def _sumForegroundInLambda(self, ws):
     """Sum the foreground region into a single histogram."""
     foreground = self._foregroundIndices(ws)
     sumIndices = [i for i in range(foreground[0], foreground[2] + 1)]
     beamPosIndex = foreground[1]
     foregroundWSName = self._names.withSuffix('foreground_grouped')
     foregroundWS = ExtractSingleSpectrum(InputWorkspace=ws,
                                          OutputWorkspace=foregroundWSName,
                                          WorkspaceIndex=beamPosIndex,
                                          EnableLogging=self._subalgLogging)
     maxIndex = ws.getNumberHistograms() - 1
     foregroundYs = foregroundWS.dataY(0)
     foregroundEs = foregroundWS.dataE(0)
     numpy.square(foregroundEs, out=foregroundEs)
     for i in sumIndices:
         if i == beamPosIndex:
             continue
         if i < 0 or i > maxIndex:
             self.log().warning(
                 'Foreground partially out of the workspace.')
         ys = ws.readY(i)
         foregroundYs += ys
         es = ws.readE(i)
         foregroundEs += es**2
     numpy.sqrt(foregroundEs, out=foregroundEs)
     self._cleanup.cleanup(ws)
     AddSampleLog(Workspace=foregroundWS,
                  LogName=common.SampleLogs.SUM_TYPE,
                  LogText=SumType.IN_LAMBDA,
                  LogType='String',
                  EnableLogging=self._subalgLogging)
     ConvertToDistribution(Workspace=foregroundWS,
                           EnableLogging=self._subalgLogging)
     return foregroundWS
Exemple #2
0
 def convert_to_matrix(self):
     ws_conv = ConvertMDHistoToMatrixWorkspace(self.name, Normalization='NumEventsNormalization',
                                               FindXAxis=False, StoreInADS=False, OutputWorkspace=self.name)
     coord = self.get_coordinates()
     bin_size = coord[coord.keys()[0]][1] - coord[coord.keys()[0]][0]
     ws_conv = Scale(ws_conv, bin_size, OutputWorkspace=self.name, StoreInADS=False)
     ConvertToDistribution(ws_conv, StoreInADS=False)
     return Workspace(ws_conv, self.name)
    def test_view_closes_on_replace_when_model_properties_change(self):
        ws = CreateSampleWorkspace()
        pres = SliceViewer(ws)
        ConvertToDistribution(ws)

        QApplication.sendPostedEvents()

        self.assert_no_toplevel_widgets()
        self.assertEqual(pres.ads_observer, None)
Exemple #4
0
    def runTest(self):
        HelperTestingClass.__init__(self)
        ws = CreateSampleWorkspace()
        pres = SliceViewer(ws)
        ConvertToDistribution(ws)

        self._qapp.sendPostedEvents()

        self.assert_no_toplevel_widgets()
        self.assertEqual(pres.ads_observer, None)
Exemple #5
0
 def _convertToDistribution(self, mainWS, wsNames, wsCleanup, subalgLogging):
     """Convert the workspace into a distribution."""
     distributionWSName = wsNames.withSuffix('as_distribution')
     distributionWS = CloneWorkspace(InputWorkspace=mainWS,
                                     OutputWorkspace=distributionWSName,
                                     EnableLogging=subalgLogging)
     wsCleanup.cleanup(mainWS)
     ConvertToDistribution(Workspace=distributionWS,
                           EnableLogging=subalgLogging)
     return distributionWS
    def PyExec(self):
        raw_ws = self.getProperty('InputWorkspace').value
        sample_geometry = self.getPropertyValue('SampleGeometry')
        sample_material = self.getPropertyValue('SampleMaterial')
        cal_file_name = self.getPropertyValue('CalFileName')
        SetSample(InputWorkspace=raw_ws,
                  Geometry=sample_geometry,
                  Material=sample_material)
        # find the closest monitor to the sample for incident spectrum
        raw_spec_info = raw_ws.spectrumInfo()
        incident_index = None
        for i in range(raw_spec_info.size()):
            if raw_spec_info.isMonitor(i):
                l2 = raw_spec_info.position(i)[2]
                if not incident_index:
                    incident_index = i
                else:
                    if raw_spec_info.position(incident_index)[2] < l2 < 0:
                        incident_index = i
        monitor = ExtractSpectra(InputWorkspace=raw_ws,
                                 WorkspaceIndexList=[incident_index])
        monitor = ConvertUnits(InputWorkspace=monitor, Target="Wavelength")
        x_data = monitor.dataX(0)
        min_x = np.min(x_data)
        max_x = np.max(x_data)
        width_x = (max_x - min_x) / x_data.size
        fit_spectra = FitIncidentSpectrum(
            InputWorkspace=monitor,
            BinningForCalc=[min_x, 1 * width_x, max_x],
            BinningForFit=[min_x, 10 * width_x, max_x],
            FitSpectrumWith="CubicSpline")
        self_scattering_correction = CalculatePlaczekSelfScattering(
            InputWorkspace=raw_ws, IncidentSpecta=fit_spectra)
        cal_workspace = LoadCalFile(InputWorkspace=self_scattering_correction,
                                    CalFileName=cal_file_name,
                                    Workspacename='cal_workspace',
                                    MakeOffsetsWorkspace=False,
                                    MakeMaskWorkspace=False)
        self_scattering_correction = DiffractionFocussing(
            InputWorkspace=self_scattering_correction,
            GroupingFilename=cal_file_name)

        n_pixel = np.zeros(self_scattering_correction.getNumberHistograms())

        for i in range(cal_workspace.getNumberHistograms()):
            grouping = cal_workspace.dataY(i)
            if grouping[0] > 0:
                n_pixel[int(grouping[0] - 1)] += 1
        correction_ws = CreateWorkspace(
            DataY=n_pixel,
            DataX=[0, 1],
            NSpec=self_scattering_correction.getNumberHistograms())
        self_scattering_correction = Divide(
            LHSWorkspace=self_scattering_correction,
            RHSWorkspace=correction_ws)
        ConvertToDistribution(Workspace=self_scattering_correction)
        self_scattering_correction = ConvertUnits(
            InputWorkspace=self_scattering_correction,
            Target="MomentumTransfer",
            EMode='Elastic')
        DeleteWorkspace('cal_workspace_group')
        DeleteWorkspace(correction_ws)
        DeleteWorkspace(fit_spectra)
        DeleteWorkspace(monitor)
        DeleteWorkspace(raw_ws)
        self.setProperty('OutputWorkspace', self_scattering_correction)
def TotalScatteringReduction(config=None):
    facility = config['Facility']
    title = config['Title']
    instr = config['Instrument']

