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import os
import random
import matplotlib.pyplot as plt
import numpy as np
import torch
from ase import units
from ase.md import MDLogger
from ase.md.nptberendsen import NPTBerendsen
from ase.md.velocitydistribution import MaxwellBoltzmannDistribution
from ase.neighborlist import neighbor_list
from checkpoint import multitask_from_checkpoint
from loguru import logger
from matsciml.datasets.transforms import (
FrameAveraging,
PeriodicPropertiesTransform,
PointCloudToGraphTransform,
)
from matsciml.lightning import MatSciMLDataModule
from tqdm import tqdm
from Utils import (
ASEcalculator,
get_initial_rdf,
get_bond_lengths_noise,
symmetricize_replicate,
replicate_system,
get_bond_lengths_TrajAvg,
convBatchtoAtoms,
minimize_structure,
get_rdf,
)
class StabilityException(Exception):
pass
def run_simulation(atoms, runsteps=1000, SimDir="./"):
traj = []
logger.info("Calculating initial RDFs ... ")
_, initial_rdf = get_initial_rdf(
atoms, perturb=20, noise_std=0.05, max_atoms=config.max_atoms, replicate=True
)
initial_bond_lengths, Initial_Pair_rdfs = get_bond_lengths_noise(
atoms,
perturb=20,
noise_std=0.05,
max_atoms=config.max_atoms,
r_max=config.rdf_r_max,
)
initial_temperature = config.temp
# Replicate_system
replication_factors, size = symmetricize_replicate(
len(atoms),
max_atoms=config.max_atoms,
box_lengths=atoms.get_cell_lengths_and_angles()[:3],
)
atoms = replicate_system(atoms, replication_factors)
# Set_calculator
Loaded_model = multitask_from_checkpoint(config.model_path)
calculator = ASEcalculator(Loaded_model, config.model_name)
# calculator = MACECalculator(model_path=config.model_path, device=config.device, default_dtype='float64')
atoms.set_calculator(calculator)
atoms = minimize_structure(atoms, steps=config.minimize_steps)
# Set_simulation
# NVE
# MaxwellBoltzmannDistribution(atoms, temperature_K=config.temperature)
# initial_energy = atoms.get_total_energy()
# dyn = VelocityVerlet(atoms, dt=timestep * units.fs)
# NPT
MaxwellBoltzmannDistribution(atoms, temperature_K=config.temperature)
dyn = NPTBerendsen(
atoms,
timestep=config.timestep * units.fs,
temperature_K=config.temperature,
pressure_au=config.pressure * units.bar,
compressibility_au=4.57e-5 / units.bar,
)
dyn.attach(
MDLogger(
dyn,
atoms,
os.path.join(SimDir, "Simulation_thermo.log"),
header=True,
stress=True,
peratom=False,
mode="w",
),
interval=config.thermo_interval,
)
def write_frame(a=atoms):
if SimDir is not None:
a.write(
os.path.join(SimDir, f"MD_{atoms.get_chemical_formula()}_NPT.xyz"),
append=True,
)
dyn.attach(write_frame, interval=config.trajdump_interval)
def append_traj(a=atoms):
traj.append(a.copy())
dyn.attach(append_traj, interval=1)
# def energy_stability(a=atoms):
# logger.info("Checking energy stability...", end='\t')
# current_energy = atoms.get_total_energy()
# energy_error = abs((current_energy - initial_energy) / initial_energy)
# if energy_error > config.energy_tolerence:
# logger.error(f"Unstable : Energy_error={energy_error:.6g} (> {config.energy_tolerence:.6g})")
# raise StabilityException("Energy_criterion violated. Stopping the simulation.")
# else:
# logger.info(f"Stable : Energy_error={energy_error:.6g} (< {config.energy_tolerence:.6g})")
# dyn.attach(energy_stability, interval=config.energy_criteria_interval)
def temperature_stability(atoms, initial_temperature, temperature_tolerance):
if len(traj) >= config.initial_equilibration_period:
logger.info("Checking temperature stability...", end="\t")
current_temperature = atoms.get_temperature()
temperature_error = abs(
(current_temperature - initial_temperature) / initial_temperature
)
if temperature_error > temperature_tolerance:
logger.error(
f"Unstable : Temperature_error={temperature_error:.6g} (> {temperature_tolerance:.6g})"
)
raise StabilityException(
"Temperature criterion violated. Stopping the simulation."
