List of usage examples for org.jfree.chart ChartFrame pack
@SuppressWarnings("deprecation") public void pack()
From source file:org.jfree.chart.demo.FirstDemo.java
public static void main(String args[]) { DefaultPieDataset defaultpiedataset = new DefaultPieDataset(); defaultpiedataset.setValue("Category 1", 43.200000000000003D); defaultpiedataset.setValue("Category 2", 27.899999999999999D); defaultpiedataset.setValue("Category 3", 79.5D); org.jfree.chart.JFreeChart jfreechart = ChartFactory.createPieChart("Sample Pie Chart", defaultpiedataset, true, true, false);/*from ww w .ja va 2 s . co m*/ ChartFrame chartframe = new ChartFrame("First", jfreechart); chartframe.pack(); chartframe.setVisible(true); }
From source file:org.jfree.chart.demo.SecondDemo.java
public static void main(String args[]) { XYSeries xyseries = new XYSeries("Advisory Range"); xyseries.add(new Integer(1200), new Integer(1)); xyseries.add(new Integer(1500), new Integer(1)); XYSeries xyseries1 = new XYSeries("Normal Range"); xyseries1.add(new Integer(2000), new Integer(4)); xyseries1.add(new Integer(2300), new Integer(4)); XYSeries xyseries2 = new XYSeries("Recommended"); xyseries2.add(new Integer(2100), new Integer(2)); XYSeries xyseries3 = new XYSeries("Current"); xyseries3.add(new Integer(2400), new Integer(3)); XYSeriesCollection xyseriescollection = new XYSeriesCollection(); xyseriescollection.addSeries(xyseries); xyseriescollection.addSeries(xyseries1); xyseriescollection.addSeries(xyseries2); xyseriescollection.addSeries(xyseries3); JFreeChart jfreechart = ChartFactory.createXYLineChart("My Chart", "Calories", "Y", xyseriescollection, PlotOrientation.VERTICAL, true, true, false); StandardXYItemRenderer standardxyitemrenderer = new StandardXYItemRenderer(3, null); XYPlot xyplot = (XYPlot) jfreechart.getPlot(); xyplot.setRenderer(standardxyitemrenderer); ValueAxis valueaxis = xyplot.getRangeAxis(); valueaxis.setTickLabelsVisible(false); valueaxis.setRange(0.0D, 5D);/*w w w . j av a2 s. com*/ ChartFrame chartframe = new ChartFrame("Test", jfreechart); chartframe.pack(); chartframe.setVisible(true); }
From source file:net.sf.jdmf.algorithms.clustering.ClusteringExample.java
public static void main(String[] args) { KMeansAlgorithm algorithm = new KMeansAlgorithm(); ChartGenerator chartGenerator = new ChartGenerator(); ClusteringInputData inputData = new ExampleClusteringInputData(); inputData.setNumberOfClusters(3);/*from w ww. j av a 2s .com*/ ClusteringDataMiningModel dataMiningModel = (ClusteringDataMiningModel) algorithm.analyze(inputData); JFreeChart xyChart = chartGenerator.generateXYChart(dataMiningModel.getClusters(), 0, "first", 1, "second"); ChartFrame chartFrame = new ChartFrame("Clustering example", xyChart); chartFrame.pack(); chartFrame.setVisible(true); JFreeChart pieChart = chartGenerator.generatePieChart(dataMiningModel.getClusters()); ChartFrame anotherChartFrame = new ChartFrame("Clustering example", pieChart); anotherChartFrame.pack(); anotherChartFrame.setVisible(true); }
From source file:org.jfree.chart.demo.First.java
/** * The starting point for the demo.// w ww .ja v a 2s . c o m * * @param args ignored. */ public static void main(final String[] args) { // create a dataset... final DefaultPieDataset data = new DefaultPieDataset(); data.setValue("Category 1", 43.2); data.setValue("Category 2", 27.9); data.setValue("Category 3", 79.5); // create a chart... final JFreeChart chart = ChartFactory.createPieChart("Sample Pie Chart", data, true, // legend? true, // tooltips? false // URLs? ); // create and display a frame... final ChartFrame frame = new ChartFrame("First", chart); frame.pack(); frame.setVisible(true); }
