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 _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 cmd_args = dict(QDimensions='Q3D', dEAnalysisMode='Elastic', Q3DFrames='HKL', QConversionScales='HKL', Uproj=uproj, Vproj=vproj, Wproj=wproj) mdn_args = 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) cmd_args.update({'MinValues': min_values, 'MaxValues': max_values}) # Convert to MD _t_md = ConvertToMD(_t_sample, OutputWorkspace='_t_md', **cmd_args) if self._bkg: _t_bkg_md = ConvertToMD(self._bkg, OutputWorkspace='_t_bkg_md', **cmd_args) # Determine aligned dimensions. Need to be done only once if mdn_args 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)) mdn_args = 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, **mdn_args) 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, **mdn_args) 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')
if have_van: MaskDetectors(event_ws, MaskedWorkspace=sa) XMin = sa.getXDimension().getMinimum() XMax = sa.getXDimension().getMaximum() event_ws = CropWorkspace(InputWorkspace=event_ws, XMin=XMin, XMax=XMax) event_ws = Rebin(event_ws, Params="{},{},{}".format(XMin, XMax - XMin, XMax), PreserveEvents=True) mde = ConvertToMD(InputWorkspace=event_ws, QDimensions='Q3D', dEAnalysisMode='Elastic', Q3DFrames='HKL', QConversionScales='HKL') for plot_param in plot_params: AxisNames = {'H': '[H,0,0]', 'K': '[0,K,0]', 'L': '[0,0,L]'} xaxis = mde.getDimension( mde.getDimensionIndexByName(AxisNames[plot_param['axis1']])) try: plot_xmin = float(plot_param['xmin']) except ValueError: plot_xmin = xaxis.getMinimum() try: plot_xmax = float(plot_param['xmax']) except ValueError: plot_xmax = xaxis.getMaximum() try: plot_xbins = int(plot_param['xsteps']) except ValueError: plot_xbins = 400 AlignedDim0 = '{},{},{},{}'.format(AxisNames[plot_param['axis1']], plot_xmin, plot_xmax, plot_xbins) yaxis = mde.getDimension(