API

adcorr

adcorr.corrections

adcorr.corrections.angular_efficiency

adcorr.corrections.angular_efficiency.correct_angular_efficiency(frames: ndarray[tuple[NumFrames, FrameWidth, FrameHeight], dtype[number]], beam_center: Tuple[float, float], pixel_sizes: Tuple[float, float], distance: float, absorption_coefficient: float, thickness: float) → ndarray[tuple[NumFrames, FrameWidth, FrameHeight], dtype[number]]

Corrects for loss due to the angular efficiency of the detector head.

Corrects for loss due to the angular efficiency of the detector head, as described in section 3.xiii and appendix C of ‘The modular small-angle X-ray scattering data correction sequence’ [https://doi.org/10.1107/S1600576717015096].

Parameters:

• frames – A stack of frames to be corrected.

• beam_center – The center position of the beam in pixels.

• pixel_sizes – The real space size of a detector pixel.

• distance – The distance between the detector and the sample head.

• absorption_coefficient – The coefficient of absorption for a given material at a given photon energy.

• thickness – The thickness of the detector head material.

Returns:

The corrected stack of frames.

adcorr.corrections.background_subtraction

adcorr.corrections.background_subtraction.subtract_background(foreground_frames: ndarray[tuple[NumFrames, FrameWidth, FrameHeight], dtype[number]], background_frame: ndarray[tuple[FrameWidth, FrameHeight], dtype[number]]) → ndarray[tuple[NumFrames, FrameWidth, FrameHeight], dtype[number]]

Subtract a background frame from a sequence of foreground frames.

Subtract a background frame from a sequence of foreground frames, as detailed in section 3.4.6 of ‘Everything SAXS: small-angle scattering pattern collection and correction’ [https://doi.org/10.1088/0953-8984/25/38/383201].

Parameters:

• foreground_frames – A sequence of foreground frames to be corrected.

• background_frame – The background which is to be corrected for.

Returns:

A sequence of corrected frames.

adcorr.corrections.dark_current

adcorr.corrections.dark_current.correct_dark_current(frames: ndarray[tuple[NumFrames, FrameWidth, FrameHeight], dtype[number]], count_times: ndarray[tuple[NumFrames | Literal[1]], dtype[number]], transmitted_flux: ndarray[tuple[NumFrames | Literal[1]], dtype[number]], base_dark_current: float, temporal_dark_current: float, flux_dependant_dark_current: float) → ndarray[tuple[NumFrames, FrameWidth, FrameHeight], dtype[number]]

Correct by subtracting base, temporal and flux-dependant dark currents.

Correct for incident dark current by subtracting a baselike, time dependant and a flux dependant count rate from frames, as detailed in section 3.3.6 of ‘Everything SAXS: small-angle scattering pattern collection and correction’ [https://doi.org/10.1088/0953-8984/25/38/383201].

Parameters:

• frames – A stack of frames to be corrected.

• count_times – The period over which photons are counted for each frame.

• transmitted_flux – The flux intensity observed downstream of the sample for each frame.

• base_dark_current – The dark current flux, irrespective of time.

• temporal_dark_current – The dark current flux, as a factor of time.

• flux_dependant_dark_current – The dark current flux, as a factor of incident flux.

Returns:

The corrected stack of frames.

adcorr.corrections.deadtime

adcorr.corrections.deadtime.correct_deadtime(frames: ndarray[tuple[NumFrames, FrameWidth, FrameHeight], dtype[number]], count_times: ndarray[tuple[NumFrames | Literal[1]], dtype[floating]], minimum_pulse_separation: float, minimum_arrival_separation: float) → ndarray[tuple[NumFrames, FrameWidth, FrameHeight], dtype[number]]

Correct for detector deadtime by accounting for overlapping events.

Correct for detector deadtime by iteratively solving for the number of incident photons required to produce the observed value in a given time period subject to detector characteristics, as detailed in section 3.3.4 of ‘Everything SAXS: small- angle scattering pattern collection and correction’ [https://doi.org/10.1088/0953-8984/25/38/383201].

Parameters:

• frames – A stack of frames to be corrected.

• count_times – The period over which photons are counted for each frame.

• minimum_pulse_separation – The minimum time difference required between a prior pulse and the current pulse for the current pulse to be recorded correctly.

