Package gov.nih.mipav.model.algorithms

Class AlgorithmTimeFitting

java.lang.Object

java.lang.Thread

gov.nih.mipav.model.algorithms.AlgorithmBase

gov.nih.mipav.model.algorithms.AlgorithmTimeFitting

All Implemented Interfaces:

ActionListener, WindowListener, Runnable, EventListener

public class AlgorithmTimeFitting
extends AlgorithmBase

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
(package private) class	AlgorithmTimeFitting.FitExponential
(package private) class	AlgorithmTimeFitting.FitGaussian
(package private) class	AlgorithmTimeFitting.FitLaplace
(package private) class	AlgorithmTimeFitting.FitLine
(package private) class	AlgorithmTimeFitting.FitLorentz
(package private) class	AlgorithmTimeFitting.FitMultiExponential
(package private) class	AlgorithmTimeFitting.FitRayleigh
class	AlgorithmTimeFitting.fittingTask

Nested classes/interfaces inherited from class java.lang.Thread

Thread.Builder, Thread.State, Thread.UncaughtExceptionHandler

Field Summary

Fields

Modifier and Type	Field	Description
private String	altTimeTag
private int	barMarker
private BitSet	bitMask
private double[]	destArray
private int[]	destExitStatusArray
private int[]	exitStatus
private ModelImage	exitStatusImage
private static final int	EXPONENTIAL_FIT
private boolean	findInitialFromData
private int	functionFit
private static final int	GAUSSIAN_FIT
private double[]	highBounds
private int	i
private double[]	initial
private static final int	LAPLACE_FIT
private static final int	LINEAR_FIT
private static final int	LORENTZ_FIT
private double[]	lowBounds
private static final int	MULTIEXPONENTIAL_FIT	From Exponential analysis in physical phenomena by Andrei A.
private int	numVariables
private int	oldBarMarker
private double[]	paramAverage
private int[]	paramInf
private double[]	paramMax
private double[]	paramMin
private int[]	paramNaN
private double[]	paramTotal
private int	processors
private static final int	RAYLEIGH_FIT
private double[]	srcArray
private int	tDim
private double[]	timeVals	A vector of center times for each volume
private boolean	useAltTimeTag
private boolean[]	useBounds
private boolean	useLog
private int	validVoxels
private int	volSize
private long	voxelsProcessed
private boolean	wholeImage
private int	xDim
private int	yDim
private int	zDim

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

destFlag, destImage, image25D, mask, maxProgressValue, minProgressValue, multiThreadingEnabled, nthreads, progress, progressModulus, progressStep, runningInSeparateThread, separable, srcImage, threadStopped

Fields inherited from class java.lang.Thread

MAX_PRIORITY, MIN_PRIORITY, NORM_PRIORITY

Constructor Summary

Constructors

Constructor	Description
AlgorithmTimeFitting(ModelImage destImage, ModelImage srcImage, ModelImage exitStatusImage, boolean useLog, int functionFit, int numVariables, boolean findInitialFromData, double[] initial, boolean[] useBounds, double[] lowBounds, double[] highBounds)	Creates a new AlgorithmTimeFitting object.
AlgorithmTimeFitting(ModelImage destImage, ModelImage srcImage, ModelImage exitStatusImage, boolean useLog, int functionFit, int numVariables, boolean findInitialFromData, double[] initial, boolean[] useBounds, double[] lowBounds, double[] highBounds, boolean useAltTimeTag, String altTimeTag)	Creates a new AlgorithmTimeFitting object.

Method Summary

Modifier and Type	Method	Description
void	finalize()	Prepares this class for destruction.
void	input(double[] y_array, int i)
void	output(double[] params, int i, int status, double chi_squared)
void	runAlgorithm()	starts the algorithm.

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

actionPerformed, addListener, addProgressChangeListener, calculateImageSize, calculatePrincipleAxis, computeElapsedTime, computeElapsedTime, convertIntoFloat, delinkProgressToAlgorithm, delinkProgressToAlgorithmMulti, displayError, errorCleanUp, fireProgressStateChanged, fireProgressStateChanged, fireProgressStateChanged, fireProgressStateChanged, fireProgressStateChanged, generateProgressValues, getDestImage, getElapsedTime, getMask, getMaxProgressValue, getMinProgressValue, getNumberOfThreads, getProgress, getProgressChangeListener, getProgressChangeListeners, getProgressModulus, getProgressStep, getProgressValues, getSrcImage, isCompleted, isImage25D, isMultiThreadingEnabled, isRunningInSeparateThread, isThreadStopped, linkProgressToAlgorithm, linkProgressToAlgorithm, makeProgress, notifyListeners, removeListener, removeProgressChangeListener, run, setCompleted, setImage25D, setMask, setMaxProgressValue, setMinProgressValue, setMultiThreadingEnabled, setNumberOfThreads, setProgress, setProgressModulus, setProgressStep, setProgressValues, setProgressValues, setRunningInSeparateThread, setSrcImage, setStartTime, setThreadStopped, startMethod, windowActivated, windowClosed, windowClosing, windowDeactivated, windowDeiconified, windowIconified, windowOpened

Methods inherited from class java.lang.Thread

activeCount, checkAccess, clone, countStackFrames, currentThread, dumpStack, enumerate, getAllStackTraces, getContextClassLoader, getDefaultUncaughtExceptionHandler, getId, getName, getPriority, getStackTrace, getState, getThreadGroup, getUncaughtExceptionHandler, holdsLock, interrupt, interrupted, isAlive, isDaemon, isInterrupted, isVirtual, join, join, join, join, ofPlatform, ofVirtual, onSpinWait, resume, setContextClassLoader, setDaemon, setDefaultUncaughtExceptionHandler, setName, setPriority, setUncaughtExceptionHandler, sleep, sleep, sleep, start, startVirtualThread, stop, suspend, threadId, toString, yield

