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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.math3.ode;
import java.io.Serializable;
import java.util.ArrayList;
import java.util.List;
import org.apache.commons.math3.exception.DimensionMismatchException;
import org.apache.commons.math3.exception.MathIllegalArgumentException;
import org.apache.commons.math3.exception.MaxCountExceededException;
import org.apache.commons.math3.exception.util.LocalizedFormats;
import org.apache.commons.math3.ode.sampling.StepHandler;
import org.apache.commons.math3.ode.sampling.StepInterpolator;
import org.apache.commons.math3.util.FastMath;
/**
* This class stores all information provided by an ODE integrator
* during the integration process and build a continuous model of the
* solution from this.
*
* This class act as a step handler from the integrator point of
* view. It is called iteratively during the integration process and
* stores a copy of all steps information in a sorted collection for
* later use. Once the integration process is over, the user can use
* the {@link #setInterpolatedTime setInterpolatedTime} and {@link
* #getInterpolatedState getInterpolatedState} to retrieve this
* information at any time. It is important to wait for the
* integration to be over before attempting to call {@link
* #setInterpolatedTime setInterpolatedTime} because some internal
* variables are set only once the last step has been handled.
*
* This is useful for example if the main loop of the user
* application should remain independent from the integration process
* or if one needs to mimic the behaviour of an analytical model
* despite a numerical model is used (i.e. one needs the ability to
* get the model value at any time or to navigate through the
* data).
*
* If problem modeling is done with several separate
* integration phases for contiguous intervals, the same
* ContinuousOutputModel can be used as step handler for all
* integration phases as long as they are performed in order and in
* the same direction. As an example, one can extrapolate the
* trajectory of a satellite with one model (i.e. one set of
* differential equations) up to the beginning of a maneuver, use
* another more complex model including thrusters modeling and
* accurate attitude control during the maneuver, and revert to the
* first model after the end of the maneuver. If the same continuous
* output model handles the steps of all integration phases, the user
* do not need to bother when the maneuver begins or ends, he has all
* the data available in a transparent manner.
*
* An important feature of this class is that it implements the
* Serializable interface. This means that the result of
* an integration can be serialized and reused later (if stored into a
* persistent medium like a filesystem or a database) or elsewhere (if
* sent to another application). Only the result of the integration is
* stored, there is no reference to the integrated problem by
* itself.
*
* One should be aware that the amount of data stored in a
* ContinuousOutputModel instance can be important if the state vector
* is large, if the integration interval is long or if the steps are
* small (which can result from small tolerance settings in {@link
* org.apache.commons.math3.ode.nonstiff.AdaptiveStepsizeIntegrator adaptive
* step size integrators}).
*
* @see StepHandler
* @see StepInterpolator
* @version $Id: ContinuousOutputModel.java 1416643 2012-12-03 19:37:14Z tn $
* @since 1.2
*/
public class ContinuousOutputModel
implements StepHandler, Serializable {
/** Serializable version identifier */
private static final long serialVersionUID = -1417964919405031606L;
/** Initial integration time. */
private double initialTime;
/** Final integration time. */
private double finalTime;
/** Integration direction indicator. */
private boolean forward;
/** Current interpolator index. */
private int index;
/** Steps table. */
private List steps;
/** Simple constructor.
* Build an empty continuous output model.
*/
public ContinuousOutputModel() {
steps = new ArrayList();
initialTime = Double.NaN;
finalTime = Double.NaN;
forward = true;
index = 0;
}
/** Append another model at the end of the instance.
* @param model model to add at the end of the instance
* @exception MathIllegalArgumentException if the model to append is not
* compatible with the instance (dimension of the state vector,
* propagation direction, hole between the dates)
* @exception MaxCountExceededException if the number of functions evaluations is exceeded
* during step finalization
*/
public void append(final ContinuousOutputModel model)
throws MathIllegalArgumentException, MaxCountExceededException {
if (model.steps.size() == 0) {
return;
}
if (steps.size() == 0) {
initialTime = model.initialTime;
forward = model.forward;
} else {
if (getInterpolatedState().length != model.getInterpolatedState().length) {
throw new DimensionMismatchException(model.getInterpolatedState().length,
getInterpolatedState().length);
}
if (forward ^ model.forward) {
throw new MathIllegalArgumentException(LocalizedFormats.PROPAGATION_DIRECTION_MISMATCH);
}
final StepInterpolator lastInterpolator = steps.get(index);
final double current = lastInterpolator.getCurrentTime();
final double previous = lastInterpolator.getPreviousTime();
final double step = current - previous;
final double gap = model.getInitialTime() - current;
if (FastMath.abs(gap) > 1.0e-3 * FastMath.abs(step)) {
throw new MathIllegalArgumentException(LocalizedFormats.HOLE_BETWEEN_MODELS_TIME_RANGES,
FastMath.abs(gap));
}
}
for (StepInterpolator interpolator : model.steps) {
steps.add(interpolator.copy());
}
index = steps.size() - 1;
finalTime = (steps.get(index)).getCurrentTime();
}
/** {@inheritDoc} */
public void init(double t0, double[] y0, double t) {
initialTime = Double.NaN;
finalTime = Double.NaN;
forward = true;
index = 0;
steps.clear();
}
/** Handle the last accepted step.
* A copy of the information provided by the last step is stored in
* the instance for later use.
