ensembles

Note

Modified ase.md ensembles to deploy the AGAT model.

Examples of using ensembles:

###############################################################################
# Detect GPU card
###############################################################################
import torch
if torch.cuda.is_available():
    device='cuda'
    print("CUDA is available.")
    print(f"Number of GPUs: {torch.cuda.device_count()}")
    print(f"GPU Name: {torch.cuda.get_device_name(0)}")
else:
    device='cpu'
    print("CUDA is NOT available.")

###############################################################################
# Modified ASE ensembles for AGAT
###############################################################################
import dgl
u, v = torch.tensor([0, 0, 0, 1], device=device), torch.tensor([1, 2, 3, 3],
                                                               device=device)
g = dgl.graph((u, v), device=device)
print(f'DGL graph device: {g.device}')

import os
from ase.io import read
from ase import units
from ase.md.npt import NPT
from ase.md import MDLogger
from agat.app.ensembles import ModifiedNPT
from agat.app.calculators import AgatEnsembleCalculator
model_ensemble_dir = os.path.join('potential_models')
graph_build_scheme_dir = os.path.join('potential_models')
atoms = read(os.path.join('potential_models', 'POSCAR'))
calculator=AgatEnsembleCalculator(model_ensemble_dir, graph_build_scheme_dir,
                                  device=device)
atoms.set_calculator(calculator)

dyn = ModifiedNPT(atoms,
          timestep=1.0 * units.fs,
          temperature_K=300,
          ttime = 25 * units.fs,
          pfactor = 75 * units.fs,
          externalstress = [0.0] * 6,
          mask=[[1,0,0],
                [0,1,0],
                [0,0,1]],
          trajectory=os.path.join('md_NPT.traj'))

dyn.attach(MDLogger(dyn, atoms, os.path.join('md_NPT.log'),
                    header=True,
                    stress=True,
                    peratom=False,
                    mode="a"),
           interval=1)

dyn.run(200)

class ModifiedNPT(NPT)

Modified ase.md.npt.NPT ensemble, which is used for the on-the-fly training of a AGAT PotentialModel.

Note

Go to https://ase-lib.org/ase/md.html for more information.

classname

'ModifiedNPT'

__init__(self, atoms, timestep, temperature, externalstress, ttime, pfactor, *arg, temperature_K, mask, trajectory, logfile, loginterval, append_trajectory, max_collected_snapshot_num=500)

Most arguments can be found at https://ase-lib.org/ase/md.html#constant-npt-simulations-the-isothermal-isobaric-ensemble

: param max_collected_snapshot_num: The maximum number of collected snashots in a on-the-fly training. Defaults to 500. : type max_collected_snapshot_num: int

run(self, steps)

Run NPT simulation.

Parameters:

steps (int) – Steps for the MD simulation.