/*
    * 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
   * limitations under the License.
   */
  
  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);
              }
          }
      }
  }