Package gov.nih.mipav.model.algorithms
Class AlgorithmFRAP.FitDoubleExponentialNoWholeModel
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- gov.nih.mipav.model.algorithms.NLConstrainedEngine
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- gov.nih.mipav.model.algorithms.AlgorithmFRAP.FitDoubleExponentialNoWholeModel
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- Enclosing class:
- AlgorithmFRAP
class AlgorithmFRAP.FitDoubleExponentialNoWholeModel extends NLConstrainedEngine
DOCUMENT ME!
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Field Summary
Fields Modifier and Type Field Description private double[]
xData
private float[]
yData
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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
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Constructor Summary
Constructors Constructor Description FitDoubleExponentialNoWholeModel(int nPoints, double[] xData, float[] yData, double[] initial)
Creates a new FitDoubleExponentialNoWholeModel object.
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Method Summary
All Methods Instance Methods Concrete Methods 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 - Fit to function - a3 + (1-a3)*[1 - ao*exp(a1*x) - (1 - a0)*exp(a2*x)].-
Methods inherited from class gov.nih.mipav.model.algorithms.NLConstrainedEngine
dumpTestResults, fitToTestFunction, getChiSquared, getExitStatus, getIterations, getParameters, getResiduals, statusMessage
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Constructor Detail
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FitDoubleExponentialNoWholeModel
public FitDoubleExponentialNoWholeModel(int nPoints, double[] xData, float[] yData, double[] initial)
Creates a new FitDoubleExponentialNoWholeModel object.- Parameters:
nPoints
- DOCUMENT ME!xData
- DOCUMENT ME!yData
- DOCUMENT ME!initial
- DOCUMENT ME!
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Method Detail
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driver
public void driver()
Starts the analysis.- Overrides:
driver
in classNLConstrainedEngine
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dumpResults
public void dumpResults()
Display results of displaying exponential fitting parameters.
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fitToFunction
public void fitToFunction(double[] a, double[] residuals, double[][] covarMat)
Fit to function - Fit to function - a3 + (1-a3)*[1 - ao*exp(a1*x) - (1 - a0)*exp(a2*x)].- Specified by:
fitToFunction
in classNLConstrainedEngine
- 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.
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