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.cudenver.bios.matrix.OrthogonalPolynomials.java

/**
 * Computes orthogonal polynomial contrasts for the specified data values.  Currently only
 * supports fitting (not prediction contrasts).  
 * /*  w  w  w  .j a v  a2s  .c o  m*/
 *    @param x the points at which the polynomials will be evaluated
 * @param maxDegree contrasts will be computed for degrees 1 to maxDegree
 * @return matrix containing 0th,1st, 2nd,...maxDegree-th degree contrasts in each column
 * @throws IllegalArgumentException
 */
public static RealMatrix orthogonalPolynomialCoefficients(double[] x, int maxDegree)
        throws IllegalArgumentException {
    if (x == null)
        throw new IllegalArgumentException("no data specified");
    if (maxDegree < 1)
        throw new IllegalArgumentException("max polynomial degree must be greater than 1");
    // count number of unique values
    HashSet<Double> s = new HashSet<Double>();
    for (double i : x)
        s.add(i);
    int uniqueCount = s.size();
    if (maxDegree >= uniqueCount)
        throw new IllegalArgumentException(
                "max polynomial degree must be less than the number of unique points");

    // center the data
    double xBar = StatUtils.mean(x);
    double[] xCentered = new double[x.length];
    for (int i = 0; i < x.length; i++)
        xCentered[i] = x[i] - xBar;
    // compute an "outer product" of the centered x vector and a vector 
    // containing the sequence 0 to maxDegree-1, but raise the x values
    // to the power in the sequence array
    double[][] xOuter = new double[x.length][maxDegree + 1];
    int row = 0;
    for (double xValue : xCentered) {
        for (int col = 0; col <= maxDegree; col++) {
            xOuter[row][col] = Math.pow(xValue, col);
        }
        row++;
    }
    // do some mysterious QR decomposition stuff.  See Emerson (1968)
    RealMatrix outerVector = new Array2DRowRealMatrix(xOuter);
    QRDecomposition qrDecomp = new QRDecomposition(outerVector);

    RealMatrix z = MatrixUtils.getDiagonalMatrix(qrDecomp.getR());
    RealMatrix raw = qrDecomp.getQ().multiply(z);

    // column sum of squared elements in raw
    double[] normalizingConstants = new double[raw.getColumnDimension()];
    for (int col = 0; col < raw.getColumnDimension(); col++) {
        normalizingConstants[col] = 0;
        for (row = 0; row < raw.getRowDimension(); row++) {
            double value = raw.getEntry(row, col);
            normalizingConstants[col] += value * value;
        }
    }

    // now normalize the raw values
    for (int col = 0; col < raw.getColumnDimension(); col++) {
        double normalConstantSqrt = Math.sqrt(normalizingConstants[col]);
        for (row = 0; row < raw.getRowDimension(); row++) {
            raw.setEntry(row, col, raw.getEntry(row, col) / normalConstantSqrt);
        }
    }

    return raw;
}

From source file:com.yahoo.egads.utilities.SpectralMethods.java

public static RealMatrix averageHankelMatrix(RealMatrix hankelMat, int windowSize) {

    int k = hankelMat.getRowDimension();
    int m = hankelMat.getColumnDimension() / windowSize;
    int n = k + windowSize - 1;

    RealMatrix result = MatrixUtils.createRealMatrix(n, m);

    for (int t = 0; t < n; ++t) {
        int i = (t < windowSize) ? 0 : (t - windowSize + 1);
        int j = (t < windowSize) ? t : (windowSize - 1);
        int counter = 0;

        for (; i < k && j >= 0; ++i, --j, ++counter) {
            for (int h = 0; h < m; ++h) {
                result.addToEntry(t, h, hankelMat.getEntry(i, j * m + h));
            }//from  ww  w  .  jav a  2 s. c o m
        }

        for (int h = 0; h < m; ++h) {
            result.setEntry(t, h, result.getEntry(t, h) / counter);
        }
    }

    return result;
}

From source file:edu.oregonstate.eecs.mcplan.util.Csv.java

public static void write(final PrintStream out, final RealMatrix m) {
    final Writer writer = new Writer(out);
    for (int i = 0; i < m.getRowDimension(); ++i) {
        for (int j = 0; j < m.getColumnDimension(); ++j) {
            writer.cell(m.getEntry(i, j));
        }//  w  w  w  . j  a  v  a  2s .  com
        writer.newline();
    }
}

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

/**
 * Returns the sums of columns.//from   w w w.j  ava 2s. c o  m
 *
 * @param matrix The matrix of which the sums of columns to be computed
 * @return A double array of column sums
 */
public static double[] colSums(RealMatrix matrix) {
    // Declare and initialize the return value:
    double[] retval = new double[matrix.getColumnDimension()];

    // Iterate over columns and compute totals:
    for (int col = 0; col < matrix.getColumnDimension(); col++) {
        for (int row = 0; row < matrix.getRowDimension(); row++) {
            retval[col] += matrix.getEntry(row, col);
        }
    }

    // Done, return col sums:
    return retval;
}

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

/**
 * Returns the sums of rows./*  www  .j  a va 2 s. com*/
 *
 * @param matrix The matrix of which the sums of rows to be computed
 * @return A double array of row sums.
 */
public static double[] rowSums(RealMatrix matrix) {
    // Declare and initialize the return value:
    double[] retval = new double[matrix.getColumnDimension()];

    // Iterate over columns and compute totals:
    for (int row = 0; row < matrix.getRowDimension(); row++) {
        for (int col = 0; col < matrix.getColumnDimension(); col++) {
            retval[row] += matrix.getEntry(row, col);
        }
    }

    // Done, return col sums:
    return retval;
}

From source file:dataGen.DataGen.java

/**
 * Do the yet created data stored in the matrix fulfill the Anti-Correlation condition?
 * Returns true if more than the half of all correlation coefficients are below the supremum coefficient.
 * @param corrMatrix//from w ww.  j a v  a2  s.  c o m
 *       The Data-Matrix
 * @param corrCoeff
 *       the Supremum correlation coefficient
 * @param dimensions
 *       how many dimensions does the test file have?
 * @return
 *       true if more than the half of all correlation coefficients are below the supremum coefficient.
 */
public static boolean isCorrMatrixValid(RealMatrix corrMatrix, double corrCoeff, int dimensions) {
    int count = 0;
    int maxVariance = sum(dimensions - 1) / 2;
    for (int i = 1; i < corrMatrix.getColumnDimension(); i++) {
        for (int j = 0; j < i; j++) {
            if (corrMatrix.getEntry(i, j) > corrCoeff) {
                if (count < maxVariance)
                    count++;
                else
                    return false;
            }
        }
    }
    return true;
}

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   w ww  .ja va 2s . co  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  ww  . j a v  a 2  s  .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//ww w . j ava 2  s .c  om
 * @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/*from  w w w.j av a2s.  c om*/
 * @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);
}