Examples of org.apache.commons.math3.linear.RealVector.toArray()

Class org.apache.commons.math3.linear.RealVector

Examples of org.apache.commons.math3.linear.RealVector.toArray()

org.apache.commons.math3.linear.RealVector.toArray()
Convert the vector to an array of {@code double}s. The array is independent from this vector data: the elements are copied. @return an array containing a copy of the vector elements.

        }
        int zIndex = (getNumObjectiveFunctions() == 1) ? 0 : 1;
        matrix.setEntry(zIndex, zIndex, maximize ? 1 : -1);
        RealVector objectiveCoefficients =
            maximize ? f.getCoefficients().mapMultiply(-1) : f.getCoefficients();
        copyArray(objectiveCoefficients.toArray(), matrix.getDataRef()[zIndex]);
        matrix.setEntry(zIndex, width - 1,
            maximize ? f.getConstantTerm() : -1 * f.getConstantTerm());


        if (!restrictToNonNegative) {
            matrix.setEntry(zIndex, getSlackVariableOffset() - 1,

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                .weight(new DiagonalMatrix(new double[]{16, 4}))
                .model(new MultivariateJacobianFunction() {
                    public Pair<RealVector, RealMatrix> value(RealVector actualPoint) {
                        //verify correct values passed in
                        Assert.assertArrayEquals(
                                point.toArray(), actualPoint.toArray(), Precision.EPSILON);
                        //return values
                        return new Pair<RealVector, RealMatrix>(
                                new ArrayRealVector(new double[]{3, 4}),
                                MatrixUtils.createRealMatrix(new double[][]{{5, 6}, {7, 8}})
                        );

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        RealVector residuals = evaluation.getResiduals();
        RealMatrix jacobian = evaluation.getJacobian();


        //verify
        Assert.assertArrayEquals(evaluation.getPoint().toArray(), point.toArray(), 0);
        Assert.assertArrayEquals(new double[]{-12, -8}, residuals.toArray(), Precision.EPSILON);
        TestUtils.assertEquals(
                "jacobian",
                jacobian,
                MatrixUtils.createRealMatrix(new double[][]{{20, 24},{14, 16}}),
                Precision.EPSILON);

View Full Code Here

        }
        int zIndex = (getNumObjectiveFunctions() == 1) ? 0 : 1;
        matrix.setEntry(zIndex, zIndex, maximize ? 1 : -1);
        RealVector objectiveCoefficients =
            maximize ? f.getCoefficients().mapMultiply(-1) : f.getCoefficients();
        copyArray(objectiveCoefficients.toArray(), matrix.getDataRef()[zIndex]);
        matrix.setEntry(zIndex, width - 1,
            maximize ? f.getConstantTerm() : -1 * f.getConstantTerm());


        if (!restrictToNonNegative) {
            matrix.setEntry(zIndex, getSlackVariableOffset() - 1,

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    /**
     * {@inheritDoc}
     */
    public double[] estimateRegressionParameters() {
        RealVector b = calculateBeta();
        return b.toArray();
    }


    /**
     * {@inheritDoc}
     */

View Full Code Here

     * {@inheritDoc}
     */
    public double[] estimateResiduals() {
        RealVector b = calculateBeta();
        RealVector e = yVector.subtract(xMatrix.operate(b));
        return e.toArray();
    }


    /**
     * {@inheritDoc}
     */

View Full Code Here

        }
        int zIndex = (getNumObjectiveFunctions() == 1) ? 0 : 1;
        matrix.setEntry(zIndex, zIndex, maximize ? 1 : -1);
        RealVector objectiveCoefficients =
            maximize ? f.getCoefficients().mapMultiply(-1) : f.getCoefficients();
        copyArray(objectiveCoefficients.toArray(), matrix.getDataRef()[zIndex]);
        matrix.setEntry(zIndex, width - 1,
            maximize ? f.getConstantTerm() : -1 * f.getConstantTerm());


        if (!restrictToNonNegative) {
            matrix.setEntry(zIndex, getSlackVariableOffset() - 1,

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        }
        int zIndex = (getNumObjectiveFunctions() == 1) ? 0 : 1;
        matrix.setEntry(zIndex, zIndex, maximize ? 1 : -1);
        RealVector objectiveCoefficients =
            maximize ? f.getCoefficients().mapMultiply(-1) : f.getCoefficients();
        copyArray(objectiveCoefficients.toArray(), matrix.getDataRef()[zIndex]);
        matrix.setEntry(zIndex, width - 1,
            maximize ? f.getConstantTerm() : -1 * f.getConstantTerm());


        if (!restrictToNonNegative) {
            matrix.setEntry(zIndex, getSlackVariableOffset() - 1,

View Full Code Here

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