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CentroidPeaks v1¶
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Summary¶
Find the centroid of single-crystal peaks in a 2D Workspace, in order to refine their positions.
See Also¶
Properties¶
Name |
Direction |
Type |
Default |
Description |
|---|---|---|---|---|
InPeaksWorkspace |
Input |
PeaksWorkspace |
Mandatory |
A PeaksWorkspace containing the peaks to centroid. |
InputWorkspace |
Input |
Mandatory |
An input 2D Workspace. |
|
PeakRadius |
Input |
number |
10 |
Fixed radius around each peak position in which to calculate the centroid. |
EdgePixels |
Input |
number |
0 |
The number of pixels where peaks are removed at edges. Only for instruments with RectangularDetectors. |
OutPeaksWorkspace |
Output |
PeaksWorkspace |
Mandatory |
The output PeaksWorkspace will be a copy of the input PeaksWorkspace with the peaks’ positions modified by the new found centroids. |
Description¶
This algorithm starts with a PeaksWorkspace containing the expected positions of peaks in detector space. It calculates the centroid of the peak by calculating the average of the coordinates of all events within a given radius of the peak, weighted by the weight (signal) of the event for event workspaces or the intensity for histogrammed workspaces.
Usage¶
# Load a SCD data set from systemtests Data and find the peaks
LoadEventNexus(Filename='TOPAZ_3132_event.nxs', OutputWorkspace='TOPAZ_3132_nxs')
ConvertToDiffractionMDWorkspace(InputWorkspace='TOPAZ_3132_nxs', OutputWorkspace='TOPAZ_3132_md', LorentzCorrection=True)
peaks = FindPeaksMD(InputWorkspace='TOPAZ_3132_md', PeakDistanceThreshold=0.14999999999999999, MaxPeaks=100)
FindUBUsingFFT(PeaksWorkspace='peaks', MinD=2, MaxD=16)
IndexPeaks(PeaksWorkspace='peaks', NumIndexed=100, AverageError=0.013759860303255647)
peak = peaks.getPeak(0)
print(peak.getBinCount())
peaks = CentroidPeaks(InPeaksWorkspace='peaks', InputWorkspace='TOPAZ_3132_nxs')
peak = peaks.getPeak(0)
print(peak.getBinCount())
Categories: AlgorithmIndex | Crystal\Peaks
Source¶
C++ header: CentroidPeaks.h
C++ source: CentroidPeaks.cpp