Пример #1
0
def _run_focus(input_workspace,
               tof_output_name,
               vanadium_integration_ws,
               vanadium_curves_ws,
               df_kwarg,
               full_calib,
               region_calib):
    simple.NormaliseByCurrent(InputWorkspace=input_workspace, OutputWorkspace=input_workspace)
    input_workspace /= vanadium_integration_ws
    simple.ReplaceSpecialValues(InputWorkspace=input_workspace, OutputWorkspace=input_workspace, NaNValue=0,
                                InfinityValue=0)
    simple.ApplyDiffCal(InstrumentWorkspace=input_workspace, CalibrationWorkspace=full_calib)
    ws_d = simple.ConvertUnits(InputWorkspace=input_workspace, Target='dSpacing')
    focused_sample = simple.DiffractionFocussing(InputWorkspace=ws_d, **df_kwarg)
    curves_rebinned = simple.RebinToWorkspace(WorkspaceToRebin=vanadium_curves_ws, WorkspaceToMatch=focused_sample)
    normalised = simple.Divide(LHSWorkspace=focused_sample, RHSWorkspace=curves_rebinned,
                               AllowDifferentNumberSpectra=True)
    simple.ApplyDiffCal(InstrumentWorkspace=normalised, CalibrationWorkspace=region_calib)
    dspacing_output_name = tof_output_name + "_dSpacing"
    simple.CloneWorkspace(InputWorkspace=normalised, OutputWorkspace=dspacing_output_name)
    simple.ConvertUnits(InputWorkspace=normalised, OutputWorkspace=tof_output_name, Target='TOF')
    simple.DeleteWorkspace(curves_rebinned)
    simple.DeleteWorkspace(focused_sample)
    simple.DeleteWorkspace(normalised)
    simple.DeleteWorkspace(ws_d)
Пример #2
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def _focus_run_and_apply_roi_calibration(ws, calibration, ws_foc_name=None):
    if not ws_foc_name:
        ws_foc_name = ws.name(
        ) + "_" + FOCUSED_OUTPUT_WORKSPACE_NAME + calibration.get_foc_ws_suffix(
        )
    ws_foc = mantid.DiffractionFocussing(
        InputWorkspace=ws,
        OutputWorkspace=ws_foc_name,
        GroupingWorkspace=calibration.get_group_ws())
    mantid.ApplyDiffCal(InstrumentWorkspace=ws_foc, ClearCalibration=True)
    ws_foc = mantid.ConvertUnits(InputWorkspace=ws_foc,
                                 OutputWorkspace=ws_foc.name(),
                                 Target='TOF')
    mantid.ApplyDiffCal(
        InstrumentWorkspace=ws_foc,
        CalibrationWorkspace=calibration.get_calibration_table())
    ws_foc = mantid.ConvertUnits(InputWorkspace=ws_foc,
                                 OutputWorkspace=ws_foc.name(),
                                 Target='dSpacing')
    return ws_foc
Пример #3
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def adjust_calibration(calibration_runs, instrument, offset_file_name,
                       grouping_file_name, calibration_dir, rebin_1_params,
                       rebin_2_params, cross_correlate_params,
                       get_det_offset_params, original_cal):
    """
    Create a calibration file from (usually) a ceria run
    :param calibration_runs: Run number(s) for this run
    :param instrument: The GEM instrument object
    :param offset_file_name: Name of the file to write detector offset information to
    :param grouping_file_name: Name of grouping calibration file
    :param calibration_dir: Path to directory containing calibration information
    :param rebin_1_params: Parameters for the first rebin step (as a string in the usual format)
    :param rebin_2_params: Parameters for the second rebin step (as a string in the usual format)
    :param cross_correlate_params: Parameters for CrossCorrelate (as a dictionary PropertyName: PropertyValue)
    :param get_det_offset_params: Parameters for GetDetectorOffsets (as a dictionary PropertyName: PropertyValue)
    :param original_cal: path to calibration file to adjust
    """
    input_ws_list = common.load_current_normalised_ws_list(
        run_number_string=calibration_runs,
        instrument=instrument,
        input_batching=INPUT_BATCHING.Summed)

