def performOperation(self):
lhs_valid, rhs_valid, err_msg = self.validateInputs()
if err_msg != str():
return lhs_valid, rhs_valid, err_msg
lhs_ws, rhs_ws = self._scale_input_workspaces()
try:
if self._operation == '+':
if self._md_lhs or self._md_rhs:
PlusMD(LHSWorkspace=lhs_ws,
RHSWorkspace=rhs_ws,
OutputWorkspace=self._output_ws)
else:
Plus(LHSWorkspace=lhs_ws,
RHSWorkspace=rhs_ws,
OutputWorkspace=self._output_ws)
elif self._operation == '-':
if self._md_lhs or self._md_rhs:
MinusMD(LHSWorkspace=lhs_ws,
RHSWorkspace=rhs_ws,
OutputWorkspace=self._output_ws)
else:
Minus(LHSWorkspace=lhs_ws,
RHSWorkspace=rhs_ws,
OutputWorkspace=self._output_ws)
elif self._operation == '*':
if self._md_lhs or self._md_rhs:
MultiplyMD(LHSWorkspace=lhs_ws,
RHSWorkspace=rhs_ws,
OutputWorkspace=self._output_ws)
else:
Multiply(LHSWorkspace=lhs_ws,
RHSWorkspace=rhs_ws,
OutputWorkspace=self._output_ws)
elif self._operation == 'WM':
if self._md_lhs or self._md_rhs:
WeightedMeanMD(LHSWorkspace=lhs_ws,
RHSWorkspace=rhs_ws,
OutputWorkspace=self._output_ws)
else:
WeightedMean(InputWorkspace1=lhs_ws,
InputWorkspace2=rhs_ws,
OutputWorkspace=self._output_ws)
else:
if self._md_lhs or self._md_rhs:
DivideMD(LHSWorkspace=lhs_ws,
RHSWorkspace=rhs_ws,
OutputWorkspace=self._output_ws)
else:
Divide(LHSWorkspace=lhs_ws,
RHSWorkspace=rhs_ws,
OutputWorkspace=self._output_ws)
except (RuntimeError, ValueError) as err:
return False, False, str(err)
else:
self._regularize_output_names(self._output_ws)
finally:
DeleteWorkspaces(WorkspaceList=[lhs_ws, rhs_ws])
return True, True, ""
def _scale_md(self, ws_name, scale):
scale_ws = 'scale_ws'
CreateSingleValuedWorkspace(DataValue=scale, OutputWorkspace=scale_ws)
if isinstance(mtd[ws_name], WorkspaceGroup):
ws_name = self._scale_md_group(ws_name, scale_ws)
else:
MultiplyMD(LHSWorkspace=ws_name,
RHSWorkspace=scale_ws,
OutputWorkspace=ws_name)
DeleteWorkspace(Workspace=scale_ws)
def _determine_single_crystal_diffraction(self):
"""
All work related to the determination of the diffraction pattern
"""
a, b, c = self.getProperty('LatticeSizes').value
alpha, beta, gamma = self.getProperty('LatticeAngles').value
u = self.getProperty('VectorU').value
v = self.getProperty('VectorV').value
uproj = self.getProperty('Uproj').value
vproj = self.getProperty('Vproj').value
wproj = self.getProperty('Wproj').value
n_bins = self.getProperty('NBins').value
self._n_bins = (n_bins, n_bins, 1)
axis0 = '{},0,1,0,1'.format(self.getProperty('PsiAngleLog').value)
axis1 = '{},0,1,0,1'.format(self.getProperty('PsiOffset').value)
# Options for SetUB independent of run
ub_args = dict(a=a,
b=b,
c=c,
alpha=alpha,
beta=beta,
gamma=gamma,
u=u,
v=v)
min_values = None
# Options for algorithm ConvertToMD independent of run
convert_to_md_kwargs = dict(QDimensions='Q3D',
dEAnalysisMode='Elastic',
Q3DFrames='HKL',
QConversionScales='HKL',
Uproj=uproj,
Vproj=vproj,
Wproj=wproj)
md_norm_scd_kwargs = None # Options for algorithm MDNormSCD
# Find solid angle and flux
if self._vanadium_files:
kwargs = dict(Filename='+'.join(self._vanadium_files),
MaskFile=self.getProperty("MaskFile").value,
MomentumMin=self._momentum_range[0],
MomentumMax=self._momentum_range[1])
_t_solid_angle, _t_int_flux = \
MDNormSCDPreprocessIncoherent(**kwargs)
else:
_t_solid_angle = self.nominal_solid_angle('_t_solid_angle')
_t_int_flux = self.nominal_integrated_flux('_t_int_flux')
# Process a sample at a time
run_numbers = self._getRuns(self.getProperty("RunNumbers").value,
doIndiv=True)
run_numbers = list(itertools.chain.from_iterable(run_numbers))
diffraction_reporter = Progress(self,
start=0.0,
end=1.0,
nreports=len(run_numbers))
for i_run, run in enumerate(run_numbers):
_t_sample = self._mask_t0_crop(run, '_t_sample')
# Set Goniometer and UB matrix
SetGoniometer(_t_sample, Axis0=axis0, Axis1=axis1)
SetUB(_t_sample, **ub_args)
if self._bkg:
self._bkg.run().getGoniometer().\
setR(_t_sample.run().getGoniometer().getR())
SetUB(self._bkg, **ub_args)
