Package gov.nih.mipav.model.algorithms
Class AlgorithmTimeFitting.FitMultiExponential
- java.lang.Object
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- gov.nih.mipav.model.algorithms.NLConstrainedEngine
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- gov.nih.mipav.model.algorithms.AlgorithmTimeFitting.FitMultiExponential
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- Enclosing class:
- AlgorithmTimeFitting
class AlgorithmTimeFitting.FitMultiExponential extends NLConstrainedEngine
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Field Summary
Fields Modifier and Type Field Description (package private) double[]
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 FitMultiExponential(int tDim, double[] ydata, double[] initial, boolean[] useBounds, double[] lowBounds, double[] highBounds)
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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 multiExponential fitting parameters.void
fitToFunction(double[] a, double[] residuals, double[][] covarMat)
Fit to function - a0 + a1*exp(a2*t) + a3*exp(a4*t) + ...-
Methods inherited from class gov.nih.mipav.model.algorithms.NLConstrainedEngine
dumpTestResults, fitToTestFunction, getChiSquared, getExitStatus, getIterations, getParameters, getResiduals, statusMessage
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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 multiExponential fitting parameters.
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fitToFunction
public void fitToFunction(double[] a, double[] residuals, double[][] covarMat)
Fit to function - a0 + a1*exp(a2*t) + a3*exp(a4*t) + ... where all the exponentials are negative decaying exponentials.- Specified by:
fitToFunction
in classNLConstrainedEngine
- Parameters:
a
- The best guess parameter values.residuals
- ymodel - yData.covarMat
- The derivative values of y with respect to fitting parameters.
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