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Field Details

LINEAR_FIT

private static final int LINEAR_FIT

See Also:

• Constant Field Values

EXPONENTIAL_FIT

private static final int EXPONENTIAL_FIT

See Also:

• Constant Field Values

GAUSSIAN_FIT

private static final int GAUSSIAN_FIT

See Also:

• Constant Field Values

LAPLACE_FIT

private static final int LAPLACE_FIT

See Also:

• Constant Field Values

LORENTZ_FIT

private static final int LORENTZ_FIT

See Also:

• Constant Field Values

MULTIEXPONENTIAL_FIT

private static final int MULTIEXPONENTIAL_FIT

From Exponential analysis in physical phenomena by Andrei A. Istratov and Oleg F. Vyvenko: Note that for a multiexponential fit nonlinear least squares analysis as used here can handle nonzero baseline offsets. However, for nonlinear least squares initial guesses are needed for the values of unknown decay parameters and, if these initial guesses are poor, the iteration may converge to a local minimum rather than to the absolute minimum. With Prony's method the baseline offset should be removed first. The differentiation of transients only allows the exponent time constants to be determined. It does not allow the amplitudes by which the exponents are multiplied to be determined. Also experimental transients are noisy, and large errors would result from their numerical differentiation. The method of modulating functions does not enable one to determine the amplitude of the transients and is not tolerant to nonzero baseline offsets. The integration method allows one to determine the baseline. However, the solution is more stable and exact if the baseline is subtracted from the raw signal before the analysis. For the integration method, on computed two-component decays with tau1/tau2 = 2.5 the reliable separation of components is impossible if the SNR is less than 30. For tau1/tau2, two components can be separated for a SNR of about 10. When two-component analysis is performed with a baseline determination the mean error of the calculated time constants increases by a factor of about 3-10. Before the method of moments can be applied, the baseline offset must be removed from the data. The Laplace-Pade approximation is not applicable to decays containing baseline offset. Tolerance of the method to baseline offsets may be very important, depending on whether a baseline offset can be encountered in the experiment. Few of the discussed techniques are tolerable of nonzero baseline offsets. Such commonly used methods as Prony's or method of moments will provide wrong results or even crash if a decay contains an offset. Unfortunately, algorithms for extrapolation of baseline offsets are poorly developed and are not always sufficiently exact. Therefore, we would recommend algorithms that do not require baseline corrections and can accommodate transients with a baseline. Taking into account stability for wide range changes in parameters and insensitivity to baseline offsets, the authors select nonlinear least squares as the best fitting method for multiexponential fits. Fitting routines are only accurate if the number of components is correct and the initial approximation is close to the true solution. A way to obtain this initial approximation is to extract it from a spectroscopic method, as was done by Provencher and Mazzola et al.

See Also:

• Constant Field Values

RAYLEIGH_FIT

private static final int RAYLEIGH_FIT

See Also:

• Constant Field Values

timeVals

private double[] timeVals

A vector of center times for each volume

srcArray

private double[] srcArray

i

private int i

xDim

private int xDim

yDim

private int yDim

zDim

private int zDim

tDim

private int tDim

volSize

private int volSize

findInitialFromData

private boolean findInitialFromData

initial

private double[] initial

useBounds

private boolean[] useBounds

lowBounds

private double[] lowBounds

highBounds

private double[] highBounds

exitStatus

private int[] exitStatus

paramNaN

private int[] paramNaN

paramInf

private int[] paramInf

paramMin

private double[] paramMin

paramMax

private double[] paramMax

paramTotal

private double[] paramTotal

paramAverage

private double[] paramAverage

processors

private int processors

destArray

private double[] destArray

destExitStatusArray

private int[] destExitStatusArray

voxelsProcessed

private long voxelsProcessed

barMarker

private int barMarker

oldBarMarker

private int oldBarMarker

bitMask

private BitSet bitMask

validVoxels

private int validVoxels

wholeImage

private boolean wholeImage

exitStatusImage

private ModelImage exitStatusImage

useLog

private boolean useLog

functionFit

private int functionFit

numVariables

private int numVariables

useAltTimeTag

private boolean useAltTimeTag

altTimeTag

private String altTimeTag

Constructor Details

AlgorithmTimeFitting

public AlgorithmTimeFitting(ModelImage destImage,
 ModelImage srcImage,
 ModelImage exitStatusImage,
 boolean useLog,
 int functionFit,
 int numVariables,
 boolean findInitialFromData,
 double[] initial,
 boolean[] useBounds,
 double[] lowBounds,
 double[] highBounds)

Creates a new AlgorithmTimeFitting object.

AlgorithmTimeFitting

public AlgorithmTimeFitting(ModelImage destImage,
 ModelImage srcImage,
 ModelImage exitStatusImage,
 boolean useLog,
 int functionFit,
 int numVariables,
 boolean findInitialFromData,
 double[] initial,
 boolean[] useBounds,
 double[] lowBounds,
 double[] highBounds,
 boolean useAltTimeTag,
 String altTimeTag)

Creates a new AlgorithmTimeFitting object.

Method Details

finalize

public void finalize()

Prepares this class for destruction.

Overrides:

finalize in class AlgorithmBase

runAlgorithm

public void runAlgorithm()

starts the algorithm.

Specified by:

runAlgorithm in class AlgorithmBase

input

public void input(double[] y_array,
 int i)

output

public void output(double[] params,
 int i,
 int status,
 double chi_squared)