version 2.0.1

DESCRIPTION

@@ -2,8 +2,8 @@ Package: crqa
 Type: Package
 Title: Recurrence Quantification Analysis for Categorical and
         Continuous Time-Series
-Version: 2.0
-Date: 2020-05-28
+Version: 2.0.1
+Date: 2020-10-29
 Authors@R: c(
     person("Moreno  I.", "Coco", role = c("cre","aut"), 
     email="[email protected]"),
@@ -31,15 +31,15 @@ Description:
     and Wallot (2018) <doi:10.1080/00273171.2018.1512846>
     for further details about the method.
 Depends: R (>= 3.0.0)
-Imports: Matrix, pracma, tseriesChaos, gplots, plot3D, rdist
+Imports: Matrix, pracma, tseriesChaos, gplots, plot3D, FSA, rdist
 License: GPL (>= 2)
 Collate: 'crqa.R' 'crqa_helpers.R' 'drpfromts.R' 'lorenzattractor.R'
         'mdDelay.R' 'mdFnn.R' 'optimizeParam.R' 'piecewiseRQA.R'
         'plotRP.R' 'simts.R' 'spdiags.R' 'wincrqa.R' 'windowdrp.R'
 RoxygenNote: 7.1.0
 LazyData: true
 NeedsCompilation: yes
-Packaged: 2020-06-05 10:08:43 UTC; nak_d
+Packaged: 2020-10-29 11:14:04 UTC; nak_d
 Author: Moreno I. Coco [cre, aut],
   Dan Monster [aut],
   Giuseppe Leonardi [aut],
@@ -48,4 +48,4 @@ Author: Moreno I. Coco [cre, aut],
   James D. Dixon [ctb],
   John C. Nash [ctb]
 Repository: CRAN
-Date/Publication: 2020-06-11 19:10:02 UTC
+Date/Publication: 2020-10-29 11:40:03 UTC

MD5

@@ -1,6 +1,6 @@
-ec2a83b1eebbedfdebf9da4effbe22f0 *DESCRIPTION
-d0d6994e20de47c258cdcf708a0580a5 *NAMESPACE
-4dc3363a73f751b1d7ca6d2539d96ea7 *NEWS.md
+1c92fcecf292a403b571e0b62a3465ef *DESCRIPTION
+bb7766780645c44eb3565570eaeabd85 *NAMESPACE
+12e02f965e6c03518a24d3cf972321d9 *NEWS.md
 781e6090f124daea60ffb1449f28141f *R/crqa.R
 6ea85a41a9ed85025c3e483bfeac54a7 *R/crqa_helpers.R
 56ee6cba73bb998b71a33a9fb546b59e *R/drpfromts.R
@@ -12,8 +12,8 @@ faf8b3d44e48b184df0d04c818408c88 *R/piecewiseRQA.R
 4739592ef7aee15b860cb90637f82933 *R/plotRP.R
 0264d4c328a7a32ec30714b4a3e16dc8 *R/simts.R
 ef263b24aca130d3cc80288cd67e1fd4 *R/spdiags.R
-9842641ec92253e357501920bee5e434 *R/wincrqa.R
-a1d4f52b660adbb23a400861464029b2 *R/windowdrp.R
+440bc17fa3d14b68ced4735b28055c2c *R/wincrqa.R
+f298f8fdd2470c8a13528955450ae39b *R/windowdrp.R
 3196caadb8b7015eeec83c4f45f3ce99 *README.md
 849715e38ed85547eed537e789296fcb *data/crqa.RData
 52c8527b184b3da3bf66cc70cf42fd42 *inst/CITATION
@@ -31,7 +31,7 @@ dd8ae8f8e4393e3cf1b499c40acbdb24 *man/lorenzattractor.Rd
 a02045e8733e9ba46c6d094654cfdb68 *man/simts.Rd
 47cbd9f5cd8e35b18bbaf1039e858951 *man/spdiags.Rd
 210cd9a2a47c02b84284c2ff5eff6a55 *man/text.Rd
-9b010573eca496fe4ba2d225034ba298 *man/wincrqa.Rd
+46fae6c9032ad871e47b1da1abcb3dad *man/wincrqa.Rd
 024d3cfd55e7f8487bd631edb8fc3c7e *man/windowdrp.Rd
 e855afb600b4fcd14f84d1e7a6834d16 *src/init.c
 a9de526d2dd2130a3b2c4eae51b6c365 *src/jspd.f

