/*
    * 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.ode.nonstiff;
  
  import org.apache.commons.math4.core.jdkmath.JdkMath;
  
  
  /**
   * This class implements the 8(5,3) Dormand-Prince integrator for Ordinary
   * Differential Equations.
   *
   * <p>This integrator is an embedded Runge-Kutta integrator
   * of order 8(5,3) used in local extrapolation mode (i.e. the solution
   * is computed using the high order formula) with stepsize control
   * (and automatic step initialization) and continuous output. This
   * method uses 12 functions evaluations per step for integration and 4
   * evaluations for interpolation. However, since the first
   * interpolation evaluation is the same as the first integration
   * evaluation of the next step, we have included it in the integrator
   * rather than in the interpolator and specified the method was an
   * <i>fsal</i>. Hence, despite we have 13 stages here, the cost is
   * really 12 evaluations per step even if no interpolation is done,
   * and the overcost of interpolation is only 3 evaluations.</p>
   *
   * <p>This method is based on an 8(6) method by Dormand and Prince
   * (i.e. order 8 for the integration and order 6 for error estimation)
   * modified by Hairer and Wanner to use a 5th order error estimator
   * with 3rd order correction. This modification was introduced because
   * the original method failed in some cases (wrong steps can be
   * accepted when step size is too large, for example in the
   * Brusselator problem) and also had <i>severe difficulties when
   * applied to problems with discontinuities</i>. This modification is
   * explained in the second edition of the first volume (Nonstiff
   * Problems) of the reference book by Hairer, Norsett and Wanner:
   * <i>Solving Ordinary Differential Equations</i> (Springer-Verlag,
   * ISBN 3-540-56670-8).</p>
   *
   * @since 1.2
   */
  
  public class DormandPrince853Integrator extends EmbeddedRungeKuttaIntegrator {
  
    /** Integrator method name. */
    private static final String METHOD_NAME = "Dormand-Prince 8 (5, 3)";
  
    /** Time steps Butcher array. */
    private static final double[] STATIC_C = {
      (12.0 - 2.0 * JdkMath.sqrt(6.0)) / 135.0, (6.0 - JdkMath.sqrt(6.0)) / 45.0, (6.0 - JdkMath.sqrt(6.0)) / 30.0,
      (6.0 + JdkMath.sqrt(6.0)) / 30.0, 1.0/3.0, 1.0/4.0, 4.0/13.0, 127.0/195.0, 3.0/5.0,
      6.0/7.0, 1.0, 1.0
    };
  
    /** Internal weights Butcher array. */
    private static final double[][] STATIC_A = {
  
      // k2
      {(12.0 - 2.0 * JdkMath.sqrt(6.0)) / 135.0},
  
      // k3
      {(6.0 - JdkMath.sqrt(6.0)) / 180.0, (6.0 - JdkMath.sqrt(6.0)) / 60.0},
  
      // k4
      {(6.0 - JdkMath.sqrt(6.0)) / 120.0, 0.0, (6.0 - JdkMath.sqrt(6.0)) / 40.0},
  
      // k5
      {(462.0 + 107.0 * JdkMath.sqrt(6.0)) / 3000.0, 0.0,
       (-402.0 - 197.0 * JdkMath.sqrt(6.0)) / 1000.0, (168.0 + 73.0 * JdkMath.sqrt(6.0)) / 375.0},
  
      // k6
      {1.0 / 27.0, 0.0, 0.0, (16.0 + JdkMath.sqrt(6.0)) / 108.0, (16.0 - JdkMath.sqrt(6.0)) / 108.0},
  
      // k7
      {19.0 / 512.0, 0.0, 0.0, (118.0 + 23.0 * JdkMath.sqrt(6.0)) / 1024.0,
       (118.0 - 23.0 * JdkMath.sqrt(6.0)) / 1024.0, -9.0 / 512.0},
  
      // k8
      {13772.0 / 371293.0, 0.0, 0.0, (51544.0 + 4784.0 * JdkMath.sqrt(6.0)) / 371293.0,
       (51544.0 - 4784.0 * JdkMath.sqrt(6.0)) / 371293.0, -5688.0 / 371293.0, 3072.0 / 371293.0},
  
