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IndirectILLReductionDIFF dialog.
Table of Contents
| Name | Direction | Type | Default | Description |
|---|---|---|---|---|
| SampleRuns | Input | list of str lists | Mandatory | File path for run(s). Allowed values: [‘nxs’] |
| OutputWorkspace | Output | MatrixWorkspace | Mandatory | The output workspace group containing reduced data. |
| MaskPixelsFromStart | Input | number | 10 | Number of pixels to mask at the start of each tube |
| MaskPixelsFromEnd | Input | number | 10 | Number of pixels to mask at the end of each tube |
| Observable | Input | string | sample.temperature | If multiple files, the parameter from SampleLog to use as an index when conjoined. |
| Transpose | Input | boolean | True | Transpose the result. |
| Sum | Input | boolean | False | Sum along the scan |
| ComponentsToMask | Input | string | Comma separated list of component names to mask, for instance: tube_1, tube_2 |
This algorithm reduces data acquired by the diffraction detectors of IN16B indirect geometry instrument at ILL.
Ultimately, it will handle both BATS and Doppler data, but the later is the only one implemented as of now.
To reduce data acquired in Doppler mode, this algorithms sums data over all Doppler channels and normalize by monitor counts.
Example - IndirectILLReductionDIFF
ws = IndirectILLEnergyTransfer(Run='ILL/IN16B/276047.nxs')
print("Reduced workspace has {:d} spectra".format(ws.getItem(0).getNumberHistograms()))
print("and {:d} bins.".format(ws.getItem(0).blocksize()))
Output:
Reduced workspace has 18 spectra
and 512 bins.
Categories: AlgorithmIndex | ILL\Indirect
Python: IndirectILLReductionDIFF.py