Package gov.nih.mipav.model.algorithms

Class AlgorithmSM2.FitAll

java.lang.Object

gov.nih.mipav.model.algorithms.NLConstrainedEngine

gov.nih.mipav.model.algorithms.AlgorithmSM2.FitAll

Enclosing class:

AlgorithmSM2

class AlgorithmSM2.FitAll
extends NLConstrainedEngine

Field Summary

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
FitAll()	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

Constructor Detail

FitAll

public FitAll()

Creates a new Fit24DModel object.

Parameters:

nPoints - DOCUMENT ME!

xData - DOCUMENT ME!

yData - DOCUMENT ME!

initial - DOCUMENT ME!

Method Detail

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.