def numeric_forces(atoms, indices=None, axes=(0, 1, 2), d=0.001,
parallel=None, name=None):
"""Evaluate finite-difference forces on several atoms.
Returns an array of forces for each specified atomic index and
each specified axis, calculated using finite difference on each
atom and direction separately. Array has same shape as if
returned from atoms.get_forces(); uncalculated elements are zero.
Calculates all forces by default."""
if indices is None:
indices = range(len(atoms))
F_ai = np.zeros_like(atoms.positions)
n = len(indices) * len(axes)
if parallel is None:
atom_tasks = [atoms] * n
master = True
calc_comm = world
else:
calc_comm, tasks_comm, tasks_rank = distribute_cpus(parallel, world)
master = calc_comm.rank == 0
calculator = atoms.get_calculator()
calculator.set(communicator=calc_comm)
atom_tasks = [None] * n
for i in range(n):
if ((i - tasks_rank) % tasks_comm.size) == 0:
atom_tasks[i] = atoms
for ia, a in enumerate(indices):
for ii, i in enumerate(axes):
atoms = atom_tasks[ia * len(axes) + ii]
if atoms is not None:
done = 0
if name:
fname = '%s.%d%s.pckl' % (name, a, 'xyz'[i])
fd = opencew(fname, calc_comm)
if fd is None:
if master:
try:
F_ai[a, i] = pickle.load(open(fname))
print '# atom', a, 'xyz'[i], 'done'
done = 1
except EOFError:
pass
done = calc_comm.sum(done)
if not done:
print '# rank', rank, 'calculating atom', a, 'xyz'[i]
force = numeric_force(atoms, a, i, d)
if master:
F_ai[a, i] = force
if name:
fd = open('%s.%d%s.pckl' % (name, a, 'xyz'[i]),
'w')
pickle.dump(force, fd)
fd.close()
if parallel is not None:
world.sum(F_ai)
return F_ai
def calculate_energies_and_forces(self, all=False):
"""Calculate and store the forces and energies for the band."""
images = self.images
if all:
self.forces['real'][0] = images[0].get_forces()
self.forces['real'][-1] = images[-1].get_forces()
if not self.integrate_forces:
self.energies[0] = images[0].get_potential_energy()
self.energies[-1] = images[-1].get_potential_energy()
if not self.parallel:
# Do all images - one at a time:
for i in range(1, self.nimages - 1):
self.calculate_image_forces(i)
for i in range(1, self.nimages - 1):
self.calculate_image_energies(i)
else:
# Parallelize over images: first the forces ...
i = rank * (self.nimages - 2) // size + 1
try:
self.calculate_image_forces(i)
except:
# Make sure other images also fail:
error = world.sum(1.0)
raise
else:
error = world.sum(0.0)
if error:
raise RuntimeError('Parallel NEB failed')
for i in range(1, self.nimages - 1):
root = (i - 1) * size // (self.nimages - 2)
world.broadcast(self.forces['real'][i], root)
# ... and now the energies
try:
self.calculate_image_energies(i)
except:
# Make sure other images also fail:
error = world.sum(1.0)
raise
else:
error = world.sum(0.0)
if error:
raise RuntimeError('Parallel NEB failed')
for i in range(1, self.nimages - 1):
root = (i - 1) * size // (self.nimages - 2)
world.broadcast(self.energies[i : i + 1], root)
if all and self.integrate_forces:
# fill in the first and last energies by force integration
self.energies[0] = 0.
self.calculate_image_energies(len(self.images)-1)
def ltidos(cell, eigs, energies, weights=None):
"""DOS from linear tetrahedron interpolation.
cell: 3x3 ndarray-like
Unit cell.
eigs: (n1, n2, n3, nbands)-shaped ndarray
Eigenvalues on a Monkhorst-Pack grid (not reduced).
energies: 1-d array-like
Energies where the DOS is calculated (must be a uniform grid).
weights: (n1, n2, n3, nbands)-shaped ndarray
Weights. Defaults to 1.
