def test_gfn2xtb_solvation():
"""Use GFN2-xTB/GBSA for a mindless molecule"""
thr = 1.0e-7
numbers = np.array([
1, 9, 15, 13, 1, 1, 13, 5, 3, 15, 8, 1, 1, 5, 16, 1,
])
positions = np.array([
[-2.14132037405479, -1.34402701877044, -2.32492500904728],
[ 4.46671289205392, -2.04800110524830, 0.44422406067087],
[-4.92212517643478, -1.73734240529793, 0.96890323821450],
[-1.30966093045696, -0.52977363497805, 3.44453452239668],
[-4.34208759006189, -4.30470270977329, 0.39887431726215],
[ 0.61788392767516, 2.62484136683297, -3.28228926932647],
[ 4.23562873444840, -1.68839322682951, -3.53824299552792],
[ 2.23130060612446, 1.93579813100155, -1.80384647554323],
[-2.32285463652832, 2.90603947535842, -1.39684847191937],
[ 2.34557941578250, 2.86074312333371, 1.82827238641666],
[-3.66431367659153, -0.42910188232667, -1.81957402856634],
[-0.34927881505446, -1.75988134003940, 5.98017466326572],
[ 0.29500802281217, -2.00226104143537, 0.53023447931897],
[ 2.10449364205058, -0.56741404446633, 0.30975625014335],
[-1.59355304432499, 3.69176153150419, 2.87878226787916],
[ 4.34858700256050, 2.39171478113440, -2.61802993563738],
])
dipole = np.array(
[ 0.24089806056398366, -0.8387798297446885, -2.490982140104827]
)
gradient = np.array([
[ 0.00665983765172852, -0.000306100468371254, 0.002975729588167250],
[-0.00075554832215171, 0.001103331394141163, 0.002917549694785815],
[ 0.00103709572973848, -0.000861474437293449, 0.005249091862608099],
[ 0.00345933752444154, -0.004301298519638866, -0.003786850195834586],
[-0.00078541037746589, -0.004659889270757375, 0.000757596433662243],
[ 0.00322292779086688, -0.003572675716601181, -0.004746876147864423],
[-0.00513395549346115, 0.011449011590338731, 0.002505538991042167],
[-0.00574879905769782, 0.004579255119010918, -0.002779923711244377],
[ 0.00241040419407409, 0.003121180180444150, 0.003515870816111050],
[-0.00021150434069988, -0.002620960429434571, -0.008691267383737740],
[-0.00323129790918273, 0.005268717780263234, -0.010531374769279896],
[ 0.00203571944238303, -0.004757311655869700, 0.005097227197421218],
[-0.00606663933320002, 0.003597297542372022, -0.002467813364587243],
[ 0.00024286212984382, -0.009680057140546466, 0.014999309475018330],
[-0.00090824770994144, 0.004745736486598619, -0.001923154458354601],
[ 0.00377321808072424, -0.003104762454655897, -0.003090654027913303],
])
calc = Calculator(Param.GFN2xTB, numbers, positions)
res = calc.singlepoint()
assert approx(res.get_energy(), abs=thr) == -25.0841508410945
calc.set_solvent(Solvent.ch2cl2)
res = calc.singlepoint(res)
assert approx(res.get_energy(), abs=thr) == -25.11573992702904
assert approx(res.get_dipole(), abs=thr) == dipole
assert approx(res.get_gradient(), abs=thr) == gradient
def _evaluate_single(
self,
positions: torch.Tensor,
evaluate_force=True,
evaluate_energy=True,
):
from xtb.interface import Calculator, XTBException
from xtb.utils import get_method, get_solvent
positions = _nm2bohr(positions)
energy, force = None, None
try:
calc = Calculator(get_method(self.method), self.numbers, positions)
calc.set_solvent(get_solvent(self.solvent))
calc.set_verbosity(self.verbosity)
calc.set_electronic_temperature(self.temperature)
try:
res = calc.singlepoint()
except XTBException:
# Try with higher temperature
calc.set_electronic_temperature(10 * self.temperature)
res = calc.singlepoint()
calc.set_electronic_temperature(self.temperature)
res = calc.singlepoint(res)
if evaluate_energy:
energy = _hartree2kbt(res.get_energy(), self.temperature)
if evaluate_force:
force = _hartree_per_bohr2kbt_per_nm(-res.get_gradient(),
self.temperature)
assert not np.isnan(energy)
assert not np.isnan(force).any()
except XTBException as e:
if self.err_handling == "error":
raise e
elif self.err_handling == "warning":
warnings.warn(f"Caught exception in xtb. "
f"Returning infinite energy and zero force. "
f"Original exception: {e}")
force = np.zeros_like(positions)
energy = np.infty
elif self.err_handling == "ignore":
force = np.zeros_like(positions)
energy = np.infty
except AssertionError:
force[np.isnan(force)] = 0.
