drtsans.mono package

Subpackages

Submodules

drtsans.mono.absolute_units module

drtsans.mono.absolute_units.empty_beam_scaling(input_workspace, empty_beam_workspace, beam_radius=None, unit='mm', attenuator_coefficient=1.0, attenuator_error=0.0, output_workspace=None)[source]

Normalize input workspace by the intensity impinging on the detector for an empty beam run, taking into account attenuation.

Mantid Algorithms used: Divide, DeleteWorkspace,

Parameters:

  • input_workspace (str, MatrixWorkspace, IEventsWorkspace) – Workspace to be normalized

  • empty_beam_workspace (str, MatrixWorkspace, IEventsWorkspace) – Attenuated intensities collected at the detector with and empty beam.

  • beam_radius (float) – Radius of the beam at the detector. If None, it will be estimated with the sample and source apertures.

  • unit (str) – Units for the beam radius, either meters (‘m’) or mili-miters (‘mm’).

  • attenuator_coefficient (float) – Fraction of the neutrons allowed to pass through the attenuator. Assumed wavelength independent.

  • attenuator_error (float) – Estimated error for the attenuator coefficient.

  • output_workspace (str) – Name of the normalized workspace. If None, then the name of input_workspace will be used, thus overwriting input_workspace.

Return type:

MatrixWorkspace, IEventsWorkspace

drtsans.mono.bar_scan_pixel_calibration module

drtsans.mono.bar_scan_pixel_calibration.generate_intermediate_files(bar_scan_files, save_dir)[source]
drtsans.mono.bar_scan_pixel_calibration.generate_pixel_map(bar_scan_files, flood_file, save_dir_root, database_file_base, calib_name_base='CG2_Pixel_Calibration', mask_file='testdata/mask_pixel_map.nxs')[source]

Generate pixel calibration map from bar scan

# Mask file containing the detector ID’s comprising the beam center. # mask_file = f’/HFIR/CG2/IPTS-{ipts}/shared/pixel_flood_mask.nxs’

Parameters:

  • bar_scan_files

  • flood_file

  • save_dir_root

  • database_file_base

  • calib_name_base (str) – Base name for calibration file

  • mask_file

Returns:

(bar scan data set, flood), calibration (step 1),

Return type:

generator

drtsans.mono.bar_scan_pixel_calibration.generate_spice_pixel_map(ipts_number, exp_number, scan_number, pt_numbers, flood_ipts_number, flood_exp_number, flood_scan_number, flood_pt_number, root_dir, save_dir_root, mask_file)[source]
drtsans.mono.bar_scan_pixel_calibration.locate_bar_scan_files(ipts_number, exp_number, scan_number, pt_numbers, root_dir)[source]
drtsans.mono.bar_scan_pixel_calibration.locate_flood_file(ipts_number, exp_number, scan_number, pt_number, root_dir='/HFIR/CG2')[source]

Locate flood Nexus file

Parameters:

  • ipts_number

  • exp_number

  • scan_number

  • pt_number

  • root_dir

Returns:

flood Nexus file path

Return type:

str

drtsans.mono.bar_scan_pixel_calibration.untilt_and_center(a_calibration)[source]

Removing the Bar Tilt and Centering the Detector

Thinking of the fitted positions for the bottom and top pixels, we can think of the detector array as a deformed rectangle (angles between sides different than 90 degrees), which must be transformed into a rectangle with squared angles (angles between sides equal to 90 degrees).

We take the tube in the middle of the main detector array as our reference. We will adjust every other tube so that for every tube, its top and bottom fitted pixel positions will coincide with the top and bottom fitted positions of the middle tube.

Also, since top and bottom fitted positions have a different variation with tube index, the fitted tube lenght changes sligtly with tube index. Thus, we will rescale the fitted tube length to coincide with the fitted tube length of the middle tube. This amounts to a rescaling of pixel heights.

