本文整理汇总了Java中weka.gui.visualize.Plot2D类的典型用法代码示例。如果您正苦于以下问题：Java Plot2D类的具体用法？Java Plot2D怎么用？Java Plot2D使用的例子？那么恭喜您, 这里精选的类代码示例或许可以为您提供帮助。
Plot2D类属于weka.gui.visualize包，在下文中一共展示了Plot2D类的6个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于我们的系统推荐出更棒的Java代码示例。
示例1: process
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import weka.gui.visualize.Plot2D; //导入依赖的package包/类
/**
* Generates the cluster assignments.
*
* @see #m_PlotShapes
* @see #m_PlotSizes
* @see #m_PlotInstances
*/
protected void process() {
double[] clusterAssignments;
int i;
double[] values;
int j;
int[] classAssignments;
clusterAssignments = m_Evaluation.getClusterAssignments();
classAssignments = null;
if (m_Instances.classIndex() >= 0) {
classAssignments = m_Evaluation.getClassesToClusters();
m_PlotShapes = new int[m_Instances.numInstances()];
for (i = 0; i < m_Instances.numInstances(); i++)
m_PlotShapes[i] = Plot2D.CONST_AUTOMATIC_SHAPE;
}
for (i = 0; i < m_Instances.numInstances(); i++) {
values = new double[m_PlotInstances.numAttributes()];
for (j = 0; j < m_Instances.numAttributes(); j++)
values[j] = m_Instances.instance(i).value(j);
if (clusterAssignments[i] < 0) {
values[j] = Utils.missingValue();
} else {
values[j] = clusterAssignments[i];
}
m_PlotInstances.add(new DenseInstance(1.0, values));
if (m_PlotShapes != null) {
if (clusterAssignments[i] >= 0) {
if ((int) m_Instances.instance(i).classValue() != classAssignments[(int) clusterAssignments[i]])
m_PlotShapes[i] = Plot2D.ERROR_SHAPE;
} else {
m_PlotShapes[i] = Plot2D.MISSING_SHAPE;
}
}
}
}
开发者ID:dsibournemouth，
项目名称:autoweka，
代码行数:45，
代码来源:ClustererAssignmentsPlotInstances.java
示例2: process
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import weka.gui.visualize.Plot2D; //导入依赖的package包/类
/**
* Generates the cluster assignments.
*
* @see #m_PlotShapes
* @see #m_PlotSizes
* @see #m_PlotInstances
*/
protected void process() {
double[] clusterAssignments;
int i;
double[] values;
int j;
int[] classAssignments;
clusterAssignments = m_Evaluation.getClusterAssignments();
classAssignments = null;
if (m_Instances.classIndex() >= 0) {
classAssignments = m_Evaluation.getClassesToClusters();
m_PlotShapes = new int[m_Instances.numInstances()];
for (i = 0; i < m_Instances.numInstances(); i++) {
m_PlotShapes[i] = Plot2D.CONST_AUTOMATIC_SHAPE;
}
}
for (i = 0; i < m_Instances.numInstances(); i++) {
values = new double[m_PlotInstances.numAttributes()];
for (j = 0; j < m_Instances.numAttributes(); j++) {
values[j] = m_Instances.instance(i).value(j);
}
if (clusterAssignments[i] < 0) {
values[j] = Utils.missingValue();
} else {
values[j] = clusterAssignments[i];
}
m_PlotInstances.add(new DenseInstance(1.0, values));
if (m_PlotShapes != null) {
if (clusterAssignments[i] >= 0) {
if ((int) m_Instances.instance(i).classValue() != classAssignments[(int) clusterAssignments[i]]) {
m_PlotShapes[i] = Plot2D.ERROR_SHAPE;
}
} else {
m_PlotShapes[i] = Plot2D.MISSING_SHAPE;
}
}
}
}
开发者ID:mydzigear，
项目名称:repo.kmeanspp.silhouette_score，
代码行数:48，
代码来源:ClustererAssignmentsPlotInstances.java
示例3: renderXYLineChart
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import weka.gui.visualize.Plot2D; //导入依赖的package包/类
/**
* Render an XY line chart
*
* @param width the width of the resulting chart in pixels
* @param height the height of the resulting chart in pixels
* @param series a list of Instances - one for each series to be plotted
