📄 dcprdataplot.html
字号:
<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN" "http://www.w3.org/TR/REC-html40/loose.dtd"><html><head> <title>Description of dcprDataPlot</title> <meta name="keywords" content="dcprDataPlot"> <meta name="description" content="dcprDataPlot: Plot of 2D data for data clustering or pattern recognition"> <meta http-equiv="Content-Type" content="text/html; charset=big5"> <meta name="generator" content="m2html © 2003 Guillaume Flandin"> <meta name="robots" content="index, follow"> <link type="text/css" rel="stylesheet" href="../m2html.css"></head><body><a name="_top"></a><div><a href="../index.html">Home</a> > <a href="index.html">dcpr</a> > dcprDataPlot.m</div><!--<table width="100%"><tr><td align="left"><a href="../index.html"><img alt="<" border="0" src="../left.png"> Master index</a></td><td align="right"><a href="index.html">Index for dcpr <img alt=">" border="0" src="../right.png"></a></td></tr></table>--><h1>dcprDataPlot</h1><h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2><div class="box"><strong>dcprDataPlot: Plot of 2D data for data clustering or pattern recognition</strong></div><h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2><div class="box"><strong>function dcprDataPlot(DS, plotTitle, displayAnnotation) </strong></div><h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2><div class="fragment"><pre class="comment"> dcprDataPlot: Plot of 2D data for data clustering or pattern recognition
Usage: dcprDataPlot(DS, plotTitle, inputName, pointLabel)
DS: data to be displayed
DS.input: input part
DS.output: output part (this part could be missing for DC)
DS.dataName: data name (or description)
DS.inputName: data input name
DS.annotation: data annotation for each data point</pre></div><!-- crossreference --><h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>This function calls:<ul style="list-style-image:url(../matlabicon.gif)"><li><a href="classConvert.html" class="code" title="function label2 = classConvert(label)">classConvert</a> classConvert: Convert class labels into integers from 1 to n</li></ul>This function is called by:<ul style="list-style-image:url(../matlabicon.gif)"><li><a href="crosscTrain.html" class="code" title="function [recogRate, coef]=crosscTrain(DS, CParam, plotOpt)">crosscTrain</a> crosscTrain: Cross classifier training</li><li><a href="dcData.html" class="code" title="function DS = dcdata(dataID)">dcData</a> DCDATA Test data sets for data clustering (no class label).</li><li><a href="knnrLoo.html" class="code" title="function [recogRate, computed, nearestIndex] = knnrLoo(DS, k, plotOpt)">knnrLoo</a> knnrLoo: Leave-one-out recognition rate of KNNR</li><li><a href="lda.html" class="code" title="function [DS2, discrimVec, eigValues] = lda(DS, discrimVecNum)">lda</a> lda: Linear discriminant analysis</li><li><a href="lincTrainMre.html" class="code" title="function [recogRate, coef, regError]=lincTrainMre(DS, CParam, plotOpt)">lincTrainMre</a> lincTrainMre: Linear classifier training for min. regression error</li><li><a href="lincTrainWidro.html" class="code" title="function [recogRate, coef, allRecogRate, allCoef]=lincTrainWidro(DS, trainParam, plotOpt)">lincTrainWidro</a> lincTrainWidro: Linear classifier (Perceptron) training using (revised) Widro-Hoff method</li><li><a href="lincTrainWidro0.html" class="code" title="function coef=linClassifier(DS, trainParam, plotOpt)">lincTrainWidro0</a> linClassifier: Linear classifier (Perceptron) using on-line learning</li><li><a href="pca.html" class="code" title="function [DS2, eigVec, eigValue] = pca(DS, eigVecNum)">pca</a> pca: Principal component analysis</li><li><a href="prData.html" class="code" title="function [DS, TS]=prData(dataName)">prData</a> prData: Various data set for PR</li><li><a href="sgcEval.html" class="code" title="function [computedClass, recogRate, hitIndex]=sgcEval(DS, classParam, plotOpt)">sgcEval</a> sgcTrain: Evaluation for single Gaussian classifier</li><li><a href="sgcTrain.html" class="code" title="function [classParam, recogRate, hitIndex]=sgcTrain(DS, prior, plotOpt)">sgcTrain</a> sgcTrain: Training for single Gaussian classifier training</li><li><a href="vqDataPlot.html" class="code" title="function vqDataPlot(data, center)">vqDataPlot</a> vqDataPlot: Plot the result of vector quantization (used in kmeans.m and vqLBG.m)</li></ul><!