)
else:
logger.info(
f"Stable : Temperature_error={temperature_error:.6g} (< {temperature_tolerance:.6g})"
)
# Attach the temperature stability check to the dynamics object
dyn.attach(
temperature_stability,
interval=config.temperature_criteria_interval,
atoms=atoms,
initial_temperature=initial_temperature,
temperature_tolerance=config.temperature_tolerance,
)
def calculate_rmsd(traj):
initial_positions = traj[0].get_positions()
N = len(traj[0])
T = len(traj)
displacements = np.zeros((N, T, 3))
for t in range(T):
current_positions = traj[t].get_positions()
displacements[:, t, :] = current_positions - initial_positions
msd = np.mean(np.sum(displacements**2, axis=2), axis=1)
rmsd = np.sqrt(msd)
return rmsd
def calculate_average_nn_distance(atoms):
i, j, _ = neighbor_list("ijd", atoms, cutoff=5.0)
distances = atoms.get_distances(i, j, mic=True)
return np.mean(distances)
def lindemann_stability(a=atoms):
if len(traj) >= config.lindemann_traj_length:
logger.info("Checking lindemann stability...", end="\t")
rmsd = calculate_rmsd(traj[-config.lindemann_traj_length :])
avg_nn_distance = calculate_average_nn_distance(traj[0])
lindemann_coefficient = np.mean(rmsd) / avg_nn_distance
if lindemann_coefficient > config.max_linedmann_coefficient:
logger.error(
f"Unstable : Lindemann_coefficient={lindemann_coefficient:.6g} (> {config.max_linedmann_coefficient:.6g})"
)
logger.error(
f"Lindemann_stability criterion violated {lindemann_coefficient:.6g} > {config.max_linedmann_coefficient:.6g}, Stopping the simulation."
)
raise StabilityException()
else:
logger.info(
f"Stable : Lindemann_coefficient={lindemann_coefficient:.6g} (< {config.max_linedmann_coefficient:.6g})"
)
dyn.attach(lindemann_stability, interval=config.lindemann_criteria_interval)
def rdf_stability(a=atoms):
if len(traj) >= config.rdf_traj_length:
logger.info("Checking RDF stability...", end="\t")
r, rdf = get_rdf(traj[-config.rdf_traj_length :], r_max=config.rdf_r_max)
RDF_len = min(len(rdf), len(initial_rdf))
r = r[:RDF_len]
rdf = rdf[:RDF_len]
initial_rdf_ = initial_rdf[:RDF_len]
error_rdf = (
100
* (((rdf - initial_rdf_) ** 2).sum())
/ (((initial_rdf_) ** 2).sum())
)
# Plotting the RDF
plt.figure()
plt.plot(r, initial_rdf_, label="Initial RDF")
plt.plot(r, rdf, label="Simulated RDF")
plt.xlabel("Distance (r)")
plt.ylabel("RDF")
plt.legend()
