TransformFromFunc

class abtem.transform.TransformFromFunc(func, func_kwargs)

Bases: ArrayObjectTransform[object, object]

__init__(func, func_kwargs)

Methods

__init__(func, func_kwargs)
apply(array_object[, max_batch])
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.
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.
func
func_kwargs
metadata	Metadata added to the waves when applying the transform.
shape	Shape of the ensemble.

property axes_metadata: AxesMetadataList

List of AxisMetadata.

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.

Return type:

Self

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.

Return type:

Generator[tuple[tuple[int, ...], tuple[slice, ...], ndarray], None, None]

property metadata: dict

Metadata added to the waves when applying the transform.

property shape: tuple[int, ...]

Shape of the ensemble.