/usr/share/pyshared/ase/neb.py is in python-ase 3.6.0.2515-1.
This file is owned by root:root, with mode 0o644.
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import numpy as np
import ase.parallel as mpi
from ase.calculators.singlepoint import SinglePointCalculator
from ase.io import read
class NEB:
def __init__(self, images, k=0.1, climb=False, parallel=False,
world=None):
self.images = images
self.k = k
self.climb = climb
self.parallel = parallel
self.natoms = len(images[0])
self.nimages = len(images)
self.emax = np.nan
if world is None:
world = mpi.world
self.world = world
assert not parallel or world.size % (self.nimages - 2) == 0
def interpolate(self):
pos1 = self.images[0].get_positions()
pos2 = self.images[-1].get_positions()
d = (pos2 - pos1) / (self.nimages - 1.0)
for i in range(1, self.nimages - 1):
self.images[i].set_positions(pos1 + i * d)
# Parallel NEB with Jacapo needs this:
try:
self.images[i].get_calculator().set_atoms(self.images[i])
except AttributeError:
pass
def get_positions(self):
positions = np.empty(((self.nimages - 2) * self.natoms, 3))
n1 = 0
for image in self.images[1:-1]:
n2 = n1 + self.natoms
positions[n1:n2] = image.get_positions()
n1 = n2
return positions
def set_positions(self, positions):
n1 = 0
for image in self.images[1:-1]:
n2 = n1 + self.natoms
image.set_positions(positions[n1:n2])
n1 = n2
# Parallel NEB with Jacapo needs this:
try:
image.get_calculator().set_atoms(image)
except AttributeError:
pass
def get_forces(self):
"""Evaluate and return the forces."""
images = self.images
forces = np.empty(((self.nimages - 2), self.natoms, 3))
energies = np.empty(self.nimages - 2)
if not self.parallel:
# Do all images - one at a time:
for i in range(1, self.nimages - 1):
energies[i - 1] = images[i].get_potential_energy()
forces[i - 1] = images[i].get_forces()
else:
# Parallelize over images:
i = self.world.rank * (self.nimages - 2) // self.world.size + 1
try:
energies[i - 1] = images[i].get_potential_energy()
forces[i - 1] = images[i].get_forces()
except:
# Make sure other images also fail:
error = self.world.sum(1.0)
raise
else:
error = self.world.sum(0.0)
if error:
raise RuntimeError('Parallel NEB failed!')
for i in range(1, self.nimages - 1):
root = (i - 1) * self.world.size // (self.nimages - 2)
self.world.broadcast(energies[i - 1:i], root)
self.world.broadcast(forces[i - 1], root)
imax = 1 + np.argsort(energies)[-1]
self.emax = energies[imax - 1]
tangent1 = images[1].get_positions() - images[0].get_positions()
for i in range(1, self.nimages - 1):
tangent2 = (images[i + 1].get_positions() -
images[i].get_positions())
if i < imax:
tangent = tangent2
elif i > imax:
tangent = tangent1
else:
tangent = tangent1 + tangent2
tt = np.vdot(tangent, tangent)
f = forces[i - 1]
ft = np.vdot(f, tangent)
if i == imax and self.climb:
f -= 2 * ft / tt * tangent
else:
f -= ft / tt * tangent
f -= (np.vdot(tangent1 - tangent2, tangent) *
self.k / tt * tangent)
tangent1 = tangent2
return forces.reshape((-1, 3))
def get_potential_energy(self):
return self.emax
def __len__(self):
return (self.nimages - 2) * self.natoms
class SingleCalculatorNEB(NEB):
def __init__(self, images, k=0.1, climb=False):
if isinstance(images, str):
# this is a filename
traj = read(images, '0:')
images = []
for atoms in traj:
images.append(atoms)
NEB.__init__(self, images, k, climb, False)
self.calculators = [None] * self.nimages
self.energies_ok = False
def interpolate(self, initial=0, final=-1):
"""Interpolate linearly between initial and final images."""
if final < 0:
final = self.nimages + final
n = final - initial
pos1 = self.images[initial].get_positions()
pos2 = self.images[final].get_positions()
d = (pos2 - pos1) / n
for i in range(1, n):
self.images[initial + i].set_positions(pos1 + i * d)
def refine(self, steps=1, begin=0, end=-1):
"""Refine the NEB trajectory."""
