def test_rattle():
i = LJInteractions({('O', 'O'): (epsilon0, sigma0)})
for calc in [
TIP3P(),
SimpleQMMM([0, 1, 2], TIP3P(), TIP3P(), TIP3P()),
EIQMMM([0, 1, 2], TIP3P(), TIP3P(), i)
]:
dimer = s22('Water_dimer')
for m in [0, 3]:
dimer.set_angle(m + 1, m, m + 2, angleHOH)
dimer.set_distance(m, m + 1, rOH, fix=0)
dimer.set_distance(m, m + 2, rOH, fix=0)
fixOH1 = [(3 * i, 3 * i + 1) for i in range(2)]
fixOH2 = [(3 * i, 3 * i + 2) for i in range(2)]
fixHH = [(3 * i + 1, 3 * i + 2) for i in range(2)]
dimer.set_constraint(FixBondLengths(fixOH1 + fixOH2 + fixHH))
dimer.calc = calc
e = dimer.get_potential_energy()
md = VelocityVerlet(dimer,
8.0 * units.fs,
trajectory=calc.name + '.traj',
logfile=calc.name + '.log',
loginterval=5)
md.run(25)
de = dimer.get_potential_energy() - e
assert abs(de - -0.028) < 0.001
def integrate_atoms(
self,
atoms,
traj_file,
n_steps,
save_interval,
steps=0,
timestep=5.0,
traj_dir="trajs",
convert=False,
):
if not os.path.exists(traj_dir):
os.mkdir(traj_dir)
traj_file = os.path.join(traj_dir, traj_file)
if not os.path.exists(traj_file):
traj = Trajectory(traj_file, "w")
print("Creating trajectory {}...".format(traj_file))
dyn = VelocityVerlet(atoms, timestep=timestep * units.fs)
count = n_steps // save_interval
for i in range(count):
dyn.run(save_interval)
energy = atoms.get_total_energy()
forces = atoms.get_forces()
traj.write(atoms)
steps += save_interval
print("Steps: {}, total energy: {}".format(steps, energy))
else:
print("Trajectory {} already exists!".format(traj_file))
if convert:
self.convert_trajectory(traj_file)
return steps, traj_file
def md(gen='poscar.gen', index=0, totstep=100):
atoms = read(gen, index=index)
atoms.calc = IRFF(atoms=atoms, libfile='ffield.json', rcut=None, nn=True)
# dyn = BFGS(atoms)
dyn = VelocityVerlet(atoms, 0.1 * units.fs) # 5 fs time step.
def printenergy(a=atoms):
"""Function to print the potential, kinetic and total energy"""
natom = len(a)
epot = a.get_potential_energy() / natom
ekin = a.get_kinetic_energy() / natom
T = ekin / (1.5 * units.kB)
try:
assert T <= 8000.0, 'Temperature goes too high!'
except:
print('Temperature goes too high, stop at step %d.' % dyn.nsteps)
dyn.max_steps = dyn.nsteps - 1
# print(a.get_forces())
print('Energy per atom: Epot = %.3feV Ekin = %.3feV (T=%3.0fK) '
'Etot = %.3feV' % (epot, ekin, T, epot + ekin))
traj = Trajectory('md.traj', 'w', atoms)
dyn = VelocityVerlet(atoms, 0.1 * units.fs) # 5 fs time step.
dyn.attach(printenergy, interval=1)
dyn.attach(traj.write, interval=1)
dyn.run(totstep)
def test_rattle_linear():
"""Test RATTLE and QM/MM for rigid linear acetonitrile."""
import numpy as np
from ase import Atoms
from ase.calculators.acn import (ACN, m_me, r_cn, r_mec, sigma_me, sigma_c,
sigma_n, epsilon_me, epsilon_c, epsilon_n)
from ase.calculators.qmmm import SimpleQMMM, EIQMMM, LJInteractionsGeneral
from ase.md.verlet import VelocityVerlet
from ase.constraints import FixLinearTriatomic
import ase.units as units
sigma = np.array([sigma_me, sigma_c, sigma_n])
epsilon = np.array([epsilon_me, epsilon_c, epsilon_n])
i = LJInteractionsGeneral(sigma, epsilon, sigma, epsilon, 3)
for calc in [
ACN(),
SimpleQMMM([0, 1, 2], ACN(), ACN(), ACN()),
EIQMMM([0, 1, 2], ACN(), ACN(), i)
]:
dimer = Atoms('CCNCCN', [(-r_mec, 0, 0), (0, 0, 0), (r_cn, 0, 0),
(r_mec, 3.7, 0), (0, 3.7, 0),
(-r_cn, 3.7, 0)])
masses = dimer.get_masses()
masses[::3] = m_me
dimer.set_masses(masses)
fixd = FixLinearTriatomic(triples=[(0, 1, 2), (3, 4, 5)])
dimer.set_constraint(fixd)
dimer.calc = calc
d1 = dimer[:3].get_all_distances()
d2 = dimer[3:].get_all_distances()
e = dimer.get_potential_energy()
md = VelocityVerlet(dimer,
2.0 * units.fs,
trajectory=calc.name + '.traj',
logfile=calc.name + '.log',
loginterval=20)
md.run(100)
de = dimer.get_potential_energy() - e
assert np.all(abs(dimer[:3].get_all_distances() - d1) < 1e-10)
assert np.all(abs(dimer[3:].get_all_distances() - d2) < 1e-10)
assert abs(de - -0.005) < 0.001
def ase_md_playground():
geom = AnaPot.get_geom((0.52, 1.80, 0), atoms=("H", ))
atoms = geom.as_ase_atoms()
# ase_calc = FakeASE(geom.calculator)
# from ase.optimize import BFGS
# dyn = BFGS(atoms)
# dyn.run(fmax=0.05)
import ase
from ase import units
from ase.io.trajectory import Trajectory
from ase.md.velocitydistribution import MaxwellBoltzmannDistribution
from ase.md.verlet import VelocityVerlet
MaxwellBoltzmannDistribution(atoms, 300 * units.kB)
momenta = atoms.get_momenta()
momenta[0, 2] = 0.
# Zero 3rd dimension
atoms.set_momenta(momenta)
dyn = VelocityVerlet(atoms, .005 * units.fs) # 5 fs time step.
