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ExtractQENSMembers v1¶

Summary ¶

Extracts the fit members from a QENS fit

Properties ¶

Name	Direction	Type	Default	Description
InputWorkspace	Input	MatrixWorkspace		The input workspace used in the fit. Ignored if ‘InputWorkspaces’ property is provided.
InputWorkspaces	Input	str list		List of the workspaces used in the fit.
ResultWorkspace	Input	WorkspaceGroup	Mandatory	The result group workspace produced in a QENS fit.
RenameConvolvedMembers	Input	boolean	False	If true, renames the n-th ‘Convolution’ member, to the n-th supplied name in the ConvolvedMembers property.
ConvolvedMembers	Input	str list		A list of the names of the members which were convolved before being output by the fit routine. These must be provided in the same order as originally provided to the fit.
OutputWorkspace	Output	WorkspaceGroup	Mandatory	The output workspace group, containing the fit members.

Description ¶

Extracts the fit members from a QENS fit and stores each of them in a group workspace.

Usage ¶

Example

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

# Set up fit 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
output_ws_name = "irs26176_graphite002_conv_1LFixF_s0_to_9"

# Run ConvolutionFitSequential algorithm
ConvolutionFitSequential(InputWorkspace=sample, Function=function,
                         PassWSIndexToFunction=True, StartX=startX, EndX=endX,
                         SpecMin=specMin, SpecMax=specMax, OutputCompositeMembers=convolve, ConvolveMembers=convolve,
                         Minimizer=minimizer, MaxIterations=maxIt,
                         OutputWorkspace=output_ws_name)

# Extract members from the output of the ConvolutionFitSequential algorithm
members_ws = ExtractQENSMembers(InputWorkspace=sample, ResultWorkspace=output_ws_name+"_Workspaces",
                                RenameConvolvedMembers=True, ConvolvedMembers=["Lorentzian"],
                                OutputWorkspace=output_ws_name+"_Members")

for member_ws in members_ws:
    print(member_ws.getName())

Output:

irs26176_graphite002_conv_1LFixF_s0_to_9_Members_Data
irs26176_graphite002_conv_1LFixF_s0_to_9_Members_Calc
irs26176_graphite002_conv_1LFixF_s0_to_9_Members_Diff
irs26176_graphite002_conv_1LFixF_s0_to_9_Members_LinearBackground
irs26176_graphite002_conv_1LFixF_s0_to_9_Members_Lorentzian

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

# Set up fit 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
output_ws_name = "irs26176_graphite002_conv_1LFixF_s0_to_9"

# Run ConvolutionFitSequential algorithm with ExtractMembers property
ConvolutionFitSequential(InputWorkspace=sample, Function=function, PassWSIndexToFunction=True,
                         StartX=startX, EndX=endX, SpecMin=specMin, SpecMax=specMax, OutputCompositeMembers=convolve,
                         ConvolveMembers=convolve, Minimizer=minimizer, MaxIterations=maxIt,
                         ExtractMembers=True, OutputWorkspace=output_ws_name)

members_ws = mtd[output_ws_name + "_Members"]

for member_ws in members_ws:
    print(member_ws.getName())

irs26176_graphite002_conv_1LFixF_s0_to_9_Members_Data
irs26176_graphite002_conv_1LFixF_s0_to_9_Members_Calc
irs26176_graphite002_conv_1LFixF_s0_to_9_Members_Diff
irs26176_graphite002_conv_1LFixF_s0_to_9_Members_LinearBackground
irs26176_graphite002_conv_1LFixF_s0_to_9_Members_Lorentzian

Categories: AlgorithmIndex | Workflow\MIDAS