1   /* Copyright 2002-2021 CS GROUP
2    * Licensed to CS GROUP (CS) under one or more
3    * contributor license agreements.  See the NOTICE file distributed with
4    * this work for additional information regarding copyright ownership.
5    * CS 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  package org.orekit.estimation.measurements.modifiers;
18  
19  import java.util.ArrayList;
20  import java.util.Collections;
21  import java.util.List;
22  
23  import org.orekit.estimation.measurements.EstimatedMeasurement;
24  import org.orekit.estimation.measurements.EstimationModifier;
25  import org.orekit.estimation.measurements.ObservedMeasurement;
26  import org.orekit.utils.ParameterDriver;
27  
28  /** Class modeling a measurement bias.
29   * @param <T> the type of the measurement
30   * @author Luc Maisonobe
31   * @since 8.0
32   */
33  public class Bias<T extends ObservedMeasurement<T>> implements EstimationModifier<T> {
34  
35      /** Parameters holding the bias value components. */
36      private final List<ParameterDriver> drivers;
37  
38      /** Partial derivatives. */
39      private final double[][] derivatives;
40  
41      /** Simple constructor.
42       * @param name name of the bias
43       * @param bias reference value of the bias
44       * @param scale scale of the bias, for normalization
45       * @param min minimum value of the bias
46       * @param max maximum value of the bias
47       */
48      public Bias(final String[] name, final double[] bias, final double[] scale,
49                  final double[] min, final double[] max) {
50  
51          drivers = new ArrayList<>(bias.length);
52          for (int i = 0; i < bias.length; ++i) {
53              drivers.add(new ParameterDriver(name[i], bias[i], scale[i], min[i], max[i]));
54          }
55  
56          derivatives = new double[bias.length][bias.length];
57          for (int i = 0; i < bias.length; ++i) {
58              // derivatives are computed with respect to the physical parameters,
59              // not with respect to the normalized parameters (normalization is
60              // performed later on), so the derivative is really 1.0 and not scale[i]
61              derivatives[i][i] = 1.0;
62          }
63  
64      }
65  
66      /** {@inheritDoc}
67       * <p>
68       * For a bias, there are {@link ObservedMeasurement#getDimension()} parameter drivers,
69       * sorted in components order.
70       * </p>
71       */
72      @Override
73      public List<ParameterDriver> getParametersDrivers() {
74          return Collections.unmodifiableList(drivers);
75      }
76  
77      /** {@inheritDoc} */
78      @Override
79      public void modify(final EstimatedMeasurement<T> estimated) {
80  
81          // apply the bias to the measurement value
82          final double[] value = estimated.getEstimatedValue();
83          for (int i = 0; i < drivers.size(); ++i) {
84              final ParameterDriver driver = drivers.get(i);
85              value[i] += driver.getValue();
86              if (driver.isSelected()) {
87                  // add the partial derivatives
88                  estimated.setParameterDerivatives(driver, derivatives[i]);
89              }
90          }
91          estimated.setEstimatedValue(value);
92  
93  
94      }
95  
96  }