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

List of usage examples for org.apache.commons.math3.linear RealMatrix setEntry

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Introduction

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

Prototype

void setEntry(int row, int column, double value) throws OutOfRangeException;

Source Link

Document

Set the entry in the specified row and column.

Usage

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

private void T(final RealMatrix S_tilde, final RealMatrix S) {
    for (int i = 0; i < S_tilde.getRowDimension(); ++i) {
        for (int j = 0; j < S_tilde.getColumnDimension(); ++j) {
            final double st = S_tilde.getEntry(i, j);
            S_tilde.setEntry(i, j, st * S.getEntry(i, j) < 0 ? st : 0);
        }//from  ww  w . ja  v  a  2 s  .  co m
    }
}

From source file:iDynoOptimizer.MOEAFramework26.src.org.moeaframework.util.RotationMatrixBuilder.java

/**
 * Returns a rotation matrix for rotating about the 2D plane defined by
 * the specified axes./*from  w ww.j a v  a  2 s . co m*/
 * 
 * @param i the first axis
 * @param j the second axis
 * @param theta the rotation angle in radians
 * @return a rotation matrix for rotating about the 2D plane defined by
 *         the specified axes
 */
private RealMatrix newRotationMatrix(int i, int j, double theta) {
    RealMatrix rotation = newIdentityMatrix();

    rotation.setEntry(i, i, Math.cos(theta));
    rotation.setEntry(i, j, -Math.sin(theta));
    rotation.setEntry(j, i, Math.sin(theta));
    rotation.setEntry(j, j, Math.cos(theta));

    return rotation;
}

From source file:hivemall.utils.math.MatrixUtilsTest.java

@Test
public void testTridiagonalEigen() {
    // Tridiagonal Matrix
    RealMatrix T = new Array2DRowRealMatrix(
            new double[][] { new double[] { 40, 60, 0, 0 }, new double[] { 60, 10, 120, 0 },
                    new double[] { 0, 120, 10, 120 }, new double[] { 0, 0, 120, 10 } });

    double[] eigvals = new double[4];
    RealMatrix eigvecs = new Array2DRowRealMatrix(new double[4][4]);

    MatrixUtils.tridiagonalEigen(T, 2, eigvals, eigvecs);

    RealMatrix actual = eigvecs.multiply(eigvecs.transpose());

    RealMatrix expected = new Array2DRowRealMatrix(new double[4][4]);
    for (int i = 0; i < 4; i++) {
        expected.setEntry(i, i, 1);
    }//from www  .  ja v  a  2s. c  o  m

    for (int i = 0; i < 4; i++) {
        for (int j = 0; j < 4; j++) {
            Assert.assertEquals(expected.getEntry(i, j), actual.getEntry(i, j), 0.001d);
        }
    }
}

From source file:mase.spec.SilhouetteDistanceCalculator.java

private RealMatrix computeDistanceMatrix(List<BehaviourResult> brs) {
    RealMatrix mat = new BlockRealMatrix(brs.size(), brs.size());
    for (int i = 0; i < brs.size(); i++) {
        for (int j = i + 1; j < brs.size(); j++) {
            double d = brs.get(i).distanceTo(brs.get(j));
            mat.setEntry(i, j, d);
            mat.setEntry(j, i, d);/*from w  w  w .  ja  va  2 s  . c  o  m*/
        }
    }
    return mat;
}

From source file:edu.ucdenver.bios.power.ConditionalOrthogonalPolynomial3FactorTest.java

/**
 * Sets up the basic X, beta matrices for each of the tests.  The individual
 * tests create different contrast matrices
 * @return/*from  ww w  .  jav a2  s  .  co m*/
 */
private GLMMPowerParameters buildInputsWithoutContrasts() {
    int Q = dataD.length * dataE.length * dataF.length;
    int P = dataA.length * dataB.length * dataC.length;
    // build the inputs
    GLMMPowerParameters params = new GLMMPowerParameters();

    // add alpha values - bonferroni corrected for 6 comparisons
    params.addAlpha(0.05);

    // build the design matrix
    params.setDesignEssence(org.apache.commons.math3.linear.MatrixUtils.createRealIdentityMatrix(Q));
    // add a concise representation of the design matrix to the alt matrix string
    matrixAltStringBuffer.append("\\begin{eqnarray*}\n");
    matrixAltStringBuffer.append("\\underset{\\left(" + Q + "\\times" + Q
            + "\\right)}{\\text{Es}\\left(\\mathbf{X}\\right)} & = & I_{" + Q + "}\n");
    matrixAltStringBuffer.append("\\end{eqnarray*}\n");
    // build beta matrix
    RealMatrix beta = MatrixUtils.getRealMatrixWithFilledValue(Q, P, 0);
    beta.setEntry(0, 0, 1);
    params.setBeta(new FixedRandomMatrix(beta.getData(), null, false));
    // add latex to represent matrix
    matrixAltStringBuffer.append("\\begin{eqnarray*}\n");
    matrixAltStringBuffer.append("\\underset{\\left(" + Q + "\\times" + P + "\\right)}{\\mathbf{B}} & = & "
            + "\\begin{bmatrix}1 & 0 & \\ldots & 0\\\\\n" + "0 &  &  & \\vdots\\\\\n"
            + "\\vdots &  &  & \\vdots\\\\\n" + "0 & \\ldots & \\ldots & 0\n" + "\\end{bmatrix}\n");
    matrixAltStringBuffer.append("\\end{eqnarray*}\n");
    // add beta scale values
    params.addBetaScale(9);
    params.addBetaScale(18);
    params.addBetaScale(27);