# Determine limits for momentum transfer in HKL space. Needs to be
# done only once. We use the first run.
if min_values is None:
kwargs = dict(QDimensions='Q3D',
dEAnalysisMode='Elastic',
Q3DFrames='HKL')
min_values, max_values = ConvertToMDMinMaxGlobal(
_t_sample, **kwargs)
convert_to_md_kwargs.update({
'MinValues': min_values,
'MaxValues': max_values
})
# Convert to MD
_t_md = ConvertToMD(_t_sample,
OutputWorkspace='_t_md',
**convert_to_md_kwargs)
if self._bkg:
_t_bkg_md = ConvertToMD(self._bkg,
OutputWorkspace='_t_bkg_md',
**convert_to_md_kwargs)
# Determine aligned dimensions. Need to be done only once
if md_norm_scd_kwargs is None:
aligned = list()
for i_dim in range(3):
kwargs = {
'name': _t_md.getDimension(i_dim).name,
'min': min_values[i_dim],
'max': max_values[i_dim],
'n_bins': self._n_bins[i_dim]
}
aligned.append(
'{name},{min},{max},{n_bins}'.format(**kwargs))
md_norm_scd_kwargs = dict(AlignedDim0=aligned[0],
AlignedDim1=aligned[1],
AlignedDim2=aligned[2],
FluxWorkspace=_t_int_flux,
SolidAngleWorkspace=_t_solid_angle,
SkipSafetyCheck=True)
# Normalize sample by solid angle and integrated flux;
# Accumulate runs into the temporary workspaces
MDNormSCD(_t_md,
OutputWorkspace='_t_data',
OutputNormalizationWorkspace='_t_norm',
TemporaryDataWorkspace='_t_data'
if mtd.doesExist('_t_data') else None,
TemporaryNormalizationWorkspace='_t_norm'
if mtd.doesExist('_t_norm') else None,
**md_norm_scd_kwargs)
if self._bkg:
MDNormSCD(_t_bkg_md,
OutputWorkspace='_t_bkg_data',
OutputNormalizationWorkspace='_t_bkg_norm',
TemporaryDataWorkspace='_t_bkg_data'
if mtd.doesExist('_t_bkg_data') else None,
TemporaryNormalizationWorkspace='_t_bkg_norm'
if mtd.doesExist('_t_bkg_norm') else None,
**md_norm_scd_kwargs)
message = 'Processing sample {} of {}'.\
format(i_run+1, len(run_numbers))
diffraction_reporter.report(message)
