Package de.gsi.math.spectra

Class TSpectrum

java.lang.Object

de.gsi.math.spectra.TSpectrum

public class TSpectrum
extends java.lang.Object

Original Author: Miroslav Morhac 27/05/99 clean up/java port: Ralph Steinhagen 18/04/18 THIS CLASS CONTAINS ADVANCED SPECTRA PROCESSING FUNCTIONS. ONE-DIMENSIONAL BACKGROUND ESTIMATION FUNCTIONS ONE-DIMENSIONAL SMOOTHING FUNCTIONS ONE-DIMENSIONAL DECONVOLUTION FUNCTIONS ONE-DIMENSIONAL PEAK SEARCH FUNCTIONS These functions were written by: Miroslav Morhac Institute of Physics Slovak Academy of Sciences Dubravska cesta 9, 842 28 BRATISLAVA SLOVAKIA email:fyzimiro@savba.sk, fax:+421 7 54772479 The original code in C has been repackaged as a C++ class by R.Brun The algorithms in this class have been published in the following references: [1] M.Morhac et al.: Background elimination methods for multidimensional coincidence gamma-ray spectra. Nuclear Instruments and Methods in Physics Research A 401 (1997) 113-132. [2] M.Morhac et al.: Efficient one- and two-dimensional Gold deconvolution and its application to gamma-ray spectra decomposition. Nuclear Instruments and Methods in Physics Research A 401 (1997) 385-408. [3] M.Morhac et al.: Identification of peaks in multidimensional coincidence gamma-ray spectra. Nuclear Instruments and Methods in Research Physics A 443(2000), 108-125. These NIM papers are also available as doc or ps files from: ftp://root.cern.ch/root/Spectrum.doc

ftp://root.cern.ch/root/SpectrumDec.ps.gz ftp://root.cern.ch/root/SpectrumSrc.ps.gz ftp://root.cern.ch/root/SpectrumBck.ps.gz The original source documentation as well as examples can be found at http://root.cern.ch/

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static class	TSpectrum.Direction
static class	TSpectrum.FilterOrder
static class	TSpectrum.SmoothWindow

Method Summary

Modifier and Type	Method	Description
static double[]	background(double[] source, double[] destination, int length, int numberIterations, TSpectrum.Direction direction, TSpectrum.FilterOrder filterOrder, TSpectrum.SmoothWindow smoothing, boolean compton)	ONE-DIMENSIONAL BACKGROUND ESTIMATION FUNCTION - GENERAL FUNCTION This function calculates background spectrum from source spectrum.
static double[]	deconvolution(double[] source, double[] response, double[] destination, int length, int numberIterations, int numberRepetitions, double boost)	ONE-DIMENSIONAL DECONVOLUTION FUNCTION This function calculates deconvolution from source spectrum according to response spectrum using Gold algorithm The result is placed in the vector pointed by destination pointer.
static double[]	deconvolutionRL(double[] source, double[] response, double[] destination, int length, int numberIterations, int numberRepetitions, double boost)	ONE-DIMENSIONAL DECONVOLUTION FUNCTION This function calculates deconvolution from source spectrum according to response spectrum using Richardson-Lucy algorithm The result is placed in the vector pointed by destination pointer.
protected static void	filterBackgroundOrder2(double[] workingSpace, int length, int numberIterations, TSpectrum.Direction direction, TSpectrum.SmoothWindow smoothing)
protected static void	filterBackgroundOrder4(double[] workingSpace, int length, int numberIterations, TSpectrum.Direction direction, TSpectrum.SmoothWindow smoothing)
protected static void	filterBackgroundOrder6(double[] workingSpace, int length, int numberIterations, TSpectrum.Direction direction, TSpectrum.SmoothWindow smoothing)
protected static void	filterBackgroundOrder8(double[] workingSpace, int length, int numberIterations, TSpectrum.Direction direction, TSpectrum.SmoothWindow smoothing)
static java.util.List<de.gsi.dataset.spi.utils.DoublePoint>	search(double[] sourceX, double[] sourceY, double[] destVector, int length, int nMaxPeaks, double sigma, double threshold, boolean backgroundRemove, int deconIterations, boolean markov, int averWindow)	ONE-DIMENSIONAL HIGH-RESOLUTION PEAK SEARCH FUNCTION This function searches for peaks in source spectrum It is based on deconvolution method.
static double[]	smoothMarkov(double[] source, double[] destination, int length, int averWindow)	ONE-DIMENSIONAL MARKOV SPECTRUM SMOOTHING FUNCTION This function calculates smoothed spectrum from source spectrum based on Markov chain method.
static double[]	unfolding(double[] source, double[][] respMatrix, double[] destination, int lengthx, int lengthy, int numberIterations, int numberRepetitions, double boost)	ONE-DIMENSIONAL UNFOLDING FUNCTION This function unfolds source spectrum according to response matrix columns.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Method Detail