    # Get an instance to Mantid's logger
    log = Logger("TotalScatteringReduction")

    # Get sample info
    sample = get_sample(config)
    sam_mass_density = sample.get('MassDensity', None)
    sam_packing_fraction = sample.get('PackingFraction', None)
    sam_geometry = sample.get('Geometry', None)
    sam_material = sample.get('Material', None)

    sam_geo_dict = {
        'Shape': 'Cylinder',
        'Radius': config['Sample']['Geometry']['Radius'],
        'Height': config['Sample']['Geometry']['Height']
    }
    sam_mat_dict = {
        'ChemicalFormula': sam_material,
        'SampleMassDensity': sam_mass_density
    }
    if 'Environment' in config:
        sam_env_dict = {
            'Name': config['Environment']['Name'],
            'Container': config['Environment']['Container']
        }
    else:
        sam_env_dict = {'Name': 'InAir', 'Container': 'PAC06'}
    # Get normalization info
    van = get_normalization(config)
    van_mass_density = van.get('MassDensity', None)
    van_packing_fraction = van.get('PackingFraction', 1.0)
    van_geometry = van.get('Geometry', None)
    van_material = van.get('Material', 'V')

    van_geo_dict = {
        'Shape': 'Cylinder',
        'Radius': config['Normalization']['Geometry']['Radius'],
        'Height': config['Normalization']['Geometry']['Height']
    }
    van_mat_dict = {
        'ChemicalFormula': van_material,
        'SampleMassDensity': van_mass_density
    }

    # Get calibration, characterization, and other settings
    merging = config['Merging']
    binning = merging['QBinning']
    characterizations = merging.get('Characterizations', None)

    # Grouping
    grouping = merging.get('Grouping', None)
    cache_dir = config.get("CacheDir", os.path.abspath('.'))
    OutputDir = config.get("OutputDir", os.path.abspath('.'))

    # Create Nexus file basenames
    sample['Runs'] = expand_ints(sample['Runs'])
    sample['Background']['Runs'] = expand_ints(sample['Background'].get(
        'Runs', None))
    '''
    Currently not implemented:
    # wkspIndices = merging.get('SumBanks', None)
    # high_q_linear_fit_range = config['HighQLinearFitRange']

    POWGEN options not used
    #alignAndFocusArgs['RemovePromptPulseWidth'] = 50
    # alignAndFocusArgs['CompressTolerance'] use defaults
    # alignAndFocusArgs['UnwrapRef'] POWGEN option
    # alignAndFocusArgs['LowResRef'] POWGEN option
    # alignAndFocusArgs['LowResSpectrumOffset'] POWGEN option

    How much of each bank gets merged has info here in the form of
    # {"ID", "Qmin", "QMax"}
    # alignAndFocusArgs['CropWavelengthMin'] from characterizations file
    # alignAndFocusArgs['CropWavelengthMax'] from characterizations file
    '''

    if facility == 'SNS':
        facility_file_format = '%s_%d'
    else:
        facility_file_format = '%s%d'

    sam_scans = ','.join(
        [facility_file_format % (instr, num) for num in sample['Runs']])
    container_scans = ','.join([
        facility_file_format % (instr, num)
        for num in sample['Background']["Runs"]
    ])
    container_bg = None
    if "Background" in sample['Background']:
        sample['Background']['Background']['Runs'] = expand_ints(
            sample['Background']['Background']['Runs'])
        container_bg = ','.join([
            facility_file_format % (instr, num)
            for num in sample['Background']['Background']['Runs']
        ])
        if len(container_bg) == 0:
            container_bg = None

    van['Runs'] = expand_ints(van['Runs'])
    van_scans = ','.join(
        [facility_file_format % (instr, num) for num in van['Runs']])

    van_bg_scans = None
    if 'Background' in van:
        van_bg_scans = van['Background']['Runs']
        van_bg_scans = expand_ints(van_bg_scans)
        van_bg_scans = ','.join(
            [facility_file_format % (instr, num) for num in van_bg_scans])

    # Override Nexus file basename with Filenames if present
    if "Filenames" in sample:
        sam_scans = ','.join(sample["Filenames"])
    if "Filenames" in sample['Background']:
        container_scans = ','.join(sample['Background']["Filenames"])
    if "Background" in sample['Background']:
        if "Filenames" in sample['Background']['Background']:
            container_bg = ','.join(
                sample['Background']['Background']['Filenames'])
    if "Filenames" in van:
        van_scans = ','.join(van["Filenames"])
    if "Background" in van:
        if "Filenames" in van['Background']:
            van_bg_scans = ','.join(van['Background']["Filenames"])

    # Output nexus filename
    nexus_filename = title + '.nxs'
    try:
        os.remove(nexus_filename)
    except OSError:
        pass

    # Get sample corrections
    sam_abs_corr = sample.get("AbsorptionCorrection", None)
    sam_ms_corr = sample.get("MultipleScatteringCorrection", None)
    sam_inelastic_corr = SetInelasticCorrection(
        sample.get('InelasticCorrection', None))

    # Warn about having absorption correction and multiple scat correction set
    if sam_abs_corr and sam_ms_corr:
        log.warning(MS_AND_ABS_CORR_WARNING)