self._temps.workspaces.append('PreprocessedDetectorsWS') # to remove
# Iteration over the sample runs is done.
# Division by vanadium, subtract background, and rename workspaces
name = self.getPropertyValue("OutputWorkspace")
_t_data = DivideMD(LHSWorkspace='_t_data', RHSWorkspace='_t_norm')
if self._bkg:
_t_bkg_data = DivideMD(LHSWorkspace='_t_bkg_data',
RHSWorkspace='_t_bkg_norm')
_t_scale = CreateSingleValuedWorkspace(DataValue=self._bkg_scale)
_t_bkg_data = MultiplyMD(_t_bkg_data, _t_scale)
ws = MinusMD(_t_data, _t_bkg_data)
RenameWorkspace(_t_data, OutputWorkspace=name + '_dat')
RenameWorkspace(_t_bkg_data, OutputWorkspace=name + '_bkg')
else:
ws = _t_data
RenameWorkspace(ws, OutputWorkspace=name)
self.setProperty("OutputWorkspace", ws)
diffraction_reporter.report(len(run_numbers), 'Done')
def PyExec(self):
# remove possible old temp workspaces
[
DeleteWorkspace(ws) for ws in self.temp_workspace_list
if mtd.doesExist(ws)
]
_background = bool(self.getProperty("Background").value)
_load_inst = bool(self.getProperty("LoadInstrument").value)
_detcal = bool(self.getProperty("DetCal").value)
_masking = bool(self.getProperty("MaskFile").value)
_outWS_name = self.getPropertyValue("OutputWorkspace")
UBList = self._generate_UBList()
dim0_min, dim0_max, dim0_bins = self.getProperty('BinningDim0').value
dim1_min, dim1_max, dim1_bins = self.getProperty('BinningDim1').value
dim2_min, dim2_max, dim2_bins = self.getProperty('BinningDim2').value
MinValues = "{},{},{}".format(dim0_min, dim1_min, dim2_min)
MaxValues = "{},{},{}".format(dim0_max, dim1_max, dim2_max)
AlignedDim0 = ",{},{},{}".format(dim0_min, dim0_max, int(dim0_bins))
AlignedDim1 = ",{},{},{}".format(dim1_min, dim1_max, int(dim1_bins))
AlignedDim2 = ",{},{},{}".format(dim2_min, dim2_max, int(dim2_bins))
LoadNexus(Filename=self.getProperty("SolidAngle").value,
OutputWorkspace='__sa')
LoadNexus(Filename=self.getProperty("Flux").value,
OutputWorkspace='__flux')
if _masking:
LoadMask(Instrument=mtd['__sa'].getInstrument().getName(),
InputFile=self.getProperty("MaskFile").value,
OutputWorkspace='__mask')
MaskDetectors(Workspace='__sa', MaskedWorkspace='__mask')
DeleteWorkspace('__mask')
XMin = mtd['__sa'].getXDimension().getMinimum()
XMax = mtd['__sa'].getXDimension().getMaximum()
if _background:
Load(Filename=self.getProperty("Background").value,
OutputWorkspace='__bkg',
FilterByTofMin=self.getProperty("FilterByTofMin").value,
FilterByTofMax=self.getProperty("FilterByTofMax").value)
if _load_inst:
LoadInstrument(
Workspace='__bkg',
Filename=self.getProperty("LoadInstrument").value,
RewriteSpectraMap=False)
if _detcal:
LoadIsawDetCal(InputWorkspace='__bkg',
Filename=self.getProperty("DetCal").value)
MaskDetectors(Workspace='__bkg', MaskedWorkspace='__sa')
ConvertUnits(InputWorkspace='__bkg',
OutputWorkspace='__bkg',
Target='Momentum')
CropWorkspace(InputWorkspace='__bkg',
OutputWorkspace='__bkg',
XMin=XMin,
XMax=XMax)
progress = Progress(
self, 0.0, 1.0,
len(UBList) * len(self.getProperty("Filename").value))
for run in self.getProperty("Filename").value:
logger.notice("Working on " + run)
Load(Filename=run,
OutputWorkspace='__run',
FilterByTofMin=self.getProperty("FilterByTofMin").value,
FilterByTofMax=self.getProperty("FilterByTofMax").value)
if _load_inst:
LoadInstrument(
Workspace='__run',
Filename=self.getProperty("LoadInstrument").value,
RewriteSpectraMap=False)
if _detcal:
LoadIsawDetCal(InputWorkspace='__run',