From source file:edu.packt.neuralnet.som.Kohonen0DTest.java
public static void main(String[] args) { RandomNumberGenerator.seed = 0;/* w ww . j a v a 2 s. c om*/ int numberOfInputs = 2; int numberOfNeurons = 10; int numberOfPoints = 100; double[][] rndDataSet = RandomNumberGenerator.GenerateMatrixBetween(numberOfPoints, numberOfInputs, -10.0, 10.0); Kohonen kn0 = new Kohonen(numberOfInputs, numberOfNeurons, new UniformInitialization(-1.0, 1.0), 0); NeuralDataSet neuralDataSet = new NeuralDataSet(rndDataSet, 2); CompetitiveLearning complrn = new CompetitiveLearning(kn0, neuralDataSet, LearningAlgorithm.LearningMode.ONLINE); complrn.show2DData = true; complrn.printTraining = true; complrn.setLearningRate(0.003); complrn.setMaxEpochs(10000); complrn.setReferenceEpoch(3000); try { String[] seriesNames = { "Training Data" }; Paint[] seriesColor = { Color.WHITE }; Chart chart = new Chart("Training", rndDataSet, seriesNames, 0, seriesColor); ChartFrame frame = new ChartFrame("Training", chart.scatterPlot("X", "Y")); frame.pack(); frame.setVisible(true); //System.in.read(); complrn.setPlot2DFrame(frame); complrn.showPlot2DData(); //System.in.read(); complrn.train(); } catch (Exception ne) { } }
From source file:edu.packt.neuralnet.som.Kohonen1DTest.java
public static void main(String[] args) { RandomNumberGenerator.seed = 0;//from www .j a va 2 s. co m int numberOfInputs = 2; int numberOfNeurons = 20; int numberOfPoints = 1000; double[][] rndDataSet = RandomNumberGenerator.GenerateMatrixBetween(numberOfPoints, numberOfInputs, -100.0, 100.0); for (int i = 0; i < numberOfPoints; i++) { rndDataSet[i][0] = i; rndDataSet[i][0] += RandomNumberGenerator.GenerateNext(); rndDataSet[i][1] = Math.cos(i / 100.0) * 1000; rndDataSet[i][1] += RandomNumberGenerator.GenerateNext() * 400; } Kohonen kn1 = new Kohonen(numberOfInputs, numberOfNeurons, new UniformInitialization(0.0, 1000.0), 1); NeuralDataSet neuralDataSet = new NeuralDataSet(rndDataSet, 2); CompetitiveLearning complrn = new CompetitiveLearning(kn1, neuralDataSet, LearningAlgorithm.LearningMode.ONLINE); complrn.show2DData = true; complrn.printTraining = true; complrn.setLearningRate(0.3); complrn.setMaxEpochs(10000); complrn.setReferenceEpoch(3000); try { String[] seriesNames = { "Training Data" }; Paint[] seriesColor = { Color.WHITE }; Chart chart = new Chart("Training", rndDataSet, seriesNames, 0, seriesColor, Chart.SeriesType.DOTS); ChartFrame frame = new ChartFrame("Training", chart.scatterPlot("X", "Y")); frame.pack(); frame.setVisible(true); complrn.setPlot2DFrame(frame); complrn.showPlot2DData(); System.in.read(); complrn.train(); } catch (Exception ne) { } }
From source file:edu.packt.neuralnet.som.Kohonen2DTest.java
public static void main(String[] args) { RandomNumberGenerator.seed = System.currentTimeMillis(); int numberOfInputs = 2; int neuronsGridX = 12; int neuronsGridY = 12; int numberOfPoints = 1000; double[][] rndDataSet; rndDataSet = RandomNumberGenerator.GenerateMatrixGaussian(numberOfPoints, numberOfInputs, 100.0, 1.0); //rndDataSet = RandomNumberGenerator.GenerateMatrixBetween(numberOfPoints, numberOfInputs, 100.0, 110.0); for (int i = 0; i < numberOfPoints; i++) { rndDataSet[i][0] *= Math.sin(i); rndDataSet[i][0] += RandomNumberGenerator.GenerateNext() * 50; rndDataSet[i][1] *= Math.cos(i); rndDataSet[i][1] += RandomNumberGenerator.GenerateNext() * 