diff options
Diffstat (limited to 'vignettes/compiled_models.html')
| -rw-r--r-- | vignettes/compiled_models.html | 42 |
1 files changed, 21 insertions, 21 deletions
diff --git a/vignettes/compiled_models.html b/vignettes/compiled_models.html index e6f21b09..5fcd88fb 100644 --- a/vignettes/compiled_models.html +++ b/vignettes/compiled_models.html @@ -94,20 +94,20 @@ 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 4969.585 5033.7311 5092.7389 5097.8773 5154.3160 -## Eigenvalue based 868.731 891.7239 909.6449 914.7169 930.1018 -## deSolve, compiled 4935.049 4935.4796 4968.2150 4935.9097 4984.7978 +<pre><code>## min lq mean median uq +## deSolve, not compiled 6980.8002 6996.4739 7024.5611 7012.1476 7046.4415 +## Eigenvalue based 925.3350 928.9405 951.8405 932.5460 965.0932 +## deSolve, compiled 747.2635 761.9405 771.4339 776.6174 783.5191 ## max neval -## deSolve, not compiled 5210.7547 3 -## Eigenvalue based 945.4867 3 -## deSolve, compiled 5033.6858 3</code></pre> -<p>We see that using the compiled model is almost a factor of 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 7080.7354 3 +## Eigenvalue based 997.6404 3 +## deSolve, compiled 790.4207 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 1.0328141 -## Eigenvalue based 0.1853188 -## deSolve, compiled 1.0000000</code></pre> +<pre><code>## median +## deSolve, not compiled 9.029089 +## Eigenvalue based 1.200779 +## deSolve, compiled 1.000000</code></pre> </div> <div id="benchmark-for-a-model-that-can-not-be-solved-with-eigenvalues" class="section level1"> <h1>Benchmark for a model that can not be solved with Eigenvalues</h1> @@ -124,16 +124,16 @@ 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 11.745276 11.754288 11.820726 11.763300 11.858451 -## deSolve, compiled 1.385829 1.386407 1.400841 1.386985 1.408347 -## max neval -## deSolve, not compiled 11.95360 3 -## deSolve, compiled 1.42971 3</code></pre> +## deSolve, not compiled 14.127630 14.245064 14.298201 14.362497 14.383486 +## deSolve, compiled 1.354744 1.362167 1.366362 1.369589 1.372171 +## max neval +## deSolve, not compiled 14.404474 3 +## deSolve, compiled 1.374752 3</code></pre> <pre class="r"><code>smb.2["median"]/smb.2["deSolve, compiled", "median"]</code></pre> -<pre><code>## median -## deSolve, not compiled 8.4812 -## deSolve, compiled 1.0000</code></pre> -<p>Here we get a performance benefit of more than a factor of 10 using the version of the differential equation model compiled from C code using the inline package!</p> +<pre><code>## median +## deSolve, not compiled 10.48672 +## deSolve, compiled 1.00000</code></pre> +<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> </div> |