1 files changed, 29 insertions, 18 deletions
diff --git a/vignettes/compiled_models.Rmd b/vignettes/compiled_models.Rmd
index 3b24acbb..9aa8b133 100644
--- a/vignettes/compiled_models.Rmd
+++ b/vignettes/compiled_models.Rmd
@@ -1,34 +1,41 @@
 ---
-title: "Performance benefit by using compiled model definitions in mkin"
+title: "`r (vignette_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{`r vignette_title`}
+  %\VignetteEngine{knitr::rmarkdown}
+  \usepackage[utf8]{inputenc}
 ---
-<!--
-%\VignetteEngine{knitr::rmarkdown}
-%\VignetteIndexEntry{Performance benefit by using compiled model definitions in mkin}
--->
 
 ```{r, include = FALSE}
 library(knitr)
 opts_chunk$set(tidy = FALSE, cache = TRUE)
 ```
 
-# Benchmark for a model that can also be solved with Eigenvalues
+## 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 compiler (gcc) is installed, you will see
 a message that the model is being compiled from autogenerated C code when
-defining a model using mkinmod.
+defining a model using mkinmod. The package tests 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 = list(type = "SFO", to = "m1", sink = TRUE),
-  m1 = list(type = "SFO"))
+  parent = mkinsub("SFO", "m1"),
+  m1 = mkinsub("SFO"))
 ```
 
 We can compare the performance of the Eigenvalue based solution against the
@@ -36,11 +43,7 @@ compiled version and the R implementation of the differential equations using
 the microbenchmark package.
 
 
-```{r benchmark_SFO_SFO, echo=-(1:2)}
-# Redefining the model, in order not to confuse the knitr cache which leads to segfaults
-suppressMessages(SFO_SFO <- mkinmod(
-  parent = list(type = "SFO", to = "m1", sink = TRUE),
-  m1 = list(type = "SFO")))
+```{r benchmark_SFO_SFO}
 library("microbenchmark")
 mb.1 <- microbenchmark(
   mkinfit(SFO_SFO, FOCUS_2006_D, solution_type = "deSolve", use_compiled = FALSE, 
@@ -63,14 +66,14 @@ iterative solution of the ODEs:
 smb.1["median"]/smb.1["deSolve, compiled", "median"]
 ```
 
-# Benchmark for a model that can not be solved with Eigenvalues
+## 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 = list(type = "FOMC", to = "m1", sink = TRUE),
-  m1 = list(type = "SFO"))
+  parent = mkinsub("FOMC", "m1"),
+  m1 = mkinsub( "SFO"))
 
 mb.2 <- microbenchmark(
   mkinfit(FOMC_SFO, FOCUS_2006_D, use_compiled = FALSE, quiet = TRUE),
@@ -80,10 +83,18 @@ 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]]))
+}
+```