BaseFrozenPhonons#

class abtem.inelastic.phonons.BaseFrozenPhonons(atomic_numbers, cell, ensemble_mean=True)[source]#

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

Base class for frozen phonons.

__init__(atomic_numbers, cell, ensemble_mean=True)[source]#

Methods

`__init__`(atomic_numbers, cell[, ensemble_mean])
`copy`()	Make a copy.
`ensemble_blocks`([chunks])	Split the ensemble into an array of smaller ensembles.
`generate_blocks`([chunks])	Generate chunks of the ensemble.
`randomize`(atoms)	Randomize the atoms.
`select_block`(index, chunks)	Select a block from the ensemble.

Attributes

`atomic_numbers`	The unique atomic number of the atoms.
`atoms`	Base atomic configuration used for displacements.
`axes_metadata`	List of AxisMetadata.
`base_axes_metadata`	List of AxisMetadata of the base axes.
`base_shape`	Shape of the base axes.
`cell`	The cell of the atoms.
`ensemble_axes_metadata`	List of AxisMetadata of the ensemble axes.
`ensemble_mean`	The mean of the ensemble of results from a multislice simulation is calculated.
`ensemble_shape`	Shape of the ensemble axes.
`num_configs`	Number of atomic configurations.
`shape`	Shape of the ensemble.

property atomic_numbers: numpy.ndarray#

The unique atomic number of the atoms.

Return type: ndarray

abstract property atoms: ase.atoms.Atoms#

Base atomic configuration used for displacements.

Return type: Atoms

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 of the base axes.

Return type: list[AxisMetadata]

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

Shape of the base axes.

Return type: tuple[int, ...]

property cell: ase.cell.Cell#

The cell of the atoms.

Return type: Cell

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_mean#: The mean of the ensemble of results from a multislice simulation is calculated.

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

Shape of the ensemble axes.

Return type: tuple[int, ...]

generate_blocks(chunks=1)#

Generate chunks of the ensemble.

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

abstract property num_configs#: Number of atomic configurations.

abstract randomize(atoms)[source]#

Randomize the atoms.

Parameters: atoms (Atoms) –
Return type: Atoms

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.