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:net.myrrix.online.factorizer.als.AlternatingLeastSquaresTest.java

private static RealMatrix buildTestXYTProduct(boolean reconstructR)
        throws ExecutionException, InterruptedException {
    System.setProperty("model.reconstructRMatrix", Boolean.toString(reconstructR));

    FastByIDMap<FastByIDFloatMap> byRow = new FastByIDMap<FastByIDFloatMap>();
    FastByIDMap<FastByIDFloatMap> byCol = new FastByIDMap<FastByIDFloatMap>();
    // Octave: R = [ 0 2 3 1 0 ; 0 0 4 5 0 ; 1 0 0 0 2 ; 3 0 1 0 5 ; 0 2 2 2 0 ]
    MatrixUtils.addTo(0, 1, 2.0f, byRow, byCol);
    MatrixUtils.addTo(0, 2, 3.0f, byRow, byCol);
    MatrixUtils.addTo(0, 3, 1.0f, byRow, byCol);
    MatrixUtils.addTo(1, 2, 4.0f, byRow, byCol);
    MatrixUtils.addTo(1, 3, 5.0f, byRow, byCol);
    MatrixUtils.addTo(2, 0, 1.0f, byRow, byCol);
    MatrixUtils.addTo(2, 4, 2.0f, byRow, byCol);
    MatrixUtils.addTo(3, 0, 3.0f, byRow, byCol);
    MatrixUtils.addTo(3, 2, 1.0f, byRow, byCol);
    MatrixUtils.addTo(3, 4, 5.0f, byRow, byCol);
    MatrixUtils.addTo(4, 1, 2.0f, byRow, byCol);
    MatrixUtils.addTo(4, 2, 2.0f, byRow, byCol);
    MatrixUtils.addTo(4, 3, 2.0f, byRow, byCol);

    // Octave: Y = [ 0.1 0.2 ; 0.2 0.5 ; 0.3 0.1 ; 0.2 0.2 ; 0.5 0.4 ];
    FastByIDMap<float[]> previousY = new FastByIDMap<float[]>();
    previousY.put(0L, new float[] { 0.1f, 0.2f });
    previousY.put(1L, new float[] { 0.2f, 0.5f });
    previousY.put(2L, new float[] { 0.3f, 0.1f });
    previousY.put(3L, new float[] { 0.2f, 0.2f });
    previousY.put(4L, new float[] { 0.5f, 0.4f });

    MatrixFactorizer als = new AlternatingLeastSquares(byRow, byCol, 2, 0.0001, 40);
    als.setPreviousY(previousY);//from  ww  w  .j  av a2 s  . c o  m
    als.call();

    RealMatrix product = MatrixUtils.multiplyXYT(als.getX(), als.getY());

    StringBuilder productString = new StringBuilder(100);
    for (int row = 0; row < product.getRowDimension(); row++) {
        productString.append('\n').append(Arrays.toString(doubleToFloatArray(product.getRow(row))));
    }
    log.info("{}", productString);

    return product;
}

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

/**
 * Calculates a pseudo-inverse using the values in the given files. They are
 * first read, then converted to a matrix, and finally used for the
 * calculation of the inverse, using Singular value decomposition (SVD).
 *
 * @param pathToA The file which contains the matrix A, represented in
 * comma-separated-value format.//w  w  w  .j  av  a2  s . co  m
 * @param targetTrajectoryFile The file which contains the target
 * trajectory, represented in comma-separated-value format.
 * @param weightsFile The file, to which the calculated weights should be
 * written to.
 * @param offset The numbers of first steps to ignore (to skip fading-memory
 * initialization steps).
 */
public static void calculateWeights(final String pathToA, final String targetTrajectoryFile,
        final String weightsFile, final int offset) {
    try {
        RealMatrix A = csvToMatrix(pathToA);
        // cut first n elements
        A = A.getSubMatrix(offset, A.getRowDimension() - 1, 0, A.getColumnDimension() - 1);
        A = addNoise(A);

        RealMatrix b = csvToMatrix(targetTrajectoryFile);

        // adjust b to cutting
        int n = offset % b.getRowDimension();

        if (n > 0) {
            RealMatrix tmp = b.getSubMatrix(n, b.getRowDimension() - 1, 0, b.getColumnDimension() - 1);
            b = b.getSubMatrix(0, n - 1, 0, b.getColumnDimension() - 1);
            double[][] tmpArray = tmp.getData();
            double[][] tmpArray2 = b.getData();
            b = MatrixUtils.createRealMatrix(concat(tmpArray, tmpArray2));
            tmpArray = b.getData();

            for (int i = 0; tmpArray.length < A.getRowDimension(); ++i) {
                tmpArray2 = new double[1][tmpArray[0].length];

                for (int j = 0; j < tmpArray[i].length; ++j) {
                    tmpArray2[0][j] = tmpArray[i][j];
                }

                tmpArray = concat(tmpArray, tmpArray2);
            }

            b = MatrixUtils.createRealMatrix(tmpArray);
        }

        DecompositionSolver solver = new SingularValueDecomposition(A).getSolver();
        RealMatrix x = solver.solve(b).transpose();
        matrixToCsv(x, weightsFile);

