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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

CentroidPeaksMD, PeakIntegration

Properties

Name

Direction

Type

Default

Description

InPeaksWorkspace

Input

PeaksWorkspace

Mandatory

A PeaksWorkspace containing the peaks to centroid.

InputWorkspace

Input

MatrixWorkspace

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