NormaliseByThickness v1

../_images/NormaliseByThickness-v1_dlg.png

NormaliseByThickness dialog.

Summary

Normalise detector counts by the sample thickness.

Properties

Name Direction Type Default Description
InputWorkspace Input MatrixWorkspace Mandatory  
OutputWorkspace Output MatrixWorkspace Mandatory Name of the workspace that will contain the normalised data
SampleThickness Input number 0 Optional sample thickness value. If not provided the sample-thickness run property will be used.
OutputMessage Output string   Output message

Description

Normalise detector counts by the sample thickness.

Usage

#create a workspace
raw=CreateSampleWorkspace()

#apply algorithm
norm=NormaliseByThickness(raw,SampleThickness=10)

#do a quick check
print(norm[1])
print("Min(raw)= {}".format(raw.dataY(0).min()))
print("Min(norm)= {}".format(norm[0].dataY(0).min()))
print("Max(raw)= {}".format(raw.dataY(0).max()))
print("Max(norm)= {}".format(norm[0].dataY(0).max()))

Output:

Normalised by thickness [10 cm]
Min(raw)= 0.3
Min(norm)= 0.03
Max(raw)= 10.3
Max(norm)= 1.03

Categories: AlgorithmIndex | Workflow\SANS

Source

Python: NormaliseByThickness.py (last modified: 2018-10-05)