3.12

SortHKL v1

../_images/SortHKL-v1_dlg.png

SortHKL dialog.

Summary

Sorts a PeaksWorkspace by HKL. Averages intensities using point group.

Properties

Name Direction Type Default Description
InputWorkspace Input PeaksWorkspace Mandatory An input PeaksWorkspace with an instrument.
PointGroup Input string -1 Which point group applies to this crystal? Allowed values: [‘-1’, ‘-3’, ‘-3 r’, ‘-31m’, ‘-3m’, ‘-3m r’, ‘-3m1’, ‘-4’, ‘-42m’, ‘-43m’, ‘-4m2’, ‘-6’, ‘-62m’, ‘-6m2’, ‘1’, ‘112’, ‘112/m’, ‘11m’, ‘2’, ‘2/m’, ‘222’, ‘23’, ‘2mm’, ‘3’, ‘3 r’, ‘312’, ‘31m’, ‘32’, ‘32 r’, ‘321’, ‘3m’, ‘3m r’, ‘3m1’, ‘4’, ‘4/m’, ‘4/mmm’, ‘422’, ‘432’, ‘4mm’, ‘6’, ‘6/m’, ‘6/mmm’, ‘622’, ‘6mm’, ‘m’, ‘m-3’, ‘m-3m’, ‘m2m’, ‘mm2’, ‘mmm’, ‘-1 (Triclinic)’, ‘-3 (Trigonal - Hexagonal)’, ‘-3 r (Trigonal - Rhombohedral)’, ‘-31m (Trigonal - Hexagonal)’, ‘-3m (Trigonal - Hexagonal)’, ‘-3m r (Trigonal - Rhombohedral)’, ‘-3m1 (Trigonal - Hexagonal)’, ‘-4 (Tetragonal)’, ‘-42m (Tetragonal)’, ‘-43m (Cubic)’, ‘-4m2 (Tetragonal)’, ‘-6 (Hexagonal)’, ‘-62m (Hexagonal)’, ‘-6m2 (Hexagonal)’, ‘1 (Triclinic)’, ‘112 (Monoclinic, unique axis c)’, ‘112/m (Monoclinic, unique axis c)’, ‘11m (Monoclinic, unique axis c)’, ‘2 (Monoclinic, unique axis b)’, ‘2/m (Monoclinic, unique axis b)’, ‘222 (Orthorhombic)’, ‘23 (Cubic)’, ‘2mm (Orthorhombic)’, ‘3 (Trigonal - Hexagonal)’, ‘3 r (Trigonal - Rhombohedral)’, ‘312 (Trigonal - Hexagonal)’, ‘31m (Trigonal - Hexagonal)’, ‘32 (Trigonal - Hexagonal)’, ‘32 r (Trigonal - Rhombohedral)’, ‘321 (Trigonal - Hexagonal)’, ‘3m (Trigonal - Hexagonal)’, ‘3m r (Trigonal - Rhombohedral)’, ‘3m1 (Trigonal - Hexagonal)’, ‘4 (Tetragonal)’, ‘4/m (Tetragonal)’, ‘4/mmm (Tetragonal)’, ‘422 (Tetragonal)’, ‘432 (Cubic)’, ‘4mm (Tetragonal)’, ‘6 (Hexagonal)’, ‘6/m (Hexagonal)’, ‘6/mmm (Hexagonal)’, ‘622 (Hexagonal)’, ‘6mm (Hexagonal)’, ‘m (Monoclinic, unique axis b)’, ‘m-3 (Cubic)’, ‘m-3m (Cubic)’, ‘m2m (Orthorhombic)’, ‘mm2 (Orthorhombic)’, ‘mmm (Orthorhombic)’, ‘222 (Orthorombic)’, ‘mm2 (Orthorombic)’, ‘2mm (Orthorombic)’, ‘m2m (Orthorombic)’, ‘mmm (Orthorombic)’]
LatticeCentering Input string P Appropriate lattice centering for the peaks. Allowed values: [‘P’, ‘C’, ‘A’, ‘B’, ‘I’, ‘F’, ‘Robv’, ‘Rrev’, ‘H’, ‘Primitive’, ‘C-face centred’, ‘A-face centred’, ‘B-face centred’, ‘Body centred’, ‘All-face centred’, ‘Rhombohedrally centred, obverse’, ‘Rhombohedrally centred, reverse’, ‘Hexagonally centred, reverse’]
OutputWorkspace Output PeaksWorkspace   Output PeaksWorkspace
OutputChi2 Output number   Chi-square is available as output
StatisticsTable Output TableWorkspace StatisticsTable An output table workspace for the statistics of the peaks.
RowName Input string Overall name of row
Append Input boolean False Append to output table workspace if true. If false, new output table workspace (default).

