Add option to correct for attenuation post integration in ISIS single-crystal reduction classes

Description of work

Adds a method to apply attenuation correction post-integration - this is how SXD like to apply the correction, in addition it is quicker than applying the correction to every bin in the raw workspace.

Fixes #37235

To test:

(1) Run through script in docs

from mantid.simpleapi import *
from os import path
from Diffraction.single_crystal.base_sx import PEAK_TYPE, INTEGRATION_TYPE
from Diffraction.single_crystal.sxd import SXD

# Setup SXD
###########

sxd = SXD(vanadium_runno=32857, empty_runno=32856, detcal_path=detcal_path)
sxd.set_sample(Geometry={'Shape': 'CSG', 'Value': sxd.sphere_shape},
               Material={'ChemicalFormula': 'Na Cl', 'SampleNumberDensity': 0.0223})
sxd.set_goniometer_axes([0,1,0,1])  # ccw rotation around vertical

# load and normalise data
#########################

runs = range(32863,32865)
sxd.process_vanadium()
sxd.process_data(runs, "wccr") # wccr is the goniometer motor log name - one arg for each axis added
# if there was no log value then the angles have to be set with a sequence e.g.
# sxd.process_data(runs, [0,45])

# Find peaks and optimise UBs
##############################

for run in runs:
    ws = sxd.get_ws(run)
    peaks = sxd.find_sx_peaks(ws, nstd=8)
    sxd.remove_peaks_on_detector_edge(peaks, 2)
    sxd.set_peaks(run, peaks)
# find UB with consistent indexing across runs
sxd.find_ub_using_lattice_params(global_B=True, tol=0.15,
                                 a=5.6402, b=5.6402, c=5.6402,
                                 alpha=90, beta=90, gamma=90)
sxd.calibrate_sample_pos(tol=0.15)  # calibrates each run independently

# Integrate and save
####################

# input arguments for skew integration
save_dir = "/babylon/Public/UserName"
skew_args= {'UseNearestPeak': True, 'IntegrateIfOnEdge': False,
            'LorentzCorrection': True,
            'NVacanciesMax': 2, 'NPixPerVacancyMin': 2, 'NTOFBinsMin': 2,
            'UpdatePeakPosition': True, 'OptimiseMask': True,
            'GetTOFWindowFromBackToBackParams': False,
            'BackScatteringTOFResolution': 0.06, 'ThetaWidth': 1.5,
            'ScaleThetaWidthByWavelength': True,
            'OptimiseXWindowSize': True, 'ThresholdIoverSigma': 15}

# integrate and save each run
peak_type = PEAK_TYPE.FOUND
integration_type = INTEGRATION_TYPE.SKEW
for run in runs:
    skew_args = {**skew_args, 'OutputFile': path.join(save_dir, f"{run}_{peak_type.value}_int.pdf")}
    sxd.integrate_data(integration_type, peak_type, run=run, **skew_args)
    sxd.calc_absorption_weighted_path_lengths(peak_type, integration_type, run=run, ApplyCorrection=True)
    sxd.save_peak_table(run, peak_type, integration_type, save_dir, save_format='SHELX')

# save combined table
sxd.save_all_peaks(peak_type, integration_type, save_dir=save_dir, save_format=fmt)

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mantidproject / mantid