java.lang.Object
- gov.nih.mipav.model.algorithms.NLConstrainedEngine
- - gov.nih.mipav.model.algorithms.NLFittedFunction
  - - gov.nih.mipav.model.algorithms.FitLaplace

```
public class FitLaplace
extends NLFittedFunction
```
FitLaplace -fits an array of points to a normal curve, general from f = a*exp(Math.abs(x-mu)/beta) Will also perform thresholding techniques to determine useful data points for fitting

Version:

0.1

Author:

senseneyj

See Also:

NLConstrainedEngine

Field Summary

Fields
Modifier and Type	Field	Description
`private double`	`amp`	Amplitude parameter
`private double`	`beta`	Beta parameter
`private int`	`dataEnd`	Location in xSeries where Gaussian data ends
`private int`	`dataStart`	Location in xSeries where Gaussian data starts
`private int`	`iters`
`private double`	`mu`	Center parameter

Fields inherited from class gov.nih.mipav.model.algorithms.NLFittedFunction
chisq, EPSILON, MAX_ITR, MIN_ITR, xSeries, yDataFitted, ySeries

Fields inherited from class gov.nih.mipav.model.algorithms.NLConstrainedEngine
a, absoluteConvergence, analyticalJacobian, bl, bounds, bu, ctrlMat, dyda, gues, internalScaling, jacobian, maxIterations, nPts, outputMes, param, parameterConvergence, relativeConvergence, residuals, secondAllowed, stdv, tolerance

Constructor Summary

Constructors
Constructor	Description
`FitLaplace()`	FitLaplace - test constructor, builds and test function.
`FitLaplace(int nPoints, double[] xData, double[] yData)`	FitLaplace.
`FitLaplace(int nPoints, float[] xData, float[] yData)`	Constructs new fit laplace distribution.

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`protected void`	`calculateChiSq()`	Calculates chi squared
`protected void`	`calculateFittedY()`	Calculates yDataFitted
`void`	`displayResults()`	Display results of displaying exponential fitting parameters.
`private double`	`dLdA(double x)`	Partial derivative of laplace dist with respect to A.
`private double`	`dLdbeta(double x)`	Partial derivative of laplace dist with respect to beta.
`private double`	`dLdmu(double x)`	Partial derivative of laplace dist with respect to mu.
`void`	`driver()`	Starts the analysis.
`private void`	`estimateInitial()`
`void`	`fitToFunction(double[] a, double[] residuals, double[][] covarMat)`	fitToFunction communicates with 3 protected variables param, nPts, and ctrlMat ctrlMat is used as a wrapper for ctrl or lctrl.
`protected Jama.Matrix`	`generateJacobian()`	Jacobian used for non-linear least squares fitting.
`protected Jama.Matrix`	`generateResiduals()`	Calculates the residuals for a given function, not implemented since some functions might prefer to only use a subset of data points, or not use yDataFitted if working during an iteration
`private double`	`laplace(double x)`	Gaussian evaluated at a point with given parameters
`private void`	`testData()`	Test data to test fitting of gaussian.

Methods inherited from class gov.nih.mipav.model.algorithms.NLFittedFunction
getChisq, getFittedY, getMedian

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 Detail
  - dataStart
```
private int dataStart
```
    Location in xSeries where Gaussian data starts
  - dataEnd
```
private int dataEnd
```
    Location in xSeries where Gaussian data ends
  - amp
```
private double amp
```
    Amplitude parameter
  - mu
```
private double mu
```
    Center parameter
  - beta
```
private double beta
```
    Beta parameter
  - iters
```
private int iters
```
- Constructor Detail
  - FitLaplace
```
public FitLaplace()
```
    FitLaplace - test constructor, builds and test function.
  - FitLaplace
```
public FitLaplace(int nPoints,
                  double[] xData,
                  double[] yData)
```
    FitLaplace.
    
    Parameters:
    
    nPoints - number of points in the function
    
    xData - DOCUMENT ME!
    
    yData - DOCUMENT ME!
  - FitLaplace
```
public FitLaplace(int nPoints,
                  float[] xData,
                  float[] yData)
```
    Constructs new fit laplace distribution.
    
    Parameters:
    
    nPoints - Number of points in the function
    
    xData - DOCUMENT ME!
    
    yData - DOCUMENT ME!
- Method Detail
  - estimateInitial
```
private void estimateInitial()
```
  - driver
```
public void driver()
```
    Starts the analysis. For some reason a guess with the wrong sign for a2 will not converge. Therefore, try both sign and take the one with the lowest chi-squared value.
    
    Overrides:
    
    driver in class NLConstrainedEngine
  - calculateChiSq
```
protected void calculateChiSq()
```
    Description copied from class: NLFittedFunction
    
    Calculates chi squared
    
    Specified by:
    
    calculateChiSq in class NLFittedFunction
  - calculateFittedY
```
protected void calculateFittedY()
```
    Description copied from class: NLFittedFunction
    
    Calculates yDataFitted
    
    Specified by:
    
    calculateFittedY in class NLFittedFunction
  - displayResults
```
public void displayResults()
```
    Display results of displaying exponential fitting parameters.
    
    Specified by:
    
    displayResults in class NLFittedFunction
  - fitToFunction
```
public void fitToFunction(double[] a,
                          double[] residuals,
                          double[][] covarMat)
```
    Description copied from class: NLConstrainedEngine
    
    fitToFunction communicates with 3 protected variables param, nPts, and ctrlMat ctrlMat is used as a wrapper for ctrl or lctrl. Evaluates the residuals or the Jacobian at a certain a[]
    
    Specified by:
    
    fitToFunction in class NLConstrainedEngine
    
    Parameters:
    
    a - DOCUMENT ME!
    
    residuals - DOCUMENT ME!
    
    covarMat - DOCUMENT ME!
  - testData
```
private void testData()
```
    Test data to test fitting of gaussian.
  - laplace
```
private double laplace(double x)
```
    Gaussian evaluated at a point with given parameters
  - dLdA
```
private double dLdA(double x)
```
    Partial derivative of laplace dist with respect to A.
  - dLdmu
```
private double dLdmu(double x)
```
    Partial derivative of laplace dist with respect to mu.
  - dLdbeta
```
private double dLdbeta(double x)
```
    Partial derivative of laplace dist with respect to beta.
  - generateJacobian
```
protected Jama.Matrix generateJacobian()
```
    Jacobian used for non-linear least squares fitting.
  - generateResiduals
```
protected Jama.Matrix generateResiduals()
```
    Description copied from class: NLFittedFunction
    
    Calculates the residuals for a given function, not implemented since some functions might prefer to only use a subset of data points, or not use yDataFitted if working during an iteration
    
    Specified by:
    
    generateResiduals in class NLFittedFunction
    
    Returns:

Class FitLaplace

Field Summary

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

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

Constructor Summary

Method Summary

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

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

Methods inherited from class java.lang.Object

Field Detail

dataStart

dataEnd

amp

mu

beta

iters

Constructor Detail

FitLaplace

FitLaplace

FitLaplace

Method Detail

estimateInitial

driver

calculateChiSq

calculateFittedY

displayResults

fitToFunction

testData

laplace

dLdA

dLdmu

dLdbeta

generateJacobian

generateResiduals