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IndirectTwoPeakFit v1

../_images/IndirectTwoPeakFit-v1_dlg.png

IndirectTwoPeakFit dialog.

Summary

Performs a convolution fit for 1 and 2 Lorentzians.

Properties

Name Direction Type Default Description
SampleWorkspace Input MatrixWorkspace Mandatory Name for the sample workspace.
EnergyMin Input number -0.5 Minimum energy for fit. Default=-0.5
EnergyMax Input number 0.5 Maximum energy for fit. Default=0.5
Minimizer Input string Levenberg-Marquardt Type of minimizer. Allowed values: [‘Levenberg-Marquardt’, ‘FABADA’]
MaxIterations Input number 500 Max iterations. Default=500
OutputName Input string   Output workspace base name

Description

This performs a one lorentzian convolution fit, and then performs a two lorentzian convolution fit on the sample workspace.

Usage

Example - IndirectTwoPeakFit

# Produce the reduced file used in the two peak fit
EnergyWindowScan(InputFiles='92762', Instrument='OSIRIS', Analyser='graphite', Reflection='002',
                 SpectraRange='963,980', ElasticRange='-0.02,0.02', InelasticRange='0.4,0.5',
                 TotalRange='-0.5,0.5', ReducedWorkspace='__reduced_group', ScanWorkspace='__scan_workspace')

# Perform a two peak fit
IndirectTwoPeakFit(SampleWorkspace='osiris92762_graphite002_red', EnergyMin=-0.5,
                   EnergyMax=0.5, OutputName='osiris92762_graphite002_two_peak_fit')

Categories: AlgorithmIndex | Workflow\Inelastic | PythonAlgorithms | Workflow\MIDAS

Source

Python: IndirectTwoPeakFit.py (last modified: 2020-03-20)