CentroidPeaks v1

../_images/CentroidPeaks-v1_dlg.png

CentroidPeaks dialog.

Summary

Find the centroid of single-crystal peaks in a 2D Workspace, in order to refine their positions.

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   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='/home/vel/workspace/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: Algorithms | Crystal

Source

C++ source: CentroidPeaks.cpp

C++ header: CentroidPeaks.h