Package gov.nih.mipav.model.algorithms

Class AlgorithmTimeFitting.FitLorentz

java.lang.Object

gov.nih.mipav.model.algorithms.NLConstrainedEngine

gov.nih.mipav.model.algorithms.AlgorithmTimeFitting.FitLorentz

Enclosing class:

AlgorithmTimeFitting

class AlgorithmTimeFitting.FitLorentz
extends NLConstrainedEngine

Field Summary

Fields

Modifier and Type	Field	Description
(package private) final double[]	ydata

Fields inherited from class gov.nih.mipav.model.algorithms.NLConstrainedEngine

a, absoluteConvergence, analyticalJacobian, bl, bounds, bu, ctrlMat, dyda, gues, internalScaling, iters, jacobian, maxIterations, nPts, outputMes, param, parameterConvergence, relativeConvergence, residuals, secondAllowed, stdv, tolerance

Constructor Summary

Constructors

Constructor	Description
FitLorentz(int tDim, double[] ydata, double[] initial, boolean[] useBounds, double[] lowBounds, double[] highBounds)

Method Summary

Modifier and Type	Method	Description
void	driver()	Starts the analysis.
void	dumpResults()	Display results of displaying Lorentz fitting parameters.
void	fitToFunction(double[] a, double[] residuals, double[][] covarMat)	Fit to function - a0/((t-a1)*(t-a1) + a2*a2)

Methods inherited from class gov.nih.mipav.model.algorithms.NLConstrainedEngine

dumpTestResults, fitToTestFunction, getChiSquared, getExitStatus, getIterations, getParameters, getResiduals, statusMessage

Methods inherited from class java.lang.Object

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

Field Details

ydata

final double[] ydata

Constructor Details

FitLorentz

public FitLorentz(int tDim,
 double[] ydata,
 double[] initial,
 boolean[] useBounds,
 double[] lowBounds,
 double[] highBounds)

Method Details

driver

public void driver()

Starts the analysis.

Overrides:

driver in class NLConstrainedEngine

dumpResults

public void dumpResults()

Display results of displaying Lorentz fitting parameters.

fitToFunction

public void fitToFunction(double[] a,
 double[] residuals,
 double[][] covarMat)

Fit to function - a0/((t-a1)*(t-a1) + a2*a2)

Specified by:

fitToFunction in class NLConstrainedEngine

Parameters:

a - The best guess parameter values.

residuals - ymodel - yData.

covarMat - The derivative values of y with respect to fitting parameters.