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1   /*
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
8    *
9    *      http://www.apache.org/licenses/LICENSE-2.0
10   *
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.
16   */
17  
18  package org.apache.commons.math3.ode;
19  
20  import org.apache.commons.math3.exception.DimensionMismatchException;
21  import org.apache.commons.math3.exception.MaxCountExceededException;
22  import org.apache.commons.math3.exception.NoBracketingException;
23  import org.apache.commons.math3.exception.NumberIsTooSmallException;
24  import org.apache.commons.math3.exception.util.LocalizedFormats;
25  import org.apache.commons.math3.linear.Array2DRowRealMatrix;
26  import org.apache.commons.math3.ode.nonstiff.AdaptiveStepsizeIntegrator;
27  import org.apache.commons.math3.ode.nonstiff.DormandPrince853Integrator;
28  import org.apache.commons.math3.ode.sampling.StepHandler;
29  import org.apache.commons.math3.ode.sampling.StepInterpolator;
30  import org.apache.commons.math3.util.FastMath;
31  
32  /**
33   * This class is the base class for multistep integrators for Ordinary
34   * Differential Equations.
35   * <p>We define scaled derivatives s<sub>i</sub>(n) at step n as:
36   * <pre>
37   * s<sub>1</sub>(n) = h y'<sub>n</sub> for first derivative
38   * s<sub>2</sub>(n) = h<sup>2</sup>/2 y''<sub>n</sub> for second derivative
39   * s<sub>3</sub>(n) = h<sup>3</sup>/6 y'''<sub>n</sub> for third derivative
40   * ...
41   * s<sub>k</sub>(n) = h<sup>k</sup>/k! y<sup>(k)</sup><sub>n</sub> for k<sup>th</sup> derivative
42   * </pre></p>
43   * <p>Rather than storing several previous steps separately, this implementation uses
44   * the Nordsieck vector with higher degrees scaled derivatives all taken at the same
45   * step (y<sub>n</sub>, s<sub>1</sub>(n) and r<sub>n</sub>) where r<sub>n</sub> is defined as:
46   * <pre>
47   * r<sub>n</sub> = [ s<sub>2</sub>(n), s<sub>3</sub>(n) ... s<sub>k</sub>(n) ]<sup>T</sup>
48   * </pre>
49   * (we omit the k index in the notation for clarity)</p>
50   * <p>
51   * Multistep integrators with Nordsieck representation are highly sensitive to
52   * large step changes because when the step is multiplied by factor a, the
53   * k<sup>th</sup> component of the Nordsieck vector is multiplied by a<sup>k</sup>
54   * and the last components are the least accurate ones. The default max growth
55   * factor is therefore set to a quite low value: 2<sup>1/order</sup>.
56   * </p>
57   *
58   * @see org.apache.commons.math3.ode.nonstiff.AdamsBashforthIntegrator
59   * @see org.apache.commons.math3.ode.nonstiff.AdamsMoultonIntegrator
60   * @version $Id: MultistepIntegrator.java 1463684 2013-04-02 19:04:13Z luc $
61   * @since 2.0
62   */
63  public abstract class MultistepIntegrator extends AdaptiveStepsizeIntegrator {
64  
65      /** First scaled derivative (h y'). */
66      protected double[] scaled;
67  
68      /** Nordsieck matrix of the higher scaled derivatives.
69       * <p>(h<sup>2</sup>/2 y'', h<sup>3</sup>/6 y''' ..., h<sup>k</sup>/k! y<sup>(k)</sup>)</p>
70       */
71      protected Array2DRowRealMatrix nordsieck;
72  
73      /** Starter integrator. */
74      private FirstOrderIntegrator starter;
75  
76      /** Number of steps of the multistep method (excluding the one being computed). */
77      private final int nSteps;
78  
79      /** Stepsize control exponent. */
80      private double exp;
81  
82      /** Safety factor for stepsize control. */
83      private double safety;
84  
85      /** Minimal reduction factor for stepsize control. */
86      private double minReduction;
87  
88      /** Maximal growth factor for stepsize control. */
89      private double maxGrowth;
90  
91      /**
92       * Build a multistep integrator with the given stepsize bounds.
93       * <p>The default starter integrator is set to the {@link
94       * DormandPrince853Integrator Dormand-Prince 8(5,3)} integrator with
95       * some defaults settings.</p>
96       * <p>
97       * The default max growth factor is set to a quite low value: 2<sup>1/order</sup>.
