Remove two vignettes from the package but not from docs

- Rebuild static documentation
- Adapt test to new approach to two component error model
  where the model is inadequate

1 files changed, 0 insertions, 102 deletions

diff --git a/vignettes/compiled_models.Rmd b/vignettes/compiled_models.Rmd
deleted file mode 100644
index b16dfea6..00000000
--- a/vignettes/compiled_models.Rmd
+++ /dev/null
@@ -1,102 +0,0 @@
----

-title: "Performance benefit by using compiled model definitions in mkin"

-author: "Johannes Ranke"

-output: rmarkdown::html_vignette

-date: "`r Sys.Date()`"

-vignette: >

-  %\VignetteIndexEntry{Performance benefit by using compiled model definitions in mkin}

-  %\VignetteEngine{knitr::rmarkdown}

-  %\VignetteEncoding{UTF-8}

----

-

-```{r, include = FALSE}

-library(knitr)

-opts_chunk$set(tidy = FALSE, cache = FALSE)

-```

-

-## 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", quietly = TRUE)

-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 benchmark package.

-

-

-```{r benchmark_SFO_SFO, fig.height = 3}

-if (require(rbenchmark)) {

-  b.1 <- benchmark(

-    "deSolve, not compiled" = mkinfit(SFO_SFO, FOCUS_2006_D,

-                                      solution_type = "deSolve",

-                                      use_compiled = FALSE, quiet = TRUE),

-    "Eigenvalue based" = mkinfit(SFO_SFO, FOCUS_2006_D,

-                                 solution_type = "eigen", quiet = TRUE),

-    "deSolve, compiled" = mkinfit(SFO_SFO, FOCUS_2006_D,

-                                  solution_type = "deSolve", quiet = TRUE),

-    replications = 3)

-  print(b.1)

-  factor_SFO_SFO <- round(b.1["1", "relative"])

-} else {

-  factor_SFO_SFO <- NA

-  print("R package benchmark is not available")

-}

-```

-

-We see that using the compiled model is by a factor of around

-`r factor_SFO_SFO`

-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.

-

-

-## Model that can not be solved with Eigenvalues

-

-This evaluation is also taken from the example section of mkinfit.

-

-```{r benchmark_FOMC_SFO, fig.height = 3}

-if (require(rbenchmark)) {

-  FOMC_SFO <- mkinmod(

-    parent = mkinsub("FOMC", "m1"),

-    m1 = mkinsub( "SFO"))

-

-  b.2 <- benchmark(

-    "deSolve, not compiled" = mkinfit(FOMC_SFO, FOCUS_2006_D,

-                                      use_compiled = FALSE, quiet = TRUE),

-    "deSolve, compiled" = mkinfit(FOMC_SFO, FOCUS_2006_D, quiet = TRUE),

-    replications = 3)

-  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]]))

-}

-```