2, 4, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 4, 1, 0, 1, 52, 52, 57, 106, 134, 98, 121, 110, 84, 92, 87, 59, 14, 62, 48, 20, 85, 76, 50, 46, 9, 32, 6, 1, 21, 59, 39, 84, 55, 21, 46, 68, 58, 48, 22, 6, 1, 44, 103, 69, 69, 56, 71, 101, 75, 17, 30, 40, 14, 2, 87, 114, 100, 123, 116, 118, 113, 90, 103, 69, 66, 87, 108, 82, 80, 47, 56, 58, 1, 19, 20, 18, 30, 0, 0, 6, 26, 14, 3, 0, 0, 0, 
+#> 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 12, 112, 49, 106, 114, 102, 70, 51, 83, 127, 93, 116, 50, 21, 61, 17, 83, 79, 46, 57, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 17, 7, 68, 79, 94, 113, 115, 102, 103, 117, 74, 81, 89, 71, 96, 15, 26, 36, 84, 94, 123, 109, 64, 78, 56, 66, 36, 1, 4, 2, 44, 108, 102, 101, 107, 106, 71, 124, 95, 92, 89, 85, 59, 83, 60, 0, 0, 7, 9, 6, 3, 10, 7, 20, 9, 6, 7, 4, 3, 6, 0, 3, 3, 4, NA, NA, 0, NA, NA, NA, NA, NA, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 4, 4, 2, 1, 1, NA, NA, NA, 
+#> 0, 6, 4, 6, 0, 0, 0, 1, 1, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, NA, NA, NA, NA, NA, NA, NA, 0, 8, 6, 3, NA, 0, 6, 0, 32, 26, 24, 96, 107, 50, 41, 74, 28, 87, 74, 103, 68, 96, 78, 34, 99, 84, 84, 121, 89, 99, 35, 79, 86, 8, 33, 49, 13, NA, 0, 0, NA, NA, NA, NA, NA, 0, 1, 2, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 3, 13, 31, 29, 24, 16, 43, 40, 31, 43, 28, 42, 10, 4, 46, 80, 108, 92, 65, 18, 65, 27, 12, 28, 59, 27, 4, 5, 13, 78, 114, 138, 132, 107, 135, 115, 92, 94, 86, 39, 79, 48, 59, 31, 41, 27, 
+#> 84, 66, 92, 115, 108, 109, 120, 97, 33, 74, 92, 31, 68, 4, 39, 17, 20, 7, 21, 3, 16, 36, 65, 53, 65, 16, 45, 90, 94, 86, 114, 84, 102, 77, 96, 100, 61, 78, 42, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 87, 39, 95, 130, 103, 100, 113, 87, 34, 92, 66, 15, 29, 69, 4, 19, 85, 120, 100, 99, 53, 47, 78, 105, 60, 69, 2, 52, 0, 1, 29, 56, 50, 92, 59, 79, 83, 72, 67, 65, 91, 18, 55, 49, 34, 12, 70, 100, 102, 97, 116, 95, 32, 38, 82, 117, 72, 54, 
+#> 56, 33, 68, 90, 79, 92, 94, 54, 77, 96, 84, 100, 100, 87, 69, 50, 26, 34, 1, 34, 0, 77, 60, 67, 13, 34, 36, 37, 26, 37, 0, 6, 47, 89, 91, 87, 94, 87, 92, 74, 43, 10, 0, 10, 16, 36, 28, 6, 4, 1, 63, 53, 93, 96, 99, 84, 74, 76, 47, 88, 88, 69, 78, 24, 9, 18, 0, 0, 52, 44, 82, 89, 83, 79, 63, 86, 94, 85, 74, 76, 80, 81, 90, 71, 67, 127, 111, 111, 101, 111, 110, 111, 103, 88, 74, 80, 28, 49, 57, 42, 45, 5, 20, 46, 94, 37, 101, 17, 81, 95, 75, 35, 21, 18, 45, 44, 30, 16, 45, 62, 62, 75, 45, 57, 43, 38, 
+#> 35, 37, 38, 15, 9, 4, 4, 44, 48, 47, 64, 64, 95, 33, 41, 70, 95, 101, 93, 42, 41, 64, 35, 4, 0, 0, 20, 43, 4, 20, 23, 76, 63, 40, 59, 85, 56, 31, 31, 61, 16, 19, NA, NA, NA, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 112, 118, 137, 133, 129, 119, 99, 100, 124, 115, 105, 85, 49, 89, 85, 1, 51, 40, 82, 57, 34, 35, 70, 78, 84, 112, 106, 128, 90, 92, 69, 90, 93, 70, 30, 4, 27, 16, 54, 68, 67, 114, 76, 65, 22, 27, 61, 61, 40, 33, 10, 0, 0, 0, 0, 2, 3, 5, 0, 0, 0, NA, 0, 0, 0, 0, 0, 0, 0, 0, 0, 12, 82, 
+#> 48, 65, 71, 70, 49, 50, 27, 42, 65, 43, 36, 22, 3, 32, 42, 12, 39, 5, 1, 3, 8, 5, 17, 9, 0, 0, 0, 0, 0, 0, 0, 2, 1, 2, 1, 0, 3, 3, 0, 0, 8, 59, 31, 34, 37, 36, 45, 44, 38, 46, 52, 17, 10, NA, 0, NA, 0, 0, 1, 1, 1, 2, 0, 0, 0, 0, 10, 53, 93, 105, 107, 108, 98, 107, 89, 99, 72, 92, 83, 40, 31, 28, 15, 0, 0, 0, 0, 0, 0, 0, 99, 74, 66, 79, 8, 35, 25, 59, 13, 18, 38, 24, 9, 2, 2, 6, 3, 3, 0, 3, 1, 0, 0, 2, 5, 77, 128, 114, 77, 102, 119, 97, 76, 64, 67, 50, 68, 47, 37, 22, 0, 50, 79, 76, 62, 88, 92, 83, 
+#> 93, 80, 57, 68, 63, 67, 66, 52, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 5, 2, 4, 6, 6, 4, 0, 0, 0, 1, 0, 3, 2, 5, 2, 1, 0, 1, 0, 0, 0, 0, 0, 4, NA, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 6, 3, 4, 0, 1, 1, 3, 0, 0, 0, 0, 0, 0, 0, 0, 9, 62, 21, 70, 83, 95, 91, 90, 120, 30, 91, 93, 91, 17, 63, 39, 16, 26, 27, 21, 76, 101, 76, 86, 99, 91, 72, 84, 54, 37, 46, 77, 28, 28, 31, 55, 63, 91, 92, 64, 90, 76, 23, 0, 23, 34, 37, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 8, 8, 92, 72, 68, 45, 0, 26, 6, 4, 2, 5, 14, 8, 11, 0, 
+#> 0, 1, 0, 2, 31, 51, 93, 61, 97, 38, 51, 0, 85, 75, 69, 12, 8, 0, 14, 87, 118, 82, 78, 91, 85, 63, 84, 79, 60, 36, 45, 19, 24, 67, 101, 82, 103, 77, 51, 38, 52, 78, 28, 1, 32, 73, 65, 88, 76, 87, 56, 79, 79, 58, 54, 23, 36, 27, 101, 61, 104, 87, 52, 2, 5, 2, 6, 9, 6, 2, 2, 1, 1, 5, 5, 11, 2, 0, 3, 0, 0, 10, 47, 1, 59, 46, 52, 79, 94, 119, 115, 116, 74, 77, 86, 84, 65, 84, 59, 73, 0, 0, 0, 0, 0, 1, 0, 2, 5, 1, 2, 0, 19, 43, 47, 90, 48, 4, 10, 15, 16, 50, 34, 42, 4, 9, 4, 6, 1, 70, 66, 42, 40, 66, 35, 
+#> 0, 9, 13, 2, 61, 110, 101, 78, 39, 72, 103, 48, 59, 21, 30, 66, 101, 112, 99, 38, 48, 63, 39, 103, 113, 90, 66, 5, 56, 57, 6, 25, 35, 49, 86, 68, 111, 86, 96, 67, 77, 44, 39, 5, 2, 15, 77, 73, 82, 78, 30, 32, 56, 64, 76, 68, 87, 39, 13, 20, 56, 55, 93, 49, 40, 10, 23, 74, 108, 54, 75, 52, 27, 19, 18, 84, 71, 59, 70, 50, 104, 69, 88, 87, 74, 54, 84, 82, 95, 88, 79, 83, 26, 0, 2, 56, 31, 43, 40, 0, 1, 22, 68, 118, 103, 118, 102, 99, 118, 104, 37, 61, 123, 100, 96, 88, 54, 1, 28, 12, 44, 77, 58, 82, 
+#> 60, 70, 67, 24, 26, 11, 17, 3, 22, 4, 0, 7, 14, 71, 84, 92, 81, 49, 84, 98, 97, 71, 59, 75, 89, 69, 66, 41, 15, 9, 72, 73, 80, 61, 60, 118, 48, 84, 84, 79, 84, 69, 23, 0, 1, 0, 2, 1, 2, 1, 2, 3, 3, 2, 4, 2, 4, 1, 1, 1, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 2, NA, 0, 0, 0, 0, 1, 1, 7, 2, 0, 0, 3, 2, 2, 0, 20, 54, 73, 62, 87, 69, 54, 74, 80, 54, 10, 11, 0, 31, 70, 55, 19, 58, 63, 67, 70, 46, 57, 37, 41, 18, 32, 3, 5, 4, 1, 1, 3, 2, 3, 4, 1, 
+#> 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 52, 104, 94, 105, 105, 87, 81, 28, 34, 65, 53, 0, 14, 69, 51, 86, 67, 36, 11, 6, 3, 53, 28, 42, 41, 33, 55, 48, 54, 23, 6, 9, 3, 39, 101, 106, 112, 91, 85, 96, 111, 111, 109, 103, 101, 64, 66, 107, 75, 82, 100, 103, 85, 60, 42, 93, 61, 65, 67, 66, 24, 29, 0, 3, 6, 0, 6, 10, 8, 9, 8, 7, 1, 0, 3, 0, 3, 0, 2, 21, 35, 28, 35, 97, 55, 43, 70, 30, 34, 44, 44, 2, 50, 4, 8, 42, 18, 65, 107, 92, 85, 103, 107, 110, 28, 18, 2, 33, 40, 32, 
+#> 61, 70, 104, 101, 136, 108, 118, 103, 123, 117, 115, 93, 95, 107, 81, 79, 25, 0, 57, 77, 106, 114, 114, 93, 80, 102, 76, 99, 88, 79, 3, 49, 2, 11, 6, 71, 74, 64, 27, 41, 45, 80, 46, 3, 13, 10, 24, 50, 87, 28, 47, 87, 74, 58, 26, 58, 105, 90, 82, 76, 46, 28, 33, 82, 107, 59, 92, 90, 68, 58, 5, 27, 64, 49, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 3, 0, 4, 1, 2, 0, 27, 99, 76, 11, 51, 72, 101, 83, 56, 73, 32, 64, 85, 70, 36, 10, 14, 39, 62, 97, 84, 97, 85, 53, 19, 63, 56, 6, 62, 19, NA, NA, 0, 
+#> 1, NA, 0, 0, 0, 0, 0, 3, 3, 5, 4, 4, 2, 4, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 119, 125, 125, 101, 92, 55, 30, 49, 62, 64, 59, 78, 62, 93, 70, 103, 103, 104, 105, 81, 77, 82, 2, 1, 28, 68, 67, 54, 76, 13, 41, 42, 18, 61, 86, 62, 98, 94, 88, 38, 81, 62, 60, 69, 13, 36, 93, 131, 104, 113, 112, 75, 54, 48, 73, 74, 14, 23, 20, 61, 51, 68, 63, 63, 51, 44, 43, 57, 68, 65, 68, 119, 120, 107, 52, 42, 95, 83, 95, 103, 83, 24, 0, 0, 9, 8, 8, 9, 9, 9, 
+#> 7, 5, 8, 3, 47, 33, 99, 122, 119, 113, 18, 83, 101, 86, 58, 94, 21, 36, 41, 99, 96, 113, 115, 88, 87, 60, 91, 63, 54, 24, 10, 76, 110, 106, 110, 104, 76, 95, 95, 114, 73, 39, 9, 90, 12, 27, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 31, 12, 51, 89, 37, 3, 99, 76, 91, 64, 72, 72, 38, 0, 4, 3, 38, 81, 63, 68, 68, 25, 78, 72, 61, 19, 57, 15, 0, 0, 1, 0, 1, 0, 0, 1, 3, 1, 0, 0, 0, 0, 0, 0, 4, 4, 5, 5, 6, 8, 4, 0, 2, 0, 0, 1, 1, 0, 0, 1, 5, 38, 11, 100, 85, 91, 99, 77, 68, 25, 47, 12, 15, 111, 134, 118, 101, 
+#> 73, 15, 34, 14, 21, 4, 20, 65, 87, 87, 63, 45, 57, 50, 51, 45, 76, 41, 83, 84, 70, 32, 40, 43, 9, 77, 58, 19, 1, 2, 34, 21, 41, 22, 94, 77, 59, 105, 57, 61, 42, 34, 5, 97, 82, 85, 119, 115, 127, 139, 76, 100, 48, 87, 102, 65, 78, 71, 2, 82, 109, 86, 103, 94, 95, 83, 82, 19, 78, 1, 23, 30, 32, 101, 105, 97, 81, 62, 56, 63, 23, 26, 13, 25, 10, 11, NA, NA, NA, NA, NA, NA, 0, NA, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 86, 118, 
+#> 115, 53, 102, 81, 91, 72, 46, 91, 92, 113, 101, 109, 108, 30, 68, 87, 9, 7, 0, 7, 2, 2, 0, NA, 0, 0, NA, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 1, 0, 2, 0, 4, 7, 3, 6, 4, 2, 5, 4, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 6, 3, 5, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 7, 8, 2, 0, 2, 3, 2, 0, 7, 17, 83, 101, 103, 90, 87, 108, 63, 12, 69, 83, 76, 5, 36, 1, 1, 65, 107, 80, 78, 100, 94, 86, 80, 44, 69, 12, 36, 29, 30, 37, 45, 34, 55, 65, 68, 40, 34, 20, 50, 62, 113, 59, 27, 30, 35, 35, 4, 
+#> 76, 10, 8, 5, 70, 78, 102, 102, 84, 95, 26, 46, 82, 14, 10, 9, 23, 2, 19, 83, 51, 31, 44, 99, 72, 93, 72, 97, 46, 61, 80, 92, 43, 47, 25, 18, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 67, 100, 96, 78, 39, 91, 83, 74, 0, 1, 12, 66, 27, 47, 46, 26, 19, 20, 3, 5, 20, 12, 42, 67, 91, 92, 70, 31, 26, 68, 96, 51, 8, 100, 45, 7, 52, 98, 43, 95, 80, 103, 73, 43, 22, 23, 29, 96, 47, 73, 53, 44, 42, 9, 10, 14, 3, 3, 8, 42, 104, 63, 19, 44, 14, 42, 53, 7, 28, 23, 80, 104, 101, 89, 93, 69, 96, 110, 65, 23, 62, 56, 19, 
+#> 49, 70, 87, 19, 103, 70, 23, 38, 93, 45, 52, 32, 0, 0, 0, 1, 0, 0, 0, 0, 0, 6, 0, 3, 5, 5, 8, 6, 16, 61, 83, 76, 68, 103, 100, 88, 74, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 2, 0, 0, 0, 6, 84, 99, 51, 110, 85, 52, 93, 84, 26, 43, 2, 29, 57, 97, 84, 30, 64, 96, 75, 57, 10, 29, 30, 47, 93, 97, 82, 115, 74, 35, 77, 80, 0, 2, 4, 5, 7, 4, 5, 4, 4, 0, 60, 70, 78, 66, 69, 31, 11, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 84, 60, 33, 10, 10, 50, 64, 8, 34, 48, 93, 57, 56, 28, 67, 38, 72, 50, 50, 
+#> 90, 92, 71, 67, 79, 54, 29, 54, NA, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 82, 109, 108, 32, 100, 43, 62, 55, 58, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 4, 0, 0, 1, 1, 0, 0, 2, 4, 6, 2, 2, 4, 4, 4, 2, 0, 3, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 2, 21, 41, 54, 85, 61, 26, 18, 18, 27, 31, 53, 111, 92, 89, 72, 35, 87, 2, 0, 0, 0, 0, 0, 5, 5, 4, 4, 5, 1, 4, 0, 5, 15, 104, 48, 101, 89, 81, 33, 72, 71, 46, 31, 3, 1, 1, 1, 3, 58, 75, 38, 7, 54, 109, 105, 64, 82, 101, 108, 11, 69, 82, 106, 101, 59, 101, 32, 95, 1, 1, 
+#> 0, 30, 4, 35, 59, 73, 60, 11, 54, 70, 33, 15, 3, 0, 3, NA, NA, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 58, 17, 78, 61, 72, 74, 65, 71, 83, 81, 59, 68, 82, 54, 105, 113, 97, 84, 100, 88, 86, 60, 13, 1, 12, 5, 0, 6, 7, 10, 3, 4, 1, 0, 1, 15, 35, 19, 75, 60, 64, 86, 49, 87, 90, 3, 28, 41, 70, 53, 53, 53, 20, 98, 94, 10, 119, 43, 92, 71, 66, 1, 2, 4, 10, 2, 8, 5, 2, 35, 37, 72, 67, 59, 13, 24, 60, 72, 28, 34, 101, 93, 90, 87, 40, 
+#> 72, 97, 106, 94, 79, 72, 59, 89, 81, 73, 5, 18, 53, 70, 69, 71, 67, 68, 77, 74, 59, 31, 55, 58, 79, 51, 13, 30, 53, 38, 44, 78, 77, 74, 72, 62, 57, 63, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 9, 28, 63, 42, 39, 44, 21, 2, 18, 90, 122, 112, 91, 76, 136, 102, 31, 73, 98, 30, 48, 81, 39, 87, 70, 66, 54, 20, 66, 17, 52, 84, 73, 105, 107, 94, 77, 85, 0, 1, 0, 5, 1, 0, 0, 16, 65, 80, 50, 77, 28, 26, 54, 22, 8, 27, 20, 1, 75, 66, 42, 66, 50, 102, 84, 39, 81, 70, 24, 79, 61, 55, 59, 
+#> 52, 68, 43, 0, 0, 0, 0, 0, 1, 0, 7, 0, 3, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 5, 41, 85, 54, 53, 67, 46, 13, 89, 78, 53, 44, 76, 85, 66, 56, 45, 45, 53, 89, 71, 66, 30, 2, 46, 75, 15, 76, 70, 73, 41, 12, 66, 73, 49, 18, 6, 0, 4, 1, 34, 62, 77, 43, 95, 59, 28, 27, 74, 74, 94, 87, 107, 97, 89, 91, 83, 50, 93, 67, 74, 79, 2, 10, 50, 48, 52, 49, 76, 100, 92, 59, 47, 40, 57, 1, 20, 129, 109, 115, 104, 98, 71, 41, 118, 1, 3, 12, 51, 54, 63, 45, 61, 65, 54, 
+#> 66, 57, 43, 38, 68, 48, 19, 6, 38, 2, 3, 62, 75, 54, 70, 54, 69, 85, 42, 14, 34, 0, 0, 63, 47, 80, 84, 89, 89, 71, 72, 0, 1, 4, 2, 3, 1, 9, 59, 65, 72, 77, 73, 69, 0, 0, 0, 0, 0, 0, 0, 0, 1, 4, 0, 0, 0, 0, 0, 4, 66, 65, 86, 54, 98, 24, 88, 38, 102, 20, 38, 48, 57, 52, 28, 82, 103, 75, 103, 49, 58, 97, 14, 79, 51, 38, 37, 72, 80, 95, 19, 42, 17, 76, 44, 60, 0, 1, 5, 50, 37, 40, 5, 1, 2, 51, 48, 7, 16, 9, 75, 103, 65, 100, 0, 44, 126, 99, 101, 42, 18, 64, 70, 46, 60, 1, 12, 14, 49, 55, 102, 87, 30, 
+#> 93, 93, 70, 53, 74, 32, 44, 17, 4, 27, 54, 55, 101, 9, 44, 71, 89, 94, 0, 0, 2, 2, 3, 2, 0, 1, 0, 0, 0, 1, 58, 70, 46, 9, 27, 56, 7, 7, 0, 0, 1, 0, 0, 22, 62, 79, 71, 85, 1, 0, 1, 0, 3, 26, 39, 59, 85, 35, 46, 47, 34, 94, 63, 45, 79, 75, 62, 89, 47, 0, 2, 5, 4, 3, 10, 9, 80, 88, 3, 3, 26, 80, 64, 85, 86, 9, 45, 61, 38, 10, 38, 63, 63, 66, 94, 68, 5, 57, 76, 62, 62, 74, 69, 40, 111, 43, 2, 20, 57, 69, 68, 57, 74, 76, 0, 2, 1, 0, 0, 0, 0, 0, 3, 5, 0, 35, 62, 70, 74, 27, 62, 62, 39, 2, 29, 90, 78, 34, 
+#> 38, 9, 92, 88, 8, 64, 41, 111, 18, 83, 73, 84, 22, 44, 52, 54, 65, 1, 34, 89, 93, 122, 24, 60, 49, 62, 92, 79, 56, 52, 87, 21, 12, 7, 86, 29, 61, 64, 12, 16, 81, 29, 34, 24, 57, 93, 7, 60, 84) x c(54, 77, 50, 59, 50, 62, 62, 2, 4, 48, 3, 12, 60, 80, 101, 101, 73, 92, 146, 115, 103, 117, 132, 148, 111, 152, 147, 144, 148, 72, 22, 58, 94, 90, 94, 81, 117, 118, 48, 93, 77, 3, 59, 78, 108, 83, 58, 60, 40, 17, 23, 39, 17, 15, 82, 72, 190, 225, 177, 179, 174, 167, 105, 10, 35, 43, 57, 50, 27, 35, 42, 23, 23, 10, 2, 5, 10, 18, 4, 22, 61, 49, 52, 40, 54, 43, 42, 13, 14, 27, 11, 18, 79, 54, 54, 57, 52, 44, 40, 29, 1, 84, 172, 191, 180, 184, 203, 237, 187, 158, 187, 169, 164, 55, 86, 13, 12, 0, 8, 
+#> 29, 31, 44, 40, 30, 52, 34, 39, 32, 22, 32, 34, 44, 33, 18, 16, 27, 26, 21, 8, 2, 1, 57, 197, 197, 118, 152, 232, 132, 1, 167, 208, 82, 214, 152, 168, 152, 227, 115, 165, 156, 108, 137, 105, 0, 8, 14, 25, 0, 32, 14, 17, 20, 14, 12, 10, 5, 1, 2, 28, 26, 28, 30, 30, 24, 20, 20, 25, 25, 22, 29, 19, 23, 8, 3, 0, 116, 193, 143, 104, 134, 152, 166, 143, 110, 31, 101, 55, 165, 184, 167, 78, 116, 6, 145, 166, 72, 49, 180, 152, 144, 13, 97, 0, 31, 80, 66, 78, 62, 68, 61, 63, 62, 3, 41, 45, 36, 13, 0, 20, 
+#> 65, 90, 64, 21, 85, 65, 83, 59, 82, 43, 26, 55, 19, 0, 0, 39, 101, 170, 185, 184, 143, 171, 166, 188, 184, 185, 170, 217, 189, 193, 183, 183, 92, 18, 0, 189, 208, 191, 165, 89, 144, 9, 9, 14, 25, 27, 18, 30, 34, 33, 5, 1, 4, 0, 1, 12, 22, 10, 13, 21, 13, 15, 8, 4, 17, 3, 0, 23, 28, 30, 38, 25, 11, 29, 13, 9, 10, 12, 1, 1, 0, 1, 36, 113, 212, 188, 216, 194, 248, 226, 167, 127, 208, 201, 225, 161, 191, 143, 197, 211, 189, 211, 157, 79, 175, 114, 2, 21, 35, 173, 160, 170, 130, 178, 141, 136, 149, 159, 
+#> 123, 138, 123, 96, 131, 95, 78, 31, 16, 3, 5, 1, 15, 133, 129, 149, 136, 135, 130, 128, 71, 126, 48, 6, 0, 79, 64, 51, 142, 114, 100, 114, 83, 127, 57, 65, 63, 36, 37, 69, 45, 15, 70, 123, 146, 110, 83, 107, 95, 117, 80, 54, 14, 80, 57, 86, 90, 162, 41, 174, 84, 37, 216, 38, 198, 70, 4, 77, 5, 83, 191, 168, 202, 184, 206, 110, 171, 145, 150, 85, 157, 129, 145, 146, 158, 113, 127, 1, 0, 1, 15, 19, 13, 20, 13, 25, 22, 18, 23, 9, 11, 4, 15, 24, 4, 15, 21, 12, 23, 21, 25, 21, 9, 9, 1, 80, 176, 192, 201, 
+#> 194, 176, 182, 171, 199, 175, 180, 201, 168, 178, 158, 181, 124, 139, 155, 124, 61, 34, 47, 117, 180, 160, 209, 122, 127, 154, 140, 144, 158, 154, 151, 149, 88, 97, 20, 136, 141, 94, 136, 127, 125, 122, 114, 35, 163, 127, 137, 73, 52, 16, 41, 0, 0, 17, 29, 12, 20, 23, 24, 27, 20, 20, 14, 17, 14, 11, 14, 13, 11, 23, 12, 6, 6, 6, 3, 3, 9, 18, 3, 0, 24, 135, 158, 98, 91, 142, 168, 173, 146, 138, 112, 137, 68, 45, 32, 22, 77, 3, 8, 90, 198, 188, 180, 189, 184, 181, 173, 168, 163, 91, 165, 224, 177, 194, 
+#> 182, 194, 147, 129, 76, 10, 0, 1, 23, 35, 83, 85, 67, 70, 62, 45, 19, 17, 4, 2, 0, 23, 81, 86, 52, 48, 16, 0, 3, 26, 168, 183, 167, 222, 189, 193, 176, 211, 184, 150, 146, 214, 183, 161, 218, 167, 167, 164, 171, 51, 18, 35, 25, 31, 29, 17, 26, 16, 21, 11, 18, 24, 8, 9, 24, 15, 4, 4, 13, 13, 24, 30, 38, 35, 30, 34, 32, 33, 40, 24, 17, 30, 22, 18, 32, 42, 20, 16, 39, 35, 45, 35, 32, 34, 32, 27, 33, 28, 25, 7, 4, 24, 1, 0, 9, 18, 23, 36, 15, 6, 14, 0, 125, 49, 37, 71, 150, 20, 145, 130, 130, 118, 150, 
+#> 150, 128, 124, 163, 117, 124, 133, 113, 18, 32, 9, 24, 46, 84, 111, 135, 125, 65, 72, 33, 78, 88, 17, 14, 1, 0, 2, 2, 16, 26, 12, 33, 16, 12, 6, 3, 17, 13, 16, 16, 15, 2, 7, 2, 41, 55, 44, 67, 69, 144, 140, 124, 151, 112, 123, 88, 88, 21, 1, 5, 0, 1, 117, 34, 114, 143, 151, 149, 128, 136, 166, 151, 153, 143, 92, 64, 29, 131, 152, 75, 14, 1, 0, 3, 6, 12, 11, 12, 23, 1, 9, 14, 0, 0, 7, 68, 50, 126, 100, 150, 155, 129, 34, 15, 19, 148, 81, 5, 8, 23, 40, 31, 57, 50, 81, 30, 15, 0, 0, 12, 47, 43, 53, 
+#> 94, 93, 55, 26, 4, 16, 8, 56, 14, 29, 45, 28, 1, 3, 21, 11, 10, 19, 0, 22, 18, 20, 25, 23, 11, 20, 25, 13, 9, 12, 9, 16, 12, 8, 0, 3, 5, 60, 81, 98, 109, 98, 64, 75, 45, 0, 6, 7, 9, 101, 180, 159, 165, 144, 141, 172, 128, 142, 144, 171, 160, 101, 63, 44, 119, 35, 3, 21, 12, 2, 2, 2, 1, 9, 165, 159, 198, 200, 190, 182, 97, 156, 154, 166, 97, 65, 0, 66, 57, 133, 103, 54, 77, 67, 69, 61, 47, 29, 55, 1, 14, 17, 13, 4, 6, 7, 2, 12, 3, 3, 3, 29, 233, 226, 197, 153, 43, 99, 202, 162, 23, 181, 218, 77, 41, 
+#> 86, 95, 86, 66, 108, 105, 80, 81, 43, 33, 21, 10, 27, 2, 61, 104, 130, 133, 118, 109, 67, 59, 28, 17, 24, 19, 13, 32, 22, 33, 30, 1, 12, 27, 29, 15, 24, 15, 19, 7, 6, 23, 25, 2, 0, 146, 176, 172, 178, 156, 164, 151, 122, 122, 148, 168, 158, 205, 146, 114, 59, 116, 172, 164, 163, 184, 135, 140, 189, 15, 118, 121, 67, 110, 134, 1, 9, 83, 132, 167, 90, 97, 154, 84, 172, 139, 97, 17, 10, 0, 8, 3, 17, 21, 23, 15, 1, 6, 9, 15, 13, 6, 10, 19, 14, 12, 3, 3, 11, 22, 150, 186, 176, 181, 143, 151, 172, 115, 
+#> 134, 166, 179, 164, 191, 169, 57, 38, 0, 3, 11, 117, 140, 163, 133, 143, 111, 152, 133, 132, 157, 185, 187, 134, 20, 10, 20, 33, 42, 49, 34, 24, 17, 67, 62, 99, 43, 27, 18, 111, 2, 56, 3, 12, 9, 82, 130, 110, 134, 67, 138, 83, 64, 4, 1, 2, 33, 50, 95, 164, 207, 140, 167, 138, 116, 41, 174, 126, 113, 14, 96, 81, 152, 153, 170, 119, 119, 80, 155, 137, 132, 53, 136, 16, 120, 155, 148, 163, 175, 154, 150, 96, 85, 12, 21, 28, 24, 18, 14, 7, 55, 88, 89, 90, 90, 55, 101, 118, 134, 130, 75, 104, 40, 94, 
+#> 84, 70, 59, 16, 14, 4, 4, 18, 12, 2, 6, 9, 15, 7, 10, 21, 1, 3, 5, 30, 88, 126, 117, 126, 125, 113, 65, 43, 67, 83, 26, 13, 156, 134, 129, 33, 71, 9, 0, 124, 179, 149, 149, 127, 141, 99, 73, 13, 31, 172, 153, 138, 161, 170, 136, 177, 113, 137, 159, 191, 182, 201, 131, 212, 221, 119, 80, 18, 98, 106, 110, 95, 96, 73, 111, 131, 105, 124, 87, 30, 94, 60, 6, 1, 0, 15, 10, 14, 17, 9, 8, 11, 12, 14, 4, 10, 18, 141, 144, 124, 142, 146, 12, 128, 131, 180, 198, 161, 158, 62, 55, 7, 88, 159, 157, 146, 134, 
+#> 104, 10, 12, 82, 78, 71, 75, 85, 106, 82, 67, 96, 79, 74, 45, 55, 30, 2, 0, 1, 15, 173, 170, 169, 174, 180, 135, 162, 181, 181, 180, 168, 86, 102, 12, 33, 1, 0, 48, 131, 149, 36, 80, 66, 9, 15, 11, 0, 7, 14, 12, 6, 5, 13, 112, 0, 131, 170, 149, 182, 158, 139, 164, 118, 113, 135, 157, 15, 8, 10, 2, 4, 75, 141, 105, 74, 28, 21, 28, 66, 99, 109, 103, 107, 78, 32, 50, 143, 101, 116, 132, 91, 132, 51, 193, 209, 135, 89, 153, 141, 91, 127, 99, 1, 67, 130, 150, 129, 131, 126, 5, 37, 15, 35, 19, 133, 113, 
+#> 113, 97, 121, 192, 180, 180, 157, 183, 104, 116, 135, 61, 19, 8, 0, 5, 15, 21, 7, 0, 11, 10, 2, 4, 1, 1, 78, 177, 190, 154, 180, 257, 216, 246, 194, 224, 178, 201, 167, 12, 205, 133, 2, 29, 37, 40, 95, 139, 172, 204, 128, 205, 200, 104, 184, 192, 173, 172, 186, 199, 156, 138, 105, 13, 48, 24, 95, 91, 66, 127, 83, 140, 153, 75, 73, 98, 108, 77, 53, 59, 14, 155, 171, 117, 163, 218, 235, 250, 163, 227, 203, 167, 205, 188, 229, 32, 118, 13, 3, 27, 7, 5, 2, 18, 3, 28, 1, 26, 3, 89, 78, 88, 33, 61, 52, 
+#> 49, 70, 6, 40, 62, 37, 7, 5, 1, 68, 160, 180, 138, 20, 0, 150, 8, 74, 13, 117, 145, 133, 151, 132, 127, 126, 169, 208, 106, 164, 177, 52, 138, 188, 3, 17, 12, 12, 10, 2, 13, 13, 14, 14, 12, 20, 14, 20, 22, 34, 131, 103, 154, 80, 170, 119, 130, 132, 4, 24, 3, 60, 88, 70, 76, 62, 112, 77, 90, 42, 43, 1, 54, 164, 78, 13, 178, 145, 162, 196, 147, 58, 185, 168, 183, 182, 173, 41, 146, 102, 3, 110, 177, 172, 144, 143, 158, 174, 128, 75, 140, 161, 207, 188, 178, 186, 26, 72, 143, 73, 7, 2, 2, 19, 7, 17, 
+#> 21, 23, 29, 25, 31, 29, 28, 36, 17, 7, 0, 4, 49, 69, 68, 91, 89, 68, 87, 115, 157, 108, 122, 82, 73, 26, 44, 7, 72, 156, 163, 143, 169, 137, 133, 156, 143, 137, 131, 167, 137, 183, 166, 156, 117, 0, 10, 7, 2, 6, 4, 14, 14, 14, 16, 23, 17, 22, 10, 161, 116, 96, 161, 201, 89, 70, 100, 158, 150, 139, 151, 126, 132, 124, 123, 119, 133, 32, 3, 16, 18, 17, 34, 27, 22, 30, 37, 24, 18, 18, 42, 26, 3, 15, 14, 11, 3, 1, 0, 1, 0, 9, 50, 0, 91, 127, 119, 141, 141, 103, 138, 144, 166, 132, 150, 142, 124, 35, 
+#> 64, 3, 96, 59, 143, 149, 132, 151, 204, 180, 177, 174, 136, 202, 0, 5, 7, 65, 150, 108, 126, 104, 157, 177, 158, 196, 99, 26, 1, 0, 1, 3, 9, 24, 4, 32, 22, 19, 14, 10, 3, 20, 16, 14, 5, 3, 59, 177, 8, 179, 211, 185, 187, 188, 216, 227, 216, 179, 202, 199, 207, 128, 93, 25, 98, 0, 15, 25, 21, 23, 33, 15, 11, 1, 1, 13, 13, 21, 20, 25, 18, 10, 7, 11, 9, 17, 2, 1, 4, 8, 11, 8, 18, 27, 22, 16, 16, 11, 13, 13, 0, 129, 72, 85, 127, 98, 141, 153, 151, 150, 131, 137, 13, 28, 36, 4, 35, 45, 77, 67, 86, 111, 
+#> 50, 83, 43, 22, 9, 143, 152, 204, 165, 185, 200, 187, 132, 114, 8, 11, 6, 4, 1, 10, 11, 16, 25, 15, 8, 8, 9, 10, 8, 10, 2, 4, 4, 0, 9, 18, 27, 30, 8, 14, 26, 49, 23, 4, 24, 4, 22, 13, 8, 12, 43, 123, 211, 168, 223, 198, 166, 171, 208, 164, 176, 187, 161, 142, 177, 168, 104, 83, 7, 6, 12, 0, 2, 31, 157, 181, 194, 172, 185, 181, 151, 60, 119, 169, 55, 54, 49, 41, 112, 79, 132, 154, 204, 215, 149, 74, 30, 15, 4, 5, 12, 16, 13, 8, 26, 18, 25, 12, 13, 11, 1, 0, 3, 1, 11, 13, 26, 80, 105, 158, 136, 98, 
+#> 72, 182, 184, 118, 125, 104, 86, 38, 4, 2, 11, 14, 7, 14, 16, 27, 2, 25, 39, 31, 31, 42, 26, 13, 7, 2, 3, 1, 11, 18, 17, 24, 15, 15, 6, 8, 12, 8, 10, 14, 6, 9, 9, 1, 9, 15, 18, 7, 25, 13, 21, 17, 18, 22, 19, 20, 18, 15, 11, 6, 9, 9, 12, 5, 0, 24, 20, 34, 26, 32, 15, 36, 2, 23, 21, 5, 118, 143, 143, 106, 144, 171, 174, 190, 173, 174, 41, 167, 115, 77, 4, 3, 41, 77, 128, 155, 135, 135, 95, 43, 43, 35, 5, 16, 6, 12, 0, 41, 127, 156, 79, 172, 168, 237, 162, 211, 197, 225, 184, 201, 183, 156, 153, 8, 
+#> 13, 11, 23, 29, 52, 33, 29, 30, 21, 28, 37, 36, 22, 10, 0, 0, 8, 3, 8, 0, 2, 17, 23, 25, 21, 16, 25, 28, 13, 5, 7, 14, 11, 2, 1, 23, 182, 167, 195, 188, 204, 187, 180, 190, 182, 102, 146, 137, 143, 2, 31, 14, 121, 154, 173, 194, 156, 159, 145, 169, 161, 138, 124, 176, 175, 95, 79, 0, 33, 1, 0, 3, 32, 27, 67, 65, 127, 144, 44, 4, 88, 144, 47, 26, 11, 76, 75, 39, 16, 39, 15, 30, 0, 0, 0, 9, 4, 17, 30, 18, 21, 13, 26, 27, 18, 8, 15, 18, 4, 1, 5, 2, 1, 0, 5, 20, 21, 13, 13, 3, 2, 7, 0, 2, 0, 0, 20, 7, 
+#> 16, 14, 10, 15, 17, 10, 12, 9, 5, 5, 1, 2, 1, 17, 74, 112, 131, 150, 164, 187, 174, 127, 167, 118, 132, 161, 166, 171, 144, 21, 75, 32, 24, 5, 0, 14, 119, 120, 114, 131, 96, 53, 57, 19, 36, 92, 6, 84, 6, 118, 166, 183, 222, 213, 165, 166, 151, 133, 106, 110, 13, 1, 25, 0, 31, 24, 19, 29, 10, 13, 17, 7, 2, 1, 12, 1, 5, 1, 4, 13, 20, 18, 9, 16, 16, 20, 18, 15, 15, 9, 11, 10, 8, 5, 3, 0, 90, 180, 117, 126, 149, 145, 162, 146, 172, 50, 30, 140, 154, 107, 11, 5, 161, 208, 160, 189, 182, 196, 192, 192, 
+#> 182, 183, 169, 190, 137, 57, 2, 14, 62, 106, 115, 78, 132, 117, 6, 172, 107, 110, 135, 131, 142, 130, 126, 82, 85, 17, 45, 12, 93, 113, 150, 132, 138, 154, 65, 138, 155, 131, 131, 70, 84, 92, 36, 48, 9, 0, 2, 2, 56, 70, 99, 92, 142, 142, 122, 110, 132, 90, 46, 50, 25, 6, 32, 12, 12, 139, 101, 146, 137, 170, 174, 160, 152, 138, 140, 131, 34, 30, 183, 253, 199, 159, 163, 212, 211, 200, 216, 200, 192, 140, 186, 117, 142, 93, 3, 25, 3, 27, 3, 13, 116, 180, 199, 201, 201, 194, 173, 159, 129, 51, 194, 
+#> 171, 163, 187, 172, 180, 43, 9, 1, 17, 18, 22, 28, 23, 20, 38, 5, 19, 26, 20, 18, 11, 12, 14, 18, 18, 20, 16, 0, 0, 0, 10, 165, 220, 197, 88, 142, 183, 228, 202, 130, 83, 189, 42, 56, 185, 110, 69, 177, 189, 141, 160, 126, 5, 171, 76, 122, 49, 3, 49, 194, 167, 227, 180, 174, 187, 176, 148, 133, 92, 137, 158, 103, 162, 26, 9, 77, 77, 65, 55, 7, 16, 41, 103, 101, 51, 21, 13, 50, 0, 8, 16, 24, 14, 32, 33, 16, 7, 20, 1, 9, 0, 0, 0, 139, 99, 137, 92, 178, 139, 15, 14, 88, 171, 181, 143, 164, 216, 175, 
+#> 52, 2, 0, 13, 159, 134, 142, 141, 146, 170, 140, 89, 15, 121, 150, 126, 104, 6, 103, 122, 84, 188, 177, 241, 204, 65, 129, 189, 214, 221, 194, 131, 91, 155, 12, 4, 0, 9, 98, 139, 159, 125, 181, 197, 2, 136, 8, 8, 8, 10, 15, 22, 22, 23, 18, 9, 6, 7, 11, 13, 8, 9, 8, 5, 13, 14, 21, 14, 14, 11, 16, 17, 2, 0, 2, 113, 43, 170, 175, 163, 198, 208, 103, 143, 96, 45, 2, 6, 1, 7, 23, 10, 15, 0, 21, 17, 23, 11, 6, 5, 9, 5, 0, 7, 17, 9, 9, 7, 3, 1, 11, 6, 129, 179, 218, 210, 166, 220, 211, 208, 198, 210, 176, 
+#> 205, 200, 170, 4, 162, 176, 134, 193, 173, 129, 153, 154, 117, 130, 154, 109, 32, 11, 13, 0, 5, 5, 22, 20, 16, 10, 24, 16, 22, 28, 17, 9, 1, 4, 13, 0, 3, 5, 10, 14, 6, 4, 1, 0, 16, 14, 21, 25, 7, 21, 1, 10, 10, 7, 0, 0, 8, 1, 0, 1, 13, 27, 13, 15, 21, 20, 13, 8, 7, 14, 5, 12, 8, 10, 4, 5, 1, 19, 17, 12, 20, 14, 13, 13, 23, 16, 11, 16, 6, 5, 2, 3, 9, 5, 4, 180, 237, 223, 200, 217, 180, 215, 191, 217, 176, 218, 219, 175, 151, 69, 6, 82, 86, 70, 39, 1, 0, 1, 39, 156, 65, 189, 185, 226, 254, 213, 225, 
+#> 153, 213, 203, 71, 66, 78, 110, 85, 122, 21, 106, 128, 115, 105, 68, 94, 81, 81, 64, 24, 0, 1, 9, 223, 221, 234, 94, 214, 188, 138, 173, 166, 133, 177, 194, 108, 43, 21, 42, 1, 75, 4, 5, 5, 9, 6, 3, 15, 18, 4, 13, 19, 27, 19, 4, 7, 17, 3, 1, 14, 16, 6, 6, 5, 3, 14, 12, 4, 8, 16, 9, 11, 3, 11, 11, 9, 2, 4, 23, 108, 61, 114, 175, 175, 150, 157, 87, 172, 157, 20, 67, 15, 13, 14, 5, 17, 28, 15, 15, 22, 14, 19, 16, 4, 2, 14, 0, 1, 20, 102, 164, 172, 231, 175, 231, 91, 161, 167, 111, 94, 28, 82, 105, 66, 
+#> 13, 149, 133, 86, 209, 36, 139, 40, 5, 12, 6, 3, 127, 161, 193, 215, 201, 119, 184, 204, 214, 201, 227, 209, 174, 132, 161, 96, 12, 35, 9, 140, 168, 138, 105, 128, 150, 123, 135, 67, 131, 131, 97, 148, 144, 122, 116, 116, 26, 27, 0, 14, 203, 181, 231, 194, 202, 183, 179, 190, 125, 80, 84, 14, 15, 26, 30, 26, 8, 16, 13, 2, 8, 4, 10, 12, 11, 8, 19, 19, 11, 14, 13, 7, 0, 1, 22, 35, 37, 31, 38, 22, 52, 36, 12, 27, 2, 11, 1, 0, 2, 7, 153, 170, 192, 188, 147, 9, 116, 4, 39, 75, 111, 171, 38, 12, 22, 0, 
+#> 18, 22, 26, 17, 14, 10, 11, 0, 10, 1, 0, 11, 3, 23, 47, 23, 41, 38, 43, 43, 35, 23, 21, 26, 22, 5, 5, 12, 13, 20, 26, 20, 23, 26, 25, 21, 9, 8, 15, 8, 11, 4, 4, 2, 3, 5, 113, 254, 202, 172, 219, 40, 70, 56, 6, 10, 42, 131, 183, 188, 150, 213, 204, 180, 185, 198, 162, 197, 168, 153, 146, 27, 42, 1, 60, 198, 181, 209, 198, 180, 187, 162, 232, 182, 159, 15, 81, 33, 2, 22, 5, 55, 139, 203, 187, 177, 186, 143, 164, 83, 175, 172, 160, 156, 161, 24, 24, 46, 3, 1, 4, 4, 10, 8, 12, 12, 10, 8, 9, 5, 2, 5, 
+#> 98, 80, 25, 146, 147, 189, 148, 145, 133, 104, 13, 74, 14, 0, 13, 1, 10, 7, 18, 18, 23, 12, 13, 16, 9, 6, 6, 5, 5, 17, 15, 12, 21, 19, 30, 23, 13, 16, 10, 11, 7, 13, 14, 0, 18, 13, 18, 16, 21, 23, 18, 13, 9, 13, 9, 15, 9, 11, 18, 18, 15, 22, 21, 19, 19, 22, 8, 7, 5, 3, 12, 11, 5, 4, 1, 1, 91, 219, 250, 200, 226, 223, 131, 127, 32, 152, 132, 113, 9, 81, 77, 9, 1, 2, 1, 3, 11, 18, 9, 13, 10, 10, 21, 13, 11, 0, 9, 5, 0, 0, 5, 19, 30, 22, 20, 17, 21, 23, 10, 18, 9, 6, 10, 5, 0, 32, 206, 173, 138, 227, 
+#> 211, 189, 173, 191, 163, 156, 7, 146, 193, 53, 77, 10, 2, 3, 10, 16, 14, 21, 21, 2, 3, 1, 1, 14, 9, 0, 1, 25, 19, 29, 30, 27, 15, 5, 5, 4, 0, 1, 0, 71, 184, 152, 160, 189, 159, 187, 141, 152, 158, 126, 80, 123, 2, 113, 77, 91, 0, 3, 145, 124, 156, 131, 152, 127, 125, 153, 176, 142, 145, 92, 99, 79, 85, 35, 6, 178, 179, 155, 159, 172, 159, 135, 130, 161, 133, 145, 161, 55, 13, 16, 114, 136, 135, 175, 159, 155, 157, 158, 148, 150, 51, 104, 110, 25, 10, 35, 4, 19, 19, 23, 16, 13, 23, 16, 15, 22, 24, 
+#> 17, 19, 13, 11, 7, 3, 3, 8, 11, 16, 12, 26, 25, 23, 7, 14, 12, 4, 6, 14, 0, 0, 172, 199, 185, 165, 183, 174, 154, 31, 58, 125, 6, 85, 0, 13, 0, 130, 97, 111, 112, 120, 95, 103, 68, 63, 104, 35, 45, 84, 74, 98, 76, 53, 46, 33, 37, 182, 198, 224, 223, 237, 190, 201, 127, 48, 171, 166, 47, 91, 165, 62, 28, 24, 46, 4, 2, 5, 2, 9, 19, 13, 14, 12, 12, 19, 8, 1, 0, 158, 180, 186, 192, 190, 151, 174, 182, 178, 118, 137, 186, 41, 30, 4, 110, 0, 200, 118, 147, 144, 129, 173, 162, 100, 76, 11, 33, 34, 23, 2, 
+#> 1, 15, 18, 15, 4, 0, 36, 11, 22, 10, 4, 0, 0, 9, 19, 17, 16, 14, 21, 11, 15, 10, 10, 11, 2, 8, 10, 16, 2, 3, 5, 63, 188, 161, 182, 128, 32, 2, 30, 84, 73, 23, 46, 140, 179, 182, 145, 180, 164, 190, 191, 175, 160, 164, 122, 155, 150, 162, 89, 115, 139, 5, 0, 1, 2, 110, 153, 192, 201, 205, 180, 153, 151, 150, 117, 1, 7, 21, 28, 21, 16, 18, 16, 14, 15, 10, 13, 1, 0, 135, 201, 203, 16, 200, 175, 156, 195, 18, 84, 145, 100, 0, 19, 58, 129, 195, 202, 214, 188, 171, 198, 183, 200, 180, 166, 182, 169, 149, 
+#> 60, 42, 0, 6, 189, 194, 115, 138, 216, 145, 193, 201, 153, 114, 11, 7, 154, 147, 166, 67, 208, 186, 153, 101, 81, 67, 141, 156, 51, 4, 0, 124, 77, 189, 131, 161, 177, 103, 79, 86, 72, 24, 84, 144, 179, 127, 172, 114, 162, 46, 12, 206, 215, 194, 176, 179, 193, 186, 146, 168, 190, 94, 158, 109, 2, 18, 32, 20, 23, 2, 10, 25, 6, 3, 6, 12, 2, 6, 12, 2, 9, 13, 5, 15, 14, 6, 20, 16, 10, 1, 3, 7, 3, 0, 2, 112, 202, 208, 181, 134, 166, 132, 156, 147, 150, 168, 36, 46, 70, 49, 85, 70, 26, 8, 69, 134, 197, 
+#> 137, 161, 204, 182, 89, 162, 197, 186, 142, 192, 21, 180, 154, 156, 148, 30, 42, 21, 116, 133, 167, 173, 195, 191, 191, 186, 166, 154, 108, 193, 92, 65, 155, 57, 153, 151, 162, 144, 182, 160, 156, 63, 59, 4, 8, 22, 17, 19, 15, 16, 12, 18, 9, 13, 14, 14, 1, 9, 12, 1, 13, 9, 13, 13, 10, 3, 5, 1, 4, 8, 1, 8, 13, 9, 12, 5, 0, 1, 1, 2, 0, 4, 10, 21, 2, 0, 8, 1, 176, 200, 207, 144, 186, 94, 32, 146, 125, 7, 121, 166, 83, 14, 22, 16, 3, 0, 3, 0, 136, 204, 179, 197, 182, 150, 165, 127, 177, 162, 102, 6, 
+#> 76, 86, 36, 26, 14, 140, 125, 212, 199, 130, 170, 139, 26, 6, 42, 25, 13, 24, 22, 13, 18, 6, 0, 0, 1, 2, 1, 0, 80, 192, 181, 179, 196, 213, 147, 148, 58, 1, 17, 10, 14, 38, 35, 3, 37, 36, 38, 29, 28, 37, 37, 26, 24, 35, 11, 27, 20, 10, 3, 5, 36, 68, 82, 63, 6, 36, 22, 23, 133, 146, 99, 74, 60, 104, 111, 69, 13, 25, 43, 76, 31, 1, 14, 14, 172, 126, 78, 199, 158, 116, 50, 113, 87, 47, 123, 116, 34, 0, 0, 0, 17, 1, 22, 23, 19, 3, 31, 18, 4, 23, 9, 0, 12, 11, 5, 2, 10, 14, 2, 10, 4, 7, 3, 2, 0, 1, 5, 
+#> 15, 4, 6, 10, 11, 13, 18, 5, 11, 4, 2, 0, 5, 27, 209, 209, 191, 162, 156, 143, 177, 160, 143, 75, 9, 45, 54, 125, 99, 127, 114, 129, 123, 167, 129, 120, 105, 102, 90, 95, 113, 69, 31, 0, 32, 37, 11, 84, 137, 163, 157, 112, 114, 10, 24, 12, 15, 20, 13, 10, 11, 11, 7, 1, 14, 4, 4, 8, 1, 159, 139, 150, 166, 152, 134, 40, 55, 72, 37, 117, 161, 173, 162, 173, 135, 79, 153, 154, 136, 87, 155, 168, 174, 165, 146, 176, 184, 137, 152, 160, 116, 170, 148, 3, 9, 17, 21, 18, 18, 4, 16, 18, 9, 17, 10, 10, 7, 
+#> 6, 9, 1, 0, 0, 12, 1, 2, 19, 21, 16, 9, 1, 7, 18, 18, 9, 14, 12, 12, 1, 0, 2, 3, 185, 193, 185, 186, 176, 181, 188, 194, 106, 169, 4, 37, 133, 114, 138, 163, 135, 69, 98, 8, 14, 50, 19, 78, 24, 29, 38, 9, 10, 39, 24, 20, 24, 24, 30, 14, 7, 12, 4, 0, 20, 13, 8, 4, 12, 13, 40, 6, 0, 11, 12, 9, 10, 7, 0, 43, 139, 135, 146, 55, 133, 141, 150, 138, 139, 154, 82, 9, 5, 13, 0, 67, 67, 48, 142, 133, 176, 115, 122, 57, 18, 2, 45, 203, 94, 54, 97, 113, 133, 35, 32, 149, 140, 174, 175, 155, 142, 143, 149, 148, 
+#> 88, 9, 7, 79, 0, 56, 137, 49, 92, 122, 143, 123, 15, 40, 47, 144, 91, 25, 38, 40, 2, 133, 143, 151, 159, 139, 49, 148, 36, 66, 29, 16, 16, 0, 0, 65, 146, 135, 173, 188, 167, 136, 65, 119, 129, 70, 13, 41, 24, 13, 1, 9, 79, 157, 140, 130, 129, 112, 100, 58, 146, 115, 55, 39, 18, 167, 131, 139, 128, 130, 125, 124, 59, 3, 2, 12, 5, 15, 25, 15, 23, 29, 6, 3, 4, 14, 4, 6, 1, 19, 13, 7, 13, 125, 170, 164, 181, 190, 139, 170, 218, 13, 117, 44, 13, 33, 100, 157, 167, 161, 128, 164, 147, 151, 132, 87, 42, 
+#> 145, 115, 192, 127, 168, 155, 20, 58, 1, 12, 2, 15, 6, 0, 6, 3, 0, 7, 6, 14, 26, 14, 17, 2, 2, 3, 15, 8, 6, 1, 1, 0, 0, 1, 16, 15, 18, 1, 3, 0, 12, 3, 5, 5, 3, 156, 71, 66, 184, 149, 117, 120, 30, 60, 16, 38, 6, 0, 0, 2, 11, 17, 21, 8, 9, 10, 1, 10, 10, 1, 0, 1, 109, 193, 158, 132, 188, 183, 162, 176, 191, 161, 115, 153, 143, 31, 86, 1, 62, 24, 53, 42, 3, 17, 59, 100, 131, 88, 125, 120, 134, 114, 155, 54, 138, 119, 110, 52, 57, 49, 8, 197, 169, 98, 182, 107, 120, 153, 0, 159, 191, 138, 156, 179, 
+#> 111, 169, 96, 139, 166, 57, 9, 1, 18, 9, 10, 12, 2, 0, 1, 7, 8, 9, 15, 10, 15, 4, 7, 8, 1, 13, 10, 15, 18, 18, 30, 7, 17, 5, 7, 0, 11, 20, 1, 5, 15, 5, 1, 0, 4, 14, 2, 9, 11, 15, 25, 0, 4, 14, 12, 19, 47, 203, 152, 187, 169, 141, 92, 3, 77, 1, 169, 148, 164, 165, 138, 157, 171, 177, 185, 113, 75, 24, 53, 104, 1, 14, 2, 16, 13, 13, 19, 17, 19, 6, 2, 14, 0, 6, 0, 11, 8, 3, 2, 1, 0, 10, 8, 0, 0, 0, 121, 138, 134, 117, 135, 119, 116, 147, 143, 140, 92, 46, 0, 54, 106, 89, 81, 89, 109, 95, 126, 24, 54, 
+#> 63, 23, 16, 205, 208, 207, 159, 185, 153, 150, 10, 45, 90, 3, 40, 1, 115, 138, 101, 186, 153, 150, 155, 161, 157, 160, 39, 97, 8, 166, 77, 141, 131, 82, 85, 12, 116, 71, 1, 12, 4, 9, 16, 20, 36, 25, 20, 11, 15, 2, 12, 14, 6, 3, 0, 4, 4, 10, 3, 0, 0, 19, 11, 15, 14, 10, 12, 1, 200, 98, 106, 104, 89, 26, 1, 0, 20, 147, 220, 197, 228, 183, 230, 207, 192, 205, 194, 200, 195, 179, 184, 176, 159, 87, 91, 107, 143, 86, 1, 1, 11, 14, 16, 13, 30, 25, 20, 9, 5, 6, 1, 6, 49, 123, 143, 126, 7, 75, 157, 77, 86, 
+#> 31, 111, 9, 107, 82, 30, 49, 3, 31, 18, 21, 126, 123, 1, 1, 103, 141, 118, 144, 82, 116, 0, 4, 60, 205, 195, 122, 146, 130, 41, 0, 71, 19, 0, 0, 8, 9, 8, 12, 29, 28, 13, 19, 19, 18, 13, 9, 10, 4, 2, 0, 43, 161, 144, 166, 183, 160, 157, 128, 176, 153, 135, 162, 137, 62, 54, 40, 71, 134, 177, 148, 63, 1, 3, 128, 166, 130, 0, 154, 73, 39, 99, 0, 4, 0, 1, 22, 10, 9, 9, 2, 7, 7, 1, 33, 147, 167, 173, 141, 158, 163, 152, 158, 145, 150, 167, 172, 116, 3, 90, 2, 2, 19, 7, 179, 140, 63, 47, 171, 165, 114, 
+#> 163, 191, 182, 184, 162, 129, 51, 21, 39, 168, 121, 158, 168, 161, 75, 10, 138, 181, 168, 122, 138, 105, 174, 156, 147, 95, 34, 64, 21, 0, 28, 34, 124, 0, 17, 12, 1, 63, 69, 71, 60, 28, 32, 24, 27, 9, 1, 0, 1, 5, 2, 19, 21, 11, 7, 6, 4, 6, 8, 3, 0, 3, 15, 9, 4, 0, 1, 6, 9, 12, 9, 4, 0, 0, 19, 43, 11, 59, 159, 28, 21, 69, 141, 162, 1, 145, 110, 104, 8, 162, 125, 94, 64, 15, 54, 99, 130, 154, 197, 177, 150, 144, 93, 106, 70, 64, 15, 6, 50, 0, 3, 93, 150, 150, 165, 156, 159, 47, 2, 22, 126, 159, 66, 
+#> 155, 171, 146, 156, 69, 47, 158, 153, 146, 67, 24, 61, 39, 31, 0, 8, 11, 7, 11, 20, 12, 21, 14, 12, 6, 7, 11, 15, 12, 7, 11, 13, 7, 8, 13, 1, 0, 1, 0, 155, 170, 195, 224, 176, 191, 190, 101, 96, 5, 4, 0, 1, 0, 0, 11, 13, 2, 10, 1, 8, 7, 1, 1, 4, 16, 17, 18, 5, 9, 1, 0, 24, 133, 46, 69, 197, 1, 87, 28, 39, 3, 103, 151, 143, 51, 149, 92, 71, 3, 159, 168, 148, 207, 159, 135, 170, 17, 100, 160, 143, 205, 173, 162, 125, 65, 104, 20, 1, 1, 138, 154, 142, 26, 188, 112, 179, 218, 191, 88, 45, 141, 24, 66, 
+#> 134, 90, 25, 92, 0, 45, 98, 68, 82, 89, 64, 15, 17, 0, 58, 185, 149, 143, 154, 191, 106, 151, 165, 199, 135, 70, 73, 0, 5, 7, 7, 14, 15, 8, 16, 12, 5, 0, 13, 4, 1, 13, 6, 3, 0, 125, 72, 6, 143, 132, 141, 79, 144, 158, 127, 19, 8, 4, 95, 95, 63, 88, 59, 36, 57, 71, 77, 40, 59, 21, 16, 4, 169, 149, 171, 184, 185, 142, 171, 165, 145, 167, 164, 140, 86, 21, 4, 2, 28, 37, 25, 20, 21, 11, 4, 19, 17, 6, 0, 0, 85, 136, 144, 154, 135, 155, 172, 138, 176, 152, 142, 171, 156, 147, 74, 33, 126, 165, 178, 169, 
+#> 145, 185, 186, 193, 189, 143, 1, 27, 195, 195, 166, 147, 145, 109, 129, 134, 109, 157, 75, 8, 82, 143, 115, 192, 161, 146, 149, 179, 147, 155, 121, 115, 134, 99, 107, 52, 43, 2, 0, 10, 7, 8, 14, 13, 16, 17, 15, 14, 13, 5, 8, 66, 127, 96, 90, 149, 129, 142, 158, 181, 118, 41, 78, 139, 79, 31, 26, 9, 33, 23, 0, 10, 1, 0, 6, 13, 11, 4, 13, 24, 5, 1, 0, 0, 124, 177, 147, 170, 149, 164, 126, 117, 40, 159, 78, 0, 4, 2, 12, 15, 5, 4, 11, 3, 0, 4, 4, 2, 0, 1, 7, 16, 15, 18, 23, 22, 18, 23, 21, 17, 22, 13, 
+#> 36, 24, 14, 21, 18, 16, 11, 4, 3, 103, 144, 171, 146, 153, 70, 132, 15, 106, 95, 18, 7, 175, 170, 203, 170, 185, 157, 159, 120, 81, 98, 134, 146, 138, 147, 146, 176, 114, 71, 30, 37, 10, 31, 42, 89, 112, 102, 76, 68, 87, 5, 125, 109, 83, 36, 25, 1, 0, 16, 18, 34, 29, 37, 21, 28, 26, 21, 19, 18, 3, 3, 1, 10, 19, 13, 17, 15, 13, 9, 9, 6, 0, 29, 27, 40, 19, 65, 69, 101, 106, 125, 95, 22, 37, 105, 61, 16, 4, 4, 9, 9, 11, 10, 8, 4, 1, 1, 0, 3, 0, 2, 7, 10, 0, 0, 3, 175, 146, 164, 196, 177, 194, 189, 134, 
+#> 52, 118, 169, 137, 19, 126, 42, 48, 5, 9, 7, 10, 7, 7, 2, 0, 0, 12, 109, 75, 97, 120, 173, 43, 97, 125, 50, 44, 20, 103, 74, 1, 13, 29, 19, 25, 8, 21, 3, 6, 7, 96, 97, 185, 172, 143, 70, 45, 118, 19, 81, 65, 127, 145, 12, 68, 125, 83, 1, 34, 0, 6, 0, 12, 120, 170, 159, 156, 129, 157, 176, 158, 146, 173, 123, 114, 39, 52, 32, 5, 8, 6, 119, 132, 119, 156, 139, 146, 158, 151, 127, 111, 35, 8, 72, 125, 123, 164, 126, 162, 82, 142, 85, 80, 22, 24, 23, 15, 42, 26, 17, 21, 5, 32, 5, 6, 144, 88, 20, 6, 77, 
+#> 119, 138, 139, 172, 162, 93, 131, 145, 125, 108, 22, 10, 4, 1, 8, 6, 12, 13, 4, 0, 11, 5, 3, 0, 0, 0, 158, 157, 121, 150, 117, 169, 200, 148, 147, 112, 60, 37, 12, 123, 150, 90, 17, 2, 65, 22, 47, 42, 6, 180, 86, 35, 128, 150, 90, 127, 96, 57, 10, 47, 42, 4, 48, 7, 0, 1, 12, 11, 19, 14, 7, 5, 3, 18, 6, 2, 1, 0, 10, 0, 0, 3, 4, 3, 1, 11, 0, 0, 1, 0, 0, 95, 129, 108, 177, 189, 197, 105, 165, 161, 164, 151, 121, 119, 27, 2, 20, 39, 161, 199, 168, 162, 198, 199, 166, 158, 139, 102, 114, 57, 69, 44, 86, 
+#> 35, 16, 13, 16, 16, 9, 8, 8, 4, 0, 19, 7, 1, 2, 116, 174, 172, 150, 164, 168, 178, 104, 90, 114, 40, 11, 19, 0, 159, 160, 141, 0, 5, 132, 153, 164, 132, 143, 135, 157, 143, 135, 120, 70, 14, 12, 123, 146, 154, 102, 152, 136, 156, 126, 109, 87, 127, 30, 195, 185, 171, 195, 208, 180, 190, 176, 189, 187, 171, 177, 159, 128, 144, 114, 139, 113, 52, 9, 44, 5, 8, 17, 5, 13, 8, 0, 5, 9, 0, 1, 2, 1, 2, 0, 7, 8, 1, 5, 5, 8, 14, 10, 4, 3, 3, 7, 11, 18, 19, 9, 1, 6, 2, 10, 8, 5, 1, 7, 0, 2, 1, 0, 0, 0, 10, 
+#> 5, 34, 138, 104, 36, 148, 138, 153, 104, 150, 55, 45, 98, 59, 1, 0, 10, 18, 9, 3, 2, 0, 0, 5, 4, 0, 1, 3, 0, 0, 91, 171, 136, 163, 158, 188, 173, 158, 154, 145, 163, 121, 54, 141, 92, 96, 108, 103, 11, 5, 12, 15, 14, 22, 15, 27, 20, 13, 20, 17, 12, 3, 10, 16, 9, 6, 5, 2, 1, 10, 151, 131, 115, 64, 1, 9, 15, 97, 151, 21, 121, 68, 35, 127, 63, 78, 92, 0, 1, 1, 7, 159, 152, 171, 201, 140, 120, 111, 26, 209, 201, 190, 196, 173, 179, 198, 146, 125, 148, 121, 92, 26, 14, 1, 47, 168, 171, 134, 178, 154, 
+#> 145, 156, 138, 107, 159, 148, 76, 104, 51, 157, 170, 167, 111, 190, 177, 160, 188, 193, 192, 148, 99, 48, 122, 78, 112, 0, 58, 36, 43, 0, 6, 1, 1, 0, 6, 15, 25, 9, 12, 14, 5, 0, 1, 0, 0, 0, 44, 38, 56, 57, 53, 39, 9, 10, 3, 1, 1, 6, 0, 3, 0, 0, 0, 0, 193, 175, 161, 152, 69, 164, 140, 152, 59, 90, 26, 18, 1, 104, 164, 165, 157, 159, 180, 187, 192, 156, 34, 88, 30, 32, 53, 64, 3, 60, 165, 179, 160, 189, 146, 115, 124, 95, 8, 11, 41, 0, 3, 2, 11, 16, 17, 14, 11, 19, 16, 8, 4, 0, 0, 2, 0, NA, 0, 0, 0, 
+#> 0, 0, 11, 17, 11, 15, 9, 16, 9, 16, 14, 9, 0, 8, 7, 0, 2, 1, 10, 16, 1, 1, 5, 3, 0, 0, 150, 170, 15, 141, 161, 132, 108, 156, 164, 149, 115, 134, 1, 0, 2, 63, 113, 189, 192, 178, 201, 198, 192, 196, 187, 191, 175, 152, 166, 140, 117, 11, 128, 175, 138, 144, 150, 167, 137, 182, 152, 175, 142, 144, 117, 137, 113, 25, 78, 11, 7, 139, 200, 194, 170, 170, 167, 153, 190, 121, 172, 154, 112, 138, 141, 94, 124, 130, 119, 87, 79, 146, 7, 20, 10, 14, 17, 6, 15, 15, 8, 17, 10, 13, 8, 15, 0, 2, 11, 163, 176, 
+#> 160, 169, 193, 179, 162, 142, 164, 98, 156, 162, 139, 158, 136, 143, 56, 16, 23, 22, 6, 19, 14, 15, 12, 6, 8, 6, 5, 2, 3, 0, 3, 0, 0, 142, 148, 148, 157, 166, 170, 140, 150, 154, 127, 182, 127, 164, 168, 173, 114, 112, 135, 166, 197, 149, 168, 138, 176, 208, 125, 174, 172, 182, 149, 113, 166, 144, 128, 86, 142, 107, 10, 28, 15, 140, 182, 144, 175, 174, 168, 194, 178, 176, 185, 139, 132, 47, 39, 3, 60, 7, 131, 189, 200, 198, 196, 223, 172, 197, 191, 201, 187, 181, 168, 184, 174, 164, 154, 162, 119, 
+#> 118, 91, 109, 62, 0, 5, 9, 20, 16, 17, 11, 11, 12, 16, 17, 17, 13, 12, 8, 12, 4, 3, 0, 0, 4, 9, 7, 20, 16, 13, 24, 21, 16, 21, 9, 1, 3, 12, 0, 2, 6, 1, 0, 7, 17, 185, 185, 169, 161, 157, 175, 169, 142, 87, 32, 15, 7, 8, 74, 111, 78, 90, 96, 77, 111, 132, 90, 115, 134, 106, 95, 59, 17, 3, 167, 6, 160, 174, 182, 149, 172, 176, 168, 172, 184, 151, 19, 72, 7, 1, 0, 42, 132, 130, 147, 126, 126, 122, 90, 65, 94, 111, 115, 80, 4, 80, 128, 47, 128, 148, 143, 155, 170, 53, 143, 95, 74, 1, 15, 10, 8, 13, 16, 
+#> 15, 13, 4, 1, 3, 3, 3, 0, 3, 6, 20, 14, 17, 13, 13, 23, 13, 12, 22, 19, 17, 5, 2, 2, 9, 3, 81, 76, 90, 118, 121, 79, 155, 138, 140, 172, 91, 105, 17, 39, 49, 0, 5, 11, 11, 8, 5, 12, 4, 4, 2, 0, 3, 4, 118, 190, 164, 121, 122, 62, 172, 167, 151, 177, 146, 55, 10, 10, 51, 87, 103, 149, 164, 122, 136, 153, 110, 132, 70, 141, 48, 2, 43, 159, 135, 146, 176, 159, 99, 78, 137, 156, 115, 16, 24, 23, 80, 30, 26, 0, 33, 138, 103, 145, 166, 185, 151, 117, 76, 83, 9, 9, 2, 62, 149, 156, 119, 147, 148, 155, 131, 
+#> 161, 134, 163, 167, 127, 52, 84, 49, 12, 60, 56, 104, 112, 104, 74, 97, 116, 133, 158, 6, 104, 52, 45, 30, 25, 3, 28, 18, 12, 22, 2, 21, 11, 12, 17, 8, 13, 2, 0, 0, 12, 50, 2, 163, 147, 160, 158, 182, 153, 157, 148, 131, 146, 32, 15, 20, 123, 160, 176, 59, 100, 0, 188, 192, 169, 182, 191, 183, 161, 6, 14, 137, 183, 149, 147, 173, 69, 25, 0, 159, 23, 39, 2, 116, 172, 125, 166, 172, 158, 84, 114, 13, 120, 152, 109, 50, 42, 10, 7, 20, 0, 4, 3, 7, 14, 10, 16, 16, 10, 12, 6, 11, 11, 9, 5, 3, 0, 1, 0, 
+#> 7, 6, 2, 2, 1, 0, 3, 4, 0, 0, 0, 1, 2, 15, 29, 19, 15, 33, 23, 10, 18, 20, 22, 25, 17, 15, 23, 10, 15, 22, 15, 6, 7, 3, 39, 121, 120, 177, 122, 80, 132, 10, 57, 105, 12, 13, 116, 130, 153, 129, 112, 127, 59, 41, 21, 2, 7, 149, 126, 136, 138, 143, 141, 102, 37, 128, 116, 43, 15, 68, 62, 89, 67, 158, 80, 149, 148, 126, 153, 157, 143, 91, 56, 102, 87, 104, 5, 41, 134, 80, 88, 23, 0, 1, 14, 10, 10, 9, 11, 16, 5, 2, 0, 0, 3, 11, 12, 16, 10, 12, 12, 16, 17, 5, 14, 5, 19, 20, 16, 3, 2, 10, 28, 110, 89, 
+#> 175, 192, 192, 148, 194, 166, 167, 164, 154, 140, 168, 160, 139, 141, 159, 97, 46, 7, 2, 1, 20, 38, 14, 126, 139, 146, 145, 110, 117, 93, 18, 58, 145, 140, 125, 151, 122, 89, 62, 87, 35, 1, 10, 36, 84, 41, 99, 118, 141, 159, 151, 84, 144, 37, 81, 107, 79, 130, 7, 156, 157, 169, 199, 200, 191, 157, 159, 77, 92, 12, 109, 139, 142, 158, 175, 163, 186, 164, 199, 201, 186, 149, 152, 3, 12, 0, 0, 135, 132, 34, 109, 150, 138, 13, 116, 20, 51, 48, 27, 30, 4, 7, 3, 120, 79, 146, 114, 98, 149, 137, 133, 164, 
+#> 175, 160, 153, 8, 70, 58, 73, 92, 143, 139, 127, 84, 166, 150, 129, 48, 80, 71, 153, 84, 27, 0, 6, 14, 9, 10, 10, 10, 2, 0, 7, 0, 4, 3, 3, 5, 1, 5, 6, 6, 3, 6, 5, 3, 1, 1, 1, 7, 19, 2, 1, 6, 4, 2, 2, 2, 0, 2, 1, 0, 0, 0, 4, 1, 2, 0, NA, 0, 9, 8, 10, 1, 2, 0, 0, 4, 1, 78, 45, 141, 116, 173, 209, 167, 181, 164, 153, 0, 16, 19, 9, 15, 10, 17, 25, 4, 8, 0, 0, 2, 1, 4, 10, 104, 92, 61, 99, 97, 111, 119, 102, 123, 91, 82, 95, 20, 121, 169, 114, 150, 128, 179, 201, 168, 192, 211, 194, 202, 209, 146, 175, 
+#> 145, 178, 118, 26, 205, 187, 208, 181, 204, 166, 204, 178, 187, 135, 126, 164, 149, 133, 121, 112, 71, 63, 152, 173, 208, 159, 173, 186, 162, 186, 174, 129, 42, 141, 169, 17, 11, 9, 8, 5, 0, 0, 1, 0, 5, 13, 147, 184, 175, 201, 203, 179, 176, 185, 188, 205, 179, 191, 166, 113, 127, 74, 2, 25, 101, 193, 123, 133, 123, 124, 168, 118, 108, 135, 96, 128, 114, 95, 34, 4, 89, 116, 148, 151, 138, 169, 164, 162, 161, 170, 127, 42, 46, 23, 20, 15, 55, 110, 91, 127, 129, 4, 63, 58, 71, 112, 99, 98, 118, 74, 
+#> 1, 42, 22, 21, 8, 0, 0, 2, 0, 3, 3, 7, 8, 15, 8, 3, 2, 1, 3, 13, 2, 5, 0, 0, 7, 2, 0, 3, 8, 4, 4, 0, 2, 6, 2, 5, 4, 2, 5, 1, 1, 2, 0, 0, 70, 29, 21, 127, 164, 160, 162, 152, 153, 105, 46, 9, 4, 1, 6, 1, 14, 3, 4, 6, 15, 20, 7, 7, 7, 3, 1, 0, 5, 9, 15, 15, 13, 16, 22, 16, 19, 39, 20, 12, 14, 3, 0, 2, 15, 18, 8, 14, 23, 23, 17, 12, 18, 15, 15, 13, NA, 0, 0, NA, 14, 10, 7, NA, 0, NA, 5, 3, 0, 0, 5, 172, 133, 111, 121, 91, 121, 144, 116, 70, 68, 76, 81, 61, 73, 9, 2, 178, 140, 131, 168, 125, 98, 99, 
+#> 74, 26, 1, 1, 0, 0, 17, 20, 12, 9, 8, 3, 10, 16, 9, 7, 0, 0, 97, 128, 230, 181, 163, 15, 98, 174, 122, 19, 123, 11, 60, 58, 71, 21, 7, 169, 181, 130, 58, 5, 2, 6, 0, 5, 9, 11, 11, 8, 11, 4, 3, 1, 0, 3, 2, 6, 5, 0, 1, 1, 0, 0, 1, 4, 3, 5, 2, 0, 3, 7, 3, 1, 2, 0, 0, 0, 0, 0, 0, 1, 0, 2, 0, 6, 6, 7, 5, 6, 7, 7, 20, 9, 155, 191, 183, 164, 154, 165, 189, 162, 154, 186, 129, 120, 160, 155, 146, 146, 165, 145, 140, 100, 83, 126, 101, 9, 6, 143, 137, 162, 171, 182, 135, 116, 79, 49, 20, 37, 27, 115, 128, 
+#> 119, 99, 54, 43, 55, 115, 101, 74, 89, 61, 26, 0, 1, 110, 53, 94, 108, 188, 200, 211, 191, 167, 172, 186, 173, 7, 2, 76, 90, 60, 90, 21, 69, 12, 74, 116, 68, 4, 0, 0, 1, 0, 21, 25, 13, 19, 21, 15, 12, 20, 26, 6, 170, 139, 209, 205, 176, 210, 218, 205, 192, 198, 230, 185, 210, 215, 204, 198, 208, 185, 140, 172, 121, 35, 72, 107, 52, 33, 157, 154, 131, 149, 126, 93, 124, 57, 70, 131, 56, 4, 30, 4, 7, 21, 20, 14, 17, 28, 14, 20, 15, 5, 14, 10, 13, NA, 0, 19, 18, 75, 121, 181, 178, 179, 162, 169, 145, 
+#> 97, 131, 126, 61, 71, 24, 3, 5, 13, 20, 18, 15, 25, 20, 8, 16, 29, 33, 15, 20, 12, 17, 5, 0, 4, 12, 7, 7, 2, 3, 5, 1, 3, 0, 0, 108, 156, 152, 86, 103, 101, 43, 11, 26, 57, 84, 117, 12, 15, 4, 15, 24, 7, 1, 87, 164, 137, 187, 185, 173, 175, 176, 142, 166, 148, 148, 140, 143, 83, 17, 61, 98, 55, 47, 79, 39, 5, 93, 5, 6, 4, 3, 217, 185, 191, 161, 136, 197, 204, 164, 9, 166, 131, 123, 26, 7, 201, 187, 166, 142, 137, 126, 128, 162, 156, 79, 139, 97, 80, 41, 68, 118, 114, 160, 90, 160, 168, 126, 24, 19, 
+#> 8, 4, 16, 22, 9, 6, 132, 122, 156, 134, 133, 156, 108, 160, 147, 62, 153, 143, 127, 100, 60, 74, 62, 6, 51, 170, 140, 167, 154, 171, 150, 151, 167, 81, 79, 29, 42, 60, 50, 31, 16, 7, 4, 145, 144, 47, 138, 102, 132, 125, 103, 145, 112, 124, 108, 4, 1, 113, 62, 147, 193, 152, 172, 132, 115, 174, 203, 230, 157, 149, 149, 89, 95, 9, 4, 14, 6, 1, 6, 1, 6, 13, 0, 1, 0, 0, 4, 73, 156, 101, 115, 146, 142, 128, 95, 143, 98, 89, 132, 105, 64, 33, 61, 173, 133, 150, 160, 145, 97, 106, 162, 145, 146, 123, 42, 
+#> 25, 24, 120, 107, 134, 90, 137, 57, 7, 22, 5, 20, 136, 149, 129, 69, 65, 79, 95, 34, 42, 87, 79, 137, 121, 56, 44, 11, 1, 129, 144, 149, 85, 100, 27, 22, 5, 0, 50, 10, 3, 5, 11, 16, 15, 8, 13, 6, 10, 15, 15, 5, 4, 2, 5, 2, 0, 1, 2, 9, 13, 11, 8, 13, 18, 16, 16, 16, NA, 0, 2, 61, 2, 2, 130, 177, 130, 81, 71, 121, 147, 154, 49, 114, 6, 3, 23, 34, 6, 129, 5, 9, 74, 115, 145, 153, 125, 103, 160, 125, 151, 145, 156, 153, 136, 110, 51, 115, 119, 53, 17, 17, 0, 3, 1, 6, 5, 3, 4, 2, 0, 1, 0, 0, 1, 1, 2, 
+#> 0, NA, 1, 4, 2, 4, 1, 2, 0, 3, 2, 0, 1, 0, 2, 0, 3, 0, 1, 0, 105, 125, 137, 125, 123, 14, 79, 92, 33, 23, 3, 4, 2, 3, 172, 124, 80, 153, 182, 121, 96, 48, 11, 11, 44, 126, 173, 158, 116, 70, 104, 79, 86, 32, 0, 16, 154, 136, 146, 129, 136, 141, 134, 156, 126, 28, 24, 16, 0, 1, 97, 130, 123, 117, 141, 97, 137, 162, 156, 107, 117, 98, 91, 129, 63, 10, 4, 109, 131, 63, 82, 75, 63, 28, 51, 21, 4, 4, 12, 15, 15, 14, 8, 15, 20, 20, 10, 6, 1, 46, 68, 85, 120, 177, 159, 105, 165, 218, 157, 210, 134, 156, 
+#> 133, 2, 90, 10, 66, 0, 0, 0, 2, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 1, 1, 3, 13, 9, 13, 1, 3, 1, 3, 0, 1, 0, 0, 1, 0, 2, 73, 68, 174, 176, 185, 186, 164, 146, 177, 158, 144, 137, 158, 158, 132, 161, 77, 51, 61, 33, 60, 51, 1, 114, 141, 54, 146, 182, 183, 206, 184, 195, 202, 200, 193, 193, 194, 163, 150, 133, 66, 123, 8, 5, 14, 11, 4, 4, 9, 10, 8, 9, 1, 11, 5, 6, 0, 0, 6, 12, 7, 16, 15, 3, 8, 1, 3, 14, 10, 6, 9, 1, 4, 0, 147, 171, 60, 139, 142, 141, 154, 185, 170, 176, 166, 157, 96, 35, 39, 14, 0, 85, 84, 
+#> 162, 89, 178, 128, 135, 111, 140, 144, 96, 74, 43, 22, 21, 1, 0, 55, 129, 120, 102, 112, 131, 196, 146, 119, 0, 1, 124, 144, 125, 133, 61, 7, 78, 83, 17, 37, 3, 0, 150, 126, 152, 70, 177, 170, 203, 218, 192, 200, 239, 188, 130, 179, 111, 167, 160, 97, 124, 11, 15, 11, 17, 18, 13, 15, 7, 17, 7, 12, 5, 9, 12, 6, 11, 6, 10, 0, 0, NA, NA, 4, 2, 16, 117, 134, 113, 149, 139, 110, 134, 47, 132, 60, 36, 88, 7, 23, 8, 15, 43, 54, 36, 33, 1, 61, 49, 155, 107, 148, 146, 133, 156, 82, 148, 106, 145, 102, 93, 
+#> 23, 11, 0, 7, 0, 14, 16, 15, 14, 28, 20, 10, 1, NA, NA, NA, 0, 0, NA, NA, 10, 13, 1, 1, 1, 2, 7, 5, 9, 12, 8, 8, 11, 15, 6, NA, NA, NA, 7, 0, 0, 1, 5, 4, 17, 10, 18, 17, 2, 6, 2, 0, 4, 139, 148, 168, 176, 175, 126, 128, 160, 144, 63, 37, 150, 132, 64, 100, 7, 99, 3, 28, 68, 70, 151, 139, 143, 117, 102, 147, 87, 42, 55, 51, 40, 147, 188, 167, 189, 158, 170, 181, 128, 95, 44, 6, 14, 155, 156, 177, 134, 145, 141, 174, 150, 109, 136, 102, 128, 90, 55, 103, 79, 42, 12, 6, 12, 96, 108, 116, 65, 80, 80, 
+#> 9, 61, 4, 41, 10, 4, 2, 1, 4, 5, 11, 12, 14, 0, NA, 0, 0, 0, 5, NA, 1, 1, 1, 1, NA, 0, 52, 27, 115, 47, 62, 16, 53, 16, 147, 10, 115, 11, 32, 14, 13, 140, 138, 110, 146, 133, 113, 130, 77, 130, 71, 169, 105, 1, 150, 42, 32, 25, 180, 74, 0, 2, 7, 6, 15, 6, 11, 8, 14, 12, 12, NA, NA, 4, 2, 62, 146, 134, 157, 181, 168, 159, 158, 151, 155, 146, 120, 28, 32, 110, 22, 0, 0, 0, 0, 0, 0, 1, 2, 0, 2, 5, 17, NA, 0, 0, NA, NA, NA, 1, 57, 81, 40, 29, 13, 47, 53, 25, 0, 0, 0, 0, 8, 13, 11, 12, 10, 11, 11, NA, 
+#> NA, NA, NA, NA, 8, 129, 126, 122, 143, 149, 144, 83, 151, 114, 1, 50, 15, 17, 1, 3, 32, 98, 152, 100, 133, 53, 106, 111, 100, 141, 83, 74, 33, 61, 23, 12, 25, 32, 165, 174, 183, 167, 128, 185, 139, 191, 150, 78, 19, 28, 0, 20, 95, 113, 154, 140, 111, 129, 120, 140, 62, 124, 117, 24, 0, 0, 139, 163, 125, 179, 128, 158, 39, 92, 112, 148, 137, 92, 44, 80, 43, 26, 160, 104, 126, 116, 147, 126, 135, 64, 146, 77, 23, 82, 5, 21, 138, 151, 101, 157, 132, 158, 146, 150, 138, 150, 140, 138, 154, 79, 146, 77, 
+#> 117, 116, 101, 74, 1, 75, 124, 127, 95, 159, 152, 139, 125, 87, 121, 96, 51, 0, 4, 11, 12, 17, 16, 17, 23, 16, 25, 14, 20, 26, 25, 21, 19, 9, 22, 19, 16, 5, NA, 7, 2, NA, NA, NA, 1, 62, 57, 11, 66, 75, 183, 186, 185, 231, 201, 192, 34, 127, 147, 3, 16, 2, 11, 136, 101, 151, 164, 140, 161, 92, 88, 130, 12, 8, 1, 1, 3, 2, 3, 2, 1, 0, 2, 1, 0, 0, 0, 0, 0, 1, 2, 1, 1, 2, NA, 0, NA, 0, 0, 11, 67, 155, 129, 184, 171, 119, 150, 31, 51, 114, 65, 26, 15, 22, 12, 11, 0, 11, 2, 9, 13, 8, 6, 16, 24, 17, 11, 
+#> NA, NA, NA, 0, 13, 98, 140, 121, 47, 21, 94, 98, 107, 131, 116, 34, 85, 61, 9, 35, 17, 1, 0, 20, 138, 134, 110, 126, 40, 19, 83, 63, 12, 12, 2, 1, 12, 103, 120, 117, 127, 69, 128, 66, 118, 118, 64, 8, 54, 89, 140, 145, 118, 131, 146, 137, 100, 121, 46, 75, 117, 140, 148, 100, 129, 149, 59, 7, 22, 137, 113, 143, 156, 135, 190, 186, 183, 183, 110, 0, 15, 14, 7, 17, 10, 15, 8, 0, 4, 4, 8, 12, 12, 15, 13, 16, 13, 13, 7, NA, 2, NA, 0, 3, 4, 10, 10, 11, 14, 4, 0, NA, NA, NA, 13, 16, 67, 64, 194, 186, 171, 
+#> 94, 95, 129, 71, 2, 15, 4, 0, 3, 12, 2, 0, 0, NA, NA, 0, 6, 10, 5, 7, NA, NA, 4, 4, 13, 14, 176, 167, 158, 175, 157, 116, 165, 120, 145, 170, 99, 100, 136, 93, 16, 78, 161, 200, 178, 162, 182, 145, 143, 100, 156, 25, 126, 148, 47, 35, 28, 86, 171, 126, 180, 133, 177, 146, 161, 155, 181, 198, 178, 171, 180, 102, 42, 132, 14, 4, 22, 137, 88, 98, 137, 138, 90, 92, 75, 16, 84, 48, 22, 20, 49, 114, 136, 156, 22, 97, 171, 188, 172, 171, 155, 170, 110, 144, 125, 100, 40, 38, 0, 7, 129, 146, 109, 105, 92, 
+#> 39, 45, 84, 19, 17, 99, 158, 168, 137, 144, 89, 100, 5, 124, 127, 152, 147, 103, 32, 39, 9, 12, 146, 146, 175, 171, 187, 166, 157, 138, 147, 140, 49, 72, 80, 31, 32, 4, 19, 47, 109, 156, 70, 84, 45, 45, 32, 36, 29, 20, 1, 5, 7, 1, 13, 17, 20, 22, NA, NA, NA, NA, NA, NA, NA, 0, NA, NA, NA, NA, 0, 25, 116, 162, 169, 153, 154, 168, 147, 149, 152, 137, 148, 137, 116, 54, 16, 28, 26, 139, 158, 170, 155, 166, 171, 158, 113, 157, 58, 17, 12, 0, 0, 2, 0, 3, 0, 1, NA, NA, NA, NA, 0, NA, 0, 7, 2, 6, 17, 13, 
+#> 15, 5, 3, 1, 0, 4, 1, 3, 0, 0, 0, 6, 7, 163, 121, 136, 5, 126, 147, 149, 161, 167, 150, 163, 151, 150, 104, 109, 112, 74, 134, 93, 89, 6, 32, 49, 51, 132, 102, 127, 104, 102, 90, 122, 70, 30, 32, 11, 3, 4, 3, 10, 16, 13, 11, 14, 14, 10, 17, NA, NA, 0, NA, NA, NA, 8, 6, NA, NA, 12, NA, NA, 0, 7, 118, 122, 101, 83, 69, 24, 0, 0, 15, 134, 125, 56, 87, 124, 169, 162, 87, 138, 89, 127, 141, 83, 129, 101, 116, 70, 110, 129, 111, 43, 10, 1, 22, 117, 100, 82, 133, 60, 36, 153, 164, 120, 105, 122, 111, 11, 
+#> 18, 0, 110, 161, 179, 168, 164, 144, 171, 148, 54, 123, 154, 83, 142, 77, 105, 53, 33, 18, 137, 162, 145, 94, 184, 178, 155, 175, 192, 130, 144, 102, 123, 133, 87, 48, 2, 3, 10, 9, 8, 7, 17, 3, NA, NA, NA, NA, NA, NA, 8, 32, 23, 108, 137, 181, 118, 174, 130, 135, 64, 127, 80, 88, 22, 41, 0, 21, 12, 37, 7, 135, 75, 12, 4, 15, 2, 141, 151, 135, 125, 132, 112, 125, 3, 126, 78, 103, 69, 136, 67, 7, 6, 21, 53, 44, 79, 37, 9, 2, 1, 2, 0, 3, 4, NA, 0, NA, 0, 0, NA, 0, 0, NA, 2, NA, 1, 0, 0, 3, 1, 0, 6, 
+#> 6, 1, 1, 2, 3, 3, 0, NA, NA, 1, 0, 69, 156, 153, 149, 177, 142, 168, 143, 150, 150, 153, 135, 137, 140, 50, 56, 1, 53, 21, 46, 20, 9, 128, 146, 153, 136, 138, 44, 122, 157, 135, 107, 132, 113, 93, 116, 84, 2, 17, 26, 86, 95, 89, 116, 87, 4, 50, 19, 35, 82, 25, 29, 12, 6, 7, 24, 22, 0, 132, 142, 145, 145, 102, 101, 50, 27, 61, 65, 2, 0, 0, 2, 3, 6, 0, 0, NA, NA, NA, 0, NA, NA, NA, NA, 4, 120, 63, 94, 113, 164, 27, 162, 205, 107, 147, 104, 93, 19, 18, 162, 161, 119, 164, 157, 135, 192, 159, 108, 173, 
+#> 115, 143, 70, 96, 11, 28, 0, 0, 32, 25, 150, 142, 100, 161, 138, 125, 129, 127, 124, 72, 45, 9, 7, 25, 152, 171, 132, 146, 126, 170, 121, 129, 132, 145, 154, 117, 50, 13, 0, 9, 7, 10, 15, 21, 9, 16, 0, 0, 0, NA, NA, NA, 2, NA, 10, 6, 14, 63, 106, 167, 137, 138, 24, 57, 117, 133, 142, 147, 92, 119, 145, 93, 125, 122, 128, 91, 57, 0, 3, 3, 10, 12, 16, 4, 0, 48, 72, 48, 118, 163, 149, 52, 152, 176, 179, 170, 123, 61, 136, 111, 70, 44, 54, 2, 7, 0, 1, 3, 3, 8, 8, 1, 1, 0, 1, NA, 0, 0, 0, 0, 1, 25, 51, 
+#> 79, 106, 200, 210, 200, 192, 202, 204, 200, 122, 176, 114, 175, 184, 142, 16, 10, 115, 110, 127, 69, 47, 133, 73, 116, 12, 87, 61, 6, 9, 18, 19, 19, 18, 36, 23, 1, 0, NA, 0, NA, NA, NA, 2, 9, 18, 70, 68, 133, 129, 149, 131, 67, 85, 37, 29, 32, 18, 2, 12, 11, 16, 10, 15, 23, 17, 12, 4, NA, 2, 69, 67, 79, 94, 167, 139, 162, 155, 170, 166, 162, 129, 164, 123, 130, 141, 81, 89, 39, 66, 15, 158, 78, 66, 96, 29, 42, 2, 42, 12, 147, 167, 132, 143, 157, 147, 89, 73, 81, 79, 108, 15, 49, 134, 157, 155, 160, 
+#> 124, 110, 24, 179, 102, 160, 134, 94, 81, 19, 173, 124, 91, 95, 32, 127, 163, 171, 60, 31, 67, 7, 72, 160, 140, 153, 149, 129, 137, 157, 112, 144, 136, 146, 152, 160, 153, 97, 30, 4, 9, 8, 12, 19, 14, 8, NA, NA, 3, 7, 108, 168, 146, 168, 154, 134, 132, 130, 111, 147, 69, 2, 10, 0, 0, NA, NA, 9, 4, 0, 0, 0, 0, 4, 2, 0, 0, 0, 5, 4, 7, 6, 0, 0, 0, 0, 1, 2, 1, 5, 0, 0, NA, NA, 27, 142, 182, 174, 161, 138, 102, 65, 137, 95, 181, 153, 102, 41, 100, 106, 91, 11, 5, 6, 4, 18, 7, 19, 13, 3, 6, NA, 0, 0, 0, 
+#> NA, NA, NA, NA, 3, NA, 18, 175, 159, 129, 161, 177, 125, 56, 141, 119, 140, 118, 114, 100, 76, 20, 85, 47, 28, 100, 157, 159, 154, 153, 133, 162, 141, 56, 0, 122, 187, 153, 109, 7, 175, 167, 172, 154, 142, 85, 117, 89, 68, 52, 3, 7, 6, 8, 13, 11, 7, 0, 12, 8, 0, 1, 4, 7, 8, 6, 4, 7, 1, 1, 5, NA, 1, NA, NA, NA, 1, 17, 50, 129, 156, 141, 129, 139, 155, 148, 150, 162, 132, 79, 85, 94, 123, 90, 115, 77, 37, 16, 18, 174, 164, 206, 213, 201, 148, 128, 177, 191, 184, 159, 200, 112, 128, 49, 0, 88, 97, 120, 
+#> 149, 153, 152, 142, 103, 147, 150, 105, 183, 140, 55, 107, 63, 8, 10, 11, 6, 5, 15, 15, 3, 2, 4, 2, 30, 158, 174, 82, 179, 162, 171, 143, 114, 84, 100, 170, 128, 98, 1, 132, 149, 149, 176, 191, 198, 176, 143, 175, 170, 159, 209, 130, 204, 184, 29, 101, 20, 47, 40, 62, 172, 168, 215, 194, 193, 153, 62, 66, 154, 173, 198, 174, 149, 97, 146, 176, 108, 12, 0, 0, NA, NA, NA, 5, NA, NA, 0, NA, NA, NA, 4, 0, 0, 0, 0, NA, 0, NA, NA, 0, 0, 0, 0, 0, 0, 4, 3, 0, 0, NA, NA, 0, 0, 1, 2, 6, 86, 28, 29, 11, 73, 
+#> 139, 172, 197, 170, 133, 144, 122, 136, 145, 149, 119, 11, 53, 31, 54, 130, 17, 135, 153, 142, 123, 127, 124, 115, 67, 102, 87, 36, 35, 18, 62, 8, 4, 91, 94, 102, 132, 144, 136, 138, 94, 118, 76, 91, 90, 91, 28, 13, 26, 29, 15, 63, 130, 113, 121, 66, 123, 134, 123, 122, 178, 112, 186, 162, 137, 165, 164, 148, 111, 73, 137, 161, 57, 149, 145, 110, 88, 152, 54, 86, 85, 47, 52, 26, 0, 5, 10, 10, 8, 12, 9, 17, 10, 10, 15, 6, 7, 14, 8, 0, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 15, 10, 11, 15, 
+#> 13, 19, 13, 10, 18, 11, 7, 11, 6, 11, 5, 7, 11, NA, NA, NA, NA, NA, NA, NA, 2, NA, NA, 0, 0, NA, NA, NA, NA, NA, 1, 1, 0, 2, 0, 0, 0, 1, 0, 1, 2, NA, 0, 0, NA, 0, NA, NA, NA, NA, 0, 0, 0, 0, 0, 0, 0, 7, 3, 6, 3, 2, 2, 6, 3, 2, 2, 0, 5, 129, 195, 215, 176, 150, 212, 175, 109, 166, 144, 107, 184, 128, 124, 180, 129, 179, 129, 169, 149, 10, 41, 89, 27, 79, 167, 147, 175, 191, 170, 113, 145, 106, 189, 183, 96, 83, 70, 10, NA, NA, 0, 0, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0, 0, 
+#> NA, 9, 8, 71, 34, 45, 133, 175, 184, 184, 148, 82, 74, 210, 114, 16, 88, 94, 0, 6, 153, 131, 145, 160, 24, 158, 135, 71, 156, 156, 96, 46, 4, 132, 11, 10, 1, 9, 14, 136, 118, 71, 98, 125, 123, 114, 110, 48, 121, 120, 91, 114, 98, 94, 104, 111, 28, 33, 57, 141, 189, 186, 177, 120, 160, 123, 134, 140, 109, 120, 90, 60, 114, 48, 14, 62, 13, 29, 24, 31, 45, 76, 102, 116, 127, 124, 148, 91, 156, 143, 130, 140, 154, 138, 126, 107, 52, 17, 24, 104, 74, 122, 114, 123, 36, 54, 30, 52, 96, 119, 125, 103, 41, 
+#> 23, 17, 65, 91, 154, 189, 133, 152, 27, 113, 66, 151, 73, 145, 120, 15, 2, 0, 7, 14, 143, 174, 147, 129, 93, 155, 137, 152, 170, 128, 171, 138, 71, 92, 58, 173, 174, 179, 186, 111, 174, 178, 180, 173, 151, 171, 171, 147, 184, 150, 144, 174, 110, 141, 59, 88, 35, 2, 20, 148, 154, 176, 178, 119, 183, 189, 132, 135, 141, 178, 179, 105, 164, 153, 150, 126, 70, 58, 16, 10, 115, 151, 139, 155, 151, 83, 155, 117, 162, 137, 136, 137, 93, 155, 26, 75, 141, 72, 4, 128, 83, 15, 148, 146, 80, 158, 165, 151, 
+#> 27, 17, 20, 4, 0, 5, 3, 8, 6, 13, 0, NA, NA, NA, NA, NA, NA, 6, 11, 10, 5, 6, 7, 6, 4, 4, NA, NA, NA, NA, NA, 109, 146, 157, 194, 155, 174, 179, 126, 7, 34, 0, 77, 43, 1, 3, 69, 155, 180, 192, 163, 193, 159, 164, 148, 127, 150, 82, 145, 185, 110, 144, 32, 49, 21, 6, 9, 19, 16, 19, 18, 10, 13, 13, 2, NA, 1, 7, 10, 11, 9, 2, 8, 10, 4, 0, 62, 200, 181, 211, 161, 96, 139, 121, 127, 154, 126, 113, 90, 129, 125, 50, 11, 29, 136, 159, 138, 118, 92, 99, 128, 54, 27, 32, 99, 3, 0, 0, 0, 0, 0, 0, NA, NA, 0, 
+#> 0, NA, NA, NA, 0, 11, 21, 115, 73, 21, 76, 48, 125, 125, 113, 92, 104, 75, 32, 15, 10, 47, 108, 163, 138, 210, 191, 115, 173, 98, 62, 171, 183, 171, 170, 96, 50, 26, 9, 147, 141, 162, 103, 142, 163, 154, 139, 44, 109, 137, 4, 59, 78, 47, 23, 10, 12, 85, 149, 165, 151, 98, 16, 35, 97, 65, 8, 0, 1, 0, 7, 8, 20, 12, 14, 18, 10, 20, 17, 18, 19, 27, 24, 12, 4, 17, 12, NA, NA, NA, 0, NA, NA, 8, 138, 121, 111, 88, 160, 206, 161, 170, 157, 160, 111, 128, 112, 131, 126, 111, 97, 73, 86, 153, 124, 83, 130, 
+#> 117, 31, 129, 141, 53, 115, 63, 105, 155, 182, 172, 166, 156, 186, 70, 163, 145, 162, 176, 173, 175, 58, 23, 102, 51, 53, 34, 19, 12, 86, 149, 161, 174, 147, 154, 179, 103, 210, 178, 186, 129, 163, 198, 190, 195, 145, 131, 147, 117, 4, 23, 104, 181, 144, 124, 103, 154, 132, 65, 124, 55, 120, 120, 110, 89, 120, 54, NA, NA, NA, NA, NA, 0, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0, NA, 0, 3, 1, 3, 1, 0, 1, 0, 0, 0, 0, 0, 13, 4, 24, 114, 95, 127, 193, 127, 182, 219, 133, 205, 203, 166, 185, 140, 
+#> 62, 119, 169, 111, 150, 170, 140, 157, 200, 161, 106, 159, 171, 174, 54, 74, 158, 148, 10, 68, 15, 13, 106, 146, 109, 129, 152, 94, 57, 136, 11, 74, 71, 24, 3, 5, 135, 139, 141, 144, 112, 155, 100, 149, 87, 32, 102, 101, 45, 63, 41, 8, 39, 132, 136, 139, 169, 181, 184, 154, 114, 151, 169, 193, 174, 148, 158, 180, 114, 13, 149, 169, 148, 74, 22, 4, 0, 81, 116, 133, 148, 147, 141, 151, 186, 85, 90, 160, 162, 129, 110, 139, 81, 14, 58, 7, 79, 109, 17, 35, 114, 133, 120, 54, 161, 143, 159, 109, 92, 10, 
+#> NA, NA, NA, NA, 0, 0, NA, NA, NA, 0, NA, NA, 0, NA, NA, 112, 165, 102, 99, 156, 12, 1, 6, 2, 179, 166, 81, 130, 132, 101, 166, 169, 130, 63, 125, 97, 85, 35, 20, 0, 0, 21, 4, 2, NA, NA, 14, NA, 10, 11, 12, 12, 10, 0, 3, NA, NA, 3, 15, 7, 89, 104, 95, 81, 117, 138, 155, 104, 39, 86, 116, 98, 53, 41, 31, 52, 73, 139, 169, 141, 176, 151, 176, 147, 168, 177, 101, 141, 140, 78, 57, 104, 29, 135, 160, 168, 135, 44, 2, 125, 124, 23, 50, 100, 113, 85, 32, 106, 62, 78, 116, 113, 7, 6, 44, 40, 105, 153, 71, 
+#> 78, 109, 49, 147, 141, 118, 1, 33, 118, 121, 196, 168, 120, 158, 98, 38, 92, 17, 13, 84, 9, 6, 1, 6, 13, 4, 3, 1, 0, 3, 5, 7, 9, 10, 22, 9, 8, 8, 11, 17, NA, NA, NA, NA, NA, 3, 4, 1, 4, 4, 4, 2, 4, 1, 2, 1, 4, 0, 1, 2, 0, 0, 1, 1, 0, 4, 0, 7, 8, 3, NA, NA, NA, 0, NA, 10, 99, 157, 98, 129, 107, 143, 122, 83, 51, 36, 34, 1, 11, 43, 185, 230, 133, 194, 159, 163, 168, 170, 170, 155, 97, 89, 70, 107, 57, 5, 0, NA, 0, 0, NA, NA, NA, 0, NA, 0, 8, 120, 127, 168, 101, 126, 161, 174, 156, 159, 205, 145, 109, 
+#> 170, 93, 28, 132, 78, 60, 45, 34, 62, 8, 54, 126, 135, 113, 72, 47, 57, 107, 89, 13, 1, 11, 136, 68, 148, 136, 143, 145, 94, 163, 146, 175, 156, 125, 123, 110, 28, 62, 61, 62, 152, 124, 140, 100, 121, 134, 106, 148, 144, 182, 155, 162, 130, 157, 153, 157, 100, 31, 64, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0, 1, 0, 131, 29, 12, 1, 0, 0, 1, 0, NA, NA, NA, NA, 0, NA, NA, NA, 9, 63, 136, 158, 85, 138, 163, 137, 150, 84, 114, 91, 103, 126, 87, 19, 45, 4, 34, 36, 10, 61, 32, 68, 95, 87, 118, 142, 145, 
+#> 180, 97, 147, 115, 121, 99, 98, 27, 22, 118, 138, 145, 146, 168, 27, 110, 148, 173, 112, 145, 168, 122, 5, 59, 77, 39, 31, 7, 24, 11, 12, 15, 8, 23, 5, 15, 13, 4, 11, 13, 17, 1, 7, 4, 3, 2, 20, 63, 112, 144, 57, 68, 54, 25, 61, 56, 69, 71, 72, 42, 62, 17, 1, 0, 0, NA, NA, NA, NA, NA, 4, 8, 12, 4, 2, NA, 2, 3, 8, 3, 0, 0, 0, 3, 0, 0, 0, 3, 0, 10, 124, 151, 160, 139, 136, 150, 137, 140, 90, 141, 160, 121, 116, 70, 23, 0, 16, 16, 17, 15, 21, 24, 13, 8, 12, 21, NA, NA, 3, 8, 9, 3, 1, 15, 0, 42, 78, 97, 
+#> 78, 52, 34, 15, 0, 96, 179, 135, 143, 150, 147, 172, 160, 104, 169, 58, 90, 159, 126, 112, 104, 35, 77, 122, 112, 21, 79, 128, 138, 21, 77, 86, 40, 15, 0, 9, 9, 3, 0, 9, 6, 11, 10, 11, 4, 8, 3, 8, 1, NA, NA, NA, NA, NA, NA, NA, NA, 0, NA, 0, NA, 0, 1, 1, NA, NA, NA, 133, 188, 157, 134, 145, 92, 179, 111, 168, 160, 155, 185, 136, 1, 130, 2, 87, 51, 69, 175, 115, 125, 125, 171, 102, 112, 16, 100, 52, NA, NA, 0, 0, NA, NA, 0, NA, 0, NA, 0, 0, NA, NA, NA, NA, NA, NA, 5, 15, 59, 104, 175, 174, 162, 156, 
+#> 15, 184, 64, 40, 177, 140, 116, 32, 29, 34, 84, 103, 77, 99, 44, 67, 48, 18, 48, 68, 45, 25, 27, NA, NA, NA, 8, 12, 13, NA, NA, NA, NA, NA, 17, 24, 120, 106, 160, 91, 168, 178, 176, 185, 163, 167, 134, 131, 81, 57, 137, 10, 6, 5, 158, 211, 195, 181, 177, 157, 152, 166, 150, 210, 160, 165, 140, 144, 178, 166, 163, 113, 79, 114, 33, 180, 175, 138, 136, 210, 171, 175, 205, 160, 198, 134, 28, 6, 8, 10, 151, 63, 185, 161, 180, 169, 119, 7, 55, 2, 0, 42, 103, 135, 146, 97, 122, 91, 173, 104, 147, 104, 
+#> 131, 106, 2, 82, 95, 168, 87, 132, 153, 127, 120, 16, 11, 1, 20, 10, 19, 3, 24, 2, 9, 5, 4, 1, 3, 9, 15, 9, 6, NA, 7, 0, 4, 2, 0, 0, NA, NA, NA, NA, NA, NA, NA, NA, NA, 29, 12, 43, 45, 111, 136, 150, 94, 139, 82, 30, 17, 104, 26, 33, 0, 0, 0, 0, NA, NA, NA, 0, 0, 0, NA, NA, NA, NA, NA, 0, 0, 5, 101, 57, 182, 158, 126, 115, 25, 146, 42, 27, 152, 142, 97, 39, 5, 57, 12, 4, 11, 13, 11, 10, 8, 12, 13, 8, 11, 12, 7, 2, NA, NA, NA, 0, 0, 0, NA, 0, NA, NA, NA, NA, NA, NA, NA, 3, 0, 4, 8, 2, 26, 38, 37, 
+#> 5, 61, 114, 88, 95, 54, 88, 80, 76, 92, 68, 25, 42, 27, 25, 34, 1, NA, 0, NA, NA, 0, 0, 4, 6, 0, 10, 15, 5, 13, 9, NA, NA, NA, 1, 13, 9, 10, 12, 1, 172, 165, 200, 186, 178, 154, 163, 176, 188, 170, 186, 141, 53, 135, 118, 9, 63, 147, 163, 156, 136, 147, 82, 133, 110, 129, 107, 99, 55, 33, 69, 34, 11, 4, 125, 172, 166, 216, 127, 177, 164, 47, 31, 168, 155, 141, 143, 44, 57, 95, 90, 68, 68, 2, 24, 13, 175, 163, 100, 179, 154, 62, 26, 59, 145, 144, 65, 0, 0, 1, 1, 2, 0, 0, NA, 0, 2, NA, NA, 7, 132, 
+#> 100, 87, 63, 19, 44, 58, 51, 10, 68, 9, 108, 131, 109, 123, 151, 146, 107, 150, 134, 37, 14, 22, 24, 53, 3, 73, 16, 118, 210, 203, 240, 207, 200, 214, 205, 187, 181, 133, 169, 125, 149, 156, 103, 122, 88, 89, 88, 115, 170, 166, 151, 149, 167, 113, 111, 107, 68, 25, 182, 163, 173, 163, 174, 44, 129, 184, 153, 112, 5, 31, 63, 115, 166, 156, 127, 139, 114, 128, 60, 85, 84, 40, 6, 80, 78, 92, 42, 81, 133, 173, 178, 161, 185, 109, 157, 189, 187, 163, 133, 88, 16, 19, 68, 26, 137, 177, 6, 63, 69, 14, 68, 
+#> 118, 141, 136, 68, 66, 42, 75, 107, 85, 132, 136, 93, 102, 94, 117, 75, 26, 2, 5, 8, 1, 1, 6, 9, 9, 5, 4, 1, 6, NA, 3, NA, 0, 1, 95, 179, 183, 192, 184, 194, 175, 116, 148, 131, 163, 162, 127, 102, 143, 57, 87, 93, 29, 3, 24, 17, 0, 0, 1, 1, 1, 0, 0, 0, NA, NA, NA, 0, 0, 0, NA, 0, NA, NA, NA, 0, 0, 9, 46, 95, 74, 91, 150, 167, 118, 135, 157, 54, 82, 109, 11, 105, 91, 59, 1, 0, 2, 4, 0, 0, 1, 5, 0, 0, 0, 0, NA, NA, 4, 3, 92, 51, 149, 119, 73, 63, 48, 32, 8, 10, 3, 5, 5, 0, 0, 15, 6, 11, 10, NA, NA, 
+#> 4, 161, 166, 130, 171, 141, 152, 140, 102, 26, 14, 21, 7, 14, 16, 8, 14, 15, 19, 14, 2, NA, 0, 0, 1, 0, 0, 0, 55, 94, 213, 197, 211, 218, 163, 203, 177, 168, 165, 175, 165, 197, 159, 220, 148, 139, 41, 33, 1, 2, 20, 18, 7, 1, 15, 9, 22, 13, 28, 14, 25, NA, 0, 6, 2, 79, 207, 211, 238, 186, 186, 191, 101, 169, 184, 154, 113, 132, 2, 11, 3, NA, 6, 0, NA, NA, 0, 0, NA, NA, NA, NA, 0, NA, NA, 3, 5, 10, 1, 4, 0, 0, 0, 0, 1, 25, 90, 114, 139, 82, 96, 114, 101, 61, 26, 6, 2, 50, 160, 156, 143, 148, 112, 
+#> 177, 152, 159, 185, 130, 120, 106, 116, 87, 45, 37, 0, 0, 0, 0, 1, 1, 0, 2, 1, 0, NA, 0, NA, 0, 0, NA, 0, NA, 134, 137, 156, 148, 151, 144, 143, 8, 128, 105, 103, 131, 120, 73, 1, 56, 26, 170, 139, 180, 160, 143, 145, 71, 63, 104, 105, 84, 47, 13, 1, 38, 30, 177, 167, 198, 188, 165, 182, 149, 159, 160, 89, 25, 110, 114, 147, 159, 163, 104, 113, 164, 145, 151, 85, 66, 48, 14, 125, 80, 165, 167, 173, 198, 169, 148, 166, 107, 49, 25, 93, 144, 121, 130, 96, 115, 154, 39, 97, 88, 111, 23, 59, 13, 11, 
+#> 18, 97, 192, 163, 179, 150, 151, 78, 30, 2, 55, 110, 131, 101, 154, 180, 141, 134, 80, 13, 161, 25, 118, 30, 15, NA, NA, NA, NA, NA, 16, 13, 11, 7, 0, 5, 0, 7, 1, 10, 144, 142, 179, 164, 173, 86, 36, 3, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, 1, 0, 0, 0, 0, 2, 0, 12, 12, 2, 1, 0, 1, 3, 7, 8, 6, 11, 12, 10, 6, 10, 7, 0, 5, 117, 143, 154, 138, 171, 150, 141, 125, 132, 144, 103, 9, 72, 94, 134, 143, 126, 41, 81, 57, 0, 22, 97, 98, 91, 156, 170, 155, 114, 106, 16, 117, 64, 13, 165, 199, 223, 
+#> 207, 234, 215, 164, 195, 210, 184, 139, 169, 9, 63, 163, 213, 186, 186, 147, 175, 152, 171, 39, 108, 102, 94, 117, 156, 159, 18, 18, 46, 109, 138, 134, 112, 132, 106, 2, 57, 39, 2, NA, NA, 0, 0, NA, NA, NA, NA, NA, NA, NA, NA, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 29, 144, 162, 187, 61, 132, 152, 90, 17, 59, 121, 121, 104, 91, 138, 120, 27, 56, 66, 13, 95, 152, 145, 152, 156, 82, 40, 110, 20, 12, 41, 106, 138, 61, 80, 97, 137, 169, 70, 57, 2, 5, 59, 72, 60, 121, 147, 119, 31, 69, 55, 3, 21, 10, 23, NA, 
+#> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0, 0, 3, 13, 9, NA, NA, NA, 1, NA, 0, 1, 2, 2, 5, 1, 0, 0, 0, 1, 2, NA, 0, 1, 0, NA, NA, NA, NA, NA, 11, NA, NA, NA, 0, NA, NA, NA, NA, NA, 2, 1, 85, 134, 138, 167, 99, 162, 103, 187, 199, 172, 78, 149, 33, 102, 28, 61, 0, 5, 71, 102, 92, 60, 72, 97, 75, 25, 1, 39, 24, 39, 30, 115, 139, 129, 130, 118, 67, 61, 19, 88, 22, 119, 48, 148, 49, 77, 32, 142, 188, 137, 67, 201, 164, 10, 171, 123, 164, 190, 194, 119, 216, 195, 211, 155, 142, 225, 164, 
+#> 141, 3, 10, 119, 46, 3, 39, 72, 144, 155, 122, 95, 141, 88, 41, 144, 120, 10, 161, 143, 113, 123, 97, 125, 28, 34, 87, 132, 104, 44, 152, 145, 72, 56, 18, 164, 122, 109, 93, 155, 97, 108, 92, 76, 127, 83, 9, 87, 66, 125, 133, 112, 48, 6, 11, 8, 133, 96, 67, 30, 57, 122, 86, 54, 23, 6, 2, 18, 191, 175, 157, 178, 153, 76, 49, 119, 161, 29, 32, 60, 42, 48, 6, 48, 27, 9, NA, 0, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0, NA, 5, 6, 5, 10, 7, 5, 1, 7, 4, 13, 6, 2, 12, NA, 4, NA, NA, 0, NA, NA, NA, NA, 
+#> NA, NA, NA, 6, 7, 11, 0, NA, 0, 0, 0, NA, 0, 0, 0, 0, 0, NA, 5, 111, 93, 124, 95, 125, 122, 111, 105, 113, 140, 111, 102, 96, 0, 10, 15, 17, 19, 11, 14, 0, 8, 15, 26, 9, NA, NA, 0, 10, 9, 0, 12, 3, 15, 99, 146, 169, 184, 162, 160, 113, 122, 48, 1, 12, 168, 118, 156, 96, 181, 159, 163, 109, 121, 151, 65, 157, 127, 42, 108, 81, 88, 110, 113, 165, 169, 113, 140, 130, 199, 100, 92, 10, 52, 3, 0, 84, 96, 143, 145, 134, 155, 135, 60, 42, 75, 46, 0, 2, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
+#> 0, 0, 12, 113, 55, 118, 30, 67, 133, 106, 111, 146, 106, 97, 63, 50, 146, 79, 153, 175, 84, 143, 66, 18, 2, 32, 8, 153, 188, 183, 183, 158, 186, 173, 172, 201, 25, 154, 138, 139, 82, 34, 0, 27, 96, 58, 99, 64, 45, 10, 10, 10, 11, 135, 192, 178, 181, 163, 42, 170, 88, 143, 87, 14, 87, 168, 184, 147, 148, 82, 79, 174, 133, 155, 190, 191, 169, 149, 45, 57, 76, 82, 3, 63, 46, 140, 160, 173, 175, 174, 109, 133, 117, 79, 103, 171, 167, 27, 56, 19, 61, 37, 0, 1, 3, NA, NA, 7, 18, 5, 2, 0, NA, NA, NA, 0, 
+#> NA, 45, 107, 174, 111, 185, 140, 162, 121, 119, 158, 154, 71, 166, 171, 124, 40, 124, 68, 100, 4, 7, 0, 70, 46, 74, 88, 75, 101, 106, 120, 100, 101, 31, 15, 0, 2, 7, 1, NA, NA, 0, NA, NA, 0, NA, 0, NA, 0, NA, NA, NA, NA, NA, 117, 163, 162, 196, 177, 170, 154, 139, 128, 137, 124, 128, 169, 76, 77, 59, NA, NA, NA, NA, NA, 13, 8, 2, 2, 3, 2, 5, 9, 5, 3, 1, 1, 31, 146, 132, 161, 163, 159, 148, 140, 135, 92, 86, 46, 17, 93, 108, 132, 110, 16, 66, 56, 1, 1, 4, 6, 3, 1, 2, 5, 2, 0, NA, NA, 0, NA, 1, 0, 
+#> 0, NA, 1, 10, 13, 8, 8, 18, 9, 4, 1, 4, NA, 0, 0, 0, 0, 3, 6, 4, 8, 7, 3, 5, 1, 1, 3, 91, 48, 82, 127, 158, 152, 95, 103, 110, 101, 28, 37, 9, 29, 3, 8, NA, NA, NA, 0, NA, NA, 0, NA, 0, NA, NA, NA, NA, NA, NA, 0, NA, 0, 0, 0, 0, NA, 0, NA, 0, 0, NA, 1, 0, 0, 0, 139, 103, 59, 7, 0, 21, 47, 16, 20, 11, 1, 73, 151, 148, 167, 147, 152, 79, 83, 135, 148, 182, 156, 160, 164, 157, 48, 109, 143, 74, 13, 20, 53, 43, 41, 74, 106, 99, 132, 125, 128, 84, 102, 121, 4, 101, 169, 156, 194, 170, 203, 28, 139, 147, 
+#> 114, 56, 70, 35, 93, 22, 10, 16, 14, 100, 113, 48, 35, 75, 39, 5, 49, 14, 88, 94, 54, 147, 114, 164, 144, 146, 78, 56, 48, 33, 26, 114, 153, 161, 170, 175, 139, 167, 174, 191, 210, 188, 101, 180, 146, 166, 178, 156, 135, 130, 0, NA, 0, NA, NA, NA, NA, NA, NA, NA, NA, 0, 0, 0, 0, 0, 0, 3, 65, 145, 85, 143, 131, 143, 128, 23, 4, 92, 141, 86, 119, 28, 37, 9, 32, 46, 54, 52, 34, 1, 40, 108, 167, 142, 90, 21, 139, 116, 75, 27, 146, 40, 33, 1, 5, 3, 17, 10, 12, 7, 4, 9, 8, 13, NA, NA, NA, 0, NA, NA, 0, 
+#> NA, 7, 13, 8, 18, 15, 14, 6, 14, 14, 10, 0, 0, 1, 3, 28, 80, 158, 158, 162, 108, 102, 18, 0, 4, 129, 40, 75, 58, 84, 61, 110, 146, 96, 42, 103, 54, 48, 31, 52, 35, 35, 10, 20, 3, 152, 159, 121, 174, 119, 60, 137, 48, 74, 211, 123, 102, 45, 110, 135, 123, 156, 52, 6, 120, 179, 179, 174, 180, 140, 67, 165, 185, 180, 173, 141, 104, 52, 41, 76, 148, 108, 146, 34, 88, 83, 18, 92, 144, 152, 144, 156, 149, 147, 181, 122, 149, 159, 155, 167, 93, 147, 156, 149, 133, 135, 12, 99, 94, 4, 5, 19, 17, 12, 18, 
+#> 15, 15, 14, 11, 10, 7, 18, 11, 15, 12, 11, 10, 11, 13, 4, 5, 9, 1, 5, 2, 9, 7, 27, 140, 142, 122, 8, 105, 67, 97, 72, 21, 0, 0, 0, 0, 2, 1, NA, NA, 0, 0, 2, 1, 0, 1, 5, 1, 1, 0, 0, 0, 0, 0, 0, NA, 0, NA, NA, NA, NA, NA, NA, 0, NA, 12, 124, 109, 124, 158, 110, 104, 45, 163, 151, 123, 66, 84, 92, 106, 23, 13, 47, 40, 159, 163, 145, 153, 110, 120, 97, 52, 94, 92, 5, 46, 32, 59, 171, 158, 120, 170, 119, 95, 122, 157, 136, 190, 102, 112, 56, 33, 34, 80, 80, 11, 93, 127, 94, 122, 105, 102, 115, 91, 77, 
+#> NA, NA, NA, NA, 2, 8, 10, 14, 14, 22, 10, 3, 0, 2, 2, 11, 10, 7, 17, 19, 14, 10, 14, 22, 14, 17, 9, 10, 8, 7, 8, 11, 13, 9, 12, 2, 145, 184, 168, 188, 177, 192, 120, 155, 193, 137, 166, 182, 189, 193, 157, 64, 69, 34, 11, 8, 123, 172, 167, 145, 113, 145, 168, 48, 155, 177, 109, 108, 115, 24, 71, 37, 9, 55, 12, 61, 121, 121, 85, 66, 47, 110, 11, 35, NA, 0, NA, 0, NA, NA, NA, NA, NA, NA, 0, 16, 160, 153, 174, 165, 147, 136, 159, 102, 141, 131, 96, 95, 74, 4, 17, 13, 12, 5, 11, 11, 0, 0, 2, 1, NA, 0, 
+#> NA, NA, 0, NA, 0, 0, 0, 159, 178, 167, 139, 179, 197, 178, 160, 176, 113, 130, 63, 163, 160, 171, 147, 130, 179, 162, 164, 171, 183, 173, 166, 168, 152, 25, 63, 178, 185, 174, 141, 152, 184, 184, 155, 148, 191, 15, 132, 146, 65, 23, 126, 147, 49, 10, 9, 67, 128, 200, 155, 168, 158, 147, 174, 164, 153, 118, 141, 158, 143, 70, 31, 22, 146, 46, 174, 141, 141, 166, 113, 103, 115, 92, 134, 19, 87, 44, 21, 81, 6, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2, 74, 109, 129, 108, 149, 192, 187, 186, 199, 126, 
+#> 136, 128, 152, 176, 139, 164, 141, 89, 21, 82, 24, 106, 27, 144, 160, 182, 169, 185, 193, 120, 180, 181, 177, 184, 183, 143, 142, 75, 27, 46, 160, 134, 134, 133, 110, 107, 78, 7, 26, 8, 101, 141, 159, 130, 127, 151, 75, 208, 165, 166, 97, 174, 161, 129, 35, 42, 91, 2, 7, 12, 7, 12, 13, 6, 6, 17, 18, 10, 17, 0, 0, 0, 0, 10, 8, 5, 0, 0, 1, 168, 87, 16, 73, 76, 24, 1, 140, 153, 108, 164, 158, 167, 150, 176, 146, 103, 142, 96, 20, 16, 9, 41, 147, 167, 181, 32, 93, 182, 163, 179, 179, 169, 180, 144, 91, 
+#> 146, 128, 9, 26, 144, 152, 166, 116, 104, 170, 158, 193, 183, 133, 173, 78, 96, 35, 0, 69, 144, 175, 182, 122, 156, 165, 163, 160, 82, 184, 88, 86, 19, 91, 143, 34, 184, 69, 76, 89, 69, 163, 111, 37, 95, 165, 163, 160, 151, 190, 166, 170, 45, 131, 94, 74, 1, 21, 31, 25, 30, 74, 123, 56, 131, 131, 77, 85, 2, 33, 71, NA, NA, NA, NA, NA, NA, 12, 5, 104, 88, 158, 180, 132, 61, 14, 102, 74, 15, 4, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0, NA, NA, NA, 0, 0, 1, NA, 0, NA, 0, NA, 0, 
+#> 0, 0, 42, 62, 99, 71, 116, 124, 73, 4, 33, 13, 26, 22, 47, 38, 6, 3, 3, 2, 2, 12, 10, 23, 15, 164, 185, 160, 149, 210, 164, 169, 140, 151, 135, 91, 48, 68, 94, 76, 123, 141, 49, 96, 85, 63, 98, 142, 143, 78, 144, 161, 158, 166, 191, 176, 156, 160, 61, 165, 154, 171, 126, 59, 47, 95, 42, 36, 149, 110, 126, 132, 122, 129, 115, 154, 27, 75, 48, 1, 29, 42, 2, 40, 85, 119, 79, 95, 18, 34, 76, 72, 41, 19, 74, 149, 180, 188, 137, 142, 207, 146, 147, 161, 145, 99, 95, 176, 157, 29, 5, 27, 46, 70, 148, 164, 
+#> 167, 187, 117, 139, 132, 167, 138, 170, 151, 106, 8, 21, 3, 95, 116, 130, 200, 114, 143, 109, 154, 197, 173, 161, 173, 166, 145, 46, 64, 50, NA, NA, NA, 1, 10, 11, 3, 7, 11, 14, 10, 5, 8, 5, 11, 15, 3, 1, 0, 1, 1, 0, 0, 0, NA, NA, NA, NA, NA, 0, 0, 0, 0, 0, 14, 146, 107, 177, 166, 172, 139, 94, 165, 108, 138, 145, 47, 56, 16, 174, 129, 150, 184, 201, 5, 42, 137, 162, 156, 151, 134, 67, 121, 100, 113, 85, 81, 171, 205, 200, 139, 175, 113, 16, 131, 136, 13, 20, 52, 71, 20, 40, 10, 59, 57, 30, 47, 45, 
+#> 43, 129, 87, 107, 107, 78, 25, 45, 82, 120, 41, 26, 49, 4, 130, 152, 172, 147, 173, 187, 174, 200, 181, 157, 60, 127, 123, 116, 43, 78, 192, 73, 104, 194, 86, 67, 35, NA, 2, 12, 18, 14, 9, 6, NA, NA, NA, NA, NA, NA, 0, 0, 1, 1, 0, 1, 8, 55, 74, 132, 116, 40, 78, 77, 18, 23, 157, 113, 65, 46, 19, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 11, 88, 35, 61, 86, 32, 25, 133, 153, 188, 191, 162, 152, 105, 144, 65, 67, 49, 93, 4, 28, 30, 3, 1, 96, 138, 143, 94, 152, 157, 182, 161, 170, 133, 158, 176, 137, 
+#> 104, 112, 17, NA, NA, NA, NA, 7, 9, 9, 3, 15, 17, 5, 3, 8, 0, 13, 0, 38, 118, 122, 147, 57, 160, 91, 58, 39, 98, 67, 4, 39, 121, 13, 6, 5, 23, 174, 144, 146, 175, 98, 79, 129, 116, 163, 123, 143, 20, 146, 102, 103, 28, 57, 8, 1, 1, NA, NA, NA, NA, 0, NA, NA, NA, NA, 2, 1, 12, 13, 8, 12, 7, 10, 0, 1, 1, 7, 2, 2, 101, 49, 157, 148, 149, 108, 156, 152, 70, 104, 90, 113, 101, 9, 0, 50, 15, 149, 131, 145, 149, 142, 115, 159, 178, 141, 114, 78, 63, 38, 43, 5, 79, 84, 104, 25, 75, 107, 84, 44, 117, 53, 
+#> 82, 72, 9, 54, 119, 170, 177, 145, 103, 167, 195, 146, 154, 156, 151, 136, 145, 148, 111, 59, 90, 105, 17, 57, 83, 160, 122, 165, 207, 166, 205, 147, 167, 126, 15, NA, NA, 0, NA, NA, NA, NA, 0, NA, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, NA, NA, NA, NA, 0, 0, NA, 0, NA, NA, NA, 0, NA, 0, 142, 176, 93, 111, 121, 49, 123, 116, 7, 6, 10, 11, 1, 8, 12, 0, 1, 4, 9, 3, 0, 0, 9, 78, 149, 170, 184, 168, 174, 154, 162, 152, 185, 175, 162, 144, 143, 109, 74, 102, 18, 61, 1, 51, 130, 95, 155, 156, 176, 145, 
+#> 114, 9, 12, 50, 1, 4, 86, 43, 163, 191, 186, 206, 169, 73, 120, 20, 126, 150, 158, 125, 4, 59, 12, 29, 89, 106, 111, 167, 147, 197, 198, 173, 219, 177, 33, 136, 112, 27, 20, 124, 64, 68, 156, 128, 151, 136, 161, 198, 180, 193, 189, 160, 144, 121, 84, 104, 25, 24, 41, 86, 142, 157, 142, 129, 137, 150, 153, 146, 154, 139, 40, 141, 119, 123, 86, 4, 78, 21, 50, 26, 15, 15, 79, 162, 131, 146, 184, 51, 155, 152, 148, 123, 150, 123, 90, 92, 64, 16, 6, 62, NA, NA, NA, NA, NA, NA, 1, 0, 3, 0, 1, 3, 0, 0, 
+#> 0, 0, 0, 1, 3, 2, 7, 4, 13, 5, 4, NA, 4, 0, 2, 0, 8, 104, 136, 105, 148, 72, 79, 129, 136, 79, 116, 126, 129, 116, 80, 80, 23, 76, 73, 152, 118, 173, 168, 167, 169, 202, 165, 166, 204, 117, 147, 121, 118, 32, 52, 154, 162, 184, 163, 154, 163, 168, 192, 182, 171, 181, 131, 40, 114, 35, 97, NA, NA, NA, NA, NA, NA, 0, 0, 1, 8, 0, 0, 0, 0, 5, 13, 43, 56, 45, 99, 132, 153, 100, 123, 153, 131, 59, 59, 92, 10, 6, 6, 68, 105, 138, 122, 139, 78, 138, 117, 81, 150, 183, 110, 74, 12, 3, 1, 0, 1, 0, 1, NA, 0, 
+#> 1, 0, 0, 0, 1, 1, 2, 0, 1, 3, 0, 0, 0, 0, 0, 0, 0, 0, 12, 183, 190, 203, 219, 201, 191, 191, 156, 188, 202, 214, 206, 179, 212, 179, 162, 216, 12, 149, 24, 139, 73, 47, 74, 54, 61, 43, 88, 34, 58, 47, 6, 68, 18, 37, 11, 33, 215, 176, 213, 143, 175, 201, 187, 181, 172, 194, 166, 183, 154, 127, 141, 103, 126, 38, 131, 34, 132, 62, 116, 184, 132, 42, 129, 128, 180, 168, 139, 105, 14, 99, 39, 26, 2, NA, NA, NA, 0, 1, 0, 0, 1, 1, 4, 5, 12, 0, 0, 1, 1, 1, 0, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 7, 5, 
+#> 6, 6, 3, 4, 8, 1, 5, 0, 0, 0, 1, 0, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 7, 6, 8, 0, 0, 0, 0, 0, 0, 0, 6, 4, 1, 6, 1, 18, 61, 178, 154, 191, 203, 163, 176, 139, 172, 181, 156, 183, 183, 163, 164, 149, 146, 142, 98, 129, 77, 124, 134, 25, 114, 117, 37, 10, 1, 5, 16, 13, 4, 21, 24, 15, 14, 20, 20, 2, 12, 16, 4, 1, 5, 3, 9, 10, 0, 0, NA, NA, NA, 1, 2, NA, 0, 0, 0, 0, 0, 0, 0, 0, 21, 209, 195, 190, 197, 24, 197, 198, 50, 49, 65, 142, 122, 43, 45, 33, 159, 174, 113, 144, 160, 97, 57, 
+#> 160, 157, 46, 154, 104, 107, 37, 108, 134, 61, 72, 15, 23, 118, 108, 86, 152, 174, 176, 149, 155, 147, 165, 134, 130, 120, 73, 40, 16, 123, 104, 91, 90, 182, 98, 91, 65, 160, 79, 48, NA, 0, 0, 8, 9, 2, 10, 11, 11, 6, 7, 0, 11, 12, 0, NA, NA, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, NA, NA, NA, NA, NA, NA, NA, NA, 4, NA, NA, NA, 1, 0, 1, 0, 0, 1, 6, 1, 0, 1, 4, 4, 16, 19, 53, 77, 102, 130, 97, 159, 117, 108, 123, 25, 68, 122, 137, 121, 99, 155, 153, 116, 206, 169, 183, 149, 9, 63, 23, 92, 
+#> 158, 163, 199, 157, 148, 165, 149, 154, 148, 127, 33, 60, 64, 47, 46, NA, NA, NA, NA, NA, 5, 7, 5, 0, 0, 1, 0, 0, 1, 0, NA, NA, 0, 0, NA, NA, NA, 0, NA, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 29, 168, 129, 166, 143, 121, 38, 4, 61, 5, 7, 10, 9, 12, 10, 6, 2, 3, 0, 0, 0, 0, 0, 0, 0, 39, 72, 68, 77, 7, 23, 139, 161, 146, 120, 146, 68, 20, 53, 64, 44, 54, 85, 2, 50, 124, 127, 84, 40, 163, 52, 87, 159, 147, 134, 48, 0, 12, 30, 84, 132, 114, 152, 94, 88, 105, 29, 78, 156, 135, 117, 113, 41, 7, NA, NA, 
+#> NA, 0, NA, NA, 0, NA, NA, 9, 9, 17, 5, 5, 3, 5, 10, 0, 1, 0, 1, 0, 0, 0, 0, 1, 3, 5, 8, 0, 3, 109, 118, 123, 175, 190, 164, 184, 166, 171, 157, 166, 118, 29, 130, 87, 34, 167, 132, 96, 111, 23, 54, 21, 12, 42, 112, 80, 153, 108, 28, 133, 159, 129, 103, 57, 18, 2, 82, 197, 151, 165, 111, 167, 185, 165, 45, 63, 134, 64, 2, 139, 185, 176, 188, 181, 180, 189, 179, 169, 117, 106, 133, 173, 160, 129, 84, 125, 111, 4, 40, 41, 50, 77, 4, 3, 25, 95, 39, 8, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 
+#> 16, 194, 92, 189, 174, 160, 86, 74, 155, 140, 153, 172, 100, 56, 102, 54, 147, 164, 94, 132, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 28, 15, 132, 136, 155, 156, 196, 160, 140, 172, 123, 157, 139, 139, 162, 28, 93, 96, 163, 155, 191, 176, 111, 151, 133, 150, 102, 5, 6, 5, 98, 202, 193, 197, 184, 206, 130, 206, 165, 200, 186, 164, 113, 178, 163, 0, 0, 7, 10, 10, 16, 23, 20, 23, 22, 11, 11, 8, 5, 12, 0, 2, 14, 5, NA, NA, 0, NA, NA, NA, NA, NA, 1, 0, 1, 0, 0, 1, 2, 1, 0, 1, 1, 9, 4, 5, 2, 2, NA, NA, NA, 
+#> 0, 11, 6, 10, 0, 0, 0, 1, 9, 1, 0, 2, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, NA, NA, NA, NA, NA, NA, NA, 0, 15, 13, 12, NA, 4, 6, 0, 82, 62, 50, 179, 193, 100, 69, 123, 38, 141, 145, 170, 129, 172, 126, 59, 161, 159, 148, 240, 163, 177, 65, 146, 166, 21, 77, 89, 26, NA, 0, 0, NA, NA, NA, NA, NA, 0, 0, 3, 0, 2, 0, 2, 0, 0, 1, 1, 0, 0, 12, 41, 64, 78, 76, 35, 109, 83, 77, 111, 95, 107, 37, 7, 91, 177, 193, 187, 114, 48, 131, 84, 23, 74, 157, 60, 13, 11, 26, 167, 185, 216, 197, 182, 209, 190, 163, 165, 
+#> 178, 79, 177, 102, 127, 57, 99, 45, 156, 152, 166, 181, 170, 178, 176, 134, 55, 113, 113, 60, 113, 7, 52, 43, 34, 20, 34, 8, 27, 46, 134, 121, 131, 27, 97, 145, 156, 148, 196, 181, 195, 150, 156, 160, 119, 149, 123, 0, 2, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 134, 89, 175, 194, 157, 175, 196, 157, 51, 165, 115, 27, 50, 126, 6, 36, 132, 160, 147, 142, 79, 52, 139, 136, 101, 147, 5, 99, 0, 1, 47, 96, 93, 145, 134, 137, 135, 122, 124, 129, 171, 
+#> 45, 109, 95, 81, 22, 151, 188, 185, 181, 189, 192, 59, 92, 177, 216, 178, 144, 98, 84, 133, 171, 146, 161, 156, 128, 166, 194, 168, 172, 175, 164, 136, 115, 67, 75, 5, 75, 6, 166, 122, 146, 23, 70, 66, 89, 46, 79, 6, 14, 88, 139, 159, 161, 166, 131, 168, 117, 82, 22, 3, 26, 42, 78, 64, 17, 7, 1, 98, 83, 139, 145, 144, 130, 135, 114, 84, 148, 138, 108, 136, 42, 14, 34, 0, 4, 98, 94, 147, 162, 145, 141, 100, 155, 172, 153, 135, 161, 152, 167, 184, 157, 125, 242, 208, 212, 262, 206, 224, 238, 213, 225, 
+#> 214, 184, 73, 105, 136, 102, 91, 10, 31, 74, 157, 89, 198, 41, 146, 191, 168, 65, 26, 41, 82, 96, 56, 27, 113, 111, 126, 139, 98, 115, 103, 100, 100, 101, 82, 47, 28, 14, 4, 73, 97, 100, 173, 148, 186, 67, 96, 139, 171, 192, 186, 70, 116, 130, 79, 28, 0, 0, 49, 84, 10, 28, 48, 126, 123, 71, 114, 148, 95, 62, 56, 115, 51, 28, NA, NA, NA, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 194, 185, 212, 196, 195, 177, 185, 187, 186, 183, 173, 173, 101, 172, 147, 4, 120, 94, 162, 107, 76, 54, 131, 142, 146, 
+#> 206, 192, 198, 151, 176, 98, 157, 159, 129, 89, 9, 76, 28, 110, 157, 138, 206, 138, 140, 35, 63, 120, 132, 83, 115, 26, 0, 1, 0, 0, 0, 9, 7, 1, 0, 0, NA, 0, 0, 0, 0, 0, 0, 0, 0, 1, 26, 159, 129, 148, 121, 130, 125, 123, 61, 95, 153, 85, 89, 44, 0, 70, 107, 38, 97, 16, 2, 18, 11, 12, 43, 27, 0, 0, 0, 0, 0, 1, 0, 7, 6, 6, 6, 0, 4, 5, 0, 0, 26, 133, 85, 105, 115, 93, 121, 123, 137, 155, 130, 52, 42, NA, 0, NA, 0, 0, 1, 1, 0, 6, 0, 0, 0, 0, 20, 85, 149, 167, 166, 204, 177, 203, 199, 214, 152, 179, 199, 
+#> 108, 63, 77, 45, 0, 0, 0, 0, 0, 0, 0, 158, 109, 140, 125, 23, 52, 38, 94, 19, 27, 72, 55, 26, 9, 4, 19, 12, 17, 6, 8, 2, 0, 0, 1, 9, 154, 209, 198, 170, 171, 179, 173, 127, 115, 128, 116, 147, 92, 56, 50, 5, 120, 173, 189, 183, 188, 185, 194, 195, 201, 133, 163, 152, 124, 163, 133, 28, 0, 0, 0, 0, 0, 0, 1, 0, 1, 10, 6, 7, 9, 12, 8, 9, 2, 0, 0, 2, 1, 7, 7, 9, 3, 2, 0, 1, 0, 0, 1, 0, 1, 7, NA, 0, 0, 0, 0, 1, 0, 0, 0, 2, 0, 0, 13, 9, 9, 0, 2, 4, 6, 0, 0, 0, 0, 0, 0, 0, 0, 14, 106, 45, 134, 158, 157, 
+#> 146, 168, 199, 50, 180, 181, 163, 37, 105, 82, 34, 43, 63, 31, 147, 180, 141, 185, 187, 164, 132, 173, 106, 59, 73, 147, 58, 49, 49, 89, 84, 146, 158, 114, 135, 132, 43, 3, 47, 52, 60, 6, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 16, 17, 163, 134, 164, 111, 1, 52, 3, 4, 14, 15, 24, 11, 18, 0, 0, 1, 0, 12, 66, 114, 157, 120, 150, 62, 94, 2, 171, 113, 153, 27, 23, 0, 30, 167, 215, 146, 167, 185, 143, 128, 164, 161, 110, 56, 99, 42, 45, 150, 200, 155, 190, 158, 121, 85, 134, 172, 72, 4, 78, 137, 156, 165, 
+#> 136, 175, 118, 163, 191, 115, 129, 52, 64, 49, 174, 118, 168, 144, 96, 7, 11, 8, 8, 14, 12, 4, 4, 5, 3, 5, 11, 19, 10, 0, 6, 1, 0, 16, 77, 0, 117, 71, 112, 129, 175, 180, 160, 182, 110, 129, 140, 162, 103, 160, 136, 144, 0, 0, 1, 1, 3, 1, 0, 2, 11, 7, 11, 3, 36, 102, 140, 193, 114, 17, 30, 47, 34, 109, 99, 109, 6, 38, 2, 27, 0, 130, 92, 82, 79, 132, 53, 2, 35, 23, 2, 116, 183, 163, 133, 54, 111, 142, 90, 109, 32, 42, 137, 153, 194, 177, 66, 85, 108, 69, 178, 154, 146, 113, 8, 95, 100, 5, 58, 56, 
+#> 109, 130, 109, 187, 168, 171, 128, 146, 117, 90, 29, 9, 46, 147, 167, 181, 169, 74, 71, 107, 149, 178, 182, 188, 108, 13, 43, 120, 137, 170, 99, 111, 28, 58, 185, 208, 113, 181, 132, 73, 42, 42, 148, 148, 126, 151, 134, 200, 154, 166, 164, 148, 119, 189, 144, 194, 199, 178, 163, 68, 2, 11, 145, 93, 125, 123, 9, 5, 47, 155, 183, 182, 170, 176, 173, 173, 168, 69, 94, 171, 180, 165, 146, 127, 5, 48, 33, 87, 133, 143, 201, 151, 148, 141, 83, 71, 24, 48, 9, 43, 12, 1, 16, 31, 151, 156, 164, 173, 104, 
+#> 156, 163, 177, 142, 105, 151, 171, 163, 159, 114, 43, 15, 89, 120, 121, 107, 83, 158, 72, 140, 126, 103, 126, 122, 55, 1, 0, 1, 6, 6, 5, 0, 4, 4, 7, 4, 9, 5, 9, 1, 1, 5, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 1, 1, 5, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 2, 8, NA, 0, 0, 0, 1, 1, 5, 5, 9, 0, 0, 11, 8, 11, 1, 53, 127, 132, 125, 166, 152, 124, 156, 133, 98, 27, 26, 1, 56, 130, 111, 51, 124, 123, 137, 132, 87, 111, 93, 76, 26, 49, 9, 10, 7, 10, 13, 10, 8, 15, 6, 4, 4, 3, 0, 2, 0, 0, 0, 0, 0, 
+#> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 11, 90, 182, 142, 153, 172, 152, 141, 57, 76, 127, 107, 2, 32, 112, 113, 149, 91, 52, 13, 15, 7, 127, 58, 118, 99, 47, 131, 117, 115, 54, 30, 19, 3, 84, 177, 198, 195, 188, 180, 198, 180, 197, 205, 193, 191, 145, 144, 172, 150, 130, 181, 180, 164, 111, 76, 190, 137, 183, 149, 161, 74, 71, 0, 1, 5, 1, 21, 27, 14, 10, 12, 11, 3, 0, 8, 0, 9, 5, 3, 46, 64, 42, 64, 169, 92, 77, 148, 60, 76, 104, 83, 4, 87, 8, 21, 69, 29, 124, 175, 176, 161, 180, 181, 179, 64, 
+#> 36, 12, 66, 75, 53, 140, 130, 178, 179, 214, 165, 178, 166, 189, 197, 169, 144, 168, 155, 146, 152, 46, 0, 96, 150, 204, 216, 221, 217, 201, 183, 174, 186, 213, 169, 16, 129, 4, 22, 16, 147, 163, 155, 48, 105, 126, 163, 121, 10, 32, 29, 61, 102, 173, 61, 97, 142, 150, 116, 50, 136, 200, 178, 176, 165, 130, 78, 98, 166, 178, 114, 156, 185, 146, 134, 14, 72, 131, 118, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 6, 6, 11, 6, 10, 0, 66, 201, 177, 51, 109, 159, 172, 146, 145, 151, 79, 155, 163, 137, 
+#> 99, 30, 24, 76, 117, 190, 160, 187, 139, 102, 60, 135, 128, 20, 160, 52, NA, NA, 0, 6, NA, 1, 0, 2, 0, 0, 12, 4, 12, 12, 8, 7, 6, 1, 4, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 185, 212, 177, 197, 163, 82, 68, 87, 105, 127, 100, 155, 165, 189, 162, 204, 200, 188, 196, 190, 187, 179, 5, 11, 57, 140, 117, 109, 154, 36, 83, 75, 33, 144, 181, 119, 176, 191, 167, 85, 174, 144, 126, 157, 32, 71, 158, 203, 176, 177, 161, 117, 103, 77, 135, 159, 25, 54, 50, 147, 
+#> 136, 153, 137, 129, 126, 101, 91, 115, 108, 116, 147, 196, 216, 173, 99, 83, 186, 132, 177, 156, 156, 64, 0, 1, 18, 16, 24, 11, 20, 28, 15, 12, 14, 6, 84, 56, 190, 194, 191, 204, 41, 159, 181, 184, 113, 175, 50, 82, 77, 176, 181, 196, 189, 164, 166, 99, 178, 132, 144, 44, 22, 105, 191, 169, 155, 172, 137, 169, 156, 173, 126, 73, 27, 147, 21, 62, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 16, 69, 27, 112, 116, 61, 9, 138, 121, 107, 95, 111, 98, 58, 0, 8, 7, 86, 166, 112, 166, 163, 57, 167, 106, 127, 43, 
+#> 147, 42, 0, 1, 3, 1, 2, 2, 2, 1, 11, 1, 1, 0, 0, 0, 0, 0, 7, 4, 10, 10, 10, 17, 13, 0, 2, 1, 0, 0, 1, 0, 0, 0, 7, 54, 22, 159, 152, 168, 150, 111, 111, 34, 69, 23, 34, 185, 190, 174, 170, 108, 27, 60, 40, 41, 24, 45, 117, 158, 155, 126, 82, 99, 89, 99, 110, 106, 77, 169, 188, 143, 76, 90, 95, 18, 171, 132, 38, 12, 2, 84, 36, 78, 45, 151, 156, 106, 189, 149, 130, 76, 77, 17, 180, 156, 165, 190, 196, 191, 212, 154, 168, 85, 152, 158, 151, 131, 116, 17, 154, 165, 162, 177, 151, 170, 182, 174, 37, 187, 
+#> 1, 46, 58, 73, 185, 206, 170, 160, 115, 118, 141, 56, 69, 36, 68, 12, 26, NA, NA, NA, NA, NA, NA, 0, NA, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 17, 165, 213, 185, 87, 195, 163, 193, 153, 111, 146, 174, 203, 188, 187, 191, 67, 141, 144, 20, 15, 2, 14, 3, 4, 0, NA, 0, 0, NA, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 2, 4, 0, 3, 3, 5, 9, 17, 9, 10, 11, 15, 10, 13, 6, 1, 0, 0, 1, 0, 1, 0, 0, 0, 7, 0, 0, 15, 10, 11, 6, 2, 0, 
+#> 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 11, 10, 7, 5, 4, 6, 3, 3, 10, 34, 173, 182, 172, 153, 176, 213, 145, 43, 171, 163, 157, 8, 77, 4, 0, 148, 187, 146, 161, 172, 183, 163, 158, 123, 173, 36, 97, 90, 97, 135, 141, 122, 145, 159, 161, 114, 132, 28, 63, 85, 165, 87, 43, 46, 61, 56, 8, 137, 24, 11, 5, 119, 128, 167, 181, 152, 145, 51, 101, 140, 33, 23, 18, 59, 10, 65, 181, 122, 60, 105, 174, 140, 173, 157, 160, 97, 112, 173, 171, 86, 141, 69, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 122, 164, 169, 118, 79, 165, 
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+#> 0.486723139707884, 0.734209481932231, -1.56034873438054, -1.10749332677157, 0.811751019761641, 0.402024698591629, 0.380460155372154, 0.100121093518988, 0.984267365517436, 0.962702822297961, 1.09209008161481, 0.294201982494257, -0.0939597954562811, -0.827154264918408, 0.596105587566898, -2.03476868520897, -1.76617755591554, 0.168021316160106, 0.519693838355677, 0.519693838355677, 0.558768563044074, 0.493512236736306, -0.407684021651731, -1.1801379574129, 1.09430974232833, -2.04303166566704, -2.00095296469395, 
+#> -1.4960085530169, 0.208178836393173, 0.544808444177878, 0.692083897583686, 0.565847794664422, 0.50272974320479, 0.755201949043319, 0.671044547097142, 0.628965846124054, 0.713123248070231, 0.50272974320479, 0.523769093691334, 0.650005196610598, 0.628965846124054, -0.675473884041678, -1.55912660447653, 0.187139485906629, -1.6059438861505, -1.5290891438422, 0.891835238869222, 0.930262610023371, 0.12328781578623, 0.718912068675549, 0.353852042711128, 0.776553125406773, 0.949476295600446, 0.296210985979903, 
+#> -1.3753796592256, -0.529977493834313, -0.707106781186548, 0.707106781186548, -1.38590742453381, -1.68556308389247, 0.326410628944255, 0.711682190976819, 0.626066288302916, 0.840106044987673, -0.144476835762211, 0.711682190976819, -0.888056041656735, -1.50969527081645, 0.532833624994041, 0.710444833325388, 1.06566724998808, 0.0888056041656735, -2.22651550155043, 0.431030565043737, 0.431030565043737, -0.048526619905586, 0.510956762535291, 0.431030565043737, 0.470993663789514, -1.51359933929831, 0.0439634662866728, 
+#> 0.0439634662866728, -1.01115972459347, -0.257500302536226, 1.55128231040117, 1.09908665716682, 0.0439634662866728, -2.43110072548694, 0.113602837639577, 0.113602837639577, 0.477131918086222, 0.295367377862899, 0.295367377862899, 0.477131918086222, 0.658896458309545, -1.17516278835534, 0.427331923038304, 0.894726213861449, -0.97485094943113, 0.827955600886714, -1.12398200257779, 0.787242455246792, -0.559715734077199, 0.896455281408196, -1.42886901662352, -0.673609679265374, 0.591960021172601, 0.836908995450919, 
+#> 0.673609679265374, -1.60976734875699, 0.439411559765688, 0.756294896135174, -0.32110844752108, 0.735169340377209, -0.0289763793899868, -0.985196899259565, 1.01417327864955, -1.22777606224949, 1.07733709810034, 0.689107513199319, -0.281466449053243, -0.354259496222185, 0.689107513199319, 0.93175100376246, 0.956015352818774, -1.64026999620683, -0.839546477348466, -1.49279801192197, 0.635547668442029, 0.418771719516066, 0.43847862396388, -0.815368043303461, -0.300398752796012, 1.11576679609947, 0.608540421252086, 
+#> 0.545587963881181, -1.15412838513327, 1.14347950034851, -0.710811581297725, -0.432667919050789, -0.338090970696901, 0.277939816401133, -0.991456957012999, -1.25280335153944, -1.30880615036653, 0.763297406235949, 1.15531699802561, 0.539286210927572, 1.15531699802561, -1.71511687076618, -0.0618060133609434, 0.602608630269198, 0.618060133609434, 0.556254120248491, -0.86993928985988, -1.50722039754793, 0.768783558480824, 0.859823716721974, -0.0505778656895281, 0.799130277894541, -1.92602645282401, -1.25273330723935, 
+#> -1.37515024280019, 0.257075564677781, 0.481506613206003, 0.971174355449395, 0.848757419888547, -0.640648629435105, 1.03238282322982, 1.11399411360372, 0.746743306921174, -0.0285639516308647, 0.563117903579901, -1.08951072649155, 0.29788120986473, -0.735562605639081, -1.41595801585523, -0.404559433101495, 0.588450084511265, 0.919453257048851, 1.04817671303569, -1.42358077622099, -0.652981495645526, 0.827380280196815, 0.421801711472886, 0.827380280196815, -1.13888851785555, 0.920471541828454, 0.920471541828454, 
+#> 0.834664872674954, -0.195015157167045, -0.538241833781046, -1.39630852531605, -1.39630852531605, -0.0234018188600455, 0.834664872674954, 1.17789154928895, -1.38672099686764, 0.420332210146618, 1.11275446703993, 1.07897777158172, -1.16717247638927, 0.0150118646480935, 1.16341951022725, -0.525415262683273, -0.71118708770343, -1.35255298821204, -0.705054217259469, 0.302166093111201, 1.02160917194739, 0.733831940412917, -1.78678348883436, 0.367494476426926, 0.473096337469146, 0.451975965260702, 0.49421670967759, 
+#> -1.47402400968094, 0.622365692976397, 0.229292623728146, 0.622365692976397, -1.42386474484478, -0.50524232881589, 0.0793355722934041, 0.914446859592395, 0.93532464177487, -0.394496331986063, -0.742581330797295, 1.13707766278336, -1.12924109518953, 0.773452804924335, 0.355788290265194, -0.633081106402271, 1.12547752249293, 0.17585586288952, -0.0703423451558078, 0.949621659603406, -1.54753159342777, -2.01427999044859, -0.638674143312966, 0.650956338376677, 0.393030242038749, 0.307054876592772, 0.564980972930701, 
+#> 0.736931703822654, -0.707106781186548, 0.707106781186548, -0.707106781186547, 0.707106781186547, -1.78125085084331, 0.311602629259796, 0.427872267043302, 0.567395832383509, 0.474380122156705, -1.25348028787531, -0.0596895375178717, 1.18715857952211, 0.126011245871062, -1.80470389748439, -0.89496772657573, -0.0265831997992792, 0.69707057251443, 0.738422216646642, 0.841801326977171, 0.448960707721158, -2.14139914541267, -0.19711623932669, 0.827290883234743, 0.200102849013458, 0.283727920242962, 0.367352991472467, 
+#> 0.660040740775734, -0.324299494442592, 1.12190095374735, -0.797601459304754, -1.83706461344914, -1.36403576736679, 0.381277561281898, 0.593324975042953, 0.544390956482709, 0.593324975042953, 0.658570333123278, 0.430211579842141, -1.14939154226538, 0.478913142610576, 0.670478399654806, -0.160702427944268, 0.248358297732051, 0.45288866057021, -1.4901497863923, -1.08108906071599, 0.65741902340837, 1.37327529334193, -1.10906783962669, 0.276188100140497, 0.832879739486188, 0.940594025644474, 1.11075173882639, 
+#> -1.27145624572042, 0.146524697462205, 0.174884316325857, -1.1012985325385, -1.11499743118271, -0.527738997677224, 0.567418621562729, 1.0753178072972, -0.770518002816772, -0.154897949019867, -1.12797480824723, 1.05648344716114, 0.996907312922731, -1.19487610589409, 0.64073066547944, -0.432926125323946, 0.987071565738596, -1.47613634810399, 0.366416823997444, 0.366416823997444, 0.7433027001091, -1.77670994843448, 0.334504033501552, 0.499014213912152, 0.608687667519218, 0.334504033501552, -1.49845255607925, 
+#> -0.571418013271602, 0.689956856450286, 0.689956856450286, 0.689956856450286, -2.01837516818398, 0.655971929659792, -0.504593792045994, 0.681201619262092, 0.80735006727359, 0.353215654432196, 0.0252296896022997, NA, NA, -0.558135672856483, -0.81349186305226, -1.10532750899029, 1.17463847490057, -0.667574040083244, 0.846323373220288, 1.24759738638508, -0.886450774536767, -0.521656217114229, 1.28407684212733, -1.35607145203054, 0.161918979346931, -0.521176714772932, 0.41491738457651, 1.30041180288004, 
+#> -1.15113847167573, 0.497082521859975, 0.654055949815756)]
+#> Groups: playerID [1,322]
+#> 
+#>   playerID yearID teamID     G    AB     R     H        G_z
+#>      <chr>  <int> <fctr> <int> <int> <int> <int>      <dbl>
+#> 1 bondto01   1874    BR2    55   245    25    54 0.39424925
+#> 2 bondto01   1875    HR1    72   289    32    77 1.02437412
+#> 3 bondto01   1876    HAR    45   182    18    50 0.02358756
+#> 4 bondto01   1877    BSN    61   259    32    59 0.61664626
+#> # ... with 19,109 more rows
+
+
+
+ + + +
+ + + +
+ + + diff --git a/docs/authors.html b/docs/authors.html new file mode 100644 index 0000000000..97229403c3 --- /dev/null +++ b/docs/authors.html @@ -0,0 +1,126 @@ + + + + + + + + +Authors • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Authors

