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ConvolutionFitSimultaneous v1

../_images/ConvolutionFitSimultaneous-v1_dlg.png

ConvolutionFitSimultaneous dialog.

Summary

Performs a simultaneous fit across convolution workspaces

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’]
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.

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 (last modified: 2020-03-20)

C++ source: ConvolutionFit.cpp (last modified: 2020-04-07)