Home | History | Annotate | Download | only in estimation 
      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.List;
     22 
     23 /**
     24  * Simple implementation of the {@link EstimationProblem
     25  * EstimationProblem} interface for boilerplate data handling.
     26  * <p>This class <em>only</em> handles parameters and measurements
     27  * storage and unbound parameters filtering. It does not compute
     28  * anything by itself. It should either be used with measurements
     29  * implementation that are smart enough to know about the
     30  * various parameters in order to compute the partial derivatives
     31  * appropriately. Since the problem-specific logic is mainly related to
     32  * the various measurements models, the simplest way to use this class
     33  * is by extending it and using one internal class extending
     34  * {@link WeightedMeasurement WeightedMeasurement} for each measurement
     35  * type. The instances of the internal classes would have access to the
     36  * various parameters and their current estimate.</p>
     37 
     38  * @version $Revision: 811827 $ $Date: 2009-09-06 17:32:50 +0200 (dim. 06 sept. 2009) $
     39  * @since 1.2
     40  * @deprecated as of 2.0, everything in package org.apache.commons.math.estimation has
     41  * been deprecated and replaced by package org.apache.commons.math.optimization.general
     42 
     43  */
     44 @Deprecated
     45 public class SimpleEstimationProblem implements EstimationProblem {
     46 
     47     /** Estimated parameters. */
     48     private final List<EstimatedParameter> parameters;
     49 
     50     /** Measurements. */
     51     private final List<WeightedMeasurement> measurements;
     52 
     53     /**
     54      * Build an empty instance without parameters nor measurements.
     55      */
     56     public SimpleEstimationProblem() {
     57         parameters   = new ArrayList<EstimatedParameter>();
     58         measurements = new ArrayList<WeightedMeasurement>();
     59     }
     60 
     61     /**
     62      * Get all the parameters of the problem.
     63      * @return parameters
     64      */
     65     public EstimatedParameter[] getAllParameters() {
     66         return parameters.toArray(new EstimatedParameter[parameters.size()]);
     67     }
     68 
     69     /**
     70      * Get the unbound parameters of the problem.
     71      * @return unbound parameters
     72      */
     73     public EstimatedParameter[] getUnboundParameters() {
     74 
     75         // filter the unbound parameters
     76         List<EstimatedParameter> unbound = new ArrayList<EstimatedParameter>(parameters.size());
     77         for (EstimatedParameter p : parameters) {
     78             if (! p.isBound()) {
     79                 unbound.add(p);
     80             }
     81         }
     82 
     83         // convert to an array
     84         return unbound.toArray(new EstimatedParameter[unbound.size()]);
     85 
     86     }
     87 
     88     /**
     89      * Get the measurements of an estimation problem.
     90      * @return measurements
     91      */
     92     public WeightedMeasurement[] getMeasurements() {
     93         return measurements.toArray(new WeightedMeasurement[measurements.size()]);
     94     }
     95 
     96     /** Add a parameter to the problem.
     97      * @param p parameter to add
     98      */
     99     protected void addParameter(EstimatedParameter p) {
    100         parameters.add(p);
    101     }
    102 
    103     /**
    104      * Add a new measurement to the set.
    105      * @param m measurement to add
    106      */
    107     protected void addMeasurement(WeightedMeasurement m) {
    108         measurements.add(m);
    109     }
    110 
    111 }
    112