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SumNeighbours dialog.
Table of Contents
Sum event lists from neighboring pixels in rectangular area detectors - e.g. to reduce the signal-to-noise of individual spectra. Each spectrum in the output workspace is a sum of a block of SumX*SumY pixels. Only works on EventWorkspaces and for instruments with RectangularDetector’s.
| Name | Direction | Type | Default | Description |
|---|---|---|---|---|
| InputWorkspace | Input | MatrixWorkspace | Mandatory | A workspace containing one or more rectangular area detectors. Each spectrum needs to correspond to only one pixelID (e.g. no grouping or previous calls to SumNeighbours). |
| OutputWorkspace | Output | MatrixWorkspace | Mandatory | The name of the workspace to be created as the output of the algorithm. |
| SumX | Input | number | 4 | The number of X (horizontal) pixels to sum together. This must evenly divide the number of X pixels in a detector. |
| SumY | Input | number | 4 | The number of Y (vertical) pixels to sum together. This must evenly divide the number of Y pixels in a detector |
The algorithm looks through the Instrument to find all the RectangularDetectors defined. For each detector, the SumX*SumY neighboring event lists are summed together and saved in the output workspace as a single spectrum. Therefore, the output workspace will have 1/(SumX*SumY) * the original number of spectra.
Example:
ws = CreateSampleWorkspace(BankPixelWidth=10,NumBanks=2)
print("ws has %i spectra to begin with" % ws.getNumberHistograms())
wsOut = SumNeighbours(ws,5,5)
print("wsOut has only %i spectra after beimng summed into 5x5 blocks" % wsOut.getNumberHistograms())
Output:
ws has 200 spectra to begin with
wsOut has only 8 spectra after beimng summed into 5x5 blocks
Categories: AlgorithmIndex | Transforms\Grouping