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")

## Loading required package: minpack.lm

## Loading required package: rootSolve

## Loading required package: inline

## Loading required package: methods

## Loading required package: parallel

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 microbenchmark package.

library("microbenchmark")
library("ggplot2")
mb.1 <- microbenchmark(
  "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),
  times = 3, control = list(warmup = 0))

## Warning in microbenchmark(`deSolve, not compiled` = mkinfit(SFO_SFO,
## FOCUS_2006_D, : Could not measure overhead. Your clock might lack
## precision.

smb.1 <- summary(mb.1)
print(mb.1)

## Unit: milliseconds
##                   expr       min        lq      mean    median        uq
##  deSolve, not compiled 5006.3815 5014.4629 5112.7115 5022.5443 5165.8765
##       Eigenvalue based  840.3027  874.3549  892.0593  908.4071  917.9376
##      deSolve, compiled  706.9909  712.8031  723.4380  718.6154  731.6615
##        max neval cld
##  5309.2087     3   b
##   927.4680     3  a 
##   744.7077     3  a

autoplot(mb.1)

We see that using the compiled model is by a factor of 7 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:

rownames(smb.1) <- smb.1$expr
smb.1["median"]/smb.1["deSolve, compiled", "median"]

##                         median
## deSolve, not compiled 6.989197
## Eigenvalue based      1.264108
## deSolve, compiled     1.000000

Model that can not be solved with Eigenvalues

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

FOMC_SFO <- mkinmod(
  parent = mkinsub("FOMC", "m1"),
  m1 = mkinsub( "SFO"))

## Successfully compiled differential equation model from auto-generated C code.

mb.2 <- microbenchmark(
  "deSolve, not compiled" = mkinfit(FOMC_SFO, FOCUS_2006_D,
                                    use_compiled = FALSE, quiet = TRUE),
  "deSolve, compiled" = mkinfit(FOMC_SFO, FOCUS_2006_D, quiet = TRUE),
  times = 3, control = list(warmup = 0))

## Warning in microbenchmark(`deSolve, not compiled` = mkinfit(FOMC_SFO,
## FOCUS_2006_D, : Could not measure overhead. Your clock might lack
## precision.

smb.2 <- summary(mb.2)
print(mb.2)

## Unit: seconds
##                   expr       min       lq     mean    median        uq
##  deSolve, not compiled 11.015990 11.17783 11.24827 11.339674 11.364403
##      deSolve, compiled  1.285264  1.29794  1.32988  1.310616  1.352189
##        max neval cld
##  11.389132     3   b
##   1.393762     3  a

smb.2["median"]/smb.2["deSolve, compiled", "median"]

##   median
## 1     NA
## 2     NA

autoplot(mb.2)

Here we get a performance benefit of a factor of 8.7 using the version of the differential equation model compiled from C code!

This vignette was built with mkin 0.9.45 on

## R version 3.3.2 (2016-10-31)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Debian GNU/Linux 8 (jessie)

## CPU model: Intel(R) Core(TM) i7-4710MQ CPU @ 2.50GHz