diff options
Diffstat (limited to 'vignettes/web_only')
| -rw-r--r-- | vignettes/web_only/compiled_models.Rmd | 2 | ||||
| -rw-r--r-- | vignettes/web_only/compiled_models.html | 92 |
2 files changed, 80 insertions, 14 deletions
diff --git a/vignettes/web_only/compiled_models.Rmd b/vignettes/web_only/compiled_models.Rmd index ae283238..26d86811 100644 --- a/vignettes/web_only/compiled_models.Rmd +++ b/vignettes/web_only/compiled_models.Rmd @@ -58,7 +58,7 @@ if (require(rbenchmark)) { factor_SFO_SFO <- round(b.1["1", "relative"])
} else {
factor_SFO_SFO <- NA
- print("R package benchmark is not available")
+ print("R package rbenchmark is not available")
}
```
diff --git a/vignettes/web_only/compiled_models.html b/vignettes/web_only/compiled_models.html index 8b4f3955..366161ee 100644 --- a/vignettes/web_only/compiled_models.html +++ b/vignettes/web_only/compiled_models.html @@ -11,7 +11,7 @@ <meta name="author" content="Johannes Ranke" /> -<meta name="date" content="2018-09-14" /> +<meta name="date" content="2019-04-04" /> <title>Performance benefit by using compiled model definitions in mkin</title> @@ -1408,9 +1408,15 @@ img { .tabbed-pane { padding-top: 12px; } +.html-widget { + margin-bottom: 20px; +} button.code-folding-btn:focus { outline: none; } +summary { + display: list-item; +} </style> @@ -1418,10 +1424,71 @@ button.code-folding-btn:focus { <div class="container-fluid main-container"> <!-- tabsets --> + +<style type="text/css"> +.tabset-dropdown > .nav-tabs { + display: inline-table; + max-height: 500px; + min-height: 44px; + overflow-y: auto; + background: white; + border: 1px solid #ddd; + border-radius: 4px; +} + +.tabset-dropdown > .nav-tabs > li.active:before { + content: ""; + font-family: 'Glyphicons Halflings'; + display: inline-block; + padding: 10px; + border-right: 1px solid #ddd; +} + +.tabset-dropdown > .nav-tabs.nav-tabs-open > li.active:before { + content: ""; + border: none; +} + +.tabset-dropdown > .nav-tabs.nav-tabs-open:before { + content: ""; + font-family: 'Glyphicons Halflings'; + display: inline-block; + padding: 10px; + border-right: 1px solid #ddd; +} + +.tabset-dropdown > .nav-tabs > li.active { + display: block; +} + +.tabset-dropdown > .nav-tabs > li > a, +.tabset-dropdown > .nav-tabs > li > a:focus, +.tabset-dropdown > .nav-tabs > li > a:hover { + border: none; + display: inline-block; + border-radius: 4px; +} + +.tabset-dropdown > .nav-tabs.nav-tabs-open > li { + display: block; + float: none; +} + +.tabset-dropdown > .nav-tabs > li { + display: none; +} +</style> + <script> $(document).ready(function () { window.buildTabsets("TOC"); }); + +$(document).ready(function () { + $('.tabset-dropdown > .nav-tabs > li').click(function () { + $(this).parent().toggleClass('nav-tabs-open') + }); +}); </script> <!-- code folding --> @@ -1436,7 +1503,6 @@ $(document).ready(function () { - <script> $(document).ready(function () { @@ -1548,7 +1614,7 @@ div.tocify { <h1 class="title toc-ignore">Performance benefit by using compiled model definitions in mkin</h1> <h4 class="author"><em>Johannes Ranke</em></h4> -<h4 class="date"><em>2018-09-14</em></h4> +<h4 class="date"><em>2019-04-04</em></h4> </div> @@ -1580,18 +1646,18 @@ SFO_SFO <- mkinmod( factor_SFO_SFO <- round(b.1["1", "relative"]) } else { factor_SFO_SFO <- NA - print("R package benchmark is not available") + print("R package rbenchmark is not available") }</code></pre> <pre><code>## Loading required package: rbenchmark</code></pre> <pre><code>## test replications elapsed relative user.self sys.self -## 3 deSolve, compiled 3 2.180 1.000 2.179 0 -## 1 deSolve, not compiled 3 16.710 7.665 16.702 0 -## 2 Eigenvalue based 3 2.721 1.248 2.719 0 +## 3 deSolve, compiled 3 3.533 1.000 3.531 0 +## 1 deSolve, not compiled 3 46.050 13.034 46.030 0 +## 2 Eigenvalue based 3 5.068 1.434 5.066 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 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 around 13 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>Model that can not be solved with Eigenvalues</h2> @@ -1614,14 +1680,14 @@ SFO_SFO <- mkinmod( }</code></pre> <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 3.703 1.000 3.700 0 -## 1 deSolve, not compiled 3 34.789 9.395 34.772 0 +## 2 deSolve, compiled 3 4.934 1.000 4.931 0 +## 1 deSolve, not compiled 3 72.993 14.794 72.961 0 ## user.child sys.child ## 2 0 0 ## 1 0 0</code></pre> -<p>Here we get a performance benefit of a factor of 9 using the version of the differential equation model compiled from C code!</p> -<p>This vignette was built with mkin 0.9.47.5 on</p> -<pre><code>## R version 3.5.1 (2018-07-02) +<p>Here we get a performance benefit of a factor of 15 using the version of the differential equation model compiled from C code!</p> +<p>This vignette was built with mkin 0.9.49.1 on</p> +<pre><code>## R version 3.5.3 (2019-03-11) ## 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> |