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/*
* 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);
}
}
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