• minimum_arrival_separation – The minimum time difference required between the current pulse and a subsequent pulse for the current pulse to be recorded correctly.

Returns:

The corrected stack of frames.

adcorr.corrections.displaced_volume

adcorr.corrections.displaced_volume.correct_displaced_volume(frames: ndarray[tuple[NumFrames, FrameWidth, FrameHeight], dtype[number]], displaced_fraction: float) → ndarray[tuple[NumFrames, FrameWidth, FrameHeight], dtype[number]]

Corrects for the volume of solvent displaced by the solute.

Corrects for displaced volume of solvent by multiplying signal by the retained fraction, as detailed in section 3.xviii and appendix B of ‘The modular small-angle X-ray scattering data correction sequence’ [https://doi.org/10.1107/S1600576717015096].

Parameters:

• frames – A stack of frames to be corrected.

• displaced_fraction – The fraction of solvent displaced by the analyte.

Returns:

The corrected stack of frames.

adcorr.corrections.flatfield

adcorr.corrections.flatfield.correct_flatfield(frames: ndarray[tuple[NumFrames, FrameWidth, FrameHeight], dtype[number]], flatfield: ndarray[tuple[FrameWidth, FrameHeight], dtype[floating]]) → ndarray[tuple[NumFrames, FrameWidth, FrameHeight], dtype[number]]

Corrects for inter-pixel sensitivity with a multiplicative flatfield.

Apply multiplicative flatfield correction, to correct for inter-pixel sensitivity, as described in section 3.xii of ‘The modular small-angle X-ray scattering data correction sequence’ [https://doi.org/10.1107/S1600576717015096].

Parameters:

• frames – A stack of frames to be corrected.

• flatfield – The multiplicative flatfield correction to be applied.

Returns:

The corrected stack of frames.

adcorr.corrections.transmission

adcorr.corrections.transmission.normalize_transmitted_flux(frames: ndarray[tuple[NumFrames, FrameWidth, FrameHeight], dtype[number]], transmitted_flux: ndarray[tuple[NumFrames | Literal[1]], dtype[number]]) → ndarray[tuple[NumFrames, FrameWidth, FrameHeight], dtype[number]]

Normalize for incident flux and transmissibility by scaling photon counts.

Normalize for incident flux and transmissibility by scaling photon counts with respect to the total observed flux, as detailed in section 4 of ‘The modular small- angle X-ray scattering data correction sequence’ [https://doi.org/10.1107/S1600576717015096].

Parameters:

• frames – A stack of frames to be normalized.

• transmitted_flux – The flux intensity observed downstream of the sample.

Returns:

The normalized stack of frames.

adcorr.corrections.frame_average

adcorr.corrections.frame_average.average_all_frames(frames: ndarray[tuple[NumFrames, FrameWidth, FrameHeight], dtype[number]]) → ndarray[tuple[FrameWidth, FrameHeight], dtype[number]]

Average all frames over the leading axis.

Parameters:

frames – A stack of frames to be averaged.

Returns:

A frame containing the average pixel values of all frames in the stack.

adcorr.corrections.frame_time

adcorr.corrections.frame_time.normalize_frame_time(frames: ndarray[tuple[NumFrames, FrameWidth, FrameHeight], dtype[number]], count_times: ndarray[tuple[NumFrames | Literal[1]], dtype[floating]]) → ndarray[tuple[NumFrames, FrameWidth, FrameHeight], dtype[floating]]

Normalize for detector frame rate by scaling with respect to to count time.

Normalize for detector frame rate by scaling photon counts according to count time, as detailed in section 3.4.3 of ‘Everything SAXS: small-angle scattering pattern collection and correction’ [https://doi.org/10.1088/0953-8984/25/38/383201].

Parameters:

• frames – A stack of frames to be normalized.

• count_times – The period over which photons are counted for each frame.

Returns:

The normalized stack of frames.

adcorr.corrections.masking

adcorr.corrections.masking.mask_frames(frames: ndarray[tuple[NumFrames, FrameWidth, FrameHeight], FrameDType], mask: ndarray[tuple[FrameWidth, FrameHeight], dtype[bool_]]) → MaskedArray[tuple[NumFrames, FrameWidth, FrameHeight], FrameDType]

Constructs a numpy masked array from a stack of frames and a mask.

Constructs a numpy masked array from a stack of frames and a mask. Restricting computation to regions which remain unmasked and allowing infill of masked regions with a given value.

