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SpatialGrouping v1

SpatialGrouping dialog.

Summary

This algorithm creates an XML grouping file, which can be used in GroupDetectors or ReadGroupsFromFile, which groups the detectors of an instrument based on the distance between the detectors. It does this by querying the getNeighbours method on the Detector object.

See Also

GroupDetectors

Properties

Name	Direction	Type	Default	Description
InputWorkspace	Input	MatrixWorkspace	Mandatory	Name of the input workspace, which is used only as a means of retrieving the instrument geometry.
Filename	Input	string	Mandatory	Name (and location) in which to save the file. Having a suffix of ‘’.xml’’ is recommended. Allowed extensions: [‘.xml’]
SearchDistance	Input	number	2.5	The number of pixel widths in which to search for neighbours of the detector.
GridSize	Input	number	3	The size of the grid that should be grouped. i.e, 3 (the default) will select a group of nine detectors centred in a 3 by 3 grid.

Description

This algorithm creates an XML Grouping file of the form:

<?xml version="1.0" encoding="UTF-8" ?>
<detector-grouping>
<group name="fwd"><detids val="1,2,17,32"/></group>
<group name="bwd"><detids val="33,36,38,60,64"/> </group>
</detector-grouping>

Based on information retrieved from the Nearest Neighbours class in Mantid Geometry.

Usage

Caution

The following is a contrived example to show the functionaity of the algorithm, However, since the sample workspace does not have a valid instrument, the written grouping file is invalid and cannot be used.

# Create a workspace with a single bank and 9x9 pixels.
ws = CreateSampleWorkspace(NumBanks=1, BankPixelWidth=9)
import os
group_file = os.path.join(config["default.savedirectory"], "mygroup.xml")
# Want to get nine groups of 3x3
SpatialGrouping(ws, group_file, SearchDistance=10)
print("File created: {}".format(os.path.exists(group_file)))

Output:

File created: True

Categories: AlgorithmIndex | Transforms\Grouping

Source

C++ header: SpatialGrouping.h

C++ source: SpatialGrouping.cpp