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Diffstat (limited to 'vignettes/compiled_models.html')
| -rw-r--r-- | vignettes/compiled_models.html | 47 |
1 files changed, 21 insertions, 26 deletions
diff --git a/vignettes/compiled_models.html b/vignettes/compiled_models.html index 3d92a7b8..92919da9 100644 --- a/vignettes/compiled_models.html +++ b/vignettes/compiled_models.html @@ -82,13 +82,8 @@ img { <pre><code>## gcc ## "/usr/bin/gcc"</code></pre> <p>First, we build a simple degradation model for a parent compound with one metabolite.</p> -<pre class="r"><code>library("mkin")</code></pre> -<pre><code>## Loading required package: minpack.lm -## Loading required package: rootSolve -## Loading required package: inline -## Loading required package: methods -## Loading required package: parallel</code></pre> -<pre class="r"><code>SFO_SFO <- mkinmod( +<pre class="r"><code>library("mkin") +SFO_SFO <- mkinmod( parent = mkinsub("SFO", "m1"), m1 = mkinsub("SFO"))</code></pre> <pre><code>## Successfully compiled differential equation model from auto-generated C code.</code></pre> @@ -104,19 +99,19 @@ smb.1 <- summary(mb.1)[-1] rownames(smb.1) <- c("deSolve, not compiled", "Eigenvalue based", "deSolve, compiled") print(smb.1)</code></pre> <pre><code>## min lq mean median uq -## 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 +## deSolve, not compiled 9307.3194 9319.9546 9332.8171 9332.5899 9345.5659 +## Eigenvalue based 855.3608 855.8081 869.4725 856.2555 876.5283 +## deSolve, compiled 686.6143 687.9256 698.0279 689.2369 703.7346 ## max neval cld -## deSolve, not compiled 5305.7406 3 b -## Eigenvalue based 906.5832 3 a -## deSolve, compiled 688.4634 3 a</code></pre> -<p>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:</p> +## deSolve, not compiled 9358.5420 3 c +## Eigenvalue based 896.8012 3 b +## deSolve, compiled 718.2324 3 a</code></pre> +<p>We see that using the compiled model is by a factor of 13.5 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:</p> <pre class="r"><code>smb.1["median"]/smb.1["deSolve, compiled", "median"]</code></pre> -<pre><code>## median -## deSolve, not compiled 7.308706 -## Eigenvalue based 1.241484 -## deSolve, compiled 1.000000</code></pre> +<pre><code>## median +## deSolve, not compiled 13.540468 +## Eigenvalue based 1.242324 +## deSolve, compiled 1.000000</code></pre> </div> <div id="benchmark-for-a-model-that-can-not-be-solved-with-eigenvalues" class="section level2"> <h2>Benchmark for a model that can not be solved with Eigenvalues</h2> @@ -133,17 +128,17 @@ smb.2 <- summary(mb.2)[-1] rownames(smb.2) <- c("deSolve, not compiled", "deSolve, compiled") print(smb.2)</code></pre> <pre><code>## min lq mean median uq -## 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 +## deSolve, not compiled 20.130709 20.147223 20.180429 20.163737 20.205289 +## deSolve, compiled 1.235864 1.255748 1.267458 1.275632 1.283255 ## max neval cld -## deSolve, not compiled 10.914558 3 b -## deSolve, compiled 1.227699 3 a</code></pre> +## deSolve, not compiled 20.246841 3 b +## deSolve, compiled 1.290878 3 a</code></pre> <pre class="r"><code>smb.2["median"]/smb.2["deSolve, compiled", "median"]</code></pre> <pre><code>## median -## deSolve, not compiled 8.950036 -## deSolve, compiled 1.000000</code></pre> -<p>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!</p> -<p>This vignette was built with mkin 0.9.40.900 on</p> +## deSolve, not compiled 15.80686 +## deSolve, compiled 1.00000</code></pre> +<p>Here we get a performance benefit of a factor of 15.8 using the version of the differential equation model compiled from C code using the inline package!</p> +<p>This vignette was built with mkin 0.9.41 on</p> <pre><code>## R version 3.2.2 (2015-08-14) ## Platform: x86_64-pc-linux-gnu (64-bit) ## Running under: Debian GNU/Linux 8 (jessie)</code></pre> |