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authorJohannes Ranke <jranke@uni-bremen.de>2016-10-06 09:40:35 +0200
committerJohannes Ranke <jranke@uni-bremen.de>2016-10-06 09:40:35 +0200
commit7c62da1269e8910a210ba1917d4dc62d186d5606 (patch)
tree57da1e788f84fe95352ff66d22a9da56dc86f9c3 /docs/articles/compiled_models.html
parent38f9e15f0c972c1516ae737a2bca8d7789581bbd (diff)
Static documentation rebuilt by pkgdown::build_site()
Diffstat (limited to 'docs/articles/compiled_models.html')
-rw-r--r--docs/articles/compiled_models.html28
1 files changed, 14 insertions, 14 deletions
diff --git a/docs/articles/compiled_models.html b/docs/articles/compiled_models.html
index 1eeb78c6..d2e1d87d 100644
--- a/docs/articles/compiled_models.html
+++ b/docs/articles/compiled_models.html
@@ -73,21 +73,21 @@ 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 6407.0333 6420.1971 6434.6510 6433.3609 6448.4598
-## Eigenvalue based 887.4338 891.8401 906.9270 896.2463 916.6735
-## deSolve, compiled 720.2433 727.8793 733.2019 735.5152 739.6812
+## deSolve, not compiled 6365.2773 6407.1609 6467.4083 6449.0446 6518.4738
+## Eigenvalue based 872.0339 912.6754 926.7178 953.3169 954.0597
+## deSolve, compiled 730.1252 740.7149 751.8881 751.3045 762.7695
## max neval cld
-## 6463.5587 3 c
-## 937.1007 3 b
-## 743.8472 3 a</code></pre>
+## 6587.9031 3 b
+## 954.8026 3 a
+## 774.2345 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 8.7 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>
+<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>) &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 8.746741
-## Eigenvalue based 1.218529
+## deSolve, not compiled 8.583796
+## Eigenvalue based 1.268882
## deSolve, compiled 1.000000</code></pre>
</div>
<div id="benchmark-for-a-model-that-can-not-be-solved-with-eigenvalues" class="section level2">
@@ -108,12 +108,12 @@ 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 13.501761 13.52142 13.697021 13.541086 13.794651
-## deSolve, compiled 1.359921 1.35996 1.366796 1.359999 1.370233
+## expr min lq mean median uq
+## deSolve, not compiled 13.464194 13.498471 13.52712 13.532748 13.558577
+## deSolve, compiled 1.328628 1.342168 1.35224 1.355707 1.364046
## max neval cld
-## 14.048217 3 b
-## 1.380468 3 a</code></pre>
+## 13.584407 3 b
+## 1.372385 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

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