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

Introduction

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

Prototype

int getColumnDimension();

Source Link

Document

Returns the number of columns in the matrix.

Usage

From source file:edu.ucdenver.bios.powersvc.resource.PowerResourceHelper.java

/**
 * Create a sigma covariate matrix from the study design.
 * @param studyDesign study design object
 * @return sigma covariate matrix// w  w  w .  j  a  v a 2  s.c  o  m
 */
public static RealMatrix sigmaCovariateMatrixFromStudyDesign(StudyDesign studyDesign) {
    if (studyDesign.getViewTypeEnum() == StudyDesignViewTypeEnum.MATRIX_MODE) {
        return toRealMatrix(studyDesign.getNamedMatrix(PowerConstants.MATRIX_SIGMA_GAUSSIAN));
    } else {
        // in Guided Mode, the user specifies this as a standard deviation, so we square it
        RealMatrix sigmaG = toRealMatrix(studyDesign.getNamedMatrix(PowerConstants.MATRIX_SIGMA_GAUSSIAN));
        if (sigmaG != null && sigmaG.getRowDimension() > 0 && sigmaG.getColumnDimension() > 0) {
            double stddev = sigmaG.getEntry(0, 0);
            sigmaG.setEntry(0, 0, stddev * stddev);
        }
        return sigmaG;
    }
}

From source file:edu.cmu.tetrad.util.MatrixUtils.java

public static RealMatrix transposeWithoutCopy(final RealMatrix apacheData) {
    return new AbstractRealMatrix(apacheData.getColumnDimension(), apacheData.getRowDimension()) {
        @Override/*from  w w w . j  a va2  s .com*/
        public int getRowDimension() {
            return apacheData.getColumnDimension();
        }

        @Override
        public int getColumnDimension() {
            return apacheData.getRowDimension();
        }

        @Override
        public RealMatrix createMatrix(int rowDimension, int columnDimension)
                throws NotStrictlyPositiveException {
            return apacheData.createMatrix(rowDimension, columnDimension);
        }

        @Override
        public RealMatrix copy() {
            throw new IllegalArgumentException("Can't copy");
        }

        @Override
        public double getEntry(int i, int j) throws OutOfRangeException {
            //                throw new UnsupportedOperationException();
            return apacheData.getEntry(j, i);
        }

        @Override
        public void setEntry(int i, int j, double v) throws OutOfRangeException {
            throw new UnsupportedOperationException();
        }
    };
}

From source file:edu.cmu.tetrad.util.MatrixUtils1.java

public static double[][] pseudoInverse(double[][] x) {
    SingularValueDecomposition svd = new SingularValueDecomposition(new BlockRealMatrix(x));

    RealMatrix U = svd.getU();/*from  ww w  . j a  va 2 s. co  m*/
    RealMatrix V = svd.getV();
    RealMatrix S = svd.getS();

    for (int i = 0; i < S.getRowDimension(); i++) {
        for (int j = 0; j < S.getColumnDimension(); j++) {
            double v = S.getEntry(i, j);
            S.setEntry(i, j, v == 0 ? 0.0 : 1.0 / v);
        }
    }

    return V.multiply(S.multiply(U.transpose())).getData();
}

From source file:com.itemanalysis.psychometrics.factoranalysis.QuartiminCriteria.java

public void computeValues(RealMatrix L) {
    int k = L.getColumnDimension();
    int p = L.getRowDimension();
    RealMatrix I = new IdentityMatrix(p);
    RealMatrix L2 = MatrixUtils.multiplyElements(L, L);

    RealMatrix N = new Array2DRowRealMatrix(k, k);
    N.walkInRowOrder(new DefaultRealMatrixChangingVisitor() {
        @Override/*from   ww  w .  j  a  va 2  s  .  c  o  m*/
        public double visit(int row, int column, double value) {
            if (row == column)
                return 0.0;
            return 1.0;
        }
    });

    RealMatrix X = L2.multiply(N);
    double sum = MatrixUtils.sumMatrix(MatrixUtils.multiplyElements(L2, X));
    functionValue = sum / 4.0;
    gradient = MatrixUtils.multiplyElements(L, X);

