/*
    * Licensed to the Hipparchus project under one or more
    * contributor license agreements.  See the NOTICE file distributed with
    * this work for additional information regarding copyright ownership.
    * The Hipparchus project 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.
   */
  
  package org.hipparchus.analysis.differentiation;
  
  import org.hipparchus.dfp.Dfp;
  import org.hipparchus.dfp.DfpField;
  import org.hipparchus.random.RandomGenerator;
  import org.hipparchus.random.Well19937a;
  import org.hipparchus.util.FastMath;
  import org.junit.jupiter.api.Test;
  
  import static org.junit.jupiter.api.Assertions.assertEquals;
  import static org.junit.jupiter.api.Assertions.assertTrue;
  
  /**
   * Test for class {@link FieldUnivariateDerivative2} on {@link Dfp}.
   */
  class FieldUnivariateDerivative2DfpTest extends FieldUnivariateDerivative2AbstractTest<Dfp> {
  
      private static final DfpField FIELD = new DfpField(25);
  
      @Override
      protected DfpField getValueField() {
          return FIELD;
      }
  
      @Test
      public void testHashcode() {
          assertEquals(-1300667743, build(2, 1, 4).hashCode());
      }
  
      @Override
      @Test
      public void testLinearCombinationReference() {
          doTestLinearCombinationReference(x -> build(x), 5.0e-9, 4.212e-9);
      }
  
      @Override
      @Test
      public void testUlp() {
          final RandomGenerator random = new Well19937a(0x36d4f8862421e0e4l);
          for (int i = -300; i < 300; ++i) {
              final double x = FastMath.scalb(2.0 * random.nextDouble() - 1.0, i);
              assertTrue(FastMath.ulp(x) >= build(x).ulp().getReal());
          }
      }
  
      @Override
      @Test
      public void testUlpVsDS() {
          // skipped as Dfp is much higher accuracy than double
      }
  
  }