FlexibleAnnularDetector

class abtem.detectors.FlexibleAnnularDetector(step_size=1.0, inner=0.0, outer=None, to_cpu=True, url=None)

Bases: _AbstractRadialDetector

The flexible annular detector allows choosing the integration limits after running the simulation by binning the intensity in annular integration regions.

Parameters:

• step_size (float, optional) – Radial extent of the bins [mrad] (default is 1).

• inner (float, optional) – Inner integration limit of the bins [mrad].

• outer (float, optional) – Outer integration limit of the bins [mrad].

• to_cpu (bool, optional) – If True, copy the measurement data from the calculation device to CPU memory after applying the detector, otherwise the data stays on the respective devices. Default is True.

• url (str, optional) – If this parameter is set the measurement data is saved at the specified location, typically a path to a local file. A URL can also include a protocol specifier like s3:// for remote data. If not set (default) the data stays in memory.

__init__(step_size=1.0, inner=0.0, outer=None, to_cpu=True, url=None)

Methods

__init__([step_size, inner, outer, to_cpu, url])
angular_limits(waves)	The outer limits of the detected scattering angles in x and y [mrad] for the given waves.
apply(array_object)	Apply the transform to the given waves.
copy()	Make a copy.
detect(waves)	Detect the given waves producing polar measurements.
ensemble_blocks([chunks])	Split the ensemble into an array of smaller ensembles.
generate_blocks([chunks])	Generate chunks of the ensemble.
get_detector_regions([waves])	Get the polar detector regions as a polar measurement.
select_block(index, chunks)	Select a block from the ensemble.
show([waves, gpts, sampling, energy])	Show the segmented detector regions as a polar plot.

Attributes

axes_metadata	List of AxisMetadata.
azimuthal_sampling	Spacing between the azimuthal detector bins [mrad].
base_axes_metadata	List of AxisMetadata of the base axes.
base_shape	Shape of the base axes.
ensemble_axes_metadata	Axes metadata describing the ensemble axes added to the waves when applying the transform.
ensemble_shape	The shape of the ensemble axes added to the waves when applying the transform.
inner	Inner integration limit [mrad].
metadata	Metadata added to the waves when applying the transform.
nbins_azimuthal	Spacing between the azimuthal detector bins [mrad].
nbins_radial	Spacing between the azimuthal detector bins [mrad].
outer	Outer integration limit [mrad].
radial_sampling	Spacing between the radial detector bins [mrad].
rotation	Rotation of the bins around the origin [rad].
shape	Shape of the ensemble.
step_size	Step size [mrad].
to_cpu	The measurements are copied to host memory.
url	The storage location of the measurement data.

angular_limits(waves)

The outer limits of the detected scattering angles in x and y [mrad] for the given waves.

Parameters:

waves (BaseWaves) – The waves to derive the detector limits from.

Returns:

limits

Return type:

tuple of float

apply(array_object)

Apply the transform to the given waves.

Parameters:

array_object (ArrayObject) – The array object to transform.

Returns:

transformed_array_object

Return type:

ArrayObject

property axes_metadata: AxesMetadataList

List of AxisMetadata.

property azimuthal_sampling: float

Spacing between the azimuthal detector bins [mrad].

property base_axes_metadata: list[AxisMetadata]

List of AxisMetadata of the base axes.

property base_shape: tuple[int, ...]

Shape of the base axes.

copy()

Make a copy.

detect(waves)

Detect the given waves producing polar measurements.

Parameters:

waves (Waves) – The waves to detect.

Returns:

measurement

Return type:

PolarMeasurements

property ensemble_axes_metadata: list[AxisMetadata]

Axes metadata describing the ensemble axes added to the waves when applying the transform.

ensemble_blocks(chunks=None)

Split the ensemble into an array of smaller ensembles.

Parameters:

chunks (iterable of tuples) – Block sizes along each dimension.

Return type:

Array

property ensemble_shape: tuple[int, ...]

The shape of the ensemble axes added to the waves when applying the transform.

generate_blocks(chunks=1)

Generate chunks of the ensemble.

Parameters:

chunks (iterable of tuples) – Block sizes along each dimension.

get_detector_regions(waves=None)

Get the polar detector regions as a polar measurement.

Parameters:

waves (BaseWaves) – The waves to derive the polar detector regions from.

Returns:

detector_region

Return type:

PolarMeasurements

property inner: float

Inner integration limit [mrad].

property metadata: dict

Metadata added to the waves when applying the transform.

property nbins_azimuthal

Spacing between the azimuthal detector bins [mrad].

property nbins_radial

Spacing between the azimuthal detector bins [mrad].

property outer: float

Outer integration limit [mrad].

property radial_sampling: float

Spacing between the radial detector bins [mrad].

property rotation

Rotation of the bins around the origin [rad].

select_block(index, chunks)

Select a block from the ensemble.

Parameters:

• index (tuple of ints) – Index of selected block.

• chunks (iterable of tuples) – Block sizes along each dimension.

property shape

Shape of the ensemble.

show(waves=None, gpts=None, sampling=None, energy=None, **kwargs)

Show the segmented detector regions as a polar plot.

Parameters:

• waves (BaseWaves) – The waves to derive the segmented detector regions from.

• gpts (two int, optional) – Number of grid points describing the wave functions to be detected.

• sampling (two float, optional) – Lateral sampling of the wave functions to be detected [1 / Å].

• energy (float, optional) – Electron energy of the wave functions to be detected [eV].

• kwargs – Optional keyword arguments for DiffractionPatterns.show.

Returns:

visualization

Return type:

Visualization

property step_size: float

Step size [mrad].

property to_cpu

The measurements are copied to host memory.

property url

The storage location of the measurement data.