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NormaliseSpectra v1¶

Summary¶

Normalise all spectra to have a max value of 1

Name

Direction

Type

Default

Description

InputWorkspace

Input

MatrixWorkspace

Mandatory

Input workspace

OutputWorkspace

Output

MatrixWorkspace

Mandatory

Output workspace

Description¶

Algorithm designed to normalise all the spectra in the input workspace so that the value of the resulting workspace has a maximum of 1. This algorithm is designed to run on workspaces where every spectra contains at least one y value greater than 0. This is the case because the data is being normalised to be a maximum of positive 1.

The algorithm works by extracting each spectrum from the workspace in turn, finding the maximum y value in the spectrum and then calculating 1/the maximum y value

to obtain the scale factor required to normalise the maximum point to 1. The whole spectrum is then scaled using the Scale algorithm and the scale factor and this is repeated for all specta. The spectra are then all returned in the outputworkspace.

Usage¶

Example - NormaliseSpectra

# Create Workspace
data = '0,1,2,3,4,5'
ws = CreateWorkspace(DataX=data, DataY=data, DataE=data, Nspec=1)

# Execute algorithm
out_ws = NormaliseSpectra(InputWorkspace=ws)

# Print resulting y values
print(out_ws.readY(0))


Output:

[ 0. 0.2  0.4  0.6  0.8  1. ]


Categories: AlgorithmIndex | Workflow\MIDAS | Inelastic

Source¶

Python: NormaliseSpectra.py