Parameters:

• frames – A stack of frames to be masked.

• mask – The boolean mask to apply to each frame.

Returns:

A stack of frames where pixels.

adcorr.corrections.polarization

adcorr.corrections.polarization.correct_polarization(frames: ndarray[tuple[NumFrames, FrameWidth, FrameHeight], dtype[number]], beam_center: Tuple[float, float], pixel_sizes: Tuple[float, float], distance: float, horizontal_poarization: float = 0.5) → ndarray[tuple[NumFrames, FrameWidth, FrameHeight], dtype[floating]]

Corrects for the effect of polarization of the incident beam.

Corrects for the effect of polarization of the incident beam, as detailed in section 3.4.1 of ‘Everything SAXS: small-angle scattering pattern collection and correction’ [https://doi.org/10.1088/0953-8984/25/38/383201].

Parameters:

• frames – A stack of frames to be corrected.

• beam_center – The center position of the beam in pixels.

• pixel_sizes – The real space size of a detector pixel.

• distance – The distance between the detector and the sample.

• horizontal_poarization – The fraction of incident radiation polarized in the horizontal plane, where 0.5 signifies an unpolarized source. Defaults to 0.5.

Returns:

The corrected stack of frames.

adcorr.corrections.self_absorption

adcorr.corrections.self_absorption.correct_self_absorption(frames: ndarray[tuple[NumFrames, FrameWidth, FrameHeight], dtype[number]], incident_flux: ndarray[tuple[NumFrames | Literal[1]], dtype[number]], transmitted_flux: ndarray[tuple[NumFrames | Literal[1]], dtype[number]], beam_center: Tuple[float, float], pixel_sizes: Tuple[float, float], distance: float) → ndarray[tuple[NumFrames, FrameWidth, FrameHeight], dtype[number]]

Correct for transmission loss due to differences in observation angle.

Correct for transmission loss due to differences in observation angle, as detailed in section 3.4.7 of ‘Everything SAXS: small-angle scattering pattern collection and correction’ [https://doi.org/10.1088/0953-8984/25/38/383201].

Parameters:

• frames – A stack of frames to be corrected.

• incident_flux – The flux intensity observed upstream of the sample.

• transmitted_flux – The flux intensity observed downstream of the sample.

• beam_center – The center position of the beam in pixels.

• pixel_sizes – The real space size of a detector pixel.

• distance – The distance between the detector and the sample.

Returns:

The corrected stack of frames.

adcorr.corrections.solid_angle

adcorr.corrections.solid_angle.correct_solid_angle(frames: ndarray[tuple[NumFrames, FrameWidth, FrameHeight], dtype[number]], beam_center: Tuple[float, float], pixel_sizes: Tuple[float, float], distance: float) → ndarray[tuple[NumFrames, FrameWidth, FrameHeight], dtype[floating]]

Corrects for the solid angle by scaling by the inverse of subtended area.

Corrects for the solid angle by scaling by the inverse of area subtended by each pixel, as detailed in section 3.4.6 of ‘Everything SAXS: small-angle scattering pattern collection and correction’ [https://doi.org/10.1088/0953-8984/25/38/383201].

Parameters:

• frames – A stack of frames to be corrected.

• beam_center – The center position of the beam in pixels.

• pixel_sizes – The real space size of a detector pixel.

• distance – The distance between the detector and the sample head.

Returns:

The corrected stack of frames.

adcorr.corrections.thickness

adcorr.corrections.thickness.normalize_thickness(frames: ndarray[tuple[NumFrames, FrameWidth, FrameHeight], dtype[number]], sample_thickness: float) → ndarray[tuple[NumFrames, FrameWidth, FrameHeight], dtype[number]]

Normailizes pixel intensities by dividing by the sample thickness.

Normailizes pixel intensities by dividing by the sample thickness, as detailed in section 3.4.3 of ‘Everything SAXS: small-angle scattering pattern collection and correction’ [https://doi.org/10.1088/0953-8984/25/38/383201].

Parameters:

• frames – A stack of frames to be corrected.

• sample_thickness – The thickness of the exposed sample.

