Table of Contents
Select a conventional cell with a specific lattice type and centering, corresponding to the UB stored with the sample for this peaks works space.
Name | Direction | Type | Default | Description |
---|---|---|---|---|
PeaksWorkspace | InOut | PeaksWorkspace | Mandatory | Input Peaks Workspace |
CellType | Input | string | Cubic | The conventional cell type to use. Allowed values: [‘Cubic’, ‘Hexagonal’, ‘Rhombohedral’, ‘Tetragonal’, ‘Orthorhombic’, ‘Monoclinic’, ‘Triclinic’] |
Centering | Input | string | P | The centering for the conventional cell. Allowed values: [‘F’, ‘I’, ‘C’, ‘P’, ‘R’] |
Apply | Input | boolean | False | Update UB and re-index the peaks |
Tolerance | Input | number | 0.12 | Indexing Tolerance |
NumIndexed | Output | number | The number of indexed peaks if apply==true. | |
AverageError | Output | number | The average HKL indexing error if apply==true. | |
AllowPermutations | Input | boolean | True | Allow permutations of conventional cells |
Given a PeaksWorkspace with a UB matrix corresponding to a Niggli reduced cell, this algorithm will allow the user to select a conventional cell with a specified cell type and centering. If the apply flag is not set, the information about the selected cell will just be displayed. If the apply flag is set, the UB matrix associated with the sample in the PeaksWorkspace will be updated to a UB corresponding to the selected cell AND the peaks will be re-indexed using the new UB matrix. NOTE: The possible conventional cells, together with the corresponding errors in the cell scalars can be seen by running the ShowPossibleCells algorithm, provided the stored UB matrix corresponds to a Niggli reduced cell.
This algorithm is based on the paper: “Lattice Symmetry and Identification – The Fundamental Role of Reduced Cells in Materials Characterization”, Alan D. Mighell, Vol. 106, Number 6, Nov-Dec 2001, Journal of Research of the National Institute of Standards and Technology, available from: nvlpubs.
Example:
ws=LoadIsawPeaks("TOPAZ_3007.peaks")
FindUBUsingFFT(ws,MinD=8.0,MaxD=13.0)
print "Lattice before SelectCellOfType:"
lattice = ws.sample().getOrientedLattice()
print lattice.a(),lattice.b(),lattice.c(),lattice.alpha(),lattice.beta(),lattice.gamma()
SelectCellOfType(PeaksWorkspace=ws, CellType='Monoclinic', Centering='C', Apply=True)
print "\nLattice after SelectCellOfType:"
lattice = ws.sample().getOrientedLattice()
print lattice.a(),lattice.b(),lattice.c(),lattice.alpha(),lattice.beta(),lattice.gamma()
Output:
Lattice before SelectCellOfType:
8.60581864273 11.935925461 11.9418127661 107.429088323 98.7529124665 98.9511934747
Lattice after SelectCellOfType:
14.1310511523 19.247332564 8.60581864273 89.8811706749 105.07133377 89.970386662
Categories: Algorithms | Crystal