50; }/*from w w w .j a va2s . com*/ // for (int i=0;i<numberOfPoints;i++){ // rndDataSet[i][0]=i; // rndDataSet[i][0]+=RandomNumberGenerator.GenerateNext(); // rndDataSet[i][1]=Math.cos(i/100.0); // rndDataSet[i][1]+=RandomNumberGenerator.GenerateNext()*5; // } Kohonen kn2 = new Kohonen(numberOfInputs, neuronsGridX, neuronsGridY, new GaussianInitialization(500.0, 20.0)); NeuralDataSet neuralDataSet = new NeuralDataSet(rndDataSet, 2); CompetitiveLearning complrn = new CompetitiveLearning(kn2, neuralDataSet, LearningAlgorithm.LearningMode.ONLINE); complrn.show2DData = true; complrn.printTraining = true; complrn.setLearningRate(0.5); complrn.setMaxEpochs(1000); complrn.setReferenceEpoch(300); complrn.sleep = -1; try { String[] seriesNames = { "Training Data" }; Paint[] seriesColor = { Color.WHITE }; Chart chart = new Chart("Training", rndDataSet, seriesNames, 0, seriesColor, Chart.SeriesType.DOTS); ChartFrame frame = new ChartFrame("Training", chart.scatterPlot("X", "Y")); frame.pack(); frame.setVisible(true); // //System.in.read(); complrn.setPlot2DFrame(frame); complrn.showPlot2DData(); //System.in.read(); complrn.train(); } catch (Exception ne) { } }
From source file:org.jfree.chart.demo.Second.java
/** * Starting point for the demo./*from w ww . j a va 2 s . c o m*/ * * @param args ignored. */ public static void main(final String[] args) { // create some data... final XYSeries series1 = new XYSeries("Advisory Range"); series1.add(new Integer(1200), new Integer(1)); series1.add(new Integer(1500), new Integer(1)); final XYSeries series2 = new XYSeries("Normal Range"); series2.add(new Integer(2000), new Integer(4)); series2.add(new Integer(2300), new Integer(4)); final XYSeries series3 = new XYSeries("Recommended"); series3.add(new Integer(2100), new Integer(2)); final XYSeries series4 = new XYSeries("Current"); series4.add(new Integer(2400), new Integer(3)); final XYSeriesCollection data = new XYSeriesCollection(); data.addSeries(series1); data.addSeries(series2); data.addSeries(series3); data.addSeries(series4); // create a chart... final JFreeChart chart = ChartFactory.createXYLineChart("My Chart", "Calories", "Y", data, PlotOrientation.VERTICAL, true, true, false); // **************************************************************************** // * JFREECHART DEVELOPER GUIDE * // * The JFreeChart Developer Guide, written by David Gilbert, is available * // * to purchase from Object Refinery Limited: * // * * // * http://www.object-refinery.com/jfreechart/guide.html * // * * // * Sales are used to provide funding for the JFreeChart project - please * // * support us so that we can continue developing free software. * // **************************************************************************** final XYItemRenderer renderer = new StandardXYItemRenderer(StandardXYItemRenderer.SHAPES_AND_LINES, null); final XYPlot plot = (XYPlot) chart.getPlot(); plot.setRenderer(renderer); final ValueAxis axis = plot.getRangeAxis(); axis.setTickLabelsVisible(false); axis.setRange(0.0, 5.0); // create and display a frame... final ChartFrame frame = new ChartFrame("Test", chart); frame.pack(); frame.setVisible(true); }
From source file:org.jfree.chart.demo.IntervalBarChartDemo1.java
/** * Starting point for the demo./* ww w. j a v a 2 s . c o m*/ * * @param args ignored. */ public static void main(final String[] args) { final IntervalBarChartDemo1 sample = new IntervalBarChartDemo1(); final JFreeChart chart = sample.getChart(); final ChartFrame frame = new ChartFrame("Interval Bar Chart Demo", chart); frame.pack(); frame.setVisible(true); }
