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authorJohannes Ranke <jranke@uni-bremen.de>2018-07-18 15:18:30 +0200
committerJohannes Ranke <jranke@uni-bremen.de>2018-07-18 15:58:46 +0200
commit0b98c459c30a0629a728acf6b311de035c55fb64 (patch)
treef146faf4802da38862aa14b0268265f3fad9ba34 /docs/articles/compiled_models.html
parentd3ed95f2a0a43ed74b02ea90e35d043ed4e1e72f (diff)
Correct references to the Rocke and Lorenzato model
Rename 'sigma_rl' to 'sigma_twocomp' as the Rocke and Lorenzato model assumes lognormal distribution for large y. Rebuild static documentation.
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1 files changed, 9 insertions, 9 deletions
diff --git a/docs/articles/compiled_models.html b/docs/articles/compiled_models.html
index 379176bf..183c9658 100644
--- a/docs/articles/compiled_models.html
+++ b/docs/articles/compiled_models.html
@@ -29,7 +29,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">mkin</a>
- <span class="label label-default" data-toggle="tooltip" data-placement="bottom" title="Released package">0.9.47.1</span>
+ <span class="label label-default" data-toggle="tooltip" data-placement="bottom" title="Released package">0.9.47.2</span>
</span>
</div>
@@ -84,7 +84,7 @@
<h1>Performance benefit by using compiled model definitions in mkin</h1>
<h4 class="author">Johannes Ranke</h4>
- <h4 class="date">2018-06-06</h4>
+ <h4 class="date">2018-07-18</h4>
<div class="hidden name"><code>compiled_models.Rmd</code></div>
@@ -125,14 +125,14 @@ SFO_SFO &lt;-<span class="st"> </span><span class="kw"><a href="../reference/mki
}</code></pre></div>
<pre><code>## Lade nötiges Paket: rbenchmark</code></pre>
<pre><code>## test replications elapsed relative user.self sys.self
-## 3 deSolve, compiled 3 2.335 1.000 2.333 0
-## 1 deSolve, not compiled 3 16.810 7.199 16.801 0
-## 2 Eigenvalue based 3 2.882 1.234 2.879 0
+## 3 deSolve, compiled 3 2.044 1.000 2.043 0
+## 1 deSolve, not compiled 3 16.571 8.107 16.565 0
+## 2 Eigenvalue based 3 2.499 1.223 2.496 0
## user.child sys.child
## 3 0 0
## 1 0 0
## 2 0 0</code></pre>
-<p>We see that using the compiled model is by a factor of around 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 around 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>
</div>
<div id="model-that-can-not-be-solved-with-eigenvalues" class="section level2">
<h2 class="hasAnchor">
@@ -156,14 +156,14 @@ SFO_SFO &lt;-<span class="st"> </span><span class="kw"><a href="../reference/mki
}</code></pre></div>
<pre><code>## Successfully compiled differential equation model from auto-generated C code.</code></pre>
<pre><code>## test replications elapsed relative user.self sys.self
-## 2 deSolve, compiled 3 3.766 1.000 3.764 0
-## 1 deSolve, not compiled 3 37.119 9.856 37.097 0
+## 2 deSolve, compiled 3 3.592 1.000 3.589 0
+## 1 deSolve, not compiled 3 35.340 9.839 35.324 0
## user.child sys.child
## 2 0 0
## 1 0 0</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!</p>
<p>This vignette was built with mkin 0.9.47.1 on</p>
-<pre><code>## R version 3.5.0 (2018-04-23)
+<pre><code>## R version 3.5.1 (2018-07-02)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Debian GNU/Linux 9 (stretch)</code></pre>
<pre><code>## CPU model: AMD Ryzen 7 1700 Eight-Core Processor</code></pre>

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