Package org.apache.commons.math3.analysis

Examples of org.apache.commons.math3.analysis.UnivariateFunction

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    }


    @Test
    public void testInverse() {
        final UnivariateFunction inv = new Inverse();
        final UnivariateFunction log = new Log();

        final double lo = 12.34;
        final double hi = 456.78;

        final GaussIntegrator integrator = factory.legendreHighPrecision(60, lo, hi);
        final double s = integrator.integrate(inv);
        final double expected = log.value(hi) - log.value(lo);
        // System.out.println("s=" + s + " e=" + expected);
        Assert.assertEquals(expected, s, 1e-15);
    }
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        final GaussIntegrator integrator
            = new GaussIntegrator(new Pair<double[], double[]>(points, weights));

        final double val = 123.456;
        final UnivariateFunction c = new Constant(val);

        final double s = integrator.integrate(c);
        Assert.assertEquals(points.length * val, s, 0d);
    }
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public class LegendreTest {
    private static final GaussIntegratorFactory factory = new GaussIntegratorFactory();

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

        final GaussIntegrator integrator = factory.legendre(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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    }


    @Test
    public void testInverse() {
        final UnivariateFunction inv = new Inverse();
        final UnivariateFunction log = new Log();

        final double lo = 12.34;
        final double hi = 456.78;

        final GaussIntegrator integrator = factory.legendre(60, lo, hi);
        final double s = integrator.integrate(inv);
        final double expected = log.value(hi) - log.value(lo);
        // System.out.println("s=" + s + " e=" + expected);
        Assert.assertEquals(expected, s, 1e-14);
    }
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     * if the number of evaluations is exceeded.
     */
    public UnivariatePointValuePair search(final double[] startPoint,
                                           final double[] direction) {
        final int n = startPoint.length;
        final UnivariateFunction f = new UnivariateFunction() {
                public double value(double alpha) {
                    final double[] x = new double[n];
                    for (int i = 0; i < n; i++) {
                        x[i] = startPoint[i] + alpha * direction[i];
                    }
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         * @throws org.apache.commons.math3.exception.TooManyEvaluationsException
         * if the number of evaluations is exceeded.
         */
        public UnivariatePointValuePair search(final double[] p, final double[] d) {
            final int n = p.length;
            final UnivariateFunction f = new UnivariateFunction() {
                    public double value(double alpha) {
                        final double[] x = new double[n];
                        for (int i = 0; i < n; i++) {
                            x[i] = p[i] + alpha * d[i];
                        }
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    }

    @Test
    public void testTransformFunctionSizeNotAPowerOfTwo() {
        final int n = 127;
        final UnivariateFunction f = new Sin();
        final DftNormalization[] norm;
        norm = DftNormalization.values();
        final TransformType[] type;
        type = TransformType.values();
        for (int i = 0; i < norm.length; i++) {
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    }

    @Test
    public void testTransformFunctionNotStrictlyPositiveNumberOfSamples() {
        final int n = -128;
        final UnivariateFunction f = new Sin();
        final DftNormalization[] norm;
        norm = DftNormalization.values();
        final TransformType[] type;
        type = TransformType.values();
        for (int i = 0; i < norm.length; i++) {
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    }

    @Test
    public void testTransformFunctionInvalidBounds() {
        final int n = 128;
        final UnivariateFunction f = new Sin();
        final DftNormalization[] norm;
        norm = DftNormalization.values();
        final TransformType[] type;
        type = TransformType.values();
        for (int i = 0; i < norm.length; i++) {
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        }
    }

    @Test
    public void testStandardTransformFunction() {
        final UnivariateFunction f = new Sinc();
        final double min = -FastMath.PI;
        final double max = FastMath.PI;
        final DftNormalization[] norm;
        norm = DftNormalization.values();
        final TransformType[] type;
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Related Classes of org.apache.commons.math3.analysis.UnivariateFunction

  • org.apache.commons.math3.analysis.differentiation.FiniteDifferencesDifferentiatorTest
  • org.apache.commons.math3.analysis.function.GaussianTest
  • org.apache.commons.math3.analysis.function.HarmonicOscillatorTest
  • org.apache.commons.math3.analysis.function.LogisticTest
  • org.apache.commons.math3.analysis.function.LogitTest
  • org.apache.commons.math3.analysis.function.SigmoidTest
  • org.apache.commons.math3.analysis.function.Sin
  • org.apache.commons.math3.analysis.function.Sinc
  • org.apache.commons.math3.analysis.function.SincTest
  • org.apache.commons.math3.analysis.function.SqrtTest
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