/*
    * 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.descriptive.rank;
  
  import static org.junit.Assert.assertEquals;
  import static org.junit.Assert.assertTrue;
  
  import org.hipparchus.stat.descriptive.StorelessUnivariateStatisticAbstractTest;
  import org.junit.Test;
  
  /**
   * Test cases for the {@link Min} class.
   */
  public class MinTest extends StorelessUnivariateStatisticAbstractTest{
  
      @Override
      public Min getUnivariateStatistic() {
          return new Min();
      }
  
      @Override
      public double expectedValue() {
          return this.min;
      }
  
      @Test
      public void testSpecialValues() {
          double[] testArray = {0d, Double.NaN, Double.POSITIVE_INFINITY, Double.NEGATIVE_INFINITY};
          Min min = getUnivariateStatistic();
          assertTrue(Double.isNaN(min.getResult()));
          min.increment(testArray[0]);
          assertEquals(0d, min.getResult(), 0);
          min.increment(testArray[1]);
          assertEquals(0d, min.getResult(), 0);
          min.increment(testArray[2]);
          assertEquals(0d, min.getResult(), 0);
          min.increment(testArray[3]);
          assertEquals(Double.NEGATIVE_INFINITY, min.getResult(), 0);
          assertEquals(Double.NEGATIVE_INFINITY, min.evaluate(testArray), 0);
      }
  
      @Test
      public void testNaNs() {
          Min min = getUnivariateStatistic();
          double nan = Double.NaN;
          assertEquals(2d, min.evaluate(new double[]{nan, 2d, 3d}), 0);
          assertEquals(1d, min.evaluate(new double[]{1d, nan, 3d}), 0);
          assertEquals(1d, min.evaluate(new double[]{1d, 2d, nan}), 0);
          assertTrue(Double.isNaN(min.evaluate(new double[]{nan, nan, nan})));
      }
  
  }