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<html><head> <meta HTTP-EQUIV="Content-Type" CONTENT="text/html;charset=ISO-8859-1"> <title>Contents.m</title><link rel="stylesheet" type="text/css" href="../stpr.css"></head><body><table border=0 width="100%" cellpadding=0 cellspacing=0><tr valign="baseline"><td valign="baseline" class="function"><b class="function">PPATTERNS</b><td valign="baseline" align="right" class="function"><a href="../visual/index.html" target="mdsdir"><img border = 0 src="../up.gif"></a></table> <p><b>Plots pattern as points in feature space.</b></p> <hr><div class='code'><code><span class=help> </span><br><span class=help> <span class=help_field>Synopsis:</span></span><br><span class=help> ppatterns(data,marker_size)</span><br><span class=help> ppatterns(data,'num')</span><br><span class=help> ppatterns(X,marker,marker_size)</span><br><span class=help> ppatterns(X,y)</span><br><span class=help> ppatterns(X,y,marker_size)</span><br><span class=help> ppatterns(X,y,'num')</span><br><span class=help></span><br><span class=help> <span class=help_field>Description:</span></span><br><span class=help> ppatterns(data,marker_size) plots data.X as points</span><br><span class=help> distinguished by marker and its color according to </span><br><span class=help> given labels data.y. The marker size can be prescribed.</span><br><span class=help></span><br><span class=help> ppatterns(data,'num') plots data.X in distinguished </span><br><span class=help> by numbers and colors according to given labels data.y. </span><br><span class=help> The marker size can be determined by argument marker_size.</span><br><span class=help></span><br><span class=help> ppatterns(X,marker,marker_size) plots data X. Marker type</span><br><span class=help> can be determined by argument marker. The marker size can </span><br><span class=help> be determined by argument marker_size.</span><br><span class=help></span><br><span class=help> ppatterns(X,y,...) instead of structure data, which contains</span><br><span class=help> items X and y these can enter the function directly.</span><br><span class=help></span><br><span class=help> If dimension of input data is greater than 3 then</span><br><span class=help> only first 3 dimensions are assumed and data are plotted </span><br><span class=help> in 3D space.</span><br><span class=help></span><br><span class=help> <span class=help_field>Output:</span></span><br><span class=help> H [struct] Handles of used graphical objects.</span><br><span class=help></span><br><span class=help> <span class=help_field>Example:</span></span><br><span class=help> data = load('riply_trn'); </span><br><span class=help> figure; ppatterns(data);</span><br><span class=help> figure; ppatterns(data,'num');</span><br><span class=help> figure; ppatterns(data.X,'xk',10);</span><br><span class=help> </span><br><span class=help> <span class=also_field>See also </span><span class=also></span><br><span class=help><span class=also> <a href = "../visual/pline.html" target="mdsbody">PLINE</a>.</span><br><span class=help></span><br></code></div> <hr> <b>Source:</b> <a href= "../visual/list/ppatterns.html">ppatterns.m</a> <p><b class="info_field">About: </b> Statistical Pattern Recognition Toolbox<br> (C) 1999-2003, Written by Vojtech Franc and Vaclav Hlavac<br> <a href="http://www.cvut.cz">Czech Technical University Prague</a><br> <a href="http://www.feld.cvut.cz">Faculty of Electrical Engineering</a><br> <a href="http://cmp.felk.cvut.cz">Center for Machine Perception</a><br> <p><b class="info_field">Modifications: </b> <br> 25-may-2004, VF<br> 11-mar-2004, VF, <br> 5-oct-2003, VF, returns handles<br> 12-feb-2003, VF, 1D, 3D added<br> 7-jan-2003, VF, created<br></body></html>⌨️ 快捷键说明
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