From ccc70e82af4ba435f0a71ba1ae4e0e92045c3852 Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Fri, 5 May 2017 12:46:31 +0200 Subject: Static docs except articles rebuilt with current pkgdown --- vignettes/compiled_models.html | 24 +++++++++++++++--------- 1 file changed, 15 insertions(+), 9 deletions(-) (limited to 'vignettes/compiled_models.html') diff --git a/vignettes/compiled_models.html b/vignettes/compiled_models.html index 53c5647f..67d0f658 100644 --- a/vignettes/compiled_models.html +++ b/vignettes/compiled_models.html @@ -229,8 +229,13 @@ div.tocify { 
##            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.

@@ -251,15 +256,16 @@ SFO_SFO <- mkinmod(
   factor_SFO_SFO <- NA
   print("R package benchmark is not available")
 }
+
## Loading required package: rbenchmark
##                    test replications elapsed relative user.self sys.self
-## 3     deSolve, compiled            3   2.742    1.000     2.740    0.000
-## 1 deSolve, not compiled            3  24.467    8.923    24.344    0.124
-## 2      Eigenvalue based            3   3.050    1.112     3.044    0.004
+## 3     deSolve, compiled            3   2.040    1.000     2.040        0
+## 1 deSolve, not compiled            3  14.622    7.168    14.624        0
+## 2      Eigenvalue based            3   2.478    1.215     2.480        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.

+

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

Model that can not be solved with Eigenvalues

@@ -282,12 +288,12 @@ SFO_SFO <- mkinmod( } 
## Successfully compiled differential equation model from auto-generated C code.
##                    test replications elapsed relative user.self sys.self
-## 2     deSolve, compiled            3   4.038    1.000     4.036    0.000
-## 1 deSolve, not compiled            3  55.209   13.672    54.888    0.324
+## 2     deSolve, compiled            3   3.500    1.000     3.500        0
+## 1 deSolve, not compiled            3  29.932    8.552    29.932        0
 ##   user.child sys.child
 ## 2          0         0
 ## 1          0         0
-

Here we get a performance benefit of a factor of 14 using the version of the differential equation model compiled from C code!

+

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

This vignette was built with mkin 0.9.45 on

## R version 3.4.0 (2017-04-21)
 ## Platform: x86_64-pc-linux-gnu (64-bit)
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