    # Compute the absorption correction on the sample if it was provided
    sam_abs_ws = ''
    con_abs_ws = ''
    if sam_abs_corr:
        msg = "Applying '{}' absorption correction to sample"
        log.notice(msg.format(sam_abs_corr["Type"]))
        sam_abs_ws, con_abs_ws = create_absorption_wksp(
            sam_scans, sam_abs_corr["Type"], sam_geo_dict, sam_mat_dict,
            sam_env_dict, **config)

    # Get vanadium corrections
    van_mass_density = van.get('MassDensity', van_mass_density)
    van_packing_fraction = van.get('PackingFraction', van_packing_fraction)
    van_abs_corr = van.get("AbsorptionCorrection", {"Type": None})
    van_ms_corr = van.get("MultipleScatteringCorrection", {"Type": None})
    van_inelastic_corr = SetInelasticCorrection(
        van.get('InelasticCorrection', None))

    # Warn about having absorption correction and multiple scat correction set
    if van_abs_corr["Type"] and van_ms_corr["Type"]:
        log.warning(MS_AND_ABS_CORR_WARNING)

    # Compute the absorption correction for the vanadium if provided
    van_abs_corr_ws = ''
    if van_abs_corr:
        msg = "Applying '{}' absorption correction to vanadium"
        log.notice(msg.format(van_abs_corr["Type"]))
        van_abs_corr_ws, van_con_ws = create_absorption_wksp(
            van_scans, van_abs_corr["Type"], van_geo_dict, van_mat_dict,
            **config)

    alignAndFocusArgs = dict()
    alignAndFocusArgs['CalFilename'] = config['Calibration']['Filename']
    # alignAndFocusArgs['GroupFilename'] don't use
    # alignAndFocusArgs['Params'] = "0.,0.02,40."
    alignAndFocusArgs['ResampleX'] = -6000
    alignAndFocusArgs['Dspacing'] = False
    alignAndFocusArgs['PreserveEvents'] = False
    alignAndFocusArgs['MaxChunkSize'] = 8
    alignAndFocusArgs['CacheDir'] = os.path.abspath(cache_dir)

    # Get any additional AlignAndFocusArgs from JSON input
    if "AlignAndFocusArgs" in config:
        otherArgs = config["AlignAndFocusArgs"]
        alignAndFocusArgs.update(otherArgs)

    # Setup grouping
    output_grouping = False
    grp_wksp = "wksp_output_group"

    if grouping:
        if 'Initial' in grouping:
            if grouping['Initial'] and not grouping['Initial'] == u'':
                alignAndFocusArgs['GroupFilename'] = grouping['Initial']
        if 'Output' in grouping:
            if grouping['Output'] and not grouping['Output'] == u'':
                output_grouping = True
                LoadDetectorsGroupingFile(InputFile=grouping['Output'],
                                          OutputWorkspace=grp_wksp)
    # If no output grouping specified, create it with Calibration Grouping
    if not output_grouping:
        LoadDiffCal(alignAndFocusArgs['CalFilename'],
                    InstrumentName=instr,
                    WorkspaceName=grp_wksp.replace('_group', ''),
                    MakeGroupingWorkspace=True,
                    MakeCalWorkspace=False,
                    MakeMaskWorkspace=False)

    # Setup the 6 bank method if no grouping specified
    if not grouping:
        CreateGroupingWorkspace(InstrumentName=instr,
                                GroupDetectorsBy='Group',
                                OutputWorkspace=grp_wksp)
        alignAndFocusArgs['GroupingWorkspace'] = grp_wksp

    # TODO take out the RecalculatePCharge in the future once tested
    # Load Sample
    print("#-----------------------------------#")
    print("# Sample")
    print("#-----------------------------------#")
    sam_wksp = load('sample', sam_scans, sam_geometry, sam_material,
                    sam_mass_density, sam_abs_ws, **alignAndFocusArgs)
    sample_title = "sample_and_container"
    save_banks(InputWorkspace=sam_wksp,
               Filename=nexus_filename,
               Title=sample_title,
               OutputDir=OutputDir,
               GroupingWorkspace=grp_wksp,
               Binning=binning)

    sam_molecular_mass = mtd[sam_wksp].sample().getMaterial(
    ).relativeMolecularMass()
    natoms = getNumberAtoms(sam_packing_fraction,
                            sam_mass_density,
                            sam_molecular_mass,
                            Geometry=sam_geometry)

    # Load Sample Container
    print("#-----------------------------------#")
    print("# Sample Container")
    print("#-----------------------------------#")
    container = load('container',
                     container_scans,
                     absorption_wksp=con_abs_ws,
                     **alignAndFocusArgs)
    save_banks(InputWorkspace=container,
               Filename=nexus_filename,
               Title=container,
               OutputDir=OutputDir,
               GroupingWorkspace=grp_wksp,
               Binning=binning)

    # Load Sample Container Background

    if container_bg is not None:
        print("#-----------------------------------#")
        print("# Sample Container's Background")
        print("#-----------------------------------#")
        container_bg = load('container_background', container_bg,
                            **alignAndFocusArgs)
        save_banks(InputWorkspace=container_bg,
                   Filename=nexus_filename,
                   Title=container_bg,
                   OutputDir=OutputDir,
                   GroupingWorkspace=grp_wksp,
                   Binning=binning)

    # Load Vanadium

    print("#-----------------------------------#")
    print("# Vanadium")
    print("#-----------------------------------#")
    van_wksp = load('vanadium', van_scans, van_geometry, van_material,
                    van_mass_density, van_abs_corr_ws, **alignAndFocusArgs)
    vanadium_title = "vanadium_and_background"

    save_banks(InputWorkspace=van_wksp,
               Filename=nexus_filename,
               Title=vanadium_title,
               OutputDir=OutputDir,
               GroupingWorkspace=grp_wksp,
               Binning=binning)

    van_material = mtd[van_wksp].sample().getMaterial()
    van_molecular_mass = van_material.relativeMolecularMass()
    nvan_atoms = getNumberAtoms(1.0,
                                van_mass_density,
                                van_molecular_mass,
                                Geometry=van_geometry)

    print("Sample natoms:", natoms)
    print("Vanadium natoms:", nvan_atoms)
    print("Vanadium natoms / Sample natoms:", nvan_atoms / natoms)

