def init_dynamics(self, Nm, V, L, dt, T):
self.L = L
# Generate the box of junk
self.__generategarbagebox__(Nm, L, T)
# Make mol
self.mol = Atoms(symbols=self.S, positions=self.X)
# Set box and PBC
self.mol.set_cell(([[L, 0, 0], [0, L, 0], [0, 0, L]]))
self.mol.set_pbc((True, True, True))
# Set ANI calculator
# Set ANI calculator
self.mol.set_calculator(ANIENS(self.aens))
#self.mol.set_calculator(ANI(False))
#self.mol.calc.setnc(self.ncl[0])
# Give molecules random velocity
acc_idx = 0
vel = np.empty_like(self.X)
for n in self.Na:
rv = np.random.uniform(-V, V, size=(3))
for k in range(n):
vel[acc_idx + k, :] = rv
acc_idx += n
#print(vel)
self.mol.set_velocities(vel)
# Declare Dyn
self.dyn = Langevin(self.mol, dt * units.fs, T * units.kB, 0.1)
def init_dynamics(self, Nm, Nembed, V, L, dt, T):
self.L = L
# Generate the box of junk
self.__generategarbagebox__(Nm, Nembed, L, T)
# Make mol
self.mol = Atoms(symbols=self.S, positions=self.X)
# Set box and PBC
self.mol.set_cell(([[L, 0, 0], [0, L, 0], [0, 0, L]]))
self.mol.set_pbc((True, True, True))
# Set ANI calculator
self.mol.set_calculator(ANIENS(self.aens))
# Open MD output
#self.mdcrd = open(xyzfile, 'w')
# Open MD output
#self.traj = open(trjfile, 'w')
# Set the velocities corresponding to a boltzmann dist @ T/4.0
MaxwellBoltzmannDistribution(self.mol, 300.0 * units.kB)
# Declare Dyn
self.dyn = Langevin(self.mol, dt * units.fs, T * units.kB, 0.1)
def ani_ase_calculator(ani_model):
"""
Return a calculator from a model.
choices are %s
""" % " ".join(models.keys())
return ANIENS(aniensloader(models[ani_model]))
def opt(self, rdkmol, dhls, logger='optlog.out'):
Na = rdkmol.GetNumAtoms()
X, S = __convert_rdkitmol_to_nparr__(rdkmol)
atm=Atoms(symbols=S, positions=X)
atm.set_calculator(ANIENS(self.ens)) #Set the ANI Ensemble as the calculator
phi_fix = []
for d in dhls:
phi_restraint=atm.get_dihedral(d)
phi_fix.append([phi_restraint, d])
c = FixInternals(dihedrals=phi_fix, epsilon=1.e-9)
atm.set_constraint(c)
dyn = LBFGS(atm, logfile=logger) #Choose optimization algorith
dyn.run(fmax=self.fmax, steps=1000) #optimize molecule to Gaussian's Opt=Tight fmax criteria, input in eV/A (I think)
e=atm.get_potential_energy()*hdt.evtokcal
s=atm.calc.stddev*hdt.evtokcal
phi_value = []
for d in dhls:
phi_value.append(atm.get_dihedral(d)*180./np.pi)
#X = mol.get_positions()
if self.printer:
print('Phi value (degrees), energy (kcal/mol), sigma= ', phi_value, "{0:.2f}".format(e), "{0:.2f}".format(s))
return phi_value, e, s, atm
def run_md(self, f, Tmax, steps, n_steps, nmfile=None, displacement=0, min_steps=0, sig=0.34, t=0.1, nm=0, record=False):
X, S, Na, cm = hdt.readxyz2(f)
if nmfile != None:
mode=self.get_mode(nmfile, Na, mn=nm)
X=X+mode*np.random.uniform(-displacement,displacement)
X=X[0]
mol=Atoms(symbols=S, positions=X)
mol.set_calculator(ANIENS(self.net,sdmx=20000000.0))
f=os.path.basename(f)
T_eff = float(random.randrange(5, Tmax, 1)) # random T (random velocities) from 0K to TK
minstep_eff = float(random.randrange(1, min_steps, 1)) # random T (random velocities) from 0K to TK
dyn = Langevin(mol, t * units.fs, T_eff * units.kB, 0.01)
MaxwellBoltzmannDistribution(mol, T_eff * units.kB)
# steps=10000 #10000=1picosecond #Max number of steps to run
# n_steps = 1 #Number of steps to run for before checking the standard deviation
hsdt_Na=[]
evkcal=hdt.evtokcal
if record==True: #Records the coordinates at every step of the dynamics
fname = f + '_record_' + str(T_eff) + 'K' + '.xyz' #name of file to store coodinated in
def printenergy(name=fname, a=mol):
"""Function to print the potential, kinetic and total energy."""
