Examples with PlotCanvas smile.plot.PlotCanvas used on opensource projects

Example 11 with PlotCanvas

use of smile.plot.PlotCanvas in project smile by haifengl.

the class SammonMappingDemo method learn.

/**
     * Execute the MDS algorithm and return a swing JComponent representing
     * the clusters.
     */
public JComponent learn() {
    JPanel pane = new JPanel(new GridLayout(1, 2));
    double[][] data = dataset[datasetIndex].toArray(new double[dataset[datasetIndex].size()][]);
    String[] labels = dataset[datasetIndex].toArray(new String[dataset[datasetIndex].size()]);
    if (labels[0] == null) {
        Attribute[] attr = dataset[datasetIndex].attributes();
        labels = new String[attr.length];
        for (int i = 0; i < labels.length; i++) {
            labels[i] = attr[i].getName();
        }
    }
    long clock = System.currentTimeMillis();
    SammonMapping sammon = new SammonMapping(data, 2);
    System.out.format("Learn Sammon's Mapping (k=2) from %d samples in %dms\n", data.length, System.currentTimeMillis() - clock);
    PlotCanvas plot = ScatterPlot.plot(sammon.getCoordinates(), labels);
    plot.setTitle("Sammon's Mapping (k = 2)");
    pane.add(plot);
    clock = System.currentTimeMillis();
    sammon = new SammonMapping(data, 3);
    System.out.format("Learn Sammon's Mapping (k=3) from %d samples in %dms\n", data.length, System.currentTimeMillis() - clock);
    plot = ScatterPlot.plot(sammon.getCoordinates(), labels);
    plot.setTitle("Sammon's Mapping (k = 3)");
    pane.add(plot);
    return pane;
}

Example 12 with PlotCanvas

use of smile.plot.PlotCanvas in project smile by haifengl.

the class IsoMapDemo method learn.

@Override
public JComponent learn() {
    JPanel pane = new JPanel(new GridLayout(1, 2));
    double[][] data = dataset[datasetIndex].toArray(new double[dataset[datasetIndex].size()][]);
    if (data.length > 1000) {
        double[][] x = new double[1000][];
        for (int i = 0; i < 1000; i++) x[i] = data[i];
        data = x;
    }
    long clock = System.currentTimeMillis();
    IsoMap isomap = new IsoMap(data, 2, k);
    System.out.format("Learn IsoMap from %d samples in %dms\n", data.length, System.currentTimeMillis() - clock);
    double[][] y = isomap.getCoordinates();
    PlotCanvas plot = new PlotCanvas(Math.colMin(y), Math.colMax(y));
    plot.points(y, 'o', Color.RED);
    int n = y.length;
    Graph graph = isomap.getNearestNeighborGraph();
    for (int i = 0; i < n; i++) {
        for (int j = 0; j < i; j++) {
            if (graph.hasEdge(i, j)) {
                plot.line(y[i], y[j]);
            }
        }
    }
    plot.setTitle("IsoMap");
    pane.add(plot);
    return pane;
}

Example 13 with PlotCanvas

use of smile.plot.PlotCanvas in project smile by haifengl.

the class LLEDemo method learn.

@Override
public JComponent learn() {
    JPanel pane = new JPanel(new GridLayout(1, 2));
    double[][] data = dataset[datasetIndex].toArray(new double[dataset[datasetIndex].size()][]);
    if (data.length > 1000) {
        double[][] x = new double[1000][];
        for (int i = 0; i < 1000; i++) x[i] = data[i];
        data = x;
    }
    long clock = System.currentTimeMillis();
    LLE lle = new LLE(data, 2, k);
    System.out.format("Learn LLE from %d samples in %dms\n", data.length, System.currentTimeMillis() - clock);
    double[][] y = lle.getCoordinates();
    PlotCanvas plot = new PlotCanvas(Math.colMin(y), Math.colMax(y));
    plot.points(y, 'o', Color.RED);
    int n = y.length;
    Graph graph = lle.getNearestNeighborGraph();
    for (int i = 0; i < n; i++) {
        for (int j = 0; j < i; j++) {
            if (graph.hasEdge(i, j)) {
                plot.line(y[i], y[j]);
            }
        }
    }
    plot.setTitle("LLE");
    pane.add(plot);
    return pane;
}

Example 14 with PlotCanvas

use of smile.plot.PlotCanvas in project smile by haifengl.

the class GHADemo method learn.

