/usr/share/pyshared/ase/cluster/cluster.py is in python-ase 3.6.0.2515-1.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
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import math
import numpy as np
import cPickle as pickle
from ase import Atoms
from ase.data import chemical_symbols
from ase.cluster.base import ClusterBase
class Cluster(Atoms, ClusterBase):
symmetry = None
surfaces = None
lattice_basis = None
resiproc_basis = None
atomic_basis = None
def copy(self):
cluster = Atoms.copy(self)
cluster.symmetry = self.symmetry
cluster.surfaces = self.surfaces.copy()
cluster.lattice_basis = self.lattice_basis.copy()
cluster.atomic_basis = self.atomic_basis.copy()
cluster.resiproc_basis = self.resiproc_basis.copy()
return cluster
def get_surfaces(self):
"""Returns the miller indexs of the stored surfaces of the cluster."""
if not self.surfaces is None:
return self.surfaces.copy()
else:
return None
def get_layers(self):
"""Return number of atomic layers in stored surfaces directions."""
layers = []
for s in self.surfaces:
n = self.miller_to_direction(s)
c = self.get_positions().mean(axis=0)
r = np.dot(self.get_positions() - c, n).max()
d = self.get_layer_distance(s, 2)
l = 2 * np.round(r / d).astype(int)
ls = np.arange(l - 1, l + 2)
ds = np.array([self.get_layer_distance(s, i) for i in ls])
mask = (np.abs(ds - r) < 1e-10)
layers.append(ls[mask][0])
return np.array(layers, int)
def get_diameter(self, method='volume'):
"""Returns an estimate of the cluster diameter based on two different
methods.
method = 'volume': Returns the diameter of a sphere with the
same volume as the atoms. (Default)
method = 'shape': Returns the averaged diameter calculated from the
directions given by the defined surfaces.
"""
if method == 'shape':
cen = self.get_positions().mean(axis=0)
pos = self.get_positions() - cen
d = 0.0
for s in self.surfaces:
n = self.miller_to_direction(s)
r = np.dot(pos, n)
d += r.max() - r.min()
return d / len(self.surfaces)
elif method == 'volume':
V_cell = np.abs(np.linalg.det(self.lattice_basis))
N_cell = len(self.atomic_basis)
N = len(self)
return 2.0 * (3.0 * N * V_cell /
(4.0 * math.pi * N_cell)) ** (1.0 / 3.0)
else:
return 0.0
#Functions to store the cluster
def write(self, filename=None):
if not isinstance(filename, str):
raise Warning('You must specify a valid filename.')
if os.path.isfile(filename):
os.rename(filename, filename + '.bak')
d = {'symmetry': self.symmetry,
'surfaces': self.surfaces,
'lattice_basis': self.lattice_basis,
'resiproc_basis': self.resiproc_basis,
'atomic_basis': self.atomic_basis,
'cell': self.get_cell(),
'pbc': self.get_pbc()}
f = open(filename, 'w')
f.write('Cluster')
pickle.dump(d, f)
pickle.dump(self.arrays, f)
f.close()
def read(self, filename):
if not os.path.isfile(filename):
raise Warning('The file specified do not exist.')
f = open(filename, 'r')
try:
if f.read(len('Cluster')) != 'Cluster':
raise Warning('This is not a compatible file.')
d = pickle.load(f)
self.arrays = pickle.load(f)
except EOFError:
raise Warinig('Bad file.')
f.close()
self.symmetry = d['symmetry']
self.surfaces = d['surfaces']
self.lattice_basis = d['lattice_basis']
self.resiproc_basis = d['resiproc_basis']
self.atomic_basis = d['atomic_basis']
self.set_cell(d['cell'])
self.set_pbc(d['pbc'])
self.set_constraint()
self.adsorbate_info = {}
self.calc = None
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