6.4

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CropWorkspaceRagged v1

../_images/CropWorkspaceRagged-v1_dlg.png

CropWorkspaceRagged dialog.

Summary

Crops each spectrum of a workspace and produces a new workspace.

Properties

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.

Description

This is an algorithm that crops each spectrum of a workspace independently.

The minimum and maximum values that are specified are interpreted as follows:

  • One value per spectrum. If there is only one value overall, it is used for all of the spectra.
  • If the given value is smaller than the first data point, it will use the first data point.
  • If the given value is larger than the last data point, it will use the last data point.

Usage

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: 0.6287
y values: 0.6235
y values: 0.6487

Categories: AlgorithmIndex | Transforms\Splitting