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:lsafunctions.LSA.java

private static RealMatrix normalizeMatrix(RealMatrix M) {
    double sumColumn = 0;
    //        Matrix row = new Matrix(1, M.getColumnDimension());
    RealMatrix row = MatrixUtils.createRealMatrix(1, M.getColumnDimension());
    for (int j = 0; j < M.getColumnDimension(); j++) {
        sumColumn = 0;//from  w  w  w  . j  a v  a2 s . co m
        for (int k = 0; k < M.getRowDimension(); k++) {
            sumColumn += Math.pow(M.getEntry(k, j), 2);
        }
        sumColumn = Math.sqrt(sumColumn);
        row.setEntry(0, j, sumColumn);
    }
    for (int j = 0; j < M.getColumnDimension(); j++) {
        for (int k = 0; k < M.getRowDimension(); k++) {
            M.setEntry(k, j, M.getEntry(k, j) / row.getEntry(0, j));
        }
    }
    return M;
}

From source file:cooccurrence.Omer_Levy.java

/**
 * Method that will extract top D singular values from CoVariance Matrix 
 * It will then identify the corresponding columns from U and V and add it to new matrices 
 * @param U//from  w ww. j av  a2  s .c om
 * @param V
 * @param coVariance
 * @param matrixUd
 * @param matrixVd
 * @param coVarD
 * @param indicesD 
 */
private static void getTopD(RealMatrix U, RealMatrix V, RealMatrix coVariance, RealMatrix matrixUd,
        RealMatrix matrixVd, RealMatrix coVarD, ArrayList<Integer> indicesD) {
    TreeMap<Double, Set<Integer>> tmap = new TreeMap<>();
    for (int i = 0; i < coVariance.getRowDimension(); i++) {
        double val = coVariance.getEntry(i, i);
        if (tmap.containsKey(val)) {
            Set<Integer> temp = tmap.get(val);
            temp.add(i);
        } else {
            Set<Integer> temp = new HashSet<>();
            temp.add(i);
            tmap.put(val, temp);
        }
    }
    Iterator iter = tmap.keySet().iterator();
    while (iter.hasNext()) {
        Double val = (Double) iter.next();
        Set<Integer> indices = tmap.get(val);
        for (int i = 0; i < indices.size(); i++) {
            Iterator iterIndices = indices.iterator();
            while (iterIndices.hasNext()) {
                int index = (Integer) iterIndices.next();
                indicesD.add(index);
                coVarD.addToEntry(index, index, val);
                matrixUd.setColumnVector(index, U.getColumnVector(index));
                matrixVd.setColumnVector(index, V.getColumnVector(index));
            }
        }
    }

}

From source file:edu.byu.nlp.stats.DirichletDistribution.java

public static double[][] sample(RealMatrix alphas, RandomGenerator rnd) {
    double[][] theta = GammaDistribution.sample(alphas, rnd);
    for (int i = 0; i < alphas.getRowDimension(); i++) {
        DoubleArrays.normalizeToSelf(theta[i]);
    }//from  w ww .  java  2s .  co m
    return theta;
}

From source file:edu.oregonstate.eecs.mcplan.ml.WekaGlue.java

public static SequentialProjectionHashLearner createSequentialProjectionHashLearner(final RandomGenerator rng,
        final Instances labeled, final Instances unlabeled, final int K, final double eta, final double alpha) {
    assert (labeled.classIndex() >= 0);
    final int Nfeatures = labeled.numAttributes() - 1;

    final RealMatrix X = new Array2DRowRealMatrix(Nfeatures, labeled.size() + unlabeled.size());
    final RealMatrix XL = new Array2DRowRealMatrix(Nfeatures, labeled.size() * 2);
    final RealMatrix S = new Array2DRowRealMatrix(XL.getColumnDimension(), XL.getColumnDimension());

    for (int j = 0; j < labeled.size(); ++j) {
        final Instance inst = labeled.get(j);
        for (int i = 0; i < XL.getRowDimension(); ++i) {
            X.setEntry(i, j, inst.value(i));
            XL.setEntry(i, j, inst.value(i));
        }/*from  w ww .  j  av  a2s  .  c  o m*/

        int sj = -1;
        Instance s = null;
        do {
            sj = rng.nextInt(labeled.size());
            s = labeled.get(sj);
        } while (s == inst || s.classValue() != inst.classValue());
        S.setEntry(j, sj, 1);

        int dj = -1;
        Instance d = null;
        do {
            dj = rng.nextInt(labeled.size());
            d = labeled.get(dj);
        } while (d == inst || d.classValue() == inst.classValue());
        S.setEntry(j, dj, -1);
    }

    for (int j = 0; j < unlabeled.size(); ++j) {
        final Instance inst = unlabeled.get(j);
        for (int i = 0; i < X.getRowDimension(); ++i) {
            X.setEntry(i, labeled.size() + j, inst.value(i));
        }
    }

    return new SequentialProjectionHashLearner(X, XL, S, K, eta, alpha);
}

From source file:edu.cudenver.bios.matrix.MatrixUtilities.java

/**
 * Create a string representing the content of a RealMatrix,
 * suitable for logging.// www  . ja  v a 2s .  c o m
 *
 * @param label An optional label.
 * @param rm    The RealMatrix.
 *
 * @return The string.
 */
public static String logMessage(String label, RealMatrix rm) {
    StringBuilder sb = new StringBuilder();