"""
from scipy.spatial import Delaunay
I, J, K = size = eigs.shape[:3]
B = (np.linalg.inv(cell) / size).T
indices = np.array([[i, j, k] for i in [0, 1] for j in [0, 1]
for k in [0, 1]])
dt = Delaunay(np.dot(indices, B))
dos = np.zeros_like(energies)
integrate = functools.partial(_lti, energies, dos)
for s in dt.simplices:
kpts = dt.points[s]
try:
M = np.linalg.inv(kpts[1:, :] - kpts[0, :])
except np.linalg.linalg.LinAlgError:
continue
n = -1
for i in range(I):
for j in range(J):
for k in range(K):
n += 1
if n % world.size != world.rank:
continue
E = np.array([
eigs[(i + a) % I, (j + b) % J, (k + c) % K]
for a, b, c in indices[s]
])
if weights is None:
integrate(kpts, M, E)
else:
w = np.array([
weights[(i + a) % I, (j + b) % J, (k + c) % K]
for a, b, c in indices[s]
])
integrate(kpts, M, E, w)
world.sum(dos)
return dos * abs(np.linalg.det(cell))
def opencew(filename, world=None):
"""Create and open filename exclusively for writing.
If master cpu gets exclusive write access to filename, a file
descriptor is returned (a dummy file descriptor is returned on the
slaves). If the master cpu does not get write access, None is
returned on all processors."""
if world is None:
from ase.parallel import world
if world.rank == 0:
try:
fd = os.open(filename, CEW_FLAGS)
except OSError as ex:
error = ex.errno
else:
error = 0
fd = os.fdopen(fd, 'wb')
else:
error = 0
fd = devnull
# Syncronize:
error = world.sum(error)
if error == errno.EEXIST:
return None
if error:
raise OSError(error, 'Error', filename)
return fd
def opencew(filename, world=None):
"""Create and open filename exclusively for writing.
If master cpu gets exclusive write access to filename, a file
descriptor is returned (a dummy file descriptor is returned on the
slaves). If the master cpu does not get write access, None is
returned on all processors."""
if world is None:
from ase.parallel import world
if world.rank == 0:
try:
fd = os.open(filename, CEW_FLAGS)
except OSError as ex:
error = ex.errno
else:
error = 0
fd = os.fdopen(fd, 'wb')
else:
error = 0
fd = devnull
# Syncronize:
error = world.sum(error)
if error == errno.EEXIST:
return None
if error:
raise OSError(error, 'Error', filename)
return fd
def opencew(filename, world=None):
"""Create and open filename exclusively for writing.
If master cpu gets exclusive write access to filename, a file
descriptor is returned (a dummy file descriptor is returned on the
slaves). If the master cpu does not get write access, None is
returned on all processors."""
if world is None:
from ase.parallel import world
if world.rank == 0:
try:
fd = os.open(filename, os.O_CREAT | os.O_EXCL | os.O_WRONLY)
except OSError:
ok = 0
else:
ok = 1
fd = os.fdopen(fd, 'wb')
else:
ok = 0
fd = devnull
# Syncronize:
if world.sum(ok) == 0:
return None
else:
return fd
def _opencew(filename, world=None):
if world is None:
from ase.parallel import world
closelater = []
def opener(file, flags):
return os.open(file, flags | CEW_FLAGS)
try:
error = 0
if world.rank == 0:
try:
fd = open(filename, 'wb', opener=opener)
except OSError as ex:
error = ex.errno
else:
closelater.append(fd)
else:
fd = open(os.devnull, 'wb')
closelater.append(fd)
# Synchronize:
error = world.sum(error)
if error == errno.EEXIST:
return None
if error:
raise OSError(error, 'Error', filename)
return fd
except BaseException:
for fd in closelater:
fd.close()
raise
def opencew(filename, world=None):
"""Create and open filename exclusively for writing.
