From 415ca2bea5d5c3815bd9f8fa1566cec5bb3fc775 Mon Sep 17 00:00:00 2001
From: Johannes Ranke <jranke@uni-bremen.de>
Date: Mon, 9 Nov 2015 08:52:01 +0100
Subject: Re-add the compiled models vignette

This was accidentally deleted in
438a889c37ffdf8f0c6585092da6abdb63b4575e on June 30!
---
 vignettes/compiled_models.Rmd | 101 ++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 101 insertions(+)
 create mode 100644 vignettes/compiled_models.Rmd

(limited to 'vignettes')

diff --git a/vignettes/compiled_models.Rmd b/vignettes/compiled_models.Rmd
new file mode 100644
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@@ -0,0 +1,101 @@
+---
+title: "Performance benefit by using compiled model definitions in mkin"
+author: "Johannes Ranke"
+date: "`r Sys.Date()`"
+output:
+  html_document:
+    css: mkin_vignettes.css
+    toc: true
+    mathjax: null
+    theme: united
+vignette: >
+  %\VignetteIndexEntry{Performance benefit by using compiled model definitions in mkin}
+  %\VignetteEngine{knitr::rmarkdown}
+  \usepackage[utf8]{inputenc}
+---
+
+```{r, include = FALSE}
+library(knitr)
+opts_chunk$set(tidy = FALSE, cache = TRUE)
+```
+
+## Benchmark for a model that can also be solved with Eigenvalues
+
+This evaluation is taken from the example section of mkinfit. When using an mkin version
+equal to or greater than 0.9-36 and a C compiler (gcc) is available, you will see
+a message that the model is being compiled from autogenerated C code when
+defining a model using mkinmod. The `mkinmod()` function checks for presence of
+the gcc compiler using 
+
+```{r check_gcc}
+Sys.which("gcc")
+```
+First, we build a simple degradation model for a parent compound with one metabolite.
+
+```{r create_SFO_SFO}
+library("mkin")
+SFO_SFO <- mkinmod(
+  parent = mkinsub("SFO", "m1"),
+  m1 = mkinsub("SFO"))
+```
+
+We can compare the performance of the Eigenvalue based solution against the
+compiled version and the R implementation of the differential equations using
+the microbenchmark package.
+
+
+```{r benchmark_SFO_SFO}
+library("microbenchmark")
+mb.1 <- microbenchmark(
+  mkinfit(SFO_SFO, FOCUS_2006_D, solution_type = "deSolve", use_compiled = FALSE, 
+          quiet = TRUE),
+  mkinfit(SFO_SFO, FOCUS_2006_D, solution_type = "eigen", quiet = TRUE),
+  mkinfit(SFO_SFO, FOCUS_2006_D, solution_type = "deSolve", quiet = TRUE),
+  times = 3, control = list(warmup = 1))
+smb.1 <- summary(mb.1)[-1]
+rownames(smb.1) <- c("deSolve, not compiled", "Eigenvalue based", "deSolve, compiled")
+print(smb.1)
+```
+
+We see that using the compiled model is by a factor of 
+`r round(smb.1["deSolve, not compiled", "median"]/smb.1["deSolve, compiled", "median"], 1)` 
+faster than using the R version with the default ode solver, and it is even
+faster than the Eigenvalue based solution implemented in R which does not need
+iterative solution of the ODEs:
+
+```{r}
+smb.1["median"]/smb.1["deSolve, compiled", "median"]
+```
+
+## Benchmark for a model that can not be solved with Eigenvalues
+
+This evaluation is also taken from the example section of mkinfit. 
+
+```{r benchmark_FOMC_SFO}
+FOMC_SFO <- mkinmod(
+  parent = mkinsub("FOMC", "m1"),
+  m1 = mkinsub( "SFO"))
+
+mb.2 <- microbenchmark(
+  mkinfit(FOMC_SFO, FOCUS_2006_D, use_compiled = FALSE, quiet = TRUE),
+  mkinfit(FOMC_SFO, FOCUS_2006_D, quiet = TRUE),
+  times = 3, control = list(warmup = 1))
+smb.2 <- summary(mb.2)[-1]
+rownames(smb.2) <- c("deSolve, not compiled", "deSolve, compiled")
+print(smb.2)
+smb.2["median"]/smb.2["deSolve, compiled", "median"]
+```
+
+Here we get a performance benefit of a factor of 
+`r round(smb.2["deSolve, not compiled", "median"]/smb.2["deSolve, compiled", "median"], 1)` 
+using the version of the differential equation model compiled from C code using
+the inline package!
+
+This vignette was built with mkin `r packageVersion("mkin")` on
+
+```{r sessionInfo, echo = FALSE}
+cat(capture.output(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]]))
+}
+```
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