def printenergy(a):
"""Function to print the potential, kinetic and total energy"""
epot = a.get_potential_energy() / len(a)
ekin = a.get_kinetic_energy() / len(a)
print('Energy per atom: Epot = %.3feV Ekin = %.3feV (T=%3.0fK) '
'Etot = %.3feV' % (epot, ekin, ekin / (1.5 * units.kB), epot + ekin))
# Now run the dynamics
printenergy(atoms)
traj_fn = 'asemd.traj'
traj = Trajectory(traj_fn, 'w', atoms)
dyn.attach(traj.write, interval=5)
# dyn.attach(bumms().bimms, interval=1)
dyn.run(10000)
printenergy(atoms)
traj.close()
traj = ase.io.read(traj_fn+"@:")#, "r")
pos = [a.get_positions() for a in traj]
from pysisyphus.constants import BOHR2ANG
pos = np.array(pos) / BOHR2ANG
calc = geom.calculator
calc.plot()
ax = calc.ax
ax.plot(*pos[:,0,:2].T)
plt.show()
def maketraj(atoms, t, nstep):
e = [atoms.get_potential_energy()]
print "Shape of force:", atoms.get_forces().shape
dyn = VelocityVerlet(atoms, 5 * units.fs)
for i in range(nstep):
dyn.run(10)
energy = atoms.get_potential_energy()
e.append(energy)
if ismaster:
print "Energy: ", energy
if t is not None:
t.write()
return e
def maketraj(atoms, t, nstep):
e = [atoms.get_potential_energy()]
print "Shape of force:", atoms.get_forces().shape
dyn = VelocityVerlet(atoms, 5*units.fs)
for i in range(nstep):
dyn.run(10)
energy = atoms.get_potential_energy()
e.append(energy)
if ismaster:
print "Energy: ", energy
if t is not None:
t.write()
return e
def test_apply_strain(self):
calc = TersoffScr(**Tersoff_PRB_39_5566_Si_C__Scr)
timestep = 1.0 * units.fs
atoms = ase.io.read('cryst_rot_mod.xyz')
atoms.set_calculator(calc)
# constraints
top = atoms.positions[:, 1].max()
bottom = atoms.positions[:, 1].min()
fixed_mask = ((abs(atoms.positions[:, 1] - top) < 1.0) |
(abs(atoms.positions[:, 1] - bottom) < 1.0))
fix_atoms = FixAtoms(mask=fixed_mask)
# strain
orig_height = (atoms.positions[:, 1].max() -
atoms.positions[:, 1].min())
delta_strain = timestep * 1e-5 * (1 / units.fs)
rigid_constraints = False
strain_atoms = ConstantStrainRate(orig_height, delta_strain)
atoms.set_constraint(fix_atoms)
# dynamics
np.random.seed(0)
simulation_temperature = 300 * units.kB
MaxwellBoltzmannDistribution(atoms, 2.0 * simulation_temperature)
dynamics = VelocityVerlet(atoms, timestep)
def apply_strain(atoms, ConstantStrainRate, rigid_constraints):
ConstantStrainRate.apply_strain(atoms, rigid_constraints)
dynamics.attach(apply_strain, 1, atoms, strain_atoms,
rigid_constraints)
dynamics.run(100)
# tests
if rigid_constraints == True:
answer = 0
temp_answer = 238.2066417638124
else:
answer = 0.013228150080099255
temp_answer = 236.76904696481486
newpos = atoms.get_positions()
current_height = newpos[:, 1].max() - newpos[:, 1].min()
diff_height = (current_height - orig_height)
self.assertAlmostEqual(diff_height, answer)
temperature = (atoms.get_kinetic_energy() /
(1.5 * units.kB * len(atoms)))
self.assertAlmostEqual(temperature, temp_answer)
def test_md(cp2k_factory):
calc = cp2k_factory.calc(label='test_H2_MD')
positions = [(0, 0, 0), (0, 0, 0.7245595)]
atoms = Atoms('HH', positions=positions, calculator=calc)
atoms.center(vacuum=2.0)
MaxwellBoltzmannDistribution(atoms,
temperature_K=0.5 * 300,
force_temp=True)
energy_start = atoms.get_potential_energy() + atoms.get_kinetic_energy()
dyn = VelocityVerlet(atoms, 0.5 * units.fs)
dyn.run(20)
energy_end = atoms.get_potential_energy() + atoms.get_kinetic_energy()
assert abs(energy_start - energy_end) < 1e-4
def test_apply_strain(self):
calc = TersoffScr(**Tersoff_PRB_39_5566_Si_C__Scr)
timestep = 1.0*units.fs
atoms = ase.io.read('cryst_rot_mod.xyz')
atoms.set_calculator(calc)
# constraints
top = atoms.positions[:, 1].max()
bottom = atoms.positions[:, 1].min()
fixed_mask = ((abs(atoms.positions[:, 1] - top) < 1.0) |
(abs(atoms.positions[:, 1] - bottom) < 1.0))
fix_atoms = FixAtoms(mask=fixed_mask)
# strain
orig_height = (atoms.positions[:, 1].max() - atoms.positions[:, 1].min())
delta_strain = timestep*1e-5*(1/units.fs)
rigid_constraints = False
strain_atoms = ConstantStrainRate(orig_height, delta_strain)
atoms.set_constraint(fix_atoms)
# dynamics
np.random.seed(0)
simulation_temperature = 300*units.kB
MaxwellBoltzmannDistribution(atoms, 2.0*simulation_temperature)
dynamics = VelocityVerlet(atoms, timestep)
def apply_strain(atoms, ConstantStrainRate, rigid_constraints):
ConstantStrainRate.apply_strain(atoms, rigid_constraints)
dynamics.attach(apply_strain, 1, atoms, strain_atoms, rigid_constraints)
dynamics.run(100)
# tests
if rigid_constraints == True:
answer = 0
temp_answer = 238.2066417638124
else:
answer = 0.013228150080099255
temp_answer = 236.76904696481486
newpos = atoms.get_positions()
current_height = newpos[:, 1].max() - newpos[:, 1].min()
diff_height = (current_height - orig_height)
self.assertAlmostEqual(diff_height, answer)
temperature = (atoms.get_kinetic_energy()/(1.5*units.kB*len(atoms)))
self.assertAlmostEqual(temperature, temp_answer)
def constant_energy(nuclear_charges, coordinates, dump=None, calculator=None):
"""
"""
if calculator is None:
# LOAD AND SET MODEL
parameters = {}
parameters["offset"] = -97084.83100465109
parameters["sigma"] = 10.0
alphas = np.load(FILENAME_ALPHAS)
X = np.load(FILENAME_REPRESENTATIONS)
Q = np.load(FILENAME_CHARGES)
alphas = np.array(alphas, order="F")
X = np.array(X, order="F")
calculator = QMLCalculator(parameters, X, Q, alphas)
molecule = ase.Atoms(nuclear_charges, coordinates)
molecule.set_calculator(calculator)
# Set the momenta corresponding to T=300K
MaxwellBoltzmannDistribution(molecule, 200 * units.kB)
# We want to run MD with constant energy using the VelocityVerlet algorithm.
dyn = VelocityVerlet(molecule, 1 * units.fs) # 5 fs time step.
# if dump is not None:
# traj = Trajectory(dump, 'w', molecule)
# dyn.attach(traj.write, interval=5)
def printenergy(a=molecule,
t=None): # store a reference to atoms in the definition.
"""Function to print the potential, kinetic and total energy."""
