Example usage for org.apache.commons.math3.linear RealMatrix getRowDimension

Introduction

In this page you can find the example usage for org.apache.commons.math3.linear RealMatrix getRowDimension.

Prototype

int getRowDimension();

Source Link

Document

Returns the number of rows in the matrix.

Usage

From source file:org.pmad.gmm.HessenbergTransformer.java

/**
 * Build the transformation to Hessenberg form of a general matrix.
 *
 * @param matrix matrix to transform//  w  w  w .  j  a v a  2 s  .  co  m
 * @throws NonSquareMatrixException if the matrix is not square
 */
public HessenbergTransformer(final RealMatrix matrix) {
    if (!matrix.isSquare()) {
        throw new NonSquareMatrixException(matrix.getRowDimension(), matrix.getColumnDimension());
    }

    final int m = matrix.getRowDimension();
    householderVectors = matrix.getData();
    ort = new double[m];
    cachedP = null;
    cachedPt = null;
    cachedH = null;

    // transform matrix
    transform();
}

From source file:org.pmad.gmm.MyEDC.java

/**
 * Calculates the eigen decomposition of the given real matrix.
 * <p>//ww  w.  j  av  a  2  s  .c  o m
 * Supports decomposition of a general matrix since 3.1.
 *
 * @param matrix Matrix to decompose.
 * @throws MaxCountExceededException if the algorithm fails to converge.
 * @throws MathArithmeticException if the decomposition of a general matrix
 * results in a matrix with zero norm
 * @since 3.1
 */
public MyEDC(final RealMatrix matrix) throws MathArithmeticException {
    final double symTol = 10 * matrix.getRowDimension() * matrix.getColumnDimension() * Precision.EPSILON;
    isSymmetric = MatrixUtils.isSymmetric(matrix, symTol);
    if (isSymmetric) {
        transformToTridiagonal(matrix);
        findEigenVectors(transformer.getQ().getData());
    } else {
        final SchurTransformer t = transformToSchur(matrix);
        findEigenVectorsFromSchur(t);
    }
}

From source file:org.pmad.gmm.SchurTransformer.java

/**
 * Build the transformation to Schur form of a general real matrix.
 *
 * @param matrix matrix to transform/* ww  w.  j a  va 2s  .com*/
 * @throws NonSquareMatrixException if the matrix is not square
 */
public SchurTransformer(final RealMatrix matrix) {
    if (!matrix.isSquare()) {
        throw new NonSquareMatrixException(matrix.getRowDimension(), matrix.getColumnDimension());
    }

    HessenbergTransformer transformer = new HessenbergTransformer(matrix);
    matrixT = transformer.getH().getData();
    matrixP = transformer.getP().getData();
    cachedT = null;
    cachedP = null;
    cachedPt = null;

    // transform matrix
    transform();
}

From source file:org.pmad.gmm.TriDiagonalTransformer.java

/**
 * Build the transformation to tridiagonal shape of a symmetrical matrix.
 * <p>The specified matrix is assumed to be symmetrical without any check.
 * Only the upper triangular part of the matrix is used.</p>
 *
 * @param matrix Symmetrical matrix to transform.
 * @throws NonSquareMatrixException if the matrix is not square.
 *//*from  w  ww.  j  a  va 2  s  .  c  o m*/
public TriDiagonalTransformer(RealMatrix matrix) {
    if (!matrix.isSquare()) {
        throw new NonSquareMatrixException(matrix.getRowDimension(), matrix.getColumnDimension());
    }

    final int m = matrix.getRowDimension();
    householderVectors = matrix.getData();
    main = new double[m];
    secondary = new double[m - 1];
    cachedQ = null;
    cachedQt = null;
    cachedT = null;

    // transform matrix
    transform();
}

From source file:org.rhwlab.BHC.NodeBase.java

public Element formElementXML() {
    List<MicroCluster> micros = new ArrayList<>();
    this.getDataAsMicroCluster(micros);
    int voxels = 0;
    long intensity = 0;

    for (MicroCluster micro : micros) {
        voxels = voxels + micro.getPointCount();
        intensity = intensity + micro.getTotalIntensity();
    }/*from   www.  j a  va  2s . co m*/
    RealVector mu = MicroCluster.mean(micros);
    RealMatrix W = MicroCluster.precision(micros, mu);
    if (W != null) {
        Element clusterEle = new Element("GaussianMixtureModel");
        //clusterEle.setAttribute("id", String.format("%d", id));
        //           clusterEle.setAttribute("parent", "-1");
        clusterEle.setAttribute("count", String.format("%d", micros.size()));
        clusterEle.setAttribute("voxels", String.format("%d", voxels));
        clusterEle.setAttribute("intensity", String.format("%d", intensity));

