    001    /*
    002     * Licensed to the Apache Software Foundation (ASF) under one or more
    003     * contributor license agreements.  See the NOTICE file distributed with
    004     * this work for additional information regarding copyright ownership.
    005     * The ASF licenses this file to You under the Apache License, Version 2.0
    006     * (the "License"); you may not use this file except in compliance with
    007     * the License.  You may obtain a copy of the License at
    008     *
    009     *      http://www.apache.org/licenses/LICENSE-2.0
    010     *
    011     * Unless required by applicable law or agreed to in writing, software
    012     * distributed under the License is distributed on an "AS IS" BASIS,
    013     * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
    014     * See the License for the specific language governing permissions and
    015     * limitations under the License.
    016     */
    017
    018    package org.apache.commons.math.ode.nonstiff;
    019
    020    import org.apache.commons.math.util.FastMath;
    021
    022
    023    /**
    024     * This class implements the 8(5,3) Dormand-Prince integrator for Ordinary
    025     * Differential Equations.
    026     *
    027     * <p>This integrator is an embedded Runge-Kutta integrator
    028     * of order 8(5,3) used in local extrapolation mode (i.e. the solution
    029     * is computed using the high order formula) with stepsize control
    030     * (and automatic step initialization) and continuous output. This
    031     * method uses 12 functions evaluations per step for integration and 4
    032     * evaluations for interpolation. However, since the first
    033     * interpolation evaluation is the same as the first integration
    034     * evaluation of the next step, we have included it in the integrator
    035     * rather than in the interpolator and specified the method was an
    036     * <i>fsal</i>. Hence, despite we have 13 stages here, the cost is
    037     * really 12 evaluations per step even if no interpolation is done,
    038     * and the overcost of interpolation is only 3 evaluations.</p>
    039     *
    040     * <p>This method is based on an 8(6) method by Dormand and Prince
    041     * (i.e. order 8 for the integration and order 6 for error estimation)
    042     * modified by Hairer and Wanner to use a 5th order error estimator
    043     * with 3rd order correction. This modification was introduced because
    044     * the original method failed in some cases (wrong steps can be
    045     * accepted when step size is too large, for example in the
    046     * Brusselator problem) and also had <i>severe difficulties when
    047     * applied to problems with discontinuities</i>. This modification is
    048     * explained in the second edition of the first volume (Nonstiff
    049     * Problems) of the reference book by Hairer, Norsett and Wanner:
    050     * <i>Solving Ordinary Differential Equations</i> (Springer-Verlag,
    051     * ISBN 3-540-56670-8).</p>
    052     *
    053     * @version $Revision: 990655 $ $Date: 2010-08-29 23:49:40 +0200 (dim. 29 ao??t 2010) $
    054     * @since 1.2
    055     */
    056
    057    public class DormandPrince853Integrator extends EmbeddedRungeKuttaIntegrator {
    058
    059      /** Integrator method name. */
    060      private static final String METHOD_NAME = "Dormand-Prince 8 (5, 3)";
    061
    062      /** Time steps Butcher array. */
    063      private static final double[] STATIC_C = {
    064        (12.0 - 2.0 * FastMath.sqrt(6.0)) / 135.0, (6.0 - FastMath.sqrt(6.0)) / 45.0, (6.0 - FastMath.sqrt(6.0)) / 30.0,
    065        (6.0 + FastMath.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,
    066        6.0/7.0, 1.0, 1.0
    067      };
    068
    069      /** Internal weights Butcher array. */
    070      private static final double[][] STATIC_A = {
    071
    072        // k2
    073        {(12.0 - 2.0 * FastMath.sqrt(6.0)) / 135.0},
    074
    075        // k3
    076        {(6.0 - FastMath.sqrt(6.0)) / 180.0, (6.0 - FastMath.sqrt(6.0)) / 60.0},
    077
    078        // k4
    079        {(6.0 - FastMath.sqrt(6.0)) / 120.0, 0.0, (6.0 - FastMath.sqrt(6.0)) / 40.0},
    080
    081        // k5
    082        {(462.0 + 107.0 * FastMath.sqrt(6.0)) / 3000.0, 0.0,
    083         (-402.0 - 197.0 * FastMath.sqrt(6.0)) / 1000.0, (168.0 + 73.0 * FastMath.sqrt(6.0)) / 375.0},
    084
    085        // k6
    086        {1.0 / 27.0, 0.0, 0.0, (16.0 + FastMath.sqrt(6.0)) / 108.0, (16.0 - FastMath.sqrt(6.0)) / 108.0},
    087
    088        // k7
    089        {19.0 / 512.0, 0.0, 0.0, (118.0 + 23.0 * FastMath.sqrt(6.0)) / 1024.0,
    090         (118.0 - 23.0 * FastMath.sqrt(6.0)) / 1024.0, -9.0 / 512.0},
    091
    092        // k8
    093        {13772.0 / 371293.0, 0.0, 0.0, (51544.0 + 4784.0 * FastMath.sqrt(6.0)) / 371293.0,
    094         (51544.0 - 4784.0 * FastMath.sqrt(6.0)) / 371293.0, -5688.0 / 371293.0, 3072.0 / 371293.0},
    095
    096        // k9
    097        {58656157643.0 / 93983540625.0, 0.0, 0.0,
    098         (-1324889724104.0 - 318801444819.0 * FastMath.sqrt(6.0)) / 626556937500.0,
