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 }