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-rw-r--r--docs/articles/compiled_models.html33
1 files changed, 18 insertions, 15 deletions
diff --git a/docs/articles/compiled_models.html b/docs/articles/compiled_models.html
index 2850a9ae..660af1d1 100644
--- a/docs/articles/compiled_models.html
+++ b/docs/articles/compiled_models.html
@@ -37,6 +37,9 @@
<a href="../articles/compiled_models.html">Performance benefit by using compiled model definitions in mkin</a>
</li>
</ul></li>
+<li>
+ <a href="../news/index.html">News</a>
+</li>
</ul><ul class="nav navbar-nav navbar-right"><li>
<a href="http://github.com/jranke/mkin">
<span class="fa fa-github fa-lg"></span>
@@ -96,21 +99,21 @@ mb<span class="fl">.1</span> &lt;-<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 4973.8901 4975.2320 5000.4065 4976.5739 5013.6648
-## Eigenvalue based 848.4335 859.7111 886.9766 870.9887 906.2481
-## deSolve, compiled 702.8916 705.1930 706.2696 707.4944 707.9587
+## 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
## max neval cld
-## 5050.7556 3 c
-## 941.5075 3 b
-## 708.4229 3 a</code></pre>
+## 5309.2087 3 b
+## 927.4680 3 a
+## 744.7077 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>) &lt;-<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 7.034082
-## Eigenvalue based 1.231089
+## deSolve, not compiled 6.989197
+## Eigenvalue based 1.264108
## deSolve, compiled 1.000000</code></pre>
</div>
<div id="model-that-can-not-be-solved-with-eigenvalues" class="section level2">
@@ -131,20 +134,20 @@ 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> &lt;-<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 10.819486 10.846433 10.863732 10.873381 10.885855
-## deSolve, compiled 1.300192 1.301168 1.304769 1.302144 1.307058
+## 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
## max neval cld
-## 10.898330 3 b
-## 1.311972 3 a</code></pre>
+## 11.389132 3 b
+## 1.393762 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 8.4 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>
+<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>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)
## Running under: Debian GNU/Linux 8 (jessie)</code></pre>

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