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Table of Contents
Converts a workspace from Q sample to a MDHisto in HKL; the UB matrix can be used from the input, or calculated from peaks found from the input.
Name | Direction | Type | Default | Description |
---|---|---|---|---|
InputWorkspace | Input | MDEventWorkspace | Mandatory | Input MDEvent workspace to convert to a MDHisto in HKL |
PeaksWorkspace | Input | IPeaksWorkspace | Optional peaks workspace to retrieve the UB matrix from, instead of InputWorkspace. | |
Uproj | Input | dbl list | 1,0,0 | Defines the first projection vector of the target Q coordinate system in HKL mode |
Vproj | Input | dbl list | 0,1,0 | Defines the second projection vector of the target Q coordinate system in HKL mode |
Wproj | Input | dbl list | 0,0,1 | Defines the third projection vector of the target Q coordinate system in HKL mode |
Extents | Input | dbl list | -6.02,6.02,-6.02,6.02,-6.02,6.02 | Binning parameters for each dimension. Enter it as acomma-separated list of values with theformat: ‘minimum,maximum,’. |
Bins | Input | long list | 301,301,301 | Number of bins to use for each dimension, Enter it as acomma-separated list of integers. |
OutputWorkspace | Output | IMDHistoWorkspace | Mandatory | Output MDWorkspace in Q-space, name is prefix if multiple input files were provided. |
This algorithm provides a way to convert from a MDEventWorkspace in QSample units to a MDHistoWorkspace in HKL units. By default, the UB matrix from the InputWorkspace is used unless PeaksWorkspace is provided. In this case, the UB matrix from the specified PeaksWorkspace will be used instead.
Note that this algorithm does not take into account normalization of the output, it only bins the data in HKL. See MDNorm (if using TOF) to account for normalizing when converting to HKL.
Categories: AlgorithmIndex | MDAlgorithms\Creation
Python: ConvertQtoHKLMDHisto.py (last modified: 2021-05-05)