From 3151647526f299686b68420a83ae38cd7f3d08f5 Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Mon, 9 Nov 2015 09:05:15 +0100 Subject: Rebuild vignettes and static documentation --- vignettes/compiled_models.html | 53 +++++++++++++++++++++++------------------- 1 file changed, 29 insertions(+), 24 deletions(-) (limited to 'vignettes/compiled_models.html') diff --git a/vignettes/compiled_models.html b/vignettes/compiled_models.html index a8f6e3ef..3d92a7b8 100644 --- a/vignettes/compiled_models.html +++ b/vignettes/compiled_models.html @@ -10,7 +10,7 @@ - + Performance benefit by using compiled model definitions in mkin @@ -65,7 +65,7 @@ img {
@@ -82,8 +82,13 @@ img { 
##            gcc 
 ## "/usr/bin/gcc"

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

-
library("mkin")
-SFO_SFO <- mkinmod(
+
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.

@@ -99,18 +104,18 @@ smb.1 <- summary(mb.1)[-1]
 rownames(smb.1) <- c("deSolve, not compiled", "Eigenvalue based", "deSolve, compiled")
 print(smb.1)
##                             min        lq      mean    median        uq
-## deSolve, not compiled 6767.3728 6834.5128 6879.5969 6901.6528 6935.7090
-## Eigenvalue based       977.5545 1161.8591 1225.1262 1346.1637 1348.9120
-## deSolve, compiled      761.0689  761.8958  772.3379  762.7228  777.9724
-##                             max neval
-## deSolve, not compiled 6969.7653     3
-## Eigenvalue based      1351.6603     3
-## deSolve, compiled      793.2221     3
-

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

+## deSolve, not compiled 4920.5498 4957.8305 5073.8005 4995.1112 5150.4259 +## Eigenvalue based 792.7603 820.6244 849.2773 848.4885 877.5358 +## deSolve, compiled 663.5431 673.4949 678.4844 683.4468 685.9551 +## max neval cld +## deSolve, not compiled 5305.7406 3 b +## Eigenvalue based 906.5832 3 a +## deSolve, compiled 688.4634 3 a +

We see that using the compiled model is by a factor of 7.3 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:

smb.1["median"]/smb.1["deSolve, compiled", "median"]
##                         median
-## deSolve, not compiled 9.048704
-## Eigenvalue based      1.764945
+## deSolve, not compiled 7.308706
+## Eigenvalue based      1.241484
 ## deSolve, compiled     1.000000
@@ -128,18 +133,18 @@ smb.2 <- summary(mb.2)[-1] rownames(smb.2) <- c("deSolve, not compiled", "deSolve, compiled") print(smb.2) 
##                             min        lq      mean    median        uq
-## deSolve, not compiled 14.161917 14.189080 14.201763 14.216243 14.221687
-## deSolve, compiled      1.358691  1.366613  1.393306  1.374535  1.410614
-##                             max neval
-## deSolve, not compiled 14.227131     3
-## deSolve, compiled      1.446693     3
+## deSolve, not compiled 10.710141 10.757988 10.810178 10.805835 10.860196 +## deSolve, compiled 1.200581 1.203966 1.211877 1.207351 1.217525 +## max neval cld +## deSolve, not compiled 10.914558 3 b +## deSolve, compiled 1.227699 3 a 
smb.2["median"]/smb.2["deSolve, compiled", "median"]
##                         median
-## deSolve, not compiled 10.34258
-## deSolve, compiled      1.00000
-

Here we get a performance benefit of a factor of 10.3 using the version of the differential equation model compiled from C code using the inline package!

-

This vignette was built with mkin 0.9.39 on

-
## R version 3.2.1 (2015-06-18)
+## deSolve, not compiled 8.950036
+## deSolve, compiled     1.000000
+

Here we get a performance benefit of a factor of 9 using the version of the differential equation model compiled from C code using the inline package!

+

This vignette was built with mkin 0.9.40.900 on

+
## R version 3.2.2 (2015-08-14)
 ## 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
-- cgit v1.2.1