/*
    * 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.stat.descriptive;
  
  import org.hipparchus.UnitTestUtils;
  import org.hipparchus.random.RandomDataGenerator;
  import org.hipparchus.stat.descriptive.moment.SecondMoment;
  import org.hipparchus.util.FastMath;
  import org.junit.jupiter.api.Test;
  
  import java.util.Arrays;
  
  import static org.junit.jupiter.api.Assertions.assertEquals;
  import static org.junit.jupiter.api.Assertions.assertNotEquals;
  import static org.junit.jupiter.api.Assertions.assertTrue;
  
  /**
   * Test cases for {@link StorelessUnivariateStatistic} classes.
   */
  public abstract class StorelessUnivariateStatisticAbstractTest
      extends UnivariateStatisticAbstractTest {
  
      /** Small sample arrays */
      protected double[][] smallSamples = {{}, {1}, {1,2}, {1,2,3}, {1,2,3,4}};
  
      /** Return a new instance of the statistic */
      @Override
      public abstract StorelessUnivariateStatistic getUnivariateStatistic();
  
      /**Expected value for the testArray defined in UnivariateStatisticAbstractTest */
      @Override
      public abstract double expectedValue();
  
      /**
       * Verifies that increment() and incrementAll work properly.
       */
      @Test
      public void testIncrementation() {
  
          StorelessUnivariateStatistic statistic = getUnivariateStatistic();
  
          // Add testArray one value at a time and check result
          for (int i = 0; i < testArray.length; i++) {
              statistic.increment(testArray[i]);
          }
  
          assertEquals(expectedValue(), statistic.getResult(), getTolerance());
          assertEquals(testArray.length, statistic.getN());
  
          statistic.clear();
  
          // Add testArray all at once and check again
          statistic.incrementAll(testArray);
          assertEquals(expectedValue(), statistic.getResult(), getTolerance());
          assertEquals(testArray.length, statistic.getN());
  
          statistic.clear();
  
          // Cleared
          checkClearValue(statistic);
          assertEquals(0, statistic.getN());
      }
  
      protected void checkClearValue(StorelessUnivariateStatistic statistic){
          assertTrue(Double.isNaN(statistic.getResult()));
      }
  
      @Test
      public void testSerialization() {
          StorelessUnivariateStatistic statistic = getUnivariateStatistic();
  
          UnitTestUtils.checkSerializedEquality(statistic);
          statistic.clear();
  
          for (int i = 0; i < testArray.length; i++) {
              statistic.increment(testArray[i]);
              if(i % 5 == 0) {
                  statistic = (StorelessUnivariateStatistic)UnitTestUtils.serializeAndRecover(statistic);
              }
          }
 
         UnitTestUtils.checkSerializedEquality(statistic);
         assertEquals(expectedValue(), statistic.getResult(), getTolerance());
 
         statistic.clear();
         checkClearValue(statistic);
     }
 
     @Test
     public void testEqualsAndHashCode() {
         StorelessUnivariateStatistic statistic = getUnivariateStatistic();
         StorelessUnivariateStatistic statistic2 = null;
 
         assertNotEquals(statistic, statistic2, "non-null, compared to null");
         assertEquals(statistic, statistic, "reflexive, non-null");
 
         int emptyHash = statistic.hashCode();
         statistic2 = getUnivariateStatistic();
         assertEquals(statistic, statistic2, "empty stats should be equal");
         assertEquals(emptyHash, statistic2.hashCode(), "empty stats should have the same hashcode");
 
         statistic.increment(1d);
         assertEquals(statistic, statistic, "reflexive, non-empty");
         assertNotEquals(statistic, statistic2, "non-empty, compared to empty");
         assertNotEquals(statistic2, statistic, "non-empty, compared to empty");
         assertTrue(statistic.hashCode() != emptyHash,
                    "non-empty stat should have different hashcode from empty stat");
 
         statistic2.increment(1d);
         assertEquals(statistic, statistic2, "stats with same data should be equal");
         assertEquals(statistic.hashCode(), statistic2.hashCode(), "stats with same data should have the same hashcode");
 
         statistic.increment(Double.POSITIVE_INFINITY);
         assertNotEquals(statistic2, statistic, "stats with different n's should not be equal");
         assertTrue(statistic.hashCode() != statistic2.hashCode(),
                    "stats with different n's should have different hashcodes");
 
         statistic2.increment(Double.POSITIVE_INFINITY);
         assertEquals(statistic, statistic2, "stats with same data should be equal");
         assertEquals(statistic.hashCode(), statistic2.hashCode(), "stats with same data should have the same hashcode");
 
         statistic.clear();
         statistic2.clear();
         assertEquals(statistic, statistic2, "cleared stats should be equal");
         assertEquals(emptyHash, statistic2.hashCode(), "cleared stats should have thashcode of empty stat");
         assertEquals(emptyHash, statistic.hashCode(), "cleared stats should have thashcode of empty stat");
 
