def test_evolve(mol_num, j_constant_value, elocalex_value, ph_info,
ph_phys_dim, evolve_dt, nsteps):
ph_list = [
Phonon.simple_phonon(Quantity(omega, "cm^{-1}"),
Quantity(displacement, "a.u."), ph_phys_dim)
for omega, displacement in ph_info
]
mol_list = MolList(
[Mol(Quantity(elocalex_value, "a.u."), ph_list)] * mol_num,
Quantity(j_constant_value, "eV"),
scheme=3,
)
ct1 = ChargeTransport(mol_list, stop_at_edge=False)
half_nsteps = nsteps // 2
ct1.evolve(evolve_dt, half_nsteps)
ct1.evolve(evolve_dt, nsteps - half_nsteps)
ct2 = ChargeTransport(mol_list, stop_at_edge=False)
ct2.evolve(evolve_dt, nsteps)
assert ct1.is_similar(ct2)
assert_iterable_equal(ct1.get_dump_dict(), ct2.get_dump_dict())
# test dump
ct2.dump_dir = "."
ct2.job_name = "test"
ct2.dump_dict()
os.remove("test.npz")
lams = hr_factors * omegas_au
phonons = [
Phonon.simplest_phonon(Quantity(o), Quantity(l), lam=True)
for o, l in zip(omegas_au, lams)
]
j_matrix_au = j_matrix_cm * cm2au
mlist = []
for j in np.diag(j_matrix_au):
m = Mol(Quantity(j), phonons)
mlist.append(m)
# starts from 1
mol_arangement = np.array([7, 5, 3, 1, 2, 4, 6]) - 1
mol_list = MolList(list(np.array(mlist)[mol_arangement]),
j_matrix_au[mol_arangement][:, mol_arangement])
evolve_dt = 40
evolve_config = EvolveConfig(evolve_dt=evolve_dt)
compress_config = CompressConfig(CompressCriteria.fixed, max_bonddim=16)
ct = ChargeTransport(mol_list,
evolve_config=evolve_config,
compress_config=compress_config)
ct.dump_dir = "./fmo"
ct.job_name = 'hybrid'
ct.stop_at_edge = False
ct.evolve(evolve_dt=evolve_dt, nsteps=10)
new_evolve_config = EvolveConfig(EvolveMethod.tdvp_mctdh_new)
ct.latest_mps.evolve_config = ct.evolve_config = new_evolve_config
ct.evolve(evolve_dt=evolve_dt, nsteps=100000)
if __name__ == "__main__":
if len(sys.argv) != 2:
print("No or more than one parameter file are provided, abort")
exit(1)
parameter_path = sys.argv[1]
with open(parameter_path) as fin:
param = yaml.safe_load(fin)
log.register_file_output(
os.path.join(param["output dir"], param["fname"] + ".log"), "w")
mol_list, temperature = load_from_dict(param, 3, False)
compress_config = CompressConfig(threshold=1e-4)
evolve_config = EvolveConfig(adaptive=True, evolve_dt=2)
ct = ChargeTransport(
mol_list,
temperature=temperature,
compress_config=compress_config,
evolve_config=evolve_config,
rdm=False,
)
# ct.stop_at_edge = True
# ct.memory_limit = 2 ** 30 # 1 GB
# ct.memory_limit /= 10 # 100 MB
ct.dump_dir = param["output dir"]
ct.job_name = param["fname"]
ct.custom_dump_info["comment"] = param["comment"]
# ct.latest_mps.compress_add = True
logger.debug(f"ground energy of the Hamiltonian: {ct.mpo_e_lbound:g}")
ct.evolve(param.get("evolve dt"), param.get("nsteps"),
param.get("evolve time"))
# ct.evolve(evolve_dt, 100, param.get("evolve time"))
hr_factors *= TOTAL_HR / hr_factors.sum()
lams = hr_factors * omegas_au
phonons = [
Phonon.simplest_phonon(Quantity(o), Quantity(l), lam=True)
for o, l in zip(omegas_au, lams)
]
j_matrix_au = j_matrix_cm * cm2au
mlist = []
for j in np.diag(j_matrix_au):
m = Mol(Quantity(j), phonons)
mlist.append(m)
# starts from 1
mol_arangement = np.array([7, 5, 3, 1, 2, 4, 6]) - 1
mol_list = MolList(list(np.array(mlist)[mol_arangement]),
j_matrix_au[mol_arangement][:, mol_arangement])
evolve_dt = 160
evolve_config = EvolveConfig(EvolveMethod.tdvp_ps, guess_dt=evolve_dt)
compress_config = CompressConfig(CompressCriteria.fixed, max_bonddim=32)
ct = ChargeTransport(mol_list,
evolve_config=evolve_config,
compress_config=compress_config,
init_electron=InitElectron.fc)
ct.dump_dir = "./"
ct.job_name = 'fmo'
ct.stop_at_edge = False
ct.evolve(evolve_dt=evolve_dt, evolve_time=40000)