      // k9
      {58656157643.0 / 93983540625.0, 0.0, 0.0,
       (-1324889724104.0 - 318801444819.0 * JdkMath.sqrt(6.0)) / 626556937500.0,
       (-1324889724104.0 + 318801444819.0 * JdkMath.sqrt(6.0)) / 626556937500.0,
       96044563816.0 / 3480871875.0, 5682451879168.0 / 281950621875.0,
      -165125654.0 / 3796875.0},
 
     // k10
     {8909899.0 / 18653125.0, 0.0, 0.0,
      (-4521408.0 - 1137963.0 * JdkMath.sqrt(6.0)) / 2937500.0,
      (-4521408.0 + 1137963.0 * JdkMath.sqrt(6.0)) / 2937500.0,
      96663078.0 / 4553125.0, 2107245056.0 / 137915625.0,
      -4913652016.0 / 147609375.0, -78894270.0 / 3880452869.0},
 
     // k11
     {-20401265806.0 / 21769653311.0, 0.0, 0.0,
      (354216.0 + 94326.0 * JdkMath.sqrt(6.0)) / 112847.0,
      (354216.0 - 94326.0 * JdkMath.sqrt(6.0)) / 112847.0,
      -43306765128.0 / 5313852383.0, -20866708358144.0 / 1126708119789.0,
      14886003438020.0 / 654632330667.0, 35290686222309375.0 / 14152473387134411.0,
      -1477884375.0 / 485066827.0},
 
     // k12
     {39815761.0 / 17514443.0, 0.0, 0.0,
      (-3457480.0 - 960905.0 * JdkMath.sqrt(6.0)) / 551636.0,
      (-3457480.0 + 960905.0 * JdkMath.sqrt(6.0)) / 551636.0,
      -844554132.0 / 47026969.0, 8444996352.0 / 302158619.0,
      -2509602342.0 / 877790785.0, -28388795297996250.0 / 3199510091356783.0,
      226716250.0 / 18341897.0, 1371316744.0 / 2131383595.0},
 
     // k13 should be for interpolation only, but since it is the same
     // stage as the first evaluation of the next step, we perform it
     // here at no cost by specifying this is an fsal method
     {104257.0/1920240.0, 0.0, 0.0, 0.0, 0.0, 3399327.0/763840.0,
      66578432.0/35198415.0, -1674902723.0/288716400.0,
      54980371265625.0/176692375811392.0, -734375.0/4826304.0,
      171414593.0/851261400.0, 137909.0/3084480.0}
   };
 
   /** Propagation weights Butcher array. */
   private static final double[] STATIC_B = {
       104257.0/1920240.0,
       0.0,
       0.0,
       0.0,
       0.0,
       3399327.0/763840.0,
       66578432.0/35198415.0,
       -1674902723.0/288716400.0,
       54980371265625.0/176692375811392.0,
       -734375.0/4826304.0,
       171414593.0/851261400.0,
       137909.0/3084480.0,
       0.0
   };
 
   /** First error weights array, element 1. */
   private static final double E1_01 =         116092271.0 / 8848465920.0;
 
   // elements 2 to 5 are zero, so they are neither stored nor used
 
   /** First error weights array, element 6. */
   private static final double E1_06 =          -1871647.0 / 1527680.0;
 
   /** First error weights array, element 7. */
   private static final double E1_07 =         -69799717.0 / 140793660.0;
 
   /** First error weights array, element 8. */
   private static final double E1_08 =     1230164450203.0 / 739113984000.0;
 
   /** First error weights array, element 9. */
   private static final double E1_09 = -1980813971228885.0 / 5654156025964544.0;
 
   /** First error weights array, element 10. */
   private static final double E1_10 =         464500805.0 / 1389975552.0;
 
   /** First error weights array, element 11. */
   private static final double E1_11 =     1606764981773.0 / 19613062656000.0;
 
   /** First error weights array, element 12. */
   private static final double E1_12 =           -137909.0 / 6168960.0;
 
 
   /** Second error weights array, element 1. */
   private static final double E2_01 =           -364463.0 / 1920240.0;
 
   // elements 2 to 5 are zero, so they are neither stored nor used
 
   /** Second error weights array, element 6. */
   private static final double E2_06 =           3399327.0 / 763840.0;
 
   /** Second error weights array, element 7. */
   private static final double E2_07 =          66578432.0 / 35198415.0;
 
