Week 4, lecture 5 notes

week-04/lecture-05-r-profiler-part-2.md

@@ -0,0 +1,42 @@
+R Profiler - Part 2
+===================
+
+Rprof()
+-------
+
+* The  Rprof() function starts the profiler in R
+	* R must be compiled with profiler support (but this is usually the case)
+* The summaryRprof() function summarizes the output from Rprof() (otherwise it's not readable)
+* NO NOT use system.time() and Rprof() together or you will be sad
+* Rprof() keeps track of the function call stack at regularly sampled intervals and tabulates how much time is spent in each function
+* Default sampling interval is 0.02 seconds
+* NOTE: If your code runs very quickly, the profiler is not useful, but then you probably don't need it in that case
+
+
+Using summaryRprof()
+--------------------
+
+* The summaryRprof() function tabulates the R profiler output and calculates how much time is spent in which function
+* There are two methods for normalizing the data
+* "by.total" divides the time spent in each function by the total run time
+* "by.self" does the same but first subtracts out time spent in functions above in the call stack
+
+
+summaryRprof() Output
+---------------------
+
+	$sample.interval
+	[1] 0.02
+
+	$sampling.time
+	[1] 7.41
+
+
+Summary
+-------
+
+* Rprof() runs the profiler for performance analysis of R code
+* summaryRprof() summarizes the output of Rprof() and gives percent of time spent in each function (with two types of normalization)
+* Good to break your code into functions so that the profiler can give useful information about where time is being spent
+* C or Fortran code is not profiled
+