epot = a.get_potential_energy() / len(a)
ekin = a.get_kinetic_energy() / len(a)
print('pEpot = %.2feV Ekin = %.2feV (T=%3.0fK) '
'Etot = %.4feV t=%.4f' % (epot, ekin, ekin /
(1.5 * units.kB), epot + ekin, t))
for i in range(10):
start = time.time()
dyn.run(0)
end = time.time()
printenergy(t=end - start)
return
def test_gfn2xtb_velocityverlet():
"""Perform molecular dynamics with GFN2-xTB and Velocity Verlet Integrator"""
thr = 1.0e-5
atoms = Atoms(
symbols="NHCHC2H3OC2H3ONHCH3",
positions=np.array([
[1.40704587284727, -1.26605342016611, -1.93713466561923],
[1.85007200612454, -0.46824072777417, -1.50918242392545],
[-0.03362432532150, -1.39269245193812, -1.74003582081606],
[-0.56857009928108, -1.01764444489068, -2.61263467107342],
[-0.44096297340282, -2.84337808903410, -1.48899734014499],
[-0.47991761226058, -0.55230954385212, -0.55520222968656],
[-1.51566045903090, -2.89187354810876, -1.32273881320610],
[-0.18116520746778, -3.45187805987944, -2.34920431470368],
[0.06989722340461, -3.23298998903001, -0.60872832703814],
[-1.56668253918793, 0.00552120970194, -0.52884675001441],
[1.99245341064342, -1.73097165236442, -3.08869239114486],
[3.42884244212567, -1.30660069291348, -3.28712665743189],
[3.87721962540768, -0.88843123009431, -2.38921453037869],
[3.46548545761151, -0.56495308290988, -4.08311788302584],
[4.00253374168514, -2.16970938132208, -3.61210068365649],
[1.40187968630565, -2.43826111827818, -3.89034127398078],
[0.40869198386066, -0.49101709352090, 0.47992424955574],
[1.15591901335007, -1.16524842262351, 0.48740266650199],
[0.00723492494701, 0.11692276177442, 1.73426297572793],
[0.88822128447468, 0.28499001838229, 2.34645658013686],
[-0.47231557768357, 1.06737634000561, 1.52286682546986],
[-0.70199987915174, -0.50485938116399, 2.28058247845421],
]),
)
calc = XTB(method="GFN2-xTB", cache_api=False)
atoms.set_calculator(calc)
dyn = VelocityVerlet(atoms, timestep=1.0 * fs)
dyn.run(20)
assert approx(atoms.get_potential_energy(), thr) == -896.9772346260584
assert approx(atoms.get_kinetic_energy(), thr) == 0.022411127028842362
atoms.calc.set(cache_api=True)
dyn.run(20)
assert approx(atoms.get_potential_energy(), thr) == -896.9913862530841
assert approx(atoms.get_kinetic_energy(), thr) == 0.036580471363852810
def MD(self):
"""Molecular Dynamic"""
from ase.md.velocitydistribution import MaxwellBoltzmannDistribution
from ase import units
from ase.md import MDLogger
from ase.io.trajectory import PickleTrajectory
from ase.md.langevin import Langevin
from ase.md.verlet import VelocityVerlet
dyndrivers = {
'Langevin': Langevin,
'None': VelocityVerlet,
}
useAsap = False
mol = self.mol
temperature = self.definedParams['temperature']
init_temperature = self.definedParams['init_temperature']
time_step = self.definedParams['time_step']
nstep = self.definedParams['nstep']
nprint = self.definedParams['nprint']
thermostat = self.definedParams['thermostat']
prop_file = os.path.join(self.definedParams['workdir'],
self.definedParams['output_prefix'] + '.out')
traj_file = os.path.join(self.definedParams['workdir'],
self.definedParams['output_prefix'] + '.traj')
MaxwellBoltzmannDistribution(mol, init_temperature * units.kB)
if thermostat == 'None':
dyn = VelocityVerlet(mol, time_step * units.fs)
elif thermostat == 'Langevin':
dyn = Langevin(mol, time_step * units.fs, temperature * units.kB,
0.01)
else:
raise ImplementationError(
method, 'Thermostat is not implemented in the MD function')
#Function to print the potential, kinetic and total energy
traj = PickleTrajectory(traj_file, "a", mol)
dyn.attach(MDLogger(dyn, mol, prop_file), interval=nprint)
dyn.attach(traj.write, interval=nprint)
dyn.run(nstep)
traj.close()
def MD(self):
"""Molecular Dynamic"""
from ase.md.velocitydistribution import MaxwellBoltzmannDistribution
from ase import units
from ase.md import MDLogger
from ase.io.trajectory import PickleTrajectory
from ase.md.langevin import Langevin
from ase.md.verlet import VelocityVerlet
dyndrivers = {
'Langevin': Langevin,
'None': VelocityVerlet,
}
useAsap = False
mol = self.mol
temperature = self.definedParams['temperature']
init_temperature = self.definedParams['init_temperature']
time_step = self.definedParams['time_step']
nstep = self.definedParams['nstep']
nprint = self.definedParams['nprint']
thermostat = self.definedParams['thermostat']
prop_file = os.path.join(self.definedParams['workdir'],
self.definedParams['output_prefix']+'.out')
traj_file = os.path.join(self.definedParams['workdir'],
self.definedParams['output_prefix']+'.traj')
MaxwellBoltzmannDistribution(mol,init_temperature*units.kB)
if thermostat == 'None':
dyn = VelocityVerlet(mol, time_step*units.fs)
elif thermostat == 'Langevin':
dyn = Langevin(mol, time_step*units.fs, temperature*units.kB, 0.01 )
else:
raise ImplementationError(method,'Thermostat is not implemented in the MD function')
#Function to print the potential, kinetic and total energy
traj = PickleTrajectory(traj_file,"a",mol)
dyn.attach(MDLogger(dyn,mol,prop_file),interval=nprint)
dyn.attach(traj.write, interval = nprint)
dyn.run(nstep)
traj.close()
def test_md(cp2k_factory):
calc = cp2k_factory.calc(label='test_H2_MD')
positions = [(0, 0, 0), (0, 0, 0.7245595)]
atoms = Atoms('HH', positions=positions, calculator=calc)
atoms.center(vacuum=2.0)
# Run MD
MaxwellBoltzmannDistribution(atoms, 0.5 * 300 * units.kB, force_temp=True)
energy_start = atoms.get_potential_energy() + atoms.get_kinetic_energy()
dyn = VelocityVerlet(atoms, 0.5 * units.fs)
#def print_md():
# energy = atoms.get_potential_energy() + atoms.get_kinetic_energy()
# print("MD total-energy: %.10feV" % energy)
#dyn.attach(print_md, interval=1)
dyn.run(20)
energy_end = atoms.get_potential_energy() + atoms.get_kinetic_energy()
assert energy_start - energy_end < 1e-4
print('passed test "H2_MD"')
def get_ANN_energy(input_file):
(structure_file, T, dt, md_steps, print_steps, trajectory_file,
potentials) = parse_input(input_file)
# atomic structure
atoms = ase.io.read(structure_file, format='vasp')
# ANN calculator
calc = ANNCalculator(potentials)
atoms.set_calculator(calc)
# initialize velocities
MaxwellBoltzmannDistribution(atoms, temp=T * units.kB)
# initialize MD
md = VelocityVerlet(atoms, dt * units.fs, trajectory=trajectory_file)
print("# {:5s} {:15s} {:15s} {:7s} {:15s}".format("step", "E_pot", "E_kin",
"T", "E_tot"))
printenergy(0, atoms)
istep = 0
for i in range(int(md_steps / print_steps)):
md.run(steps=print_steps)
istep += print_steps
printenergy(istep, atoms)
def run_md():
# Use Asap for a huge performance increase if it is installed
use_asap = True
if use_asap:
from asap3 import EMT
size = 10
else:
from ase.calculators.emt import EMT
size = 3
# Set up a crystal
atoms = FaceCenteredCubic(directions=[[1, 0, 0], [0, 1, 0], [0, 0, 1]],
symbol="Cu",
size=(size, size, size),
pbc=True)
# Describe the interatomic interactions with the Effective Medium Theory
atoms.calc = EMT()
# Set the momenta corresponding to T=300K
MaxwellBoltzmannDistribution(atoms, 300 * units.kB)
# We want to run MD with constant energy using the VelocityVerlet algorithm.
dyn = VelocityVerlet(atoms, 5 * units.fs) # 5 fs time step.
traj = Trajectory('cu.traj', 'w', atoms)
dyn.attach(traj.write, interval=10)
def printenergy(a=atoms): # store a reference to atoms in the definition.