Filename=self.getProperty("DetCal").value)
MaskDetectors(Workspace='__run', MaskedWorkspace='__sa')
ConvertUnits(InputWorkspace='__run',
OutputWorkspace='__run',
Target='Momentum')
CropWorkspace(InputWorkspace='__run',
OutputWorkspace='__run',
XMin=XMin,
XMax=XMax)
if self.getProperty('SetGoniometer').value:
SetGoniometer(
Workspace='__run',
Goniometers=self.getProperty('Goniometers').value,
Axis0=self.getProperty('Axis0').value,
Axis1=self.getProperty('Axis1').value,
Axis2=self.getProperty('Axis2').value)
# Set background Goniometer to be the same as data
if _background:
mtd['__bkg'].run().getGoniometer().setR(
mtd['__run'].run().getGoniometer().getR())
for ub in UBList:
SetUB(Workspace='__run', UB=ub)
ConvertToMD(InputWorkspace='__run',
OutputWorkspace='__md',
QDimensions='Q3D',
dEAnalysisMode='Elastic',
Q3DFrames='HKL',
QConversionScales='HKL',
Uproj=self.getProperty('Uproj').value,
Vproj=self.getProperty('Vproj').value,
Wproj=self.getProperty('wproj').value,
MinValues=MinValues,
MaxValues=MaxValues)
MDNormSCD(
InputWorkspace=mtd['__md'],
FluxWorkspace='__flux',
SolidAngleWorkspace='__sa',
OutputWorkspace='__data',
SkipSafetyCheck=True,
TemporaryDataWorkspace='__data'
if mtd.doesExist('__data') else None,
OutputNormalizationWorkspace='__norm',
TemporaryNormalizationWorkspace='__norm'
if mtd.doesExist('__norm') else None,
AlignedDim0=mtd['__md'].getDimension(0).name + AlignedDim0,
AlignedDim1=mtd['__md'].getDimension(1).name + AlignedDim1,
AlignedDim2=mtd['__md'].getDimension(2).name + AlignedDim2)
DeleteWorkspace('__md')
if _background:
SetUB(Workspace='__bkg', UB=ub)
ConvertToMD(InputWorkspace='__bkg',
OutputWorkspace='__bkg_md',
QDimensions='Q3D',
dEAnalysisMode='Elastic',
Q3DFrames='HKL',
QConversionScales='HKL',
Uproj=self.getProperty('Uproj').value,
Vproj=self.getProperty('Vproj').value,
Wproj=self.getProperty('Wproj').value,
MinValues=MinValues,
MaxValues=MaxValues)
MDNormSCD(
InputWorkspace='__bkg_md',
FluxWorkspace='__flux',
SolidAngleWorkspace='__sa',
SkipSafetyCheck=True,
OutputWorkspace='__bkg_data',
TemporaryDataWorkspace='__bkg_data'
if mtd.doesExist('__bkg_data') else None,
OutputNormalizationWorkspace='__bkg_norm',
TemporaryNormalizationWorkspace='__bkg_norm'
if mtd.doesExist('__bkg_norm') else None,
AlignedDim0=mtd['__bkg_md'].getDimension(0).name +
AlignedDim0,
AlignedDim1=mtd['__bkg_md'].getDimension(1).name +
AlignedDim1,
AlignedDim2=mtd['__bkg_md'].getDimension(2).name +
AlignedDim2)
DeleteWorkspace('__bkg_md')
progress.report()
DeleteWorkspace('__run')
if _background:
# outWS = data / norm - bkg_data / bkg_norm * BackgroundScale
DivideMD(LHSWorkspace='__data',
RHSWorkspace='__norm',
OutputWorkspace=_outWS_name + '_normalizedData')
DivideMD(LHSWorkspace='__bkg_data',
RHSWorkspace='__bkg_norm',
OutputWorkspace=_outWS_name + '_normalizedBackground')
CreateSingleValuedWorkspace(
OutputWorkspace='__scale',
DataValue=self.getProperty('BackgroundScale').value)
MultiplyMD(LHSWorkspace=_outWS_name + '_normalizedBackground',
RHSWorkspace='__scale',
OutputWorkspace='__scaled_background')
DeleteWorkspace('__scale')
MinusMD(LHSWorkspace=_outWS_name + '_normalizedData',
RHSWorkspace='__scaled_background',
OutputWorkspace=_outWS_name)
if self.getProperty('KeepTemporaryWorkspaces').value:
RenameWorkspaces(InputWorkspaces=[
'__data', '__norm', '__bkg_data', '__bkg_norm'
],
WorkspaceNames=[
_outWS_name + '_data',
_outWS_name + '_normalization',
_outWS_name + '_background_data',
