/*
    * 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.math4.legacy.analysis.integration;
  
  import org.apache.commons.math4.legacy.analysis.QuinticFunction;
  import org.apache.commons.math4.legacy.analysis.UnivariateFunction;
  import org.apache.commons.math4.legacy.analysis.function.Sin;
  import org.apache.commons.math4.legacy.exception.NumberIsTooLargeException;
  import org.apache.commons.math4.legacy.exception.NumberIsTooSmallException;
  import org.apache.commons.math4.core.jdkmath.JdkMath;
  import org.junit.Assert;
  import org.junit.Test;
  
  
  /**
   * Test case for Romberg integrator.
   * <p>
   * Romberg algorithm is very fast for good behavior integrand. Test runs
   * show that for a default relative accuracy of 1E-6, it generally takes
   * takes less than 5 iterations for the integral to converge.
   *
   */
  public final class RombergIntegratorTest {
  
      /**
       * Test of integrator for the sine function.
       */
      @Test
      public void testSinFunction() {
          UnivariateFunction f = new Sin();
          UnivariateIntegrator integrator = new RombergIntegrator();
          double min;
          double max;
          double expected;
          double result;
          double tolerance;
  
          min = 0; max = JdkMath.PI; expected = 2;
          tolerance = JdkMath.abs(expected * integrator.getRelativeAccuracy());
          result = integrator.integrate(100, f, min, max);
          Assert.assertTrue(integrator.getEvaluations() < 50);
          Assert.assertTrue(integrator.getIterations()  < 10);
          Assert.assertEquals(expected, result, tolerance);
  
          min = -JdkMath.PI/3; max = 0; expected = -0.5;
          tolerance = JdkMath.abs(expected * integrator.getRelativeAccuracy());
          result = integrator.integrate(100, f, min, max);
          Assert.assertTrue(integrator.getEvaluations() < 50);
          Assert.assertTrue(integrator.getIterations()  < 10);
          Assert.assertEquals(expected, result, tolerance);
      }
  
      /**
       * Test of integrator for the quintic function.
       */
      @Test
      public void testQuinticFunction() {
          UnivariateFunction f = new QuinticFunction();
          UnivariateIntegrator integrator = new RombergIntegrator();
          double min;
          double max;
          double expected;
          double result;
          double tolerance;
  
          min = 0; max = 1; expected = -1.0/48;
          tolerance = JdkMath.abs(expected * integrator.getRelativeAccuracy());
          result = integrator.integrate(100, f, min, max);
          Assert.assertTrue(integrator.getEvaluations() < 10);
          Assert.assertTrue(integrator.getIterations()  < 5);
          Assert.assertEquals(expected, result, tolerance);
  
          min = 0; max = 0.5; expected = 11.0/768;
          tolerance = JdkMath.abs(expected * integrator.getRelativeAccuracy());
          result = integrator.integrate(100, f, min, max);
          Assert.assertTrue(integrator.getEvaluations() < 10);
          Assert.assertTrue(integrator.getIterations()  < 5);
          Assert.assertEquals(expected, result, tolerance);
  
          min = -1; max = 4; expected = 2048/3.0 - 78 + 1.0/48;
          tolerance = JdkMath.abs(expected * integrator.getRelativeAccuracy());
          result = integrator.integrate(100, f, min, max);
          Assert.assertTrue(integrator.getEvaluations() < 10);
          Assert.assertTrue(integrator.getIterations()  < 5);
          Assert.assertEquals(expected, result, tolerance);
     }
 
     /**
      * Test of parameters for the integrator.
      */
     @Test
     public void testParameters() {
         UnivariateFunction f = new Sin();
 
         try {
             // bad interval
             new RombergIntegrator().integrate(1000, f, 1, -1);
             Assert.fail("Expecting NumberIsTooLargeException - bad interval");
         } catch (NumberIsTooLargeException ex) {
             // expected
         }
         try {
             // bad iteration limits
             new RombergIntegrator(5, 4);
             Assert.fail("Expecting NumberIsTooSmallException - bad iteration limits");
         } catch (NumberIsTooSmallException ex) {
             // expected
         }
         try {
             // bad iteration limits
             new RombergIntegrator(10, 50);
             Assert.fail("Expecting NumberIsTooLargeException - bad iteration limits");
         } catch (NumberIsTooLargeException ex) {
             // expected
         }
     }
 }