commons-math-legacy/src/test/java/org/apache/commons/math4/legacy/stat/descriptive/moment/VectorialCovarianceTest.java

/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You 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
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package org.apache.commons.math4.legacy.stat.descriptive.moment;

import org.apache.commons.math4.legacy.exception.DimensionMismatchException;
import org.apache.commons.math4.legacy.linear.RealMatrix;
import org.junit.Test;
import org.junit.Assert;

public class VectorialCovarianceTest {
    private double[][] points;

    public VectorialCovarianceTest() {
        points = new double[][] {
            { 1.2, 2.3,  4.5},
            {-0.7, 2.3,  5.0},
            { 3.1, 0.0, -3.1},
            { 6.0, 1.2,  4.2},
            {-0.7, 2.3,  5.0}
        };
    }

    @Test
    public void testMismatch() {
        try {
            new VectorialCovariance(8, true).increment(new double[5]);
            Assert.fail("an exception should have been thrown");
        } catch (DimensionMismatchException dme) {
            Assert.assertEquals(5, dme.getArgument());
            Assert.assertEquals(8, dme.getDimension());
        }
    }

    @Test
    public void testSimplistic() {
        VectorialCovariance stat = new VectorialCovariance(2, true);
        stat.increment(new double[] {-1.0,  1.0});
        stat.increment(new double[] { 1.0, -1.0});
        RealMatrix c = stat.getResult();
        Assert.assertEquals( 2.0, c.getEntry(0, 0), 1.0e-12);
        Assert.assertEquals(-2.0, c.getEntry(1, 0), 1.0e-12);
        Assert.assertEquals( 2.0, c.getEntry(1, 1), 1.0e-12);
    }

    @Test
    public void testBasicStats() {

        VectorialCovariance stat = new VectorialCovariance(points[0].length, true);
        for (int i = 0; i < points.length; ++i) {
            stat.increment(points[i]);
        }

        Assert.assertEquals(points.length, stat.getN());

        RealMatrix c = stat.getResult();
        double[][] refC    = new double[][] {
                { 8.0470, -1.9195, -3.4445},
                {-1.9195,  1.0470,  3.2795},
                {-3.4445,  3.2795, 12.2070}
        };

        for (int i = 0; i < c.getRowDimension(); ++i) {
            for (int j = 0; j <= i; ++j) {
                Assert.assertEquals(refC[i][j], c.getEntry(i, j), 1.0e-12);
            }
        }

    }
}