_outWS_name + '_background_normalization'
])
else:
# outWS = data / norm
DivideMD(LHSWorkspace='__data',
RHSWorkspace='__norm',
OutputWorkspace=_outWS_name)
if self.getProperty('KeepTemporaryWorkspaces').value:
RenameWorkspaces(InputWorkspaces=['__data', '__norm'],
WorkspaceNames=[
_outWS_name + '_data',
_outWS_name + '_normalization'
])
self.setProperty("OutputWorkspace", mtd[_outWS_name])
# remove temp workspaces
[
DeleteWorkspace(ws) for ws in self.temp_workspace_list
if mtd.doesExist(ws)
]
def _scale_md_group(ws_group, scale_ws):
for entry in mtd[ws_group]:
MultiplyMD(LHSWorkspace=entry,
RHSWorkspace=scale_ws,
OutputWorkspace=entry)
def PyExec(self):
# remove possible old temp workspaces
[
DeleteWorkspace(ws) for ws in self.temp_workspace_list
if mtd.doesExist(ws)
]
_background = bool(self.getProperty("Background").value)
self._load_inst = bool(self.getProperty("LoadInstrument").value)
self._apply_cal = bool(self.getProperty("ApplyCalibration").value)
self._detcal = bool(self.getProperty("DetCal").value)
self._copy_params = bool(
self.getProperty("CopyInstrumentParameters").value)
_masking = bool(self.getProperty("MaskFile").value)
_outWS_name = self.getPropertyValue("OutputWorkspace")
_UB = self.getProperty("UBMatrix").value
if len(_UB) == 1:
_UB = np.tile(_UB, len(self.getProperty("Filename").value))
_offsets = self.getProperty("OmegaOffset").value
if len(_offsets) == 0:
_offsets = np.zeros(len(self.getProperty("Filename").value))
if self.getProperty("ReuseSAFlux").value and mtd.doesExist(
'__sa') and mtd.doesExist('__flux'):
logger.notice(
"Reusing previously loaded SolidAngle and Flux workspaces. "
"Set ReuseSAFlux to False if new files are selected or you change the momentum range."
)
else:
logger.notice("Loading SolidAngle and Flux from file")
LoadNexus(Filename=self.getProperty("SolidAngle").value,
OutputWorkspace='__sa')
LoadNexus(Filename=self.getProperty("Flux").value,
OutputWorkspace='__flux')
if _masking:
LoadMask(Instrument=mtd['__sa'].getInstrument().getName(),
InputFile=self.getProperty("MaskFile").value,
OutputWorkspace='__mask')
MaskDetectors(Workspace='__sa', MaskedWorkspace='__mask')
DeleteWorkspace('__mask')
self.XMin = mtd['__sa'].getXDimension().getMinimum()
self.XMax = mtd['__sa'].getXDimension().getMaximum()
newXMin = self.getProperty("MomentumMin").value
newXMax = self.getProperty("MomentumMax").value
if newXMin != Property.EMPTY_DBL or newXMax != Property.EMPTY_DBL:
if newXMin != Property.EMPTY_DBL:
self.XMin = max(self.XMin, newXMin)
if newXMax != Property.EMPTY_DBL:
self.XMax = min(self.XMax, newXMax)
logger.notice("Using momentum range {} to {} A^-1".format(
self.XMin, self.XMax))
CropWorkspace(InputWorkspace='__flux',
OutputWorkspace='__flux',
XMin=self.XMin,
XMax=self.XMax)
for spectrumNumber in range(mtd['__flux'].getNumberHistograms()):
Y = mtd['__flux'].readY(spectrumNumber)
mtd['__flux'].setY(spectrumNumber,
(Y - Y.min()) / (Y.max() - Y.min()))
MinValues = [-self.XMax * 2] * 3
MaxValues = [self.XMax * 2] * 3
if _background:
self.load_file_and_apply(
self.getProperty("Background").value, '__bkg', 0)
progress = Progress(self, 0.0, 1.0,
len(self.getProperty("Filename").value))
for n, run in enumerate(self.getProperty("Filename").value):
logger.notice("Working on " + run)
self.load_file_and_apply(run, '__run', _offsets[n])
LoadIsawUB('__run', _UB[n])
ConvertToMD(InputWorkspace='__run',
OutputWorkspace='__md',
QDimensions='Q3D',
