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ChopData v1

ChopData dialog.

Summary

Splits an input workspace into a grouped workspace, where each spectra if ‘chopped’ at a certain point (given in ‘Step’ input value) and the X values adjusted to give all the workspace in the group the same binning.

See Also

ExtractSpectra

Properties

Name	Direction	Type	Default	Description
InputWorkspace	Input	MatrixWorkspace	Mandatory	Name of the input workspace to be split.
OutputWorkspace	Output	WorkspaceGroup	Mandatory	Name for the WorkspaceGroup that will be created.
Step	Input	number	20000
NChops	Input	number	5
IntegrationRangeLower	Input	number	Optional
IntegrationRangeUpper	Input	number	Optional
MonitorWorkspaceIndex	Input	number	Optional

Description

This algorithm will chop the input workspace into equally sized workspaces, and adjust the X-values given so that they all begin from the same point. This is useful if your raw files contain multiple frames.

Identifying Extended Frames

Figure 1: Example Monitor Spectrum with Extended Frames

If the parameters IntegrationRangeLower, IntegrationRangeUpper and MonitorWorkspaceIndex are provided to the algorithm, then it will attempt to identify where in the workspace the frames have been extended.

For example: looking at Figure 1 which shows an input workspace covering 100000 microseconds, we can see that the first frame covers forty thousand, and the other three cover twenty thousand each.

In order for Mantid to determine this programmatically, it integrates over a range (defined by IntegrationRangeLower and IntegrationRangeUpper) for each “chop” of the data. If the relative values for this integration fall within certain bounds, then the chop is deemed to be a continuation of the previous one rather than a separate frame. If this happens, then they will be placed in the same workspace within the result group.

The algorithm will only look at the workspace given in MonitorWorkspaceIndex property to determine this. Though it is expected and recommended that you use a monitor spectrum for this purpose, it is not enforced so you may use a regular detector if you have cause to do so.

Usage

Example - Roughly Chop Workspace

Note

To run these usage examples please first download the usage data, and add these to your path. In Mantid this is done using Manage User Directories.

# Creates a dummy ws with a single spectrum with 100 bins.  There is exactly 1 count in every bin.
ws = CreateSampleWorkspace("Histogram", "Flat background", NumBanks=1, BankPixelWidth=1)

time_diff = (ws.readX(0)[99] - ws.readX(0)[0])

# Chop the workspace roughly in two.
result = ChopData(ws, NChops=2, Step=time_diff/2)

print("The time range of the original workspace was {:.0f}.".format(time_diff))
print("The number of bins in the original workspace was {}.".format(ws.blocksize()))
print("The number of bins in the 1st chop is {}.".format(result[0][0].blocksize()))
print("The number of bins in the 2nd chop is {}.".format(result[0][1].blocksize()))

Output:

The time range of the original workspace was 19800.
The number of bins in the original workspace was 100.
The number of bins in the 1st chop is 48.
The number of bins in the 2nd chop is 48.

Categories: AlgorithmIndex | Transforms\Splitting

Source

C++ header: ChopData.h

C++ source: ChopData.cpp