background

public static double[] background(double[] source,
                                  double[] destination,
                                  int length,
                                  int numberIterations,
                                  TSpectrum.Direction direction,
                                  TSpectrum.FilterOrder filterOrder,
                                  TSpectrum.SmoothWindow smoothing,
                                  boolean compton)

ONE-DIMENSIONAL BACKGROUND ESTIMATION FUNCTION - GENERAL FUNCTION This function calculates background spectrum from source spectrum. The result is placed in the vector pointed by spectrum pointer.

Parameters:

source - vector of source spectrum

destination - where to copy the filtered background

length - length of the spectrum vector

numberIterations - maximal width of clipping window,

direction - direction of change of clipping window - possible values=kBackIncreasingWindow kBackDecreasingWindow

filterOrder - order of clipping filter, -possible values=kBackOrder2 kBackOrder4 kBackOrder6 kBackOrder8

smoothing - logical variable whether the smoothing operation in the estimation of background will be included resp. smoothing window

compton - logical variable whether the estimation of Compton edge will be included - possible values=kFALSE kTRUE

Returns:

filtered array, N.B. if destination is null or has insufficient length a new array is being allocated, otherwise calculations are done in-place.

deconvolution

public static double[] deconvolution(double[] source,
                                     double[] response,
                                     double[] destination,
                                     int length,
                                     int numberIterations,
                                     int numberRepetitions,
                                     double boost)

ONE-DIMENSIONAL DECONVOLUTION FUNCTION This function calculates deconvolution from source spectrum according to response spectrum using Gold algorithm The result is placed in the vector pointed by destination pointer.

Parameters:

source - vector of source spectrum

response - vector of response spectrum

destination - vector to store result (if null or too small, new vector is allocated and returned)

length - length of source and response spectra

numberIterations - for details we refer to the reference given below

numberRepetitions - for repeated boosted deconvolution @boost, boosting coefficient M. Morhac, J. Kliman, V. Matousek, M. Veselsk, I. Turzo.: Efficient one- and two-dimensional Gold deconvolution and its application to gamma-ray spectra decomposition. NIM, A401 (1997) 385-408.

boost - ???

Returns:

filtered array, N.B. if destination is null or has insufficient length a new array is being allocated, otherwise calculations are done in-place.

deconvolutionRL

public static double[] deconvolutionRL(double[] source,
                                       double[] response,
                                       double[] destination,
                                       int length,
                                       int numberIterations,
                                       int numberRepetitions,
                                       double boost)

ONE-DIMENSIONAL DECONVOLUTION FUNCTION This function calculates deconvolution from source spectrum according to response spectrum using Richardson-Lucy algorithm The result is placed in the vector pointed by destination pointer.

