Package org.apache.commons.math3.analysis.function

Examples of org.apache.commons.math3.analysis.function.Cos

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public class LegendreHighPrecisionTest {
    private static GaussIntegratorFactory factory = new GaussIntegratorFactory();

    @Test
    public void testCos() {
        final UnivariateFunction cos = new Cos();

        final GaussIntegrator integrator = factory.legendreHighPrecision(7, 0, Math.PI / 2);
        final double s = integrator.integrate(cos);
        // System.out.println("s=" + s + " e=" + 1);
        Assert.assertEquals(1, s, Math.ulp(1d));
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        final double a = 1.2345678;
        Assert.assertEquals(8 * a, FunctionUtils.multiply(c, id, id).value(new DerivativeStructure(1, 1, 0, a)).getPartialDerivative(1), EPS);

        UnivariateDifferentiableFunction inv = new Inverse();
        UnivariateDifferentiableFunction pow = new Power(2.5);
        UnivariateDifferentiableFunction cos = new Cos();
        Assert.assertEquals(1.5 * Math.sqrt(a) * Math.cos(a) - Math.pow(a, 1.5) * Math.sin(a),
                            FunctionUtils.multiply(inv, pow, cos).value(new DerivativeStructure(1, 1, 0, a)).getPartialDerivative(1), EPS);

        UnivariateDifferentiableFunction cosh = new Cosh();
        Assert.assertEquals(1.5 * Math.sqrt(a) * Math.cosh(a) + Math.pow(a, 1.5) * Math.sinh(a),
 
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        v_mapTanhToSelf.mapToSelf(new Tanh());
        double[] result_mapTanhToSelf = {7.615941559557649e-01d,9.640275800758169e-01d,9.950547536867305e-01d};
        assertClose("compare vectors" ,result_mapTanhToSelf,v_mapTanhToSelf.toArray(),normTolerance);

        //octave =  cos(v1)
        RealVector v_mapCos = v1.map(new Cos());
        double[] result_mapCos = {5.403023058681398e-01d,-4.161468365471424e-01d, -9.899924966004454e-01d};
        assertClose("compare vectors" ,result_mapCos,v_mapCos.toArray(),normTolerance);

        //octave =  cos(v1)
        RealVector v_mapCosToSelf = v1.copy();
        v_mapCosToSelf.mapToSelf(new Cos());
        double[] result_mapCosToSelf = {5.403023058681398e-01d,-4.161468365471424e-01d, -9.899924966004454e-01d};
        assertClose("compare vectors" ,result_mapCosToSelf,v_mapCosToSelf.toArray(),normTolerance);

        //octave =  sin(v1)
        RealVector v_mapSin = v1.map(new Sin());
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        v_mapTanhToSelf.mapToSelf(new Tanh());
        double[] result_mapTanhToSelf = {7.615941559557649e-01d,9.640275800758169e-01d,9.950547536867305e-01d};
        assertClose("compare vectors" ,result_mapTanhToSelf,v_mapTanhToSelf.toArray(),normTolerance);

        //octave =  cos(v1)
        RealVector v_mapCos = v1.map(new Cos());
        double[] result_mapCos = {5.403023058681398e-01d,-4.161468365471424e-01d, -9.899924966004454e-01d};
        assertClose("compare vectors" ,result_mapCos,v_mapCos.toArray(),normTolerance);

        //octave =  cos(v1)
        RealVector v_mapCosToSelf = v1.copy();
        v_mapCosToSelf.mapToSelf(new Cos());
        double[] result_mapCosToSelf = {5.403023058681398e-01d,-4.161468365471424e-01d, -9.899924966004454e-01d};
        assertClose("compare vectors" ,result_mapCosToSelf,v_mapCosToSelf.toArray(),normTolerance);

        //octave =  sin(v1)
        RealVector v_mapSin = v1.map(new Sin());
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        final double a = 1.2345678;
        Assert.assertEquals(8 * a, FunctionUtils.multiply(c, id, id).derivative().value(a), EPS);

