Package org.apache.mahout.matrix

Examples of org.apache.mahout.matrix.DenseVector

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  // Override the paint() method
  public void paint(Graphics g) {
    Graphics2D g2 = (Graphics2D) g;
    plotSampleData(g);
    Vector v = new DenseVector(2);
    Vector dv = new DenseVector(2);
    g2.setColor(Color.RED);
    for (Vector param : sampleParams) {
      v.set(0, param.get(0));
      v.set(1, param.get(1));
      dv.set(0, param.get(2) * 3);
      dv.set(1, param.get(3) * 3);
      plotEllipse(g2, v, dv);
    }
  }
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    double sx = (double) res / ds;
    g2.setTransform(AffineTransform.getScaleInstance(sx, sx));

    // plot the axes
    g2.setColor(Color.BLACK);
    Vector dv = new DenseVector(2).assign(size / 2);
    plotRectangle(g2, new DenseVector(2).assign(2), dv);
    plotRectangle(g2, new DenseVector(2).assign(-2), dv);

    // plot the sample data
    g2.setColor(Color.DARK_GRAY);
    dv.assign(0.03);
    for (Vector v : sampleData)
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   * @param dv a Vector of rectangle sizes
   */
  void plotRectangle(Graphics2D g2, Vector v, Vector dv) {
    int h = size / 2;
    double[] flip = { 1, -1 };
    Vector v2 = v.copy().assign(new DenseVector(flip), new TimesFunction());
    v2 = v2.minus(dv.divide(2));
    double x = v2.get(0) + h;
    double y = v2.get(1) + h;
    g2.draw(new Rectangle2D.Double(x * ds, y * ds, dv.get(0) * ds, dv.get(1)
        * ds));
 
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   * @param dv a Vector of rectangle sizes
   */
  void plotEllipse(Graphics2D g2, Vector v, Vector dv) {
    int h = size / 2;
    double[] flip = { 1, -1 };
    Vector v2 = v.copy().assign(new DenseVector(flip), new TimesFunction());
    v2 = v2.minus(dv.divide(2));
    double x = v2.get(0) + h;
    double y = v2.get(1) + h;
    g2
        .draw(new Ellipse2D.Double(x * ds, y * ds, dv.get(0) * ds, dv.get(1)
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   * @param my double y-value of the sample mean
   * @param sd double standard deviation of the samples
   */
  public static void generateSamples(int num, double mx, double my, double sd) {
    double[] params = { mx, my, sd, sd };
    sampleParams.add(new DenseVector(params));
    System.out.println("Generating " + num + " samples m=[" + mx + ", " + my
        + "] sd=" + sd);
    for (int i = 0; i < num; i++)
      sampleData.add(new DenseVector(new double[] {
          UncommonDistributions.rNorm(mx, sd),
          UncommonDistributions.rNorm(my, sd) }));
  }
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   * @param sdy double y-value standard deviation of the samples
   */
  public static void generate2dSamples(int num, double mx, double my,
      double sdx, double sdy) {
    double[] params = { mx, my, sdx, sdy };
    sampleParams.add(new DenseVector(params));
    System.out.println("Generating " + num + " samples m=[" + mx + ", " + my
        + "] sd=[" + sdx + ", " + sdy + "]");
    for (int i = 0; i < num; i++)
      sampleData.add(new DenseVector(new double[] {
          UncommonDistributions.rNorm(mx, sdx),
          UncommonDistributions.rNorm(my, sdy) }));
  }
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  public void paint(Graphics g) {
    super.plotSampleData(g);
    Graphics2D g2 = (Graphics2D) g;

    Vector dv = new DenseVector(2);
    int i = result.size() - 1;
    for (Model<Vector>[] models : result) {
      g2.setStroke(new BasicStroke(i == 0 ? 3 : 1));
      g2.setColor(colors[Math.min(colors.length - 1, i--)]);
      for (Model<Vector> m : models) {
        AsymmetricSampledNormalModel mm = (AsymmetricSampledNormalModel) m;
        dv.set(0, mm.sd.get(0) * 3);
        dv.set(1, mm.sd.get(1) * 3);
        if (isSignificant(mm))
          plotEllipse(g2, mm.mean, dv);
      }
    }
  }
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  public void paint(Graphics g) {
    super.plotSampleData(g);
    Graphics2D g2 = (Graphics2D) g;

    Vector dv = new DenseVector(2);
    int i = result.size() - 1;
    for (Model<Vector>[] models : result) {
      g2.setStroke(new BasicStroke(i == 0 ? 3 : 1));
      g2.setColor(colors[Math.min(colors.length - 1, i--)]);
      for (Model<Vector> m : models) {
        AsymmetricSampledNormalModel mm = (AsymmetricSampledNormalModel) m;
        dv.assign(mm.sd.times(3));
        if (isSignificant(mm))
          plotEllipse(g2, mm.mean, dv);
      }
    }
  }
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  public void paint(Graphics g) {
    super.plotSampleData(g);
    Graphics2D g2 = (Graphics2D) g;

    Vector dv = new DenseVector(2);
    int i = result.size() - 1;
    for (Model<Vector>[] models : result) {
      g2.setStroke(new BasicStroke(i == 0 ? 3 : 1));
      g2.setColor(colors[Math.min(colors.length - 1, i--)]);
      for (Model<Vector> m : models) {
        NormalModel mm = (NormalModel) m;
        dv.assign(mm.sd * 3);
        if (isSignificant(mm))
          plotEllipse(g2, mm.mean, dv);
      }
    }
  }
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  public void paint(Graphics g) {
    super.plotSampleData(g);
    Graphics2D g2 = (Graphics2D) g;

    Vector dv = new DenseVector(2);
    int i = result.size() - 1;
    for (Model<Vector>[] models : result) {
      g2.setStroke(new BasicStroke(i == 0 ? 3 : 1));
      g2.setColor(colors[Math.min(colors.length - 1, i--)]);
      for (Model<Vector> m : models) {
        AsymmetricSampledNormalModel mm = (AsymmetricSampledNormalModel) m;
        dv.assign(mm.sd.times(3));
        if (isSignificant(mm))
          plotEllipse(g2, mm.mean, dv);
      }
    }
  }
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Related Classes of org.apache.mahout.matrix.DenseVector

  • org.apache.hadoop.io.Text
  • org.apache.mahout.clustering.canopy.DisplayCanopy
  • org.apache.mahout.clustering.dirichlet.DirichletClusterer
  • org.apache.mahout.clustering.dirichlet.DirichletMapper
  • org.apache.mahout.clustering.dirichlet.DirichletState
  • org.apache.mahout.clustering.dirichlet.Display2dASNDirichlet
  • org.apache.mahout.clustering.dirichlet.DisplayASNDirichlet
  • org.apache.mahout.clustering.dirichlet.DisplayASNOutputState
  • org.apache.mahout.clustering.dirichlet.DisplayDirichlet
  • org.apache.mahout.clustering.dirichlet.DisplayNDirichlet
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