Returns:

The normalized stack of frames.

adcorr.sequences

adcorr.sequences.pauw

adcorr.sequences.pauw.pauw_instrumental_background_sequence(frames: ndarray[tuple[NumFrames, FrameWidth, FrameHeight], dtype[number]], mask: ndarray[tuple[FrameWidth, FrameHeight], dtype[bool_]], count_times: ndarray[tuple[NumFrames | Literal[1]], dtype[floating]], incident_flux: ndarray[tuple[NumFrames | Literal[1]], dtype[number]], transmitted_flux: ndarray[tuple[NumFrames | Literal[1]], dtype[number]], minimum_pulse_separation: float, minimum_arrival_separation: float, base_dark_current: float, temporal_dark_current: float, flux_dependant_dark_current: float, beam_center_pixels: tuple[float, float], pixel_sizes: tuple[float, float], sample_detector_separation: float) → ndarray[tuple[NumFrames, FrameWidth, FrameHeight], dtype[number]]

Applies a sequence of corrections to correct for instrumental background.

Applies an ordered sequence of corrections to correct for instrumental background, as detailed as Process A in section 2 of ‘The modular small-angle X-ray scattering data correction sequence’ [https://doi.org/10.1107/S1600576717015096].

Parameters:

• frames – A sequence of frames, on which the series of corrections should be applied.

• mask – The boolean mask to apply to each frame.

• count_times – The period over which photons are counted for each frame in the sequence, or a single value which is applied to all frames in the sequence.

• incident_flux – The flux intensity observed upstream of the sample.

• transmitted_flux – The flux intensity observed downstream of the sample.

• minimum_pulse_separation – The minimum time difference required between a prior pulse and the current pulse for the current pulse to be recorded correctly.

• minimum_arrival_separation – The minimum time difference required between the current pulse and a subsequent pulse for the current pulse to be recorded correctly.

• base_dark_current – The dark current flux, irrespective of time.

• temporal_dark_current – The dark current flux, as a factor of time.

• flux_dependant_dark_current – The dark current flux, as a factor of incident flux.

• beam_center_pixels – The center position of the beam in pixels.

• pixel_sizes – The real space size of a detector pixel.

Returns:

The corrected stack of frames.

class adcorr.sequences.pauw.NumBackgrounds

The number of background frames in a stack of frames

alias of TypeVar(‘NumBackgrounds’, bound=int)

adcorr.sequences.pauw.pauw_simple_sample_sequence(frames: ndarray[tuple[NumFrames, FrameWidth, FrameHeight], dtype[number]], backgrounds: ndarray[tuple[NumBackgrounds, FrameWidth, FrameHeight], dtype[number]], mask: ndarray[tuple[FrameWidth, FrameHeight], dtype[bool_]], flatfield: ndarray[tuple[FrameWidth, FrameHeight], dtype[floating]], frames_count_times: ndarray[tuple[NumFrames | Literal[1]], dtype[floating]], backgrounds_count_times: ndarray[tuple[NumBackgrounds | Literal[1]], dtype[floating]], frames_incident_flux: ndarray[tuple[NumFrames | Literal[1]], dtype[number]], frames_transmitted_flux: ndarray[tuple[NumFrames | Literal[1]], dtype[number]], background_incident_flux: ndarray[tuple[NumBackgrounds | Literal[1]], dtype[number]], background_transmitted_flux: ndarray[tuple[NumBackgrounds | Literal[1]], dtype[number]], minimum_pulse_separation: float, minimum_arrival_separation: float, base_dark_current: float, temporal_dark_current: float, flux_dependant_dark_current: float, beam_center_pixels: tuple[float, float], pixel_sizes: tuple[float, float], sample_detector_separation: float, sensor_absorption_coefficient: float, sample_thickness: float, sensor_thickness: float, beam_polarization: float) → ndarray[tuple[NumFrames, FrameWidth, FrameHeight], dtype[number]]

Applies an ordered sequence of corrections to frames containing a simple sample.

Applies an ordered sequence of corrections to correct for instrumental and experiment backgrounds as detailed as Process B in section 2 of ‘The modular small- angle X-ray scattering data correction sequence [https://doi.org/10.1107/S1600576717015096].

Parameters:

• frames – A sequence of frames, on which the series of corrections should be applied.

• backgrounds – A sequence of background frames, which should be subtracted from the foreground frames post correction.

• mask – The boolean mask to apply to each frame.

• flatfield – The multiplicative flatfield correction to be applied to detector readings. If None, a uniform flatfield of ones is applied, resulting in no change to the frame.