Finally, after removing the tilt we displace the detector so that the center of mass lies at Y=0.

drtsans.mono.convert_xml_to_nexus module

class drtsans.mono.convert_xml_to_nexus.EventNexusConverter(beam_line, instrument_name, num_banks)[source]

Bases: ABC

Class to provide service to convert to event NeXus from various input

static convert_log_units(spice_log_dict)[source]

Convert log unit from SPICE log to Nexus log

Parameters:

spice_log_dict (~dict) – key: Nexus das log name, value: (log value, log unit)

Returns:

key: DAS log name, value: DasLog

Return type:

~dict

property detector_counts

Get detector counts

Returns:

detector counts

Return type:

array

generate_event_nexus(target_nexus)[source]

Generate event NeXus properly

num_banks: int

CG2 = 48, CG3 = 88

Parameters:

target_nexus (str) – name of the output Nexus file

abstract get_pid_range(bank_id)[source]

Set GPSANS bank and pixel ID relation

Parameters:

bank_id (int) – bank ID from 1 to 48

Returns:

start PID, end PID (assuming PID are consecutive in a bank and end PID is inclusive)

Return type:

tuple

load_idf(template_nexus_file)[source]

Load IDF content from a template NeXus file

Parameters:

template_nexus_file

load_sans_xml(xml_file_name, das_log_map, prefix='')[source]

Load data and meta data from legacy SANS XML data file

Parameters:

  • xml_file_name (str) – name of SANS XML file

  • prefix (str) – prefix for output workspace name

  • das_log_map (~dict) – meta data map between event NeXus and SPICE

mask_spice_detector_pixels(pixel_index_list: List[int])[source]

Mask detector pixels with SPICE counts by set the counts to zero

Parameters:

pixel_index_list (~list) – list of integers as workspace index detector pixels

drtsans.mono.dark_current module

Links to mantid algorithms Minus <https://docs.mantidproject.org/nightly/algorithms/Minus-v1.html> DeleteWorkspace <https://docs.mantidproject.org/nightly/algorithms/DeleteWorkspace-v1.html> Integration <https://docs.mantidproject.org/nightly/algorithms/Integration-v1.html> Scale <https://docs.mantidproject.org/nightly/algorithms/Scale-v1.html>

drtsans.mono.dark_current.load_dark_current_workspace(dark_current_filename, output_workspace)[source]

Loads dark current workspace. Useful to avoid multiple loads from disk.

Mantid algorithms used: LoadEventNexus,

Parameters:

  • dark_current_filename (str) – file containing previously calculated sensitivity correction

  • output_workspace (int, str) – run number or file path for dark current

drtsans.mono.dark_current.normalize_dark_current(dark_workspace, output_workspace=None)[source]

Divide a dark current workspace by its duration.

Entry ‘normalizing_duration’ is added to the logs of the normalized dark current to annotate what log entry was used to find the duration

Mantid algorithms used: Scale, DeleteWorkspace,

Parameters:

  • dark_workspace (str, MatrixWorkspace) – Dark current workspace

  • output_workspace (str) – Name of the normalized dark workspace. If None, the name of the input workspace dark_workspace is chosen (and the input workspace is overwritten).

Returns:

Output workspace

Return type:

MatrixWorkspace

drtsans.mono.dark_current.subtract_dark_current(data_workspace, dark, output_workspace=None)[source]

Subtract normalized dark from data, taking into account the duration of both the data and dark runs.

normalized_data = data - (data_duration / dark_duration) * dark

Mantid algorithms used: Scale, Minus DeleteWorkspace

Parameters:

  • data_workspace (MatrixWorkspace) – Sample scattering with intensities versus wavelength.

  • dark (int, str, MatrixWorkspace) – run number, file path, workspace name, or MatrixWorkspace for dark current.

  • output_workspace (str) – Name of the output workspace. If None, the name of the input workspace data_workspace is chosen (and the input workspace is overwritten).