    # Load Vanadium Background
    van_bg = None
    if van_bg_scans is not None:
        print("#-----------------------------------#")
        print("# Vanadium Background")
        print("#-----------------------------------#")
        van_bg = load('vanadium_background', van_bg_scans, **alignAndFocusArgs)
        vanadium_bg_title = "vanadium_background"
        save_banks(InputWorkspace=van_bg,
                   Filename=nexus_filename,
                   Title=vanadium_bg_title,
                   OutputDir=OutputDir,
                   GroupingWorkspace=grp_wksp,
                   Binning=binning)

    # Load Instrument Characterizations
    if characterizations:
        PDDetermineCharacterizations(
            InputWorkspace=sam_wksp,
            Characterizations='characterizations',
            ReductionProperties='__snspowderreduction')
        propMan = PropertyManagerDataService.retrieve('__snspowderreduction')
        qmax = 2. * np.pi / propMan['d_min'].value
        qmin = 2. * np.pi / propMan['d_max'].value
        for a, b in zip(qmin, qmax):
            print('Qrange:', a, b)
        # TODO: Add when we apply Qmin, Qmax cropping
        # mask_info = generate_cropping_table(qmin, qmax)

    # STEP 1: Subtract Backgrounds

    sam_raw = 'sam_raw'
    CloneWorkspace(InputWorkspace=sam_wksp,
                   OutputWorkspace=sam_raw)  # for later

    container_raw = 'container_raw'
    CloneWorkspace(InputWorkspace=container,
                   OutputWorkspace=container_raw)  # for later

    if van_bg is not None:
        RebinToWorkspace(WorkspaceToRebin=van_bg,
                         WorkspaceToMatch=van_wksp,
                         OutputWorkspace=van_bg)
        Minus(LHSWorkspace=van_wksp,
              RHSWorkspace=van_bg,
              OutputWorkspace=van_wksp)

    RebinToWorkspace(WorkspaceToRebin=container,
                     WorkspaceToMatch=sam_wksp,
                     OutputWorkspace=container)
    Minus(LHSWorkspace=sam_wksp,
          RHSWorkspace=container,
          OutputWorkspace=sam_wksp)

    if container_bg is not None:
        RebinToWorkspace(WorkspaceToRebin=container_bg,
                         WorkspaceToMatch=container,
                         OutputWorkspace=container_bg)
        Minus(LHSWorkspace=container,
              RHSWorkspace=container_bg,
              OutputWorkspace=container)

    for wksp in [container, van_wksp, sam_wksp]:
        ConvertUnits(InputWorkspace=wksp,
                     OutputWorkspace=wksp,
                     Target="MomentumTransfer",
                     EMode="Elastic")
    container_title = "container_minus_back"
    vanadium_title = "vanadium_minus_back"
    sample_title = "sample_minus_back"
    save_banks(InputWorkspace=container,
               Filename=nexus_filename,
               Title=container_title,
               OutputDir=OutputDir,
               GroupingWorkspace=grp_wksp,
               Binning=binning)
    save_banks(InputWorkspace=van_wksp,
               Filename=nexus_filename,
               Title=vanadium_title,
               OutputDir=OutputDir,
               GroupingWorkspace=grp_wksp,
               Binning=binning)
    save_banks(InputWorkspace=sam_wksp,
               Filename=nexus_filename,
               Title=sample_title,
               OutputDir=OutputDir,
               GroupingWorkspace=grp_wksp,
               Binning=binning)

    # STEP 2.0: Prepare vanadium as normalization calibrant

    # Multiple-Scattering and Absorption (Steps 2-4) for Vanadium

    van_corrected = 'van_corrected'
    ConvertUnits(InputWorkspace=van_wksp,
                 OutputWorkspace=van_corrected,
                 Target="Wavelength",
                 EMode="Elastic")

    if "Type" in van_abs_corr:
        if van_abs_corr['Type'] == 'Carpenter' \
                or van_ms_corr['Type'] == 'Carpenter':
            CarpenterSampleCorrection(
                InputWorkspace=van_corrected,
                OutputWorkspace=van_corrected,
                CylinderSampleRadius=van['Geometry']['Radius'])
        elif van_abs_corr['Type'] == 'Mayers' \
                or van_ms_corr['Type'] == 'Mayers':
            if van_ms_corr['Type'] == 'Mayers':
                MayersSampleCorrection(InputWorkspace=van_corrected,
                                       OutputWorkspace=van_corrected,
                                       MultipleScattering=True)
            else:
                MayersSampleCorrection(InputWorkspace=van_corrected,
                                       OutputWorkspace=van_corrected,
                                       MultipleScattering=False)
        else:
            print("NO VANADIUM absorption or multiple scattering!")
    else:
        CloneWorkspace(InputWorkspace=van_corrected,
                       OutputWorkspace=van_corrected)

    ConvertUnits(InputWorkspace=van_corrected,
                 OutputWorkspace=van_corrected,
                 Target='MomentumTransfer',
                 EMode='Elastic')
    vanadium_title += "_ms_abs_corrected"
    save_banks(InputWorkspace=van_corrected,
               Filename=nexus_filename,
               Title=vanadium_title,
               OutputDir=OutputDir,
               GroupingWorkspace=grp_wksp,
               Binning=binning)
    save_banks(InputWorkspace=van_corrected,
               Filename=nexus_filename,
               Title=vanadium_title + "_with_peaks",
               OutputDir=OutputDir,
               GroupingWorkspace=grp_wksp,
               Binning=binning)