• frames_count_times – The period over which photons are counted for each frame in the frames sequence, or a single value which is applied to all frames in the sequence.

• backgrounds_count_times – The period over which photons are counted for each frame in the backgrounds sequence, or a single value which is applied to all frames in the sequence.

• frames_incident_flux – The flux intensity observed upstream of the sample for each frame in the frames sequence.

• frames_transmitted_flux – The flux intensity observed downstream of the sample for each frame in the frames sequence.

• background_incident_flux – The flux intensity observed upstream of the sample for each frame in the backgrounds sequence.

• background_transmitted_flux – The flux intensity observed downstream of the sample for each frame in the backgrounds sequence.

• minimum_pulse_separation – The minimum time difference required between a prior pulse and the current pulse for the current pulse to be recorded correctly.

• minimum_arrival_separation – The minimum time difference required between the current pulse and a subsequent pulse for the current pulse to be recorded correctly.

• base_dark_current – The dark current flux, irrespective of time.

• temporal_dark_current – The dark current flux, as a factor of time.

• flux_dependant_dark_current – The dark current flux, as a factor of incident flux.

• beam_center_pixels – The center position of the beam in pixels.

• pixel_sizes – The real space size of a detector pixel.

• sample_detector_separation – The distance between the detector and the sample.

• sensor_absorption_coefficient – The coefficient of absorption for a given detector head material at a given photon energy.

• sample_thickness – The thickness of the sample material.

• sensor_thickness – The thickness of the detector head material.

• beam_polarization – The fraction of incident radiation polarized in the horizontal plane, where 0.5 signifies an unpolarized source.

Returns:

The corrected stack of frames.

class adcorr.sequences.pauw.NumDispersants

The number of dispersant frames in a stack of frames

alias of TypeVar(‘NumDispersants’, bound=int)

adcorr.sequences.pauw.pauw_dispersed_sample_sequence(frames: ndarray[tuple[NumFrames, FrameWidth, FrameHeight], dtype[number]], dispersants: ndarray[tuple[NumDispersants, FrameWidth, FrameHeight], dtype[number]], backgrounds: ndarray[tuple[NumBackgrounds, FrameWidth, FrameHeight], dtype[number]], mask: ndarray[tuple[FrameWidth, FrameHeight], dtype[bool_]], flatfield: ndarray[tuple[FrameWidth, FrameHeight], dtype[floating]], frame_count_times: ndarray[tuple[NumFrames | Literal[1]], dtype[floating]], dispersant_count_times: ndarray[tuple[NumDispersants | Literal[1]], dtype[floating]], background_count_times: ndarray[tuple[NumBackgrounds | Literal[1]], dtype[floating]], frames_incident_flux: ndarray[tuple[NumFrames | Literal[1]], dtype[number]], frames_transmitted_flux: ndarray[tuple[NumFrames | Literal[1]], dtype[number]], dispersant_incident_flux: ndarray[tuple[NumDispersants | Literal[1]], dtype[number]], dispersant_transmitted_flux: ndarray[tuple[NumDispersants | Literal[1]], dtype[number]], background_incident_flux: ndarray[tuple[NumBackgrounds | Literal[1]], dtype[number]], background_transmitted_flux: ndarray[tuple[NumBackgrounds | Literal[1]], dtype[number]], minimum_pulse_separation: float, minimum_arrival_separation: float, base_dark_current: float, temporal_dark_current: float, flux_dependant_dark_current: float, beam_center_pixels: tuple[float, float], pixel_sizes: tuple[float, float], sample_detector_separation: float, sensor_absorption_coefficient: float, sample_thickness: float, sensor_thickness: float, beam_polarization: float, displaced_fraction: float) → ndarray[tuple[NumFrames, FrameWidth, FrameHeight], dtype[number]]

Applies a sequence of corrections to frames containing a dispersed sample.

Applies an ordered sequence of corrections to correct for instrumental background, as detailed as Process C in section 2 of ‘The modular small-angle X-ray scattering data correction sequence’ [https://doi.org/10.1107/S1600576717015096].

Parameters:

• frames – A sequence of frames, on which the series of corrections should be applied.

• dispersants – A sequence of dispersant frames, which should be subtracted from the foreground frames following simple sample corrections.