    } catch (IOException ex) {
        JOptionPane.showMessageDialog(null, "Could not read a file: " + ex.getMessage(), "File Error",
                JOptionPane.ERROR_MESSAGE);
        Logger.getLogger(Weights.class.getName()).log(Level.WARNING, "Could not read a file: {0}", ex);
    } catch (DimensionMismatchException ex) {
        JOptionPane.showMessageDialog(null,
                "<html>Could not calculate the " + "pseudo-inverse since a dimension mismatch occurred.<br />"
                        + "Please make sure that all lines of the CSV file posses "
                        + "the same amount of entries.<br />Hint: Remove the last "
                        + "line and try it again.</html>",
                "Matrix Dimension Mismatch", JOptionPane.ERROR_MESSAGE);
        Logger.getLogger(Weights.class.getName()).log(Level.WARNING, "A dimension mismatch occurred: {0}", ex);
    }
}

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

private static void matrixToCsv(final RealMatrix matrix, final String targetFilePath) throws IOException {
    Writer out = new FileWriter(targetFilePath);

    for (int i = 0; i < matrix.getRowDimension(); ++i) {
        for (int j = 0; j < matrix.getColumnDimension(); ++j) {
            out.append("" + matrix.getEntry(i, j));
            if (j < matrix.getColumnDimension() - 1) {
                out.append(",");
            }/*from   w  ww . j  a  v a 2s .c  o m*/
        }
        out.append("\n");
        out.flush();
    }

}

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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));
        }/*from ww w .j  a  v  a 2  s  . com*/
        writer.newline();
    }
}

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

public static RealMatrix createHankelMatrix(RealMatrix data, int windowSize) {

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

    RealMatrix res = MatrixUtils.createRealMatrix(k, m * windowSize);
    double[] buffer = {};

    for (int i = 0; i < n; ++i) {
        double[] row = data.getRow(i);
        buffer = ArrayUtils.addAll(buffer, row);

        if (i >= windowSize - 1) {
            RealMatrix mat = MatrixUtils.createRowRealMatrix(buffer);
            res.setRowMatrix(i - windowSize + 1, mat);
            buffer = ArrayUtils.subarray(buffer, m, buffer.length);
        }//from w w  w.  j av  a2s.  co m
    }

    return res;
}

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

/** Returns an array of logs of samples from the specified Dirichlet distributions.
 * Similar to calling:/*w w  w  . j a va  2  s  .  co  m*/
 * <pre>
 *   double[][] thetas = sample(alpha, rnd);
 *   for (int k = 0; k < thetas.length; k++) {
 *      DoubleArrays.logToSelf(thetas[k]);
 *   }
 * </pre>
 * EXCEPT that precision is better preserved.
 **/
public static double[][] logSample(RealMatrix alphas, RandomGenerator rnd) {
    double[][] thetas = new double[alphas.getRowDimension()][];
    for (int i = 0; i < thetas.length; i++) {
        thetas[i] = logSample(alphas.getRowVector(i), rnd);
    }
    return thetas;
}

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From source file:edu.mit.genecircuits.GcUtils.java

/** Convert dense Apache Commons to Colt matrix */
static public DoubleMatrix2D apache2colt(RealMatrix apache) {

    // Convert apache commons matrix to colt
    DoubleMatrix2D colt = new DenseDoubleMatrix2D(apache.getRowDimension(), apache.getColumnDimension());
    for (int i = 0; i < apache.getRowDimension(); i++)
        for (int j = 0; j < apache.getColumnDimension(); j++)
            colt.set(i, j, apache.getEntry(i, j));

    return colt;//  w  ww .  j  av  a 2s.  c o m
}

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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));
            }//  w  w w .  java 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:com.vsthost.rnd.commons.math.ext.linear.EMatrixUtils.java

/**
 * Returns the standard deviations of rows.
 *
 * @param matrix The matrix of which the standard deviations of rows to be computed
 * @return A double array of row standard deviations.
 *//*from   www . j a v a 2 s.  co  m*/
public static double[] rowStdDevs(RealMatrix matrix) {
    double[] retval = new double[matrix.getRowDimension()];
    for (int i = 0; i < retval.length; i++) {
        retval[i] = new DescriptiveStatistics(matrix.getRow(i)).getStandardDeviation();
    }
    return retval;
}

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

/**
 * Returns the column range from the matrix as a new matrix.
 *
 * @param matrix The input matrix//from www  . j av a 2  s . c o  m
 * @param start The index of the column to start with (inclusive)
 * @param end The index of the column to end with (inclusive)
 * @return A new matrix with columns specified
 */
public static RealMatrix getColumRange(RealMatrix matrix, int start, int end) {
    return matrix.getSubMatrix(0, matrix.getRowDimension() - 1, start, end);
}

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