    input_ws = input_ws_list[0]
    mantid.ApplyDiffCal(InstrumentWorkspace=input_ws,
                        CalibrationFile=original_cal)
    input_ws = mantid.ConvertUnits(InputWorkspace=input_ws, Target="dSpacing")
    mantid.ApplyDiffCal(InstrumentWorkspace=input_ws, ClearCalibration=True)
    offset_file = os.path.join(calibration_dir, offset_file_name)
    focused = _calibration_processing(calibration_dir, calibration_runs,
                                      cross_correlate_params,
                                      get_det_offset_params,
                                      grouping_file_name, input_ws, instrument,
                                      offset_file, rebin_1_params,
                                      rebin_2_params)
    _adjust_cal_file(original_cal, offset_file)
    return focused
Пример #4
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def _load_run_and_convert_to_dSpacing(filepath, instrument, full_calib):
    runno = path_handling.get_run_number_from_path(filepath, instrument)
    ws = mantid.Load(Filename=filepath, OutputWorkspace=str(runno))
    if ws.getRun().getProtonCharge() > 0:
        ws = mantid.NormaliseByCurrent(InputWorkspace=ws,
                                       OutputWorkspace=ws.name())
    else:
        logger.warning(f"Run {ws.name()} has invalid proton charge.")
        mantid.DeleteWorkspace(ws)
        return None
    mantid.ApplyDiffCal(InstrumentWorkspace=ws,
                        CalibrationWorkspace=full_calib)
    ws = mantid.ConvertUnits(InputWorkspace=ws,
                             OutputWorkspace=ws.name(),
                             Target='dSpacing')
    return ws
Пример #5
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    def focus_and_make_van_curves(ceria_d, vanadium_d, grouping_kwarg):
        # focus ceria
        focused_ceria = simple.DiffractionFocussing(InputWorkspace=ceria_d, **grouping_kwarg)
        simple.ApplyDiffCal(InstrumentWorkspace=focused_ceria, ClearCalibration=True)
        tof_focused = simple.ConvertUnits(InputWorkspace=focused_ceria, Target='TOF')

        # focus van data
        focused_van = simple.DiffractionFocussing(InputWorkspace=vanadium_d, **grouping_kwarg)

        background_van = simple.EnggEstimateFocussedBackground(InputWorkspace=focused_van, NIterations='15',
                                                               XWindow=0.03)

        simple.DeleteWorkspace(focused_ceria)
        simple.DeleteWorkspace(focused_van)

        return tof_focused, background_van
Пример #6
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def run_calibration(ceria_ws, calibration, full_instrument_cal_ws):
    """
    Creates Engineering calibration files with PDCalibration
    :param ceria_ws: The workspace with the ceria data.
    :param bank: The bank to crop to, both if none.
    :param calfile: The custom calibration file to crop to, not used if none.
    :param spectrum_numbers: The spectrum numbers to crop to, no crop if none.
    :return: dict containing calibrated diffractometer constants, and copy of the raw ceria workspace
    """

    # initial process of ceria ws
    mantid.NormaliseByCurrent(InputWorkspace=ceria_ws,
                              OutputWorkspace=ceria_ws)
    mantid.ApplyDiffCal(InstrumentWorkspace=ceria_ws,
                        CalibrationWorkspace=full_instrument_cal_ws)
    mantid.ConvertUnits(InputWorkspace=ceria_ws,
                        OutputWorkspace=ceria_ws,
                        Target='dSpacing')

    # get grouping workspace and focus
    grp_ws = calibration.get_group_ws()  # (creates if doesn't exist)
    focused_ceria = mantid.DiffractionFocussing(InputWorkspace=ceria_ws,
                                                GroupingWorkspace=grp_ws)
    mantid.ApplyDiffCal(
        InstrumentWorkspace=focused_ceria,
        ClearCalibration=True)  # DIFC of detector in middle of bank
    focused_ceria = mantid.ConvertUnits(InputWorkspace=focused_ceria,
                                        Target='TOF')

    # Run mantid.PDCalibration to fit peaks in TOF
    foc_name = focused_ceria.name(
    )  # PDCal invalidates ptr during rebin so keep track of ws name
    cal_table_name = "engggui_calibration_" + calibration.get_group_suffix()
    diag_ws_name = "diag_" + calibration.get_group_suffix()
    cal_table, diag_ws, mask = mantid.PDCalibration(
        InputWorkspace=foc_name,
        OutputCalibrationTable=cal_table_name,
        DiagnosticWorkspaces=diag_ws_name,
        PeakPositions=default_ceria_expected_peaks(final=True),
        TofBinning=[12000, -0.0003, 52000],
        PeakWindow=default_ceria_expected_peak_windows(final=True),
        MinimumPeakHeight=0.5,
        PeakFunction='BackToBackExponential',
        CalibrationParameters='DIFC+TZERO+DIFA',
        UseChiSq=True)
    mantid.ApplyDiffCal(InstrumentWorkspace=foc_name,
                        CalibrationWorkspace=cal_table)