+
+ +
    +
  • +

    Hadley Wickham. Author, maintainer. +

    +
    • +
  • +

    Romain Francois. Author. +

    +
    • +
  • +

    . Copyright holder, funder. +

    +
    • +
+ +
+ +
+ + + +
+ + + diff --git a/docs/index.html b/docs/index.html new file mode 100644 index 0000000000..26808a26fb --- /dev/null +++ b/docs/index.html @@ -0,0 +1,284 @@ + + + + + + + +A Grammar of Data Manipulation • dplyr + + + + + + +
+
+ + + +
+
+ + + + +
+ +
+

+dplyr

+ +

dplyr is the next iteration of plyr, focussed on tools for working with data frames (hence the d in the name). It has three main goals:

+
    +

  • Identify the most important data manipulation tools needed for data analysis and make them easy to use from R.

    • +

  • Provide blazing fast performance for in-memory data by writing key pieces in C++.

    • +

  • Use the same interface to work with data no matter where it’s stored, whether in a data frame, a data table or database.

    • +
+

You can install:

+
    +
  • +

    the latest released version from CRAN with

    +
    install.packages("dplyr")
    +
    • +
  • +

    the latest development version from github with

    +
    if (packageVersion("devtools") < 1.6) {
+  install.packages("devtools")
+}
+devtools::install_github("tidyverse/lazyeval")
+devtools::install_github("tidyverse/dplyr")
    +
    • +
+

You’ll probably also want to install the data packages used in most examples: install.packages(c("nycflights13", "Lahman")).

+

If you encounter a clear bug, please file a minimal reproducible example on github. For questions and other discussion, please use the manipulatr mailing list.

+
+

+Learning dplyr

+

To get started, read the notes below, then read the intro vignette: vignette("introduction", package = "dplyr"). To make the most of dplyr, I also recommend that you familiarise yourself with the principles of tidy data: this will help you get your data into a form that works well with dplyr, ggplot2 and R’s many modelling functions.

+

If you need more help, I recommend the following (paid) resources:

+
    +

  • dplyr on datacamp, by Garrett Grolemund. Learn the basics of dplyr at your own pace in this interactive online course.

    • +

  • Introduction to Data Science with R: How to Manipulate, Visualize, and Model Data with the R Language, by Garrett Grolemund. This O’Reilly video series will teach you the basics needed to be an effective analyst in R.

    • +
+
+
+

+Key data structures

+

The key object in dplyr is a tbl, a representation of a tabular data structure. Currently dplyr supports:

+ +

You can create them as follows:

+
library(dplyr) # for functions
+library(nycflights13) # for data
+flights
+#> # A tibble: 336,776 × 19
+#>     year month   day dep_time sched_dep_time dep_delay arr_time
+#>    <int> <int> <int>    <int>          <int>     <dbl>    <int>
+#> 1   2013     1     1      517            515         2      830
+#> 2   2013     1     1      533            529         4      850
+#> 3   2013     1     1      542            540         2      923
+#> 4   2013     1     1      544            545        -1     1004
+#> 5   2013     1     1      554            600        -6      812
+#> 6   2013     1     1      554            558        -4      740
+#> 7   2013     1     1      555            600        -5      913
+#> 8   2013     1     1      557            600        -3      709
+#> 9   2013     1     1      557            600        -3      838
+#> 10  2013     1     1      558            600        -2      753
+#> # ... with 336,766 more rows, and 12 more variables: sched_arr_time <int>,
+#> #   arr_delay <dbl>, carrier <chr>, flight <int>, tailnum <chr>,
+#> #   origin <chr>, dest <chr>, air_time <dbl>, distance <dbl>, hour <dbl>,
+#> #   minute <dbl>, time_hour <dttm>
+
+# Caches data in local SQLite db
+flights_db1 <- tbl(dbplyr::nycflights13_sqlite(), "flights")
+
+# Caches data in local postgres db
+flights_db2 <- tbl(dbplyr::nycflights13_postgres(host = "localhost"), "flights")
+

Each tbl also comes in a grouped variant which allows you to easily perform operations “by group”:

+
carriers_df  <- flights %>% group_by(carrier)
+carriers_db1 <- flights_db1 %>% group_by(carrier)
+carriers_db2 <- flights_db2 %>% group_by(carrier)
+
+
+

+Single table verbs

+

dplyr implements the following verbs useful for data manipulation:

+
    +
  • +select(): focus on a subset of variables
    • +
  • +filter(): focus on a subset of rows
    • +
  • +mutate(): add new columns
    • +
  • +summarise(): reduce each group to a smaller number of summary statistics
    • +
  • +arrange(): re-order the rows
    • +
+

They all work as similarly as possible across the range of data sources. The main difference is performance:

+
system.time(carriers_df %>% summarise(delay = mean(arr_delay)))
+#>    user  system elapsed 
+#>   0.051   0.001   0.052
+system.time(carriers_db1 %>% summarise(delay = mean(arr_delay)) %>% collect())
+#>    user  system elapsed 
+#>   0.236   0.142   0.381
+system.time(carriers_db2 %>% summarise(delay = mean(arr_delay)) %>% collect())
+#>    user  system elapsed 
+#>   0.012   0.000   0.207
+

Data frame methods are much much faster than the plyr equivalent. The database methods are slower, but can work with data that don’t fit in memory.

+
system.time(plyr::ddply(flights, "carrier", plyr::summarise,
+  delay = mean(arr_delay, na.rm = TRUE)))
+#>    user  system elapsed 
+#>   0.121   0.040   0.162
+
+
+

+Multiple table verbs

+

As well as verbs that work on a single tbl, there are also a set of useful verbs that work with two tbls at a time: joins and set operations.

+

dplyr implements the four most useful joins from SQL:

+ +

And provides methods for:

+ +
+
+

+Plyr compatibility

+

You’ll need to be a little careful if you load both plyr and dplyr at the same time. I’d recommend loading plyr first, then dplyr, so that the faster dplyr functions come first in the search path. By and large, any function provided by both dplyr and plyr works in a similar way, although dplyr functions tend to be faster and more general.

+
+ +
+
+
+ + + +
+ + + +
+ + + diff --git a/docs/jquery.sticky-kit.min.js b/docs/jquery.sticky-kit.min.js new file mode 100644 index 0000000000..e2a3c6de9e --- /dev/null +++ b/docs/jquery.sticky-kit.min.js @@ -0,0 +1,9 @@ +/* + Sticky-kit v1.1.2 | WTFPL | Leaf Corcoran 2015 | http://leafo.net +*/ +(function(){var b,f;b=this.jQuery||window.jQuery;f=b(window);b.fn.stick_in_parent=function(d){var A,w,J,n,B,K,p,q,k,E,t;null==d&&(d={});t=d.sticky_class;B=d.inner_scrolling;E=d.recalc_every;k=d.parent;q=d.offset_top;p=d.spacer;w=d.bottoming;null==q&&(q=0);null==k&&(k=void 0);null==B&&(B=!0);null==t&&(t="is_stuck");A=b(document);null==w&&(w=!0);J=function(a,d,n,C,F,u,r,G){var v,H,m,D,I,c,g,x,y,z,h,l;if(!a.data("sticky_kit")){a.data("sticky_kit",!0);I=A.height();g=a.parent();null!=k&&(g=g.closest(k)); +if(!g.length)throw"failed to find stick parent";v=m=!1;(h=null!=p?p&&a.closest(p):b("
"))&&h.css("position",a.css("position"));x=function(){var c,f,e;if(!G&&(I=A.height(),c=parseInt(g.css("border-top-width"),10),f=parseInt(g.css("padding-top"),10),d=parseInt(g.css("padding-bottom"),10),n=g.offset().top+c+f,C=g.height(),m&&(v=m=!1,null==p&&(a.insertAfter(h),h.detach()),a.css({position:"",top:"",width:"",bottom:""}).removeClass(t),e=!0),F=a.offset().top-(parseInt(a.css("margin-top"),10)||0)-q, +u=a.outerHeight(!0),r=a.css("float"),h&&h.css({width:a.outerWidth(!0),height:u,display:a.css("display"),"vertical-align":a.css("vertical-align"),"float":r}),e))return l()};x();if(u!==C)return D=void 0,c=q,z=E,l=function(){var b,l,e,k;if(!G&&(e=!1,null!=z&&(--z,0>=z&&(z=E,x(),e=!0)),e||A.height()===I||x(),e=f.scrollTop(),null!=D&&(l=e-D),D=e,m?(w&&(k=e+u+c>C+n,v&&!k&&(v=!1,a.css({position:"fixed",bottom:"",top:c}).trigger("sticky_kit:unbottom"))),eb&&!v&&(c-=l,c=Math.max(b-u,c),c=Math.min(q,c),m&&a.css({top:c+"px"})))):e>F&&(m=!0,b={position:"fixed",top:c},b.width="border-box"===a.css("box-sizing")?a.outerWidth()+"px":a.width()+"px",a.css(b).addClass(t),null==p&&(a.after(h),"left"!==r&&"right"!==r||h.append(a)),a.trigger("sticky_kit:stick")),m&&w&&(null==k&&(k=e+u+c>C+n),!v&&k)))return v=!0,"static"===g.css("position")&&g.css({position:"relative"}), +a.css({position:"absolute",bottom:d,top:"auto"}).trigger("sticky_kit:bottom")},y=function(){x();return l()},H=function(){G=!0;f.off("touchmove",l);f.off("scroll",l);f.off("resize",y);b(document.body).off("sticky_kit:recalc",y);a.off("sticky_kit:detach",H);a.removeData("sticky_kit");a.css({position:"",bottom:"",top:"",width:""});g.position("position","");if(m)return null==p&&("left"!==r&&"right"!==r||a.insertAfter(h),h.remove()),a.removeClass(t)},f.on("touchmove",l),f.on("scroll",l),f.on("resize", +y),b(document.body).on("sticky_kit:recalc",y),a.on("sticky_kit:detach",H),setTimeout(l,0)}};n=0;for(K=this.length;n + + + + + diff --git a/docs/news/index.html b/docs/news/index.html new file mode 100644 index 0000000000..44a5a3d3dc --- /dev/null +++ b/docs/news/index.html @@ -0,0 +1,986 @@ + + + + + + + + +All news • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+ +
+
+

Change log All releases

+
+ +
+
+

+dplyr 0.5.0.9000

+
+

+New data, functions, and features

+
    +

  • Five new datasets provide some interesting built-in datasets to demonstrate dplyr verbs (#2094):

    • +
  • +starwars dataset about starwars characters; has list columns
    • +
  • +storms has the trajectories of ~200 tropical storms
    • +

  • band_members, band_instruments and band_instruments2 has some simple data to demonstrate joins.

    • +

  • New add_count() and add_tally() for adding an n column within groups (#2078, @dgrtwo).

    • +

  • arrange() for grouped data frames gains a .by_group argument so you can choose to sort by groups if you want to (defaults to FALSE) (#2318)

    • +

  • New pull() generic for extracting a single column either by name (as a string) or a position (either from the left or the right). Thanks to @paulponcet for the idea (#2054).

    • +

  • as_tibble() is re-exported from tibble. This is the recommend way to create tibbles from existing data frames. tbl_df() has been softly deprecated. tribble() is now imported from tibble (#2336, @chrMongeau); this is now prefered to frame_data().

    • +
+
+
+

+Deprecated and defunct

+
    +

  • dplyr no longer messages that you need dtplyr to work with data.table (#2489).

    • +

  • Long deprecated regroup() has been removed.

    • +

  • Deprecated failwith(). I’m not even sure why it was here.

    • +
+
+
+

+Databases

+

This version of dplyr includes some major changes to how database connections work. By and large, you should be able to continue using your existing dplyr database code without modification, but there are two big changes that you should be aware of:

+
    +

  • Almost all database related code has been moved out of dplyr and into a new package, dbplyr. This makes dplyr simpler, and will make it easier to release fixes for bugs that only affect databases. src_mysql(), src_postgres(), and src_sqlite() will still live dplyr so your existing code continues to work.

    • +

  • It is no longer necessary to create a remote “src”. Instead you can work directly with the database connection returned by DBI. This reflects the maturity of the DBI ecosystem. Thanks largely to the work of Kirill Muller (funded by the R Consortium) DBI backends are now much more consistent, comprehensive, and easier to use. That means that there’s no longer a need for a layer in between you and DBI.

    • +
+

You can continue to use src_mysql(), src_postgres(), and src_sqlite(), but I recommend a new style that makes the connection to DBI more clear:

+
library(dplyr)
+
+con <- DBI::dbConnect(RSQLite::SQLite(), ":memory:")
+dbWriteTable(con, "mtcars", mtcars)
+
+mtcars2 <- tbl(con, "mtcars")
+mtcars2
+

This is particularly useful if you want to perform non-SELECT queries as you can do whatever you want with DBI::dbGetQuery() and DBI::dbExecute().

+

If you’ve implemented a database backend for dplyr, please read the backend news to see what’s changed from your perspective (not much).

+
+
+

+UTF-8

+
    +

  • Internally, column names are always represented as character vectors, and not as language symbols, to avoid encoding problems on Windows (#1950, #2387, #2388).

    • +

  • Error messages and explanations of data frame inequality are now encoded in UTF-8, also on Windows (#2441).

    • +

  • Joins now always reencode character columns to UTF-8 if necessary. This gives a nice speedup, because now pointer comparison can be used instead of string comparison, but relies on a proper encoding tag for all strings (#2514).

    • +

  • Fixed problems when joining factor or character encodings with a mix of native and UTF-8 encoded values (#1885, #2118, #2271, #2451).

    • +

  • Fix group_by() for data frames that have UTF-8 encoded names (#2284, #2382).

    • +

  • New group_vars() generic that returns the grouping as character vector, to avoid the potentially lossy conversion to language symbols. The list returned by group_by_prepare() now has a new group_names component (#1950, #2384).

    • +
+
+
+

+Colwise functions

+
    +

  • rename(), select(), group_by(), filter() and transmute() now have scoped variants (verbs suffixed with _if(), _at() and _all()). Like mutate_all(), summarise_if(), etc, these variants apply an operation to a selection of variables.

    • +

  • The scoped verbs taking predicates (mutate_if(), summarise_if(), etc) now support S3 objects and lazy tables. S3 objects should implement methods for length(), [[ and tbl_vars(). For lazy tables, the first 100 rows are collected and the predicate is applied on this subset of the data. This is robust for the common case of checking the type of a column (#2129).

    • +

  • Summarise and mutate colwise functions pass ... on the the manipulation functions.

    • +

  • The performance of colwise verbs like mutate_all() is now back to where it was in mutate_each().

    • +

  • funs() has better handling of namespaced functions (#2089).

    • +

  • Fix issue with mutate_if() and summarise_if() when a predicate function returns a vector of FALSE (#1989, #2009, #2011, @lionel-).

    • +
+
+
+

+Tidyeval

+

dplyr has a new approach to non-standard evaluation (NSE) called tidyeval. Tidyeval is described in detail in vignette("programming-dplyr") but, in brief, gives you the ability to interpolate values in contexts where dplyr usually works with expressions:

+
my_var <- quo(homeworld)
+
+starwars %>%
+  group_by(!!my_var) %>%
+  summarise_at(vars(height:mass), mean, na.rm = TRUE)
+

This means that the underscored version of each main verb is no longer needed, and so these functions have been deprecated (but remain around for backward compatibility).

+
    +

  • order_by(), top_n(), sample_n() and sample_frac() now use tidyeval to capture their arguments by expression. This makes it possible to use unquoting idioms (see vignette("programming")) and fixes scoping issues (#2297).

    • +

  • Most verbs taking dots now ignore the last argument if empty. This makes it easier to copy lines of code without having to worry about deleting trailing commas (#1039).

    • +
  • +

    [API] The new .data and .env environments can be used inside all verbs that operate on data: .data$column_name accesses the column column_name, whereas .env$var accesses the external variable var. Columns or external variables named .data or .env are shadowed, use .data$... and/or .env$... to access them.

    +

    The column() and global() functions have been removed. They were never documented officially. Use the new .data and .env environments instead.

    +
    • +

  • Expressions in verbs are now interpreted correctly in many cases that failed before (e.g., use of $, case_when(), nonstandard evaluation, …). These expressions are now evaluated in a specially constructed temporary environment that retrieves column data on demand with the help of the bindrcpp package (#2190). This temporary environment poses restrictions on assignments using <- inside verbs. To prevent leaking of broken bindings, the temporary environment is cleared after the evaluation (#2435).

    • +
+
+
+

+Verbs

+
+

+Joins

+
    +

  • [API] xxx_join.tbl_df() by default treats all NA values as different from each other (and from any other value), so that they never match. This corresponds to the behavior of joins for database sources, and of database joins in general. To match NA values, pass na_matches = "na" to the join verbs; this is only supported for data frames. The default can also be tweaked by calling pkgconfig::set_config("dplyr::na_matches", "na") (#2033).

    • +

  • common_by() gets a better error message for unexpected inputs (#2091)

    • +

  • Fix groups when joining grouped data frames with duplicate columns (#2330, #2334, @davidkretch).

    • +

  • One of the two join suffixes can now be an empty string, dplyr no longer hangs (#2228, #2445).

