Package org.apache.commons.math3.distribution

Examples of org.apache.commons.math3.distribution.RealDistribution

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        for (int i = 0; i < testPoints.length; i++) {
            final int bin = findBin(testPoints[i]);
            final double lower = bin == 0 ? empiricalDistribution.getSupportLowerBound() :
                binBounds[bin - 1];
            final double upper = binBounds[bin];
            final RealDistribution kernel = findKernel(lower, upper);
            final double withinBinKernelMass = kernel.cumulativeProbability(lower, upper);
            final double density = kernel.density(testPoints[i]);
            densityValues[i] = density * (bin == 0 ? firstBinMass : binMass) / withinBinKernelMass;  
        }
        return densityValues;
    }
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     * across no more than 3 bin boundaries.
     */
    @Override
    @Test
    public void testDensityIntegrals() {
        final RealDistribution distribution = makeDistribution();
        final double tol = 1.0e-9;
        final BaseAbstractUnivariateIntegrator integrator =
            new IterativeLegendreGaussIntegrator(5, 1.0e-12, 1.0e-10);
        final UnivariateFunction d = new UnivariateFunction() {
            public double value(double x) {
                return distribution.density(x);
            }
        };
        final double[] lower = {0, 5, 1000, 5001, 9995};
        final double[] upper = {5, 12, 1030, 5010, 10000};
        for (int i = 1; i < 5; i++) {
            Assert.assertEquals(
                    distribution.cumulativeProbability(
                            lower[i], upper[i]),
                            integrator.integrate(
                                    1000000, // Triangle integrals are very slow to converge
                                    d, lower[i], upper[i]), tol);
        }
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        final UnivariateFunction h2 = new HarmonicOscillator(radius, omega, 0.5 * Math.PI);

        final UnivariateFunction f1 = FunctionUtils.add(h1, new Constant(centre[0]));
        final UnivariateFunction f2 = FunctionUtils.add(h2, new Constant(centre[1]));

        final RealDistribution u
            = new UniformRealDistribution(random, -0.05 * radius, 0.05 * radius);

        return new FeatureInitializer[] {
            FeatureInitializerFactory.randomize(u, FeatureInitializerFactory.function(f1, 0, 1)),
            FeatureInitializerFactory.randomize(u, FeatureInitializerFactory.function(f2, 0, 1))
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*/
@Deprecated
public class PolynomialFitterTest {
    @Test
    public void testFit() {
        final RealDistribution rng = new UniformRealDistribution(-100, 100);
        rng.reseedRandomGenerator(64925784252L);

        final LevenbergMarquardtOptimizer optim = new LevenbergMarquardtOptimizer();
        final PolynomialFitter fitter = new PolynomialFitter(optim);
        final double[] coeff = { 12.9, -3.4, 2.1 }; // 12.9 - 3.4 x + 2.1 x^2
        final PolynomialFunction f = new PolynomialFunction(coeff);

        // Collect data from a known polynomial.
        for (int i = 0; i < 100; i++) {
            final double x = rng.sample();
            fitter.addObservedPoint(x, f.value(x));
        }

        // Start fit from initial guesses that are far from the optimal values.
        final double[] best = fitter.fit(new double[] { -1e-20, 3e15, -5e25 });
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* Test for class {@link PolynomialCurveFitter}.
*/
public class PolynomialCurveFitterTest {
    @Test
    public void testFit() {
        final RealDistribution rng = new UniformRealDistribution(-100, 100);
        rng.reseedRandomGenerator(64925784252L);

        final double[] coeff = { 12.9, -3.4, 2.1 }; // 12.9 - 3.4 x + 2.1 x^2
        final PolynomialFunction f = new PolynomialFunction(coeff);

        // Collect data from a known polynomial.
        final WeightedObservedPoints obs = new WeightedObservedPoints();
        for (int i = 0; i < 100; i++) {
            final double x = rng.sample();
            obs.add(x, f.value(x));
        }

        // Start fit from initial guesses that are far from the optimal values.
        final PolynomialCurveFitter fitter
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    public double density(double x) {
        if (x < min || x > max) {
            return 0d;
        }
        final int binIndex = findBin(x);
        final RealDistribution kernel = getKernel(binStats.get(binIndex));
        return kernel.density(x) * pB(binIndex) / kB(binIndex);
    }
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        final double pBminus = pBminus(binIndex);
        final double pB = pB(binIndex);
        final double[] binBounds = getUpperBounds();
        final double kB = kB(binIndex);
        final double lower = binIndex == 0 ? min : binBounds[binIndex - 1];
        final RealDistribution kernel = k(x);
        final double withinBinCum =
            (kernel.cumulativeProbability(x) -  kernel.cumulativeProbability(lower)) / kB;
        return pBminus + pB * withinBinCum;
    }
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        int i = 0;
        while (cumBinP(i) < p) {
            i++;
        }

        final RealDistribution kernel = getKernel(binStats.get(i));
        final double kB = kB(i);
        final double[] binBounds = getUpperBounds();
        final double lower = i == 0 ? min : binBounds[i - 1];
        final double kBminus = kernel.cumulativeProbability(lower);
        final double pB = pB(i);
        final double pBminus = pBminus(i);
        final double pCrit = p - pBminus;
        if (pCrit <= 0) {
            return lower;
        }
        return kernel.inverseCumulativeProbability(kBminus + pCrit * kB / pB);
    }
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     * upper and lower endpoints of bin i
     */
    @SuppressWarnings("deprecation")
    private double kB(int i) {
        final double[] binBounds = getUpperBounds();
        final RealDistribution kernel = getKernel(binStats.get(i));
        return i == 0 ? kernel.cumulativeProbability(min, binBounds[0]) :
            kernel.cumulativeProbability(binBounds[i - 1], binBounds[i]);
    }
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        // Create two rings lying in xy-plane.
        final UnitSphereRandomVectorGenerator unit
            = new UnitSphereRandomVectorGenerator(2);

        final RealDistribution radius1
            = new UniformRealDistribution(radiusRing1 - halfWidthRing1,
                                          radiusRing1 + halfWidthRing1);
        final RealDistribution widthRing1
            = new UniformRealDistribution(-halfWidthRing1, halfWidthRing1);

        for (int i = 0; i < numPointsRing1; i++) {
            final double[] v = unit.nextVector();
            final double r = radius1.sample();
            // First ring is in the xy-plane, centered at (0, 0, 0).
            firstRing[i] = new Vector3D(v[0] * r,
                                        v[1] * r,
                                        widthRing1.sample());
        }

        final RealDistribution radius2
            = new UniformRealDistribution(radiusRing2 - halfWidthRing2,
                                          radiusRing2 + halfWidthRing2);
        final RealDistribution widthRing2
            = new UniformRealDistribution(-halfWidthRing2, halfWidthRing2);

        for (int i = 0; i < numPointsRing2; i++) {
            final double[] v = unit.nextVector();
            final double r = radius2.sample();
            // Second ring is in the xz-plane, centered at (radiusRing1, 0, 0).
            secondRing[i] = new Vector3D(radiusRing1 + v[0] * r,
                                         widthRing2.sample(),
                                         v[1] * r);
        }

        // Move first and second rings into position.
        final Rotation rot = new Rotation(Vector3D.PLUS_K,
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Related Classes of org.apache.commons.math3.distribution.RealDistribution

  • 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.MultivariateFunction
  • org.apache.commons.math3.analysis.QuinticFunction
  • org.apache.commons.math3.analysis.solvers.BrentSolver
  • org.apache.commons.math3.analysis.UnivariateFunction
  • org.apache.commons.math3.complex.Complex
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