diff options
Diffstat (limited to 'vignettes/compiled_models.html')
| -rw-r--r-- | vignettes/compiled_models.html | 32 |
1 files changed, 16 insertions, 16 deletions
diff --git a/vignettes/compiled_models.html b/vignettes/compiled_models.html index fc71debe..ed61b47a 100644 --- a/vignettes/compiled_models.html +++ b/vignettes/compiled_models.html @@ -99,18 +99,18 @@ 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 5379.4269 5431.6605 5455.0396 5483.8940 5492.8460 -## Eigenvalue based 930.6245 951.6701 959.4653 972.7157 973.8857 -## deSolve, compiled 755.9828 771.1000 794.1810 786.2172 813.2800 +## deSolve, not compiled 6585.7039 6651.4937 6685.6248 6717.2836 6735.5853 +## Eigenvalue based 971.2893 981.5618 998.2746 991.8344 1011.7673 +## deSolve, compiled 760.5522 765.4274 780.3243 770.3026 790.2103 ## max neval -## deSolve, not compiled 5501.7979 3 -## Eigenvalue based 975.0556 3 -## deSolve, compiled 840.3428 3</code></pre> -<p>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:</p> +## deSolve, not compiled 6753.8871 3 +## Eigenvalue based 1031.7003 3 +## deSolve, compiled 810.1179 3</code></pre> +<p>We see that using the compiled model is by a factor of 8.7 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:</p> <pre class="r"><code>smb.1["median"]/smb.1["deSolve, compiled", "median"]</code></pre> <pre><code>## median -## deSolve, not compiled 6.975037 -## Eigenvalue based 1.237210 +## deSolve, not compiled 8.720318 +## Eigenvalue based 1.287591 ## deSolve, compiled 1.000000</code></pre> </div> <div id="benchmark-for-a-model-that-can-not-be-solved-with-eigenvalues" class="section level2"> @@ -127,17 +127,17 @@ print(smb.1)</code></pre> 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 11.815894 11.84960 12.03290 11.883305 12.141404 -## deSolve, compiled 1.387086 1.43514 1.45956 1.483194 1.495796 +<pre><code>## min lq mean median uq +## deSolve, not compiled 14.271472 14.285039 14.303450 14.298607 14.319440 +## deSolve, compiled 1.350642 1.390549 1.412823 1.430456 1.443914 ## max neval -## deSolve, not compiled 12.399502 3 -## deSolve, compiled 1.508399 3</code></pre> +## deSolve, not compiled 14.340272 3 +## deSolve, compiled 1.457372 3</code></pre> <pre class="r"><code>smb.2["median"]/smb.2["deSolve, compiled", "median"]</code></pre> <pre><code>## median -## deSolve, not compiled 8.011968 +## deSolve, not compiled 9.995841 ## deSolve, compiled 1.000000</code></pre> -<p>Here we get a performance benefit of a factor of 8 using the version of the differential equation model compiled from C code using the inline package!</p> +<p>Here we get a performance benefit of a factor of 10 using the version of the differential equation model compiled from C code using the inline package!</p> <p>This vignette was built with mkin 0.9.37 on</p> <pre><code>## R version 3.2.1 (2015-06-18) ## Platform: x86_64-pc-linux-gnu (64-bit) |