org.jenetics.stat.LongMomentStatisticsTest.java Source code

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Here is the source code for org.jenetics.stat.LongMomentStatisticsTest.java

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/*
 * Java Genetic Algorithm Library (@__identifier__@).
 * Copyright (c) @__year__@ Franz Wilhelmsttter
 *
 * 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 Wilhelmsttter (franz.wilhelmstoetter@gmx.at)
 */
package org.jenetics.stat;

import static org.jenetics.stat.LongMomentStatistics.toLongMomentStatistics;

import java.util.ArrayList;
import java.util.List;
import java.util.Random;

import org.apache.commons.math3.stat.descriptive.DescriptiveStatistics;
import org.testng.Assert;
import org.testng.annotations.DataProvider;
import org.testng.annotations.Test;

/**
 * @author <a href="mailto:franz.wilhelmstoetter@gmx.at">Franz Wilhelmsttter</a>
 */
public class LongMomentStatisticsTest {

    private List<Long> numbers(final int size) {
        final Random random = new Random(123);
        final List<Long> numbers = new ArrayList<>(size);
        for (int i = 0; i < size; ++i) {
            numbers.add((long) (random.nextDouble() * 10_000));
        }

        return numbers;
    }

    @Test(dataProvider = "sampleCounts")
    public void summary(final Integer sampleCounts, final Double epsilon) {
        final List<Long> numbers = numbers(sampleCounts);

        final DescriptiveStatistics expected = new DescriptiveStatistics();
        numbers.forEach(expected::addValue);

        final LongMomentStatistics summary = numbers.stream().collect(toLongMomentStatistics(Long::longValue));

        Assert.assertEquals(summary.getCount(), numbers.size());
        assertEqualsDouble(min(summary.getMin()), expected.getMin(), 0.0);
        assertEqualsDouble(max(summary.getMax()), expected.getMax(), 0.0);
        assertEqualsDouble(summary.getSum(), expected.getSum(), epsilon);
        assertEqualsDouble(summary.getMean(), expected.getMean(), epsilon);
        assertEqualsDouble(summary.getVariance(), expected.getVariance(), epsilon);
        assertEqualsDouble(summary.getSkewness(), expected.getSkewness(), epsilon);
        assertEqualsDouble(summary.getKurtosis(), expected.getKurtosis(), epsilon);
    }

    @Test(dataProvider = "parallelSampleCounts")
    public void parallelSummary(final Integer sampleCounts, final Double epsilon) {
        final List<Long> numbers = numbers(sampleCounts);

        final DescriptiveStatistics expected = new DescriptiveStatistics();
        numbers.forEach(expected::addValue);

        final LongMomentStatistics summary = numbers.stream().collect(toLongMomentStatistics(Long::longValue));

        Assert.assertEquals(summary.getCount(), numbers.size());
        assertEqualsDouble(min(summary.getMin()), expected.getMin(), 0.0);
        assertEqualsDouble(max(summary.getMax()), expected.getMax(), 0.0);
        assertEqualsDouble(summary.getSum(), expected.getSum(), epsilon);
        assertEqualsDouble(summary.getMean(), expected.getMean(), epsilon);
        assertEqualsDouble(summary.getVariance(), expected.getVariance(), epsilon);
        assertEqualsDouble(summary.getSkewness(), expected.getSkewness(), epsilon);
        assertEqualsDouble(summary.getKurtosis(), expected.getKurtosis(), epsilon);
    }

    private static double min(final long value) {
        return value == Long.MAX_VALUE ? Double.NaN : value;
    }

    private static double max(final long value) {
        return value == Long.MIN_VALUE ? Double.NaN : value;
    }

    private static void assertEqualsDouble(final double a, final double b, final double e) {
        if (Double.isNaN(b)) {
            Assert.assertTrue(Double.isNaN(a), String.format("Expected: Double.NaN \nActual: %s", a));
        } else {
            Assert.assertEquals(a, b, e);
        }
    }

    @DataProvider(name = "sampleCounts")
    public Object[][] sampleCounts() {
        return new Object[][] { { 0, 0.0 }, { 1, 0.0 }, { 2, 0.05 }, { 3, 0.05 }, { 100, 0.05 }, { 1_000, 0.0001 },
                { 10_000, 0.00001 }, { 100_000, 0.000001 }, { 1_000_000, 0.000001 }, { 2_000_000, 0.0000005 } };
    }

    @DataProvider(name = "parallelSampleCounts")
    public Object[][] parallelSampleCounts() {
        return new Object[][] { { 0, 0.0 }, { 1, 0.0 }, { 2, 0.05 }, { 3, 0.05 }, { 100, 0.5 }, { 1_000, 0.003 },
                { 10_000, 0.00001 }, { 100_000, 0.000001 }, { 1_000_000, 0.000001 }, { 2_000_000, 0.0000005 } };
    }

}