/*
    * The baseCode project
    *
    * Copyright (c) 2004-2011 University of British Columbia
    *
    * Licensed 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 ubic.basecode.math;
  
  import static org.junit.Assert.assertEquals;
  
  import org.junit.Test;
  
  import ubic.basecode.math.distribution.ProbabilityComputer;
  import ubic.basecode.math.distribution.UniformProbabilityComputer;
  import cern.colt.list.DoubleArrayList;
  
  /**
   * @author pavlidis
   * 
   */
  public class TestKSTest {
  
      // uniform (r)
      DoubleArrayList x = new DoubleArrayList( new double[] { 0.42084388, 0.08428030, 0.51525081, 0.02165163, 0.99627802,
              0.79237273, 0.52478154, 0.21394388, 0.19654006, 0.88131869 } );
  
      // normal (n)
      DoubleArrayList y = new DoubleArrayList( new double[] { -0.09503411, 2.33677197, 0.61934707, 0.83549049,
              0.09643316, -0.57449861, -1.40573974, 0.51279445, -0.09593008, 1.48125008 } );
  
      @Test
      public void testKSTestOneSample() {
          // ks.test(n, punif, 0, 1)
  
          // x<-punif(sort(n)) - (0 : (10-1)) / 10
          // max(c(x, 1/10 - x))
  
          ProbabilityComputer ps = new UniformProbabilityComputer();
          double actualReturn = KSTest.oneSample( y, ps );
          double expectedReturn = 0.07698; // D is 0.4036
  
          assertEquals( 0.4036, KSTest.oneSampleStatistic( y, ps ), 0.001 );
  
          assertEquals( expectedReturn, actualReturn, 0.0001 );
      }
  
      /**
       *
       */
      @Test
      public void testKSTestTwoSample() {
          double actualReturn = KSTest.twoSample( x, y );
          double expectedReturn = 0.4175; // from R ks.test(x,y); D = 0.4.
  
          assertEquals( 0.40, KSTest.twoSampleStatistic( x, y ), 0.001 );
  
          assertEquals( expectedReturn, actualReturn, 0.0001 );
      }
  
  }