def _group_and_SofQW(self, wsName, etRebins, isSample=True): """ Transforms from wavelength and detector ID to S(Q,E) @param wsName: workspace as a function of wavelength and detector id @return: S(Q,E) """ api.ConvertUnits(InputWorkspace=wsName, OutputWorkspace=wsName, Target='DeltaE', EMode='Indirect') api.CorrectKiKf(InputWorkspace=wsName, OutputWorkspace=wsName, EMode='Indirect') api.Rebin(InputWorkspace=wsName, OutputWorkspace=wsName, Params=etRebins) if self._groupDetOpt != "None": if self._groupDetOpt == "Low-Resolution": grp_file = "BASIS_Grouping_LR.xml" else: grp_file = "BASIS_Grouping.xml" # If mask override used, we need to add default grouping file # location to search paths if self._overrideMask: config.appendDataSearchDir(DEFAULT_MASK_GROUP_DIR) api.GroupDetectors(InputWorkspace=wsName, OutputWorkspace=wsName, MapFile=grp_file, Behaviour="Sum") wsSqwName = wsName + '_divided_sqw' if isSample and self._doNorm else wsName + '_sqw' api.SofQW3(InputWorkspace=wsName, OutputWorkspace=wsSqwName, QAxisBinning=self._qBins, EMode='Indirect', EFixed='2.0826') return wsSqwName
def _group_and_SofQW(self, wsName, etRebins, isSample=True): """ Transforms from wavelength and detector ID to S(Q,E) @param wsName: workspace as a function of wavelength and detector id @param etRebins: final energy domain and bin width @param isSample: discriminates between sample and vanadium @return: S(Q,E) """ sapi.ConvertUnits(InputWorkspace=wsName, OutputWorkspace=wsName, Target='DeltaE', EMode='Indirect') sapi.CorrectKiKf(InputWorkspace=wsName, OutputWorkspace=wsName, EMode='Indirect') sapi.Rebin(InputWorkspace=wsName, OutputWorkspace=wsName, Params=etRebins) if self._groupDetOpt != "None": if self._groupDetOpt == "Low-Resolution": grp_file = "BASIS_Grouping_LR.xml" else: grp_file = "BASIS_Grouping.xml" # If mask override used, we need to add default grouping file # location to search paths if self._overrideMask: config.appendDataSearchDir(DEFAULT_MASK_GROUP_DIR) sapi.GroupDetectors(InputWorkspace=wsName, OutputWorkspace=wsName, MapFile=grp_file, Behaviour="Sum") wsSqwName = wsName + '_divided_sqw' if isSample and self._doNorm else wsName + '_sqw' sapi.SofQW3(InputWorkspace=wsName, QAxisBinning=self._qBins, EMode='Indirect', EFixed=self._reflection["default_energy"], OutputWorkspace=wsSqwName) # Rebin the vanadium within the elastic line if not isSample: sapi.Rebin(InputWorkspace=wsSqwName, OutputWorkspace=wsSqwName, Params=self._reflection["vanadium_bins"]) return wsSqwName
def _group_and_SofQW(self, wsName, prefix, etRebins, isSample=True): r""" Transforms from wavelength and detector ID to S(Q,E) Parameters ---------- wsName: str Name of a workspace as a function of wavelength and detector id prefix: str Name prefix for output workspaces and files etRebins: list Final energy domain and bin width isSample: bool Discriminates between sample and vanadium Returns ------- str Name of S(Q,E) workspace """ sapi.ConvertUnits(InputWorkspace=wsName, OutputWorkspace=wsName, Target='DeltaE', EMode='Indirect', EFixed=self._reflection['default_energy']) sapi.CorrectKiKf(InputWorkspace=wsName, OutputWorkspace=wsName, EMode='Indirect', EFixed=self._reflection['default_energy']) sapi.Rebin(InputWorkspace=wsName, OutputWorkspace=wsName, Params=etRebins) if self._groupDetOpt != 'None': if self._groupDetOpt == 'Low-Resolution': grp_file = 'BASIS_Grouping_LR.xml' else: grp_file = 'BASIS_Grouping.xml' # If mask override used, we need to add default grouping file # location to search paths if self._overrideMask: mantid_config.appendDataSearchDir(DEFAULT_MASK_GROUP_DIR) sapi.GroupDetectors(InputWorkspace=wsName, OutputWorkspace=wsName, MapFile=grp_file, Behaviour='Sum') # Output NXSPE file (must be done before transforming the # vertical axis to point data) if isSample and self._nsxpe_do: extension = '.nxspe' run = mtd[wsName].getRun() if run.hasProperty(self._nxspe_psi_angle_log): psi_angle_logproperty = \ run.getProperty(self._nxspe_psi_angle_log) psi_angle = np.average(psi_angle_logproperty.value) psi_angle += self._nxspe_offset nxspe_filename = prefix + extension sapi.SaveNXSPE(InputWorkspace=wsName, Filename=nxspe_filename, Efixed=self._reflection['default_energy'], Psi=psi_angle, KiOverKfScaling=1) else: error_message = 'Runs have no log entry named {}'\ .format(self._nxspe_psi_angle_log) self.log().error(error_message) wsSqwName = prefix if isSample is True else wsName wsSqwName += '_divided_sqw' if self._doNorm is True else '_sqw' sapi.SofQW3(InputWorkspace=wsName, QAxisBinning=self._qBins, EMode='Indirect', EFixed=self._reflection['default_energy'], OutputWorkspace=wsSqwName) # Rebin the vanadium within the elastic line if not isSample: sapi.Rebin(InputWorkspace=wsSqwName, OutputWorkspace=wsSqwName, Params=self._reflection['vanadium_bins']) return wsSqwName
