/*
    * 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.correlation;
  
  import org.hipparchus.UnitTestUtils;
  import org.hipparchus.exception.MathIllegalArgumentException;
  import org.hipparchus.linear.BlockRealMatrix;
  import org.hipparchus.linear.MatrixUtils;
  import org.hipparchus.linear.RealMatrix;
  import org.hipparchus.stat.ranking.NaNStrategy;
  import org.hipparchus.stat.ranking.NaturalRanking;
  import org.junit.jupiter.api.Test;
  
  import static org.junit.jupiter.api.Assertions.assertEquals;
  import static org.junit.jupiter.api.Assertions.assertThrows;
  import static org.junit.jupiter.api.Assertions.assertTrue;
  import static org.junit.jupiter.api.Assertions.fail;
  
  /**
   * Test cases for Spearman's rank correlation
   *
   */
  class SpearmansRankCorrelationTest extends PearsonsCorrelationTest {
  
      /**
       * Test Longley dataset against R.
       */
      @Override
      @Test
      public void testLongly() {
          RealMatrix matrix = createRealMatrix(longleyData, 16, 7);
          SpearmansCorrelation corrInstance = new SpearmansCorrelation(matrix);
          RealMatrix correlationMatrix = corrInstance.getCorrelationMatrix();
          double[] rData = new double[] {
                  1, 0.982352941176471, 0.985294117647059, 0.564705882352941, 0.2264705882352941, 0.976470588235294,
                  0.976470588235294, 0.982352941176471, 1, 0.997058823529412, 0.664705882352941, 0.2205882352941176,
                  0.997058823529412, 0.997058823529412, 0.985294117647059, 0.997058823529412, 1, 0.638235294117647,
                  0.2235294117647059, 0.9941176470588236, 0.9941176470588236, 0.564705882352941, 0.664705882352941,
                  0.638235294117647, 1, -0.3411764705882353, 0.685294117647059, 0.685294117647059, 0.2264705882352941,
                  0.2205882352941176, 0.2235294117647059, -0.3411764705882353, 1, 0.2264705882352941, 0.2264705882352941,
                  0.976470588235294, 0.997058823529412, 0.9941176470588236, 0.685294117647059, 0.2264705882352941, 1, 1,
                  0.976470588235294, 0.997058823529412, 0.9941176470588236, 0.685294117647059, 0.2264705882352941, 1, 1
          };
          UnitTestUtils.customAssertEquals("Spearman's correlation matrix", createRealMatrix(rData, 7, 7), correlationMatrix, 10E-15);
      }
  
      /**
       * Test R swiss fertility dataset.
       */
      @Test
      void testSwiss() {
          RealMatrix matrix = createRealMatrix(swissData, 47, 5);
          SpearmansCorrelation corrInstance = new SpearmansCorrelation(matrix);
          RealMatrix correlationMatrix = corrInstance.getCorrelationMatrix();
          double[] rData = new double[] {
                  1, 0.2426642769364176, -0.660902996352354, -0.443257690360988, 0.4136455623012432,
                  0.2426642769364176, 1, -0.598859938748963, -0.650463814145816, 0.2886878090882852,
                 -0.660902996352354, -0.598859938748963, 1, 0.674603831406147, -0.4750575257171745,
                 -0.443257690360988, -0.650463814145816, 0.674603831406147, 1, -0.1444163088302244,
                  0.4136455623012432, 0.2886878090882852, -0.4750575257171745, -0.1444163088302244, 1
          };
          UnitTestUtils.customAssertEquals("Spearman's correlation matrix", createRealMatrix(rData, 5, 5), correlationMatrix, 10E-15);
      }
  
      /**
       * Constant column
       */
      @Override
      @Test
      public void testConstant() {
          double[] noVariance = new double[] {1, 1, 1, 1};
          double[] values = new double[] {1, 2, 3, 4};
          assertTrue(Double.isNaN(new SpearmansCorrelation().correlation(noVariance, values)));
      }
  
      /**
       * Insufficient data
       */
      @Override
      @Test
     public void testInsufficientData() {
         double[] one = new double[] {1};
         double[] two = new double[] {2};
         try {
             new SpearmansCorrelation().correlation(one, two);
             fail("Expecting MathIllegalArgumentException");
         } catch (MathIllegalArgumentException ex) {
             // Expected
         }
         RealMatrix matrix = new BlockRealMatrix(new double[][] {{0},{1}});
         try {
             new SpearmansCorrelation(matrix);
             fail("Expecting MathIllegalArgumentException");
         } catch (MathIllegalArgumentException ex) {
             // Expected
         }
     }
 
     @Override
     @Test
     public void testConsistency() {
         RealMatrix matrix = createRealMatrix(longleyData, 16, 7);
         SpearmansCorrelation corrInstance = new SpearmansCorrelation(matrix);
         double[][] data = matrix.getData();
         double[] x = matrix.getColumn(0);
         double[] y = matrix.getColumn(1);
         assertEquals(new SpearmansCorrelation().correlation(x, y),
                 corrInstance.getCorrelationMatrix().getEntry(0, 1), Double.MIN_VALUE);
         UnitTestUtils.customAssertEquals("Correlation matrix", corrInstance.getCorrelationMatrix(),
                                          new SpearmansCorrelation().computeCorrelationMatrix(data), Double.MIN_VALUE);
     }
 
     @Test
     void testMath891Array() {
         assertThrows(MathIllegalArgumentException.class, () -> {
             // NaNStrategy.REMOVED is not supported since 4.0
             final double[] xArray = new double[]{Double.NaN, 1.9, 2, 100, 3};
             final double[] yArray = new double[]{10, 2, 10, Double.NaN, 4};
 
             NaturalRanking ranking = new NaturalRanking(NaNStrategy.REMOVED);
             SpearmansCorrelation spearman = new SpearmansCorrelation(ranking);
 
             assertEquals(0.5, spearman.correlation(xArray, yArray), Double.MIN_VALUE);
         });
     }
 
     @Test
     void testMath891Matrix() {
         assertThrows(MathIllegalArgumentException.class, () -> {
             // NaNStrategy.REMOVED is not supported since 4.0
             final double[] xArray = new double[]{Double.NaN, 1.9, 2, 100, 3};
             final double[] yArray = new double[]{10, 2, 10, Double.NaN, 4};
 
             RealMatrix matrix = MatrixUtils.createRealMatrix(xArray.length, 2);
             for (int i = 0; i < xArray.length; i++) {
                 matrix.addToEntry(i, 0, xArray[i]);
                 matrix.addToEntry(i, 1, yArray[i]);
             }
 
             // compute correlation
             NaturalRanking ranking = new NaturalRanking(NaNStrategy.REMOVED);
             SpearmansCorrelation spearman = new SpearmansCorrelation(matrix, ranking);
 
             assertEquals(0.5, spearman.getCorrelationMatrix().getEntry(0, 1), Double.MIN_VALUE);
         });
     }
 
     // Not relevant here
     @Override
     @Test
     public void testStdErrorConsistency() {}
     @Override
     @Test
     public void testCovarianceConsistency() {}
 
 }