    • +
+
+
+

+Select

+
    +

  • For selecting variables, the first selector decides if it’s an inclusive selection (i.e., the initial column list is empty), or an exclusive selection (i.e., the initial column list contains all columns). This means that select(mtcars, contains("am"), contains("FOO"), contains("vs")) now returns again both am and vs columns like in dplyr 0.4.3 (#2275, #2289, @r2evans).

    • +

  • Select helpers now throw an error if called when no variables have been set (#2452)

    • +

  • Helper functions in select() (and related verbs) are now evaluated in a context where column names do not exist (#2184).

    • +
+
+
+

+Other

+
    +

  • recode(), case_when() and coalesce() now support splicing of arguments with rlang’s !!! operator.

    • +

  • count() now preserves the grouping of its input (#2021).

    • +

  • distinct() no longer duplicates variables (#2001).

    • +

  • Empty distinct() with a grouped data frame works the same way as an empty distinct() on an ungrouped data frame, namely it uses all variables (#2476).

    • +

  • copy_to() now returns it’s output invisibly (since you’re often just calling for the side-effect).

    • +

  • filter() and lag() throw informative error if used with ts objects (#2219)

    • +

  • mutate() recycles list columns of length 1 (#2171).

    • +

  • mutate() gives better error message when attempting to add a non-vector column (#2319), or attempting to remove a column with NULL (#2187, #2439).

    • +

  • summarise() now correctly evaluates newly created factors (#2217), and can create ordered factors (#2200).

    • +

  • Ungrouped summarise() uses summary variables correctly (#2404, #2453).

    • +

  • Grouped summarise() no longer converts character NA to empty strings (#1839).

    • +
+
+
+
+

+Combining and comparing

+
    +

  • all_equal() now reports multiple problems as a character vector (#1819, #2442).

    • +

  • all_equal() checks that factor levels are equal (#2440, #2442).

    • +

  • bind_rows() and bind_cols() give an error for database tables (#2373).

    • +

  • bind_rows() works correctly with NULL arguments and an .id argument (#2056), and also for zero-column data frames (#2175).

    • +

  • Breaking change: bind_rows() and combine() are more strict when coercing. Logical values are no longer coerced to integer and numeric. Date, POSIXct and other integer or double-based classes are no longer coerced to integer or double as there is chance of attributes or information being lost (#2209, @zeehio).

    • +

  • bind_cols() now calls tibble::repair_names() to ensure that all names are unique (#2248).

    • +

  • bind_cols() handles empty argument list (#2048).

    • +

  • bind_cols() better handles NULL inputs (#2303, #2443).

    • +

  • bind_rows() explicitly rejects data frame columns (#2015, #2446).

    • +

  • combine() accepts NA values (#2203, @zeehio)

    • +

  • combine() and bind_rows() with character and factor types now always warn about the coercion to character (#2317, @zeehio)

    • +

  • combine() and bind_rows() accept difftime objects.

    • +

  • mutate coerces results from grouped dataframes accepting combinable data types (such as integer and numeric). (#1892, @zeehio)

    • +

  • tbl_df gains rbind() and cbind() methods that call bind_rows() and bind_cols() respectively (#2138)

    • +
+
+
+

+Vector functions

+
    +

  • %in% gets new hybrid handler (#126).

    • +

  • between() returns NA if left or right is NA (fixes #2562).

    • +

  • case_when() supports NA values (#2000, @tjmahr).

    • +

  • first(), last(), and nth() have better default values for factor, Dates, POSIXct, and data frame inputs (#2029).

    • +

  • Fixed segmentation faults in hybrid evaluation of first(), last(), nth(), lead(), and lag(). These functions now always fall back to the R implementation if called with arguments that the hybrid evaluator cannot handle (#948, #1980).

    • +

  • n_distinct() gets larger hash tables given slightly better performance (#977).

    • +

  • nth() and ntile() are more careful about proper data types of their return values (#2306).

    • +

  • ntile() ignores NA when computing group membership (#2564).

    • +

  • lag() enforces integer n (#2162, @kevinushey).

    • +

  • hybrid min() and max() now always return a numeric and work correctly in edge cases (empty input, all NA, …) (#2305, #2436).

    • +

  • min_rank("string") no longer segfaults in hybrid evaluation (#2279, #2444).

    • +

  • recode() can now recode a factor to other types (#2268)

    • +

  • recode() gains .dots argument to support passing replacements as list (#2110, @jlegewie).

    • +
+
+
+

+Other minor changes and bug fixes

+
    +

  • New is_grouped_df() alias to is.grouped_df().

    • +

  • tbl_vars() now has a group_vars argument set to TRUE by default. If FALSE, group variables are not returned.

    • +

  • Fixed segmentation fault after calling rename() on an invalid grouped data frame (#2031).

    • +

  • rename_vars() gains a strict argument to control if an error is thrown when you try and rename a variable that doesn’t exist.

    • +

  • Fixed undefined behavior for slice() on a zero-column data frame (#2490).

    • +

  • Fixed very rare case of false match during join (#2515).

    • +

  • Restricted workaround for match() to R 3.3.0. (#1858).

    • +

  • dplyr now warns on load when the version of R or Rcpp during installation is different to the currently installed version (#2514).

    • +

  • Fixed improper reuse of attributes when creating a list column in summarise() and perhaps mutate() (#2231).

    • +

  • mutate() and summarise() always strip the names attribute from new or updated columns, even for ungrouped operations (#1689).

    • +

  • Fixed rare error that could lead to a segmentation fault in all_equal(ignore_col_order = FALSE) (#2502).

    • +

  • The “dim” and “dimnames” attributes are always stripped when copying a vector (#1918, #2049).

    • +

  • grouped_df is registered officially as an S3 class. This makes it easier to use with S4 (#2276, , @joranE).

    • +

  • Makeflags uses PKG_CPPFLAGS for defining preprocessor macros.

    • +

  • astyle formatting for C++ code, tested but not changed as part of the tests (#2086, #2103).

    • +

  • Update RStudio project settings to install tests (#1952).

    • +
+
+
+
+

+dplyr 0.5.0

+
+

+Breaking changes

+
+

+Existing functions

+
    +

  • arrange() once again ignores grouping (#1206).

    • +

  • distinct() now only keeps the distinct variables. If you want to return all variables (using the first row for non-distinct values) use .keep_all = TRUE (#1110). For SQL sources, .keep_all = FALSE is implemented using GROUP BY, and .keep_all = TRUE raises an error (#1937, #1942, @krlmlr). (The default behaviour of using all variables when none are specified remains - this note only applies if you select some variables).

    • +

  • The select helper functions starts_with(), ends_with() etc are now real exported functions. This means that you’ll need to import those functions if you’re using from a package where dplyr is not attached. i.e. dplyr::select(mtcars, starts_with("m")) used to work, but now you’ll need dplyr::select(mtcars, dplyr::starts_with("m")).

    • +
+
+
+

+Deprecated and defunct functions

+
    +

  • The long deprecated chain(), chain_q() and %.% have been removed. Please use %>% instead.

    • +

  • id() has been deprecated. Please use group_indices() instead (#808).

    • +

  • rbind_all() and rbind_list() are formally deprecated. Please use bind_rows() instead (#803).

    • +

  • Outdated benchmarking demos have been removed (#1487).

    • +

  • Code related to starting and signalling clusters has been moved out to multidplyr.

    • +
+
+
+
+

+New functions

+
    +

  • coalesce() finds the first non-missing value from a set of vectors. (#1666, thanks to @krlmlr for initial implementation).

    • +

  • case_when() is a general vectorised if + else if (#631).

    • +

  • if_else() is a vectorised if statement: it’s a stricter (type-safe), faster, and more predictable version of ifelse(). In SQL it is translated to a CASE statement.

    • +

  • na_if() makes it easy to replace a certain value with an NA (#1707). In SQL it is translated to NULL_IF.

    • +

  • near(x, y) is a helper for abs(x - y) < tol (#1607).

    • +

  • recode() is vectorised equivalent to switch() (#1710).

    • +

  • union_all() method. Maps to UNION ALL for SQL sources, bind_rows() for data frames/tbl_dfs, and combine() for vectors (#1045).

    • +

  • A new family of functions replace summarise_each() and mutate_each() (which will thus be deprecated in a future release). summarise_all() and mutate_all() apply a function to all columns while summarise_at() and mutate_at() operate on a subset of columns. These columuns are selected with either a character vector of columns names, a numeric vector of column positions, or a column specification with select() semantics generated by the new columns() helper. In addition, summarise_if() and mutate_if() take a predicate function or a logical vector (these verbs currently require local sources). All these functions can now take ordinary functions instead of a list of functions generated by funs() (though this is only useful for local sources). (#1845, @lionel-)

    • +

  • select_if() lets you select columns with a predicate function. Only compatible with local sources. (#497, #1569, @lionel-)

    • +
+
+
+

+Local backends

+
+

+dtplyr

+

All data table related code has been separated out in to a new dtplyr package. This decouples the development of the data.table interface from the development of the dplyr package. If both data.table and dplyr are loaded, you’ll get a message reminding you to load dtplyr.

+
+
+

+Tibble

+

Functions related to the creation and coercion of tbl_dfs, now live in their own package: tibble. See vignette("tibble") for more details.

+
    +

  • $ and [[ methods that never do partial matching (#1504), and throw an error if the variable does not exist.

    • +

  • all_equal() allows to compare data frames ignoring row and column order, and optionally ignoring minor differences in type (e.g. int vs. double) (#821). The test handles the case where the df has 0 columns (#1506). The test fails fails when convert is FALSE and types don’t match (#1484).

    • +

  • all_equal() shows better error message when comparing raw values or when types are incompatible and convert = TRUE (#1820, @krlmlr).

    • +

  • add_row() makes it easy to add a new row to data frame (#1021)

    • +

  • as_data_frame() is now an S3 generic with methods for lists (the old as_data_frame()), data frames (trivial), and matrices (with efficient C++ implementation) (#876). It no longer strips subclasses.

    • +

  • The internals of data_frame() and as_data_frame() have been aligned, so as_data_frame() will now automatically recycle length-1 vectors. Both functions give more informative error messages if you attempting to create an invalid data frame. You can no longer create a data frame with duplicated names (#820). Both check for POSIXlt columns, and tell you to use POSIXct instead (#813).

    • +

  • frame_data() properly constructs rectangular tables (#1377, @kevinushey), and supports list-cols.

    • +

  • glimpse() is now a generic. The default method dispatches to str() (#1325). It now (invisibly) returns its first argument (#1570).

    • +

  • lst() and lst_() which create lists in the same way that data_frame() and data_frame_() create data frames (#1290).

    • +

  • print.tbl_df() is considerably faster if you have very wide data frames. It will now also only list the first 100 additional variables not already on screen - control this with the new n_extra parameter to print() (#1161). When printing a grouped data frame the number of groups is now printed with thousands separators (#1398). The type of list columns is correctly printed (#1379)

    • +

  • Package includes setOldClass(c("tbl_df", "tbl", "data.frame")) to help with S4 dispatch (#969).

    • +

  • tbl_df automatically generates column names (#1606).

    • +
+
+
+

+tbl_cube

+
    +

  • new as_data_frame.tbl_cube() (#1563, @krlmlr).

    • +

  • tbl_cubes are now constructed correctly from data frames, duplicate dimension values are detected, missing dimension values are filled with NA. The construction from data frames now guesses the measure variables by default, and allows specification of dimension and/or measure variables (#1568, @krlmlr).

    • +

  • Swap order of dim_names and met_name arguments in as.tbl_cube (for array, table and matrix) for consistency with tbl_cube and as.tbl_cube.data.frame. Also, the met_name argument to as.tbl_cube.table now defaults to "Freq" for consistency with as.data.frame.table (@krlmlr, #1374).

    • +
+
+
+
+

+Remote backends

+
    +

  • as_data_frame() on SQL sources now returns all rows (#1752, #1821, @krlmlr).

    • +

  • compute() gets new parameters indexes and unique_indexes that make it easier to add indexes (#1499, @krlmlr).

    • +

  • db_explain() gains a default method for DBIConnections (#1177).

    • +

  • The backend testing system has been improved. This lead to the removal of temp_srcs(). In the unlikely event that you were using this function, you can instead use test_register_src(), test_load(), and test_frame().

    • +

  • You can now use right_join() and full_join() with remote tables (#1172).

    • +
+
+

+SQLite

+
    +

  • src_memdb() is a session-local in-memory SQLite database. memdb_frame() works like data_frame(), but creates a new table in that database.

    • +

  • src_sqlite() now uses a stricter quoting character, `, instead of ". SQLite “helpfully” will convert "x" into a string if there is no identifier called x in the current scope (#1426).

    • +

  • src_sqlite() throws errors if you try and use it with window functions (#907).

    • +
+
+
+

+SQL translation

+
    +

  • filter.tbl_sql() now puts parens around each argument (#934).

    • +

  • Unary - is better translated (#1002).

    • +

  • escape.POSIXt() method makes it easier to use date times. The date is rendered in ISO 8601 format in UTC, which should work in most databases (#857).

    • +

  • is.na() gets a missing space (#1695).

    • +

  • if, is.na(), and is.null() get extra parens to make precendence more clear (#1695).

    • +

  • pmin() and pmax() are translated to MIN() and MAX() (#1711).

    • +
  • +

    Window functions:

    +
      +

    • Work on ungrouped data (#1061).

      • +

    • Warning if order is not set on cumulative window functions.

      • +

    • Multiple partitions or ordering variables in windowed functions no longer generate extra parentheses, so should work for more databases (#1060)

      • +
    +
    • +
+
+
+

+Internals

+

This version includes an almost total rewrite of how dplyr verbs are translated into SQL. Previously, I used a rather ad-hoc approach, which tried to guess when a new subquery was needed. Unfortunately this approach was fraught with bugs, so in this version I’ve implemented a much richer internal data model. Now there is a three step process:

+
    +

  1. When applied to a tbl_lazy, each dplyr verb captures its inputs and stores in a op (short for operation) object.

    2. +

  2. sql_build() iterates through the operations building to build up an object that represents a SQL query. These objects are convenient for testing as they are lists, and are backend agnostics.

    3. +

  3. sql_render() iterates through the queries and generates the SQL, using generics (like sql_select()) that can vary based on the backend.

    4. +
+

In the short-term, this increased abstraction is likely to lead to some minor performance decreases, but the chance of dplyr generating correct SQL is much much higher. In the long-term, these abstractions will make it possible to write a query optimiser/compiler in dplyr, which would make it possible to generate much more succinct queries.

+

If you have written a dplyr backend, you’ll need to make some minor changes to your package:

+
    +

  • sql_join() has been considerably simplified - it is now only responsible for generating the join query, not for generating the intermediate selects that rename the variable. Similarly for sql_semi_join(). If you’ve provided new methods in your backend, you’ll need to rewrite.

    • +

  • select_query() gains a distinct argument which is used for generating queries for distinct(). It loses the offset argument which was never used (and hence never tested).

    • +

  • src_translate_env() has been replaced by sql_translate_env() which should have methods for the connection object.

    • +
+

There were two other tweaks to the exported API, but these are less likely to affect anyone.

+
    +

  • translate_sql() and partial_eval() got a new API: now use connection + variable names, rather than a tbl. This makes testing considerably easier. translate_sql_q() has been renamed to translate_sql_().

    • +

  • Also note that the sql generation generics now have a default method, instead methods for DBIConnection and NULL.

    • +
+
+
+
+

+Minor improvements and bug fixes

+
+

+Single table verbs

+
    +

  • Avoiding segfaults in presence of raw columns (#1803, #1817, @krlmlr).

    • +

  • arrange() fails gracefully on list columns (#1489) and matrices (#1870, #1945, @krlmlr).

    • +

  • count() now adds additional grouping variables, rather than overriding existing (#1703). tally() and count() can now count a variable called n (#1633). Weighted count()/tally() ignore NAs (#1145).

    • +

  • The progress bar in do() is now updated at most 20 times per second, avoiding uneccessary redraws (#1734, @mkuhn)

    • +

  • distinct() doesn’t crash when given a 0-column data frame (#1437).

    • +

  • filter() throws an error if you supply an named arguments. This is usually a type: filter(df, x = 1) instead of filter(df, x == 1) (#1529).

    • +

  • summarise() correctly coerces factors with different levels (#1678), handles min/max of already summarised variable (#1622), and supports data frames as columns (#1425).

    • +
  • +

    select() now informs you that it adds missing grouping variables (#1511). It works even if the grouping variable has a non-syntactic name (#1138). Negating a failed match (e.g. select(mtcars, -contains("x"))) returns all columns, instead of no columns (#1176)

    +

    The select() helpers are now exported and have their own documentation (#1410). one_of() gives a useful error message if variables names are not found in data frame (#1407).

    +
    • +

  • The naming behaviour of summarise_each() and mutate_each() has been tweaked so that you can force inclusion of both the function and the variable name: summarise_each(mtcars, funs(mean = mean), everything()) (#442).

    • +

  • mutate() handles factors that are all NA (#1645), or have different levels in different groups (#1414). It disambiguates NA and NaN (#1448), and silently promotes groups that only contain NA (#1463). It deep copies data in list columns (#1643), and correctly fails on incompatible columns (#1641). mutate() on a grouped data no longer droups grouping attributes (#1120). rowwise() mutate gives expected results (#1381).

    • +

  • one_of() tolerates unknown variables in vars, but warns (#1848, @jennybc).

    • +

  • print.grouped_df() passes on ... to print() (#1893).

    • +

  • slice() correctly handles grouped attributes (#1405).

    • +

  • ungroup() generic gains ... (#922).

    • +
+
+
+

+Dual table verbs

+
    +

  • bind_cols() matches the behaviour of bind_rows() and ignores NULL inputs (#1148). It also handles POSIXcts with integer base type (#1402).

    • +

  • bind_rows() handles 0-length named lists (#1515), promotes factors to characters (#1538), and warns when binding factor and character (#1485). bind_rows()` is more flexible in the way it can accept data frames, lists, list of data frames, and list of lists (#1389).

    • +

  • bind_rows() rejects POSIXlt columns (#1875, @krlmlr).

    • +

  • Both bind_cols() and bind_rows() infer classes and grouping information from the first data frame (#1692).

    • +

  • rbind() and cbind() get grouped_df() methods that make it harder to
    +create corrupt data frames (#1385). You should still prefer bind_rows() and bind_cols().

    • +

  • Joins now use correct class when joining on POSIXct columns (#1582, @joel23888), and consider time zones (#819). Joins handle a by that is empty (#1496), or has duplicates (#1192). Suffixes grow progressively to avoid creating repeated column names (#1460). Joins on string columns should be substantially faster (#1386). Extra attributes are ok if they are identical (#1636). Joins work correct when factor levels not equal (#1712, #1559), and anti and semi joins give correct result when by variable is a factor (#1571). A clear error message is given for joins where an explicit by contains unavailable columns (#1928, #1932, @krlmlr).

    • +

  • inner_join(), left_join(), right_join(), and full_join() gain a suffix argument which allows you to control what suffix duplicated variable names recieve (#1296).

    • +

  • Set operations (intersect(), union() etc) respect coercion rules (#799). setdiff() handles factors with NA levels (#1526).

    • +

  • There were a number of fixes to enable joining of data frames that don’t have the same encoding of column names (#1513), including working around bug 16885 regarding match() in R 3.3.0 (#1806, #1810, @krlmlr).

    • +
+
+
+

+Vector functions

+
    +

  • combine() silently drops NULL inputs (#1596).

    • +

  • Hybrid cummean() is more stable against floating point errors (#1387).

    • +

  • Hybrid lead() and lag() received a considerable overhaul. They are more careful about more complicated expressions (#1588), and falls back more readily to pure R evaluation (#1411). They behave correctly in summarise() (#1434). and handle default values for string columns.

    • +

  • Hybrid min() and max() handle empty sets (#1481).

    • +

  • n_distinct() uses multiple arguments for data frames (#1084), falls back to R evaluation when needed (#1657), reverting decision made in (#567). Passing no arguments gives an error (#1957, #1959, @krlmlr).

    • +

  • nth() now supports negative indices to select from end, e.g. nth(x, -2) selects the 2nd value from the end of x (#1584).

    • +

  • top_n() can now also select bottom n values by passing a negative value to n (#1008, #1352).

    • +

  • Hybrid evaluation leaves formulas untouched (#1447).

    • +
+
+
+
+
+

+dplyr 0.4.3

+
+

+Improved encoding support

+

Until now, dplyr’s support for non-UTF8 encodings has been rather shaky. This release brings a number of improvement to fix these problems: it’s probably not perfect, but should be a lot better than the previously version. This includes fixes to arrange() (#1280), bind_rows() (#1265), distinct() (#1179), and joins (#1315). print.tbl_df() also recieved a fix for strings with invalid encodings (#851).

+
+
+

+Other minor improvements and bug fixes

+
    +

  • frame_data() provides a means for constructing data_frames using a simple row-wise language. (#1358, @kevinushey)

    • +

  • all.equal() no longer runs all outputs together (#1130).

    • +

  • as_data_frame() gives better error message with NA column names (#1101).

    • +

  • [.tbl_df is more careful about subsetting column names (#1245).

    • +

  • arrange() and mutate() work on empty data frames (#1142).

    • +

  • arrange(), filter(), slice(), and summarise() preserve data frame meta attributes (#1064).

    • +

  • bind_rows() and bind_cols() accept lists (#1104): during initial data cleaning you no longer need to convert lists to data frames, but can instead feed them to bind_rows() directly.

    • +

  • bind_rows() gains a .id argument. When supplied, it creates a new column that gives the name of each data frame (#1337, @lionel-).

    • +

  • bind_rows() respects the ordered attribute of factors (#1112), and does better at comparing POSIXcts (#1125). The tz attribute is ignored when determining if two POSIXct vectors are comparable. If the tz of all inputs is the same, it’s used, otherwise its set to UTC.

    • +

  • data_frame() always produces a tbl_df (#1151, @kevinushey)

    • +

  • filter(x, TRUE, TRUE) now just returns x (#1210), it doesn’t internally modify the first argument (#971), and it now works with rowwise data (#1099). It once again works with data tables (#906).

    • +

  • glimpse() also prints out the number of variables in addition to the number of observations (@ilarischeinin, #988).

    • +

  • Joins handles matrix columns better (#1230), and can join Date objects with heterogenous representations (some Dates are integers, while other are numeric). This also improves all.equal() (#1204).

    • +

  • Fixed percent_rank() and cume_dist() so that missing values no longer affect denominator (#1132).

    • +

  • print.tbl_df() now displays the class for all variables, not just those that don’t fit on the screen (#1276). It also displays duplicated column names correctly (#1159).

    • +

  • print.grouped_df() now tells you how many groups there are.

    • +

  • mutate() can set to NULL the first column (used to segfault, #1329) and it better protects intermediary results (avoiding random segfaults, #1231).

    • +

  • mutate() on grouped data handles the special case where for the first few groups, the result consists of a logical vector with only NA. This can happen when the condition of an ifelse is an all NA logical vector (#958).

    • +

  • mutate.rowwise_df() handles factors (#886) and correctly handles 0-row inputs (#1300).

    • +

  • n_distinct() gains an na_rm argument (#1052).

    • +

  • The Progress bar used by do() now respects global option dplyr.show_progress (default is TRUE) so you can turn it off globally (@jimhester #1264, #1226).

    • +

  • summarise() handles expressions that returning heterogenous outputs, e.g. median(), which that sometimes returns an integer, and other times a numeric (#893).

    • +

  • slice() silently drops columns corresponding to an NA (#1235).

    • +

  • ungroup.rowwise_df() gives a tbl_df (#936).

    • +

  • More explicit duplicated column name error message (#996).

    • +

  • When “,” is already being used as the decimal point (getOption("OutDec")), use “.” as the thousands separator when printing out formatted numbers (@ilarischeinin, #988).

    • +
+
+
+

+Databases

+
    +

  • db_query_fields.SQLiteConnection uses build_sql rather than paste0 (#926, @NikNakk)

    • +

  • Improved handling of log() (#1330).

    • +

  • n_distinct(x) is translated to COUNT(DISTINCT(x)) (@skparkes, #873).

    • +

  • print(n = Inf) now works for remote sources (#1310).

    • +
+
+
+

+Hybrid evaluation

+
    +

  • Hybrid evaluation does not take place for objects with a class (#1237).

    • +

  • Improved $ handling (#1134).

    • +

  • Simplified code for lead() and lag() and make sure they work properly on factors (#955). Both repsect the default argument (#915).

    • +

  • mutate can set to NULL the first column (used to segfault, #1329).

    • +

  • filter on grouped data handles indices correctly (#880).

    • +

  • sum() issues a warning about integer overflow (#1108).

    • +
+
+
+
+

+dplyr 0.4.2

+

This is a minor release containing fixes for a number of crashes and issues identified by R CMD CHECK. There is one new “feature”: dplyr no longer complains about unrecognised attributes, and instead just copies them over to the output.

+
    +

  • lag() and lead() for grouped data were confused about indices and therefore produced wrong results (#925, #937). lag() once again overrides lag() instead of just the default method lag.default(). This is necesary due to changes in R CMD check. To use the lag function provided by another package, use pkg::lag.

    • +

  • Fixed a number of memory issues identified by valgrind.

    • +

  • Improved performance when working with large number of columns (#879).

    • +

  • Lists-cols that contain data frames now print a slightly nicer summary (#1147)

    • +

  • Set operations give more useful error message on incompatible data frames (#903).

    • +

  • all.equal() gives the correct result when ignore_row_order is TRUE (#1065) and all.equal() correctly handles character missing values (#1095).

    • +

  • bind_cols() always produces a tbl_df (#779).

    • +

  • bind_rows() gains a test for a form of data frame corruption (#1074).

    • +

  • bind_rows() and summarise() now handles complex columns (#933).

    • +

  • Workaround for using the constructor of DataFrame on an unprotected object (#998)

    • +

  • Improved performance when working with large number of columns (#879).

    • +
+
+
+

+dplyr 0.4.1

+
    +
  • Don’t assume that RPostgreSQL is available.
    • +
+
+
+

+dplyr 0.4.0

+
+

+New features

+
    +

  • add_rownames() turns row names into an explicit variable (#639).

    • +

  • as_data_frame() efficiently coerces a list into a data frame (#749).

    • +

  • bind_rows() and bind_cols() efficiently bind a list of data frames by row or column. combine() applies the same coercion rules to vectors (it works like c() or unlist() but is consistent with the bind_rows() rules).

    • +

  • right_join() (include all rows in y, and matching rows in x) and full_join() (include all rows in x and y) complete the family of mutating joins (#96).

    • +

  • group_indices() computes a unique integer id for each group (#771). It can be called on a grouped_df without any arguments or on a data frame with same arguments as group_by().

    • +
+
+
+

+New vignettes

+
    +

  • vignette("data_frames") describes dplyr functions that make it easier and faster to create and coerce data frames. It subsumes the old memory vignette.

    • +

  • vignette("two-table") describes how two-table verbs work in dplyr.

    • +
+
+
+

+Minor improvements

+
    +

  • data_frame() (and as_data_frame() & tbl_df()) now explicitly forbid columns that are data frames or matrices (#775). All columns must be either a 1d atomic vector or a 1d list.

    • +

  • do() uses lazyeval to correctly evaluate its arguments in the correct environment (#744), and new do_() is the SE equivalent of do() (#718). You can modify grouped data in place: this is probably a bad idea but it’s sometimes convenient (#737). do() on grouped data tables now passes in all columns (not all columns except grouping vars) (#735, thanks to @kismsu). do() with database tables no longer potentially includes grouping variables twice (#673). Finally, do() gives more consistent outputs when there are no rows or no groups (#625).

    • +

  • first() and last() preserve factors, dates and times (#509).

    • +

  • Overhaul of single table verbs for data.table backend. They now all use a consistent (and simpler) code base. This ensures that (e.g.) n() now works in all verbs (#579).

    • +

  • In *_join(), you can now name only those variables that are different between the two tables, e.g. inner_join(x, y, c("a", "b", "c" = "d")) (#682). If non-join colums are the same, dplyr will add .x and .y suffixes to distinguish the source (#655).

    • +

  • mutate() handles complex vectors (#436) and forbids POSIXlt results (instead of crashing) (#670).

    • +

  • select() now implements a more sophisticated algorithm so if you’re doing multiples includes and excludes with and without names, you’re more likely to get what you expect (#644). You’ll also get a better error message if you supply an input that doesn’t resolve to an integer column position (#643).

    • +
  • +

    Printing has recieved a number of small tweaks. All print() method methods invisibly return their input so you can interleave print() statements into a pipeline to see interim results. print() will column names of 0 row data frames (#652), and will never print more 20 rows (i.e. options(dplyr.print_max) is now 20), not 100 (#710). Row names are no never printed since no dplyr method is guaranteed to preserve them (#669).

    +

    glimpse() prints the number of observations (#692)

    +

    type_sum() gains a data frame method.

    +
    • +

  • summarise() handles list output columns (#832)

    • +

  • slice() works for data tables (#717). Documentation clarifies that slice can’t work with relational databases, and the examples show how to achieve the same results using filter() (#720).

    • +

  • dplyr now requires RSQLite >= 1.0. This shouldn’t affect your code in any way (except that RSQLite now doesn’t need to be attached) but does simplify the internals (#622).

    • +
  • +

    Functions that need to combine multiple results into a single column (e.g. join(), bind_rows() and summarise()) are more careful about coercion.

    +

    Joining factors with the same levels in the same order preserves the original levels (#675). Joining factors with non-identical levels generates a warning and coerces to character (#684). Joining a character to a factor (or vice versa) generates a warning and coerces to character. Avoid these warnings by ensuring your data is compatible before joining.

    +

    rbind_list() will throw an error if you attempt to combine an integer and factor (#751). rbind()ing a column full of NAs is allowed and just collects the appropriate missing value for the column type being collected (#493).

    +

    summarise() is more careful about NA, e.g. the decision on the result type will be delayed until the first non NA value is returned (#599). It will complain about loss of precision coercions, which can happen for expressions that return integers for some groups and a doubles for others (#599).

    +
    • +
  • +

    A number of functions gained new or improved hybrid handlers: first(), last(), nth() (#626), lead() & lag() (#683), %in% (#126). That means when you use these functions in a dplyr verb, we handle them in C++, rather than calling back to R, and hence improving performance.

    +

    Hybrid min_rank() correctly handles NaN values (#726). Hybrid implementation of nth() falls back to R evaluation when n is not a length one integer or numeric, e.g. when it’s an expression (#734).

    +

    Hybrid dense_rank(), min_rank(), cume_dist(), ntile(), row_number() and percent_rank() now preserve NAs (#774)

    +
    • +

  • filter returns its input when it has no rows or no columns (#782).

    • +

  • Join functions keep attributes (e.g. time zone information) from the left argument for POSIXct and Date objects (#819), and only only warn once about each incompatibility (#798).

    • +
+
+
+

+Bug fixes

+
    +

  • [.tbl_df correctly computes row names for 0-column data frames, avoiding problems with xtable (#656). [.grouped_df will silently drop grouping if you don’t include the grouping columns (#733).

    • +

  • data_frame() now acts correctly if the first argument is a vector to be recycled. (#680 thanks @jimhester)

    • +

  • filter.data.table() works if the table has a variable called “V1” (#615).

    • +

  • *_join() keeps columns in original order (#684). Joining a factor to a character vector doesn’t segfault (#688). *_join functions can now deal with multiple encodings (#769), and correctly name results (#855).

    • +

  • *_join.data.table() works when data.table isn’t attached (#786).

    • +

  • group_by() on a data table preserves original order of the rows (#623). group_by() supports variables with more than 39 characters thanks to a fix in lazyeval (#705). It gives meaninful error message when a variable is not found in the data frame (#716).

    • +

  • grouped_df() requires vars to be a list of symbols (#665).

    • +

  • min(.,na.rm = TRUE) works with Dates built on numeric vectors (#755)

    • +

  • rename_() generic gets missing .dots argument (#708).

    • +

  • row_number(), min_rank(), percent_rank(), dense_rank(), ntile() and cume_dist() handle data frames with 0 rows (#762). They all preserve missing values (#774). row_number() doesn’t segfault when giving an external variable with the wrong number of variables (#781)

    • +

  • group_indices handles the edge case when there are no variables (#867)

    • +
+
+
+
+

+dplyr 0.3.0.1

+
    +
  • Fixed problem with test script on Windows.
    • +
+
+
+

+dplyr 0.3

+
+

+New functions

+
    +

  • between() vector function efficiently determines if numeric values fall in a range, and is translated to special form for SQL (#503).

    • +

  • count() makes it even easier to do (weighted) counts (#358).

    • +

  • data_frame() by @kevinushey is a nicer way of creating data frames. It never coerces column types (no more stringsAsFactors = FALSE!), never munges column names, and never adds row names. You can use previously defined columns to compute new columns (#376).

    • +

  • distinct() returns distinct (unique) rows of a tbl (#97). Supply additional variables to return the first row for each unique combination of variables.

    • +

  • Set operations, intersect(), union() and setdiff() now have methods for data frames, data tables and SQL database tables (#93). They pass their arguments down to the base functions, which will ensure they raise errors if you pass in two many arguments.

    • +

  • Joins (e.g. left_join(), inner_join(), semi_join(), anti_join()) now allow you to join on different variables in x and y tables by supplying a named vector to by. For example, by = c("a" = "b") joins x.a to y.b.

    • +

  • n_groups() function tells you how many groups in a tbl. It returns 1 for ungrouped data. (#477)

    • +

  • transmute() works like mutate() but drops all variables that you didn’t explicitly refer to (#302).

    • +

  • rename() makes it easy to rename variables - it works similarly to select() but it preserves columns that you didn’t otherwise touch.

    • +

  • slice() allows you to selecting rows by position (#226). It includes positive integers, drops negative integers and you can use expression like n().

    • +
+
+
+

+Programming with dplyr (non-standard evaluation)

+
    +

  • You can now program with dplyr - every function that does non-standard evaluation (NSE) has a standard evaluation (SE) version ending in _. This is powered by the new lazyeval package which provides all the tools needed to implement NSE consistently and correctly.

    • +

  • See vignette("nse") for full details.

    • +

  • regroup() is deprecated. Please use the more flexible group_by_() instead.

    • +

  • summarise_each_q() and mutate_each_q() are deprecated. Please use summarise_each_() and mutate_each_() instead.

    • +

  • funs_q has been replaced with funs_.

    • +
+
+
+

+Removed and deprecated features

+
    +

  • %.% has been deprecated: please use %>% instead. chain() is defunct. (#518)

    • +

  • filter.numeric() removed. Need to figure out how to reimplement with new lazy eval system.

    • +

  • The Progress refclass is no longer exported to avoid conflicts with shiny. Instead use progress_estimated() (#535).

    • +

  • src_monetdb() is now implemented in MonetDB.R, not dplyr.

    • +

  • show_sql() and explain_sql() and matching global options dplyr.show_sql and dplyr.explain_sql have been removed. Instead use show_query() and explain().

    • +
+
+
+

+Minor improvements and bug fixes

+
    +

  • Main verbs now have individual documentation pages (#519).

    • +

  • %>% is simply re-exported from magrittr, instead of creating a local copy (#496, thanks to @jimhester)

    • +

  • Examples now use nycflights13 instead of hflights because it the variables have better names and there are a few interlinked tables (#562). Lahman and nycflights13 are (once again) suggested packages. This means many examples will not work unless you explicitly install them with install.packages(c("Lahman", "nycflights13")) (#508). dplyr now depends on Lahman 3.0.1. A number of examples have been updated to reflect modified field names (#586).

    • +

  • do() now displays the progress bar only when used in interactive prompts and not when knitting (#428, @jimhester).

    • +

  • glimpse() now prints a trailing new line (#590).

    • +

  • group_by() has more consistent behaviour when grouping by constants: it creates a new column with that value (#410). It renames grouping variables (#410). The first argument is now .data so you can create new groups with name x (#534).

    • +

  • Now instead of overriding lag(), dplyr overrides lag.default(), which should avoid clobbering lag methods added by other packages. (#277).

    • +

  • mutate(data, a = NULL) removes the variable a from the returned dataset (#462).

    • +

  • trunc_mat() and hence print.tbl_df() and friends gets a width argument to control the deafult output width. Set options(dplyr.width = Inf) to always show all columns (#589).

    • +

  • select() gains one_of() selector: this allows you to select variables provided by a character vector (#396). It fails immediately if you give an empty pattern to starts_with(), ends_with(), contains() or matches() (#481, @leondutoit). Fixed buglet in select() so that you can now create variables called val (#564).

    • +

  • Switched from RC to R6.

    • +

  • tally() and top_n() work consistently: neither accidentally evaluates the the wt param. (#426, @mnel)

    • +

  • rename handles grouped data (#640).

    • +
+
+
+

+Minor improvements and bug fixes by backend

+
+

+Databases

+
    +

  • Correct SQL generation for paste() when used with the collapse parameter targeting a Postgres database. (@rbdixon, #1357)

    • +

  • The db backend system has been completely overhauled in order to make it possible to add backends in other packages, and to support a much wider range of databases. See vignette("new-sql-backend") for instruction on how to create your own (#568).

    • +

  • src_mysql() gains a method for explain().

    • +

  • When mutate() creates a new variable that uses a window function, automatically wrap the result in a subquery (#484).

    • +

  • Correct SQL generation for first() and last() (#531).

    • +

  • order_by() now works in conjunction with window functions in databases that support them.

    • +
+
+
+

+Data frames/tbl_df +

+
    +

  • All verbs now understand how to work with difftime() (#390) and AsIs (#453) objects. They all check that colnames are unique (#483), and are more robust when columns are not present (#348, #569, #600).

    • +
  • +

    Hybrid evaluation bugs fixed:

    +
      +

    • Call substitution stopped too early when a sub expression contained a $ (#502).

      • +

    • Handle :: and ::: (#412).

      • +

    • cumany() and cumall() properly handle NA (#408).

      • +

    • nth() now correctly preserve the class when using dates, times and factors (#509).

      • +

    • no longer substitutes within order_by() because order_by() needs to do its own NSE (#169).

      • +
    +
    • +

  • [.tbl_df always returns a tbl_df (i.e. drop = FALSE is the default) (#587, #610). [.grouped_df preserves important output attributes (#398).

    • +

  • arrange() keeps the grouping structure of grouped data (#491, #605), and preserves input classes (#563).

    • +

  • contains() accidentally matched regular expressions, now it passes fixed = TRUE to grep() (#608).

    • +

  • filter() asserts all variables are white listed (#566).

    • +

  • mutate() makes a rowwise_df when given a rowwise_df (#463).

    • +

  • rbind_all() creates tbl_df objects instead of raw data.frames.

    • +

  • If select() doesn’t match any variables, it returns a 0-column data frame, instead of the original (#498). It no longer fails when if some columns are not named (#492)

    • +

  • sample_n() and sample_frac() methods for data.frames exported. (#405, @alyst)

    • +

  • A grouped data frame may have 0 groups (#486). Grouped df objects gain some basic validity checking, which should prevent some crashes related to corrupt grouped_df objects made by rbind() (#606).

    • +

  • More coherence when joining columns of compatible but different types, e.g. when joining a character vector and a factor (#455), or a numeric and integer (#450)

    • +

  • mutate() works for on zero-row grouped data frame, and with list columns (#555).

    • +

  • LazySubset was confused about input data size (#452).

    • +

  • Internal n_distinct() is stricter about it’s inputs: it requires one symbol which must be from the data frame (#567).

    • +

  • rbind_*() handle data frames with 0 rows (#597). They fill character vector columns with NA instead of blanks (#595). They work with list columns (#463).

    • +

  • Improved handling of encoding for column names (#636).

    • +

  • Improved handling of hybrid evaluation re $ and @ (#645).

    • +
+
+
+

+Data tables

+
    +

  • Fix major omission in tbl_dt() and grouped_dt() methods - I was accidentally doing a deep copy on every result :(

    • +

  • summarise() and group_by() now retain over-allocation when working with data.tables (#475, @arunsrinivasan).

    • +

  • joining two data.tables now correctly dispatches to data table methods, and result is a data table (#470)

    • +
+
+
+

+Cubes

+
    +
  • +summarise.tbl_cube() works with single grouping variable (#480).
    • +
+
+
+
+
+

+dplyr 0.2

+
+

+Piping

+

dplyr now imports %>% from magrittr (#330). I recommend that you use this instead of %.% because it is easier to type (since you can hold down the shift key) and is more flexible. With you %>%, you can control which argument on the RHS recieves the LHS by using the pronoun .. This makes %>% more useful with base R functions because they don’t always take the data frame as the first argument. For example you could pipe mtcars to xtabs() with:

+
mtcars %>% xtabs( ~ cyl + vs, data = .)
+

Thanks to @smbache for the excellent magrittr package. dplyr only provides %>% from magrittr, but it contains many other useful functions. To use them, load magrittr explicitly: library(magrittr). For more details, see vignette("magrittr").

+

%.% will be deprecated in a future version of dplyr, but it won’t happen for a while. I’ve also deprecated chain() to encourage a single style of dplyr usage: please use %>% instead.

+
+
+

+Do

+

do() has been completely overhauled. There are now two ways to use it, either with multiple named arguments or a single unnamed arguments. group_by() + do() is equivalent to plyr::dlply, except it always returns a data frame.

+

If you use named arguments, each argument becomes a list-variable in the output. A list-variable can contain any arbitrary R object so it’s particularly well suited for storing models.

+
library(dplyr)
+models <- mtcars %>% group_by(cyl) %>% do(lm = lm(mpg ~ wt, data = .))
+models %>% summarise(rsq = summary(lm)$r.squared)
+

If you use an unnamed argument, the result should be a data frame. This allows you to apply arbitrary functions to each group.

+
mtcars %>% group_by(cyl) %>% do(head(., 1))
+

Note the use of the . pronoun to refer to the data in the current group.

+

do() also has an automatic progress bar. It appears if the computation takes longer than 5 seconds and lets you know (approximately) how much longer the job will take to complete.

+
+
+

+New verbs

+

dplyr 0.2 adds three new verbs:

+
    +

  • glimpse() makes it possible to see all the columns in a tbl, displaying as much data for each variable as can be fit on a single line.

    • +

  • sample_n() randomly samples a fixed number of rows from a tbl; sample_frac() randomly samples a fixed fraction of rows. Only works for local data frames and data tables (#202).

    • +

  • summarise_each() and mutate_each() make it easy to apply one or more functions to multiple columns in a tbl (#178).

    • +
+
+
+

+Minor improvements

+
    +

  • If you load plyr after dplyr, you’ll get a message suggesting that you load plyr first (#347).

    • +

  • as.tbl_cube() gains a method for matrices (#359, @paulstaab)

    • +

  • compute() gains temporary argument so you can control whether the results are temporary or permanent (#382, @cpsievert)

    • +

  • group_by() now defaults to add = FALSE so that it sets the grouping variables rather than adding to the existing list. I think this is how most people expected group_by to work anyway, so it’s unlikely to cause problems (#385).

    • +

  • Support for MonetDB tables with src_monetdb() (#8, thanks to @hannesmuehleisen).

    • +
  • +

    New vignettes:

    +
      +

    • memory vignette which discusses how dplyr minimises memory usage for local data frames (#198).

      • +

    • new-sql-backend vignette which discusses how to add a new SQL backend/source to dplyr.

      • +
    +
    • +

  • changes() output more clearly distinguishes which columns were added or deleted.

    • +

  • explain() is now generic.

    • +

  • dplyr is more careful when setting the keys of data tables, so it never accidentally modifies an object that it doesn’t own. It also avoids unnecessary key setting which negatively affected performance. (#193, #255).

    • +

  • print() methods for tbl_df, tbl_dt and tbl_sql gain n argument to control the number of rows printed (#362). They also works better when you have columns containing lists of complex objects.

    • +

  • row_number() can be called without arguments, in which case it returns the same as 1:n() (#303).

    • +

  • "comment" attribute is allowed (white listed) as well as names (#346).

    • +

  • hybrid versions of min, max, mean, var, sd and sum handle the na.rm argument (#168). This should yield substantial performance improvements for those functions.

    • +

  • Special case for call to arrange() on a grouped data frame with no arguments. (#369)

    • +
+
+
+

+Bug fixes

+
    +

  • Code adapted to Rcpp > 0.11.1

    • +

  • internal DataDots class protects against missing variables in verbs (#314), including the case where ... is missing. (#338)

    • +

  • all.equal.data.frame from base is no longer bypassed. we now have all.equal.tbl_df and all.equal.tbl_dt methods (#332).

    • +

  • arrange() correctly handles NA in numeric vectors (#331) and 0 row data frames (#289).

    • +

  • copy_to.src_mysql() now works on windows (#323)

    • +

  • *_join() doesn’t reorder column names (#324).

    • +

  • rbind_all() is stricter and only accepts list of data frames (#288)

    • +

  • rbind_* propagates time zone information for POSIXct columns (#298).

    • +

  • rbind_* is less strict about type promotion. The numeric Collecter allows collection of integer and logical vectors. The integer Collecter also collects logical values (#321).

    • +

  • internal sum correctly handles integer (under/over)flow (#308).

    • +

  • summarise() checks consistency of outputs (#300) and drops names attribute of output columns (#357).

    • +

  • join functions throw error instead of crashing when there are no common variables between the data frames, and also give a better error message when only one data frame has a by variable (#371).

    • +

  • top_n() returns n rows instead of n - 1 (@leondutoit, #367).

    • +

  • SQL translation always evaluates subsetting operators ($, [, [[) locally. (#318).

    • +

  • select() now renames variables in remote sql tbls (#317) and
    +implicitly adds grouping variables (#170).

    • +

  • internal grouped_df_impl function errors if there are no variables to group by (#398).

    • +

  • n_distinct did not treat NA correctly in the numeric case #384.

    • +

  • Some compiler warnings triggered by -Wall or -pedantic have been eliminated.

    • +

  • group_by only creates one group for NA (#401).

    • +

  • Hybrid evaluator did not evaluate expression in correct environment (#403).

    • +
+
+
+
+

+dplyr 0.1.3

+
+

+Bug fixes

+
    +

  • select() actually renames columns in a data table (#284).

    • +

  • rbind_all() and rbind_list() now handle missing values in factors (#279).

    • +

  • SQL joins now work better if names duplicated in both x and y tables (#310).

    • +

  • Builds against Rcpp 0.11.1

    • +

  • select() correctly works with the vars attribute (#309).

    • +

  • Internal code is stricter when deciding if a data frame is grouped (#308): this avoids a number of situations which previously causedd .

    • +

  • More data frame joins work with missing values in keys (#306).

    • +
+
+
+
+

+dplyr 0.1.2

+
+

+New features

+
    +

  • select() is substantially more powerful. You can use named arguments to rename existing variables, and new functions starts_with(), ends_with(), contains(), matches() and num_range() to select variables based on their names. It now also makes a shallow copy, substantially reducing its memory impact (#158, #172, #192, #232).

    • +

  • summarize() added as alias for summarise() for people from countries that don’t don’t spell things correctly ;) (#245)

    • +
+
+
+

+Bug fixes

+
    +

  • filter() now fails when given anything other than a logical vector, and correctly handles missing values (#249). filter.numeric() proxies stats::filter() so you can continue to use filter() function with numeric inputs (#264).

    • +

  • summarise() correctly uses newly created variables (#259).

    • +

  • mutate() correctly propagates attributes (#265) and mutate.data.frame() correctly mutates the same variable repeatedly (#243).

    • +

  • lead() and lag() preserve attributes, so they now work with dates, times and factors (#166).

    • +

  • n() never accepts arguments (#223).

    • +

  • row_number() gives correct results (#227).

    • +

  • rbind_all() silently ignores data frames with 0 rows or 0 columns (#274).

    • +

  • group_by() orders the result (#242). It also checks that columns are of supported types (#233, #276).

    • +

  • The hybrid evaluator did not handle some expressions correctly, for example in if(n() > 5) 1 else 2 the subexpression n() was not substituted correctly. It also correctly processes $ (#278).

    • +

  • arrange() checks that all columns are of supported types (#266). It also handles list columns (#282).

    • +

  • Working towards Solaris compatibility.

    • +

  • Benchmarking vignette temporarily disabled due to microbenchmark problems reported by BDR.

    • +
+
+
+
+

+dplyr 0.1.1

+
+

+Improvements

+
    +

  • new location() and changes() functions which provide more information about how data frames are stored in memory so that you can see what gets copied.

    • +

  • renamed explain_tbl() to explain() (#182).

    • +

  • tally() gains sort argument to sort output so highest counts come first (#173).

    • +

  • ungroup.grouped_df(), tbl_df(), as.data.frame.tbl_df() now only make shallow copies of their inputs (#191).

    • +

  • The benchmark-baseball vignette now contains fairer (including grouping times) comparisons with data.table. (#222)

    • +
+
+
+

+Bug fixes

+
    +

  • filter() (#221) and summarise() (#194) correctly propagate attributes.

    • +

  • summarise() throws an error when asked to summarise an unknown variable instead of crashing (#208).

    • +

  • group_by() handles factors with missing values (#183).

    • +

  • filter() handles scalar results (#217) and better handles scoping, e.g. filter(., variable) where variable is defined in the function that calls filter. It also handles T and F as aliases to TRUE and FALSE if there are no T or F variables in the data or in the scope.

    • +

  • select.grouped_df fails when the grouping variables are not included in the selected variables (#170)

    • +

  • all.equal.data.frame() handles a corner case where the data frame has NULL names (#217)

    • +

  • mutate() gives informative error message on unsupported types (#179)

    • +

  • dplyr source package no longer includes pandas benchmark, reducing download size from 2.8 MB to 0.5 MB.

    • +
+
+
+
+
+ + + +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/pkgdown.css b/docs/pkgdown.css new file mode 100644 index 0000000000..d038ec69a5 --- /dev/null +++ b/docs/pkgdown.css @@ -0,0 +1,202 @@ +img.icon { + float: left; + margin-left: -35px; + width: 30px; + height: 30px; +} + +/* Fixes for fixed navbar --------------------------*/ + +body { + position: relative; + padding-top: 65px; +} + +.contents h1, .contents h2, .contents h3, .contents h4 { + padding-top: 65px; + margin-top: -45px; +} + +.page-header { + margin-top: 0; +} + +/* Table of contents --------------------------*/ + +#sidebar { + /* + Needed to avoid bug in sticky-kit: + https://github.com/leafo/sticky-kit/issues/169 + */ + position:static; +} + +#sidebar h2 { + font-size: 1.6em; + margin-top: 1em; + margin-bottom: 0.25em; +} + +#sidebar .list-unstyled li { + margin-bottom: 0.5em; + line-height: 1.4; +} + +#sidebar small { + color: #777; +} + + +/* Syntax highlighting ---------------------------------------------------- */ + +.fl,.number {color:rgb(21,20,181);} +.fu,.functioncall {color:#264D66 ;} +.ch,.st,.string {color:#375D81 ;} +.kw,.keyword {font-weight:600;} +.argument {color:#264D66 ;} +.co,.comment {color: #333;} +.formalargs {color: #264D66;} +.eqformalargs {color:#264D66;} +.slot {font-style:italic;} +.symbol {color:black ;} +.prompt {color:black ;} + +pre a { + font-weight: bolder; +} + +pre img { + background-color: #fff; + display: block; +} + +/* Status --------------------------- */ + +.status-container { + padding-top:32px; +} + +.status-container a { + display: block; + margin-bottom: 5px; +} + +/* For shrinking navbar ------------------ */ + +/* For big header + + &-brand { + font-family: $font-family-monospace; + font-weight: normal; + font-size: 48px; + padding: 35px 15px; + + padding-left: 84px; + background-image:url(../logo.png); + background-size: 60px auto; + background-repeat: no-repeat; + background-position: 15px center; + + } +*/ + + +/* Reference index & topics ----------------------------------------------- */ + +.ref-index th {font-weight: normal;} +.ref-index h2 {font-size: 20px;} + +.ref-index td {vertical-align: top;} +.ref-index .alias {width: 40%;} +.ref-index .title {width: 60%;} + +.ref-index .alias {width: 40%;} +.ref-index .title {width: 60%;} + +.ref-arguments th {text-align: right; padding-right: 10px;} +.ref-arguments th, .ref-arguments td {vertical-align: top;} +.ref-arguments .name {width: 20%;} +.ref-arguments .desc {width: 80%;} + +/* For the rstudio footer ------- */ + +footer { + margin-top: 45px; + padding: 35px 0 36px; + border-top: 1px solid #e5e5e5; + + display: flex; + color: #666; +} +footer p { + margin-bottom: 0; +} +footer .tidyverse { + flex: 1; +} +footer .author { + flex: 1; + text-align: right; +} + +/* --------------------- darken code link color */ + +code a { + color: #375f84; + font-weight: 600; +} + +/* ---------------------- hover anchor tags */ + +.hasAnchor { + margin-left: -30px; +} + +a.anchor { + display:inline-block; + width: 30px; + height: 30px; + visibility: hidden; + + background-image: url(./link.svg); + background-repeat: no-repeat; + background-size: 20px 20px; + background-position: center center; +} + +.hasAnchor:hover a.anchor { + visibility: visible; +} + +/* Tweak appearance of navigation in sidebar ---------------------- */ + +#sidebar .nav { + padding-left: 0px; + list-style-type: none; + color: #5a9ddb; +} + +#sidebar .nav > li { + padding: 10px 0 0px 20px; + display: list-item; + line-height: 20px; + background-image: url(./tocBullet.svg); + background-repeat: no-repeat; + background-size: 16px 280px; + background-position: left 0px; +} + +#sidebar .nav > li.active { + background-position: left -240px; +} + +#sidebar a { + padding: 0px; + color: #5a9ddb; + background-color: transparent; +} + +#sidebar a:hover { + background-color: transparent; + text-decoration: underline; +} diff --git a/docs/pkgdown.js b/docs/pkgdown.js new file mode 100644 index 0000000000..da3b067dd2 --- /dev/null +++ b/docs/pkgdown.js @@ -0,0 +1,8 @@ +$(function() { + $("#sidebar").stick_in_parent({ + offset_top: $("#sidebar").offset().top + }); + $('body').scrollspy({ + target: '#sidebar' + }); +}); diff --git a/docs/reference/add_rownames.html b/docs/reference/add_rownames.html new file mode 100644 index 0000000000..0c8eb5f95a --- /dev/null +++ b/docs/reference/add_rownames.html @@ -0,0 +1,167 @@ + + + + + + + + +Convert row names to an explicit variable. — add_rownames • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Convert row names to an explicit variable.

+
+ + +

Deprecated, use tibble::rownames_to_column() instead.

+ + + 
add_rownames(df, var = "rowname")
+ +

Arguments

+ + + + + + + + + + +
df

Input data frame with rownames.

var

Name of variable to use

+ + +

Examples

+ 
mtcars %>% tbl_df()
#> # A tibble: 32 × 11
+#>      mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
+#> *  <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
+#> 1   21.0     6 160.0   110  3.90 2.620 16.46     0     1     4     4
+#> 2   21.0     6 160.0   110  3.90 2.875 17.02     0     1     4     4
+#> 3   22.8     4 108.0    93  3.85 2.320 18.61     1     1     4     1
+#> 4   21.4     6 258.0   110  3.08 3.215 19.44     1     0     3     1
+#> 5   18.7     8 360.0   175  3.15 3.440 17.02     0     0     3     2
+#> 6   18.1     6 225.0   105  2.76 3.460 20.22     1     0     3     1
+#> 7   14.3     8 360.0   245  3.21 3.570 15.84     0     0     3     4
+#> 8   24.4     4 146.7    62  3.69 3.190 20.00     1     0     4     2
+#> 9   22.8     4 140.8    95  3.92 3.150 22.90     1     0     4     2
+#> 10  19.2     6 167.6   123  3.92 3.440 18.30     1     0     4     4
+#> # ... with 22 more rows

+mtcars %>% add_rownames()
#> Warning: Deprecated, use tibble::rownames_to_column() instead.
#> # A tibble: 32 × 12
+#>              rowname   mpg   cyl  disp    hp  drat    wt  qsec    vs    am
+#>                <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
+#> 1          Mazda RX4  21.0     6 160.0   110  3.90 2.620 16.46     0     1
+#> 2      Mazda RX4 Wag  21.0     6 160.0   110  3.90 2.875 17.02     0     1
+#> 3         Datsun 710  22.8     4 108.0    93  3.85 2.320 18.61     1     1
+#> 4     Hornet 4 Drive  21.4     6 258.0   110  3.08 3.215 19.44     1     0
+#> 5  Hornet Sportabout  18.7     8 360.0   175  3.15 3.440 17.02     0     0
+#> 6            Valiant  18.1     6 225.0   105  2.76 3.460 20.22     1     0
+#> 7         Duster 360  14.3     8 360.0   245  3.21 3.570 15.84     0     0
+#> 8          Merc 240D  24.4     4 146.7    62  3.69 3.190 20.00     1     0
+#> 9           Merc 230  22.8     4 140.8    95  3.92 3.150 22.90     1     0
+#> 10          Merc 280  19.2     6 167.6   123  3.92 3.440 18.30     1     0
+#> # ... with 22 more rows, and 2 more variables: gear <dbl>, carb <dbl>
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/all_equal.html b/docs/reference/all_equal.html new file mode 100644 index 0000000000..3216e7f3c3 --- /dev/null +++ b/docs/reference/all_equal.html @@ -0,0 +1,177 @@ + + + + + + + + +Flexible equality comparison for data frames. — all_equal • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Flexible equality comparison for data frames.

+
+ + +

You can use all_equal() with any data frame, and dplyr also provides +tbl_df methods for all.equal().

+ + + 
all_equal(target, current, ignore_col_order = TRUE, ignore_row_order = TRUE,
+  convert = FALSE, ...)
+
+# S3 method for tbl_df
+all.equal(target, current, ignore_col_order = TRUE,
+  ignore_row_order = TRUE, convert = FALSE, ...)
+ +

Arguments

+ + + + + + + + + + + + + + + + + + + + + + +
target, current

Two data frames to compare.

ignore_col_order

Should order of columns be ignored?

ignore_row_order

Should order of rows be ignored?

convert

Should similar classes be converted? Currently this will +convert factor to character and integer to double.

...

Ignored. Needed for compatibility with all.equal().

+ +

Value

+ +

TRUE if equal, otherwise a character vector describing +the reasons why they're not equal. Use isTRUE() if using the +result in an if expression.

+ + +

Examples

+ 
scramble <- function(x) x[sample(nrow(x)), sample(ncol(x))]
+
+# By default, ordering of rows and columns ignored
+all_equal(mtcars, scramble(mtcars))
#> [1] TRUE

+# But those can be overriden if desired
+all_equal(mtcars, scramble(mtcars), ignore_col_order = FALSE)
#> [1] "Same column names, but different order"
all_equal(mtcars, scramble(mtcars), ignore_row_order = FALSE)
#> [1] "Same row values, but different order"

+# By default all_equal is sensitive to variable differences
+df1 <- data.frame(x = "a")
+df2 <- data.frame(x = factor("a"))
+all_equal(df1, df2)
#> [1] TRUE
# But you can request dplyr convert similar types
+all_equal(df1, df2, convert = TRUE)
#> [1] TRUE
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/all_vars.html b/docs/reference/all_vars.html new file mode 100644 index 0000000000..21879f2c4d --- /dev/null +++ b/docs/reference/all_vars.html @@ -0,0 +1,151 @@ + + + + + + + + +Apply predicate to all variables. — all_vars • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Apply predicate to all variables.

+
+ + +

These quoting functions signal to scoped filtering verbs +(e.g. filter_if() or filter_all()) that a predicate expression +should be applied to all relevant variables. The all_vars() +variant takes the intersection of the predicate expressions with +& while the any_vars() variant takes the union with |.

+ + + 
all_vars(expr)
+
+any_vars(expr)
+ +

Arguments

+ + + + + + +
expr

A predicate expression. This variable supports +unquoting and will be evaluated in the +context of the data frame. It should return a logical vector.

+

This argument is automatically quoted and later +evaluated in the context of the data +frame. It supports unquoting. See +vignette("programming") for an introduction to these concepts.

+ +

See also

+ +

funs() and vars() for other quoting functions that you +can use with scoped verbs.

+ + +
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/arrange.html b/docs/reference/arrange.html new file mode 100644 index 0000000000..4c4ee695dd --- /dev/null +++ b/docs/reference/arrange.html @@ -0,0 +1,278 @@ + + + + + + + + +Arrange rows by variables — arrange • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Arrange rows by variables

+
+ + +

Use desc() to sort a variable in descending order.

+ + + 
arrange(.data, ...)
+
+# S3 method for grouped_df
+arrange(.data, ..., .by_group = FALSE)
+ +

Arguments

+ + + + + + + + + + + + + + +
.data

A tbl. All main verbs are S3 generics and provide methods +for tbl_df(), dtplyr::tbl_dt() and dbplyr::tbl_dbi().

...

Comma separated list of unquoted variable names. Use +desc() to sort a variable in descending order.

.by_group

If TRUE, will sort first by grouping variable. Applies to +grouped data frames only.

+ +

Value

+ +

An object of the same class as .data.

+ +

Locales

+ + +

The sort order for character vectors will depend on the collating sequence +of the locale in use: see locales().

+ +

Tidy data

+ + +

When applied to a data frame, row names are silently dropped. To preserve, +convert to an explicit variable with tibble::rownames_to_column().

+ +

See also

+ +

Other single table verbs: filter, + mutate, select, + slice, summarise

+ + +

Examples

+ 
arrange(mtcars, cyl, disp)
#>     mpg cyl  disp  hp drat    wt  qsec vs am gear carb
+#> 1  33.9   4  71.1  65 4.22 1.835 19.90  1  1    4    1
+#> 2  30.4   4  75.7  52 4.93 1.615 18.52  1  1    4    2
+#> 3  32.4   4  78.7  66 4.08 2.200 19.47  1  1    4    1
+#> 4  27.3   4  79.0  66 4.08 1.935 18.90  1  1    4    1
+#> 5  30.4   4  95.1 113 3.77 1.513 16.90  1  1    5    2
+#> 6  22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1
+#> 7  21.5   4 120.1  97 3.70 2.465 20.01  1  0    3    1
+#> 8  26.0   4 120.3  91 4.43 2.140 16.70  0  1    5    2
+#> 9  21.4   4 121.0 109 4.11 2.780 18.60  1  1    4    2
+#> 10 22.8   4 140.8  95 3.92 3.150 22.90  1  0    4    2
+#> 11 24.4   4 146.7  62 3.69 3.190 20.00  1  0    4    2
+#> 12 19.7   6 145.0 175 3.62 2.770 15.50  0  1    5    6
+#> 13 21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4
+#> 14 21.0   6 160.0 110 3.90 2.875 17.02  0  1    4    4
+#> 15 19.2   6 167.6 123 3.92 3.440 18.30  1  0    4    4
+#> 16 17.8   6 167.6 123 3.92 3.440 18.90  1  0    4    4
+#> 17 18.1   6 225.0 105 2.76 3.460 20.22  1  0    3    1
+#> 18 21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1
+#> 19 16.4   8 275.8 180 3.07 4.070 17.40  0  0    3    3
+#> 20 17.3   8 275.8 180 3.07 3.730 17.60  0  0    3    3
+#> 21 15.2   8 275.8 180 3.07 3.780 18.00  0  0    3    3
+#> 22 15.0   8 301.0 335 3.54 3.570 14.60  0  1    5    8
+#> 23 15.2   8 304.0 150 3.15 3.435 17.30  0  0    3    2
+#> 24 15.5   8 318.0 150 2.76 3.520 16.87  0  0    3    2
+#> 25 13.3   8 350.0 245 3.73 3.840 15.41  0  0    3    4
+#> 26 15.8   8 351.0 264 4.22 3.170 14.50  0  1    5    4
+#> 27 18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2
+#> 28 14.3   8 360.0 245 3.21 3.570 15.84  0  0    3    4
+#> 29 19.2   8 400.0 175 3.08 3.845 17.05  0  0    3    2
+#> 30 14.7   8 440.0 230 3.23 5.345 17.42  0  0    3    4
+#> 31 10.4   8 460.0 215 3.00 5.424 17.82  0  0    3    4
+#> 32 10.4   8 472.0 205 2.93 5.250 17.98  0  0    3    4
arrange(mtcars, desc(disp))
#>     mpg cyl  disp  hp drat    wt  qsec vs am gear carb
+#> 1  10.4   8 472.0 205 2.93 5.250 17.98  0  0    3    4
+#> 2  10.4   8 460.0 215 3.00 5.424 17.82  0  0    3    4
+#> 3  14.7   8 440.0 230 3.23 5.345 17.42  0  0    3    4
+#> 4  19.2   8 400.0 175 3.08 3.845 17.05  0  0    3    2
+#> 5  18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2
+#> 6  14.3   8 360.0 245 3.21 3.570 15.84  0  0    3    4
+#> 7  15.8   8 351.0 264 4.22 3.170 14.50  0  1    5    4
+#> 8  13.3   8 350.0 245 3.73 3.840 15.41  0  0    3    4
+#> 9  15.5   8 318.0 150 2.76 3.520 16.87  0  0    3    2
+#> 10 15.2   8 304.0 150 3.15 3.435 17.30  0  0    3    2
+#> 11 15.0   8 301.0 335 3.54 3.570 14.60  0  1    5    8
+#> 12 16.4   8 275.8 180 3.07 4.070 17.40  0  0    3    3
+#> 13 17.3   8 275.8 180 3.07 3.730 17.60  0  0    3    3
+#> 14 15.2   8 275.8 180 3.07 3.780 18.00  0  0    3    3
+#> 15 21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1
+#> 16 18.1   6 225.0 105 2.76 3.460 20.22  1  0    3    1
+#> 17 19.2   6 167.6 123 3.92 3.440 18.30  1  0    4    4
+#> 18 17.8   6 167.6 123 3.92 3.440 18.90  1  0    4    4
+#> 19 21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4
+#> 20 21.0   6 160.0 110 3.90 2.875 17.02  0  1    4    4
+#> 21 24.4   4 146.7  62 3.69 3.190 20.00  1  0    4    2
+#> 22 19.7   6 145.0 175 3.62 2.770 15.50  0  1    5    6
+#> 23 22.8   4 140.8  95 3.92 3.150 22.90  1  0    4    2
+#> 24 21.4   4 121.0 109 4.11 2.780 18.60  1  1    4    2
+#> 25 26.0   4 120.3  91 4.43 2.140 16.70  0  1    5    2
+#> 26 21.5   4 120.1  97 3.70 2.465 20.01  1  0    3    1
+#> 27 22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1
+#> 28 30.4   4  95.1 113 3.77 1.513 16.90  1  1    5    2
+#> 29 27.3   4  79.0  66 4.08 1.935 18.90  1  1    4    1
+#> 30 32.4   4  78.7  66 4.08 2.200 19.47  1  1    4    1
+#> 31 30.4   4  75.7  52 4.93 1.615 18.52  1  1    4    2
+#> 32 33.9   4  71.1  65 4.22 1.835 19.90  1  1    4    1

+# grouped arrange ignores groups
+by_cyl <- mtcars %>% group_by(cyl)
+by_cyl %>% arrange(desc(wt))
#> Source: local data frame [32 x 11]
+#> Groups: cyl [3]
+#> 
+#>      mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
+#>    <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
+#> 1   10.4     8 460.0   215  3.00 5.424 17.82     0     0     3     4
+#> 2   14.7     8 440.0   230  3.23 5.345 17.42     0     0     3     4
+#> 3   10.4     8 472.0   205  2.93 5.250 17.98     0     0     3     4
+#> 4   16.4     8 275.8   180  3.07 4.070 17.40     0     0     3     3
+#> 5   19.2     8 400.0   175  3.08 3.845 17.05     0     0     3     2
+#> 6   13.3     8 350.0   245  3.73 3.840 15.41     0     0     3     4
+#> 7   15.2     8 275.8   180  3.07 3.780 18.00     0     0     3     3
+#> 8   17.3     8 275.8   180  3.07 3.730 17.60     0     0     3     3
+#> 9   14.3     8 360.0   245  3.21 3.570 15.84     0     0     3     4
+#> 10  15.0     8 301.0   335  3.54 3.570 14.60     0     1     5     8
+#> # ... with 22 more rows
# Unless you specifically ask:
+by_cyl %>% arrange(desc(wt), .by_group = TRUE)
#> Source: local data frame [32 x 11]
+#> Groups: cyl [3]
+#> 
+#>      mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
+#>    <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
+#> 1   24.4     4 146.7    62  3.69 3.190 20.00     1     0     4     2
+#> 2   22.8     4 140.8    95  3.92 3.150 22.90     1     0     4     2
+#> 3   21.4     4 121.0   109  4.11 2.780 18.60     1     1     4     2
+#> 4   21.5     4 120.1    97  3.70 2.465 20.01     1     0     3     1
+#> 5   22.8     4 108.0    93  3.85 2.320 18.61     1     1     4     1
+#> 6   32.4     4  78.7    66  4.08 2.200 19.47     1     1     4     1
+#> 7   26.0     4 120.3    91  4.43 2.140 16.70     0     1     5     2
+#> 8   27.3     4  79.0    66  4.08 1.935 18.90     1     1     4     1
+#> 9   33.9     4  71.1    65  4.22 1.835 19.90     1     1     4     1
+#> 10  30.4     4  75.7    52  4.93 1.615 18.52     1     1     4     2
+#> # ... with 22 more rows
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/as.table.tbl_cube.html b/docs/reference/as.table.tbl_cube.html new file mode 100644 index 0000000000..2708fc78a4 --- /dev/null +++ b/docs/reference/as.table.tbl_cube.html @@ -0,0 +1,150 @@ + + + + + + + + +Coerce a <code>tbl_cube</code> to other data structures — as.table.tbl_cube • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Coerce a tbl_cube to other data structures

+
+ + +

Supports conversion to tables, data frames, tibbles.

+

For a cube, the data frame returned by +tibble::as_data_frame() resulting data frame contains the +dimensions as character values (and not as factors).

+ + + 
# S3 method for tbl_cube
+as.table(x, ..., measure = 1L)
+
+# S3 method for tbl_cube
+as.data.frame(x, ...)
+
+# S3 method for tbl_cube
+as_data_frame(x, ...)
+ +

Arguments

+ + + + + + + + + + + + + + +
x

a tbl_cube

...

Passed on to individual methods; otherwise ignored.

measure

A measure name or index, default: the first measure

+ + +
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/as.tbl_cube.html b/docs/reference/as.tbl_cube.html new file mode 100644 index 0000000000..1483dd89fa --- /dev/null +++ b/docs/reference/as.tbl_cube.html @@ -0,0 +1,162 @@ + + + + + + + + +Coerce an existing data structure into a <code>tbl_cube</code> — as.tbl_cube • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Coerce an existing data structure into a tbl_cube

+
+ + +

Coerce an existing data structure into a tbl_cube

+ + + 
as.tbl_cube(x, ...)
+
+# S3 method for array
+as.tbl_cube(x, dim_names = names(dimnames(x)),
+  met_name = deparse(substitute(x)), ...)
+
+# S3 method for table
+as.tbl_cube(x, dim_names = names(dimnames(x)),
+  met_name = "Freq", ...)
+
+# S3 method for matrix
+as.tbl_cube(x, dim_names = names(dimnames(x)),
+  met_name = deparse(substitute(x)), ...)
+
+# S3 method for data.frame
+as.tbl_cube(x, dim_names = NULL,
+  met_name = guess_met(x), ...)
+ +

Arguments

+ + + + + + + + + + + + + + + + + + +
x

an object to convert. Built in methods will convert arrays, +tables and data frames.

...

Passed on to individual methods; otherwise ignored.

dim_names

names of the dimesions. Defaults to the names of

met_name

a string to use as the name for the measure +the dimnames().

+ + +
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/auto_copy.html b/docs/reference/auto_copy.html new file mode 100644 index 0000000000..faecc28303 --- /dev/null +++ b/docs/reference/auto_copy.html @@ -0,0 +1,143 @@ + + + + + + + + +Copy tables to same source, if necessary. — auto_copy • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Copy tables to same source, if necessary.

+
+ + +

Copy tables to same source, if necessary.

+ + + 
auto_copy(x, y, copy = FALSE, ...)
+ +

Arguments

+ + + + + + + + + + + + + + +
x, y

y will be copied to x, if neccessary.

copy

If x and y are not from the same data source, +and copy is TRUE, then y will be copied into the +same src as x. This allows you to join tables across srcs, but +it is a potentially expensive operation so you must opt into it.

...

Other arguments passed on to methods.

+ + +
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/backend_dbplyr.html b/docs/reference/backend_dbplyr.html new file mode 100644 index 0000000000..b3518541f6 --- /dev/null +++ b/docs/reference/backend_dbplyr.html @@ -0,0 +1,230 @@ + + + + + + + + +Database and SQL generics. — backend_dbplyr • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Database and SQL generics.

+
+ + +

The sql_ generics are used to build the different types of SQL queries. +The default implementations in dbplyr generates ANSI 92 compliant SQL. +The db_ generics execute actions on the database. The default +implementations in dbplyr typically just call the standard DBI S4 +method.

+ + + 
db_desc(x)
+
+sql_translate_env(con)
+
+db_list_tables(con)
+
+db_has_table(con, table)
+
+db_data_type(con, fields)
+
+db_save_query(con, sql, name, temporary = TRUE, ...)
+
+db_begin(con, ...)
+
+db_commit(con, ...)
+
+db_rollback(con, ...)
+
+db_write_table(con, table, types, values, temporary = FALSE, ...)
+
+db_create_table(con, table, types, temporary = FALSE, ...)
+
+db_insert_into(con, table, values, ...)
+
+db_create_indexes(con, table, indexes = NULL, unique = FALSE, ...)
+
+db_create_index(con, table, columns, name = NULL, unique = FALSE, ...)
+
+db_drop_table(con, table, force = FALSE, ...)
+
+db_analyze(con, table, ...)
+
+db_explain(con, sql, ...)
+
+db_query_fields(con, sql, ...)
+
+db_query_rows(con, sql, ...)
+
+sql_select(con, select, from, where = NULL, group_by = NULL,
+  having = NULL, order_by = NULL, limit = NULL, distinct = FALSE, ...)
+
+sql_subquery(con, from, name = random_table_name(), ...)
+
+sql_join(con, x, y, vars, type = "inner", by = NULL, ...)
+
+sql_semi_join(con, x, y, anti = FALSE, by = NULL, ...)
+
+sql_set_op(con, x, y, method)
+
+sql_escape_string(con, x)
+
+sql_escape_ident(con, x)
+ +

Arguments

+ + + + + + + + + + + + + + +
con

A database connection.

table

A string, the table name.

fields

A list of fields, as in a data frame.

+ +

Value

+ +

Usually a logical value indicating success. Most failures should generate +an error. However, db_has_table() should return NA if +temporary tables cannot be listed with DBI::dbListTables() (due to backend +API limitations for example). As a result, you methods will rely on the +backend to throw an error if a table exists when it shouldn't.

+ +

Details

+ +

A few backend methods do not call the standard DBI S4 methods including

    +

  • db_data_type(): Calls DBI::dbDataType() for every field +(e.g. data frame column) and returns a vector of corresponding SQL data +types

    • +

  • db_save_query(): Builds and executes a +CREATE [TEMPORARY] TABLE <table> ... SQL command.

    • +

  • db_create_index(): Builds and executes a +CREATE INDEX <name> ON <table> SQL command.

    • +

  • db_drop_table(): Builds and executes a +DROP TABLE [IF EXISTS] <table> SQL command.

    • +

  • db_analyze(): Builds and executes an +ANALYZE <table> SQL command.

    • +
+

Currently, copy_to() is the only user of db_begin(), db_commit(), +db_rollback(), db_write_table(), db_create_indexes(), db_drop_table() and +db_analyze(). If you find yourself overriding many of these +functions it may suggest that you should just override copy_to() +instead. + db_create_table() and db_insert_into() have been deprecated +in favour of db_write_table().

+ + +
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/band_members.html b/docs/reference/band_members.html new file mode 100644 index 0000000000..002f0ad187 --- /dev/null +++ b/docs/reference/band_members.html @@ -0,0 +1,162 @@ + + + + + + + + +Band membership — band_members • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Band membership

+
+ + +

These data sets describe band members of the Beatles and Rolling Stones. They +are toy data sets that can be displayed in their entirety on a slide (e.g. to +demonstrate a join).

+ + + 
band_members
+
+band_instruments
+
+band_instruments2
+ +

Format

+ +

Each is a tibble with two variables and three observations

+ +

Details

+ +

band_instruments and band_instruments2 contain the same data but use +different column names for the first column of the data set. +band_instruments uses name, which matches the name of the key column of +band_members; band_instruments2 uses artist, which does not.

+ + +

Examples

+ 
band_members
#> # A tibble: 3 × 2
+#>    name    band
+#>   <chr>   <chr>
+#> 1  Mick  Stones
+#> 2  John Beatles
+#> 3  Paul Beatles
band_instruments
#> # A tibble: 3 × 2
+#>    name  plays
+#>   <chr>  <chr>
+#> 1  John guitar
+#> 2  Paul   bass
+#> 3 Keith guitar
band_instruments2
#> # A tibble: 3 × 2
+#>   artist  plays
+#>    <chr>  <chr>
+#> 1   John guitar
+#> 2   Paul   bass
+#> 3  Keith guitar
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/bench_compare.html b/docs/reference/bench_compare.html new file mode 100644 index 0000000000..f5fd7e38c6 --- /dev/null +++ b/docs/reference/bench_compare.html @@ -0,0 +1,219 @@ + + + + + + + + +Evaluate, compare, benchmark operations of a set of srcs. — bench_compare • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Evaluate, compare, benchmark operations of a set of srcs.

+
+ + +

These functions support the comparison of results and timings across +multiple sources.

+ + + 
bench_tbls(tbls, op, ..., times = 10)
+
+compare_tbls(tbls, op, ref = NULL, compare = equal_data_frame, ...)
+
+compare_tbls2(tbls_x, tbls_y, op, ref = NULL, compare = equal_data_frame,
+  ...)
+
+eval_tbls(tbls, op)
+
+eval_tbls2(tbls_x, tbls_y, op)
+ +

Arguments

+ + + + + + + + + + + + + + + + + + + + + + + + + + +
tbls, tbls_x, tbls_y

A list of tbl()s.

op

A function with a single argument, called often with each +element of tbls.

…

For compare_tbls(): additional parameters passed on the +compare() function

+

For bench_tbls(): additional benchmarks to run.

times

For benchmarking, the number of times each operation is +repeated.

ref

For checking, an data frame to test results against. If not +supplied, defaults to the results from the first src.

compare

A function used to compare the results. Defaults to +equal_data_frame which ignores the order of rows and columns.

+ +

Value

+ +

eval_tbls(): a list of data frames. + +compare_tbls(): an invisible TRUE on success, otherwise +an error is thrown. + +bench_tbls(): an object of class +microbenchmark::microbenchmark()

+ +

See also

+ +

src_local() for working with local data

+ + +

Examples

+ 
## Not run: ------------------------------------
+# if (require("microbenchmark") && has_lahman()) {
+# lahman_local <- lahman_srcs("df", "sqlite")
+# teams <- lapply(lahman_local, function(x) x %>% tbl("Teams"))
+# 
+# compare_tbls(teams, function(x) x %>% filter(yearID == 2010))
+# bench_tbls(teams, function(x) x %>% filter(yearID == 2010))
+# 
+# # You can also supply arbitrary additional arguments to bench_tbls
+# # if there are other operations you'd like to compare.
+# bench_tbls(teams, function(x) x %>% filter(yearID == 2010),
+#    base = subset(Lahman::Teams, yearID == 2010))
+# 
+# # A more complicated example using multiple tables
+# setup <- function(src) {
+#   list(
+#     src %>% tbl("Batting") %>% filter(stint == 1) %>% select(playerID:H),
+#     src %>% tbl("Master") %>% select(playerID, birthYear)
+#   )
+# }
+# two_tables <- lapply(lahman_local, setup)
+# 
+# op <- function(tbls) {
+#   semi_join(tbls[[1]], tbls[[2]], by = "playerID")
+# }
+# # compare_tbls(two_tables, op)
+# bench_tbls(two_tables, op, times = 2)
+# 
+# }
+## ---------------------------------------------
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/between.html b/docs/reference/between.html new file mode 100644 index 0000000000..6c6f977c3c --- /dev/null +++ b/docs/reference/between.html @@ -0,0 +1,153 @@ + + + + + + + + +Do values in a numeric vector fall in specified range? — between • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Do values in a numeric vector fall in specified range?

+
+ + +

This is a shortcut for x >= left & x <= right, implemented +efficiently in C++ for local values, and translated to the +appropriate SQL for remote tables.

+ + + 
between(x, left, right)
+ +

Arguments

+ + + + + + + + + + +
x

A numeric vector of values

left, right

Boundary values

+ + +

Examples

+ 
x <- rnorm(1e2)
+x[between(x, -1, 1)]
#>  [1] -0.86072428  0.42123042  0.19439244 -0.69120544 -0.94410166 -0.71605867
+#>  [7]  0.91107847 -0.77219209 -0.78207767 -0.43219524 -0.66756477  0.91187392
+#> [13]  0.20538939 -0.78938814  0.58807712 -0.71128732  0.67638957 -0.23276176
+#> [19]  0.63747287 -0.68326687 -0.97967535 -0.46251911  0.74786883 -0.80534353
+#> [25]  0.77599004  0.70359786  0.71540139  0.40152349  0.40427794 -0.77705556
+#> [31] -0.28045548  0.29738725 -0.23564615  0.04433469 -0.32849189  0.46205231
+#> [37]  0.69362435 -0.70859443 -0.20889688  0.35227917 -0.77928540  0.70005531
+#> [43]  0.11759261 -0.28362275  0.49790884  0.38624909  0.71752478  0.13191018
+#> [49] -0.92066340  0.26726762 -0.23854626 -0.78447669 -0.82776894  0.94433756
+#> [55] -0.63969296 -0.21714460  0.57991478 -0.95260348 -0.96767371  0.79245114
+#> [61] -0.93697260  0.86130054
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/bind.html b/docs/reference/bind.html new file mode 100644 index 0000000000..eec27e58f4 --- /dev/null +++ b/docs/reference/bind.html @@ -0,0 +1,299 @@ + + + + + + + + +Efficiently bind multiple data frames by row and column. — bind • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Efficiently bind multiple data frames by row and column.

+
+ + +

This is an efficient implementation of the common pattern of +do.call(rbind, dfs) or do.call(cbind, dfs) for binding many +data frames into one. combine() acts like c() or +unlist() but uses consistent dplyr coercion rules.

+ + + 
bind_rows(..., .id = NULL)
+
+bind_cols(...)
+
+combine(...)
+ +

Arguments

+ + + + + + + + + + +
...

Data frames to combine.

+

Each argument can either be a data frame, a list that could be a data +frame, or a list of data frames.

+

When row-binding, columns are matched by name, and any missing +columns with be filled with NA.

+

When column-binding, rows are matched by position, so all data +frames must have the same number of rows. To match by value, not +position, see join.

.id

Data frame identifier.

+

When .id is supplied, a new column of identifiers is +created to link each row to its original data frame. The labels +are taken from the named arguments to bind_rows(). When a +list of data frames is supplied, the labels are taken from the +names of the list. If no names are found a numeric sequence is +used instead.

+ +

Value

+ +

bind_rows() and bind_cols() return the same type as +the first input, either a data frame, tbl_df, or grouped_df.

+ +

Details

+ +

The output of bind_rows() will contain a column if that column +appears in any of the inputs.

+ +

Deprecated functions

+ +

rbind_list() and rbind_all() have been deprecated. Instead use +bind_rows().

