FrozenPhonons#

class abtem.inelastic.phonons.FrozenPhonons(atoms, num_configs, sigmas, directions='xyz', ensemble_mean=True, seed=None)[source]#

Bases: abtem.inelastic.phonons.BaseFrozenPhonons

The frozen phonons randomly displace the atomic positions to emulate thermal vibrations.

Parameters

atoms (ASE.Atoms) – Atomic configuration used for displacements.
num_configs (int) – Number of frozen phonon configurations.
sigmas (float or dict or list) –
If float, the standard deviation of the displacements is assumed to be identical for all atoms. If dict, a displacement standard deviation should be provided for each species. The atomic species can be specified as atomic number or a symbol, using the ASE standard. If list or array, a displacement standard deviation should be provided for each atom.

Anistropic displacements may be given by providing a standard deviation for each principal direction. This may be a tuple of three numbers for identical displacements for all atoms. A dict of tuples of three numbers to specify displacements for each species. A list or array with three numbers for each atom.
directions (str, optional) – The displacement directions of the atoms as a string; for example ‘xy’ (default) for displacement in the x- and y-direction (i.e. perpendicular to the propagation direction).
ensemble_mean (bool, optional) – If True (default), the mean of the ensemble of results from a multislice simulation is calculated, otherwise, the result of every frozen phonon configuration is returned.
seed (int or sequence of int) – Seed(s) for the random number generator used to generate the displacements, or one seed for each configuration in the frozen phonon ensemble.

__init__(atoms, num_configs, sigmas, directions='xyz', ensemble_mean=True, seed=None)[source]#

Methods

`__init__`(atoms, num_configs, sigmas[, ...])
`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.
`to_atoms_ensemble`()	Convert the frozen phonons to an ensemble of atoms.

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.
`directions`	The directions of the random displacements.
`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.
`seed`	Random seed for each displacement configuration.
`shape`	Shape of the ensemble.
`sigmas`	Displacement standard deviation for each atom.

property atomic_numbers: numpy.ndarray#

The unique atomic number of the atoms.

Return type: ndarray

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 directions: str#

The directions of the random displacements.

Return type: str

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#: Shape of the ensemble axes.

generate_blocks(chunks=1)#

Generate chunks of the ensemble.

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

property num_configs: int#

Number of atomic configurations.

Return type: int

randomize(atoms)[source]#

Randomize the atoms.

Parameters: atoms (Atoms) –
Return type: Atoms

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

Random seed for each displacement configuration.

Return type: tuple[int, ...]

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.

property sigmas: float | dict[str | int, float] | Sequence[float]#

Displacement standard deviation for each atom.

Return type: float | dict[str | int, float] | Sequence[float]

to_atoms_ensemble()[source]#

Convert the frozen phonons to an ensemble of atoms.

Returns: atoms_ensemble
Return type: AtomsEnsemble