    # warn user which spectra were unsuccessfully calibrated
    focused_ceria = ADS.retrieve(foc_name)
    masked_detIDs = mask.getMaskedDetectors()
    for ispec in range(focused_ceria.getNumberHistograms()):
        if focused_ceria.getSpectrum(
                ispec).getDetectorIDs()[0] in masked_detIDs:
            logger.warning(
                f'mantid.PDCalibration failed for spectrum index {ispec} - proceeding with uncalibrated DIFC.'
            )

    # store cal_table in calibration
    calibration.set_calibration_table(cal_table_name)

    return focused_ceria, cal_table, diag_ws
Пример #7
0
def _focus_one_ws(input_workspace,
                  run_number,
                  instrument,
                  perform_vanadium_norm,
                  absorb,
                  sample_details,
                  vanadium_path,
                  empty_can_subtraction_method,
                  paalman_pings_events_per_point=None):
    run_details = instrument._get_run_details(run_number_string=run_number)
    if perform_vanadium_norm:
        _test_splined_vanadium_exists(instrument, run_details)

    # Subtract empty instrument runs, as long as this run isn't an empty, user hasn't turned empty subtraction off, or
    # The user has not supplied a sample empty
    is_run_empty = common.runs_overlap(run_number, run_details.empty_inst_runs)
    summed_empty = None
    if not is_run_empty and instrument.should_subtract_empty_inst(
    ) and not run_details.sample_empty:
        if os.path.isfile(run_details.summed_empty_inst_file_path):
            logger.warning('Pre-summed empty instrument workspace found at ' +
                           run_details.summed_empty_inst_file_path)
            summed_empty = mantid.LoadNexus(
                Filename=run_details.summed_empty_inst_file_path)
        else:
            summed_empty = common.generate_summed_runs(
                empty_sample_ws_string=run_details.empty_inst_runs,
                instrument=instrument)
    elif run_details.sample_empty:
        scale_factor = 1.0
        if empty_can_subtraction_method != 'PaalmanPings':
            scale_factor = instrument._inst_settings.sample_empty_scale
        # Subtract a sample empty if specified ie empty can
        summed_empty = common.generate_summed_runs(
            empty_sample_ws_string=run_details.sample_empty,
            instrument=instrument,
            scale_factor=scale_factor)

    if absorb and empty_can_subtraction_method == 'PaalmanPings':
        if run_details.sample_empty:  # need summed_empty including container
            input_workspace = instrument._apply_paalmanpings_absorb_and_subtract_empty(
                workspace=input_workspace,
                summed_empty=summed_empty,
                sample_details=sample_details,
                paalman_pings_events_per_point=paalman_pings_events_per_point)
            # Crop to largest acceptable TOF range
            input_workspace = instrument._crop_raw_to_expected_tof_range(
                ws_to_crop=input_workspace)
        else:
            raise TypeError(
                "The PaalmanPings absorption method requires 'sample_empty' to be supplied."
            )
    else:
        if summed_empty:
            input_workspace = common.subtract_summed_runs(
                ws_to_correct=input_workspace, empty_sample=summed_empty)
        # Crop to largest acceptable TOF range
        input_workspace = instrument._crop_raw_to_expected_tof_range(
            ws_to_crop=input_workspace)

        if absorb:
            input_workspace = instrument._apply_absorb_corrections(
                run_details=run_details, ws_to_correct=input_workspace)
        else:
            # Set sample material if specified by the user
            if sample_details is not None:
                mantid.SetSample(
                    InputWorkspace=input_workspace,
                    Geometry=sample_details.generate_sample_geometry(),
                    Material=sample_details.generate_sample_material())

    # Align
    mantid.ApplyDiffCal(InstrumentWorkspace=input_workspace,
                        CalibrationFile=run_details.offset_file_path)
    aligned_ws = mantid.ConvertUnits(InputWorkspace=input_workspace,
                                     Target="dSpacing")

    solid_angle = instrument.get_solid_angle_corrections(
        run_details.vanadium_run_numbers, run_details)
    if solid_angle:
        aligned_ws = mantid.Divide(LHSWorkspace=aligned_ws,
                                   RHSWorkspace=solid_angle)
        mantid.DeleteWorkspace(solid_angle)