Return type:

MatrixWorkspace

drtsans.mono.geometry module

drtsans.mono.geometry.beam_radius(input_workspace, unit='mm')[source]

Calculate the beam radius impinging on the detector

R_beam = R_sampleAp + SDD * (R_sampleAp + R_sourceAp) / SSD, where R_sampleAp: radius of the sample aperture, SDD: distance between the sample and the detector, R_sourceAp: radius of the source aperture, SSD: distance between the source and the sample.

Parameters:

  • input_workspace (MatrixWorkspace, str) – Input workspace

  • unit (str) – Units of the output beam radius. Either ‘mm’ or ‘m’.

Return type:

float

drtsans.mono.load module

drtsans.mono.load.load_and_split(run, sample_to_si_name, si_nominal_distance, data_dir=None, output_workspace=None, output_suffix='', overwrite_instrument=True, pixel_calibration=False, time_interval: float | List[float] | None = None, time_offset: float = 0.0, time_period: float | None = None, log_name=None, log_value_interval=None, sample_to_si_value=None, sample_detector_distance_value=None, reuse_workspace=False, monitors=False, **kwargs)[source]

Load an event NeXus file and filter into a WorkspaceGroup depending on the provided filter options. Either a time_interval must be provided or a log_name and log_value_interval.

Metadata added to output workspace includes the slice number, number_of_slices, slice_parameter, slice_interval, slice_start and slice_end.

For EQSANS two WorkspaceGroup’s are return, one for the filtered data and one for filtered monitors

Parameters:

  • run (str, IEventWorkspace) – Examples: CG3_55555, CG355555 or file path.

  • sample_to_si_name (str) – Meta data name for sample to Silicon window distance

  • si_nominal_distance (float) – distance between nominal position to silicon window. unit = meter

  • data_dir (str, list) – Additional data search directories

  • output_workspace (str) – If not specified it will be BIOSANS_55555 determined from the supplied value of run.

  • output_suffix (str) – If the output_workspace is not specified, this is appended to the automatically generated output workspace name.

  • overwrite_instrument (bool, str) – If not False, ignore the instrument embedeed in the Nexus file. If True, use the latest instrument definition file (IDF) available in Mantid. If str, then it should be the filepath to the desired IDF.

  • pixel_calibration (bool) – Adjust pixel heights and widths according to bar-scan and tube-width calibrations.

  • time_interval – Array for lengths of time intervals for splitters. If the array has one value, then all splitters will have same time intervals. If the size of the array is larger than one, then the splitters can have various time interval values.

  • time_offset – Offset to be added to the start time of the first splitter, in seconds.

  • time_period – A multiple integer of the time interval. If specified, it indicates that the time slicing is periodic so that events in time intervals separated by one (or more) period should be reduced together.

  • sample_to_si_value (float or None) – Sample to silicon window distance to overwrite the EPICS value. None for no operation. unit = meter

  • sample_detector_distance_value (float or None) – Sample to detector distance to overwrite the EPICS value. None for no operation. unit = meter

  • log_name (string) – Name of the sample log to use to filter. For example, the pulse charge is recorded in ‘ProtonCharge’.

  • log_value_interval (float) – Delta of log value to be sliced into from min log value and max log value.

  • reuse_workspace (bool) – When true, return the output_workspace if it already exists

  • monitors (bool) – flag to load monitors

  • kwargs (dict) – Additional positional arguments for LoadEventNexus.

Returns:

Reference to the workspace groups containing all the split workspaces

Return type:

WorkspaceGroup

drtsans.mono.load.load_events(run, data_dir=None, output_workspace=None, overwrite_instrument=True, output_suffix='', pixel_calibration=False, detector_offset=0.0, sample_offset=0.0, reuse_workspace=False, **kwargs)[source]

Load an event Nexus file produced by the instruments at ORNL.

Parameters:

  • run (str, IEventWorkspace) – Examples: CG3_55555, CG355555 or file path.