If master cpu gets exclusive write access to filename, a file
descriptor is returned (a dummy file descriptor is returned on the
slaves). If the master cpu does not get write access, None is
returned on all processors."""
if world is None:
from ase.parallel import world
if world.rank == 0:
try:
fd = os.open(filename, os.O_CREAT | os.O_EXCL | os.O_WRONLY)
except OSError:
ok = 0
else:
ok = 1
fd = os.fdopen(fd, 'w')
else:
ok = 0
fd = devnull
# Syncronize:
if world.sum(ok) == 0:
return None
else:
return fd
def lti_dos(simplices, eigs, weights, energies, dos, world):
shape = eigs.shape[:3]
nweights = weights.shape[-1]
dos[:] = 0.0
n = -1
for index in np.indices(shape).reshape((3, -1)).T:
n += 1
if n % world.size != world.rank:
continue
i = ((index + simplices) % shape).T
E = eigs[i[0], i[1], i[2]].reshape((4, -1))
W = weights[i[0], i[1], i[2]].reshape((4, -1, nweights))
for e, w in zip(E.T, W.transpose((1, 0, 2))):
lti_dos1(e, w, energies, dos)
dos /= 6.0
world.sum(dos)
def __init__(self,
atoms,
control=None,
eigenmodes=None,
random_seed=None,
**kwargs):
self.minmode_init = True
self.atoms = atoms
# Initialize to None to avoid strange behaviour due to __getattr__
self.eigenmodes = eigenmodes
self.curvatures = None
if control is None:
self.control = DimerControl(**kwargs)
w = 'Missing control object in ' + self.__class__.__name__ + \
'. Using default: DimerControl()'
warnings.warn(w, UserWarning)
if self.control.logfile is not None:
self.control.logfile.write('DIM:WARN: ' + w + '\n')
self.control.logfile.flush()
else:
self.control = control
logfile = self.control.get_logfile()
mlogfile = self.control.get_eigenmode_logfile()
for key in kwargs:
if key == 'logfile':
logfile = kwargs[key]
elif key == 'eigenmode_logfile':
mlogfile = kwargs[key]
else:
self.control.set_parameter(key, kwargs[key])
self.control.initialize_logfiles(logfile=logfile,
eigenmode_logfile=mlogfile)
# Seed the randomness
if random_seed is None:
t = time.time()
if world.size > 1:
t = world.sum(t) / world.size
# Harvest the latter part of the current time
random_seed = int(('%30.9f' % t)[-9:])
self.random_state = np.random.RandomState(random_seed)
# Check the order
self.order = self.control.get_parameter('order')
# Construct the curvatures list
self.curvatures = [100.0] * self.order
# Save the original state of the atoms.
self.atoms0 = self.atoms.copy()
self.save_original_forces()
# Get a reference to the log files
self.logfile = self.control.get_logfile()
self.mlogfile = self.control.get_eigenmode_logfile()
def __init__(self, atoms, control=None, eigenmodes=None, basis=None, random_seed=None, **kwargs):
self.minmode_init = True
self.atoms = atoms
# Initialize to None to avoid strange behaviour due to __getattr__
self.eigenmodes = eigenmodes
self.basis = basis
self.curvatures = None
if control is None:
self.control = DimerControl(**kwargs)
w = 'Missing control object in ' + self.__class__.__name__ + \
'. Using default: DimerControl()'
warnings.warn(w, UserWarning)
if self.control.logfile is not None:
self.control.logfile.write('DIM:WARN: ' + w + '\n')
self.control.logfile.flush()
else:
self.control = control
logfile = self.control.get_logfile()
mlogfile = self.control.get_eigenmode_logfile()
for key in kwargs:
if key == 'logfile':
logfile = kwargs[key]
elif key == 'eigenmode_logfile':
mlogfile = kwargs[key]
else:
self.control.set_parameter(key, kwargs[key])
self.control.initialize_logfiles(logfile = logfile,
eigenmode_logfile = mlogfile)
# Print the log header
self.control.log_header()
# Seed the randomness
if random_seed is None:
t = time.time()
if size > 1:
t = world.sum(t) / float(size)
# Harvest the latter part of the current time
random_seed = int(('%30.9f' % t)[-9:])
self.random_state = np.random.RandomState(random_seed)
# Check the order
self.order = self.control.get_parameter('order')
# Construct the curvatures list
self.curvatures = [100.0] * self.order
# Save the original state of the atoms.
self.atoms0 = self.atoms.copy()
self.save_original_forces()
# Get a reference to the log files
self.logfile = self.control.get_logfile()
self.mlogfile = self.control.get_eigenmode_logfile()
def numeric_forces(atoms,
indices=None,
axes=(0, 1, 2),
d=0.001,
parallel=None):
"""Evaluate finite-difference forces on several atoms.
