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(v1.0.1.9002) PCA unit tests

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dr. M.S. (Matthijs) Berends
2020-03-08 11:18:59 +01:00
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@ -6,7 +6,7 @@
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Principal Component Analysis (for AMR) — prcomp.data.frame • AMR (for R)</title>
<title>Principal Component Analysis (for AMR) — pca • AMR (for R)</title>
<!-- favicons -->
<link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png">
@ -44,8 +44,8 @@
<link href="../extra.css" rel="stylesheet">
<script src="../extra.js"></script>
<meta property="og:title" content="Principal Component Analysis (for AMR) — prcomp.data.frame" />
<meta property="og:description" content="Performs a principal component analysis (PCA) based on a data set with automatic determination for afterwards plotting the groups and labels." />
<meta property="og:title" content="Principal Component Analysis (for AMR) — pca" />
<meta property="og:description" content="Performs a principal component analysis (PCA) based on a data set with automatic determination for afterwards plotting the groups and labels, and automatic filtering on only suitable (i.e. non-empty and numeric) variables." />
<meta property="og:image" content="https://msberends.gitlab.io/AMR/logo.png" />
<meta name="twitter:card" content="summary" />
@ -79,7 +79,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.0.1.9000</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.0.1.9002</span>
</span>
</div>
@ -229,11 +229,10 @@
</div>
<div class="ref-description">
<p>Performs a principal component analysis (PCA) based on a data set with automatic determination for afterwards plotting the groups and labels.</p>
<p>Performs a principal component analysis (PCA) based on a data set with automatic determination for afterwards plotting the groups and labels, and automatic filtering on only suitable (i.e. non-empty and numeric) variables.</p>
</div>
<pre class="usage"><span class='co'># S3 method for data.frame</span>
<span class='fu'><a href='https://rdrr.io/r/stats/prcomp.html'>prcomp</a></span>(
<pre class="usage"><span class='fu'>pca</span>(
<span class='no'>x</span>,
<span class='no'>...</span>,
<span class='kw'>retx</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
@ -241,9 +240,7 @@
<span class='kw'>scale.</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
<span class='kw'>tol</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
<span class='kw'>rank.</span> <span class='kw'>=</span> <span class='kw'>NULL</span>
)
<span class='fu'>pca</span>(<span class='no'>x</span>, <span class='no'>...</span>)</pre>
)</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
@ -297,10 +294,13 @@
</tr>
</table>
<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
<p>An object of classes pca and <a href='https://rdrr.io/r/stats/prcomp.html'>prcomp</a></p>
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p>The <code>pca()</code> function takes a <a href='https://rdrr.io/r/base/data.frame.html'>data.frame</a> as input and performs the actual PCA with the R function <code><a href='https://rdrr.io/r/stats/prcomp.html'>prcomp()</a></code>.</p>
<p>The result of the <code>pca()</code> function is a <code><a href='https://rdrr.io/r/stats/prcomp.html'>prcomp</a></code> object, with an additional attribute <code>non_numeric_cols</code> which is a vector with the column names of all columns that do not contain numeric values. These are probably the groups and labels, and will be used by <code><a href='ggplot_pca.html'>ggplot_pca()</a></code>.</p>
<p>The <code>pca()</code> function takes a <a href='https://rdrr.io/r/base/data.frame.html'>data.frame</a> as input and performs the actual PCA with the <span style="R">R</span> function <code><a href='https://rdrr.io/r/stats/prcomp.html'>prcomp()</a></code>.</p>
<p>The result of the <code>pca()</code> function is a <a href='https://rdrr.io/r/stats/prcomp.html'>prcomp</a> object, with an additional attribute <code>non_numeric_cols</code> which is a vector with the column names of all columns that do not contain numeric values. These are probably the groups and labels, and will be used by <code><a href='ggplot_pca.html'>ggplot_pca()</a></code>.</p>
<h2 class="hasAnchor" id="experimental-lifecycle"><a class="anchor" href="#experimental-lifecycle"></a>Experimental lifecycle</h2>
@ -332,6 +332,7 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>experimen
<h2>Contents</h2>
<ul class="nav nav-pills nav-stacked">
<li><a href="#arguments">Arguments</a></li>
<li><a href="#value">Value</a></li>
<li><a href="#details">Details</a></li>
<li><a href="#experimental-lifecycle">Experimental lifecycle</a></li>
<li><a href="#examples">Examples</a></li>