xal.tools.math

Class LeastSquareParameterFitting

java.lang.Object

xal.tools.math.LeastSquareParameterFitting

All Implemented Interfaces:

java.lang.Runnable

public class LeastSquareParameterFitting
extends java.lang.Object
implements java.lang.Runnable

Least Squares parameter fitting tool which takes a differentiable operation as a model.

Field Summary

Fields

Modifier and Type	Field and Description
static DifferentiableVariable	INDEPENDENT_VARIABLE independent (sampled) variable (typically "x")

Constructor Summary

Constructors

Constructor and Description
LeastSquareParameterFitting(DifferentiableOperation model, BoundedDifferentiableVariable... parameters) Constructor

Method Summary

Modifier and Type	Method and Description
void	addSample(double x, double y) Add a data sample without specifying statistical error (either all or none must specify error)
void	addSample(double x, double y, double sigma) Add a data sample including statistical error (either all or none must specify error)
void	clear() clear samples
double	getFitPenalty() get the penalty for the best fit found
double	getFitValueForParameter(BoundedDifferentiableVariable parameter) get the value of the parameter for the best fit found
int	getMaxEvaluations() get the maximum number of model evaluations for a run
void	run() run the minimizer to find the best parameter fit for the model to the samples
void	runFor(int evaluations) set the maximum evaluations and run
void	setMaxEvaluations(int evaluations) set the maximum number of model evaluations for a run

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

INDEPENDENT_VARIABLE

public static final DifferentiableVariable INDEPENDENT_VARIABLE

independent (sampled) variable (typically "x")

Constructor Detail

LeastSquareParameterFitting

public LeastSquareParameterFitting(DifferentiableOperation model,
                                   BoundedDifferentiableVariable... parameters)

Constructor

Method Detail

addSample

public void addSample(double x,
                      double y,
                      double sigma)

Add a data sample including statistical error (either all or none must specify error)

Parameters:

x - independent variable value

y - dependent (measured) variable value

sigma - statistical measurement error

addSample

public void addSample(double x,
                      double y)

Add a data sample without specifying statistical error (either all or none must specify error)

Parameters:

x - independent variable value

y - dependent (measured) variable value

clear

public void clear()

clear samples

getMaxEvaluations

public int getMaxEvaluations()

get the maximum number of model evaluations for a run

setMaxEvaluations

public void setMaxEvaluations(int evaluations)

set the maximum number of model evaluations for a run

run

public void run()
         throws java.lang.IllegalStateException

run the minimizer to find the best parameter fit for the model to the samples

Specified by:

run in interface java.lang.Runnable

Throws:

java.lang.IllegalStateException

runFor

public void runFor(int evaluations)

set the maximum evaluations and run

getFitPenalty

public double getFitPenalty()

get the penalty for the best fit found

getFitValueForParameter

public double getFitValueForParameter(BoundedDifferentiableVariable parameter)

get the value of the parameter for the best fit found