fil= open(name,'a')
Na=a.get_number_of_atoms()
c = a.get_positions(wrap=True)
fil.write('%s \n comment \n' %Na)
for j, i in zip(a, c):
fil.write(str(j.symbol) + ' ' + str(i[0]) + ' ' + str(i[1]) + ' ' + str(i[2]) + '\n')
fil.close()
dyn.attach(printenergy, interval=1)
e=mol.get_potential_energy() #Calculate the energy of the molecule. Must be done to get the standard deviation
s=mol.calc.stddev
stddev = 0
tot_steps = 0
failed = False
while (tot_steps <= steps):
if stddev > sig and tot_steps > minstep_eff: #Check the standard deviation
self.hstd.append(stddev)
c = mol.get_positions()
s = mol.get_chemical_symbols()
Na=mol.get_number_of_atoms()
self.Na_train.append(Na)
self.coor_train.append(c)
self.S_train.append(s)
failed=True
break
else: #if the standard deviation is low, run dynamics, then check it again
tot_steps = tot_steps + n_steps
dyn.run(n_steps)
stddev = evkcal*mol.calc.stddev
c = mol.get_positions()
s = mol.get_chemical_symbols()
e=mol.get_potential_energy()
#print("{0:.2f}".format(tot_steps*t),':',"{0:.2f}".format(stddev),':',"{0:.2f}".format(evkcal*e))
return c, s, tot_steps*t, stddev, failed, T_eff
def get_modes(self,atm,freqname="vib."):
for f in [f for f in os.listdir(".") if freqname in f and '.pckl' in f]:
os.remove(f)
new_target = open(os.devnull, "w")
old_target, sys.stdout = sys.stdout, new_target
atm.set_calculator(ANIENS(self.ens))
vib = Vibrations(atm, nfree=2, name=freqname)
vib.run()
freq = vib.get_frequencies()
modes = np.stack(vib.get_mode(i) for i in range(freq.size))
vib.clean()
sys.stdout = old_target
return modes
def __run_rand_dyn__(self, mid, T1, T2, dt, Nc, Ns, dS):
# Setup calculator
mol = self.mols[0].copy()
# Setup PBC if active
if self.pbc:
mol.set_cell(([[self.pbl, 0, 0],
[0, self.pbl, 0],
[0, 0, self.pbl]]))
mol.set_pbc((self.pbc, self.pbc, self.pbc))
# Setup calculator
mol.set_calculator(ANIENS(self.aens))
#mol.set_calculator(ANI(False))
#mol.calc.setnc(self.ncl[0])
# Set chemical symbols
spc = mol.get_chemical_symbols()
# Set the velocities corresponding to a boltzmann dist @ T/4.0
MaxwellBoltzmannDistribution(mol, T1 * units.kB)
# Set the thermostat
dyn = Langevin(mol, dt * units.fs, T1 * units.kB, 0.02)
dT = (T2 - T1)/Nc
#print('Running...')
for i in range(Nc):
# Set steps temperature
dyn.set_temperature((T1 + dT*i) * units.kB)
# Do Ns steps of dynamics
dyn.run(Ns)
# Return sigma
sigma = hdt.evtokcal * mol.calc.stddev
ekin = mol.get_kinetic_energy() / len(mol)
# Check for dynamics failure
if sigma > dS:
self.Nbad += 1
self.X.append(mol.get_positions())
#print('Step:', dyn.get_number_of_steps(), 'Sig:', sigma, 'Temp:',
# str(ekin / (1.5 * units.kB)) + '(' + str(T1 + dT * i) + ')')
return True,dyn.get_number_of_steps()
return False,dyn.get_number_of_steps()
def get_energy_force_function(self, molecule):
atoms = Atoms(numbers=molecule.atoms, positions=molecule.coords)
atoms.set_calculator(ANIENS(self.aens))
def get_energy_and_force(xyz_coords, do_force=True):
nonlocal atoms
atoms.set_positions(xyz_coords)
energy = atoms.get_potential_energy() * (eV / Hartree)
if (do_force):
force = atoms.get_forces() * (eV / (kJ / mol) * 1000)
return energy, force
else:
return energy
return get_energy_and_force
def optimize_molecule(self, X, S, fmax=0.1, steps=10000, logger='opt.out'):
mol = Atoms(symbols=S, positions=X)
mol.set_pbc((False, False, False))
mol.set_calculator(ANIENS(self.ens))
dyn = LBFGS(mol,logfile=logger)
#dyn = LBFGS(mol)
#dyn = QuasiNewton(mol,logfile=logger)
dyn.run(fmax=fmax,steps=steps)
stps = dyn.get_number_of_steps()
opt = True
if steps == stps:
opt = False
return np.array(mol.get_positions(),dtype=np.float32), opt
def optimize_rdkit_molecule(self, mrdk, cid, fmax=0.1, steps=10000, logger='opt.out'):
mol = __convert_rdkitmol_to_aseatoms__(mrdk,cid)
mol.set_pbc((False, False, False))
mol.set_calculator(ANIENS(self.ens))
dyn = LBFGS(mol,logfile=logger)
#dyn = LBFGS(mol)
#dyn = QuasiNewton(mol,logfile=logger)
dyn.run(fmax=fmax,steps=steps)
