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📄 dormandprince853integrator.java

📁 Apache的common math数学软件包
💻 JAVA
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/* * 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.math.ode;/** * 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> * * @version $Revision: 620312 $ $Date: 2008-02-10 12:28:59 -0700 (Sun, 10 Feb 2008) $ * @since 1.2 */public class DormandPrince853Integrator  extends EmbeddedRungeKuttaIntegrator {  /** Integrator method name. */  private static final String methodName = "Dormand-Prince 8 (5, 3)";  /** Time steps Butcher array. */  private static final double[] staticC = {    (12.0 - 2.0 * Math.sqrt(6.0)) / 135.0, (6.0 - Math.sqrt(6.0)) / 45.0, (6.0 - Math.sqrt(6.0)) / 30.0,    (6.0 + Math.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[][] staticA = {    // k2    {(12.0 - 2.0 * Math.sqrt(6.0)) / 135.0},    // k3    {(6.0 - Math.sqrt(6.0)) / 180.0, (6.0 - Math.sqrt(6.0)) / 60.0},    // k4    {(6.0 - Math.sqrt(6.0)) / 120.0, 0.0, (6.0 - Math.sqrt(6.0)) / 40.0},    // k5    {(462.0 + 107.0 * Math.sqrt(6.0)) / 3000.0, 0.0,     (-402.0 - 197.0 * Math.sqrt(6.0)) / 1000.0, (168.0 + 73.0 * Math.sqrt(6.0)) / 375.0},    // k6    {1.0 / 27.0, 0.0, 0.0, (16.0 + Math.sqrt(6.0)) / 108.0, (16.0 - Math.sqrt(6.0)) / 108.0},    // k7    {19.0 / 512.0, 0.0, 0.0, (118.0 + 23.0 * Math.sqrt(6.0)) / 1024.0,     (118.0 - 23.0 * Math.sqrt(6.0)) / 1024.0, -9.0 / 512.0},    // k8    {13772.0 / 371293.0, 0.0, 0.0, (51544.0 + 4784.0 * Math.sqrt(6.0)) / 371293.0,     (51544.0 - 4784.0 * Math.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 * Math.sqrt(6.0)) / 626556937500.0,     (-1324889724104.0 + 318801444819.0 * Math.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 * Math.sqrt(6.0)) / 2937500.0,     (-4521408.0 + 1137963.0 * Math.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 * Math.sqrt(6.0)) / 112847.0,     (354216.0 - 94326.0 * Math.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 * Math.sqrt(6.0)) / 551636.0,     (-3457480.0 + 960905.0 * Math.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[] staticB = {      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 (must be positive even for backward   * integration), the last step can be smaller than this   * @param maxStep maximal step (must be positive even for backward   * integration)   * @param scalAbsoluteTolerance allowed absolute error   * @param scalRelativeTolerance allowed relative error   */  public DormandPrince853Integrator(double minStep, double maxStep,                                    double scalAbsoluteTolerance,                                    double scalRelativeTolerance) {    super(true, staticC, staticA, staticB,          new DormandPrince853StepInterpolator(),          minStep, maxStep, scalAbsoluteTolerance, scalRelativeTolerance);  }  /** Simple constructor.   * Build an eighth order Dormand-Prince integrator with the given step bounds   * @param minStep minimal step (must be positive even for backward   * integration), the last step can be smaller than this   * @param maxStep maximal step (must be positive even for backward   * integration)   * @param vecAbsoluteTolerance allowed absolute error   * @param vecRelativeTolerance allowed relative error   */  public DormandPrince853Integrator(double minStep, double maxStep,                                    double[] vecAbsoluteTolerance,                                    double[] vecRelativeTolerance) {    super(true, staticC, staticA, staticB,          new DormandPrince853StepInterpolator(),          minStep, maxStep, vecAbsoluteTolerance, vecRelativeTolerance);  }  /** Get the name of the method.   * @return name of the method   */  public String getName() {    return methodName;  }  /** Get the order of the method.   * @return order of the method   */  public int getOrder() {    return 8;  }  /** Compute the error ratio.   * @param yDotK derivatives computed during the first stages   * @param y0 estimate of the step at the start of the step   * @param y1 estimate of the step at the end of the step   * @param h  current step   * @return error ratio, greater than 1 if step should be rejected   */  protected double estimateError(double[][] yDotK,                                 double[] y0, double[] y1,                                 double h) {    double error1 = 0;    double error2 = 0;    for (int j = 0; j < y0.length; ++j) {      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];      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];      double yScale = Math.max(Math.abs(y0[j]), Math.abs(y1[j]));      double tol = (vecAbsoluteTolerance == null) ?                   (scalAbsoluteTolerance + scalRelativeTolerance * yScale) :                   (vecAbsoluteTolerance[j] + vecRelativeTolerance[j] * yScale);      double ratio1  = errSum1 / tol;      error1        += ratio1 * ratio1;      double ratio2  = errSum2 / tol;      error2        += ratio2 * ratio2;    }    double den = error1 + 0.01 * error2;    if (den <= 0.0) {      den = 1.0;    }    return Math.abs(h) * error1 / Math.sqrt(y0.length * den);  }}

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