1 /*
2 * Licensed to the Apache Software Foundation (ASF) under one or more
3 * contributor license agreements. See the NOTICE file distributed with
4 * this work for additional information regarding copyright ownership.
5 * The ASF 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
18 package org.apache.commons.math.estimation;
19
20 import java.util.ArrayList;
21 import java.util.Iterator;
22 import java.util.List;
23
24 /**
25 * Simple implementation of the {@link EstimationProblem
26 * EstimationProblem} interface for boilerplate data handling.
27 * <p>This class <em>only</em> handles parameters and measurements
28 * storage and unbound parameters filtering. It does not compute
29 * anything by itself. It should either be used with measurements
30 * implementation that are smart enough to know about the
31 * various parameters in order to compute the partial derivatives
32 * appropriately. Since the problem-specific logic is mainly related to
33 * the various measurements models, the simplest way to use this class
34 * is by extending it and using one internal class extending
35 * {@link WeightedMeasurement WeightedMeasurement} for each measurement
36 * type. The instances of the internal classes would have access to the
37 * various parameters and their current estimate.</p>
38
39 * @version $Revision: 627989 $ $Date: 2008-02-15 03:04:02 -0700 (Fri, 15 Feb 2008) $
40 * @since 1.2
41
42 */
43 public class SimpleEstimationProblem implements EstimationProblem {
44
45 /**
46 * Build an empty instance without parameters nor measurements.
47 */
48 public SimpleEstimationProblem() {
49 parameters = new ArrayList();
50 measurements = new ArrayList();
51 }
52
53 /**
54 * Get all the parameters of the problem.
55 * @return parameters
56 */
57 public EstimatedParameter[] getAllParameters() {
58 return (EstimatedParameter[]) parameters.toArray(new EstimatedParameter[parameters.size()]);
59 }
60
61 /**
62 * Get the unbound parameters of the problem.
63 * @return unbound parameters
64 */
65 public EstimatedParameter[] getUnboundParameters() {
66
67 // filter the unbound parameters
68 List unbound = new ArrayList(parameters.size());
69 for (Iterator iterator = parameters.iterator(); iterator.hasNext();) {
70 EstimatedParameter p = (EstimatedParameter) iterator.next();
71 if (! p.isBound()) {
72 unbound.add(p);
73 }
74 }
75
76 // convert to an array
77 return (EstimatedParameter[]) unbound.toArray(new EstimatedParameter[unbound.size()]);
78
79 }
80
81 /**
82 * Get the measurements of an estimation problem.
83 * @return measurements
84 */
85 public WeightedMeasurement[] getMeasurements() {
86 return (WeightedMeasurement[]) measurements.toArray(new WeightedMeasurement[measurements.size()]);
87 }
88
89 /** Add a parameter to the problem.
90 * @param p parameter to add
91 */
92 protected void addParameter(EstimatedParameter p) {
93 parameters.add(p);
94 }
95
96 /**
97 * Add a new measurement to the set.
98 * @param m measurement to add
99 */
100 protected void addMeasurement(WeightedMeasurement m) {
101 measurements.add(m);
102 }
103
104 /** Estimated parameters. */
105 private final List parameters;
106
107 /** Measurements. */
108 private final List measurements;
109
110 }