1   /* Copyright 2002-2025 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.EstimatedMeasurementBase;
25  import org.orekit.estimation.measurements.EstimationModifier;
26  import org.orekit.estimation.measurements.ObservedMeasurement;
27  import org.orekit.utils.ParameterDriver;
28  import org.orekit.utils.TimeSpanMap.Span;
29  
30  /** Class modeling a measurement bias.
31   * @param <T> the type of the measurement
32   * @author Luc Maisonobe
33   * @since 8.0
34   */
35  public class Bias<T extends ObservedMeasurement<T>> implements EstimationModifier<T> {
36  
37      /** Parameters holding the bias value components. */
38      private final List<ParameterDriver> drivers;
39  
40      /** Partial derivatives. */
41      private final double[][] derivatives;
42  
43      /** Simple constructor.
44       * @param name name of the bias
45       * @param bias reference value of the bias
46       * @param scale scale of the bias, for normalization
47       * @param min minimum value of the bias
48       * @param max maximum value of the bias
49       */
50      public Bias(final String[] name, final double[] bias, final double[] scale,
51                  final double[] min, final double[] max) {
52  
53          drivers = new ArrayList<>(bias.length);
54          for (int i = 0; i < bias.length; ++i) {
55              drivers.add(new ParameterDriver(name[i], bias[i], scale[i], min[i], max[i]));
56          }
57  
58          derivatives = new double[bias.length][bias.length];
59          for (int i = 0; i < bias.length; ++i) {
60              // derivatives are computed with respect to the physical parameters,
61              // not with respect to the normalized parameters (normalization is
62              // performed later on), so the derivative is really 1.0 and not scale[i]
63              derivatives[i][i] = 1.0;
64          }
65  
66      }
67  
68      /** {@inheritDoc} */
69      @Override
70      public String getEffectName() {
71          return drivers.get(0).getName();
72      }
73  
74      /** {@inheritDoc}
75       * <p>
76       * For a bias, there are {@link ObservedMeasurement#getDimension()} parameter drivers,
77       * sorted in components order.
78       * </p>
79       */
80      @Override
81      public List<ParameterDriver> getParametersDrivers() {
82          return Collections.unmodifiableList(drivers);
83      }
84  
85      /** {@inheritDoc} */
86      @Override
87      public void modifyWithoutDerivatives(final EstimatedMeasurementBase<T> estimated) {
88  
89          // apply the bias to the measurement value
90          final double[] value = estimated.getEstimatedValue();
91          int nb = 0;
92          for (final ParameterDriver driver : drivers) {
93              for (Span<String> span = driver.getNamesSpanMap().getFirstSpan();
94                   span != null; span = span.next()) {
95                  value[nb++] += driver.getValue(span.getStart());
96              }
97          }
98          estimated.modifyEstimatedValue(this, value);
99  
100     }
101 
102     /** {@inheritDoc} */
103     @Override
104     public void modify(final EstimatedMeasurement<T> estimated) {
105 
106         // apply the bias to the measurement value
107         int nb = 0;
108         for (final ParameterDriver driver : drivers) {
109             for (Span<String> span = driver.getNamesSpanMap().getFirstSpan();
110                  span != null; span = span.next()) {
111                 if (driver.isSelected()) {
112                     // add the partial derivatives
113                     estimated.setParameterDerivatives(driver, span.getStart(),
114                                                       derivatives[nb++]);
115                 }
116             }
117         }
118 
119         modifyWithoutDerivatives(estimated);
120 
121     }
122 
123 }