package org.spaceroots.mantissa.estimation;

import java.io.Serializable;

/** This class represents measurements in estimation problems.

 * 

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.

*

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 * independant of the problem, or directly if they are implemented as * inner classes of the problem.

*

The instances for which the ignored 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.

* @see EstimationProblem * @version $Id: WeightedMeasurement.java 1679 2005-12-16 11:12:23Z luc $ * @author L. Maisonobe */ public abstract class WeightedMeasurement implements Serializable { /** 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 *

The theoretical value is the value expected for this measurement * if the model and its parameter were all perfectly known.

*

The value must be computed using the current estimate of the parameters * set by the solver in the problem.

* @return theoretical value */ public abstract double getTheoreticalValue(); /** Get the partial derivative of the {@link #getTheoreticalValue * theoretical value} according to the parameter. *

The value must be computed using the current estimate of the parameters * set by the solver in the problem.

* @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; } private final double weight; private final double measuredValue; private boolean ignored; }

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