98       * </p>
99       * @param name name of the method
100      * @param nSteps number of steps of the multistep method
101      * (excluding the one being computed)
102      * @param order order of the method
103      * @param minStep minimal step (must be positive even for backward
104      * integration), the last step can be smaller than this
105      * @param maxStep maximal step (must be positive even for backward
106      * integration)
107      * @param scalAbsoluteTolerance allowed absolute error
108      * @param scalRelativeTolerance allowed relative error
109      * @exception NumberIsTooSmallException if number of steps is smaller than 2
110      */
111     protected MultistepIntegrator(final String name, final int nSteps,
112                                   final int order,
113                                   final double minStep, final double maxStep,
114                                   final double scalAbsoluteTolerance,
115                                   final double scalRelativeTolerance)
116         throws NumberIsTooSmallException {
117 
118         super(name, minStep, maxStep, scalAbsoluteTolerance, scalRelativeTolerance);
119 
120         if (nSteps < 2) {
121             throw new NumberIsTooSmallException(
122                   LocalizedFormats.INTEGRATION_METHOD_NEEDS_AT_LEAST_TWO_PREVIOUS_POINTS,
123                   nSteps, 2, true);
124         }
125 
126         starter = new DormandPrince853Integrator(minStep, maxStep,
127                                                  scalAbsoluteTolerance,
128                                                  scalRelativeTolerance);
129         this.nSteps = nSteps;
130 
131         exp = -1.0 / order;
132 
133         // set the default values of the algorithm control parameters
134         setSafety(0.9);
135         setMinReduction(0.2);
136         setMaxGrowth(FastMath.pow(2.0, -exp));
137 
138     }
139 
140     /**
141      * Build a multistep integrator with the given stepsize bounds.
142      * <p>The default starter integrator is set to the {@link
143      * DormandPrince853Integrator Dormand-Prince 8(5,3)} integrator with
144      * some defaults settings.</p>
145      * <p>
146      * The default max growth factor is set to a quite low value: 2<sup>1/order</sup>.
147      * </p>
148      * @param name name of the method
149      * @param nSteps number of steps of the multistep method
150      * (excluding the one being computed)
151      * @param order order of the method
152      * @param minStep minimal step (must be positive even for backward
153      * integration), the last step can be smaller than this
154      * @param maxStep maximal step (must be positive even for backward
155      * integration)
156      * @param vecAbsoluteTolerance allowed absolute error
157      * @param vecRelativeTolerance allowed relative error
158      */
159     protected MultistepIntegrator(final String name, final int nSteps,
160                                   final int order,
161                                   final double minStep, final double maxStep,
162                                   final double[] vecAbsoluteTolerance,
163                                   final double[] vecRelativeTolerance) {
164         super(name, minStep, maxStep, vecAbsoluteTolerance, vecRelativeTolerance);
165         starter = new DormandPrince853Integrator(minStep, maxStep,
166                                                  vecAbsoluteTolerance,
167                                                  vecRelativeTolerance);
168         this.nSteps = nSteps;
169 
170         exp = -1.0 / order;
171 
172         // set the default values of the algorithm control parameters
173         setSafety(0.9);
174         setMinReduction(0.2);
175         setMaxGrowth(FastMath.pow(2.0, -exp));
176 
177     }
178 
179     /**
180      * Get the starter integrator.
181      * @return starter integrator
182      */
183     public ODEIntegrator getStarterIntegrator() {
184         return starter;
185     }
186 
187     /**
188      * Set the starter integrator.
189      * <p>The various step and event handlers for this starter integrator
190      * will be managed automatically by the multi-step integrator. Any
191      * user configuration for these elements will be cleared before use.</p>
192      * @param starterIntegrator starter integrator
193      */
194     public void setStarterIntegrator(FirstOrderIntegrator starterIntegrator) {
195         this.starter = starterIntegrator;
196     }
197 
198     /** Start the integration.