energy = np.infty
if self.err_handling in ["error", "warning"]:
warnings.warn(
"Found nan in xtb force or energy. Returning infinite energy and zero force."
)
return energy, force
def test_gfn1xtb_solvation():
"""Use GFN1-xTB/GBSA for a mindless molecule"""
thr = 1.0e-7
numbers = np.array([
1, 1, 6, 5, 1, 15, 8, 17, 13, 15, 5, 1, 9, 15, 1, 15,
])
positions = np.array([
[ 2.79274810283778, 3.82998228828316, -2.79287054959216],
[-1.43447454186833, 0.43418729987882, 5.53854345129809],
[-3.26268343665218, -2.50644032426151, -1.56631149351046],
[ 2.14548759959147, -0.88798018953965, -2.24592534506187],
[-4.30233097423181, -3.93631518670031, -0.48930754109119],
[ 0.06107643564880, -3.82467931731366, -2.22333344469482],
[ 0.41168550401858, 0.58105573172764, 5.56854609916143],
[ 4.41363836635653, 3.92515871809283, 2.57961724984000],
[ 1.33707758998700, 1.40194471661647, 1.97530004949523],
[ 3.08342709834868, 1.72520024666801, -4.42666116106828],
[-3.02346932078505, 0.04438199934191, -0.27636197425010],
[ 1.11508390868455, -0.97617412809198, 6.25462847718180],
[ 0.61938955433011, 2.17903547389232, -6.21279842416963],
[-2.67491681346835, 3.00175899761859, 1.05038813614845],
[-4.13181080289514, -2.34226739863660, -3.44356159392859],
[ 2.85007173009739, -2.64884892757600, 0.71010806424206],
])
dipole = np.array(
[-1.7019679049596192, -2.3705248395254794, 2.3242138027827446]
)
gradient = np.array([
[ 0.009559998512721449, 0.003160492649991202, 0.002493263404035152],
[-0.014057002659599450, 0.001307143355963449, -0.006896995523674975],
[ 0.003153682694711128, 0.000577646576754350, 0.003242310422859749],
[ 0.003450958779103499, -0.003371154526376105, 0.006833209066374420],
[-0.001015432627909870, -0.003296949677104424, 0.001316980539002961],
[-0.006952278070976579, 0.004741461728853791, -0.010835641525482725],
[ 0.004676820346825542, 0.013884337727247118, -0.001369508087834928],
[-0.008836453325485083, -0.008509582724068617, -0.004439799174447864],
[ 0.014459308335089790, 0.005276511880967742, 0.004903442725946663],
[-0.036094040309768836, -0.003785312815195147, 0.006658677483987865],
[ 0.008136405754401969, 0.004504379636843624, 0.003321663239613836],
[ 0.008869982110786701, -0.011001116814485038, -0.001446882216395328],
[ 0.016590179303752735, -0.004068517105666850, 0.002429055885660720],
[-0.007907876155693029, -0.003802464713817357, -0.003873086023200218],
[-0.000245758070628337, 0.000875351650743832, -0.003291567698024252],
[ 0.006211505382668360, 0.003507773169348530, 0.000954877481578866],
])
calc = Calculator(Param.GFN1xTB, numbers, positions)
calc.set_solvent(Solvent.methanol)
res = calc.singlepoint()
assert approx(res.get_energy(), abs=thr) == -33.66717660261584
assert approx(res.get_dipole(), abs=thr) == dipole
assert approx(res.get_gradient(), abs=thr) == gradient
calc.set_solvent()
res = calc.singlepoint(res, copy=True)
assert approx(res.get_energy(), abs=thr) == -33.63768565903155