    # Focus the spectra into banks
    focused_ws = mantid.DiffractionFocussing(
        InputWorkspace=aligned_ws,
        GroupingFileName=run_details.grouping_file_path)

    instrument.apply_calibration_to_focused_data(focused_ws)

    calibrated_spectra = _apply_vanadium_corrections(
        instrument=instrument,
        input_workspace=focused_ws,
        perform_vanadium_norm=perform_vanadium_norm,
        vanadium_splines=vanadium_path)

    output_spectra = instrument._crop_banks_to_user_tof(calibrated_spectra)

    bin_widths = instrument._get_instrument_bin_widths()
    if bin_widths:
        # Reduce the bin width if required on this instrument
        output_spectra = common.rebin_workspace_list(
            workspace_list=output_spectra, bin_width_list=bin_widths)

    # Output
    d_spacing_group, tof_group = instrument._output_focused_ws(
        output_spectra, run_details=run_details)

    common.keep_single_ws_unit(d_spacing_group=d_spacing_group,
                               tof_group=tof_group,
                               unit_to_keep=instrument._get_unit_to_keep())

    # Tidy workspaces from Mantid
    common.remove_intermediate_workspace(input_workspace)
    common.remove_intermediate_workspace(aligned_ws)
    common.remove_intermediate_workspace(focused_ws)
    common.remove_intermediate_workspace(output_spectra)

    return d_spacing_group
Пример #8
0
 def ws_initial_process(ws):
     """Run some processing common to both the sample and vanadium workspaces"""
     simple.NormaliseByCurrent(InputWorkspace=ws, OutputWorkspace=ws)
     simple.ApplyDiffCal(InstrumentWorkspace=ws, CalibrationWorkspace=full_inst_calib)
     simple.ConvertUnits(InputWorkspace=ws, OutputWorkspace=ws, Target='dSpacing')
     return ws
Пример #9
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def create_calibration(calibration_runs, instrument, offset_file_name,
                       grouping_file_name, calibration_dir, rebin_1_params,
                       rebin_2_params, cross_correlate_params,
                       get_det_offset_params, output_name):
    """
    Create a calibration file from (usually) a ceria run
    :param calibration_runs: Run number(s) for this run
    :param instrument: The PEARL instrument object
    :param offset_file_name: Name of the file to write detector offset information to
    :param grouping_file_name: Name of grouping calibration file
    :param calibration_dir: Path to directory containing calibration information
    :param rebin_1_params: Parameters for the first rebin step (as a string in the usual format)
    :param rebin_2_params: Parameters for the second rebin step (as a string in the usual format)
    :param cross_correlate_params: Parameters for CrossCorrelate (as a dictionary PropertyName: PropertyValue)
    :param get_det_offset_params: Parameters for GetDetectorOffsets (as a dictionary PropertyName: PropertyValue)
    :param output_name: The name of the focused output workspace
    """
    input_ws_list = common.load_current_normalised_ws_list(
        run_number_string=calibration_runs,
        instrument=instrument,
        input_batching=INPUT_BATCHING.Summed)

    input_ws = input_ws_list[0]
    calibration_ws = mantid.Rebin(InputWorkspace=input_ws,
                                  Params=rebin_1_params)

    if calibration_ws.getAxis(
            0).getUnit().unitID() != WORKSPACE_UNITS.d_spacing:
        calibration_ws = mantid.ConvertUnits(InputWorkspace=calibration_ws,
                                             Target="dSpacing")

    rebinned = mantid.Rebin(InputWorkspace=calibration_ws,
                            Params=rebin_2_params)
    cross_correlated = mantid.CrossCorrelate(InputWorkspace=rebinned,
                                             **cross_correlate_params)

    offset_file = os.path.join(calibration_dir, offset_file_name)
    # Offsets workspace must be referenced as string so it can be deleted, as simpleapi doesn't recognise it as a ws
    offsets_ws_name = "offsets"
    mantid.GetDetectorOffsets(InputWorkspace=cross_correlated,
                              GroupingFileName=offset_file,
                              OutputWorkspace=offsets_ws_name,
                              **get_det_offset_params)

    rebinned_tof = mantid.ConvertUnits(InputWorkspace=rebinned, Target="TOF")
    mantid.ApplyDiffCal(InstrumentWorkspace=rebinned_tof,
                        CalibrationFile=offset_file)
    aligned = mantid.ConvertUnits(InputWorkspace=rebinned_tof,
                                  Target="dSpacing")
    mantid.ApplyDiffCal(InstrumentWorkspace=aligned, ClearCalibration=True)

