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ExtractMaskToTable dialog.
Table of Contents
| Name | Direction | Type | Default | Description |
|---|---|---|---|---|
| InputWorkspace | Input | MatrixWorkspace | Mandatory | A workspace whose masking is to be extracted or a MaskWorkspace. |
| MaskTableWorkspace | Input | TableWorkspace | A mask table workspace containing 3 columns: XMin, XMax and DetectorIDsList. | |
| OutputWorkspace | Output | TableWorkspace | A comma separated list or array containing a list of masked detector ID’s | |
| Xmin | Input | number | Optional | Minimum of X-value. |
| Xmax | Input | number | Optional | Maximum of X-value. |
It can be either a MaskWorkspace, containing the masking information, or a Data workspace (EventWorkspace or Workspace2D), having detectors masked.
If the optional input ‘MaskTableWorkspace’ is given, it must be a table workspace having the same format as output TableWorkspace such that it contains 3 columns, XMin, XMax and DetectorIDsList.
The contents in this mask table workspace will be copied to output workspace.
If a detector is masked in this input ‘MaskTableWorkspace’, and it is also masked in input MaskWorkspace or data workspace, the setup (Xmin and Xmax) in MaskTableWorkspace has higher priority, i.e., in the output mask table workspace, the masked detector will be recorded in the row copied from input MaskTableWrokspace.
Example - Extract mask to table without optional input table workspace:
# load data
dataws = LoadNexusProcessed(Filename="PG3_2538_2k.nxs")
# mask some detectors
for i in range(100):
dataws.maskDetectors(100+i)
# Run algorithm
outmaskws = ExtractMaskToTable(InputWorkspace=dataws, Xmin = 12300., Xmax = 24500.)
# Output
print("Number of rows: {}".format(outmaskws.rowCount()))
print("Row 0: Xmin = %.5f, Xmax = %.5f, DetectorIDsList = %s." % (outmaskws.cell(0, 0), outmaskws.cell(0, 1), outmaskws.cell(0, 2)))
Output:
Number of rows: 1
Row 0: Xmin = 12300.00000, Xmax = 24500.00000, DetectorIDsList = 27599-27698.
Example - Extract mask to table with an optional input table workspace:
# load data
dataws = LoadNexusProcessed(Filename="PG3_2538_2k.nxs")
# mask some detectors
for i in range(100):
dataws.maskDetectors(100+i)
# create a mask table workspacetws =
tws = CreateEmptyTableWorkspace()
tws.addColumn("double", "XMin")
tws.addColumn("double", "XMax")
tws.addColumn("str", "DetectorIDsList")
tws.addRow([10000, 20000, "10000"])
tws.addRow([12000, 20000, "20000, 20002-20004"])
# run algorithm
outmaskws = ExtractMaskToTable(InputWorkspace=dataws, MaskTableWorkspace=tws, Xmin = 12300., Xmax = 24500.)
# Write some result
print("Number of rows: {}".format(outmaskws.rowCount()))
print("Row 0: Xmin = %.5f, Xmax = %.5f, DetectorIDsList = %s." % (outmaskws.cell(0, 0), outmaskws.cell(0, 1), outmaskws.cell(0, 2)))
print("Row 1: Xmin = %.5f, Xmax = %.5f, DetectorIDsList = %s." % (outmaskws.cell(1, 0), outmaskws.cell(1, 1), outmaskws.cell(1, 2)))
print("Row 2: Xmin = %.5f, Xmax = %.5f, DetectorIDsList = %s." % (outmaskws.cell(2, 0), outmaskws.cell(2, 1), outmaskws.cell(2, 2)))
Output:
Number of rows: 3
Row 0: Xmin = 10000.00000, Xmax = 20000.00000, DetectorIDsList = 10000.
Row 1: Xmin = 12000.00000, Xmax = 20000.00000, DetectorIDsList = 20000, 20002-20004.
Row 2: Xmin = 12300.00000, Xmax = 24500.00000, DetectorIDsList = 27599-27698.
Categories: AlgorithmIndex | Transforms\Masking