2
* Licensed to the Apache Software Foundation (ASF) under one or more
3
* contributor license agreements. See the NOTICE file distributed with
4
* this work for additional information regarding copyright ownership.
5
* The ASF licenses this file to You under the Apache License, Version 2.0
6
* (the "License"); you may not use this file except in compliance with
7
* the License. You may obtain a copy of the License at
9
* http://www.apache.org/licenses/LICENSE-2.0
11
* Unless required by applicable law or agreed to in writing, software
12
* distributed under the License is distributed on an "AS IS" BASIS,
13
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14
* See the License for the specific language governing permissions and
15
* limitations under the License.
18
package org.apache.commons.math.ode;
21
* This class implements the 5(4) Dormand-Prince integrator for Ordinary
22
* Differential Equations.
24
* <p>This integrator is an embedded Runge-Kutta integrator
25
* of order 5(4) used in local extrapolation mode (i.e. the solution
26
* is computed using the high order formula) with stepsize control
27
* (and automatic step initialization) and continuous output. This
28
* method uses 7 functions evaluations per step. However, since this
29
* is an <i>fsal</i>, the last evaluation of one step is the same as
30
* the first evaluation of the next step and hence can be avoided. So
31
* the cost is really 6 functions evaluations per step.</p>
33
* <p>This method has been published (whithout the continuous output
34
* that was added by Shampine in 1986) in the following article :
36
* A family of embedded Runge-Kutta formulae
37
* J. R. Dormand and P. J. Prince
38
* Journal of Computational and Applied Mathematics
39
* volume 6, no 1, 1980, pp. 19-26
42
* @version $Revision: 620312 $ $Date: 2008-02-10 12:28:59 -0700 (Sun, 10 Feb 2008) $
46
public class DormandPrince54Integrator
47
extends EmbeddedRungeKuttaIntegrator {
49
/** Integrator method name. */
50
private static final String methodName = "Dormand-Prince 5(4)";
52
/** Time steps Butcher array. */
53
private static final double[] staticC = {
54
1.0/5.0, 3.0/10.0, 4.0/5.0, 8.0/9.0, 1.0, 1.0
57
/** Internal weights Butcher array. */
58
private static final double[][] staticA = {
61
{44.0/45.0, -56.0/15.0, 32.0/9.0},
62
{19372.0/6561.0, -25360.0/2187.0, 64448.0/6561.0, -212.0/729.0},
63
{9017.0/3168.0, -355.0/33.0, 46732.0/5247.0, 49.0/176.0, -5103.0/18656.0},
64
{35.0/384.0, 0.0, 500.0/1113.0, 125.0/192.0, -2187.0/6784.0, 11.0/84.0}
67
/** Propagation weights Butcher array. */
68
private static final double[] staticB = {
69
35.0/384.0, 0.0, 500.0/1113.0, 125.0/192.0, -2187.0/6784.0, 11.0/84.0, 0.0
72
/** Error array, element 1. */
73
private static final double e1 = 71.0 / 57600.0;
75
// element 2 is zero, so it is neither stored nor used
77
/** Error array, element 3. */
78
private static final double e3 = -71.0 / 16695.0;
80
/** Error array, element 4. */
81
private static final double e4 = 71.0 / 1920.0;
83
/** Error array, element 5. */
84
private static final double e5 = -17253.0 / 339200.0;
86
/** Error array, element 6. */
87
private static final double e6 = 22.0 / 525.0;
89
/** Error array, element 7. */
90
private static final double e7 = -1.0 / 40.0;
92
/** Simple constructor.
93
* Build a fifth order Dormand-Prince integrator with the given step bounds
94
* @param minStep minimal step (must be positive even for backward
95
* integration), the last step can be smaller than this
96
* @param maxStep maximal step (must be positive even for backward
98
* @param scalAbsoluteTolerance allowed absolute error
99
* @param scalRelativeTolerance allowed relative error
101
public DormandPrince54Integrator(double minStep, double maxStep,
102
double scalAbsoluteTolerance,
103
double scalRelativeTolerance) {
104
super(true, staticC, staticA, staticB, new DormandPrince54StepInterpolator(),
105
minStep, maxStep, scalAbsoluteTolerance, scalRelativeTolerance);
108
/** Simple constructor.
109
* Build a fifth order Dormand-Prince integrator with the given step bounds
110
* @param minStep minimal step (must be positive even for backward
111
* integration), the last step can be smaller than this
112
* @param maxStep maximal step (must be positive even for backward
114
* @param vecAbsoluteTolerance allowed absolute error
115
* @param vecRelativeTolerance allowed relative error
117
public DormandPrince54Integrator(double minStep, double maxStep,
118
double[] vecAbsoluteTolerance,
119
double[] vecRelativeTolerance) {
120
super(true, staticC, staticA, staticB, new DormandPrince54StepInterpolator(),
121
minStep, maxStep, vecAbsoluteTolerance, vecRelativeTolerance);
124
/** Get the name of the method.
125
* @return name of the method
127
public String getName() {
131
/** Get the order of the method.
132
* @return order of the method
134
public int getOrder() {
138
/** Compute the error ratio.
139
* @param yDotK derivatives computed during the first stages
140
* @param y0 estimate of the step at the start of the step
141
* @param y1 estimate of the step at the end of the step
142
* @param h current step
143
* @return error ratio, greater than 1 if step should be rejected
145
protected double estimateError(double[][] yDotK,
146
double[] y0, double[] y1,
151
for (int j = 0; j < y0.length; ++j) {
152
double errSum = e1 * yDotK[0][j] + e3 * yDotK[2][j] +
153
e4 * yDotK[3][j] + e5 * yDotK[4][j] +
154
e6 * yDotK[5][j] + e7 * yDotK[6][j];
156
double yScale = Math.max(Math.abs(y0[j]), Math.abs(y1[j]));
157
double tol = (vecAbsoluteTolerance == null) ?
158
(scalAbsoluteTolerance + scalRelativeTolerance * yScale) :
159
(vecAbsoluteTolerance[j] + vecRelativeTolerance[j] * yScale);
160
double ratio = h * errSum / tol;
161
error += ratio * ratio;
165
return Math.sqrt(error / y0.length);