From 218a9c55bd80fb708b15fa7196422f759bfe4b27 Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Wed, 13 May 2020 16:20:23 +0200 Subject: Further formatting improvement of benchmark vignette Also, use .rmd extension instead of .Rmd for vignettes. --- vignettes/web_only/compiled_models.Rmd | 141 --------------------------------- 1 file changed, 141 deletions(-) delete mode 100644 vignettes/web_only/compiled_models.Rmd (limited to 'vignettes/web_only/compiled_models.Rmd') diff --git a/vignettes/web_only/compiled_models.Rmd b/vignettes/web_only/compiled_models.Rmd deleted file mode 100644 index f99ea808..00000000 --- a/vignettes/web_only/compiled_models.Rmd +++ /dev/null @@ -1,141 +0,0 @@ ---- -title: "Performance benefit by using compiled model definitions in mkin" -author: "Johannes Ranke" -output: - html_document: - toc: true - toc_float: true - code_folding: show - fig_retina: null -date: "`r Sys.Date()`" -vignette: > - %\VignetteEngine{knitr::rmarkdown} - %\VignetteEncoding{UTF-8} ---- - -```{r, include = FALSE} -library(knitr) -opts_chunk$set(tidy = FALSE, cache = FALSE) -``` - -## How to benefit from compiled models - -When using an mkin version equal to or greater than 0.9-36 and a C compiler is -available, you will see a message that the model is being compiled from -autogenerated C code when defining a model using mkinmod. Starting from -version 0.9.49.9, the `mkinmod()` function checks for presence of a compiler -using - -```{r check_gcc, eval = FALSE} -pkgbuild::has_compiler() -``` - -In previous versions, it used `Sys.which("gcc")` for this check. - -On Linux, you need to have the essential build tools like make and gcc or clang -installed. On Debian based linux distributions, these will be pulled in by installing -the build-essential package. - -On MacOS, which I do not use personally, I have had reports that a compiler is -available by default. - -On Windows, you need to install Rtools and have the path to its bin directory -in your PATH variable. You do not need to modify the PATH variable when -installing Rtools. Instead, I would recommend to put the line - -```{r Rprofile, eval = FALSE} -Sys.setenv(PATH = paste("C:/Rtools/bin", Sys.getenv("PATH"), sep=";")) -``` -into your .Rprofile startup file. This is just a text file with some R -code that is executed when your R session starts. It has to be named .Rprofile -and has to be located in your home directory, which will generally be your -Documents folder. You can check the location of the home directory used by R by -issuing - -```{r HOME, eval = FALSE} -Sys.getenv("HOME") -``` - -## Comparison with other solution methods - -First, we build a simple degradation model for a parent compound with one metabolite, -and we remove zero values from the dataset. - -```{r create_SFO_SFO} -library("mkin", quietly = TRUE) -SFO_SFO <- mkinmod( - parent = mkinsub("SFO", "m1"), - m1 = mkinsub("SFO")) -FOCUS_D <- subset(FOCUS_2006_D, value != 0) -``` - -We can compare the performance of the Eigenvalue based solution against the -compiled version and the R implementation of the differential equations using -the benchmark package. In the output of below code, the warnings about zero -being removed from the FOCUS D dataset are suppressed. Since mkin version -0.9.49.11, an analytical solution is also implemented, which is included -in the tests below. - -```{r benchmark_SFO_SFO, fig.height = 3, message = FALSE, warning = FALSE} -if (require(rbenchmark)) { - b.1 <- benchmark( - "deSolve, not compiled" = mkinfit(SFO_SFO, FOCUS_D, - solution_type = "deSolve", - use_compiled = FALSE, quiet = TRUE), - "Eigenvalue based" = mkinfit(SFO_SFO, FOCUS_D, - solution_type = "eigen", quiet = TRUE), - "deSolve, compiled" = mkinfit(SFO_SFO, FOCUS_D, - solution_type = "deSolve", quiet = TRUE), - "analytical" = mkinfit(SFO_SFO, FOCUS_D, - solution_type = "analytical", - use_compiled = FALSE, quiet = TRUE), - replications = 1, order = "relative", - columns = c("test", "replications", "relative", "elapsed")) - print(b.1) -} else { - print("R package rbenchmark is not available") -} -``` - -We see that using the compiled model is by more than a factor of 10 faster -than using deSolve without compiled code. - -## Model without analytical solution - -This evaluation is also taken from the example section of mkinfit. No analytical -solution is available for this system, and now Eigenvalue based solution -is possible, so only deSolve using with or without compiled code is -available. - -```{r benchmark_FOMC_SFO, fig.height = 3, warning = FALSE} -if (require(rbenchmark)) { - FOMC_SFO <- mkinmod( - parent = mkinsub("FOMC", "m1"), - m1 = mkinsub( "SFO")) - - b.2 <- benchmark( - "deSolve, not compiled" = mkinfit(FOMC_SFO, FOCUS_D, - use_compiled = FALSE, quiet = TRUE), - "deSolve, compiled" = mkinfit(FOMC_SFO, FOCUS_D, quiet = TRUE), - replications = 1, order = "relative", - columns = c("test", "replications", "relative", "elapsed")) - print(b.2) - factor_FOMC_SFO <- round(b.2["1", "relative"]) -} else { - factor_FOMC_SFO <- NA - print("R package benchmark is not available") -} -``` - -Here we get a performance benefit of a factor of -`r factor_FOMC_SFO` -using the version of the differential equation model compiled from C code! - -This vignette was built with mkin `r utils::packageVersion("mkin")` on - -```{r sessionInfo, echo = FALSE} -cat(utils::capture.output(utils::sessionInfo())[1:3], sep = "\n") -if(!inherits(try(cpuinfo <- readLines("/proc/cpuinfo")), "try-error")) { - cat(gsub("model name\t: ", "CPU model: ", cpuinfo[grep("model name", cpuinfo)[1]])) -} -``` -- cgit v1.2.3