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GeneratePeaks v1

Summary

Generate peaks in an output workspace according to a TableWorkspace containing a list of peak’s parameters.

See Also

FindPeaks, MatchPeaks

Properties

Name	Direction	Type	Default	Description
PeakParametersWorkspace	Input	TableWorkspace		Input TableWorkspace for peak’s parameters.
PeakType	Input	string	Mandatory	Peak function type. Allowed values: [‘AsymmetricPearsonVII’, ‘AsymmetricPearsonVII (PeakHeight, PeakCentre, Width, LeftShape, RightShape)’, ‘BackToBackExponential’, ‘BackToBackExponential (I, A, B, X0, S)’, ‘Bk2BkExpConvPV’, ‘Bk2BkExpConvPV (X0, Intensity, Alpha, Beta, Sigma2, Gamma)’, ‘DeltaFunction’, ‘DeltaFunction (Height, Centre)’, ‘ElasticDiffRotDiscreteCircle’, ‘ElasticDiffRotDiscreteCircle (Height, Centre, Radius)’, ‘ElasticDiffSphere’, ‘ElasticDiffSphere (Height, Centre, Radius)’, ‘ElasticIsoRotDiff’, ‘ElasticIsoRotDiff (Height, Centre, Radius)’, ‘ExamplePeakFunction’, ‘ExamplePeakFunction (Height, PeakCentre, Sigma)’, ‘Gaussian’, ‘Gaussian (Height, PeakCentre, Sigma)’, ‘IkedaCarpenterPV’, ‘IkedaCarpenterPV (I, Alpha0, Alpha1, Beta0, Kappa, SigmaSquared, Gamma, X0)’, ‘Lorentzian’, ‘Lorentzian (Amplitude, PeakCentre, FWHM)’, ‘PearsonIV’, ‘PearsonIV (Intensity, Centre, Sigma, Exponent, Skew)’, ‘PseudoVoigt’, ‘PseudoVoigt (Mixing, Intensity, PeakCentre, FWHM)’, ‘Voigt’, ‘Voigt (LorentzAmp, LorentzPos, LorentzFWHM, GaussianFWHM)’]
PeakParameterValues	Input	dbl list		List of peak parameter values. They must have a 1-to-1 mapping to PeakParameterNames list.
BackgroundType	Input	string	Mandatory	Type of Background. Allowed values: [‘Auto’, ‘Flat (A0)’, ‘Linear (A0, A1)’, ‘Quadratic (A0, A1, A2)’, ‘FlatLinear’, ‘Quadratic’]
BackgroundParameterValues	Input	dbl list		List of background parameter values. They must have a 1-to-1 mapping to PeakParameterNames list.
InputWorkspace	Input	MatrixWorkspace		InputWorkspace (optional) to take information for the instrument, and where to evaluate the x-axis.
WorkspaceIndex	Input	number	0	Spectrum of the peak to be generated. It is only applied to the case by input parameter values in vector format.
BinningParameters	Input	dbl list		A comma separated list of first bin boundary, width, last bin boundary. Optionally this can be followed by a comma and more widths and last boundary pairs. Negative width values indicate logarithmic binning.
NumberWidths	Input	number	2	Number of peak width to evaluate each peak for. Default=2.
OutputWorkspace	Output	MatrixWorkspace	Mandatory	Output Workspace to put the calculated data.
GenerateBackground	Input	boolean	True	Whether or not to generate the background
MaxAllowedChi2	Input	number	100	Maximum chi^2 of the peak allowed to calculate. Default 100.
IgnoreWidePeaks	Input	boolean	False	If selected, the peaks that are wider than fit window (denoted by negative chi^2) are ignored.
IsRawParameter	Input	boolean	True	Flag to show whether the parameter table contains raw parameters. In the case that parameter values are input via vector, and this flag is set to false, the default order of effective peak parameters is centre, height and width; the default order of effective background parameters is A0, A1 and A2.

Description

Generate a workspace by summing over the peak functions and optionally background functions. The peaks’ and background’ parameters are either (1) given in a TableWorkspace or (2) given by an array of doubles.

Function Parameters

There are 2 different approaches to input parameter values of peak and background function.

TableWorkspace

Peak and background parameters must have the following columns, which are case sensitive in input TableWorkspace

The definition of this table workspace is consistent with the output peak and background parameter TableWorkspace of algorithm FindPeaks.

The following table contains the effective peak and background parameters.

Column	Name	Comment
1	spectrum
2	centre
3	height
4	width	FWHM
5	backgroundintercept	A0
6	backgroundslope	A1
7	A2	A2
8	chi2

Double Array

An alternative way to input function parameters is to specify parameter values in property ‘PeakParameterValues’ and ‘BackgroundParameterValues’.

In this case, there is only one peak function that can be specified and generated.

The order of the parameters are pre-determined, which can be found in the dropdown list of ‘PeakType’ and ‘BackgroundType’. For example in ‘PeakType’, there is an item named ‘Gaussian(Height,PeakCentre, Sigma)’. Therefore, the order of parameters for Gaussian is height, peak centre and sigma. It does not matter whether ‘Gaussian’ or ‘Gaussian(Height,PeakCentre, Sigma)’ is selected.

Effective Peak and Background Parameters

GeneratePeak supports effective peak and background parameters.

For peak parameters, the effective parameters are centre, height and FWHM. This order must be followed if the parameter values are input through ‘PeakParameterValues’.

For background parameters, the effective parameters are interception, slope and A2. This order must be followed if the parameter values are input through ‘BackgroundParameterValues’.

Output

Output can be either pure peak with ‘GenerateBackground’ deselected or peak and background.

If ‘InputWorkspace’, which is optional, is not given, then a single spectrum workspace can be generatged from scratch according to property ‘BinningParameters’.

Usage

Generate peaks from a TableWorkspace

params = CreateEmptyTableWorkspace()
params.addColumn("int", "spectrum")
params.addColumn("double", "Height")
params.addColumn("double", "PeakCentre")
params.addColumn("double", "Sigma")
params.addColumn("double", "A0")
params.addColumn("double", "A1")
params.addColumn("double", "chi2")
# match array example below
params.addRow([3, 10.0, 1, 0.2, 5.0, 1.0, 0.01])
fromtable = GeneratePeaks(PeakParametersWorkspace=params, PeakType='Gaussian', BackgroundType='Linear (A0, A1)',
                          BinningParameters='0,0.01,20', NumberWidths=5)

for i in [92,93,94,95]:
    print("X = {:.6f}, Y = {:.6f}".format(fromtable.readX(0)[i], fromtable.readY(0)[i]))

Output:

X = 0.920000, Y = 15.151163
X = 0.930000, Y = 15.335881
X = 0.940000, Y = 15.499975
X = 0.950000, Y = 15.642332

Generate peaks from arrays

GeneratePeaks(PeakType='Gaussian (Height, PeakCentre, Sigma)', PeakParameterValues='10,1,0.2',
    BackgroundType='Linear (A0, A1)', BackgroundParameterValues='5,1',
    BinningParameters='0,0.01,20', NumberWidths=5, OutputWorkspace='GaussianPeak')

outws = mtd["GaussianPeak"]
for i in [92,93,94,95]:
    print("X = {:.6f}, Y = {:.6f}".format(outws.readX(0)[i], outws.readY(0)[i]))

Output:

X = 0.920000, Y = 15.151163
X = 0.930000, Y = 15.335881
X = 0.940000, Y = 15.499975
X = 0.950000, Y = 15.642332

Categories: AlgorithmIndex | Crystal\Peaks

Source

C++ header: GeneratePeaks.h

C++ source: GeneratePeaks.cpp