# -*- coding: utf-8 -*-
"""Copyright 2019 DScribe developers
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
"""
from ase import Atoms
from dscribe.core.system import System
import numpy as np
[docs]
def system_stats(system_iterator):
"""
Args:
system_stats(iterable containing ASE.Atoms or System): The atomic
systems for which to gather statistics.
Returns:
Dict: A dictionary of different statistics for the system. The
dictionary will contain:
n_atoms_max: The maximum number of atoms in a system.
max_atomic_number: The highest atomic number
min_atomic_number: The lowest atomic number
atomic_numbers: List of present atomic numbers
element_symbols: List of present atomic symbols
min_distance: Minimum distance in the system
"""
n_atoms_max = 0
atomic_numbers = set()
symbols = set()
min_distance = None
for system in system_iterator:
n_atoms = len(system)
# Make ASE.Atoms into a System object
if isinstance(system, Atoms):
system = System.from_atoms(system)
i_atomic_numbers = set(system.get_atomic_numbers())
i_symbols = set(system.get_chemical_symbols())
distance_matrix = system.get_distance_matrix()
# Gather atomic numbers and symbols
atomic_numbers = atomic_numbers.union(i_atomic_numbers)
symbols = symbols.union(i_symbols)
# Gather maximum number of atoms
n_atoms_max = max(n_atoms, n_atoms_max)
# Gather min distance. For periodic systems we must also consider
# distances from an atom to it's periodic copy, as given by
# get_distance_matrix() on the diagonal.
if np.any(system.get_pbc()):
triu_indices = np.triu_indices(len(distance_matrix), k=0)
else:
triu_indices = np.triu_indices(len(distance_matrix), k=1)
distances = distance_matrix[triu_indices]
i_min_dist = distances.min()
if min_distance is None or i_min_dist < min_distance:
min_distance = i_min_dist
return {
"n_atoms_max": n_atoms_max,
"max_atomic_number": max(list(atomic_numbers)),
"min_atomic_number": min(list(atomic_numbers)),
"atomic_numbers": list(atomic_numbers),
"element_symbols": list(symbols),
"min_distance": min_distance,
}