+ + +

Examples

+ 
one <- mtcars[1:4, ]
+two <- mtcars[11:14, ]
+
+# You can either supply data frames as arguments
+bind_rows(one, two)
#>    mpg cyl  disp  hp drat    wt  qsec vs am gear carb
+#> 1 21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4
+#> 2 21.0   6 160.0 110 3.90 2.875 17.02  0  1    4    4
+#> 3 22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1
+#> 4 21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1
+#> 5 17.8   6 167.6 123 3.92 3.440 18.90  1  0    4    4
+#> 6 16.4   8 275.8 180 3.07 4.070 17.40  0  0    3    3
+#> 7 17.3   8 275.8 180 3.07 3.730 17.60  0  0    3    3
+#> 8 15.2   8 275.8 180 3.07 3.780 18.00  0  0    3    3
# Or a single argument containing a list of data frames
+bind_rows(list(one, two))
#>    mpg cyl  disp  hp drat    wt  qsec vs am gear carb
+#> 1 21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4
+#> 2 21.0   6 160.0 110 3.90 2.875 17.02  0  1    4    4
+#> 3 22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1
+#> 4 21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1
+#> 5 17.8   6 167.6 123 3.92 3.440 18.90  1  0    4    4
+#> 6 16.4   8 275.8 180 3.07 4.070 17.40  0  0    3    3
+#> 7 17.3   8 275.8 180 3.07 3.730 17.60  0  0    3    3
+#> 8 15.2   8 275.8 180 3.07 3.780 18.00  0  0    3    3
bind_rows(split(mtcars, mtcars$cyl))
#>     mpg cyl  disp  hp drat    wt  qsec vs am gear carb
+#> 1  22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1
+#> 2  24.4   4 146.7  62 3.69 3.190 20.00  1  0    4    2
+#> 3  22.8   4 140.8  95 3.92 3.150 22.90  1  0    4    2
+#> 4  32.4   4  78.7  66 4.08 2.200 19.47  1  1    4    1
+#> 5  30.4   4  75.7  52 4.93 1.615 18.52  1  1    4    2
+#> 6  33.9   4  71.1  65 4.22 1.835 19.90  1  1    4    1
+#> 7  21.5   4 120.1  97 3.70 2.465 20.01  1  0    3    1
+#> 8  27.3   4  79.0  66 4.08 1.935 18.90  1  1    4    1
+#> 9  26.0   4 120.3  91 4.43 2.140 16.70  0  1    5    2
+#> 10 30.4   4  95.1 113 3.77 1.513 16.90  1  1    5    2
+#> 11 21.4   4 121.0 109 4.11 2.780 18.60  1  1    4    2
+#> 12 21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4
+#> 13 21.0   6 160.0 110 3.90 2.875 17.02  0  1    4    4
+#> 14 21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1
+#> 15 18.1   6 225.0 105 2.76 3.460 20.22  1  0    3    1
+#> 16 19.2   6 167.6 123 3.92 3.440 18.30  1  0    4    4
+#> 17 17.8   6 167.6 123 3.92 3.440 18.90  1  0    4    4
+#> 18 19.7   6 145.0 175 3.62 2.770 15.50  0  1    5    6
+#> 19 18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2
+#> 20 14.3   8 360.0 245 3.21 3.570 15.84  0  0    3    4
+#> 21 16.4   8 275.8 180 3.07 4.070 17.40  0  0    3    3
+#> 22 17.3   8 275.8 180 3.07 3.730 17.60  0  0    3    3
+#> 23 15.2   8 275.8 180 3.07 3.780 18.00  0  0    3    3
+#> 24 10.4   8 472.0 205 2.93 5.250 17.98  0  0    3    4
+#> 25 10.4   8 460.0 215 3.00 5.424 17.82  0  0    3    4
+#> 26 14.7   8 440.0 230 3.23 5.345 17.42  0  0    3    4
+#> 27 15.5   8 318.0 150 2.76 3.520 16.87  0  0    3    2
+#> 28 15.2   8 304.0 150 3.15 3.435 17.30  0  0    3    2
+#> 29 13.3   8 350.0 245 3.73 3.840 15.41  0  0    3    4
+#> 30 19.2   8 400.0 175 3.08 3.845 17.05  0  0    3    2
+#> 31 15.8   8 351.0 264 4.22 3.170 14.50  0  1    5    4
+#> 32 15.0   8 301.0 335 3.54 3.570 14.60  0  1    5    8

+# When you supply a column name with the `.id` argument, a new
+# column is created to link each row to its original data frame
+bind_rows(list(one, two), .id = "id")
#>   id  mpg cyl  disp  hp drat    wt  qsec vs am gear carb
+#> 1  1 21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4
+#> 2  1 21.0   6 160.0 110 3.90 2.875 17.02  0  1    4    4
+#> 3  1 22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1
+#> 4  1 21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1
+#> 5  2 17.8   6 167.6 123 3.92 3.440 18.90  1  0    4    4
+#> 6  2 16.4   8 275.8 180 3.07 4.070 17.40  0  0    3    3
+#> 7  2 17.3   8 275.8 180 3.07 3.730 17.60  0  0    3    3
+#> 8  2 15.2   8 275.8 180 3.07 3.780 18.00  0  0    3    3
bind_rows(list(a = one, b = two), .id = "id")
#>   id  mpg cyl  disp  hp drat    wt  qsec vs am gear carb
+#> 1  a 21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4
+#> 2  a 21.0   6 160.0 110 3.90 2.875 17.02  0  1    4    4
+#> 3  a 22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1
+#> 4  a 21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1
+#> 5  b 17.8   6 167.6 123 3.92 3.440 18.90  1  0    4    4
+#> 6  b 16.4   8 275.8 180 3.07 4.070 17.40  0  0    3    3
+#> 7  b 17.3   8 275.8 180 3.07 3.730 17.60  0  0    3    3
+#> 8  b 15.2   8 275.8 180 3.07 3.780 18.00  0  0    3    3
bind_rows("group 1" = one, "group 2" = two, .id = "groups")
#>    groups  mpg cyl  disp  hp drat    wt  qsec vs am gear carb
+#> 1 group 1 21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4
+#> 2 group 1 21.0   6 160.0 110 3.90 2.875 17.02  0  1    4    4
+#> 3 group 1 22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1
+#> 4 group 1 21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1
+#> 5 group 2 17.8   6 167.6 123 3.92 3.440 18.90  1  0    4    4
+#> 6 group 2 16.4   8 275.8 180 3.07 4.070 17.40  0  0    3    3
+#> 7 group 2 17.3   8 275.8 180 3.07 3.730 17.60  0  0    3    3
+#> 8 group 2 15.2   8 275.8 180 3.07 3.780 18.00  0  0    3    3

+# Columns don't need to match when row-binding
+bind_rows(data.frame(x = 1:3), data.frame(y = 1:4))
#>    x  y
+#> 1  1 NA
+#> 2  2 NA
+#> 3  3 NA
+#> 4 NA  1
+#> 5 NA  2
+#> 6 NA  3
+#> 7 NA  4
## Not run: ------------------------------------
+# # Rows do need to match when column-binding
+# bind_cols(data.frame(x = 1), data.frame(y = 1:2))
+## ---------------------------------------------
+
+bind_cols(one, two)
#>    mpg cyl disp  hp drat    wt  qsec vs am gear carb mpg1 cyl1 disp1 hp1 drat1
+#> 1 21.0   6  160 110 3.90 2.620 16.46  0  1    4    4 17.8    6 167.6 123  3.92
+#> 2 21.0   6  160 110 3.90 2.875 17.02  0  1    4    4 16.4    8 275.8 180  3.07
+#> 3 22.8   4  108  93 3.85 2.320 18.61  1  1    4    1 17.3    8 275.8 180  3.07
+#> 4 21.4   6  258 110 3.08 3.215 19.44  1  0    3    1 15.2    8 275.8 180  3.07
+#>    wt1 qsec1 vs1 am1 gear1 carb1
+#> 1 3.44  18.9   1   0     4     4
+#> 2 4.07  17.4   0   0     3     3
+#> 3 3.73  17.6   0   0     3     3
+#> 4 3.78  18.0   0   0     3     3
bind_cols(list(one, two))
#>    mpg cyl disp  hp drat    wt  qsec vs am gear carb mpg1 cyl1 disp1 hp1 drat1
+#> 1 21.0   6  160 110 3.90 2.620 16.46  0  1    4    4 17.8    6 167.6 123  3.92
+#> 2 21.0   6  160 110 3.90 2.875 17.02  0  1    4    4 16.4    8 275.8 180  3.07
+#> 3 22.8   4  108  93 3.85 2.320 18.61  1  1    4    1 17.3    8 275.8 180  3.07
+#> 4 21.4   6  258 110 3.08 3.215 19.44  1  0    3    1 15.2    8 275.8 180  3.07
+#>    wt1 qsec1 vs1 am1 gear1 carb1
+#> 1 3.44  18.9   1   0     4     4
+#> 2 4.07  17.4   0   0     3     3
+#> 3 3.73  17.6   0   0     3     3
+#> 4 3.78  18.0   0   0     3     3

+# combine applies the same coercion rules
+f1 <- factor("a")
+f2 <- factor("b")
+c(f1, f2)
#> [1] 1 1
unlist(list(f1, f2))
#> [1] a b
+#> Levels: a b

+combine(f1, f2)
#> Warning: Unequal factor levels: coercing to character
#> Warning: binding character and factor vector, coercing into character vector
#> Warning: binding character and factor vector, coercing into character vector
#> [1] "a" "b"
combine(list(f1, f2))
#> Warning: Unequal factor levels: coercing to character
#> Warning: binding character and factor vector, coercing into character vector
#> Warning: binding character and factor vector, coercing into character vector
#> [1] "a" "b"
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/case_when.html b/docs/reference/case_when.html new file mode 100644 index 0000000000..cbf7e38ac0 --- /dev/null +++ b/docs/reference/case_when.html @@ -0,0 +1,212 @@ + + + + + + + + +A general vectorised if. — case_when • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

A general vectorised if.

+
+ + +

This function allows you to vectorise multiple if and else if +statements. It is an R equivalent of the SQL CASE WHEN statement.

+ + + 
case_when(...)
+ +

Arguments

+ + + + + + +
...

A sequence of two-sided formulas. The left hand side (LHS) +determines which values match this case. The right hand side (RHS) +provides the replacement value.

+

The LHS must evaluate to a logical vector. Each logical vector can +either have length 1 or a common length. All RHSs must evaluate to +the same type of vector.

+

These dots are evaluated with explicit splicing.

+ +

Value

+ +

A vector as long as the longest LHS, with the type (and +attributes) of the first RHS. Inconsistent lengths or types will +generate an error.

+ + +

Examples

+ 
x <- 1:50
+case_when(
+  x %% 35 == 0 ~ "fizz buzz",
+  x %% 5 == 0 ~ "fizz",
+  x %% 7 == 0 ~ "buzz",
+  TRUE ~ as.character(x)
+)
#>  [1] "1"         "2"         "3"         "4"         "fizz"      "6"        
+#>  [7] "buzz"      "8"         "9"         "fizz"      "11"        "12"       
+#> [13] "13"        "buzz"      "fizz"      "16"        "17"        "18"       
+#> [19] "19"        "fizz"      "buzz"      "22"        "23"        "24"       
+#> [25] "fizz"      "26"        "27"        "buzz"      "29"        "fizz"     
+#> [31] "31"        "32"        "33"        "34"        "fizz buzz" "36"       
+#> [37] "37"        "38"        "39"        "fizz"      "41"        "buzz"     
+#> [43] "43"        "44"        "fizz"      "46"        "47"        "48"       
+#> [49] "buzz"      "fizz"     

+# Like an if statement, the arguments are evaluated in order, so you must
+# proceed from the most specific to the most general. This won't work:
+case_when(
+  TRUE ~ as.character(x),
+  x %%  5 == 0 ~ "fizz",
+  x %%  7 == 0 ~ "buzz",
+  x %% 35 == 0 ~ "fizz buzz"
+)
#>  [1] "1"  "2"  "3"  "4"  "5"  "6"  "7"  "8"  "9"  "10" "11" "12" "13" "14" "15"
+#> [16] "16" "17" "18" "19" "20" "21" "22" "23" "24" "25" "26" "27" "28" "29" "30"
+#> [31] "31" "32" "33" "34" "35" "36" "37" "38" "39" "40" "41" "42" "43" "44" "45"
+#> [46] "46" "47" "48" "49" "50"

+# case_when is particularly useful inside mutate when you want to
+# create a new variable that relies on a complex combination of existing
+# variables
+starwars %>%
+  select(name:mass, gender, species) %>%
+  mutate(
+    type = case_when(
+      height > 200 | mass > 200 ~ "large",
+      species == "Droid"        ~ "robot",
+      TRUE                      ~  "other"
+    )
+  )
#> # A tibble: 87 × 6
+#>                  name height  mass gender species  type
+#>                 <chr>  <int> <dbl>  <chr>   <chr> <chr>
+#> 1      Luke Skywalker    172    77   male   Human other
+#> 2               C-3PO    167    75   <NA>   Droid robot
+#> 3               R2-D2     96    32   <NA>   Droid robot
+#> 4         Darth Vader    202   136   male   Human large
+#> 5         Leia Organa    150    49 female   Human other
+#> 6           Owen Lars    178   120   male   Human other
+#> 7  Beru Whitesun lars    165    75 female   Human other
+#> 8               R5-D4     97    32   <NA>   Droid robot
+#> 9   Biggs Darklighter    183    84   male   Human other
+#> 10     Obi-Wan Kenobi    182    77   male   Human other
+#> # ... with 77 more rows

+# Dots support splicing:
+patterns <- list(
+  TRUE ~ as.character(x),
+  x %%  5 == 0 ~ "fizz",
+  x %%  7 == 0 ~ "buzz",
+  x %% 35 == 0 ~ "fizz buzz"
+)
+case_when(!!! patterns)
#>  [1] "1"  "2"  "3"  "4"  "5"  "6"  "7"  "8"  "9"  "10" "11" "12" "13" "14" "15"
+#> [16] "16" "17" "18" "19" "20" "21" "22" "23" "24" "25" "26" "27" "28" "29" "30"
+#> [31] "31" "32" "33" "34" "35" "36" "37" "38" "39" "40" "41" "42" "43" "44" "45"
+#> [46] "46" "47" "48" "49" "50"
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/coalesce.html b/docs/reference/coalesce.html new file mode 100644 index 0000000000..12afdbf0ad --- /dev/null +++ b/docs/reference/coalesce.html @@ -0,0 +1,165 @@ + + + + + + + + +Find first non-missing element — coalesce • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Find first non-missing element

+
+ + +

Given a set of vectors, coalesce() finds the first non-missing value +at each position. This is inspired by the SQL COALESCE function +which does the same thing for NULLs.

+ + + 
coalesce(...)
+ +

Arguments

+ + + + + + +
...

Vectors. All inputs should either be length 1, or the +same length as the first argument.

+

These dots are evaluated with explicit splicing.

+ +

Value

+ +

A vector the same length as the first ... argument with +missing values replaced by the first non-missing value.

+ +

See also

+ +

na_if() to replace specified values with a NA.

+ + +

Examples

+ 
# Use a single value to replace all missing values
+x <- sample(c(1:5, NA, NA, NA))
+coalesce(x, 0L)
#> [1] 0 2 1 0 3 0 5 4

+# Or match together a complete vector from missing pieces
+y <- c(1, 2, NA, NA, 5)
+z <- c(NA, NA, 3, 4, 5)
+coalesce(y, z)
#> [1] 1 2 3 4 5

+# Supply lists by splicing them into dots:
+vecs <- list(
+  c(1, 2, NA, NA, 5),
+  c(NA, NA, 3, 4, 5)
+)
+coalesce(!!! vecs)
#> [1] 1 2 3 4 5
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/common_by.html b/docs/reference/common_by.html new file mode 100644 index 0000000000..8ae373a370 --- /dev/null +++ b/docs/reference/common_by.html @@ -0,0 +1,122 @@ + + + + + + + + +Extract out common by variables — common_by • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Extract out common by variables

+
+ + +

Extract out common by variables

+ + + 
common_by(by = NULL, x, y)
+ + +
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/compute.html b/docs/reference/compute.html new file mode 100644 index 0000000000..1ad25fcb3c --- /dev/null +++ b/docs/reference/compute.html @@ -0,0 +1,201 @@ + + + + + + + + +Force computation of a database query — compute • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Force computation of a database query

+
+ + +

compute() stores results in a remote temporary table. +collect() retrieves data into a local tibble. +collapse() is slightly different: it doesn't force computation, but +instead forces generation of the SQL query. This is sometimes needed to work +around bugs in dplyr's SQL generation.

+ + + 
compute(x, name = random_table_name(), ...)
+
+collect(x, ...)
+
+collapse(x, ...)
+ +

Arguments

+ + + + + + + + + + + + + + +
x

A tbl

name

Name of temporary table on database.

...

Other arguments passed on to methods

+ +

Details

+ +

All functions preserve grouping and ordering.

+ +

See also

+ +

copy_to(), the opposite of collect(): it takes a local data +frame and uploads it to the remote source.

+ + +

Examples

+ 
if (require(dbplyr)) {
+  mtcars2 <- src_memdb() %>%
+    copy_to(mtcars, name = "mtcars2-cc", overwrite = TRUE)
+
+  remote <- mtcars2 %>%
+    filter(cyl == 8) %>%
+    select(mpg:drat)
+
+  # Compute query and save in remote table
+  compute(remote)
+
+  # Compute query bring back to this session
+  collect(remote)
+
+  # Creates a fresh query based on the generated SQL
+  collapse(remote)
+}
#> Loading required package: dbplyr
#> 
+#> Attaching package: ‘dbplyr’
#> The following object is masked from ‘package:stats’:
+#> 
+#>     filter
#> The following objects are masked from ‘package:base’:
+#> 
+#>     intersect, setdiff, union
#> Source:     SQL [?? x 5]
+#> Database:   sqlite 3.11.1 [:memory:]
+#> 
+#>      mpg   cyl  disp    hp  drat
+#>    <dbl> <dbl> <dbl> <dbl> <dbl>
+#> 1   18.7     8 360.0   175  3.15
+#> 2   14.3     8 360.0   245  3.21
+#> 3   16.4     8 275.8   180  3.07
+#> 4   17.3     8 275.8   180  3.07
+#> 5   15.2     8 275.8   180  3.07
+#> 6   10.4     8 472.0   205  2.93
+#> 7   10.4     8 460.0   215  3.00
+#> 8   14.7     8 440.0   230  3.23
+#> 9   15.5     8 318.0   150  2.76
+#> 10  15.2     8 304.0   150  3.15
+#> # ... with more rows
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/copy_to.html b/docs/reference/copy_to.html new file mode 100644 index 0000000000..c264ee25fa --- /dev/null +++ b/docs/reference/copy_to.html @@ -0,0 +1,172 @@ + + + + + + + + +Copy a local data frame to a remote src. — copy_to • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Copy a local data frame to a remote src.

+
+ + +

This function uploads a local data frame into a remote data source, creating +the table definition as needed. Wherever possible, the new object will be +temporary, limited to the current connection to the source.

+ + + 
copy_to(dest, df, name = deparse(substitute(df)), overwrite = FALSE, ...)
+ +

Arguments

+ + + + + + + + + + + + + + + + + + + + + + +
dest

remote data source

df

local data frame

name

name for new remote table.

overwrite

If TRUE, will overwrite an existing table with +name name. If FALSE, will throw an error if name already +exists.

...

other parameters passed to methods.

+ +

Value

+ +

a tbl object in the remote source

+ +

See also

+ +

collect() for the opposite action; downloading remote data into +a local dbl.

+ + +

Examples

+ 
## Not run: ------------------------------------
+# iris2 <- src_memdb() %>% copy_to(iris, overwrite = TRUE)
+# iris2
+## ---------------------------------------------
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/cumall.html b/docs/reference/cumall.html new file mode 100644 index 0000000000..586a8437b8 --- /dev/null +++ b/docs/reference/cumall.html @@ -0,0 +1,139 @@ + + + + + + + + +Cumulativate versions of any, all, and mean — cumall • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Cumulativate versions of any, all, and mean

+
+ + +

dplyr adds cumall(), cumany(), and cummean() to complete +R's set of cumulate functions to match the aggregation functions available +in most databases

+ + + 
cumall(x)
+
+cumany(x)
+
+cummean(x)
+ +

Arguments

+ + + + + + +
x

For cumall() and cumany(), a logical vector; for +cummean() an integer or numeric vector

+ + +
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/desc.html b/docs/reference/desc.html new file mode 100644 index 0000000000..2a314976ba --- /dev/null +++ b/docs/reference/desc.html @@ -0,0 +1,156 @@ + + + + + + + + +Descending order. — desc • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Descending order.

+
+ + +

Transform a vector into a format that will be sorted in descending order. +This is useful within arrange().

+ + + 
desc(x)
+ +

Arguments

+ + + + + + +
x

vector to transform

+ + +

Examples

+ 
desc(1:10)
#>  [1]  -1  -2  -3  -4  -5  -6  -7  -8  -9 -10
desc(factor(letters))
#>  [1]  -1  -2  -3  -4  -5  -6  -7  -8  -9 -10 -11 -12 -13 -14 -15 -16 -17 -18 -19
+#> [20] -20 -21 -22 -23 -24 -25 -26

+first_day <- seq(as.Date("1910/1/1"), as.Date("1920/1/1"), "years")
+desc(first_day)
#>  [1] 21915 21550 21185 20819 20454 20089 19724 19358 18993 18628 18263

+starwars %>% arrange(desc(mass))
#> # A tibble: 87 × 13
+#>                     name height  mass  hair_color       skin_color
+#>                    <chr>  <int> <dbl>       <chr>            <chr>
+#> 1  Jabba Desilijic Tiure    175  1358        <NA> green-tan, brown
+#> 2               Grievous    216   159        none     brown, white
+#> 3                  IG-88    200   140        none            metal
+#> 4            Darth Vader    202   136        none            white
+#> 5                Tarfful    234   136       brown            brown
+#> 6              Owen Lars    178   120 brown, grey            light
+#> 7                  Bossk    190   113        none            green
+#> 8              Chewbacca    228   112       brown          unknown
+#> 9       Jek Tono Porkins    180   110       brown             fair
+#> 10       Dexter Jettster    198   102        none            brown
+#> # ... with 77 more rows, and 8 more variables: eye_color <chr>,
+#> #   birth_year <dbl>, gender <chr>, homeworld <chr>, species <chr>,
+#> #   films <list>, vehicles <list>, starships <list>
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/dim_desc.html b/docs/reference/dim_desc.html new file mode 100644 index 0000000000..6b69dc1397 --- /dev/null +++ b/docs/reference/dim_desc.html @@ -0,0 +1,137 @@ + + + + + + + + +Describing dimensions — dim_desc • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Describing dimensions

+
+ + +

Prints the dimensions of an array-like object in a user-friendly manner, +substituting NA with ?? (for SQL queries).

+ + + 
dim_desc(x)
+ +

Arguments

+ + + + + + +
x

Object to show dimensions for.

+ + +

Examples

+ 
dim_desc(mtcars)
#> [1] "[32 x 11]"
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/distinct.html b/docs/reference/distinct.html new file mode 100644 index 0000000000..77d6ad6c52 --- /dev/null +++ b/docs/reference/distinct.html @@ -0,0 +1,239 @@ + + + + + + + + +Select distinct/unique rows. — distinct • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Select distinct/unique rows.

+
+ + +

Retain only unique/distinct rows from an input tbl. This is similar +to unique.data.frame(), but considerably faster.

+ + + 
distinct(.data, ..., .keep_all = FALSE)
+ +

Arguments

+ + + + + + + + + + + + + + +
.data

a tbl

...

Optional variables to use when determining uniqueness. If there +are multiple rows for a given combination of inputs, only the first +row will be preserved. If omitted, will use all variables.

.keep_all

If TRUE, keep all variables in .data. +If a combination of ... is not distinct, this keeps the +first row of values.

+ + +

Examples

+ 
df <- tibble(
+  x = sample(10, 100, rep = TRUE),
+  y = sample(10, 100, rep = TRUE)
+)
+nrow(df)
#> [1] 100
nrow(distinct(df))
#> [1] 67
nrow(distinct(df, x, y))
#> [1] 67

+distinct(df, x)
#> # A tibble: 10 × 1
+#>        x
+#>    <int>
+#> 1      6
+#> 2      8
+#> 3      4
+#> 4      9
+#> 5      2
+#> 6      1
+#> 7     10
+#> 8      7
+#> 9      5
+#> 10     3
distinct(df, y)
#> # A tibble: 10 × 1
+#>        y
+#>    <int>
+#> 1      7
+#> 2      2
+#> 3      3
+#> 4      9
+#> 5      6
+#> 6      4
+#> 7      8
+#> 8      1
+#> 9      5
+#> 10    10

+# Can choose to keep all other variables as well
+distinct(df, x, .keep_all = TRUE)
#> # A tibble: 10 × 2
+#>        x     y
+#>    <int> <int>
+#> 1      6     7
+#> 2      8     2
+#> 3      4     3
+#> 4      9     9
+#> 5      2     3
+#> 6      1     1
+#> 7     10     1
+#> 8      7     3
+#> 9      5     2
+#> 10     3     9
distinct(df, y, .keep_all = TRUE)
#> # A tibble: 10 × 2
+#>        x     y
+#>    <int> <int>
+#> 1      6     7
+#> 2      8     2
+#> 3      4     3
+#> 4      9     9
+#> 5      8     6
+#> 6      2     4
+#> 7      4     8
+#> 8      1     1
+#> 9      2     5
+#> 10     9    10

+# You can also use distinct on computed variables
+distinct(df, diff = abs(x - y))
#> # A tibble: 10 × 1
+#>     diff
+#>    <int>
+#> 1      1
+#> 2      6
+#> 3      0
+#> 4      2
+#> 5      3
+#> 6      5
+#> 7      4
+#> 8      9
+#> 9      7
+#> 10     8

+# The same behaviour applies for grouped data frames
+# except that the grouping variables are always included
+df <- tibble(
+  g = c(1, 1, 2, 2),
+  x = c(1, 1, 2, 1)
+) %>% group_by(g)
+df %>% distinct()
#> Source: local data frame [3 x 2]
+#> Groups: g [2]
+#> 
+#>       g     x
+#>   <dbl> <dbl>
+#> 1     1     1
+#> 2     2     2
+#> 3     2     1
df %>% distinct(x)
#> Source: local data frame [3 x 2]
+#> Groups: g [2]
+#> 
+#>       g     x
+#>   <dbl> <dbl>
+#> 1     1     1
+#> 2     2     2
+#> 3     2     1
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/do.html b/docs/reference/do.html new file mode 100644 index 0000000000..6a11646435 --- /dev/null +++ b/docs/reference/do.html @@ -0,0 +1,287 @@ + + + + + + + + +Do arbitrary operations on a tbl. — do • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Do arbitrary operations on a tbl.

+
+ + +

This is a general purpose complement to the specialised manipulation +functions filter(), select(), mutate(), +summarise() and arrange(). You can use do() +to perform arbitrary computation, returning either a data frame or +arbitrary objects which will be stored in a list. This is particularly +useful when working with models: you can fit models per group with +do() and then flexibly extract components with either another +do() or summarise().

+ + + 
do(.data, ...)
+ +

Arguments

+ + + + + + + + + + +
.data

a tbl

...

Expressions to apply to each group. If named, results will be +stored in a new column. If unnamed, should return a data frame. You can +use . to refer to the current group. You can not mix named and +unnamed arguments.

+ +

Value

+ +

do() always returns a data frame. The first columns in the data frame +will be the labels, the others will be computed from .... Named +arguments become list-columns, with one element for each group; unnamed +elements must be data frames and labels will be duplicated accordingly.

+

Groups are preserved for a single unnamed input. This is different to +summarise() because do() generally does not reduce the +complexity of the data, it just expresses it in a special way. For +multiple named inputs, the output is grouped by row with +rowwise(). This allows other verbs to work in an intuitive +way.

+ +

Details

+ +

For an empty data frame, the expressions will be evaluated once, even in the +presence of a grouping. This makes sure that the format of the resulting +data frame is the same for both empty and non-empty input.

+ +

Connection to plyr

+ + +

If you're familiar with plyr, do() with named arguments is basically +equivalent to plyr::dlply(), and do() with a single unnamed argument +is basically equivalent to plyr::ldply(). However, instead of storing +labels in a separate attribute, the result is always a data frame. This +means that summarise() applied to the result of do() can +act like ldply().

+ + +

Examples

+ 
by_cyl <- group_by(mtcars, cyl)
+do(by_cyl, head(., 2))
#> Source: local data frame [6 x 11]
+#> Groups: cyl [3]
+#> 
+#>     mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
+#>   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
+#> 1  22.8     4 108.0    93  3.85 2.320 18.61     1     1     4     1
+#> 2  24.4     4 146.7    62  3.69 3.190 20.00     1     0     4     2
+#> 3  21.0     6 160.0   110  3.90 2.620 16.46     0     1     4     4
+#> 4  21.0     6 160.0   110  3.90 2.875 17.02     0     1     4     4
+#> 5  18.7     8 360.0   175  3.15 3.440 17.02     0     0     3     2
+#> 6  14.3     8 360.0   245  3.21 3.570 15.84     0     0     3     4

+models <- by_cyl %>% do(mod = lm(mpg ~ disp, data = .))
+models
#> Source: local data frame [3 x 2]
+#> Groups: <by row>
+#> 
+#> # A tibble: 3 × 2
+#>     cyl      mod
+#> * <dbl>   <list>
+#> 1     4 <S3: lm>
+#> 2     6 <S3: lm>
+#> 3     8 <S3: lm>

+summarise(models, rsq = summary(mod)$r.squared)
#> # A tibble: 3 × 1
+#>          rsq
+#>        <dbl>
+#> 1 0.64840514
+#> 2 0.01062604
+#> 3 0.27015777
models %>% do(data.frame(coef = coef(.$mod)))
#> Source: local data frame [6 x 1]
+#> Groups: <by row>
+#> 
+#> # A tibble: 6 × 1
+#>           coef
+#> *        <dbl>
+#> 1 40.871955322
+#> 2 -0.135141815
+#> 3 19.081987419
+#> 4  0.003605119
+#> 5 22.032798914
+#> 6 -0.019634095
models %>% do(data.frame(
+  var = names(coef(.$mod)),
+  coef(summary(.$mod)))
+)
#> Source: local data frame [6 x 5]
+#> Groups: <by row>
+#> 
+#> # A tibble: 6 × 5
+#>           var     Estimate  Std..Error    t.value     Pr...t..
+#> *      <fctr>        <dbl>       <dbl>      <dbl>        <dbl>
+#> 1 (Intercept) 40.871955322 3.589605400 11.3861973 1.202715e-06
+#> 2        disp -0.135141815 0.033171608 -4.0740206 2.782827e-03
+#> 3 (Intercept) 19.081987419 2.913992892  6.5483988 1.243968e-03
+#> 4        disp  0.003605119 0.015557115  0.2317344 8.259297e-01
+#> 5 (Intercept) 22.032798914 3.345241115  6.5863112 2.588765e-05
+#> 6        disp -0.019634095 0.009315926 -2.1075838 5.677488e-02

+models <- by_cyl %>% do(
+  mod_linear = lm(mpg ~ disp, data = .),
+  mod_quad = lm(mpg ~ poly(disp, 2), data = .)
+)
+models
#> Source: local data frame [3 x 3]
+#> Groups: <by row>
+#> 
+#> # A tibble: 3 × 3
+#>     cyl mod_linear mod_quad
+#> * <dbl>     <list>   <list>
+#> 1     4   <S3: lm> <S3: lm>
+#> 2     6   <S3: lm> <S3: lm>
+#> 3     8   <S3: lm> <S3: lm>
compare <- models %>% do(aov = anova(.$mod_linear, .$mod_quad))
+# compare %>% summarise(p.value = aov$`Pr(>F)`)
+
+if (require("nycflights13")) {
+# You can use it to do any arbitrary computation, like fitting a linear
+# model. Let's explore how carrier departure delays vary over the time
+carriers <- group_by(flights, carrier)
+group_size(carriers)
+
+mods <- do(carriers, mod = lm(arr_delay ~ dep_time, data = .))
+mods %>% do(as.data.frame(coef(.$mod)))
+mods %>% summarise(rsq = summary(mod)$r.squared)
+
+## Not run: ------------------------------------
+# # This longer example shows the progress bar in action
+# by_dest <- flights %>% group_by(dest) %>% filter(n() > 100)
+# library(mgcv)
+# by_dest %>% do(smooth = gam(arr_delay ~ s(dep_time) + month, data = .))
+## ---------------------------------------------
+}
#> Loading required package: nycflights13
#> # A tibble: 16 × 1
+#>            rsq
+#>          <dbl>
+#> 1  0.051350400
+#> 2  0.050413957
+#> 3  0.082775968
+#> 4  0.024073896
+#> 5  0.034721220
+#> 6  0.083602600
+#> 7  0.101147945
+#> 8  0.026441622
+#> 9  0.001700796
+#> 10 0.049918201
+#> 11 0.017496868
+#> 12 0.067322008
+#> 13 0.057505652
+#> 14 0.110919798
+#> 15 0.118660669
+#> 16 0.139066954
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/dplyr-package.html b/docs/reference/dplyr-package.html new file mode 100644 index 0000000000..c3ed8b6e2d --- /dev/null +++ b/docs/reference/dplyr-package.html @@ -0,0 +1,184 @@ + + + + + + + + +dplyr: a grammar of data manipulation — dplyr-package • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

dplyr: a grammar of data manipulation

+
+ + +

dplyr provides a flexible grammar of data manipulation. It's the next +iteration of plyr, focused on tools for working with data frames (hence the +d in the name).

+ + + +

Details

+ +

It has three main goals:

    +

  • Identify the most important data manipulation verbs and make them +easy to use from R.

    • +

  • Provide blazing fast performance for in-memory data by writing key +pieces in C++ (using Rcpp)

    • +

  • Use the same interface to work with data no matter where it's stored, +whether in a data frame, a data table or database.

    • +
+

To learn more about dplyr, start with the vignettes: +browseVignettes(package = "dplyr")

+ +

Package options

+ + +
+
dplyr.show_progress

Should lengthy operations such as do() +show a progress bar? Default: TRUE

+
+ +

Package configurations

+ + +

These can be set on a package-by-package basis, or for the global environment. +See pkgconfig::set_config() for usage.

+
dplyr::na_matches

Should NA values be matched in data frame joins +by default? Default: "never", alternative value: "na". See also +join.tbl_df().

+
+ +

See also

+ +

Useful links:

+ + +
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/explain.html b/docs/reference/explain.html new file mode 100644 index 0000000000..1640397960 --- /dev/null +++ b/docs/reference/explain.html @@ -0,0 +1,183 @@ + + + + + + + + +Explain details of a tbl — explain • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Explain details of a tbl

+
+ + +

This is a generic function which gives more details about an object than +print(), and is more focussed on human readable output than +str().

+ + + 
explain(x, ...)
+
+show_query(x, ...)
+ +

Arguments

+ + + + + + + + + + +
x

An object to explain

...

Other parameters possibly used by generic

+ +

Value

+ +

The first argument, invisibly.

+ +

Databases

+ + +

Explaining a tbl_sql will run the SQL EXPLAIN command which +will describe the query plan. This requires a little bit of knowledge about +how EXPLAIN works for your database, but is very useful for +diagnosing performance problems.

+ + +

Examples

+ 

+if (require("dbplyr")) {
+
+lahman_s <- lahman_sqlite()
+batting <- tbl(lahman_s, "Batting")
+batting %>% show_query()
+batting %>% explain()
+
+# The batting database has indices on all ID variables:
+# SQLite automatically picks the most restrictive index
+batting %>% filter(lgID == "NL" & yearID == 2000L) %>% explain()
+
+# OR's will use multiple indexes
+batting %>% filter(lgID == "NL" | yearID == 2000) %>% explain()
+
+# Joins will use indexes in both tables
+teams <- tbl(lahman_s, "Teams")
+batting %>% left_join(teams, c("yearID", "teamID")) %>% explain()
+}
#> Creating table: AllstarFull
#> Creating table: Appearances
#> Creating table: AwardsManagers
#> Creating table: AwardsPlayers
#> Creating table: AwardsShareManagers
#> Creating table: AwardsSharePlayers
#> Creating table: Batting
#> Creating table: BattingPost
#> Creating table: CollegePlaying
#> Creating table: Fielding
#> Creating table: FieldingOF
#> Creating table: FieldingPost
#> Creating table: HallOfFame
#> Creating table: LahmanData
#> Creating table: Managers
#> Creating table: ManagersHalf
#> Creating table: Master
#> Creating table: Pitching
#> Creating table: PitchingPost
#> Creating table: Salaries
#> Creating table: Schools
#> Creating table: SeriesPost
#> Creating table: Teams
#> Creating table: TeamsFranchises
#> Creating table: TeamsHalf
#> <SQL>
+#> SELECT *
+#> FROM `Batting`
#> <SQL>
+#> SELECT *
+#> FROM `Batting`
#> 
#> Error in UseMethod("db_explain"): no applicable method for 'db_explain' applied to an object of class "NULL"

+
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/failwith.html b/docs/reference/failwith.html new file mode 100644 index 0000000000..181dd9c919 --- /dev/null +++ b/docs/reference/failwith.html @@ -0,0 +1,152 @@ + + + + + + + + +Fail with specified value. — failwith • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Fail with specified value.

+
+ + +

Deprecated. Please use purrr::possibly() instead.

+ + + 
failwith(default = NULL, f, quiet = FALSE)
+ +

Arguments

+ + + + + + + + + + + + + + +
default

default value

f

function

quiet

all error messages be suppressed?

+ +

Value

+ +

a function

+ +

See also

+ +

plyr::try_default()

+ + +
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/filter.html b/docs/reference/filter.html new file mode 100644 index 0000000000..2f0dd9187b --- /dev/null +++ b/docs/reference/filter.html @@ -0,0 +1,265 @@ + + + + + + + + +Return rows with matching conditions — filter • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Return rows with matching conditions

+
+ + +

Use filter() find rows/cases where conditions are true. Unlike +base subsetting, rows where the condition evaluates to NA are dropped.

+ + + 
filter(.data, ...)
+ +

Arguments

+ + + + + + + + + + +
.data

A tbl. All main verbs are S3 generics and provide methods +for tbl_df(), dtplyr::tbl_dt() and dbplyr::tbl_dbi().

...

Logical predicates defined in terms of the variables in .data. +Multiple conditions are combined with &. Only rows where the +conditon evalutes to TRUE are kept.

+

These arguments are automatically quoted and +evaluated in the context of the data +frame. They support unquoting and +splicing. See vignette("programming") for an introduction to +these concepts.

+ +

Value

+ +

An object of the same class as .data.

+ +

Details

+ +

Note that dplyr is not yet smart enough to optimise filtering optimisation +on grouped datasets that don't need grouped calculations. For this reason, +filtering is often considerably faster on ungroup()ed data.

+ +

Useful filter functions

+ + + + +

Tidy data

+ + +

When applied to a data frame, row names are silently dropped. To preserve, +convert to an explicit variable with tibble::rownames_to_column().

+ +

Scoped filtering

+ + +

The three scoped variants (filter_all(), filter_if() and +filter_at()) make it easy to apply a filtering condition to a +selection of variables.

+ +

See also

+ +

filter_all(), filter_if() and filter_at().

+

Other single table verbs: arrange, + mutate, select, + slice, summarise

+ + +

Examples

+ 
filter(starwars, species == "Human")
#> # A tibble: 35 × 13
+#>                  name height  mass    hair_color skin_color eye_color
+#>                 <chr>  <int> <dbl>         <chr>      <chr>     <chr>
+#> 1      Luke Skywalker    172    77         blond       fair      blue
+#> 2         Darth Vader    202   136          none      white    yellow
+#> 3         Leia Organa    150    49         brown      light     brown
+#> 4           Owen Lars    178   120   brown, grey      light      blue
+#> 5  Beru Whitesun lars    165    75         brown      light      blue
+#> 6   Biggs Darklighter    183    84         black      light     brown
+#> 7      Obi-Wan Kenobi    182    77 auburn, white       fair blue-gray
+#> 8    Anakin Skywalker    188    84         blond       fair      blue
+#> 9      Wilhuff Tarkin    180    NA  auburn, grey       fair      blue
+#> 10           Han Solo    180    80         brown       fair     brown
+#> # ... with 25 more rows, and 7 more variables: birth_year <dbl>, gender <chr>,
+#> #   homeworld <chr>, species <chr>, films <list>, vehicles <list>,
+#> #   starships <list>
filter(starwars, mass > 1000)
#> # A tibble: 1 × 13
+#>                    name height  mass hair_color       skin_color eye_color
+#>                   <chr>  <int> <dbl>      <chr>            <chr>     <chr>
+#> 1 Jabba Desilijic Tiure    175  1358       <NA> green-tan, brown    orange
+#> # ... with 7 more variables: birth_year <dbl>, gender <chr>, homeworld <chr>,
+#> #   species <chr>, films <list>, vehicles <list>, starships <list>

+# Multiple criteria
+filter(starwars, hair_color == "none" & eye_color == "black")
#> # A tibble: 9 × 13
+#>         name height  mass hair_color       skin_color eye_color birth_year
+#>        <chr>  <int> <dbl>      <chr>            <chr>     <chr>      <dbl>
+#> 1  Nien Nunb    160    68       none             grey     black         NA
+#> 2    Gasgano    122    NA       none      white, blue     black         NA
+#> 3  Kit Fisto    196    87       none            green     black         NA
+#> 4   Plo Koon    188    80       none           orange     black         22
+#> 5    Lama Su    229    88       none             grey     black         NA
+#> 6    Taun We    213    NA       none             grey     black         NA
+#> 7   Shaak Ti    178    57       none red, blue, white     black         NA
+#> 8 Tion Medon    206    80       none             grey     black         NA
+#> 9        BB8     NA    NA       none             none     black         NA
+#> # ... with 6 more variables: gender <chr>, homeworld <chr>, species <chr>,
+#> #   films <list>, vehicles <list>, starships <list>
filter(starwars, hair_color == "none" | eye_color == "black")
#> # A tibble: 38 × 13
+#>             name height  mass hair_color    skin_color eye_color birth_year
+#>            <chr>  <int> <dbl>      <chr>         <chr>     <chr>      <dbl>
+#> 1    Darth Vader    202   136       none         white    yellow       41.9
+#> 2         Greedo    173    74       <NA>         green     black       44.0
+#> 3          IG-88    200   140       none         metal       red       15.0
+#> 4          Bossk    190   113       none         green       red       53.0
+#> 5          Lobot    175    79       none         light      blue       37.0
+#> 6         Ackbar    180    83       none  brown mottle    orange       41.0
+#> 7      Nien Nunb    160    68       none          grey     black         NA
+#> 8    Nute Gunray    191    90       none mottled green       red         NA
+#> 9  Jar Jar Binks    196    66       none        orange    orange       52.0
+#> 10  Roos Tarpals    224    82       none          grey    orange         NA
+#> # ... with 28 more rows, and 6 more variables: gender <chr>, homeworld <chr>,
+#> #   species <chr>, films <list>, vehicles <list>, starships <list>

+# Multiple arguments are equivalent to and
+filter(starwars, hair_color == "none", eye_color == "black")
#> # A tibble: 9 × 13
+#>         name height  mass hair_color       skin_color eye_color birth_year
+#>        <chr>  <int> <dbl>      <chr>            <chr>     <chr>      <dbl>
+#> 1  Nien Nunb    160    68       none             grey     black         NA
+#> 2    Gasgano    122    NA       none      white, blue     black         NA
+#> 3  Kit Fisto    196    87       none            green     black         NA
+#> 4   Plo Koon    188    80       none           orange     black         22
+#> 5    Lama Su    229    88       none             grey     black         NA
+#> 6    Taun We    213    NA       none             grey     black         NA
+#> 7   Shaak Ti    178    57       none red, blue, white     black         NA
+#> 8 Tion Medon    206    80       none             grey     black         NA
+#> 9        BB8     NA    NA       none             none     black         NA
+#> # ... with 6 more variables: gender <chr>, homeworld <chr>, species <chr>,
+#> #   films <list>, vehicles <list>, starships <list>
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/filter_all.html b/docs/reference/filter_all.html new file mode 100644 index 0000000000..6612ac9b31 --- /dev/null +++ b/docs/reference/filter_all.html @@ -0,0 +1,223 @@ + + + + + + + + +Filter within a selection of variables. — filter_all • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Filter within a selection of variables.

+
+ + +

These scoped filtering verbs apply a predicate expression to a +selection of variables. The predicate expression should be quoted +with all_vars() or any_vars() and should mention the pronoun +. to refer to variables.

+ + + 
filter_all(.tbl, .vars_predicate)
+
+filter_if(.tbl, .predicate, .vars_predicate)
+
+filter_at(.tbl, .vars, .vars_predicate)
+ +

Arguments

+ + + + + + + + + + + + + + + + + + +
.tbl

A tbl object.

.vars_predicate

A quoted predicate expression as returned by +all_vars() or any_vars().

.predicate

A predicate function to be applied to the columns +or a logical vector. The variables for which .predicate is or +returns TRUE are selected. This argument is passed to +rlang::as_function() and thus supports quosure-style lambda +functions and strings representing function names.

.vars

A list of columns generated by vars(), +or a character vector of column names, or a numeric vector of column +positions.

+ + +

Examples

+ 
# While filter() accepts expressions with specific variables, the
+# scoped filter verbs take an expression with the pronoun `.` and
+# replicate it over all variables. This expression should be quoted
+# with all_vars() or any_vars():
+all_vars(is.na(.))
#> <predicate intersection>
+#> ~is.na(.)
+#> <environment: 0x10e664068>
any_vars(is.na(.))
#> <predicate union>
+#> ~is.na(.)
+#> <environment: 0x10e664068>

+
+# You can take the intersection of the replicated expressions:
+filter_all(mtcars, all_vars(. > 150))
#>  [1] mpg  cyl  disp hp   drat wt   qsec vs   am   gear carb
+#> <0 rows> (or 0-length row.names)

+# Or the union:
+filter_all(mtcars, any_vars(. > 150))
#>     mpg cyl  disp  hp drat    wt  qsec vs am gear carb
+#> 1  21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4
+#> 2  21.0   6 160.0 110 3.90 2.875 17.02  0  1    4    4
+#> 3  21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1
+#> 4  18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2
+#> 5  18.1   6 225.0 105 2.76 3.460 20.22  1  0    3    1
+#> 6  14.3   8 360.0 245 3.21 3.570 15.84  0  0    3    4
+#> 7  19.2   6 167.6 123 3.92 3.440 18.30  1  0    4    4
+#> 8  17.8   6 167.6 123 3.92 3.440 18.90  1  0    4    4
+#> 9  16.4   8 275.8 180 3.07 4.070 17.40  0  0    3    3
+#> 10 17.3   8 275.8 180 3.07 3.730 17.60  0  0    3    3
+#> 11 15.2   8 275.8 180 3.07 3.780 18.00  0  0    3    3
+#> 12 10.4   8 472.0 205 2.93 5.250 17.98  0  0    3    4
+#> 13 10.4   8 460.0 215 3.00 5.424 17.82  0  0    3    4
+#> 14 14.7   8 440.0 230 3.23 5.345 17.42  0  0    3    4
+#> 15 15.5   8 318.0 150 2.76 3.520 16.87  0  0    3    2
+#> 16 15.2   8 304.0 150 3.15 3.435 17.30  0  0    3    2
+#> 17 13.3   8 350.0 245 3.73 3.840 15.41  0  0    3    4
+#> 18 19.2   8 400.0 175 3.08 3.845 17.05  0  0    3    2
+#> 19 15.8   8 351.0 264 4.22 3.170 14.50  0  1    5    4
+#> 20 19.7   6 145.0 175 3.62 2.770 15.50  0  1    5    6
+#> 21 15.0   8 301.0 335 3.54 3.570 14.60  0  1    5    8

+
+# You can vary the selection of columns on which to apply the
+# predicate. filter_at() takes a vars() specification:
+filter_at(mtcars, vars(starts_with("d")), any_vars((. %% 2) == 0))
#>     mpg cyl disp  hp drat    wt  qsec vs am gear carb
+#> 1  21.0   6  160 110 3.90 2.620 16.46  0  1    4    4
+#> 2  21.0   6  160 110 3.90 2.875 17.02  0  1    4    4
+#> 3  22.8   4  108  93 3.85 2.320 18.61  1  1    4    1
+#> 4  21.4   6  258 110 3.08 3.215 19.44  1  0    3    1
+#> 5  18.7   8  360 175 3.15 3.440 17.02  0  0    3    2
+#> 6  14.3   8  360 245 3.21 3.570 15.84  0  0    3    4
+#> 7  10.4   8  472 205 2.93 5.250 17.98  0  0    3    4
+#> 8  10.4   8  460 215 3.00 5.424 17.82  0  0    3    4
+#> 9  14.7   8  440 230 3.23 5.345 17.42  0  0    3    4
+#> 10 15.5   8  318 150 2.76 3.520 16.87  0  0    3    2
+#> 11 15.2   8  304 150 3.15 3.435 17.30  0  0    3    2
+#> 12 13.3   8  350 245 3.73 3.840 15.41  0  0    3    4
+#> 13 19.2   8  400 175 3.08 3.845 17.05  0  0    3    2

+# And filter_if() selects variables with a predicate function:
+filter_if(mtcars, ~ all(floor(.) == .), all_vars(. != 0))
#>    mpg cyl  disp  hp drat    wt  qsec vs am gear carb
+#> 1 22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1
+#> 2 32.4   4  78.7  66 4.08 2.200 19.47  1  1    4    1
+#> 3 30.4   4  75.7  52 4.93 1.615 18.52  1  1    4    2
+#> 4 33.9   4  71.1  65 4.22 1.835 19.90  1  1    4    1
+#> 5 27.3   4  79.0  66 4.08 1.935 18.90  1  1    4    1
+#> 6 30.4   4  95.1 113 3.77 1.513 16.90  1  1    5    2
+#> 7 21.4   4 121.0 109 4.11 2.780 18.60  1  1    4    2
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/funs.html b/docs/reference/funs.html new file mode 100644 index 0000000000..008577840c --- /dev/null +++ b/docs/reference/funs.html @@ -0,0 +1,164 @@ + + + + + + + + +Create a list of functions calls. — funs • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Create a list of functions calls.

+
+ + +

funs() provides a flexible way to generate a named list of +functions for input to other functions like summarise_at().

+ + + 
funs(..., .args = list())
+ +

Arguments

+ + + + + + + + + + +
...

A list of functions specified by:

    +

  • Their name, "mean"

    • +

  • The function itself, mean

    • +

  • A call to the function with . as a dummy argument, +mean(., na.rm = TRUE)

    • +
+ +

These arguments are automatically quoted. They +support unquoting and splicing. See +vignette("programming") for an introduction to these concepts.

.args, args

A named list of additional arguments to be added +to all function calls.

+ + +

Examples

+ 
funs(mean, "mean", mean(., na.rm = TRUE))
#> <fun_calls>
+#> $ mean: mean(.)
+#> $ mean: mean(.)
+#> $ mean: mean(., na.rm = TRUE)

+# Override default names
+funs(m1 = mean, m2 = "mean", m3 = mean(., na.rm = TRUE))
#> <fun_calls>
+#> $ m1: mean(.)
+#> $ m2: mean(.)
+#> $ m3: mean(., na.rm = TRUE)

+# If you have function names in a vector, use funs_
+fs <- c("min", "max")
+funs_(fs)
#> <fun_calls>
+#> $ min: min(.)
+#> $ max: max(.)
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/group_by.html b/docs/reference/group_by.html new file mode 100644 index 0000000000..d85d814ec1 --- /dev/null +++ b/docs/reference/group_by.html @@ -0,0 +1,272 @@ + + + + + + + + +Group a tbl by one or more variables. — group_by • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Group a tbl by one or more variables.

+
+ + +

Most data operations are usefully done on groups defined by variables. +group_by() takes an existing tbl and converts it into a grouped tbl +where operations are performed "by group". + + groups() and group_vars() tell you how a table is grouped. +ungroup() removes grouping.

+ + + 
group_by(.data, ..., add = FALSE)
+
+groups(x)
+
+group_vars(x)
+
+ungroup(x, ...)
+ +

Arguments

+ + + + + + + + + + + + + + + + + + +
.data

a tbl

...

Variables to group by. All tbls accept variable names, +some will also accept functions of variables. Duplicated groups +will be silently dropped.

add

When add = FALSE, the default, group_by() will +override existing groups. To instead add to the existing groups, +use add = TRUE

x

data tbl()

+ +

Tbl types

+ + +

group_by() is an S3 generic with methods for the three built-in +tbls. See the help for the corresponding classes and their manip +methods for more details:

+ +

Scoped grouping

+ + +

The three scoped variants (group_by_all(), group_by_if() and +group_by_at()) make it easy to group a dataset by a selection of +variables.

+ + +

Examples

+ 
by_cyl <- mtcars %>% group_by(cyl)
+
+# grouping doesn't change how the data looks (apart from listing
+# how it's grouped):
+by_cyl
#> Source: local data frame [32 x 11]
+#> Groups: cyl [3]
+#> 
+#>      mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
+#> *  <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
+#> 1   21.0     6 160.0   110  3.90 2.620 16.46     0     1     4     4
+#> 2   21.0     6 160.0   110  3.90 2.875 17.02     0     1     4     4
+#> 3   22.8     4 108.0    93  3.85 2.320 18.61     1     1     4     1
+#> 4   21.4     6 258.0   110  3.08 3.215 19.44     1     0     3     1
+#> 5   18.7     8 360.0   175  3.15 3.440 17.02     0     0     3     2
+#> 6   18.1     6 225.0   105  2.76 3.460 20.22     1     0     3     1
+#> 7   14.3     8 360.0   245  3.21 3.570 15.84     0     0     3     4
+#> 8   24.4     4 146.7    62  3.69 3.190 20.00     1     0     4     2
+#> 9   22.8     4 140.8    95  3.92 3.150 22.90     1     0     4     2
+#> 10  19.2     6 167.6   123  3.92 3.440 18.30     1     0     4     4
+#> # ... with 22 more rows

+# It changes how it acts with the other dplyr verbs:
+by_cyl %>% summarise(
+  disp = mean(disp),
+  hp = mean(hp)
+)
#> # A tibble: 3 × 3
+#>     cyl     disp        hp
+#>   <dbl>    <dbl>     <dbl>
+#> 1     4 105.1364  82.63636
+#> 2     6 183.3143 122.28571
+#> 3     8 353.1000 209.21429
by_cyl %>% filter(disp == max(disp))
#> Source: local data frame [3 x 11]
+#> Groups: cyl [3]
+#> 
+#>     mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
+#>   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
+#> 1  21.4     6 258.0   110  3.08 3.215 19.44     1     0     3     1
+#> 2  24.4     4 146.7    62  3.69 3.190 20.00     1     0     4     2
+#> 3  10.4     8 472.0   205  2.93 5.250 17.98     0     0     3     4

+# Each call to summarise() removes a layer of grouping
+by_vs_am <- mtcars %>% group_by(vs, am)
+by_vs <- by_vs_am %>% summarise(n = n())
+by_vs
#> Source: local data frame [4 x 3]
+#> Groups: vs [?]
+#> 
+#>      vs    am     n
+#>   <dbl> <dbl> <int>
+#> 1     0     0    12
+#> 2     0     1     6
+#> 3     1     0     7
+#> 4     1     1     7
by_vs %>% summarise(n = sum(n))
#> # A tibble: 2 × 2
+#>      vs     n
+#>   <dbl> <int>
+#> 1     0    18
+#> 2     1    14

+# To removing grouping, use ungroup
+by_vs %>%
+  ungroup() %>%
+  summarise(n = sum(n))
#> # A tibble: 1 × 1
+#>       n
+#>   <int>
+#> 1    32

+# You can group by expressions: this is just short-hand for
+# a mutate/rename followed by a simple group_by
+mtcars %>% group_by(vsam = vs + am)
#> Source: local data frame [32 x 12]
+#> Groups: vsam [3]
+#> 
+#>      mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb  vsam
+#>    <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
+#> 1   21.0     6 160.0   110  3.90 2.620 16.46     0     1     4     4     1
+#> 2   21.0     6 160.0   110  3.90 2.875 17.02     0     1     4     4     1
+#> 3   22.8     4 108.0    93  3.85 2.320 18.61     1     1     4     1     2
+#> 4   21.4     6 258.0   110  3.08 3.215 19.44     1     0     3     1     1
+#> 5   18.7     8 360.0   175  3.15 3.440 17.02     0     0     3     2     0
+#> 6   18.1     6 225.0   105  2.76 3.460 20.22     1     0     3     1     1
+#> 7   14.3     8 360.0   245  3.21 3.570 15.84     0     0     3     4     0
+#> 8   24.4     4 146.7    62  3.69 3.190 20.00     1     0     4     2     1
+#> 9   22.8     4 140.8    95  3.92 3.150 22.90     1     0     4     2     1
+#> 10  19.2     6 167.6   123  3.92 3.440 18.30     1     0     4     4     1
+#> # ... with 22 more rows

+# By default, group_by overrides existing grouping
+by_cyl %>%
+  group_by(vs, am) %>%
+  group_vars()
#> [1] "vs" "am"

+# Use add = TRUE to instead append
+by_cyl %>%
+  group_by(vs, am, add = TRUE) %>%
+  group_vars()
#> [1] "cyl" "vs"  "am"
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/group_by_all.html b/docs/reference/group_by_all.html new file mode 100644 index 0000000000..bb5662e085 --- /dev/null +++ b/docs/reference/group_by_all.html @@ -0,0 +1,254 @@ + + + + + + + + +Group by a selection of variables. — group_by_all • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Group by a selection of variables.

+
+ + +

These scoped variants of group_by() group a data frame by a +selection of variables. Like group_by(), they have optional +mutate semantics.

+ + + 
group_by_all(.tbl, .funs = list(), ...)
+
+group_by_at(.tbl, .vars, .funs = list(), ..., .add = FALSE)
+
+group_by_if(.tbl, .predicate, .funs = list(), ..., .add = FALSE)
+ +

Arguments

+ + + + + + + + + + + + + + + + + + + + + + + + + + +
.tbl

A tbl object.

.funs

List of function calls generated by funs(), or a +character vector of function names, or simply a function.

...

Additional arguments for the function calls in +.funs. These are evaluated only once, with explicit +splicing.

.vars

A list of columns generated by vars(), +or a character vector of column names, or a numeric vector of column +positions.

.add

Passed to the add argument of group_by().

.predicate

A predicate function to be applied to the columns +or a logical vector. The variables for which .predicate is or +returns TRUE are selected. This argument is passed to +rlang::as_function() and thus supports quosure-style lambda +functions and strings representing function names.

+ + +

Examples

+ 
# Group a data frame by all variables:
+group_by_all(mtcars)
#> Source: local data frame [32 x 11]
+#> Groups: mpg, cyl, disp, hp, drat, wt, qsec, vs, am, gear, carb [32]
+#> 
+#>      mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
+#> *  <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
+#> 1   21.0     6 160.0   110  3.90 2.620 16.46     0     1     4     4
+#> 2   21.0     6 160.0   110  3.90 2.875 17.02     0     1     4     4
+#> 3   22.8     4 108.0    93  3.85 2.320 18.61     1     1     4     1
+#> 4   21.4     6 258.0   110  3.08 3.215 19.44     1     0     3     1
+#> 5   18.7     8 360.0   175  3.15 3.440 17.02     0     0     3     2
+#> 6   18.1     6 225.0   105  2.76 3.460 20.22     1     0     3     1
+#> 7   14.3     8 360.0   245  3.21 3.570 15.84     0     0     3     4
+#> 8   24.4     4 146.7    62  3.69 3.190 20.00     1     0     4     2
+#> 9   22.8     4 140.8    95  3.92 3.150 22.90     1     0     4     2
+#> 10  19.2     6 167.6   123  3.92 3.440 18.30     1     0     4     4
+#> # ... with 22 more rows

+# Group by variables selected with a predicate:
+group_by_if(iris, is.factor)
#> Source: local data frame [150 x 5]
+#> Groups: Species [3]
+#> 
+#>    Sepal.Length Sepal.Width Petal.Length Petal.Width Species
+#>           <dbl>       <dbl>        <dbl>       <dbl>  <fctr>
+#> 1           5.1         3.5          1.4         0.2  setosa
+#> 2           4.9         3.0          1.4         0.2  setosa
+#> 3           4.7         3.2          1.3         0.2  setosa
+#> 4           4.6         3.1          1.5         0.2  setosa
+#> 5           5.0         3.6          1.4         0.2  setosa
+#> 6           5.4         3.9          1.7         0.4  setosa
+#> 7           4.6         3.4          1.4         0.3  setosa
+#> 8           5.0         3.4          1.5         0.2  setosa
+#> 9           4.4         2.9          1.4         0.2  setosa
+#> 10          4.9         3.1          1.5         0.1  setosa
+#> # ... with 140 more rows

+# Group by variables selected by name:
+group_by_at(mtcars, vars(vs, am))
#> Source: local data frame [32 x 11]
+#> Groups: vs, am [4]
+#> 
+#>      mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
+#> *  <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
+#> 1   21.0     6 160.0   110  3.90 2.620 16.46     0     1     4     4
+#> 2   21.0     6 160.0   110  3.90 2.875 17.02     0     1     4     4
+#> 3   22.8     4 108.0    93  3.85 2.320 18.61     1     1     4     1
+#> 4   21.4     6 258.0   110  3.08 3.215 19.44     1     0     3     1
+#> 5   18.7     8 360.0   175  3.15 3.440 17.02     0     0     3     2
+#> 6   18.1     6 225.0   105  2.76 3.460 20.22     1     0     3     1
+#> 7   14.3     8 360.0   245  3.21 3.570 15.84     0     0     3     4
+#> 8   24.4     4 146.7    62  3.69 3.190 20.00     1     0     4     2
+#> 9   22.8     4 140.8    95  3.92 3.150 22.90     1     0     4     2
+#> 10  19.2     6 167.6   123  3.92 3.440 18.30     1     0     4     4
+#> # ... with 22 more rows

+# Like group_by(), the scoped variants have optional mutate
+# semantics. This provide a shortcut for group_by() + mutate():
+group_by_all(mtcars, as.factor)
#> Source: local data frame [32 x 11]
+#> Groups: mpg, cyl, disp, hp, drat, wt, qsec, vs, am, gear, carb [32]
+#> 
+#>       mpg    cyl   disp     hp   drat     wt   qsec     vs     am   gear   carb
+#>    <fctr> <fctr> <fctr> <fctr> <fctr> <fctr> <fctr> <fctr> <fctr> <fctr> <fctr>
+#> 1      21      6    160    110    3.9   2.62  16.46      0      1      4      4
+#> 2      21      6    160    110    3.9  2.875  17.02      0      1      4      4
+#> 3    22.8      4    108     93   3.85   2.32  18.61      1      1      4      1
+#> 4    21.4      6    258    110   3.08  3.215  19.44      1      0      3      1
+#> 5    18.7      8    360    175   3.15   3.44  17.02      0      0      3      2
+#> 6    18.1      6    225    105   2.76   3.46  20.22      1      0      3      1
+#> 7    14.3      8    360    245   3.21   3.57  15.84      0      0      3      4
+#> 8    24.4      4  146.7     62   3.69   3.19     20      1      0      4      2
+#> 9    22.8      4  140.8     95   3.92   3.15   22.9      1      0      4      2
+#> 10   19.2      6  167.6    123   3.92   3.44   18.3      1      0      4      4
+#> # ... with 22 more rows
group_by_if(iris, is.factor, as.character)
#> Source: local data frame [150 x 5]
+#> Groups: Species [3]
+#> 
+#>    Sepal.Length Sepal.Width Petal.Length Petal.Width Species
+#>           <dbl>       <dbl>        <dbl>       <dbl>   <chr>
+#> 1           5.1         3.5          1.4         0.2  setosa
+#> 2           4.9         3.0          1.4         0.2  setosa
+#> 3           4.7         3.2          1.3         0.2  setosa
+#> 4           4.6         3.1          1.5         0.2  setosa
+#> 5           5.0         3.6          1.4         0.2  setosa
+#> 6           5.4         3.9          1.7         0.4  setosa
+#> 7           4.6         3.4          1.4         0.3  setosa
+#> 8           5.0         3.4          1.5         0.2  setosa
+#> 9           4.4         2.9          1.4         0.2  setosa
+#> 10          4.9         3.1          1.5         0.1  setosa
+#> # ... with 140 more rows
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/group_by_prepare.html b/docs/reference/group_by_prepare.html new file mode 100644 index 0000000000..7092c317bb --- /dev/null +++ b/docs/reference/group_by_prepare.html @@ -0,0 +1,133 @@ + + + + + + + + +Prepare for grouping. — group_by_prepare • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Prepare for grouping.

+
+ + +

Performs standard operations that should happen before individual methods +process the data. This includes mutating the tbl to add new grouping columns +and updating the groups (based on add)

+ + + 
group_by_prepare(.data, ..., .dots = list(), add = FALSE)
+ +

Value

+ +

A list

+
data

Modified tbl

+
groups

Modified groups

+ + + +
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/group_indices.html b/docs/reference/group_indices.html new file mode 100644 index 0000000000..da489d4cad --- /dev/null +++ b/docs/reference/group_indices.html @@ -0,0 +1,148 @@ + + + + + + + + +Group id. — group_indices • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Group id.

+
+ + +

Generate a unique id for each group

+ + + 
group_indices(.data, ...)
+ +

Arguments

+ + + + + + + + + + +
.data

a tbl

...

Variables to group by. All tbls accept variable names, +some will also accept functions of variables. Duplicated groups +will be silently dropped.

+ +

See also

+ +

group_by()

+ + +

Examples

+ 
group_indices(mtcars, cyl)
#>  [1] 2 2 1 2 3 2 3 1 1 2 2 3 3 3 3 3 3 1 1 1 1 3 3 3 3 1 1 1 3 2 3 1
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/group_size.html b/docs/reference/group_size.html new file mode 100644 index 0000000000..865741ed26 --- /dev/null +++ b/docs/reference/group_size.html @@ -0,0 +1,155 @@ + + + + + + + + +Calculate group sizes. — group_size • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Calculate group sizes.

+
+ + +

Calculate group sizes.

+ + + 
group_size(x)
+
+n_groups(x)
+ +

Arguments

+ + + + + + +
x

a grouped tbl

+ + +

Examples

+ 
if (require("nycflights13")) {
+
+by_day <- flights %>% group_by(year, month, day)
+n_groups(by_day)
+group_size(by_day)
+
+by_dest <- flights %>% group_by(dest)
+n_groups(by_dest)
+group_size(by_dest)
+}
#>   [1]   254   265   439     8 17215  2439   275   443   375   297  6333 15508
+#>  [13]   896  2589  4681   371  1781    36   116   864    52  2884  4573 14064
+#>  [25]  3524   138  3941  1525  9705  7266  8738   569  9384   213    17 12055
+#>  [37]   765  1606   849    15   707  2115  5700  7198   110  2077    25  2720
+#>  [49]  5997 16174     1     1   668  2008 14082  4113  1789  1009 11728  2802
+#>  [61]   572  7185  3799    15   221    59   312   346   849 17283  1536  6554
+#>  [73]  1354  1632  4656  2875   365    19   376  2352  8163  2454  2416  3537
+#>  [85]  2737   686   804    10  1157  3923 13331   329  5819  2467   284   825
+#>  [97]  1211  4339   522  1761  7466   315   101   631  1036
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/grouped_df.html b/docs/reference/grouped_df.html new file mode 100644 index 0000000000..315deca72d --- /dev/null +++ b/docs/reference/grouped_df.html @@ -0,0 +1,147 @@ + + + + + + + + +A grouped data frame. — grouped_df • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

A grouped data frame.

+
+ + +

The easiest way to create a grouped data frame is to call the group_by() +method on a data frame or tbl: this will take care of capturing +the unevaluated expressions for you.

+ + + 
grouped_df(data, vars, drop = TRUE)
+
+is.grouped_df(x)
+
+is_grouped_df(x)
+ +

Arguments

+ + + + + + + + + + + + + + +
data

a tbl or data frame.

vars

a character vector or a list of name()

drop

if TRUE preserve all factor levels, even those without +data.

+ + +
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/id.html b/docs/reference/id.html new file mode 100644 index 0000000000..b79266ea3a --- /dev/null +++ b/docs/reference/id.html @@ -0,0 +1,147 @@ + + + + + + + + +Compute a unique numeric id for each unique row in a data frame. — id • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Compute a unique numeric id for each unique row in a data frame.

+
+ + +

Properties:

    +

  • order(id) is equivalent to do.call(order, df)

    • +

  • rows containing the same data have the same value

    • +

  • if drop = FALSE then room for all possibilites

    • +
+ + + 
id(.variables, drop = FALSE)
+ +

Arguments

+ + + + + + + + + + +
.variables

list of variables

drop

drop unusued factor levels?

+ +

Value

+ +

a numeric vector with attribute n, giving total number of +possibilities

+ + +
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/if_else.html b/docs/reference/if_else.html new file mode 100644 index 0000000000..7210586ec9 --- /dev/null +++ b/docs/reference/if_else.html @@ -0,0 +1,166 @@ + + + + + + + + +Vectorised if. — if_else • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Vectorised if.

+
+ + +

Compared to the base ifelse(), this function is more strict. +It checks that true and false are the same type. This +strictness makes the output type more predictable, and makes it somewhat +faster.

+ + + 
if_else(condition, true, false, missing = NULL)
+ +

Arguments

+ + + + + + + + + + + + + + +
condition

Logical vector

true, false

Values to use for TRUE and FALSE values of +condition. They must be either the same length as condition, +or length 1. They must also be the same type: if_else() checks that +they have the same type and same class. All other attributes are +taken from true.

missing

If not NULL, will be used to replace missing +values.

+ +

Value

+ +

Where condition is TRUE, the matching value from +true, where it's FALSE, the matching value from false, +otherwise NA.

+ + +

Examples

+ 
x <- c(-5:5, NA)
+if_else(x < 0, NA_integer_, x)
#>  [1] NA NA NA NA NA  0  1  2  3  4  5 NA
if_else(x < 0, "negative", "positive", "missing")
#>  [1] "negative" "negative" "negative" "negative" "negative" "positive"
+#>  [7] "positive" "positive" "positive" "positive" "positive" "missing" 

+# Unlike ifelse, if_else preserves types
+x <- factor(sample(letters[1:5], 10, replace = TRUE))
+ifelse(x %in% c("a", "b", "c"), x, factor(NA))
#>  [1]  2  3  1 NA NA NA  3 NA  3 NA
if_else(x %in% c("a", "b", "c"), x, factor(NA))
#>  [1] b    c    a    <NA> <NA> <NA> c    <NA> c    <NA>
+#> Levels: a b c d e
# Attributes are taken from the `true` vector,
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/index.html b/docs/reference/index.html new file mode 100644 index 0000000000..4e4590855b --- /dev/null +++ b/docs/reference/index.html @@ -0,0 +1,520 @@ + + + + + + + + +Function reference • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Function reference

+

version 0.5.0.9001

+
+ +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+

All functions

+

+
+

all_equal all.equal.tbl_df

+

Flexible equality comparison for data frames.

+

all_vars any_vars

+

Apply predicate to all variables.

+

arrange arrange.grouped_df

+

Arrange rows by variables

+

as.table.tbl_cube as.data.frame.tbl_cube as_data_frame.tbl_cube

+

Coerce a <code>tbl_cube</code> to other data structures

+

as.tbl_cube as.tbl_cube.array as.tbl_cube.table as.tbl_cube.matrix as.tbl_cube.data.frame

+

Coerce an existing data structure into a <code>tbl_cube</code>

+

auto_copy

+

Copy tables to same source, if necessary.

+

band_members band_instruments band_instruments2

+

Band membership

+

bench_compare bench_tbls compare_tbls compare_tbls2 eval_tbls eval_tbls2

+

Evaluate, compare, benchmark operations of a set of srcs.

+

between

+

Do values in a numeric vector fall in specified range?

+

bind rbind_all rbind_list bind_rows bind_cols combine rbind_list rbind_all

+

Efficiently bind multiple data frames by row and column.

+

case_when

+

A general vectorised if.

+

coalesce

+

Find first non-missing element

+

compute collect collapse

+

Force computation of a database query

+

copy_to

+

Copy a local data frame to a remote src.

+

cumall cumany cummean

+

Cumulativate versions of any, all, and mean

+

desc

+

Descending order.

+

distinct

+

Select distinct/unique rows.

+

do

+

Do arbitrary operations on a tbl.

+

dplyr dplyr-package

+

dplyr: a grammar of data manipulation

+

explain show_query

+

Explain details of a tbl

+

filter_all filter_if filter_at

+

Filter within a selection of variables.

+

filter

+

Return rows with matching conditions

+

funs

+

Create a list of functions calls.

+

group_by_all group_by_at group_by_if

+

Group by a selection of variables.

+

group_by groups group_vars ungroup

+

Group a tbl by one or more variables.

+

group_indices

+

Group id.

+

group_size n_groups

+

Calculate group sizes.

+

if_else

+

Vectorised if.

+

join inner_join left_join right_join full_join semi_join anti_join

+

Join two tbls together

+

join.tbl_df inner_join.tbl_df left_join.tbl_df right_join.tbl_df full_join.tbl_df semi_join.tbl_df anti_join.tbl_df

+

Join data frame tbls.

+

lead-lag lead lag

+

Lead and lag.

+

location changes

+

Print the location in memory of a data frame

+

mutate transmute

+

Add new variables

+

n_distinct

+

Efficiently count the number of unique values in a set of vector

+

n

+

The number of observations in the current group.

+

na_if

+

Convert values to NA.

+

nasa

+

NASA spatio-temporal data

+

near

+

Compare two numeric vectors.

+

nth first last

+

Extract the first, last or nth value from a vector.

+

order_by

+

A helper function for ordering window function output

+

pull

+

Pull out a single variable

+

ranking row_number ntile min_rank dense_rank percent_rank cume_dist

+

Windowed rank functions.

+

recode recode_factor

+

Recode values

+

rowwise

+

Group input by rows

+

sample sample_n sample_frac

+

Sample n rows from a table.

+

scoped

+

Operate on a selection of variables.

+

tally_ count_ add_tally_ add_count_ distinct_ do_ funs_ group_by_ group_indices_ filter_ slice_ summarise_ summarize_ mutate_ transmute_ arrange_ select_ rename_ se-deprecated select_vars_ rename_vars_

+

Deprecated SE versions of main verbs.

+

select_all rename_all select_if rename_if select_at rename_at

+

Select and rename a selection of variables.

+

select_helpers current_vars starts_with ends_with contains matches num_range one_of everything

+

Select helpers

+

select rename

+

Select/rename variables by name

+

setops intersect union union_all setdiff setequal

+

Set operations.

+

slice

+

Select rows by position

+

src_dbi src_mysql src_postgres src_sqlite

+

Source for database backends

+

src_tbls

+

List all tbls provided by a source.

+

starwars

+

Starwars characters

+

storms

+

Storm tracks data

+

summarise_all summarise_if summarise_at summarize_all summarize_if summarize_at mutate_all mutate_if mutate_at transmute_all transmute_if transmute_at

+

Summarise and mutate multiple columns.

+

summarise summarize

+

Summarise multiple values to a single value

+

tally count add_tally add_count

+

Counts/tally observations by group.

+

tbl_cube

+

A data cube tbl.

+

tbl_vars tbl_nongroup_vars

+

List variables provided by a tbl.

+

tbl is.tbl as.tbl

+

Create a table from a data source

+

top_n

+

Select top (or bottom) n rows (by value).

+

vars

+

Select variables.

+
+
+ + +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/init_logging.html b/docs/reference/init_logging.html new file mode 100644 index 0000000000..7d431f712f --- /dev/null +++ b/docs/reference/init_logging.html @@ -0,0 +1,134 @@ + + + + + + + + +Enable internal logging — init_logging • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Enable internal logging

+
+ + +

Log entries, depending on the log level, will be printed to the standard +error stream.

+ + + 
init_logging(log_level)
+ +

Arguments

+ + + + + + +
log_level

A character value, one of "WARN", "INFO", "DEBUG", "VERB", +or "NONE".

+ + +
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/join.html b/docs/reference/join.html new file mode 100644 index 0000000000..76c76cc7a3 --- /dev/null +++ b/docs/reference/join.html @@ -0,0 +1,258 @@ + + + + + + + + +Join two tbls together — join • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Join two tbls together

+
+ + +

These are generic functions that dispatch to individual tbl methods - see the +method documentation for details of individual data sources. x and +y should usually be from the same data source, but if copy is +TRUE, y will automatically be copied to the same source as x.

+ + + 
inner_join(x, y, by = NULL, copy = FALSE, suffix = c(".x", ".y"), ...)
+
+left_join(x, y, by = NULL, copy = FALSE, suffix = c(".x", ".y"), ...)
+
+right_join(x, y, by = NULL, copy = FALSE, suffix = c(".x", ".y"), ...)
+
+full_join(x, y, by = NULL, copy = FALSE, suffix = c(".x", ".y"), ...)
+
+semi_join(x, y, by = NULL, copy = FALSE, ...)
+
+anti_join(x, y, by = NULL, copy = FALSE, ...)
+ +

Arguments

+ + + + + + + + + + + + + + + + + + + + + + +
x, y

tbls to join

by

a character vector of variables to join by. If NULL, the +default, *_join() will do a natural join, using all variables with +common names across the two tables. A message lists the variables so +that you can check they're right (to suppress the message, simply +explicitly list the variables that you want to join).

+

To join by different variables on x and y use a named vector. +For example, by = c("a" = "b") will match x.a to +y.b.

copy

If x and y are not from the same data source, +and copy is TRUE, then y will be copied into the +same src as x. This allows you to join tables across srcs, but +it is a potentially expensive operation so you must opt into it.

suffix

If there are non-joined duplicate variables in x and +y, these suffixes will be added to the output to diambiguate them. +Should be a character vector of length 2.

...

other parameters passed onto methods

+ +

Join types

+ + +

Currently dplyr supports four join types:

+
inner_join()

return all rows from x where there are matching +values in y, and all columns from x and y. If there are multiple matches +between x and y, all combination of the matches are returned.

+
left_join()

return all rows from x, and all columns from x +and y. Rows in x with no match in y will have NA values in the new +columns. If there are multiple matches between x and y, all combinations +of the matches are returned.

+
right_join()

return all rows from y, and all columns from x +and y. Rows in y with no match in x will have NA values in the new +columns. If there are multiple matches between x and y, all combinations +of the matches are returned.

+
semi_join()

return all rows from x where there are matching +values in y, keeping just columns from x. + A semi join differs from an inner join because an inner join will return +one row of x for each matching row of y, where a semi +join will never duplicate rows of x.

+
anti_join()

return all rows from x where there are not +matching values in y, keeping just columns from x.

+
full_join()

return all rows and all columns from both x and y. +Where there are not matching values, returns NA for the one missing.

+
+ +

Grouping

+ + +

Groups are ignored for the purpose of joining, but the result preserves +the grouping of x.

+ + +

Examples

+ 
# "Mutating" joins add variables to the LHS
+band_members %>% inner_join(band_instruments)
#> Joining, by = "name"
#> # A tibble: 2 × 3
+#>    name    band  plays
+#>   <chr>   <chr>  <chr>
+#> 1  John Beatles guitar
+#> 2  Paul Beatles   bass
band_members %>% left_join(band_instruments)
#> Joining, by = "name"
#> # A tibble: 3 × 3
+#>    name    band  plays
+#>   <chr>   <chr>  <chr>
+#> 1  Mick  Stones   <NA>
+#> 2  John Beatles guitar
+#> 3  Paul Beatles   bass
band_members %>% right_join(band_instruments)
#> Joining, by = "name"
#> # A tibble: 3 × 3
+#>    name    band  plays
+#>   <chr>   <chr>  <chr>
+#> 1  John Beatles guitar
+#> 2  Paul Beatles   bass
+#> 3 Keith    <NA> guitar
band_members %>% full_join(band_instruments)
#> Joining, by = "name"
#> # A tibble: 4 × 3
+#>    name    band  plays
+#>   <chr>   <chr>  <chr>
+#> 1  Mick  Stones   <NA>
+#> 2  John Beatles guitar
+#> 3  Paul Beatles   bass
+#> 4 Keith    <NA> guitar

+# "Filtering" joins keep cases from the LHS
+band_members %>% semi_join(band_instruments)
#> Joining, by = "name"
#> # A tibble: 2 × 2
+#>    name    band
+#>   <chr>   <chr>
+#> 1  John Beatles
+#> 2  Paul Beatles
band_members %>% anti_join(band_instruments)
#> Joining, by = "name"
#> # A tibble: 1 × 2
+#>    name   band
+#>   <chr>  <chr>
+#> 1  Mick Stones

+# To suppress the message, supply by
+band_members %>% inner_join(band_instruments, by = "name")
#> # A tibble: 2 × 3
+#>    name    band  plays
+#>   <chr>   <chr>  <chr>
+#> 1  John Beatles guitar
+#> 2  Paul Beatles   bass
# This is good practice in production code
+
+# Use a named `by` if the join variables have different names
+band_members %>% full_join(band_instruments2, by = c("name" = "artist"))
#> # A tibble: 4 × 3
+#>    name    band  plays
+#>   <chr>   <chr>  <chr>
+#> 1  Mick  Stones   <NA>
+#> 2  John Beatles guitar
+#> 3  Paul Beatles   bass
+#> 4 Keith    <NA> guitar
# Note that only the key from the LHS is kept
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/join.tbl_df.html b/docs/reference/join.tbl_df.html new file mode 100644 index 0000000000..6ee0d85772 --- /dev/null +++ b/docs/reference/join.tbl_df.html @@ -0,0 +1,237 @@ + + + + + + + + +Join data frame tbls. — join.tbl_df • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Join data frame tbls.

+
+ + +

See join for a description of the general purpose of the +functions.

+ + + 
# S3 method for tbl_df
+inner_join(x, y, by = NULL, copy = FALSE,
+  suffix = c(".x", ".y"), ...,
+  na_matches = pkgconfig::get_config("dplyr::na_matches"))
+
+# S3 method for tbl_df
+left_join(x, y, by = NULL, copy = FALSE, suffix = c(".x",
+  ".y"), ..., na_matches = pkgconfig::get_config("dplyr::na_matches"))
+
+# S3 method for tbl_df
+right_join(x, y, by = NULL, copy = FALSE,
+  suffix = c(".x", ".y"), ...,
+  na_matches = pkgconfig::get_config("dplyr::na_matches"))
+
+# S3 method for tbl_df
+full_join(x, y, by = NULL, copy = FALSE, suffix = c(".x",
+  ".y"), ..., na_matches = pkgconfig::get_config("dplyr::na_matches"))
+
+# S3 method for tbl_df
+semi_join(x, y, by = NULL, copy = FALSE, ...,
+  na_matches = pkgconfig::get_config("dplyr::na_matches"))
+
+# S3 method for tbl_df
+anti_join(x, y, by = NULL, copy = FALSE, ...,
+  na_matches = pkgconfig::get_config("dplyr::na_matches"))
+ +

Arguments

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
x

tbls to join

y

tbls to join

by

a character vector of variables to join by. If NULL, the +default, *_join() will do a natural join, using all variables with +common names across the two tables. A message lists the variables so +that you can check they're right (to suppress the message, simply +explicitly list the variables that you want to join).

+

To join by different variables on x and y use a named vector. +For example, by = c("a" = "b") will match x.a to +y.b.

copy

If x and y are not from the same data source, +and copy is TRUE, then y will be copied into the +same src as x. This allows you to join tables across srcs, but +it is a potentially expensive operation so you must opt into it.

suffix

If there are non-joined duplicate variables in x and +y, these suffixes will be added to the output to diambiguate them. +Should be a character vector of length 2.

...

included for compatibility with the generic; otherwise ignored.

na_matches

Use "na" to treat two NA or NaN values as equal, like merge(). +The default, "never", always treats two NA or NaN values as +different, like joins for database sources, similarly to +merge(incomparables = FALSE). +Users and package authors can change the default behavior by calling +pkgconfig::set_config("dplyr::na_matches" = "na").

+ + +

Examples

+ 
if (require("Lahman")) {
+batting_df <- tbl_df(Batting)
+person_df <- tbl_df(Master)
+
+uperson_df <- tbl_df(Master[!duplicated(Master$playerID), ])
+
+# Inner join: match batting and person data
+inner_join(batting_df, person_df)
+inner_join(batting_df, uperson_df)
+
+# Left join: match, but preserve batting data
+left_join(batting_df, uperson_df)
+
+# Anti join: find batters without person data
+anti_join(batting_df, person_df)
+# or people who didn't bat
+anti_join(person_df, batting_df)
+}
#> Loading required package: Lahman
#> Joining, by = "playerID"
#> Joining, by = "playerID"
#> Joining, by = "playerID"
#> Joining, by = "playerID"
#> Joining, by = "playerID"
#> # A tibble: 187 × 26
+#>     playerID birthYear birthMonth birthDay birthCountry birthState  birthCity
+#>        <chr>     <int>      <int>    <int>        <chr>      <chr>      <chr>
+#> 1  youngni99      1840          9       12          USA         NY  Amsterdam
+#> 2  wrighal99      1842          3       31          USA         NY   New York
+#> 3  wilsoju99      1896          2       28          USA         VA  Remington
+#> 4  willijo99      1885          4        6          USA         TX     Seguin
+#> 5  williji99      1847          1        4          USA         OH    Catawba
+#> 6  wilkijl99      1878          5       14          USA         IA      Perry
+#> 7  whiteso99      1868          6       12          USA         OH   Bellaire
+#> 8  weissge99      1894          6       23          USA         CT  New Haven
+#> 9  waltzjo99      1860          1       12          USA         MD Hagerstown
+#> 10 walshmi99      1850          4       29      Ireland       <NA>       <NA>
+#> # ... with 177 more rows, and 19 more variables: deathYear <int>,
+#> #   deathMonth <int>, deathDay <int>, deathCountry <chr>, deathState <chr>,
+#> #   deathCity <chr>, nameFirst <chr>, nameLast <chr>, nameGiven <chr>,
+#> #   weight <int>, height <int>, bats <fctr>, throws <fctr>, debut <chr>,
+#> #   finalGame <chr>, retroID <chr>, bbrefID <chr>, deathDate <date>,
+#> #   birthDate <date>
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/lead-lag.html b/docs/reference/lead-lag.html new file mode 100644 index 0000000000..5b6557caf1 --- /dev/null +++ b/docs/reference/lead-lag.html @@ -0,0 +1,184 @@ + + + + + + + + +Lead and lag. — lead-lag • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Lead and lag.

+
+ + +

Find the "next" or "previous" values in a vector. Useful for comparing values +ahead of or behind the current values.

+ + + 
lead(x, n = 1L, default = NA, order_by = NULL, ...)
+
+lag(x, n = 1L, default = NA, order_by = NULL, ...)
+ +

Arguments

+ + + + + + + + + + + + + + + + + + + + + + +
x

a vector of values

n

a postive integer of length 1, giving the number of positions to +lead or lag by

default

value used for non-existant rows. Defaults to NA.

order_by

override the default ordering to use another vector

...

Needed for compatibility with lag generic.

+ + +

Examples

+ 
lead(1:10, 1)
#>  [1]  2  3  4  5  6  7  8  9 10 NA
lead(1:10, 2)
#>  [1]  3  4  5  6  7  8  9 10 NA NA

+lag(1:10, 1)
#>  [1] NA  1  2  3  4  5  6  7  8  9
lead(1:10, 1)
#>  [1]  2  3  4  5  6  7  8  9 10 NA

+x <- runif(5)
+cbind(ahead = lead(x), x, behind = lag(x))
#>          ahead         x    behind
+#> [1,] 0.3789607 0.6390610        NA
+#> [2,] 0.3595307 0.3789607 0.6390610
+#> [3,] 0.8442314 0.3595307 0.3789607
+#> [4,] 0.4567492 0.8442314 0.3595307
+#> [5,]        NA 0.4567492 0.8442314

+# Use order_by if data not already ordered
+df <- data.frame(year = 2000:2005, value = (0:5) ^ 2)
+scrambled <- df[sample(nrow(df)), ]
+
+wrong <- mutate(scrambled, prev = lag(value))
+arrange(wrong, year)
#>   year value prev
+#> 1 2000     0    4
+#> 2 2001     1   NA
+#> 3 2002     4   16
+#> 4 2003     9   25
+#> 5 2004    16    1
+#> 6 2005    25    0

+right <- mutate(scrambled, prev = lag(value, order_by = year))
+arrange(right, year)
#>   year value prev
+#> 1 2000     0   NA
+#> 2 2001     1    0
+#> 3 2002     4    1
+#> 4 2003     9    4
+#> 5 2004    16    9
+#> 6 2005    25   16
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/location.html b/docs/reference/location.html new file mode 100644 index 0000000000..4b21f7ebc4 --- /dev/null +++ b/docs/reference/location.html @@ -0,0 +1,187 @@ + + + + + + + + +Print the location in memory of a data frame — location • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Print the location in memory of a data frame

+
+ + +

This is useful for understand how and when dplyr makes copies of data +frames

+ + + 
location(df)
+
+changes(x, y)
+ +

Arguments

+ + + + + + + + + + +
df

a data frame

x, y

two data frames to compare

+ + +

Examples

+ 
location(mtcars)
#> <0x10ed85aa8>
+#> Variables:
+#>  * mpg:       <0x101ad8a30>
+#>  * cyl:       <0x101ad8b60>
+#>  * disp:      <0x101ac9f90>
+#>  * hp:        <0x101aca0c0>
+#>  * drat:      <0x101a85360>
+#>  * wt:        <0x101a85490>
+#>  * qsec:      <0x101a81430>
+#>  * vs:        <0x101a81560>
+#>  * am:        <0x101a809b0>
+#>  * gear:      <0x101a80ae0>
+#>  * carb:      <0x101a5dd90>
+#> Attributes:
+#>  * names:     <0x10ed85a00>
+#>  * row.names: <0x101a5dec0>
+#>  * class:     <0x1108dc688>

+mtcars2 <- mutate(mtcars, cyl2 = cyl * 2)
+location(mtcars2)
#> <0x10e761750>
+#> Variables:
+#>  * mpg:       <0x101ad8a30>
+#>  * cyl:       <0x101ad8b60>
+#>  * disp:      <0x101ac9f90>
+#>  * hp:        <0x101aca0c0>
+#>  * drat:      <0x101a85360>
+#>  * wt:        <0x101a85490>
+#>  * qsec:      <0x101a81430>
+#>  * vs:        <0x101a81560>
+#>  * am:        <0x101a809b0>
+#>  * gear:      <0x101a80ae0>
+#>  * carb:      <0x101a5dd90>
+#>  * cyl2:      <0x10f2a2410>
+#> Attributes:
+#>  * class:     <0x1027e1588>
+#>  * names:     <0x10ed85bf8>
+#>  * row.names: <0x11028de08>

+changes(mtcars, mtcars)
#> <identical>
changes(mtcars, mtcars2)
#> Changed variables:
+#>           old     new        
+#> cyl2      <added> 0x10f2a2410
+#> 
+#> Changed attributes:
+#>           old         new        
+#> names     0x10ed85a00 0x10ed85bf8
+#> row.names 0x101a5dec0 0x10de03a98
+#> class     0x1108dc688 0x1027e1588
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/make_tbl.html b/docs/reference/make_tbl.html new file mode 100644 index 0000000000..61436a9d9b --- /dev/null +++ b/docs/reference/make_tbl.html @@ -0,0 +1,161 @@ + + + + + + + + +Create a "tbl" object — make_tbl • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Create a "tbl" object

+
+ + +

tbl() is the standard constructor for tbls. as.tbl() coerces, +and is.tbl() tests.