Description

SortHKL calculates some data set statistics using the intensities of the peaks in the supplied input workspace, such as R_{merge} and R_{p.i.m.}, (formulas and references for example here) but also redundancy and completeness.

At first, the algorithm determines the minimum and maximum d-value from the input peaks. Using these limits, the unit cell, centering and point group all possible unique reflections are calculated, the number of which is N_{theor.}.

After removing invalid peaks with I \leq 0, \sigma \leq 0 and h=k=l=0, the peaks are assigned to their respective unique reflection so that each theoretically present reflection may have n observations (n can be zero). The number of unique reflections which have at least one observation can be labeled N_{unique}. The completeness is defined as the fraction \frac{N_{unique}}{N_{theor.}} and ranges between 0 and 1. The total number of observations N_{observed} and N_{unique} determine the average redundancy \frac{N_{observed}}{N_{unique}} in the data set, which is the average number of observations for each unique reflection.

The intensities of peaks in each reflection are checked for outliers, which are removed. Outliers in this context are peaks with an intensity that deviates more than 3\sigma_{hkl} from the mean of the reflection, where \sigma_{hkl} is the standard deviation of the peak intensities.

The intensities and errors of each peak is set to the mean intensity and sigma of the unique reflection it belongs to, so that equivalent reflections have the same intensity and error in the output workspace.

Finally, the peaks in the output workspace are sorted by H, K and L.

Usage

The following usage example uses data obtained from a trigonal structure. The peaks are loaded and a UB matrix is determined. The peaks are transformed to conform with a conventional cell, which has hexagonal metric and rhombohedral centering:

# Load example peak data and find cell
peaks = LoadIsawPeaks(Filename=r'Peaks5637.integrate')

FindUBUsingFFT(peaks, MinD=0.25, MaxD=10, Tolerance=0.2)
SelectCellWithForm(peaks, FormNumber=9, Apply=True, Tolerance=0.15)
OptimizeLatticeForCellType(peaks,
                           CellType='Hexagonal', Apply=True, Tolerance=0.2)

# Run the SortHKL algorithm
sorted, chi2, statistics_table = SortHKL(peaks, PointGroup='-3m1 (Trigonal - Hexagonal)',
                                         LatticeCentering='Rhombohedrally centred, obverse')

statistics = statistics_table.row(0)

print('Data set statistics:')
print('        Peaks: {0}'.format(sorted.getNumberPeaks()))
print('       Unique: {0}'.format(statistics['No. of Unique Reflections']))
print(' Completeness: {0}%'.format(round(statistics['Data Completeness'], 2)))
print('   Redundancy: {0}'.format(round(statistics['Multiplicity'], 2)))

Output:

Data set statistics:
        Peaks: 408
       Unique: 337
 Completeness: 9.11%
   Redundancy: 1.21

Categories: Algorithms | Crystal\Peaks | DataHandling\Text | Utility\Sorting

Source

C++ source: SortHKL.cpp (last modified: 2018-02-27)

C++ header: SortHKL.h (last modified: 2017-03-07)