epot, ekin = calcenergy(a)
print('Energy per atom: Epot = %.3feV Ekin = %.3feV (T=%3.0fK) '
'Etot = %.3feV' % (epot, ekin, ekin /
(1.5 * units.kB), epot + ekin))
# Now run the dynamics
dyn.attach(printenergy, interval=10)
printenergy()
dyn.run(200)
def main():
if "ASE_CP2K_COMMAND" not in os.environ:
raise NotAvailable('$ASE_CP2K_COMMAND not defined')
calc = CP2K(label='test_H2_MD')
positions = [(0, 0, 0), (0, 0, 0.7245595)]
atoms = Atoms('HH', positions=positions, calculator=calc)
atoms.center(vacuum=2.0)
# Run MD
MaxwellBoltzmannDistribution(atoms, 0.5 * 300 * units.kB, force_temp=True)
energy_start = atoms.get_potential_energy() + atoms.get_kinetic_energy()
dyn = VelocityVerlet(atoms, 0.5 * units.fs)
#def print_md():
# energy = atoms.get_potential_energy() + atoms.get_kinetic_energy()
# print("MD total-energy: %.10feV" % energy)
#dyn.attach(print_md, interval=1)
dyn.run(20)
energy_end = atoms.get_potential_energy() + atoms.get_kinetic_energy()
assert energy_start - energy_end < 1e-4
print('passed test "H2_MD"')
def main():
if "ASE_CP2K_COMMAND" not in os.environ:
raise NotAvailable('$ASE_CP2K_COMMAND not defined')
calc = CP2K(label='test_H2_MD')
positions = [(0, 0, 0), (0, 0, 0.7245595)]
atoms = Atoms('HH', positions=positions, calculator=calc)
atoms.center(vacuum=2.0)
# Run MD
MaxwellBoltzmannDistribution(atoms, 0.5 * 300 * units.kB, force_temp=True)
energy_start = atoms.get_potential_energy() + atoms.get_kinetic_energy()
dyn = VelocityVerlet(atoms, 0.5 * units.fs)
#def print_md():
# energy = atoms.get_potential_energy() + atoms.get_kinetic_energy()
# print("MD total-energy: %.10feV" % energy)
#dyn.attach(print_md, interval=1)
dyn.run(20)
energy_end = atoms.get_potential_energy() + atoms.get_kinetic_energy()
assert energy_start - energy_end < 1e-4
print('passed test "H2_MD"')
def run_md_Morse(Morse_parameters, A0, steps=10000, trajectory="md.traj"):
hbar_fs = (ase.units._hbar / ase.units._e) * 1.E15
D, a, R0, frequency = Morse_parameters[0:4]
r0 = R0
calculator = MorsePotential2(a=a, D=D, r0=r0)
#calculator = MorsePotential(rho0=6.0, epsilon=2.0, r0=1.0)
period = (hbar_fs / frequency) / (2 * pi)
pos = 1 * (r0 + A0)
atoms = Atoms("HH", positions=[[0, 0, 0], [pos, 0, 0]], masses=[1.0, 1.0])
constr = FixAtoms(indices=[0])
atoms.set_constraint(constr)
atoms.set_calculator(calculator)
# def V(d):
# atoms.set_positions([[0,0,0],[d,0,0]])
# return atoms.get_potential_energy()
# r_plot = linspace(-4.0,4.0,1000)
# V_plot = array([V(d) for d in r_plot])
# plt.plot(r_plot,V_plot)
# plt.show()
dynamics = VelocityVerlet(atoms,
dt=(period / 20.) * ase.units.fs,
trajectory=trajectory)
dynamics.run(20000)
Driver_Velocities_empty='<<+ "velocities.txt"',
Driver_Steps=500,
Driver_KeepStationary='Yes',
Driver_TimeStep=8.26,
Driver_Thermostat_='Berendsen',
Driver_Thermostat_Temperature=0.00339845142, # 800 deg Celcius
# Driver_Thermostat_Temperature=0.0, # 0 deg Kelvin
Driver_Thermostat_CouplingStrength=0.01)
write_dftb_velocities(test, 'velocities.txt')
os.system('rm md.log.* md.out* geo_end*xyz')
test.set_calculator(calculator_NVE)
dyn = VelocityVerlet(test, 0.000 * fs) # fs time step.
dyn.attach(MDLogger(dyn, test, 'md.log.NVE', header=True, stress=False,
peratom=False, mode='w'), interval=1)
dyn.run(1) # run NVE ensemble using DFTB's own driver
test = read('geo_end.gen')
write('test.afterNVE.xyz', test)
read_dftb_velocities(test, filename='geo_end.xyz')
write_dftb_velocities(test, 'velocities.txt')
os.system('mv md.out md.out.NVE')
os.system('mv geo_end.xyz geo_end_NVE.xyz')
test.set_calculator(calculator_NVT)
os.system('rm md.log.NVT')
dyn.attach(MDLogger(dyn, test, 'md.log.NVT', header=True, stress=False,
peratom=False, mode='w'), interval=1)
dyn.run(1) # run NVT ensemble using DFTB's own driver
test = read('geo_end.gen')
def run_md(atoms, id, settings_fn):
"""The function does Molecular Dyanamic simulation (MD) on a material, given by argument atoms.
Parameters:
atoms (obj): an atoms object defined by class in ase. This is the material which MD
will run on.
id (int): an identifying number for the material.
Returns:
obj:atoms object defined in ase, is returned.
"""
# Read settings
settings = read_settings_file(settings_fn)
initial_unitcell_atoms = copy.deepcopy(atoms)
# Scale atoms object, cubic
size = settings['supercell_size']
atoms = atoms * size * (1, 1, 1)
# atoms = atoms * (size,size,size)
#print(atoms.get_chemical_symbols())
N = len(atoms.get_chemical_symbols())
# Use KIM for potentials from OpenKIM
use_kim = settings['use_kim']
# Use Asap for a huge performance increase if it is installed
use_asap = True
# Create a copy of the initial atoms object for future reference
old_atoms = copy.deepcopy(atoms)
# Describe the interatomic interactions with OpenKIM potential
if use_kim: # use KIM potential
atoms.calc = KIM(
"LJ_ElliottAkerson_2015_Universal__MO_959249795837_003")
else: # otherwise, default to asap3 LennardJones
atoms.calc = LennardJones([18], [0.010323], [3.40],
rCut=6.625,
modified=True)
# Set the momenta corresponding to temperature from settings file
MaxwellBoltzmannDistribution(atoms, settings['temperature'] * units.kB)
# Select integrator
if settings['ensemble'] == "NVE":
from ase.md.verlet import VelocityVerlet
dyn = VelocityVerlet(atoms, settings['time_step'] * units.fs)
elif settings['ensemble'] == "NVT":
from ase.md.langevin import Langevin
dyn = Langevin(atoms, settings['time_step'] * units.fs,
settings['temperature'] * units.kB,
settings['friction'])
interval = settings['interval']
# Creates trajectory files in directory trajectory_files
traj = Trajectory("trajectory_files/" + id + ".traj", 'w', atoms)
dyn.attach(traj.write, interval=interval)
# Number of decimals for most calculated properties.
decimals = settings['decimals']
# Boolean indicating if the material is monoatomic.
monoatomic = len(set(atoms.get_chemical_symbols())) == 1
# Calculation and writing of properties
properties.initialize_properties_file(atoms, initial_unitcell_atoms, id,
decimals, monoatomic)
dyn.attach(properties.calc_properties, 100, old_atoms, atoms, id, decimals,
monoatomic)
# unnecessary, used for logging md runs
# we should write some kind of logger for the MD
def logger(a=atoms): # store a reference to atoms in the definition.
"""Function to print the potential, kinetic and total energy."""
epot = a.get_potential_energy() / len(a)
ekin = a.get_kinetic_energy() / len(a)
t = ekin / (1.5 * units.kB)
print('Energy per atom: Epot = %.3feV Ekin = %.3feV (T=%3.0fK) '
'Etot = %.3feV' % (epot, ekin, t, epot + ekin))
# Running the dynamics
dyn.attach(logger, interval=interval)
#logger()
#dyn.run(settings['max_steps'])
# check for thermal equilibrium
counter = 0
equilibrium = False
for i in range(round(settings['max_steps'] /
settings['search_interval'])): # hyperparameter
epot, ekin_pre, etot, t = properties.energies_and_temp(atoms)
# kör steg som motsvarar säg 5 fs
dyn.run(settings['search_interval']) # hyperparamter
epot, ekin_post, etot, t = properties.energies_and_temp(atoms)
#print(abs(ekin_pre-ekin_post) / math.sqrt(N))
#print(counter)
if (abs(ekin_pre - ekin_post) / math.sqrt(N)) < settings['tolerance']:
counter += 1
else:
counter = 0
if counter > settings['threshold']: # hyperparameter
print("reached equilibrium")
equilibrium = True
break
if equilibrium:
dyn.run(settings['max_steps'])
properties.finalize_properties_file(atoms, id, decimals, monoatomic)
else:
properties.delete_properties_file(id)
raise RuntimeError("MD did not find equilibrium")
return atoms
ReportTest("Initial potential energy", epot, -301358.3, 0.5)
etot = epot + atoms.get_kinetic_energy()
if 0:
if cpulayout:
traj = ParallelNetCDFTrajectory("parallel.nc", atoms)
else:
traj = NetCDFTrajectory("serial.nc", atoms)
traj.Add("PotentialEnergies")
traj.Update()
traj.Close()
print "Trajectory done"
dyn = VelocityVerlet(atoms, 3*units.fs)
etot2 = None
for i in range(5):
dyn.run(15)
newetot = atoms.get_potential_energy()+ atoms.get_kinetic_energy()
print >>stdout, "Total energy:", newetot
temp = atoms.get_kinetic_energy() / (1.5*units.kB*natoms)
print >>stdout, "Temp:", temp, "K"
if etot2 == None:
ReportTest("Total energy (first step)", newetot, etot, 40.0)
etot2=newetot
else:
ReportTest(("Total energy (step %d)" % (i+1,)),
newetot, etot2, 20.0)
print >>stdout, " *** This test completed ***"
ReportTest.Summary()
from asap3 import EMT
size = 10
else:
size = 3
# Set up a crystal
atoms = FaceCenteredCubic(directions=[[1,0,0],[0,1,0],[0,0,1]], symbol="Cu",
size=(size,size,size), pbc=True)
# Describe the interatomic interactions with the Effective Medium Theory
atoms.set_calculator(EMT())
# Set the momenta corresponding to T=300K
MaxwellBoltzmannDistribution(atoms, 300*units.kB)
# We want to run MD with constant energy using the VelocityVerlet algorithm.
dyn = VelocityVerlet(atoms, 5*units.fs) # 5 fs time step.
