PlotPeakByLogValue v1¶

Summary¶

Fits a number of spectra with the same function.

Properties¶

Description¶

This algorithm fits a series of spectra with the same function. Each spectrum is fit independently and the result is a table of fitting parameters unique for each spectrum. The sources for the spectra are defined in the Input property. The Input property expects a list of spectra identifiers separated by semicolons (;). An identifier is itself a comma-separated list of values. The first value is the name of the source. It can be either a workspace name or a name of a file (RAW or Nexus). If it is a name of a WorkspaceGroup all its members will be included in the fit. The second value selects a spectrum within the workspace or file. It is an integer number with a prefix defining the meaning of the number: “sp” for a spectrum number, “i” for a workspace index, or “v” for a range of values on the numeric axis associated with the workspace index. For example, sp12, i125, v0.5:2.3. If the data source is a file only the spectrum number option is accepted. The third value of the spectrum identifier is optional period number. It is used if the input file contains multiperiod data. In case of workspaces this third parameter is ignored. This are examples of Input property

Internally PlotPeakByLogValue uses Fit v1 algorithm to perform fitting and the following properties have the same meaning as in Fit v1: StartX, EndX, Minimizer, CostFunction. Property FitType defines the way of setting initial values. If it is set to “Sequential” every next fit starts with parameters returned by the previous fit. If set to “Individual” each fit starts with the same initial values defined in the Function property.

The Function property can be a single domain function in which case this function is used to fit each of the inputs, or it can be a multi-domain function. In the latter case the number of domains must equal the number of inputs and each input is fitted to the equivalent function from the multi-domain function.

LogValue property specifies a log value to be included into the output. If this property is empty the values of axis 1 will be used instead. Setting this property to “SourceName” makes the first column of the output table contain the names of the data sources (files or workspaces).

Output workspace format¶

PlotPeakByLogValue_Output.png

In this example a group of three Matrix workspaces were fitted with a Gaussian on a linear background.

The output workspace is a table in which rows correspond to the spectra in the order they (spectra) appear in the Input property. The first column of the table has the log values. It is followed by pairs of columns with parameter values and fitting errors. If a parameter was fixed or tied the error will be zero. If the function being fitted is a Peak function, a column for its integrated intensity is added after its parameter columns. Here is an example of the output workspace:

Usage¶

Example - fitting a single spectrum of in a workspace:

ws = CreateSampleWorkspace()
function = "name=Gaussian,Height=10.0041,PeakCentre=10098.6,Sigma=48.8581;name=FlatBackground,A0=0.3"
peaks = PlotPeakByLogValue(ws, function, Spectrum=1)

Example - sequentially fitting a workspace:

import numpy as np

ws = CreateSampleWorkspace()
function = "name=Gaussian,Height=10.0041,PeakCentre=10098.6,Sigma=48.8581;name=FlatBackground,A0=0.3"

#create string of workspaces to fit (ws,i0; ws,i1, ws,i2 ...)
workspaces = [ws.name() + ',i%d' % i for i in range(ws.getNumberHistograms())]
workspaces = ';'.join(workspaces)

peaks = PlotPeakByLogValue(workspaces, function, Spectrum=1)

#get peak centres for comparison
peak_centres = peaks.column('f0.PeakCentre')
ref = np.empty(len(peak_centres))
ref.fill(10098.6)

print(np.allclose(ref, peak_centres, 1e-3))

Output:

True

Example - sequentially fitting a workspace with Output Status:

import numpy as np

ws = CreateSampleWorkspace()
function = "name=Gaussian,Height=10.0041,PeakCentre=10098.6,Sigma=48.8581;name=FlatBackground,A0=0.3"

#create string of workspaces to fit (ws,i0; ws,i1, ws,i2 ...)
workspaces = [ws.name() + ',i%d' % i for i in range(ws.getNumberHistograms())]
workspaces = ';'.join(workspaces)

peaks, status, chi2 = PlotPeakByLogValue(workspaces, function, Spectrum=1, OutputFitStatus=True)

# Print status of first 10 fits
print("Fit status = {}".format(status[0:10]))
print("Fit chi2 = {}".format(chi2[0:10]))

Output:

Fit status = ['success', 'success', 'success', 'success', 'success', 'success', 'success', 'success', 'success', 'success']
Fit chi2 = [  5.09648779e-08   6.89426130e-09   9.33124574e-10   1.26539259e-10
   1.73025195e-11   2.45555803e-12   4.06465408e-13   1.04496124e-13
   4.79987355e-14   3.01813222e-14]

Example - Fitting multiDomain function:

ws = CreateSampleWorkspace()
function = mantid.api.FunctionFactory.createInitializedMultiDomainFunction("name=Gaussian,Height=10.0041,PeakCentre=10098.6,Sigma=48.8581;name=FlatBackground,A0=0.3", 200)

#create string of workspaces to fit (ws,i0; ws,i1, ws,i2 ...)
workspaces = [ws.name() + ',i%d' % i for i in range(ws.getNumberHistograms())]
workspaces = ';'.join(workspaces)

peaks, status, chi2 = PlotPeakByLogValue(workspaces, function, Spectrum=1, OutputFitStatus=True)

# Print status of first 10 fits
print("Fit status = {}".format(status[0:10]))
print("Fit chi2 = {}".format(chi2[0:10]))

Output:

Fit status = ['success', 'success', 'success', 'success', 'success', 'success', 'success', 'success', 'success', 'success']
Fit chi2 = [  5.09648779e-08   6.89426130e-09   9.33124574e-10   1.26539259e-10
   1.73025195e-11   2.45555803e-12   4.06465408e-13   1.04496124e-13
   4.79987355e-14   3.01813222e-14]

Example - :

ws = CreateSampleWorkspace(BankPixelWidth=3)
function = "name=Gaussian,Height=10.0041,PeakCentre=10098.6,Sigma=48.8581;name=FlatBackground,A0=0.3"

#create string of workspaces to fit (ws,i0; ws,i1, ws,i2 ...)
workspaces = [ws.name() + ',i%d' % i for i in range(3)]
workspaces = ';'.join(workspaces)

exclude_range = ["5000,7500", "7500,12500", "0.0,0.0"]

peaks, status, chi2 = PlotPeakByLogValue(workspaces, function, Spectrum=1, OutputFitStatus=True, ExcludeMultiple=exclude_range)

# Print status of first 10 fits
print("Fit status = {}".format(status[0:3]))
print("Fit chi2 = [{0:.4e}, {1:.4e}, {2:.4e}]".format(chi2[0], chi2[1], chi2[2]))

Output:

Fit status = ['success', 'success', 'success']
Fit chi2 = [5.0965e-08, 0.0000e+00, 6.8943e-09]

Categories: AlgorithmIndex | Optimization

Source¶

C++ header: PlotPeakByLogValue.h (last modified: 2021-05-26)

C++ source: PlotPeakByLogValue.cpp (last modified: 2021-05-26)