StatisticsAssert.java

/*
 * Java Genetic Algorithm Library (@__identifier__@).
 * Copyright (c) @__year__@ Franz Wilhelmstötter
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *      http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 *
 * Author:
 *    Franz Wilhelmstötter (franz.wilhelmstoetter@gmx.at)
 */
package org.jenetics.stat;

import static java.lang.String.format;

import java.util.Arrays;

import org.apache.commons.math3.distribution.ChiSquaredDistribution;
import org.apache.commons.math3.stat.inference.ChiSquareTest;
import org.testng.Assert;

import org.jenetics.internal.util.require;

/**
 * @author <a href="mailto:franz.wilhelmstoetter@gmx.at">Franz Wilhelmstötter</a>
 */
public final class StatisticsAssert {
	private StatisticsAssert() {require.noInstance();}

	public static <C extends Comparable<? super C>> void assertDistribution(
		final Histogram<C> histogram,
		final Distribution<C> distribution
	) {
		final double χ2 =  histogram.χ2(distribution.getCDF());
		final int degreeOfFreedom = histogram.length();
		assert (degreeOfFreedom > 0);

		final double maxChi = chi(0.999, degreeOfFreedom)*2;

		if (χ2 > maxChi) {
			System.out.println(format(
				"The histogram %s doesn't follow the distribution %s. \n" +
					"χ2 must be smaller than %f but was %f",
				histogram, distribution,
				maxChi, χ2
			));
		}

		Assert.assertTrue(
				χ2 <= maxChi,
				format(
					"The histogram %s doesn't follow the distribution %s. \n" +
						"χ2 must be smaller than %f but was %f",
					histogram, distribution,
					maxChi, χ2
				)
			);
	}

	public static <C extends Comparable<? super C>> void assertDistribution(
		final Histogram<C> distribution,
		final double[] expected
	) {
		assertDistribution(distribution, expected, 0.05);
	}

	public static <C extends Comparable<? super C>> void assertDistribution(
		final Histogram<C> distribution,
		final double[] expected,
		final double alpha,
		final double safety
	) {
		final double[] exp = Arrays.stream(expected)
			.map(v -> Math.max(v, Double.MIN_VALUE))
			.toArray();

		final long[] dist = distribution.getHistogram();

		final double χ2 = new ChiSquareTest().chiSquare(exp, dist);
		final double max_χ2 = chi(1 - alpha, distribution.length());
		final boolean reject = χ2 > max_χ2*safety;
		//final boolean reject = new ChiSquareTest().chiSquareTest(exp, dist, alpha);

		Assert.assertFalse(
			reject,
			format(
				"The histogram doesn't follow the given distribution." +
					"χ2 must be smaller than %f but was %f",
				max_χ2, χ2
			)
		);
	}

	public static <C extends Comparable<? super C>> void assertDistribution(
		final Histogram<C> distribution,
		final double[] expected,
		final double alpha
	) {
		assertDistribution(distribution, expected, alpha, 1.75);
	}

	private static double chi(final double p, final int degreeOfFreedom) {
		return new ChiSquaredDistribution(degreeOfFreedom)
			.inverseCumulativeProbability(p);
	}

	public static <C extends Comparable<? super C>> void assertUniformDistribution(
		final Histogram<C> histogram
	) {
		final double[] expected = dist.uniform(histogram.length());
		assertDistribution(histogram, expected);
	}

}