d4s.py

# SPDX-Identifier: CC0-1.0
import tad_mctc as mctc
import torch

import tad_dftd4 as d4

numbers = mctc.convert.symbol_to_number(
    symbols="C C C C N C S H H H H H".split()
)

# coordinates in Bohr
positions = torch.tensor(
    [
        [-2.56745685564671, -0.02509985979910, 0.00000000000000],
        [-1.39177582455797, +2.27696188880014, 0.00000000000000],
        [+1.27784995624894, +2.45107479759386, 0.00000000000000],
        [+2.62801937615793, +0.25927727028120, 0.00000000000000],
        [+1.41097033661123, -1.99890996077412, 0.00000000000000],
        [-1.17186102298849, -2.34220576284180, 0.00000000000000],
        [-2.39505990368378, -5.22635838332362, 0.00000000000000],
        [+2.41961980455457, -3.62158019253045, 0.00000000000000],
        [-2.51744374846065, +3.98181713686746, 0.00000000000000],
        [+2.24269048384775, +4.24389473203647, 0.00000000000000],
        [+4.66488984573956, +0.17907568006409, 0.00000000000000],
        [-4.60044244782237, -0.17794734637413, 0.00000000000000],
    ]
)

# total charge of the system
charge = torch.tensor(0.0)

# Create the D4S model
model = d4.model.D4SModel(numbers)

param = d4.get_params(method="d4", functional="tpssh")
energy = d4.dftd4(numbers, positions, charge, param, model=model)
torch.set_printoptions(precision=10)
print(energy)
# tensor([-0.0020843975, -0.0019013016, -0.0018165035, -0.0018363572,
#         -0.0021877293, -0.0019495023, -0.0022923108, -0.0004326892,
#         -0.0004439871, -0.0004362087, -0.0004454589, -0.0005344027])