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PredictFractionalPeaks v1¶

Summary ¶

The offsets can be from hkl values in a range of hkl values or from peaks in the input PeaksWorkspace

Properties ¶

Name	Direction	Type	Default	Description
Peaks	Input	PeaksWorkspace	Mandatory	Workspace of Peaks with orientation matrix that indexed the peaks and instrument loaded
Hoffset	Input	dbl list	-0.5,0,0.5	Offset in the h direction
Koffset	Input	dbl list	0	Offset in the k direction
Loffset	Input	dbl list	-0.5,0.5	Offset in the h direction
IncludeAllPeaksInRange	Input	boolean	False	If false only offsets from peaks from Peaks are used
Hmin	Input	number	-8	Minimum H value to use during search
Hmax	Input	number	8	Maximum H value to use during search
Kmin	Input	number	-8	Minimum K value to use during search
Kmax	Input	number	8	Maximum K value to use during search
Lmin	Input	number	-8	Minimum L value to use during search
Lmax	Input	number	8	Maximum L value to use during search
ReflectionCondition	Input	string		If provided, generate a list of possible peaks from this reflection condition and use them to predict the fractional peaks. This option requires a range of HKL values and implies IncludeAllPeaksInRange=true. Allowed values: [‘’, ‘Primitive’, ‘C-face centred’, ‘A-face centred’, ‘B-face centred’, ‘Body centred’, ‘All-face centred’, ‘Rhombohedrally centred, obverse’, ‘Rhombohedrally centred, reverse’, ‘Hexagonally centred, reverse’]
RequirePeaksOnDetector	Input	boolean	True	If true then the predicted peaks are required to hit a detector pixel. Default=true
ModVector1	Input	dbl list	0,0,0	Modulation Vector 1: dh, dk, dl
ModVector2	Input	dbl list	0,0,0	Modulation Vector 2: dh, dk, dl
ModVector3	Input	dbl list	0,0,0	Modulation Vector 3: dh, dk, dl
MaxOrder	Input	number	0	Maximum order to apply Modulation Vectors. Default = 0
CrossTerms	Input	boolean	False	Include combinations of modulation vectors in satellite search
FracPeaks	Output	PeaksWorkspace	Mandatory	Workspace of Peaks with peaks with fractional h,k, and/or l values

Description ¶

This Algorithm creates a PeaksWorkspace with peaks occurring at specific fractional offsets from h,k,or l values.

There are options to create Peaks offset from peaks from the input PeaksWorkspace, or to create peaks offset from h,k, and l values in a range. Zero offsets are allowed if some or all integer h,k, or l values are desired

The input PeaksWorkspace must contain an orientation matrix and have been INDEXED by THIS MATRIX when the new peaks are not created from a range of h ,k, and l values

Usage ¶

Example:

peaks = LoadIsawPeaks("TOPAZ_3007.peaks")
LoadIsawUB(peaks,"TOPAZ_3007.mat")
IndexPeaks(peaks)

fractional_peaks = PredictFractionalPeaks(peaks, HOffset=[-0.5,0,0.5],KOffset=0,LOffset=0.2)
print("Number of fractional peaks: {}".format(fractional_peaks.getNumberPeaks()))