plt.title(f"RDF Comparison\nInitial vs Simulated\nError={error_rdf:.6g}")
plot_path = os.path.join(
SimDir, f"RDF_{atoms.get_chemical_formula()}_{len(traj)}.png"
)
plt.savefig(plot_path)
logger.info("Saved figure at {}", plot_path)
plt.close()
if error_rdf > config.max_rdf_error_percent:
logger.error(
f"Unstable : RDF Error={error_rdf:.6g} (> {config.max_rdf_error_percent:.6g})"
)
logger.error(
f"RDF criterion violated. Stopping the simulation. WF={error_rdf:.6g}"
)
raise StabilityException()
else:
logger.info(
f"Stable : RDF Error={error_rdf:.6g} (< {config.max_rdf_error_percent:.6g})"
)
dyn.attach(rdf_stability, interval=config.rdf_criteria_interval)
def bond_lengths_stability(a=atoms):
if len(traj) >= config.lindemann_traj_length:
logger.info("Checking Bonds stability...", end="\t")
curr_bond_lengths, Pair_rdfs = get_bond_lengths_TrajAvg(
traj[-config.rdf_traj_length :], r_max=config.rdf_r_max
)
for key in curr_bond_lengths.keys():
r, initial_rdf = Initial_Pair_rdfs[key]
r, rdf = Pair_rdfs[key]
RDF_len = min(len(rdf), len(initial_rdf))
r = r[:RDF_len]
rdf = rdf[:RDF_len]
initial_rdf_ = initial_rdf[:RDF_len]
error_percent = (
100
* (((rdf - initial_rdf_) ** 2).sum())
/ (((initial_rdf_) ** 2).sum())
)
plt.figure()
plt.plot(r, initial_rdf_, label="Initial RDF")
plt.plot(r, rdf, label="Simulated RDF")
plt.xlabel("Distance (r)")
plt.ylabel("RDF")
plt.legend()
plt.title(
f"RDF Comparison: Bond {key}={curr_bond_lengths[key]:.6g}, Initial={initial_bond_lengths[key]:.6g}, Error={error_percent:.6g}"
)
plot_path = os.path.join(
SimDir,
f"PartialRDF_{atoms.get_chemical_formula()}_{key}_{len(traj)}.png",
)
plt.savefig(plot_path)
logger.info("Saved figure at {}", plot_path)
if False: # error_percent > config.max_bond_error_percent:
logger.error(
f"Unstable : Bond {key}={curr_bond_lengths[key]:.6g}, Initial={initial_bond_lengths[key]:.6g}, Error={error_percent:.6g} (> {config.max_bond_error_percent:.6g})"
)
logger.error(
f"Bond length stability violated. Stopping the simulation. Bond {key}={curr_bond_lengths[key]:.6g}, Initial={initial_bond_lengths[key]:.6g}"
)
raise StabilityException()
else:
logger.info(
f"Stable : Bond {key}: {error_percent: .6g} < {config.max_bond_error_percent:.6g} % Error"
)
dyn.attach(bond_lengths_stability, interval=config.rdf_criteria_interval)
try:
logger.info(
f"Simulating {atoms.get_chemical_formula()} {len(atoms)} atoms system ...."