+ + + 
make_tbl(subclass, ...)
+ +

Arguments

+ + + + + + + + + + + + + + +
subclass

name of subclass. "tbl" is an abstract base class, so you +must supply this value. tbl_ is automatically prepended to the +class name

...

For tbl(), other fields used by class. For as.tbl(), +other arguments passed to methods.

object

to test/coerce.

+ + +

Examples

+ 
as.tbl(mtcars)
#> # A tibble: 32 × 11
+#>      mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
+#> *  <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
+#> 1   21.0     6 160.0   110  3.90 2.620 16.46     0     1     4     4
+#> 2   21.0     6 160.0   110  3.90 2.875 17.02     0     1     4     4
+#> 3   22.8     4 108.0    93  3.85 2.320 18.61     1     1     4     1
+#> 4   21.4     6 258.0   110  3.08 3.215 19.44     1     0     3     1
+#> 5   18.7     8 360.0   175  3.15 3.440 17.02     0     0     3     2
+#> 6   18.1     6 225.0   105  2.76 3.460 20.22     1     0     3     1
+#> 7   14.3     8 360.0   245  3.21 3.570 15.84     0     0     3     4
+#> 8   24.4     4 146.7    62  3.69 3.190 20.00     1     0     4     2
+#> 9   22.8     4 140.8    95  3.92 3.150 22.90     1     0     4     2
+#> 10  19.2     6 167.6   123  3.92 3.440 18.30     1     0     4     4
+#> # ... with 22 more rows
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/mutate.html b/docs/reference/mutate.html new file mode 100644 index 0000000000..ce2bc18090 --- /dev/null +++ b/docs/reference/mutate.html @@ -0,0 +1,362 @@ + + + + + + + + +Add new variables — mutate • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Add new variables

+
+ + +

mutate() adds new variables and preserves existing; +transmute() drops existing variables.

+ + + 
mutate(.data, ...)
+
+transmute(.data, ...)
+ +

Arguments

+ + + + + + + + + + +
.data

A tbl. All main verbs are S3 generics and provide methods +for tbl_df(), dtplyr::tbl_dt() and dbplyr::tbl_dbi().

...

Name-value pairs of expressions. Use NULL to drop +a variable.

+

These arguments are automatically quoted and +evaluated in the context of the data +frame. They support unquoting and +splicing. See vignette("programming") for an introduction to +these concepts.

+ +

Value

+ +

An object of the same class as .data.

+ +

Useful functions

+ + + + +

Scoped mutation and transmuation

+ + +

The three scoped variants of mutate() (mutate_all(), +mutate_if() and mutate_at()) and the three variants of +transmute() (transmute_all(), transmute_if(), +transmute_at()) make it easy to apply a transformation to a +selection of variables.

+ +

Tidy data

+ + +

When applied to a data frame, row names are silently dropped. To preserve, +convert to an explicit variable with tibble::rownames_to_column().

+ +

See also

+ +

Other single table verbs: arrange, + filter, select, + slice, summarise

+ + +

Examples

+ 
# Newly created variables are available immediately
+mtcars %>% as_tibble() %>% mutate(
+  cyl2 = cyl * 2,
+  cyl4 = cyl2 * 2
+)
#> # A tibble: 32 × 13
+#>      mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb  cyl2
+#>    <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
+#> 1   21.0     6 160.0   110  3.90 2.620 16.46     0     1     4     4    12
+#> 2   21.0     6 160.0   110  3.90 2.875 17.02     0     1     4     4    12
+#> 3   22.8     4 108.0    93  3.85 2.320 18.61     1     1     4     1     8
+#> 4   21.4     6 258.0   110  3.08 3.215 19.44     1     0     3     1    12
+#> 5   18.7     8 360.0   175  3.15 3.440 17.02     0     0     3     2    16
+#> 6   18.1     6 225.0   105  2.76 3.460 20.22     1     0     3     1    12
+#> 7   14.3     8 360.0   245  3.21 3.570 15.84     0     0     3     4    16
+#> 8   24.4     4 146.7    62  3.69 3.190 20.00     1     0     4     2     8
+#> 9   22.8     4 140.8    95  3.92 3.150 22.90     1     0     4     2     8
+#> 10  19.2     6 167.6   123  3.92 3.440 18.30     1     0     4     4    12
+#> # ... with 22 more rows, and 1 more variables: cyl4 <dbl>

+# You can also use mutate() to remove variables and
+# modify existing variables
+mtcars %>% as_tibble() %>% mutate(
+  mpg = NULL,
+  disp = disp * 0.0163871 # convert to litres
+)
#> # A tibble: 32 × 10
+#>      cyl     disp    hp  drat    wt  qsec    vs    am  gear  carb
+#>    <dbl>    <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
+#> 1      6 2.621936   110  3.90 2.620 16.46     0     1     4     4
+#> 2      6 2.621936   110  3.90 2.875 17.02     0     1     4     4
+#> 3      4 1.769807    93  3.85 2.320 18.61     1     1     4     1
+#> 4      6 4.227872   110  3.08 3.215 19.44     1     0     3     1
+#> 5      8 5.899356   175  3.15 3.440 17.02     0     0     3     2
+#> 6      6 3.687098   105  2.76 3.460 20.22     1     0     3     1
+#> 7      8 5.899356   245  3.21 3.570 15.84     0     0     3     4
+#> 8      4 2.403988    62  3.69 3.190 20.00     1     0     4     2
+#> 9      4 2.307304    95  3.92 3.150 22.90     1     0     4     2
+#> 10     6 2.746478   123  3.92 3.440 18.30     1     0     4     4
+#> # ... with 22 more rows

+
+# window functions are useful for grouped mutates
+mtcars %>%
+ group_by(cyl) %>%
+ mutate(rank = min_rank(desc(mpg)))
#> Source: local data frame [32 x 12]
+#> Groups: cyl [3]
+#> 
+#>      mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb  rank
+#>    <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <int>
+#> 1   21.0     6 160.0   110  3.90 2.620 16.46     0     1     4     4     2
+#> 2   21.0     6 160.0   110  3.90 2.875 17.02     0     1     4     4     2
+#> 3   22.8     4 108.0    93  3.85 2.320 18.61     1     1     4     1     8
+#> 4   21.4     6 258.0   110  3.08 3.215 19.44     1     0     3     1     1
+#> 5   18.7     8 360.0   175  3.15 3.440 17.02     0     0     3     2     2
+#> 6   18.1     6 225.0   105  2.76 3.460 20.22     1     0     3     1     6
+#> 7   14.3     8 360.0   245  3.21 3.570 15.84     0     0     3     4    11
+#> 8   24.4     4 146.7    62  3.69 3.190 20.00     1     0     4     2     7
+#> 9   22.8     4 140.8    95  3.92 3.150 22.90     1     0     4     2     8
+#> 10  19.2     6 167.6   123  3.92 3.440 18.30     1     0     4     4     5
+#> # ... with 22 more rows
# see `vignette("window-functions")` for more details
+
+# You can drop variables by setting them to NULL
+mtcars %>% mutate(cyl = NULL)
#>     mpg  disp  hp drat    wt  qsec vs am gear carb
+#> 1  21.0 160.0 110 3.90 2.620 16.46  0  1    4    4
+#> 2  21.0 160.0 110 3.90 2.875 17.02  0  1    4    4
+#> 3  22.8 108.0  93 3.85 2.320 18.61  1  1    4    1
+#> 4  21.4 258.0 110 3.08 3.215 19.44  1  0    3    1
+#> 5  18.7 360.0 175 3.15 3.440 17.02  0  0    3    2
+#> 6  18.1 225.0 105 2.76 3.460 20.22  1  0    3    1
+#> 7  14.3 360.0 245 3.21 3.570 15.84  0  0    3    4
+#> 8  24.4 146.7  62 3.69 3.190 20.00  1  0    4    2
+#> 9  22.8 140.8  95 3.92 3.150 22.90  1  0    4    2
+#> 10 19.2 167.6 123 3.92 3.440 18.30  1  0    4    4
+#> 11 17.8 167.6 123 3.92 3.440 18.90  1  0    4    4
+#> 12 16.4 275.8 180 3.07 4.070 17.40  0  0    3    3
+#> 13 17.3 275.8 180 3.07 3.730 17.60  0  0    3    3
+#> 14 15.2 275.8 180 3.07 3.780 18.00  0  0    3    3
+#> 15 10.4 472.0 205 2.93 5.250 17.98  0  0    3    4
+#> 16 10.4 460.0 215 3.00 5.424 17.82  0  0    3    4
+#> 17 14.7 440.0 230 3.23 5.345 17.42  0  0    3    4
+#> 18 32.4  78.7  66 4.08 2.200 19.47  1  1    4    1
+#> 19 30.4  75.7  52 4.93 1.615 18.52  1  1    4    2
+#> 20 33.9  71.1  65 4.22 1.835 19.90  1  1    4    1
+#> 21 21.5 120.1  97 3.70 2.465 20.01  1  0    3    1
+#> 22 15.5 318.0 150 2.76 3.520 16.87  0  0    3    2
+#> 23 15.2 304.0 150 3.15 3.435 17.30  0  0    3    2
+#> 24 13.3 350.0 245 3.73 3.840 15.41  0  0    3    4
+#> 25 19.2 400.0 175 3.08 3.845 17.05  0  0    3    2
+#> 26 27.3  79.0  66 4.08 1.935 18.90  1  1    4    1
+#> 27 26.0 120.3  91 4.43 2.140 16.70  0  1    5    2
+#> 28 30.4  95.1 113 3.77 1.513 16.90  1  1    5    2
+#> 29 15.8 351.0 264 4.22 3.170 14.50  0  1    5    4
+#> 30 19.7 145.0 175 3.62 2.770 15.50  0  1    5    6
+#> 31 15.0 301.0 335 3.54 3.570 14.60  0  1    5    8
+#> 32 21.4 121.0 109 4.11 2.780 18.60  1  1    4    2

+# mutate() vs transmute --------------------------
+# mutate() keeps all existing variables
+mtcars %>%
+  mutate(displ_l = disp / 61.0237)
#>     mpg cyl  disp  hp drat    wt  qsec vs am gear carb  displ_l
+#> 1  21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4 2.621932
+#> 2  21.0   6 160.0 110 3.90 2.875 17.02  0  1    4    4 2.621932
+#> 3  22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1 1.769804
+#> 4  21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1 4.227866
+#> 5  18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2 5.899347
+#> 6  18.1   6 225.0 105 2.76 3.460 20.22  1  0    3    1 3.687092
+#> 7  14.3   8 360.0 245 3.21 3.570 15.84  0  0    3    4 5.899347
+#> 8  24.4   4 146.7  62 3.69 3.190 20.00  1  0    4    2 2.403984
+#> 9  22.8   4 140.8  95 3.92 3.150 22.90  1  0    4    2 2.307300
+#> 10 19.2   6 167.6 123 3.92 3.440 18.30  1  0    4    4 2.746474
+#> 11 17.8   6 167.6 123 3.92 3.440 18.90  1  0    4    4 2.746474
+#> 12 16.4   8 275.8 180 3.07 4.070 17.40  0  0    3    3 4.519556
+#> 13 17.3   8 275.8 180 3.07 3.730 17.60  0  0    3    3 4.519556
+#> 14 15.2   8 275.8 180 3.07 3.780 18.00  0  0    3    3 4.519556
+#> 15 10.4   8 472.0 205 2.93 5.250 17.98  0  0    3    4 7.734700
+#> 16 10.4   8 460.0 215 3.00 5.424 17.82  0  0    3    4 7.538055
+#> 17 14.7   8 440.0 230 3.23 5.345 17.42  0  0    3    4 7.210313
+#> 18 32.4   4  78.7  66 4.08 2.200 19.47  1  1    4    1 1.289663
+#> 19 30.4   4  75.7  52 4.93 1.615 18.52  1  1    4    2 1.240502
+#> 20 33.9   4  71.1  65 4.22 1.835 19.90  1  1    4    1 1.165121
+#> 21 21.5   4 120.1  97 3.70 2.465 20.01  1  0    3    1 1.968088
+#> 22 15.5   8 318.0 150 2.76 3.520 16.87  0  0    3    2 5.211090
+#> 23 15.2   8 304.0 150 3.15 3.435 17.30  0  0    3    2 4.981671
+#> 24 13.3   8 350.0 245 3.73 3.840 15.41  0  0    3    4 5.735477
+#> 25 19.2   8 400.0 175 3.08 3.845 17.05  0  0    3    2 6.554830
+#> 26 27.3   4  79.0  66 4.08 1.935 18.90  1  1    4    1 1.294579
+#> 27 26.0   4 120.3  91 4.43 2.140 16.70  0  1    5    2 1.971365
+#> 28 30.4   4  95.1 113 3.77 1.513 16.90  1  1    5    2 1.558411
+#> 29 15.8   8 351.0 264 4.22 3.170 14.50  0  1    5    4 5.751864
+#> 30 19.7   6 145.0 175 3.62 2.770 15.50  0  1    5    6 2.376126
+#> 31 15.0   8 301.0 335 3.54 3.570 14.60  0  1    5    8 4.932510
+#> 32 21.4   4 121.0 109 4.11 2.780 18.60  1  1    4    2 1.982836

+# transmute keeps only the variables you create
+mtcars %>%
+  transmute(displ_l = disp / 61.0237)
#>     displ_l
+#> 1  2.621932
+#> 2  2.621932
+#> 3  1.769804
+#> 4  4.227866
+#> 5  5.899347
+#> 6  3.687092
+#> 7  5.899347
+#> 8  2.403984
+#> 9  2.307300
+#> 10 2.746474
+#> 11 2.746474
+#> 12 4.519556
+#> 13 4.519556
+#> 14 4.519556
+#> 15 7.734700
+#> 16 7.538055
+#> 17 7.210313
+#> 18 1.289663
+#> 19 1.240502
+#> 20 1.165121
+#> 21 1.968088
+#> 22 5.211090
+#> 23 4.981671
+#> 24 5.735477
+#> 25 6.554830
+#> 26 1.294579
+#> 27 1.971365
+#> 28 1.558411
+#> 29 5.751864
+#> 30 2.376126
+#> 31 4.932510
+#> 32 1.982836

+
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/n.html b/docs/reference/n.html new file mode 100644 index 0000000000..5b8ef3e31f --- /dev/null +++ b/docs/reference/n.html @@ -0,0 +1,150 @@ + + + + + + + + +The number of observations in the current group. — n • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

The number of observations in the current group.

+
+ + +

This function is implemented specifically for each data source and can only +be used from within summarise(), mutate() and +filter().

+ + + 
n()
+ + +

Examples

+ 
if (require("nycflights13")) {
+carriers <- group_by(flights, carrier)
+summarise(carriers, n())
+mutate(carriers, n = n())
+filter(carriers, n() < 100)
+}
#> Source: local data frame [32 x 19]
+#> Groups: carrier [1]
+#> 
+#>     year month   day dep_time sched_dep_time dep_delay arr_time sched_arr_time
+#>    <int> <int> <int>    <int>          <int>     <dbl>    <int>          <int>
+#> 1   2013     1    30     1222           1115        67     1402           1215
+#> 2   2013    11     3     1424           1430        -6     1629           1634
+#> 3   2013    11    10     1443           1430        13     1701           1634
+#> 4   2013    11    17     1422           1430        -8     1610           1634
+#> 5   2013    11    25     1803           1759         4     2011           2017
+#> 6   2013    11    30     1648           1647         1     1814           1811
+#> 7   2013     6    15     1626           1635        -9     1810           1830
+#> 8   2013     6    22     1846           1635       131     2107           1830
+#> 9   2013     8    27     1755           1805       -10     1956           1953
+#> 10  2013     8    28     2039           1805       154     2213           1953
+#> # ... with 22 more rows, and 11 more variables: arr_delay <dbl>, carrier <chr>,
+#> #   flight <int>, tailnum <chr>, origin <chr>, dest <chr>, air_time <dbl>,
+#> #   distance <dbl>, hour <dbl>, minute <dbl>, time_hour <dttm>
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/n_distinct.html b/docs/reference/n_distinct.html new file mode 100644 index 0000000000..ceade25b18 --- /dev/null +++ b/docs/reference/n_distinct.html @@ -0,0 +1,141 @@ + + + + + + + + +Efficiently count the number of unique values in a set of vector — n_distinct • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Efficiently count the number of unique values in a set of vector

+
+ + +

This is a faster and more concise equivalent of length(unique(x))

+ + + 
n_distinct(..., na.rm = FALSE)
+ +

Arguments

+ + + + + + + + + + +
…

vectors of values

na.rm

id TRUE missing values don't count

+ + +

Examples

+ 
x <- sample(1:10, 1e5, rep = TRUE)
+length(unique(x))
#> [1] 10
n_distinct(x)
#> [1] 10
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/na_if.html b/docs/reference/na_if.html new file mode 100644 index 0000000000..506cf4b9e7 --- /dev/null +++ b/docs/reference/na_if.html @@ -0,0 +1,159 @@ + + + + + + + + +Convert values to NA. — na_if • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Convert values to NA.

+
+ + +

This is a translation of the SQL command NULL_IF. It is useful +if you want to convert an annoying value to NA.

+ + + 
na_if(x, y)
+ +

Arguments

+ + + + + + + + + + +
x

Vector to modify

y

Value to replace with NA

+ +

Value

+ +

A modified version of x that replaces any values that +are equal to y with NA.

+ +

See also

+ +

coalesce() to replace missing values with a specified +value.

+ + +

Examples

+ 
na_if(1:5, 5:1)
#> [1]  1  2 NA  4  5

+x <- c(1, -1, 0, 10)
+100 / x
#> [1]  100 -100  Inf   10
100 / na_if(x, 0)
#> [1]  100 -100   NA   10

+y <- c("abc", "def", "", "ghi")
+na_if(y, "")
#> [1] "abc" "def" NA    "ghi"
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/nasa.html b/docs/reference/nasa.html new file mode 100644 index 0000000000..63e9f3b597 --- /dev/null +++ b/docs/reference/nasa.html @@ -0,0 +1,173 @@ + + + + + + + + +NASA spatio-temporal data — nasa • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

NASA spatio-temporal data

+
+ + +

This data comes from the ASA 2007 data expo, +http://stat-computing.org/dataexpo/2006/. The data are geographic and +atmospheric measures on a very coarse 24 by 24 grid covering Central +America. The variables are: temperature (surface and air), ozone, +air pressure, and cloud cover (low, mid, and high). All variables are +monthly averages, with observations for Jan 1995 to Dec 2000. These data +were obtained from the NASA Langley Research Center Atmospheric Sciences +Data Center (with permission; see important copyright terms below).

+ + + 
nasa
+ +

Format

+ +

A tbl_cube with 41,472 observations.

+ +

Dimensions

+ + +
    +

  • lat, long: latitude and longitude

    • +

  • year, month: month and year

    • +
+ +

Measures

+ + +
    +

  • cloudlow, cloudmed, cloudhigh: cloud cover +at three heights

    • +

  • ozone

    • +

  • surftemp and temperature

    • +

  • pressure

    • +
+ + +

Examples

+ 
nasa
#> Source: local array [41,472 x 4]
+#> D: lat [dbl, 24]
+#> D: long [dbl, 24]
+#> D: month [int, 12]
+#> D: year [int, 6]
+#> M: cloudhigh [dbl]
+#> M: cloudlow [dbl]
+#> M: cloudmid [dbl]
+#> M: ozone [dbl]
+#> M: pressure [dbl]
+#> M: surftemp [dbl]
+#> M: temperature [dbl]
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/near.html b/docs/reference/near.html new file mode 100644 index 0000000000..d3114cfe3a --- /dev/null +++ b/docs/reference/near.html @@ -0,0 +1,142 @@ + + + + + + + + +Compare two numeric vectors. — near • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Compare two numeric vectors.

+
+ + +

This is a safe way of comparing if two vectors of floating point numbers +are (pairwise) equal. This is safer than using ==, because it has +a built in tolerance

+ + + 
near(x, y, tol = .Machine$double.eps^0.5)
+ +

Arguments

+ + + + + + + + + + +
x, y

Numeric vectors to compare

tol

Tolerance of comparison.

+ + +

Examples

+ 
sqrt(2) ^ 2 == 2
#> [1] FALSE
near(sqrt(2) ^ 2, 2)
#> [1] TRUE
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/nth.html b/docs/reference/nth.html new file mode 100644 index 0000000000..a8999a97a7 --- /dev/null +++ b/docs/reference/nth.html @@ -0,0 +1,177 @@ + + + + + + + + +Extract the first, last or nth value from a vector. — nth • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Extract the first, last or nth value from a vector.

+
+ + +

These are straightforward wrappers around [[. The main +advantage is that you can provide an optional secondary vector that defines +the ordering, and provide a default value to use when the input is shorter +than expected.

+ + + 
nth(x, n, order_by = NULL, default = default_missing(x))
+
+first(x, order_by = NULL, default = default_missing(x))
+
+last(x, order_by = NULL, default = default_missing(x))
+ +

Arguments

+ + + + + + + + + + + + + + + + + + +
x

A vector

n

For nth_value(), a single integer specifying the position. +Negative integers index from the end (i.e. -1L will return the +last value in the vector).

+

If a double is supplied, it will be silently truncated.

order_by

An optional vector used to determine the order

default

A default value to use if the position does not exist in +the input. This is guessed by default for base vectors, where a +missing value of the appropriate type is returned, and for lists, where +a NULL is return.

+

For more complicated objects, you'll need to supply this value. +Make sure it is the same type as x.

+ +

Value

+ +

A single value. [[ is used to do the subsetting.

+ + +

Examples

+ 
x <- 1:10
+y <- 10:1
+
+first(x)
#> [1] 1
last(y)
#> [1] 1

+nth(x, 1)
#> [1] 1
nth(x, 5)
#> [1] 5
nth(x, -2)
#> [1] 9
nth(x, 11)
#> [1] NA

+last(x)
#> [1] 10
# Second argument provides optional ordering
+last(x, y)
#> [1] 1

+# These functions always return a single value
+first(integer())
#> [1] NA
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/order_by.html b/docs/reference/order_by.html new file mode 100644 index 0000000000..5d6cbb9f56 --- /dev/null +++ b/docs/reference/order_by.html @@ -0,0 +1,171 @@ + + + + + + + + +A helper function for ordering window function output — order_by • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

A helper function for ordering window function output

+
+ + +

This function makes it possible to control the ordering of window functions +in R that don't have a specific ordering parameter. When translated to SQL +it will modify the order clause of the OVER function.

+ + + 
order_by(order_by, call)
+ +

Arguments

+ + + + + + + + + + +
order_by

a vector to order_by

call

a function call to a window function, where the first argument +is the vector being operated on

+ +

Details

+ +

This function works by changing the call to instead call +with_order() with the appropriate arguments.

+ + +

Examples

+ 
order_by(10:1, cumsum(1:10))
#>  [1] 55 54 52 49 45 40 34 27 19 10
x <- 10:1
+y <- 1:10
+order_by(x, cumsum(y))
#>  [1] 55 54 52 49 45 40 34 27 19 10

+df <- data.frame(year = 2000:2005, value = (0:5) ^ 2)
+scrambled <- df[sample(nrow(df)), ]
+
+wrong <- mutate(scrambled, running = cumsum(value))
+arrange(wrong, year)
#>   year value running
+#> 1 2000     0      38
+#> 2 2001     1      55
+#> 3 2002     4      29
+#> 4 2003     9      38
+#> 5 2004    16      54
+#> 6 2005    25      25

+right <- mutate(scrambled, running = order_by(year, cumsum(value)))
+arrange(right, year)
#>   year value running
+#> 1 2000     0       0
+#> 2 2001     1       1
+#> 3 2002     4       5
+#> 4 2003     9      14
+#> 5 2004    16      30
+#> 6 2005    25      55
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/progress_estimated.html b/docs/reference/progress_estimated.html new file mode 100644 index 0000000000..694697df22 --- /dev/null +++ b/docs/reference/progress_estimated.html @@ -0,0 +1,169 @@ + + + + + + + + +Progress bar with estimated time. — progress_estimated • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Progress bar with estimated time.

+
+ + +

This reference class represents a text progress bar displayed estimated +time remaining. When finished, it displays the total duration. The +automatic progress bar can be disabled by setting option +dplyr.show_progress to FALSE.

+ + + 
progress_estimated(n, min_time = 0)
+ +

Arguments

+ + + + + + + + + + +
n

Total number of items

min_time

Progress bar will wait until at least min_time +seconds have elapsed before displaying any results.

+ +

Value

+ +

A ref class with methods tick(), print(), +pause(), and stop().

+ + +

Examples

+ 
p <- progress_estimated(3)
+p$tick()
+p$tick()
+p$tick()
+
+p <- progress_estimated(3)
+for (i in 1:3) p$pause(0.1)$tick()$print()
#> 
|==================                                    | 33% ~0 s remaining     
|====================================                  | 67% ~0 s remaining     
|======================================================|100% ~0 s remaining     

+p <- progress_estimated(3)
+p$tick()$print()$
+ pause(1)$stop()
#> 
Killed after 1 s                                                                

+# If min_time is set, progress bar not shown until that many
+# seconds have elapsed
+p <- progress_estimated(3, min_time = 3)
+for (i in 1:3) p$pause(0.1)$tick()$print()
+
+## Not run: ------------------------------------
+# p <- progress_estimated(10, min_time = 3)
+# for (i in 1:10) p$pause(0.5)$tick()$print()
+## ---------------------------------------------
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/pull.html b/docs/reference/pull.html new file mode 100644 index 0000000000..efb0736959 --- /dev/null +++ b/docs/reference/pull.html @@ -0,0 +1,158 @@ + + + + + + + + +Pull out a single variable — pull • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Pull out a single variable

+
+ + +

This works like [[ for local data frames, and automatically collects +before indexing for remote data tables.

+ + + 
pull(.data, var = -1)
+ +

Arguments

+ + + + + + + + + + +
.data

A table of data

var

A variable specified as:

    +

  • a single string, the variable name

    • +

  • a positive integer, giving the position counting from the left

    • +

  • a negative integer, giving the position counting from the right.

    • +
+ +

The default returns the last column (on the assumption that's the +column you've created most recently).

+ + +

Examples

+ 
mtcars %>% pull(-1)
#>  [1] 4 4 1 1 2 1 4 2 2 4 4 3 3 3 4 4 4 1 2 1 1 2 2 4 2 1 2 2 4 6 8 2
mtcars %>% pull(1)
#>  [1] 21.0 21.0 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 17.8 16.4 17.3 15.2 10.4
+#> [16] 10.4 14.7 32.4 30.4 33.9 21.5 15.5 15.2 13.3 19.2 27.3 26.0 30.4 15.8 19.7
+#> [31] 15.0 21.4
mtcars %>% pull("cyl")
#>  [1] 6 6 4 6 8 6 8 4 4 6 6 8 8 8 8 8 8 4 4 4 4 8 8 8 8 4 4 4 8 6 8 4

+# Also works for remote sources
+if (requireNamespace("dbplyr", quietly = TRUE)) {
+df <- dbplyr::memdb_frame(x = 1:10, y = 10:1, .name = "pull-ex")
+df %>%
+  mutate(z = x * y) %>%
+  pull()
+}
#>  [1] 10 18 24 28 30 30 28 24 18 10

+
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/ranking.html b/docs/reference/ranking.html new file mode 100644 index 0000000000..be977d0073 --- /dev/null +++ b/docs/reference/ranking.html @@ -0,0 +1,223 @@ + + + + + + + + +Windowed rank functions. — ranking • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Windowed rank functions.

+
+ + +

Six variations on ranking functions, mimicing the ranking functions +described in SQL2003. They are currently implemented using the built in +rank function, and are provided mainly as a convenience when +converting between R and SQL. All ranking functions map smallest inputs +to smallest outputs. Use desc() to reverse the direction.

+ + + 
row_number(x)
+
+ntile(x, n)
+
+min_rank(x)
+
+dense_rank(x)
+
+percent_rank(x)
+
+cume_dist(x)
+ +

Arguments

+ + + + + + + + + + +
x

a vector of values to rank. Missing values are left as is. +If you want to treat them as the smallest or largest values, replace +with Inf or -Inf before ranking.

n

number of groups to split up into.

+ +

Details

+ +
    +

  • row_number(): equivalent to rank(ties.method = "first")

    • +

  • min_rank(): equivalent to rank(ties.method = "min")

    • +

  • dense_rank(): like min_rank(), but with no gaps between +ranks

    • +

  • percent_rank(): a number between 0 and 1 computed by +rescaling min_rank to [0, 1]

    • +

  • cume_dist(): a cumulative distribution function. Proportion +of all values less than or equal to the current rank.

    • +

  • ntile(): a rough rank, which breaks the input vector into +n buckets.

    • +
+ + +

Examples

+ 
x <- c(5, 1, 3, 2, 2, NA)
+row_number(x)
#> [1]  5  1  4  2  3 NA
min_rank(x)
#> [1]  5  1  4  2  2 NA
dense_rank(x)
#> [1]  4  1  3  2  2 NA
percent_rank(x)
#> [1] 1.00 0.00 0.75 0.25 0.25   NA
cume_dist(x)
#> [1] 1.0 0.2 0.8 0.6 0.6  NA

+ntile(x, 2)
#> [1]  2  1  2  1  1 NA
ntile(runif(100), 10)
#>   [1]  9  1  4  8  8  9  5  8 10  9  9  3  2  4  7  9 10  5  4  5  4  1  2  8  9
+#>  [26]  4  3  6  7  6 10  9  8  4 10  7 10  4  6  7  1  4  6  8 10  8  6  5  1  5
+#>  [51]  2  2 10  1  5 10  9  7  8  7  6  2 10  9  9  6  2  1  3  1 10  3  2  3  7
+#>  [76]  3  5  7  6  1  1  8  3  5  1  4  7  3  3  3  5  6  8  2  5  2  6  4  2  7

+# row_number can be used with single table verbs without specifying x
+# (for data frames and databases that support windowing)
+mutate(mtcars, row_number() == 1L)
#>     mpg cyl  disp  hp drat    wt  qsec vs am gear carb row_number() == 1L
+#> 1  21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4               TRUE
+#> 2  21.0   6 160.0 110 3.90 2.875 17.02  0  1    4    4              FALSE
+#> 3  22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1              FALSE
+#> 4  21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1              FALSE
+#> 5  18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2              FALSE
+#> 6  18.1   6 225.0 105 2.76 3.460 20.22  1  0    3    1              FALSE
+#> 7  14.3   8 360.0 245 3.21 3.570 15.84  0  0    3    4              FALSE
+#> 8  24.4   4 146.7  62 3.69 3.190 20.00  1  0    4    2              FALSE
+#> 9  22.8   4 140.8  95 3.92 3.150 22.90  1  0    4    2              FALSE
+#> 10 19.2   6 167.6 123 3.92 3.440 18.30  1  0    4    4              FALSE
+#> 11 17.8   6 167.6 123 3.92 3.440 18.90  1  0    4    4              FALSE
+#> 12 16.4   8 275.8 180 3.07 4.070 17.40  0  0    3    3              FALSE
+#> 13 17.3   8 275.8 180 3.07 3.730 17.60  0  0    3    3              FALSE
+#> 14 15.2   8 275.8 180 3.07 3.780 18.00  0  0    3    3              FALSE
+#> 15 10.4   8 472.0 205 2.93 5.250 17.98  0  0    3    4              FALSE
+#> 16 10.4   8 460.0 215 3.00 5.424 17.82  0  0    3    4              FALSE
+#> 17 14.7   8 440.0 230 3.23 5.345 17.42  0  0    3    4              FALSE
+#> 18 32.4   4  78.7  66 4.08 2.200 19.47  1  1    4    1              FALSE
+#> 19 30.4   4  75.7  52 4.93 1.615 18.52  1  1    4    2              FALSE
+#> 20 33.9   4  71.1  65 4.22 1.835 19.90  1  1    4    1              FALSE
+#> 21 21.5   4 120.1  97 3.70 2.465 20.01  1  0    3    1              FALSE
+#> 22 15.5   8 318.0 150 2.76 3.520 16.87  0  0    3    2              FALSE
+#> 23 15.2   8 304.0 150 3.15 3.435 17.30  0  0    3    2              FALSE
+#> 24 13.3   8 350.0 245 3.73 3.840 15.41  0  0    3    4              FALSE
+#> 25 19.2   8 400.0 175 3.08 3.845 17.05  0  0    3    2              FALSE
+#> 26 27.3   4  79.0  66 4.08 1.935 18.90  1  1    4    1              FALSE
+#> 27 26.0   4 120.3  91 4.43 2.140 16.70  0  1    5    2              FALSE
+#> 28 30.4   4  95.1 113 3.77 1.513 16.90  1  1    5    2              FALSE
+#> 29 15.8   8 351.0 264 4.22 3.170 14.50  0  1    5    4              FALSE
+#> 30 19.7   6 145.0 175 3.62 2.770 15.50  0  1    5    6              FALSE
+#> 31 15.0   8 301.0 335 3.54 3.570 14.60  0  1    5    8              FALSE
+#> 32 21.4   4 121.0 109 4.11 2.780 18.60  1  1    4    2              FALSE
mtcars %>% filter(between(row_number(), 1, 10))
#>     mpg cyl  disp  hp drat    wt  qsec vs am gear carb
+#> 1  21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4
+#> 2  21.0   6 160.0 110 3.90 2.875 17.02  0  1    4    4
+#> 3  22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1
+#> 4  21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1
+#> 5  18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2
+#> 6  18.1   6 225.0 105 2.76 3.460 20.22  1  0    3    1
+#> 7  14.3   8 360.0 245 3.21 3.570 15.84  0  0    3    4
+#> 8  24.4   4 146.7  62 3.69 3.190 20.00  1  0    4    2
+#> 9  22.8   4 140.8  95 3.92 3.150 22.90  1  0    4    2
+#> 10 19.2   6 167.6 123 3.92 3.440 18.30  1  0    4    4
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/recode.html b/docs/reference/recode.html new file mode 100644 index 0000000000..ab9eb408ef --- /dev/null +++ b/docs/reference/recode.html @@ -0,0 +1,222 @@ + + + + + + + + +Recode values — recode • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Recode values

+
+ + +

This is a vectorised version of switch(): you can replace +numeric values based on their position, and character values by their +name. This is an S3 generic: dplyr provides methods for numeric, character, +and factors. For logical vectors, use if_else(). For more complicated +criteria, use case_when().

+ + + 
recode(.x, ..., .default = NULL, .missing = NULL)
+
+recode_factor(.x, ..., .default = NULL, .missing = NULL, .ordered = FALSE)
+ +

Arguments

+ + + + + + + + + + + + + + + + + + + + + + +
.x

A vector to modify

...

Replacements. These should be named for character and factor +.x, and can be named for numeric .x. The argument names should be the +current values to be replaced, and the argument values should be the new +(replacement) values.

+

All replacements must be the same type, and must have either +length one or the same length as x.

+

These dots are evaluated with explicit splicing.

.default

If supplied, all values not otherwise matched will +be given this value. If not supplied and if the replacements are +the same type as the original values in .x, unmatched +values are not changed. If not supplied and if the replacements +are not compatible, unmatched values are replaced with NA. + +.default must be either length 1 or the same length as +.x.

.missing

If supplied, any missing values in .x will be +replaced by this value. Must be either length 1 or the same length as +.x.

.ordered

If TRUE, recode_factor() creates an +ordered factor.

+ +

Value

+ +

A vector the same length as .x, and the same type as +the first of ..., .default, or .missing. +recode_factor() returns a factor whose levels are in the +same order as in ....

+ +

Details

+ +

You can use recode() directly with factors; it will preserve the existing +order of levels while changing the values. Alternatively, you can +use recode_factor(), which will change the order of levels to match +the order of replacements. See the forcats +package for more tools for working with factors and their levels.

+ + +

Examples

+ 
# Recode values with named arguments
+x <- sample(c("a", "b", "c"), 10, replace = TRUE)
+recode(x, a = "Apple")
#>  [1] "b"     "b"     "Apple" "c"     "c"     "Apple" "c"     "c"     "Apple"
+#> [10] "c"    
recode(x, a = "Apple", .default = NA_character_)
#>  [1] NA      NA      "Apple" NA      NA      "Apple" NA      NA      "Apple"
+#> [10] NA     

+# Named arguments also work with numeric values
+x <- c(1:5, NA)
+recode(x, `2` = 20L, `4` = 40L)
#> [1]  1 20  3 40  5 NA

+# Note that if the replacements are not compatible with .x,
+# unmatched values are replaced by NA and a warning is issued.
+recode(x, `2` = "b", `4` = "d")
#> Warning: Unreplaced values treated as NA as .x is not compatible. Please specify replacements exhaustively or supply .default
#> [1] NA  "b" NA  "d" NA  NA 

+# If you don't name the arguments, recode() matches by position
+recode(x, "a", "b", "c")
#> Warning: Unreplaced values treated as NA as .x is not compatible. Please specify replacements exhaustively or supply .default
#> [1] "a" "b" "c" NA  NA  NA 
recode(x, "a", "b", "c", .default = "other")
#> [1] "a"     "b"     "c"     "other" "other" NA     
recode(x, "a", "b", "c", .default = "other", .missing = "missing")
#> [1] "a"       "b"       "c"       "other"   "other"   "missing"

+# Supply default with levels() for factors
+x <- factor(c("a", "b", "c"))
+recode(x, a = "Apple", .default = levels(x))
#> [1] Apple b     c    
+#> Levels: Apple b c

+# Use recode_factor() to create factors with levels ordered as they
+# appear in the recode call. The levels in .default and .missing
+# come last.
+x <- c(1:4, NA)
+recode_factor(x, `1` = "z", `2` = "y", `3` = "x")
#> Warning: Unreplaced values treated as NA as .x is not compatible. Please specify replacements exhaustively or supply .default
#> [1] z    y    x    <NA> <NA>
+#> Levels: z y x
recode_factor(x, `1` = "z", `2` = "y", .default = "D")
#> [1] z    y    D    D    <NA>
+#> Levels: z y D
recode_factor(x, `1` = "z", `2` = "y", .default = "D", .missing = "M")
#> [1] z y D D M
+#> Levels: z y D M

+# When the input vector is a compatible vector (character vector or
+# factor), it is reused as default.
+recode_factor(letters[1:3], b = "z", c = "y")
#> [1] a z y
+#> Levels: z y a
recode_factor(factor(letters[1:3]), b = "z", c = "y")
#> [1] a z y
+#> Levels: z y a
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/reexports.html b/docs/reference/reexports.html new file mode 100644 index 0000000000..f5dbab4fd1 --- /dev/null +++ b/docs/reference/reexports.html @@ -0,0 +1,128 @@ + + + + + + + + +Objects exported from other packages — reexports • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Objects exported from other packages

+
+ + +

These objects are imported from other packages. Follow the links +below to see their documentation.

+
magrittr

%>%

+ +
rlang

quo, quos, enquo, quo_name, splice

+ +
tibble

data_frame, data_frame_, as_data_frame, lst, lst_, add_row, type_sum, glimpse, frame_data, tribble, tibble, as_tibble, trunc_mat

+
+ + + + +
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/rowwise.html b/docs/reference/rowwise.html new file mode 100644 index 0000000000..35534854bf --- /dev/null +++ b/docs/reference/rowwise.html @@ -0,0 +1,165 @@ + + + + + + + + +Group input by rows — rowwise • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Group input by rows

+
+ + +

rowwise() is used for the results of do() when you +create list-variables. It is also useful to support arbitrary +complex operations that need to be applied to each row.

+ + + 
rowwise(data)
+ +

Arguments

+ + + + + + +
data

Input data frame.

+ +

Details

+ +

Currently, rowwise grouping only works with data frames. Its +main impact is to allow you to work with list-variables in +summarise() and mutate() without having to +use [[1]]. This makes summarise() on a rowwise tbl +effectively equivalent to [plyr::ldply()].

+

[[1]: R:[1 +[plyr::ldply()]: R:plyr::ldply()

+ + +

Examples

+ 
df <- expand.grid(x = 1:3, y = 3:1)
+df %>% rowwise() %>% do(i = seq(.$x, .$y))
#> Source: local data frame [9 x 1]
+#> Groups: <by row>
+#> 
+#> # A tibble: 9 × 1
+#>           i
+#> *    <list>
+#> 1 <int [3]>
+#> 2 <int [2]>
+#> 3 <int [1]>
+#> 4 <int [2]>
+#> 5 <int [1]>
+#> 6 <int [2]>
+#> 7 <int [1]>
+#> 8 <int [2]>
+#> 9 <int [3]>
.Last.value %>% summarise(n = length(i))
#> Error in UseMethod("summarise_"): no applicable method for 'summarise_' applied to an object of class "function"
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/same_src.html b/docs/reference/same_src.html new file mode 100644 index 0000000000..3576ca0d2f --- /dev/null +++ b/docs/reference/same_src.html @@ -0,0 +1,138 @@ + + + + + + + + +Figure out if two sources are the same (or two tbl have the same source) — same_src • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Figure out if two sources are the same (or two tbl have the same source)

+
+ + +

Figure out if two sources are the same (or two tbl have the same source)

+ + + 
same_src(x, y)
+ +

Arguments

+ + + + + + +
x, y

src or tbls to test

+ +

Value

+ +

a logical flag

+ + +
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/sample.html b/docs/reference/sample.html new file mode 100644 index 0000000000..ca076fd80c --- /dev/null +++ b/docs/reference/sample.html @@ -0,0 +1,397 @@ + + + + + + + + +Sample n rows from a table. — sample • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Sample n rows from a table.

+
+ + +

This is a wrapper around sample.int() to make it easy to +select random rows from a table. It currently only works for local +tbls.

+ + + 
sample_n(tbl, size, replace = FALSE, weight = NULL, .env = NULL)
+
+sample_frac(tbl, size = 1, replace = FALSE, weight = NULL, .env = NULL)
+ +

Arguments

+ + + + + + + + + + + + + + + + + + + + + + +
tbl

tbl of data.

size

For sample_n(), the number of rows to select. +For sample_frac(), the fraction of rows to select. +If tbl is grouped, size applies to each group.

replace

Sample with or without replacement?

weight

Sampling weights. This must evaluate to a vector of +non-negative numbers the same length as the input. Weights are +automatically standardised to sum to 1.

+

This argument is automatically quoted and later +evaluated in the context of the data +frame. It supports unquoting. See +vignette("programming") for an introduction to these concepts.

.env

This variable is deprecated and no longer has any +effect. To evaluate weight in a particular context, you can +now unquote a quosure.

+ + +

Examples

+ 
by_cyl <- mtcars %>% group_by(cyl)
+
+# Sample fixed number per group
+sample_n(mtcars, 10)
#>                     mpg cyl  disp  hp drat    wt  qsec vs am gear carb
+#> Cadillac Fleetwood 10.4   8 472.0 205 2.93 5.250 17.98  0  0    3    4
+#> Mazda RX4          21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4
+#> Porsche 914-2      26.0   4 120.3  91 4.43 2.140 16.70  0  1    5    2
+#> Camaro Z28         13.3   8 350.0 245 3.73 3.840 15.41  0  0    3    4
+#> Merc 280C          17.8   6 167.6 123 3.92 3.440 18.90  1  0    4    4
+#> Maserati Bora      15.0   8 301.0 335 3.54 3.570 14.60  0  1    5    8
+#> Dodge Challenger   15.5   8 318.0 150 2.76 3.520 16.87  0  0    3    2
+#> Chrysler Imperial  14.7   8 440.0 230 3.23 5.345 17.42  0  0    3    4
+#> Pontiac Firebird   19.2   8 400.0 175 3.08 3.845 17.05  0  0    3    2
+#> Merc 230           22.8   4 140.8  95 3.92 3.150 22.90  1  0    4    2
sample_n(mtcars, 50, replace = TRUE)
#>                        mpg cyl  disp  hp drat    wt  qsec vs am gear carb
+#> Valiant               18.1   6 225.0 105 2.76 3.460 20.22  1  0    3    1
+#> Lotus Europa          30.4   4  95.1 113 3.77 1.513 16.90  1  1    5    2
+#> Chrysler Imperial     14.7   8 440.0 230 3.23 5.345 17.42  0  0    3    4
+#> Merc 450SL            17.3   8 275.8 180 3.07 3.730 17.60  0  0    3    3
+#> Merc 280C             17.8   6 167.6 123 3.92 3.440 18.90  1  0    4    4
+#> Toyota Corona         21.5   4 120.1  97 3.70 2.465 20.01  1  0    3    1
+#> Hornet Sportabout     18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2
+#> Merc 450SLC           15.2   8 275.8 180 3.07 3.780 18.00  0  0    3    3
+#> Merc 230              22.8   4 140.8  95 3.92 3.150 22.90  1  0    4    2
+#> Honda Civic           30.4   4  75.7  52 4.93 1.615 18.52  1  1    4    2
+#> Hornet 4 Drive        21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1
+#> Merc 280C.1           17.8   6 167.6 123 3.92 3.440 18.90  1  0    4    4
+#> AMC Javelin           15.2   8 304.0 150 3.15 3.435 17.30  0  0    3    2
+#> Merc 280C.2           17.8   6 167.6 123 3.92 3.440 18.90  1  0    4    4
+#> Chrysler Imperial.1   14.7   8 440.0 230 3.23 5.345 17.42  0  0    3    4
+#> Porsche 914-2         26.0   4 120.3  91 4.43 2.140 16.70  0  1    5    2
+#> Lincoln Continental   10.4   8 460.0 215 3.00 5.424 17.82  0  0    3    4
+#> Merc 450SE            16.4   8 275.8 180 3.07 4.070 17.40  0  0    3    3
+#> Merc 230.1            22.8   4 140.8  95 3.92 3.150 22.90  1  0    4    2
+#> Cadillac Fleetwood    10.4   8 472.0 205 2.93 5.250 17.98  0  0    3    4
+#> Lincoln Continental.1 10.4   8 460.0 215 3.00 5.424 17.82  0  0    3    4
+#> Ford Pantera L        15.8   8 351.0 264 4.22 3.170 14.50  0  1    5    4
+#> Lotus Europa.1        30.4   4  95.1 113 3.77 1.513 16.90  1  1    5    2
+#> Merc 240D             24.4   4 146.7  62 3.69 3.190 20.00  1  0    4    2
+#> Lotus Europa.2        30.4   4  95.1 113 3.77 1.513 16.90  1  1    5    2
+#> Toyota Corona.1       21.5   4 120.1  97 3.70 2.465 20.01  1  0    3    1
+#> Merc 280C.3           17.8   6 167.6 123 3.92 3.440 18.90  1  0    4    4
+#> Toyota Corona.2       21.5   4 120.1  97 3.70 2.465 20.01  1  0    3    1
+#> Dodge Challenger      15.5   8 318.0 150 2.76 3.520 16.87  0  0    3    2
+#> Merc 450SL.1          17.3   8 275.8 180 3.07 3.730 17.60  0  0    3    3
+#> Lotus Europa.3        30.4   4  95.1 113 3.77 1.513 16.90  1  1    5    2
+#> Fiat 128              32.4   4  78.7  66 4.08 2.200 19.47  1  1    4    1
+#> Camaro Z28            13.3   8 350.0 245 3.73 3.840 15.41  0  0    3    4
+#> Volvo 142E            21.4   4 121.0 109 4.11 2.780 18.60  1  1    4    2
+#> Merc 450SLC.1         15.2   8 275.8 180 3.07 3.780 18.00  0  0    3    3
+#> Volvo 142E.1          21.4   4 121.0 109 4.11 2.780 18.60  1  1    4    2
+#> Merc 280C.4           17.8   6 167.6 123 3.92 3.440 18.90  1  0    4    4
+#> Ford Pantera L.1      15.8   8 351.0 264 4.22 3.170 14.50  0  1    5    4
+#> Duster 360            14.3   8 360.0 245 3.21 3.570 15.84  0  0    3    4
+#> Datsun 710            22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1
+#> Toyota Corona.3       21.5   4 120.1  97 3.70 2.465 20.01  1  0    3    1
+#> Merc 450SLC.2         15.2   8 275.8 180 3.07 3.780 18.00  0  0    3    3
+#> Cadillac Fleetwood.1  10.4   8 472.0 205 2.93 5.250 17.98  0  0    3    4
+#> Valiant.1             18.1   6 225.0 105 2.76 3.460 20.22  1  0    3    1
+#> Fiat X1-9             27.3   4  79.0  66 4.08 1.935 18.90  1  1    4    1
+#> Fiat X1-9.1           27.3   4  79.0  66 4.08 1.935 18.90  1  1    4    1
+#> Duster 360.1          14.3   8 360.0 245 3.21 3.570 15.84  0  0    3    4
+#> Hornet 4 Drive.1      21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1
+#> Lincoln Continental.2 10.4   8 460.0 215 3.00 5.424 17.82  0  0    3    4
+#> Merc 240D.1           24.4   4 146.7  62 3.69 3.190 20.00  1  0    4    2
sample_n(mtcars, 10, weight = mpg)
#>                   mpg cyl  disp  hp drat    wt  qsec vs am gear carb
+#> Lotus Europa     30.4   4  95.1 113 3.77 1.513 16.90  1  1    5    2
+#> Pontiac Firebird 19.2   8 400.0 175 3.08 3.845 17.05  0  0    3    2
+#> Mazda RX4 Wag    21.0   6 160.0 110 3.90 2.875 17.02  0  1    4    4
+#> Honda Civic      30.4   4  75.7  52 4.93 1.615 18.52  1  1    4    2
+#> Fiat 128         32.4   4  78.7  66 4.08 2.200 19.47  1  1    4    1
+#> Merc 450SL       17.3   8 275.8 180 3.07 3.730 17.60  0  0    3    3
+#> Maserati Bora    15.0   8 301.0 335 3.54 3.570 14.60  0  1    5    8
+#> Porsche 914-2    26.0   4 120.3  91 4.43 2.140 16.70  0  1    5    2
+#> Merc 280         19.2   6 167.6 123 3.92 3.440 18.30  1  0    4    4
+#> Ferrari Dino     19.7   6 145.0 175 3.62 2.770 15.50  0  1    5    6

+sample_n(by_cyl, 3)
#> Source: local data frame [9 x 11]
+#> Groups: cyl [3]
+#> 
+#>     mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
+#>   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
+#> 1  22.8     4 140.8    95  3.92 3.150 22.90     1     0     4     2
+#> 2  22.8     4 108.0    93  3.85 2.320 18.61     1     1     4     1
+#> 3  30.4     4  95.1   113  3.77 1.513 16.90     1     1     5     2
+#> 4  17.8     6 167.6   123  3.92 3.440 18.90     1     0     4     4
+#> 5  19.2     6 167.6   123  3.92 3.440 18.30     1     0     4     4
+#> 6  21.0     6 160.0   110  3.90 2.620 16.46     0     1     4     4
+#> 7  10.4     8 472.0   205  2.93 5.250 17.98     0     0     3     4
+#> 8  18.7     8 360.0   175  3.15 3.440 17.02     0     0     3     2
+#> 9  13.3     8 350.0   245  3.73 3.840 15.41     0     0     3     4
sample_n(by_cyl, 10, replace = TRUE)
#> Source: local data frame [30 x 11]
+#> Groups: cyl [3]
+#> 
+#>      mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
+#>    <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
+#> 1   22.8     4 140.8    95  3.92 3.150 22.90     1     0     4     2
+#> 2   27.3     4  79.0    66  4.08 1.935 18.90     1     1     4     1
+#> 3   30.4     4  75.7    52  4.93 1.615 18.52     1     1     4     2
+#> 4   27.3     4  79.0    66  4.08 1.935 18.90     1     1     4     1
+#> 5   32.4     4  78.7    66  4.08 2.200 19.47     1     1     4     1
+#> 6   30.4     4  95.1   113  3.77 1.513 16.90     1     1     5     2
+#> 7   22.8     4 140.8    95  3.92 3.150 22.90     1     0     4     2
+#> 8   22.8     4 140.8    95  3.92 3.150 22.90     1     0     4     2
+#> 9   32.4     4  78.7    66  4.08 2.200 19.47     1     1     4     1
+#> 10  32.4     4  78.7    66  4.08 2.200 19.47     1     1     4     1
+#> # ... with 20 more rows
sample_n(by_cyl, 3, weight = mpg / mean(mpg))
#> Source: local data frame [9 x 11]
+#> Groups: cyl [3]
+#> 
+#>     mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
+#>   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
+#> 1  22.8     4 140.8    95  3.92 3.150 22.90     1     0     4     2
+#> 2  27.3     4  79.0    66  4.08 1.935 18.90     1     1     4     1
+#> 3  21.5     4 120.1    97  3.70 2.465 20.01     1     0     3     1
+#> 4  21.0     6 160.0   110  3.90 2.620 16.46     0     1     4     4
+#> 5  17.8     6 167.6   123  3.92 3.440 18.90     1     0     4     4
+#> 6  21.4     6 258.0   110  3.08 3.215 19.44     1     0     3     1
+#> 7  15.8     8 351.0   264  4.22 3.170 14.50     0     1     5     4
+#> 8  14.7     8 440.0   230  3.23 5.345 17.42     0     0     3     4
+#> 9  16.4     8 275.8   180  3.07 4.070 17.40     0     0     3     3

+# Sample fixed fraction per group
+# Default is to sample all data = randomly resample rows
+sample_frac(mtcars)
#>                      mpg cyl  disp  hp drat    wt  qsec vs am gear carb
+#> Merc 280            19.2   6 167.6 123 3.92 3.440 18.30  1  0    4    4
+#> Fiat 128            32.4   4  78.7  66 4.08 2.200 19.47  1  1    4    1
+#> Merc 230            22.8   4 140.8  95 3.92 3.150 22.90  1  0    4    2
+#> Dodge Challenger    15.5   8 318.0 150 2.76 3.520 16.87  0  0    3    2
+#> Porsche 914-2       26.0   4 120.3  91 4.43 2.140 16.70  0  1    5    2
+#> Fiat X1-9           27.3   4  79.0  66 4.08 1.935 18.90  1  1    4    1
+#> Camaro Z28          13.3   8 350.0 245 3.73 3.840 15.41  0  0    3    4
+#> Chrysler Imperial   14.7   8 440.0 230 3.23 5.345 17.42  0  0    3    4
+#> Volvo 142E          21.4   4 121.0 109 4.11 2.780 18.60  1  1    4    2
+#> Duster 360          14.3   8 360.0 245 3.21 3.570 15.84  0  0    3    4
+#> Toyota Corona       21.5   4 120.1  97 3.70 2.465 20.01  1  0    3    1
+#> Toyota Corolla      33.9   4  71.1  65 4.22 1.835 19.90  1  1    4    1
+#> Mazda RX4           21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4
+#> Merc 450SLC         15.2   8 275.8 180 3.07 3.780 18.00  0  0    3    3
+#> Merc 450SL          17.3   8 275.8 180 3.07 3.730 17.60  0  0    3    3
+#> Merc 240D           24.4   4 146.7  62 3.69 3.190 20.00  1  0    4    2
+#> Lotus Europa        30.4   4  95.1 113 3.77 1.513 16.90  1  1    5    2
+#> Hornet 4 Drive      21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1
+#> Ford Pantera L      15.8   8 351.0 264 4.22 3.170 14.50  0  1    5    4
+#> Honda Civic         30.4   4  75.7  52 4.93 1.615 18.52  1  1    4    2
+#> Hornet Sportabout   18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2
+#> AMC Javelin         15.2   8 304.0 150 3.15 3.435 17.30  0  0    3    2
+#> Mazda RX4 Wag       21.0   6 160.0 110 3.90 2.875 17.02  0  1    4    4
+#> Maserati Bora       15.0   8 301.0 335 3.54 3.570 14.60  0  1    5    8
+#> Valiant             18.1   6 225.0 105 2.76 3.460 20.22  1  0    3    1
+#> Ferrari Dino        19.7   6 145.0 175 3.62 2.770 15.50  0  1    5    6
+#> Datsun 710          22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1
+#> Merc 450SE          16.4   8 275.8 180 3.07 4.070 17.40  0  0    3    3
+#> Merc 280C           17.8   6 167.6 123 3.92 3.440 18.90  1  0    4    4
+#> Pontiac Firebird    19.2   8 400.0 175 3.08 3.845 17.05  0  0    3    2
+#> Cadillac Fleetwood  10.4   8 472.0 205 2.93 5.250 17.98  0  0    3    4
+#> Lincoln Continental 10.4   8 460.0 215 3.00 5.424 17.82  0  0    3    4

+sample_frac(mtcars, 0.1)
#>                   mpg cyl  disp  hp drat    wt  qsec vs am gear carb
+#> Ford Pantera L   15.8   8 351.0 264 4.22 3.170 14.50  0  1    5    4
+#> Honda Civic      30.4   4  75.7  52 4.93 1.615 18.52  1  1    4    2
+#> Pontiac Firebird 19.2   8 400.0 175 3.08 3.845 17.05  0  0    3    2
sample_frac(mtcars, 1.5, replace = TRUE)
#>                      mpg cyl  disp  hp drat    wt  qsec vs am gear carb
+#> Pontiac Firebird    19.2   8 400.0 175 3.08 3.845 17.05  0  0    3    2
+#> AMC Javelin         15.2   8 304.0 150 3.15 3.435 17.30  0  0    3    2
+#> Ford Pantera L      15.8   8 351.0 264 4.22 3.170 14.50  0  1    5    4
+#> Merc 280C           17.8   6 167.6 123 3.92 3.440 18.90  1  0    4    4
+#> Porsche 914-2       26.0   4 120.3  91 4.43 2.140 16.70  0  1    5    2
+#> Ferrari Dino        19.7   6 145.0 175 3.62 2.770 15.50  0  1    5    6
+#> Fiat 128            32.4   4  78.7  66 4.08 2.200 19.47  1  1    4    1
+#> Merc 450SL          17.3   8 275.8 180 3.07 3.730 17.60  0  0    3    3
+#> Hornet Sportabout   18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2
+#> Mazda RX4           21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4
+#> Toyota Corona       21.5   4 120.1  97 3.70 2.465 20.01  1  0    3    1
+#> Ford Pantera L.1    15.8   8 351.0 264 4.22 3.170 14.50  0  1    5    4
+#> Merc 240D           24.4   4 146.7  62 3.69 3.190 20.00  1  0    4    2
+#> Duster 360          14.3   8 360.0 245 3.21 3.570 15.84  0  0    3    4
+#> Toyota Corona.1     21.5   4 120.1  97 3.70 2.465 20.01  1  0    3    1
+#> Merc 450SL.1        17.3   8 275.8 180 3.07 3.730 17.60  0  0    3    3
+#> Honda Civic         30.4   4  75.7  52 4.93 1.615 18.52  1  1    4    2
+#> Hornet Sportabout.1 18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2
+#> Merc 450SLC         15.2   8 275.8 180 3.07 3.780 18.00  0  0    3    3
+#> Fiat 128.1          32.4   4  78.7  66 4.08 2.200 19.47  1  1    4    1
+#> Merc 240D.1         24.4   4 146.7  62 3.69 3.190 20.00  1  0    4    2
+#> Lincoln Continental 10.4   8 460.0 215 3.00 5.424 17.82  0  0    3    4
+#> Datsun 710          22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1
+#> Merc 280            19.2   6 167.6 123 3.92 3.440 18.30  1  0    4    4
+#> Chrysler Imperial   14.7   8 440.0 230 3.23 5.345 17.42  0  0    3    4
+#> Datsun 710.1        22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1
+#> Mazda RX4 Wag       21.0   6 160.0 110 3.90 2.875 17.02  0  1    4    4
+#> Merc 450SL.2        17.3   8 275.8 180 3.07 3.730 17.60  0  0    3    3
+#> Hornet Sportabout.2 18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2
+#> Hornet Sportabout.3 18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2
+#> Merc 450SL.3        17.3   8 275.8 180 3.07 3.730 17.60  0  0    3    3
+#> Lotus Europa        30.4   4  95.1 113 3.77 1.513 16.90  1  1    5    2
+#> Hornet 4 Drive      21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1
+#> Hornet 4 Drive.1    21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1
+#> Hornet Sportabout.4 18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2
+#> Porsche 914-2.1     26.0   4 120.3  91 4.43 2.140 16.70  0  1    5    2
+#> Hornet Sportabout.5 18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2
+#> Merc 230            22.8   4 140.8  95 3.92 3.150 22.90  1  0    4    2
+#> AMC Javelin.1       15.2   8 304.0 150 3.15 3.435 17.30  0  0    3    2
+#> Ferrari Dino.1      19.7   6 145.0 175 3.62 2.770 15.50  0  1    5    6
+#> Cadillac Fleetwood  10.4   8 472.0 205 2.93 5.250 17.98  0  0    3    4
+#> Lotus Europa.1      30.4   4  95.1 113 3.77 1.513 16.90  1  1    5    2
+#> Merc 450SLC.1       15.2   8 275.8 180 3.07 3.780 18.00  0  0    3    3
+#> Fiat 128.2          32.4   4  78.7  66 4.08 2.200 19.47  1  1    4    1
+#> Maserati Bora       15.0   8 301.0 335 3.54 3.570 14.60  0  1    5    8
+#> Dodge Challenger    15.5   8 318.0 150 2.76 3.520 16.87  0  0    3    2
+#> Mazda RX4 Wag.1     21.0   6 160.0 110 3.90 2.875 17.02  0  1    4    4
+#> Merc 240D.2         24.4   4 146.7  62 3.69 3.190 20.00  1  0    4    2
sample_frac(mtcars, 0.1, weight = 1 / mpg)
#>             mpg cyl  disp  hp drat   wt qsec vs am gear carb
+#> Volvo 142E 21.4   4 121.0 109 4.11 2.78 18.6  1  1    4    2
+#> Merc 240D  24.4   4 146.7  62 3.69 3.19 20.0  1  0    4    2
+#> Merc 450SE 16.4   8 275.8 180 3.07 4.07 17.4  0  0    3    3

+sample_frac(by_cyl, 0.2)
#> Source: local data frame [6 x 11]
+#> Groups: cyl [3]
+#> 
+#>     mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
+#>   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
+#> 1  21.5     4 120.1    97  3.70 2.465 20.01     1     0     3     1
+#> 2  26.0     4 120.3    91  4.43 2.140 16.70     0     1     5     2
+#> 3  21.4     6 258.0   110  3.08 3.215 19.44     1     0     3     1
+#> 4  10.4     8 460.0   215  3.00 5.424 17.82     0     0     3     4
+#> 5  10.4     8 472.0   205  2.93 5.250 17.98     0     0     3     4
+#> 6  16.4     8 275.8   180  3.07 4.070 17.40     0     0     3     3
sample_frac(by_cyl, 1, replace = TRUE)
#> Source: local data frame [32 x 11]
+#> Groups: cyl [3]
+#> 
+#>      mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
+#>    <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
+#> 1   26.0     4 120.3    91  4.43 2.140 16.70     0     1     5     2
+#> 2   27.3     4  79.0    66  4.08 1.935 18.90     1     1     4     1
+#> 3   30.4     4  95.1   113  3.77 1.513 16.90     1     1     5     2
+#> 4   33.9     4  71.1    65  4.22 1.835 19.90     1     1     4     1
+#> 5   30.4     4  75.7    52  4.93 1.615 18.52     1     1     4     2
+#> 6   21.4     4 121.0   109  4.11 2.780 18.60     1     1     4     2
+#> 7   30.4     4  75.7    52  4.93 1.615 18.52     1     1     4     2
+#> 8   33.9     4  71.1    65  4.22 1.835 19.90     1     1     4     1
+#> 9   21.5     4 120.1    97  3.70 2.465 20.01     1     0     3     1
+#> 10  30.4     4  95.1   113  3.77 1.513 16.90     1     1     5     2
+#> # ... with 22 more rows
+
+ +
+ +
+
+

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+ + + +
+ +
+
+
+

Operate on a selection of variables.

+
+ + +

The variants suffixed with _if, _at or _all apply an +expression (sometimes several) to all variables within a specified +subset. This subset can contain all variables (_all variants), a +vars() selection (_at variants), or variables selected with a +predicate (_if variants).

+ + + +

Arguments

+ + + + + + + + + + + + + + + + + + + + + + +
.tbl

A tbl object.

.funs

List of function calls generated by funs(), or a +character vector of function names, or simply a function.

.vars

A list of columns generated by vars(), +or a character vector of column names, or a numeric vector of column +positions.

.predicate

A predicate function to be applied to the columns +or a logical vector. The variables for which .predicate is or +returns TRUE are selected. This argument is passed to +rlang::as_function() and thus supports quosure-style lambda +functions and strings representing function names.

...

Additional arguments for the function calls in +.funs. These are evaluated only once, with explicit +splicing.

+ +

Details

+ +

The verbs with scoped variants are:

+

There are three kinds of scoped variants. They differ in the scope +of the variable selection on which operations are applied:

    +

  • Verbs suffixed with _all() apply an operation on all variables.

    • +

  • Verbs suffixed with _at() apply an operation on a subset of +variables specified with the quoting function vars(). This +quoting function accepts select_vars() helpers like +starts_with(). Instead of a vars() selection, you can also +supply an integerish vector of column +positions or a character vector of column names.

    • +

  • Verbs suffixed with _if() apply an operation on the subset of +variables for which a predicate function returns TRUE. Instead +of a predicate function, you can also supply a logical vector.

    • +
+ + +
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/se-deprecated.html b/docs/reference/se-deprecated.html new file mode 100644 index 0000000000..9fd6c9bbf9 --- /dev/null +++ b/docs/reference/se-deprecated.html @@ -0,0 +1,242 @@ + + + + + + + + +Deprecated SE versions of main verbs. — tally_ • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Deprecated SE versions of main verbs.

+
+ + +

dplyr used to offer twin versions of each verb suffixed with an +underscore. These versions had standard evaluation (SE) semantics: +rather than taking arguments by code, like NSE verbs, they took +arguments by value. Their purpose was to make it possible to +program with dplyr. However, dplyr now uses tidy evaluation +semantics. NSE verbs still capture their arguments, but you can now +unquote parts of these arguments. This offers full programmability +with NSE verbs. Thus, the underscored versions are now superfluous.

+ + + 
tally_(x, wt, sort = FALSE)
+
+count_(x, vars, wt = NULL, sort = FALSE)
+
+add_tally_(x, wt, sort = FALSE)
+
+add_count_(x, vars, wt = NULL, sort = FALSE)
+
+distinct_(.data, ..., .dots, .keep_all = FALSE)
+
+do_(.data, ..., .dots = list())
+
+funs_(dots, args = list(), env = base_env())
+
+group_by_(.data, ..., .dots = list(), add = FALSE)
+
+group_indices_(.data, ..., .dots = list())
+
+filter_(.data, ..., .dots = list())
+
+slice_(.data, ..., .dots = list())
+
+summarise_(.data, ..., .dots = list())
+
+summarize_(.data, ..., .dots = list())
+
+mutate_(.data, ..., .dots = list())
+
+transmute_(.data, ..., .dots = list())
+
+arrange_(.data, ..., .dots = list())
+
+select_(.data, ..., .dots = list())
+
+rename_(.data, ..., .dots = list())
+
+select_vars_(vars, args, include = character(), exclude = character())
+
+rename_vars_(vars, args)
+ +

Arguments

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
x

a tbl() to tally/count.

wt

(Optional) If omitted, will count the number of rows. If +specified, will perform a "weighted" tally by summing the +(non-missing) values of variable wt. This argument is +automatically quoted and later +evaluated in the context of the data +frame. It supports unquoting. See +vignette("programming") for an introduction to these concepts.

sort

if TRUE will sort output in descending order of n

vars

Various meanings depending on the verb.

.data

A data frame.

.keep_all

If TRUE, keep all variables in .data. +If a combination of ... is not distinct, this keeps the +first row of values.

dots, .dots, ...

Pair/values of expressions coercible to lazy objects.

args

Various meanings depending on the verb.

env

The environment in which functions should be evaluated.

add

When add = FALSE, the default, group_by() will +override existing groups. To instead add to the existing groups, +use add = TRUE

include

Character vector of column names to always +include/exclude.

exclude

Character vector of column names to always +include/exclude.

+ +

Details

+ +

Unquoting triggers immediate evaluation of its operand and inlines +the result within the captured expression. This result can be a +value or an expression to be evaluated later with the rest of the +argument. See vignette("programming") for more information.

+ + +
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/select.html b/docs/reference/select.html new file mode 100644 index 0000000000..9809b88632 --- /dev/null +++ b/docs/reference/select.html @@ -0,0 +1,313 @@ + + + + + + + + +Select/rename variables by name — select • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Select/rename variables by name

+
+ + +

select() keeps only the variables you mention; rename() +keeps all variables.

+ + + 
select(.data, ...)
+
+rename(.data, ...)
+ +

Arguments

+ + + + + + + + + + +
.data

A tbl. All main verbs are S3 generics and provide methods +for tbl_df(), dtplyr::tbl_dt() and dbplyr::tbl_dbi().

...

One or more unquoted expressions separated by commas. +You can treat variable names like they are positions.

+

Positive values select variables; negative values to drop variables.

+

Use named arguments to rename selected variables.

+

These arguments are automatically quoted and +evaluated in a context where column names +represent column positions. They support +unquoting and splicing. See +vignette("programming") for an introduction to these concepts.

+ +

Value

+ +

An object of the same class as .data.

+ +

Useful functions

+ + +

As well as using existing functions like : and c(), there are +a number of special functions that only work inside select

+

To drop variables, use -.

+ +

Scoped selection and renaming

+ + +

The three scoped variants of select() (select_all(), +select_if() and select_at()) and the three variants of +rename() (rename_all(), rename_if(), rename_at()) make it +easy to apply a renaming function to a selection of variables.

+ +

Tidy data

+ + +

When applied to a data frame, row names are silently dropped. To preserve, +convert to an explicit variable with tibble::rownames_to_column().

+ +

See also

+ +

Other single table verbs: arrange, + filter, mutate, + slice, summarise

+ + +

Examples

+ 
iris <- as_tibble(iris) # so it prints a little nicer
+select(iris, starts_with("Petal"))
#> # A tibble: 150 × 2
+#>    Petal.Length Petal.Width
+#>           <dbl>       <dbl>
+#> 1           1.4         0.2
+#> 2           1.4         0.2
+#> 3           1.3         0.2
+#> 4           1.5         0.2
+#> 5           1.4         0.2
+#> 6           1.7         0.4
+#> 7           1.4         0.3
+#> 8           1.5         0.2
+#> 9           1.4         0.2
+#> 10          1.5         0.1
+#> # ... with 140 more rows
select(iris, ends_with("Width"))
#> # A tibble: 150 × 2
+#>    Sepal.Width Petal.Width
+#>          <dbl>       <dbl>
+#> 1          3.5         0.2
+#> 2          3.0         0.2
+#> 3          3.2         0.2
+#> 4          3.1         0.2
+#> 5          3.6         0.2
+#> 6          3.9         0.4
+#> 7          3.4         0.3
+#> 8          3.4         0.2
+#> 9          2.9         0.2
+#> 10         3.1         0.1
+#> # ... with 140 more rows

+# Move Species variable to the front
+select(iris, Species, everything())
#> # A tibble: 150 × 5
+#>    Species Sepal.Length Sepal.Width Petal.Length Petal.Width
+#>     <fctr>        <dbl>       <dbl>        <dbl>       <dbl>
+#> 1   setosa          5.1         3.5          1.4         0.2
+#> 2   setosa          4.9         3.0          1.4         0.2
+#> 3   setosa          4.7         3.2          1.3         0.2
+#> 4   setosa          4.6         3.1          1.5         0.2
+#> 5   setosa          5.0         3.6          1.4         0.2
+#> 6   setosa          5.4         3.9          1.7         0.4
+#> 7   setosa          4.6         3.4          1.4         0.3
+#> 8   setosa          5.0         3.4          1.5         0.2
+#> 9   setosa          4.4         2.9          1.4         0.2
+#> 10  setosa          4.9         3.1          1.5         0.1
+#> # ... with 140 more rows

+df <- as.data.frame(matrix(runif(100), nrow = 10))
+df <- tbl_df(df[c(3, 4, 7, 1, 9, 8, 5, 2, 6, 10)])
+select(df, V4:V6)
#> # A tibble: 10 × 8
+#>            V4         V7        V1        V9          V8         V5         V2
+#>         <dbl>      <dbl>     <dbl>     <dbl>       <dbl>      <dbl>      <dbl>
+#> 1  0.87959719 0.00250323 0.6477019 0.6523589 0.789947051 0.26714756 0.79909120
+#> 2  0.37491998 0.84770109 0.0647610 0.6675703 0.004801874 0.60840493 0.13193857
+#> 3  0.43416063 0.66004509 0.3374612 0.1980866 0.252908190 0.77196657 0.54759937
+#> 4  0.80684989 0.29450061 0.5698746 0.8681269 0.563169963 0.51975041 0.09701772
+#> 5  0.63560582 0.57010194 0.3383233 0.1732694 0.952278358 0.86047988 0.98637755
+#> 6  0.06871643 0.83903090 0.4992534 0.2049636 0.685113066 0.79302051 0.83954213
+#> 7  0.14484133 0.63062556 0.3084174 0.2171490 0.470041074 0.78391104 0.39959635
+#> 8  0.29457026 0.49672970 0.8404281 0.1508981 0.289851467 0.42372128 0.95222495
+#> 9  0.04144781 0.38952535 0.0651790 0.7745374 0.510124689 0.01551256 0.05949630
+#> 10 0.11654699 0.73144890 0.4399482 0.5330259 0.750690085 0.41620118 0.27691599
+#> # ... with 1 more variables: V6 <dbl>
select(df, num_range("V", 4:6))
#> # A tibble: 10 × 3
+#>            V4         V5          V6
+#>         <dbl>      <dbl>       <dbl>
+#> 1  0.87959719 0.26714756 0.006950771
+#> 2  0.37491998 0.60840493 0.390183412
+#> 3  0.43416063 0.77196657 0.238652540
+#> 4  0.80684989 0.51975041 0.384401472
+#> 5  0.63560582 0.86047988 0.073094374
+#> 6  0.06871643 0.79302051 0.766595044
+#> 7  0.14484133 0.78391104 0.687511492
+#> 8  0.29457026 0.42372128 0.841570623
+#> 9  0.04144781 0.01551256 0.105449455
+#> 10 0.11654699 0.41620118 0.340091229

+# Drop variables with -
+select(iris, -starts_with("Petal"))
#> # A tibble: 150 × 3
+#>    Sepal.Length Sepal.Width Species
+#>           <dbl>       <dbl>  <fctr>
+#> 1           5.1         3.5  setosa
+#> 2           4.9         3.0  setosa
+#> 3           4.7         3.2  setosa
+#> 4           4.6         3.1  setosa
+#> 5           5.0         3.6  setosa
+#> 6           5.4         3.9  setosa
+#> 7           4.6         3.4  setosa
+#> 8           5.0         3.4  setosa
+#> 9           4.4         2.9  setosa
+#> 10          4.9         3.1  setosa
+#> # ... with 140 more rows

+# Renaming -----------------------------------------
+# * select() keeps only the variables you specify
+select(iris, petal_length = Petal.Length)
#> # A tibble: 150 × 1
+#>    petal_length
+#>           <dbl>
+#> 1           1.4
+#> 2           1.4
+#> 3           1.3
+#> 4           1.5
+#> 5           1.4
+#> 6           1.7
+#> 7           1.4
+#> 8           1.5
+#> 9           1.4
+#> 10          1.5
+#> # ... with 140 more rows

+# * rename() keeps all variables
+rename(iris, petal_length = Petal.Length)
#> # A tibble: 150 × 5
+#>    Sepal.Length Sepal.Width petal_length Petal.Width Species
+#>           <dbl>       <dbl>        <dbl>       <dbl>  <fctr>
+#> 1           5.1         3.5          1.4         0.2  setosa
+#> 2           4.9         3.0          1.4         0.2  setosa
+#> 3           4.7         3.2          1.3         0.2  setosa
+#> 4           4.6         3.1          1.5         0.2  setosa
+#> 5           5.0         3.6          1.4         0.2  setosa
+#> 6           5.4         3.9          1.7         0.4  setosa
+#> 7           4.6         3.4          1.4         0.3  setosa
+#> 8           5.0         3.4          1.5         0.2  setosa
+#> 9           4.4         2.9          1.4         0.2  setosa
+#> 10          4.9         3.1          1.5         0.1  setosa
+#> # ... with 140 more rows
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/select_all.html b/docs/reference/select_all.html new file mode 100644 index 0000000000..0ff37a76e3 --- /dev/null +++ b/docs/reference/select_all.html @@ -0,0 +1,378 @@ + + + + + + + + +Select and rename a selection of variables. — select_all • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Select and rename a selection of variables.

+
+ + +

These scoped variants of select() and rename() operate on a +selection of variables. The semantics of these verbs have simple +but important differences:

    +

  • Selection drops variables that are not in the selection while +renaming retains them.

    • +

  • The renaming function is optional for selection but not for +renaming.

    • +
+ + + 
select_all(.tbl, .funs = list(), ...)
+
+rename_all(.tbl, .funs = list(), ...)
+
+select_if(.tbl, .predicate, .funs = list(), ...)
+
+rename_if(.tbl, .predicate, .funs = list(), ...)
+
+select_at(.tbl, .vars, .funs = list(), ...)
+
+rename_at(.tbl, .vars, .funs = list(), ...)
+ +

Arguments

+ + + + + + + + + + + + + + + + + + + + + + +
.tbl

A tbl object.

.funs

A single expression quoted with funs() or within a +quosure, a string naming a function, or a function.

...

Additional arguments for the function calls in +.funs. These are evaluated only once, with explicit +splicing.

.predicate

A predicate function to be applied to the columns +or a logical vector. The variables for which .predicate is or +returns TRUE are selected. This argument is passed to +rlang::as_function() and thus supports quosure-style lambda +functions and strings representing function names.

.vars

A list of columns generated by vars(), +or a character vector of column names, or a numeric vector of column +positions.

+ + +

Examples

+ 
# Supply a renaming function:
+select_all(mtcars, toupper)
#>                      MPG CYL  DISP  HP DRAT    WT  QSEC VS AM GEAR CARB
+#> Mazda RX4           21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4
+#> Mazda RX4 Wag       21.0   6 160.0 110 3.90 2.875 17.02  0  1    4    4
+#> Datsun 710          22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1
+#> Hornet 4 Drive      21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1
+#> Hornet Sportabout   18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2
+#> Valiant             18.1   6 225.0 105 2.76 3.460 20.22  1  0    3    1
+#> Duster 360          14.3   8 360.0 245 3.21 3.570 15.84  0  0    3    4
+#> Merc 240D           24.4   4 146.7  62 3.69 3.190 20.00  1  0    4    2
+#> Merc 230            22.8   4 140.8  95 3.92 3.150 22.90  1  0    4    2
+#> Merc 280            19.2   6 167.6 123 3.92 3.440 18.30  1  0    4    4
+#> Merc 280C           17.8   6 167.6 123 3.92 3.440 18.90  1  0    4    4
+#> Merc 450SE          16.4   8 275.8 180 3.07 4.070 17.40  0  0    3    3
+#> Merc 450SL          17.3   8 275.8 180 3.07 3.730 17.60  0  0    3    3
+#> Merc 450SLC         15.2   8 275.8 180 3.07 3.780 18.00  0  0    3    3
+#> Cadillac Fleetwood  10.4   8 472.0 205 2.93 5.250 17.98  0  0    3    4
+#> Lincoln Continental 10.4   8 460.0 215 3.00 5.424 17.82  0  0    3    4
+#> Chrysler Imperial   14.7   8 440.0 230 3.23 5.345 17.42  0  0    3    4
+#> Fiat 128            32.4   4  78.7  66 4.08 2.200 19.47  1  1    4    1
+#> Honda Civic         30.4   4  75.7  52 4.93 1.615 18.52  1  1    4    2
+#> Toyota Corolla      33.9   4  71.1  65 4.22 1.835 19.90  1  1    4    1
+#> Toyota Corona       21.5   4 120.1  97 3.70 2.465 20.01  1  0    3    1
+#> Dodge Challenger    15.5   8 318.0 150 2.76 3.520 16.87  0  0    3    2
+#> AMC Javelin         15.2   8 304.0 150 3.15 3.435 17.30  0  0    3    2
+#> Camaro Z28          13.3   8 350.0 245 3.73 3.840 15.41  0  0    3    4
+#> Pontiac Firebird    19.2   8 400.0 175 3.08 3.845 17.05  0  0    3    2
+#> Fiat X1-9           27.3   4  79.0  66 4.08 1.935 18.90  1  1    4    1
+#> Porsche 914-2       26.0   4 120.3  91 4.43 2.140 16.70  0  1    5    2
+#> Lotus Europa        30.4   4  95.1 113 3.77 1.513 16.90  1  1    5    2
+#> Ford Pantera L      15.8   8 351.0 264 4.22 3.170 14.50  0  1    5    4
+#> Ferrari Dino        19.7   6 145.0 175 3.62 2.770 15.50  0  1    5    6
+#> Maserati Bora       15.0   8 301.0 335 3.54 3.570 14.60  0  1    5    8
+#> Volvo 142E          21.4   4 121.0 109 4.11 2.780 18.60  1  1    4    2
select_all(mtcars, "toupper")
#>                      MPG CYL  DISP  HP DRAT    WT  QSEC VS AM GEAR CARB
+#> Mazda RX4           21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4
+#> Mazda RX4 Wag       21.0   6 160.0 110 3.90 2.875 17.02  0  1    4    4
+#> Datsun 710          22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1
+#> Hornet 4 Drive      21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1
+#> Hornet Sportabout   18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2
+#> Valiant             18.1   6 225.0 105 2.76 3.460 20.22  1  0    3    1
+#> Duster 360          14.3   8 360.0 245 3.21 3.570 15.84  0  0    3    4
+#> Merc 240D           24.4   4 146.7  62 3.69 3.190 20.00  1  0    4    2
+#> Merc 230            22.8   4 140.8  95 3.92 3.150 22.90  1  0    4    2
+#> Merc 280            19.2   6 167.6 123 3.92 3.440 18.30  1  0    4    4
+#> Merc 280C           17.8   6 167.6 123 3.92 3.440 18.90  1  0    4    4
+#> Merc 450SE          16.4   8 275.8 180 3.07 4.070 17.40  0  0    3    3
+#> Merc 450SL          17.3   8 275.8 180 3.07 3.730 17.60  0  0    3    3
+#> Merc 450SLC         15.2   8 275.8 180 3.07 3.780 18.00  0  0    3    3
+#> Cadillac Fleetwood  10.4   8 472.0 205 2.93 5.250 17.98  0  0    3    4
+#> Lincoln Continental 10.4   8 460.0 215 3.00 5.424 17.82  0  0    3    4
+#> Chrysler Imperial   14.7   8 440.0 230 3.23 5.345 17.42  0  0    3    4
+#> Fiat 128            32.4   4  78.7  66 4.08 2.200 19.47  1  1    4    1
+#> Honda Civic         30.4   4  75.7  52 4.93 1.615 18.52  1  1    4    2
+#> Toyota Corolla      33.9   4  71.1  65 4.22 1.835 19.90  1  1    4    1
+#> Toyota Corona       21.5   4 120.1  97 3.70 2.465 20.01  1  0    3    1
+#> Dodge Challenger    15.5   8 318.0 150 2.76 3.520 16.87  0  0    3    2
+#> AMC Javelin         15.2   8 304.0 150 3.15 3.435 17.30  0  0    3    2
+#> Camaro Z28          13.3   8 350.0 245 3.73 3.840 15.41  0  0    3    4
+#> Pontiac Firebird    19.2   8 400.0 175 3.08 3.845 17.05  0  0    3    2
+#> Fiat X1-9           27.3   4  79.0  66 4.08 1.935 18.90  1  1    4    1
+#> Porsche 914-2       26.0   4 120.3  91 4.43 2.140 16.70  0  1    5    2
+#> Lotus Europa        30.4   4  95.1 113 3.77 1.513 16.90  1  1    5    2
+#> Ford Pantera L      15.8   8 351.0 264 4.22 3.170 14.50  0  1    5    4
+#> Ferrari Dino        19.7   6 145.0 175 3.62 2.770 15.50  0  1    5    6
+#> Maserati Bora       15.0   8 301.0 335 3.54 3.570 14.60  0  1    5    8
+#> Volvo 142E          21.4   4 121.0 109 4.11 2.780 18.60  1  1    4    2
select_all(mtcars, funs(toupper(.)))
#>                      MPG CYL  DISP  HP DRAT    WT  QSEC VS AM GEAR CARB
+#> Mazda RX4           21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4
+#> Mazda RX4 Wag       21.0   6 160.0 110 3.90 2.875 17.02  0  1    4    4
+#> Datsun 710          22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1
+#> Hornet 4 Drive      21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1
+#> Hornet Sportabout   18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2
+#> Valiant             18.1   6 225.0 105 2.76 3.460 20.22  1  0    3    1
+#> Duster 360          14.3   8 360.0 245 3.21 3.570 15.84  0  0    3    4
+#> Merc 240D           24.4   4 146.7  62 3.69 3.190 20.00  1  0    4    2
+#> Merc 230            22.8   4 140.8  95 3.92 3.150 22.90  1  0    4    2
+#> Merc 280            19.2   6 167.6 123 3.92 3.440 18.30  1  0    4    4
+#> Merc 280C           17.8   6 167.6 123 3.92 3.440 18.90  1  0    4    4
+#> Merc 450SE          16.4   8 275.8 180 3.07 4.070 17.40  0  0    3    3
+#> Merc 450SL          17.3   8 275.8 180 3.07 3.730 17.60  0  0    3    3
+#> Merc 450SLC         15.2   8 275.8 180 3.07 3.780 18.00  0  0    3    3
+#> Cadillac Fleetwood  10.4   8 472.0 205 2.93 5.250 17.98  0  0    3    4
+#> Lincoln Continental 10.4   8 460.0 215 3.00 5.424 17.82  0  0    3    4
+#> Chrysler Imperial   14.7   8 440.0 230 3.23 5.345 17.42  0  0    3    4
+#> Fiat 128            32.4   4  78.7  66 4.08 2.200 19.47  1  1    4    1
+#> Honda Civic         30.4   4  75.7  52 4.93 1.615 18.52  1  1    4    2
+#> Toyota Corolla      33.9   4  71.1  65 4.22 1.835 19.90  1  1    4    1
+#> Toyota Corona       21.5   4 120.1  97 3.70 2.465 20.01  1  0    3    1
+#> Dodge Challenger    15.5   8 318.0 150 2.76 3.520 16.87  0  0    3    2
+#> AMC Javelin         15.2   8 304.0 150 3.15 3.435 17.30  0  0    3    2
+#> Camaro Z28          13.3   8 350.0 245 3.73 3.840 15.41  0  0    3    4
+#> Pontiac Firebird    19.2   8 400.0 175 3.08 3.845 17.05  0  0    3    2
+#> Fiat X1-9           27.3   4  79.0  66 4.08 1.935 18.90  1  1    4    1
+#> Porsche 914-2       26.0   4 120.3  91 4.43 2.140 16.70  0  1    5    2
+#> Lotus Europa        30.4   4  95.1 113 3.77 1.513 16.90  1  1    5    2
+#> Ford Pantera L      15.8   8 351.0 264 4.22 3.170 14.50  0  1    5    4
+#> Ferrari Dino        19.7   6 145.0 175 3.62 2.770 15.50  0  1    5    6
+#> Maserati Bora       15.0   8 301.0 335 3.54 3.570 14.60  0  1    5    8
+#> Volvo 142E          21.4   4 121.0 109 4.11 2.780 18.60  1  1    4    2

+# Selection drops unselected variables:
+is_whole <- function(x) all(floor(x) == x)
+select_if(mtcars, is_whole, toupper)
#>                     CYL  HP VS AM GEAR CARB
+#> Mazda RX4             6 110  0  1    4    4
+#> Mazda RX4 Wag         6 110  0  1    4    4
+#> Datsun 710            4  93  1  1    4    1
+#> Hornet 4 Drive        6 110  1  0    3    1
+#> Hornet Sportabout     8 175  0  0    3    2
+#> Valiant               6 105  1  0    3    1
+#> Duster 360            8 245  0  0    3    4
+#> Merc 240D             4  62  1  0    4    2
+#> Merc 230              4  95  1  0    4    2
+#> Merc 280              6 123  1  0    4    4
+#> Merc 280C             6 123  1  0    4    4
+#> Merc 450SE            8 180  0  0    3    3
+#> Merc 450SL            8 180  0  0    3    3
+#> Merc 450SLC           8 180  0  0    3    3
+#> Cadillac Fleetwood    8 205  0  0    3    4
+#> Lincoln Continental   8 215  0  0    3    4
+#> Chrysler Imperial     8 230  0  0    3    4
+#> Fiat 128              4  66  1  1    4    1
+#> Honda Civic           4  52  1  1    4    2
+#> Toyota Corolla        4  65  1  1    4    1
+#> Toyota Corona         4  97  1  0    3    1
+#> Dodge Challenger      8 150  0  0    3    2
+#> AMC Javelin           8 150  0  0    3    2
+#> Camaro Z28            8 245  0  0    3    4
+#> Pontiac Firebird      8 175  0  0    3    2
+#> Fiat X1-9             4  66  1  1    4    1
+#> Porsche 914-2         4  91  0  1    5    2
+#> Lotus Europa          4 113  1  1    5    2
+#> Ford Pantera L        8 264  0  1    5    4
+#> Ferrari Dino          6 175  0  1    5    6
+#> Maserati Bora         8 335  0  1    5    8
+#> Volvo 142E            4 109  1  1    4    2

+# But renaming retains them:
+rename_if(mtcars, is_whole, toupper)
#>                      mpg CYL  disp  HP drat    wt  qsec VS AM GEAR CARB
+#> Mazda RX4           21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4
+#> Mazda RX4 Wag       21.0   6 160.0 110 3.90 2.875 17.02  0  1    4    4
+#> Datsun 710          22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1
+#> Hornet 4 Drive      21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1
+#> Hornet Sportabout   18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2
+#> Valiant             18.1   6 225.0 105 2.76 3.460 20.22  1  0    3    1
+#> Duster 360          14.3   8 360.0 245 3.21 3.570 15.84  0  0    3    4
+#> Merc 240D           24.4   4 146.7  62 3.69 3.190 20.00  1  0    4    2
+#> Merc 230            22.8   4 140.8  95 3.92 3.150 22.90  1  0    4    2
+#> Merc 280            19.2   6 167.6 123 3.92 3.440 18.30  1  0    4    4
+#> Merc 280C           17.8   6 167.6 123 3.92 3.440 18.90  1  0    4    4
+#> Merc 450SE          16.4   8 275.8 180 3.07 4.070 17.40  0  0    3    3
+#> Merc 450SL          17.3   8 275.8 180 3.07 3.730 17.60  0  0    3    3
+#> Merc 450SLC         15.2   8 275.8 180 3.07 3.780 18.00  0  0    3    3
+#> Cadillac Fleetwood  10.4   8 472.0 205 2.93 5.250 17.98  0  0    3    4
+#> Lincoln Continental 10.4   8 460.0 215 3.00 5.424 17.82  0  0    3    4
+#> Chrysler Imperial   14.7   8 440.0 230 3.23 5.345 17.42  0  0    3    4
+#> Fiat 128            32.4   4  78.7  66 4.08 2.200 19.47  1  1    4    1
+#> Honda Civic         30.4   4  75.7  52 4.93 1.615 18.52  1  1    4    2
+#> Toyota Corolla      33.9   4  71.1  65 4.22 1.835 19.90  1  1    4    1
+#> Toyota Corona       21.5   4 120.1  97 3.70 2.465 20.01  1  0    3    1
+#> Dodge Challenger    15.5   8 318.0 150 2.76 3.520 16.87  0  0    3    2
+#> AMC Javelin         15.2   8 304.0 150 3.15 3.435 17.30  0  0    3    2
+#> Camaro Z28          13.3   8 350.0 245 3.73 3.840 15.41  0  0    3    4
+#> Pontiac Firebird    19.2   8 400.0 175 3.08 3.845 17.05  0  0    3    2
+#> Fiat X1-9           27.3   4  79.0  66 4.08 1.935 18.90  1  1    4    1
+#> Porsche 914-2       26.0   4 120.3  91 4.43 2.140 16.70  0  1    5    2
+#> Lotus Europa        30.4   4  95.1 113 3.77 1.513 16.90  1  1    5    2
+#> Ford Pantera L      15.8   8 351.0 264 4.22 3.170 14.50  0  1    5    4
+#> Ferrari Dino        19.7   6 145.0 175 3.62 2.770 15.50  0  1    5    6
+#> Maserati Bora       15.0   8 301.0 335 3.54 3.570 14.60  0  1    5    8
+#> Volvo 142E          21.4   4 121.0 109 4.11 2.780 18.60  1  1    4    2

+# The renaming function is optional for selection:
+select_if(mtcars, is_whole)
#>                     cyl  hp vs am gear carb
+#> Mazda RX4             6 110  0  1    4    4
+#> Mazda RX4 Wag         6 110  0  1    4    4
+#> Datsun 710            4  93  1  1    4    1
+#> Hornet 4 Drive        6 110  1  0    3    1
+#> Hornet Sportabout     8 175  0  0    3    2
+#> Valiant               6 105  1  0    3    1
+#> Duster 360            8 245  0  0    3    4
+#> Merc 240D             4  62  1  0    4    2
+#> Merc 230              4  95  1  0    4    2
+#> Merc 280              6 123  1  0    4    4
+#> Merc 280C             6 123  1  0    4    4
+#> Merc 450SE            8 180  0  0    3    3
+#> Merc 450SL            8 180  0  0    3    3
+#> Merc 450SLC           8 180  0  0    3    3
+#> Cadillac Fleetwood    8 205  0  0    3    4
+#> Lincoln Continental   8 215  0  0    3    4
+#> Chrysler Imperial     8 230  0  0    3    4
+#> Fiat 128              4  66  1  1    4    1
+#> Honda Civic           4  52  1  1    4    2
+#> Toyota Corolla        4  65  1  1    4    1
+#> Toyota Corona         4  97  1  0    3    1
+#> Dodge Challenger      8 150  0  0    3    2
+#> AMC Javelin           8 150  0  0    3    2
+#> Camaro Z28            8 245  0  0    3    4
+#> Pontiac Firebird      8 175  0  0    3    2
+#> Fiat X1-9             4  66  1  1    4    1
+#> Porsche 914-2         4  91  0  1    5    2
+#> Lotus Europa          4 113  1  1    5    2
+#> Ford Pantera L        8 264  0  1    5    4
+#> Ferrari Dino          6 175  0  1    5    6
+#> Maserati Bora         8 335  0  1    5    8
+#> Volvo 142E            4 109  1  1    4    2
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/select_helpers.html b/docs/reference/select_helpers.html new file mode 100644 index 0000000000..780927b770 --- /dev/null +++ b/docs/reference/select_helpers.html @@ -0,0 +1,285 @@ + + + + + + + + +Select helpers — select_helpers • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Select helpers

+
+ + +

These functions allow you to select variables based on their names.