}

From source file:com.itemanalysis.psychometrics.measurement.DiagonalMatrix.java

/**
 * Extracts the diagonal elements from a matrix.
 *
 * @param matrix a matrix from which teh diagonal elements are extracted.
 *///from   www . ja  v a  2 s. c o m
public DiagonalMatrix(RealMatrix matrix) {
    super(matrix.getColumnDimension(), matrix.getColumnDimension());
    int ncol = matrix.getColumnDimension();
    for (int i = 0; i < ncol; i++) {
        for (int j = 0; j < ncol; j++) {
            if (i == j) {
                this.setEntry(i, j, matrix.getEntry(i, j));
            } else {
                this.setEntry(i, j, 0.0);
            }
        }
    }

}

From source file:com.itemanalysis.psychometrics.statistics.MatrixToVector.java

public MatrixToVector(RealMatrix matrix) {
    this.matrix = matrix;
    numEelements = (int) ((matrix.getColumnDimension() * (matrix.getColumnDimension() + 1)) / 2.0);
    realVector = new Array2DRowRealMatrix(numEelements, 1);
}

From source file:com.caseystella.analytics.outlier.batch.rpca.RidgeRegression.java

private double[] getDiagonal(RealMatrix X) {
    double[] diag = new double[X.getColumnDimension()];
    for (int i = 0; i < diag.length; i++) {
        diag[i] = X.getEntry(i, i);/*from w  ww  .ja  v a2  s .c om*/
    }
    return diag;
}

From source file:com.itemanalysis.psychometrics.factoranalysis.ObliminCriteria.java

public void computeValues(RealMatrix L) {
    final int k = L.getColumnDimension();
    final int p = L.getRowDimension();
    RealMatrix I = new IdentityMatrix(p);
    RealMatrix L2 = MatrixUtils.multiplyElements(L, L);

    RealMatrix N = new Array2DRowRealMatrix(k, k);
    N.walkInRowOrder(new DefaultRealMatrixChangingVisitor() {
        @Override//from   w  w w .j a v a  2 s  . c o  m
        public double visit(int row, int column, double value) {
            if (row == column)
                return 0.0;
            return 1.0;
        }
    });

    RealMatrix C = new Array2DRowRealMatrix(p, p);
    C.walkInRowOrder(new DefaultRealMatrixChangingVisitor() {
        @Override
        public double visit(int row, int column, double value) {
            return gam / (double) p;
        }
    });

    RealMatrix X = I.subtract(C).multiply(L2).multiply(N);
    double sum = MatrixUtils.sumMatrix(MatrixUtils.multiplyElements(L2, X));
    functionValue = sum / 4.0;
    gradient = MatrixUtils.multiplyElements(L, X);

}

From source file:io.warp10.script.functions.TOVEC.java

@Override
public Object apply(WarpScriptStack stack) throws WarpScriptException {

    Object o = stack.pop();/*from   w w  w .  j  a va2s .  c o  m*/

    if (o instanceof RealMatrix) {
        RealMatrix matrix = (RealMatrix) o;

        if (1 != matrix.getColumnDimension()) {
            throw new WarpScriptException(
                    getName() + " expects a matrix with a single column on top of the stack.");
        }

        RealVector vector = matrix.getColumnVector(0);
        stack.push(vector);
        return stack;
    }

    if (!(o instanceof List)) {
        throw new WarpScriptException(getName() + " expects a list onto the stack.");
    }

    double[] data = new double[((List) o).size()];

    for (int i = 0; i < data.length; i++) {
        Object oo = ((List) o).get(i);
        if (!(oo instanceof Number)) {
            throw new WarpScriptException(getName() + " expects a list of numbers onto the stack.");
        }
        data[i] = ((Number) oo).doubleValue();
    }

    stack.push(MatrixUtils.createRealVector(data));

    return stack;
}

From source file:com.clust4j.algo.preprocess.MedianCenterer.java

@Override
public MedianCenterer fit(RealMatrix X) {
    synchronized (fitLock) {
        final int n = X.getColumnDimension();

        // need to mean center...
        this.medians = new double[n];
        final double[][] y = X.transpose().getData();

        // First pass, compute median...
        for (int j = 0; j < n; j++) {
            this.medians[j] = VecUtils.median(y[j]);
        }//from  w w  w .j  av  a  2  s .co  m

        return this;
    }
}