ShortPeriodicsInterpolatedCoefficient.java
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package org.orekit.propagation.semianalytical.dsst.utilities;
import org.hipparchus.analysis.interpolation.HermiteInterpolator;
import org.hipparchus.util.FastMath;
import org.orekit.time.AbsoluteDate;
import java.util.ArrayList;
/** Interpolated short periodics coefficients.
* <p>
* Representation of a coefficient that need to be interpolated over time.
* </p><p>
* The short periodics coefficients can be interpolated for faster computation.
* This class stores computed values of the coefficients through the method
* {@link #addGridPoint} and gives an interpolated result through the method
* {@link #value}.
* </p>
* @author Nicolas Bernard
*
*/
public class ShortPeriodicsInterpolatedCoefficient {
/**Values of the already computed coefficients.*/
private ArrayList<double[]> values;
/**Grid points.*/
private ArrayList<AbsoluteDate> abscissae;
/**Number of points used in the interpolation.*/
private int interpolationPoints;
/**Index of the latest closest neighbor.*/
private int latestClosestNeighbor;
/**Simple constructor.
* @param interpolationPoints number of points used in the interpolation
*/
public ShortPeriodicsInterpolatedCoefficient(final int interpolationPoints) {
this.interpolationPoints = interpolationPoints;
this.abscissae = new ArrayList<>();
this.values = new ArrayList<>();
this.latestClosestNeighbor = 0;
}
/**Compute the value of the coefficient.
* @param date date at which the coefficient should be computed
* @return value of the coefficient
*/
public double[] value(final AbsoluteDate date) {
//Get the closest points from the input date
final int[] neighbors = getNeighborsIndices(date);
//Creation and set up of the interpolator
final HermiteInterpolator interpolator = new HermiteInterpolator();
for (int i : neighbors) {
interpolator.addSamplePoint(abscissae.get(i).durationFrom(date), values.get(i));
}
//interpolation
return interpolator.value(0.0);
}
/**Find the closest available points from the specified date.
* @param date date of interest
* @return indices corresponding to the closest points on the time scale
*/
private int[] getNeighborsIndices(final AbsoluteDate date) {
final int sizeofNeighborhood = FastMath.min(interpolationPoints, abscissae.size());
final int[] neighborsIndices = new int[sizeofNeighborhood];
//If the size of the complete sample is less than
//the desired number of interpolation points,
//then the entire sample is considered as the neighborhood
if (interpolationPoints >= abscissae.size()) {
for (int i = 0; i < sizeofNeighborhood; i++) {
neighborsIndices[i] = i;
}
} else {
// get indices around closest neighbor
int inf = getClosestNeighbor(date);
int sup = inf + 1;
while (sup - inf < interpolationPoints) {
if (inf == 0) { //This means that we have reached the earliest date
sup++;
} else if (sup >= abscissae.size()) { //This means that we have reached the latest date
inf--;
} else { //the choice is made between the two next neighbors
final double lowerNeighborDistance = FastMath.abs(abscissae.get(inf - 1).durationFrom(date));
final double upperNeighborDistance = FastMath.abs(abscissae.get(sup).durationFrom(date));
if (lowerNeighborDistance <= upperNeighborDistance) {
inf--;
} else {
sup++;
}
}
}
for (int i = 0; i < interpolationPoints; ++i) {
neighborsIndices[i] = inf + i;
}
}
return neighborsIndices;
}
/**Find the closest point from a specific date amongst the available points.
* @param date date of interest
* @return index of the closest abscissa from the date of interest
*/
private int getClosestNeighbor(final AbsoluteDate date) {
//the starting point is the latest result of a call to this method.
//Indeed, as this class is meant to be called during an integration process
//with an input date evolving often continuously in time, there is a high
//probability that the result will be the same as for last call of
//this method.
final int closestNeighbor;
//case where the date is before the available points
if (date.compareTo(abscissae.get(0)) <= 0) {
closestNeighbor = 0;
}
//case where the date is after the available points
else if (date.compareTo(abscissae.get(abscissae.size() - 1)) >= 0) {
closestNeighbor = abscissae.size() - 1;
}
//general case: one is looking for the two consecutives entries that surround the input date
//then one choose the closest one
else {
int lowerBorder = latestClosestNeighbor;
int upperBorder = latestClosestNeighbor;
final int searchDirection = date.compareTo(abscissae.get(latestClosestNeighbor));
if (searchDirection > 0) {
upperBorder++;
while (date.compareTo(abscissae.get(upperBorder)) > 0) {
upperBorder++;
lowerBorder++;
}
}
else {
lowerBorder--;
while (date.compareTo(abscissae.get(lowerBorder)) < 0) {
upperBorder--;
lowerBorder--;
}
}
final double lowerDistance = FastMath.abs(date.durationFrom(abscissae.get(lowerBorder)));
final double upperDistance = FastMath.abs(date.durationFrom(abscissae.get(upperBorder)));
closestNeighbor = (lowerDistance < upperDistance) ? lowerBorder : upperBorder;
}
//The result is stored in order to speed up the next call to the function
//Indeed, it is highly likely that the requested result will be the same
this.latestClosestNeighbor = closestNeighbor;
return closestNeighbor;
}
/** Clear the recorded values from the interpolation grid.
*/
public void clearHistory() {
abscissae.clear();
values.clear();
}
/** Add a point to the interpolation grid.
* @param date abscissa of the point
* @param value value of the element
*/
public void addGridPoint(final AbsoluteDate date, final double[] value) {
//If the grid is empty, the value is directly added to both arrays
if (abscissae.isEmpty()) {
abscissae.add(date);
values.add(value);
}
//If the grid already contains this point, only its value is changed
else if (abscissae.contains(date)) {
values.set(abscissae.indexOf(date), value);
}
//If the grid does not contain this point, the position of the point
//in the grid is computed first
else {
final int closestNeighbor = getClosestNeighbor(date);
final int index = (date.compareTo(abscissae.get(closestNeighbor)) < 0) ? closestNeighbor : closestNeighbor + 1;
abscissae.add(index, date);
values.add(index, value);
}
}
}