    +

  • starts_with(): starts with a prefix

    • +

  • ends_with(): ends with a prefix

    • +

  • contains(): contains a literal string

    • +

  • matches(): matches a regular expression

    • +

  • num_range(): a numerical range like x01, x02, x03.

    • +

  • one_of(): variables in character vector.

    • +

  • everything(): all variables.

    • +
+ + + 
current_vars()
+
+starts_with(match, ignore.case = TRUE, vars = current_vars())
+
+ends_with(match, ignore.case = TRUE, vars = current_vars())
+
+contains(match, ignore.case = TRUE, vars = current_vars())
+
+matches(match, ignore.case = TRUE, vars = current_vars())
+
+num_range(prefix, range, width = NULL, vars = current_vars())
+
+one_of(..., vars = current_vars())
+
+everything(vars = current_vars())
+ +

Arguments

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
match

A string.

ignore.case

If TRUE, the default, ignores case when matching +names.

vars

A character vector of variable names. When called from inside +select() these are automatically set to the names of the +table.

prefix

A prefix that starts the numeric range.

range

A sequence of integers, like 1:5

width

Optionally, the "width" of the numeric range. For example, +a range of 2 gives "01", a range of three "001", etc.

...

One or more character vectors.

+ +

Value

+ +

An integer vector giving the position of the matched variables.

+ + +

Examples

+ 
iris <- tbl_df(iris) # so it prints a little nicer
+select(iris, starts_with("Petal"))
#> # A tibble: 150 × 2
+#>    Petal.Length Petal.Width
+#>           <dbl>       <dbl>
+#> 1           1.4         0.2
+#> 2           1.4         0.2
+#> 3           1.3         0.2
+#> 4           1.5         0.2
+#> 5           1.4         0.2
+#> 6           1.7         0.4
+#> 7           1.4         0.3
+#> 8           1.5         0.2
+#> 9           1.4         0.2
+#> 10          1.5         0.1
+#> # ... with 140 more rows
select(iris, ends_with("Width"))
#> # A tibble: 150 × 2
+#>    Sepal.Width Petal.Width
+#>          <dbl>       <dbl>
+#> 1          3.5         0.2
+#> 2          3.0         0.2
+#> 3          3.2         0.2
+#> 4          3.1         0.2
+#> 5          3.6         0.2
+#> 6          3.9         0.4
+#> 7          3.4         0.3
+#> 8          3.4         0.2
+#> 9          2.9         0.2
+#> 10         3.1         0.1
+#> # ... with 140 more rows
select(iris, contains("etal"))
#> # A tibble: 150 × 2
+#>    Petal.Length Petal.Width
+#>           <dbl>       <dbl>
+#> 1           1.4         0.2
+#> 2           1.4         0.2
+#> 3           1.3         0.2
+#> 4           1.5         0.2
+#> 5           1.4         0.2
+#> 6           1.7         0.4
+#> 7           1.4         0.3
+#> 8           1.5         0.2
+#> 9           1.4         0.2
+#> 10          1.5         0.1
+#> # ... with 140 more rows
select(iris, matches(".t."))
#> # A tibble: 150 × 4
+#>    Sepal.Length Sepal.Width Petal.Length Petal.Width
+#>           <dbl>       <dbl>        <dbl>       <dbl>
+#> 1           5.1         3.5          1.4         0.2
+#> 2           4.9         3.0          1.4         0.2
+#> 3           4.7         3.2          1.3         0.2
+#> 4           4.6         3.1          1.5         0.2
+#> 5           5.0         3.6          1.4         0.2
+#> 6           5.4         3.9          1.7         0.4
+#> 7           4.6         3.4          1.4         0.3
+#> 8           5.0         3.4          1.5         0.2
+#> 9           4.4         2.9          1.4         0.2
+#> 10          4.9         3.1          1.5         0.1
+#> # ... with 140 more rows
select(iris, Petal.Length, Petal.Width)
#> # A tibble: 150 × 2
+#>    Petal.Length Petal.Width
+#>           <dbl>       <dbl>
+#> 1           1.4         0.2
+#> 2           1.4         0.2
+#> 3           1.3         0.2
+#> 4           1.5         0.2
+#> 5           1.4         0.2
+#> 6           1.7         0.4
+#> 7           1.4         0.3
+#> 8           1.5         0.2
+#> 9           1.4         0.2
+#> 10          1.5         0.1
+#> # ... with 140 more rows
select(iris, everything())
#> # A tibble: 150 × 5
+#>    Sepal.Length Sepal.Width Petal.Length Petal.Width Species
+#>           <dbl>       <dbl>        <dbl>       <dbl>  <fctr>
+#> 1           5.1         3.5          1.4         0.2  setosa
+#> 2           4.9         3.0          1.4         0.2  setosa
+#> 3           4.7         3.2          1.3         0.2  setosa
+#> 4           4.6         3.1          1.5         0.2  setosa
+#> 5           5.0         3.6          1.4         0.2  setosa
+#> 6           5.4         3.9          1.7         0.4  setosa
+#> 7           4.6         3.4          1.4         0.3  setosa
+#> 8           5.0         3.4          1.5         0.2  setosa
+#> 9           4.4         2.9          1.4         0.2  setosa
+#> 10          4.9         3.1          1.5         0.1  setosa
+#> # ... with 140 more rows
vars <- c("Petal.Length", "Petal.Width")
+select(iris, one_of(vars))
#> # A tibble: 150 × 2
+#>    Petal.Length Petal.Width
+#>           <dbl>       <dbl>
+#> 1           1.4         0.2
+#> 2           1.4         0.2
+#> 3           1.3         0.2
+#> 4           1.5         0.2
+#> 5           1.4         0.2
+#> 6           1.7         0.4
+#> 7           1.4         0.3
+#> 8           1.5         0.2
+#> 9           1.4         0.2
+#> 10          1.5         0.1
+#> # ... with 140 more rows
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/select_vars.html b/docs/reference/select_vars.html new file mode 100644 index 0000000000..7d54e479f7 --- /dev/null +++ b/docs/reference/select_vars.html @@ -0,0 +1,195 @@ + + + + + + + + +Select variables. — select_vars • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Select variables.

+
+ + +

These functions power select() and rename().

+ + + 
select_vars(vars, ..., include = character(), exclude = character())
+
+rename_vars(vars, ..., strict = TRUE)
+ +

Arguments

+ + + + + + + + + + + + + + + + + + +
vars

A character vector of existing column names.

..., args

Expressions to compute

+

These arguments are automatically quoted and +evaluated in a context where elements of +vars are objects representing their positions within +vars. They support unquoting and +splicing. See vignette("programming") for an introduction to +these concepts.

include, exclude

Character vector of column names to always +include/exclude.

strict

If TRUE, will throw an error if you attempt to rename a +variable that doesn't exist.

+ +

Value

+ +

A named character vector. Values are existing column names, +names are new names.

+ + +

Examples

+ 
# Keep variables
+select_vars(names(iris), everything())
#>   Sepal.Length    Sepal.Width   Petal.Length    Petal.Width        Species 
+#> "Sepal.Length"  "Sepal.Width" "Petal.Length"  "Petal.Width"      "Species" 
select_vars(names(iris), starts_with("Petal"))
#>   Petal.Length    Petal.Width 
+#> "Petal.Length"  "Petal.Width" 
select_vars(names(iris), ends_with("Width"))
#>   Sepal.Width   Petal.Width 
+#> "Sepal.Width" "Petal.Width" 
select_vars(names(iris), contains("etal"))
#>   Petal.Length    Petal.Width 
+#> "Petal.Length"  "Petal.Width" 
select_vars(names(iris), matches(".t."))
#>   Sepal.Length    Sepal.Width   Petal.Length    Petal.Width 
+#> "Sepal.Length"  "Sepal.Width" "Petal.Length"  "Petal.Width" 
select_vars(names(iris), Petal.Length, Petal.Width)
#>   Petal.Length    Petal.Width 
+#> "Petal.Length"  "Petal.Width" 
select_vars(names(iris), one_of("Petal.Length", "Petal.Width"))
#>   Petal.Length    Petal.Width 
+#> "Petal.Length"  "Petal.Width" 

+df <- as.data.frame(matrix(runif(100), nrow = 10))
+df <- df[c(3, 4, 7, 1, 9, 8, 5, 2, 6, 10)]
+select_vars(names(df), num_range("V", 4:6))
#>   V4   V5   V6 
+#> "V4" "V5" "V6" 

+# Drop variables
+select_vars(names(iris), -starts_with("Petal"))
#>   Sepal.Length    Sepal.Width        Species 
+#> "Sepal.Length"  "Sepal.Width"      "Species" 
select_vars(names(iris), -ends_with("Width"))
#>   Sepal.Length   Petal.Length        Species 
+#> "Sepal.Length" "Petal.Length"      "Species" 
select_vars(names(iris), -contains("etal"))
#>   Sepal.Length    Sepal.Width        Species 
+#> "Sepal.Length"  "Sepal.Width"      "Species" 
select_vars(names(iris), -matches(".t."))
#>   Species 
+#> "Species" 
select_vars(names(iris), -Petal.Length, -Petal.Width)
#>   Sepal.Length    Sepal.Width        Species 
+#> "Sepal.Length"  "Sepal.Width"      "Species" 

+# Rename variables
+select_vars(names(iris), petal_length = Petal.Length)
#>   petal_length 
+#> "Petal.Length" 
select_vars(names(iris), petal = starts_with("Petal"))
#>         petal1         petal2 
+#> "Petal.Length"  "Petal.Width" 

+# Rename variables preserving all existing
+rename_vars(names(iris), petal_length = Petal.Length)
#>   Sepal.Length    Sepal.Width   petal_length    Petal.Width        Species 
+#> "Sepal.Length"  "Sepal.Width" "Petal.Length"  "Petal.Width"      "Species" 

+# You can unquote names or formulas (or lists of)
+select_vars(names(iris), !!! list(~Petal.Length))
#>   Petal.Length 
+#> "Petal.Length" 
select_vars(names(iris), !! quote(Petal.Length))
#>   Petal.Length 
+#> "Petal.Length"
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/setops.html b/docs/reference/setops.html new file mode 100644 index 0000000000..8c04c4dc58 --- /dev/null +++ b/docs/reference/setops.html @@ -0,0 +1,262 @@ + + + + + + + + +Set operations. — setops • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Set operations.

+
+ + +

These functions override the set functions provided in base to make them +generic so that efficient versions for data frames and other tables can be +provided. The default methods call the base versions.

+ + + 
intersect(x, y, ...)
+
+union(x, y, ...)
+
+union_all(x, y, ...)
+
+setdiff(x, y, ...)
+
+setequal(x, y, ...)
+ +

Arguments

+ + + + + + + + + + +
x, y

objects to perform set function on (ignoring order)

...

other arguments passed on to methods

+ + +

Examples

+ 
mtcars$model <- rownames(mtcars)
+first <- mtcars[1:20, ]
+second <- mtcars[10:32, ]
+
+intersect(first, second)
#>     mpg cyl  disp  hp drat    wt  qsec vs am gear carb               model
+#> 1  19.2   6 167.6 123 3.92 3.440 18.30  1  0    4    4            Merc 280
+#> 2  17.8   6 167.6 123 3.92 3.440 18.90  1  0    4    4           Merc 280C
+#> 3  16.4   8 275.8 180 3.07 4.070 17.40  0  0    3    3          Merc 450SE
+#> 4  17.3   8 275.8 180 3.07 3.730 17.60  0  0    3    3          Merc 450SL
+#> 5  15.2   8 275.8 180 3.07 3.780 18.00  0  0    3    3         Merc 450SLC
+#> 6  10.4   8 472.0 205 2.93 5.250 17.98  0  0    3    4  Cadillac Fleetwood
+#> 7  10.4   8 460.0 215 3.00 5.424 17.82  0  0    3    4 Lincoln Continental
+#> 8  14.7   8 440.0 230 3.23 5.345 17.42  0  0    3    4   Chrysler Imperial
+#> 9  32.4   4  78.7  66 4.08 2.200 19.47  1  1    4    1            Fiat 128
+#> 10 30.4   4  75.7  52 4.93 1.615 18.52  1  1    4    2         Honda Civic
+#> 11 33.9   4  71.1  65 4.22 1.835 19.90  1  1    4    1      Toyota Corolla
union(first, second)
#>     mpg cyl  disp  hp drat    wt  qsec vs am gear carb               model
+#> 1  21.4   4 121.0 109 4.11 2.780 18.60  1  1    4    2          Volvo 142E
+#> 2  15.0   8 301.0 335 3.54 3.570 14.60  0  1    5    8       Maserati Bora
+#> 3  19.7   6 145.0 175 3.62 2.770 15.50  0  1    5    6        Ferrari Dino
+#> 4  15.8   8 351.0 264 4.22 3.170 14.50  0  1    5    4      Ford Pantera L
+#> 5  30.4   4  95.1 113 3.77 1.513 16.90  1  1    5    2        Lotus Europa
+#> 6  26.0   4 120.3  91 4.43 2.140 16.70  0  1    5    2       Porsche 914-2
+#> 7  27.3   4  79.0  66 4.08 1.935 18.90  1  1    4    1           Fiat X1-9
+#> 8  19.2   8 400.0 175 3.08 3.845 17.05  0  0    3    2    Pontiac Firebird
+#> 9  13.3   8 350.0 245 3.73 3.840 15.41  0  0    3    4          Camaro Z28
+#> 10 15.2   8 304.0 150 3.15 3.435 17.30  0  0    3    2         AMC Javelin
+#> 11 15.5   8 318.0 150 2.76 3.520 16.87  0  0    3    2    Dodge Challenger
+#> 12 21.5   4 120.1  97 3.70 2.465 20.01  1  0    3    1       Toyota Corona
+#> 13 33.9   4  71.1  65 4.22 1.835 19.90  1  1    4    1      Toyota Corolla
+#> 14 30.4   4  75.7  52 4.93 1.615 18.52  1  1    4    2         Honda Civic
+#> 15 32.4   4  78.7  66 4.08 2.200 19.47  1  1    4    1            Fiat 128
+#> 16 14.7   8 440.0 230 3.23 5.345 17.42  0  0    3    4   Chrysler Imperial
+#> 17 10.4   8 460.0 215 3.00 5.424 17.82  0  0    3    4 Lincoln Continental
+#> 18 10.4   8 472.0 205 2.93 5.250 17.98  0  0    3    4  Cadillac Fleetwood
+#> 19 15.2   8 275.8 180 3.07 3.780 18.00  0  0    3    3         Merc 450SLC
+#> 20 17.3   8 275.8 180 3.07 3.730 17.60  0  0    3    3          Merc 450SL
+#> 21 16.4   8 275.8 180 3.07 4.070 17.40  0  0    3    3          Merc 450SE
+#> 22 17.8   6 167.6 123 3.92 3.440 18.90  1  0    4    4           Merc 280C
+#> 23 19.2   6 167.6 123 3.92 3.440 18.30  1  0    4    4            Merc 280
+#> 24 22.8   4 140.8  95 3.92 3.150 22.90  1  0    4    2            Merc 230
+#> 25 24.4   4 146.7  62 3.69 3.190 20.00  1  0    4    2           Merc 240D
+#> 26 14.3   8 360.0 245 3.21 3.570 15.84  0  0    3    4          Duster 360
+#> 27 18.1   6 225.0 105 2.76 3.460 20.22  1  0    3    1             Valiant
+#> 28 18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2   Hornet Sportabout
+#> 29 21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1      Hornet 4 Drive
+#> 30 22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1          Datsun 710
+#> 31 21.0   6 160.0 110 3.90 2.875 17.02  0  1    4    4       Mazda RX4 Wag
+#> 32 21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4           Mazda RX4
setdiff(first, second)
#>    mpg cyl  disp  hp drat    wt  qsec vs am gear carb             model
+#> 1 21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4         Mazda RX4
+#> 2 21.0   6 160.0 110 3.90 2.875 17.02  0  1    4    4     Mazda RX4 Wag
+#> 3 22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1        Datsun 710
+#> 4 21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1    Hornet 4 Drive
+#> 5 18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2 Hornet Sportabout
+#> 6 18.1   6 225.0 105 2.76 3.460 20.22  1  0    3    1           Valiant
+#> 7 14.3   8 360.0 245 3.21 3.570 15.84  0  0    3    4        Duster 360
+#> 8 24.4   4 146.7  62 3.69 3.190 20.00  1  0    4    2         Merc 240D
+#> 9 22.8   4 140.8  95 3.92 3.150 22.90  1  0    4    2          Merc 230
setdiff(second, first)
#>     mpg cyl  disp  hp drat    wt  qsec vs am gear carb            model
+#> 1  21.5   4 120.1  97 3.70 2.465 20.01  1  0    3    1    Toyota Corona
+#> 2  15.5   8 318.0 150 2.76 3.520 16.87  0  0    3    2 Dodge Challenger
+#> 3  15.2   8 304.0 150 3.15 3.435 17.30  0  0    3    2      AMC Javelin
+#> 4  13.3   8 350.0 245 3.73 3.840 15.41  0  0    3    4       Camaro Z28
+#> 5  19.2   8 400.0 175 3.08 3.845 17.05  0  0    3    2 Pontiac Firebird
+#> 6  27.3   4  79.0  66 4.08 1.935 18.90  1  1    4    1        Fiat X1-9
+#> 7  26.0   4 120.3  91 4.43 2.140 16.70  0  1    5    2    Porsche 914-2
+#> 8  30.4   4  95.1 113 3.77 1.513 16.90  1  1    5    2     Lotus Europa
+#> 9  15.8   8 351.0 264 4.22 3.170 14.50  0  1    5    4   Ford Pantera L
+#> 10 19.7   6 145.0 175 3.62 2.770 15.50  0  1    5    6     Ferrari Dino
+#> 11 15.0   8 301.0 335 3.54 3.570 14.60  0  1    5    8    Maserati Bora
+#> 12 21.4   4 121.0 109 4.11 2.780 18.60  1  1    4    2       Volvo 142E

+union_all(first, second)
#>     mpg cyl  disp  hp drat    wt  qsec vs am gear carb               model
+#> 1  21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4           Mazda RX4
+#> 2  21.0   6 160.0 110 3.90 2.875 17.02  0  1    4    4       Mazda RX4 Wag
+#> 3  22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1          Datsun 710
+#> 4  21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1      Hornet 4 Drive
+#> 5  18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2   Hornet Sportabout
+#> 6  18.1   6 225.0 105 2.76 3.460 20.22  1  0    3    1             Valiant
+#> 7  14.3   8 360.0 245 3.21 3.570 15.84  0  0    3    4          Duster 360
+#> 8  24.4   4 146.7  62 3.69 3.190 20.00  1  0    4    2           Merc 240D
+#> 9  22.8   4 140.8  95 3.92 3.150 22.90  1  0    4    2            Merc 230
+#> 10 19.2   6 167.6 123 3.92 3.440 18.30  1  0    4    4            Merc 280
+#> 11 17.8   6 167.6 123 3.92 3.440 18.90  1  0    4    4           Merc 280C
+#> 12 16.4   8 275.8 180 3.07 4.070 17.40  0  0    3    3          Merc 450SE
+#> 13 17.3   8 275.8 180 3.07 3.730 17.60  0  0    3    3          Merc 450SL
+#> 14 15.2   8 275.8 180 3.07 3.780 18.00  0  0    3    3         Merc 450SLC
+#> 15 10.4   8 472.0 205 2.93 5.250 17.98  0  0    3    4  Cadillac Fleetwood
+#> 16 10.4   8 460.0 215 3.00 5.424 17.82  0  0    3    4 Lincoln Continental
+#> 17 14.7   8 440.0 230 3.23 5.345 17.42  0  0    3    4   Chrysler Imperial
+#> 18 32.4   4  78.7  66 4.08 2.200 19.47  1  1    4    1            Fiat 128
+#> 19 30.4   4  75.7  52 4.93 1.615 18.52  1  1    4    2         Honda Civic
+#> 20 33.9   4  71.1  65 4.22 1.835 19.90  1  1    4    1      Toyota Corolla
+#> 21 19.2   6 167.6 123 3.92 3.440 18.30  1  0    4    4            Merc 280
+#> 22 17.8   6 167.6 123 3.92 3.440 18.90  1  0    4    4           Merc 280C
+#> 23 16.4   8 275.8 180 3.07 4.070 17.40  0  0    3    3          Merc 450SE
+#> 24 17.3   8 275.8 180 3.07 3.730 17.60  0  0    3    3          Merc 450SL
+#> 25 15.2   8 275.8 180 3.07 3.780 18.00  0  0    3    3         Merc 450SLC
+#> 26 10.4   8 472.0 205 2.93 5.250 17.98  0  0    3    4  Cadillac Fleetwood
+#> 27 10.4   8 460.0 215 3.00 5.424 17.82  0  0    3    4 Lincoln Continental
+#> 28 14.7   8 440.0 230 3.23 5.345 17.42  0  0    3    4   Chrysler Imperial
+#> 29 32.4   4  78.7  66 4.08 2.200 19.47  1  1    4    1            Fiat 128
+#> 30 30.4   4  75.7  52 4.93 1.615 18.52  1  1    4    2         Honda Civic
+#> 31 33.9   4  71.1  65 4.22 1.835 19.90  1  1    4    1      Toyota Corolla
+#> 32 21.5   4 120.1  97 3.70 2.465 20.01  1  0    3    1       Toyota Corona
+#> 33 15.5   8 318.0 150 2.76 3.520 16.87  0  0    3    2    Dodge Challenger
+#> 34 15.2   8 304.0 150 3.15 3.435 17.30  0  0    3    2         AMC Javelin
+#> 35 13.3   8 350.0 245 3.73 3.840 15.41  0  0    3    4          Camaro Z28
+#> 36 19.2   8 400.0 175 3.08 3.845 17.05  0  0    3    2    Pontiac Firebird
+#> 37 27.3   4  79.0  66 4.08 1.935 18.90  1  1    4    1           Fiat X1-9
+#> 38 26.0   4 120.3  91 4.43 2.140 16.70  0  1    5    2       Porsche 914-2
+#> 39 30.4   4  95.1 113 3.77 1.513 16.90  1  1    5    2        Lotus Europa
+#> 40 15.8   8 351.0 264 4.22 3.170 14.50  0  1    5    4      Ford Pantera L
+#> 41 19.7   6 145.0 175 3.62 2.770 15.50  0  1    5    6        Ferrari Dino
+#> 42 15.0   8 301.0 335 3.54 3.570 14.60  0  1    5    8       Maserati Bora
+#> 43 21.4   4 121.0 109 4.11 2.780 18.60  1  1    4    2          Volvo 142E
setequal(mtcars, mtcars[32:1, ])
#> TRUE
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/slice.html b/docs/reference/slice.html new file mode 100644 index 0000000000..d903f01dce --- /dev/null +++ b/docs/reference/slice.html @@ -0,0 +1,228 @@ + + + + + + + + +Select rows by position — slice • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Select rows by position

+
+ + +

Slice does not work with relational databases because they have no +intrinsic notion of row order. If you want to perform the equivalent +operation, use filter() and row_number().

+ + + 
slice(.data, ...)
+ +

Arguments

+ + + + + + + + + + +
.data

A tbl.

...

Integer row values.

+

These arguments are automatically quoted and +evaluated in the context of the data +frame. They support unquoting and +splicing. See vignette("programming") for an introduction to +these concepts.

+ +

Tidy data

+ + +

When applied to a data frame, row names are silently dropped. To preserve, +convert to an explicit variable with tibble::rownames_to_column().

+ +

See also

+ +

Other single table verbs: arrange, + filter, mutate, + select, summarise

+ + +

Examples

+ 
slice(mtcars, 1L)
#> # A tibble: 1 × 11
+#>     mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
+#>   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
+#> 1    21     6   160   110   3.9  2.62 16.46     0     1     4     4
slice(mtcars, n())
#> # A tibble: 1 × 11
+#>     mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
+#>   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
+#> 1  21.4     4   121   109  4.11  2.78  18.6     1     1     4     2
slice(mtcars, 5:n())
#> # A tibble: 28 × 11
+#>      mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
+#>    <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
+#> 1   18.7     8 360.0   175  3.15  3.44 17.02     0     0     3     2
+#> 2   18.1     6 225.0   105  2.76  3.46 20.22     1     0     3     1
+#> 3   14.3     8 360.0   245  3.21  3.57 15.84     0     0     3     4
+#> 4   24.4     4 146.7    62  3.69  3.19 20.00     1     0     4     2
+#> 5   22.8     4 140.8    95  3.92  3.15 22.90     1     0     4     2
+#> 6   19.2     6 167.6   123  3.92  3.44 18.30     1     0     4     4
+#> 7   17.8     6 167.6   123  3.92  3.44 18.90     1     0     4     4
+#> 8   16.4     8 275.8   180  3.07  4.07 17.40     0     0     3     3
+#> 9   17.3     8 275.8   180  3.07  3.73 17.60     0     0     3     3
+#> 10  15.2     8 275.8   180  3.07  3.78 18.00     0     0     3     3
+#> # ... with 18 more rows

+by_cyl <- group_by(mtcars, cyl)
+slice(by_cyl, 1:2)
#> Source: local data frame [6 x 11]
+#> Groups: cyl [3]
+#> 
+#>     mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
+#>   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
+#> 1  22.8     4 108.0    93  3.85 2.320 18.61     1     1     4     1
+#> 2  24.4     4 146.7    62  3.69 3.190 20.00     1     0     4     2
+#> 3  21.0     6 160.0   110  3.90 2.620 16.46     0     1     4     4
+#> 4  21.0     6 160.0   110  3.90 2.875 17.02     0     1     4     4
+#> 5  18.7     8 360.0   175  3.15 3.440 17.02     0     0     3     2
+#> 6  14.3     8 360.0   245  3.21 3.570 15.84     0     0     3     4

+# Equivalent code using filter that will also work with databases,
+# but won't be as fast for in-memory data. For many databases, you'll
+# need to supply an explicit variable to use to compute the row number.
+filter(mtcars, row_number() == 1L)
#>   mpg cyl disp  hp drat   wt  qsec vs am gear carb
+#> 1  21   6  160 110  3.9 2.62 16.46  0  1    4    4
filter(mtcars, row_number() == n())
#>    mpg cyl disp  hp drat   wt qsec vs am gear carb
+#> 1 21.4   4  121 109 4.11 2.78 18.6  1  1    4    2
filter(mtcars, between(row_number(), 5, n()))
#>     mpg cyl  disp  hp drat    wt  qsec vs am gear carb
+#> 1  18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2
+#> 2  18.1   6 225.0 105 2.76 3.460 20.22  1  0    3    1
+#> 3  14.3   8 360.0 245 3.21 3.570 15.84  0  0    3    4
+#> 4  24.4   4 146.7  62 3.69 3.190 20.00  1  0    4    2
+#> 5  22.8   4 140.8  95 3.92 3.150 22.90  1  0    4    2
+#> 6  19.2   6 167.6 123 3.92 3.440 18.30  1  0    4    4
+#> 7  17.8   6 167.6 123 3.92 3.440 18.90  1  0    4    4
+#> 8  16.4   8 275.8 180 3.07 4.070 17.40  0  0    3    3
+#> 9  17.3   8 275.8 180 3.07 3.730 17.60  0  0    3    3
+#> 10 15.2   8 275.8 180 3.07 3.780 18.00  0  0    3    3
+#> 11 10.4   8 472.0 205 2.93 5.250 17.98  0  0    3    4
+#> 12 10.4   8 460.0 215 3.00 5.424 17.82  0  0    3    4
+#> 13 14.7   8 440.0 230 3.23 5.345 17.42  0  0    3    4
+#> 14 32.4   4  78.7  66 4.08 2.200 19.47  1  1    4    1
+#> 15 30.4   4  75.7  52 4.93 1.615 18.52  1  1    4    2
+#> 16 33.9   4  71.1  65 4.22 1.835 19.90  1  1    4    1
+#> 17 21.5   4 120.1  97 3.70 2.465 20.01  1  0    3    1
+#> 18 15.5   8 318.0 150 2.76 3.520 16.87  0  0    3    2
+#> 19 15.2   8 304.0 150 3.15 3.435 17.30  0  0    3    2
+#> 20 13.3   8 350.0 245 3.73 3.840 15.41  0  0    3    4
+#> 21 19.2   8 400.0 175 3.08 3.845 17.05  0  0    3    2
+#> 22 27.3   4  79.0  66 4.08 1.935 18.90  1  1    4    1
+#> 23 26.0   4 120.3  91 4.43 2.140 16.70  0  1    5    2
+#> 24 30.4   4  95.1 113 3.77 1.513 16.90  1  1    5    2
+#> 25 15.8   8 351.0 264 4.22 3.170 14.50  0  1    5    4
+#> 26 19.7   6 145.0 175 3.62 2.770 15.50  0  1    5    6
+#> 27 15.0   8 301.0 335 3.54 3.570 14.60  0  1    5    8
+#> 28 21.4   4 121.0 109 4.11 2.780 18.60  1  1    4    2
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/src.html b/docs/reference/src.html new file mode 100644 index 0000000000..be33eb2def --- /dev/null +++ b/docs/reference/src.html @@ -0,0 +1,145 @@ + + + + + + + + +Create a "src" object — src • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Create a "src" object

+
+ + +

src() is the standard constructor for srcs and is.src() tests.

+ + + 
src(subclass, ...)
+
+is.src(x)
+ +

Arguments

+ + + + + + + + + + + + + + +
subclass

name of subclass. "src" is an abstract base class, so you +must supply this value. src_ is automatically prepended to the +class name

...

fields used by object.

+

These dots are evaluated with explicit splicing.

x

object to test for "src"-ness.

+ + +
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/src_dbi.html b/docs/reference/src_dbi.html new file mode 100644 index 0000000000..daba3ba246 --- /dev/null +++ b/docs/reference/src_dbi.html @@ -0,0 +1,253 @@ + + + + + + + + +Source for database backends — src_dbi • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Source for database backends

+
+ + +

For backward compatibility dplyr provides three srcs for popular +open source databases:

+ +

However, modern best practice is to use tbl() directly on an DBIConnection.

+ + + 
src_mysql(dbname, host = NULL, port = 0L, username = "root",
+  password = "", ...)
+
+src_postgres(dbname = NULL, host = NULL, port = NULL, user = NULL,
+  password = NULL, ...)
+
+src_sqlite(path, create = FALSE)
+ +

Arguments

+ + + + + + + + + + + + + + + + + + + + + + + + + + +
dbname

Database name

host, port

Host name and port number of database

...

for the src, other arguments passed on to the underlying +database connector, DBI::dbConnect(). For the tbl, included for +compatibility with the generic, but otherwise ignored.

user, username, password

User name and password.

+

Generally, you should avoid saving username and password in your +scripts as it is easy to accidentally expose valuable credentials. +Instead, retrieve them from environment variables, or use database +specific credential scores. For example, with MySQL you can set up my.cnf +as described in RMySQL::MySQL().

path

Path to SQLite database. You can use the special path +":memory:" to create a temporary in memory database.

create

if FALSE, path must already exist. If +TRUE, will create a new SQlite3 database at path if +path does not exist and connect to the existing database if +path does exist.

+ +

Value

+ +

An S3 object with class src_dbi, src_sql, src.

+ +

Details

+ +

All data manipulation on SQL tbls are lazy: they will not actually +run the query or retrieve the data unless you ask for it: they all return +a new tbl_dbi object. Use compute() to run the query and save the +results in a temporary in the database, or use collect() to retrieve the +results to R. You can see the query with show_query().

+

For best performance, the database should have an index on the variables +that you are grouping by. Use explain() to check that the database is using +the indexes that you expect.

+

There is one excpetion: do() is not lazy since it must pull the data +into R.

+ + +

Examples

+ 
# Basic connection using DBI -------------------------------------------
+if (require(dbplyr, quietly = TRUE)) {
+
+con <- DBI::dbConnect(RSQLite::SQLite(), ":memory:")
+copy_to(con, mtcars)
+
+DBI::dbListTables(con)
+
+# To retrieve a single table from a source, use `tbl()`
+con %>% tbl("mtcars")
+
+# You can also use pass raw SQL if you want a more sophisticated query
+con %>% tbl(sql("SELECT * FROM mtcars WHERE cyl == 8"))
+
+# To show off the full features of dplyr's database integration,
+# we'll use the Lahman database. lahman_sqlite() takes care of
+# creating the database.
+lahman_p <- lahman_sqlite()
+batting <- lahman_p %>% tbl("Batting")
+batting
+
+# Basic data manipulation verbs work in the same way as with a tibble
+batting %>% filter(yearID > 2005, G > 130)
+batting %>% select(playerID:lgID)
+batting %>% arrange(playerID, desc(yearID))
+batting %>% summarise(G = mean(G), n = n())
+
+# There are a few exceptions. For example, databases give integer results
+# when dividing one integer by another. Multiply by 1 to fix the problem
+batting %>%
+  select(playerID:lgID, AB, R, G) %>%
+  mutate(
+   R_per_game1 = R / G,
+   R_per_game2 = R * 1.0 / G
+ )
+
+# All operations are lazy: they don't do anything until you request the
+# data, either by `print()`ing it (which shows the first ten rows),
+# or by `collect()`ing the results locally.
+system.time(recent <- filter(batting, yearID > 2010))
+system.time(collect(recent))
+
+# You can see the query that dplyr creates with show_query()
+batting %>%
+  filter(G > 0) %>%
+  group_by(playerID) %>%
+  summarise(n = n()) %>%
+  show_query()
+}
#> <SQL>
+#> SELECT `playerID`, COUNT() AS `n`
+#> FROM `Batting`
+#> WHERE (`G` > 0.0)
+#> GROUP BY `playerID`
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/src_local.html b/docs/reference/src_local.html new file mode 100644 index 0000000000..f4b06a770e --- /dev/null +++ b/docs/reference/src_local.html @@ -0,0 +1,153 @@ + + + + + + + + +A local source. — src_local • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

A local source.

+
+ + +

This is mainly useful for testing, since makes it possible to refer to +local and remote tables using exactly the same syntax.

+ + + 
src_local(tbl, pkg = NULL, env = NULL)
+
+src_df(pkg = NULL, env = NULL)
+ +

Arguments

+ + + + + + + + + + +
tbl

name of the function used to generate tbl objects

pkg, env

Either the name of a package or an environment object in +which to look for objects.

+ +

Details

+ +

Generally, src_local() should not be called directly, but instead +one of the constructors should be used.

+ + +

Examples

+ 
if (require("Lahman")) {
+batting_df <- tbl(src_df("Lahman"), "Batting")
+}
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/src_tbls.html b/docs/reference/src_tbls.html new file mode 100644 index 0000000000..03e3a103b8 --- /dev/null +++ b/docs/reference/src_tbls.html @@ -0,0 +1,134 @@ + + + + + + + + +List all tbls provided by a source. — src_tbls • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

List all tbls provided by a source.

+
+ + +

This is a generic method which individual src's will provide methods for. +Most methods will not be documented because it's usually pretty obvious what +possible results will be.

+ + + 
src_tbls(x)
+ +

Arguments

+ + + + + + +
x

a data src.

+ + +
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/starwars.html b/docs/reference/starwars.html new file mode 100644 index 0000000000..b006de4850 --- /dev/null +++ b/docs/reference/starwars.html @@ -0,0 +1,159 @@ + + + + + + + + +Starwars characters — starwars • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Starwars characters

+
+ + +

This data comes from SWAPI, the Star Wars API, http://swapi.co/

+ + + 
starwars
+ +

Format

+ +

A tibble with 87 rows and 13 variables:

+
name

Name of the character

+
height

Height (cm)

+
mass

Weight (kg)

+
hair_color,skin_color,eye_color

Hair, skin, and eye colors

+
birth_year

Year born (BBY = Before Battle of Yavin)

+
gender

male, female, hermaphrodite, or none.

+
homeworld

Name of homeworld

+
species

Name of species

+
films

List of films the character appeared in

+
vehicles

List of vehicles the character has piloted

+
starships

List of starships the character has piloted

+
+ + +

Examples

+ 
starwars
#> # A tibble: 87 × 13
+#>                  name height  mass    hair_color  skin_color eye_color
+#>                 <chr>  <int> <dbl>         <chr>       <chr>     <chr>
+#> 1      Luke Skywalker    172    77         blond        fair      blue
+#> 2               C-3PO    167    75          <NA>        gold    yellow
+#> 3               R2-D2     96    32          <NA> white, blue       red
+#> 4         Darth Vader    202   136          none       white    yellow
+#> 5         Leia Organa    150    49         brown       light     brown
+#> 6           Owen Lars    178   120   brown, grey       light      blue
+#> 7  Beru Whitesun lars    165    75         brown       light      blue
+#> 8               R5-D4     97    32          <NA>  white, red       red
+#> 9   Biggs Darklighter    183    84         black       light     brown
+#> 10     Obi-Wan Kenobi    182    77 auburn, white        fair blue-gray
+#> # ... with 77 more rows, and 7 more variables: birth_year <dbl>, gender <chr>,
+#> #   homeworld <chr>, species <chr>, films <list>, vehicles <list>,
+#> #   starships <list>
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/storms.html b/docs/reference/storms.html new file mode 100644 index 0000000000..0474c0d8bd --- /dev/null +++ b/docs/reference/storms.html @@ -0,0 +1,162 @@ + + + + + + + + +Storm tracks data — storms • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Storm tracks data

+
+ + +

This data is a subset of the NOAA Atlantic hurricane database best track +data, http://www.nhc.noaa.gov/data/#hurdat. The data includes the +positions and attributes of 198 tropical storms, measured every six hours +during the lifetime of a storm.

+ + + 
storms
+ +

Format

+ +

A tibble with 10,010 observations and 13 variables:

+
name

Storm Name

+
year,month,day

Date of report

+
hour

Hour of report (in UTC)

+
lat,long

Location of storm center

+
status

Storm classification (Tropical Depression, Tropical Storm, +or Hurricane)

+
category

Saffir-Simpson storm category (estimated from wind speed. +-1 = Tropical Depression, 0 = Tropical Storm)

+
wind

storm's maximum sustained wind speed (in knots)

+
pressure

Air pressure at the storm's center (in millibars)

+
ts_diameter

Diameter of the area experiencing tropical storm strength winds (34 knots or above)

+
hu_diameter

Diameter of the area experiencing hurricane strength winds (64 knots or above)

+
+ + +

Examples

+ 
storms
#> # A tibble: 10,010 × 13
+#>     name  year month   day  hour   lat  long              status category  wind
+#>    <chr> <dbl> <dbl> <int> <dbl> <dbl> <dbl>               <chr>    <ord> <int>
+#> 1    Amy  1975     6    27     0  27.5 -79.0 tropical depression       -1    25
+#> 2    Amy  1975     6    27     6  28.5 -79.0 tropical depression       -1    25
+#> 3    Amy  1975     6    27    12  29.5 -79.0 tropical depression       -1    25
+#> 4    Amy  1975     6    27    18  30.5 -79.0 tropical depression       -1    25
+#> 5    Amy  1975     6    28     0  31.5 -78.8 tropical depression       -1    25
+#> 6    Amy  1975     6    28     6  32.4 -78.7 tropical depression       -1    25
+#> 7    Amy  1975     6    28    12  33.3 -78.0 tropical depression       -1    25
+#> 8    Amy  1975     6    28    18  34.0 -77.0 tropical depression       -1    30
+#> 9    Amy  1975     6    29     0  34.4 -75.8      tropical storm        0    35
+#> 10   Amy  1975     6    29     6  34.0 -74.8      tropical storm        0    40
+#> # ... with 10,000 more rows, and 3 more variables: pressure <int>,
+#> #   ts_diameter <dbl>, hu_diameter <dbl>
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/summarise.html b/docs/reference/summarise.html new file mode 100644 index 0000000000..85bf2ccff6 --- /dev/null +++ b/docs/reference/summarise.html @@ -0,0 +1,224 @@ + + + + + + + + +Summarise multiple values to a single value — summarise • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Summarise multiple values to a single value

+
+ + +

summarise() is typically used on grouped data created by group_by(). +The output will have one row for each group.

+ + + 
summarise(.data, ...)
+
+summarize(.data, ...)
+ +

Arguments

+ + + + + + + + + + +
.data

A tbl. All main verbs are S3 generics and provide methods +for tbl_df(), dtplyr::tbl_dt() and dbplyr::tbl_dbi().

...

Name-value pairs of summary functions. The name will be the +name of the variable in the result. The value should be an expression +that returns a single value like min(x), n(), or sum(is.na(y)).

+

These arguments are automatically quoted and +evaluated in the context of the data +frame. They support unquoting and +splicing. See vignette("programming") for an introduction to +these concepts.

+ +

Value

+ +

An object of the same class as .data. One grouping level will +be dropped.

+ +

Useful functions

+ + +
    +

  • Center: mean(), median()

    • +

  • Spread: sd(), IQR(), mad()

    • +

  • Range: min(), max(), quantile()

    • +

  • Position: first(), last(), nth(),

    • +

  • Count: n(), n_distinct()

    • +

  • Logical: any(), all()

    • +
+ +

Backend variations

+ + +

Data frames are the only backend that supports creating a variable and +using it in the same summary. See examples for more details.

+ +

Tidy data

+ + +

When applied to a data frame, row names are silently dropped. To preserve, +convert to an explicit variable with tibble::rownames_to_column().

+ +

See also

+ +

Other single table verbs: arrange, + filter, mutate, + select, slice

+ + +

Examples

+ 
# A summary applied to ungrouped tbl returns a single row
+mtcars %>%
+  summarise(mean = mean(disp), n = n())
#>       mean  n
+#> 1 230.7219 32

+# Usually, you'll want to group first
+mtcars %>%
+  group_by(cyl) %>%
+  summarise(mean = mean(disp), n = n())
#> # A tibble: 3 × 3
+#>     cyl     mean     n
+#>   <dbl>    <dbl> <int>
+#> 1     4 105.1364    11
+#> 2     6 183.3143     7
+#> 3     8 353.1000    14

+# Each summary call removes one grouping level (since that group
+# is now just a single row)
+mtcars %>%
+  group_by(cyl, vs) %>%
+  summarise(cyl_n = n()) %>%
+  group_vars()
#> [1] "cyl"

+# Note that with data frames, newly created summaries immediately
+# overwrite existing variables
+mtcars %>%
+  group_by(cyl) %>%
+  summarise(disp = mean(disp), sd = sd(disp))
#> # A tibble: 3 × 3
+#>     cyl     disp    sd
+#>   <dbl>    <dbl> <dbl>
+#> 1     4 105.1364    NA
+#> 2     6 183.3143    NA
+#> 3     8 353.1000    NA
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/summarise_all.html b/docs/reference/summarise_all.html new file mode 100644 index 0000000000..29db072ff9 --- /dev/null +++ b/docs/reference/summarise_all.html @@ -0,0 +1,333 @@ + + + + + + + + +Summarise and mutate multiple columns. — summarise_all • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Summarise and mutate multiple columns.

+
+ + +

These verbs are scoped variants of summarise(), mutate() and +transmute(). They apply operations on a selection of variables.

    +

  • summarise_all(), mutate_all() and transmute_all() apply the +functions to all (non-grouping) columns.

    • +

  • summarise_at(), mutate_at() and transmute_at() allow you to +select columns using the same name-based select_helpers just +like with select().

    • +

  • summarise_if(), mutate_if() and transmute_if() operate on +columns for which a predicate returns TRUE.

    • +

  • summarise_each() and mutate_each() are older variants that +are now deprecated.

    • +
+ + + 
summarise_all(.tbl, .funs, ...)
+
+summarise_if(.tbl, .predicate, .funs, ...)
+
+summarise_at(.tbl, .vars, .funs, ..., .cols = NULL)
+
+summarize_all(.tbl, .funs, ...)
+
+summarize_if(.tbl, .predicate, .funs, ...)
+
+summarize_at(.tbl, .vars, .funs, ..., .cols = NULL)
+
+mutate_all(.tbl, .funs, ...)
+
+mutate_if(.tbl, .predicate, .funs, ...)
+
+mutate_at(.tbl, .vars, .funs, ..., .cols = NULL)
+
+transmute_all(.tbl, .funs, ...)
+
+transmute_if(.tbl, .predicate, .funs, ...)
+
+transmute_at(.tbl, .vars, .funs, ..., .cols = NULL)
+ +

Arguments

+ + + + + + + + + + + + + + + + + + + + + + + + + + +
.tbl

A tbl object.

.funs

List of function calls generated by funs(), or a +character vector of function names, or simply a function.

...

Additional arguments for the function calls in +.funs. These are evaluated only once, with explicit +splicing.

.predicate

A predicate function to be applied to the columns +or a logical vector. The variables for which .predicate is or +returns TRUE are selected. This argument is passed to +rlang::as_function() and thus supports quosure-style lambda +functions and strings representing function names.

.vars

A list of columns generated by vars(), +or a character vector of column names, or a numeric vector of column +positions.

.cols

This argument has been renamed to .vars to fit +dplyr's terminology and is deprecated.

+ +

Value

+ +

A data frame. By default, the newly created columns have the shortest +names needed to uniquely identify the output. To force inclusion of a name, +even when not needed, name the input (see examples for details).

+ +

See also

+ +

vars(), funs()

+ + +

Examples

+ 
# The scoped variants of summarise() and mutate() make it easy to
+# apply the same transformation to multiple variables:
+
+iris %>%
+  group_by(Species) %>%
+  summarise_all(mean)
#> # A tibble: 3 × 5
+#>      Species Sepal.Length Sepal.Width Petal.Length Petal.Width
+#>       <fctr>        <dbl>       <dbl>        <dbl>       <dbl>
+#> 1     setosa        5.006       3.428        1.462       0.246
+#> 2 versicolor        5.936       2.770        4.260       1.326
+#> 3  virginica        6.588       2.974        5.552       2.026

+# There are three variants.
+# * _all affects every variable
+# * _at affects variables selected with a character vector or vars()
+# * _if affects variables selected with a predicate function:
+
+starwars %>% summarise_at(vars(height:mass), mean, na.rm = TRUE)
#> # A tibble: 1 × 2
+#>    height     mass
+#>     <dbl>    <dbl>
+#> 1 174.358 97.31186
starwars %>% summarise_at(c("height", "mass"), mean, na.rm = TRUE)
#> # A tibble: 1 × 2
+#>    height     mass
+#>     <dbl>    <dbl>
+#> 1 174.358 97.31186
starwars %>% summarise_if(is.numeric, mean, na.rm = TRUE)
#> # A tibble: 1 × 3
+#>    height     mass birth_year
+#>     <dbl>    <dbl>      <dbl>
+#> 1 174.358 97.31186   87.56512

+# mutate_if is particularly useful for transforming variables from
+# one type to another
+iris %>% as_tibble() %>% mutate_if(is.factor, as.character)
#> # A tibble: 150 × 5
+#>    Sepal.Length Sepal.Width Petal.Length Petal.Width Species
+#>           <dbl>       <dbl>        <dbl>       <dbl>   <chr>
+#> 1           5.1         3.5          1.4         0.2  setosa
+#> 2           4.9         3.0          1.4         0.2  setosa
+#> 3           4.7         3.2          1.3         0.2  setosa
+#> 4           4.6         3.1          1.5         0.2  setosa
+#> 5           5.0         3.6          1.4         0.2  setosa
+#> 6           5.4         3.9          1.7         0.4  setosa
+#> 7           4.6         3.4          1.4         0.3  setosa
+#> 8           5.0         3.4          1.5         0.2  setosa
+#> 9           4.4         2.9          1.4         0.2  setosa
+#> 10          4.9         3.1          1.5         0.1  setosa
+#> # ... with 140 more rows
iris %>% as_tibble() %>% mutate_if(is.double, as.integer)
#> # A tibble: 150 × 5
+#>    Sepal.Length Sepal.Width Petal.Length Petal.Width Species
+#>           <int>       <int>        <int>       <int>  <fctr>
+#> 1             5           3            1           0  setosa
+#> 2             4           3            1           0  setosa
+#> 3             4           3            1           0  setosa
+#> 4             4           3            1           0  setosa
+#> 5             5           3            1           0  setosa
+#> 6             5           3            1           0  setosa
+#> 7             4           3            1           0  setosa
+#> 8             5           3            1           0  setosa
+#> 9             4           2            1           0  setosa
+#> 10            4           3            1           0  setosa
+#> # ... with 140 more rows

+# ---------------------------------------------------------------------------
+# If you want apply multiple transformations, use funs()
+by_species <- iris %>% group_by(Species)
+
+by_species %>% summarise_all(funs(min, max))
#> # A tibble: 3 × 9
+#>      Species Sepal.Length_min Sepal.Width_min Petal.Length_min Petal.Width_min
+#>       <fctr>            <dbl>           <dbl>            <dbl>           <dbl>
+#> 1     setosa              4.3             2.3              1.0             0.1
+#> 2 versicolor              4.9             2.0              3.0             1.0
+#> 3  virginica              4.9             2.2              4.5             1.4
+#> # ... with 4 more variables: Sepal.Length_max <dbl>, Sepal.Width_max <dbl>,
+#> #   Petal.Length_max <dbl>, Petal.Width_max <dbl>
# Note that output variable name now includes the function name, in order to
+# keep things distinct.
+
+# You can express more complex inline transformations using .
+by_species %>% mutate_all(funs(. / 2.54))
#> Source: local data frame [150 x 5]
+#> Groups: Species [3]
+#> 
+#>    Sepal.Length Sepal.Width Petal.Length Petal.Width Species
+#>           <dbl>       <dbl>        <dbl>       <dbl>  <fctr>
+#> 1      2.007874    1.377953    0.5511811  0.07874016  setosa
+#> 2      1.929134    1.181102    0.5511811  0.07874016  setosa
+#> 3      1.850394    1.259843    0.5118110  0.07874016  setosa
+#> 4      1.811024    1.220472    0.5905512  0.07874016  setosa
+#> 5      1.968504    1.417323    0.5511811  0.07874016  setosa
+#> 6      2.125984    1.535433    0.6692913  0.15748031  setosa
+#> 7      1.811024    1.338583    0.5511811  0.11811024  setosa
+#> 8      1.968504    1.338583    0.5905512  0.07874016  setosa
+#> 9      1.732283    1.141732    0.5511811  0.07874016  setosa
+#> 10     1.929134    1.220472    0.5905512  0.03937008  setosa
+#> # ... with 140 more rows

+# Function names will be included if .funs has names or multiple inputs
+by_species %>% mutate_all(funs(cm = . / 2.54))
#> Source: local data frame [150 x 9]
+#> Groups: Species [3]
+#> 
+#>    Sepal.Length Sepal.Width Petal.Length Petal.Width Species Sepal.Length_cm
+#>           <dbl>       <dbl>        <dbl>       <dbl>  <fctr>           <dbl>
+#> 1           5.1         3.5          1.4         0.2  setosa        2.007874
+#> 2           4.9         3.0          1.4         0.2  setosa        1.929134
+#> 3           4.7         3.2          1.3         0.2  setosa        1.850394
+#> 4           4.6         3.1          1.5         0.2  setosa        1.811024
+#> 5           5.0         3.6          1.4         0.2  setosa        1.968504
+#> 6           5.4         3.9          1.7         0.4  setosa        2.125984
+#> 7           4.6         3.4          1.4         0.3  setosa        1.811024
+#> 8           5.0         3.4          1.5         0.2  setosa        1.968504
+#> 9           4.4         2.9          1.4         0.2  setosa        1.732283
+#> 10          4.9         3.1          1.5         0.1  setosa        1.929134
+#> # ... with 140 more rows, and 3 more variables: Sepal.Width_cm <dbl>,
+#> #   Petal.Length_cm <dbl>, Petal.Width_cm <dbl>
by_species %>% summarise_all(funs(med = median))
#> # A tibble: 3 × 5
+#>      Species Sepal.Length_med Sepal.Width_med Petal.Length_med Petal.Width_med
+#>       <fctr>            <dbl>           <dbl>            <dbl>           <dbl>
+#> 1     setosa              5.0             3.4             1.50             0.2
+#> 2 versicolor              5.9             2.8             4.35             1.3
+#> 3  virginica              6.5             3.0             5.55             2.0
by_species %>% summarise_all(funs(Q3 = quantile), probs = 0.75)
#> # A tibble: 3 × 5
+#>      Species Sepal.Length_Q3 Sepal.Width_Q3 Petal.Length_Q3 Petal.Width_Q3
+#>       <fctr>           <dbl>          <dbl>           <dbl>          <dbl>
+#> 1     setosa             5.2          3.675           1.575            0.3
+#> 2 versicolor             6.3          3.000           4.600            1.5
+#> 3  virginica             6.9          3.175           5.875            2.3
by_species %>% summarise_all(c("min", "max"))
#> # A tibble: 3 × 9
+#>      Species Sepal.Length_min Sepal.Width_min Petal.Length_min Petal.Width_min
+#>       <fctr>            <dbl>           <dbl>            <dbl>           <dbl>
+#> 1     setosa              4.3             2.3              1.0             0.1
+#> 2 versicolor              4.9             2.0              3.0             1.0
+#> 3  virginica              4.9             2.2              4.5             1.4
+#> # ... with 4 more variables: Sepal.Length_max <dbl>, Sepal.Width_max <dbl>,
+#> #   Petal.Length_max <dbl>, Petal.Width_max <dbl>
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/summarise_each.html b/docs/reference/summarise_each.html new file mode 100644 index 0000000000..7e506f524b --- /dev/null +++ b/docs/reference/summarise_each.html @@ -0,0 +1,139 @@ + + + + + + + + +Summarise and mutate multiple columns. — summarise_each • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Summarise and mutate multiple columns.

+
+ + +

mutate_each() and summarise_each() are deprecated in favour of +a more featureful family of functions: mutate_all(), +mutate_at(), mutate_if(), summarise_all(), summarise_at() +and summarise_if().

+ + + 
summarise_each(tbl, funs, ...)
+
+summarise_each_(tbl, funs, vars)
+
+mutate_each(tbl, funs, ...)
+
+mutate_each_(tbl, funs, vars)
+
+summarise_each_q(...)
+
+mutate_each_q(...)
+
+summarize_each(tbl, funs, ...)
+
+summarize_each_(tbl, funs, vars)
+ + +
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/tally.html b/docs/reference/tally.html new file mode 100644 index 0000000000..64b21f2544 --- /dev/null +++ b/docs/reference/tally.html @@ -0,0 +1,275 @@ + + + + + + + + +Counts/tally observations by group. — tally • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Counts/tally observations by group.

+
+ + +

tally() is a convenient wrapper for summarise that will either call +n() or sum(n) depending on whether you're tallying +for the first time, or re-tallying. count() is similar, but also +does the group_by() for you. + + add_tally() adds a column "n" to a table based on the number +of items within each existing group, while add_count() is a shortcut that +does the grouping as well. These functions are to tally() +and count() as mutate() is to summarise(): +they add an additional column rather than collapsing each group.

+ + + 
tally(x, wt, sort = FALSE)
+
+count(x, ..., wt = NULL, sort = FALSE)
+
+add_tally(x, wt, sort = FALSE)
+
+add_count(x, ..., wt = NULL, sort = FALSE)
+ +

Arguments

+ + + + + + + + + + + + + + + + + + +
x

a tbl() to tally/count.

wt

(Optional) If omitted, will count the number of rows. If +specified, will perform a "weighted" tally by summing the +(non-missing) values of variable wt. This argument is +automatically quoted and later +evaluated in the context of the data +frame. It supports unquoting. See +vignette("programming") for an introduction to these concepts.

sort

if TRUE will sort output in descending order of n

...

Variables to group by.

+ +

Value

+ +

A tbl, grouped the same way as x.

+ +

Note

+ +

The column name in the returned data is usually n, even if you +have supplied a weight.

+

If the data already already has a column named n, the output column +will be called nn. If the table already has columns called n and nn +then the column returned will be nnn, and so on.

+

There is currently no way to control the output variable name - if you +need to change the default, you'll have to write the summarise() +yourself.

+ + +

Examples

+ 
# tally() is short-hand for mutate()
+mtcars %>% tally()
#>    n
+#> 1 32
# count() is a short-hand for group_by() + tally()
+mtcars %>% count(cyl)
#> # A tibble: 3 × 2
+#>     cyl     n
+#>   <dbl> <int>
+#> 1     4    11
+#> 2     6     7
+#> 3     8    14

+# add_tally() is short-hand for mutate()
+mtcars %>% add_tally()
#> # A tibble: 32 × 12
+#>      mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb     n
+#>    <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <int>
+#> 1   21.0     6 160.0   110  3.90 2.620 16.46     0     1     4     4    32
+#> 2   21.0     6 160.0   110  3.90 2.875 17.02     0     1     4     4    32
+#> 3   22.8     4 108.0    93  3.85 2.320 18.61     1     1     4     1    32
+#> 4   21.4     6 258.0   110  3.08 3.215 19.44     1     0     3     1    32
+#> 5   18.7     8 360.0   175  3.15 3.440 17.02     0     0     3     2    32
+#> 6   18.1     6 225.0   105  2.76 3.460 20.22     1     0     3     1    32
+#> 7   14.3     8 360.0   245  3.21 3.570 15.84     0     0     3     4    32
+#> 8   24.4     4 146.7    62  3.69 3.190 20.00     1     0     4     2    32
+#> 9   22.8     4 140.8    95  3.92 3.150 22.90     1     0     4     2    32
+#> 10  19.2     6 167.6   123  3.92 3.440 18.30     1     0     4     4    32
+#> # ... with 22 more rows
# add_count() is a short-hand for group_by() + add_tally()
+mtcars %>% add_count(cyl)
#> # A tibble: 32 × 12
+#>      mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb     n
+#>    <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <int>
+#> 1   21.0     6 160.0   110  3.90 2.620 16.46     0     1     4     4     7
+#> 2   21.0     6 160.0   110  3.90 2.875 17.02     0     1     4     4     7
+#> 3   22.8     4 108.0    93  3.85 2.320 18.61     1     1     4     1    11
+#> 4   21.4     6 258.0   110  3.08 3.215 19.44     1     0     3     1     7
+#> 5   18.7     8 360.0   175  3.15 3.440 17.02     0     0     3     2    14
+#> 6   18.1     6 225.0   105  2.76 3.460 20.22     1     0     3     1     7
+#> 7   14.3     8 360.0   245  3.21 3.570 15.84     0     0     3     4    14
+#> 8   24.4     4 146.7    62  3.69 3.190 20.00     1     0     4     2    11
+#> 9   22.8     4 140.8    95  3.92 3.150 22.90     1     0     4     2    11
+#> 10  19.2     6 167.6   123  3.92 3.440 18.30     1     0     4     4     7
+#> # ... with 22 more rows

+# count and tally are designed so that you can call
+# them repeatedly, each time rolling up a level of detail
+species <- starwars %>% count(species, homeworld, sort = TRUE)
+species
#> # A tibble: 58 × 3
+#>     species homeworld     n
+#>       <chr>     <chr> <int>
+#> 1     Human  Tatooine     8
+#> 2     Human     Naboo     5
+#> 3     Human      <NA>     5
+#> 4    Gungan     Naboo     3
+#> 5     Human  Alderaan     3
+#> 6     Droid  Tatooine     2
+#> 7     Droid      <NA>     2
+#> 8     Human  Corellia     2
+#> 9     Human Coruscant     2
+#> 10 Kaminoan    Kamino     2
+#> # ... with 48 more rows
species %>% count(species, sort = TRUE)
#> # A tibble: 38 × 2
+#>     species    nn
+#>       <chr> <int>
+#> 1     Human    16
+#> 2     Droid     3
+#> 3      <NA>     3
+#> 4    Zabrak     2
+#> 5    Aleena     1
+#> 6  Besalisk     1
+#> 7    Cerean     1
+#> 8  Chagrian     1
+#> 9  Clawdite     1
+#> 10      Dug     1
+#> # ... with 28 more rows

+# add_count() is useful for groupwise filtering
+# e.g.: show only species that have a single member
+starwars %>%
+  add_count(species) %>%
+  filter(n == 1)
#> # A tibble: 29 × 14
+#>                     name height  mass hair_color       skin_color eye_color
+#>                    <chr>  <int> <dbl>      <chr>            <chr>     <chr>
+#> 1                 Greedo    173    74       <NA>            green     black
+#> 2  Jabba Desilijic Tiure    175  1358       <NA> green-tan, brown    orange
+#> 3                   Yoda     66    17      white            green     brown
+#> 4                  Bossk    190   113       none            green       red
+#> 5                 Ackbar    180    83       none     brown mottle    orange
+#> 6  Wicket Systri Warrick     88    20      brown            brown     brown
+#> 7              Nien Nunb    160    68       none             grey     black
+#> 8            Nute Gunray    191    90       none    mottled green       red
+#> 9                  Watto    137    NA      black       blue, grey    yellow
+#> 10               Sebulba    112    40       none        grey, red    orange
+#> # ... with 19 more rows, and 8 more variables: birth_year <dbl>, gender <chr>,
+#> #   homeworld <chr>, species <chr>, films <list>, vehicles <list>,
+#> #   starships <list>, n <int>
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/tbl.html b/docs/reference/tbl.html new file mode 100644 index 0000000000..97b067dd80 --- /dev/null +++ b/docs/reference/tbl.html @@ -0,0 +1,144 @@ + + + + + + + + +Create a table from a data source — tbl • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Create a table from a data source

+
+ + +

This is a generic method that dispatches based on the first argument.

+ + + 
tbl(src, ...)
+
+is.tbl(x)
+
+as.tbl(x, ...)
+ +

Arguments

+ + + + + + + + + + + + + + +
src

A data source

...

Other arguments passed on to the individual methods

x

an object to coerce to a tbl

+ + +
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/tbl_cube.html b/docs/reference/tbl_cube.html new file mode 100644 index 0000000000..88ae81883b --- /dev/null +++ b/docs/reference/tbl_cube.html @@ -0,0 +1,282 @@ + + + + + + + + +A data cube tbl. — tbl_cube • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

A data cube tbl.

+
+ + +

A cube tbl stores data in a compact array format where dimension +names are not needlessly repeated. They are particularly appropriate for +experimental data where all combinations of factors are tried (e.g. +complete factorial designs), or for storing the result of aggregations. +Compared to data frames, they will occupy much less memory when variables +are crossed, not nested.

+ + + 
tbl_cube(dimensions, measures)
+ +

Arguments

+ + + + + + + + + + +
dimensions

A named list of vectors. A dimension is a variable +whose values are known before the experiement is conducted; they are +fixed by design (in reshape2 they are known as id variables). +tbl_cubes are dense which means that almost every combination of +the dimensions should have associated measurements: missing values require +an explicit NA, so if the variables are nested, not crossed, the +majority of the data structure will be empty. Dimensions are typically, +but not always, categorical variables.

measures

A named list of arrays. A measure is something that is +actually measured, and is not known in advance. The dimension of each +array should be the same as the length of the dimensions. Measures are +typically, but not always, continuous values.

+ +

Details

+ +

tbl_cube support is currently experimental and little performance +optimisation has been done, but you may find them useful if your data +already comes in this form, or you struggle with the memory overhead of the +sparse/crossed of data frames. There is no support for hierarchical +indices (although I think that would be a relatively straightforward +extension to storing data frames for indices rather than vectors).

+ +

Implementation

+ + +

Manipulation functions:

    +

  • select() (M)

    • +

  • summarise() (M), corresponds to roll-up, but rather more +limited since there are no hierarchies.

    • +

  • filter() (D), corresponds to slice/dice.

    • +

  • mutate() (M) is not implemented, but should be relatively +straightforward given the implementation of summarise.

    • +

  • arrange() (D?) Not implemented: not obvious how much sense +it would make

    • +
+

Joins: not implemented. See vignettes/joins.graffle for ideas. +Probably straightforward if you get the indexes right, and that's probably +some straightforward array/tensor operation.

+ +

See also

+ +

as.tbl_cube() for ways of coercing existing data +structures into a tbl_cube.

+ + +

Examples

+ 
# The built in nasa dataset records meterological data (temperature,
+# cloud cover, ozone etc) for a 4d spatio-temporal dataset (lat, long,
+# month and year)
+nasa
#> Source: local array [41,472 x 4]
+#> D: lat [dbl, 24]
+#> D: long [dbl, 24]
+#> D: month [int, 12]
+#> D: year [int, 6]
+#> M: cloudhigh [dbl]
+#> M: cloudlow [dbl]
+#> M: cloudmid [dbl]
+#> M: ozone [dbl]
+#> M: pressure [dbl]
+#> M: surftemp [dbl]
+#> M: temperature [dbl]
head(as.data.frame(nasa))
#>        lat   long month year cloudhigh cloudlow cloudmid ozone pressure
+#> 1 36.20000 -113.8     1 1995      26.0      7.5     34.5   304      835
+#> 2 33.70435 -113.8     1 1995      20.0     11.5     32.5   304      940
+#> 3 31.20870 -113.8     1 1995      16.0     16.5     26.0   298      960
+#> 4 28.71304 -113.8     1 1995      13.0     20.5     14.5   276      990
+#> 5 26.21739 -113.8     1 1995       7.5     26.0     10.5   274     1000
+#> 6 23.72174 -113.8     1 1995       8.0     30.0      9.5   264     1000
+#>   surftemp temperature
+#> 1    272.7       272.1
+#> 2    279.5       282.2
+#> 3    284.7       285.2
+#> 4    289.3       290.7
+#> 5    292.2       292.7
+#> 6    294.1       293.6

+titanic <- as.tbl_cube(Titanic)
+head(as.data.frame(titanic))
#>   Class    Sex   Age Survived Freq
+#> 1   1st   Male Child       No    0
+#> 2   2nd   Male Child       No    0
+#> 3   3rd   Male Child       No   35
+#> 4  Crew   Male Child       No    0
+#> 5   1st Female Child       No    0
+#> 6   2nd Female Child       No    0

+admit <- as.tbl_cube(UCBAdmissions)
+head(as.data.frame(admit))
#>      Admit Gender Dept Freq
+#> 1 Admitted   Male    A  512
+#> 2 Rejected   Male    A  313
+#> 3 Admitted Female    A   89
+#> 4 Rejected Female    A   19
+#> 5 Admitted   Male    B  353
+#> 6 Rejected   Male    B  207

+as.tbl_cube(esoph, dim_names = 1:3)
#> Source: local array [96 x 3]
+#> D: agegp [ord, 6]
+#> D: alcgp [ord, 4]
+#> D: tobgp [ord, 4]
+#> M: ncases [dbl]
+#> M: ncontrols [dbl]

+# Some manipulation examples with the NASA dataset --------------------------
+
+# select() operates only on measures: it doesn't affect dimensions in any way
+select(nasa, cloudhigh:cloudmid)
#> Source: local array [41,472 x 4]
+#> D: lat [dbl, 24]
+#> D: long [dbl, 24]
+#> D: month [int, 12]
+#> D: year [int, 6]
+#> M: cloudhigh [dbl]
+#> M: cloudlow [dbl]
+#> M: cloudmid [dbl]
select(nasa, matches("temp"))
#> Source: local array [41,472 x 4]
+#> D: lat [dbl, 24]
+#> D: long [dbl, 24]
+#> D: month [int, 12]
+#> D: year [int, 6]
+#> M: surftemp [dbl]
+#> M: temperature [dbl]

+# filter() operates only on dimensions
+filter(nasa, lat > 0, year == 2000)
#> Source: local array [4,320 x 4]
+#> D: lat [dbl, 15]
+#> D: long [dbl, 24]
+#> D: month [int, 12]
+#> D: year [int, 1]
+#> M: cloudhigh [dbl]
+#> M: cloudlow [dbl]
+#> M: cloudmid [dbl]
+#> M: ozone [dbl]
+#> M: pressure [dbl]
+#> M: surftemp [dbl]
+#> M: temperature [dbl]
# Each component can only refer to one dimensions, ensuring that you always
+# create a rectangular subset
+## Not run: filter(nasa, lat &gt; long)
+
+# Arrange is meaningless for tbl_cubes
+
+by_loc <- group_by(nasa, lat, long)
+summarise(by_loc, pressure = max(pressure), temp = mean(temperature))
#> Source: local array [576 x 2]
+#> D: lat [dbl, 24]
+#> D: long [dbl, 24]
+#> M: pressure [dbl]
+#> M: temp [dbl]
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/tbl_df.html b/docs/reference/tbl_df.html new file mode 100644 index 0000000000..39faac77a8 --- /dev/null +++ b/docs/reference/tbl_df.html @@ -0,0 +1,132 @@ + + + + + + + + +Create a data frame tbl. — tbl_df • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Create a data frame tbl.

+
+ + +

Deprecated: please use tibble::as_tibble() instead.

+ + + 
tbl_df(data)
+ +

Arguments

+ + + + + + +
data

a data frame

+ + +
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/tbl_vars.html b/docs/reference/tbl_vars.html new file mode 100644 index 0000000000..67178be0c2 --- /dev/null +++ b/docs/reference/tbl_vars.html @@ -0,0 +1,142 @@ + + + + + + + + +List variables provided by a tbl. — tbl_vars • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

List variables provided by a tbl.

+
+ + +

tbl_vars() returns all variables while tbl_nongroup_vars() +returns only non-grouping variables.

+ + + 
tbl_vars(x)
+
+tbl_nongroup_vars(x)
+ +

Arguments

+ + + + + + +
x

A tbl object

+ +

See also

+ +

group_vars() for a function that returns grouping +variables.

+ + +
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/top_n.html b/docs/reference/top_n.html new file mode 100644 index 0000000000..650e047684 --- /dev/null +++ b/docs/reference/top_n.html @@ -0,0 +1,193 @@ + + + + + + + + +Select top (or bottom) n rows (by value). — top_n • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Select top (or bottom) n rows (by value).

+
+ + +

This is a convenient wrapper that uses filter() and +min_rank() to select the top or bottom entries in each group, +ordered by wt.

+ + + 
top_n(x, n, wt)
+ +

Arguments

+ + + + + + + + + + + + + + +
x

a tbl() to filter

n

number of rows to return. If x is grouped, this is the +number of rows per group. Will include more than n rows if +there are ties.

+

If n is positive, selects the top n rows. If negative, +selects the bottom n rows.

wt

(Optional). The variable to use for ordering. If not +specified, defaults to the last variable in the tbl.

+

This argument is automatically quoted and later +evaluated in the context of the data +frame. It supports unquoting. See +vignette("programming") for an introduction to these concepts.

+ + +

Examples

+ 
df <- data.frame(x = c(10, 4, 1, 6, 3, 1, 1))
+df %>% top_n(2)
#> Selecting by x
#>    x
+#> 1 10
+#> 2  6

+# Negative values select bottom from group. Note that we get more
+# than 2 values here because there's a tie: top_n() either takes
+# all rows with a value, or none.
+df %>% top_n(-2)
#> Selecting by x
#>   x
+#> 1 1
+#> 2 1
+#> 3 1

+if (require("Lahman")) {
+# Find 10 players with most games
+# A little nicer with %>%
+tbl_df(Batting) %>%
+  group_by(playerID) %>%
+  tally(G) %>%
+  top_n(10)
+
+# Find year with most games for each player
+tbl_df(Batting) %>% group_by(playerID) %>% top_n(1, G)
+}
#> Selecting by n
#> Source: local data frame [19,516 x 22]
+#> Groups: playerID [18,659]
+#> 
+#>     playerID yearID stint teamID   lgID     G    AB     R     H   X2B   X3B
+#>        <chr>  <int> <int> <fctr> <fctr> <int> <int> <int> <int> <int> <int>
+#> 1  abercda01   1871     1    TRO     NA     1     4     0     0     0     0
+#> 2  armstbo01   1871     1    FW1     NA    12    49     9    11     2     1
+#> 3  barkeal01   1871     1    RC1     NA     1     4     0     1     0     0
+#> 4  barrebi01   1871     1    FW1     NA     1     5     1     1     1     0
+#> 5  barrofr01   1871     1    BS1     NA    18    86    13    13     2     1
+#> 6   bassjo01   1871     1    CL1     NA    22    89    18    27     1    10
+#> 7  bellast01   1871     1    TRO     NA    29   128    26    32     3     3
+#> 8  berkena01   1871     1    PH1     NA     1     4     0     0     0     0
+#> 9  berryto01   1871     1    PH1     NA     1     4     0     1     0     0
+#> 10 berthha01   1871     1    WS3     NA    17    73    17    17     1     1
+#> # ... with 19,506 more rows, and 11 more variables: HR <int>, RBI <int>,
+#> #   SB <int>, CS <int>, BB <int>, SO <int>, IBB <int>, HBP <int>, SH <int>,
+#> #   SF <int>, GIDP <int>
+
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/vars.html b/docs/reference/vars.html new file mode 100644 index 0000000000..101f9975c4 --- /dev/null +++ b/docs/reference/vars.html @@ -0,0 +1,155 @@ + + + + + + + + +Select variables. — vars • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Select variables.

+
+ + +

This helper is intended to provide equivalent semantics to +select(). It is used for instance in scoped summarising and +mutating verbs (mutate_at() and summarise_at()).

+ + + 
vars(...)
+ +

Arguments

+ + + + + + +
...

Variables to include/exclude in mutate/summarise. You +can use same specifications as in select(). If missing, +defaults to all non-grouping variables.

+

These arguments are automatically quoted and later +evaluated in the context of the data +frame. They support unquoting. See +vignette("programming") for an introduction to these concepts.

+ +

Details

+ +

Note that verbs accepting a vars() specification also accept an +integerish vector of positions or a +character vector of column names.

+ +

See also

+ +

funs(), all_vars() and any_vars() for other quoting +functions that you can use with scoped verbs.

+ + +
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/reference/with_order.html b/docs/reference/with_order.html new file mode 100644 index 0000000000..6444b448d3 --- /dev/null +++ b/docs/reference/with_order.html @@ -0,0 +1,140 @@ + + + + + + + + +Run a function with one order, translating result back to original order — with_order • dplyr + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Run a function with one order, translating result back to original order

+
+ + +

This is used to power the ordering parameters of dplyr's window functions

+ + + 
with_order(order_by, fun, x, ...)
+ +

Arguments

+ + + + + + + + + + + + + + +
order_by

vector to order by

fun

window function

x, ...

arguments to f

+ + +
+ +
+ +
+
+

dplyr is a part of the tidyverse, an ecosystem of packages designed with common APIs and a shared philosophy. Learn more at tidyverse.org.

+
+ +
+

Developed by Hadley Wickham, Romain Francois, .

+

Site built by pkgdown.