199      * <p>This method computes one step using the underlying starter integrator,
200      * and initializes the Nordsieck vector at step start. The starter integrator
201      * purpose is only to establish initial conditions, it does not really change
202      * time by itself. The top level multistep integrator remains in charge of
203      * handling time propagation and events handling as it will starts its own
204      * computation right from the beginning. In a sense, the starter integrator
205      * can be seen as a dummy one and so it will never trigger any user event nor
206      * call any user step handler.</p>
207      * @param t0 initial time
208      * @param y0 initial value of the state vector at t0
209      * @param t target time for the integration
210      * (can be set to a value smaller than <code>t0</code> for backward integration)
211      * @exception DimensionMismatchException if arrays dimension do not match equations settings
212      * @exception NumberIsTooSmallException if integration step is too small
213      * @exception MaxCountExceededException if the number of functions evaluations is exceeded
214      * @exception NoBracketingException if the location of an event cannot be bracketed
215      */
216     protected void start(final double t0, final double[] y0, final double t)
217         throws DimensionMismatchException, NumberIsTooSmallException,
218                MaxCountExceededException, NoBracketingException {
219 
220         // make sure NO user event nor user step handler is triggered,
221         // this is the task of the top level integrator, not the task
222         // of the starter integrator
223         starter.clearEventHandlers();
224         starter.clearStepHandlers();
225 
226         // set up one specific step handler to extract initial Nordsieck vector
227         starter.addStepHandler(new NordsieckInitializer(nSteps, y0.length));
228 
229         // start integration, expecting a InitializationCompletedMarkerException
230         try {
231 
232             if (starter instanceof AbstractIntegrator) {
233                 ((AbstractIntegrator) starter).integrate(getExpandable(), t);
234             } else {
235                 starter.integrate(new FirstOrderDifferentialEquations() {
236 
237                     /** {@inheritDoc} */
238                     public int getDimension() {
239                         return getExpandable().getTotalDimension();
240                     }
241 
242                     /** {@inheritDoc} */
243                     public void computeDerivatives(double t, double[] y, double[] yDot) {
244                         getExpandable().computeDerivatives(t, y, yDot);
245                     }
246 
247                 }, t0, y0, t, new double[y0.length]);
248             }
249 
250         } catch (InitializationCompletedMarkerException icme) { // NOPMD
251             // this is the expected nominal interruption of the start integrator
252 
253             // count the evaluations used by the starter
254             getEvaluationsCounter().incrementCount(starter.getEvaluations());
255 
256         }
257 
258         // remove the specific step handler
259         starter.clearStepHandlers();
260 
261     }
262 
263     /** Initialize the high order scaled derivatives at step start.
264      * @param h step size to use for scaling
265      * @param t first steps times
266      * @param y first steps states
267      * @param yDot first steps derivatives
268      * @return Nordieck vector at first step (h<sup>2</sup>/2 y''<sub>n</sub>,
269      * h<sup>3</sup>/6 y'''<sub>n</sub> ... h<sup>k</sup>/k! y<sup>(k)</sup><sub>n</sub>)
270      */
271     protected abstract Array2DRowRealMatrix initializeHighOrderDerivatives(final double h, final double[] t,
272                                                                            final double[][] y,
273                                                                            final double[][] yDot);
274 
275     /** Get the minimal reduction factor for stepsize control.
276      * @return minimal reduction factor
277      */
278     public double getMinReduction() {
279         return minReduction;
280     }
281 
282     /** Set the minimal reduction factor for stepsize control.
283      * @param minReduction minimal reduction factor
284      */
285     public void setMinReduction(final double minReduction) {
286         this.minReduction = minReduction;
287     }
288 
289     /** Get the maximal growth factor for stepsize control.
290      * @return maximal growth factor
291      */
292     public double getMaxGrowth() {
293         return maxGrowth;
294     }
295 
296     /** Set the maximal growth factor for stepsize control.
297      * @param maxGrowth maximal growth factor
298      */
299     public void setMaxGrowth(final double maxGrowth) {
300         this.maxGrowth = maxGrowth;
301     }
302 
303     /** Get the safety factor for stepsize control.
304      * @return safety factor
305      */
306     public double getSafety() {
307       return safety;
308     }
309 
310     /** Set the safety factor for stepsize control.
311      * @param safety safety factor
312      */
313     public void setSafety(final double safety) {
314       this.safety = safety;
315     }
316 
317     /** Compute step grow/shrink factor according to normalized error.
318      * @param error normalized error of the current step
319      * @return grow/shrink factor for next step
320      */
321     protected double computeStepGrowShrinkFactor(final double error) {
322         return FastMath.min(maxGrowth, FastMath.max(minReduction, safety * FastMath.pow(error, exp)));
323     }
324 
325     /** Transformer used to convert the first step to Nordsieck representation. */
326     public interface NordsieckTransformer {
327         /** Initialize the high order scaled derivatives at step start.
