from . import operations
from .. import Gratoms
from ..gen import utils
import pkg_resources
import json
import numpy as np
import ase
[docs]class Fingerprinter():
"""Parent class for all fingerprint generators."""
def __init__(self, images=None):
"""Store the properties of the databases being loaded as
as needed.
Parameters
----------
images : list
Atoms objects to generate fingerprints for.
"""
if isinstance(images, ase.Atoms):
images = [images]
self._images = images
self._data = None
self._slab_d_data = None
self._bulk_d_data = None
self._mendeleev_data = None
def _get_data(self):
"""A lazy evaluator for loading general data."""
data = self._data
if data is None:
path = pkg_resources.resource_filename(
'catkit', 'data/properties.json')
with open(path, 'r') as f:
data = json.load(f)
self._data = data
return data
def _get_atoms_parameters(self, atoms, parameters):
"""Return the parameters associated with a specific atoms
object and seed parameters set.
Parameters
----------
atoms : object
Structure to return parameters for, contains n atoms.
parameters : list of str (m,)
Seed parameters to use for atom specific parameter
generation.
Returns
-------
atoms_parameters : ndarray (m, n)
General chemical properties specific to this atoms object
and list of seed parameters.
"""
data = self._get_data()
num = atoms.numbers
atoms_parameters = np.zeros((len(parameters), len(num)))
for i, k in enumerate(parameters):
atoms_parameters[i] = np.asarray(data[k])[num]
return atoms_parameters
[docs] def get_fp(self, parameters, operation_list):
"""Return the fingerprints for a list of images of single atoms
object for the given parameters.
Parameters
----------
parameters : list of str
Names of seeding parameters available in the parameters
database.
operation_list : list of functions
A list of operation functions to produce the fingerprints from.
Returns
-------
fingerprints : ndarray (n, m)
Fingerprints for the images produced from the provided
seed parameters.
"""
fingerprints = [[] for _ in self._images]
for i, atoms in enumerate(self._images):
atoms_parameters = self._get_atoms_parameters(atoms, parameters)
method = None
if np.all(atoms.pbc):
method = 'voronoi'
if isinstance(atoms, Gratoms):
connectivity = atoms.connectivity
else:
connectivity = get_connectivity(atoms, method=method)
for j, operation in enumerate(operation_list):
kwargs = {}
if isinstance(operation, list):
operation, kwargs = operation
if isinstance(operation, str):
operation = getattr(operations, operation)
fingerprint = _generate_fingerprint(
operation,
atoms,
atoms_parameters,
connectivity,
**kwargs)
fingerprints[i] += [fingerprint]
fingerprints = np.block(fingerprints)
return fingerprints
def _generate_fingerprint(
operation,
atoms,
atoms_parameters,
connectivity,
**kwargs):
"""Return the parameters of a convolutions of atomic properties
based on connectivity in a periodic unit cell.
Parameters
----------
operations : list of functions
A list of operation functions to produce the fingerprints from.
atoms : object
Atomic structure to generate fingerprint for.
atoms_parameters : ndarray (n, m)
General chemical properties specific to this atoms object
and list of seed parameters.
connectivity : ndarray (n, n)
Estimated connectivity matrix where n is the number
of atoms in the atoms-object.
Returns
-------
fingerprint : ndarray (m,)
Fingerprint produced from a given operation and seed parameters.
"""
fingerprint = operation(
atoms=atoms,
atoms_parameters=atoms_parameters,
connectivity=connectivity,
**kwargs)
return fingerprint
[docs]def get_connectivity(atoms, method=None):
"""Returns an estimate of the connectivity matrix
for a given atoms-object from CatGen.
Parameters
----------
atoms : object
Molecular structure with out without adsorbates.
method : str (None or 'voronoi')
Method for estimating the connectivity matrix:
None - standard cutoff radius method.
voronoi - best suited for bulk characterization.
Returns
-------
connectivity : ndarray (n, n)
Estimated connectivity matrix where n is the number
of atoms in the atoms-object.
"""
if method == 'voronoi':
connectivity = utils.get_voronoi_neighbors(atoms)
else:
connectivity = utils.get_cutoff_neighbors(atoms)
return connectivity