From source file:PowerMethod.power_method.java
public static void main(String[] args) { ////////////////////////////////////////////////////// // Edit vals to contain values for matrix A // // Edit vals2 to contain values for initial vector // ////////////////////////////////////////////////////// double[][] vals = { { 3, 4 }, { 3, 1 } }; RealMatrix A = new Array2DRowRealMatrix(vals); double[][] vals2 = { { 1 }, { 1 } }; RealMatrix u = new Array2DRowRealMatrix(vals2); power_object a = power_method(A, u, .1, 7); List<RealMatrix> matrices = genMatrices(); List<trace_det> trace_dets = new ArrayList<>(); double trace; double det;// ww w.ja v a2s . c o m int iterA; int iterInverseA; for (RealMatrix r : matrices) { MatrixMethods m = new MatrixMethods(r); RealMatrix inverseR = m.inverseMatrix(); power_object largestVal = power_method(r, u, .00005, 100); power_object smallestVal = power_method(inverseR, u, .00005, 100); if (largestVal == null || smallestVal == null) { continue; } trace = m.trace(); det = m.determinant(); iterA = largestVal.getNumN(); iterInverseA = smallestVal.getNumN(); trace_det td = new trace_det(trace, det, iterA, iterInverseA); trace_dets.add(td); } JFreeChart chart = ChartFactory.createXYLineChart("Trace vs. Determinant for Power Method", "Determinant", "Trace", createDataSetA(trace_dets), PlotOrientation.VERTICAL, true, true, false); ChartPanel chartPanel = new ChartPanel(chart); chartPanel.setPreferredSize(new java.awt.Dimension(560, 367)); final XYPlot plot = chart.getXYPlot(); XYLineAndShapeRenderer renderer = new XYLineAndShapeRenderer(); renderer.setSeriesPaint(0, Color.RED); renderer.setSeriesPaint(1, Color.BLUE); renderer.setSeriesPaint(2, Color.GREEN); renderer.setSeriesPaint(3, Color.BLACK); renderer.setSeriesPaint(4, Color.YELLOW); renderer.setSeriesPaint(5, Color.PINK); renderer.setSeriesPaint(6, Color.ORANGE); renderer.setSeriesPaint(7, Color.GRAY); renderer.setSeriesPaint(8, Color.MAGENTA); renderer.setSeriesPaint(9, Color.LIGHT_GRAY); renderer.setSeriesPaint(10, Color.DARK_GRAY); //renderer.setSeriesStroke( 0 , new BasicStroke( 3.0f ) ); //renderer.setSeriesStroke( 1 , new BasicStroke( 2.0f ) ); plot.setRenderer(renderer); ChartFrame frame = new ChartFrame("Power Method", chart); frame.pack(); frame.setVisible(true); JFreeChart inverseChart = ChartFactory.createXYLineChart("Trace vs. Determinant for Inverse Power Method", "Determinant", "Trace", createDataSetAInverse(trace_dets), PlotOrientation.VERTICAL, true, true, false); ChartPanel inverseChartPanel = new ChartPanel(inverseChart); inverseChartPanel.setPreferredSize(new java.awt.Dimension(560, 367)); final XYPlot inversePlot = inverseChart.getXYPlot(); XYLineAndShapeRenderer inverseRenderer = new XYLineAndShapeRenderer(); inverseRenderer.setSeriesPaint(0, Color.RED); inverseRenderer.setSeriesPaint(1, Color.BLUE); inverseRenderer.setSeriesPaint(2, Color.GREEN); inverseRenderer.setSeriesPaint(3, Color.BLACK); inverseRenderer.setSeriesPaint(4, Color.YELLOW); inverseRenderer.setSeriesPaint(5, Color.PINK); inverseRenderer.setSeriesPaint(6, Color.ORANGE); inverseRenderer.setSeriesPaint(7, Color.GRAY); inverseRenderer.setSeriesPaint(8, Color.MAGENTA); inverseRenderer.setSeriesPaint(9, Color.LIGHT_GRAY); inverseRenderer.setSeriesPaint(10, Color.DARK_GRAY); inversePlot.setRenderer(renderer); ChartFrame inverseFrame = new ChartFrame("Power Method", inverseChart); inverseFrame.pack(); inverseFrame.setVisible(true); }