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 2fbef8ae..a415c735 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 6760.8015 6766.0464 6785.8509 6771.2913 6798.3756 -## Eigenvalue based 930.9980 944.5895 973.5743 958.1810 994.8625 -## deSolve, compiled 758.2721 811.0584 836.3348 863.8448 875.3661 +## deSolve, not compiled 6958.1752 7034.5639 7074.0173 7110.9526 7131.9383 +## Eigenvalue based 978.8821 988.5741 1012.6283 998.2660 1029.5014 +## deSolve, compiled 756.0280 767.9740 800.3639 779.9199 822.5318 ## max neval -## deSolve, not compiled 6825.4600 3 -## Eigenvalue based 1031.5439 3 -## deSolve, compiled 886.8875 3</code></pre> -<p>We see that using the compiled model is by a factor of 7.8 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 7152.9240 3 +## Eigenvalue based 1060.7367 3 +## deSolve, compiled 865.1437 3</code></pre> +<p>We see that using the compiled model is by a factor of 9.1 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 7.838551 -## Eigenvalue based 1.109205 +## deSolve, not compiled 9.117542 +## Eigenvalue based 1.279960 ## deSolve, compiled 1.000000</code></pre> </div> <div id="benchmark-for-a-model-that-can-not-be-solved-with-eigenvalues" class="section level2"> @@ -128,16 +128,16 @@ 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 14.231863 14.287058 14.336780 14.342252 14.389238 -## deSolve, compiled 1.344761 1.345452 1.361713 1.346142 1.370189 +## deSolve, not compiled 14.586587 14.604167 14.614147 14.621747 14.627927 +## deSolve, compiled 1.428573 1.449463 1.459828 1.470352 1.475455 ## max neval -## deSolve, not compiled 14.436224 3 -## deSolve, compiled 1.394235 3</code></pre> +## deSolve, not compiled 14.634107 3 +## deSolve, compiled 1.480558 3</code></pre> <pre class="r"><code>smb.2["median"]/smb.2["deSolve, compiled", "median"]</code></pre> <pre><code>## median -## deSolve, not compiled 10.65434 -## deSolve, compiled 1.00000</code></pre> -<p>Here we get a performance benefit of a factor of 10.7 using the version of the differential equation model compiled from C code using the inline package!</p> +## deSolve, not compiled 9.944383 +## deSolve, compiled 1.000000</code></pre> +<p>Here we get a performance benefit of a factor of 9.9 using the version of the differential equation model compiled from C code using the inline package!</p> <p>This vignette was built with mkin 0.9.37 on</p> <pre><code>## R version 3.2.1 (2015-06-18) ## Platform: x86_64-pc-linux-gnu (64-bit) |