if end < 0:
end = self.nimages + end
j = begin
n = end - begin
for i in range(n):
for k in range(steps):
self.images.insert(j + 1, self.images[j].copy())
self.calculators.insert(j + 1, None)
self.nimages = len(self.images)
self.interpolate(j, j + steps + 1)
j += steps + 1
def set_positions(self, positions):
# new positions -> new forces
if self.energies_ok:
# restore calculators
self.set_calculators(self.calculators[1:-1])
NEB.set_positions(self, positions)
def get_calculators(self):
"""Return the original calculators."""
calculators = []
for i, image in enumerate(self.images):
if self.calculators[i] is None:
calculators.append(image.get_calculator())
else:
calculators.append(self.calculators[i])
return calculators
def set_calculators(self, calculators):
"""Set new calculators to the images."""
self.energies_ok = False
if not isinstance(calculators, list):
calculators = [calculators] * self.nimages
n = len(calculators)
if n == self.nimages:
for i in range(self.nimages):
self.images[i].set_calculator(calculators[i])
elif n == self.nimages - 2:
for i in range(1, self.nimages -1):
self.images[i].set_calculator(calculators[i-1])
else:
raise RuntimeError(
'len(calculators)=%d does not fit to len(images)=%d'
% (n, self.nimages))
def get_energies_and_forces(self, all=False):
"""Evaluate energies and forces and hide the calculators"""
if self.energies_ok:
return
images = self.images
forces = np.zeros(((self.nimages - 2), self.natoms, 3))
energies = np.zeros(self.nimages - 2)
self.emax = -1.e32
def calculate_and_hide(i):
image = self.images[i]
calc = image.get_calculator()
if self.calculators[i] is None:
self.calculators[i] = calc
if calc is not None:
if not isinstance(calc, SinglePointCalculator):
self.images[i].set_calculator(
SinglePointCalculator(image.get_potential_energy(),
image.get_forces(),
None,
None,
image))
self.emax = min(self.emax, image.get_potential_energy())
if all and self.calculators[0] is None:
calculate_and_hide(0)
# Do all images - one at a time:
for i in range(1, self.nimages - 1):
calculate_and_hide(i)
if all and self.calculators[-1] is None:
calculate_and_hide(-1)
self.energies_ok = True
def get_forces(self):
self.get_energies_and_forces()
return NEB.get_forces(self)
def n(self):
return self.nimages
def write(self, filename):
from ase.io.trajectory import PickleTrajectory
traj = PickleTrajectory(filename, 'w', self)
traj.write()
traj.close()
def __add__(self, other):
for image in other:
self.images.append(image)
return self
def fit(images):
E = [i.get_potential_energy() for i in images]
F = [i.get_forces() for i in images]
R = [i.get_positions() for i in images]
return fit0(E, F, R)
def fit0(E, F, R):
E = np.array(E) - E[0]
n = len(E)
Efit = np.empty((n - 1) * 20 + 1)
Sfit = np.empty((n - 1) * 20 + 1)
s = [0]
for i in range(n - 1):
s.append(s[-1] + sqrt(((R[i + 1] - R[i])**2).sum()))
lines = []
for i in range(n):
if i == 0:
d = R[1] - R[0]
ds = 0.5 * s[1]
elif i == n - 1:
d = R[-1] - R[-2]
ds = 0.5 * (s[-1] - s[-2])
else:
d = R[i + 1] - R[i - 1]
ds = 0.25 * (s[i + 1] - s[i - 1])
d = d / sqrt((d**2).sum())
dEds = -(F[i] * d).sum()
x = np.linspace(s[i] - ds, s[i] + ds, 3)
y = E[i] + dEds * (x - s[i])
lines.append((x, y))
if i > 0:
s0 = s[i - 1]
s1 = s[i]
x = np.linspace(s0, s1, 20, endpoint=False)
c = np.linalg.solve(np.array([(1, s0, s0**2, s0**3),
(1, s1, s1**2, s1**3),
(0, 1, 2 * s0, 3 * s0**2),
(0, 1, 2 * s1, 3 * s1**2)]),
np.array([E[i - 1], E[i], dEds0, dEds]))
y = c[0] + x * (c[1] + x * (c[2] + x * c[3]))
Sfit[(i - 1) * 20:i * 20] = x
Efit[(i - 1) * 20:i * 20] = y
dEds0 = dEds
Sfit[-1] = s[-1]
Efit[-1] = E[-1]
return s, E, Sfit, Efit, lines
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