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.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  .jav  a  2 s  .  co  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.oregonstate.eecs.mcplan.ml.HilbertSpace.java

public static double inner_prod(final RealVector x, final RealMatrix M, final RealVector y) {
    // return x.dotProduct( M.operate( y ) );
    double s = 0.0;
    for (int i = 0; i < M.getRowDimension(); ++i) {
        for (int j = 0; j < M.getColumnDimension(); ++j) {
            s += x.getEntry(i) * M.getEntry(i, j) * y.getEntry(j);
        }//from  w  w w  . ja  v  a  2 s. c  o  m
    }
    return s;
}

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;/*w w  w.  ja  v a  2s  .  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:com.rapidminer.tools.math.LinearRegression.java

/** Calculates the coefficients of linear ridge regression. */
public static double[] performRegression(Matrix a, Matrix b, double ridge) {
    RealMatrix x = MatrixUtils.createRealMatrix(a.getArray());
    RealMatrix y = MatrixUtils.createRealMatrix(b.getArray());
    int numberOfColumns = x.getColumnDimension();
    double[] coefficients = new double[numberOfColumns];
    RealMatrix xTransposed = x.transpose();
    Matrix result;/*from  w ww .  j a  v  a2 s .  c  om*/
    boolean finished = false;
    while (!finished) {
        RealMatrix xTx = xTransposed.multiply(x);

        for (int i = 0; i < numberOfColumns; i++) {
            xTx.addToEntry(i, i, ridge);
        }

        RealMatrix xTy = xTransposed.multiply(y);
        coefficients = xTy.getColumn(0);

        try {
            // do not use Apache LUDecomposition for solve instead because it creates different
            // results
            result = new Matrix(xTx.getData()).solve(new Matrix(coefficients, coefficients.length));
            for (int i = 0; i < numberOfColumns; i++) {
                coefficients[i] = result.get(i, 0);
            }
            finished = true;
        } catch (Exception ex) {
            double ridgeOld = ridge;
            if (ridge > 0) {
                ridge *= 10;
            } else {
                ridge = 0.0000001;
            }
            finished = false;
            logger.warning("Error during calculation: " + ex.getMessage() + ": Increasing ridge factor from "
                    + ridgeOld + " to " + ridge);
        }
    }
    return coefficients;
}

From source file:gedi.util.MathUtils.java

public static double colSum(RealMatrix m, int c) {
    double re = 0;
    for (int i = 0; i < m.getColumnDimension(); i++)
        re += m.getEntry(i, c);/*from  w ww.  ja v a2s .co  m*/
    return re;
}

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

/**
 * Computes a Newton-Raphson update in-place to alpha.
 *//*from   w ww.  j  a va  2  s  . co m*/
private static RealVector newtonRaphsonUpdate(final double[][] data, double[] alpha) {
    // We'll compute the gold-standard value the "long" way (taking the inverse of the Hessian)
    RealMatrix hessian = new Array2DRowRealMatrix(alpha.length, alpha.length);
    for (int r = 0; r < hessian.getRowDimension(); r++) {
        for (int c = 0; c < hessian.getColumnDimension(); c++) {
            hessian.addToEntry(r, c, data.length * Gamma.trigamma(DoubleArrays.sum(alpha)));
            if (r == c) {
                hessian.addToEntry(r, c, -data.length * Gamma.trigamma(alpha[r]));
            }
        }
    }
    RealVector derivative = new ArrayRealVector(alpha.length);
    for (int k = 0; k < alpha.length; k++) {
        derivative.setEntry(k,
                data.length * (Gamma.digamma(DoubleArrays.sum(alpha)) - Gamma.digamma(alpha[k])));
        for (double[] theta : data) {
            derivative.addToEntry(k, theta[k]);
        }
    }

    RealMatrix hessianInverse = new LUDecomposition(hessian).getSolver().getInverse();
    RealVector negDiff = hessianInverse.preMultiply(derivative);
    negDiff.mapMultiplyToSelf(-1.0);

    RealVector expected = new ArrayRealVector(alpha, true);
    return expected.add(negDiff);
}

From source file:ch.zhaw.iamp.rct.weights.Weights.java

private static RealMatrix addNoise(final RealMatrix A) {
    RealMatrix buffer = A.copy();//from  w  w  w  . j a va2 s  .com
    RealMatrix noise = MatrixUtils.createRealMatrix(A.getRowDimension(), A.getColumnDimension());

    for (int i = 0; i < A.getRowDimension(); ++i) {
        for (int j = 0; j < A.getColumnDimension(); ++j) {
            double noiseSign = Math.random() > 0.5 ? 1 : -1;
            double noiseAmplitude = 1;
            noise.setEntry(i, j, noiseSign * Math.random() * noiseAmplitude);
        }
    }

    buffer = buffer.add(noise);
    return buffer;
}

From source file:cooccurrence.Omer_Levy.java

/**
 * Generic Method to take squareRoot of individual Values.
 * @param coVariance// w  ww. ja  v  a 2  s .  c  om
 * @return 
 */
private static RealMatrix squareRoot(RealMatrix coVariance) {
    RealMatrix squareRoot = MatrixUtils.createRealMatrix(coVariance.getRowDimension(),
            coVariance.getColumnDimension());
    for (int i = 0; i < coVariance.getRowDimension(); i++) {
        for (int j = 0; j < coVariance.getColumnDimension(); j++) {
            double val = coVariance.getEntry(i, j);
            val = Math.sqrt(val);
            squareRoot.addToEntry(i, j, val);
        }
    }
    return squareRoot;
}

From source file:IO.java

public static void display(RealMatrix mat, String name) {

    int row = mat.getRowDimension();
    int col = mat.getColumnDimension();

    System.out.println(name + ":" + row + "x" + col);
    for (int i = 0; i < row; i++) {
        for (int j = 0; j < col; j++) {
            System.out.print(mat.getEntry(i, j) + ",");
        }//from   w  w  w  . java 2s  .com
        System.out.println();
    }
}

From source file:game.utils.Utils.java

public static String matrixToString(RealMatrix matrix) {
    StringBuilder ret = new StringBuilder();

    for (int i = 0; i < matrix.getRowDimension(); i++) {
        for (int j = 0; j < matrix.getColumnDimension(); j++) {
            ret.append(String.format("%.5f", matrix.getEntry(i, j)));
            if (j == matrix.getColumnDimension() - 1)
                ret.append('\n');
            else// w ww  .jav  a2s. com
                ret.append(", ");
        }
    }

    return ret.toString();
}