| summaryRprof {utils} | R Documentation |
Summarise the output of the Rprof function to show the
amount of time used by different R functions.
summaryRprof(filename = "Rprof.out", chunksize = 5000,
memory=c("none","both","tseries","stats"),
index=2, diff=TRUE, exclude=NULL)
filename |
Name of a file produced by |
chunksize |
Number of lines to read at a time |
memory |
Summaries for memory information. See ‘Details’ below |
index |
How to summarize the stack trace for memory information. See ‘Details’ below. |
diff |
If |
exclude |
Functions to exclude when summarizing the stack trace for memory summaries |
This function provides the analysis code for Rprof files
used by R CMD Rprof.
As the profiling output file could be larger than available memory, it
is read in blocks of chunksize lines. Increasing chunksize
will make the function run faster if sufficient memory is available.
When called with memory.profiling = TRUE, the profiler writes
information on three aspects of memory use: vector memory in small
blocks on the R heap, vector memory in large blocks (from
malloc), memory in nodes on the R heap. It also records the number of
calls to the internal function duplicate in the time
interval. duplicate is called by C code when arguments need to be
copied. Note that the profiler does not track which function actually
allocated the memory.
With memory = "both" the change in total memory (truncated at zero)
is reported in addition to timing data.
With memory = "tseries" or memory = "stats" the index
argument specifies how to summarize the stack trace. A positive number
specifies that many calls from the bottom of the stack; a negative
number specifies the number of calls from the top of the stack. With
memory = "tseries" the index is used to construct labels and may be
a vector to give multiple sets of labels. With memory = "stats" the
index must be a single number and specifies how to aggregate the data to
the maximum and average of the memory statistics. With both
memory = "tseries" and memory = "stats" the argument
diff = TRUE asks for summaries of the increase in memory use over
the sampling interval and diff = FALSE asks for the memory use at
the end of the interval.
If memory = "none", a list with components
by.self |
Timings sorted by ‘self’ time |
by.total |
Timings sorted by ‘total’ time |
sample.interval |
The sampling interval |
sampling.time |
Total length of profiling run |
If memory = "both" the same list but with memory consumption in Mb
in addition to the timings.
If memory = "tseries" a data frame giving memory statistics over
time
If memory = "stats" a by object giving memory statistics
by function.
The chapter on “Tidying and profiling R code” in “Writing R Extensions” (see the ‘doc/manual’ subdirectory of the R source tree).
tracemem traces copying of an object via the C function
duplicate.
Rprofmem is a non-sampling memory-use profiler.
http://developer.r-project.org/memory-profiling.html
## Not run: ## Rprof() is not available on all platforms Rprof(tmp <- tempfile()) example(glm) Rprof() summaryRprof(tmp) unlink(tmp) ## End(Not run)