    099         (-1324889724104.0 + 318801444819.0 * FastMath.sqrt(6.0)) / 626556937500.0,
    100         96044563816.0 / 3480871875.0, 5682451879168.0 / 281950621875.0,
    101         -165125654.0 / 3796875.0},
    102
    103        // k10
    104        {8909899.0 / 18653125.0, 0.0, 0.0,
    105         (-4521408.0 - 1137963.0 * FastMath.sqrt(6.0)) / 2937500.0,
    106         (-4521408.0 + 1137963.0 * FastMath.sqrt(6.0)) / 2937500.0,
    107         96663078.0 / 4553125.0, 2107245056.0 / 137915625.0,
    108         -4913652016.0 / 147609375.0, -78894270.0 / 3880452869.0},
    109
    110        // k11
    111        {-20401265806.0 / 21769653311.0, 0.0, 0.0,
    112         (354216.0 + 94326.0 * FastMath.sqrt(6.0)) / 112847.0,
    113         (354216.0 - 94326.0 * FastMath.sqrt(6.0)) / 112847.0,
    114         -43306765128.0 / 5313852383.0, -20866708358144.0 / 1126708119789.0,
    115         14886003438020.0 / 654632330667.0, 35290686222309375.0 / 14152473387134411.0,
    116         -1477884375.0 / 485066827.0},
    117
    118        // k12
    119        {39815761.0 / 17514443.0, 0.0, 0.0,
    120         (-3457480.0 - 960905.0 * FastMath.sqrt(6.0)) / 551636.0,
    121         (-3457480.0 + 960905.0 * FastMath.sqrt(6.0)) / 551636.0,
    122         -844554132.0 / 47026969.0, 8444996352.0 / 302158619.0,
    123         -2509602342.0 / 877790785.0, -28388795297996250.0 / 3199510091356783.0,
    124         226716250.0 / 18341897.0, 1371316744.0 / 2131383595.0},
    125
    126        // k13 should be for interpolation only, but since it is the same
    127        // stage as the first evaluation of the next step, we perform it
    128        // here at no cost by specifying this is an fsal method
    129        {104257.0/1920240.0, 0.0, 0.0, 0.0, 0.0, 3399327.0/763840.0,
    130         66578432.0/35198415.0, -1674902723.0/288716400.0,
    131         54980371265625.0/176692375811392.0, -734375.0/4826304.0,
    132         171414593.0/851261400.0, 137909.0/3084480.0}
    133
    134      };
    135
    136      /** Propagation weights Butcher array. */
    137      private static final double[] STATIC_B = {
    138          104257.0/1920240.0,
    139          0.0,
    140          0.0,
    141          0.0,
    142          0.0,
    143          3399327.0/763840.0,
    144          66578432.0/35198415.0,
    145          -1674902723.0/288716400.0,
    146          54980371265625.0/176692375811392.0,
    147          -734375.0/4826304.0,
    148          171414593.0/851261400.0,
    149          137909.0/3084480.0,
    150          0.0
    151      };
    152
    153      /** First error weights array, element 1. */
    154      private static final double E1_01 =         116092271.0 / 8848465920.0;
    155
    156      // elements 2 to 5 are zero, so they are neither stored nor used
    157
    158      /** First error weights array, element 6. */
    159      private static final double E1_06 =          -1871647.0 / 1527680.0;
    160
    161      /** First error weights array, element 7. */
    162      private static final double E1_07 =         -69799717.0 / 140793660.0;
    163
    164      /** First error weights array, element 8. */
    165      private static final double E1_08 =     1230164450203.0 / 739113984000.0;
    166
    167      /** First error weights array, element 9. */
    168      private static final double E1_09 = -1980813971228885.0 / 5654156025964544.0;
    169
    170      /** First error weights array, element 10. */
    171      private static final double E1_10 =         464500805.0 / 1389975552.0;
    172
    173      /** First error weights array, element 11. */
    174      private static final double E1_11 =     1606764981773.0 / 19613062656000.0;
    175
    176      /** First error weights array, element 12. */
    177      private static final double E1_12 =           -137909.0 / 6168960.0;
    178
    179
    180      /** Second error weights array, element 1. */
    181      private static final double E2_01 =           -364463.0 / 1920240.0;
    182
    183      // elements 2 to 5 are zero, so they are neither stored nor used
    184
    185      /** Second error weights array, element 6. */
    186      private static final double E2_06 =           3399327.0 / 763840.0;
    187
    188      /** Second error weights array, element 7. */
    189      private static final double E2_07 =          66578432.0 / 35198415.0;
    190
    191      /** Second error weights array, element 8. */
    192      private static final double E2_08 =       -1674902723.0 / 288716400.0;
    193
    194      /** Second error weights array, element 9. */
    195      private static final double E2_09 =   -74684743568175.0 / 176692375811392.0;
    196
    197      /** Second error weights array, element 10. */
    198      private static final double E2_10 =           -734375.0 / 4826304.0;
    199
    200      /** Second error weights array, element 11. */
    201      private static final double E2_11 =         171414593.0 / 851261400.0;
    202
    203      /** Second error weights array, element 12. */
    204      private static final double E2_12 =             69869.0 / 3084480.0;
    205
    206      /** Simple constructor.