Returns an array of forces for each specified atomic index and
each specified axis, calculated using finite difference on each
atom and direction separately. Array has same shape as if
returned from atoms.get_forces(); uncalculated elements are zero.
Calculates all forces by default."""
if indices is None:
indices = range(len(atoms))
F_ai = np.zeros_like(atoms.positions)
n = len(indices) * len(axes)
if parallel is None:
atom_tasks = [atoms] * n
master = True
else:
calc_comm, tasks_comm, tasks_rank = distribute_cpus(parallel, world)
master = calc_comm.rank == 0
calculator = atoms.get_calculator()
calculator.set(communicator=calc_comm)
atom_tasks = [None] * n
for i in range(n):
if ((i - tasks_rank) % tasks_comm.size) == 0:
atom_tasks[i] = atoms
for ia, a in enumerate(indices):
for ii, i in enumerate(axes):
atoms = atom_tasks[ia * len(axes) + ii]
if atoms is not None:
print '# rank', rank, 'calculating atom', a, 'xyz'[i]
force = numeric_force(atoms, a, i, d)
if master:
F_ai[a, i] = force
if parallel is not None:
world.sum(F_ai)
return F_ai
def calculate_eigenmodes(self):
if self.parallel:
i = rank * (self.nimages - 2) // size + 1
try:
self.calculate_image_eigenmode(i)
except:
# Make sure other images also fail:
error = world.sum(1.0)
raise
else:
error = world.sum(0.0)
if error:
raise RuntimeError('Parallel ERM failed during eigenmode calculations.')
for i in range(1, self.nimages - 1):
if self.images[i].eigenmodes is None:
self.images[i].eigenmodes = [np.zeros(self.images[i].get_positions().shape)]
root = (i - 1) * size // (self.nimages - 2)
world.broadcast(self.images[i].eigenmodes[0], root)
# world.broadcast(self.images[i : i + 1].curvatures, root)
else:
for i in range(1, self.nimages - 1):
self.calculate_image_eigenmode(i)
def numeric_forces(atoms, indices=None, axes=(0, 1, 2), d=0.001,
parallel=None):
"""Evaluate finite-difference forces on several atoms.
Returns an array of forces for each specified atomic index and
each specified axis, calculated using finite difference on each
atom and direction separately. Array has same shape as if
returned from atoms.get_forces(); uncalculated elements are zero.
Calculates all forces by default."""
if indices is None:
indices = range(len(atoms))
F_ai = np.zeros_like(atoms.positions)
n = len(indices) * len(axes)
if parallel is None:
atom_tasks = [atoms] * n
master = True
else:
calc_comm, tasks_comm, tasks_rank = distribute_cpus(parallel, world)
master = calc_comm.rank == 0
calculator = atoms.get_calculator()
calculator.set(communicator=calc_comm)
atom_tasks = [None] * n
for i in range(n):
if ((i - tasks_rank) % tasks_comm.size) == 0:
atom_tasks[i] = atoms
for ia, a in enumerate(indices):
for ii, i in enumerate(axes):
atoms = atom_tasks[ia * len(axes) + ii]
if atoms is not None:
print '# rank', rank, 'calculating atom', a, 'xyz'[i]
force = numeric_force(atoms, a, i, d)
if master:
F_ai[a, i] = force
if parallel is not None:
world.sum(F_ai)
return F_ai
def isfile(filename):
"""Check if a file is opened, taking into account the MPI environment
input:
filename
output:
0 when the file does not exist, 1 if it does
"""
if world.rank == 0:
isf = os.path.isfile(filename)
else:
isf = 0
# Synchronize:
return world.sum(isf)
def calculate_energies_and_forces(self):
images = self.images
