Java tutorial
/* * Encog(tm) Workbench v3.0 * http://www.heatonresearch.com/encog/ * http://code.google.com/p/encog-java/ * Copyright 2008-2011 Heaton Research, Inc. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. * * For more information on Heaton Research copyrights, licenses * and trademarks visit: * http://www.heatonresearch.com/copyright */ package org.encog.workbench.dialogs.validate; import java.awt.BorderLayout; import java.awt.Color; import java.util.ArrayList; import java.util.Vector; import javax.swing.JScrollPane; import javax.swing.JTabbedPane; import javax.swing.JTable; import org.encog.ml.MLClassification; import org.encog.ml.MLMethod; import org.encog.ml.MLRegression; import org.encog.ml.data.MLData; import org.encog.ml.data.MLDataPair; import org.encog.ml.data.MLDataSet; import org.encog.ml.data.basic.BasicMLData; import org.encog.workbench.WorkBenchError; import org.encog.workbench.tabs.EncogCommonTab; import org.jfree.chart.ChartFactory; import org.jfree.chart.ChartPanel; import org.jfree.chart.ChartUtilities; import org.jfree.chart.JFreeChart; import org.jfree.chart.plot.PlotOrientation; import org.jfree.chart.plot.XYPlot; import org.jfree.chart.renderer.xy.StandardXYItemRenderer; import org.jfree.chart.renderer.xy.XYItemRenderer; import org.jfree.data.xy.XYSeries; import org.jfree.data.xy.XYSeriesCollection; public class ResultValidationChart extends EncogCommonTab { private static final long serialVersionUID = -2859655432840760344L; private JTabbedPane tabs = new JTabbedPane(); private ArrayList<JFreeChart> charts = new ArrayList<JFreeChart>(); private ArrayList<ChartPanel> chartPanels = new ArrayList<ChartPanel>(); public ResultValidationChart() { super(null); setLayout(new BorderLayout()); this.add(tabs, BorderLayout.CENTER); } public void setData(MLDataSet validationData, MLMethod method) { ArrayList<XYSeries> validation = new ArrayList<XYSeries>(); ArrayList<XYSeries> computation = new ArrayList<XYSeries>(); Vector<Vector<String>> tableData = new Vector<Vector<String>>(); Vector<String> tableHeaders = null; int key = 0; Vector<String> tableDataRow; for (MLDataPair dataRow : validationData) { MLData input = dataRow.getInput(); MLData validIdeal = dataRow.getIdeal(); MLData computatedIdeal = getCalculatedResult(dataRow, method); int inputCount = input.size(); int idealCount = validIdeal == null ? 0 : validIdeal.size(); tableDataRow = new Vector<String>(); if (tableHeaders == null) { tableHeaders = new Vector<String>(); for (int i = 0; i < inputCount; i++) { tableHeaders.add("Input " + i); } for (int i = 0; i < computatedIdeal.size(); i++) { tableHeaders.add("Ideal " + i); tableHeaders.add("Result " + i); } } for (int i = 0; i < inputCount; i++) { tableDataRow.add(new Double(input.getData(i)).toString()); } for (int i = validation.size(); i < idealCount; i++) { validation.add(new XYSeries("Validation")); computation.add(new XYSeries("Computation")); createChart(); } for (int i = 0; i < computatedIdeal.size(); i++) { double c = computatedIdeal.getData(i); if (idealCount > 0) { double v = validIdeal.getData(i); validation.get(i).add(key, v); tableDataRow.add(new Double(v).toString()); computation.get(i).add(key, c); } else { tableDataRow.add("N/A"); } tableDataRow.add(new Double(c).toString()); } tableData.add(tableDataRow); key++; } drawGraphs(validation, computation); drawTable(tableData, tableHeaders); } private void drawGraphs(ArrayList<XYSeries> validation, ArrayList<XYSeries> computation) { // Add charts int size = validation.size(); for (int i = 0; i < size; i++) { XYSeries vSeries = validation.get(i); XYSeries cSeries = computation.get(i); JFreeChart chart = charts.get(i); ChartPanel chartPanel = chartPanels.get(i); XYPlot plot = chart.getXYPlot(); plot.setDataset(0, new XYSeriesCollection(vSeries)); final XYItemRenderer renderer1 = new StandardXYItemRenderer(); renderer1.setSeriesPaint(0, Color.blue); plot.setRenderer(0, renderer1); plot.setDataset(1, new XYSeriesCollection(cSeries)); final XYItemRenderer renderer2 = new StandardXYItemRenderer(); renderer2.setSeriesPaint(0, Color.red); plot.setRenderer(1, renderer2); ChartUtilities.applyCurrentTheme(chart); tabs.addTab("Ideal" + (i + 1), chartPanel); } } private void drawTable(Vector<Vector<String>> tableData, Vector<String> tableHeaders) { JTable table = new JTable(tableData, tableHeaders) { private static final long serialVersionUID = 8364655578079933961L; public boolean isCellEditable(int rowIndex, int vColIndex) { return false; } }; table.setAutoResizeMode(JTable.AUTO_RESIZE_OFF); tabs.addTab("Data", new JScrollPane(table)); } private MLData getCalculatedResult(MLDataPair data, MLMethod method) { MLData out; if (method instanceof MLRegression) { out = ((MLRegression) method).compute(data.getInput()); } else if (method instanceof MLClassification) { out = new BasicMLData(1); out.setData(0, ((MLClassification) method).classify(data.getInput())); } else { throw new WorkBenchError("Unsupported Machine Learning Method:" + method.getClass().getSimpleName()); } return out; } /** * Create the initial chart. * * @return The chart. */ private void createChart() { JFreeChart chart = ChartFactory.createXYLineChart(null, "Result", "Increment", null, PlotOrientation.VERTICAL, true, true, false); ChartPanel chartPanel = new ChartPanel(chart); chartPanel.setPreferredSize(new java.awt.Dimension(600, 360)); chartPanel.setDomainZoomable(true); chartPanel.setRangeZoomable(true); charts.add(chart); chartPanels.add(chartPanel); } @Override public String getName() { return "Validation"; } }