+
+ + +
+
+ + + diff --git a/docs/tidyverse.css b/docs/tidyverse.css new file mode 100644 index 0000000000..1e691967a0 --- /dev/null +++ b/docs/tidyverse.css @@ -0,0 +1,6496 @@ +@charset "UTF-8"; +/*! + * Bootstrap v3.3.7 (http://getbootstrap.com) + * Copyright 2011-2016 Twitter, Inc. + * Licensed under MIT (https://github.com/twbs/bootstrap/blob/master/LICENSE) + */ +/*! normalize.css v3.0.3 | MIT License | github.com/necolas/normalize.css */ +@import url("https://fonts.googleapis.com/css?family=Source+Code+Pro:300,400,700|Source+Sans+Pro:300,400,700"); +html { + font-family: sans-serif; + -ms-text-size-adjust: 100%; + -webkit-text-size-adjust: 100%; } + +body { + margin: 0; } + +article, +aside, +details, +figcaption, +figure, +footer, +header, +hgroup, +main, +menu, +nav, +section, +summary { + display: block; } + +audio, +canvas, +progress, +video { + display: inline-block; + vertical-align: baseline; } + +audio:not([controls]) { + display: none; + height: 0; } + +[hidden], +template { + display: none; } + +a { + background-color: transparent; } + +a:active, +a:hover { + outline: 0; } + +abbr[title] { + border-bottom: 1px dotted; } + +b, +strong { + font-weight: bold; } + +dfn { + font-style: italic; } + +h1 { + font-size: 2em; + margin: 0.67em 0; } + +mark { + background: #ff0; + color: #000; } + +small { + font-size: 80%; } + +sub, +sup { + font-size: 75%; + line-height: 0; + position: relative; + vertical-align: baseline; } + +sup { + top: -0.5em; } + +sub { + bottom: -0.25em; } + +img { + border: 0; } + +svg:not(:root) { + overflow: hidden; } + +figure { + margin: 1em 40px; } + +hr { + box-sizing: content-box; + height: 0; } + +pre { + overflow: auto; } + +code, +kbd, +pre, +samp { + font-family: monospace, monospace; + font-size: 1em; } + +button, +input, +optgroup, +select, +textarea { + color: inherit; + font: inherit; + margin: 0; } + +button { + overflow: visible; } + +button, +select { + text-transform: none; } + +button, +html input[type="button"], +input[type="reset"], +input[type="submit"] { + -webkit-appearance: button; + cursor: pointer; } + +button[disabled], +html input[disabled] { + cursor: default; } + +button::-moz-focus-inner, +input::-moz-focus-inner { + border: 0; + padding: 0; } + +input { + line-height: normal; } + +input[type="checkbox"], +input[type="radio"] { + box-sizing: border-box; + padding: 0; } + +input[type="number"]::-webkit-inner-spin-button, +input[type="number"]::-webkit-outer-spin-button { + height: auto; } + +input[type="search"] { + -webkit-appearance: textfield; + box-sizing: content-box; } + +input[type="search"]::-webkit-search-cancel-button, +input[type="search"]::-webkit-search-decoration { + -webkit-appearance: none; } + +fieldset { + border: 1px solid #c0c0c0; + margin: 0 2px; + padding: 0.35em 0.625em 0.75em; } + +legend { + border: 0; + padding: 0; } + +textarea { + overflow: auto; } + +optgroup { + font-weight: bold; } + +table { + border-collapse: collapse; + border-spacing: 0; } + +td, +th { + padding: 0; } + +/*! Source: https://github.com/h5bp/html5-boilerplate/blob/master/src/css/main.css */ +@media print { + *, + *:before, + *:after { + background: transparent !important; + color: #000 !important; + box-shadow: none !important; + text-shadow: none !important; } + + a, + a:visited { + text-decoration: underline; } + + a[href]:after { + content: " (" attr(href) ")"; } + + abbr[title]:after { + content: " (" attr(title) ")"; } + + a[href^="#"]:after, + a[href^="javascript:"]:after { + content: ""; } + + pre, + blockquote { + border: 1px solid #999; + page-break-inside: avoid; } + + thead { + display: table-header-group; } + + tr, + img { + page-break-inside: avoid; } + + img { + max-width: 100% !important; } + + p, + h2, + h3 { + orphans: 3; + widows: 3; } + + h2, + h3 { + page-break-after: avoid; } + + .navbar { + display: none; } + + .btn > .caret, + .dropup > .btn > .caret { + border-top-color: #000 !important; } + + .label { + border: 1px solid #000; } + + .table { + border-collapse: collapse !important; } + .table td, + .table th { + background-color: #fff !important; } + + .table-bordered th, + .table-bordered td { + border: 1px solid #ddd !important; } } +@font-face { + font-family: 'Glyphicons Halflings'; + src: url("../fonts/bootstrap/glyphicons-halflings-regular.eot"); + src: url("../fonts/bootstrap/glyphicons-halflings-regular.eot?#iefix") format("embedded-opentype"), url("../fonts/bootstrap/glyphicons-halflings-regular.woff2") format("woff2"), url("../fonts/bootstrap/glyphicons-halflings-regular.woff") format("woff"), url("../fonts/bootstrap/glyphicons-halflings-regular.ttf") format("truetype"), url("../fonts/bootstrap/glyphicons-halflings-regular.svg#glyphicons_halflingsregular") format("svg"); } +.glyphicon { + position: relative; + top: 1px; + display: inline-block; + font-family: 'Glyphicons Halflings'; + font-style: normal; + font-weight: normal; + line-height: 1; + -webkit-font-smoothing: antialiased; + -moz-osx-font-smoothing: grayscale; } + +.glyphicon-asterisk:before { + content: "\002a"; } + +.glyphicon-plus:before { + content: "\002b"; } + +.glyphicon-euro:before, +.glyphicon-eur:before { + content: "\20ac"; } + +.glyphicon-minus:before { + content: "\2212"; } + +.glyphicon-cloud:before { + content: "\2601"; } + +.glyphicon-envelope:before { + content: "\2709"; } + +.glyphicon-pencil:before { + content: "\270f"; } + +.glyphicon-glass:before { + content: "\e001"; } + +.glyphicon-music:before { + content: "\e002"; } + +.glyphicon-search:before { + content: "\e003"; } + +.glyphicon-heart:before { + content: "\e005"; } + +.glyphicon-star:before { + content: "\e006"; } + +.glyphicon-star-empty:before { + content: "\e007"; } + +.glyphicon-user:before { + content: "\e008"; } + +.glyphicon-film:before { + content: "\e009"; } + +.glyphicon-th-large:before { + content: "\e010"; } + +.glyphicon-th:before { + content: "\e011"; } + +.glyphicon-th-list:before { + content: "\e012"; } + +.glyphicon-ok:before { + content: "\e013"; } + +.glyphicon-remove:before { + content: "\e014"; } + +.glyphicon-zoom-in:before { + content: "\e015"; } + +.glyphicon-zoom-out:before { + content: "\e016"; } + +.glyphicon-off:before { + content: "\e017"; } + +.glyphicon-signal:before { + content: "\e018"; } + +.glyphicon-cog:before { + content: "\e019"; } + +.glyphicon-trash:before { + content: "\e020"; } + +.glyphicon-home:before { + content: "\e021"; } + +.glyphicon-file:before { + content: "\e022"; } + +.glyphicon-time:before { + content: "\e023"; } + +.glyphicon-road:before { + content: "\e024"; } + +.glyphicon-download-alt:before { + content: "\e025"; } + +.glyphicon-download:before { + content: "\e026"; } + +.glyphicon-upload:before { + content: "\e027"; } + +.glyphicon-inbox:before { + content: "\e028"; } + +.glyphicon-play-circle:before { + content: "\e029"; } + +.glyphicon-repeat:before { + content: "\e030"; } + +.glyphicon-refresh:before { + content: "\e031"; } + +.glyphicon-list-alt:before { + content: "\e032"; } + +.glyphicon-lock:before { + content: "\e033"; } + +.glyphicon-flag:before { + content: "\e034"; } + +.glyphicon-headphones:before { + content: "\e035"; } + +.glyphicon-volume-off:before { + content: "\e036"; } + +.glyphicon-volume-down:before { + content: "\e037"; } + +.glyphicon-volume-up:before { + content: "\e038"; } + +.glyphicon-qrcode:before { + content: "\e039"; } + +.glyphicon-barcode:before { + content: "\e040"; } + +.glyphicon-tag:before { + content: "\e041"; } + +.glyphicon-tags:before { + content: "\e042"; } + +.glyphicon-book:before { + content: "\e043"; } + +.glyphicon-bookmark:before { + content: "\e044"; } + +.glyphicon-print:before { + content: "\e045"; } + +.glyphicon-camera:before { + content: "\e046"; } + +.glyphicon-font:before { + content: "\e047"; } + +.glyphicon-bold:before { + content: "\e048"; } + +.glyphicon-italic:before { + content: "\e049"; } + +.glyphicon-text-height:before { + content: "\e050"; } + +.glyphicon-text-width:before { + content: "\e051"; } + +.glyphicon-align-left:before { + content: "\e052"; } + +.glyphicon-align-center:before { + content: "\e053"; } + +.glyphicon-align-right:before { + content: "\e054"; } + +.glyphicon-align-justify:before { + content: "\e055"; } + +.glyphicon-list:before { + content: "\e056"; } + +.glyphicon-indent-left:before { + content: "\e057"; } + +.glyphicon-indent-right:before { + content: "\e058"; } + +.glyphicon-facetime-video:before { + content: "\e059"; } + +.glyphicon-picture:before { + content: "\e060"; } + +.glyphicon-map-marker:before { + content: "\e062"; } + +.glyphicon-adjust:before { + content: "\e063"; } + +.glyphicon-tint:before { + content: "\e064"; } + +.glyphicon-edit:before { + content: "\e065"; } + +.glyphicon-share:before { + content: "\e066"; } + +.glyphicon-check:before { + content: "\e067"; } + +.glyphicon-move:before { + content: "\e068"; } + +.glyphicon-step-backward:before { + content: "\e069"; } + +.glyphicon-fast-backward:before { + content: "\e070"; } + +.glyphicon-backward:before { + content: "\e071"; } + +.glyphicon-play:before { + content: "\e072"; } + +.glyphicon-pause:before { + content: "\e073"; } + +.glyphicon-stop:before { + content: "\e074"; } + +.glyphicon-forward:before { + content: "\e075"; } + +.glyphicon-fast-forward:before { + content: "\e076"; } + +.glyphicon-step-forward:before { + content: "\e077"; } + +.glyphicon-eject:before { + content: "\e078"; } + +.glyphicon-chevron-left:before { + content: "\e079"; } + +.glyphicon-chevron-right:before { + content: "\e080"; } + +.glyphicon-plus-sign:before { + content: "\e081"; } + +.glyphicon-minus-sign:before { + content: "\e082"; } + +.glyphicon-remove-sign:before { + content: "\e083"; } + +.glyphicon-ok-sign:before { + content: "\e084"; } + +.glyphicon-question-sign:before { + content: "\e085"; } + +.glyphicon-info-sign:before { + content: "\e086"; } + +.glyphicon-screenshot:before { + content: "\e087"; } + +.glyphicon-remove-circle:before { + content: "\e088"; } + +.glyphicon-ok-circle:before { + content: "\e089"; } + +.glyphicon-ban-circle:before { + content: "\e090"; } + +.glyphicon-arrow-left:before { + content: "\e091"; } + +.glyphicon-arrow-right:before { + content: "\e092"; } + +.glyphicon-arrow-up:before { + content: "\e093"; } + +.glyphicon-arrow-down:before { + content: "\e094"; } + +.glyphicon-share-alt:before { + content: "\e095"; } + +.glyphicon-resize-full:before { + content: "\e096"; } + +.glyphicon-resize-small:before { + content: "\e097"; } + +.glyphicon-exclamation-sign:before { + content: "\e101"; } + +.glyphicon-gift:before { + content: "\e102"; } + +.glyphicon-leaf:before { + content: "\e103"; } + +.glyphicon-fire:before { + content: "\e104"; } + +.glyphicon-eye-open:before { + content: "\e105"; } + +.glyphicon-eye-close:before { + content: "\e106"; } + +.glyphicon-warning-sign:before { + content: "\e107"; } + +.glyphicon-plane:before { + content: "\e108"; } + +.glyphicon-calendar:before { + content: "\e109"; } + +.glyphicon-random:before { + content: "\e110"; } + +.glyphicon-comment:before { + content: "\e111"; } + +.glyphicon-magnet:before { + content: "\e112"; } + +.glyphicon-chevron-up:before { + content: "\e113"; } + +.glyphicon-chevron-down:before { + content: "\e114"; } + +.glyphicon-retweet:before { + content: "\e115"; } + +.glyphicon-shopping-cart:before { + content: "\e116"; } + +.glyphicon-folder-close:before { + content: "\e117"; } + +.glyphicon-folder-open:before { + content: "\e118"; } + +.glyphicon-resize-vertical:before { + content: "\e119"; } + +.glyphicon-resize-horizontal:before { + content: "\e120"; } + +.glyphicon-hdd:before { + content: "\e121"; } + +.glyphicon-bullhorn:before { + content: "\e122"; } + +.glyphicon-bell:before { + content: "\e123"; } + +.glyphicon-certificate:before { + content: "\e124"; } + +.glyphicon-thumbs-up:before { + content: "\e125"; } + +.glyphicon-thumbs-down:before { + content: "\e126"; } + +.glyphicon-hand-right:before { + content: "\e127"; } + +.glyphicon-hand-left:before { + content: "\e128"; } + +.glyphicon-hand-up:before { + content: "\e129"; } + +.glyphicon-hand-down:before { + content: "\e130"; } + +.glyphicon-circle-arrow-right:before { + content: "\e131"; } + +.glyphicon-circle-arrow-left:before { + content: "\e132"; } + +.glyphicon-circle-arrow-up:before { + content: "\e133"; } + +.glyphicon-circle-arrow-down:before { + content: "\e134"; } + +.glyphicon-globe:before { + content: "\e135"; } + +.glyphicon-wrench:before { + content: "\e136"; } + +.glyphicon-tasks:before { + content: "\e137"; } + +.glyphicon-filter:before { + content: "\e138"; } + +.glyphicon-briefcase:before { + content: "\e139"; } + +.glyphicon-fullscreen:before { + content: "\e140"; } + +.glyphicon-dashboard:before { + content: "\e141"; } + +.glyphicon-paperclip:before { + content: "\e142"; } + +.glyphicon-heart-empty:before { + content: "\e143"; } + +.glyphicon-link:before { + content: "\e144"; } + +.glyphicon-phone:before { + content: "\e145"; } + +.glyphicon-pushpin:before { + content: "\e146"; } + +.glyphicon-usd:before { + content: "\e148"; } + +.glyphicon-gbp:before { + content: "\e149"; } + +.glyphicon-sort:before { + content: "\e150"; } + +.glyphicon-sort-by-alphabet:before { + content: "\e151"; } + +.glyphicon-sort-by-alphabet-alt:before { + content: "\e152"; } + +.glyphicon-sort-by-order:before { + content: "\e153"; } + +.glyphicon-sort-by-order-alt:before { + content: "\e154"; } + +.glyphicon-sort-by-attributes:before { + content: "\e155"; } + +.glyphicon-sort-by-attributes-alt:before { + content: "\e156"; } + +.glyphicon-unchecked:before { + content: "\e157"; } + +.glyphicon-expand:before { + content: "\e158"; } + +.glyphicon-collapse-down:before { + content: "\e159"; } + +.glyphicon-collapse-up:before { + content: "\e160"; } + +.glyphicon-log-in:before { + content: "\e161"; } + +.glyphicon-flash:before { + content: "\e162"; } + +.glyphicon-log-out:before { + content: "\e163"; } + +.glyphicon-new-window:before { + content: "\e164"; } + +.glyphicon-record:before { + content: "\e165"; } + +.glyphicon-save:before { + content: "\e166"; } + +.glyphicon-open:before { + content: "\e167"; } + +.glyphicon-saved:before { + content: "\e168"; } + +.glyphicon-import:before { + content: "\e169"; } + +.glyphicon-export:before { + content: "\e170"; } + +.glyphicon-send:before { + content: "\e171"; } + +.glyphicon-floppy-disk:before { + content: "\e172"; } + +.glyphicon-floppy-saved:before { + content: "\e173"; } + +.glyphicon-floppy-remove:before { + content: "\e174"; } + +.glyphicon-floppy-save:before { + content: "\e175"; } + +.glyphicon-floppy-open:before { + content: "\e176"; } + +.glyphicon-credit-card:before { + content: "\e177"; } + +.glyphicon-transfer:before { + content: "\e178"; } + +.glyphicon-cutlery:before { + content: "\e179"; } + +.glyphicon-header:before { + content: "\e180"; } + +.glyphicon-compressed:before { + content: "\e181"; } + +.glyphicon-earphone:before { + content: "\e182"; } + +.glyphicon-phone-alt:before { + content: "\e183"; } + +.glyphicon-tower:before { + content: "\e184"; } + +.glyphicon-stats:before { + content: "\e185"; } + +.glyphicon-sd-video:before { + content: "\e186"; } + +.glyphicon-hd-video:before { + content: "\e187"; } + +.glyphicon-subtitles:before { + content: "\e188"; } + +.glyphicon-sound-stereo:before { + content: "\e189"; } + +.glyphicon-sound-dolby:before { + content: "\e190"; } + +.glyphicon-sound-5-1:before { + content: "\e191"; } + +.glyphicon-sound-6-1:before { + content: "\e192"; } + +.glyphicon-sound-7-1:before { + content: "\e193"; } + +.glyphicon-copyright-mark:before { + content: "\e194"; } + +.glyphicon-registration-mark:before { + content: "\e195"; } + +.glyphicon-cloud-download:before { + content: "\e197"; } + +.glyphicon-cloud-upload:before { + content: "\e198"; } + +.glyphicon-tree-conifer:before { + content: "\e199"; } + +.glyphicon-tree-deciduous:before { + content: "\e200"; } + +.glyphicon-cd:before { + content: "\e201"; } + +.glyphicon-save-file:before { + content: "\e202"; } + +.glyphicon-open-file:before { + content: "\e203"; } + +.glyphicon-level-up:before { + content: "\e204"; } + +.glyphicon-copy:before { + content: "\e205"; } + +.glyphicon-paste:before { + content: "\e206"; } + +.glyphicon-alert:before { + content: "\e209"; } + +.glyphicon-equalizer:before { + content: "\e210"; } + +.glyphicon-king:before { + content: "\e211"; } + +.glyphicon-queen:before { + content: "\e212"; } + +.glyphicon-pawn:before { + content: "\e213"; } + +.glyphicon-bishop:before { + content: "\e214"; } + +.glyphicon-knight:before { + content: "\e215"; } + +.glyphicon-baby-formula:before { + content: "\e216"; } + +.glyphicon-tent:before { + content: "\26fa"; } + +.glyphicon-blackboard:before { + content: "\e218"; } + +.glyphicon-bed:before { + content: "\e219"; } + +.glyphicon-apple:before { + content: "\f8ff"; } + +.glyphicon-erase:before { + content: "\e221"; } + +.glyphicon-hourglass:before { + content: "\231b"; } + +.glyphicon-lamp:before { + content: "\e223"; } + +.glyphicon-duplicate:before { + content: "\e224"; } + +.glyphicon-piggy-bank:before { + content: "\e225"; } + +.glyphicon-scissors:before { + content: "\e226"; } + +.glyphicon-bitcoin:before { + content: "\e227"; } + +.glyphicon-btc:before { + content: "\e227"; } + +.glyphicon-xbt:before { + content: "\e227"; } + +.glyphicon-yen:before { + content: "\00a5"; } + +.glyphicon-jpy:before { + content: "\00a5"; } + +.glyphicon-ruble:before { + content: "\20bd"; } + +.glyphicon-rub:before { + content: "\20bd"; } + +.glyphicon-scale:before { + content: "\e230"; } + +.glyphicon-ice-lolly:before { + content: "\e231"; } + +.glyphicon-ice-lolly-tasted:before { + content: "\e232"; } + +.glyphicon-education:before { + content: "\e233"; } + +.glyphicon-option-horizontal:before { + content: "\e234"; } + +.glyphicon-option-vertical:before { + content: "\e235"; } + +.glyphicon-menu-hamburger:before { + content: "\e236"; } + +.glyphicon-modal-window:before { + content: "\e237"; } + +.glyphicon-oil:before { + content: "\e238"; } + +.glyphicon-grain:before { + content: "\e239"; } + +.glyphicon-sunglasses:before { + content: "\e240"; } + +.glyphicon-text-size:before { + content: "\e241"; } + +.glyphicon-text-color:before { + content: "\e242"; } + +.glyphicon-text-background:before { + content: "\e243"; } + +.glyphicon-object-align-top:before { + content: "\e244"; } + +.glyphicon-object-align-bottom:before { + content: "\e245"; } + +.glyphicon-object-align-horizontal:before { + content: "\e246"; } + +.glyphicon-object-align-left:before { + content: "\e247"; } + +.glyphicon-object-align-vertical:before { + content: "\e248"; } + +.glyphicon-object-align-right:before { + content: "\e249"; } + +.glyphicon-triangle-right:before { + content: "\e250"; } + +.glyphicon-triangle-left:before { + content: "\e251"; } + +.glyphicon-triangle-bottom:before { + content: "\e252"; } + +.glyphicon-triangle-top:before { + content: "\e253"; } + +.glyphicon-console:before { + content: "\e254"; } + +.glyphicon-superscript:before { + content: "\e255"; } + +.glyphicon-subscript:before { + content: "\e256"; } + +.glyphicon-menu-left:before { + content: "\e257"; } + +.glyphicon-menu-right:before { + content: "\e258"; } + +.glyphicon-menu-down:before { + content: "\e259"; } + +.glyphicon-menu-up:before { + content: "\e260"; } + +* { + -webkit-box-sizing: border-box; + -moz-box-sizing: border-box; + box-sizing: border-box; } + +*:before, +*:after { + -webkit-box-sizing: border-box; + -moz-box-sizing: border-box; + box-sizing: border-box; } + +html { + font-size: 10px; + -webkit-tap-highlight-color: transparent; } + +body { + font-family: "Source Sans Pro", "Helvetica Neue", Helvetica, Arial, sans-serif; + font-size: 15px; + line-height: 1.846; + color: #444; + background-color: #fff; } + +input, +button, +select, +textarea { + font-family: inherit; + font-size: inherit; + line-height: inherit; } + +a { + color: #5a9ddb; + text-decoration: none; } + a:hover, a:focus { + color: #2a77bf; + text-decoration: underline; } + a:focus { + outline: 5px auto -webkit-focus-ring-color; + outline-offset: -2px; } + +figure { + margin: 0; } + +img { + vertical-align: middle; } + +.img-responsive { + display: block; + max-width: 100%; + height: auto; } + +.img-rounded { + border-radius: 3px; } + +.img-thumbnail { + padding: 4px; + line-height: 1.846; + background-color: #fff; + border: 1px solid #ddd; + border-radius: 3px; + -webkit-transition: all 0.2s ease-in-out; + -o-transition: all 0.2s ease-in-out; + transition: all 0.2s ease-in-out; + display: inline-block; + max-width: 100%; + height: auto; } + +.img-circle { + border-radius: 50%; } + +hr { + margin-top: 27px; + margin-bottom: 27px; + border: 0; + border-top: 1px solid #eeeeee; } + +.sr-only { + position: absolute; + width: 1px; + height: 1px; + margin: -1px; + padding: 0; + overflow: hidden; + clip: rect(0, 0, 0, 0); + border: 0; } + +.sr-only-focusable:active, .sr-only-focusable:focus { + position: static; + width: auto; + height: auto; + margin: 0; + overflow: visible; + clip: auto; } + +[role="button"] { + cursor: pointer; } + +h1, h2, h3, h4, h5, h6, +.h1, .h2, .h3, .h4, .h5, .h6 { + font-family: inherit; + font-weight: 300; + line-height: 1.1; + color: #444; } + h1 small, + h1 .small, h2 small, + h2 .small, h3 small, + h3 .small, h4 small, + h4 .small, h5 small, + h5 .small, h6 small, + h6 .small, + .h1 small, + .h1 .small, .h2 small, + .h2 .small, .h3 small, + .h3 .small, .h4 small, + .h4 .small, .h5 small, + .h5 .small, .h6 small, + .h6 .small { + font-weight: normal; + line-height: 1; + color: #bbb; } + +h1, .h1, +h2, .h2, +h3, .h3 { + margin-top: 27px; + margin-bottom: 13.5px; } + h1 small, + h1 .small, .h1 small, + .h1 .small, + h2 small, + h2 .small, .h2 small, + .h2 .small, + h3 small, + h3 .small, .h3 small, + .h3 .small { + font-size: 65%; } + +h4, .h4, +h5, .h5, +h6, .h6 { + margin-top: 13.5px; + margin-bottom: 13.5px; } + h4 small, + h4 .small, .h4 small, + .h4 .small, + h5 small, + h5 .small, .h5 small, + .h5 .small, + h6 small, + h6 .small, .h6 small, + .h6 .small { + font-size: 75%; } + +h1, .h1 { + font-size: 48px; } + +h2, .h2 { + font-size: 40px; } + +h3, .h3 { + font-size: 32px; } + +h4, .h4 { + font-size: 24px; } + +h5, .h5 { + font-size: 20px; } + +h6, .h6 { + font-size: 14px; } + +p { + margin: 0 0 13.5px; } + +.lead { + margin-bottom: 27px; + font-size: 17px; + font-weight: 300; + line-height: 1.4; } + @media (min-width: 768px) { + .lead { + font-size: 22.5px; } } + +small, +.small { + font-size: 86%; } + +mark, +.mark { + background-color: #ffe0b2; + padding: .2em; } + +.text-left { + text-align: left; } + +.text-right { + text-align: right; } + +.text-center { + text-align: center; } + +.text-justify { + text-align: justify; } + +.text-nowrap { + white-space: nowrap; } + +.text-lowercase { + text-transform: lowercase; } + +.text-uppercase, .initialism { + text-transform: uppercase; } + +.text-capitalize { + text-transform: capitalize; } + +.text-muted { + color: #bbb; } + +.text-primary { + color: #5a9ddb; } + +a.text-primary:hover, +a.text-primary:focus { + color: #3084d2; } + +.text-success { + color: #4CAF50; } + +a.text-success:hover, +a.text-success:focus { + color: #3d8b40; } + +.text-info { + color: #9C27B0; } + +a.text-info:hover, +a.text-info:focus { + color: #771e86; } + +.text-warning { + color: #ff9800; } + +a.text-warning:hover, +a.text-warning:focus { + color: #cc7a00; } + +.text-danger { + color: #e51c23; } + +a.text-danger:hover, +a.text-danger:focus { + color: #b9151b; } + +.bg-primary { + color: #fff; } + +.bg-primary { + background-color: #5a9ddb; } + +a.bg-primary:hover, +a.bg-primary:focus { + background-color: #3084d2; } + +.bg-success { + background-color: #dff0d8; } + +a.bg-success:hover, +a.bg-success:focus { + background-color: #c1e2b3; } + +.bg-info { + background-color: #e1bee7; } + +a.bg-info:hover, +a.bg-info:focus { + background-color: #d099d9; } + +.bg-warning { + background-color: #ffe0b2; } + +a.bg-warning:hover, +a.bg-warning:focus { + background-color: #ffcb7f; } + +.bg-danger { + background-color: #f9bdbb; } + +a.bg-danger:hover, +a.bg-danger:focus { + background-color: #f5908c; } + +.page-header { + padding-bottom: 12.5px; + margin: 54px 0 27px; + border-bottom: 1px solid #eeeeee; } + +ul, +ol { + margin-top: 0; + margin-bottom: 13.5px; } + ul ul, + ul ol, + ol ul, + ol ol { + margin-bottom: 0; } + +.list-unstyled { + padding-left: 0; + list-style: none; } + +.list-inline { + padding-left: 0; + list-style: none; + margin-left: -5px; } + .list-inline > li { + display: inline-block; + padding-left: 5px; + padding-right: 5px; } + +dl { + margin-top: 0; + margin-bottom: 27px; } + +dt, +dd { + line-height: 1.846; } + +dt { + font-weight: bold; } + +dd { + margin-left: 0; } + +.dl-horizontal dd:before, .dl-horizontal dd:after { + content: " "; + display: table; } +.dl-horizontal dd:after { + clear: both; } +@media (min-width: 768px) { + .dl-horizontal dt { + float: left; + width: 160px; + clear: left; + text-align: right; + overflow: hidden; + text-overflow: ellipsis; + white-space: nowrap; } + .dl-horizontal dd { + margin-left: 180px; } } + +abbr[title], +abbr[data-original-title] { + cursor: help; + border-bottom: 1px dotted #bbb; } + +.initialism { + font-size: 90%; } + +blockquote { + padding: 13.5px 27px; + margin: 0 0 27px; + font-size: 18.75px; + border-left: 5px solid #eeeeee; } + blockquote p:last-child, + blockquote ul:last-child, + blockquote ol:last-child { + margin-bottom: 0; } + blockquote footer, + blockquote small, + blockquote .small { + display: block; + font-size: 80%; + line-height: 1.846; + color: #bbb; } + blockquote footer:before, + blockquote small:before, + blockquote .small:before { + content: '\2014 \00A0'; } + +.blockquote-reverse, +blockquote.pull-right { + padding-right: 15px; + padding-left: 0; + border-right: 5px solid #eeeeee; + border-left: 0; + text-align: right; } + .blockquote-reverse footer:before, + .blockquote-reverse small:before, + .blockquote-reverse .small:before, + blockquote.pull-right footer:before, + blockquote.pull-right small:before, + blockquote.pull-right .small:before { + content: ''; } + .blockquote-reverse footer:after, + .blockquote-reverse small:after, + .blockquote-reverse .small:after, + blockquote.pull-right footer:after, + blockquote.pull-right small:after, + blockquote.pull-right .small:after { + content: '\00A0 \2014'; } + +address { + margin-bottom: 27px; + font-style: normal; + line-height: 1.846; } + +code, +kbd, +pre, +samp { + font-family: "Source Code Pro", Menlo, Monaco, Consolas, "Courier New", monospace; } + +code { + padding: 2px 4px; + font-size: 90%; + color: #444; + background-color: #f2f2f2; + border-radius: 3px; } + +kbd { + padding: 2px 4px; + font-size: 90%; + color: #fff; + background-color: #333; + border-radius: 3px; + box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.25); } + kbd kbd { + padding: 0; + font-size: 100%; + font-weight: bold; + box-shadow: none; } + +pre { + display: block; + padding: 13px; + margin: 0 0 13.5px; + font-size: 14px; + line-height: 1.846; + word-break: break-all; + word-wrap: break-word; + color: #212121; + background-color: #f5f5f5; + border: 1px solid #ccc; + border-radius: 3px; } + pre code { + padding: 0; + font-size: inherit; + color: inherit; + white-space: pre-wrap; + background-color: transparent; + border-radius: 0; } + +.pre-scrollable { + max-height: 340px; + overflow-y: scroll; } + +.container { + margin-right: auto; + margin-left: auto; + padding-left: 15px; + padding-right: 15px; } + .container:before, .container:after { + content: " "; + display: table; } + .container:after { + clear: both; } + @media (min-width: 768px) { + .container { + width: 750px; } } + @media (min-width: 992px) { + .container { + width: 970px; } } + @media (min-width: 1200px) { + .container { + width: 1170px; } } + +.container-fluid { + margin-right: auto; + margin-left: auto; + padding-left: 15px; + padding-right: 15px; } + .container-fluid:before, .container-fluid:after { + content: " "; + display: table; } + .container-fluid:after { + clear: both; } + +.row { + margin-left: -15px; + margin-right: -15px; } + .row:before, .row:after { + content: " "; + display: table; } + .row:after { + clear: both; } + +.col-xs-1, .col-sm-1, .col-md-1, .col-lg-1, .col-xs-2, .col-sm-2, .col-md-2, .col-lg-2, .col-xs-3, .col-sm-3, .col-md-3, .col-lg-3, .col-xs-4, .col-sm-4, .col-md-4, .col-lg-4, .col-xs-5, .col-sm-5, .col-md-5, .col-lg-5, .col-xs-6, .col-sm-6, .col-md-6, .col-lg-6, .col-xs-7, .col-sm-7, .col-md-7, .col-lg-7, .col-xs-8, .col-sm-8, .col-md-8, .col-lg-8, .col-xs-9, .col-sm-9, .col-md-9, .col-lg-9, .col-xs-10, .col-sm-10, .col-md-10, .col-lg-10, .col-xs-11, .col-sm-11, .col-md-11, .col-lg-11, .col-xs-12, .col-sm-12, .col-md-12, .col-lg-12 { + position: relative; + min-height: 1px; + padding-left: 15px; + padding-right: 15px; } + +.col-xs-1, .col-xs-2, .col-xs-3, .col-xs-4, .col-xs-5, .col-xs-6, .col-xs-7, .col-xs-8, .col-xs-9, .col-xs-10, .col-xs-11, .col-xs-12 { + float: left; } + +.col-xs-1 { + width: 8.33333%; } + +.col-xs-2 { + width: 16.66667%; } + +.col-xs-3 { + width: 25%; } + +.col-xs-4 { + width: 33.33333%; } + +.col-xs-5 { + width: 41.66667%; } + +.col-xs-6 { + width: 50%; } + +.col-xs-7 { + width: 58.33333%; } + +.col-xs-8 { + width: 66.66667%; } + +.col-xs-9 { + width: 75%; } + +.col-xs-10 { + width: 83.33333%; } + +.col-xs-11 { + width: 91.66667%; } + +.col-xs-12 { + width: 100%; } + +.col-xs-pull-0 { + right: auto; } + +.col-xs-pull-1 { + right: 8.33333%; } + +.col-xs-pull-2 { + right: 16.66667%; } + +.col-xs-pull-3 { + right: 25%; } + +.col-xs-pull-4 { + right: 33.33333%; } + +.col-xs-pull-5 { + right: 41.66667%; } + +.col-xs-pull-6 { + right: 50%; } + +.col-xs-pull-7 { + right: 58.33333%; } + +.col-xs-pull-8 { + right: 66.66667%; } + +.col-xs-pull-9 { + right: 75%; } + +.col-xs-pull-10 { + right: 83.33333%; } + +.col-xs-pull-11 { + right: 91.66667%; } + +.col-xs-pull-12 { + right: 100%; } + +.col-xs-push-0 { + left: auto; } + +.col-xs-push-1 { + left: 8.33333%; } + +.col-xs-push-2 { + left: 16.66667%; } + +.col-xs-push-3 { + left: 25%; } + +.col-xs-push-4 { + left: 33.33333%; } + +.col-xs-push-5 { + left: 41.66667%; } + +.col-xs-push-6 { + left: 50%; } + +.col-xs-push-7 { + left: 58.33333%; } + +.col-xs-push-8 { + left: 66.66667%; } + +.col-xs-push-9 { + left: 75%; } + +.col-xs-push-10 { + left: 83.33333%; } + +.col-xs-push-11 { + left: 91.66667%; } + +.col-xs-push-12 { + left: 100%; } + +.col-xs-offset-0 { + margin-left: 0%; } + +.col-xs-offset-1 { + margin-left: 8.33333%; } + +.col-xs-offset-2 { + margin-left: 16.66667%; } + +.col-xs-offset-3 { + margin-left: 25%; } + +.col-xs-offset-4 { + margin-left: 33.33333%; } + +.col-xs-offset-5 { + margin-left: 41.66667%; } + +.col-xs-offset-6 { + margin-left: 50%; } + +.col-xs-offset-7 { + margin-left: 58.33333%; } + +.col-xs-offset-8 { + margin-left: 66.66667%; } + +.col-xs-offset-9 { + margin-left: 75%; } + +.col-xs-offset-10 { + margin-left: 83.33333%; } + +.col-xs-offset-11 { + margin-left: 91.66667%; } + +.col-xs-offset-12 { + margin-left: 100%; } + +@media (min-width: 768px) { + .col-sm-1, .col-sm-2, .col-sm-3, .col-sm-4, .col-sm-5, .col-sm-6, .col-sm-7, .col-sm-8, .col-sm-9, .col-sm-10, .col-sm-11, .col-sm-12 { + float: left; } + + .col-sm-1 { + width: 8.33333%; } + + .col-sm-2 { + width: 16.66667%; } + + .col-sm-3 { + width: 25%; } + + .col-sm-4 { + width: 33.33333%; } + + .col-sm-5 { + width: 41.66667%; } + + .col-sm-6 { + width: 50%; } + + .col-sm-7 { + width: 58.33333%; } + + .col-sm-8 { + width: 66.66667%; } + + .col-sm-9 { + width: 75%; } + + .col-sm-10 { + width: 83.33333%; } + + .col-sm-11 { + width: 91.66667%; } + + .col-sm-12 { + width: 100%; } + + .col-sm-pull-0 { + right: auto; } + + .col-sm-pull-1 { + right: 8.33333%; } + + .col-sm-pull-2 { + right: 16.66667%; } + + .col-sm-pull-3 { + right: 25%; } + + .col-sm-pull-4 { + right: 33.33333%; } + + .col-sm-pull-5 { + right: 41.66667%; } + + .col-sm-pull-6 { + right: 50%; } + + .col-sm-pull-7 { + right: 58.33333%; } + + .col-sm-pull-8 { + right: 66.66667%; } + + .col-sm-pull-9 { + right: 75%; } + + .col-sm-pull-10 { + right: 83.33333%; } + + .col-sm-pull-11 { + right: 91.66667%; } + + .col-sm-pull-12 { + right: 100%; } + + .col-sm-push-0 { + left: auto; } + + .col-sm-push-1 { + left: 8.33333%; } + + .col-sm-push-2 { + left: 16.66667%; } + + .col-sm-push-3 { + left: 25%; } + + .col-sm-push-4 { + left: 33.33333%; } + + .col-sm-push-5 { + left: 41.66667%; } + + .col-sm-push-6 { + left: 50%; } + + .col-sm-push-7 { + left: 58.33333%; } + + .col-sm-push-8 { + left: 66.66667%; } + + .col-sm-push-9 { + left: 75%; } + + .col-sm-push-10 { + left: 83.33333%; } + + .col-sm-push-11 { + left: 91.66667%; } + + .col-sm-push-12 { + left: 100%; } + + .col-sm-offset-0 { + margin-left: 0%; } + + .col-sm-offset-1 { + margin-left: 8.33333%; } + + .col-sm-offset-2 { + margin-left: 16.66667%; } + + .col-sm-offset-3 { + margin-left: 25%; } + + .col-sm-offset-4 { + margin-left: 33.33333%; } + + .col-sm-offset-5 { + margin-left: 41.66667%; } + + .col-sm-offset-6 { + margin-left: 50%; } + + .col-sm-offset-7 { + margin-left: 58.33333%; } + + .col-sm-offset-8 { + margin-left: 66.66667%; } + + .col-sm-offset-9 { + margin-left: 75%; } + + .col-sm-offset-10 { + margin-left: 83.33333%; } + + .col-sm-offset-11 { + margin-left: 91.66667%; } + + .col-sm-offset-12 { + margin-left: 100%; } } +@media (min-width: 992px) { + .col-md-1, .col-md-2, .col-md-3, .col-md-4, .col-md-5, .col-md-6, .col-md-7, .col-md-8, .col-md-9, .col-md-10, .col-md-11, .col-md-12 { + float: left; } + + .col-md-1 { + width: 8.33333%; } + + .col-md-2 { + width: 16.66667%; } + + .col-md-3 { + width: 25%; } + + .col-md-4 { + width: 33.33333%; } + + .col-md-5 { + width: 41.66667%; } + + .col-md-6 { + width: 50%; } + + .col-md-7 { + width: 58.33333%; } + + .col-md-8 { + width: 66.66667%; } + + .col-md-9 { + width: 75%; } + + .col-md-10 { + width: 83.33333%; } + + .col-md-11 { + width: 91.66667%; } + + .col-md-12 { + width: 100%; } + + .col-md-pull-0 { + right: auto; } + + .col-md-pull-1 { + right: 8.33333%; } + + .col-md-pull-2 { + right: 16.66667%; } + + .col-md-pull-3 { + right: 25%; } + + .col-md-pull-4 { + right: 33.33333%; } + + .col-md-pull-5 { + right: 41.66667%; } + + .col-md-pull-6 { + right: 50%; } + + .col-md-pull-7 { + right: 58.33333%; } + + .col-md-pull-8 { + right: 66.66667%; } + + .col-md-pull-9 { + right: 75%; } + + .col-md-pull-10 { + right: 83.33333%; } + + .col-md-pull-11 { + right: 91.66667%; } + + .col-md-pull-12 { + right: 100%; } + + .col-md-push-0 { + left: auto; } + + .col-md-push-1 { + left: 8.33333%; } + + .col-md-push-2 { + left: 16.66667%; } + + .col-md-push-3 { + left: 25%; } + + .col-md-push-4 { + left: 33.33333%; } + + .col-md-push-5 { + left: 41.66667%; } + + .col-md-push-6 { + left: 50%; } + + .col-md-push-7 { + left: 58.33333%; } + + .col-md-push-8 { + left: 66.66667%; } + + .col-md-push-9 { + left: 75%; } + + .col-md-push-10 { + left: 83.33333%; } + + .col-md-push-11 { + left: 91.66667%; } + + .col-md-push-12 { + left: 100%; } + + .col-md-offset-0 { + margin-left: 0%; } + + .col-md-offset-1 { + margin-left: 8.33333%; } + + .col-md-offset-2 { + margin-left: 16.66667%; } + + .col-md-offset-3 { + margin-left: 25%; } + + .col-md-offset-4 { + margin-left: 33.33333%; } + + .col-md-offset-5 { + margin-left: 41.66667%; } + + .col-md-offset-6 { + margin-left: 50%; } + + .col-md-offset-7 { + margin-left: 58.33333%; } + + .col-md-offset-8 { + margin-left: 66.66667%; } + + .col-md-offset-9 { + margin-left: 75%; } + + .col-md-offset-10 { + margin-left: 83.33333%; } + + .col-md-offset-11 { + margin-left: 91.66667%; } + + .col-md-offset-12 { + margin-left: 100%; } } +@media (min-width: 1200px) { + .col-lg-1, .col-lg-2, .col-lg-3, .col-lg-4, .col-lg-5, .col-lg-6, .col-lg-7, .col-lg-8, .col-lg-9, .col-lg-10, .col-lg-11, .col-lg-12 { + float: left; } + + .col-lg-1 { + width: 8.33333%; } + + .col-lg-2 { + width: 16.66667%; } + + .col-lg-3 { + width: 25%; } + + .col-lg-4 { + width: 33.33333%; } + + .col-lg-5 { + width: 41.66667%; } + + .col-lg-6 { + width: 50%; } + + .col-lg-7 { + width: 58.33333%; } + + .col-lg-8 { + width: 66.66667%; } + + .col-lg-9 { + width: 75%; } + + .col-lg-10 { + width: 83.33333%; } + + .col-lg-11 { + width: 91.66667%; } + + .col-lg-12 { + width: 100%; } + + .col-lg-pull-0 { + right: auto; } + + .col-lg-pull-1 { + right: 8.33333%; } + + .col-lg-pull-2 { + right: 16.66667%; } + + .col-lg-pull-3 { + right: 25%; } + + .col-lg-pull-4 { + right: 33.33333%; } + + .col-lg-pull-5 { + right: 41.66667%; } + + .col-lg-pull-6 { + right: 50%; } + + .col-lg-pull-7 { + right: 58.33333%; } + + .col-lg-pull-8 { + right: 66.66667%; } + + .col-lg-pull-9 { + right: 75%; } + + .col-lg-pull-10 { + right: 83.33333%; } + + .col-lg-pull-11 { + right: 91.66667%; } + + .col-lg-pull-12 { + right: 100%; } + + .col-lg-push-0 { + left: auto; } + + .col-lg-push-1 { + left: 8.33333%; } + + .col-lg-push-2 { + left: 16.66667%; } + + .col-lg-push-3 { + left: 25%; } + + .col-lg-push-4 { + left: 33.33333%; } + + .col-lg-push-5 { + left: 41.66667%; } + + .col-lg-push-6 { + left: 50%; } + + .col-lg-push-7 { + left: 58.33333%; } + + .col-lg-push-8 { + left: 66.66667%; } + + .col-lg-push-9 { + left: 75%; } + + .col-lg-push-10 { + left: 83.33333%; } + + .col-lg-push-11 { + left: 91.66667%; } + + .col-lg-push-12 { + left: 100%; } + + .col-lg-offset-0 { + margin-left: 0%; } + + .col-lg-offset-1 { + margin-left: 8.33333%; } + + .col-lg-offset-2 { + margin-left: 16.66667%; } + + .col-lg-offset-3 { + margin-left: 25%; } + + .col-lg-offset-4 { + margin-left: 33.33333%; } + + .col-lg-offset-5 { + margin-left: 41.66667%; } + + .col-lg-offset-6 { + margin-left: 50%; } + + .col-lg-offset-7 { + margin-left: 58.33333%; } + + .col-lg-offset-8 { + margin-left: 66.66667%; } + + .col-lg-offset-9 { + margin-left: 75%; } + + .col-lg-offset-10 { + margin-left: 83.33333%; } + + .col-lg-offset-11 { + margin-left: 91.66667%; } + + .col-lg-offset-12 { + margin-left: 100%; } } +table { + background-color: transparent; } + +caption { + padding-top: 8px; + padding-bottom: 8px; + color: #bbb; + text-align: left; } + +th { + text-align: left; } + +.table { + width: 100%; + max-width: 100%; + margin-bottom: 27px; } + .table > thead > tr > th, + .table > thead > tr > td, + .table > tbody > tr > th, + .table > tbody > tr > td, + .table > tfoot > tr > th, + .table > tfoot > tr > td { + padding: 8px; + line-height: 1.846; + vertical-align: top; + border-top: 1px solid #ddd; } + .table > thead > tr > th { + vertical-align: bottom; + border-bottom: 2px solid #ddd; } + .table > caption + thead > tr:first-child > th, + .table > caption + thead > tr:first-child > td, + .table > colgroup + thead > tr:first-child > th, + .table > colgroup + thead > tr:first-child > td, + .table > thead:first-child > tr:first-child > th, + .table > thead:first-child > tr:first-child > td { + border-top: 0; } + .table > tbody + tbody { + border-top: 2px solid #ddd; } + .table .table { + background-color: #fff; } + +.table-condensed > thead > tr > th, +.table-condensed > thead > tr > td, +.table-condensed > tbody > tr > th, +.table-condensed > tbody > tr > td, +.table-condensed > tfoot > tr > th, +.table-condensed > tfoot > tr > td { + padding: 5px; } + +.table-bordered { + border: 1px solid #ddd; } + .table-bordered > thead > tr > th, + .table-bordered > thead > tr > td, + .table-bordered > tbody > tr > th, + .table-bordered > tbody > tr > td, + .table-bordered > tfoot > tr > th, + .table-bordered > tfoot > tr > td { + border: 1px solid #ddd; } + .table-bordered > thead > tr > th, + .table-bordered > thead > tr > td { + border-bottom-width: 2px; } + +.table-striped > tbody > tr:nth-of-type(odd) { + background-color: #f9f9f9; } + +.table-hover > tbody > tr:hover { + background-color: #f5f5f5; } + +table col[class*="col-"] { + position: static; + float: none; + display: table-column; } + +table td[class*="col-"], +table th[class*="col-"] { + position: static; + float: none; + display: table-cell; } + +.table > thead > tr > td.active, +.table > thead > tr > th.active, .table > thead > tr.active > td, .table > thead > tr.active > th, +.table > tbody > tr > td.active, +.table > tbody > tr > th.active, +.table > tbody > tr.active > td, +.table > tbody > tr.active > th, +.table > tfoot > tr > td.active, +.table > tfoot > tr > th.active, +.table > tfoot > tr.active > td, +.table > tfoot > tr.active > th { + background-color: #f5f5f5; } + +.table-hover > tbody > tr > td.active:hover, +.table-hover > tbody > tr > th.active:hover, .table-hover > tbody > tr.active:hover > td, .table-hover > tbody > tr:hover > .active, .table-hover > tbody > tr.active:hover > th { + background-color: #e8e8e8; } + +.table > thead > tr > td.success, +.table > thead > tr > th.success, .table > thead > tr.success > td, .table > thead > tr.success > th, +.table > tbody > tr > td.success, +.table > tbody > tr > th.success, +.table > tbody > tr.success > td, +.table > tbody > tr.success > th, +.table > tfoot > tr > td.success, +.table > tfoot > tr > th.success, +.table > tfoot > tr.success > td, +.table > tfoot > tr.success > th { + background-color: #dff0d8; } + +.table-hover > tbody > tr > td.success:hover, +.table-hover > tbody > tr > th.success:hover, .table-hover > tbody > tr.success:hover > td, .table-hover > tbody > tr:hover > .success, .table-hover > tbody > tr.success:hover > th { + background-color: #d0e9c6; } + +.table > thead > tr > td.info, +.table > thead > tr > th.info, .table > thead > tr.info > td, .table > thead > tr.info > th, +.table > tbody > tr > td.info, +.table > tbody > tr > th.info, +.table > tbody > tr.info > td, +.table > tbody > tr.info > th, +.table > tfoot > tr > td.info, +.table > tfoot > tr > th.info, +.table > tfoot > tr.info > td, +.table > tfoot > tr.info > th { + background-color: #e1bee7; } + +.table-hover > tbody > tr > td.info:hover, +.table-hover > tbody > tr > th.info:hover, .table-hover > tbody > tr.info:hover > td, .table-hover > tbody > tr:hover > .info, .table-hover > tbody > tr.info:hover > th { + background-color: #d8abe0; } + +.table > thead > tr > td.warning, +.table > thead > tr > th.warning, .table > thead > tr.warning > td, .table > thead > tr.warning > th, +.table > tbody > tr > td.warning, +.table > tbody > tr > th.warning, +.table > tbody > tr.warning > td, +.table > tbody > tr.warning > th, +.table > tfoot > tr > td.warning, +.table > tfoot > tr > th.warning, +.table > tfoot > tr.warning > td, +.table > tfoot > tr.warning > th { + background-color: #ffe0b2; } + +.table-hover > tbody > tr > td.warning:hover, +.table-hover > tbody > tr > th.warning:hover, .table-hover > tbody > tr.warning:hover > td, .table-hover > tbody > tr:hover > .warning, .table-hover > tbody > tr.warning:hover > th { + background-color: #ffd699; } + +.table > thead > tr > td.danger, +.table > thead > tr > th.danger, .table > thead > tr.danger > td, .table > thead > tr.danger > th, +.table > tbody > tr > td.danger, +.table > tbody > tr > th.danger, +.table > tbody > tr.danger > td, +.table > tbody > tr.danger > th, +.table > tfoot > tr > td.danger, +.table > tfoot > tr > th.danger, +.table > tfoot > tr.danger > td, +.table > tfoot > tr.danger > th { + background-color: #f9bdbb; } + +.table-hover > tbody > tr > td.danger:hover, +.table-hover > tbody > tr > th.danger:hover, .table-hover > tbody > tr.danger:hover > td, .table-hover > tbody > tr:hover > .danger, .table-hover > tbody > tr.danger:hover > th { + background-color: #f7a6a4; } + +.table-responsive { + overflow-x: auto; + min-height: 0.01%; } + @media screen and (max-width: 767px) { + .table-responsive { + width: 100%; + margin-bottom: 20.25px; + overflow-y: hidden; + -ms-overflow-style: -ms-autohiding-scrollbar; + border: 1px solid #ddd; } + .table-responsive > .table { + margin-bottom: 0; } + .table-responsive > .table > thead > tr > th, + .table-responsive > .table > thead > tr > td, + .table-responsive > .table > tbody > tr > th, + .table-responsive > .table > tbody > tr > td, + .table-responsive > .table > tfoot > tr > th, + .table-responsive > .table > tfoot > tr > td { + white-space: nowrap; } + .table-responsive > .table-bordered { + border: 0; } + .table-responsive > .table-bordered > thead > tr > th:first-child, + .table-responsive > .table-bordered > thead > tr > td:first-child, + .table-responsive > .table-bordered > tbody > tr > th:first-child, + .table-responsive > .table-bordered > tbody > tr > td:first-child, + .table-responsive > .table-bordered > tfoot > tr > th:first-child, + .table-responsive > .table-bordered > tfoot > tr > td:first-child { + border-left: 0; } + .table-responsive > .table-bordered > thead > tr > th:last-child, + .table-responsive > .table-bordered > thead > tr > td:last-child, + .table-responsive > .table-bordered > tbody > tr > th:last-child, + .table-responsive > .table-bordered > tbody > tr > td:last-child, + .table-responsive > .table-bordered > tfoot > tr > th:last-child, + .table-responsive > .table-bordered > tfoot > tr > td:last-child { + border-right: 0; } + .table-responsive > .table-bordered > tbody > tr:last-child > th, + .table-responsive > .table-bordered > tbody > tr:last-child > td, + .table-responsive > .table-bordered > tfoot > tr:last-child > th, + .table-responsive > .table-bordered > tfoot > tr:last-child > td { + border-bottom: 0; } } + +fieldset { + padding: 0; + margin: 0; + border: 0; + min-width: 0; } + +legend { + display: block; + width: 100%; + padding: 0; + margin-bottom: 27px; + font-size: 22.5px; + line-height: inherit; + color: #212121; + border: 0; + border-bottom: 1px solid #e5e5e5; } + +label { + display: inline-block; + max-width: 100%; + margin-bottom: 5px; + font-weight: bold; } + +input[type="search"] { + -webkit-box-sizing: border-box; + -moz-box-sizing: border-box; + box-sizing: border-box; } + +input[type="radio"], +input[type="checkbox"] { + margin: 4px 0 0; + margin-top: 1px \9; + line-height: normal; } + +input[type="file"] { + display: block; } + +input[type="range"] { + display: block; + width: 100%; } + +select[multiple], +select[size] { + height: auto; } + +input[type="file"]:focus, +input[type="radio"]:focus, +input[type="checkbox"]:focus { + outline: 5px auto -webkit-focus-ring-color; + outline-offset: -2px; } + +output { + display: block; + padding-top: 7px; + font-size: 15px; + line-height: 1.846; + color: #666; } + +.form-control { + display: block; + width: 100%; + height: 41px; + padding: 6px 16px; + font-size: 15px; + line-height: 1.846; + color: #666; + background-color: transparent; + background-image: none; + border: 1px solid transparent; + border-radius: 3px; + -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075); + box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075); + -webkit-transition: border-color ease-in-out 0.15s, box-shadow ease-in-out 0.15s; + -o-transition: border-color ease-in-out 0.15s, box-shadow ease-in-out 0.15s; + transition: border-color ease-in-out 0.15s, box-shadow ease-in-out 0.15s; } + .form-control:focus { + border-color: #66afe9; + outline: 0; + -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 8px rgba(102, 175, 233, 0.6); + box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 8px rgba(102, 175, 233, 0.6); } + .form-control::-moz-placeholder { + color: #bbb; + opacity: 1; } + .form-control:-ms-input-placeholder { + color: #bbb; } + .form-control::-webkit-input-placeholder { + color: #bbb; } + .form-control::-ms-expand { + border: 0; + background-color: transparent; } + .form-control[disabled], .form-control[readonly], fieldset[disabled] .form-control { + background-color: transparent; + opacity: 1; } + .form-control[disabled], fieldset[disabled] .form-control { + cursor: not-allowed; } + +textarea.form-control { + height: auto; } + +input[type="search"] { + -webkit-appearance: none; } + +@media screen and (-webkit-min-device-pixel-ratio: 0) { + input[type="date"].form-control, + input[type="time"].form-control, + input[type="datetime-local"].form-control, + input[type="month"].form-control { + line-height: 41px; } + input[type="date"].input-sm, .input-group-sm > input[type="date"].form-control, + .input-group-sm > input[type="date"].input-group-addon, + .input-group-sm > .input-group-btn > input[type="date"].btn, .input-group-sm input[type="date"], + input[type="time"].input-sm, + .input-group-sm > input[type="time"].form-control, + .input-group-sm > input[type="time"].input-group-addon, + .input-group-sm > .input-group-btn > input[type="time"].btn, .input-group-sm + input[type="time"], + input[type="datetime-local"].input-sm, + .input-group-sm > input[type="datetime-local"].form-control, + .input-group-sm > input[type="datetime-local"].input-group-addon, + .input-group-sm > .input-group-btn > input[type="datetime-local"].btn, .input-group-sm + input[type="datetime-local"], + input[type="month"].input-sm, + .input-group-sm > input[type="month"].form-control, + .input-group-sm > input[type="month"].input-group-addon, + .input-group-sm > .input-group-btn > input[type="month"].btn, .input-group-sm + input[type="month"] { + line-height: 31px; } + input[type="date"].input-lg, .input-group-lg > input[type="date"].form-control, + .input-group-lg > input[type="date"].input-group-addon, + .input-group-lg > .input-group-btn > input[type="date"].btn, .input-group-lg input[type="date"], + input[type="time"].input-lg, + .input-group-lg > input[type="time"].form-control, + .input-group-lg > input[type="time"].input-group-addon, + .input-group-lg > .input-group-btn > input[type="time"].btn, .input-group-lg + input[type="time"], + input[type="datetime-local"].input-lg, + .input-group-lg > input[type="datetime-local"].form-control, + .input-group-lg > input[type="datetime-local"].input-group-addon, + .input-group-lg > .input-group-btn > input[type="datetime-local"].btn, .input-group-lg + input[type="datetime-local"], + input[type="month"].input-lg, + .input-group-lg > input[type="month"].form-control, + .input-group-lg > input[type="month"].input-group-addon, + .input-group-lg > .input-group-btn > input[type="month"].btn, .input-group-lg + input[type="month"] { + line-height: 48px; } } +.form-group { + margin-bottom: 15px; } + +.radio, +.checkbox { + position: relative; + display: block; + margin-top: 10px; + margin-bottom: 10px; } + .radio label, + .checkbox label { + min-height: 27px; + padding-left: 20px; + margin-bottom: 0; + font-weight: normal; + cursor: pointer; } + +.radio input[type="radio"], +.radio-inline input[type="radio"], +.checkbox input[type="checkbox"], +.checkbox-inline input[type="checkbox"] { + position: absolute; + margin-left: -20px; + margin-top: 4px \9; } + +.radio + .radio, +.checkbox + .checkbox { + margin-top: -5px; } + +.radio-inline, +.checkbox-inline { + position: relative; + display: inline-block; + padding-left: 20px; + margin-bottom: 0; + vertical-align: middle; + font-weight: normal; + cursor: pointer; } + +.radio-inline + .radio-inline, +.checkbox-inline + .checkbox-inline { + margin-top: 0; + margin-left: 10px; } + +input[type="radio"][disabled], input[type="radio"].disabled, fieldset[disabled] input[type="radio"], +input[type="checkbox"][disabled], +input[type="checkbox"].disabled, fieldset[disabled] +input[type="checkbox"] { + cursor: not-allowed; } + +.radio-inline.disabled, fieldset[disabled] .radio-inline, +.checkbox-inline.disabled, fieldset[disabled] +.checkbox-inline { + cursor: not-allowed; } + +.radio.disabled label, fieldset[disabled] .radio label, +.checkbox.disabled label, fieldset[disabled] +.checkbox label { + cursor: not-allowed; } + +.form-control-static { + padding-top: 7px; + padding-bottom: 7px; + margin-bottom: 0; + min-height: 42px; } + .form-control-static.input-lg, .input-group-lg > .form-control-static.form-control, + .input-group-lg > .form-control-static.input-group-addon, + .input-group-lg > .input-group-btn > .form-control-static.btn, .form-control-static.input-sm, .input-group-sm > .form-control-static.form-control, + .input-group-sm > .form-control-static.input-group-addon, + .input-group-sm > .input-group-btn > .form-control-static.btn { + padding-left: 0; + padding-right: 0; } + +.input-sm, .input-group-sm > .form-control, +.input-group-sm > .input-group-addon, +.input-group-sm > .input-group-btn > .btn { + height: 31px; + padding: 5px 10px; + font-size: 13px; + line-height: 1.5; + border-radius: 3px; } + +select.input-sm, .input-group-sm > select.form-control, +.input-group-sm > select.input-group-addon, +.input-group-sm > .input-group-btn > select.btn { + height: 31px; + line-height: 31px; } + +textarea.input-sm, .input-group-sm > textarea.form-control, +.input-group-sm > textarea.input-group-addon, +.input-group-sm > .input-group-btn > textarea.btn, +select[multiple].input-sm, +.input-group-sm > select[multiple].form-control, +.input-group-sm > select[multiple].input-group-addon, +.input-group-sm > .input-group-btn > select[multiple].btn { + height: auto; } + +.form-group-sm .form-control { + height: 31px; + padding: 5px 10px; + font-size: 13px; + line-height: 1.5; + border-radius: 3px; } +.form-group-sm select.form-control { + height: 31px; + line-height: 31px; } +.form-group-sm textarea.form-control, +.form-group-sm select[multiple].form-control { + height: auto; } +.form-group-sm .form-control-static { + height: 31px; + min-height: 40px; + padding: 6px 10px; + font-size: 13px; + line-height: 1.5; } + +.input-lg, .input-group-lg > .form-control, +.input-group-lg > .input-group-addon, +.input-group-lg > .input-group-btn > .btn { + height: 48px; + padding: 10px 16px; + font-size: 19px; + line-height: 1.33333; + border-radius: 3px; } + +select.input-lg, .input-group-lg > select.form-control, +.input-group-lg > select.input-group-addon, +.input-group-lg > .input-group-btn > select.btn { + height: 48px; + line-height: 48px; } + +textarea.input-lg, .input-group-lg > textarea.form-control, +.input-group-lg > textarea.input-group-addon, +.input-group-lg > .input-group-btn > textarea.btn, +select[multiple].input-lg, +.input-group-lg > select[multiple].form-control, +.input-group-lg > select[multiple].input-group-addon, +.input-group-lg > .input-group-btn > select[multiple].btn { + height: auto; } + +.form-group-lg .form-control { + height: 48px; + padding: 10px 16px; + font-size: 19px; + line-height: 1.33333; + border-radius: 3px; } +.form-group-lg select.form-control { + height: 48px; + line-height: 48px; } +.form-group-lg textarea.form-control, +.form-group-lg select[multiple].form-control { + height: auto; } +.form-group-lg .form-control-static { + height: 48px; + min-height: 46px; + padding: 11px 16px; + font-size: 19px; + line-height: 1.33333; } + +.has-feedback { + position: relative; } + .has-feedback .form-control { + padding-right: 51.25px; } + +.form-control-feedback { + position: absolute; + top: 0; + right: 0; + z-index: 2; + display: block; + width: 41px; + height: 41px; + line-height: 41px; + text-align: center; + pointer-events: none; } + +.input-lg + .form-control-feedback, .input-group-lg > .form-control + .form-control-feedback, +.input-group-lg > .input-group-addon + .form-control-feedback, +.input-group-lg > .input-group-btn > .btn + .form-control-feedback, +.input-group-lg + .form-control-feedback, +.form-group-lg .form-control + .form-control-feedback { + width: 48px; + height: 48px; + line-height: 48px; } + +.input-sm + .form-control-feedback, .input-group-sm > .form-control + .form-control-feedback, +.input-group-sm > .input-group-addon + .form-control-feedback, +.input-group-sm > .input-group-btn > .btn + .form-control-feedback, +.input-group-sm + .form-control-feedback, +.form-group-sm .form-control + .form-control-feedback { + width: 31px; + height: 31px; + line-height: 31px; } + +.has-success .help-block, +.has-success .control-label, +.has-success .radio, +.has-success .checkbox, +.has-success .radio-inline, +.has-success .checkbox-inline, .has-success.radio label, .has-success.checkbox label, .has-success.radio-inline label, .has-success.checkbox-inline label { + color: #4CAF50; } +.has-success .form-control { + border-color: #4CAF50; + -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075); + box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075); } + .has-success .form-control:focus { + border-color: #3d8b40; + -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #92cf94; + box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #92cf94; } +.has-success .input-group-addon { + color: #4CAF50; + border-color: #4CAF50; + background-color: #dff0d8; } +.has-success .form-control-feedback { + color: #4CAF50; } + +.has-warning .help-block, +.has-warning .control-label, +.has-warning .radio, +.has-warning .checkbox, +.has-warning .radio-inline, +.has-warning .checkbox-inline, .has-warning.radio label, .has-warning.checkbox label, .has-warning.radio-inline label, .has-warning.checkbox-inline label { + color: #ff9800; } +.has-warning .form-control { + border-color: #ff9800; + -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075); + box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075); } + .has-warning .form-control:focus { + border-color: #cc7a00; + -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #ffc166; + box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #ffc166; } +.has-warning .input-group-addon { + color: #ff9800; + border-color: #ff9800; + background-color: #ffe0b2; } +.has-warning .form-control-feedback { + color: #ff9800; } + +.has-error .help-block, +.has-error .control-label, +.has-error .radio, +.has-error .checkbox, +.has-error .radio-inline, +.has-error .checkbox-inline, .has-error.radio label, .has-error.checkbox label, .has-error.radio-inline label, .has-error.checkbox-inline label { + color: #e51c23; } +.has-error .form-control { + border-color: #e51c23; + -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075); + box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075); } + .has-error .form-control:focus { + border-color: #b9151b; + -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #ef787c; + box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #ef787c; } +.has-error .input-group-addon { + color: #e51c23; + border-color: #e51c23; + background-color: #f9bdbb; } +.has-error .form-control-feedback { + color: #e51c23; } + +.has-feedback label ~ .form-control-feedback { + top: 32px; } +.has-feedback label.sr-only ~ .form-control-feedback { + top: 0; } + +.help-block { + display: block; + margin-top: 5px; + margin-bottom: 10px; + color: #848484; } + +@media (min-width: 768px) { + .form-inline .form-group { + display: inline-block; + margin-bottom: 0; + vertical-align: middle; } + .form-inline .form-control { + display: inline-block; + width: auto; + vertical-align: middle; } + .form-inline .form-control-static { + display: inline-block; } + .form-inline .input-group { + display: inline-table; + vertical-align: middle; } + .form-inline .input-group .input-group-addon, + .form-inline .input-group .input-group-btn, + .form-inline .input-group .form-control { + width: auto; } + .form-inline .input-group > .form-control { + width: 100%; } + .form-inline .control-label { + margin-bottom: 0; + vertical-align: middle; } + .form-inline .radio, + .form-inline .checkbox { + display: inline-block; + margin-top: 0; + margin-bottom: 0; + vertical-align: middle; } + .form-inline .radio label, + .form-inline .checkbox label { + padding-left: 0; } + .form-inline .radio input[type="radio"], + .form-inline .checkbox input[type="checkbox"] { + position: relative; + margin-left: 0; } + .form-inline .has-feedback .form-control-feedback { + top: 0; } } + +.form-horizontal .radio, +.form-horizontal .checkbox, +.form-horizontal .radio-inline, +.form-horizontal .checkbox-inline { + margin-top: 0; + margin-bottom: 0; + padding-top: 7px; } +.form-horizontal .radio, +.form-horizontal .checkbox { + min-height: 34px; } +.form-horizontal .form-group { + margin-left: -15px; + margin-right: -15px; } + .form-horizontal .form-group:before, .form-horizontal .form-group:after { + content: " "; + display: table; } + .form-horizontal .form-group:after { + clear: both; } +@media (min-width: 768px) { + .form-horizontal .control-label { + text-align: right; + margin-bottom: 0; + padding-top: 7px; } } +.form-horizontal .has-feedback .form-control-feedback { + right: 15px; } +@media (min-width: 768px) { + .form-horizontal .form-group-lg .control-label { + padding-top: 11px; + font-size: 19px; } } +@media (min-width: 768px) { + .form-horizontal .form-group-sm .control-label { + padding-top: 6px; + font-size: 13px; } } + +.btn { + display: inline-block; + margin-bottom: 0; + font-weight: normal; + text-align: center; + vertical-align: middle; + touch-action: manipulation; + cursor: pointer; + background-image: none; + border: 1px solid transparent; + white-space: nowrap; + padding: 6px 16px; + font-size: 15px; + line-height: 1.846; + border-radius: 3px; + -webkit-user-select: none; + -moz-user-select: none; + -ms-user-select: none; + user-select: none; } + .btn:focus, .btn.focus, .btn:active:focus, .btn:active.focus, .btn.active:focus, .btn.active.focus { + outline: 5px auto -webkit-focus-ring-color; + outline-offset: -2px; } + .btn:hover, .btn:focus, .btn.focus { + color: #444; + text-decoration: none; } + .btn:active, .btn.active { + outline: 0; + background-image: none; + -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125); + box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125); } + .btn.disabled, .btn[disabled], fieldset[disabled] .btn { + cursor: not-allowed; + opacity: 0.65; + filter: alpha(opacity=65); + -webkit-box-shadow: none; + box-shadow: none; } + +a.btn.disabled, fieldset[disabled] a.btn { + pointer-events: none; } + +.btn-default { + color: #444; + background-color: #fff; + border-color: transparent; } + .btn-default:focus, .btn-default.focus { + color: #444; + background-color: #e6e6e6; + border-color: transparent; } + .btn-default:hover { + color: #444; + background-color: #e6e6e6; + border-color: transparent; } + .btn-default:active, .btn-default.active, .open > .btn-default.dropdown-toggle { + color: #444; + background-color: #e6e6e6; + border-color: transparent; } + .btn-default:active:hover, .btn-default:active:focus, .btn-default:active.focus, .btn-default.active:hover, .btn-default.active:focus, .btn-default.active.focus, .open > .btn-default.dropdown-toggle:hover, .open > .btn-default.dropdown-toggle:focus, .open > .btn-default.dropdown-toggle.focus { + color: #444; + background-color: #d4d4d4; + border-color: transparent; } + .btn-default:active, .btn-default.active, .open > .btn-default.dropdown-toggle { + background-image: none; } + .btn-default.disabled:hover, .btn-default.disabled:focus, .btn-default.disabled.focus, .btn-default[disabled]:hover, .btn-default[disabled]:focus, .btn-default[disabled].focus, fieldset[disabled] .btn-default:hover, fieldset[disabled] .btn-default:focus, fieldset[disabled] .btn-default.focus { + background-color: #fff; + border-color: transparent; } + .btn-default .badge { + color: #fff; + background-color: #444; } + +.btn-primary { + color: #fff; + background-color: #5a9ddb; + border-color: transparent; } + .btn-primary:focus, .btn-primary.focus { + color: #fff; + background-color: #3084d2; + border-color: transparent; } + .btn-primary:hover { + color: #fff; + background-color: #3084d2; + border-color: transparent; } + .btn-primary:active, .btn-primary.active, .open > .btn-primary.dropdown-toggle { + color: #fff; + background-color: #3084d2; + border-color: transparent; } + .btn-primary:active:hover, .btn-primary:active:focus, .btn-primary:active.focus, .btn-primary.active:hover, .btn-primary.active:focus, .btn-primary.active.focus, .open > .btn-primary.dropdown-toggle:hover, .open > .btn-primary.dropdown-toggle:focus, .open > .btn-primary.dropdown-toggle.focus { + color: #fff; + background-color: #2872b6; + border-color: transparent; } + .btn-primary:active, .btn-primary.active, .open > .btn-primary.dropdown-toggle { + background-image: none; } + .btn-primary.disabled:hover, .btn-primary.disabled:focus, .btn-primary.disabled.focus, .btn-primary[disabled]:hover, .btn-primary[disabled]:focus, .btn-primary[disabled].focus, fieldset[disabled] .btn-primary:hover, fieldset[disabled] .btn-primary:focus, fieldset[disabled] .btn-primary.focus { + background-color: #5a9ddb; + border-color: transparent; } + .btn-primary .badge { + color: #5a9ddb; + background-color: #fff; } + +.btn-success { + color: #fff; + background-color: #4CAF50; + border-color: transparent; } + .btn-success:focus, .btn-success.focus { + color: #fff; + background-color: #3d8b40; + border-color: transparent; } + .btn-success:hover { + color: #fff; + background-color: #3d8b40; + border-color: transparent; } + .btn-success:active, .btn-success.active, .open > .btn-success.dropdown-toggle { + color: #fff; + background-color: #3d8b40; + border-color: transparent; } + .btn-success:active:hover, .btn-success:active:focus, .btn-success:active.focus, .btn-success.active:hover, .btn-success.active:focus, .btn-success.active.focus, .open > .btn-success.dropdown-toggle:hover, .open > .btn-success.dropdown-toggle:focus, .open > .btn-success.dropdown-toggle.focus { + color: #fff; + background-color: #327334; + border-color: transparent; } + .btn-success:active, .btn-success.active, .open > .btn-success.dropdown-toggle { + background-image: none; } + .btn-success.disabled:hover, .btn-success.disabled:focus, .btn-success.disabled.focus, .btn-success[disabled]:hover, .btn-success[disabled]:focus, .btn-success[disabled].focus, fieldset[disabled] .btn-success:hover, fieldset[disabled] .btn-success:focus, fieldset[disabled] .btn-success.focus { + background-color: #4CAF50; + border-color: transparent; } + .btn-success .badge { + color: #4CAF50; + background-color: #fff; } + +.btn-info { + color: #fff; + background-color: #9C27B0; + border-color: transparent; } + .btn-info:focus, .btn-info.focus { + color: #fff; + background-color: #771e86; + border-color: transparent; } + .btn-info:hover { + color: #fff; + background-color: #771e86; + border-color: transparent; } + .btn-info:active, .btn-info.active, .open > .btn-info.dropdown-toggle { + color: #fff; + background-color: #771e86; + border-color: transparent; } + .btn-info:active:hover, .btn-info:active:focus, .btn-info:active.focus, .btn-info.active:hover, .btn-info.active:focus, .btn-info.active.focus, .open > .btn-info.dropdown-toggle:hover, .open > .btn-info.dropdown-toggle:focus, .open > .btn-info.dropdown-toggle.focus { + color: #fff; + background-color: #5d1769; + border-color: transparent; } + .btn-info:active, .btn-info.active, .open > .btn-info.dropdown-toggle { + background-image: none; } + .btn-info.disabled:hover, .btn-info.disabled:focus, .btn-info.disabled.focus, .btn-info[disabled]:hover, .btn-info[disabled]:focus, .btn-info[disabled].focus, fieldset[disabled] .btn-info:hover, fieldset[disabled] .btn-info:focus, fieldset[disabled] .btn-info.focus { + background-color: #9C27B0; + border-color: transparent; } + .btn-info .badge { + color: #9C27B0; + background-color: #fff; } + +.btn-warning { + color: #fff; + background-color: #ff9800; + border-color: transparent; } + .btn-warning:focus, .btn-warning.focus { + color: #fff; + background-color: #cc7a00; + border-color: transparent; } + .btn-warning:hover { + color: #fff; + background-color: #cc7a00; + border-color: transparent; } + .btn-warning:active, .btn-warning.active, .open > .btn-warning.dropdown-toggle { + color: #fff; + background-color: #cc7a00; + border-color: transparent; } + .btn-warning:active:hover, .btn-warning:active:focus, .btn-warning:active.focus, .btn-warning.active:hover, .btn-warning.active:focus, .btn-warning.active.focus, .open > .btn-warning.dropdown-toggle:hover, .open > .btn-warning.dropdown-toggle:focus, .open > .btn-warning.dropdown-toggle.focus { + color: #fff; + background-color: #a86400; + border-color: transparent; } + .btn-warning:active, .btn-warning.active, .open > .btn-warning.dropdown-toggle { + background-image: none; } + .btn-warning.disabled:hover, .btn-warning.disabled:focus, .btn-warning.disabled.focus, .btn-warning[disabled]:hover, .btn-warning[disabled]:focus, .btn-warning[disabled].focus, fieldset[disabled] .btn-warning:hover, fieldset[disabled] .btn-warning:focus, fieldset[disabled] .btn-warning.focus { + background-color: #ff9800; + border-color: transparent; } + .btn-warning .badge { + color: #ff9800; + background-color: #fff; } + +.btn-danger { + color: #fff; + background-color: #e51c23; + border-color: transparent; } + .btn-danger:focus, .btn-danger.focus { + color: #fff; + background-color: #b9151b; + border-color: transparent; } + .btn-danger:hover { + color: #fff; + background-color: #b9151b; + border-color: transparent; } + .btn-danger:active, .btn-danger.active, .open > .btn-danger.dropdown-toggle { + color: #fff; + background-color: #b9151b; + border-color: transparent; } + .btn-danger:active:hover, .btn-danger:active:focus, .btn-danger:active.focus, .btn-danger.active:hover, .btn-danger.active:focus, .btn-danger.active.focus, .open > .btn-danger.dropdown-toggle:hover, .open > .btn-danger.dropdown-toggle:focus, .open > .btn-danger.dropdown-toggle.focus { + color: #fff; + background-color: #991216; + border-color: transparent; } + .btn-danger:active, .btn-danger.active, .open > .btn-danger.dropdown-toggle { + background-image: none; } + .btn-danger.disabled:hover, .btn-danger.disabled:focus, .btn-danger.disabled.focus, .btn-danger[disabled]:hover, .btn-danger[disabled]:focus, .btn-danger[disabled].focus, fieldset[disabled] .btn-danger:hover, fieldset[disabled] .btn-danger:focus, fieldset[disabled] .btn-danger.focus { + background-color: #e51c23; + border-color: transparent; } + .btn-danger .badge { + color: #e51c23; + background-color: #fff; } + +.btn-link { + color: #5a9ddb; + font-weight: normal; + border-radius: 0; } + .btn-link, .btn-link:active, .btn-link.active, .btn-link[disabled], fieldset[disabled] .btn-link { + background-color: transparent; + -webkit-box-shadow: none; + box-shadow: none; } + .btn-link, .btn-link:hover, .btn-link:focus, .btn-link:active { + border-color: transparent; } + .btn-link:hover, .btn-link:focus { + color: #2a77bf; + text-decoration: underline; + background-color: transparent; } + .btn-link[disabled]:hover, .btn-link[disabled]:focus, fieldset[disabled] .btn-link:hover, fieldset[disabled] .btn-link:focus { + color: #bbb; + text-decoration: none; } + +.btn-lg, .btn-group-lg > .btn { + padding: 10px 16px; + font-size: 19px; + line-height: 1.33333; + border-radius: 3px; } + +.btn-sm, .btn-group-sm > .btn { + padding: 5px 10px; + font-size: 13px; + line-height: 1.5; + border-radius: 3px; } + +.btn-xs, .btn-group-xs > .btn { + padding: 1px 5px; + font-size: 13px; + line-height: 1.5; + border-radius: 3px; } + +.btn-block { + display: block; + width: 100%; } + +.btn-block + .btn-block { + margin-top: 5px; } + +input[type="submit"].btn-block, +input[type="reset"].btn-block, +input[type="button"].btn-block { + width: 100%; } + +.fade { + opacity: 0; + -webkit-transition: opacity 0.15s linear; + -o-transition: opacity 0.15s linear; + transition: opacity 0.15s linear; } + .fade.in { + opacity: 1; } + +.collapse { + display: none; } + .collapse.in { + display: block; } + +tr.collapse.in { + display: table-row; } + +tbody.collapse.in { + display: table-row-group; } + +.collapsing { + position: relative; + height: 0; + overflow: hidden; + -webkit-transition-property: height, visibility; + transition-property: height, visibility; + -webkit-transition-duration: 0.35s; + transition-duration: 0.35s; + -webkit-transition-timing-function: ease; + transition-timing-function: ease; } + +.caret { + display: inline-block; + width: 0; + height: 0; + margin-left: 2px; + vertical-align: middle; + border-top: 4px dashed; + border-top: 4px solid \9; + border-right: 4px solid transparent; + border-left: 4px solid transparent; } + +.dropup, +.dropdown { + position: relative; } + +.dropdown-toggle:focus { + outline: 0; } + +.dropdown-menu { + position: absolute; + top: 100%; + left: 0; + z-index: 1000; + display: none; + float: left; + min-width: 160px; + padding: 5px 0; + margin: 2px 0 0; + list-style: none; + font-size: 15px; + text-align: left; + background-color: #fff; + border: 1px solid #ccc; + border: 1px solid rgba(0, 0, 0, 0.15); + border-radius: 3px; + -webkit-box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175); + box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175); + background-clip: padding-box; } + .dropdown-menu.pull-right { + right: 0; + left: auto; } + .dropdown-menu .divider { + height: 1px; + margin: 12.5px 0; + overflow: hidden; + background-color: #e5e5e5; } + .dropdown-menu > li > a { + display: block; + padding: 3px 20px; + clear: both; + font-weight: normal; + line-height: 1.846; + color: #444; + white-space: nowrap; } + +.dropdown-menu > li > a:hover, .dropdown-menu > li > a:focus { + text-decoration: none; + color: #141414; + background-color: #eeeeee; } + +.dropdown-menu > .active > a, .dropdown-menu > .active > a:hover, .dropdown-menu > .active > a:focus { + color: #fff; + text-decoration: none; + outline: 0; + background-color: #5a9ddb; } + +.dropdown-menu > .disabled > a, .dropdown-menu > .disabled > a:hover, .dropdown-menu > .disabled > a:focus { + color: #bbb; } +.dropdown-menu > .disabled > a:hover, .dropdown-menu > .disabled > a:focus { + text-decoration: none; + background-color: transparent; + background-image: none; + filter: progid:DXImageTransform.Microsoft.gradient(enabled = false); + cursor: not-allowed; } + +.open > .dropdown-menu { + display: block; } +.open > a { + outline: 0; } + +.dropdown-menu-right { + left: auto; + right: 0; } + +.dropdown-menu-left { + left: 0; + right: auto; } + +.dropdown-header { + display: block; + padding: 3px 20px; + font-size: 13px; + line-height: 1.846; + color: #bbb; + white-space: nowrap; } + +.dropdown-backdrop { + position: fixed; + left: 0; + right: 0; + bottom: 0; + top: 0; + z-index: 990; } + +.pull-right > .dropdown-menu { + right: 0; + left: auto; } + +.dropup .caret, +.navbar-fixed-bottom .dropdown .caret { + border-top: 0; + border-bottom: 4px dashed; + border-bottom: 4px solid \9; + content: ""; } +.dropup .dropdown-menu, +.navbar-fixed-bottom .dropdown .dropdown-menu { + top: auto; + bottom: 100%; + margin-bottom: 2px; } + +@media (min-width: 768px) { + .navbar-right .dropdown-menu { + right: 0; + left: auto; } + .navbar-right .dropdown-menu-left { + left: 0; + right: auto; } } +.btn-group, +.btn-group-vertical { + position: relative; + display: inline-block; + vertical-align: middle; } + .btn-group > .btn, + .btn-group-vertical > .btn { + position: relative; + float: left; } + .btn-group > .btn:hover, .btn-group > .btn:focus, .btn-group > .btn:active, .btn-group > .btn.active, + .btn-group-vertical > .btn:hover, + .btn-group-vertical > .btn:focus, + .btn-group-vertical > .btn:active, + .btn-group-vertical > .btn.active { + z-index: 2; } + +.btn-group .btn + .btn, +.btn-group .btn + .btn-group, +.btn-group .btn-group + .btn, +.btn-group .btn-group + .btn-group { + margin-left: -1px; } + +.btn-toolbar { + margin-left: -5px; } + .btn-toolbar:before, .btn-toolbar:after { + content: " "; + display: table; } + .btn-toolbar:after { + clear: both; } + .btn-toolbar .btn, + .btn-toolbar .btn-group, + .btn-toolbar .input-group { + float: left; } + .btn-toolbar > .btn, + .btn-toolbar > .btn-group, + .btn-toolbar > .input-group { + margin-left: 5px; } + +.btn-group > .btn:not(:first-child):not(:last-child):not(.dropdown-toggle) { + border-radius: 0; } + +.btn-group > .btn:first-child { + margin-left: 0; } + .btn-group > .btn:first-child:not(:last-child):not(.dropdown-toggle) { + border-bottom-right-radius: 0; + border-top-right-radius: 0; } + +.btn-group > .btn:last-child:not(:first-child), +.btn-group > .dropdown-toggle:not(:first-child) { + border-bottom-left-radius: 0; + border-top-left-radius: 0; } + +.btn-group > .btn-group { + float: left; } + +.btn-group > .btn-group:not(:first-child):not(:last-child) > .btn { + border-radius: 0; } + +.btn-group > .btn-group:first-child:not(:last-child) > .btn:last-child, +.btn-group > .btn-group:first-child:not(:last-child) > .dropdown-toggle { + border-bottom-right-radius: 0; + border-top-right-radius: 0; } + +.btn-group > .btn-group:last-child:not(:first-child) > .btn:first-child { + border-bottom-left-radius: 0; + border-top-left-radius: 0; } + +.btn-group .dropdown-toggle:active, +.btn-group.open .dropdown-toggle { + outline: 0; } + +.btn-group > .btn + .dropdown-toggle { + padding-left: 8px; + padding-right: 8px; } + +.btn-group > .btn-lg + .dropdown-toggle, .btn-group-lg.btn-group > .btn + .dropdown-toggle { + padding-left: 12px; + padding-right: 12px; } + +.btn-group.open .dropdown-toggle { + -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125); + box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125); } + .btn-group.open .dropdown-toggle.btn-link { + -webkit-box-shadow: none; + box-shadow: none; } + +.btn .caret { + margin-left: 0; } + +.btn-lg .caret, .btn-group-lg > .btn .caret { + border-width: 5px 5px 0; + border-bottom-width: 0; } + +.dropup .btn-lg .caret, .dropup .btn-group-lg > .btn .caret { + border-width: 0 5px 5px; } + +.btn-group-vertical > .btn, +.btn-group-vertical > .btn-group, +.btn-group-vertical > .btn-group > .btn { + display: block; + float: none; + width: 100%; + max-width: 100%; } +.btn-group-vertical > .btn-group:before, .btn-group-vertical > .btn-group:after { + content: " "; + display: table; } +.btn-group-vertical > .btn-group:after { + clear: both; } +.btn-group-vertical > .btn-group > .btn { + float: none; } +.btn-group-vertical > .btn + .btn, +.btn-group-vertical > .btn + .btn-group, +.btn-group-vertical > .btn-group + .btn, +.btn-group-vertical > .btn-group + .btn-group { + margin-top: -1px; + margin-left: 0; } + +.btn-group-vertical > .btn:not(:first-child):not(:last-child) { + border-radius: 0; } +.btn-group-vertical > .btn:first-child:not(:last-child) { + border-top-right-radius: 3px; + border-top-left-radius: 3px; + border-bottom-right-radius: 0; + border-bottom-left-radius: 0; } +.btn-group-vertical > .btn:last-child:not(:first-child) { + border-top-right-radius: 0; + border-top-left-radius: 0; + border-bottom-right-radius: 3px; + border-bottom-left-radius: 3px; } + +.btn-group-vertical > .btn-group:not(:first-child):not(:last-child) > .btn { + border-radius: 0; } + +.btn-group-vertical > .btn-group:first-child:not(:last-child) > .btn:last-child, +.btn-group-vertical > .btn-group:first-child:not(:last-child) > .dropdown-toggle { + border-bottom-right-radius: 0; + border-bottom-left-radius: 0; } + +.btn-group-vertical > .btn-group:last-child:not(:first-child) > .btn:first-child { + border-top-right-radius: 0; + border-top-left-radius: 0; } + +.btn-group-justified { + display: table; + width: 100%; + table-layout: fixed; + border-collapse: separate; } + .btn-group-justified > .btn, + .btn-group-justified > .btn-group { + float: none; + display: table-cell; + width: 1%; } + .btn-group-justified > .btn-group .btn { + width: 100%; } + .btn-group-justified > .btn-group .dropdown-menu { + left: auto; } + +[data-toggle="buttons"] > .btn input[type="radio"], +[data-toggle="buttons"] > .btn input[type="checkbox"], +[data-toggle="buttons"] > .btn-group > .btn input[type="radio"], +[data-toggle="buttons"] > .btn-group > .btn input[type="checkbox"] { + position: absolute; + clip: rect(0, 0, 0, 0); + pointer-events: none; } + +.input-group { + position: relative; + display: table; + border-collapse: separate; } + .input-group[class*="col-"] { + float: none; + padding-left: 0; + padding-right: 0; } + .input-group .form-control { + position: relative; + z-index: 2; + float: left; + width: 100%; + margin-bottom: 0; } + .input-group .form-control:focus { + z-index: 3; } + +.input-group-addon, +.input-group-btn, +.input-group .form-control { + display: table-cell; } + .input-group-addon:not(:first-child):not(:last-child), + .input-group-btn:not(:first-child):not(:last-child), + .input-group .form-control:not(:first-child):not(:last-child) { + border-radius: 0; } + +.input-group-addon, +.input-group-btn { + width: 1%; + white-space: nowrap; + vertical-align: middle; } + +.input-group-addon { + padding: 6px 16px; + font-size: 15px; + font-weight: normal; + line-height: 1; + color: #666; + text-align: center; + background-color: transparent; + border: 1px solid transparent; + border-radius: 3px; } + .input-group-addon.input-sm, + .input-group-sm > .input-group-addon, + .input-group-sm > .input-group-btn > .input-group-addon.btn { + padding: 5px 10px; + font-size: 13px; + border-radius: 3px; } + .input-group-addon.input-lg, + .input-group-lg > .input-group-addon, + .input-group-lg > .input-group-btn > .input-group-addon.btn { + padding: 10px 16px; + font-size: 19px; + border-radius: 3px; } + .input-group-addon input[type="radio"], + .input-group-addon input[type="checkbox"] { + margin-top: 0; } + +.input-group .form-control:first-child, +.input-group-addon:first-child, +.input-group-btn:first-child > .btn, +.input-group-btn:first-child > .btn-group > .btn, +.input-group-btn:first-child > .dropdown-toggle, +.input-group-btn:last-child > .btn:not(:last-child):not(.dropdown-toggle), +.input-group-btn:last-child > .btn-group:not(:last-child) > .btn { + border-bottom-right-radius: 0; + border-top-right-radius: 0; } + +.input-group-addon:first-child { + border-right: 0; } + +.input-group .form-control:last-child, +.input-group-addon:last-child, +.input-group-btn:last-child > .btn, +.input-group-btn:last-child > .btn-group > .btn, +.input-group-btn:last-child > .dropdown-toggle, +.input-group-btn:first-child > .btn:not(:first-child), +.input-group-btn:first-child > .btn-group:not(:first-child) > .btn { + border-bottom-left-radius: 0; + border-top-left-radius: 0; } + +.input-group-addon:last-child { + border-left: 0; } + +.input-group-btn { + position: relative; + font-size: 0; + white-space: nowrap; } + .input-group-btn > .btn { + position: relative; } + .input-group-btn > .btn + .btn { + margin-left: -1px; } + .input-group-btn > .btn:hover, .input-group-btn > .btn:focus, .input-group-btn > .btn:active { + z-index: 2; } + .input-group-btn:first-child > .btn, + .input-group-btn:first-child > .btn-group { + margin-right: -1px; } + .input-group-btn:last-child > .btn, + .input-group-btn:last-child > .btn-group { + z-index: 2; + margin-left: -1px; } + +.nav { + margin-bottom: 0; + padding-left: 0; + list-style: none; } + .nav:before, .nav:after { + content: " "; + display: table; } + .nav:after { + clear: both; } + .nav > li { + position: relative; + display: block; } + .nav > li > a { + position: relative; + display: block; + padding: 10px 15px; } + .nav > li > a:hover, .nav > li > a:focus { + text-decoration: none; + background-color: #eeeeee; } + .nav > li.disabled > a { + color: #bbb; } + .nav > li.disabled > a:hover, .nav > li.disabled > a:focus { + color: #bbb; + text-decoration: none; + background-color: transparent; + cursor: not-allowed; } + .nav .open > a, .nav .open > a:hover, .nav .open > a:focus { + background-color: #eeeeee; + border-color: #5a9ddb; } + .nav .nav-divider { + height: 1px; + margin: 12.5px 0; + overflow: hidden; + background-color: #e5e5e5; } + .nav > li > a > img { + max-width: none; } + +.nav-tabs { + border-bottom: 1px solid transparent; } + .nav-tabs > li { + float: left; + margin-bottom: -1px; } + .nav-tabs > li > a { + margin-right: 2px; + line-height: 1.846; + border: 1px solid transparent; + border-radius: 3px 3px 0 0; } + .nav-tabs > li > a:hover { + border-color: #eeeeee #eeeeee transparent; } + .nav-tabs > li.active > a, .nav-tabs > li.active > a:hover, .nav-tabs > li.active > a:focus { + color: #666; + background-color: transparent; + border: 1px solid transparent; + border-bottom-color: transparent; + cursor: default; } + +.nav-pills > li { + float: left; } + .nav-pills > li > a { + border-radius: 3px; } + .nav-pills > li + li { + margin-left: 2px; } + .nav-pills > li.active > a, .nav-pills > li.active > a:hover, .nav-pills > li.active > a:focus { + color: #fff; + background-color: #5a9ddb; } + +.nav-stacked > li { + float: none; } + .nav-stacked > li + li { + margin-top: 2px; + margin-left: 0; } + +.nav-justified, .nav-tabs.nav-justified { + width: 100%; } + .nav-justified > li, .nav-tabs.nav-justified > li { + float: none; } + .nav-justified > li > a, .nav-tabs.nav-justified > li > a { + text-align: center; + margin-bottom: 5px; } + .nav-justified > .dropdown .dropdown-menu { + top: auto; + left: auto; } + @media (min-width: 768px) { + .nav-justified > li, .nav-tabs.nav-justified > li { + display: table-cell; + width: 1%; } + .nav-justified > li > a, .nav-tabs.nav-justified > li > a { + margin-bottom: 0; } } + +.nav-tabs-justified, .nav-tabs.nav-justified { + border-bottom: 0; } + .nav-tabs-justified > li > a, .nav-tabs.nav-justified > li > a { + margin-right: 0; + border-radius: 3px; } + .nav-tabs-justified > .active > a, .nav-tabs.nav-justified > .active > a, + .nav-tabs-justified > .active > a:hover, + .nav-tabs.nav-justified > .active > a:hover, + .nav-tabs-justified > .active > a:focus, + .nav-tabs.nav-justified > .active > a:focus { + border: 1px solid transparent; } + @media (min-width: 768px) { + .nav-tabs-justified > li > a, .nav-tabs.nav-justified > li > a { + border-bottom: 1px solid transparent; + border-radius: 3px 3px 0 0; } + .nav-tabs-justified > .active > a, .nav-tabs.nav-justified > .active > a, + .nav-tabs-justified > .active > a:hover, + .nav-tabs.nav-justified > .active > a:hover, + .nav-tabs-justified > .active > a:focus, + .nav-tabs.nav-justified > .active > a:focus { + border-bottom-color: #fff; } } + +.tab-content > .tab-pane { + display: none; } +.tab-content > .active { + display: block; } + +.nav-tabs .dropdown-menu { + margin-top: -1px; + border-top-right-radius: 0; + border-top-left-radius: 0; } + +.navbar { + position: relative; + min-height: 110px; + margin-bottom: 27px; + border: 1px solid transparent; } + .navbar:before, .navbar:after { + content: " "; + display: table; } + .navbar:after { + clear: both; } + @media (min-width: 768px) { + .navbar { + border-radius: 3px; } } + +.navbar-header:before, .navbar-header:after { + content: " "; + display: table; } +.navbar-header:after { + clear: both; } +@media (min-width: 768px) { + .navbar-header { + float: left; } } + +.navbar-collapse { + overflow-x: visible; + padding-right: 15px; + padding-left: 15px; + border-top: 1px solid transparent; + box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1); + -webkit-overflow-scrolling: touch; } + .navbar-collapse:before, .navbar-collapse:after { + content: " "; + display: table; } + .navbar-collapse:after { + clear: both; } + .navbar-collapse.in { + overflow-y: auto; } + @media (min-width: 768px) { + .navbar-collapse { + width: auto; + border-top: 0; + box-shadow: none; } + .navbar-collapse.collapse { + display: block !important; + height: auto !important; + padding-bottom: 0; + overflow: visible !important; } + .navbar-collapse.in { + overflow-y: visible; } + .navbar-fixed-top .navbar-collapse, .navbar-static-top .navbar-collapse, .navbar-fixed-bottom .navbar-collapse { + padding-left: 0; + padding-right: 0; } } + +.navbar-fixed-top .navbar-collapse, +.navbar-fixed-bottom .navbar-collapse { + max-height: 340px; } + @media (max-device-width: 480px) and (orientation: landscape) { + .navbar-fixed-top .navbar-collapse, + .navbar-fixed-bottom .navbar-collapse { + max-height: 200px; } } + +.container > .navbar-header, +.container > .navbar-collapse, +.container-fluid > .navbar-header, +.container-fluid > .navbar-collapse { + margin-right: -15px; + margin-left: -15px; } + @media (min-width: 768px) { + .container > .navbar-header, + .container > .navbar-collapse, + .container-fluid > .navbar-header, + .container-fluid > .navbar-collapse { + margin-right: 0; + margin-left: 0; } } + +.navbar-static-top { + z-index: 1000; + border-width: 0 0 1px; } + @media (min-width: 768px) { + .navbar-static-top { + border-radius: 0; } } + +.navbar-fixed-top, +.navbar-fixed-bottom { + position: fixed; + right: 0; + left: 0; + z-index: 1030; } + @media (min-width: 768px) { + .navbar-fixed-top, + .navbar-fixed-bottom { + border-radius: 0; } } + +.navbar-fixed-top { + top: 0; + border-width: 0 0 1px; } + +.navbar-fixed-bottom { + bottom: 0; + margin-bottom: 0; + border-width: 1px 0 0; } + +.navbar-brand { + float: left; + padding: 41.5px 15px; + font-size: 19px; + line-height: 27px; + height: 110px; } + .navbar-brand:hover, .navbar-brand:focus { + text-decoration: none; } + .navbar-brand > img { + display: block; } + @media (min-width: 768px) { + .navbar > .container .navbar-brand, .navbar > .container-fluid .navbar-brand { + margin-left: -15px; } } + +.navbar-toggle { + position: relative; + float: right; + margin-right: 15px; + padding: 9px 10px; + margin-top: 38px; + margin-bottom: 38px; + background-color: transparent; + background-image: none; + border: 1px solid transparent; + border-radius: 3px; } + .navbar-toggle:focus { + outline: 0; } + .navbar-toggle .icon-bar { + display: block; + width: 22px; + height: 2px; + border-radius: 1px; } + .navbar-toggle .icon-bar + .icon-bar { + margin-top: 4px; } + @media (min-width: 768px) { + .navbar-toggle { + display: none; } } + +.navbar-nav { + margin: 20.75px -15px; } + .navbar-nav > li > a { + padding-top: 10px; + padding-bottom: 10px; + line-height: 27px; } + @media (max-width: 767px) { + .navbar-nav .open .dropdown-menu { + position: static; + float: none; + width: auto; + margin-top: 0; + background-color: transparent; + border: 0; + box-shadow: none; } + .navbar-nav .open .dropdown-menu > li > a, + .navbar-nav .open .dropdown-menu .dropdown-header { + padding: 5px 15px 5px 25px; } + .navbar-nav .open .dropdown-menu > li > a { + line-height: 27px; } + .navbar-nav .open .dropdown-menu > li > a:hover, .navbar-nav .open .dropdown-menu > li > a:focus { + background-image: none; } } + @media (min-width: 768px) { + .navbar-nav { + float: left; + margin: 0; } + .navbar-nav > li { + float: left; } + .navbar-nav > li > a { + padding-top: 41.5px; + padding-bottom: 41.5px; } } + +.navbar-form { + margin-left: -15px; + margin-right: -15px; + padding: 10px 15px; + border-top: 1px solid transparent; + border-bottom: 1px solid transparent; + -webkit-box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1); + box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1); + margin-top: 34.5px; + margin-bottom: 34.5px; } + @media (min-width: 768px) { + .navbar-form .form-group { + display: inline-block; + margin-bottom: 0; + vertical-align: middle; } + .navbar-form .form-control { + display: inline-block; + width: auto; + vertical-align: middle; } + .navbar-form .form-control-static { + display: inline-block; } + .navbar-form .input-group { + display: inline-table; + vertical-align: middle; } + .navbar-form .input-group .input-group-addon, + .navbar-form .input-group .input-group-btn, + .navbar-form .input-group .form-control { + width: auto; } + .navbar-form .input-group > .form-control { + width: 100%; } + .navbar-form .control-label { + margin-bottom: 0; + vertical-align: middle; } + .navbar-form .radio, + .navbar-form .checkbox { + display: inline-block; + margin-top: 0; + margin-bottom: 0; + vertical-align: middle; } + .navbar-form .radio label, + .navbar-form .checkbox label { + padding-left: 0; } + .navbar-form .radio input[type="radio"], + .navbar-form .checkbox input[type="checkbox"] { + position: relative; + margin-left: 0; } + .navbar-form .has-feedback .form-control-feedback { + top: 0; } } + @media (max-width: 767px) { + .navbar-form .form-group { + margin-bottom: 5px; } + .navbar-form .form-group:last-child { + margin-bottom: 0; } } + @media (min-width: 768px) { + .navbar-form { + width: auto; + border: 0; + margin-left: 0; + margin-right: 0; + padding-top: 0; + padding-bottom: 0; + -webkit-box-shadow: none; + box-shadow: none; } } + +.navbar-nav > li > .dropdown-menu { + margin-top: 0; + border-top-right-radius: 0; + border-top-left-radius: 0; } + +.navbar-fixed-bottom .navbar-nav > li > .dropdown-menu { + margin-bottom: 0; + border-top-right-radius: 3px; + border-top-left-radius: 3px; + border-bottom-right-radius: 0; + border-bottom-left-radius: 0; } + +.navbar-btn { + margin-top: 34.5px; + margin-bottom: 34.5px; } + .navbar-btn.btn-sm, .btn-group-sm > .navbar-btn.btn { + margin-top: 39.5px; + margin-bottom: 39.5px; } + .navbar-btn.btn-xs, .btn-group-xs > .navbar-btn.btn { + margin-top: 44px; + margin-bottom: 44px; } + +.navbar-text { + margin-top: 41.5px; + margin-bottom: 41.5px; } + @media (min-width: 768px) { + .navbar-text { + float: left; + margin-left: 15px; + margin-right: 15px; } } + +@media (min-width: 768px) { + .navbar-left { + float: left !important; } + + .navbar-right { + float: right !important; + margin-right: -15px; } + .navbar-right ~ .navbar-right { + margin-right: 0; } } +.navbar-default { + background-color: #fff; + border-color: transparent; } + .navbar-default .navbar-brand { + color: #444; } + .navbar-default .navbar-brand:hover, .navbar-default .navbar-brand:focus { + color: #222; + background-color: transparent; } + .navbar-default .navbar-text { + color: #bbb; } + .navbar-default .navbar-nav > li > a { + color: #444; } + .navbar-default .navbar-nav > li > a:hover, .navbar-default .navbar-nav > li > a:focus { + color: #222; + background-color: transparent; } + .navbar-default .navbar-nav > .active > a, .navbar-default .navbar-nav > .active > a:hover, .navbar-default .navbar-nav > .active > a:focus { + color: #212121; + background-color: #fcfcfc; } + .navbar-default .navbar-nav > .disabled > a, .navbar-default .navbar-nav > .disabled > a:hover, .navbar-default .navbar-nav > .disabled > a:focus { + color: #ccc; + background-color: transparent; } + .navbar-default .navbar-toggle { + border-color: transparent; } + .navbar-default .navbar-toggle:hover, .navbar-default .navbar-toggle:focus { + background-color: transparent; } + .navbar-default .navbar-toggle .icon-bar { + background-color: rgba(0, 0, 0, 0.5); } + .navbar-default .navbar-collapse, + .navbar-default .navbar-form { + border-color: transparent; } + .navbar-default .navbar-nav > .open > a, .navbar-default .navbar-nav > .open > a:hover, .navbar-default .navbar-nav > .open > a:focus { + background-color: #fcfcfc; + color: #212121; } + @media (max-width: 767px) { + .navbar-default .navbar-nav .open .dropdown-menu > li > a { + color: #444; } + .navbar-default .navbar-nav .open .dropdown-menu > li > a:hover, .navbar-default .navbar-nav .open .dropdown-menu > li > a:focus { + color: #222; + background-color: transparent; } + .navbar-default .navbar-nav .open .dropdown-menu > .active > a, .navbar-default .navbar-nav .open .dropdown-menu > .active > a:hover, .navbar-default .navbar-nav .open .dropdown-menu > .active > a:focus { + color: #212121; + background-color: #fcfcfc; } + .