Bias.java
/* Copyright 2002-2022 CS GROUP
* Licensed to CS GROUP (CS) under one or more
* 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
* (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,
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package org.orekit.estimation.measurements.modifiers;
import java.util.ArrayList;
import java.util.Collections;
import java.util.List;
import org.orekit.estimation.measurements.EstimatedMeasurement;
import org.orekit.estimation.measurements.EstimationModifier;
import org.orekit.estimation.measurements.ObservedMeasurement;
import org.orekit.utils.ParameterDriver;
/** Class modeling a measurement bias.
* @param <T> the type of the measurement
* @author Luc Maisonobe
* @since 8.0
*/
public class Bias<T extends ObservedMeasurement<T>> implements EstimationModifier<T> {
/** Parameters holding the bias value components. */
private final List<ParameterDriver> drivers;
/** Partial derivatives. */
private final double[][] derivatives;
/** Simple constructor.
* @param name name of the bias
* @param bias reference value of the bias
* @param scale scale of the bias, for normalization
* @param min minimum value of the bias
* @param max maximum value of the bias
*/
public Bias(final String[] name, final double[] bias, final double[] scale,
final double[] min, final double[] max) {
drivers = new ArrayList<>(bias.length);
for (int i = 0; i < bias.length; ++i) {
drivers.add(new ParameterDriver(name[i], bias[i], scale[i], min[i], max[i]));
}
derivatives = new double[bias.length][bias.length];
for (int i = 0; i < bias.length; ++i) {
// derivatives are computed with respect to the physical parameters,
// not with respect to the normalized parameters (normalization is
// performed later on), so the derivative is really 1.0 and not scale[i]
derivatives[i][i] = 1.0;
}
}
/** {@inheritDoc}
* <p>
* For a bias, there are {@link ObservedMeasurement#getDimension()} parameter drivers,
* sorted in components order.
* </p>
*/
@Override
public List<ParameterDriver> getParametersDrivers() {
return Collections.unmodifiableList(drivers);
}
/** {@inheritDoc} */
@Override
public void modify(final EstimatedMeasurement<T> estimated) {
// apply the bias to the measurement value
final double[] value = estimated.getEstimatedValue();
for (int i = 0; i < drivers.size(); ++i) {
final ParameterDriver driver = drivers.get(i);
value[i] += driver.getValue();
if (driver.isSelected()) {
// add the partial derivatives
estimated.setParameterDerivatives(driver, derivatives[i]);
}
}
estimated.setEstimatedValue(value);
}
}