* @param interpolator interpolator for the last accepted step.
* @param isLast true if the step is the last one
* @exception MaxCountExceededException if the number of functions evaluations is exceeded
* during step finalization
*/
public void handleStep(final StepInterpolator interpolator, final boolean isLast)
throws MaxCountExceededException {
if (steps.size() == 0) {
initialTime = interpolator.getPreviousTime();
forward = interpolator.isForward();
}
steps.add(interpolator.copy());
if (isLast) {
finalTime = interpolator.getCurrentTime();
index = steps.size() - 1;
}
}
/**
* Get the initial integration time.
* @return initial integration time
*/
public double getInitialTime() {
return initialTime;
}
/**
* Get the final integration time.
* @return final integration time
*/
public double getFinalTime() {
return finalTime;
}
/**
* Get the time of the interpolated point.
* If {@link #setInterpolatedTime} has not been called, it returns
* the final integration time.
* @return interpolation point time
*/
public double getInterpolatedTime() {
return steps.get(index).getInterpolatedTime();
}
/** Set the time of the interpolated point.
* This method should not be called before the
* integration is over because some internal variables are set only
* once the last step has been handled.
* Setting the time outside of the integration interval is now
* allowed (it was not allowed up to version 5.9 of Mantissa), but
* should be used with care since the accuracy of the interpolator
* will probably be very poor far from this interval. This allowance
* has been added to simplify implementation of search algorithms
* near the interval endpoints.
* @param time time of the interpolated point
*/
public void setInterpolatedTime(final double time) {
// initialize the search with the complete steps table
int iMin = 0;
final StepInterpolator sMin = steps.get(iMin);
double tMin = 0.5 * (sMin.getPreviousTime() + sMin.getCurrentTime());
int iMax = steps.size() - 1;
final StepInterpolator sMax = steps.get(iMax);
double tMax = 0.5 * (sMax.getPreviousTime() + sMax.getCurrentTime());
// handle points outside of the integration interval
// or in the first and last step
if (locatePoint(time, sMin) <= 0) {
index = iMin;
sMin.setInterpolatedTime(time);
return;
}
if (locatePoint(time, sMax) >= 0) {
index = iMax;
sMax.setInterpolatedTime(time);
return;
}
// reduction of the table slice size
while (iMax - iMin > 5) {
// use the last estimated index as the splitting index
final StepInterpolator si = steps.get(index);
final int location = locatePoint(time, si);
if (location < 0) {
iMax = index;
tMax = 0.5 * (si.getPreviousTime() + si.getCurrentTime());
} else if (location > 0) {
iMin = index;
tMin = 0.5 * (si.getPreviousTime() + si.getCurrentTime());
} else {
// we have found the target step, no need to continue searching
si.setInterpolatedTime(time);
return;
}
// compute a new estimate of the index in the reduced table slice
final int iMed = (iMin + iMax) / 2;
final StepInterpolator sMed = steps.get(iMed);
final double tMed = 0.5 * (sMed.getPreviousTime() + sMed.getCurrentTime());
if ((FastMath.abs(tMed - tMin) < 1e-6) || (FastMath.abs(tMax - tMed) < 1e-6)) {
// too close to the bounds, we estimate using a simple dichotomy
index = iMed;
} else {
// estimate the index using a reverse quadratic polynom
// (reverse means we have i = P(t), thus allowing to simply
// compute index = P(time) rather than solving a quadratic equation)
final double d12 = tMax - tMed;
final double d23 = tMed - tMin;
final double d13 = tMax - tMin;
final double dt1 = time - tMax;
final double dt2 = time - tMed;
final double dt3 = time - tMin;
final double iLagrange = ((dt2 * dt3 * d23) * iMax -
(dt1 * dt3 * d13) * iMed +
(dt1 * dt2 * d12) * iMin) /
(d12 * d23 * d13);
index = (int) FastMath.rint(iLagrange);
}
// force the next size reduction to be at least one tenth
final int low = FastMath.max(iMin + 1, (9 * iMin + iMax) / 10);
final int high = FastMath.min(iMax - 1, (iMin + 9 * iMax) / 10);
if (index < low) {
index = low;
} else if (index > high) {
index = high;
}
}
// now the table slice is very small, we perform an iterative search
index = iMin;
while ((index <= iMax) && (locatePoint(time, steps.get(index)) > 0)) {
++index;
}
steps.get(index).setInterpolatedTime(time);
}
/**
* Get the state vector of the interpolated point.
* @return state vector at time {@link #getInterpolatedTime}
* @exception MaxCountExceededException if the number of functions evaluations is exceeded
*/
public double[] getInterpolatedState() throws MaxCountExceededException {
return steps.get(index).getInterpolatedState();
}
/** Compare a step interval and a double.
* @param time point to locate
* @param interval step interval
* @return -1 if the double is before the interval, 0 if it is in
* the interval, and +1 if it is after the interval, according to
* the interval direction
*/
private int locatePoint(final double time, final StepInterpolator interval) {
if (forward) {
if (time < interval.getPreviousTime()) {
return -1;
} else if (time > interval.getCurrentTime()) {
return +1;
} else {
return 0;
}
}
if (time > interval.getPreviousTime()) {
return -1;
} else if (time < interval.getCurrentTime()) {
return +1;
} else {
return 0;
}
}
}