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authorJohannes Ranke <jranke@uni-bremen.de>2015-06-22 22:18:44 +0200
committerJohannes Ranke <jranke@uni-bremen.de>2015-06-22 22:18:44 +0200
commit4a2809943b4bcb234f1eb979619c8cd27341c124 (patch)
tree81e5e6290c4506b11b85c7f85c371b21081abdd0 /vignettes/compiled_models.html
parent72846ba8a3d75eed97901670eafee36b84f359df (diff)
Vignettes rebuilt by staticdocs::build_site() for static documentation on r-forge
Diffstat (limited to 'vignettes/compiled_models.html')
-rw-r--r--vignettes/compiled_models.html34
1 files changed, 17 insertions, 17 deletions
diff --git a/vignettes/compiled_models.html b/vignettes/compiled_models.html
index ed61b47a..0b77f1c2 100644
--- a/vignettes/compiled_models.html
+++ b/vignettes/compiled_models.html
@@ -98,19 +98,19 @@ mb.1 &lt;- microbenchmark(
smb.1 &lt;- summary(mb.1)[-1]
rownames(smb.1) &lt;- c(&quot;deSolve, not compiled&quot;, &quot;Eigenvalue based&quot;, &quot;deSolve, compiled&quot;)
print(smb.1)</code></pre>
-<pre><code>## min lq mean median uq
-## deSolve, not compiled 6585.7039 6651.4937 6685.6248 6717.2836 6735.5853
-## Eigenvalue based 971.2893 981.5618 998.2746 991.8344 1011.7673
-## deSolve, compiled 760.5522 765.4274 780.3243 770.3026 790.2103
-## max neval
-## deSolve, not compiled 6753.8871 3
-## Eigenvalue based 1031.7003 3
-## deSolve, compiled 810.1179 3</code></pre>
-<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>
+<pre><code>## min lq mean median uq
+## deSolve, not compiled 6737.589 6818.2149 6911.3916 6898.8407 6998.2929
+## Eigenvalue based 945.433 968.8592 979.7477 992.2854 996.9051
+## deSolve, compiled 744.785 748.8107 770.7521 752.8364 783.7357
+## max neval
+## deSolve, not compiled 7097.745 3
+## Eigenvalue based 1001.525 3
+## deSolve, compiled 814.635 3</code></pre>
+<p>We see that using the compiled model is by a factor of 9.2 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[&quot;median&quot;]/smb.1[&quot;deSolve, compiled&quot;, &quot;median&quot;]</code></pre>
<pre><code>## median
-## deSolve, not compiled 8.720318
-## Eigenvalue based 1.287591
+## deSolve, not compiled 9.163798
+## Eigenvalue based 1.318062
## deSolve, compiled 1.000000</code></pre>
</div>
<div id="benchmark-for-a-model-that-can-not-be-solved-with-eigenvalues" class="section level2">
@@ -128,15 +128,15 @@ smb.2 &lt;- summary(mb.2)[-1]
rownames(smb.2) &lt;- c(&quot;deSolve, not compiled&quot;, &quot;deSolve, compiled&quot;)
print(smb.2)</code></pre>
<pre><code>## min lq mean median uq
-## deSolve, not compiled 14.271472 14.285039 14.303450 14.298607 14.319440
-## deSolve, compiled 1.350642 1.390549 1.412823 1.430456 1.443914
+## deSolve, not compiled 13.955273 13.961009 14.041563 13.966745 14.084708
+## deSolve, compiled 1.350567 1.371225 1.381397 1.391882 1.396812
## max neval
-## deSolve, not compiled 14.340272 3
-## deSolve, compiled 1.457372 3</code></pre>
+## deSolve, not compiled 14.202672 3
+## deSolve, compiled 1.401743 3</code></pre>
<pre class="r"><code>smb.2[&quot;median&quot;]/smb.2[&quot;deSolve, compiled&quot;, &quot;median&quot;]</code></pre>
<pre><code>## median
-## deSolve, not compiled 9.995841
-## deSolve, compiled 1.000000</code></pre>
+## deSolve, not compiled 10.03443
+## deSolve, compiled 1.00000</code></pre>
<p>Here we get a performance benefit of a factor of 10 using the version of the differential equation model compiled from C code using the inline package!</p>
<p>This vignette was built with mkin 0.9.37 on</p>
<pre><code>## R version 3.2.1 (2015-06-18)

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