/* * Licensed to the Apache Software Foundation (ASF) under one or more * contributor license agreements. See the NOTICE file distributed with * this work for additional information regarding copyright ownership. * The ASF licenses this file to You under the Apache License, Version 2.0 * (the "License"); you may not use this file except in compliance with * the License. You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ package org.apache.commons.math.estimation; import java.util.ArrayList; import java.util.List; /** * Simple implementation of the {@link EstimationProblem * EstimationProblem} interface for boilerplate data handling. * <p>This class <em>only</em> handles parameters and measurements * storage and unbound parameters filtering. It does not compute * anything by itself. It should either be used with measurements * implementation that are smart enough to know about the * various parameters in order to compute the partial derivatives * appropriately. Since the problem-specific logic is mainly related to * the various measurements models, the simplest way to use this class * is by extending it and using one internal class extending * {@link WeightedMeasurement WeightedMeasurement} for each measurement * type. The instances of the internal classes would have access to the * various parameters and their current estimate.</p> * @version $Revision: 811827 $ $Date: 2009-09-06 17:32:50 +0200 (dim. 06 sept. 2009) $ * @since 1.2 * @deprecated as of 2.0, everything in package org.apache.commons.math.estimation has * been deprecated and replaced by package org.apache.commons.math.optimization.general */ @Deprecated public class SimpleEstimationProblem implements EstimationProblem { /** Estimated parameters. */ private final List<EstimatedParameter> parameters; /** Measurements. */ private final List<WeightedMeasurement> measurements; /** * Build an empty instance without parameters nor measurements. */ public SimpleEstimationProblem() { parameters = new ArrayList<EstimatedParameter>(); measurements = new ArrayList<WeightedMeasurement>(); } /** * Get all the parameters of the problem. * @return parameters */ public EstimatedParameter[] getAllParameters() { return parameters.toArray(new EstimatedParameter[parameters.size()]); } /** * Get the unbound parameters of the problem. * @return unbound parameters */ public EstimatedParameter[] getUnboundParameters() { // filter the unbound parameters List<EstimatedParameter> unbound = new ArrayList<EstimatedParameter>(parameters.size()); for (EstimatedParameter p : parameters) { if (! p.isBound()) { unbound.add(p); } } // convert to an array return unbound.toArray(new EstimatedParameter[unbound.size()]); } /** * Get the measurements of an estimation problem. * @return measurements */ public WeightedMeasurement[] getMeasurements() { return measurements.toArray(new WeightedMeasurement[measurements.size()]); } /** Add a parameter to the problem. * @param p parameter to add */ protected void addParameter(EstimatedParameter p) { parameters.add(p); } /** * Add a new measurement to the set. * @param m measurement to add */ protected void addMeasurement(WeightedMeasurement m) { measurements.add(m); } }