328          * @param h step size to use for scaling
329          * @param t first steps times
330          * @param y first steps states
331          * @param yDot first steps derivatives
332          * @return Nordieck vector at first step (h<sup>2</sup>/2 y''<sub>n</sub>,
333          * h<sup>3</sup>/6 y'''<sub>n</sub> ... h<sup>k</sup>/k! y<sup>(k)</sup><sub>n</sub>)
334          */
335         Array2DRowRealMatrix initializeHighOrderDerivatives(final double h, final double[] t,
336                                                             final double[][] y,
337                                                             final double[][] yDot);
338     }
339 
340     /** Specialized step handler storing the first step. */
341     private class NordsieckInitializer implements StepHandler {
342 
343         /** Steps counter. */
344         private int count;
345 
346         /** First steps times. */
347         private final double[] t;
348 
349         /** First steps states. */
350         private final double[][] y;
351 
352         /** First steps derivatives. */
353         private final double[][] yDot;
354 
355         /** Simple constructor.
356          * @param nSteps number of steps of the multistep method (excluding the one being computed)
357          * @param n problem dimension
358          */
359         public NordsieckInitializer(final int nSteps, final int n) {
360             this.count = 0;
361             this.t     = new double[nSteps];
362             this.y     = new double[nSteps][n];
363             this.yDot  = new double[nSteps][n];
364         }
365 
366         /** {@inheritDoc} */
367         public void handleStep(StepInterpolator interpolator, boolean isLast)
368             throws MaxCountExceededException {
369 
370             final double prev = interpolator.getPreviousTime();
371             final double curr = interpolator.getCurrentTime();
372 
373             if (count == 0) {
374                 // first step, we need to store also the beginning of the step
375                 interpolator.setInterpolatedTime(prev);
376                 t[0] = prev;
377                 final ExpandableStatefulODE expandable = getExpandable();
378                 final EquationsMapper primary = expandable.getPrimaryMapper();
379                 primary.insertEquationData(interpolator.getInterpolatedState(), y[count]);
380                 primary.insertEquationData(interpolator.getInterpolatedDerivatives(), yDot[count]);
381                 int index = 0;
382                 for (final EquationsMapper secondary : expandable.getSecondaryMappers()) {
383                     secondary.insertEquationData(interpolator.getInterpolatedSecondaryState(index), y[count]);
384                     secondary.insertEquationData(interpolator.getInterpolatedSecondaryDerivatives(index), yDot[count]);
385                     ++index;
386                 }
387             }
388 
389             // store the end of the step
390             ++count;
391             interpolator.setInterpolatedTime(curr);
392             t[count] = curr;
393 
394             final ExpandableStatefulODE expandable = getExpandable();
395             final EquationsMapper primary = expandable.getPrimaryMapper();
396             primary.insertEquationData(interpolator.getInterpolatedState(), y[count]);
397             primary.insertEquationData(interpolator.getInterpolatedDerivatives(), yDot[count]);
398             int index = 0;
399             for (final EquationsMapper secondary : expandable.getSecondaryMappers()) {
400                 secondary.insertEquationData(interpolator.getInterpolatedSecondaryState(index), y[count]);
401                 secondary.insertEquationData(interpolator.getInterpolatedSecondaryDerivatives(index), yDot[count]);
402                 ++index;
403             }
404 
405             if (count == t.length - 1) {
406 
407                 // this was the last step we needed, we can compute the derivatives
408                 stepStart = t[0];
409                 stepSize  = (t[t.length - 1] - t[0]) / (t.length - 1);
410 
411                 // first scaled derivative
412                 scaled = yDot[0].clone();
413                 for (int j = 0; j < scaled.length; ++j) {
414                     scaled[j] *= stepSize;
415                 }
416 
417                 // higher order derivatives
418                 nordsieck = initializeHighOrderDerivatives(stepSize, t, y, yDot);
419 
420                 // stop the integrator now that all needed steps have been handled
421                 throw new InitializationCompletedMarkerException();
422 
423             }
424 
425         }
426 
427         /** {@inheritDoc} */
428         public void init(double t0, double[] y0, double time) {
429             // nothing to do
430         }
431 
432     }
433 
434     /** Marker exception used ONLY to stop the starter integrator after first step. */
435     private static class InitializationCompletedMarkerException
436         extends RuntimeException {
437 
438         /** Serializable version identifier. */
439         private static final long serialVersionUID = -1914085471038046418L;
440 
441         /** Simple constructor. */
442         public InitializationCompletedMarkerException() {
443             super((Throwable) null);
444         }
445 
446     }
447 
448 }