@Override
public JComponent learn() {
    JPanel pane = new JPanel(new GridLayout(2, 2));
    double[][] data = Math.clone(dataset[datasetIndex].toArray(new double[dataset[datasetIndex].size()][]));
    String[] names = dataset[datasetIndex].toArray(new String[dataset[datasetIndex].size()]);
    if (names[0] == null) {
        names = null;
    }
    long clock = System.currentTimeMillis();
    PCA pca = new PCA(data, true);
    System.out.format("Learn PCA from %d samples in %dms\n", data.length, System.currentTimeMillis() - clock);
    pca.setProjection(2);
    double[][] y = pca.project(data);
    PlotCanvas plot = new PlotCanvas(Math.colMin(y), Math.colMax(y));
    if (names != null) {
        plot.points(y, names);
    } else if (dataset[datasetIndex].response() != null) {
        int[] labels = dataset[datasetIndex].toArray(new int[dataset[datasetIndex].size()]);
        for (int i = 0; i < y.length; i++) {
            plot.point(pointLegend, Palette.COLORS[labels[i]], y[i]);
        }
    } else {
        plot.points(y, pointLegend);
    }
    plot.setTitle("PCA");
    pane.add(plot);
    pca.setProjection(3);
    y = pca.project(data);
    plot = new PlotCanvas(Math.colMin(y), Math.colMax(y));
    if (names != null) {
        plot.points(y, names);
    } else if (dataset[datasetIndex].response() != null) {
        int[] labels = dataset[datasetIndex].toArray(new int[dataset[datasetIndex].size()]);
        for (int i = 0; i < y.length; i++) {
            plot.point(pointLegend, Palette.COLORS[labels[i]], y[i]);
        }
    } else {
        plot.points(y, pointLegend);
    }
    plot.setTitle("PCA");
    pane.add(plot);
    clock = System.currentTimeMillis();
    GHA gha = new GHA(data[0].length, 2, 0.00001);
    for (int iter = 1; iter <= 500; iter++) {
        double error = 0.0;
        for (int i = 0; i < data.length; i++) {
            error += gha.learn(data[i]);
        }
        error /= data.length;
        if (iter % 100 == 0) {
            System.out.format("Iter %3d, Error = %.5g\n", iter, error);
        }
    }
    System.out.format("Learn GHA from %d samples in %dms\n", data.length, System.currentTimeMillis() - clock);
    y = gha.project(data);
    plot = new PlotCanvas(Math.colMin(y), Math.colMax(y));
    if (names != null) {
        plot.points(y, names);
    } else if (dataset[datasetIndex].response() != null) {
        int[] labels = dataset[datasetIndex].toArray(new int[dataset[datasetIndex].size()]);
        for (int i = 0; i < y.length; i++) {
            plot.point(pointLegend, Palette.COLORS[labels[i]], y[i]);
        }
    } else {
        plot.points(y, pointLegend);
    }
    plot.setTitle("GHA");
    pane.add(plot);
    clock = System.currentTimeMillis();
    gha = new GHA(data[0].length, 3, 0.00001);
    for (int iter = 1; iter <= 500; iter++) {
        double error = 0.0;
        for (int i = 0; i < data.length; i++) {
            error += gha.learn(data[i]);
        }
        error /= data.length;
        if (iter % 100 == 0) {
            System.out.format("Iter %3d, Error = %.5g\n", iter, error);
        }
    }
    System.out.format("Learn GHA from %d samples in %dms\n", data.length, System.currentTimeMillis() - clock);
    y = gha.project(data);
    plot = new PlotCanvas(Math.colMin(y), Math.colMax(y));
    if (names != null) {
        plot.points(y, names);
    } else if (dataset[datasetIndex].response() != null) {
        int[] labels = dataset[datasetIndex].toArray(new int[dataset[datasetIndex].size()]);
        for (int i = 0; i < y.length; i++) {
            plot.point(pointLegend, Palette.COLORS[labels[i]], y[i]);
        }
    } else {
        plot.points(y, pointLegend);
    }
    plot.setTitle("GHA");
    pane.add(plot);
    return pane;
}

