FlexibleAnnularDetector#

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

Bases: abtem.detectors._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)[source]#

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])	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.
`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: abtem.core.axes.AxesMetadataList#

List of AxisMetadata.

Return type: AxesMetadataList

property azimuthal_sampling: float#

Spacing between the azimuthal detector bins [mrad].

Return type: float

property base_axes_metadata: list[abtem.core.axes.AxisMetadata]#

List of AxisMetadata of the base axes.

Return type: list[AxisMetadata]

property base_shape: tuple[int, ...]#

Shape of the base axes.

Return type: tuple[int, ...]

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[abtem.core.axes.AxisMetadata]#

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

Return type: list[AxisMetadata]

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.

Return type: tuple[int, ...]

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].

Return type: float

property metadata: dict#

Metadata added to the waves when applying the transform.

Return type: dict

property outer: float#

Outer integration limit [mrad].

Return type: float

property radial_sampling: float#

Spacing between the radial detector bins [mrad].

Return type: float

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, **kwargs)#

Show the segmented detector regions as a polar plot.

Parameters

waves (BaseWaves) – The waves to derive the segmented detector regions from.
kwargs – Optional keyword arguments for PolarMeasurements.show.

Returns

visualization

Return type

MeasurementVisualization2D

property step_size: float#

Step size [mrad].

Return type: float

property to_cpu#: The measurements are copied to host memory.

property url#: The storage location of the measurement data.