stps = dyn.get_number_of_steps()
opt = True
if steps == stps:
opt = False
xyz = mol.get_positions()
for i,x in enumerate(xyz):
mrdk.GetConformer(cid).SetAtomPosition(i,x)
return opt
from ase_interface import ANIENS
from ase_interface import aniensloader
import ase
import time
from ase import units
from ase.io import read, write
from ase.optimize import BFGS, LBFGS
# Read molecule from xyz
mol = read('data/water.xyz')
# Current ANI model options are:
# '../ani_models/ani-1ccx_8x.info' Coupled cluster transfer learned model
# '../ani_models/ani-1x_8x.info' Full ANI-1x wb97x/6-31g* dataset model
mol.set_calculator(ANIENS(aniensloader('../ani_models/ani-1ccx_8x.info', 0)))
# Calculate energy
ei = mol.get_potential_energy()
print("Initial Energy: ", ei)
# Optimize molecule
print("Optimizing...")
start_time = time.time()
dyn = LBFGS(mol)
dyn.run(fmax=0.001)
print('[ANI Optimization - Total time:', time.time() - start_time, 'seconds]')
# Calculate energy
ef = mol.get_potential_energy()
print("Final Energy: ", ef)
def run_task_ase_one_layer(self, settings, systems, n_sweeps, n_steps_per_sweep=100, verbose_freq=1, temperature_pot_mm=unit.Quantity(300, unit.kelvin),
temperature_kin_mm=unit.Quantity(300, unit.kelvin), label="0", checkpoint_freq=100, restart=False, ):
"""
Method that runs a HMC sampler.
Parameters
----------
settings : dict
Dictionary containing global ParaMol settings.
systems : list of :obj:`ParaMol.System.system.ParaMolSystem`
List containing instances of ParaMol systems.
n_sweeps : int
Number of MC sweeps to perform.
n_steps_per_sweep : int
Number of MD steps per MC sweep.
verbose_freq : int
Verbose frequency.
temperature_pot_mm : unit.Quantity
Temperature used for the MM potential part.
temperature_kin_mm : unit.Quantity
Temperature used for the MM kinetic part.
label : int
HMC sampler label. It has to be an integer number.
checkpoint_freq : int
Frequency at which checkpoint restart files are written.
restart : bool
Flag that controls whether or not to perform a restart.
Returns
-------
systems : list
List with the updated instances of ParaMol System.
"""
from ase_interface import ANIENS
from ase_interface import aniensloader
from ase import units as ase_unit
assert len(systems) == 1, "HMC task currently only supports one system at once."
# Create QM Engines and initiate OpenMM
for system in systems:
system.convert_system_ref_arrays_to_list()
# Create OpenMM system
system.engine.init_openmm(create_system_params=system.engine._create_system_params)
system.engine.get_masses()
# Create QM Engine
if system.interface is None:
system.interface = ParaMolInterface()
system.create_qm_engines(settings.qm_engine["qm_engine"], settings.qm_engine[settings.qm_engine["qm_engine"].lower()])
# Create ASE NN calculator
# Get atom list and atomic numbers list
system.engine.get_atom_list()
"""
mm_ase_engine = ASEWrapper(system_name=system.name,
interface=system.interface,
calculator=ANIENS(aniensloader('../ani_models/ani-1ccx_8x.info', 0)),
n_atoms=system.n_atoms,
atom_list=system.engine.atom_list,
n_calculations=1,
cell=None,
work_dir_prefix="NN_ASEWorkDir_")
"""
calc = ANIENS(aniensloader('/home/joao/programs/ASE_ANI/ani_models/ani-2x_8x.info',0))
#calc = DFTD3(dft=calc, cutoff=np.sqrt(9000) * ase_units.Bohr, damping="bj", a1=0.5719, a2=3.6017, s8=0.5883, s6=1.000, alpha6=1.0)
mm_ase_engine = ASEWrapper(system_name=system.name,
interface=system.interface,
calculator=calc,
n_atoms=system.n_atoms,
atom_list=system.engine.atom_list,
n_calculations=1,
cell=None,
work_dir_prefix="NN_ASEWorkDir_")
system = systems[0]
self._label = label
parameter_space, objective_function, optimizer = (None, None, None)
# TODO: Once this is included in the main ParaMol version, add this line to the default dictionary
settings.restart["restart_hmc_file_{}".format(self._label)] = "restart_hmc_{}.pickle".format(self._label)
if restart:
logging.info("Starting HMC sampler parametrization from a previous restart.")