Example 15 with PlotCanvas

use of smile.plot.PlotCanvas in project smile by haifengl.

the class BIRCHDemo method learn.

@Override
public JComponent learn() {
    try {
        B = Integer.parseInt(BNumberField.getText().trim());
        if (B < 2) {
            JOptionPane.showMessageDialog(this, "Invalid B: " + B, ERROR, JOptionPane.ERROR_MESSAGE);
            return null;
        }
    } catch (Exception e) {
        JOptionPane.showMessageDialog(null, "Invalid B: " + BNumberField.getText(), ERROR, JOptionPane.ERROR_MESSAGE);
        return null;
    }
    try {
        T = Double.parseDouble(TNumberField.getText().trim());
        if (T <= 0) {
            JOptionPane.showMessageDialog(this, "Invalid T: " + T, ERROR, JOptionPane.ERROR_MESSAGE);
            return null;
        }
    } catch (Exception e) {
        JOptionPane.showMessageDialog(this, "Invalid T: " + TNumberField.getText(), ERROR, JOptionPane.ERROR_MESSAGE);
        return null;
    }
    try {
        minPts = Integer.parseInt(minPtsNumberField.getText().trim());
        if (minPts < 0) {
            JOptionPane.showMessageDialog(this, "Invalid minPts: " + minPts, ERROR, JOptionPane.ERROR_MESSAGE);
            return null;
        }
    } catch (Exception e) {
        JOptionPane.showMessageDialog(this, "Invalid minPts: " + minPtsNumberField.getText(), ERROR, JOptionPane.ERROR_MESSAGE);
        return null;
    }
    long clock = System.currentTimeMillis();
    BIRCH birch = new BIRCH(2, B, T);
    for (int i = 0; i < dataset[datasetIndex].length; i++) birch.add(dataset[datasetIndex][i]);
    if (birch.partition(clusterNumber, minPts) < clusterNumber) {
        JOptionPane.showMessageDialog(this, "The number of non-outlier leaves is less than " + clusterNumber + ". Try larger T.", "ERROR", JOptionPane.ERROR_MESSAGE);
        return null;
    }
    int[] membership = new int[dataset[datasetIndex].length];
    int[] clusterSize = new int[clusterNumber];
    for (int i = 0; i < dataset[datasetIndex].length; i++) {
        membership[i] = birch.predict(dataset[datasetIndex][i]);
        if (membership[i] != Clustering.OUTLIER) {
            clusterSize[membership[i]]++;
        }
    }
    System.out.format("BIRCH clusterings %d samples in %dms\n", dataset[datasetIndex].length, System.currentTimeMillis() - clock);
    PlotCanvas plot = ScatterPlot.plot(birch.centroids(), '@');
    for (int k = 0; k < clusterNumber; k++) {
        if (clusterSize[k] > 0) {
            double[][] cluster = new double[clusterSize[k]][];
            for (int i = 0, j = 0; i < dataset[datasetIndex].length; i++) {
                if (membership[i] == k) {
                    cluster[j++] = dataset[datasetIndex][i];
                }
            }
            plot.points(cluster, pointLegend, Palette.COLORS[k % Palette.COLORS.length]);
        }
    }
    plot.points(birch.centroids(), '@');
    return plot;
}