        clusterEle.setAttribute("intensityRSD", Double.toString(getIntensityRSD()));
        clusterEle.setAttribute("sourceNode", String.format("%d", label));

        clusterEle.setAttribute("posterior", Double.toString(lnR));

        clusterEle.setAttribute("x", Double.toString(mu.getEntry(0)));
        clusterEle.setAttribute("y", Double.toString(mu.getEntry(1)));
        clusterEle.setAttribute("z", Double.toString(mu.getEntry(2)));

        StringBuilder builder = new StringBuilder();
        for (int row = 0; row < W.getRowDimension(); ++row) {
            for (int col = 0; col < W.getColumnDimension(); ++col) {
                if (row > 0 || col > 0) {
                    builder.append(" ");
                }
                builder.append(W.getEntry(row, col));
            }
        }
        clusterEle.setAttribute("precision", builder.toString());
        return clusterEle;
    } else {
        return null;
    }
}

From source file:org.rhwlab.BHCnotused.Cluster.java

public void saveAsXML(Element root, int id) throws Exception {
    Element clusterEle = new Element("GaussianMixtureModel");
    clusterEle.setAttribute("id", String.format("%d", id));
    clusterEle.setAttribute("parent", "-1");

    StringBuilder builder = new StringBuilder();
    for (int j = 0; j < data.getMean().getDimension(); ++j) {
        if (j > 0) {
            builder.append(" ");
        }//ww w.  ja  v  a 2 s  . co  m
        builder.append(data.getMean().getEntry(j));

    }
    clusterEle.setAttribute("m", builder.toString());

    RealMatrix W = data.getPrecision();
    builder = new StringBuilder();
    for (int row = 0; row < W.getRowDimension(); ++row) {
        for (int col = 0; col < W.getColumnDimension(); ++col) {
            if (row > 0 || col > 0) {
                builder.append(" ");
            }
            builder.append(W.getEntry(row, col));
        }
    }
    clusterEle.setAttribute("W", builder.toString());

    clusterEle.setAttribute("pi", pi.toString());
    clusterEle.setAttribute("likelihood", data.likelihood().toString());
    clusterEle.setAttribute("DPM", dpm.toString());
    clusterEle.setAttribute("posterior", r.toString());

    clusterEle.setAttribute("d", d.toString());

    clusterEle.addContent(data.asString());

    root.addContent(clusterEle);
}

From source file:org.rhwlab.dispim.nucleus.BHCNucleusData.java

public void printMat(String label, RealMatrix m) {
    System.out.println(label);/* ww  w  .j a v a 2s.c  om*/
    for (int r = 0; r < m.getRowDimension(); ++r) {
        for (int c = 0; c < m.getColumnDimension(); ++c) {
            System.out.printf("%f\t", m.getEntry(r, c));
        }
        System.out.println();
    }
}

From source file:org.rhwlab.dispim.nucleus.Nucleus.java

private void reportMatrix(PrintStream stream, String label, RealMatrix m) {
    stream.printf("%s: ", label);
    for (int r = 0; r < m.getRowDimension(); ++r) {
        for (int c = 0; c < m.getColumnDimension(); ++c) {
            stream.printf("%f ", m.getEntry(r, c));
        }// w w w .  j a v a 2 s.  co m
        stream.print(" : ");
    }
    stream.println();
}

From source file:org.rhwlab.dispim.nucleus.NucleusData.java

static public String precisionAsString(RealMatrix m) {
    StringBuffer buf = new StringBuffer();
    for (int r = 0; r < m.getRowDimension(); ++r) {
        for (int c = 0; c < m.getColumnDimension(); ++c) {
            if (r != 0 || c != 0) {
                buf.append(" ");
            }//from ww  w . ja va2  s .  co m
            buf.append(Double.toString(m.getEntry(r, c)));
        }
    }
    return buf.toString();
}

From source file:org.rhwlab.variationalbayesian.GaussianMixture.java

public void reportMatrix(PrintStream str, String name, RealMatrix mat) {
    str.printf("%s\n", name);
    for (int r = 0; r < mat.getRowDimension(); ++r) {
        for (int c = 0; c < mat.getColumnDimension(); ++c) {
            str.printf(" %e", mat.getEntry(r, c));
        }/*from ww  w  .  j ava2  s. co m*/
        str.println();
    }
}