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MSDFit v1

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

diagram generation was disabled

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: [ ...]
  A1: [ ...]
  Using Yi Model
  A0: [ ...]
  A1: [ ...]

Categories: AlgorithmIndex | Workflow\MIDAS

Source

Python: MSDFit.py