  • output_workspace (str) – If not specified it will be BIOSANS_55555 determined from the supplied value of run.

  • data_dir (str, list) – Additional data search directories

  • overwrite_instrument (bool, str) – If not False, ignore the instrument embedeed in the Nexus file. If True, use the latest instrument definition file (IDF) available in Mantid. If str, then it should be the filepath to the desired IDF.

  • output_suffix (str) – If the output_workspace is not specified, this is appended to the automatically generated output workspace name.

  • pixel_calibration (bool, str) – Adjust pixel heights and widths according to bar-scan and tube-width calibrations. Options are (1) No calibration (2) Using default calibration file (True) and (3) User specified calibration file (str)

  • detector_offset (float) – Additional translation of the detector along the Z-axis, in mm. Positive moves the detector downstream.

  • sample_offset (float) – Additional translation of the sample, in mm. The sample flange remains at the origin of coordinates. Positive moves the sample downstream.

  • reuse_workspace (bool) – When true, return the output_workspace if it already exists

  • kwargs (dict) – Additional positional arguments for LoadEventNexus.

Returns:

Reference to the events workspace

Return type:

IEventWorkspace

drtsans.mono.load.load_events_and_histogram(run, data_dir=None, output_workspace=None, output_suffix='', overwrite_instrument=True, pixel_calibration=False, reuse_workspace=False, sample_to_si_name=None, si_nominal_distance=None, sample_to_si_value=None, sample_detector_distance_value=None, **kwargs)[source]

Load one or more event Nexus file produced by the instruments at HFIR. Convert to wavelength and sums the data.

Parameters:

  • run (str, list of runs to load) – Examples: CG3_55555, CG355555, file path, CG3_55555,CG3_55556

  • data_dir (str, list) – Additional data search directories

  • output_workspace (str) – If not specified it will be BIOSANS_55555 determined from the supplied value of run.

  • output_suffix (str) – If the output_workspace is not specified, this is appended to the automatically generated output workspace name.

  • overwrite_instrument (bool, str) – If not False, ignore the instrument embedeed in the Nexus file. If True, use the latest instrument definition file (IDF) available in Mantid. If str, then it should be the filepath to the desired IDF.

  • pixel_calibration (bool) – Adjust pixel heights and widths according to bar-scan and tube-width calibrations.

  • sample_to_si_name (str) – Meta data name for sample to Silicon window distance

  • si_nominal_distance (float) – distance between nominal position to silicon window. unit = meter

  • sample_to_si_value (float or None) – Sample to silicon window distance to overwrite the EPICS value. None for no operation. unit = meter

  • sample_detector_distance_value (float or None) – Sample to detector distance to overwrite the EPICS value. None for no operation. unit = meter

  • reuse_workspace (bool) – When true, return the output_workspace if it already exists

  • kwargs (dict) – Additional positional arguments for LoadEventNexus.

Return type:

MatrixWorkspace

drtsans.mono.load.load_histogram(filename, output_workspace=None, wavelength=None, wavelength_spread=None, sample_det_cent=None)[source]

Loads a SANS data file produce by the HFIR instruments at ORNL. The instrument geometry is also loaded. The center of the detector is placed at (0, 0, sample_det_cent )

Parameters:

  • filename (str) – The name of the input xml file to load

  • output_workspace (str, optional) – The optional name of the output workspace. If None is the filename stripped of the extension.

  • wavelength (float) – The wavelength value to use when loading the data file (Angstrom). This value will be used instead of the value found in the data file.

  • wavelength_spread (float) – wavelength spread value to use when loading the data file (Angstrom). This value will be used instead of the value found in the data file.

  • sample_det_cent (float) – Sample to detector distance to use (overrides meta data) in mm

Returns:

A reference for the workspace created.

Return type:

MatrixWorkspace

drtsans.mono.load.load_mono(filename, **kwargs)[source]

Loads a SANS data file produce by the HFIR instruments at ORNL.

