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 a62f3826..a8f6e3ef 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 7047.6039 7083.3201 7123.5962 7119.0364 7161.5924 -## Eigenvalue based 901.5593 924.3357 968.8689 947.1121 1002.5238 -## deSolve, compiled 765.7604 770.7657 786.8638 775.7709 797.4156 +## 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 7204.1483 3 -## Eigenvalue based 1057.9355 3 -## deSolve, compiled 819.0602 3</code></pre> -<p>We see that using the compiled model is by a factor of 9.2 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 6969.7653 3 +## Eigenvalue based 1351.6603 3 +## deSolve, compiled 793.2221 3</code></pre> +<p>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:</p> <pre class="r"><code>smb.1["median"]/smb.1["deSolve, compiled", "median"]</code></pre> <pre><code>## median -## deSolve, not compiled 9.176725 -## Eigenvalue based 1.220866 +## deSolve, not compiled 9.048704 +## Eigenvalue based 1.764945 ## 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 14.080456 14.209689 14.287313 14.338922 14.390742 -## deSolve, compiled 1.467266 1.521451 1.555168 1.575636 1.599119 +## 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 14.442561 3 -## deSolve, compiled 1.622601 3</code></pre> +## deSolve, not compiled 14.227131 3 +## deSolve, compiled 1.446693 3</code></pre> <pre class="r"><code>smb.2["median"]/smb.2["deSolve, compiled", "median"]</code></pre> <pre><code>## median -## deSolve, not compiled 9.100402 -## deSolve, compiled 1.000000</code></pre> -<p>Here we get a performance benefit of a factor of 9.1 using the version of the differential equation model compiled from C code using the inline package!</p> +## deSolve, not compiled 10.34258 +## deSolve, compiled 1.00000</code></pre> +<p>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!</p> <p>This vignette was built with mkin 0.9.39 on</p> <pre><code>## R version 3.2.1 (2015-06-18) ## Platform: x86_64-pc-linux-gnu (64-bit) |