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a, .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a:hover, .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a:focus { + color: #ccc; + background-color: transparent; } } + .navbar-default .navbar-link { + color: #444; } + .navbar-default .navbar-link:hover { + color: #222; } + .navbar-default .btn-link { + color: #444; } + .navbar-default .btn-link:hover, .navbar-default .btn-link:focus { + color: #222; } + .navbar-default .btn-link[disabled]:hover, .navbar-default .btn-link[disabled]:focus, fieldset[disabled] .navbar-default .btn-link:hover, fieldset[disabled] .navbar-default .btn-link:focus { + color: #ccc; } + +.navbar-inverse { + background-color: #5a9ddb; + border-color: transparent; } + .navbar-inverse .navbar-brand { + color: #d8e8f6; } + .navbar-inverse .navbar-brand:hover, .navbar-inverse .navbar-brand:focus { + color: #fff; + background-color: transparent; } + .navbar-inverse .navbar-text { + color: #bbb; } + .navbar-inverse .navbar-nav > li > a { + color: #d8e8f6; } + .navbar-inverse .navbar-nav > li > a:hover, .navbar-inverse .navbar-nav > li > a:focus { + color: #fff; + background-color: transparent; } + .navbar-inverse .navbar-nav > .active > a, .navbar-inverse .navbar-nav > .active > a:hover, .navbar-inverse .navbar-nav > .active > a:focus { + color: #fff; + background-color: #3084d2; } + .navbar-inverse .navbar-nav > .disabled > a, .navbar-inverse .navbar-nav > .disabled > a:hover, .navbar-inverse .navbar-nav > .disabled > a:focus { + color: #444; + background-color: transparent; } + .navbar-inverse .navbar-toggle { + border-color: transparent; } + .navbar-inverse .navbar-toggle:hover, .navbar-inverse .navbar-toggle:focus { + background-color: transparent; } + .navbar-inverse .navbar-toggle .icon-bar { + background-color: rgba(0, 0, 0, 0.5); } + .navbar-inverse .navbar-collapse, + .navbar-inverse .navbar-form { + border-color: #3d8cd5; } + .navbar-inverse .navbar-nav > .open > a, .navbar-inverse .navbar-nav > .open > a:hover, .navbar-inverse .navbar-nav > .open > a:focus { + background-color: #3084d2; + color: #fff; } + @media (max-width: 767px) { + .navbar-inverse .navbar-nav .open .dropdown-menu > .dropdown-header { + border-color: transparent; } + .navbar-inverse .navbar-nav .open .dropdown-menu .divider { + background-color: transparent; } + .navbar-inverse .navbar-nav .open .dropdown-menu > li > a { + color: #d8e8f6; } + .navbar-inverse .navbar-nav .open .dropdown-menu > li > a:hover, .navbar-inverse .navbar-nav .open .dropdown-menu > li > a:focus { + color: #fff; + background-color: transparent; } + .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a, .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a:hover, .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a:focus { + color: #fff; + background-color: #3084d2; } + .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a, .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a:hover, .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a:focus { + color: #444; + background-color: transparent; } } + .navbar-inverse .navbar-link { + color: #d8e8f6; } + .navbar-inverse .navbar-link:hover { + color: #fff; } + .navbar-inverse .btn-link { + color: #d8e8f6; } + .navbar-inverse .btn-link:hover, .navbar-inverse .btn-link:focus { + color: #fff; } + .navbar-inverse .btn-link[disabled]:hover, .navbar-inverse .btn-link[disabled]:focus, fieldset[disabled] .navbar-inverse .btn-link:hover, fieldset[disabled] .navbar-inverse .btn-link:focus { + color: #444; } + +.breadcrumb { + padding: 8px 15px; + margin-bottom: 27px; + list-style: none; + background-color: #f5f5f5; + border-radius: 3px; } + .breadcrumb > li { + display: inline-block; } + .breadcrumb > li + li:before { + content: "/ "; + padding: 0 5px; + color: #ccc; } + .breadcrumb > .active { + color: #bbb; } + +.pagination { + display: inline-block; + padding-left: 0; + margin: 27px 0; + border-radius: 3px; } + .pagination > li { + display: inline; } + .pagination > li > a, + .pagination > li > span { + position: relative; + float: left; + padding: 6px 16px; + line-height: 1.846; + text-decoration: none; + color: #5a9ddb; + background-color: #fff; + border: 1px solid #ddd; + margin-left: -1px; } + .pagination > li:first-child > a, + .pagination > li:first-child > span { + margin-left: 0; + border-bottom-left-radius: 3px; + border-top-left-radius: 3px; } + .pagination > li:last-child > a, + .pagination > li:last-child > span { + border-bottom-right-radius: 3px; + border-top-right-radius: 3px; } + .pagination > li > a:hover, .pagination > li > a:focus, + .pagination > li > span:hover, + .pagination > li > span:focus { + z-index: 2; + color: #2a77bf; + background-color: #eeeeee; + border-color: #ddd; } + .pagination > .active > a, .pagination > .active > a:hover, .pagination > .active > a:focus, + .pagination > .active > span, + .pagination > .active > span:hover, + .pagination > .active > span:focus { + z-index: 3; + color: #fff; + background-color: #5a9ddb; + border-color: #5a9ddb; + cursor: default; } + .pagination > .disabled > span, + .pagination > .disabled > span:hover, + .pagination > .disabled > span:focus, + .pagination > .disabled > a, + .pagination > .disabled > a:hover, + .pagination > .disabled > a:focus { + color: #bbb; + background-color: #fff; + border-color: #ddd; + cursor: not-allowed; } + +.pagination-lg > li > a, +.pagination-lg > li > span { + padding: 10px 16px; + font-size: 19px; + line-height: 1.33333; } +.pagination-lg > li:first-child > a, +.pagination-lg > li:first-child > span { + border-bottom-left-radius: 3px; + border-top-left-radius: 3px; } +.pagination-lg > li:last-child > a, +.pagination-lg > li:last-child > span { + border-bottom-right-radius: 3px; + border-top-right-radius: 3px; } + +.pagination-sm > li > a, +.pagination-sm > li > span { + padding: 5px 10px; + font-size: 13px; + line-height: 1.5; } +.pagination-sm > li:first-child > a, +.pagination-sm > li:first-child > span { + border-bottom-left-radius: 3px; + border-top-left-radius: 3px; } +.pagination-sm > li:last-child > a, +.pagination-sm > li:last-child > span { + border-bottom-right-radius: 3px; + border-top-right-radius: 3px; } + +.pager { + padding-left: 0; + margin: 27px 0; + list-style: none; + text-align: center; } + .pager:before, .pager:after { + content: " "; + display: table; } + .pager:after { + clear: both; } + .pager li { + display: inline; } + .pager li > a, + .pager li > span { + display: inline-block; + padding: 5px 14px; + background-color: #fff; + border: 1px solid #ddd; + border-radius: 15px; } + .pager li > a:hover, + .pager li > a:focus { + text-decoration: none; + background-color: #eeeeee; } + .pager .next > a, + .pager .next > span { + float: right; } + .pager .previous > a, + .pager .previous > span { + float: left; } + .pager .disabled > a, + .pager .disabled > a:hover, + .pager .disabled > a:focus, + .pager .disabled > span { + color: #bbb; + background-color: #fff; + cursor: not-allowed; } + +.label { + display: inline; + padding: .2em .6em .3em; + font-size: 75%; + font-weight: bold; + line-height: 1; + color: #fff; + text-align: center; + white-space: nowrap; + vertical-align: baseline; + border-radius: .25em; } + .label:empty { + display: none; } + .btn .label { + position: relative; + top: -1px; } + +a.label:hover, a.label:focus { + color: #fff; + text-decoration: none; + cursor: pointer; } + +.label-default { + background-color: #bbb; } + .label-default[href]:hover, .label-default[href]:focus { + background-color: #a2a2a2; } + +.label-primary { + background-color: #5a9ddb; } + .label-primary[href]:hover, .label-primary[href]:focus { + background-color: #3084d2; } + +.label-success { + background-color: #4CAF50; } + .label-success[href]:hover, .label-success[href]:focus { + background-color: #3d8b40; } + +.label-info { + background-color: #9C27B0; } + .label-info[href]:hover, .label-info[href]:focus { + background-color: #771e86; } + +.label-warning { + background-color: #ff9800; } + .label-warning[href]:hover, .label-warning[href]:focus { + background-color: #cc7a00; } + +.label-danger { + background-color: #e51c23; } + .label-danger[href]:hover, .label-danger[href]:focus { + background-color: #b9151b; } + +.badge { + display: inline-block; + min-width: 10px; + padding: 3px 7px; + font-size: 13px; + font-weight: normal; + color: #fff; + line-height: 1; + vertical-align: middle; + white-space: nowrap; + text-align: center; + background-color: #bbb; + border-radius: 10px; } + .badge:empty { + display: none; } + .btn .badge { + position: relative; + top: -1px; } + .btn-xs .badge, .btn-group-xs > .btn .badge, .btn-group-xs > .btn .badge { + top: 0; + padding: 1px 5px; } + .list-group-item.active > .badge, .nav-pills > .active > a > .badge { + color: #5a9ddb; + background-color: #fff; } + .list-group-item > .badge { + float: right; } + .list-group-item > .badge + .badge { + margin-right: 5px; } + .nav-pills > li > a > .badge { + margin-left: 3px; } + +a.badge:hover, a.badge:focus { + color: #fff; + text-decoration: none; + cursor: pointer; } + +.jumbotron { + padding-top: 30px; + padding-bottom: 30px; + margin-bottom: 30px; + color: inherit; + background-color: #f5f5f5; } + .jumbotron h1, + .jumbotron .h1 { + color: #444; } + .jumbotron p { + margin-bottom: 15px; + font-size: 23px; + font-weight: 200; } + .jumbotron > hr { + border-top-color: gainsboro; } + .container .jumbotron, .container-fluid .jumbotron { + border-radius: 3px; + padding-left: 15px; + padding-right: 15px; } + .jumbotron .container { + max-width: 100%; } + @media screen and (min-width: 768px) { + .jumbotron { + padding-top: 48px; + padding-bottom: 48px; } + .container .jumbotron, .container-fluid .jumbotron { + padding-left: 60px; + padding-right: 60px; } + .jumbotron h1, + .jumbotron .h1 { + font-size: 68px; } } + +.thumbnail { + display: block; + padding: 4px; + margin-bottom: 27px; + line-height: 1.846; + background-color: #fff; + border: 1px solid #ddd; + border-radius: 3px; + -webkit-transition: border 0.2s ease-in-out; + -o-transition: border 0.2s ease-in-out; + transition: border 0.2s ease-in-out; } + .thumbnail > img, + .thumbnail a > img { + display: block; + max-width: 100%; + height: auto; + margin-left: auto; + margin-right: auto; } + .thumbnail .caption { + padding: 9px; + color: #444; } + +a.thumbnail:hover, +a.thumbnail:focus, +a.thumbnail.active { + border-color: #5a9ddb; } + +.alert { + padding: 15px; + margin-bottom: 27px; + border: 1px solid transparent; + border-radius: 3px; } + .alert h4 { + margin-top: 0; + color: inherit; } + .alert .alert-link { + font-weight: bold; } + .alert > p, + .alert > ul { + margin-bottom: 0; } + .alert > p + p { + margin-top: 5px; } + +.alert-dismissable, +.alert-dismissible { + padding-right: 35px; } + .alert-dismissable .close, + .alert-dismissible .close { + position: relative; + top: -2px; + right: -21px; + color: inherit; } + +.alert-success { + background-color: #dff0d8; + border-color: #d6e9c6; + color: #4CAF50; } + .alert-success hr { + border-top-color: #c9e2b3; } + .alert-success .alert-link { + color: #3d8b40; } + +.alert-info { + background-color: #e1bee7; + border-color: #cba4dd; + color: #9C27B0; } + .alert-info hr { + border-top-color: #c191d6; } + .alert-info .alert-link { + color: #771e86; } + +.alert-warning { + background-color: #ffe0b2; + border-color: #ffc599; + color: #ff9800; } + .alert-warning hr { + border-top-color: #ffb67f; } + .alert-warning .alert-link { + color: #cc7a00; } + +.alert-danger { + background-color: #f9bdbb; + border-color: #f7a4af; + color: #e51c23; } + .alert-danger hr { + border-top-color: #f58c9a; } + .alert-danger .alert-link { + color: #b9151b; } + +@-webkit-keyframes progress-bar-stripes { + from { + background-position: 40px 0; } + to { + background-position: 0 0; } } +@keyframes progress-bar-stripes { + from { + background-position: 40px 0; } + to { + background-position: 0 0; } } +.progress { + overflow: hidden; + height: 27px; + margin-bottom: 27px; + background-color: #f5f5f5; + border-radius: 3px; + -webkit-box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.1); + box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.1); } + +.progress-bar { + float: left; + width: 0%; + height: 100%; + font-size: 13px; + line-height: 27px; + color: #fff; + text-align: center; + background-color: #5a9ddb; + -webkit-box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.15); + box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.15); + -webkit-transition: width 0.6s ease; + -o-transition: width 0.6s ease; + transition: width 0.6s ease; } + +.progress-striped .progress-bar, +.progress-bar-striped { + background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent); + background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent); + background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent); + background-size: 40px 40px; } + +.progress.active .progress-bar, +.progress-bar.active { + -webkit-animation: progress-bar-stripes 2s linear infinite; + -o-animation: progress-bar-stripes 2s linear infinite; + animation: progress-bar-stripes 2s linear infinite; } + +.progress-bar-success { + background-color: #4CAF50; } + .progress-striped .progress-bar-success { + background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent); + background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent); + background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent); } + +.progress-bar-info { + background-color: #9C27B0; } + .progress-striped .progress-bar-info { + background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent); + background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent); + background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent); } + +.progress-bar-warning { + background-color: #ff9800; } + .progress-striped .progress-bar-warning { + background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent); + background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent); + background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent); } + +.progress-bar-danger { + background-color: #e51c23; } + .progress-striped .progress-bar-danger { + background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent); + background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent); + background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent); } + +.media { + margin-top: 15px; } + .media:first-child { + margin-top: 0; } + +.media, +.media-body { + zoom: 1; + overflow: hidden; } + +.media-body { + width: 10000px; } + +.media-object { + display: block; } + .media-object.img-thumbnail { + max-width: none; } + +.media-right, +.media > .pull-right { + padding-left: 10px; } + +.media-left, +.media > .pull-left { + padding-right: 10px; } + +.media-left, +.media-right, +.media-body { + display: table-cell; + vertical-align: top; } + +.media-middle { + vertical-align: middle; } + +.media-bottom { + vertical-align: bottom; } + +.media-heading { + margin-top: 0; + margin-bottom: 5px; } + +.media-list { + padding-left: 0; + list-style: none; } + +.list-group { + margin-bottom: 20px; + padding-left: 0; } + +.list-group-item { + position: relative; + display: block; + padding: 10px 15px; + margin-bottom: -1px; + background-color: #fff; + border: 1px solid #ddd; } + .list-group-item:first-child { + border-top-right-radius: 3px; + border-top-left-radius: 3px; } + .list-group-item:last-child { + margin-bottom: 0; + border-bottom-right-radius: 3px; + border-bottom-left-radius: 3px; } + +a.list-group-item, +button.list-group-item { + color: #555; } + a.list-group-item .list-group-item-heading, + button.list-group-item .list-group-item-heading { + color: #333; } + a.list-group-item:hover, a.list-group-item:focus, + button.list-group-item:hover, + button.list-group-item:focus { + text-decoration: none; + color: #555; + background-color: #f5f5f5; } + +button.list-group-item { + width: 100%; + text-align: left; } + +.list-group-item.disabled, .list-group-item.disabled:hover, .list-group-item.disabled:focus { + background-color: #eeeeee; + color: #bbb; + cursor: not-allowed; } + .list-group-item.disabled .list-group-item-heading, .list-group-item.disabled:hover .list-group-item-heading, .list-group-item.disabled:focus .list-group-item-heading { + color: inherit; } + .list-group-item.disabled .list-group-item-text, .list-group-item.disabled:hover .list-group-item-text, .list-group-item.disabled:focus .list-group-item-text { + color: #bbb; } +.list-group-item.active, .list-group-item.active:hover, .list-group-item.active:focus { + z-index: 2; + color: #fff; + background-color: #5a9ddb; + border-color: #5a9ddb; } + .list-group-item.active .list-group-item-heading, + .list-group-item.active .list-group-item-heading > small, + .list-group-item.active .list-group-item-heading > .small, .list-group-item.active:hover .list-group-item-heading, + .list-group-item.active:hover .list-group-item-heading > small, + .list-group-item.active:hover .list-group-item-heading > .small, .list-group-item.active:focus .list-group-item-heading, + .list-group-item.active:focus .list-group-item-heading > small, + .list-group-item.active:focus .list-group-item-heading > .small { + color: inherit; } + .list-group-item.active .list-group-item-text, .list-group-item.active:hover .list-group-item-text, .list-group-item.active:focus .list-group-item-text { + color: white; } + +.list-group-item-success { + color: #4CAF50; + background-color: #dff0d8; } + +a.list-group-item-success, +button.list-group-item-success { + color: #4CAF50; } + a.list-group-item-success .list-group-item-heading, + button.list-group-item-success .list-group-item-heading { + color: inherit; } + a.list-group-item-success:hover, a.list-group-item-success:focus, + button.list-group-item-success:hover, + button.list-group-item-success:focus { + color: #4CAF50; + background-color: #d0e9c6; } + a.list-group-item-success.active, a.list-group-item-success.active:hover, a.list-group-item-success.active:focus, + button.list-group-item-success.active, + button.list-group-item-success.active:hover, + button.list-group-item-success.active:focus { + color: #fff; + background-color: #4CAF50; + border-color: #4CAF50; } + +.list-group-item-info { + color: #9C27B0; + background-color: #e1bee7; } + +a.list-group-item-info, +button.list-group-item-info { + color: #9C27B0; } + a.list-group-item-info .list-group-item-heading, + button.list-group-item-info .list-group-item-heading { + color: inherit; } + a.list-group-item-info:hover, a.list-group-item-info:focus, + button.list-group-item-info:hover, + button.list-group-item-info:focus { + color: #9C27B0; + background-color: #d8abe0; } + a.list-group-item-info.active, a.list-group-item-info.active:hover, a.list-group-item-info.active:focus, + button.list-group-item-info.active, + button.list-group-item-info.active:hover, + button.list-group-item-info.active:focus { + color: #fff; + background-color: #9C27B0; + border-color: #9C27B0; } + +.list-group-item-warning { + color: #ff9800; + background-color: #ffe0b2; } + +a.list-group-item-warning, +button.list-group-item-warning { + color: #ff9800; } + a.list-group-item-warning .list-group-item-heading, + button.list-group-item-warning .list-group-item-heading { + color: inherit; } + a.list-group-item-warning:hover, a.list-group-item-warning:focus, + button.list-group-item-warning:hover, + button.list-group-item-warning:focus { + color: #ff9800; + background-color: #ffd699; } + a.list-group-item-warning.active, a.list-group-item-warning.active:hover, a.list-group-item-warning.active:focus, + button.list-group-item-warning.active, + button.list-group-item-warning.active:hover, + button.list-group-item-warning.active:focus { + color: #fff; + background-color: #ff9800; + border-color: #ff9800; } + +.list-group-item-danger { + color: #e51c23; + background-color: #f9bdbb; } + +a.list-group-item-danger, +button.list-group-item-danger { + color: #e51c23; } + a.list-group-item-danger .list-group-item-heading, + button.list-group-item-danger .list-group-item-heading { + color: inherit; } + a.list-group-item-danger:hover, a.list-group-item-danger:focus, + button.list-group-item-danger:hover, + button.list-group-item-danger:focus { + color: #e51c23; + background-color: #f7a6a4; } + a.list-group-item-danger.active, a.list-group-item-danger.active:hover, a.list-group-item-danger.active:focus, + button.list-group-item-danger.active, + button.list-group-item-danger.active:hover, + button.list-group-item-danger.active:focus { + color: #fff; + background-color: #e51c23; + border-color: #e51c23; } + +.list-group-item-heading { + margin-top: 0; + margin-bottom: 5px; } + +.list-group-item-text { + margin-bottom: 0; + line-height: 1.3; } + +.panel { + margin-bottom: 27px; + background-color: #fff; + border: 1px solid transparent; + border-radius: 3px; + -webkit-box-shadow: 0 1px 1px rgba(0, 0, 0, 0.05); + box-shadow: 0 1px 1px rgba(0, 0, 0, 0.05); } + +.panel-body { + padding: 15px; } + .panel-body:before, .panel-body:after { + content: " "; + display: table; } + .panel-body:after { + clear: both; } + +.panel-heading { + padding: 10px 15px; + border-bottom: 1px solid transparent; + border-top-right-radius: 2px; + border-top-left-radius: 2px; } + .panel-heading > .dropdown .dropdown-toggle { + color: inherit; } + +.panel-title { + margin-top: 0; + margin-bottom: 0; + font-size: 17px; + color: inherit; } + .panel-title > a, + .panel-title > small, + .panel-title > .small, + .panel-title > small > a, + .panel-title > .small > a { + color: inherit; } + +.panel-footer { + padding: 10px 15px; + background-color: #f5f5f5; + border-top: 1px solid #ddd; + border-bottom-right-radius: 2px; + border-bottom-left-radius: 2px; } + +.panel > .list-group, +.panel > .panel-collapse > .list-group { + margin-bottom: 0; } + .panel > .list-group .list-group-item, + .panel > .panel-collapse > .list-group .list-group-item { + border-width: 1px 0; + border-radius: 0; } + .panel > .list-group:first-child .list-group-item:first-child, + .panel > .panel-collapse > .list-group:first-child .list-group-item:first-child { + border-top: 0; + border-top-right-radius: 2px; + border-top-left-radius: 2px; } + .panel > .list-group:last-child .list-group-item:last-child, + .panel > .panel-collapse > .list-group:last-child .list-group-item:last-child { + border-bottom: 0; + border-bottom-right-radius: 2px; + border-bottom-left-radius: 2px; } +.panel > .panel-heading + .panel-collapse > .list-group .list-group-item:first-child { + border-top-right-radius: 0; + border-top-left-radius: 0; } + +.panel-heading + .list-group .list-group-item:first-child { + border-top-width: 0; } + +.list-group + .panel-footer { + border-top-width: 0; } + +.panel > .table, +.panel > .table-responsive > .table, +.panel > .panel-collapse > .table { + margin-bottom: 0; } + .panel > .table caption, + .panel > .table-responsive > .table caption, + .panel > .panel-collapse > .table caption { + padding-left: 15px; + padding-right: 15px; } +.panel > .table:first-child, +.panel > .table-responsive:first-child > .table:first-child { + border-top-right-radius: 2px; + border-top-left-radius: 2px; } + .panel > .table:first-child > thead:first-child > tr:first-child, + .panel > .table:first-child > tbody:first-child > tr:first-child, + .panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child, + .panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child { + border-top-left-radius: 2px; + border-top-right-radius: 2px; } + .panel > .table:first-child > thead:first-child > tr:first-child td:first-child, + .panel > .table:first-child > thead:first-child > tr:first-child th:first-child, + .panel > .table:first-child > tbody:first-child > tr:first-child td:first-child, + .panel > .table:first-child > tbody:first-child > tr:first-child th:first-child, + .panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child td:first-child, + .panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child th:first-child, + .panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child td:first-child, + .panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child th:first-child { + border-top-left-radius: 2px; } + .panel > .table:first-child > thead:first-child > tr:first-child td:last-child, + .panel > .table:first-child > thead:first-child > tr:first-child th:last-child, + .panel > .table:first-child > tbody:first-child > tr:first-child td:last-child, + .panel > .table:first-child > tbody:first-child > tr:first-child th:last-child, + .panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child td:last-child, + .panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child th:last-child, + .panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child td:last-child, + .panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child th:last-child { + border-top-right-radius: 2px; } +.panel > .table:last-child, +.panel > .table-responsive:last-child > .table:last-child { + border-bottom-right-radius: 2px; + border-bottom-left-radius: 2px; } + .panel > .table:last-child > tbody:last-child > tr:last-child, + .panel > .table:last-child > tfoot:last-child > tr:last-child, + .panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child, + .panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child { + border-bottom-left-radius: 2px; + border-bottom-right-radius: 2px; } + .panel > .table:last-child > tbody:last-child > tr:last-child td:first-child, + .panel > .table:last-child > tbody:last-child > tr:last-child th:first-child, + .panel > .table:last-child > tfoot:last-child > tr:last-child td:first-child, + .panel > .table:last-child > tfoot:last-child > tr:last-child th:first-child, + .panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child td:first-child, + .panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child th:first-child, + .panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child td:first-child, + .panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child th:first-child { + border-bottom-left-radius: 2px; } + .panel > .table:last-child > tbody:last-child > tr:last-child td:last-child, + .panel > .table:last-child > tbody:last-child > tr:last-child th:last-child, + .panel > .table:last-child > tfoot:last-child > tr:last-child td:last-child, + .panel > .table:last-child > tfoot:last-child > tr:last-child th:last-child, + .panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child td:last-child, + .panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child th:last-child, + .panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child td:last-child, + .panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child th:last-child { + border-bottom-right-radius: 2px; } +.panel > .panel-body + .table, +.panel > .panel-body + .table-responsive, +.panel > .table + .panel-body, +.panel > .table-responsive + .panel-body { + border-top: 1px solid #ddd; } +.panel > .table > tbody:first-child > tr:first-child th, +.panel > .table > tbody:first-child > tr:first-child td { + border-top: 0; } +.panel > .table-bordered, +.panel > .table-responsive > .table-bordered { + border: 0; } + .panel > .table-bordered > thead > tr > th:first-child, + .panel > .table-bordered > thead > tr > td:first-child, + .panel > .table-bordered > tbody > tr > th:first-child, + .panel > .table-bordered > tbody > tr > td:first-child, + .panel > .table-bordered > tfoot > tr > th:first-child, + .panel > .table-bordered > tfoot > tr > td:first-child, + .panel > .table-responsive > .table-bordered > thead > tr > th:first-child, + .panel > .table-responsive > .table-bordered > thead > tr > td:first-child, + .panel > .table-responsive > .table-bordered > tbody > tr > th:first-child, + .panel > .table-responsive > .table-bordered > tbody > tr > td:first-child, + .panel > .table-responsive > .table-bordered > tfoot > tr > th:first-child, + .panel > .table-responsive > .table-bordered > tfoot > tr > td:first-child { + border-left: 0; } + .panel > .table-bordered > thead > tr > th:last-child, + .panel > .table-bordered > thead > tr > td:last-child, + .panel > .table-bordered > tbody > tr > th:last-child, + .panel > .table-bordered > tbody > tr > td:last-child, + .panel > .table-bordered > tfoot > tr > th:last-child, + .panel > .table-bordered > tfoot > tr > td:last-child, + .panel > .table-responsive > .table-bordered > thead > tr > th:last-child, + .panel > .table-responsive > .table-bordered > thead > tr > td:last-child, + .panel > .table-responsive > .table-bordered > tbody > tr > th:last-child, + .panel > .table-responsive > .table-bordered > tbody > tr > td:last-child, + .panel > .table-responsive > .table-bordered > tfoot > tr > th:last-child, + .panel > .table-responsive > .table-bordered > tfoot > tr > td:last-child { + border-right: 0; } + .panel > .table-bordered > thead > tr:first-child > td, + .panel > .table-bordered > thead > tr:first-child > th, + .panel > .table-bordered > tbody > tr:first-child > td, + .panel > .table-bordered > tbody > tr:first-child > th, + .panel > .table-responsive > .table-bordered > thead > tr:first-child > td, + .panel > .table-responsive > .table-bordered > thead > tr:first-child > th, + .panel > .table-responsive > .table-bordered > tbody > tr:first-child > td, + .panel > .table-responsive > .table-bordered > tbody > tr:first-child > th { + border-bottom: 0; } + .panel > .table-bordered > tbody > tr:last-child > td, + .panel > .table-bordered > tbody > tr:last-child > th, + .panel > .table-bordered > tfoot > tr:last-child > td, + .panel > .table-bordered > tfoot > tr:last-child > th, + .panel > .table-responsive > .table-bordered > tbody > tr:last-child > td, + .panel > .table-responsive > .table-bordered > tbody > tr:last-child > th, + .panel > .table-responsive > .table-bordered > tfoot > tr:last-child > td, + .panel > .table-responsive > .table-bordered > tfoot > tr:last-child > th { + border-bottom: 0; } +.panel > .table-responsive { + border: 0; + margin-bottom: 0; } + +.panel-group { + margin-bottom: 27px; } + .panel-group .panel { + margin-bottom: 0; + border-radius: 3px; } + .panel-group .panel + .panel { + margin-top: 5px; } + .panel-group .panel-heading { + border-bottom: 0; } + .panel-group .panel-heading + .panel-collapse > .panel-body, + .panel-group .panel-heading + .panel-collapse > .list-group { + border-top: 1px solid #ddd; } + .panel-group .panel-footer { + border-top: 0; } + .panel-group .panel-footer + .panel-collapse .panel-body { + border-bottom: 1px solid #ddd; } + +.panel-default { + border-color: #ddd; } + .panel-default > .panel-heading { + color: #212121; + background-color: #f5f5f5; + border-color: #ddd; } + .panel-default > .panel-heading + .panel-collapse > .panel-body { + border-top-color: #ddd; } + .panel-default > .panel-heading .badge { + color: #f5f5f5; + background-color: #212121; } + .panel-default > .panel-footer + .panel-collapse > .panel-body { + border-bottom-color: #ddd; } + +.panel-primary { + border-color: #5a9ddb; } + .panel-primary > .panel-heading { + color: #fff; + background-color: #5a9ddb; + border-color: #5a9ddb; } + .panel-primary > .panel-heading + .panel-collapse > .panel-body { + border-top-color: #5a9ddb; } + .panel-primary > .panel-heading .badge { + color: #5a9ddb; + background-color: #fff; } + .panel-primary > .panel-footer + .panel-collapse > .panel-body { + border-bottom-color: #5a9ddb; } + +.panel-success { + border-color: #d6e9c6; } + .panel-success > .panel-heading { + color: #fff; + background-color: #4CAF50; + border-color: #d6e9c6; } + .panel-success > .panel-heading + .panel-collapse > .panel-body { + border-top-color: #d6e9c6; } + .panel-success > .panel-heading .badge { + color: #4CAF50; + background-color: #fff; } + .panel-success > .panel-footer + .panel-collapse > .panel-body { + border-bottom-color: #d6e9c6; } + +.panel-info { + border-color: #cba4dd; } + .panel-info > .panel-heading { + color: #fff; + background-color: #9C27B0; + border-color: #cba4dd; } + .panel-info > .panel-heading + .panel-collapse > .panel-body { + border-top-color: #cba4dd; } + .panel-info > .panel-heading .badge { + color: #9C27B0; + background-color: #fff; } + .panel-info > .panel-footer + .panel-collapse > .panel-body { + border-bottom-color: #cba4dd; } + +.panel-warning { + border-color: #ffc599; } + .panel-warning > .panel-heading { + color: #fff; + background-color: #ff9800; + border-color: #ffc599; } + .panel-warning > .panel-heading + .panel-collapse > .panel-body { + border-top-color: #ffc599; } + .panel-warning > .panel-heading .badge { + color: #ff9800; + background-color: #fff; } + .panel-warning > .panel-footer + .panel-collapse > .panel-body { + border-bottom-color: #ffc599; } + +.panel-danger { + border-color: #f7a4af; } + .panel-danger > .panel-heading { + color: #fff; + background-color: #e51c23; + border-color: #f7a4af; } + .panel-danger > .panel-heading + .panel-collapse > .panel-body { + border-top-color: #f7a4af; } + .panel-danger > .panel-heading .badge { + color: #e51c23; + background-color: #fff; } + .panel-danger > .panel-footer + .panel-collapse > .panel-body { + border-bottom-color: #f7a4af; } + +.embed-responsive { + position: relative; + display: block; + height: 0; + padding: 0; + overflow: hidden; } + .embed-responsive .embed-responsive-item, + .embed-responsive iframe, + .embed-responsive embed, + .embed-responsive object, + .embed-responsive video { + position: absolute; + top: 0; + left: 0; + bottom: 0; + height: 100%; + width: 100%; + border: 0; } + +.embed-responsive-16by9 { + padding-bottom: 56.25%; } + +.embed-responsive-4by3 { + padding-bottom: 75%; } + +.well { + min-height: 20px; + padding: 19px; + margin-bottom: 20px; + background-color: #f5f5f5; + border: 1px solid transparent; + border-radius: 3px; + -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05); + box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05); } + .well blockquote { + border-color: #ddd; + border-color: rgba(0, 0, 0, 0.15); } + +.well-lg { + padding: 24px; + border-radius: 3px; } + +.well-sm { + padding: 9px; + border-radius: 3px; } + +.close { + float: right; + font-size: 22.5px; + font-weight: normal; + line-height: 1; + color: #000; + text-shadow: none; + opacity: 0.2; + filter: alpha(opacity=20); } + .close:hover, .close:focus { + color: #000; + text-decoration: none; + cursor: pointer; + opacity: 0.5; + filter: alpha(opacity=50); } + +button.close { + padding: 0; + cursor: pointer; + background: transparent; + border: 0; + -webkit-appearance: none; } + +.modal-open { + overflow: hidden; } + +.modal { + display: none; + overflow: hidden; + position: fixed; + top: 0; + right: 0; + bottom: 0; + left: 0; + z-index: 1050; + -webkit-overflow-scrolling: touch; + outline: 0; } + .modal.fade .modal-dialog { + -webkit-transform: translate(0, -25%); + -ms-transform: translate(0, -25%); + -o-transform: translate(0, -25%); + transform: translate(0, -25%); + -webkit-transition: -webkit-transform 0.3s ease-out; + -moz-transition: -moz-transform 0.3s ease-out; + -o-transition: -o-transform 0.3s ease-out; + transition: transform 0.3s ease-out; } + .modal.in .modal-dialog { + -webkit-transform: translate(0, 0); + -ms-transform: translate(0, 0); + -o-transform: translate(0, 0); + transform: translate(0, 0); } + +.modal-open .modal { + overflow-x: hidden; + overflow-y: auto; } + +.modal-dialog { + position: relative; + width: auto; + margin: 10px; } + +.modal-content { + position: relative; + background-color: #fff; + border: 1px solid #999; + border: 1px solid transparent; + border-radius: 3px; + -webkit-box-shadow: 0 3px 9px rgba(0, 0, 0, 0.5); + box-shadow: 0 3px 9px rgba(0, 0, 0, 0.5); + background-clip: padding-box; + outline: 0; } + +.modal-backdrop { + position: fixed; + top: 0; + right: 0; + bottom: 0; + left: 0; + z-index: 1040; + background-color: #000; } + .modal-backdrop.fade { + opacity: 0; + filter: alpha(opacity=0); } + .modal-backdrop.in { + opacity: 0.5; + filter: alpha(opacity=50); } + +.modal-header { + padding: 15px; + border-bottom: 1px solid transparent; } + .modal-header:before, .modal-header:after { + content: " "; + display: table; } + .modal-header:after { + clear: both; } + +.modal-header .close { + margin-top: -2px; } + +.modal-title { + margin: 0; + line-height: 1.846; } + +.modal-body { + position: relative; + padding: 15px; } + +.modal-footer { + padding: 15px; + text-align: right; + border-top: 1px solid transparent; } + .modal-footer:before, .modal-footer:after { + content: " "; + display: table; } + .modal-footer:after { + clear: both; } + .modal-footer .btn + .btn { + margin-left: 5px; + margin-bottom: 0; } + .modal-footer .btn-group .btn + .btn { + margin-left: -1px; } + .modal-footer .btn-block + .btn-block { + margin-left: 0; } + +.modal-scrollbar-measure { + position: absolute; + top: -9999px; + width: 50px; + height: 50px; + overflow: scroll; } + +@media (min-width: 768px) { + .modal-dialog { + width: 600px; + margin: 30px auto; } + + .modal-content { + -webkit-box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5); + box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5); } + + .modal-sm { + width: 300px; } } +@media (min-width: 992px) { + .modal-lg { + width: 900px; } } +.tooltip { + position: absolute; + z-index: 1070; + display: block; + font-family: "Source Sans Pro", "Helvetica Neue", Helvetica, Arial, sans-serif; + font-style: normal; + font-weight: normal; + letter-spacing: normal; + line-break: auto; + line-height: 1.846; + text-align: left; + text-align: start; + text-decoration: none; + text-shadow: none; + text-transform: none; + white-space: normal; + word-break: normal; + word-spacing: normal; + word-wrap: normal; + font-size: 13px; + opacity: 0; + filter: alpha(opacity=0); } + .tooltip.in { + opacity: 0.9; + filter: alpha(opacity=90); } + .tooltip.top { + margin-top: -3px; + padding: 5px 0; } + .tooltip.right { + margin-left: 3px; + padding: 0 5px; } + .tooltip.bottom { + margin-top: 3px; + padding: 5px 0; } + .tooltip.left { + margin-left: -3px; + padding: 0 5px; } + +.tooltip-inner { + max-width: 200px; + padding: 3px 8px; + color: #fff; + text-align: center; + background-color: #727272; + border-radius: 3px; } + +.tooltip-arrow { + position: absolute; + width: 0; + height: 0; + border-color: transparent; + border-style: solid; } + +.tooltip.top .tooltip-arrow { + bottom: 0; + left: 50%; + margin-left: -5px; + border-width: 5px 5px 0; + border-top-color: #727272; } +.tooltip.top-left .tooltip-arrow { + bottom: 0; + right: 5px; + margin-bottom: -5px; + border-width: 5px 5px 0; + border-top-color: #727272; } +.tooltip.top-right .tooltip-arrow { + bottom: 0; + left: 5px; + margin-bottom: -5px; + border-width: 5px 5px 0; + border-top-color: #727272; } +.tooltip.right .tooltip-arrow { + top: 50%; + left: 0; + margin-top: -5px; + border-width: 5px 5px 5px 0; + border-right-color: #727272; } +.tooltip.left .tooltip-arrow { + top: 50%; + right: 0; + margin-top: -5px; + border-width: 5px 0 5px 5px; + border-left-color: #727272; } +.tooltip.bottom .tooltip-arrow { + top: 0; + left: 50%; + margin-left: -5px; + border-width: 0 5px 5px; + border-bottom-color: #727272; } +.tooltip.bottom-left .tooltip-arrow { + top: 0; + right: 5px; + margin-top: -5px; + border-width: 0 5px 5px; + border-bottom-color: #727272; } +.tooltip.bottom-right .tooltip-arrow { + top: 0; + left: 5px; + margin-top: -5px; + border-width: 0 5px 5px; + border-bottom-color: #727272; } + +.popover { + position: absolute; + top: 0; + left: 0; + z-index: 1060; + display: none; + max-width: 276px; + padding: 1px; + font-family: "Source Sans Pro", "Helvetica Neue", Helvetica, Arial, sans-serif; + font-style: normal; + font-weight: normal; + letter-spacing: normal; + line-break: auto; + line-height: 1.846; + text-align: left; + text-align: start; + text-decoration: none; + text-shadow: none; + text-transform: none; + white-space: normal; + word-break: normal; + word-spacing: normal; + word-wrap: normal; + font-size: 15px; + background-color: #fff; + background-clip: padding-box; + border: 1px solid transparent; + border: 1px solid transparent; + border-radius: 3px; + -webkit-box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2); + box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2); } + .popover.top { + margin-top: -10px; } + .popover.right { + margin-left: 10px; } + .popover.bottom { + margin-top: 10px; } + .popover.left { + margin-left: -10px; } + +.popover-title { + margin: 0; + padding: 8px 14px; + font-size: 15px; + background-color: #f7f7f7; + border-bottom: 1px solid #ebebeb; + border-radius: 2px 2px 0 0; } + +.popover-content { + padding: 9px 14px; } + +.popover > .arrow, .popover > .arrow:after { + position: absolute; + display: block; + width: 0; + height: 0; + border-color: transparent; + border-style: solid; } + +.popover > .arrow { + border-width: 11px; } + +.popover > .arrow:after { + border-width: 10px; + content: ""; } + +.popover.top > .arrow { + left: 50%; + margin-left: -11px; + border-bottom-width: 0; + border-top-color: transparent; + border-top-color: fadein(transparent, 12%); + bottom: -11px; } + .popover.top > .arrow:after { + content: " "; + bottom: 1px; + margin-left: -10px; + border-bottom-width: 0; + border-top-color: #fff; } +.popover.right > .arrow { + top: 50%; + left: -11px; + margin-top: -11px; + border-left-width: 0; + border-right-color: transparent; + border-right-color: fadein(transparent, 12%); } + .popover.right > .arrow:after { + content: " "; + left: 1px; + bottom: -10px; + border-left-width: 0; + border-right-color: #fff; } +.popover.bottom > .arrow { + left: 50%; + margin-left: -11px; + border-top-width: 0; + border-bottom-color: transparent; + border-bottom-color: fadein(transparent, 12%); + top: -11px; } + .popover.bottom > .arrow:after { + content: " "; + top: 1px; + margin-left: -10px; + border-top-width: 0; + border-bottom-color: #fff; } +.popover.left > .arrow { + top: 50%; + right: -11px; + margin-top: -11px; + border-right-width: 0; + border-left-color: transparent; + border-left-color: fadein(transparent, 12%); } + .popover.left > .arrow:after { + content: " "; + right: 1px; + border-right-width: 0; + border-left-color: #fff; + bottom: -10px; } + +.carousel { + position: relative; } + +.carousel-inner { + position: relative; + overflow: hidden; + width: 100%; } + .carousel-inner > .item { + display: none; + position: relative; + -webkit-transition: 0.6s ease-in-out left; + -o-transition: 0.6s ease-in-out left; + transition: 0.6s ease-in-out left; } + .carousel-inner > .item > img, + .carousel-inner > .item > a > img { + display: block; + max-width: 100%; + height: auto; + line-height: 1; } + @media all and (transform-3d), (-webkit-transform-3d) { + .carousel-inner > .item { + -webkit-transition: -webkit-transform 0.6s ease-in-out; + -moz-transition: -moz-transform 0.6s ease-in-out; + -o-transition: -o-transform 0.6s ease-in-out; + transition: transform 0.6s ease-in-out; + -webkit-backface-visibility: hidden; + -moz-backface-visibility: hidden; + backface-visibility: hidden; + -webkit-perspective: 1000px; + -moz-perspective: 1000px; + perspective: 1000px; } + .carousel-inner > .item.next, .carousel-inner > .item.active.right { + -webkit-transform: translate3d(100%, 0, 0); + transform: translate3d(100%, 0, 0); + left: 0; } + .carousel-inner > .item.prev, .carousel-inner > .item.active.left { + -webkit-transform: translate3d(-100%, 0, 0); + transform: translate3d(-100%, 0, 0); + left: 0; } + .carousel-inner > .item.next.left, .carousel-inner > .item.prev.right, .carousel-inner > .item.active { + -webkit-transform: translate3d(0, 0, 0); + transform: translate3d(0, 0, 0); + left: 0; } } + .carousel-inner > .active, + .carousel-inner > .next, + .carousel-inner > .prev { + display: block; } + .carousel-inner > .active { + left: 0; } + .carousel-inner > .next, + .carousel-inner > .prev { + position: absolute; + top: 0; + width: 100%; } + .carousel-inner > .next { + left: 100%; } + .carousel-inner > .prev { + left: -100%; } + .carousel-inner > .next.left, + .carousel-inner > .prev.right { + left: 0; } + .carousel-inner > .active.left { + left: -100%; } + .carousel-inner > .active.right { + left: 100%; } + +.carousel-control { + position: absolute; + top: 0; + left: 0; + bottom: 0; + width: 15%; + opacity: 0.5; + filter: alpha(opacity=50); + font-size: 20px; + color: #fff; + text-align: center; + text-shadow: 0 1px 2px rgba(0, 0, 0, 0.6); + background-color: transparent; } + .carousel-control.left { + background-image: -webkit-linear-gradient(left, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%); + background-image: -o-linear-gradient(left, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%); + background-image: linear-gradient(to right, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%); + background-repeat: repeat-x; + filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#80000000', endColorstr='#00000000', GradientType=1); } + .carousel-control.right { + left: auto; + right: 0; + background-image: -webkit-linear-gradient(left, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%); + background-image: -o-linear-gradient(left, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%); + background-image: linear-gradient(to right, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%); + background-repeat: repeat-x; + filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#00000000', endColorstr='#80000000', GradientType=1); } + .carousel-control:hover, .carousel-control:focus { + outline: 0; + color: #fff; + text-decoration: none; + opacity: 0.9; + filter: alpha(opacity=90); } + .carousel-control .icon-prev, + .carousel-control .icon-next, + .carousel-control .glyphicon-chevron-left, + .carousel-control .glyphicon-chevron-right { + position: absolute; + top: 50%; + margin-top: -10px; + z-index: 5; + display: inline-block; } + .carousel-control .icon-prev, + .carousel-control .glyphicon-chevron-left { + left: 50%; + margin-left: -10px; } + .carousel-control .icon-next, + .carousel-control .glyphicon-chevron-right { + right: 50%; + margin-right: -10px; } + .carousel-control .icon-prev, + .carousel-control .icon-next { + width: 20px; + height: 20px; + line-height: 1; + font-family: serif; } + .carousel-control .icon-prev:before { + content: '\2039'; } + .carousel-control .icon-next:before { + content: '\203a'; } + +.carousel-indicators { + position: absolute; + bottom: 10px; + left: 50%; + z-index: 15; + width: 60%; + margin-left: -30%; + padding-left: 0; + list-style: none; + text-align: center; } + .carousel-indicators li { + display: inline-block; + width: 10px; + height: 10px; + margin: 1px; + text-indent: -999px; + border: 1px solid #fff; + border-radius: 10px; + cursor: pointer; + background-color: #000 \9; + background-color: transparent; } + .carousel-indicators .active { + margin: 0; + width: 12px; + height: 12px; + background-color: #fff; } + +.carousel-caption { + position: absolute; + left: 15%; + right: 15%; + bottom: 20px; + z-index: 10; + padding-top: 20px; + padding-bottom: 20px; + color: #fff; + text-align: center; + text-shadow: 0 1px 2px rgba(0, 0, 0, 0.6); } + .carousel-caption .btn { + text-shadow: none; } + +@media screen and (min-width: 768px) { + .carousel-control .glyphicon-chevron-left, + .carousel-control .glyphicon-chevron-right, + .carousel-control .icon-prev, + .carousel-control .icon-next { + width: 30px; + height: 30px; + margin-top: -10px; + font-size: 30px; } + .carousel-control .glyphicon-chevron-left, + .carousel-control .icon-prev { + margin-left: -10px; } + .carousel-control .glyphicon-chevron-right, + .carousel-control .icon-next { + margin-right: -10px; } + + .carousel-caption { + left: 20%; + right: 20%; + padding-bottom: 30px; } + + .carousel-indicators { + bottom: 20px; } } +.clearfix:before, .clearfix:after { + content: " "; + display: table; } +.clearfix:after { + clear: both; } + +.center-block { + display: block; + margin-left: auto; + margin-right: auto; } + +.pull-right { + float: right !important; } + +.pull-left { + float: left !important; } + +.hide { + display: none !important; } + +.show { + display: block !important; } + +.invisible { + visibility: hidden; } + +.text-hide { + font: 0/0 a; + color: transparent; + text-shadow: none; + background-color: transparent; + border: 0; } + +.hidden { + display: none !important; } + +.affix { + position: fixed; } + +@-ms-viewport { + width: device-width; } +.visible-xs { + display: none !important; } + +.visible-sm { + display: none !important; } + +.visible-md { + display: none !important; } + +.visible-lg { + display: none !important; } + +.visible-xs-block, +.visible-xs-inline, +.visible-xs-inline-block, +.visible-sm-block, +.visible-sm-inline, +.visible-sm-inline-block, +.visible-md-block, +.visible-md-inline, +.visible-md-inline-block, +.visible-lg-block, +.visible-lg-inline, +.visible-lg-inline-block { + display: none !important; } + +@media (max-width: 767px) { + .visible-xs { + display: block !important; } + + table.visible-xs { + display: table !important; } + + tr.visible-xs { + display: table-row !important; } + + th.visible-xs, + td.visible-xs { + display: table-cell !important; } } +@media (max-width: 767px) { + .visible-xs-block { + display: block !important; } } + +@media (max-width: 767px) { + .visible-xs-inline { + display: inline !important; } } + +@media (max-width: 767px) { + .visible-xs-inline-block { + display: inline-block !important; } } + +@media (min-width: 768px) and (max-width: 991px) { + .visible-sm { + display: block !important; } + + table.visible-sm { + display: table !important; } + + tr.visible-sm { + display: table-row !important; } + + th.visible-sm, + td.visible-sm { + display: table-cell !important; } } +@media (min-width: 768px) and (max-width: 991px) { + .visible-sm-block { + display: block !important; } } + +@media (min-width: 768px) and (max-width: 991px) { + .visible-sm-inline { + display: inline !important; } } + +@media (min-width: 768px) and (max-width: 991px) { + .visible-sm-inline-block { + display: inline-block !important; } } + +@media (min-width: 992px) and (max-width: 1199px) { + .visible-md { + display: block !important; } + + table.visible-md { + display: table !important; } + + tr.visible-md { + display: table-row !important; } + + th.visible-md, + td.visible-md { + display: table-cell !important; } } +@media (min-width: 992px) and (max-width: 1199px) { + .visible-md-block { + display: block !important; } } + +@media (min-width: 992px) and (max-width: 1199px) { + .visible-md-inline { + display: inline !important; } } + +@media (min-width: 992px) and (max-width: 1199px) { + .visible-md-inline-block { + display: inline-block !important; } } + +@media (min-width: 1200px) { + .visible-lg { + display: block !important; } + + table.visible-lg { + display: table !important; } + + tr.visible-lg { + display: table-row !important; } + + th.visible-lg, + td.visible-lg { + display: table-cell !important; } } +@media (min-width: 1200px) { + .visible-lg-block { + display: block !important; } } + +@media (min-width: 1200px) { + .visible-lg-inline { + display: inline !important; } } + +@media (min-width: 1200px) { + .visible-lg-inline-block { + display: inline-block !important; } } + +@media (max-width: 767px) { + .hidden-xs { + display: none !important; } } +@media (min-width: 768px) and (max-width: 991px) { + .hidden-sm { + display: none !important; } } +@media (min-width: 992px) and (max-width: 1199px) { + .hidden-md { + display: none !important; } } +@media (min-width: 1200px) { + .hidden-lg { + display: none !important; } } +.visible-print { + display: none !important; } + +@media print { + .visible-print { + display: block !important; } + + table.visible-print { + display: table !important; } + + tr.visible-print { + display: table-row !important; } + + th.visible-print, + td.visible-print { + display: table-cell !important; } } +.visible-print-block { + display: none !important; } + @media print { + .visible-print-block { + display: block !important; } } + +.visible-print-inline { + display: none !important; } + @media print { + .visible-print-inline { + display: inline !important; } } + +.visible-print-inline-block { + display: none !important; } + @media print { + .visible-print-inline-block { + display: inline-block !important; } } + +@media print { + .hidden-print { + display: none !important; } } +/*! + * tidyverse theme + * Copyright 2016 RStudio, Inc. + */ +.navbar { + border: none; + -webkit-box-shadow: 0 3px 15px 0px rgba(0, 0, 0, 0.1); + box-shadow: 0 3px 15px 0px rgba(0, 0, 0, 0.1); + min-height: 50px; + padding: 5px 0; } + .navbar-brand { + font-family: "Source Code Pro", Menlo, Monaco, Consolas, "Courier New", monospace; + font-weight: normal; + font-size: 32px; + padding: 0 0 0 54px; + height: 50px; + line-height: 50px; + background-image: url(../logo.png); + background-size: 32px auto; + background-repeat: no-repeat; + background-position: 15px center; } + .navbar-nav li a { + padding-top: 10px; + padding-bottom: 0; + line-height: inherit; } + .navbar-inverse .navbar-form input[type=text], + .navbar-inverse .navbar-form input[type=password] { + color: #fff; + -webkit-box-shadow: inset 0 -1px 0 #d8e8f6; + box-shadow: inset 0 -1px 0 #d8e8f6; } + .navbar-inverse .navbar-form input[type=text]::-moz-placeholder, + .navbar-inverse .navbar-form input[type=password]::-moz-placeholder { + color: #d8e8f6; + opacity: 1; } + .navbar-inverse .navbar-form input[type=text]:-ms-input-placeholder, + .navbar-inverse .navbar-form input[type=password]:-ms-input-placeholder { + color: #d8e8f6; } + .navbar-inverse .navbar-form input[type=text]::-webkit-input-placeholder, + .navbar-inverse .navbar-form input[type=password]::-webkit-input-placeholder { + color: #d8e8f6; } + .navbar-inverse .navbar-form input[type=text]:focus, + .navbar-inverse .navbar-form input[type=password]:focus { + -webkit-box-shadow: inset 0 -2px 0 #fff; + box-shadow: inset 0 -2px 0 #fff; } + +.btn-default:focus { + background-color: #fff; } +.btn-default:hover, .btn-default:active:hover { + background-color: #f0f0f0; } +.btn-default:active { + -webkit-box-shadow: 2px 2px 4px rgba(0, 0, 0, 0.4); + box-shadow: 2px 2px 4px rgba(0, 0, 0, 0.4); } + +.btn-primary:focus { + background-color: #5a9ddb; } +.btn-primary:hover, .btn-primary:active:hover { + background-color: #418ed6; } +.btn-primary:active { + -webkit-box-shadow: 2px 2px 4px rgba(0, 0, 0, 0.4); + box-shadow: 2px 2px 4px rgba(0, 0, 0, 0.4); } + +.btn-success:focus { + background-color: #4CAF50; } +.btn-success:hover, .btn-success:active:hover { + background-color: #439a46; } +.btn-success:active { + -webkit-box-shadow: 2px 2px 4px rgba(0, 0, 0, 0.4); + box-shadow: 2px 2px 4px rgba(0, 0, 0, 0.4); } + +.btn-info:focus { + background-color: #9C27B0; } +.btn-info:hover, .btn-info:active:hover { + background-color: #862197; } +.btn-info:active { + -webkit-box-shadow: 2px 2px 4px rgba(0, 0, 0, 0.4); + box-shadow: 2px 2px 4px rgba(0, 0, 0, 0.4); } + +.btn-warning:focus { + background-color: #ff9800; } +.btn-warning:hover, .btn-warning:active:hover { + background-color: #e08600; } +.btn-warning:active { + -webkit-box-shadow: 2px 2px 4px rgba(0, 0, 0, 0.4); + box-shadow: 2px 2px 4px rgba(0, 0, 0, 0.4); } + +.btn-danger:focus { + background-color: #e51c23; } +.btn-danger:hover, .btn-danger:active:hover { + background-color: #cb171e; } +.btn-danger:active { + -webkit-box-shadow: 2px 2px 4px rgba(0, 0, 0, 0.4); + box-shadow: 2px 2px 4px rgba(0, 0, 0, 0.4); } + +.btn-link:focus { + background-color: #fff; } +.btn-link:hover, .btn-link:active:hover { + background-color: #f0f0f0; } +.btn-link:active { + -webkit-box-shadow: 2px 2px 4px rgba(0, 0, 0, 0.4); + box-shadow: 2px 2px 4px rgba(0, 0, 0, 0.4); } + +.btn { + text-transform: uppercase; + border: none; + -webkit-box-shadow: 1px 1px 4px rgba(0, 0, 0, 0.4); + box-shadow: 1px 1px 4px rgba(0, 0, 0, 0.4); + -webkit-transition: all 0.4s; + -o-transition: all 0.4s; + transition: all 0.4s; + position: relative; } + .btn:after { + content: ""; + display: block; + position: absolute; + width: 100%; + height: 100%; + top: 0; + left: 0; + background-image: -webkit-radial-gradient(circle, #000 10%, transparent 10.01%); + background-image: radial-gradient(circle, #000 10%, transparent 10.01%); + background-repeat: no-repeat; + background-size: 1000% 1000%; + background-position: 50%; + opacity: 0; + pointer-events: none; + transition: background .5s, opacity 1s; } + .btn:active:after { + background-size: 0% 0%; + opacity: .2; + transition: 0s; } + .btn-link { + border-radius: 3px; + -webkit-box-shadow: none; + box-shadow: none; + color: #444; } + .btn-link:hover, .btn-link:focus { + -webkit-box-shadow: none; + box-shadow: none; + color: #444; + text-decoration: none; } + .btn-default.disabled { + background-color: rgba(0, 0, 0, 0.1); + color: rgba(0, 0, 0, 0.4); + opacity: 1; } + +.btn-group .btn + .btn, +.btn-group .btn + .btn-group, +.btn-group .btn-group + .btn, +.btn-group .btn-group + .btn-group { + margin-left: 0; } +.btn-group-vertical > .btn + .btn, +.btn-group-vertical > .btn + .btn-group, +.btn-group-vertical > .btn-group + .btn, +.btn-group-vertical > .btn-group + .btn-group { + margin-top: 0; } + +body { + -webkit-font-smoothing: antialiased; + letter-spacing: .1px; } + +p { + margin: 0 0 1em; } + +input, +button { + -webkit-font-smoothing: antialiased; + letter-spacing: .1px; } + +a { + -webkit-transition: all 0.25s; + -o-transition: all 0.25s; + transition: all 0.25s; } + +.table-hover > tbody > tr, +.table-hover > tbody > tr > th, +.table-hover > tbody > tr > td { + -webkit-transition: all 0.2s; + -o-transition: all 0.2s; + transition: all 0.2s; } + +label { + font-weight: normal; } + +textarea, +textarea.form-control, +input.form-control, +input[type=text], +input[type=password], +input[type=email], +input[type=number], +[type=text].form-control, +[type=password].form-control, +[type=email].form-control, +[type=tel].form-control, +[contenteditable].form-control { + padding: 0; + border: none; + border-radius: 0; + -webkit-appearance: none; + -webkit-box-shadow: inset 0 -1px 0 #ddd; + box-shadow: inset 0 -1px 0 #ddd; + font-size: 16px; } + textarea:focus, + textarea.form-control:focus, + input.form-control:focus, + input[type=text]:focus, + input[type=password]:focus, + input[type=email]:focus, + input[type=number]:focus, + [type=text].form-control:focus, + [type=password].form-control:focus, + [type=email].form-control:focus, + [type=tel].form-control:focus, + [contenteditable].form-control:focus { + -webkit-box-shadow: inset 0 -2px 0 #5a9ddb; + box-shadow: inset 0 -2px 0 #5a9ddb; } + textarea[disabled], textarea[readonly], + textarea.form-control[disabled], + textarea.form-control[readonly], + input.form-control[disabled], + input.form-control[readonly], + input[type=text][disabled], + input[type=text][readonly], + input[type=password][disabled], + input[type=password][readonly], + input[type=email][disabled], + input[type=email][readonly], + input[type=number][disabled], + input[type=number][readonly], + [type=text].form-control[disabled], + [type=text].form-control[readonly], + [type=password].form-control[disabled], + [type=password].form-control[readonly], + [type=email].form-control[disabled], + [type=email].form-control[readonly], + [type=tel].form-control[disabled], + [type=tel].form-control[readonly], + [contenteditable].form-control[disabled], + [contenteditable].form-control[readonly] { + -webkit-box-shadow: none; + box-shadow: none; + border-bottom: 1px dotted #ddd; } + textarea.input-sm, .input-group-sm > textarea.form-control, + .input-group-sm > textarea.input-group-addon, + .input-group-sm > .input-group-btn > textarea.btn, + textarea.form-control.input-sm, + .input-group-sm > textarea.form-control, + .input-group-sm > .input-group-btn > textarea.form-control.btn, + input.form-control.input-sm, + .input-group-sm > input.form-control, + .input-group-sm > .input-group-btn > input.form-control.btn, + input[type=text].input-sm, + .input-group-sm > input[type=text].form-control, + .input-group-sm > input[type=text].input-group-addon, + .input-group-sm > .input-group-btn > input[type=text].btn, + input[type=password].input-sm, + .input-group-sm > input[type=password].form-control, + .input-group-sm > input[type=password].input-group-addon, + .input-group-sm > .input-group-btn > input[type=password].btn, + input[type=email].input-sm, + .input-group-sm > input[type=email].form-control, + .input-group-sm > input[type=email].input-group-addon, + .input-group-sm > .input-group-btn > input[type=email].btn, + input[type=number].input-sm, + .input-group-sm > input[type=number].form-control, + .input-group-sm > input[type=number].input-group-addon, + .input-group-sm > .input-group-btn > input[type=number].btn, + [type=text].form-control.input-sm, + .input-group-sm > [type=text].form-control, + .input-group-sm > .input-group-btn > [type=text].form-control.btn, + [type=password].form-control.input-sm, + .input-group-sm > [type=password].form-control, + .input-group-sm > .input-group-btn > [type=password].form-control.btn, + [type=email].form-control.input-sm, + .input-group-sm > [type=email].form-control, + .input-group-sm > .input-group-btn > [type=email].form-control.btn, + [type=tel].form-control.input-sm, + .input-group-sm > [type=tel].form-control, + .input-group-sm > .input-group-btn > [type=tel].form-control.btn, + [contenteditable].form-control.input-sm, + .input-group-sm > [contenteditable].form-control, + .input-group-sm > .input-group-btn > [contenteditable].form-control.btn { + font-size: 13px; } + textarea.input-lg, .input-group-lg > textarea.form-control, + .input-group-lg > textarea.input-group-addon, + .input-group-lg > .input-group-btn > textarea.btn, + textarea.form-control.input-lg, + .input-group-lg > textarea.form-control, + .input-group-lg > .input-group-btn > textarea.form-control.btn, + input.form-control.input-lg, + .input-group-lg > input.form-control, + .input-group-lg > .input-group-btn > input.form-control.btn, + input[type=text].input-lg, + .input-group-lg > input[type=text].form-control, + .input-group-lg > input[type=text].input-group-addon, + .input-group-lg > .input-group-btn > input[type=text].btn, + input[type=password].input-lg, + .input-group-lg > input[type=password].form-control, + .input-group-lg > input[type=password].input-group-addon, + .input-group-lg > .input-group-btn > input[type=password].btn, + input[type=email].input-lg, + .input-group-lg > input[type=email].form-control, + .input-group-lg > input[type=email].input-group-addon, + .input-group-lg > .input-group-btn > input[type=email].btn, + input[type=number].input-lg, + .input-group-lg > input[type=number].form-control, + .input-group-lg > input[type=number].input-group-addon, + .input-group-lg > .input-group-btn > input[type=number].btn, + [type=text].form-control.input-lg, + .input-group-lg > [type=text].form-control, + .input-group-lg > .input-group-btn > [type=text].form-control.btn, + [type=password].form-control.input-lg, + .input-group-lg > [type=password].form-control, + .input-group-lg > .input-group-btn > [type=password].form-control.btn, + [type=email].form-control.input-lg, + .input-group-lg > [type=email].form-control, + .input-group-lg > .input-group-btn > [type=email].form-control.btn, + [type=tel].form-control.input-lg, + .input-group-lg > [type=tel].form-control, + .input-group-lg > .input-group-btn > [type=tel].form-control.btn, + [contenteditable].form-control.input-lg, + .input-group-lg > [contenteditable].form-control, + .input-group-lg > .input-group-btn > [contenteditable].form-control.btn { + font-size: 19px; } + +select, +select.form-control { + border: 0; + border-radius: 0; + -webkit-appearance: none; + -moz-appearance: none; + appearance: none; + padding-left: 0; + padding-right: 0\9; + background-image: url(data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABoAAAAaCAMAAACelLz8AAAAJ1BMVEVmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmaP/QSjAAAADHRSTlMAAgMJC0uWpKa6wMxMdjkoAAAANUlEQVR4AeXJyQEAERAAsNl7Hf3X6xt0QL6JpZWq30pdvdadme+0PMdzvHm8YThHcT1H7K0BtOMDniZhWOgAAAAASUVORK5CYII=); + background-size: 13px; + background-repeat: no-repeat; + background-position: right center; + -webkit-box-shadow: inset 0 -1px 0 #ddd; + box-shadow: inset 0 -1px 0 #ddd; + font-size: 16px; + line-height: 1.5; } + select::-ms-expand, + select.form-control::-ms-expand { + display: none; } + select.input-sm, .input-group-sm > select.form-control, + .input-group-sm > select.input-group-addon, + .input-group-sm > .input-group-btn > select.btn, + select.form-control.input-sm, + .input-group-sm > select.form-control, + .input-group-sm > .input-group-btn > select.form-control.btn { + font-size: 13px; } + select.input-lg, .input-group-lg > select.form-control, + .input-group-lg > select.input-group-addon, + .input-group-lg > .input-group-btn > select.btn, + select.form-control.input-lg, + .input-group-lg > select.form-control, + .input-group-lg > .input-group-btn > select.form-control.btn { + font-size: 19px; } + select:focus, + select.form-control:focus { + -webkit-box-shadow: inset 0 -2px 0 #5a9ddb; + box-shadow: inset 0 -2px 0 #5a9ddb; + background-image: url(data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABoAAAAaCAMAAACelLz8AAAAJ1BMVEUhISEhISEhISEhISEhISEhISEhISEhISEhISEhISEhISEhISEhISF8S9ewAAAADHRSTlMAAgMJC0uWpKa6wMxMdjkoAAAANUlEQVR4AeXJyQEAERAAsNl7Hf3X6xt0QL6JpZWq30pdvdadme+0PMdzvHm8YThHcT1H7K0BtOMDniZhWOgAAAAASUVORK5CYII=); } + select[multiple], + select.form-control[multiple] { + background: none; } + +.radio label, +.radio-inline label, +.checkbox label, +.checkbox-inline label { + padding-left: 25px; } +.radio input[type="radio"], +.radio input[type="checkbox"], +.radio-inline input[type="radio"], +.radio-inline input[type="checkbox"], +.checkbox input[type="radio"], +.checkbox input[type="checkbox"], +.checkbox-inline input[type="radio"], +.checkbox-inline input[type="checkbox"] { + margin-left: -25px; } + +input[type="radio"], +.radio input[type="radio"], +.radio-inline input[type="radio"] { + position: relative; + margin-top: 6px; + margin-right: 4px; + vertical-align: top; + border: none; + background-color: transparent; + -webkit-appearance: none; + appearance: none; + cursor: pointer; } + input[type="radio"]:focus, + .radio input[type="radio"]:focus, + .radio-inline input[type="radio"]:focus { + outline: none; } + input[type="radio"]:before, input[type="radio"]:after, + .radio input[type="radio"]:before, + .radio input[type="radio"]:after, + .radio-inline input[type="radio"]:before, + .radio-inline input[type="radio"]:after { + content: ""; + display: block; + width: 18px; + height: 18px; + border-radius: 50%; + -webkit-transition: 240ms; + -o-transition: 240ms; + transition: 240ms; } + input[type="radio"]:before, + .radio input[type="radio"]:before, + .radio-inline input[type="radio"]:before { + position: absolute; + left: 0; + top: -3px; + background-color: #5a9ddb; + -webkit-transform: scale(0); + -ms-transform: scale(0); + -o-transform: scale(0); + transform: scale(0); } + input[type="radio"]:after, + .radio input[type="radio"]:after, + .radio-inline input[type="radio"]:after { + position: relative; + top: -3px; + border: 2px solid #666; } + input[type="radio"]:checked:before, + .radio input[type="radio"]:checked:before, + .radio-inline input[type="radio"]:checked:before { + -webkit-transform: scale(0.5); + -ms-transform: scale(0.5); + -o-transform: scale(0.5); + transform: scale(0.5); } + input[type="radio"]:disabled:checked:before, + .radio input[type="radio"]:disabled:checked:before, + .radio-inline input[type="radio"]:disabled:checked:before { + background-color: #bbb; } + input[type="radio"]:checked:after, + .radio input[type="radio"]:checked:after, + .radio-inline input[type="radio"]:checked:after { + border-color: #5a9ddb; } + input[type="radio"]:disabled:after, input[type="radio"]:disabled:checked:after, + .radio input[type="radio"]:disabled:after, + .radio input[type="radio"]:disabled:checked:after, + .radio-inline input[type="radio"]:disabled:after, + .radio-inline input[type="radio"]:disabled:checked:after { + border-color: #bbb; } + +input[type="checkbox"], +.checkbox input[type="checkbox"], +.checkbox-inline input[type="checkbox"] { + position: relative; + border: none; + margin-bottom: -4px; + -webkit-appearance: none; + appearance: none; + cursor: pointer; } + input[type="checkbox"]:focus, + .checkbox input[type="checkbox"]:focus, + .checkbox-inline input[type="checkbox"]:focus { + outline: none; } + input[type="checkbox"]:focus:after, + .checkbox input[type="checkbox"]:focus:after, + .checkbox-inline input[type="checkbox"]:focus:after { + border-color: #5a9ddb; } + input[type="checkbox"]:after, + .checkbox input[type="checkbox"]:after, + .checkbox-inline input[type="checkbox"]:after { + content: ""; + display: block; + width: 18px; + height: 18px; + margin-top: -2px; + margin-right: 5px; + border: 2px solid #666; + border-radius: 2px; + -webkit-transition: 240ms; + -o-transition: 240ms; + transition: 240ms; } + input[type="checkbox"]:checked:before, + .checkbox input[type="checkbox"]:checked:before, + .checkbox-inline input[type="checkbox"]:checked:before { + content: ""; + position: absolute; + top: 0; + left: 6px; + display: table; + width: 6px; + height: 12px; + border: 2px solid #fff; + border-top-width: 0; + border-left-width: 0; + -webkit-transform: rotate(45deg); + -ms-transform: rotate(45deg); + -o-transform: rotate(45deg); + transform: rotate(45deg); } + input[type="checkbox"]:checked:after, + .checkbox input[type="checkbox"]:checked:after, + .checkbox-inline input[type="checkbox"]:checked:after { + background-color: #5a9ddb; + border-color: #5a9ddb; } + input[type="checkbox"]:disabled:after, + .checkbox input[type="checkbox"]:disabled:after, + .checkbox-inline input[type="checkbox"]:disabled:after { + border-color: #bbb; } + input[type="checkbox"]:disabled:checked:after, + .checkbox input[type="checkbox"]:disabled:checked:after, + .checkbox-inline input[type="checkbox"]:disabled:checked:after { + background-color: #bbb; + border-color: transparent; } + +.has-warning input:not([type=checkbox]), +.has-warning .form-control, +.has-warning input.form-control[readonly], +.has-warning input[type=text][readonly], +.has-warning [type=text].form-control[readonly], +.has-warning input:not([type=checkbox]):focus, +.has-warning .form-control:focus { + border-bottom: none; + -webkit-box-shadow: inset 0 -2px 0 #ff9800; + box-shadow: inset 0 -2px 0 #ff9800; } + +.has-error input:not([type=checkbox]), +.has-error .form-control, +.has-error input.form-control[readonly], +.has-error input[type=text][readonly], +.has-error [type=text].form-control[readonly], +.has-error input:not([type=checkbox]):focus, +.has-error .form-control:focus { + border-bottom: none; + -webkit-box-shadow: inset 0 -2px 0 #e51c23; + box-shadow: inset 0 -2px 0 #e51c23; } + +.has-success input:not([type=checkbox]), +.has-success .form-control, +.has-success input.form-control[readonly], +.has-success input[type=text][readonly], +.has-success [type=text].form-control[readonly], +.has-success input:not([type=checkbox]):focus, +.has-success .form-control:focus { + border-bottom: none; + -webkit-box-shadow: inset 0 -2px 0 #4CAF50; + box-shadow: inset 0 -2px 0 #4CAF50; } + +.has-warning .input-group-addon, .has-error .input-group-addon, .has-success .input-group-addon { + color: #666; + border-color: transparent; + background-color: transparent; } + +.form-group-lg select, +.form-group-lg select.form-control { + line-height: 1.5; } + +.nav-tabs > li > a, +.nav-tabs > li > a:focus { + margin-right: 0; + background-color: transparent; + border: none; + color: #444; + -webkit-box-shadow: inset 0 -1px 0 #ddd; + box-shadow: inset 0 -1px 0 #ddd; + -webkit-transition: all 0.2s; + -o-transition: all 0.2s; + transition: all 0.2s; } + .nav-tabs > li > a:hover, + .nav-tabs > li > a:focus:hover { + background-color: transparent; + -webkit-box-shadow: inset 0 -2px 0 #5a9ddb; + box-shadow: inset 0 -2px 0 #5a9ddb; + color: #5a9ddb; } +.nav-tabs > li.active > a, .nav-tabs > li.active > a:focus { + border: none; + -webkit-box-shadow: inset 0 -2px 0 #5a9ddb; + box-shadow: inset 0 -2px 0 #5a9ddb; + color: #5a9ddb; } + .nav-tabs > li.active > a:hover, .nav-tabs > li.active > a:focus:hover { + border: none; + color: #5a9ddb; } +.nav-tabs > li.disabled > a { + -webkit-box-shadow: inset 0 -1px 0 #ddd; + box-shadow: inset 0 -1px 0 #ddd; } +.nav-tabs.nav-justified > li > a, .nav-tabs.nav-justified > li > a:hover, .nav-tabs.nav-justified > li > a:focus, .nav-tabs.nav-justified > .active > a, .nav-tabs.nav-justified > .active > a:hover, .nav-tabs.nav-justified > .active > a:focus { + border: none; } +.nav-tabs .dropdown-menu { + margin-top: 0; } + +.dropdown-menu { + margin-top: 0; + border: none; + -webkit-box-shadow: 0 1px 4px rgba(0, 0, 0, 0.3); + box-shadow: 0 1px 4px rgba(0, 0, 0, 0.3); } + +.alert { + border: none; + color: #fff; } + .alert-success { + background-color: #4CAF50; } + .alert-info { + background-color: #9C27B0; } + .alert-warning { + background-color: #ff9800; } + .alert-danger { + background-color: #e51c23; } + .alert a:not(.close):not(.btn), + .alert .alert-link { + color: #fff; + font-weight: bold; } + .alert .close { + color: #fff; } + +.badge { + padding: 4px 6px 4px; } + +.progress { + position: relative; + z-index: 1; + height: 6px; + border-radius: 0; + -webkit-box-shadow: none; + box-shadow: none; } + .progress-bar { + -webkit-box-shadow: none; + box-shadow: none; } + .progress-bar:last-child { + border-radius: 0 3px 3px 0; } + .progress-bar:last-child:before { + display: block; + content: ""; + position: absolute; + width: 100%; + height: 100%; + left: 0; + right: 0; + z-index: -1; + background-color: #edf4fb; } + .progress-bar-success:last-child.progress-bar:before { + background-color: #c7e7c8; } + .progress-bar-info:last-child.progress-bar:before { + background-color: #edc9f3; } + .progress-bar-warning:last-child.progress-bar:before { + background-color: #ffe0b3; } + .progress-bar-danger:last-child.progress-bar:before { + background-color: #f28e92; } + +.close { + font-size: 34px; + font-weight: 300; + line-height: 24px; + opacity: 0.6; + -webkit-transition: all 0.2s; + -o-transition: all 0.2s; + transition: all 0.2s; } + .close:hover { + opacity: 1; } + +.list-group-item { + padding: 15px; } +.list-group-item-text { + color: #bbb; } + +.well { + border-radius: 0; + -webkit-box-shadow: none; + box-shadow: none; } + +.panel { + border: none; + border-radius: 2px; + -webkit-box-shadow: 0 1px 4px rgba(0, 0, 0, 0.3); + box-shadow: 0 1px 4px rgba(0, 0, 0, 0.3); } + .panel-heading { + border-bottom: none; } + .panel-footer { + border-top: none; } + +.popover { + border: none; + -webkit-box-shadow: 0 1px 4px rgba(0, 0, 0, 0.3); + box-shadow: 0 1px 4px rgba(0, 0, 0, 0.3); } + +.carousel-caption h1, .carousel-caption h2, .carousel-caption h3, .carousel-caption h4, .carousel-caption h5, .carousel-caption h6 { + color: inherit; } + +/*# sourceMappingURL=tidyverse.css.map */ diff --git a/docs/tocBullet.svg b/docs/tocBullet.svg new file mode 100644 index 0000000000..29abb514fc --- /dev/null +++ b/docs/tocBullet.svg @@ -0,0 +1,11 @@ + + + + + + + diff --git a/man/dplyr-package.Rd b/man/dplyr-package.Rd index 2350f3df28..f7b110674b 100644 --- a/man/dplyr-package.Rd +++ b/man/dplyr-package.Rd @@ -62,7 +62,7 @@ Authors: Other contributors: \itemize{ - \item RStudio [copyright holder] + \item RStudio [copyright holder, funder] } }