Parameters:

  • filename (int, str) – Examples: 55555 or CG3_55555 or file path.

  • kwargs – keyword arguments for load_events or load_histogram.

Return type:

MatrixWorkspace

drtsans.mono.load.set_init_uncertainties(input_workspace, output_workspace=None)[source]

Set the initial uncertainty of a MatrixWorkspace

Mantid algorithm SetUncertainties will be called to make sure 1: set the uncertainty to square root of intensity 2: make sure all zero uncertainties will be set to 1

In case of output workspace is py:obj:None, the input workspace will be replaced by output workspace.

Raises:

RuntimeError – output workspace (string) is empty

Mantid algorithms used: CloneWorkspace SetUncertainties

Parameters:

  • input_workspace (MatrixWorkspace) – Input workspace

  • output_workspace (str) – Output workspace (workspace name or instance) or py:obj:None for in-place operation

Return type:

MatrixWorkspace

drtsans.mono.load.sum_data(data_list, output_workspace, sum_logs=('duration', 'timer', 'monitor', 'monitor1'))[source]

Merge data set together, summing the listed logs

Parameters:

  • data_list (list of Workspace2D, list of workspace names, comma separated list of workspace names, WorkspaceGroup) – Examples: [ws1, ws1], [‘ws1’, ‘ws2’] or ‘ws1, ws2’

  • output_workspace (str) – Name of output workspace, required

  • sum_logs (list of str) – numeric logs that will be summed during merging

Return type:

Workspace2D

drtsans.mono.load.transform_to_wavelength(input_workspace, output_workspace=None)[source]

Transforms the event files with fake time of flight from the SANS instruments at HFIR into histograms in wavelength.

Mantid Algorithms used: HFIRSANS2Wavelength,

Parameters:

  • input_workspace (str, IEventWorkspace) – Events workspace in time-of-flight.

  • output_workspace (str) – Name of the output workspace. If None, the name of the input_workspace will be used, thus overwriting the input workspace.

Return type:

MatrixWorkspace

drtsans.mono.meta_data module

drtsans.mono.meta_data.get_sample_detector_offset(workspace, sample_si_meta_name, zero_sample_offset_sample_si_distance, overwrite_sample_si_distance=None, overwrite_sample_detector_distance=None)[source]

Get sample offset and detector offset from meta data

This method is based on the assumption and fact that “sample position is set to nominal position (0, 0, 0) regardless of sample log SampleToSi” “detector1 is set to [0, 0, sample_detector_distance] It will be re-implemented

Parameters:

  • workspace (str, MatrixWorkspace) – Mantid workspace instance or workspace name

  • sample_si_meta_name (str) – Sample to Si (window) meta data name

  • zero_sample_offset_sample_si_distance (float) – default sample to Si window distance, i.e., distance without sample offset. unit = meter

  • overwrite_sample_si_distance (float or None) – sample to Si window distance to overwrite. Unit = mm (consistent with the unit of original meta data)

  • overwrite_sample_detector_distance (float or None) – sample detector distance to overwrite. Unit = m (consistent with the unit of original meta data)

Returns:

sample offset (float) in unit meter and detector offset (float) in unit meter

Return type:

~tuple

drtsans.mono.meta_data.parse_json_meta_data(reduction_input, meta_name, unit_conversion_factor, beam_center_run=False, background_run=False, empty_transmission_run=False, transmission_run=False, background_transmission=False, block_beam_run=False, dark_current_run=False)[source]

Parse user specified meta data from JSON from configuration part

Parameters:

  • reduction_input (dict) – dictionary parsed from JSON

  • meta_name (str) – meta data name

  • unit_conversion_factor (float) – unit conversion conversion factor from user preferred unit to drt-sans preferred unit

  • beam_center_run (bool) – flag whether beam center run will have the same meta data

  • background_run (bool) – flag whether beam center run will have the same meta data

  • empty_transmission_run (bool) – flag whether beam center run will have the same meta data