#Function to print the potential, kinetic and total energy
def printenergy(a):
epot = a.get_potential_energy() / len(a)
ekin = a.get_kinetic_energy() / len(a)
print ("Energy per atom: Epot = %.3feV Ekin = %.3feV (T=%3.0fK) Etot = %.3feV" %
(epot, ekin, ekin/(1.5*units.kB), epot+ekin))
# Now run the dynamics
printenergy(atoms)
for i in range(20):
dyn.run(10)
printenergy(atoms)
#Use same random seed so that initialisations are deterministic.
if not args.restart:
print 'Thermalizing atoms'
np.random.seed(42)
MaxwellBoltzmannDistribution(atoms, 2.0*sim_T)
dynamics = VelocityVerlet(atoms, timestep)
def print_context(ats=atoms, dyn=dynamics):
print 'steps, T', dyn.nsteps, ats.get_kinetic_energy()/(1.5*units.kB*len(ats))
print 'G', get_energy_release_rate(ats)/(units.J/units.m**2)
print 'strain', get_strain(ats)
dynamics.attach(print_context, interval=8)
print 'Running Crack Simulation'
dynamics.run(nsteps)
print 'Crack Simulation Finished'
elif args.lotf:
crack_pos = atoms.info['CrackPos']
r_scale = 1.00894848312
mm_pot = Potential('IP EAM_ErcolAd do_rescale_r=T r_scale={0}'.format(r_scale), param_filename=eam_pot, cutoff_skin=2.0)
#test potential
#quippy using atomic units
atoms.cutoff = 3.0
atoms.set_cutoff(3.0)
atoms.calc_connect()
qmmm_pot = ForceMixingPotential(pot1=mm_pot, pot2=qm_pot, atoms=atoms,
qm_args_str='carve_cluster=T cluster_periodic_z=T cluster_calc_connect=T '+
'single_cluster=T cluster_vacuum=5.0 terminate=F print_clusters=F '+
(1.5*units.kB*len(atoms)))
atoms.info['strain'] = get_strain(atoms)
atoms.info['G'] = get_energy_release_rate(atoms)/(units.J/units.m**2)
crack_pos = find_crack_tip_stress_field(atoms, calc=mm_pot)
atoms.info['crack_pos_x'] = crack_pos[0]
atoms.info['d_crack_pos_x'] = crack_pos[0] - orig_crack_pos[0]
print log_format % atoms.info
dynamics.attach(printstatus)
# Check if the crack has advanced, and stop incrementing the strain if it has
def check_if_cracked(atoms):
crack_pos = find_crack_tip_stress_field(atoms, calc=mm_pot)
# stop straining if crack has advanced more than tip_move_tol
if not atoms.info['is_cracked'] and (crack_pos[0] - orig_crack_pos[0]) > tip_move_tol:
atoms.info['is_cracked'] = True
del atoms.constraints[atoms.constraints.index(strain_atoms)]
dynamics.attach(check_if_cracked, 1, atoms)
# Save frames to the trajectory every `traj_interval` time steps
trajectory = AtomsWriter(traj_file)
dynamics.attach(trajectory, traj_interval, atoms)
# Start running!
dynamics.run(nsteps)
print log_format % atoms.info
dynamics.attach(printstatus)
# Check if the crack has advanced, and stop incrementing the strain if it has
def check_if_cracked(atoms):
#crack_pos = find_tip_stress_field(atoms)
# FIXME TS has no local virial
crack_pos = [0.0, 0.0, 0.0]
# stop straining if crack has advanced more than tip_move_tol
if (not atoms.info['is_cracked'] and
(crack_pos[0] - orig_crack_pos[0]) > params.tip_move_tol):
atoms.info['is_cracked'] = True
del atoms.constraints[atoms.constraints.index(strain_atoms)]
dynamics.attach(check_if_cracked, 1, atoms)
# Save frames to the trajectory every `traj_interval` time steps
traj_file = open('traj_verlet_6R.xyz', 'w')
trajectory_write = lambda: ase.io.extxyz.write_xyz(traj_file, atoms)
dynamics.attach(trajectory_write, params.traj_interval)
try:
# Start running!
dynamics.run(params.nsteps)
finally:
traj_file.close()
def test_lammpslib():
# potential_path must be set as an environment variable
cmds = [
"pair_style eam/alloy", "pair_coeff * * NiAlH_jea.eam.alloy Ni H"
]
nickel = bulk('Ni', cubic=True)
nickel += Atom('H', position=nickel.cell.diagonal() / 2)
# Bit of distortion
nickel.set_cell(nickel.cell +
[[0.1, 0.2, 0.4], [0.3, 0.2, 0.0], [0.1, 0.1, 0.1]],
scale_atoms=True)
lammps = LAMMPSlib(lmpcmds=cmds,
atom_types={
'Ni': 1,
'H': 2
},
log_file='test.log',
keep_alive=True)
nickel.calc = lammps
E = nickel.get_potential_energy()
F = nickel.get_forces()
S = nickel.get_stress()
print('Energy: ', E)
print('Forces:', F)
print('Stress: ', S)
print()
E = nickel.get_potential_energy()
F = nickel.get_forces()
S = nickel.get_stress()
lammps = LAMMPSlib(lmpcmds=cmds, log_file='test.log', keep_alive=True)
nickel.calc = lammps
E2 = nickel.get_potential_energy()
F2 = nickel.get_forces()
S2 = nickel.get_stress()
assert_allclose(E, E2, atol=1e-4, rtol=1e-4)
assert_allclose(F, F2, atol=1e-4, rtol=1e-4)
assert_allclose(S, S2, atol=1e-4, rtol=1e-4)
nickel.rattle(stdev=0.2)
E3 = nickel.get_potential_energy()
F3 = nickel.get_forces()
S3 = nickel.get_stress()
print('rattled atoms')
print('Energy: ', E3)
print('Forces:', F3)
print('Stress: ', S3)
print()
assert not np.allclose(E, E3)
assert not np.allclose(F, F3)
assert not np.allclose(S, S3)
nickel += Atom('H', position=nickel.cell.diagonal() / 4)
E4 = nickel.get_potential_energy()
F4 = nickel.get_forces()
S4 = nickel.get_stress()
assert not np.allclose(E4, E3)
assert not np.allclose(F4[:-1, :], F3)
assert not np.allclose(S4, S3)
# the example from the docstring
cmds = [
"pair_style eam/alloy", "pair_coeff * * NiAlH_jea.eam.alloy Al H"
]
Ni = bulk('Ni', cubic=True)
H = Atom('H', position=Ni.cell.diagonal() / 2)
NiH = Ni + H
lammps = LAMMPSlib(lmpcmds=cmds, log_file='test.log')
NiH.calc = lammps
print("Energy ", NiH.get_potential_energy())
# a more complicated example, reading in a LAMMPS data file
# then we run the actual test
with open('lammps.data', 'w') as fd:
fd.write(lammps_data_file)
at = ase.io.read('lammps.data',
format='lammps-data',
Z_of_type={1: 26},
units='real')
header = [
"units real", "atom_style full",
"boundary p p p", "box tilt large",
"pair_style lj/cut/coul/long 12.500",
"bond_style harmonic", "angle_style harmonic",
"kspace_style ewald 0.0001", "kspace_modify gewald 0.01",
"read_data lammps.data"
]
cmds = []
lammps = LAMMPSlib(lammps_header=header,
lmpcmds=cmds,
atom_types={'Fe': 1},
create_atoms=False,
create_box=False,
boundary=False,
keep_alive=True,
log_file='test.log')
at.calc = lammps
dyn = VelocityVerlet(at, 1 * units.fs)
assert_allclose(at.get_potential_energy(),
2041.411982950972,
atol=1e-4,
rtol=1e-4)
dyn.run(10)
assert_allclose(at.get_potential_energy(),
312.4315854721744,
atol=1e-4,
rtol=1e-4)
class SpinLatticeModel():
def __init__(self,
spin_model,
lattice_model,
spin_lattice_coupling,
atoms=None):
self._spin_model = spin_model
self._lattice_model = lattice_model
self._slc = spin_lattice_coupling