* @param xAxis the name of the attribute for the x-axis (all series Instances
* are expected to have an attribute of the same type with this name)
* @param yAxis the name of the attribute for the y-axis (all series Instances
* are expected to have an attribute of the same type with this name)
* @param optionalArgs optional arguments to the renderer (may be null)
*
* @return a BufferedImage containing the chart
* @throws Exception if there is a problem rendering the chart
*/
public BufferedImage renderXYLineChart(int width, int height,
List<Instances> series, String xAxis, String yAxis,
List<String> optionalArgs) throws Exception {
BufferedImage osi = new BufferedImage(width, height,
BufferedImage.TYPE_INT_RGB);
String plotTitle = "Line chart";
String userTitle = getOption(optionalArgs, "-title");
plotTitle = (userTitle != null) ? userTitle : plotTitle;
Plot2D offScreenPlot = new Plot2D();
offScreenPlot.setSize(width, height);
// master plot
PlotData2D master = new PlotData2D(series.get(0));
master.setPlotName(plotTitle);
boolean[] connectPoints = new boolean[series.get(0).numInstances()];
for (int i = 0; i < connectPoints.length; i++) {
connectPoints[i] = true;
}
master.setConnectPoints(connectPoints);
offScreenPlot.setMasterPlot(master);
// find x and y axis
Instances masterInstances = series.get(0);
int xAx = getIndexOfAttribute(masterInstances, xAxis);
int yAx = getIndexOfAttribute(masterInstances, yAxis);
if (xAx < 0) {
xAx = 0;
}
if (yAx < 0) {
yAx = 0;
}
// plotting axes and color
offScreenPlot.setXindex(xAx);
offScreenPlot.setYindex(yAx);
offScreenPlot.setCindex(masterInstances.numAttributes() - 1);
String colorAtt = getOption(optionalArgs, "-color");
int tempC = getIndexOfAttribute(masterInstances, colorAtt);
if (tempC >= 0) {
offScreenPlot.setCindex(tempC);
}
// additional plots
if (series.size() > 1) {
for (Instances plotI : series) {
PlotData2D plotD = new PlotData2D(plotI);
connectPoints = new boolean[plotI.numInstances()];
for (int i = 0; i < connectPoints.length; i++) {
connectPoints[i] = true;
}
plotD.setConnectPoints(connectPoints);
offScreenPlot.addPlot(plotD);
}
}
// render
java.awt.Graphics g = osi.getGraphics();
offScreenPlot.paintComponent(g);
return osi;
}
开发者ID:mydzigear，
项目名称:repo.kmeanspp.silhouette_score，
代码行数:78，
代码来源:WekaOffscreenChartRenderer.java
示例4: process
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import weka.gui.visualize.Plot2D; //导入依赖的package包/类
public void process(Instances batch, double[][] predictions, Evaluation eval) {
try {
for (int j = 0; j < batch.numInstances(); j++) {
Instance toPredict = batch.instance(j);
double[] preds = predictions[j];
double pred = 0;
if (batch.classAttribute().isNominal()) {
pred = (Utils.sum(preds) == 0)
? Utils.missingValue() : Utils.maxIndex(preds);
} else {
pred = preds[0];
}
eval.evaluationForSingleInstance(preds, toPredict, true);
if (!m_SaveForVisualization) {
continue;
}
if (m_PlotInstances != null) {
double[] values = new double[m_PlotInstances.numAttributes()];
for (int i = 0; i < m_PlotInstances.numAttributes(); i++) {
if (i < toPredict.classIndex()) {
values[i] = toPredict.value(i);
}
else if (i == toPredict.classIndex()) {
values[i] = pred;
values[i+1] = toPredict.value(i);
i++;
}
else {
values[i] = toPredict.value(i-1);
}
}
m_PlotInstances.add(new DenseInstance(1.0, values));