        DifferentiableUnivariateFunction inv = new Inverse();
        DifferentiableUnivariateFunction pow = new Power(2.5);
        DifferentiableUnivariateFunction cos = new Cos();
        Assert.assertEquals(1.5 * Math.sqrt(a) * Math.cos(a) - Math.pow(a, 1.5) * Math.sin(a),
                            FunctionUtils.multiply(inv, pow, cos).derivative().value(a), EPS);

        DifferentiableUnivariateFunction cosh = new Cosh();
        Assert.assertEquals(1.5 * Math.sqrt(a) * Math.cosh(a) + Math.pow(a, 1.5) * Math.sinh(a),
 
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                        final double baseRoot = forward ?
                                                solver.solve(maxIterationCount, f, ta, tb) :
                                                solver.solve(maxIterationCount, f, tb, ta);
                        final int remainingEval = maxIterationCount - solver.getEvaluations();
                        BracketedUnivariateSolver<UnivariateFunction> bracketing =
                                new PegasusSolver(solver.getRelativeAccuracy(), solver.getAbsoluteAccuracy());
                        root = forward ?
                               UnivariateSolverUtils.forceSide(remainingEval, f, bracketing,
                                                                   baseRoot, ta, tb, AllowedSolution.RIGHT_SIDE) :
                               UnivariateSolverUtils.forceSide(remainingEval, f, bracketing,
                                                                   baseRoot, tb, ta, AllowedSolution.LEFT_SIDE);
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                // tests for termination and stringent tolerances
                if (FastMath.abs(actRed) <= TWO_EPS &&
                    preRed <= TWO_EPS &&
                    ratio <= 2.0) {
                    throw new ConvergenceException(LocalizedFormats.TOO_SMALL_COST_RELATIVE_TOLERANCE,
                                                   costRelativeTolerance);
                } else if (delta <= TWO_EPS * xNorm) {
                    throw new ConvergenceException(LocalizedFormats.TOO_SMALL_PARAMETERS_RELATIVE_TOLERANCE,
                                                   parRelativeTolerance);
                } else if (maxCosine <= TWO_EPS) {
                    throw new ConvergenceException(LocalizedFormats.TOO_SMALL_ORTHOGONALITY_TOLERANCE,
                                                   orthoTolerance);
                }
            }
        }
    }
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                for (int j = k; j < nR; ++j) {
                    double aki = weightedJacobian[j][permutation[i]];
                    norm2 += aki * aki;
                }
                if (Double.isInfinite(norm2) || Double.isNaN(norm2)) {
                    throw new ConvergenceException(LocalizedFormats.UNABLE_TO_PERFORM_QR_DECOMPOSITION_ON_JACOBIAN,
                                                   nR, nC);
                }
                if (norm2 > ak2) {
                    nextColumn = i;
                    ak2        = norm2;
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     * length.
     */
    protected double[] computeResiduals(double[] objectiveValue) {
        final double[] target = getTarget();
        if (objectiveValue.length != target.length) {
            throw new DimensionMismatchException(target.length,
                                                 objectiveValue.length);
        }

        final double[] residuals = new double[target.length];
        for (int i = 0; i < target.length; i++) {
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        /** {@inheritDoc} */
        public RealVector solve(final RealVector b) {
            final int m = lTData.length;
            if (b.getDimension() != m) {
                throw new DimensionMismatchException(b.getDimension(), m);
            }

            final double[] x = b.toArray();

            // Solve LY = b
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Related Classes of org.apache.commons.math3.analysis.function.Cos

  • org.apache.commons.math3.analysis.differentiation.DerivativeStructure
  • org.apache.commons.math3.analysis.differentiation.MultivariateDifferentiableVectorFunction
  • org.apache.commons.math3.analysis.function.HarmonicOscillator
  • org.apache.commons.math3.analysis.function.Sin
  • org.apache.commons.math3.analysis.function.Sinc
  • org.apache.commons.math3.analysis.FunctionUtilsTest
  • org.apache.commons.math3.analysis.integration.gauss.LegendreHighPrecisionTest
  • org.apache.commons.math3.analysis.integration.gauss.LegendreTest
  • org.apache.commons.math3.analysis.MultivariateFunction
  • org.apache.commons.math3.analysis.QuinticFunction
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