/*
    * 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.
   */
  
  /*
   * This is not the original file distributed by the Apache Software Foundation
   * It has been modified by the Hipparchus project
   */
  package org.hipparchus.distribution.discrete;
  
  import org.hipparchus.exception.MathIllegalArgumentException;
  import org.hipparchus.exception.MathRuntimeException;
  import org.hipparchus.util.Pair;
  import org.junit.jupiter.api.Test;
  
  import java.util.HashMap;
  import java.util.List;
  import java.util.Map;
  
  import static org.junit.jupiter.api.Assertions.assertEquals;
  import static org.junit.jupiter.api.Assertions.assertNull;
  import static org.junit.jupiter.api.Assertions.assertTrue;
  import static org.junit.jupiter.api.Assertions.fail;
  
  /**
   * Test class for {@link EnumeratedIntegerDistribution}.
   */
  public class EnumeratedIntegerDistributionTest {
  
      /**
       * The distribution object used for testing.
       */
      private final EnumeratedIntegerDistribution testDistribution;
  
      /**
       * Creates the default distribution object used for testing.
       */
      public EnumeratedIntegerDistributionTest() {
          // Non-sorted singleton array with duplicates should be allowed.
          // Values with zero-probability do not extend the support.
          testDistribution = new EnumeratedIntegerDistribution(
                  new int[]{3, -1, 3, 7, -2, 8},
                  new double[]{0.2, 0.2, 0.3, 0.3, 0.0, 0.0});
      }
  
      /**
       * Tests if the EnumeratedIntegerDistribution constructor throws
       * exceptions for invalid data.
       */
      @Test
      void testExceptions() {
          EnumeratedIntegerDistribution invalid = null;
          try {
              new EnumeratedIntegerDistribution(new int[]{1, 2}, new double[]{0.0});
              fail("Expected MathIllegalArgumentException");
          } catch (MathIllegalArgumentException e) {
          }
          try {
              new EnumeratedIntegerDistribution(new int[]{1, 2}, new double[]{0.0, -1.0});
              fail("Expected MathIllegalArgumentException");
          } catch (MathIllegalArgumentException e) {
          }
          try {
              new EnumeratedIntegerDistribution(new int[]{1, 2}, new double[]{0.0, 0.0});
              fail("Expected MathRuntimeException");
          } catch (MathRuntimeException e) {
          }
          try {
            new EnumeratedIntegerDistribution(new int[]{1, 2}, new double[]{0.0, Double.NaN});
              fail("Expected MathIllegalArgumentException");
          } catch (MathIllegalArgumentException e) {
          }
          try {
          new EnumeratedIntegerDistribution(new int[]{1, 2}, new double[]{0.0, Double.POSITIVE_INFINITY});
              fail("Expected NotFiniteNumberException");
          } catch (MathIllegalArgumentException e) {
          }
          assertNull(invalid, "Expected non-initialized DiscreteRealDistribution");
      }
  
      /**
       * Tests if the distribution returns proper probability values.
       */
      @Test
      void testProbability() {
          int[] points = new int[]{-2, -1, 0, 1, 2, 3, 4, 5, 6, 7, 8};
         double[] results = new double[]{0, 0.2, 0, 0, 0, 0.5, 0, 0, 0, 0.3, 0};
         for (int p = 0; p < points.length; p++) {
             double probability = testDistribution.probability(points[p]);
             assertEquals(results[p], probability, 0.0);
         }
     }
 
     /**
      * Tests if the distribution returns proper cumulative probability values.
      */
     @Test
     void testCumulativeProbability() {
         int[] points = new int[]{-2, -1, 0, 1, 2, 3, 4, 5, 6, 7, 8};
         double[] results = new double[]{0, 0.2, 0.2, 0.2, 0.2, 0.7, 0.7, 0.7, 0.7, 1.0, 1.0};
         for (int p = 0; p < points.length; p++) {
             double probability = testDistribution.cumulativeProbability(points[p]);
             assertEquals(results[p], probability, 1e-10);
         }
     }
 
     /**
      * Tests if the distribution returns proper mean value.
      */
     @Test
     void testGetNumericalMean() {
         assertEquals(3.4, testDistribution.getNumericalMean(), 1e-10);
     }
 
     /**
      * Tests if the distribution returns proper variance.
      */
     @Test
     void testGetNumericalVariance() {
         assertEquals(7.84, testDistribution.getNumericalVariance(), 1e-10);
     }
 
     /**
      * Tests if the distribution returns proper lower bound.
      */
     @Test
     void testGetSupportLowerBound() {
         assertEquals(-1, testDistribution.getSupportLowerBound());
     }
 
     /**
      * Tests if the distribution returns proper upper bound.
      */
     @Test
     void testGetSupportUpperBound() {
         assertEquals(7, testDistribution.getSupportUpperBound());
     }
 
     /**
      * Tests if the distribution returns properly that the support is connected.
      */
     @Test
     void testIsSupportConnected() {
         assertTrue(testDistribution.isSupportConnected());
     }
 
     @Test
     void testCreateFromIntegers() {
         final int[] data = new int[] {0, 1, 1, 2, 2, 2};
         EnumeratedIntegerDistribution distribution = new EnumeratedIntegerDistribution(data);
         assertEquals(0.5, distribution.probability(2), 0);
         assertEquals(0.5, distribution.cumulativeProbability(1), 0);
     }
 
     @Test
     void testGetPmf() {
         final int[] values = new int[] {0,1,2,3,4};
         final double[] masses = new double[] {0.2, 0.2, 0.4, 0.1, 0.1};
         final EnumeratedIntegerDistribution distribution = new EnumeratedIntegerDistribution(values, masses);
         final List<Pair<Integer, Double>> pmf = distribution.getPmf();
         assertEquals(5, pmf.size());
         final Map<Integer, Double> pmfMap = new HashMap<Integer, Double>();
         for (int i = 0; i < 5; i++) {
             pmfMap.put(i, masses[i]);
         }
         for (int i = 0; i < 5; i++) {
             assertEquals(pmf.get(i).getSecond(), pmfMap.get(pmf.get(i).getFirst()), 0);
         }
     }
 }