EnggFitPeaks v1¶

Summary¶

The algorithm fits an expected diffraction pattern to a spectrum from a workspace by fitting one peak at a time (single peak fits).

Properties¶

Description¶

Fits a series of single peaks to a spectrum with an expected diffraction pattern. The pattern is specified by providing a list of dSpacing values where Bragg peaks are expected. These expected values are used as initial peak positions when fitting the peaks. The expected dSpacing values can be given as an input string or in a file with values separated by commas.

The peaks are fitted one at a time. The dSpacing values given in the property ExpectedPeaks are then converted to time-of-flight (TOF). After the conversion of units, the algorithm tries to fit (in time-of-flight) a peak in the neighborhood of every expected peak using a peak shape or function. The conversion is done as in the Mantid algorithm AlignDetectors (following GSAS equations) if the workspace is focused (single spectrum) and has a log entry named “difc”, where the GSAS DIFC parameter is expected. Otherwise the conversion of units is done as in the Mantid ConvertUnits. See also EnggFitDIFCFromPeaks.

This algorithm currently fits (single) peaks of type Back2BackExponential. Other alternatives might be added as optional in the future (for example the simpler Gaussian or the more complex Bk2BkExpConvPV <func-Bk2BkExpConvPV or IkedaCarpenterPV). To produce an initial guess for the peak function parameters this algorithm uses the FindPeaks algorithm starting from the expected peaks list given in the inputs.

The algorithm produces an output table workspace with information about the peaks fitted. The table has one row per peak and several columns for the different fitted parameters (and the errors of these parameters). If a name is given in the input OutFittedPeaksTable, the table will be available in the “analysis data service” (workspaces window) with that name.

Usage¶

Example - Fitting two peaks:

# Two BackB2Back exponential peaks
peak1 = "name=BackToBackExponential,I=6000,A=1,B=0.5,X0=15000,S=250"
peak2 = "name=BackToBackExponential,I=5000,A=1,B=0.7,X0=35000,S=300"

# Create workpsace with the above peaks and a single detector pixel
ws = CreateSampleWorkspace(Function="User Defined",
                           UserDefinedFunction=peak1 + ";" + peak2,
                           NumBanks=1,
                           BankPixelWidth=1,
                           XMin=6000,
                           XMax=45000,
                           BinWidth=10)

# Update instrument geometry to something that would allow converting to some sane dSpacing values
EditInstrumentGeometry(Workspace = ws, L2 = [1.5], Polar = [90], PrimaryFlightPath = 50)

# Run the algorithm. Defaults are shown below. Files entered must be in .csv format and if both ExpectedPeaks and ExpectedPeaksFromFile are entered, the latter will be used.

peaks_tbl = EnggFitPeaks(ws, 0, [0.8, 1.9])


# Print the results
print "Number of peaks fitted: {0}".format(peaks_tbl.rowCount())
print "First peak expected (dSpacing): {0}".format(peaks_tbl.column('dSpacing')[0])
print "First fitted peak center (ToF): {0:.1f}".format(peaks_tbl.column('X0')[0])
print "Second peak expected (dSpacing): {0}".format(peaks_tbl.column('dSpacing')[1])
print "Second fitted peak center (ToF): {0:.0f}".format(round(peaks_tbl.column('X0')[1],-1))

Output:

Number of peaks fitted: 2
First peak expected (dSpacing): 0.8
First fitted peak center (ToF): 15006.0
Second peak expected (dSpacing): 1.9
Second fitted peak center (ToF): 35010

Categories: Algorithms | Diffraction\Engineering | Diffraction\Fitting

Source¶

Python: EnggFitPeaks.py