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

Sys.which("gcc")
##            gcc 
## "/usr/bin/gcc"

First, we build a simple degradation model for a parent compound with one metabolite.

library("mkin", quietly = TRUE)
SFO_SFO <- mkinmod(
  parent = mkinsub("SFO", "m1"),
  m1 = mkinsub("SFO"))
## Successfully compiled differential equation model from auto-generated C code.

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.

## Lade nötiges Paket: rbenchmark
## Warning in mkinfit(SFO_SFO, FOCUS_2006_D, solution_type = "deSolve",
## use_compiled = FALSE, : Observations with value of zero were removed from
## the data
## Warning in mkinfit(SFO_SFO, FOCUS_2006_D, solution_type = "eigen", quiet =
## TRUE): Observations with value of zero were removed from the data
## Warning in mkinfit(SFO_SFO, FOCUS_2006_D, solution_type = "deSolve", quiet
## = TRUE): Observations with value of zero were removed from the data
## Warning in mkinfit(SFO_SFO, FOCUS_2006_D, solution_type = "deSolve",
## use_compiled = FALSE, : Observations with value of zero were removed from
## the data

## Warning in mkinfit(SFO_SFO, FOCUS_2006_D, solution_type = "deSolve",
## use_compiled = FALSE, : Observations with value of zero were removed from
## the data

## Warning in mkinfit(SFO_SFO, FOCUS_2006_D, solution_type = "deSolve",
## use_compiled = FALSE, : Observations with value of zero were removed from
## the data
## Warning in mkinfit(SFO_SFO, FOCUS_2006_D, solution_type = "eigen", quiet =
## TRUE): Observations with value of zero were removed from the data

## Warning in mkinfit(SFO_SFO, FOCUS_2006_D, solution_type = "eigen", quiet =
## TRUE): Observations with value of zero were removed from the data

## Warning in mkinfit(SFO_SFO, FOCUS_2006_D, solution_type = "eigen", quiet =
## TRUE): Observations with value of zero were removed from the data
## Warning in mkinfit(SFO_SFO, FOCUS_2006_D, solution_type = "deSolve", quiet
## = TRUE): Observations with value of zero were removed from the data

## Warning in mkinfit(SFO_SFO, FOCUS_2006_D, solution_type = "deSolve", quiet
## = TRUE): Observations with value of zero were removed from the data

## Warning in mkinfit(SFO_SFO, FOCUS_2006_D, solution_type = "deSolve", quiet
## = TRUE): Observations with value of zero were removed from the data
##                    test replications elapsed relative user.self sys.self
## 3     deSolve, compiled            3   3.067    1.000     3.065        0
## 1 deSolve, not compiled            3  28.135    9.173    28.122        0
## 2      Eigenvalue based            3   4.306    1.404     4.303        0
##   user.child sys.child
## 3          0         0
## 1          0         0
## 2          0         0

We see that using the compiled model is by a factor of around 9 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.

## Successfully compiled differential equation model from auto-generated C code.
## Warning in mkinfit(FOMC_SFO, FOCUS_2006_D, use_compiled = FALSE, quiet =
## TRUE): Observations with value of zero were removed from the data
## Warning in mkinfit(FOMC_SFO, FOCUS_2006_D, quiet = TRUE): Observations with
## value of zero were removed from the data
## Warning in mkinfit(FOMC_SFO, FOCUS_2006_D, use_compiled = FALSE, quiet =
## TRUE): Observations with value of zero were removed from the data

## Warning in mkinfit(FOMC_SFO, FOCUS_2006_D, use_compiled = FALSE, quiet =
## TRUE): Observations with value of zero were removed from the data

## Warning in mkinfit(FOMC_SFO, FOCUS_2006_D, use_compiled = FALSE, quiet =
## TRUE): Observations with value of zero were removed from the data
## Warning in mkinfit(FOMC_SFO, FOCUS_2006_D, quiet = TRUE): Observations with
## value of zero were removed from the data

## Warning in mkinfit(FOMC_SFO, FOCUS_2006_D, quiet = TRUE): Observations with
## value of zero were removed from the data

## Warning in mkinfit(FOMC_SFO, FOCUS_2006_D, quiet = TRUE): Observations with
## value of zero were removed from the data
##                    test replications elapsed relative user.self sys.self
## 2     deSolve, compiled            3   4.827    1.000     4.825        0
## 1 deSolve, not compiled            3  52.646   10.907    52.622        0
##   user.child sys.child
## 2          0         0
## 1          0         0

Here we get a performance benefit of a factor of 11 using the version of the differential equation model compiled from C code!

This vignette was built with mkin 0.9.49.4 on

## R version 3.6.0 (2019-04-26)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Debian GNU/Linux 9 (stretch)
## CPU model: AMD Ryzen 7 1700 Eight-Core Processor