NAMESPACE

@@ -1,24 +1,25 @@
-useDynLib(crqa, .registration = TRUE)
-
-export(crqa,
-       drpfromts,
-       lorenzattractor,
-       mdDelay, 
-       mdFnn,
-       optimizeParam,
-       piecewiseRQA,
-       plotRP,
-       simts,
-       spdiags,
-       wincrqa,
-       windowdrp)
-
-importFrom("graphics", mtext, hist, matpoints, plot, points)
-importFrom("gplots", hist2d)
-importFrom("Matrix", diag, t, Matrix, sparseMatrix)
-importFrom("plot3D", scatter3D)
-importFrom("pracma", circshift, eps, pdist2, polyfit)
-importFrom("stats", sd, median, rnorm, runif, var)  
-importFrom("rdist", cdist)
-importFrom("tseriesChaos", mutual, false.nearest)
-importFrom("utils", tail)
+useDynLib(crqa, .registration = TRUE)
+
+export(crqa,
+       drpfromts,
+       lorenzattractor,
+       mdDelay, 
+       mdFnn,
+       optimizeParam,
+       piecewiseRQA,
+       plotRP,
+       simts,
+       spdiags,
+       wincrqa,
+       windowdrp)
+
+importFrom("graphics", mtext, hist, matpoints, plot, points)
+importFrom("gplots", hist2d)
+importFrom("FSA", diags)
+importFrom("Matrix", diag, t, Matrix, sparseMatrix)
+importFrom("plot3D", scatter3D)
+importFrom("pracma", circshift, eps, pdist2, polyfit)
+importFrom("stats", sd, median, rnorm, runif, var)  
+importFrom("rdist", cdist)
+importFrom("tseriesChaos", mutual, false.nearest)
+importFrom("utils", tail)

NEWS.md

@@ -1,5 +1,11 @@
 # crqa (cross-recurrence quantification analysis)
 
+# crqa 2.0.1
+
+* Fixed bug on wincrqa() and windowdrp() to run windowed RQA on multidimensional data.
+    * Simplified output of wincrqa() now returning a dataframe
+    * Included new import from FSA() package to use diags() function. 
+
 # crqa 2.0.0
 
 # Major features

R/wincrqa.R

@@ -1,4 +1,3 @@
-
 ## written by Moreno I. Coco 2013 ([email protected])
 ## original Matlab code by Rick Dale
 
@@ -28,67 +27,116 @@ wincrqa <- function(ts1, ts2, windowstep, windowsize, delay, embed,
                     tw = 0, whiteline = FALSE, recpt = FALSE, side = 'both', 
                     method = 'crqa', metric = 'euclidean', 
                     datatype = 'continuous', trend = FALSE){
-
-    ## we do not expect as input a recurrent plot
+
+  irregular = FALSE; # initialize a flag that will be used to check whether the last window is included
+  ## check the different contexts in which the analyses are running
+  if (method == "rqa"){
+    ## check that the user as provided the same data to allow windowed recurrence
+    if (exists("ts2")) ts2 = ts2 else stop("Please provide the same vector as argument of t2")
+  }
+
+  if (method == "crqa"){
     ts1 = as.vector(as.matrix(ts1));   ts2 = as.vector(as.matrix(ts2))
-    points = seq(1, (length(ts1) - (windowsize)-1), windowstep)
+    maxd = length(ts1) ## the total number of points
+    points = seq(1, (maxd - (windowsize)-1), windowstep)
+  }
+
+  if (method == "mdcrqa"){
+    ts1 = as.matrix(ts1);   ts2 = as.matrix(ts2)
+    maxd = nrow(ts1) ## the total number of points
+    points = seq(1, (maxd - (windowsize)-1), windowstep)
+  }
+
+  ## need to make sure to include also "irregular" final segments
+  fpoint = points[length(points)] ## beginning of last window
+    ## as the dimension of the data often may not be that precise
+    if (fpoint != (fpoint + windowsize)){
+      irregular = TRUE ## flag used later on
+      fpoint = fpoint + windowsize # update last point
+      points = c(points,  fpoint) ## add final point
+  }
+
+  crqwin = vector()
+  tsp = 0 ## set a counter with the win at which rec was found    
+
+  # i = 1621
+  for (i in points){
+    tsp = tsp +1
 