  • transmission_run – flag whether beam center run will have the same meta data

  • background_transmission – flag whether beam center run will have the same meta data

  • block_beam_run – flag whether beam center run will have the same meta data

  • dark_current_run – flag whether beam center run will have the same meta data

Returns:

keys: strings stands for sample (run), background (run) and etc used in JSON; value: JSON value if value is None, it indicates that the meta data won’t be overwritten

Return type:

dict

drtsans.mono.meta_data.set_meta_data(workspace, wave_length=None, wavelength_spread=None, sample_offset=0.0, sample_aperture_diameter=None, sample_thickness=None, source_aperture_diameter=None, smearing_pixel_size_x=None, smearing_pixel_size_y=None)[source]

Set meta data to SANS Mantid Workspace as run properties

Parameters:

  • workspace (str, MatrixWorkspace) – Mantid workspace instance or workspace name

  • wave_length (float, None) – wave length in Angstrom

  • wavelength_spread (float, None) – wave length spread in Angstrom

  • sample_offset (float) – offset of sample from origin in unit mm

  • sample_aperture_diameter (float, None) – sample aperture diameter in mm

  • sample_thickness (None, float) – sample thickness in unit cm

  • source_aperture_diameter (float, None) – source aperture size radius in unit mm

  • smearing_pixel_size_x (float, None) – pixel size in x direction in unit as meter, only for Q-resolution calculation

  • smearing_pixel_size_y (float, None) – pixel size in Y direction in unit as meter, only for Q-resolution calculation

drtsans.mono.momentum_transfer module

drtsans.mono.momentum_transfer.convert_to_q(ws, mode, resolution_function=<function mono_resolution>, **kwargs)[source]

Convert a workspace with units of wavelength into a series of arrays: intensity, error, q (or q components), delta q (or delta q components), and wavelength

Using the scattering angle as \(2\theta\) and azimuthan angle as \(\phi\),the calculaion of momentum transfer is:

  • ‘scalar’ mode:

\[|Q| = \frac{4\pi}{\lambda}\sin\theta\]

  • ‘azimuthal’ mode:

\[ \begin{align}\begin{aligned}Q_x=\frac{4\pi}{\lambda}\sin\theta\cos\phi\\Q_y=\frac{4\pi}{\lambda}\sin\theta\sin\phi\end{aligned}\end{align} \]

  • ‘crystallographic’ mode:

\[ \begin{align}\begin{aligned}Q_x=\frac{2\pi}{\lambda}\sin(2\theta)\cos\phi\\Q_y=\frac{2\pi}{\lambda}\sin(2\theta)\sin\phi\\Qz_=\frac{2\pi}{\lambda}(\cos(2\theta)-1)\end{aligned}\end{align} \]

It calls drtsans.momentum_transfer.convert_to_q

Parameters:

  • ws (str, IEventWorkspace, MatrixWorkspace) – Workspace in units of wavelength

  • mode (str) – Available options are ‘scalar’, ‘azimuthal’, and ‘crystallographic’

  • resolution_function – Function to calculate resolution

  • kwargs – Parameters to be passed to the resolution function

Returns:

A namedtuple with fields for

  • intensity

  • error

  • mod_q (\(|Q|\)) or qx, qy (\(Q_x, Q_y\)) or qx, qy, qz (\(Q_x, Q_y, Q_z\)) (depending on the mode)

  • delta_q or delta_qx, delta_qy or delta_qx, delta_qy, delta_qz - the resolution along the q components

  • wavelength

Return type:

namedtuple

drtsans.mono.normalization module

Links to mantid algorithms CreateSingleValuedWorkspace <https://docs.mantidproject.org/nightly/algorithms/CreateSingleValuedWorkspace-v1.html> Divide <https://docs.mantidproject.org/nightly/algorithms/Divide-v1.html>

drtsans.mono.normalization.normalize_by_flux(ws, method)[source]

Normalize to time or monitor

Parameters:

