def create_solid_angle_corrections(self, vanadium, run_details):
"""
Creates the solid angle corrections from a vanadium run, only applicable on HRPD otherwise return None
:param vanadium: The vanadium used to create this
:param run_details: the run details of to use
"""
if not self._inst_settings.do_solid_angle:
return
solid_angle = mantid.SolidAngle(InputWorkspace=vanadium)
scale = mantid.CreateSingleValuedWorkspace(DataValue='100')
correction = mantid.Multiply(LHSWorkspace=solid_angle,
RHSWorkspace=scale)
eff = mantid.Divide(LHSWorkspace=vanadium, RHSWorkspace=correction)
eff = mantid.ConvertUnits(InputWorkspace=eff, Target='Wavelength')
eff = mantid.Integration(InputWorkspace=eff,
RangeLower='1.3999999999999999',
RangeUpper='3')
correction = mantid.Multiply(LHSWorkspace=correction, RHSWorkspace=eff)
scale = mantid.CreateSingleValuedWorkspace(DataValue='100000')
correction = mantid.Divide(LHSWorkspace=correction, RHSWorkspace=scale)
name = "sac" + common.generate_splined_name(run_details.run_number, [])
path = run_details.van_paths
mantid.SaveNexus(InputWorkspace=correction,
Filename=os.path.join(path, name))
common.remove_intermediate_workspace(solid_angle)
common.remove_intermediate_workspace(scale)
common.remove_intermediate_workspace(eff)
common.remove_intermediate_workspace(correction)
def correct_for_multiple_scattering(ws_name,first_spectrum,last_spectrum, sample_properties, transmission_guess,
multiple_scattering_order, number_of_events, g_log, masses, mean_intensity_ratios):
g_log.debug( "Evaluating the Multiple Scattering Correction.")
dens, trans = sapi.VesuvioThickness(Masses=masses, Amplitudes=mean_intensity_ratios, TransmissionGuess=transmission_guess,Thickness=0.1)
_TotScattering, _MulScattering = sapi.VesuvioCalculateMS(ws_name, NoOfMasses=len(masses), SampleDensity=dens.cell(9,1),
AtomicProperties=sample_properties, BeamRadius=2.5,
NumScatters=multiple_scattering_order,
NumEventsPerRun=int(number_of_events))
data_normalisation = sapi.Integration(ws_name)
simulation_normalisation = sapi.Integration("_TotScattering")
for workspace in ("_MulScattering","_TotScattering"):
ws = sapi.mtd[workspace]
for j in range(ws.getNumberHistograms()):
for k in range(ws.blocksize()):
ws.dataE(j)[
k] =0. # set the errors from the MonteCarlo simulation to zero - no propagation of such uncertainties
#- Use high number of events for final corrections!!!
sapi.Divide(LHSWorkspace = workspace, RHSWorkspace = simulation_normalisation, OutputWorkspace = workspace)
sapi.Multiply(LHSWorkspace = workspace, RHSWorkspace = data_normalisation, OutputWorkspace = workspace)
sapi.RenameWorkspace(InputWorkspace = workspace, OutputWorkspace = str(ws_name)+workspace)
safe_delete_ws(data_normalisation)
safe_delete_ws(simulation_normalisation)
safe_delete_ws(trans)
safe_delete_ws(dens)
return
def create_solid_angle_corrections(self, vanadium, run_details):
"""
Creates the solid angle corrections from a vanadium run, only applicable on HRPD otherwise return None
:param vanadium: The vanadium used to create this
:param run_details: the run details of to use
"""
settings = self._inst_settings
if not settings.do_solid_angle:
return
solid_angle = mantid.SolidAngle(InputWorkspace=vanadium)
solid_angle = mantid.Scale(InputWorkspace=solid_angle, Factor=100, Operation='Multiply')
eff = mantid.Divide(LHSWorkspace=vanadium, RHSWorkspace=solid_angle)
eff = mantid.ConvertUnits(InputWorkspace=eff, Target='Wavelength')
integration_range = settings.eff_integration_range
# use full range if no range is supplied
integration_range = integration_range if integration_range is not None else (None, None)
eff = mantid.Integration(InputWorkspace=eff,
RangeLower=integration_range[0],
RangeUpper=integration_range[1])
correction = mantid.Multiply(LHSWorkspace=solid_angle, RHSWorkspace=eff)
correction = mantid.Scale(InputWorkspace=correction, Factor=1e-5,
Operation='Multiply')
name = "sac" + common.generate_splined_name(run_details.run_number, [])
path = run_details.van_paths
mantid.SaveNexus(InputWorkspace=correction, Filename=os.path.join(path, name))
common.remove_intermediate_workspace(eff)
common.remove_intermediate_workspace(correction)
def _normalize_one_spectrum(single_spectrum_ws, spline, instrument):
rebinned_spline = mantid.RebinToWorkspace(
WorkspaceToRebin=spline,
WorkspaceToMatch=single_spectrum_ws,
StoreInADS=False)
divided = mantid.Divide(LHSWorkspace=single_spectrum_ws,
RHSWorkspace=rebinned_spline,
StoreInADS=False)
if instrument.get_instrument_prefix() == "GEM":
values_replaced = mantid.ReplaceSpecialValues(InputWorkspace=divided,