     }
 
     @Test
     public void testMomentSmallSamples() {
         UnivariateStatistic stat = getUnivariateStatistic();
         if (stat instanceof SecondMoment) {
             SecondMoment moment = (SecondMoment) getUnivariateStatistic();
             assertTrue(Double.isNaN(moment.getResult()));
             moment.increment(1d);
             assertEquals(0d, moment.getResult(), 0);
         }
     }
 
     /**
      * Make sure that evaluate(double[]) and inrementAll(double[]),
      * getResult() give same results.
      */
     @Test
     public void testConsistency() {
         StorelessUnivariateStatistic stat = getUnivariateStatistic();
         stat.incrementAll(testArray);
         assertEquals(stat.getResult(), stat.evaluate(testArray), getTolerance());
         for (int i = 0; i < smallSamples.length; i++) {
             stat.clear();
             for (int j =0; j < smallSamples[i].length; j++) {
                 stat.increment(smallSamples[i][j]);
             }
             UnitTestUtils.customAssertEquals(stat.getResult(), stat.evaluate(smallSamples[i]), getTolerance());
         }
     }
 
     /**
      * Verifies that copied statistics remain equal to originals when
      * incremented the same way.
      */
     @Test
     public void testCopyConsistency() {
 
         StorelessUnivariateStatistic master = getUnivariateStatistic();
 
         StorelessUnivariateStatistic replica = null;
 
         // Randomly select a portion of testArray to load first
         long index = FastMath.round((FastMath.random()) * testArray.length);
 
         // Put first half in master and copy master to replica
         master.incrementAll(testArray, 0, (int) index);
         replica = master.copy();
 
         // Check same
         assertEquals(replica, master);
         assertEquals(master, replica);
 
         // Now add second part to both and check again
         master.incrementAll(testArray, (int) index, (int) (testArray.length - index));
         replica.incrementAll(testArray, (int) index, (int) (testArray.length - index));
         assertEquals(replica, master);
         assertEquals(master, replica);
     }
 
     @Test
     public void testSerial() {
         StorelessUnivariateStatistic s = getUnivariateStatistic();
         assertEquals(s, UnitTestUtils.serializeAndRecover(s));
     }
 
     /**
      * Make sure that evaluate(double[]) does not alter the internal state.
      */
     @Test
     public void testEvaluateInternalState() {
         StorelessUnivariateStatistic stat = getUnivariateStatistic();
         stat.evaluate(testArray);
         assertEquals(0, stat.getN());
 
         stat.incrementAll(testArray);
 
         StorelessUnivariateStatistic savedStatistic = stat.copy();
 
         assertNotEquals(stat.getResult(), stat.evaluate(testArray, 0, 5), getTolerance());
 
         assertEquals(savedStatistic.getResult(), stat.getResult(), 0.0);
         assertEquals(savedStatistic.getN(), stat.getN());
     }
 
     /**
      * Test that the aggregate operation is consistent with individual increment.
      */
     @Test
     @SuppressWarnings("unchecked")
     public <T> void testAggregate() {
         // Union of both statistics.
         StorelessUnivariateStatistic statU = getUnivariateStatistic();
         if (!(statU instanceof AggregatableStatistic<?>)) {
             return;
         }
 
         // Aggregated statistic.
         AggregatableStatistic<T> aggregated = (AggregatableStatistic<T>) getUnivariateStatistic();
         StorelessUnivariateStatistic statAgg = (StorelessUnivariateStatistic) aggregated;
 
         final RandomDataGenerator randomDataGenerator = new RandomDataGenerator(100);
         // Create Set A
         StorelessUnivariateStatistic statA = getUnivariateStatistic();
         for (int i = 0; i < 10; i++) {
             final double val = randomDataGenerator.nextGaussian();
             statA.increment(val);
             statU.increment(val);
         }
 
         aggregated.aggregate((T) statA);
         assertEquals(statA.getN(), statAgg.getN(), getTolerance());
         assertEquals(statA.getResult(), statAgg.getResult(), getTolerance());
 
         // Create Set B
         StorelessUnivariateStatistic statB = getUnivariateStatistic();
         for (int i = 0; i < 4; i++) {
             final double val = randomDataGenerator.nextGaussian();
             statB.increment(val);
             statU.increment(val);
         }
 
         aggregated.aggregate((T) statB);
         assertEquals(statU.getN(), statAgg.getN(), getTolerance());
         assertEquals(statU.getResult(), statAgg.getResult(), getTolerance());
     }
 
     @Test
     public void testConsume() {
         StorelessUnivariateStatistic stat = getUnivariateStatistic();
 
         Arrays.stream(testArray)
               .forEach(stat);
 
         assertEquals(expectedValue(), stat.getResult(), getTolerance());
 
         StorelessUnivariateStatistic stat2 = getUnivariateStatistic();
         stat2.incrementAll(testArray);
         assertEquals(stat2.getResult(), stat.getResult(), getTolerance());
     }
 }