  • input_workspace (MatrixWorkspace)

  • method (str) – Normalization method: ‘time’ or ‘monitor’

drtsans.mono.normalization.normalize_by_monitor(input_workspace, output_workspace=None)[source]

Normalize by the monitor value

Mantid algorithms used: :ref: CreateSingleValuedWorkspace <algm-CreateSingleValuedWorkspace-v1> :ref:`Divide <algm-Divide-v1>,

Parameters:

  • input_workspace (MatrixWorkspace)

  • output_workspace (str) – Optional name of the output workspace. Default is to replace the input workspace

Returns:

the normalized input workspace

Return type:

MatrixWorkspace

Raises:

RuntimeError – No monitor metadata found in the sample logs of the input workspace

drtsans.mono.normalization.normalize_by_time(input_workspace, output_workspace=None)[source]

Normalize by time Used to normalize dark current

Mantid algorithms used: Divide,

Parameters:

  • input_workspace (MatrixWorkspace)

  • output_workspace (str) – Optional name of the output workspace. Default is to replace the input workspace

drtsans.mono.spice_data module

class drtsans.mono.spice_data.SpiceRun(beam_line, ipts_number, exp_number, scan_number, pt_number)[source]

Bases: NamedTuple

beam_line: str

Alias for field number 0

exp_number: int

Alias for field number 2

property hfir_ipts_dir

Standard HFIR SPICE data directory

Returns:

Path to IPTS directory

Return type:

str

ipts_number: int

Alias for field number 1

locate_spice_file(data_dir=None, raise_if_not_exist=True)[source]

Locate SPICE file

Parameters:

  • data_dir (str or None) – None is by default

  • raise_if_not_exist (bool) – raise RuntimeError if the file does not exist

Returns:

Path to the SPICE file

Return type:

str

pt_number: int

Alias for field number 4

scan_number: int

Alias for field number 3

unique_nexus_name(nexus_dir=None, raise_if_not_exist=False)[source]
Parameters:

  • nexus_dir (str, None) – Path to nexus file. If None

  • raise_if_not_exist (bool) – Check the nexus file exists or not. Raise exception if it does not

Returns:

full path to Nexus file

Return type:

str

property unique_run_number

Create a unique run number

Note: HFIR experiment has unique experiment number.

Returns:

run number

Return type:

int

drtsans.mono.spice_data.map_to_nexus(beam_line: str, ipts_number: int, exp_number: int, scan_pt_list: List[Tuple[int, int] | None], nexus_dir: str | None = None) → List[str][source]

Map SPICE information to converted NeXus file path

Parameters:

  • beam_line (str) – CG2 or CG3

  • ipts_number (int) – IPTS number

  • exp_number (int) – experiment number

  • scan_pt_list (tuple) – scan number, pt number

  • nexus_dir (str or None) – directory to locate nexus file. None with default

Returns:

list of Nexus files with the same order with scan-pt

Return type:

~list

drtsans.mono.spice_xml_parser module

Module contains class and method to parse SPICE SANS XML file for DAS sample logs.

class drtsans.mono.spice_xml_parser.SpiceXMLParser(spice_xml_name)[source]

Bases: object

Class to parse SPICE SANS data file in XML format

close()[source]

Close the opened XML file

get_node_value(node_name, value_type)[source]

Get an XML node value regardless of the level of the node in the XML tree

Parameters:

  • node_name (str) – Name of the XML node to retrieve

  • value_type (type) – type to cast the value

Returns:

value, unit

Return type:

tuple

get_xml_node(node_name, required_attribs=None)[source]

Get an XML node by its name regardless its level in XML tree

Parameters:

  • node_name (str) – Name of the XML node to retrieve

  • required_attribs (dict, None) – required attributes for the node

Return type:

xlm.etree.Element

drtsans.mono.transmission module

drtsans.mono.transmission.apply_transmission_correction(input_workspace, trans_workspace=None, trans_value=None, trans_error=0.0, theta_dependent=True, output_workspace=None)[source]

Correct the intensities with transmission coefficient(s).