• backgrounds – A sequence of background frames, which should be subtracted from the dispersant and foreground frames following instrumental background corrections.

• mask – The boolean mask to apply to each frame.

• flatfield – The multiplicative flatfield correction to be applied to detector readings. If None, a uniform flatfield of ones is applied, resulting in no change to the frame.

• frame_count_times – The period over which photons are counted for each frame in the frames sequence, or a single value which is applied to all frames in the sequence.

• dispersant_count_times – The period over which photons are counted for each frame in the despersants sequence, or a single value which is applied to all frames in the sequence.

• background_count_times – The period over which photons are counted for each frame in the backgrounds sequence, or a single value which is applied to all frames in the sequence.

• frames_incident_flux – The flux intensity observed upstream of the sample for each frame in the frames sequence.

• frames_transmitted_flux – The flux intensity observed downstream of the sample for each frame in the frames sequence.

• background_incident_flux – The flux intensity observed upstream of the sample for each frame in the backgrounds sequence.

• background_transmitted_flux – The flux intensity observed downstream of the sample for each frame in the backgrounds sequence.

• dispersants_incident_flux – The flux intensity observed upstream of the sample for each frame in the dispersants sequence.

• dispersants_transmitted_flux – The flux intensity observed downstream of the sample for each frame in the dispersants sequence.

• minimum_pulse_separation – The minimum time difference required between a prior pulse and the current pulse for the current pulse to be recorded correctly.

• minimum_arrival_separation – The minimum time difference required between the current pulse and a subsequent pulse for the current pulse to be recorded correctly.

• base_dark_current – The dark current flux, irrespective of time.

• temporal_dark_current – The dark current flux, as a factor of time.

• flux_dependant_dark_current – The dark current flux, as a factor of incident flux.

• beam_center_pixels – The center position of the beam in pixels.

• pixel_sizes – The real space size of a detector pixel.

• sample_detector_separation – The distance between the detector and the sample.

• sensor_absorption_coefficient – The coefficient of absorption for a given detector head material at a given photon energy.

• sample_thickness – The thickness of the sample material.

• sensor_thickness – The thickness of the detector head material.

• beam_polarization – The fraction of incident radiation polarized in the horizontal plane, where 0.5 signifies an unpolarized source.

• displaced_fraction – The fraction of solvent displaced by the analyte.

Returns:

The corrected stack of frames.

adcorr.utils

adcorr.utils.geometry

adcorr.utils.geometry.scattering_angles(frame_shape: Tuple[int, int], beam_center: Tuple[float, float], pixel_sizes: Tuple[float, float], distance: float) → ndarray[Tuple[int, int], dtype[floating]]

Computes the angles of pixels from the sample for a given geometry.

Parameters:

• frame_shape – The shape of a frame.

• beam_center – The center position of the beam in pixels.

• pixel_sizes – The real space size of a detector pixel.

• distance – The distance between the detector and the sample.

Returns:

An array of pixel angles from the sample.

adcorr.utils.geometry.azimuthal_angles(frame_shape: Tuple[int, int], beam_center: Tuple[float, float], pixel_sizes: Tuple[float, float]) → ndarray[Tuple[int, int], dtype[floating]]

Computes the azimuthal angles of pixels from the beam center.

Parameters:

• frame_shape – The shape of the frame.

• beam_center – The center position of the beam in pixels.

Returns:

An array of pixel azimuthal angles from the beam center.

adcorr.utils.typing

class adcorr.utils.typing.FrameDType

The underlying data type of a frame.

alias of TypeVar(‘FrameDType’, bound=dtype)

class adcorr.utils.typing.NumFrames

The number of frames in a stack of frames.

alias of TypeVar(‘NumFrames’, bound=int)

class adcorr.utils.typing.FrameWidth

The number of pixels spanning the width of a frame.

alias of TypeVar(‘FrameWidth’, bound=int)

class adcorr.utils.typing.FrameHeight

The number of pixels spanning the height of a frame.

alias of TypeVar(‘FrameHeight’, bound=int)

adcorr.utils.typing.VectorOrSingle

An array with the given length, or a singular value

adcorr.utils.typing.Frame

A frame; Comprising a shape and a data type

adcorr.utils.typing.Frames

A stack of frames; Comprising a shape and a data type

adcorr.__version__: str

Version number as calculated by dls-controls/versiongit