dEAnalysisMode='Elastic',
Q3DFrames='Q_sample',
MinValues=MinValues,
MaxValues=MaxValues)
RecalculateTrajectoriesExtents(InputWorkspace='__md',
OutputWorkspace='__md')
MDNorm(
InputWorkspace='__md',
FluxWorkspace='__flux',
SolidAngleWorkspace='__sa',
OutputDataWorkspace='__data',
TemporaryDataWorkspace='__data'
if mtd.doesExist('__data') else None,
OutputNormalizationWorkspace='__norm',
TemporaryNormalizationWorkspace='__norm'
if mtd.doesExist('__norm') else None,
OutputWorkspace=_outWS_name,
QDimension0=self.getProperty('QDimension0').value,
QDimension1=self.getProperty('QDimension1').value,
QDimension2=self.getProperty('QDimension2').value,
Dimension0Binning=self.getProperty('Dimension0Binning').value,
Dimension1Binning=self.getProperty('Dimension1Binning').value,
Dimension2Binning=self.getProperty('Dimension2Binning').value,
SymmetryOperations=self.getProperty(
'SymmetryOperations').value)
DeleteWorkspace('__md')
if _background:
# Set background Goniometer and UB to be the same as data
CopySample(InputWorkspace='__run',
OutputWorkspace='__bkg',
CopyName=False,
CopyMaterial=False,
CopyEnvironment=False,
CopyShape=False,
CopyLattice=True)
mtd['__bkg'].run().getGoniometer().setR(
mtd['__run'].run().getGoniometer().getR())
ConvertToMD(InputWorkspace='__bkg',
OutputWorkspace='__bkg_md',
QDimensions='Q3D',
dEAnalysisMode='Elastic',
Q3DFrames='Q_sample',
MinValues=MinValues,
MaxValues=MaxValues)
RecalculateTrajectoriesExtents(InputWorkspace='__bkg_md',
OutputWorkspace='__bkg_md')
MDNorm(InputWorkspace='__bkg_md',
FluxWorkspace='__flux',
SolidAngleWorkspace='__sa',
OutputDataWorkspace='__bkg_data',
TemporaryDataWorkspace='__bkg_data'
if mtd.doesExist('__bkg_data') else None,
OutputNormalizationWorkspace='__bkg_norm',
TemporaryNormalizationWorkspace='__bkg_norm'
if mtd.doesExist('__bkg_norm') else None,
OutputWorkspace='__normalizedBackground',
QDimension0=self.getProperty('QDimension0').value,
QDimension1=self.getProperty('QDimension1').value,
QDimension2=self.getProperty('QDimension2').value,
Dimension0Binning=self.getProperty(
'Dimension0Binning').value,
Dimension1Binning=self.getProperty(
'Dimension1Binning').value,
Dimension2Binning=self.getProperty(
'Dimension2Binning').value,
SymmetryOperations=self.getProperty(
'SymmetryOperations').value)
DeleteWorkspace('__bkg_md')
progress.report()
DeleteWorkspace('__run')
if _background:
# outWS = data / norm - bkg_data / bkg_norm * BackgroundScale
CreateSingleValuedWorkspace(
OutputWorkspace='__scale',
DataValue=self.getProperty('BackgroundScale').value)
MultiplyMD(LHSWorkspace='__normalizedBackground',
RHSWorkspace='__scale',
OutputWorkspace='__normalizedBackground')
DeleteWorkspace('__scale')
MinusMD(LHSWorkspace=_outWS_name,
RHSWorkspace='__normalizedBackground',
OutputWorkspace=_outWS_name)
if self.getProperty('KeepTemporaryWorkspaces').value:
RenameWorkspaces(InputWorkspaces=[
'__data', '__norm', '__bkg_data', '__bkg_norm'
],
WorkspaceNames=[
_outWS_name + '_data',
_outWS_name + '_normalization',
_outWS_name + '_background_data',
_outWS_name + '_background_normalization'
])
else:
if self.getProperty('KeepTemporaryWorkspaces').value:
RenameWorkspaces(InputWorkspaces=['__data', '__norm'],
WorkspaceNames=[
_outWS_name + '_data',
_outWS_name + '_normalization'
])
self.setProperty("OutputWorkspace", mtd[_outWS_name])
# remove temp workspaces
[
DeleteWorkspace(ws) for ws in self.temp_workspace_list
if mtd.doesExist(ws)
]
