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-rw-r--r--docs/articles/compiled_models.html32
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> &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 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>) &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 8.824334
-## 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> &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 13.587184 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)

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