MATH-1636: Remove "isSupportedConnected" (as per STATISTICS-48).
This commit is contained in:
Gilles Sadowski
parent
142dcaa921
commit
226c1fc638
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@ -164,31 +164,10 @@ public abstract class AbstractRealDistribution
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}
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};
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double x = UnivariateSolverUtils.solve(toSolve,
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lowerBound,
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upperBound,
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getSolverAbsoluteAccuracy());
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if (!isSupportConnected()) {
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/* Test for plateau. */
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final double dx = getSolverAbsoluteAccuracy();
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if (x - dx >= getSupportLowerBound()) {
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double px = cumulativeProbability(x);
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if (cumulativeProbability(x - dx) == px) {
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upperBound = x;
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while (upperBound - lowerBound > dx) {
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final double midPoint = 0.5 * (lowerBound + upperBound);
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if (cumulativeProbability(midPoint) < px) {
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lowerBound = midPoint;
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} else {
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upperBound = midPoint;
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}
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}
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return upperBound;
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}
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}
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}
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return x;
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return UnivariateSolverUtils.solve(toSolve,
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lowerBound,
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upperBound,
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getSolverAbsoluteAccuracy());
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}
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/**
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@ -465,15 +465,6 @@ public final class EmpiricalDistribution extends AbstractRealDistribution
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return max;
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}
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/**
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* {@inheritDoc}
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* @since 3.1
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*/
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@Override
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public boolean isSupportConnected() {
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return true;
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}
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/**
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* The probability of bin i.
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*
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@ -620,12 +611,6 @@ public final class EmpiricalDistribution extends AbstractRealDistribution
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return value;
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}
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/** {@inheritDoc} */
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@Override
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public boolean isSupportConnected() {
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return true;
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}
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/**
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* {@inheritDoc}
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*
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@ -215,18 +215,6 @@ public class EnumeratedIntegerDistribution extends AbstractIntegerDistribution {
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return max;
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}
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/**
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* {@inheritDoc}
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*
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* The support of this distribution is connected.
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*
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* @return {@code true}
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*/
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@Override
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public boolean isSupportConnected() {
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return true;
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}
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/**
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* {@inheritDoc}
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*
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@ -251,18 +251,6 @@ public class EnumeratedRealDistribution
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return max;
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}
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/**
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* {@inheritDoc}
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*
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* The support of this distribution is connected.
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*
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* @return {@code true}
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*/
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@Override
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public boolean isSupportConnected() {
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return true;
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}
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/** {@inheritDoc} */
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@Override
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public ContinuousDistribution.Sampler createSampler(final UniformRandomProvider rng) {
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@ -120,10 +120,5 @@ public class AbstractIntegerDistributionTest {
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public int getSupportUpperBound() {
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return 6;
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}
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@Override
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public final boolean isSupportConnected() {
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return true;
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}
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}
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}
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@ -1,201 +0,0 @@
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/*
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* Licensed to the Apache Software Foundation (ASF) under one or more
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* contributor license agreements. See the NOTICE file distributed with
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* this work for additional information regarding copyright ownership.
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* The ASF licenses this file to You under the Apache License, Version 2.0
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* (the "License"); you may not use this file except in compliance with
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* the License. You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package org.apache.commons.math4.legacy.distribution;
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import org.apache.commons.math4.legacy.analysis.UnivariateFunction;
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import org.apache.commons.math4.legacy.analysis.integration.RombergIntegrator;
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import org.apache.commons.math4.legacy.analysis.integration.UnivariateIntegrator;
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import org.apache.commons.math4.legacy.exception.OutOfRangeException;
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import org.junit.Assert;
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import org.junit.Test;
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/** Various tests related to MATH-699. */
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public class AbstractRealDistributionTest {
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@Test
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public void testContinuous() {
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final double x0 = 0.0;
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final double x1 = 1.0;
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final double x2 = 2.0;
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final double x3 = 3.0;
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final double p12 = 0.5;
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final AbstractRealDistribution distribution;
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distribution = new AbstractRealDistribution() {
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private static final long serialVersionUID = 1L;
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@Override
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public double cumulativeProbability(final double x) {
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if ((x < x0) || (x > x3)) {
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throw new OutOfRangeException(x, x0, x3);
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}
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if (x <= x1) {
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return p12 * (x - x0) / (x1 - x0);
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} else if (x <= x2) {
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return p12;
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} else if (x <= x3) {
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return p12 + (1.0 - p12) * (x - x2) / (x3 - x2);
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}
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return 0.0;
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}
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@Override
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public double density(final double x) {
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if ((x < x0) || (x > x3)) {
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throw new OutOfRangeException(x, x0, x3);
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}