    207       * Build an eighth order Dormand-Prince integrator with the given step bounds
    208       * @param minStep minimal step (must be positive even for backward
    209       * integration), the last step can be smaller than this
    210       * @param maxStep maximal step (must be positive even for backward
    211       * integration)
    212       * @param scalAbsoluteTolerance allowed absolute error
    213       * @param scalRelativeTolerance allowed relative error
    214       */
    215      public DormandPrince853Integrator(final double minStep, final double maxStep,
    216                                        final double scalAbsoluteTolerance,
    217                                        final double scalRelativeTolerance) {
    218        super(METHOD_NAME, true, STATIC_C, STATIC_A, STATIC_B,
    219              new DormandPrince853StepInterpolator(),
    220              minStep, maxStep, scalAbsoluteTolerance, scalRelativeTolerance);
    221      }
    222
    223      /** Simple constructor.
    224       * Build an eighth order Dormand-Prince integrator with the given step bounds
    225       * @param minStep minimal step (must be positive even for backward
    226       * integration), the last step can be smaller than this
    227       * @param maxStep maximal step (must be positive even for backward
    228       * integration)
    229       * @param vecAbsoluteTolerance allowed absolute error
    230       * @param vecRelativeTolerance allowed relative error
    231       */
    232      public DormandPrince853Integrator(final double minStep, final double maxStep,
    233                                        final double[] vecAbsoluteTolerance,
    234                                        final double[] vecRelativeTolerance) {
    235        super(METHOD_NAME, true, STATIC_C, STATIC_A, STATIC_B,
    236              new DormandPrince853StepInterpolator(),
    237              minStep, maxStep, vecAbsoluteTolerance, vecRelativeTolerance);
    238      }
    239
    240      /** {@inheritDoc} */
    241      @Override
    242      public int getOrder() {
    243        return 8;
    244      }
    245
    246      /** {@inheritDoc} */
    247      @Override
    248      protected double estimateError(final double[][] yDotK,
    249                                     final double[] y0, final double[] y1,
    250                                     final double h) {
    251        double error1 = 0;
    252        double error2 = 0;
    253
    254        for (int j = 0; j < mainSetDimension; ++j) {
    255          final double errSum1 = E1_01 * yDotK[0][j]  + E1_06 * yDotK[5][j] +
    256                                 E1_07 * yDotK[6][j]  + E1_08 * yDotK[7][j] +
    257                                 E1_09 * yDotK[8][j]  + E1_10 * yDotK[9][j] +
    258                                 E1_11 * yDotK[10][j] + E1_12 * yDotK[11][j];
    259          final double errSum2 = E2_01 * yDotK[0][j]  + E2_06 * yDotK[5][j] +
    260                                 E2_07 * yDotK[6][j]  + E2_08 * yDotK[7][j] +
    261                                 E2_09 * yDotK[8][j]  + E2_10 * yDotK[9][j] +
    262                                 E2_11 * yDotK[10][j] + E2_12 * yDotK[11][j];
    263
    264          final double yScale = FastMath.max(FastMath.abs(y0[j]), FastMath.abs(y1[j]));
    265          final double tol = (vecAbsoluteTolerance == null) ?
    266                             (scalAbsoluteTolerance + scalRelativeTolerance * yScale) :
    267                             (vecAbsoluteTolerance[j] + vecRelativeTolerance[j] * yScale);
    268          final double ratio1  = errSum1 / tol;
    269          error1        += ratio1 * ratio1;
    270          final double ratio2  = errSum2 / tol;
    271          error2        += ratio2 * ratio2;
    272        }
    273
    274        double den = error1 + 0.01 * error2;
    275        if (den <= 0.0) {
    276          den = 1.0;
    277        }
    278
    279        return FastMath.abs(h) * error1 / FastMath.sqrt(mainSetDimension * den);
    280
    281      }
    282
    283    }