-    TREND = crawin = vector()
-    tsp = 0 ## set a counter with the win at which rec was found    
-
-    i = 1
-    for (i in points){
-        tsp = tsp +1
-
-        ts1win = ts1[i:(i + windowsize - 1)];
-        ts2win = ts2[i:(i + windowsize - 1)];
+    if (irregular == TRUE & i == fpoint){ ## this is the last window to consider 
+      ixs = i:maxd 
+      # warning(paste("Your latest window was shorter: ", length(ixs)))
+    } else {
+    ixs = i:(i + windowsize - 1)
+    }
+
+    if (method == "crqa" | method == "rqa"){
+      ## the data consists of two vectors  
+      ts1win = ts1[ixs];
+      ts2win = ts2[ixs];
+    }
+
+    if (method == "mdcrqa"){
+      ## the data consists of two matrices 
+      ts1win = ts1[ixs, ];
+      ts2win = ts2[ixs, ];
+    }
+
+    ans = crqa(ts1win, ts2win, delay, embed, rescale,
+               radius, normalize, mindiagline, minvertline,
+               tw, whiteline, recpt, side, method, metric,
+               datatype)
+
+    RP = ans$RP
+    if (length(RP) == 1) RP = vector() ## a trick for cases
+    ## with empty recurrence plot
+    ans = as.numeric( unlist(ans[1:10]) )
+    ## if trend needs to be calculated do it here
+
+    if (trend == TRUE){
+
+      if (length(RP) > 0){
+        RP = as.matrix(RP) ## diags() has changed behaviour 
+        NX = ncol(RP)
+        T = vector("numeric", length = NX-1)
+
+
+        ## below some test matrices
+        # RP = matrix(1:16,nrow=4)
+        # RP = cbind(c(2,7), c(1,9), c(10, 12))
 
-        ans = crqa(ts1win, ts2win, delay, embed, rescale,
-                   radius, normalize, mindiagline, minvertline,
-                   tw, whiteline, recpt, side, method, metric,
-                   datatype)
+        # do we need to span the full matrix or just half?
+        ## create a vector of indeces for all diagonals of the matrix  
+        # ixi_diag = -(ncol(RP)-1):(nrow(RP)-1) 
 
-        RP = ans$RP
-        if (length(RP) == 1) RP = vector() ## a trick for cases
-                                           ## with empty recurrence plot
-        ans = as.numeric( unlist(ans[1:10]) )
-        ## if trend needs to be calculated do it here
-
-        if (trend == TRUE){
-
-            if (length(RP) > 0){
-
-                NX = ncol(RP)
-                T = vector("numeric", length = NX-1)
-
-                k = 1
-                for (k in 1:(NX-1)){
-                    T[k] = length(
-                         which(diag(RP, k) != F)) / (NX-k)*100;
-                }
-
-                Ntau = NX - 1 - round(0.1*NX);
-
-                ## last 10% of the RP will be skipped
-                p = polyfit(2:(Ntau+1),T[1:Ntau], 1) # slope
-                TREND = c(TREND, 1000 * p[1])
-            ## Webber's definition includes factor 1000
-
-            } else { TREND = NA}
-        } else {
-            TREND = c(TREND, NA)
+        # k = 1
+        for (k in 1:(NX-1)){  ##ixi_diag
+#          print(diags(RP, k)) ## check the diagonal
+          ixi_rec = which(diags(RP, k) != F) ## find recurrence
+          T[k] = length(ixi_rec)/ (NX-k)*100;
         }
 
+        Ntau = NX - 1 - round(0.1*NX);
 
-        crawin = rbind(crawin, c(ans, tsp), deparse.level = 0)
+        ## last 10% of the RP will be skipped
+        p = polyfit(2:(Ntau+1),T[1:Ntau], 1) # slope
+        TREND = 1000 * p[1]
+        ## Webber's definition includes factor 1000
 
+      } else { TREND = NA}
+    } else {
+      TREND = NA
     }
-
-    ## name the measures
-    colnames(crawin) = c("RR", "DET", "NRLINE", "maxL", "L", 
-                         "ENTR", "rENTR", "LAM", "TT", "catH", "TREND")
 
-    return(list(crqwin = crawin, TREND = TREND))
+    crqwin = rbind(crqwin, c(ans, tsp, TREND), deparse.level = 0)
 
+  }
+
+  ## name the measures
+  colnames(crqwin) = c("RR", "DET", "NRLINE", "maxL", "L", 
+                       "ENTR", "rENTR", "LAM", "TT", "catH", "win", "TREND")
+
+  return(as.data.frame(crqwin))
+
 }