dscribe.descriptors.acsf module

Copyright 2019 DScribe developers

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class dscribe.descriptors.acsf.ACSF(rcut, g2_params=None, g3_params=None, g4_params=None, g5_params=None, species=None, periodic=False, sparse=False)[source]

Bases: dscribe.descriptors.descriptor.Descriptor

Implementation of Atom-Centered Symmetry Functions.

Notice that the species of the central atom is not encoded in the output, only the surrounding environment is encoded. In a typical application one can train a different model for each central species.

For reference, see:

“Atom-centered symmetry functions for constructing high-dimensional neural network potentials”, Jörg Behler, The Journal of Chemical Physics, 134, 074106 (2011), https://doi.org/10.1063/1.3553717

Parameters

  • rcut (float) – The smooth cutoff value in angstroms. This cutoff value is used throughout the calculations for all symmetry functions.

  • g2_params (n*2 np.ndarray) – A list of pairs of \(\eta\) and \(R_s\) parameters for \(G^2\) functions.

  • g3_params (n*1 np.ndarray) – A list of \(\kappa\) parameters for \(G^3\) functions.

  • g4_params (n*3 np.ndarray) – A list of triplets of \(\eta\), \(\zeta\) and \(\lambda\) parameters for \(G^4\) functions.

  • g5_params (n*3 np.ndarray) – A list of triplets of \(\eta\), \(\zeta\) and \(\lambda\) parameters for \(G^5\) functions.

  • species (iterable) – The chemical species as a list of atomic numbers or as a list of chemical symbols. Notice that this is not the atomic numbers that are present for an individual system, but should contain all the elements that are ever going to be encountered when creating the descriptors for a set of systems. Keeping the number of chemical species as low as possible is preferable.

  • periodic (bool) – Set to true if you want the descriptor output to respect the periodicity of the atomic systems (see the pbc-parameter in the constructor of ase.Atoms).

  • sparse (bool) – Whether the output should be a sparse matrix or a dense numpy array.

create(system, positions=None, n_jobs=1, only_physical_cores=False, verbose=False)[source]

Return the ACSF output for the given systems and given positions.

Parameters

  • system (ase.Atoms or list of ase.Atoms) – One or many atomic structures.

  • positions (list) – Positions where to calculate ACSF. Can be provided as cartesian positions or atomic indices. If no positions are defined, the SOAP output will be created for all atoms in the system. When calculating SOAP for multiple systems, provide the positions as a list for each system.

  • n_jobs (int) – Number of parallel jobs to instantiate. Parallellizes the calculation across samples. Defaults to serial calculation with n_jobs=1. If a negative number is given, the used cpus will be calculated with, n_cpus + n_jobs, where n_cpus is the amount of CPUs as reported by the OS. With only_physical_cores you can control which types of CPUs are counted in n_cpus.

  • only_physical_cores (bool) – If a negative n_jobs is given, determines which types of CPUs are used in calculating the number of jobs. If set to False (default), also virtual CPUs are counted. If set to True, only physical CPUs are counted.

  • verbose (bool) – Controls whether to print the progress of each job into to the console.

Returns

The ACSF output for the given systems and positions. The return type depends on the ‘sparse’-attribute. The first dimension is determined by the amount of positions and systems and the second dimension is determined by the get_number_of_features()-function. When multiple systems are provided the results are ordered by the input order of systems and their positions.

Return type

np.ndarray | sparse.COO

create_single(system, positions=None)[source]

Creates the descriptor for the given system.

Parameters

  • system (ase.Atoms | System) – Input system.

  • positions (iterable) – Indices of the atoms around which the ACSF will be returned. If no positions defined, ACSF will be created for all atoms in the system.

Returns

The ACSF output for the given system and positions. The return type depends on the ‘sparse’-attribute. The first dimension is given by the number of positions and the second dimension is determined by the get_number_of_features()-function.

Return type

np.ndarray | sparse.COO

property g2_params
property g3_params
property g4_params
property g5_params
get_number_of_features()[source]

Used to inquire the final number of features that this descriptor will have.

Returns

Number of features for this descriptor.

Return type

int

property rcut
property species