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Table of Contents
Name | Direction | Type | Default | Description |
---|---|---|---|---|
InputWorkspace | Input | MatrixWorkspace | Mandatory | The input workspace |
OutputWorkspace | Output | MatrixWorkspace | Mandatory | Name to be given to the cropped workspace. |
XMin | Input | dbl list | Mandatory | The value(s) to start the cropping from. Should be either a single value or a list. |
XMax | Input | dbl list | Mandatory | The value(s) to end the cropping at. Should be either a single value or a list. |
This is an algorithm that crops each spectrum of a workspace independently.
The minimum and maximum values that are specified are interpreted as follows:
Example - Crop a workspace.
ws = CreateWorkspace([0,1,2,3,4,2, 3,4,5,6],[0,1,2,3,4,3,4,5,6,7], NSpec=2)
x_min=[]
x_max =[]
for j in range(ws.getNumberHistograms()):
x_min.append(1.0+j)
x_max.append(14.0)
new=CropWorkspaceRagged(ws,x_min,x_max)
print("The number of bins in spectrum 1 is: {}".format(new.readX(0).size))
print("The number of bins in spectrum 2 is: {}".format(new.readX(1).size))
Output:
The number of bins in spectrum 1 is: 4
The number of bins in spectrum 2 is: 5
Example - Crop a workspace as part of a workflow.
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.
This is an example of how CropWorkspaceRagged
would be used near
the end of a workflow to generate a real-space distribution of data
after it had been reduced into a number of “banks” or “spectra.” As
mentioned above, numpy.nan
or math.nan
can both be used.
from numpy import nan
NOM_91796 = LoadNexusProcessed(Filename='NOM_91796_banks.nxs')
CropWorkspaceRagged(InputWorkspace=NOM_91796, OutputWorkspace='cropped',
Xmin=[0.67, 1.20, 2.42, 3.70, 4.12, 0.39],
Xmax=[10.20, 20.8, nan, nan, nan, 9.35])
binning=(0.,.02,40.)
Rebin(InputWorkspace='cropped', OutputWorkspace='cropped',
Params=binning)
# put into a single spectrum and Fourier transform
SumSpectra(InputWorkspace='cropped', OutputWorkspace='FQ',
WeightedSum=True, RemoveSpecialValues=True)
gr=PDFFourierTransform(InputWorkspace='FQ', OutputWorkspace='Gr',
Direction="Backward", DeltaR=.02)
for j in range(10,13):
print("y values: {:.4f}".format(gr.readY(0)[j]))
Output:
y values: 0.6285
y values: 0.6237
y values: 0.6486
Categories: AlgorithmIndex | Transforms\Splitting
C++ header: CropWorkspaceRagged.h (last modified: 2021-03-31)
C++ source: CropWorkspaceRagged.cpp (last modified: 2021-03-31)