self._spin_model.add_term(self._slc, name='slc')
self._lattice_model.add_term(self._slc, name='slc')
#self.atoms = copy.deepcopy(self._lattice_model.ref_atoms)
if atoms is not None:
self.atoms = atoms
else:
self.atoms = copy.deepcopy(self._lattice_model.ref_atoms)
self.atoms.set_calculator(self._lattice_model)
self._lattice_model.atoms = self.atoms
@property
def spin_model(self):
return self._spin_model
@property
def lattice_model(self):
return self._lattice_model
@property
def slc(self):
return self._slc
def set_atoms(self, atoms, copy=False):
if copy:
self.atoms = copy.deepcopy(atoms)
else:
self.atoms = atoms
self.atoms.set_calculator(self._lattice_model)
self._lattice_model.atoms = atoms
def set_spin_params(self, **kwargs):
self.spin_model.set(**kwargs)
def set_lattice_params(self, md='NVE', **kwargs):
#self.lattice_model.set(**kwargs)
self.lattice_temperature = kwargs['lattice_temperature']
self.lattice_time_step = kwargs['lattice_time_step']
self.lattice_friction = kwargs['lattice_friction']
if md == 'Langevin':
self._lattice_dyn = Langevin(self.atoms,
self.lattice_time_step,
self.lattice_temperature,
self.lattice_friction,
trajectory='LattHist.traj')
elif md == 'NVE':
self._lattice_dyn = VelocityVerlet(self.atoms,
dt=self.lattice_time_step,
trajectory='LattHist.traj')
def make_supercell(self, sc_matrix):
smaker = SupercellMaker(sc_matrix)
sc_spin_model = self._spin_model.make_supercell(supercell_maker=smaker)
sc_lattice_model = self._lattice_model.make_supercell(
supercell_maker=smaker)
sc_slc = self._slc.make_supercell(supercell_maker=smaker,
sc_spin_model=sc_spin_model,
sc_lattice_model=sc_lattice_model)
return SpinLatticeModel(sc_spin_model, sc_lattice_model, sc_slc)
#@profile
def run(self, nstep=1):
self._slc.S = self._spin_model.S
self._slc.displacement = self._lattice_model.dx
for istep in range(nstep):
self._lattice_dyn.run(1)
self._spin_model.run_one_step()
self._slc.displacement = self._lattice_model.dx
self._slc.S = self._spin_model.S
def test(temp, frict):
output = file('Langevin.dat', 'w')
# Make a small perturbation of the momenta
atoms.set_momenta(1e-6 * np.random.random([len(atoms), 3]))
print 'Initializing ...'
predyn = VelocityVerlet(atoms, 0.5)
predyn.run(2500)
dyn = Langevin(atoms, timestep, temp, frict)
print ''
print ('Testing Langevin dynamics with T = %f eV and lambda = %f' %
(temp, frict))
ekin = atoms.get_kinetic_energy()/len(atoms)
print ekin
output.write('%.8f\n' % ekin)
print 'Equilibrating ...'
# Initial guesses for least-squares fit
a = 0.04
b = 2*frict
c = temp
params = (a,b,c)
fitdata = [(0, 2.0 / 3.0 * ekin)]
tstart = time.time()
for i in xrange(1,nequil+1):
dyn.run(nminor)
ekin = atoms.get_kinetic_energy() / len(atoms)
fitdata.append((i*nminor*timestep, 2.0/3.0 * ekin))
if usescipy and i % nequilprint == 0:
(params, chisq) = leastSquaresFit(targetfunc, params, fitdata)
print '%.6f T_inf = %.6f (goal: %f), tau = %.2f, k = %.6f' % \
(ekin, params[2], temp, 1.0/params[1], params[0])
output.write('%.8f\n' % ekin)
tequil = time.time() - tstart
print 'This took %s minutes.' % (tequil / 60)
output.write('&\n')
assert abs(temp-params[2]) < 0.25*temp, 'Least-squares fit is way off'
assert nequil*nminor*timestep > 3.0/params[1], 'Equiliberation was too short'
fitdata = np.array(fitdata)
print 'Recording statistical data - this takes ten times longer!'
temperatures = []
tstart = time.time()
for i in xrange(1,nsteps+1):
dyn.run(nminor)
ekin = atoms.get_kinetic_energy() / len(atoms)
temperatures.append(2.0/3.0 * ekin)
if i % nprint == 0:
tnow = time.time() - tstart
tleft = (nsteps-i) * tnow / i
print '%.6f (time left: %.1f minutes)' % (ekin, tleft/60)
output.write('%.8f\n' % ekin)
output.write('&\n')
output.close()
temperatures = np.array(temperatures)
mean = sum(temperatures) / len(temperatures)
print 'Mean temperature:', mean, 'eV'
print
print 'This test is statistical, and may in rare cases fail due to a'
print 'statistical fluctuation.'
print
assert abs(mean - temp) <= reltol*temp, 'Deviation is too large.'
print 'Mean temperature:', mean, ' in ', temp, ' +/- ', reltol*temp
return fitdata, params, temperatures
def molecular_dynamics(molecule,
calculator,
temperature=300.0,
sample_interval=10,
total_time=10.0,
time_step=0.1,
seed=None):
"""
Run molecular dynamics on a structure
"""
if seed is not None:
np.random.seed(seed)
dt = time_step * ase.units.fs
temp = temperature * ase.units.kB
steps = int(total_time * 1000.0 / time_step)
velocitydistribution.MaxwellBoltzmannDistribution(molecule,
temp,
force_temp=True)
velocitydistribution.Stationary(molecule)
velocitydistribution.ZeroRotation(molecule)
print("Initial temperature from velocities %.2f" %
molecule.get_temperature())
print("Performing %d steps of %f fs for a total time of %f ps" %
(steps, time_step, total_time))
molecule.set_calculator(calculator)
# dyn = Langevin(
# molecule,
# 1.0*ase.units.fs,
# temp,
# friction=0.001,
# logfile='-',
# loginterval=sample_interval
# )
dyn = VelocityVerlet(molecule,
dt,
logfile='-',
loginterval=sample_interval,
trajectory='dynamics.traj')
md_path = []
count_steps = 0
ave_temp = 0
def log_md_path(atoms):
nonlocal md_path
nonlocal count_steps
nonlocal ave_temp
if count_steps % sample_interval == 0:
md_path.append(atoms.copy())
ave_temp += atoms.get_temperature()
count_steps += 1
start_time = time.time()
dyn.attach(log_md_path, 10, molecule)
dyn.run(steps)
end_time = time.time()
print("Time to sample dynamics %.2f s" % (end_time - start_time))
#ave_temp /= len(md_path)
#print("Total MD time %.2f" % (steps / 1000.0))
#print("Average Temperature during MD %.2f" % (ave_temp))
return md_path
(options, args) = parser.parse_args()
def printenergy(a, it, t0):
"""Function to print the potential, kinetic and total energy"""
epot = a.get_potential_energy() / len(a)
ekin = a.get_kinetic_energy() / len(a)
t_now = time()
print('Step: %4d [%6.2f]: Epot = %.3feV Ekin = %.3feV (T=%3.0fK) '
'Etot = %.3feV ' % (\
it, t_now-t0, epot, ekin, ekin / (1.5 * units.kB), epot + ekin))
return t_now
ff = PyXtal_FF(model={'system': ["Si"]}, logo=False)
ff.run(mode='predict', mliap=options.file)
calc = PyXtalFFCalculator(ff=ff)
si = bulk('Si', 'diamond', a=5.459, cubic=True)
si = si * 5
print("MD simulation for ", len(si), " atoms")
si.set_calculator(calc)
MaxwellBoltzmannDistribution(si, 300 * units.kB)
dyn = VelocityVerlet(si, 1 * units.fs) # 2 fs time step.