NaNValue=0,
StoreInADS=False)
# crop based off max between 1000 and 2000 tof as the vanadium peak on Gem will always occur here
complete = _crop_spline_to_percent_of_max(rebinned_spline,
values_replaced,
single_spectrum_ws, 1000,
2000)
else:
complete = mantid.ReplaceSpecialValues(
InputWorkspace=divided,
NaNValue=0,
OutputWorkspace=single_spectrum_ws)
if instrument.perform_abs_vanadium_norm():
vanadium_material = spline.sample().getMaterial()
v_number_density = vanadium_material.numberDensityEffective
v_cross_section = vanadium_material.totalScatterXSection()
vanadium_shape = spline.sample().getShape()
# number density in Angstroms-3, volume in m3. Don't bother with 1E30 factor because will cancel
num_v_atoms = vanadium_shape.volume() * v_number_density
sample_material = single_spectrum_ws.sample().getMaterial()
sample_number_density = sample_material.numberDensityEffective
sample_shape = spline.sample().getShape()
num_sample_atoms = sample_shape.volume() * sample_number_density
abs_norm_factor = v_cross_section * num_v_atoms / \
(num_sample_atoms * 4 * math.pi)
logger.notice(
"Performing absolute normalisation, multiplying by factor=" +
str(abs_norm_factor))
# avoid "Variable invalidated, data has been deleted" error when debugging
output_ws_name = single_spectrum_ws.name()
abs_norm_factor_ws = mantid.CreateSingleValuedWorkspace(
DataValue=abs_norm_factor, OutputWorkspace="__abs_norm_factor_ws")
complete = mantid.Multiply(LHSWorkspace=complete,
RHSWorkspace=abs_norm_factor_ws,
OutputWorkspace=output_ws_name)
return complete
def _correct_sample_can(self):
"""
Correct for sample and container.
"""
logger.information('Correcting sample and container')
corrected_can_ws = '__corrected_can'
factor_types = ['_ass']
if self._use_can:
factor_types.extend(['_acc', '_acsc', '_assc'])
corr_unit = s_api.mtd[self._corrections +
'_ass'].getAxis(0).getUnit().unitID()
for f_type in factor_types:
self._convert_units_wavelength(corr_unit,
self._corrections + f_type,
self._corrections + f_type,
"Wavelength")
if self._rebin_container_ws:
s_api.RebinToWorkspace(
WorkspaceToRebin=self._scaled_container_wavelength,
WorkspaceToMatch=self._corrections + '_acc',
OutputWorkspace=self._scaled_container_wavelength)
# Acc
s_api.Divide(LHSWorkspace=self._scaled_container_wavelength,
RHSWorkspace=self._corrections + '_acc',
OutputWorkspace=corrected_can_ws)
# Acsc
s_api.Multiply(LHSWorkspace=corrected_can_ws,
RHSWorkspace=self._corrections + '_acsc',
OutputWorkspace=corrected_can_ws)
s_api.Minus(LHSWorkspace=self._sample_ws_wavelength,
RHSWorkspace=corrected_can_ws,
OutputWorkspace=self._output_ws_name)
# Assc
s_api.Divide(LHSWorkspace=self._output_ws_name,
RHSWorkspace=self._corrections + '_assc',
OutputWorkspace=self._output_ws_name)
for f_type in factor_types:
self._convert_units_wavelength(corr_unit,
self._corrections + f_type,
self._corrections + f_type,
corr_unit)
s_api.DeleteWorkspace(corrected_can_ws)
def calculate(self, reducer, wave_wksps=[]):
"""
Multiplies all the wavelength scalings into one workspace and all the detector
dependent scalings into another workspace that can be used by ConvertToQ. It is important
that the wavelength correction workspaces have a know distribution/non-distribution state
@param reducer: settings used for this reduction
@param wave_wksps: additional wavelength dependent correction workspaces to include
"""
for step in self._wave_steps:
if step.output_wksp:
wave_wksps.append(step.output_wksp)
wave_adj = None
for wksp in wave_wksps:
# before the workspaces can be combined they all need to match
api.RebinToWorkspace(WorkspaceToRebin=wksp,
WorkspaceToMatch=reducer.output_wksp,
OutputWorkspace=self.TMP_WORKSPACE_NAME)
if not wave_adj:
# first time around this loop
wave_adj = self.WAVE_CORR_NAME
api.RenameWorkspace(InputWorkspace=self.TMP_WORKSPACE_NAME,
OutputWorkspace=wave_adj)
else:
api.Multiply(LHSWorkspace=self.TMP_WORKSPACE_NAME,
RHSWorkspace=wave_adj,
OutputWorkspace=wave_adj)
# read pixel correction file
# note the python code below is an attempt to emulate function overloading
# If a derived class overwrite self._load and self._load_params then
# a custom specific loading can be achieved
pixel_adj = ''
if self._pixel_file:
pixel_adj = self.PIXEL_CORR_NAME
load_com = self._load + '(Filename="' + self._pixel_file + '",OutputWorkspace="' + pixel_adj + '"'
if self._load_params:
load_com += ',' + self._load_params
load_com += ')'
eval(load_com)
if AnalysisDataService.doesExist(self.TMP_WORKSPACE_NAME):
AnalysisDataService.remove(self.TMP_WORKSPACE_NAME)
return wave_adj, pixel_adj