package mychartsample;
import java.util.ArrayList;
import javafx.application.Application;
import javafx.collections.FXCollections;
import javafx.collections.ObservableList;
import javafx.scene.Scene;
import javafx.scene.chart.NumberAxis;
import javafx.scene.chart.XYChart;
import javafx.scene.chart.XYChart.Series;
import javafx.stage.Stage;
import org.apache.commons.math3.stat.regression.OLSMultipleLinearRegression;
import org.apache.commons.math3.stat.regression.SimpleRegression;
/**
* MyChart1Sample - for sample of MyChart1, customized LineChart
*
* @author bitwalk
*/
public class MyChart1Sample extends Application {
@Override
public void start(Stage stage) {
stage.setTitle("MyChart Sample");
final NumberAxis xAxis = new NumberAxis();
final NumberAxis yAxis = new NumberAxis();
xAxis.setLabel("Ｘ軸ラベル（時間）");
yAxis.setLabel("Ｙ軸ラベル（数値）");
final MyChart1<Number, Number> myChart = new MyChart1<>(xAxis, yAxis);
myChart.setTitle("最小二乗法のサンプル");
myChart.setAnimated(false);
myChart.setCreateSymbols(true);
myChart.setData(getChartData());
Scene scene = new Scene(myChart, 600, 400);
scene.getStylesheets().add(getClass().getResource("MyChart1.css").toExternalForm());
stage.setScene(scene);
stage.show();
}
/**
* getChartData
*
* @return ObservableList<XYChart.Series<String, Double>>
*/
private ObservableList<XYChart.Series<Number, Number>> getChartData() {
Series<Number, Number> series1 = new Series<>();
Series<Number, Number> series2 = new Series<>();
Series<Number, Number> series3 = new Series<>();
ArrayList<PairData> dataArr = new ArrayList<>();
dataArr.add(setPair(1d, 3d));
dataArr.add(setPair(2d, 7d));
dataArr.add(setPair(3d, 14d));
dataArr.add(setPair(4d, 10d));
dataArr.add(setPair(5d, 17d));
ArrayList<Double> xRange = new ArrayList<>();
xRange.add(0.5);
xRange.add(5.5);
SimpleRegression regression = new SimpleRegression();
OLSMultipleLinearRegression mulreg = new OLSMultipleLinearRegression();
double[] y_mulreg = new double[dataArr.size()];
double[][] x_mulreg = new double[dataArr.size()][];
series1.setName("観測データ");
for (int i = 0; i < dataArr.size(); i++) {
double x = dataArr.get(i).X;
double y = dataArr.get(i).Y;
series1.getData().add(new XYChart.Data(x, y));
regression.addData(x, y);
y_mulreg[i] = y;
x_mulreg[i] = new double[]{x, x * x, x * x * x};
}
series2.setName("単回帰（直線）");
xRange.stream().forEach((xr) -> {
series2.getData().add(new XYChart.Data(xr, regression.predict(xr)));
});
series3.setName("重回帰（三次式）");
mulreg.newSampleData(y_mulreg, x_mulreg);
double[] beta = mulreg.estimateRegressionParameters();
double x0 = xRange.get(0);
while (x0 <= xRange.get(1)) {
series3.getData().add(new XYChart.Data(x0, getPolynomialValue(beta, x0)));
x0 = x0 + 0.01;
}
ObservableList<XYChart.Series<Number, Number>> seriesList = FXCollections.observableArrayList();
seriesList.addAll(series1, series2, series3);
return seriesList;
}
/**
* getPolynomialValue
*
* @param coef coefficient
* @param x x value
* @return calculated polynomial
*/
private double getPolynomialValue(double[] coef, double x) {
double y = 0d;
for (int i = 0; i < coef.length; i++) {
y = y + coef[i] * Math.pow(x, i);
}
return y;
}
/**
* setPair - set pair of data to the PairData structure
*
* @param x
* @param y
* @return PairData
*/
private PairData setPair(double x, double y) {
PairData data = new PairData();
data.X = x;
data.Y = y;
return data;
}
/**
* PairData - structure for handling (x, y) data
*/
private class PairData {
double X;
double Y;
}
/**
* @param args the command line arguments
*/
public static void main(String[] args) {
launch(args);
}
}
