def get_angles_distribution(atoms, ang_grid=9):
"""
Method to get the distribution of bond angles
in bins (default 9) with bonds defined from
the get_neighbor_list().
"""
conn = get_neighbor_list(atoms)
if conn is None:
conn = get_neighborlist(atoms)
bins = [0] * ang_grid
for atom in atoms:
for i in conn[atom.index]:
for j in conn[atom.index]:
if j != i:
a = atoms.get_angle(i, atom.index, j)
for k in range(ang_grid):
if (k + 1) * 180. / ang_grid > a > k * 180. / ang_grid:
bins[k] += 1
# Removing dobbelt counting
for i in range(ang_grid):
bins[i] /= 2.
return bins
def get_angles_distribution(atoms, ang_grid=9):
"""
Method to get the distribution of bond angles
in bins (default 9) with bonds defined from
the get_neighbor_list().
"""
from math import pi
conn = get_neighbor_list(atoms)
if conn is None:
conn = get_neighborlist(atoms)
bins = [0] * ang_grid
for atom in atoms:
for i in conn[atom.index]:
for j in conn[atom.index]:
if j != i:
a = atoms.get_angle([i, atom.index, j]) * 180 / pi
for k in range(ang_grid):
if (k + 1) * 180. / ang_grid > a > k * 180. / ang_grid:
bins[k] += 1
# Removing dobbelt counting
for i in range(ang_grid):
bins[i] /= 2.
return bins
def get_atoms_connections(atoms, max_conn=5):
"""
This method returns a list of the numbers of atoms
with X number of neighbors. The method utilizes the
neighbor list and hence inherit the restrictions for
neighbors.
"""
conn = get_neighbor_list(atoms)
if conn is None:
conn = get_neighborlist(atoms)
no_of_conn = [0] * max_conn
for i in range(len(atoms)):
no_of_conn[min(len(conn[i]), max_conn - 1)] += 1
return no_of_conn
def get_rings(atoms, rings=[5, 6, 7]):
"""
This method return a list of the number of atoms involved
in rings in the structures. It uses the neighbor
list hence inherit the restriction used for neighbors.
"""
conn = get_neighbor_list(atoms)
if conn is None:
conn = get_neighborlist(atoms)
no_of_loops = [0] * 8
for s1 in range(len(atoms)):
for s2 in conn[s1]:
v12 = [s1] + [s2]
for s3 in [s for s in conn[s2] if s not in v12]:
v13 = v12 + [s3]
if s1 in conn[s3]:
no_of_loops[3] += 1
for s4 in [s for s in conn[s3] if s not in v13]:
v14 = v13 + [s4]
if s1 in conn[s4]:
no_of_loops[4] += 1
for s5 in [s for s in conn[s4] if s not in v14]:
v15 = v14 + [s5]
if s1 in conn[s5]:
no_of_loops[5] += 1
for s6 in [s for s in conn[s5] if s not in v15]:
v16 = v15 + [s6]
if s1 in conn[s6]:
no_of_loops[6] += 1
for s7 in [s for s in conn[s6] if s not in v16]:
# v17 = v16 + [s7]
if s1 in conn[s7]:
no_of_loops[7] += 1
to_return = []
for ring in rings:
to_return.append(no_of_loops[ring])
return to_return
def get_connections_index(atoms, max_conn=5, no_count_types=None):
"""
This method returns a dictionary where each key value are a
specific number of neighbors and list of atoms indices with
that amount of neighbors respectively. The method utilizes the
neighbor list and hence inherit the restrictions for
neighbors. Option added to remove connections between
defined atom types.
Parameters
----------
atoms : Atoms object
The connections will be counted using this supplied Atoms object
max_conn : int
Any atom with more connections than this will be counted as
having max_conn connections.
Default 5
no_count_types : list or None
List of atomic numbers that should be excluded in the count.
Default None (meaning all atoms count).
"""
conn = get_neighbor_list(atoms)
if conn is None:
conn = get_neighborlist(atoms)
if no_count_types is None:
no_count_types = []
conn_index = {}
for i in range(len(atoms)):
if atoms[i].number not in no_count_types:
cconn = min(len(conn[i]), max_conn - 1)
if cconn not in conn_index:
conn_index[cconn] = []
conn_index[cconn].append(i)
return conn_index
def get_rings(atoms, rings=[5, 6, 7]):
"""
This method return a list of the number of atoms involved
in rings in the structures. It uses the neighbor
list hence inherit the restriction used for neighbors.
"""
conn = get_neighbor_list(atoms)
if conn is None:
conn = get_neighborlist(atoms)
no_of_loops = [0] * 8
for s1 in range(len(atoms)):
for s2 in conn[s1]:
v12 = [s1] + [s2]
for s3 in [s for s in conn[s2] if s not in v12]:
v13 = v12 + [s3]
if s1 in conn[s3]:
no_of_loops[3] += 1
for s4 in [s for s in conn[s3] if s not in v13]:
v14 = v13 + [s4]
if s1 in conn[s4]:
no_of_loops[4] += 1
for s5 in [s for s in conn[s4] if s not in v14]:
v15 = v14 + [s5]
if s1 in conn[s5]:
no_of_loops[5] += 1
for s6 in [s for s in conn[s5] if s not in v15]:
v16 = v15 + [s6]
if s1 in conn[s6]:
no_of_loops[6] += 1
for s7 in [s for s in conn[s6] if s not in v16]:
# v17 = v16 + [s7]
if s1 in conn[s7]:
no_of_loops[7] += 1
to_return = []
for ring in rings:
to_return.append(no_of_loops[ring])
return to_return
def get_connections_index(atoms, max_conn=5, no_count_types=None):
"""
This method returns a dictionary where each key value are a
specific number of neighbors and list of atoms indices with
that amount of neighbors respectively. The method utilizes the
neighbor list and hence inherit the restrictions for
neighbors. Option added to remove connections between
defined atom types.
Parameters
----------
atoms : Atoms object
The connections will be counted using this supplied Atoms object
max_conn : int
Any atom with more connections than this will be counted as
having max_conn connections.
Default 5
no_count_types : list or None
List of atomic numbers that should be excluded in the count.
Default None (meaning all atoms count).
"""
conn = get_neighbor_list(atoms)
if conn is None:
conn = get_neighborlist(atoms)
if no_count_types is None:
no_count_types = []
conn_index = {}
for i in range(len(atoms)):
if atoms[i].number not in no_count_types:
cconn = min(len(conn[i]), max_conn - 1)
if cconn not in conn_index:
conn_index[cconn] = []
conn_index[cconn].append(i)
return conn_index
