Package gov.nih.mipav.model.algorithms

Class AlgorithmFRAP.Fit24DModel

java.lang.Object

gov.nih.mipav.model.algorithms.NLConstrainedEngine

gov.nih.mipav.model.algorithms.AlgorithmFRAP.Fit24DModel

Enclosing class:

AlgorithmFRAP

class AlgorithmFRAP.Fit24DModel
extends NLConstrainedEngine

DOCUMENT ME!

Field Summary

Fields

Modifier and Type	Field	Description
private double[]	xData
private float[]	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
Fit24DModel(int nPoints, double[] xData, float[] yData, double[] initial)	Creates a new Fit24DModel object.

Method Summary

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

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

xData

private double[] xData

yData

private float[] yData

Constructor Details

Fit24DModel

public Fit24DModel(int nPoints,
 double[] xData,
 float[] yData,
 double[] initial)

Creates a new Fit24DModel object.

Parameters:

nPoints - DOCUMENT ME!

xData - DOCUMENT ME!

yData - DOCUMENT ME!

initial - DOCUMENT ME!

Method Details

driver

public void driver()

Starts the analysis.

Overrides:

driver in class NLConstrainedEngine

dumpResults

public void dumpResults()

Display results of displaying exponential fitting parameters.

fitToFunction

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

Fit to function - a0 - a1*(a2**x).

Specified by:

fitToFunction in class NLConstrainedEngine

Parameters:

a - The x value of the data point.

residuals - The best guess parameter values.

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