t0 = time()
for i in range(10):
dyn.run(steps=1)
t_now = printenergy(si, i, t0)
t0 = t_now
atoms.set_pbc(False)
atoms.center(vacuum=6.0)
atoms.set_velocities(np.zeros_like(atoms.get_positions()))
cell_c = np.sum(atoms.get_cell()**2, axis=1)**0.5
N_c = 16 * np.round(cell_c / (0.25 * 16))
calc = GPAW(gpts=N_c, nbands=1, basis='dzp', setups={'Na': '1'},
txt=name + '_gs.txt')
atoms.set_calculator(calc)
atoms.get_potential_energy()
calc.write(name + '_gs.gpw', mode='all')
del atoms, calc
time.sleep(10)
while not os.path.isfile(name + '_gs.gpw'):
print 'Node %d waiting for file...' % world.rank
time.sleep(10)
world.barrier()
tdcalc = GPAW(name + '_gs.gpw', txt=name + '_td.txt')
tdcalc.forces.reset() #XXX debug
tdcalc.initialize_positions()
atoms = tdcalc.get_atoms()
traj = PickleTrajectory(name + '_td.traj', 'w', atoms)
verlet = VelocityVerlet(atoms, timestep * 1e-3 * fs,
logfile=paropen(name + '_td.verlet', 'w'),
trajectory=traj)
verlet.attach(Timing(paropen(name + '_td.log', 'w')), ndiv, atoms)
verlet.run(niter)
traj.close()
Z_of_type = {1:26}
atom_types = {'Fe':1,}
at = ase.io.read('lammps.data', format='lammps-data', Z_of_type=Z_of_type, units='real')
header = ["units real",
"atom_style full",
"boundary p p p",
"box tilt large",
"pair_style lj/cut/coul/long 12.500",
"bond_style harmonic",
"angle_style harmonic",
"kspace_style ewald 0.0001",
"read_data lammps.data"]
cmds = []
lammps = LAMMPSlib(lammps_header=header, lmpcmds=cmds, atom_types=atom_types, create_atoms=False, create_box=False, boundary=False, keep_alive=True, log_file='test.log')
at.set_calculator(lammps)
dyn = VelocityVerlet(at, 1 * units.fs)
energy = at.get_potential_energy()
energy_ref = 2041.41198295
diff = abs((energy - energy_ref) / energy_ref)
assert diff < 1e-10
dyn.run(10)
energy = at.get_potential_energy()
energy_ref = 312.431585607
diff = abs((energy - energy_ref) / energy_ref)
assert diff < 1e-10, "%d" % energy
# pass
def __repr__(self):
return 'Push atoms out of the cell back to the cell'
def copy(self):
return ConstantForce(a=self.index, force=self.force)
if __name__ == '__main__':
from ase.cluster.cubic import FaceCenteredCubic
from ase.calculators.emt import EMT
from ase.md.verlet import VelocityVerlet
from ase.units import fs
from constantforce import ConstantForce
atoms = FaceCenteredCubic(
'Ag', [(1, 0, 0)], [1], 4.09)
atoms.center(10)
atoms.pbc = True
atoms.set_calculator( EMT() )
cf = ConstantForce( 10, [0,1,0] ) # y=dircted force
ic = ImprisonConstraint()
atoms.set_constraint( [cf, ic] )
md = VelocityVerlet( atoms, 1*fs, trajectory = 'cf_test.traj', logfile='-' )
md.run(200)
#~ from ase.visualize import view
#~ view(atoms)
"""
# This section imports the Python packages required during this exercise.
from MorseCalculator import MorsePotential
from ase.io import write, read
from ase import units
from ase.md.verlet import VelocityVerlet
# Parameters for the Morse potential for Cu
D = 0.3429
r0 = 2.866
alpha = 1.3588
atoms = read('berendsen.traj', index=-1)
atoms.set_calculator(MorsePotential(D=D, alpha=alpha, r0=r0))
del atoms[39]
open('md.log', 'w').close() # clean current log file
dyn = VelocityVerlet(atoms,
dt=5 * units.fs,
trajectory='md.traj',
logfile='md.log')
dyn.run(10000)
write('md.xyz', read('md.traj@:'))
# Here is some code missing!
dist = 0.001
energy += self.A / dist**self.alpha
return energy
def __repr__(self):
return 'Repulsion potential'
def copy(self):
return CentralRepulsion(self, R=self.R, A=self.A, alpha=self.alpha)
if __name__ == '__main__':
from ase.cluster.cubic import FaceCenteredCubic
from ase.calculators.emt import EMT
from ase.md.verlet import VelocityVerlet
from ase.units import fs
atoms = FaceCenteredCubic('Ag', [(1, 0, 0)], [1], 4.09)
atoms.center(10)
atoms.set_calculator(EMT())
c = ConstantForce(10, [0, 1, 0]) # y=dircted force
atoms.set_constraint(c)
md = VelocityVerlet(atoms, 1*fs, trajectory='cf_test.traj',
logfile='-')
md.run(100)
# from ase.visualize import view
# view(atoms)
# Describe the interatomic interactions with the Effective Medium Theory
atoms.set_calculator(lammps['ref'])
np.random.seed(42)
# Set the momenta corresponding to T=300K
MaxwellBoltzmannDistribution(atoms, 1000 * units.kB)
# We want to run MD with constant energy using the VelocityVerlet algorithm.
dyn = VelocityVerlet(atoms, 1 * units.fs) # 5 fs time step.
