Further formatting improvement of benchmark vignette

Also, use .rmd extension instead of .Rmd for vignettes.

1 files changed, 0 insertions, 141 deletions

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----

-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]]))

-}

-```