Use mantid fitting in IntegratePeaks1DProfile (instead of scipy as was too slow)

[RichardWaiteSTFC]

Description of work

Use mantid fitting in IntegratePeaks1DProfile for speed. Previously scipy fitting used, but the only minimizer that worked robustly was a simplex/Nelder-Mead method which was very slow (slow to converge, lots of function evaluations per iteration). The original issue was to add mantid fitting as an option, but the mantid fitting with the relatively new option StepSizeMethod="Sqrt epsilon" seems more robust than scipy fitting and orders of magnitude quicker. So in order to reduce duplication the scipy fitting has been completely replaced by mantid Fit algorithm.

In order to do this have also exposed a couple of IPEakFunction methods to python

• getWidthParameterName
• getCentreParameterName

Which are used to construct function parameter constraints.

Fixes #37526

Report to: Nick Funnell (LMX/PEARL)

To test:

(1) Run this script

# import mantid algorithms, numpy and matplotlib
from mantid.simpleapi import *
import matplotlib.pyplot as plt
import numpy as np

ws  =Load(Filename=r'C:/Users/xhg73778/Desktop/SXD34361.nxs', OutputWorkspace='SXD34361')
peaks = FindSXPeaksConvolve(InputWorkspace=ws, PeakFindingStrategy="IOverSigma", NCols=7, NRows=7, NFWHM=6, ThresholdIoverSigma=5)

profile_kwargs = {"GetNBinsFromBackToBackParams": True, "NFWHM": 6,
                "CostFunction": "Poisson", "FixPeakParameters": "A",
                "FractionalChangeDSpacing": 0.05,
                "IntegrateIfOnEdge": False,
                "LorentzCorrection": True,
                "IOverSigmaThreshold": 2.5,
                'BackgroundFunction': 'FlatBackground',         
                "OutputFile": "SXD34361_profile_testpdf"}

peaks_int = IntegratePeaks1DProfile(ws, peaks_small, **profile_kwargs)

(2) Check the pdf file, peaks should be integrated well, with peak shape in TOF spectrum a good fit and most intense pixels included in peak mask

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