FiniteDifferencePropagatorConverter.java
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* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* CS licenses this file to You under the Apache License, Version 2.0
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*
* http://www.apache.org/licenses/LICENSE-2.0
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* Unless required by applicable law or agreed to in writing, software
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package org.orekit.propagation.conversion;
import org.hipparchus.analysis.MultivariateVectorFunction;
import org.hipparchus.linear.MatrixUtils;
import org.hipparchus.linear.RealMatrix;
import org.hipparchus.linear.RealVector;
import org.hipparchus.optim.nonlinear.vector.leastsquares.MultivariateJacobianFunction;
import org.hipparchus.util.Pair;
import org.orekit.errors.OrekitException;
import org.orekit.propagation.Propagator;
import org.orekit.propagation.SpacecraftState;
import org.orekit.utils.PVCoordinates;
/** Propagator converter using finite differences to compute the Jacobian.
* @author Pascal Parraud
* @since 6.0
*/
public class FiniteDifferencePropagatorConverter extends AbstractPropagatorConverter {
/** Propagator builder. */
private final PropagatorBuilder builder;
/** Simple constructor.
* @param factory builder for adapted propagator
* @param threshold absolute threshold for optimization algorithm
* @param maxIterations maximum number of iterations for fitting
*/
public FiniteDifferencePropagatorConverter(final PropagatorBuilder factory,
final double threshold,
final int maxIterations) {
super(factory, threshold, maxIterations);
this.builder = factory;
}
/** {@inheritDoc} */
protected MultivariateVectorFunction getObjectiveFunction() {
return new ObjectiveFunction();
}
/** {@inheritDoc} */
protected MultivariateJacobianFunction getModel() {
return new ObjectiveFunctionJacobian();
}
/** Internal class for computing position/velocity at sample points. */
private class ObjectiveFunction implements MultivariateVectorFunction {
/** {@inheritDoc} */
public double[] value(final double[] arg)
throws IllegalArgumentException, OrekitException {
final Propagator propagator = builder.buildPropagator(arg);
final double[] eval = new double[getTargetSize()];
int k = 0;
for (SpacecraftState state : getSample()) {
final PVCoordinates pv = propagator.getPVCoordinates(state.getDate(), getFrame());
if (Double.isNaN(pv.getMomentum().getNorm())) {
propagator.getPVCoordinates(state.getDate(), getFrame());
}
eval[k++] = pv.getPosition().getX();
eval[k++] = pv.getPosition().getY();
eval[k++] = pv.getPosition().getZ();
if (!isOnlyPosition()) {
eval[k++] = pv.getVelocity().getX();
eval[k++] = pv.getVelocity().getY();
eval[k++] = pv.getVelocity().getZ();
}
}
return eval;
}
}
/** Internal class for computing position/velocity Jacobian at sample points. */
private class ObjectiveFunctionJacobian implements MultivariateJacobianFunction {
/** {@inheritDoc} */
public Pair<RealVector, RealMatrix> value(final RealVector point)
throws IllegalArgumentException, OrekitException {
final double[] arg = point.toArray();
final MultivariateVectorFunction f = new ObjectiveFunction();
final double[][] jacob = new double[getTargetSize()][arg.length];
final double[] eval = f.value(arg);
final double[] arg1 = new double[arg.length];
for (int j = 0; j < arg.length; j++) {
System.arraycopy(arg, 0, arg1, 0, arg.length);
arg1[j] += 1;
final double[] eval1 = f.value(arg1);
for (int t = 0; t < eval.length; t++) {
jacob[t][j] = eval1[t] - eval[t];
}
}
return new Pair<RealVector, RealMatrix>(MatrixUtils.createRealVector(eval),
MatrixUtils.createRealMatrix(jacob));
}
}
}