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MSDFit v1

MSDFit dialog.

Summary

Fits Intensity vs Q for 3 models to obtain the mean squared displacement.

Properties

Name	Direction	Type	Default	Description
InputWorkspace	Input	MatrixWorkspace	Mandatory	Sample input workspace
Model	Input	string	Gauss	Model options : Gauss, Peters, Yi. Allowed values: [‘Gauss’, ‘Peters’, ‘Yi’]
XStart	Input	number	0	Start of fitting range
XEnd	Input	number	0	End of fitting range
SpecMin	Input	number	0	Start of spectra range to be fit
SpecMax	Input	number	0	End of spectra range to be fit
OutputWorkspace	Output	MatrixWorkspace	Mandatory	Output mean squared displacement
ParameterWorkspace	Output	TableWorkspace		Output fit parameters table
FitWorkspaces	Output	WorkspaceGroup		Output fitted workspaces

Description

Fits \(intensity\) vs \(Q\) with a straight line for each run to obtain the mean square displacement for a given range of runs.

This algorithm operates on the \(Q\) workspace (_eq) generated by the ElasticWindowMultiple algorithm.

The model used for obtaining the mean squared displacement can be selected. These models include ‘Gaussian’, ‘Peters’, ‘Yi’.

Workflow

Usage

Example - Performing MSDFit on simulated data.

# Create some data that is similar to the output of ElasticWindowMultiple
sample = CreateSampleWorkspace(Function='User Defined',
                UserDefinedFunction='name=ExpDecay,Height=1,Lifetime=6',
                NumBanks=1, BankPixelWidth=1, XUnit='momentum', XMin=0.0,
                XMax=5.0, BinWidth=0.1)

g_msd, g_param, g_fit = MSDFit(InputWorkspace=sample,
                               Model="Gauss",
                               XStart=0.0, XEnd=5.0,
                               SpecMin=0, SpecMax=0)

y_msd, y_param, y_fit = MSDFit(InputWorkspace=sample,
                               Model="Yi",
                               XStart=0.0, XEnd=5.0,
                               SpecMin=0, SpecMax=0)

print('Using Gauss Model')
print('A0: ' + str(g_msd.readY(0)))
print('A1: ' + str(g_msd.readY(1)))
print('Using Yi Model')
print('A0: ' + str(y_msd.readY(0)))
print('A1: ' + str(y_msd.readY(1)))

Output (the numbers on your machine my not match exactly):

  Using Gauss Model
  A0: [ 0.87...]
  A1: [ 0.19...]
  Using Yi Model
  A0: [ 0.95...]
  A1: [ 0.58...]

Categories: AlgorithmIndex | Workflow\MIDAS

Source

Python: MSDFit.py