if (toPredict.classAttribute().isNominal()) {
if (toPredict.isMissing(toPredict.classIndex()) || Utils.isMissingValue(pred)) {
m_PlotShapes.addElement(new Integer(Plot2D.MISSING_SHAPE));
}
else if (pred != toPredict.classValue()) {
// set to default error point shape
m_PlotShapes.addElement(new Integer(Plot2D.ERROR_SHAPE));
}
else {
// otherwise set to constant (automatically assigned) point shape
m_PlotShapes.addElement(new Integer(Plot2D.CONST_AUTOMATIC_SHAPE));
}
m_PlotSizes.addElement(new Integer(Plot2D.DEFAULT_SHAPE_SIZE));
}
else {
// store the error (to be converted to a point size later)
Double errd = null;
if (!toPredict.isMissing(toPredict.classIndex()) && !Utils.isMissingValue(pred)) {
errd = new Double(pred - toPredict.classValue());
m_PlotShapes.addElement(new Integer(Plot2D.CONST_AUTOMATIC_SHAPE));
}
else {
// missing shape if actual class not present or prediction is missing
m_PlotShapes.addElement(new Integer(Plot2D.MISSING_SHAPE));
}
m_PlotSizes.addElement(errd);
}
}
}
} catch (Exception ex) {
ex.printStackTrace();
}
}
开发者ID:dsibournemouth，
项目名称:autoweka，
代码行数:73，
代码来源:ClassifierErrorsPlotInstances.java
示例5: setUpVisualizableInstances
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import weka.gui.visualize.Plot2D; //导入依赖的package包/类
/**
* Sets up the structure for the visualizable instances. This dataset contains
* the original attributes plus the clusterer's cluster assignments
*
* @param testInstances the instances that the clusterer has clustered
* @param eval the evaluation to use
* @return a PlotData2D object encapsulating the visualizable instances. The
* instances contain one more attribute (predicted cluster) than the
* testInstances
*/
public static PlotData2D setUpVisualizableInstances(Instances testInstances,
ClusterEvaluation eval) throws Exception {
int numClusters = eval.getNumClusters();
double[] clusterAssignments = eval.getClusterAssignments();
FastVector hv = new FastVector();
Instances newInsts;
Attribute predictedCluster;
FastVector clustVals = new FastVector();
for (int i = 0; i < numClusters; i++) {
clustVals.addElement(Messages.getInstance().getString(
"ClustererPanel_SetUpVisualizableInstances_ClustVals_Text")
+ i);
}
predictedCluster = new Attribute(Messages.getInstance().getString(
"ClustererPanel_SetUpVisualizableInstances_PredictedCluster_Text"),
clustVals);
for (int i = 0; i < testInstances.numAttributes(); i++) {
hv.addElement(testInstances.attribute(i).copy());
}
hv.addElement(predictedCluster);
newInsts = new Instances(testInstances.relationName() + "_clustered", hv,
testInstances.numInstances());
double[] values;
int j;
int[] pointShapes = null;
int[] classAssignments = null;
if (testInstances.classIndex() >= 0) {
classAssignments = eval.getClassesToClusters();
pointShapes = new int[testInstances.numInstances()];
for (int i = 0; i < testInstances.numInstances(); i++) {
pointShapes[i] = Plot2D.CONST_AUTOMATIC_SHAPE;
}
}
for (int i = 0; i < testInstances.numInstances(); i++) {
values = new double[newInsts.numAttributes()];
for (j = 0; j < testInstances.numAttributes(); j++) {
values[j] = testInstances.instance(i).value(j);
}
if (clusterAssignments[i] < 0) {
values[j] = Instance.missingValue();
} else {
values[j] = clusterAssignments[i];
}
newInsts.add(new Instance(1.0, values));
if (pointShapes != null) {
if (clusterAssignments[i] >= 0) {