    # TODO subtract self-scattering of vanadium (According to Eq. 7 of Howe,
    # McGreevey, and Howells, JPCM, 1989)

    # Smooth Vanadium (strip peaks plus smooth)

    ConvertUnits(InputWorkspace=van_corrected,
                 OutputWorkspace=van_corrected,
                 Target='dSpacing',
                 EMode='Elastic')

    # After StripVanadiumPeaks, the workspace goes from EventWorkspace ->
    # Workspace2D
    StripVanadiumPeaks(InputWorkspace=van_corrected,
                       OutputWorkspace=van_corrected,
                       BackgroundType='Quadratic')
    ConvertUnits(InputWorkspace=van_corrected,
                 OutputWorkspace=van_corrected,
                 Target='MomentumTransfer',
                 EMode='Elastic')
    vanadium_title += '_peaks_stripped'
    save_banks(InputWorkspace=van_corrected,
               Filename=nexus_filename,
               Title=vanadium_title,
               OutputDir=OutputDir,
               GroupingWorkspace=grp_wksp,
               Binning=binning)

    ConvertUnits(InputWorkspace=van_corrected,
                 OutputWorkspace=van_corrected,
                 Target='TOF',
                 EMode='Elastic')

    FFTSmooth(InputWorkspace=van_corrected,
              OutputWorkspace=van_corrected,
              Filter="Butterworth",
              Params='20,2',
              IgnoreXBins=True,
              AllSpectra=True)

    ConvertUnits(InputWorkspace=van_corrected,
                 OutputWorkspace=van_corrected,
                 Target='MomentumTransfer',
                 EMode='Elastic')

    vanadium_title += '_smoothed'
    save_banks(InputWorkspace=van_corrected,
               Filename=nexus_filename,
               Title=vanadium_title,
               OutputDir=OutputDir,
               GroupingWorkspace=grp_wksp,
               Binning=binning)

    # Inelastic correction
    if van_inelastic_corr['Type'] == "Placzek":
        van_scan = van['Runs'][0]
        van_incident_wksp = 'van_incident_wksp'
        van_inelastic_opts = van['InelasticCorrection']
        lambda_binning_fit = van_inelastic_opts['LambdaBinningForFit']
        lambda_binning_calc = van_inelastic_opts['LambdaBinningForCalc']
        print('van_scan:', van_scan)
        GetIncidentSpectrumFromMonitor(Filename=facility_file_format %
                                       (instr, van_scan),
                                       OutputWorkspace=van_incident_wksp)

        fit_type = van['InelasticCorrection']['FitSpectrumWith']
        FitIncidentSpectrum(InputWorkspace=van_incident_wksp,
                            OutputWorkspace=van_incident_wksp,
                            FitSpectrumWith=fit_type,
                            BinningForFit=lambda_binning_fit,
                            BinningForCalc=lambda_binning_calc,
                            PlotDiagnostics=False)

        van_placzek = 'van_placzek'

        SetSample(InputWorkspace=van_incident_wksp,
                  Material={
                      'ChemicalFormula': str(van_material),
                      'SampleMassDensity': str(van_mass_density)
                  })

        CalculatePlaczekSelfScattering(IncidentWorkspace=van_incident_wksp,
                                       ParentWorkspace=van_corrected,
                                       OutputWorkspace=van_placzek,
                                       L1=19.5,
                                       L2=alignAndFocusArgs['L2'],
                                       Polar=alignAndFocusArgs['Polar'])

        ConvertToHistogram(InputWorkspace=van_placzek,
                           OutputWorkspace=van_placzek)

        # Save before rebin in Q
        for wksp in [van_placzek, van_corrected]:
            ConvertUnits(InputWorkspace=wksp,
                         OutputWorkspace=wksp,
                         Target='MomentumTransfer',
                         EMode='Elastic')

            Rebin(InputWorkspace=wksp,
                  OutputWorkspace=wksp,
                  Params=binning,
                  PreserveEvents=True)

        save_banks(InputWorkspace=van_placzek,
                   Filename=nexus_filename,
                   Title="vanadium_placzek",
                   OutputDir=OutputDir,
                   GroupingWorkspace=grp_wksp,
                   Binning=binning)

        # Rebin in Wavelength
        for wksp in [van_placzek, van_corrected]:
            ConvertUnits(InputWorkspace=wksp,
                         OutputWorkspace=wksp,
                         Target='Wavelength',
                         EMode='Elastic')
            Rebin(InputWorkspace=wksp,
                  OutputWorkspace=wksp,
                  Params=lambda_binning_calc,
                  PreserveEvents=True)

        # Save after rebin in Q
        for wksp in [van_placzek, van_corrected]:
            ConvertUnits(InputWorkspace=wksp,
                         OutputWorkspace=wksp,
                         Target='MomentumTransfer',
                         EMode='Elastic')

        # Subtract correction in Wavelength
        for wksp in [van_placzek, van_corrected]:
            ConvertUnits(InputWorkspace=wksp,
                         OutputWorkspace=wksp,
                         Target='Wavelength',
                         EMode='Elastic')
            if not mtd[wksp].isDistribution():
                ConvertToDistribution(wksp)

        Minus(LHSWorkspace=van_corrected,
              RHSWorkspace=van_placzek,
              OutputWorkspace=van_corrected)

        # Save after subtraction
        for wksp in [van_placzek, van_corrected]:
            ConvertUnits(InputWorkspace=wksp,
                         OutputWorkspace=wksp,
                         Target='MomentumTransfer',
                         EMode='Elastic')

        vanadium_title += '_placzek_corrected'
        save_banks(InputWorkspace=van_corrected,
                   Filename=nexus_filename,
                   Title=vanadium_title,
                   OutputDir=OutputDir,
                   GroupingWorkspace=grp_wksp,
                   Binning=binning)

    ConvertUnits(InputWorkspace=van_corrected,
                 OutputWorkspace=van_corrected,
                 Target='MomentumTransfer',
                 EMode='Elastic')