def printenergy(a):
"""Function to print the potential, kinetic and total energy"""
epot = a.get_potential_energy() / len(a)
ekin = a.get_kinetic_energy() / len(a)
delta = np.max(np.abs(a.get_forces() - lammps['our'].get_forces(a)))
print('Energy per atom: Epot = %.3feV Ekin = %.3feV (T=%3.0fK) '
'Etot = %.3feV d=%.3e' % (epot, ekin, ekin /
(1.5 * units.kB), epot + ekin, delta))
from ase.io.trajectory import Trajectory
traj = Trajectory('example.traj', 'w', atoms)
dyn.attach(traj.write, interval=1)
# Now run the dynamics
printenergy(atoms)
for i in range(100):
dyn.run(1)
printenergy(atoms)
dimer = Atoms('CCNCCN', [(-r_mec, 0, 0), (0, 0, 0), (r_cn, 0, 0),
(r_mec, 3.7, 0), (0, 3.7, 0), (-r_cn, 3.7, 0)])
masses = dimer.get_masses()
masses[::3] = m_me
dimer.set_masses(masses)
fixd = FixLinearTriatomic(triples=[(0, 1, 2), (3, 4, 5)])
dimer.set_constraint(fixd)
dimer.calc = calc
d1 = dimer[:3].get_all_distances()
d2 = dimer[3:].get_all_distances()
e = dimer.get_potential_energy()
md = VelocityVerlet(dimer,
2.0 * units.fs,
trajectory=calc.name + '.traj',
logfile=calc.name + '.log',
loginterval=20)
md.run(100)
de = dimer.get_potential_energy() - e
assert np.all(abs(dimer[:3].get_all_distances() - d1) < 1e-10)
assert np.all(abs(dimer[3:].get_all_distances() - d2) < 1e-10)
assert abs(de - -0.005) < 0.001
velocities_t1 = velocities
coordinates_t1 = coordinates
force_up_t1 = force_up_t2
force_down_t1 = force_down_t2
force_mid_t1 = force_mid_t2
# condition to avoid hops immediately after each other
if skip_next:
if skip_count == 3:
skip_count = 0
skip_next = False
else:
skip_count += 1
# if the hop was accepted
if hop:
# decrement j_md because we made one MD step back
j_md -= 1
skip_next = True
hop = False
# increment global MD counter
j_md += 1
"""Launcher for molecular dynamics"""
# run MD for n_md steps with TSH module
dyn.attach(tsh, interval=1)
dyn.run(n_md)
# close data files
df.close()
#df2.close()
crack_pos = find_tip_stress_field(atoms)
atoms.info['crack_pos_x'] = crack_pos[0]
atoms.info['d_crack_pos_x'] = crack_pos[0] - orig_crack_pos[0]
print log_format % atoms.info
dynamics.attach(printstatus)
# Check if the crack has advanced, and stop incrementing the strain if it has
def check_if_cracked(atoms):
crack_pos = find_tip_stress_field(atoms)
# stop straining if crack has advanced more than tip_move_tol
if (not atoms.info['is_cracked']
and (crack_pos[0] - orig_crack_pos[0]) > params.tip_move_tol):
atoms.info['is_cracked'] = True
del atoms.constraints[atoms.constraints.index(strain_atoms)]
dynamics.attach(check_if_cracked, 1, atoms)
# Save frames to the trajectory every `traj_interval` time steps
trajectory = NetCDFTrajectory(params.traj_file, mode='w')
dynamics.attach(trajectory.write, params.traj_interval)
# Start running!
dynamics.run(params.nsteps)
def update_atoms(self):
pass
def set_atoms(self, atoms):
self.atoms = atoms
self.update_atoms()
if __name__ == '__main__':
from ase import Atoms
atoms = Atoms(symbols='CeO', cell=[2, 2, 5], positions=np.array([[0.0, 0.0, 0.0], [0.0, 0.0, 2.4935832]]))
atoms[0].charge = +4
atoms[1].charge = -2
calc = Buck({('Ce', 'O'): (1176.3, 0.381, 0.0)})
#calc = Buck( {('Ce', 'O'): (0.0, 0.149, 0.0)} )
atoms.set_calculator(calc)
print('Epot = ', atoms.get_potential_energy())
print('Force = ', atoms.get_forces())
from ase.md.verlet import VelocityVerlet
dyn = VelocityVerlet(atoms, dt=0.1*units.fs, trajectory='test.traj', logfile='-')
dyn.run(1000)
print('coodrs = ', atoms.get_positions())
from ase.visualize import view
view(atoms)
else:
i += 1
c = FixAtoms(indices = array)
atoms.set_constraint(c)
# relax with Quasi Newtonian
qn = QuasiNewton(atoms, trajectory='qn.traj')
qn.run(fmax=0.001)
write('qn.final.xyz', atoms)
# Set the momenta corresponding to T=300K
MaxwellBoltzmannDistribution(atoms, 300*units.kB)
print 'Removing linear momentum and angular momentum'
Stationary(atoms) # zero linear momentum
ZeroRotation(atoms) # zero angular momentum
# We want to run MD using the VelocityVerlet algorithm.
dyn = VelocityVerlet(atoms, 0.1*units.fs, trajectory='moldyn4.traj') # save trajectory.
#Function to print the potential, kinetic and total energy.
def printenergy(a=atoms): #store a reference to atoms in the definition.
epot = a.get_potential_energy() / len(a)
ekin = a.get_kinetic_energy() / len(a)
print ("Energy per atom: Epot = %.3feV Ekin = %.3feV (T=%3.0fK) Etot = %.3feV" %
(epot, ekin, ekin/(1.5*units.kB), epot+ekin))
dyn.attach(printenergy, interval=10)
# Now run the dynamics
printenergy()
dyn.run(2000)
Driver_Velocities_empty='<<+ "velocities.txt"',
Driver_Steps=500,
Driver_KeepStationary='Yes',
Driver_TimeStep=8.26,
Driver_Thermostat_='Berendsen',
Driver_Thermostat_Temperature=0.00339845142, # 800 deg Celcius
# Driver_Thermostat_Temperature=0.0, # 0 deg Kelvin
Driver_Thermostat_CouplingStrength=0.01)
write_dftb_velocities(test, 'velocities.txt')
os.system('rm md.log.* md.out* geo_end*xyz')
test.set_calculator(calculator_NVE)
dyn = VelocityVerlet(test, 0.000 * fs) # fs time step.
dyn.attach(MDLogger(dyn, test, 'md.log.NVE', header=True, stress=False,
peratom=False, mode='w'), interval=1)
dyn.run(1) # run NVE ensemble using DFTB's own driver
test = read('geo_end.gen')
write('test.afterNVE.xyz', test)
read_dftb_velocities(test, filename='geo_end.xyz')
write_dftb_velocities(test, 'velocities.txt')
os.system('mv md.out md.out.NVE')
os.system('mv geo_end.xyz geo_end_NVE.xyz')
test.set_calculator(calculator_NVT)
os.system('rm md.log.NVT')
dyn.attach(MDLogger(dyn, test, 'md.log.NVT', header=True, stress=False,
peratom=False, mode='w'), interval=1)
dyn.run(1) # run NVT ensemble using DFTB's own driver
test = read('geo_end.gen')
size = 3
# Set up a crystal
atoms = FaceCenteredCubic(directions=[[1, 0, 0], [0, 1, 0], [0, 0, 1]],
symbol="Cu",
size=(size, size, size),
pbc=True)
# Describe the interatomic interactions with the Effective Medium Theory
atoms.calc = EMT()
# Set the momenta corresponding to T=300K
MaxwellBoltzmannDistribution(atoms, 300 * units.kB)
# We want to run MD with constant energy using the VelocityVerlet algorithm.
dyn = VelocityVerlet(atoms, 5 * units.fs) # 5 fs time step.
def printenergy(a=atoms): # store a reference to atoms in the definition.
"""Function to print the potential, kinetic and total energy."""
epot = a.get_potential_energy() / len(a)
ekin = a.get_kinetic_energy() / len(a)
print('Energy per atom: Epot = %.3feV Ekin = %.3feV (T=%3.0fK) '
'Etot = %.3feV' % (epot, ekin, ekin / (1.5 * units.kB), epot + ekin))
# Now run the dynamics
dyn.attach(printenergy, interval=10)
printenergy()
dyn.run(200)
ZeroRotation(atoms) # zero angular momentum
# We want to run MD using the VelocityVerlet algorithm.
dyn = VelocityVerlet(atoms, 0.1*units.fs, trajectory='moldyn4.traj') # save trajectory.
#Function to print the potential, kinetic and total energy.
def printenergy(t=atoms): #store a reference to atoms in the definition.
epot = t.get_potential_energy() / len(t)
ekin = t.get_kinetic_energy() / len(t)
print ("Energy per atom: Epot = %.3feV Ekin = %.3feV (T=%3.0fK) Etot = %.3feV" %
(epot, ekin, ekin/(1.5*units.kB), epot+ekin))
ETOT = ekin + epot
print ETOT
x_dist = atoms.get_distance(a0 = 0, a1 = 1)
forces = atoms.get_forces()
OP.append(x_dist)
OP.append(ekin+epot)
dyn.attach(printenergy, interval=10)
# Now run the dynamics
dyn.run(400)
OP_f = [OP[i:i+2] for i in xrange(0,len(OP),2)]
OP_f_text = np.savetxt('out.tmp', OP_f) # reads array and saves into a file as a string
OP_f_infile = open('out.tmp','r') # open file to write string array onto
OP_f_text = OP_f_infile.read()
text_file.write(OP_f_text)
text_file.close()