    // build theta null matrix
    double[][] theta0 = { { 0, 0, 0, 0 } };
    params.setTheta(new Array2DRowRealMatrix(theta0));
    matrixAltStringBuffer.append("\\begin{eqnarray*}\n");
    matrixAltStringBuffer
            .append("\\underset{\\left(" + 1 + "\\times" + 4 + "\\right)}{\\mathbf{\\Theta}_{0}} & = & "
                    + "\\begin{bmatrix}0 & 0 & 0 & 0\n" + "\\end{bmatrix}\n");
    matrixAltStringBuffer.append("\\end{eqnarray*}\n");
    // build sigma matrix
    RealMatrix sigma = org.apache.commons.math3.linear.MatrixUtils.createRealIdentityMatrix(P);
    for (int i = 0; i < P; i++)
        sigma.setEntry(i, i, i + 1);
    params.setSigmaError(sigma);
    // add sigma scale values
    params.addSigmaScale(1);
    matrixAltStringBuffer.append("\\begin{eqnarray*}\n");
    matrixAltStringBuffer.append("\\underset{\\left(" + P + "\\times" + P
            + "\\right)}{\\mathbf{\\Sigma}_{E}} & = & " + "\\begin{bmatrix}1 & 2 & 3 & \\ldots & " + P + "\n"
            + "\\end{bmatrix} \\times I_{" + P + "}\n");
    matrixAltStringBuffer.append("\\end{eqnarray*}\n");
    // add sample size multipliers
    for (int perGroupN = 2; perGroupN <= 12; perGroupN += 2)
        params.addSampleSize(perGroupN);
    //params.addSampleSize(2);
    return params;
}

From source file:edu.cudenver.bios.power.test.paper.TestConditionalOrthogonalPolynomial3Factor.java

/**
 * Sets up the basic X, beta matrices for each of the tests.  The individual
 * tests create different contrast matrices
 * @return//from  ww w.jav  a2  s  .  c o m
 */
private GLMMPowerParameters buildInputsWithoutContrasts() {
    int Q = dataD.length * dataE.length * dataF.length;
    int P = dataA.length * dataB.length * dataC.length;
    // build the inputs        
    GLMMPowerParameters params = new GLMMPowerParameters();

    // add alpha values - bonferroni corrected for 6 comparisons
    params.addAlpha(0.05);

    // build the design matrix 
    params.setDesignEssence(org.apache.commons.math3.linear.MatrixUtils.createRealIdentityMatrix(Q));
    // add a concise representation of the design matrix to the alt matrix string
    matrixAltStringBuffer.append("\\begin{eqnarray*}\n");
    matrixAltStringBuffer.append("\\underset{\\left(" + Q + "\\times" + Q
            + "\\right)}{\\text{Es}\\left(\\mathbf{X}\\right)} & = & I_{" + Q + "}\n");
    matrixAltStringBuffer.append("\\end{eqnarray*}\n");
    // build beta matrix
    RealMatrix beta = MatrixUtils.getRealMatrixWithFilledValue(Q, P, 0);
    beta.setEntry(0, 0, 1);
    params.setBeta(new FixedRandomMatrix(beta.getData(), null, false));
    // add latex to represent matrix
    matrixAltStringBuffer.append("\\begin{eqnarray*}\n");
    matrixAltStringBuffer.append("\\underset{\\left(" + Q + "\\times" + P + "\\right)}{\\mathbf{B}} & = & "
            + "\\begin{bmatrix}1 & 0 & \\ldots & 0\\\\\n" + "0 &  &  & \\vdots\\\\\n"
            + "\\vdots &  &  & \\vdots\\\\\n" + "0 & \\ldots & \\ldots & 0\n" + "\\end{bmatrix}\n");
    matrixAltStringBuffer.append("\\end{eqnarray*}\n");
    // add beta scale values
    params.addBetaScale(9);
    params.addBetaScale(18);
    params.addBetaScale(27);