    SetUncertainties(InputWorkspace=van_corrected,
                     OutputWorkspace=van_corrected,
                     SetError='zero')

    # STEP 2.1: Normalize by Vanadium

    wksp_list = [sam_wksp, sam_raw, van_corrected]
    for name in wksp_list:
        ConvertUnits(InputWorkspace=name,
                     OutputWorkspace=name,
                     Target='MomentumTransfer',
                     EMode='Elastic',
                     ConvertFromPointData=False)

        Rebin(InputWorkspace=name,
              OutputWorkspace=name,
              Params=binning,
              PreserveEvents=True)

    # Save the sample - back / normalized
    Divide(LHSWorkspace=sam_wksp,
           RHSWorkspace=van_corrected,
           OutputWorkspace=sam_wksp)

    sample_title += "_normalized"
    save_banks(InputWorkspace=sam_wksp,
               Filename=nexus_filename,
               Title=sample_title,
               OutputDir=OutputDir,
               GroupingWorkspace=grp_wksp,
               Binning=binning)

    # Save the sample / normalized (ie no background subtraction)
    Divide(LHSWorkspace=sam_raw,
           RHSWorkspace=van_corrected,
           OutputWorkspace=sam_raw)

    save_banks(InputWorkspace=sam_raw,
               Filename=nexus_filename,
               Title="sample_normalized",
               OutputDir=OutputDir,
               GroupingWorkspace=grp_wksp,
               Binning=binning)

    # Output an initial I(Q) for sample
    iq_filename = title + '_initial_iofq_banks.nxs'
    save_banks(InputWorkspace=sam_wksp,
               Filename=iq_filename,
               Title="IQ_banks",
               OutputDir=OutputDir,
               GroupingWorkspace=grp_wksp,
               Binning=binning)

    wksp_list = [container, container_raw, van_corrected]
    if container_bg is not None:
        wksp_list.append(container_bg)
    if van_bg is not None:
        wksp_list.append(van_bg)

    for name in wksp_list:
        ConvertUnits(InputWorkspace=name,
                     OutputWorkspace=name,
                     Target='MomentumTransfer',
                     EMode='Elastic',
                     ConvertFromPointData=False)

        Rebin(InputWorkspace=name,
              OutputWorkspace=name,
              Params=binning,
              PreserveEvents=True)

    # Save the container - container_background / normalized
    Divide(LHSWorkspace=container,
           RHSWorkspace=van_corrected,
           OutputWorkspace=container)

    container_title += '_normalized'
    save_banks(InputWorkspace=container,
               Filename=nexus_filename,
               Title=container_title,
               OutputDir=OutputDir,
               GroupingWorkspace=grp_wksp,
               Binning=binning)

    # Save the container / normalized (ie no background subtraction)
    Divide(LHSWorkspace=container_raw,
           RHSWorkspace=van_corrected,
           OutputWorkspace=container_raw)

    save_banks(InputWorkspace=container_raw,
               Filename=nexus_filename,
               Title="container_normalized",
               OutputDir=OutputDir,
               GroupingWorkspace=grp_wksp,
               Binning=binning)

    # Save the container_background / normalized
    if container_bg is not None:
        Divide(LHSWorkspace=container_bg,
               RHSWorkspace=van_corrected,
               OutputWorkspace=container_bg)

        container_bg_title = "container_back_normalized"
        save_banks(InputWorkspace=container_bg,
                   Filename=nexus_filename,
                   Title=container_bg_title,
                   OutputDir=OutputDir,
                   GroupingWorkspace=grp_wksp,
                   Binning=binning)

    # Save the vanadium_background / normalized
    if van_bg is not None:
        Divide(LHSWorkspace=van_bg,
               RHSWorkspace=van_corrected,
               OutputWorkspace=van_bg)

        vanadium_bg_title += "_normalized"
        save_banks(InputWorkspace=van_bg,
                   Filename=nexus_filename,
                   Title=vanadium_bg_title,
                   OutputDir=OutputDir,
                   GroupingWorkspace=grp_wksp,
                   Binning=binning)

    # STEP 3 & 4: Subtract multiple scattering and apply absorption correction

    ConvertUnits(InputWorkspace=sam_wksp,
                 OutputWorkspace=sam_wksp,
                 Target="Wavelength",
                 EMode="Elastic")

    sam_corrected = 'sam_corrected'
    if sam_abs_corr and sam_ms_corr:
        if sam_abs_corr['Type'] == 'Carpenter' \
                or sam_ms_corr['Type'] == 'Carpenter':
            CarpenterSampleCorrection(
                InputWorkspace=sam_wksp,
                OutputWorkspace=sam_corrected,
                CylinderSampleRadius=sample['Geometry']['Radius'])
        elif sam_abs_corr['Type'] == 'Mayers' \
                or sam_ms_corr['Type'] == 'Mayers':
            if sam_ms_corr['Type'] == 'Mayers':
                MayersSampleCorrection(InputWorkspace=sam_wksp,
                                       OutputWorkspace=sam_corrected,
                                       MultipleScattering=True)
            else:
                MayersSampleCorrection(InputWorkspace=sam_wksp,
                                       OutputWorkspace=sam_corrected,
                                       MultipleScattering=False)
        else:
            print("NO SAMPLE absorption or multiple scattering!")
            CloneWorkspace(InputWorkspace=sam_wksp,
                           OutputWorkspace=sam_corrected)

        ConvertUnits(InputWorkspace=sam_corrected,
                     OutputWorkspace=sam_corrected,
                     Target='MomentumTransfer',
                     EMode='Elastic')

        sample_title += "_ms_abs_corrected"
        save_banks(InputWorkspace=sam_corrected,
                   Filename=nexus_filename,
                   Title=sample_title,
                   OutputDir=OutputDir,
                   GroupingWorkspace=grp_wksp,
                   Binning=binning)
    else:
        CloneWorkspace(InputWorkspace=sam_wksp, OutputWorkspace=sam_corrected)

