def del_atoms(x=None):
rcut = 2.0
#x = Atoms('crack.xyz')
if x == None:
x = Atoms('1109337334_frac.xyz')
else:
pass
x.set_cutoff(3.0)
x.calc_connect()
x.calc_dists()
rem=[]
r = farray(0.0)
u = fzeros(3)
print len(x)
for i in frange(x.n):
for n in frange(x.n_neighbours(i)):
j = x.neighbour(i, n, distance=3.0, diff=u)
if x.distance_min_image(i, j) < rcut and j!=i:
rem.append(sorted([j,i]))
if i%10000==0: print i
rem = list(set([a[0] for a in rem]))
if len(rem) > 0:
print rem
x.remove_atoms(rem)
else:
print 'No duplicate atoms in list.'
x.write('crack_nodup.xyz')
return x
def delete_atoms(self, grain=None, rcut=2.0):
"""
Delete atoms below a certain distance threshold.
Args:
grain(:class:`quippy.Atoms`): Atoms object of the grain.
rcut(float): Atom deletion criterion.
Returns:
:class:`quippy.Atoms` object with atoms nearer than deletion criterion removed.
"""
io = ImeallIO()
if grain == None:
x = Atoms('{0}.xyz'.format(os.path.join(self.grain_dir,
self.gbid)))
else:
x = Atoms(grain)
x.set_cutoff(2.4)
x.calc_connect()
x.calc_dists()
rem = []
u = fzeros(3)
for i in frange(x.n):
for n in frange(x.n_neighbours(i)):
j = x.neighbour(i, n, distance=3.0, diff=u)
if x.distance_min_image(i, j) < rcut and j != i:
rem.append(sorted([j, i]))
rem = list(set([a[0] for a in rem]))
if len(rem) > 0:
x.remove_atoms(rem)
else:
print 'No duplicate atoms in list.'
if grain == None:
self.name = '{0}_d{1}'.format(self.gbid, str(rcut))
self.subgrain_dir = io.make_dir(self.calc_dir, self.name)
self.struct_file = gbid + '_' + 'n' + str(
len(rem)) + 'd' + str(rcut)
x.write('{0}.xyz'.format(
os.path.join(self.subgrain_dir, self.struct_file)))
return len(rem)
else:
return x
def add_bonds(at,
pts,
cutoff_factor=1.2,
bond_radius=0.2,
bond_colour=(.55, .55, .55)):
at.calc_connect()
bonds = []
for i in quippy.frange(at.n):
i_is_min_image = at.connect.is_min_image[i]
for n in at.neighbours[i]:
# only include minimum image bonds with i < j
j_is_min_image = at.connect.is_min_image[n.j]
if i_is_min_image and j_is_min_image and i > n.j: continue
# only include bonds within this periodic image
if any(n.shift != (0, 0, 0)): continue
bonds.append([i - 1, n.j - 1])
pts.mlab_source.dataset.lines = np.array(bonds)
return mlab.pipeline.surface(mlab.pipeline.tube(pts,
tube_radius=bond_radius),
color=bond_colour)