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Diffstat (limited to 'docs/articles/compiled_models.html')
| -rw-r--r-- | docs/articles/compiled_models.html | 32 |
1 files changed, 16 insertions, 16 deletions
diff --git a/docs/articles/compiled_models.html b/docs/articles/compiled_models.html index 31340867..87913685 100644 --- a/docs/articles/compiled_models.html +++ b/docs/articles/compiled_models.html @@ -16,7 +16,7 @@ </div> <div id="navbar" class="navbar-collapse collapse"> <ul class="nav navbar-nav"><li> - <a href="../reference/index.html">Function reference</a> + <a href="../reference/index.html">Functions and data</a> </li> <li class="dropdown"> <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false"> @@ -91,21 +91,21 @@ 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 6559.0772 6574.0500 6642.0659 6589.0229 6683.5603 -## Eigenvalue based 921.0723 931.1284 940.3973 941.1845 950.0598 -## deSolve, compiled 736.6534 741.6706 756.3600 746.6878 766.2132 +## deSolve, not compiled 6126.4954 6152.1764 6170.8152 6177.8573 6192.9751 +## Eigenvalue based 864.8441 891.7069 902.0212 918.5697 920.6098 +## deSolve, compiled 706.9115 711.1015 714.9195 715.2915 718.9235 ## max neval cld -## 6778.0978 3 c -## 958.9351 3 b -## 785.7386 3 a</code></pre> +## 6208.0929 3 c +## 922.6498 3 b +## 722.5556 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 8.8 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> +<p>We see that using the compiled model is by a factor of 8.6 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 8.824334 -## Eigenvalue based 1.260479 +## deSolve, not compiled 8.636839 +## Eigenvalue based 1.284189 ## deSolve, compiled 1.000000</code></pre> </div> <div id="model-that-can-not-be-solved-with-eigenvalues" class="section level2"> @@ -126,19 +126,19 @@ 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 13.587184 13.616178 13.673277 13.64517 13.716324 -## deSolve, compiled 1.307508 1.317114 1.337594 1.32672 1.352637 +## expr min lq mean median uq +## deSolve, not compiled 13.163796 13.205491 13.478255 13.247187 13.635484 +## deSolve, compiled 1.267154 1.268198 1.272722 1.269242 1.275506 ## max neval cld -## 13.787476 3 b -## 1.378553 3 a</code></pre> +## 14.023782 3 b +## 1.281771 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 10.3 using the version of the differential equation model compiled from C code!</p> +<p>Here we get a performance benefit of a factor of 10.4 using the version of the differential equation model compiled from C code!</p> <p>This vignette was built with mkin 0.9.44.9000 on</p> <pre><code>## R version 3.3.2 (2016-10-31) ## Platform: x86_64-pc-linux-gnu (64-bit) |