    # STEP 5: Divide by number of atoms in sample

    mtd[sam_corrected] = (nvan_atoms / natoms) * mtd[sam_corrected]
    ConvertUnits(InputWorkspace=sam_corrected,
                 OutputWorkspace=sam_corrected,
                 Target='MomentumTransfer',
                 EMode='Elastic')

    sample_title += "_norm_by_atoms"
    save_banks(InputWorkspace=sam_corrected,
               Filename=nexus_filename,
               Title=sample_title,
               OutputDir=OutputDir,
               GroupingWorkspace=grp_wksp,
               Binning=binning)

    # STEP 6: Divide by total scattering length squared = total scattering
    # cross-section over 4 * pi
    van_material = mtd[van_corrected].sample().getMaterial()
    sigma_v = van_material.totalScatterXSection()
    prefactor = (sigma_v / (4. * np.pi))
    msg = "Total scattering cross-section of Vanadium:{} sigma_v / 4*pi: {}"
    print(msg.format(sigma_v, prefactor))

    mtd[sam_corrected] = prefactor * mtd[sam_corrected]
    sample_title += '_multiply_by_vanSelfScat'
    save_banks(InputWorkspace=sam_corrected,
               Filename=nexus_filename,
               Title=sample_title,
               OutputDir=OutputDir,
               GroupingWorkspace=grp_wksp,
               Binning=binning)

    # STEP 7: Inelastic correction
    ConvertUnits(InputWorkspace=sam_corrected,
                 OutputWorkspace=sam_corrected,
                 Target='Wavelength',
                 EMode='Elastic')

    if sam_inelastic_corr['Type'] == "Placzek":
        if sam_material is None:
            error = "For Placzek correction, must specifiy a sample material."
            raise Exception(error)
        for sam_scan in sample['Runs']:
            sam_incident_wksp = 'sam_incident_wksp'
            sam_inelastic_opts = sample['InelasticCorrection']
            lambda_binning_fit = sam_inelastic_opts['LambdaBinningForFit']
            lambda_binning_calc = sam_inelastic_opts['LambdaBinningForCalc']
            GetIncidentSpectrumFromMonitor(Filename=facility_file_format %
                                           (instr, sam_scan),
                                           OutputWorkspace=sam_incident_wksp)

            fit_type = sample['InelasticCorrection']['FitSpectrumWith']
            FitIncidentSpectrum(InputWorkspace=sam_incident_wksp,
                                OutputWorkspace=sam_incident_wksp,
                                FitSpectrumWith=fit_type,
                                BinningForFit=lambda_binning_fit,
                                BinningForCalc=lambda_binning_calc)

            sam_placzek = 'sam_placzek'
            SetSample(InputWorkspace=sam_incident_wksp,
                      Material={
                          'ChemicalFormula': str(sam_material),
                          'SampleMassDensity': str(sam_mass_density)
                      })
            CalculatePlaczekSelfScattering(IncidentWorkspace=sam_incident_wksp,
                                           ParentWorkspace=sam_corrected,
                                           OutputWorkspace=sam_placzek,
                                           L1=19.5,
                                           L2=alignAndFocusArgs['L2'],
                                           Polar=alignAndFocusArgs['Polar'])

            ConvertToHistogram(InputWorkspace=sam_placzek,
                               OutputWorkspace=sam_placzek)

        # Save before rebin in Q
        for wksp in [sam_placzek, sam_corrected]:
            ConvertUnits(InputWorkspace=wksp,
                         OutputWorkspace=wksp,
                         Target='MomentumTransfer',
                         EMode='Elastic')

            Rebin(InputWorkspace=wksp,
                  OutputWorkspace=wksp,
                  Params=binning,
                  PreserveEvents=True)

        save_banks(InputWorkspace=sam_placzek,
                   Filename=nexus_filename,
                   Title="sample_placzek",
                   OutputDir=OutputDir,
                   GroupingWorkspace=grp_wksp,
                   Binning=binning)

        # Save after rebin in Q
        for wksp in [sam_placzek, sam_corrected]:
            ConvertUnits(InputWorkspace=wksp,
                         OutputWorkspace=wksp,
                         Target='MomentumTransfer',
                         EMode='Elastic')

        Minus(LHSWorkspace=sam_corrected,
              RHSWorkspace=sam_placzek,
              OutputWorkspace=sam_corrected)

        # Save after subtraction
        for wksp in [sam_placzek, sam_corrected]:
            ConvertUnits(InputWorkspace=wksp,
                         OutputWorkspace=wksp,
                         Target='MomentumTransfer',
                         EMode='Elastic')

        sample_title += '_placzek_corrected'
        save_banks(InputWorkspace=sam_corrected,
                   Filename=nexus_filename,
                   Title=sample_title,
                   OutputDir=OutputDir,
                   GroupingWorkspace=grp_wksp,
                   Binning=binning)

    # STEP 7: Output spectrum

    # TODO Since we already went from Event -> 2D workspace, can't use this
    # anymore
    print('sam:', mtd[sam_corrected].id())
    print('van:', mtd[van_corrected].id())
    if alignAndFocusArgs['PreserveEvents']:
        CompressEvents(InputWorkspace=sam_corrected,
                       OutputWorkspace=sam_corrected)

    # F(Q) bank-by-bank Section
    fq_banks_wksp = "FQ_banks_wksp"
    CloneWorkspace(InputWorkspace=sam_corrected, OutputWorkspace=fq_banks_wksp)
    # TODO: Add the following when implemented - FQ_banks = 'FQ_banks'

    # S(Q) bank-by-bank Section
    material = mtd[sam_corrected].sample().getMaterial()
    if material.name() is None or len(material.name().strip()) == 0:
        raise RuntimeError('Sample material was not set')
    bcoh_avg_sqrd = material.cohScatterLength() * material.cohScatterLength()
    btot_sqrd_avg = material.totalScatterLengthSqrd()
    laue_monotonic_diffuse_scat = btot_sqrd_avg / bcoh_avg_sqrd
    sq_banks_wksp = 'SQ_banks_wksp'
    CloneWorkspace(InputWorkspace=sam_corrected, OutputWorkspace=sq_banks_wksp)