if ((int) testInstances.instance(i).classValue() != classAssignments[(int) clusterAssignments[i]]) {
pointShapes[i] = Plot2D.ERROR_SHAPE;
}
} else {
pointShapes[i] = Plot2D.MISSING_SHAPE;
}
}
}
PlotData2D plotData = new PlotData2D(newInsts);
if (pointShapes != null) {
plotData.setShapeType(pointShapes);
}
plotData.addInstanceNumberAttribute();
return plotData;
}
开发者ID:williamClanton，
项目名称:jbossBA，
代码行数:79，
代码来源:ClustererPanel.java
示例6: processClassifierPrediction
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import weka.gui.visualize.Plot2D; //导入依赖的package包/类
/**
* Process a classifier's prediction for an instance and update a set of
* plotting instances and additional plotting info. plotInfo for nominal class
* datasets holds shape types (actual data points have automatic shape type
* assignment; classifier error data points have box shape type). For numeric
* class datasets, the actual data points are stored in plotInstances and
* plotInfo stores the error (which is later converted to shape size values)
*
* @param toPredict the actual data point
* @param classifier the classifier
* @param eval the evaluation object to use for evaluating the classifier on
* the instance to predict
* @param plotInstances a set of plottable instances
* @param plotShape additional plotting information (shape)
* @param plotSize additional plotting information (size)
*/
public static void processClassifierPrediction(Instance toPredict,
Classifier classifier, Evaluation eval, Instances plotInstances,
FastVector plotShape, FastVector plotSize) {
try {
double pred = eval.evaluateModelOnceAndRecordPrediction(classifier,
toPredict);
if (plotInstances != null) {
double[] values = new double[plotInstances.numAttributes()];
for (int i = 0; i < plotInstances.numAttributes(); i++) {
if (i < toPredict.classIndex()) {
values[i] = toPredict.value(i);
} else if (i == toPredict.classIndex()) {
values[i] = pred;
values[i + 1] = toPredict.value(i);
/*
* // if the class value of the instances to predict is missing then
* // set it to the predicted value if (toPredict.isMissing(i)) {
* values[i+1] = pred; }
*/
i++;
} else {
values[i] = toPredict.value(i - 1);
}
}
plotInstances.add(new Instance(1.0, values));
if (toPredict.classAttribute().isNominal()) {
if (toPredict.isMissing(toPredict.classIndex())
|| Instance.isMissingValue(pred)) {
plotShape.addElement(new Integer(Plot2D.MISSING_SHAPE));
} else if (pred != toPredict.classValue()) {
// set to default error point shape
plotShape.addElement(new Integer(Plot2D.ERROR_SHAPE));
} else {
// otherwise set to constant (automatically assigned) point shape
plotShape.addElement(new Integer(Plot2D.CONST_AUTOMATIC_SHAPE));
}
plotSize.addElement(new Integer(Plot2D.DEFAULT_SHAPE_SIZE));
} else {
// store the error (to be converted to a point size later)
Double errd = null;
if (!toPredict.isMissing(toPredict.classIndex())
&& !Instance.isMissingValue(pred)) {
errd = new Double(pred - toPredict.classValue());
plotShape.addElement(new Integer(Plot2D.CONST_AUTOMATIC_SHAPE));
} else {
// missing shape if actual class not present or prediction is
// missing
plotShape.addElement(new Integer(Plot2D.MISSING_SHAPE));
}
plotSize.addElement(errd);
}
}
} catch (Exception ex) {
ex.printStackTrace();
}
}
开发者ID:williamClanton，
项目名称:jbossBA，
代码行数:75，
代码来源:ClassifierPanel.java
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