/*******************************************************************************
* Copyright (c) 2010 Haifeng Li
*
* 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.
*******************************************************************************/
package smile.demo.stat.distribution;
import java.awt.Color;
import java.awt.GridLayout;
import javax.swing.JFrame;
import javax.swing.JPanel;
import smile.math.Math;
import smile.plot.Histogram;
import smile.plot.PlotCanvas;
import smile.plot.QQPlot;
import smile.stat.distribution.ExponentialFamilyMixture;
import smile.stat.distribution.GaussianDistribution;
import smile.stat.distribution.GaussianMixture;
/**
*
* @author Haifeng Li
*/
@SuppressWarnings("serial")
public class GaussianMixtureDemo extends JPanel {
public GaussianMixtureDemo() {
super(new GridLayout(2, 2));
// Gaussian mixture with singular component.
double[] data = {
23.0, 23.0, 22.0, 22.0, 21.0, 24.0, 24.0, 24.0, 24.0,
24.0, 24.0, 24.0, 24.0, 22.0, 22.0, 16.0, 16.0, 16.0,
23.0, 23.0, 15.0, 21.0, 21.0, 21.0, 21.0, 24.0, 24.0,
21.0, 21.0, 24.0, 24.0, 24.0, 24.0, 1.0, 1.0, 23.0,
23.0, 22.0, 22.0, 14.0, 24.0, 24.0, 23.0, 23.0, 18.0,
18.0, 23.0, 23.0, 24.0, 24.0, 22.0, 22.0, 17.0, 17.0,
17.0, 21.0, 21.0, 15.0, 14.0
};
ExponentialFamilyMixture mixture = new GaussianMixture(data);
PlotCanvas canvas = Histogram.plot(data, 24);
canvas.setTitle("Gaussian Mixture with Singular Component");
add(canvas);
double width = (Math.max(data) - Math.min(data)) / 24;
double[][] p = new double[50][2];
for (int i = 0; i < p.length; i++) {
p[i][0] = i*0.5;
p[i][1] = mixture.p(p[i][0]) * width;
}
canvas.line(p, Color.RED);
canvas = QQPlot.plot(data, mixture);
canvas.setTitle("Q-Q Plot");
add(canvas);
// Gaussian mixture of five components.
data = new double[3000];
GaussianDistribution g1 = new GaussianDistribution(1.0, 1.0);
for (int i = 0; i < 500; i++)
data[i] = g1.rand();
GaussianDistribution g2 = new GaussianDistribution(4.0, 1.0);
for (int i = 500; i < 1000; i++)
data[i] = g2.rand();
GaussianDistribution g3 = new GaussianDistribution(8.0, 1.0);
for (int i = 1000; i < 2000; i++)
data[i] = g3.rand();
GaussianDistribution g4 = new GaussianDistribution(-3.0, 1.0);
for (int i = 2000; i < 2500; i++)
data[i] = g4.rand();
GaussianDistribution g5 = new GaussianDistribution(-6.0, 1.0);
for (int i = 2500; i < 3000; i++)
data[i] = g5.rand();
mixture = new GaussianMixture(data, 5);
canvas = Histogram.plot(data, 50);
canvas.setTitle("Gaussian Mixture of Five Components");
add(canvas);
width = (Math.max(data) - Math.min(data)) / 50;
p = new double[220][2];
for (int i = 0; i < p.length; i++) {
p[i][0] = -10 + i*0.1;
p[i][1] = mixture.p(p[i][0]) * width;
}
canvas.line(p, Color.RED);
canvas = QQPlot.plot(data, mixture);
canvas.setTitle("Q-Q Plot");
add(canvas);
}
@Override
public String toString() {
return "Gaussian Mixture";
}
public static void main(String[] args) {
JFrame frame = new JFrame("Gaussian Mixture");
frame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
frame.setLocationRelativeTo(null);
frame.getContentPane().add(new GaussianMixtureDemo());
frame.setVisible(true);
}
}