/*
    * 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.rng.sampling.distribution;
  
  import org.apache.commons.rng.UniformRandomProvider;
  import org.apache.commons.rng.sampling.RandomAssert;
  import org.apache.commons.rng.sampling.distribution.LargeMeanPoissonSampler.LargeMeanPoissonSamplerState;
  import org.junit.jupiter.api.Assertions;
  import org.junit.jupiter.api.Test;
  
  /**
   * This test checks the {@link LargeMeanPoissonSampler} can be created
   * from a saved state.
   */
  class LargeMeanPoissonSamplerTest {
  
      // Edge cases for construction
  
      /**
       * Test the constructor with a bad mean.
       */
      @Test
      void testConstructorThrowsWithMeanLargerThanUpperBound() {
          final UniformRandomProvider rng = RandomAssert.seededRNG();
          final double mean = Integer.MAX_VALUE / 2 + 1;
          Assertions.assertThrows(IllegalArgumentException.class,
              () -> LargeMeanPoissonSampler.of(rng, mean));
      }
  
      /**
       * Test the constructor with a mean below 1.
       */
      @Test
      void testConstructorThrowsWithMeanBelow1() {
          final UniformRandomProvider rng = RandomAssert.seededRNG();
          final double mean = Math.nextDown(1);
          Assertions.assertThrows(IllegalArgumentException.class,
              () -> LargeMeanPoissonSampler.of(rng, mean));
      }
  
      /**
       * Test the constructor using the state with a negative fractional mean.
       */
      @Test
      void testConstructorThrowsWithStateAndNegativeFractionalMean() {
          final UniformRandomProvider rng = RandomAssert.seededRNG();
          final LargeMeanPoissonSamplerState state = new LargeMeanPoissonSampler(rng, 1).getState();
          Assertions.assertThrows(IllegalArgumentException.class,
              () -> new LargeMeanPoissonSampler(rng, state, -0.1));
      }
  
      /**
       * Test the constructor with a non-fractional mean.
       */
      @Test
      void testConstructorThrowsWithStateAndNonFractionalMean() {
          final UniformRandomProvider rng = RandomAssert.seededRNG();
          final LargeMeanPoissonSamplerState state = new LargeMeanPoissonSampler(rng, 1).getState();
          Assertions.assertThrows(IllegalArgumentException.class,
              () -> new LargeMeanPoissonSampler(rng, state, 1.1));
      }
  
      /**
       * Test the constructor with fractional mean of 1.
       */
      @Test
      void testConstructorThrowsWithStateAndFractionalMeanOne() {
          final UniformRandomProvider rng = RandomAssert.seededRNG();
          final LargeMeanPoissonSamplerState state = new LargeMeanPoissonSampler(rng, 1).getState();
          Assertions.assertThrows(IllegalArgumentException.class,
              () -> new LargeMeanPoissonSampler(rng, state, 1));
      }
  
      // Sampling tests
  
      /**
       * Test the {@link LargeMeanPoissonSampler} returns the same samples when it
       * is created using the saved state.
       */
      @Test
      void testCanComputeSameSamplesWhenConstructedWithState() {
          // Two identical RNGs
          final UniformRandomProvider rng1 = RandomAssert.seededRNG();
          final UniformRandomProvider rng2 = RandomAssert.seededRNG();
  
         // The sampler is suitable for mean > 40
         for (int i = 40; i < 44; i++) {
             // Test integer mean (no SmallMeanPoissonSampler required)
             testPoissonSamples(rng1, rng2, i);
             // Test non-integer mean (SmallMeanPoissonSampler required)
             testPoissonSamples(rng1, rng2, i + 0.5);
         }
     }
 
     /**
      * Test the {@link LargeMeanPoissonSampler} returns the same samples when it
      * is created using the saved state. The random providers must be
      * identical (including state).
      *
      * @param rng1  the first random provider
      * @param rng2  the second random provider
      * @param mean  the mean
      */
     private static void testPoissonSamples(
             final UniformRandomProvider rng1,
             final UniformRandomProvider rng2,
             double mean) {
         final LargeMeanPoissonSampler s1 = new LargeMeanPoissonSampler(rng1, mean);
         final int n = (int) Math.floor(mean);
         final double lambdaFractional = mean - n;
         final LargeMeanPoissonSamplerState state1 = s1.getState();
         final LargeMeanPoissonSampler s2 = new LargeMeanPoissonSampler(rng2, state1, lambdaFractional);
         final LargeMeanPoissonSamplerState state2 = s2.getState();
         Assertions.assertEquals(state1.getLambda(), state2.getLambda(), "State lambdas are not equal");
         Assertions.assertNotSame(state1, state2, "States are the same object");
         RandomAssert.assertProduceSameSequence(s1, s2);
     }
 
     /**
      * Test the SharedStateSampler implementation.
      */
     @Test
     void testSharedStateSamplerWithFractionalMean() {
         testSharedStateSampler(34.5);
     }
 
     /**
      * Test the SharedStateSampler implementation with the edge case when there is no
      * small mean sampler (i.e. no fraction part to the mean).
      */
     @Test
     void testSharedStateSamplerWithIntegerMean() {
         testSharedStateSampler(34.0);
     }
 
     /**
      * Test the SharedStateSampler implementation.
      *
      * @param mean Mean.
      */
     private static void testSharedStateSampler(double mean) {
         final UniformRandomProvider rng1 = RandomAssert.seededRNG();
         final UniformRandomProvider rng2 = RandomAssert.seededRNG();
         final SharedStateDiscreteSampler sampler1 =
             LargeMeanPoissonSampler.of(rng1, mean);
         final SharedStateDiscreteSampler sampler2 = sampler1.withUniformRandomProvider(rng2);
         RandomAssert.assertProduceSameSequence(sampler1, sampler2);
     }
 }