    # TODO: Add the following when implemented
    '''
    SQ_banks = (1. / bcoh_avg_sqrd) * \
        mtd[sq_banks_wksp] - laue_monotonic_diffuse_scat + 1.
    '''

    # Save S(Q) and F(Q) to diagnostics NeXus file
    save_banks(InputWorkspace=fq_banks_wksp,
               Filename=nexus_filename,
               Title="FQ_banks",
               OutputDir=OutputDir,
               GroupingWorkspace=grp_wksp,
               Binning=binning)

    save_banks(InputWorkspace=sq_banks_wksp,
               Filename=nexus_filename,
               Title="SQ_banks",
               OutputDir=OutputDir,
               GroupingWorkspace=grp_wksp,
               Binning=binning)

    # Output a main S(Q) and F(Q) file
    fq_filename = title + '_fofq_banks_corrected.nxs'
    save_banks(InputWorkspace=fq_banks_wksp,
               Filename=fq_filename,
               Title="FQ_banks",
               OutputDir=OutputDir,
               GroupingWorkspace=grp_wksp,
               Binning=binning)

    sq_filename = title + '_sofq_banks_corrected.nxs'
    save_banks(InputWorkspace=sq_banks_wksp,
               Filename=sq_filename,
               Title="SQ_banks",
               OutputDir=OutputDir,
               GroupingWorkspace=grp_wksp,
               Binning=binning)

    # Print log information
    print("<b>^2:", bcoh_avg_sqrd)
    print("<b^2>:", btot_sqrd_avg)
    print("Laue term:", laue_monotonic_diffuse_scat)
    print("sample total xsection:",
          mtd[sam_corrected].sample().getMaterial().totalScatterXSection())
    print("vanadium total xsection:",
          mtd[van_corrected].sample().getMaterial().totalScatterXSection())

    # Output Bragg Diffraction
    ConvertUnits(InputWorkspace=sam_corrected,
                 OutputWorkspace=sam_corrected,
                 Target="TOF",
                 EMode="Elastic")

    ConvertToHistogram(InputWorkspace=sam_corrected,
                       OutputWorkspace=sam_corrected)

    xmin, xmax = get_each_spectra_xmin_xmax(mtd[sam_corrected])

    CropWorkspaceRagged(InputWorkspace=sam_corrected,
                        OutputWorkspace=sam_corrected,
                        Xmin=xmin,
                        Xmax=xmax)

    xmin_rebin = min(xmin)
    xmax_rebin = max(xmax)
    tof_binning = "{xmin},-0.01,{xmax}".format(xmin=xmin_rebin,
                                               xmax=xmax_rebin)

    Rebin(InputWorkspace=sam_corrected,
          OutputWorkspace=sam_corrected,
          Params=tof_binning)

    SaveGSS(InputWorkspace=sam_corrected,
            Filename=os.path.join(os.path.abspath(OutputDir), title + ".gsa"),
            SplitFiles=False,
            Append=False,
            MultiplyByBinWidth=True,
            Format="SLOG",
            ExtendedHeader=True)

    return mtd[sam_corrected]
Exemple #8
0
 def _convertToDistribution(self, mainWS):
     """Convert the workspace into a distribution."""
     ConvertToDistribution(Workspace=mainWS,
                           EnableLogging=self._subalgLogging)
     return mainWS
Exemple #9
0
def save_banks(InputWorkspace,
               Filename,
               Title,
               OutputDir,
               Binning=None,
               GroupingWorkspace=None):
    """
    Saves input workspace to processed NeXus file in specified
    output directory with optional rebinning and grouping
    (to coarsen) the output in a bank-by-bank manner. Mainly
    wraps Mantid `SaveNexusProcessed` algorithm.

    :param InputWorkspace: Mantid workspace to save out
    :type InputWorkspace: MatrixWorkspace
    :param Filename: Filename to save output
    :type Filename: str
    :param Title: A title to describe the saved workspace
    :type Title: str
    :param OutputDir: Output directory to save the processed NeXus file
    :type OutputDir: path str
    :param Binning: Optional rebinning of event workspace.
                    See `Rebin` in Mantid for options
    :type Binning: dbl list
    :param GroupingWorkspace: A workspace with grouping
                              information for the output spectra
    :type GroupWorkspace: GroupWorkspace
    """

    # Make a local clone
    CloneWorkspace(InputWorkspace=InputWorkspace, OutputWorkspace="__tmp")
    tmp_wksp = mtd["__tmp"]

    # Rebin if requested
    if Binning:
        tmp_wksp = Rebin(InputWorkspace=tmp_wksp,
                         Params=Binning,
                         PreserveEvents=True)

    # Convert to distributions to remove bin width dependence
    yunit = tmp_wksp.YUnit()
    if yunit == "Counts":
        try:
            ConvertToDistribution(tmp_wksp)
        except BaseException:
            pass

    # Output to desired level of grouping
    isEventWksp = isinstance(tmp_wksp, IEventWorkspace)
    if isEventWksp and GroupingWorkspace and yunit == "Counts":
        tmp_wksp = DiffractionFocussing(InputWorkspace=tmp_wksp,
                                        GroupingWorkspace=GroupingWorkspace,
                                        PreserveEvents=False)

    # Save out wksp to file
    filename = os.path.join(os.path.abspath(OutputDir), Filename)
    SaveNexusProcessed(InputWorkspace=tmp_wksp,
                       Filename=filename,
                       Title=Title,
                       Append=True,
                       PreserveEvents=False,
                       WorkspaceIndexList=range(
                           tmp_wksp.getNumberHistograms()))
    DeleteWorkspace(tmp_wksp)