ConvolutionFitSequential dialog.
Table of Contents
| Name | Direction | Type | Default | Description |
|---|---|---|---|---|
| InputWorkspace | Input | MatrixWorkspace | The input workspace for the fit. This property will be ignored if ‘Input’ is provided. | |
| SpecMin | Input | number | 0 | The first spectrum to be used in the fit. Spectra values can not be negative. This property will be ignored if ‘Input’ is provided. |
| SpecMax | Input | number | 0 | The final spectrum to be used in the fit. Spectra values can not be negative. This property will be ignored if ‘Input’ is provided. |
| Input | Input | string | A list of sources of data to fit. Sources can be either workspace names or file names followed optionally by a list of spectra/workspace-indices or values using the notation described in the description section of the help page. | |
| ResultXAxisUnit | Input | string | MomentumTransfer | The unit to assign to the X Axis of the result workspace, defaults to MomentumTransfer. Allowed values: [‘Degrees’, ‘DeltaE’, ‘DeltaE_inFrequency’, ‘DeltaE_inWavenumber’, ‘dSpacing’, ‘dSpacingPerpendicular’, ‘Empty’, ‘Energy’, ‘Energy_inWavenumber’, ‘Label’, ‘Momentum’, ‘MomentumTransfer’, ‘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 | |
| Function | InOut | Function | Mandatory | The fitting function, common for all workspaces in the input. |
| LogName | Input | string | axis-1 | Name of the log value to plot the parameters against. Default: use spectra numbers. |
| StartX | Input | number | Optional | A value of x in, or on the low x boundary of, the first bin to include in the fit (default lowest value of x) |
| EndX | Input | number | Optional | A value in, or on the high x boundary of, the last bin the fitting range (default the highest value of x) |
| PassWSIndexToFunction | Input | boolean | False | For each spectrum in Input pass its workspace index to all functions thathave attribute WorkspaceIndex. |
| Minimizer | Input | string | Levenberg-Marquardt | Minimizer to use for fitting. Minimizers available are ‘Levenberg-Marquardt’, ‘Simplex’, ‘FABADA’, ‘Conjugate gradient (Fletcher-Reeves imp.)’, ‘Conjugate gradient (Polak-Ribiere imp.)’ and ‘BFGS’ |
| CostFunction | InOut | string | Least squares | Cost functions to use for fitting. Cost functions available are ‘Least squares’ and ‘Ignore positive peaks’. Allowed values: [‘Least squares’, ‘Poisson’, ‘Rwp’, ‘Unweighted least squares’] |
| MaxIterations | Input | number | 500 | Stop after this number of iterations if a good fit is not found |
| 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. |
| 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 and OutputCompositeMembers is true members of any Convolution are output convolved with corresponding resolution |
| EvaluationType | Input | string | CentrePoint | The way the function is evaluated: CentrePoint or Histogram. Allowed values: [‘CentrePoint’, ‘Histogram’] |
| Exclude | Input | dbl list | A list of pairs of real numbers, defining the regions to exclude from the fit. | |
| IgnoreInvalidData | Input | boolean | False | Flag to ignore infinities, NaNs and data with zero errors. |
Performs a sequential fit involving a convolution with a defined resolution. This algorithm is a special-case of QENSFitSequential, which calculates the elastic incoherent scattering factor when a delta function is provided in the fitting model.
Example - ConvolutionFitSequential
from __future__ import print_function
# Load sample and resolution files
sample = Load('irs26176_graphite002_red.nxs')
resolution = Load('irs26173_graphite002_red.nxs')
# Set up algorithm parameters
function = """name=LinearBackground,A0=0,A1=0,ties=(A0=0.000000,A1=0.0);
(composite=Convolution,FixResolution=true,NumDeriv=true;
name=Resolution,Workspace=resolution,WorkspaceIndex=0;
name=Lorentzian,Amplitude=1,PeakCentre=0,FWHM=0.0175)"""
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
result_ws, _, _ = ConvolutionFitSequential(InputWorkspace=sample,
Function=function,
PassWSIndexToFunction=True,
StartX=startX, EndX=endX,
SpecMin=specMin, SpecMax=specMax,
ConvolveMembers=convolve,
Minimizer=minimizer, MaxIterations=maxIt)
result_ws = result_ws[0]
print("Result has %i Spectra" %result_ws.getNumberHistograms())
print("Amplitude 0: %.3f" %(result_ws.readY(0)[0]))
print("Amplitude 1: %.3f" %(result_ws.readY(0)[1]))
print("Amplitude 2: %.3f" %(result_ws.readY(0)[2]))
print("X axis at 0: %.5f" %(result_ws.readX(0)[0]))
print("X axis at 1: %.5f" %(result_ws.readX(0)[1]))
print("X axis at 2: %.5f" %(result_ws.readX(0)[2]))
print("Amplitude Err 0: %.5f" %(result_ws.readE(0)[0]))
print("Amplitude Err 1: %.5f" %(result_ws.readE(0)[1]))
print("Amplitude Err 2: %.5f" %(result_ws.readE(0)[2]))
Output:
Result has 3 Spectra
Amplitude 0: 4.314
Amplitude 1: 4.213
Amplitude 2: 4.555
X axis at 0: 0.52531
X axis at 1: 0.72917
X axis at 2: 0.92340
Amplitude Err 0: 0.00460
Amplitude Err 1: 0.00468
Amplitude Err 2: 0.00577
Categories: AlgorithmIndex | Workflow\MIDAS
C++ source: ConvolutionFit.cpp (last modified: 2019-03-27)
C++ header: ConvolutionFit.h (last modified: 2018-10-05)