diff options
Diffstat (limited to 'vignettes/compiled_models.html')
| -rw-r--r-- | vignettes/compiled_models.html | 34 |
1 files changed, 17 insertions, 17 deletions
diff --git a/vignettes/compiled_models.html b/vignettes/compiled_models.html index 0b77f1c2..8fb08136 100644 --- a/vignettes/compiled_models.html +++ b/vignettes/compiled_models.html @@ -98,19 +98,19 @@ mb.1 <- microbenchmark( 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 6737.589 6818.2149 6911.3916 6898.8407 6998.2929 -## Eigenvalue based 945.433 968.8592 979.7477 992.2854 996.9051 -## deSolve, compiled 744.785 748.8107 770.7521 752.8364 783.7357 -## max neval -## deSolve, not compiled 7097.745 3 -## Eigenvalue based 1001.525 3 -## deSolve, compiled 814.635 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> +<pre><code>## min lq mean median uq +## deSolve, not compiled 6896.8680 6933.3330 6963.5277 6969.7979 6996.8575 +## Eigenvalue based 933.0581 937.8984 963.5002 942.7388 978.7213 +## deSolve, compiled 784.9729 807.9919 822.4500 831.0110 841.1886 +## max neval +## deSolve, not compiled 7023.9171 3 +## Eigenvalue based 1014.7039 3 +## deSolve, compiled 851.3663 3</code></pre> +<p>We see that using the compiled model is by a factor of 8.4 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 9.163798 -## Eigenvalue based 1.318062 +## deSolve, not compiled 8.387131 +## Eigenvalue based 1.134448 ## 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 13.955273 13.961009 14.041563 13.966745 14.084708 -## deSolve, compiled 1.350567 1.371225 1.381397 1.391882 1.396812 +## deSolve, not compiled 14.661881 14.668453 14.701870 14.675025 14.721864 +## deSolve, compiled 1.393051 1.394908 1.415653 1.396764 1.426953 ## max neval -## deSolve, not compiled 14.202672 3 -## deSolve, compiled 1.401743 3</code></pre> +## deSolve, not compiled 14.768704 3 +## deSolve, compiled 1.457143 3</code></pre> <pre class="r"><code>smb.2["median"]/smb.2["deSolve, compiled", "median"]</code></pre> <pre><code>## median -## deSolve, not compiled 10.03443 +## deSolve, not compiled 10.50644 ## deSolve, compiled 1.00000</code></pre> -<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>Here we get a performance benefit of a factor of 10.5 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) |