//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
   
   //https://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.hipparchus.stat.descriptive.vector;
  
  import static org.junit.Assert.assertEquals;
  import static org.junit.Assert.fail;
  
  import org.hipparchus.UnitTestUtils;
  import org.hipparchus.exception.MathIllegalArgumentException;
  import org.hipparchus.linear.RealMatrix;
  import org.junit.Test;
  
  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]);
              fail("an exception should have been thrown");
          } catch (MathIllegalArgumentException dme) {
              assertEquals(5, ((Integer) dme.getParts()[0]).intValue());
              assertEquals(8, ((Integer) dme.getParts()[1]).intValue());
          }
      }
  
      @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();
          assertEquals( 2.0, c.getEntry(0, 0), 1.0e-12);
          assertEquals(-2.0, c.getEntry(1, 0), 1.0e-12);
          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]);
          }
  
          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) {
                  assertEquals(refC[i][j], c.getEntry(i, j), 1.0e-12);
              }
          }
  
      }
  
      @Test
      public void testSerial(){
          VectorialCovariance stat = new VectorialCovariance(points[0].length, true);
          assertEquals(stat, UnitTestUtils.serializeAndRecover(stat));
      }
  }