    // build theta null matrix
    double[][] theta0 = { { 0, 0, 0, 0 } };
    params.setTheta(new Array2DRowRealMatrix(theta0));
    matrixAltStringBuffer.append("\\begin{eqnarray*}\n");
    matrixAltStringBuffer
            .append("\\underset{\\left(" + 1 + "\\times" + 4 + "\\right)}{\\mathbf{\\Theta}_{0}} & = & "
                    + "\\begin{bmatrix}0 & 0 & 0 & 0\n" + "\\end{bmatrix}\n");
    matrixAltStringBuffer.append("\\end{eqnarray*}\n");
    // build sigma matrix
    RealMatrix sigma = org.apache.commons.math3.linear.MatrixUtils.createRealIdentityMatrix(P);
    for (int i = 0; i < P; i++)
        sigma.setEntry(i, i, i + 1);
    params.setSigmaError(sigma);
    // add sigma scale values
    params.addSigmaScale(1);
    matrixAltStringBuffer.append("\\begin{eqnarray*}\n");
    matrixAltStringBuffer.append("\\underset{\\left(" + P + "\\times" + P
            + "\\right)}{\\mathbf{\\Sigma}_{E}} & = & " + "\\begin{bmatrix}1 & 2 & 3 & \\ldots & " + P + "\n"
            + "\\end{bmatrix} \\times I_{" + P + "}\n");
    matrixAltStringBuffer.append("\\end{eqnarray*}\n");
    // add sample size multipliers
    for (int perGroupN = 2; perGroupN <= 12; perGroupN += 2)
        params.addSampleSize(perGroupN);
    //params.addSampleSize(2);
    return params;
}

From source file:io.github.malapert.jwcs.coordsystem.Utility.java

/**
 * Remove the elliptic component of annual aberration when this is included
 * in a catalogue fk4 position.//  w w w.ja v  a  2  s. c om
 * 
 * Notes:
 * ------
 * Return a new position where the elliptic terms of aberration 
 * are removed i.e. convert a apparent position from a catalog to
 * a mean place.
 * The effects of ecliptic aberration were included in the 
 * catalog positions to facilitate telescope pointing.
 * See also notes at 'addEterms'.
 * 
 * @param xyz vector xyz
 * @param eterm E-terms vector (as returned by getEterms()). If input a is 
 * omitted (== *null*), the e-terms for 1950 will be substituted.
 * @return **Mean place**
 */
public final static RealMatrix removeEterms(final RealMatrix xyz, RealMatrix eterm) {
    RealMatrix xyzeterm = xyz.copy();

    if (eterm == null) {
        eterm = FK4.getEterms(1950);
    }
    double x = xyz.getEntry(0, 0);
    double y = xyz.getEntry(1, 0);
    double z = xyz.getEntry(2, 0);
    x -= eterm.getEntry(0, 0);
    y -= eterm.getEntry(0, 1);
    z -= eterm.getEntry(0, 2);
    xyzeterm.setEntry(0, 0, x);
    xyzeterm.setEntry(1, 0, y);
    xyzeterm.setEntry(2, 0, z);

    return xyzeterm;
}

From source file:ffnn.FFNNTubesAI.java

@Override
public double[] distributionForInstance(Instance instance) throws Exception {
    RealMatrix input_matrix = new BlockRealMatrix(1, input_layer + 1);

    instance = filterNominalNumeric(instance);

    for (int k = 0; k < input_layer; k++) {
        input_matrix.setEntry(0, k, instance.value(k));
    }//from   w  w  w  . ja va 2 s .  co m
    input_matrix.setEntry(0, input_layer, 1.0); // bias

    RealMatrix hidden_matrix = input_matrix.multiply(weight1);
    for (int y = 0; y < hidden_layer; ++y) {
        hidden_matrix.setEntry(0, y, sig(hidden_matrix.getEntry(0, y)));
    }
    RealMatrix output_matrix = hidden_matrix.multiply(weight2).add(bias2);
    for (int y = 0; y < output_layer; ++y) {
        output_matrix.setEntry(0, y, sig(output_matrix.getEntry(0, y)));
    }
    double[][] m = output_matrix.getData();

    return m[0];
}

From source file:io.yields.math.concepts.operator.Smoothness.java

private RealMatrix computeDistance(List<Tuple> normalizedData) {
    RealMatrix a = new Array2DRowRealMatrix(normalizedData.size(), order + 1);
    RealMatrix b = new Array2DRowRealMatrix(normalizedData.size(), 1);
    int row = 0;/*  w w  w. j a v  a2  s.com*/
    for (Tuple tuple : normalizedData) {
        final int currentRow = row;
        IntStream.rangeClosed(0, order)
                .forEach(power -> a.setEntry(currentRow, power, Math.pow(tuple.getX(), power)));
        b.setEntry(currentRow, 0, tuple.getY());
        row++;
    }
    DecompositionSolver solver = new QRDecomposition(a, EPS).getSolver();
    if (solver.isNonSingular() && !isConstant(b)) {
        RealMatrix solution = solver.solve(b);
        return a.multiply(solution).subtract(b);
    } else {
        return new Array2DRowRealMatrix(normalizedData.size(), 1);
    }
}

From source file:iDynoOptimizer.MOEAFramework26.src.org.moeaframework.util.RotationMatrixBuilder.java

/**
 * Returns an identity matrix./*  www .  j av  a2 s  . co m*/
 * 
 * @return an identity matrix
 */
private RealMatrix newIdentityMatrix() {
    RealMatrix identity = MatrixUtils.createRealMatrix(dimension, dimension);

    for (int i = 0; i < dimension; i++) {
        identity.setEntry(i, i, 1.0);
    }

    return identity;
}