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   * 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.cassandra.stress.generate;
  
  import org.junit.Test;
  
  import org.apache.cassandra.stress.settings.OptionDistribution;
  
  import static java.lang.Math.toIntExact;
  import static org.junit.Assert.*;
  
  public class DistributionGaussianTest
  {
      @Test
      public void simpleGaussian()
      {
          Distribution dist = OptionDistribution.get("gaussian(1..10)").get();
          assertTrue(dist instanceof DistributionBoundApache);
  
          assertEquals(1, dist.minValue());
          assertEquals(10, dist.maxValue());
          assertEquals(5, dist.average());
  
          assertEquals(1, dist.inverseCumProb(0d));
          assertEquals(10, dist.inverseCumProb(1d));
  
          int testCount = 100000;
          int[] results = new int[11];
          for (int i = 0; i < testCount; i++)
          {
              int val = toIntExact(dist.next());
              results[val]++;
          }
  
          // Increasing for the first half
          for (int i = toIntExact(dist.minValue()); i < dist.average(); i++)
          {
              assertTrue(results[i] < results[i + 1]);
          }
  
          // Decreasing for the second half
          for (int i = toIntExact(dist.average()) + 1; i < dist.maxValue(); i++)
          {
              assertTrue(results[i] > results[i + 1]);
          }
      }
  
      @Test
      public void negValueGaussian()
      {
          Distribution dist = OptionDistribution.get("gaussian(-1000..-10)").get();
          assertTrue(dist instanceof DistributionBoundApache);
  
          assertEquals(-1000, dist.minValue());
          assertEquals( -10, dist.maxValue());
          assertEquals(-504, dist.average());
  
          assertEquals(-1000, dist.inverseCumProb(0d));
          assertEquals(-10, dist.inverseCumProb(1d));
      }
  }
  