Package org.apache.commons.math3.analysis.differentiation

Examples of org.apache.commons.math3.analysis.differentiation.UnivariateDifferentiableFunction

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     * @deprecated this conversion method is temporary in version 3.1, as the {@link
     * DifferentiableUnivariateFunction} interface itself is deprecated
     */
    @Deprecated
    public static UnivariateDifferentiableFunction toUnivariateDifferential(final DifferentiableUnivariateFunction f) {
        return new UnivariateDifferentiableFunction() {

            /** {@inheritDoc} */
            public double value(final double x) {
                return f.value(x);
            }
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     * @param f List of functions.
     * @return the composite function.
     * @since 3.1
     */
    public static UnivariateDifferentiableFunction compose(final UnivariateDifferentiableFunction ... f) {
        return new UnivariateDifferentiableFunction() {

            /** {@inheritDoc} */
            public double value(final double t) {
                double r = t;
                for (int i = f.length - 1; i >= 0; i--) {
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     * @param f List of functions.
     * @return a function that computes the sum of the functions.
     * @since 3.1
     */
    public static UnivariateDifferentiableFunction add(final UnivariateDifferentiableFunction ... f) {
        return new UnivariateDifferentiableFunction() {

            /** {@inheritDoc} */
            public double value(final double t) {
                double r = f[0].value(t);
                for (int i = 1; i < f.length; i++) {
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     * @param f List of functions.
     * @return a function that computes the product of the functions.
     * @since 3.1
     */
    public static UnivariateDifferentiableFunction multiply(final UnivariateDifferentiableFunction ... f) {
        return new UnivariateDifferentiableFunction() {

            /** {@inheritDoc} */
            public double value(final double t) {
                double r = f[0].value(t);
                for (int i = 1; i < f.length; i++) {
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     * @deprecated this conversion method is temporary in version 3.1, as the {@link
     * DifferentiableUnivariateFunction} interface itself is deprecated
     */
    @Deprecated
    public static UnivariateDifferentiableFunction toUnivariateDifferential(final DifferentiableUnivariateFunction f) {
        return new UnivariateDifferentiableFunction() {

            /** {@inheritDoc} */
            public double value(final double x) {
                return f.value(x);
            }
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        final double lo = 2;
        final double hi = 3;
        final Logit f = new Logit(lo, hi);
        final Sigmoid g = new Sigmoid(lo, hi);
        RandomGenerator random = new Well1024a(0x49914cdd9f0b8db5l);
        final UnivariateDifferentiableFunction id = FunctionUtils.compose((UnivariateDifferentiableFunction) g,
                                                                (UnivariateDifferentiableFunction) f);

        for (int i = 0; i < 10; i++) {
            final double x = lo + random.nextDouble() * (hi - lo);
            Assert.assertEquals(x, id.value(new DerivativeStructure(1, 1, 0, x)).getValue(), EPS);
        }

        Assert.assertEquals(lo, id.value(new DerivativeStructure(1, 1, 0, lo)).getValue(), EPS);
        Assert.assertEquals(hi, id.value(new DerivativeStructure(1, 1, 0, hi)).getValue(), EPS);
    }
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        final double lo = 2;
        final double hi = 3;
        final Logit f = new Logit(lo, hi);
        final Sigmoid g = new Sigmoid(lo, hi);
        RandomGenerator random = new Well1024a(0x96885e9c1f81cea5l);
        final UnivariateDifferentiableFunction id =
                FunctionUtils.compose((UnivariateDifferentiableFunction) g, (UnivariateDifferentiableFunction) f);
        for (int maxOrder = 0; maxOrder < 6; ++maxOrder) {
            double max = 0;
            for (int i = 0; i < 10; i++) {
                final double x = lo + random.nextDouble() * (hi - lo);
                final DerivativeStructure dsX = new DerivativeStructure(1, maxOrder, 0, x);
                max = FastMath.max(max, FastMath.abs(dsX.getPartialDerivative(maxOrder) -
                                                     id.value(dsX).getPartialDerivative(maxOrder)));
                Assert.assertEquals(dsX.getPartialDerivative(maxOrder),
                                    id.value(dsX).getPartialDerivative(maxOrder),
                                    epsilon[maxOrder]);
            }

