MultisliceTransform

MultisliceTransform#

class abtem.multislice.MultisliceTransform(potential, detectors=None, multislice_func=None, **multislice_func_kwargs)[source]#

Transformation applying the multislice algorithm to wave functions, producing new wave functions or measurements.

Parameters:

potential (BasePotential) – A potential as BasePotential object.
detectors ((list of) BaseDetector, optional) – A detector or a list of detectors defining how the wave functions should be converted to measurements after running the multislice algorithm.
multislice_func (callable, optional) – The multislice function defining the multislice algorithm used (default is multislice_and_detect()).
**multislice_func_kwargs – Additional keyword arguments passed to the multislice function.

__init__(potential, detectors=None, multislice_func=None, **multislice_func_kwargs)[source]#

Methods

`__init__`(potential[, detectors, multislice_func])
`apply`(waves[, max_batch])	Run the multislice algorithm on the given wave functions.
`copy`()	Make a copy.
`ensemble_blocks`([chunks])	Split the ensemble into an array of smaller ensembles.
`generate_blocks`([chunks])	Generate chunks of the ensemble.

Attributes

`axes_metadata`	List of AxisMetadata.
`base_axes_metadata`	List of AxisMetadata of the base axes.
`base_shape`	Shape of the base axes.
`detectors`	List of detectors defining how the wave functions should be converted to measurements.
`distributions`
`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.
`metadata`	Metadata added to the waves when applying the transform.
`multislice_func`	The multislice function defining the multislice algorithm used.
`potential`	Electrostatic potential for each multislice slice.
`shape`	Shape of the ensemble.

apply(waves, max_batch='auto')[source]#

Run the multislice algorithm on the given wave functions. An output is returned for each detector.

Parameters:

waves (Waves) – The wave functions to run the multislice algorithm on.
max_batch (int or str, optional) – The maximum batch size to use for the multislice algorithm. If ‘auto’ the batch size is chosen automatically based on the available memory.

Returns:

waves – The wave functions after running the multislice algorithm.

Return type:

tuple of Waves and BaseMeasurements

property base_axes_metadata: list[AxisMetadata]#: List of AxisMetadata of the base axes.

copy()#

Make a copy.

property detectors: list[BaseDetector]#: List of detectors defining how the wave functions should be converted to measurements.

property ensemble_axes_metadata#: 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#: 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.
Return type:: Generator[tuple[tuple[int, ...], tuple[slice, ...], ndarray], None, None]

property metadata: dict#: Metadata added to the waves when applying the transform.

property multislice_func: Callable#: The multislice function defining the multislice algorithm used.

property potential: BasePotential#: Electrostatic potential for each multislice slice.