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if (x <= x1) {
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return p12 / (x1 - x0);
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} else if (x <= x2) {
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return 0.0;
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} else if (x <= x3) {
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return (1.0 - p12) / (x3 - x2);
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}
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return 0.0;
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}
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@Override
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public double getMean() {
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return ((x0 + x1) * p12 + (x2 + x3) * (1.0 - p12)) / 2.0;
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}
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@Override
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public double getVariance() {
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final double meanX = getMean();
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final double meanX2;
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meanX2 = ((x0 * x0 + x0 * x1 + x1 * x1) * p12 + (x2 * x2 + x2
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* x3 + x3 * x3)
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* (1.0 - p12)) / 3.0;
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return meanX2 - meanX * meanX;
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}
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@Override
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public double getSupportLowerBound() {
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return x0;
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}
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@Override
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public double getSupportUpperBound() {
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return x3;
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}
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@Override
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public boolean isSupportConnected() {
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return false;
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}
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};
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final double expected = x1;
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final double actual = distribution.inverseCumulativeProbability(p12);
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Assert.assertEquals("", expected, actual,
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distribution.getSolverAbsoluteAccuracy());
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}
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@Test
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public void testDiscontinuous() {
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final double x0 = 0.0;
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final double x1 = 0.25;
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final double x2 = 0.5;
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final double x3 = 0.75;
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final double x4 = 1.0;
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final double p12 = 1.0 / 3.0;
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final double p23 = 2.0 / 3.0;
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final AbstractRealDistribution distribution;
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distribution = new AbstractRealDistribution() {
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private static final long serialVersionUID = 1L;
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@Override
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public double cumulativeProbability(final double x) {
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if ((x < x0) || (x > x4)) {
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throw new OutOfRangeException(x, x0, x4);
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}
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if (x <= x1) {
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return p12 * (x - x0) / (x1 - x0);
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} else if (x <= x2) {
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return p12;
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} else if (x <= x3) {
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return p23;
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} else {
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return (1.0 - p23) * (x - x3) / (x4 - x3) + p23;
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}
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}
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@Override
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public double density(final double x) {
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if ((x < x0) || (x > x4)) {
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throw new OutOfRangeException(x, x0, x4);
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}
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if (x <= x1) {
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return p12 / (x1 - x0);
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} else if (x <= x2) {
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return 0.0;
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} else if (x <= x3) {
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return 0.0;
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} else {
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return (1.0 - p23) / (x4 - x3);
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}
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}
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@Override
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public double getMean() {
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final UnivariateFunction f = new UnivariateFunction() {
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@Override
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public double value(final double x) {
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return x * density(x);
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}
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};
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final UnivariateIntegrator integrator = new RombergIntegrator();
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return integrator.integrate(Integer.MAX_VALUE, f, x0, x4);
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}
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@Override
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public double getVariance() {
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final double meanX = getMean();
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final UnivariateFunction f = new UnivariateFunction() {
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@Override
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public double value(final double x) {
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return x * x * density(x);
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}
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};
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final UnivariateIntegrator integrator = new RombergIntegrator();
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final double meanX2 = integrator.integrate(Integer.MAX_VALUE,
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f, x0, x4);
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return meanX2 - meanX * meanX;
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}
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@Override
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public double getSupportLowerBound() {
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return x0;
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}
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@Override
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public double getSupportUpperBound() {
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return x4;
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}
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@Override
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public boolean isSupportConnected() {
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return false;
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}
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};
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final double expected = x2;
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final double actual = distribution.inverseCumulativeProbability(p23);
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Assert.assertEquals("", expected, actual,
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distribution.getSolverAbsoluteAccuracy());
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}
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}
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@ -142,14 +142,6 @@ public class EnumeratedIntegerDistributionTest {
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Assert.assertEquals(7, testDistribution.getSupportUpperBound());
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}
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/**
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* Tests if the distribution returns properly that the support is connected.
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*/
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@Test
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public void testIsSupportConnected() {
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Assert.assertTrue(testDistribution.isSupportConnected());
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}
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/**
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* Tests sampling.
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*/
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@ -162,14 +162,6 @@ public class EnumeratedRealDistributionTest {
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Assert.assertEquals(7, testDistribution.getSupportUpperBound(), 0);
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}
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/**
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* Tests if the distribution returns properly that the support is connected.
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*/
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@Test
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public void testIsSupportConnected() {
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Assert.assertTrue(testDistribution.isSupportConnected());
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}
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/**
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* Tests sampling.
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*/
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