            // each function evaluates correctly near boundaries,
            // but combination leads to NaN as some intermediate point is infinite
            final DerivativeStructure dsLo = new DerivativeStructure(1, maxOrder, 0, lo);
            if (maxOrder == 0) {
                Assert.assertTrue(Double.isInfinite(f.value(dsLo).getPartialDerivative(maxOrder)));
                Assert.assertEquals(lo, id.value(dsLo).getPartialDerivative(maxOrder), epsilon[maxOrder]);
            } else if (maxOrder == 1) {
                Assert.assertTrue(Double.isInfinite(f.value(dsLo).getPartialDerivative(maxOrder)));
                Assert.assertTrue(Double.isNaN(id.value(dsLo).getPartialDerivative(maxOrder)));
            } else {
                Assert.assertTrue(Double.isNaN(f.value(dsLo).getPartialDerivative(maxOrder)));
                Assert.assertTrue(Double.isNaN(id.value(dsLo).getPartialDerivative(maxOrder)));
            }

            final DerivativeStructure dsHi = new DerivativeStructure(1, maxOrder, 0, hi);
            if (maxOrder == 0) {
                Assert.assertTrue(Double.isInfinite(f.value(dsHi).getPartialDerivative(maxOrder)));
                Assert.assertEquals(hi, id.value(dsHi).getPartialDerivative(maxOrder), epsilon[maxOrder]);
            } else if (maxOrder == 1) {
                Assert.assertTrue(Double.isInfinite(f.value(dsHi).getPartialDerivative(maxOrder)));
                Assert.assertTrue(Double.isNaN(id.value(dsHi).getPartialDerivative(maxOrder)));
            } else {
                Assert.assertTrue(Double.isNaN(f.value(dsHi).getPartialDerivative(maxOrder)));
                Assert.assertTrue(Double.isNaN(id.value(dsHi).getPartialDerivative(maxOrder)));
            }

        }
    }
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    /**
     *
     */
    @Test
    public void testQuinticZero() {
        final UnivariateDifferentiableFunction q = new QuinticFunction();
        DifferentiableUnivariateFunction f = new DifferentiableUnivariateFunction() {

            public double value(double x) {
                return q.value(x);
            }

            public UnivariateFunction derivative() {
                return new UnivariateFunction() {
                    public double value(double x) {
                        return q.value(new DerivativeStructure(1, 1, 0, x)).getPartialDerivative(1);
                    }
                };
            }

        };
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    /**
     *
     */
    @Test
    public void testSinZero() {
        UnivariateDifferentiableFunction f = new Sin();
        double result;

        NewtonRaphsonSolver solver = new NewtonRaphsonSolver();
        result = solver.solve(100, f, 3, 4);
        Assert.assertEquals(result, FastMath.PI, solver.getAbsoluteAccuracy());
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    /**
     *
     */
    @Test
    public void testQuinticZero() {
        final UnivariateDifferentiableFunction f = new QuinticFunction();
        double result;

        NewtonRaphsonSolver solver = new NewtonRaphsonSolver();
        result = solver.solve(100, f, -0.2, 0.2);
        Assert.assertEquals(result, 0, solver.getAbsoluteAccuracy());
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Related Classes of org.apache.commons.math3.analysis.differentiation.UnivariateDifferentiableFunction

  • 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.LogitTest
  • org.apache.commons.math3.analysis.function.Sin
  • org.apache.commons.math3.analysis.function.Sinc
  • org.apache.commons.math3.analysis.function.SqrtTest
  • org.apache.commons.math3.analysis.FunctionUtils
  • org.apache.commons.math3.analysis.FunctionUtilsTest
  • org.apache.commons.math3.analysis.MultivariateFunction
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