)
counter = 0
for k in tqdm(range(runsteps)):
dyn.run(1)
counter += 1
return runsteps # Simulation completed successfully
except StabilityException:
logger.error(
f"Simulation of {atoms.get_chemical_formula()} {len(atoms)} atoms system failed after {counter} steps"
)
return len(traj) # Return the number of steps completed before failure
class TestArgs:
runsteps = 50000
model_path = "/home/m3rg2000/Simulation/checkpoints-2024/FAENet_250k.ckpt"
model_name = "faenet" ##[tensornet, faenet, mace]
data_path = "/home/m3rg2000/Universal_matscimal/Data/stability_new"
timestep = 1.0
temp = 298
out_dir = "/home/m3rg2000/Universal_matscimal/Sim_output/"
device = "cuda"
replicate = True
max_atoms = 200 # Replicate upto max_atoms (Min. will be max_atoms/2) (#Won't reduce if more than max_atoms)
# energy_tolerence=0.1
# energy_criteria_interval=100
max_linedmann_coefficient = 0.3
lindemann_criteria_interval = 1000
lindemann_traj_length = 1000
max_rdf_error_percent = 80
max_bond_error_percent = 80
bond_criteria_interval = 1000
rdf_dr = 0.02
rdf_r_max = 6.0
rdf_traj_length = 1000
rdf_criteria_interval = 1000
trajdump_interval = 10
minimize_steps = 200
temperature = 300
temperature_tolerance = 0.8
thermo_interval = 10
pressure = 1.01325
temperature_criteria_interval = 1000
initial_equilibration_period = 3000
# config=TestArgs()
def main(args, config):
transforms = []
if config.model_name == "faenet":
transforms += [FrameAveraging(frame_averaging="3D", fa_method="stochastic")]
# Load Data
if config.model_name == "tensornet":
graph_type = "dgl"
else:
graph_type = "pyg"
dm = MatSciMLDataModule(
"MaterialsProjectDataset",
train_path=config.data_path,
dset_kwargs={
"transforms": [
PeriodicPropertiesTransform(cutoff_radius=6.0, adaptive_cutoff=True),
PointCloudToGraphTransform(
graph_type,
node_keys=["pos", "atomic_numbers"],
),
]
+ transforms,
},
batch_size=1,
)
dm.setup()
train_loader = dm.train_dataloader()
# dataset_iter = iter(train_loader)
time_steps = []
# unreadable_files = []
# Range = [0, 120]
index = int(args.index)
print("Index:", index)
counter_batch = 0
for batch in train_loader:
if counter_batch == index:
atoms = convBatchtoAtoms(batch)
SimDir = os.path.join(
config.out_dir, f"Simulation_{index}_{atoms.get_chemical_formula()}"
)
os.makedirs(SimDir, exist_ok=True)
# Initialize logger
logger.add(os.path.join(SimDir, "simulation.log"), rotation="500 MB")
logger.info("All seeds set!")
steps_completed = run_simulation(atoms, config.runsteps, SimDir)
time_steps.append(steps_completed)
logger.info(
"System: {} : {} with originally {} atoms stopped at {} steps",
counter_batch,
atoms.get_chemical_formula(),
len(atoms),
steps_completed,
)
counter_batch += 1
else:
counter_batch += 1
continue
logger.info("Completed...")
logger.info("Time Steps: {}", time_steps)
if __name__ == "__main__":
config = TestArgs()
# Seed for the Python random module
random.seed(123)
np.random.seed(123)
torch.manual_seed(123)
if torch.cuda.is_available():
torch.cuda.manual_seed(123)
torch.cuda.manual_seed_all(123) # if you are using multi-GPU.
parser = argparse.ArgumentParser(description="Run MD simulation with MACE model")
parser.add_argument("--index", type=int, default=0, help="index of folder")
# parser.add_argument("--init_conf_path", type=str, default="example/lips20/data/test/botnet.xyz", help="Path to the initial configuration")
# parser.add_argument("--device", type=str, default="cuda", help="Device: ['cpu', 'cuda']")
# parser.add_argument("--input_dir", type=str, default="./", help="folder path")
# parser.add_argument("--out_dir", type=str, default="out_dir_sl/neqip/lips20/exp.csv", help="Output path")
# parser.add_argument("--results_dir", type=str, default="out_dir_sl/neqip/lips20/", help="Output directory path")
# parser.add_argument("--temp", type=float, default=300, help="Temperature in Kelvin")
# parser.add_argument("--pressure", type=float, default=1, help="pressure in atm")
# parser.add_argument("--timestep", type=float, default=1.0, help="Timestep in fs units")
# parser.add_argument("--runsteps", type=int, default=1000, help="No. of steps to run")
# parser.add_argument("--sys_name", type=str, default='System', help="System name")
# parser.add_argument("--traj_folder", type=str, default="/home/civil/phd/cez218288/Benchmarking/MDBENCHGNN/mace_universal_2.0/EXP/Quartz/a.xyz")
args = parser.parse_args()
main(args, config)
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