    grouping_file = os.path.join(calibration_dir, grouping_file_name)
    focused = mantid.DiffractionFocussing(InputWorkspace=aligned,
                                          GroupingFileName=grouping_file,
                                          OutputWorkspace=output_name)

    common.remove_intermediate_workspace([
        calibration_ws, rebinned, cross_correlated, rebinned_tof, aligned,
        offsets_ws_name
    ])
    return focused
Пример #10
0
def create_van(instrument, run_details, absorb):
    """
    Creates a splined vanadium run for the following instrument. Requires the run_details for the
    vanadium workspace we will process and whether to apply absorption corrections.
    :param instrument: The instrument object that will be used to supply various instrument specific methods
    :param run_details: The run details associated with this vanadium run
    :param absorb: Boolean flag whether to apply absorption corrections
    :return: Processed workspace group in dSpacing (but not splined)
    """
    van = run_details.vanadium_run_numbers
    # Always sum a range of inputs as its a vanadium run over multiple captures
    input_van_ws_list = common.load_current_normalised_ws_list(
        run_number_string=van,
        instrument=instrument,
        input_batching=INPUT_BATCHING.Summed)
    input_van_ws = input_van_ws_list[
        0]  # As we asked for a summed ws there should only be one returned

    instrument.create_solid_angle_corrections(input_van_ws, run_details)

    if not (run_details.empty_runs is None):
        summed_empty = common.generate_summed_runs(
            empty_sample_ws_string=run_details.empty_runs,
            instrument=instrument)
        mantid.SaveNexus(Filename=run_details.summed_empty_file_path,
                         InputWorkspace=summed_empty)
        corrected_van_ws = common.subtract_summed_runs(
            ws_to_correct=input_van_ws, empty_sample=summed_empty)

    # Crop the tail end of the data on PEARL if they are not capturing slow neutrons
    corrected_van_ws = instrument._crop_raw_to_expected_tof_range(
        ws_to_crop=corrected_van_ws)

    if absorb:
        corrected_van_ws = instrument._apply_absorb_corrections(
            run_details=run_details, ws_to_correct=corrected_van_ws)
    else:
        # Assume that create_van only uses Vanadium runs
        mantid.SetSampleMaterial(InputWorkspace=corrected_van_ws,
                                 ChemicalFormula='V')

    mantid.ApplyDiffCal(InstrumentWorkspace=corrected_van_ws,
                        CalibrationFile=run_details.offset_file_path)
    aligned_ws = mantid.ConvertUnits(InputWorkspace=corrected_van_ws,
                                     Target="dSpacing")
    solid_angle = instrument.get_solid_angle_corrections(
        run_details.run_number, run_details)
    if solid_angle:
        aligned_ws = mantid.Divide(LHSWorkspace=aligned_ws,
                                   RHSWorkspace=solid_angle)
        mantid.DeleteWorkspace(solid_angle)
    focused_vanadium = mantid.DiffractionFocussing(
        InputWorkspace=aligned_ws,
        GroupingFileName=run_details.grouping_file_path)
    # convert back to TOF based on engineered detector positions
    mantid.ApplyDiffCal(InstrumentWorkspace=focused_vanadium,
                        ClearCalibration=True)
    focused_spectra = common.extract_ws_spectra(focused_vanadium)
    focused_spectra = instrument._crop_van_to_expected_tof_range(
        focused_spectra)

    d_spacing_group, tof_group = instrument._output_focused_ws(
        processed_spectra=focused_spectra, run_details=run_details)
    _create_vanadium_splines(focused_spectra, instrument, run_details)

    common.keep_single_ws_unit(d_spacing_group=d_spacing_group,
                               tof_group=tof_group,
                               unit_to_keep=instrument._get_unit_to_keep())

    common.remove_intermediate_workspace(corrected_van_ws)
    common.remove_intermediate_workspace(aligned_ws)
    common.remove_intermediate_workspace(focused_vanadium)
    common.remove_intermediate_workspace(focused_spectra)

    return d_spacing_group
Пример #11
0
 def apply_calibration_to_focused_data(self, focused_ws):
     # convert back to TOF based on engineered detector positions
     mantid.ApplyDiffCal(InstrumentWorkspace=focused_ws,
                         ClearCalibration=True)