Parameters:

source - vector of source spectrum

response - vector of response spectrum

destination - vector to store result (if null or too small, new vector is allocated and returned)

length - length of source and response spectra

numberIterations - for details we refer to the reference given above

numberRepetitions - for repeated boosted deconvolution

boost - boosting coefficient

Returns:

filtered array, N.B. if destination is null or has insufficient length a new array is being allocated, otherwise calculations are done in-place.

filterBackgroundOrder2

protected static void filterBackgroundOrder2(double[] workingSpace,
                                             int length,
                                             int numberIterations,
                                             TSpectrum.Direction direction,
                                             TSpectrum.SmoothWindow smoothing)

filterBackgroundOrder4

protected static void filterBackgroundOrder4(double[] workingSpace,
                                             int length,
                                             int numberIterations,
                                             TSpectrum.Direction direction,
                                             TSpectrum.SmoothWindow smoothing)

filterBackgroundOrder6

protected static void filterBackgroundOrder6(double[] workingSpace,
                                             int length,
                                             int numberIterations,
                                             TSpectrum.Direction direction,
                                             TSpectrum.SmoothWindow smoothing)

filterBackgroundOrder8

protected static void filterBackgroundOrder8(double[] workingSpace,
                                             int length,
                                             int numberIterations,
                                             TSpectrum.Direction direction,
                                             TSpectrum.SmoothWindow smoothing)

search

public static java.util.List<de.gsi.dataset.spi.utils.DoublePoint> search(double[] sourceX,
                                                                          double[] sourceY,
                                                                          double[] destVector,
                                                                          int length,
                                                                          int nMaxPeaks,
                                                                          double sigma,
                                                                          double threshold,
                                                                          boolean backgroundRemove,
                                                                          int deconIterations,
                                                                          boolean markov,
                                                                          int averWindow)

ONE-DIMENSIONAL HIGH-RESOLUTION PEAK SEARCH FUNCTION This function searches for peaks in source spectrum It is based on deconvolution method. First the background is removed (if desired), then Markov spectrum is calculated (if desired), then the response function is generated according to given sigma and deconvolution is carried out.

Parameters:

sourceX - vector of source spectrum

sourceY - vector of source spectrum

destVector - vector of resulting deconvolved spectrum

length - length of source spectrum

nMaxPeaks - maximum number of peaks to search for (upper bound)

sigma - sigma of searched peaks, for details we refer to manual

threshold - threshold value in % for selected peaks, peaks with amplitude less than threshold*highest_peak/100 are ignored, see manual

backgroundRemove - logical variable, set if the removal of background before deconvolution is desired

deconIterations - number of iterations in deconvolution operation

markov - logical variable, if it is true, first the source spectrum is replaced by new spectrum calculated using Markov chains method.

averWindow - averaging window of searched peaks, for details we refer to manual (applies only for Markov method)

Returns:

list with identified peaks

smoothMarkov

public static double[] smoothMarkov(double[] source,
                                    double[] destination,
                                    int length,
                                    int averWindow)

ONE-DIMENSIONAL MARKOV SPECTRUM SMOOTHING FUNCTION This function calculates smoothed spectrum from source spectrum based on Markov chain method. The result is placed in the array pointed by source pointer.

Parameters:

source - array of source spectrum

destination - array where to store the filtered background

length - length of source array

averWindow - width of averaging smoothing window

Returns:

filtered array, N.B. if destination is null or has insufficient length a new array is being allocated, otherwise calculations are done in-place.

unfolding

public static double[] unfolding(double[] source,
                                 double[][] respMatrix,
                                 double[] destination,
                                 int lengthx,
                                 int lengthy,
                                 int numberIterations,
                                 int numberRepetitions,
                                 double boost)

ONE-DIMENSIONAL UNFOLDING FUNCTION This function unfolds source spectrum according to response matrix columns. The result is placed in the vector pointed by source pointer.

Parameters:

source - vector of source spectrum

respMatrix - matrix of response spectra

destination - vector of unfolded source spectrum

lengthx - length of source spectrum and # of columns of response matrix

lengthy - length of destination spectrum and # of rows of response matrix

numberIterations - Note!!! lengthx must be >= lengthy

numberRepetitions - repetition count

boost - boosting coefficient

Returns:

filtered array, N.B. if destination is null or has insufficient length a new array is being allocated, otherwise calculations are done in-place.