Mantid algorithms used: ApplyTransmissionCorrection ReplaceSpecialValues

Parameters:

  • input_workspace (str, MatrixWorkspace) – Input workspace to correct its intensities

  • trans_workspace (str, MatrixWorkspace) – Workspace containing the transmission coefficient(s). The result of applying calculate_transmission to the input workspace. If None, trans_value will be used.

  • trans_value (float) – A single transmission coefficient to correct the intensities. If None, trans_workspace will be used.

  • trans_error (float) – Error associated to trans_value.

  • theta_dependent (bool) – Flag to do theta dependent correction

  • output_workspace (str) – Name of the workspace containing the corrected intensities. If None, the input_workspace will be overwritten.

Return type:

MatrixWorkspace

drtsans.mono.transmission.calculate_transmission(input_sample, input_reference, radius=None, radius_unit='mm', output_workspace=None)[source]

Module contents

drtsans.mono.empty_beam_scaling(input_workspace, empty_beam_workspace, beam_radius=None, unit='mm', attenuator_coefficient=1.0, attenuator_error=0.0, output_workspace=None)[source]

Normalize input workspace by the intensity impinging on the detector for an empty beam run, taking into account attenuation.

Mantid Algorithms used: Divide, DeleteWorkspace,

Parameters:

  • input_workspace (str, MatrixWorkspace, IEventsWorkspace) – Workspace to be normalized

  • empty_beam_workspace (str, MatrixWorkspace, IEventsWorkspace) – Attenuated intensities collected at the detector with and empty beam.

  • beam_radius (float) – Radius of the beam at the detector. If None, it will be estimated with the sample and source apertures.

  • unit (str) – Units for the beam radius, either meters (‘m’) or mili-miters (‘mm’).

  • attenuator_coefficient (float) – Fraction of the neutrons allowed to pass through the attenuator. Assumed wavelength independent.

  • attenuator_error (float) – Estimated error for the attenuator coefficient.

  • output_workspace (str) – Name of the normalized workspace. If None, then the name of input_workspace will be used, thus overwriting input_workspace.

Return type:

MatrixWorkspace, IEventsWorkspace

drtsans.mono.load_dark_current_workspace(dark_current_filename, output_workspace)[source]

Loads dark current workspace. Useful to avoid multiple loads from disk.

Mantid algorithms used: LoadEventNexus,

Parameters:

  • dark_current_filename (str) – file containing previously calculated sensitivity correction

  • output_workspace (int, str) – run number or file path for dark current

drtsans.mono.normalize_dark_current(dark_workspace, output_workspace=None)[source]

Divide a dark current workspace by its duration.

Entry ‘normalizing_duration’ is added to the logs of the normalized dark current to annotate what log entry was used to find the duration

Mantid algorithms used: Scale, DeleteWorkspace,

Parameters:

  • dark_workspace (str, MatrixWorkspace) – Dark current workspace

  • output_workspace (str) – Name of the normalized dark workspace. If None, the name of the input workspace dark_workspace is chosen (and the input workspace is overwritten).

Returns:

Output workspace

Return type:

MatrixWorkspace

drtsans.mono.subtract_dark_current(data_workspace, dark, output_workspace=None)[source]

Subtract normalized dark from data, taking into account the duration of both the data and dark runs.

normalized_data = data - (data_duration / dark_duration) * dark

Mantid algorithms used: Scale, Minus DeleteWorkspace

Parameters:

  • data_workspace (MatrixWorkspace) – Sample scattering with intensities versus wavelength.

  • dark (int, str, MatrixWorkspace) – run number, file path, workspace name, or MatrixWorkspace for dark current.

  • output_workspace (str) – Name of the output workspace. If None, the name of the input workspace data_workspace is chosen (and the input workspace is overwritten).

Return type:

MatrixWorkspace