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Diffstat (limited to 'docs/articles/compiled_models.html')
| -rw-r--r-- | docs/articles/compiled_models.html | 28 |
1 files changed, 14 insertions, 14 deletions
diff --git a/docs/articles/compiled_models.html b/docs/articles/compiled_models.html index 660af1d1..457f5a1d 100644 --- a/docs/articles/compiled_models.html +++ b/docs/articles/compiled_models.html @@ -99,21 +99,21 @@ mb<span class="fl">.1</span> <-<span class="st"> </span><span class="kw">micr <span class="kw">print</span>(mb<span class="fl">.1</span>)</code></pre></div> <pre><code>## Unit: milliseconds ## expr min lq mean median uq -## deSolve, not compiled 5006.3815 5014.4629 5112.7115 5022.5443 5165.8765 -## Eigenvalue based 840.3027 874.3549 892.0593 908.4071 917.9376 -## deSolve, compiled 706.9909 712.8031 723.4380 718.6154 731.6615 +## deSolve, not compiled 5185.0893 5231.5690 5266.8769 5278.0487 5307.7706 +## Eigenvalue based 843.3153 847.1503 876.5398 850.9853 893.1520 +## deSolve, compiled 723.0636 740.5682 755.9995 758.0729 772.4674 ## max neval cld -## 5309.2087 3 b -## 927.4680 3 a -## 744.7077 3 a</code></pre> +## 5337.4926 3 b +## 935.3187 3 a +## 786.8620 3 a</code></pre> <div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw">autoplot</span>(mb<span class="fl">.1</span>)</code></pre></div> <p><img src="compiled_models_files/figure-html/benchmark_SFO_SFO-1.png" width="672"></p> <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> <div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw">rownames</span>(smb<span class="fl">.1</span>) <-<span class="st"> </span>smb<span class="fl">.1</span>$expr smb<span class="fl">.1</span>[<span class="st">"median"</span>]/smb<span class="fl">.1</span>[<span class="st">"deSolve, compiled"</span>, <span class="st">"median"</span>]</code></pre></div> <pre><code>## median -## deSolve, not compiled 6.989197 -## Eigenvalue based 1.264108 +## deSolve, not compiled 6.962456 +## Eigenvalue based 1.122564 ## deSolve, compiled 1.000000</code></pre> </div> <div id="model-that-can-not-be-solved-with-eigenvalues" class="section level2"> @@ -134,19 +134,19 @@ smb<span class="fl">.1</span>[<span class="st">"median"</span>]/smb<span class=" <div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r">smb<span class="fl">.2</span> <-<span class="st"> </span><span class="kw">summary</span>(mb<span class="fl">.2</span>) <span class="kw">print</span>(mb<span class="fl">.2</span>)</code></pre></div> <pre><code>## Unit: seconds -## expr min lq mean median uq -## deSolve, not compiled 11.015990 11.17783 11.24827 11.339674 11.364403 -## deSolve, compiled 1.285264 1.29794 1.32988 1.310616 1.352189 +## expr min lq mean median uq +## deSolve, not compiled 10.963655 10.992677 11.033360 11.02170 11.068212 +## deSolve, compiled 1.287898 1.309754 1.322972 1.33161 1.340509 ## max neval cld -## 11.389132 3 b -## 1.393762 3 a</code></pre> +## 11.114726 3 b +## 1.349408 3 a</code></pre> <div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r">smb<span class="fl">.2</span>[<span class="st">"median"</span>]/smb<span class="fl">.2</span>[<span class="st">"deSolve, compiled"</span>, <span class="st">"median"</span>]</code></pre></div> <pre><code>## median ## 1 NA ## 2 NA</code></pre> <div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw">autoplot</span>(mb<span class="fl">.2</span>)</code></pre></div> <p><img src="compiled_models_files/figure-html/benchmark_FOMC_SFO-1.png" width="672"></p> -<p>Here we get a performance benefit of a factor of 8.7 using the version of the differential equation model compiled from C code!</p> +<p>Here we get a performance benefit of a factor of 8.3 using the version of the differential equation model compiled from C code!</p> <p>This vignette was built with mkin 0.9.45 on</p> <pre><code>## R version 3.3.2 (2016-10-31) ## Platform: x86_64-pc-linux-gnu (64-bit) |