-- crossreference --><h2><a name="_subfunctions"></a>SUBFUNCTIONS <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2><ul style="list-style-image:url(../matlabicon.gif)"><li><a href="#_sub1" class="code">function selfdemo</a></li></ul><h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2><div class="fragment"><pre>0001 <a name="_sub0" href="#_subfunctions" class="code">function dcprDataPlot(DS, plotTitle, displayAnnotation)</a>0002 <span class="comment">% dcprDataPlot: Plot of 2D data for data clustering or pattern recognition</span>0003 <span class="comment">% Usage: dcprDataPlot(DS, plotTitle, inputName, pointLabel)</span>0004 <span class="comment">% DS: data to be displayed</span>0005 <span class="comment">% DS.input: input part</span>0006 <span class="comment">% DS.output: output part (this part could be missing for DC)</span>0007 <span class="comment">% DS.dataName: data name (or description)</span>0008 <span class="comment">% DS.inputName: data input name</span>0009 <span class="comment">% DS.annotation: data annotation for each data point</span>0010 0011 <span class="comment">% Roger Jang, 20040910</span>0012 0013 <span class="keyword">if</span> nargin<1, <a href="#_sub1" class="code" title="subfunction selfdemo">selfdemo</a>; <span class="keyword">return</span>; <span class="keyword">end</span>0014 [dim, dataNum]=size(DS.input);0015 <span class="keyword">if</span> dim<2, <span class="keyword">return</span>; <span class="keyword">end</span>0016 <span class="keyword">if</span> nargin<2, plotTitle=<span class="string">''</span>; <span class="keyword">end</span>0017 <span class="keyword">if</span> nargin<3, displayAnnotation=1; <span class="keyword">end</span>0018 0019 <span class="keyword">if</span> ~isfield(DS, <span class="string">'dataName'</span>), DS.dataName=<span class="string">''</span>; <span class="keyword">end</span>0020 <span class="keyword">if</span> ~isfield(DS, <span class="string">'inputName'</span>), <span class="keyword">for</span> i=1:dim, DS.inputName{i}=[<span class="string">'Input '</span>, int2str(i)]; <span class="keyword">end</span>, <span class="keyword">end</span>0021 <span class="keyword">if</span> ~isfield(DS, <span class="string">'annotation'</span>), <span class="keyword">for</span> i=1:dataNum, DS.annotation{i}=int2str(i); <span class="keyword">end</span>, <span class="keyword">end</span>0022 0023 markerSize=5;0024 <span class="keyword">if</span> isfield(DS, <span class="string">'output'</span>)0025 DS.output=<a href="classConvert.html" class="code" title="function label2 = classConvert(label)">classConvert</a>(DS.output); <span class="comment">% Convert the output to be intergers from 1 to classNum</span>0026 classNum=length(unique(DS.output));0027 <span class="keyword">for</span> i=1:classNum0028 index=find(DS.output==i);0029 xData=DS.input(1, index);0030 yData=DS.input(2, index);0031 line(xData, yData, <span class="string">'marker'</span>, <span class="string">'.'</span>, <span class="string">'lineStyle'</span>, <span class="string">'none'</span>, <span class="string">'color'</span>, getColor(i));0032 <span class="keyword">end</span>0033 <span class="keyword">else</span>0034 xData=DS.input(1, :);0035 yData=DS.input(2, :);0036 line(xData, yData, <span class="string">'marker'</span>, <span class="string">'.'</span>, <span class="string">'lineStyle'</span>, <span class="string">'none'</span>, <span class="string">'color'</span>, getColor(1));0037 <span class="keyword">end</span>0038 0039 box on0040 xlabel(DS.inputName{1});0041 ylabel(DS.inputName{2});0042 title(DS.dataName);0043 axis image0044 0045 <span class="comment">% For visual display of annotation on each data point of the plot</span>0046 <span class="keyword">if</span> displayAnnotation0047 circleH=line(nan, nan, <span class="string">'marker'</span>, <span class="string">'o'</span>, <span class="string">'color'</span>, <span class="string">'k'</span>, <span class="string">'erase'</span>, <span class="string">'xor'</span>);0048 textH=text(0, 0, <span class="string">''</span>, <span class="string">'hori'</span>, <span class="string">'center'</span>, <span class="string">'vertical'</span>, <span class="string">'top'</span>, <span class="string">'erase'</span>, <span class="string">'xor'</span>);0049 userData.inData=DS.input;0050 userData.pointLabel=DS.annotation;0051 userData.circleH=circleH;0052 userData.textH=textH;0053 set(gcf, <span class="string">'userData'</span>, userData);0054 set(gcf, <span class="string">'WindowButtonMotionFcn'</span>, <span class="string">'windowButtonMotionFcn'</span>);0055 axis image0056 <span class="keyword">end</span>0057 0058 <span class="comment">% ====== Self demo</span>0059 <a name="_sub1" href="#_subfunctions" class="code">function selfdemo</a>0060 dataNum=100;0061 DS.input=2*rand(2, dataNum)-1;0062 DS.output=DS.input(1,:)+DS.input(2,:)>0;0063 DS.dataName=<span class="string">'Test Data (Click the data point to show its index)'</span>;0064 <span class="keyword">for</span> i=1:length(DS.output)0065 DS.annotation{i}=sprintf(<span class="string">'??%d?”????\n(%f, %f)'</span>, i, DS.input(1,i), DS.input(2,i));0066 <span class="keyword">end</span>0067 feval(mfilename, DS);</pre></div><hr><address>Generated on Thu 30-Oct-2008 12:53:56 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/">m2html</a></strong> © 2003</address></body></html>⌨️ 快捷键说明
复制代码
Ctrl + C
搜索代码
Ctrl + F
全屏模式
F11
切换主题
Ctrl + Shift + D
显示快捷键
?
增大字号
Ctrl + =
减小字号
Ctrl + -