Table of Contents
Name | Direction | Type | Default | Description |
---|---|---|---|---|
InputWorkspace | Input | MatrixWorkspace | Mandatory | The _iqt.nxs InputWorkspace used by the algorithm |
Function | Input | string | The function to use in fitting | |
FitType | Input | string | The type of fit being carried out | |
StartX | Input | number | 0 | The first value for X |
EndX | Input | number | 0.2 | The last value for X |
SpecMin | Input | number | 0 | Minimum spectra in the worksapce to fit |
SpecMax | Input | number | 1 | Maximum spectra in the worksapce to fit |
Minimizer | Input | string | Levenberg-Marquardt | The minimizer to use in fitting |
MaxIterations | Input | number | 500 | The Maximum number of iterations for the fit |
ConstrainIntensities | Input | boolean | False | If the Intensities should be constrained during the fit |
OutputResultWorkspace | Output | MatrixWorkspace | Mandatory | The outputworkspace containing the results of the fit data |
OutputParameterWorkspace | Output | TableWorkspace | Mandatory | The outputworkspace containing the parameters for each fit |
OutputWorkspaceGroup | Output | WorkspaceGroup | Mandatory | The OutputWorkspace group Data, Calc and Diff, values for the fit of each spectra |
Fits an *_iqt file generated by I(Q,t) sequentially.
Example - Running IqtFitSequential on an reduced workspace.
#Load in iqt data
input_ws = Load(Filename='iris26176_graphite002_iqt.nxs')
function = r'name=LinearBackground,A0=0.027668,A1=0,ties=(A1=0);name=UserFunction,Formula=Intensity*exp(-(x/Tau)^Beta),Intensity=0.972332,Tau=0.0247558,Beta=1;ties=(f1.Intensity=1-f0.A0)'
#run IqtFitSequential
result, params, fit_group = IqtFitSequential(InputWorkspace=input_ws, Function=function, FitType='1S_s', StartX=0, EndX=0.2, SpecMin=0, SpecMax=16)
Categories: Algorithms | Workflow\MIDAS
Python: IqtFitSequential.py