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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.io.Serializable;
/**
* This class represents measurements in estimation problems.
*
* <p>This abstract class implements all the methods needed to handle
* measurements in a general way. It defines neither the {@link
* #getTheoreticalValue getTheoreticalValue} nor the {@link
* #getPartial getPartial} methods, which should be defined by
* sub-classes according to the specific problem.</p>
*
* <p>The {@link #getTheoreticalValue getTheoreticalValue} and {@link
* #getPartial getPartial} methods must always use the current
* estimate of the parameters set by the solver in the problem. These
* parameters can be retrieved through the {@link
* EstimationProblem#getAllParameters
* EstimationProblem.getAllParameters} method if the measurements are
* independent of the problem, or directly if they are implemented as
* inner classes of the problem.</p>
*
* <p>The instances for which the <code>ignored</code> flag is set
* through the {@link #setIgnored setIgnored} method are ignored by the
* solvers. This can be used to reject wrong measurements at some
* steps of the estimation.</p>
*
* @see EstimationProblem
*
* @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 abstract class WeightedMeasurement implements Serializable {
/** Serializable version identifier. */
private static final long serialVersionUID = 4360046376796901941L;
/** Measurement weight. */
private final double weight;
/** Value of the measurements. */
private final double measuredValue;
/** Ignore measurement indicator. */
private boolean ignored;
/**
* Simple constructor.
* Build a measurement with the given parameters, and set its ignore
* flag to false.
* @param weight weight of the measurement in the least squares problem
* (two common choices are either to use 1.0 for all measurements, or to
* use a value proportional to the inverse of the variance of the measurement
* type)
*
* @param measuredValue measured value
*/
public WeightedMeasurement(double weight, double measuredValue) {
this.weight = weight;
this.measuredValue = measuredValue;
ignored = false;
}
/** Simple constructor.
*
* Build a measurement with the given parameters
*
* @param weight weight of the measurement in the least squares problem
* @param measuredValue measured value
* @param ignored true if the measurement should be ignored
*/
public WeightedMeasurement(double weight, double measuredValue,
boolean ignored) {
this.weight = weight;
this.measuredValue = measuredValue;
this.ignored = ignored;
}
/**
* Get the weight of the measurement in the least squares problem
*
* @return weight
*/
public double getWeight() {
return weight;
}
/**
* Get the measured value
*
* @return measured value
*/
public double getMeasuredValue() {
return measuredValue;
}
/**
* Get the residual for this measurement
* The residual is the measured value minus the theoretical value.
*
* @return residual
*/
public double getResidual() {
return measuredValue - getTheoreticalValue();
}
/**
* Get the theoretical value expected for this measurement
* <p>The theoretical value is the value expected for this measurement
* if the model and its parameter were all perfectly known.</p>
* <p>The value must be computed using the current estimate of the parameters
* set by the solver in the problem.</p>
*
* @return theoretical value
*/
public abstract double getTheoreticalValue();
/**
* Get the partial derivative of the {@link #getTheoreticalValue
* theoretical value} according to the parameter.
* <p>The value must be computed using the current estimate of the parameters
* set by the solver in the problem.</p>
*
* @param parameter parameter against which the partial derivative
* should be computed
* @return partial derivative of the {@link #getTheoreticalValue
* theoretical value}
*/
public abstract double getPartial(EstimatedParameter parameter);
/**
* Set the ignore flag to the specified value
* Setting the ignore flag to true allow to reject wrong
* measurements, which sometimes can be detected only rather late.
*
* @param ignored value for the ignore flag
*/
public void setIgnored(boolean ignored) {
this.ignored = ignored;
}
/**
* Check if this measurement should be ignored
*
* @return true if the measurement should be ignored
*/
public boolean isIgnored() {
return ignored;
}
}
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