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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

See Also

PredictPeaks

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

C++ source: PredictFractionalPeaks.cpp