Table of Contents
Name | Direction | Type | Default | Description |
---|---|---|---|---|
InputWorkspace | Input | MatrixWorkspace | Mandatory | The workspace containing the Masking to extract. |
OutputFile | Input | string | Mandatory | The file for the results. Allowed values: [‘cal’] |
Invert | Input | boolean | False | If True, masking is inverted in the input workspace. Default: False |
This algorithms writes a cal file with the selection column set to the masking status of the workspaces provided. The offsets and grouping details of the cal file are not completed, so you would normally use MargeCalFiles afterwards to import these values from another file.
import os
# Create a workspace containing some data.
ws = CreateSampleWorkspace()
# Mask two detectors by specifying detector IDs 101 and 103
MaskDetectors(ws,DetectorList=[101,103])
# Create a file path in the user home directory
calFilePath = os.path.expanduser('~/MantidUsageExample_CalFile.cal')
# Save the masking in a cal file.
MaskWorkspaceToCalFile( ws, calFilePath );
# Read the saved file back
f = open( calFilePath, 'r' )
calFile = f.read().split('\n')
f.close()
# Print out first 10 lines of the file
for line in calFile[:10]:
print line
# basic_rect detector file
# Format: number UDET offset select group
0 100 0.0000000 1 1
1 101 0.0000000 0 0
2 102 0.0000000 1 1
3 103 0.0000000 0 0
4 104 0.0000000 1 1
5 105 0.0000000 1 1
6 106 0.0000000 1 1
7 107 0.0000000 1 1
Categories: Algorithms | DataHandling\Text | Diffraction\DataHandling | Diffraction\Masking
Python: MaskWorkspaceToCalFile.py