if not self.parallel:
# Do all images - one at a time:
for i in range(1, self.nimages - 1):
self.calculate_image_energies_and_forces(i)
else:
# Parallelize over images:
i = rank * (self.nimages - 2) // size + 1
try:
self.calculate_image_energies_and_forces(i)
except:
# Make sure other images also fail:
error = world.sum(1.0)
raise
else:
error = world.sum(0.0)
if error:
raise RuntimeError('Parallel NEB failed')
for i in range(1, self.nimages - 1):
root = (i - 1) * size // (self.nimages - 2)
world.broadcast(self.energies[i : i + 1], root)
world.broadcast(self.forces['real'][i], root)
def calculate(self, atoms):
self.positions = atoms.get_positions().copy()
self.cell = atoms.get_cell().copy()
self.pbc = atoms.get_pbc().copy()
natoms = len(atoms)
nH2O = natoms // 3
assert self.pbc.all()
C = self.cell.diagonal()
assert not (self.cell - np.diag(C)).any()
assert (C >= 2 * self.rc2).all()
self.numbers = atoms.get_atomic_numbers()
Z = self.numbers.reshape((-1, 3))
assert (Z[:, 1:] == 1).all() and (Z[:, 0] == 8).all()
R = self.positions.reshape((nH2O, 3, 3))
RO = R[:, 0]
self.energy = 0.0
self.forces = np.zeros((natoms, 3))
if world is None:
mya = range(nH2O - 1)
else:
rank = world.rank
size = world.size
assert nH2O // (2 * size) == 0
mynH2O = nH2O // 2 // size
mya = (range(rank * n, (rank + 1) * n) +
range((size - rank - 1) * n, (size - rank) * n))
q = np.empty(3)
q[:] = qH * (units.Hartree * units.Bohr)**0.5
q[0] *= -2
for a in mya:
DOO = (RO[a + 1:] - RO[a] + 0.5 * C) % C - 0.5 * C
dOO = (DOO**2).sum(axis=1)**0.5
x1 = dOO > self.rc1
x2 = dOO < self.rc2
f = np.zeros(nH2O - a - 1)
f[x2] = 1.0
dfdd = np.zeros(nH2O - a - 1)
x12 = np.logical_and(x1, x2)
d = (dOO[x12] - self.rc1) / (self.rc2 - self.rc1)
f[x12] -= d**2 * (3.0 - 2.0 * d)
dfdd[x12] -= 6.0 / (self.rc2 - self.rc1) * d * (1.0 - d)
y = (sigma0 / dOO)**6
y2 = y**2
e = 4 * epsilon0 * (y2 - y)
self.energy += np.dot(e, f)
dedd = 24 * epsilon0 * (2 * y2 - y) / dOO * f - e * dfdd
F = (dedd / dOO)[:, np.newaxis] * DOO
self.forces[(a + 1) * 3::3] += F
self.forces[a * 3] -= F.sum(axis=0)
for i in range(3):
D = (R[a + 1:] - R[a, i] + 0.5 * C) % C - 0.5 * C
d = (D**2).sum(axis=2)**0.5
e = q[i] * q / d
self.energy += np.dot(f, e).sum()
F = (e / d**2 * f[:, np.newaxis])[:, :, np.newaxis] * D
F[:, 0] -= (e.sum(axis=1) * dfdd / dOO)[:, np.newaxis] * DOO
self.forces[(a + 1) * 3:] += F.reshape((-1, 3))
self.forces[a * 3 + i] -= F.sum(axis=0).sum(axis=0)
if world is not None:
self.energy = world.sum(self.energy)
world.sum(self.forces)
def calculate(self, atoms):
self.positions = atoms.get_positions().copy()
self.cell = atoms.get_cell().copy()
self.pbc = atoms.get_pbc().copy()
natoms = len(atoms)
nH2O = natoms // 3
assert self.pbc.all()
C = self.cell.diagonal()
assert not (self.cell - np.diag(C)).any()
assert (C >= 2 * self.rc2).all()
self.numbers = atoms.get_atomic_numbers()
Z = self.numbers.reshape((-1, 3))
assert (Z[:, 1:] == 1).all() and (Z[:, 0] == 8).all()
R = self.positions.reshape((nH2O, 3, 3))
RO = R[:, 0]
self.energy = 0.0
self.forces = np.zeros((natoms, 3))
if world.size == 1:
mya = list(range(nH2O - 1))
else:
rank = world.rank
size = world.size
assert nH2O // (2 * size) == 0
mynH2O = nH2O // 2 // size
mya = (list(range(rank * n, (rank + 1) * n)) +
