BasePotential#

class abtem.potentials.iam.BasePotential[source]#

Bases: abtem.core.ensemble.Ensemble, abtem.core.grid.HasGridMixin, abtem.core.utils.EqualityMixin, abtem.core.utils.CopyMixin

Base class of all potentials. Documented in the subclasses.

__init__()#

Methods

`__init__`()
`build`([first_slice, last_slice, chunks, lazy])
`copy`()	Make a copy.
`ensemble_blocks`([chunks])	Split the ensemble into an array of smaller ensembles.
`generate_blocks`([chunks])	Generate chunks of the ensemble.
`generate_slices`([first_slice, last_slice])
`match_grid`(other[, check_match])	Match the grid to another object with a Grid.
`project`()	Sum of the potential slices as an image.
`select_block`(index, chunks)	Select a block from the ensemble.
`show`([project])	Show the potential projection.
`to_images`()	Converts the potential to an ensemble of images.

Attributes

`axes_metadata`	List of AxisMetadata.
`base_axes_metadata`	List of AxisMetadata for the base axes.
`base_shape`	Shape of the base axes of the potential.
`ensemble_axes_metadata`	List of AxisMetadata of the ensemble axes.
`ensemble_shape`	Shape of the ensemble axes.
`exit_planes`	The "exit planes" of the potential.
`exit_thicknesses`	The "exit thicknesses" of the potential.
`extent`	Extent of grid for each dimension in Ångstrom.
`gpts`	Number of grid points for each dimension.
`grid`	Simulation grid.
`num_exit_planes`	Number of exit planes.
`num_frozen_phonons`	Number of frozen phonons in the ensemble of potentials.
`num_slices`	Number of projected potential slices.
`reciprocal_space_sampling`	Reciprocal-space sampling in reciprocal Ångstrom.
`sampling`	Grid sampling for each dimension in Ångstrom per grid point.
`shape`	Shape of the ensemble.
`slice_limits`	The entrance and exit thicknesses of each slice [Å].
`slice_thickness`	Slice thicknesses for each slice.
`thickness`	Thickness of the potential [Å].

property axes_metadata: abtem.core.axes.AxesMetadataList#

List of AxisMetadata.

Return type: AxesMetadataList

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

List of AxisMetadata for the base axes.

Return type: list[AxisMetadata]

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

Shape of the base axes of the potential.

Return type: tuple[int, ...]

copy()#: Make a copy.

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

List of AxisMetadata of the ensemble axes.

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, ...]#

Shape of the ensemble axes.

Return type: tuple[int, ...]

abstract property exit_planes: tuple[int, ...]#

The “exit planes” of the potential. The indices of slices where a measurement is returned.

Return type: tuple[int, ...]

property exit_thicknesses: tuple[float]#

The “exit thicknesses” of the potential. The thicknesses in the potential where a measurement is returned.

Return type: tuple[float]

property extent: tuple[float] | tuple[float, float] | tuple[float, ...]#

Extent of grid for each dimension in Ångstrom.

Return type: tuple[float] | tuple[float, float] | tuple[float, …]

generate_blocks(chunks=1)#

Generate chunks of the ensemble.

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

property gpts: tuple[int] | tuple[int, int] | tuple[int, ...]#

Number of grid points for each dimension.

Return type: tuple[int] | tuple[int, int] | tuple[int, …]

property grid: abtem.core.grid.Grid#

Simulation grid.

Return type: Grid

match_grid(other, check_match=False)#: Match the grid to another object with a Grid.

property num_exit_planes: int#

Number of exit planes.

Return type: int

abstract property num_frozen_phonons: int#

Number of frozen phonons in the ensemble of potentials.

Return type: int

property num_slices: int#

Number of projected potential slices.

Return type: int

project()[source]#

Sum of the potential slices as an image.

Returns: projected – The projected potential.
Return type: Images

property reciprocal_space_sampling: tuple[float] | tuple[float, float] | tuple[float, ...]#

Reciprocal-space sampling in reciprocal Ångstrom.

Return type: tuple[float] | tuple[float, float] | tuple[float, …]

property sampling: tuple[float] | tuple[float, float] | tuple[float, ...]#

Grid sampling for each dimension in Ångstrom per grid point.

Return type: tuple[float] | tuple[float, float] | tuple[float, …]

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(project=True, **kwargs)[source]#

Show the potential projection. This requires building all potential slices.

Parameters

project (bool, optional) – Show the projected potential (True, default) or show all potential slices. It is recommended to index a subset of the potential slices when this keyword set to False.
kwargs – Additional keyword arguments for the show method of Images.

property slice_limits: list[tuple[float, float]]#

The entrance and exit thicknesses of each slice [Å].

Return type: list[tuple[float, float]]

abstract property slice_thickness: numpy.ndarray#

Slice thicknesses for each slice.

Return type: ndarray

property thickness: float#

Thickness of the potential [Å].

Return type: float

to_images()[source]#

Converts the potential to an ensemble of images.

Returns: image_ensemble – The potential slices as images.
Return type: Images