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IntegratePeaks1DProfile v1

Summary

Integrate single-crystal Bragg peaks in MatrixWorkspaces by fitting peaks TOF in adjacent pixels unitl I/sigma of the peak in a pixel is below a threshold. Algorithm is adapted and extendedfrom an algorithm in Gutmann, M. J. (2005). SXD2001. ISIS Facility, RAL

See Also

IntegratePeaksSkew, IntegratePeaksShoeboxTOF

Properties

Name	Direction	Type	Default	Description
InputWorkspace	Input	MatrixWorkspace	Mandatory	A MatrixWorkspace to integrate (x-axis must be TOF).
PeaksWorkspace	Input	IPeaksWorkspace	Mandatory	A PeaksWorkspace containing the peaks to integrate.
OutputWorkspace	Output	IPeaksWorkspace	Mandatory	The output PeaksWorkspace will be a copy of the input PeaksWorkspace with the integrated intensities.
NRows	Input	number	11	Number of row components in the detector to use in the convolution kernel. For WISH row components correspond to pixels along a single tube.
NCols	Input	number	11	Number of column components in the detector to use in the convolution kernel. For WISH column components correspond to tubes.
NBins	Input	number	11	Number of TOF bins to use in the convolution kernel.
GetNBinsFromBackToBackParams	Input	boolean	False	If true the number of TOF bins used in the convolution kernel will be calculated from the FWHM of the BackToBackExponential peak using parameters defined in the instrument parameters.xml file.
NFWHM	Input	number	10	If GetNBinsFromBackToBackParams=True then the number of TOF bins will be NFWHM x FWHM of the BackToBackExponential at the peak detector and TOF.
CostFunction	Input	string	Mandatory	Cost funtion to minimise. Allowed values: [‘RSq’, ‘ChiSq’, ‘Poisson’]
PeakFunction	Input	string	BackToBackExponential	Peak profile funtion to fit. Allowed values: [‘BackToBackExponential’, ‘Gaussian’]
FixPeakParameters	Input	str list		Peak parameters to fix in the fits (recommend fixing A for back-to-back exponential based functions).
BackgroundFunction	Input	string	FlatBackground	Background function to fit. Allowed values: [‘FlatBackground’, ‘LinearBackground’]
ErrorStrategy	Input	string	Summation	If Hessian then error on the integrated intensity will be determined from the partial derivatives of the cost-function wrt the parameters (this is only supported for BackToBackExponential function for which the integrated intensity is a parameter. If Summation then the error will be the quadrature sum of the individual errors. Allowed values: [‘Hessian’, ‘Summation’]
IOverSigmaThreshold	Input	number	2.5	Criterion to stop fitting.
FractionalChangeDSpacing	Input	number	0.02	Fractional change in peak centre allowed - this is a constraint in the fit.
IntegrateIfOnEdge	Input	boolean	False	If IntegrateIfOnEdge=False then peaks on the detector edge will not be integrated.
NRowsEdge	Input	number	1	Shoeboxes containing detectors NRowsEdge from the detector edge are defined as on the edge.
NColsEdge	Input	number	1	Shoeboxes containing detectors NColsEdge from the detector edge are defined as on the edge.
LorentzCorrection	Input	boolean	True	Correct the integrated intensity by multiplying by the Lorentz factor sin(theta)^2 / lambda^4 - do not do this if the data have already been corrected.
OutputFile	Input	string		Optional file path in which to write diagnostic plots (note this will slow the execution of algorithm). Allowed extensions: [‘.pdf’]

Description

This is an algorithm to integrate single-crystal Bragg peaks in a MatrixWorkspace with x-units of Time-of-Flight (TOF). It is adapted and extended from an algorithm in SXD2001 [1].

The algorithm proceeds by fitting a PeakFunction and BackgroundFunction to the TOF spectrum of individual pixels. If the fit is successful (fit converged and the ratio of intensity/sigma > IOverSigmaThreshold), then the fit is attempted on a pixel that is adjacent to a previously successfully fit pixel. The algorithm stops when no adjacent pixels can be successfully fitted.

The algorithm requires the user to define the number of pixels in the vicinity of a peak using the input NRows and NCols and the TOF extent of the data to fit, which can be specified in one of two ways:

1. Provide NBins directly - number of TOF bins in the kernel

2. Setting GetNBinsFromBackToBackParams=True and providing NFWHM - in which case NBins will be NFWHM x FWHM of a BackToBackExponential peak at the center of each detector panel/bank at the middle of the spectrum.

Note to use method 2, back-to-back exponential coefficients must be defined in the Parameters.xml file for the instrument.

Optionally if OutputFile is provided a pdf can be output that shows the shoebox kernel and the data integrated along each dimension like so

Usage

Example - IntegratePeaks1DProfile

from mantid.simpleapi import *

Load(Filename="SXD23767.raw", OutputWorkspace="SXD23767")
CreatePeaksWorkspace(InstrumentWorkspace="SXD23767", NumberOfPeaks=0, OutputWorkspace="peaks")
AddPeak(PeaksWorkspace="peaks", RunWorkspace="SXD23767", TOF=8303.3735339704781, DetectorID=7646)

peaks_out = IntegratePeaks1DProfile(InputWorkspace="SXD23767", PeaksWorkspace="peaks", OutputWorkspace="peaks_int",
                                    GetNBinsFromBackToBackParams=True, NFWHM=6, CostFunction="Poisson",
                                    PeakFunction="BackToBackExponential", FixPeakParameters='A',
                                    FractionalChangeDSpacing=0.01, IntegrateIfOnEdge=True)

print(f"I/sigma = {peaks_out.getPeak(0).getIntensityOverSigma():.2f}")

Output:

I/sigma = 100.46

References

[1]

Gutmann, M. J. (2005). SXD2001. ISIS Facility, Rutherford Appleton Laboratory, Oxfordshire, England.

Categories: AlgorithmIndex | Diffraction\Reduction

Source

Python: IntegratePeaks1DProfile.py