def lattice_sumX(func, positions, elem_cell=np.eye(3), periodic_directions=(False, False, False), cutoff_radius=DF_CUTOFF_RADIUS):
"""Computes the lattice sum of interactions within the (0,0,0) copy
as well as the interactions to all other copies that lie whithin
a sphere defined by the "cutoff_radius". Thereby the interaction
is defined by a distance-vector-dependent function "func"
"""
# Number of atoms within a single copy
N_atoms = len(positions)
# Maximum distance of two atoms within a copy
# Serves as measure for extension of a single copy
Rij_max = maxdist(positions)
# use this below as cutoff radius:
cutoff = cutoff_radius + Rij_max
#
# So far we have to provide the meaningfull (non-linearly dependent) cell vectors
# also for directions that are not periodic in order to be able to invert the 3x3
# matrix. FIXME: Is there a better way? Also ASE sets the system in that way?
#
# compute the size of the box enclosing a sphere of radius |cutoff|
# in "fractional" coordinates:
box = minbox(elem_cell, cutoff)
# round them in very conservative fashion, all box[i] >= 1,
box = [ int(ceil(k)) for k in box ]
#
# This rounding approach appears to never restrict the summation
# later to a single cell, rather to at least three at
#
# -1, 0 , +1
#
# of the cell vector in each direction.
#
# reset the values for non-periodic directions to zero:
for i in range(len(box)):
if not periodic_directions[i]:
# in this direction treat only the unit cell itself:
box[i] = 0
#
# Now we are ready to sum over all cells in the box
#
# Initialization of output data by call for the 000 cell
f = func(np.array([0.,0.,0.]))
#
# Running over all residual copies in the box
u = 0
v = 0
# u, v = 0 case. Summation over w, with w != 0
for w in xrange(-box[2], 0):
t_vec = u * elem_cell[0] + v * elem_cell[1] + w * elem_cell[2]
t2 = np.dot(t_vec, t_vec)
if t2 > cutoff**2: continue
f += func(t_vec)
for w in xrange(1, box[2] + 1):
t_vec = u * elem_cell[0] + v * elem_cell[1] + w * elem_cell[2]
t2 = np.dot(t_vec, t_vec)
if t2 > cutoff**2: continue
f += func(t_vec)
#
# u = 0 case. Summation over v and w, with v != 0
for v in xrange(-box[1], 0):
for w in xrange(-box[2], box[2] + 1):
t_vec = u * elem_cell[0] + v * elem_cell[1] + w * elem_cell[2]
t2 = np.dot(t_vec, t_vec)
if t2 > cutoff**2: continue
f += func(t_vec)
#
for w in xrange(-box[2], box[2] + 1):
t_vec = u * elem_cell[0] - v * elem_cell[1] + w * elem_cell[2]
t2 = np.dot(t_vec, t_vec)
if t2 > cutoff**2: continue
f += func(t_vec)
#
# General case. Summation over u, v, and w, with u != 0
for u in xrange(-box[0], 0):
for v in xrange(-box[1], box[1] + 1):
for w in xrange(-box[2], box[2] + 1):
t_vec = u * elem_cell[0] + v * elem_cell[1] + w * elem_cell[2]
t2 = np.dot(t_vec, t_vec)
if t2 > cutoff**2: continue
f += func(t_vec)
#
for v in xrange(-box[1], box[1] + 1):
for w in xrange(-box[2], box[2] + 1):
t_vec = -u * elem_cell[0] + v * elem_cell[1] + w * elem_cell[2]
t2 = np.dot(t_vec, t_vec)
if t2 > cutoff**2: continue
f += func(t_vec)
#
return f
def lattice_sum(func, f0, f0_prime, positions, elem_cell=np.eye(3), periodic_directions=(False, False, False), cutoff_radius=DF_CUTOFF_RADIUS):
"""Computes the lattice sum of interactions within the (0,0,0) copy
as well as the interactions to all other copies that lie whithin
a sphere defined by the "cutoff_radius". Thereby the interaction
is defined by a distance-vector-dependent function "func"
>>> from math import pi
>>> v, g = lattice_sum(lambda x: (1, 1), [[0., 0., 0.]], periodic_directions=3*(True,))
>>> v / (4. * pi / 3. * DF_CUTOFF_RADIUS**3)
1.0056889511012566
"""
# Number of atoms within a single copy
N_atoms = len(positions)
# Maximum distance of two atoms within a copy
# Serves as measure for extension of a single copy
Rij_max = maxdist(positions)
# use this below as cutoff radius:
cutoff = cutoff_radius / AU_TO_ANG + Rij_max
#
# So far we have to provide the meaningfull (non-linearly dependent) cell vectors
# also for directions that are not periodic in order to be able to invert the 3x3
# matrix. FIXME: Is there a better way? Also ASE sets the system in that way?
#
# compute the size of the box enclosing a sphere of radius |cutoff|
# in "fractional" coordinates:
box = minbox(elem_cell, cutoff)
# round them in very conservative fashion, all box[i] >= 1,
box = [ int(ceil(k)) for k in box ]
#
# This rounding approach appears to never restrict the summation
# later to a single cell, rather to at least three at
#
# -1, 0 , +1
#
# of the cell vector in each direction.
#
# reset the values for non-periodic directions to zero:
for i in range(len(box)):
if not periodic_directions[i]:
# in this direction treat only the unit cell itself:
box[i] = 0
#
f = f0
f_prime = f0_prime
# Now we are ready to sum over all cells in the box
#
# scan over indices u, v, w
for u in xrange(-box[0], box[0] + 1):
for v in xrange(-box[1], box[1] + 1):
for w in xrange(-box[2], box[2] + 1):
# Calculate translation vector to actual copy
t_vec = u * elem_cell[0] + v * elem_cell[1] + w * elem_cell[2]
# Calculate the squared distance to copy, cycle if that is too long:
t2 = np.dot(t_vec, t_vec)
if t2 > cutoff**2: continue
# Calculate the dispersion interaction between
# the considered pair of copies
f1, fprime1 = func(t_vec)
#
# Actualize dispersion correction and contributions to forces
f += f1
f_prime += fprime1
#
#
#
return f, f_prime
