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 insertions(+) create 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 new file mode 100644 index 00000000..0b8c617a --- /dev/null +++ b/vignettes/web_only/compiled_models.rmd @@ -0,0 +1,141 @@ +--- +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 v1.2.1