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ConvolutionFitSimultaneous v1

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Summary

Performs a simultaneous fit across convolution workspaces

See Also

QENSFitSimultaneous

Properties

Name	Direction	Type	Default	Description
Function	InOut	Function	Mandatory	Parameters defining the fitting function and its initial values
InputWorkspace	Input	Workspace	Mandatory	Name of the input Workspace
IgnoreInvalidData	Input	boolean	False	Flag to ignore infinities, NaNs and data with zero errors.
DomainType	Input	string	Simple	The type of function domain to use: Simple, Sequential, or Parallel. Allowed values: [‘Simple’, ‘Sequential’, ‘Parallel’]
EvaluationType	Input	string	CentrePoint	The way the function is evaluated on histogram data sets. If value is “CentrePoint” then function is evaluated at centre of each bin. If it is “Histogram” then function is integrated within the bin and the integrals returned. Allowed values: [‘CentrePoint’, ‘Histogram’]
StepSizeMethod	Input	string	Default	The way the step size is calculated for numerical derivatives. See the section about step sizes in the Fit algorithm documentation to understand the difference between “Default” and “Sqrt epsilon”. Allowed values: [‘Default’, ‘Sqrt epsilon’]
PeakRadius	Input	number	0	A value of the peak radius the peak functions should use. A peak radius defines an interval on the x axis around the centre of the peak where its values are calculated. Values outside the interval are not calculated and assumed zeros.Numerically the radius is a whole number of peak widths (FWHM) that fit into the interval on each side from the centre. The default value of 0 means the whole x axis.
Ties	Input	string		Math expressions defining ties between parameters of the fitting function.
Constraints	Input	string		List of constraints
MaxIterations	Input	number	500	Stop after this number of iterations if a good fit is not found
Minimizer	Input	string	Levenberg-Marquardt	Minimizer to use for fitting. Allowed values: [‘BFGS’, ‘Conjugate gradient (Fletcher-Reeves imp.)’, ‘Conjugate gradient (Polak-Ribiere imp.)’, ‘Damped GaussNewton’, ‘FABADA’, ‘Levenberg-Marquardt’, ‘Levenberg-MarquardtMD’, ‘Simplex’, ‘SteepestDescent’, ‘Trust Region’]
CalcErrors	Input	boolean	False	Set to true to calcuate errors when output isn’t created (default is false).
ExtractMembers	Input	boolean	False	If true, then each member of the fit will be extracted, into their own workspace. These workspaces will have a histogram for each spectrum (Q-value) and will be grouped.
ConvolveMembers	Input	boolean	False	If true members of any Convolution are output convolved with corresponding resolution
OutputCompositeMembers	Input	boolean	False	If true and CreateOutput is true then the value of each member of a Composite Function is also output.
ResultXAxisUnit	Input	string	MomentumTransfer	The unit to assign to the X Axis of the result workspace, defaults to MomentumTransfer. Allowed values: [‘AtomicDistance’, ‘Degrees’, ‘DeltaE’, ‘DeltaE_inFrequency’, ‘DeltaE_inWavenumber’, ‘dSpacing’, ‘dSpacingPerpendicular’, ‘Empty’, ‘Energy’, ‘Energy_inWavenumber’, ‘Label’, ‘Momentum’, ‘MomentumTransfer’, ‘Phi’, ‘QSquared’, ‘SpinEchoLength’, ‘SpinEchoTime’, ‘Temperature’, ‘Time’, ‘TOF’, ‘Wavelength’, ‘’]
OutputWorkspace	Output	WorkspaceGroup	Mandatory	The output result workspace(s)
OutputParameterWorkspace	Output	TableWorkspace		The output parameter workspace
OutputWorkspaceGroup	Output	WorkspaceGroup		The output group workspace
OutputFitStatus	Input	boolean	True	Flag to output fit status information, which consists of the fit OutputStatus and the OutputChiSquared
CostFunction	InOut	string	Least squares	The cost function to be used for the fit, default is Least squares. Allowed values: [‘Least squares’, ‘Poisson’, ‘Rwp’, ‘Unweighted least squares’]

Description

Performs a simultaneous fit involving a convolution with a defined resolution. This algorithm is a special-case of QENSFitSimultaneous, which calculates the elastic incoherent scattering factor when a delta function is provided in the fitting model.

Workflow

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Usage

Example - ConvolutionFitSimultaneous

# Load sample and resolution files
sample = Load('irs26176_graphite002_red.nxs')
resolution = Load('irs26173_graphite002_red.nxs')

# Set up algorithm parameters
background = LinearBackground(A0=0, A1=0)
peak_function = Lorentzian(Amplitude=1, PeakCentre=0, FWHM=0.0175)
resolution_function = Resolution(Workspace=resolution.getName(), WorkspaceIndex=0)
model = CompositeFunction(background, Convolution(peak_function, resolution_function))
multi_function = MultiDomainFunction(model, model)
startX = -0.547608
endX = 0.543217
specMin = 0
specMax = sample.getNumberHistograms() - 1
convolve = True  # Convolve the fitted model components with the resolution
minimizer = "Levenberg-Marquardt"
maxIt = 500

# Run algorithm (fit spectra 1 and 2)
result, params, fit_group, status, chi2 = ConvolutionFitSimultaneous(Function=multi_function,
                                                                     InputWorkspace=sample,
                                                                     WorkspaceIndex=0,
                                                                     InputWorkspace_1=sample,
                                                                     WorkspaceIndex_1=1,
                                                                     StartX=startX, EndX=endX,
                                                                     StartX_1=startX, EndX_1=endX,
                                                                     ConvolveMembers=convolve,
                                                                     Minimizer=minimizer,
                                                                     MaxIterations=maxIt,
                                                                     OutputWorkspace="ConvFitResult")

Categories: AlgorithmIndex | Workflow\MIDAS

Source

C++ header: ConvolutionFit.h

C++ source: ConvolutionFit.cpp