list(range((size - rank - 1) * n, (size - rank) * n)))
q = np.empty(3)
q[:] = qH * (units.Hartree * units.Bohr)**0.5
q[0] *= -2
for a in mya:
DOO = (RO[a + 1:] - RO[a] + 0.5 * C) % C - 0.5 * C
dOO = (DOO**2).sum(axis=1)**0.5
x1 = dOO > self.rc1
x2 = dOO < self.rc2
f = np.zeros(nH2O - a - 1)
f[x2] = 1.0
dfdd = np.zeros(nH2O - a - 1)
x12 = np.logical_and(x1, x2)
d = (dOO[x12] - self.rc1) / (self.rc2 - self.rc1)
f[x12] -= d**2 * (3.0 - 2.0 * d)
dfdd[x12] -= 6.0 / (self.rc2 - self.rc1) * d * (1.0 - d)
y = (sigma0 / dOO)**6
y2 = y**2
e = 4 * epsilon0 * (y2 - y)
self.energy += np.dot(e, f)
dedd = 24 * epsilon0 * (2 * y2 - y) / dOO * f - e * dfdd
F = (dedd / dOO)[:, np.newaxis] * DOO
self.forces[(a + 1) * 3::3] += F
self.forces[a * 3] -= F.sum(axis=0)
for i in range(3):
D = (R[a + 1:] - R[a, i] + 0.5 * C) % C - 0.5 * C
d = (D**2).sum(axis=2)**0.5
e = q[i] * q / d
self.energy += np.dot(f, e).sum()
F = (e / d**2 * f[:, np.newaxis])[:, :, np.newaxis] * D
F[:, 0] -= (e.sum(axis=1) * dfdd / dOO)[:, np.newaxis] * DOO
self.forces[(a + 1) * 3:] += F.reshape((-1, 3))
self.forces[a * 3 + i] -= F.sum(axis=0).sum(axis=0)
self.energy = world.sum(self.energy)
world.sum(self.forces)
def numeric_forces(self,atoms, axes=(0, 1, 2), d=0.001,
parallel=None, name=None):
"""Evaluate finite-difference forces on several atoms.
Returns an array of forces for each specified atomic index and
each specified axis, calculated using finite difference on each
atom and direction separately. Array has same shape as if
returned from atoms.get_forces(); uncalculated elements are zero.
Calculates all forces by default."""
import numpy as np
from ase.parallel import world, rank, distribute_cpus
from ase.utils import opencew
indices = range(len(atoms))
F_ai = np.zeros_like(atoms.positions)
n = len(indices) * len(axes)
total_calculation = len(indices)*len(axes)
if parallel is None:
atom_tasks = [atoms] * n
master = True
calc_comm = world
else:
calc_comm, tasks_comm, tasks_rank = distribute_cpus(parallel, world)
master = calc_comm.rank == 0
calculator = atoms.get_calculator()
calculator.set(communicator=calc_comm)
atom_tasks = [None] * n
for i in range(n):
if ((i - tasks_rank) % tasks_comm.size) == 0:
atom_tasks[i] = atoms
counter = 0
for ia, a in enumerate(indices):
for ii, i in enumerate(axes):
atoms = atom_tasks[ia * len(axes) + ii]
if atoms is not None:
done = 0
if name:
fname = '%s.%d%s.pckl' % (name, a, 'xyz'[i])
fd = opencew(fname, calc_comm)
if fd is None:
if master:
try:
F_ai[a, i] = pickle.load(open(fname))
print '# atom', a, 'xyz'[i], 'done'
done = 1
except EOFError:
pass
done = calc_comm.sum(done)
if not done:
# print '# rank', rank, 'calculating atom', a, 'xyz'[i]
force = self.__numeric_force(atoms, a, i, d)
if master:
F_ai[a, i] = force
if name:
fd = open('%s.%d%s.pckl' % (name, a, 'xyz'[i]),
'w')
pickle.dump(force, fd)
fd.close()
counter += 1
fan = ['-', '\\', '|', '/']
sys.stderr.write("\r[%-100s]%3.1f%% %1s" % tuple([int(float(counter)/float(total_calculation)*100)*'=',float(counter)/float(total_calculation)*100,fan[counter%4]]))
sys.stderr.flush()
if parallel is not None:
world.sum(F_ai)
return F_ai
def numeric_forces(self,
atoms,
axes=(0, 1, 2),
d=0.001,
parallel=None,
name=None):
"""Evaluate finite-difference forces on several atoms.