    sb.append(EOL);

    if (label != null) {
        sb.append("  ").append(label).append(EOL);
    }

    if (rm == null) {
        sb.append("   (null)");
        sb.append(EOL);
    } else {
        int m = rm.getRowDimension();
        int n = rm.getColumnDimension();

        sb.append("   (").append(m).append(" x ").append(n).append(")").append(EOL);

        for (int i = 0; i < m; ++i) {
            sb.append("    ");

            for (int j = 0; j < n; ++j) {
                sb.append(rm.getEntry(i, j)).append(' ');
            }

            sb.append(EOL);
        }
    }

    return sb.toString();
}

From source file:com.vsthost.rnd.commons.math.ext.linear.EMatrixUtils.java

/**
 * Returns a new matrix by subtracting elements column by column.
 *
 * @param matrix The input matrix/*from  ww  w.j  a v  a 2  s .c o m*/
 * @param vector The vector to be subtracted from columns
 * @return A new matrix of which the vector is subtracted column by column
 */
public static RealMatrix colSubtract(RealMatrix matrix, double[] vector) {
    // Declare and initialize the new matrix:
    double[][] retval = new double[matrix.getRowDimension()][matrix.getColumnDimension()];

    // Iterate over rows:
    for (int col = 0; col < retval.length; col++) {
        // Iterate over columns:
        for (int row = 0; row < retval[0].length; row++) {
            retval[row][col] = matrix.getEntry(row, col) - vector[row];
        }
    }

    // Done, return a new matrix:
    return MatrixUtils.createRealMatrix(retval);
}

From source file:com.vsthost.rnd.commons.math.ext.linear.EMatrixUtils.java

/**
 * Returns a new matrix by subtracting elements row by row.
 *
 * @param matrix The input matrix//from   w w w . j  av a  2s .  com
 * @param vector The vector to be subtracted from rows
 * @return A new matrix of which the vector is subtracted row by row
 */
public static RealMatrix rowSubtract(RealMatrix matrix, double[] vector) {
    // Declare and initialize the new matrix:
    double[][] retval = new double[matrix.getRowDimension()][matrix.getColumnDimension()];

    // Iterate over rows:
    for (int row = 0; row < retval.length; row++) {
        // Iterate over columns:
        for (int col = 0; col < retval[0].length; col++) {
            retval[row][col] = matrix.getEntry(row, col) - vector[col];
        }
    }

    // Done, return a new matrix:
    return MatrixUtils.createRealMatrix(retval);
}

From source file:com.vsthost.rnd.commons.math.ext.linear.EMatrixUtils.java

/**
 * Returns a new matrix by adding elements row by row.
 *
 * @param matrix The input matrix//w  w  w.  j a v a  2  s  .  com
 * @param vector The vector to be added to rows
 * @return A new matrix of which the vector is added row by row
 */
public static RealMatrix columnAdd(RealMatrix matrix, double[] vector) {
    // Declare and initialize the new matrix:
    double[][] retval = new double[matrix.getRowDimension()][matrix.getColumnDimension()];

    // Iterate over rows:
    for (int col = 0; col < retval.length; col++) {
        // Iterate over columns:
        for (int row = 0; row < retval[0].length; row++) {
            retval[row][col] = matrix.getEntry(row, col) + vector[row];
        }
    }

    // Done, return a new matrix:
    return MatrixUtils.createRealMatrix(retval);
}

From source file:com.vsthost.rnd.commons.math.ext.linear.EMatrixUtils.java

/**
 * Returns a new matrix by adding elements row by row.
 *
 * @param matrix The input matrix//w  ww  . java 2s .  c  o  m
 * @param vector The vector to be added to rows
 * @return A new matrix of which the vector is added row by row
 */
public static RealMatrix rowAdd(RealMatrix matrix, double[] vector) {
    // Declare and initialize the new matrix:
    double[][] retval = new double[matrix.getRowDimension()][matrix.getColumnDimension()];

    // Iterate over rows:
    for (int row = 0; row < retval.length; row++) {
        // Iterate over columns:
        for (int col = 0; col < retval[0].length; col++) {
            retval[row][col] = matrix.getEntry(row, col) + vector[col];
        }
    }

    // Done, return a new matrix:
    return MatrixUtils.createRealMatrix(retval);
}

From source file:com.vsthost.rnd.commons.math.ext.linear.EMatrixUtils.java

/**
 * Multiplies the matrix' rows using the vector element-by-element.
 *
 * @param matrix The input matrix.//  w w w. j  a v a 2s .c o m
 * @param vector The vector which will be used to multiply rows of the matrix element-by-element.
 * @return The new matrix of which rows are multiplied with the vector element-by-element.
 */
public static RealMatrix rbrMultiply(RealMatrix matrix, RealVector vector) {
    // Define the return value:
    RealMatrix retval = MatrixUtils.createRealMatrix(matrix.getRowDimension(), matrix.getColumnDimension());

    // Iterate over rows:
    for (int i = 0; i < retval.getRowDimension(); i++) {
        retval.setRowVector(i, matrix.getRowVector(i).ebeMultiply(vector));
    }

    // Done, return:
    return retval;
}