def PyExec(self): config['default.facility'] = "SNS" config['default.instrument'] = self._long_inst self._doIndiv = self.getProperty("DoIndividual").value self._etBins = self.getProperty( "EnergyBins").value / MICROEV_TO_MILLIEV self._qBins = self.getProperty("MomentumTransferBins").value self._noMonNorm = self.getProperty("NoMonitorNorm").value self._maskFile = self.getProperty("MaskFile").value self._groupDetOpt = self.getProperty("GroupDetectors").value datasearch = config["datasearch.searcharchive"] if datasearch != "On": config["datasearch.searcharchive"] = "On" # Handle masking file override if necessary self._overrideMask = bool(self._maskFile) if not self._overrideMask: config.appendDataSearchDir(DEFAULT_MASK_GROUP_DIR) self._maskFile = DEFAULT_MASK_FILE api.LoadMask(Instrument='BASIS', OutputWorkspace='BASIS_MASK', InputFile=self._maskFile) # Work around length issue _dMask = api.ExtractMask('BASIS_MASK') self._dMask = _dMask[1] api.DeleteWorkspace(_dMask[0]) # Do normalization if run numbers are present norm_runs = self.getProperty("NormRunNumbers").value self._doNorm = bool(norm_runs) self.log().information("Do Norm: " + str(self._doNorm)) if self._doNorm: if ";" in norm_runs: raise SyntaxError("Normalization does not support run groups") # Setup the integration (rebin) parameters normRange = self.getProperty("NormWavelengthRange").value self._normRange = [ normRange[0], normRange[1] - normRange[0], normRange[1] ] # Process normalization runs self._norm_run_list = self._getRuns(norm_runs) for norm_set in self._norm_run_list: extra_extension = "_norm" self._normWs = self._makeRunName(norm_set[0]) self._normWs += extra_extension self._normMonWs = self._normWs + "_monitors" self._sumRuns(norm_set, self._normWs, self._normMonWs, extra_extension) self._calibData(self._normWs, self._normMonWs) api.Rebin(InputWorkspace=self._normWs, OutputWorkspace=self._normWs,\ Params=self._normRange) api.FindDetectorsOutsideLimits(InputWorkspace=self._normWs,\ OutputWorkspace="BASIS_NORM_MASK") self._run_list = self._getRuns(self.getProperty("RunNumbers").value) for run_set in self._run_list: self._samWs = self._makeRunName(run_set[0]) self._samMonWs = self._samWs + "_monitors" self._samWsRun = str(run_set[0]) self._sumRuns(run_set, self._samWs, self._samMonWs) # After files are all added, run the reduction self._calibData(self._samWs, self._samMonWs) if self._doNorm: api.MaskDetectors(Workspace=self._samWs,\ MaskedWorkspace='BASIS_NORM_MASK') api.Divide(LHSWorkspace=self._samWs, RHSWorkspace=self._normWs,\ OutputWorkspace=self._samWs) api.ConvertUnits(InputWorkspace=self._samWs, OutputWorkspace=self._samWs, Target='DeltaE', EMode='Indirect') api.CorrectKiKf(InputWorkspace=self._samWs, OutputWorkspace=self._samWs, EMode='Indirect') api.Rebin(InputWorkspace=self._samWs, OutputWorkspace=self._samWs, Params=self._etBins) if self._groupDetOpt != "None": if self._groupDetOpt == "Low-Resolution": grp_file = "BASIS_Grouping_LR.xml" else: grp_file = "BASIS_Grouping.xml" # If mask override used, we need to add default grouping file location to # search paths if self._overrideMask: config.appendDataSearchDir(DEFAULT_MASK_GROUP_DIR) api.GroupDetectors(InputWorkspace=self._samWs, OutputWorkspace=self._samWs, MapFile=grp_file, Behaviour="Sum") self._samSqwWs = self._samWs + '_sqw' api.SofQW3(InputWorkspace=self._samWs, OutputWorkspace=self._samSqwWs, QAxisBinning=self._qBins, EMode='Indirect', EFixed=DEFAULT_ENERGY) dave_grp_filename = self._makeRunName(self._samWsRun, False) + ".dat" api.SaveDaveGrp(Filename=dave_grp_filename, InputWorkspace=self._samSqwWs, ToMicroEV=True) processed_filename = self._makeRunName(self._samWsRun, False) + "_sqw.nxs" api.SaveNexus(Filename=processed_filename, InputWorkspace=self._samSqwWs)
from mantid import simpleapi as msa ws = msa.Load('sim.nxs') out = msa.DgsReduction(SampleInputWorkspace=ws, IncidentEnergyGuess=70.49, UseIncidentEnergyGuess=1, TimeZeroGuess=25.415) msa.SofQW3( InputWorkspace='out', OutputWorkspace='iqw', QAxisBinning="0,0.05,7", EMode='Direct', ) msa.SaveNexus( InputWorkspace='iqw', Filename='iqe.nxs', Title='iqw', )