Returns an array of forces for each specified atomic index and
each specified axis, calculated using finite difference on each
atom and direction separately. Array has same shape as if
returned from atoms.get_forces(); uncalculated elements are zero.
Calculates all forces by default."""
import numpy as np
from ase.parallel import world, rank, distribute_cpus
from ase.utils import opencew
indices = range(len(atoms))
F_ai = np.zeros_like(atoms.positions)
n = len(indices) * len(axes)
total_calculation = len(indices) * len(axes)
if parallel is None:
atom_tasks = [atoms] * n
master = True
calc_comm = world
else:
calc_comm, tasks_comm, tasks_rank = distribute_cpus(
parallel, world)
master = calc_comm.rank == 0
calculator = atoms.get_calculator()
calculator.set(communicator=calc_comm)
atom_tasks = [None] * n
for i in range(n):
if ((i - tasks_rank) % tasks_comm.size) == 0:
atom_tasks[i] = atoms
counter = 0
for ia, a in enumerate(indices):
for ii, i in enumerate(axes):
atoms = atom_tasks[ia * len(axes) + ii]
if atoms is not None:
done = 0
if name:
fname = '%s.%d%s.pckl' % (name, a, 'xyz'[i])
fd = opencew(fname, calc_comm)
if fd is None:
if master:
try:
F_ai[a, i] = pickle.load(open(fname))
print '# atom', a, 'xyz'[i], 'done'
done = 1
except EOFError:
pass
done = calc_comm.sum(done)
if not done:
# print '# rank', rank, 'calculating atom', a, 'xyz'[i]
force = self.__numeric_force(atoms, a, i, d)
if master:
F_ai[a, i] = force
if name:
fd = open('%s.%d%s.pckl' % (name, a, 'xyz'[i]),
'w')
pickle.dump(force, fd)
fd.close()
counter += 1
fan = ['-', '\\', '|', '/']
sys.stderr.write("\r[%-100s]%3.1f%% %1s" % tuple([
int(float(counter) / float(total_calculation) * 100) * '=',
float(counter) / float(total_calculation) * 100,
fan[counter % 4]
]))
sys.stderr.flush()
if parallel is not None:
world.sum(F_ai)
return F_ai
def __len__(self):
return world.sum(len(self.backend))
def __len__(self):
return world.sum(len(self.backend))
def numeric_forces(atoms,
indices=None,
axes=(0, 1, 2),
d=0.001,
parallel=None,
name=None):
"""Evaluate finite-difference forces on several atoms.
Returns an array of forces for each specified atomic index and
each specified axis, calculated using finite difference on each
atom and direction separately. Array has same shape as if
returned from atoms.get_forces(); uncalculated elements are zero.
Calculates all forces by default."""
if indices is None:
indices = range(len(atoms))
F_ai = np.zeros_like(atoms.positions)
n = len(indices) * len(axes)
if parallel is None:
atom_tasks = [atoms] * n
master = True
calc_comm = world
else:
calc_comm, tasks_comm, tasks_rank = distribute_cpus(parallel, world)
master = calc_comm.rank == 0
calculator = atoms.get_calculator()
calculator.set(communicator=calc_comm)
atom_tasks = [None] * n
for i in range(n):
if ((i - tasks_rank) % tasks_comm.size) == 0:
atom_tasks[i] = atoms
for ia, a in enumerate(indices):
for ii, i in enumerate(axes):
atoms = atom_tasks[ia * len(axes) + ii]
if atoms is not None:
done = 0
if name:
fname = '%s.%d%s.pckl' % (name, a, 'xyz'[i])
fd = opencew(fname, calc_comm)
if fd is None:
if master:
try:
F_ai[a, i] = pickle.load(open(fname))
print '# atom', a, 'xyz'[i], 'done'
done = 1
except EOFError:
pass
done = calc_comm.sum(done)
if not done:
print '# rank', rank, 'calculating atom', a, 'xyz'[i]
force = numeric_force(atoms, a, i, d)
if master:
F_ai[a, i] = force
if name:
fd = open('%s.%d%s.pckl' % (name, a, 'xyz'[i]),
'w')
pickle.dump(force, fd)
fd.close()
if parallel is not None:
world.sum(F_ai)
return F_ai