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

Introduction

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

Prototype

void setSubMatrix(double[][] subMatrix, int row, int column)
        throws NoDataException, OutOfRangeException, DimensionMismatchException, NullArgumentException;

Source Link

Document

Replace the submatrix starting at row, column using data in the input subMatrix array.

Usage

From source file:org.knime.al.util.noveltydetection.knfst.KNFST.java

public static RealMatrix projection(final RealMatrix kernelMatrix, final String[] labels)
        throws KNFSTException {

    final ClassWrapper[] classes = ClassWrapper.classes(labels);

    // check labels
    if (classes.length == 1) {
        throw new IllegalArgumentException(
                "not able to calculate a nullspace from data of a single class using KNFST (input variable \"labels\" only contains a single value)");
    }//from  www  . ja v  a  2 s.c o  m

    // check kernel matrix
    if (!kernelMatrix.isSquare()) {
        throw new IllegalArgumentException("The KernelMatrix must be quadratic!");
    }

    // calculate weights of orthonormal basis in kernel space
    final RealMatrix centeredK = centerKernelMatrix(kernelMatrix);

    final EigenDecomposition eig = new EigenDecomposition(centeredK);
    final double[] eigVals = eig.getRealEigenvalues();
    final ArrayList<Integer> nonZeroEigValIndices = new ArrayList<Integer>();
    for (int i = 0; i < eigVals.length; i++) {
        if (eigVals[i] > 1e-12) {
            nonZeroEigValIndices.add(i);
        }
    }

    int eigIterator = 0;
    final RealMatrix eigVecs = eig.getV();
    RealMatrix basisvecs = null;
    try {
        basisvecs = MatrixUtils.createRealMatrix(eigVecs.getRowDimension(), nonZeroEigValIndices.size());
    } catch (final Exception e) {
        throw new KNFSTException("Something went wrong. Try different parameters or a different kernel.");
    }

    for (final Integer index : nonZeroEigValIndices) {
        final double normalizer = 1 / Math.sqrt(eigVals[index]);
        final RealVector basisVec = eigVecs.getColumnVector(eigIterator).mapMultiply(normalizer);
        basisvecs.setColumnVector(eigIterator++, basisVec);
    }

    // calculate transformation T of within class scatter Sw:
    // T= B'*K*(I-L) and L a block matrix
    final RealMatrix L = kernelMatrix.createMatrix(kernelMatrix.getRowDimension(),
            kernelMatrix.getColumnDimension());
    int start = 0;
    for (final ClassWrapper cl : classes) {
        final int count = cl.getCount();
        L.setSubMatrix(MatrixFunctions.ones(count, count).scalarMultiply(1.0 / count).getData(), start, start);
        start += count;
    }

    // need Matrix M with all entries 1/m to modify basisvecs which allows
    // usage of
    // uncentered kernel values (eye(size(M)).M)*basisvecs
    final RealMatrix M = MatrixFunctions
            .ones(kernelMatrix.getColumnDimension(), kernelMatrix.getColumnDimension())
            .scalarMultiply(1.0 / kernelMatrix.getColumnDimension());
    final RealMatrix I = MatrixUtils.createRealIdentityMatrix(M.getColumnDimension());

    // compute helper matrix H
    final RealMatrix H = ((I.subtract(M)).multiply(basisvecs)).transpose().multiply(kernelMatrix)
            .multiply(I.subtract(L));

    // T = H*H' = B'*Sw*B with B=basisvecs
    final RealMatrix T = H.multiply(H.transpose());

    // calculate weights for null space
    RealMatrix eigenvecs = MatrixFunctions.nullspace(T);

    if (eigenvecs == null) {
        final EigenDecomposition eigenComp = new EigenDecomposition(T);
        final double[] eigenvals = eigenComp.getRealEigenvalues();
        eigenvecs = eigenComp.getV();
        final int minId = MatrixFunctions.argmin(MatrixFunctions.abs(eigenvals));
        final double[] eigenvecsData = eigenvecs.getColumn(minId);
        eigenvecs = MatrixUtils.createColumnRealMatrix(eigenvecsData);
    }

    // System.out.println("eigenvecs:");
    // test.printMatrix(eigenvecs);

    // calculate null space projection
    final RealMatrix proj = ((I.subtract(M)).multiply(basisvecs)).multiply(eigenvecs);

    return proj;
}

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From source file:org.orekit.frames.TransformTest.java

@Test
public void testLinear() {

    RandomGenerator random = new Well19937a(0x14f6411217b148d8l);
    for (int n = 0; n < 100; ++n) {
        Transform t = randomTransform(random);

        // build an equivalent linear transform by extracting raw translation/rotation
        RealMatrix linearA = MatrixUtils.createRealMatrix(3, 4);
        linearA.setSubMatrix(t.getRotation().getMatrix(), 0, 0);
        Vector3D rt = t.getRotation().applyTo(t.getTranslation());
        linearA.setEntry(0, 3, rt.getX());
        linearA.setEntry(1, 3, rt.getY());
        linearA.setEntry(2, 3, rt.getZ());

        // build an equivalent linear transform by observing transformed points
        RealMatrix linearB = MatrixUtils.createRealMatrix(3, 4);
        Vector3D p0 = t.transformPosition(Vector3D.ZERO);
        Vector3D pI = t.transformPosition(Vector3D.PLUS_I).subtract(p0);
        Vector3D pJ = t.transformPosition(Vector3D.PLUS_J).subtract(p0);
        Vector3D pK = t.transformPosition(Vector3D.PLUS_K).subtract(p0);
        linearB.setColumn(0, new double[] { pI.getX(), pI.getY(), pI.getZ() });
        linearB.setColumn(1, new double[] { pJ.getX(), pJ.getY(), pJ.getZ() });
        linearB.setColumn(2, new double[] { pK.getX(), pK.getY(), pK.getZ() });
        linearB.setColumn(3, new double[] { p0.getX(), p0.getY(), p0.getZ() });

        // both linear transforms should be equal
        Assert.assertEquals(0.0, linearB.subtract(linearA).getNorm(), 1.0e-15 * linearA.getNorm());

        for (int i = 0; i < 100; ++i) {
            Vector3D p = randomVector(1.0e3, random);
            Vector3D q = t.transformPosition(p);

            double[] qA = linearA.operate(new double[] { p.getX(), p.getY(), p.getZ(), 1.0 });
            Assert.assertEquals(q.getX(), qA[0], 1.0e-13 * p.getNorm());
            Assert.assertEquals(q.getY(), qA[1], 1.0e-13 * p.getNorm());
            Assert.assertEquals(q.getZ(), qA[2], 1.0e-13 * p.getNorm());

            double[] qB = linearB.operate(new double[] { p.getX(), p.getY(), p.getZ(), 1.0 });
            Assert.assertEquals(q.getX(), qB[0], 1.0e-10 * p.getNorm());
            Assert.assertEquals(q.getY(), qB[1], 1.0e-10 * p.getNorm());
            Assert.assertEquals(q.getZ(), qB[2], 1.0e-10 * p.getNorm());

        }//  w ww. j a v  a2 s . c  om

    }

}

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