   /** Second error weights array, element 8. */
   private static final double E2_08 =       -1674902723.0 / 288716400.0;
 
   /** Second error weights array, element 9. */
   private static final double E2_09 =   -74684743568175.0 / 176692375811392.0;
 
   /** Second error weights array, element 10. */
   private static final double E2_10 =           -734375.0 / 4826304.0;
 
   /** Second error weights array, element 11. */
   private static final double E2_11 =         171414593.0 / 851261400.0;
 
   /** Second error weights array, element 12. */
   private static final double E2_12 =             69869.0 / 3084480.0;
 
   /** Simple constructor.
    * Build an eighth order Dormand-Prince integrator with the given step bounds
    * @param minStep minimal step (sign is irrelevant, regardless of
    * integration direction, forward or backward), the last step can
    * be smaller than this
    * @param maxStep maximal step (sign is irrelevant, regardless of
    * integration direction, forward or backward), the last step can
    * be smaller than this
    * @param scalAbsoluteTolerance allowed absolute error
    * @param scalRelativeTolerance allowed relative error
    */
   public DormandPrince853Integrator(final double minStep, final double maxStep,
                                     final double scalAbsoluteTolerance,
                                     final double scalRelativeTolerance) {
     super(METHOD_NAME, true, STATIC_C, STATIC_A, STATIC_B,
           new DormandPrince853StepInterpolator(),
           minStep, maxStep, scalAbsoluteTolerance, scalRelativeTolerance);
   }
 
   /** Simple constructor.
    * Build an eighth order Dormand-Prince integrator with the given step bounds
    * @param minStep minimal step (sign is irrelevant, regardless of
    * integration direction, forward or backward), the last step can
    * be smaller than this
    * @param maxStep maximal step (sign is irrelevant, regardless of
    * integration direction, forward or backward), the last step can
    * be smaller than this
    * @param vecAbsoluteTolerance allowed absolute error
    * @param vecRelativeTolerance allowed relative error
    */
   public DormandPrince853Integrator(final double minStep, final double maxStep,
                                     final double[] vecAbsoluteTolerance,
                                     final double[] vecRelativeTolerance) {
     super(METHOD_NAME, true, STATIC_C, STATIC_A, STATIC_B,
           new DormandPrince853StepInterpolator(),
           minStep, maxStep, vecAbsoluteTolerance, vecRelativeTolerance);
   }
 
   /** {@inheritDoc} */
   @Override
   public int getOrder() {
     return 8;
   }
 
   /** {@inheritDoc} */
   @Override
   protected double estimateError(final double[][] yDotK,
                                  final double[] y0, final double[] y1,
                                  final double h) {
     double error1 = 0;
     double error2 = 0;
 
     for (int j = 0; j < mainSetDimension; ++j) {
       final double errSum1 = E1_01 * yDotK[0][j]  + E1_06 * yDotK[5][j] +
                              E1_07 * yDotK[6][j]  + E1_08 * yDotK[7][j] +
                              E1_09 * yDotK[8][j]  + E1_10 * yDotK[9][j] +
                              E1_11 * yDotK[10][j] + E1_12 * yDotK[11][j];
       final double errSum2 = E2_01 * yDotK[0][j]  + E2_06 * yDotK[5][j] +
                              E2_07 * yDotK[6][j]  + E2_08 * yDotK[7][j] +
                              E2_09 * yDotK[8][j]  + E2_10 * yDotK[9][j] +
                              E2_11 * yDotK[10][j] + E2_12 * yDotK[11][j];
 
       final double yScale = JdkMath.max(JdkMath.abs(y0[j]), JdkMath.abs(y1[j]));
       final double tol = (vecAbsoluteTolerance == null) ?
                          (scalAbsoluteTolerance + scalRelativeTolerance * yScale) :
                          (vecAbsoluteTolerance[j] + vecRelativeTolerance[j] * yScale);
       final double ratio1  = errSum1 / tol;
       error1        += ratio1 * ratio1;
       final double ratio2  = errSum2 / tol;
       error2        += ratio2 * ratio2;
     }
 
     double den = error1 + 0.01 * error2;
     if (den <= 0.0) {
       den = 1.0;
     }
 
     return JdkMath.abs(h) * error1 / JdkMath.sqrt(mainSetDimension * den);
   }
 }