# Read HMCSampler pickle
self.__dict__ = self.read_restart_pickle(settings.restart, system.interface, "restart_hmc_file_{}".format(self._label))
# Read data into system
system.read_data(os.path.join(settings.restart["restart_dir"], "{}_hmc_{}.nc".format(system.name, self._label)))
else:
self._n = 1
# MM chain
self._n_total_mm = 0
self._n_accepted_mm = 0
while self._n <= n_sweeps:
if self._n % verbose_freq == 0:
print("HMC sampler of system {} # Sweep number {}.".format(system.name, self._n))
print("HMC sampler of system {} # Acceptance rate of MM chain {:.4f}".format(system.name, self._acceptance_rate_mm()))
if len(system.ref_coordinates) > 0 and self._n != 1:
# Do not need to compute the QM energy if there are structures in the top ensemble or if we are not in the first ever iteration.
system.engine.set_positions(system.ref_coordinates[-1])
potential_initial_mm = mm_ase_engine.run_calculation(coords=system.ref_coordinates[-1] * 10, label=int(self._label))
coord_to_run = system.ref_coordinates[-1] * 10
else:
# Compute MM initial kinetic and potential energy
potential_initial_mm = mm_ase_engine.run_calculation(coords=system.engine.get_positions().in_units_of(unit.angstrom)._value, label=int(self._label))
coord_to_run = system.engine.get_positions().in_units_of(unit.angstrom)._value
# Run short MD using ASE
coords, potential_initial_mm, kinetic_initial, forces_initial, potential_final_mm, kinetic_final, forces_final = mm_ase_engine.run_md(coords=coord_to_run,
label=int(self._label),
steps=n_steps_per_sweep,
dt=0.5*ase_unit.fs,
initial_temperature=300.0*ase_unit.kB,)
# Compute MM final kinetic and potential energy
kinetic_initial = unit.Quantity(kinetic_initial, unit.kilojoules_per_mole)
potential_initial_mm = unit.Quantity(potential_initial_mm, unit.kilojoules_per_mole)
kinetic_final = unit.Quantity(kinetic_final, unit.kilojoules_per_mole)
potential_final_mm = unit.Quantity(potential_final_mm, unit.kilojoules_per_mole)
coords = unit.Quantity(coords, unit.nanometers)
if self._hmc_acceptance_criterion_mm(potential_final_mm, potential_initial_mm, kinetic_final, kinetic_initial, temperature_pot_mm, temperature_kin_mm):
# Append energies, forces and conformations
system.ref_energies.append(potential_final_mm._value)
system.ref_coordinates.append(coords._value)
system.n_structures += 1
# TODO: include code related to partial momentum refreshment
elif len(system.ref_coordinates) > 0:
# Append last accepted structure
system.ref_energies.append(system.ref_energies[-1])
system.ref_coordinates.append(system.ref_coordinates[-1])
system.n_structures += 1
else:
# No structures have been accepted yet.
pass
# Write restart files
if self._n % checkpoint_freq == 0:
self.write_restart_pickle(settings.restart, system.interface, "restart_hmc_file_{}".format(self._label), self.__dict__)
system.write_data(os.path.join(settings.restart["restart_dir"], "{}_hmc_{}.nc".format(system.name, self._label)))
system.write_coordinates_xyz("{}_hmc_{}.xyz".format(system.name, self._label))
self._n += 1
return systems
# Load molecule
mol = read(molfile)
#print('test')
L = 70.0
mol.set_cell(([[L, 0, 0], [0, L, 0], [0, 0, L]]))
mol.set_pbc((True, True, True))
#print(mol.get_chemical_symbols())
# Set NC
aens = ensemblemolecule(cnstfile, saefile, nnfdir, Nn, 5)
# Set ANI calculator
mol.set_calculator(ANIENS(aens, sdmx=20000000.0))
print(mol.get_potential_energy())
print(np.where(mol.get_forces() > 200.0))
print("size: ", len(mol.get_chemical_symbols()))
# Optimize molecule
start_time = time.time()
dyn = QuasiNewton(mol)
dyn.run(fmax=C)
print('[ANI Total time:', time.time() - start_time, 'seconds]')
#print(hdt.evtokcal*mol.get_potential_energy())
#print(hdt.evtokcal*mol.get_forces())
