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PredictFractionalPeaks v1

../_images/PredictFractionalPeaks-v1_dlg.png

PredictFractionalPeaks dialog.

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()))
Number of fractional peaks: 117

Categories: AlgorithmIndex | Crystal\Peaks

Source

C++ header: PredictFractionalPeaks.h (last modified: 2021-03-31)

C++ source: PredictFractionalPeaks.cpp (last modified: 2021-03-31)