def test_gfn1xtb_orbitals():
"""Try to access the GFN1-xTB wavefunction for a small molecule like water"""
thr = 1.0e-6
numbers = np.array([8, 1, 1])
positions = np.array([
[0.00000000000000, 0.00000000000000, -0.73578586109551],
[1.44183152868459, 0.00000000000000, 0.36789293054775],
[-1.44183152868459, 0.00000000000000, 0.36789293054775],
])
eigenvalues = np.array([
-0.75821687,
-0.61119872,
-0.54824272,
-0.50023252,
-0.15792833,
-0.05043755,
0.33342098,
0.45699087,
])
occupations = np.array([2.0, 2.0, 2.0, 2.0, 0.0, 0.0, 0.0, 0.0])
calc = Calculator(Param.GFN1xTB, numbers, positions)
res = calc.singlepoint()
assert res.get_number_of_orbitals() == 8
assert approx(res.get_orbital_eigenvalues(), abs=thr) == eigenvalues
assert approx(res.get_orbital_occupations(), abs=thr) == occupations
def test_gfn2xtb_orbitals():
"""Test orbital coefficients for a system without degenerate orbitals"""
thr = 1.0e-6
numbers = np.array([7, 6, 6, 7, 1, 1, 1, 1, 1, 1, 1, 1])
positions = np.array([
[ 1.29564977905513, -0.25290920475305, 2.56431729511582],
[-0.96996014152233, 0.50549670256050, 1.15516418827219],
[-0.91468278512195, -0.62528117704831, -1.51114193758061],
[ 1.23123794095007, 0.11828270927591, -3.08042885289515],
[ 1.20535391108832, -2.10460878458761, 3.05393708716811],
[ 1.49042362477934, 0.75515391572193, 4.17948790921212],
[ 1.10488653650763, 1.97453133190190, -3.54628265772418],
[ 2.84484320055627, -0.08607163127153, -2.06195525106275],
[-2.75154898001475, -0.03520463067517, 2.08717732882173],
[-0.96236115663776, 2.56883627236741, 1.01250854959263],
[-2.66115023536726, -0.12666205649124, -2.49751707017796],
[-0.91269171316999, -2.69156344700073, -1.35526658874193],
])
coefficients17 = np.array([
-6.23542257e-02, 1.04694368e-01, 1.58485657e-01,
1.83104316e-01, -7.05782247e-02, -2.55264595e-01,
1.14873610e-01, -7.77202601e-02, 2.36091783e-01,
1.93087565e-01, -8.34786636e-02, 1.13285466e-01,
3.30533141e-02, -3.77529214e-01, 8.08999443e-02,
3.41942901e-01, -5.04839035e-01, 1.42553998e-02,
2.83101516e-01, -5.35092121e-01, -3.50715725e-01,
1.39252075e-01, 5.45998733e-01, -5.72505850e-02,
])
coefficients18 = np.array([
-5.31639437e-02, 1.30249689e-01, 1.72599509e-01,
7.52424950e-02, 2.83853028e-01, 6.30744199e-02,
-1.59748206e-01, -1.82193248e-01, -1.15126255e-01,
-2.33248691e-01, -6.73553228e-03, 6.21219585e-02,
8.75501496e-02, -4.65395744e-01, 2.14504764e-01,
-1.94199501e-01, -2.69338288e-01, -3.51436996e-01,
3.03687890e-01, 3.92897713e-01, -8.63647836e-02,
-6.19103446e-01, -4.42942142e-01, -5.99557028e-02,
])
calc = Calculator(Param.GFN2xTB, numbers, positions)
res = calc.singlepoint()
assert res.get_number_of_orbitals() == 24
this_coefficients = res.get_orbital_coefficients()
assert approx(this_coefficients[16], thr) == +coefficients17 \
or approx(this_coefficients[16], thr) == -coefficients17
assert approx(this_coefficients[17], thr) == +coefficients18 \
or approx(this_coefficients[17], thr) == -coefficients18
def test_gfn2_xtb_3d():
"""Test if GFN2-xTB correctly fails for periodic input"""
numbers = np.array(
[6, 6, 6, 6, 6, 6, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 7, 7, 7, 7])
positions = np.array([
[9.77104501e-01, 1.24925555e-01, 8.22139769e+00],
[8.37995371e-01, 8.23489051e+00, 3.74893761e+00],
[4.62693404e+00, -2.45721089e+00, 8.22052352e+00],
[4.62532610e+00, 1.41051267e+00, 5.97940016e+00],
[9.71618351e-01, 1.17570237e-01, 3.75065164e+00],
[-2.80917006e+00, 6.94865315e+00, 5.99166085e+00],
[4.06610161e+00, 4.51252077e+00, 6.46827038e-01],
[2.76223056e-01, -8.50055887e-01, 2.06420987e+00],
[2.84806942e-01, 2.07039689e+00, 8.22836360e+00],
[2.90284064e+00, 8.22939158e+00, 3.73820878e+00],
[6.69188274e+00, -2.46191735e+00, 8.22593771e+00],
[6.69035555e+00, 1.41863696e+00, 5.97712614e+00],
[7.73011343e+00, 1.91963880e+00, 6.45533278e-01],
[3.94842571e+00, 3.36121142e+00, 5.97668593e+00],
[-3.49960564e+00, 5.97197638e+00, 7.67502785e+00],
[2.79250975e-01, 2.06298102e+00, 3.73907675e+00],
[-3.50586965e+00, 5.96534053e+00, 4.31491171e+00],
[1.56432603e-01, 7.25773353e+00, 2.06229892e+00],
[-4.98732693e-02, 6.88619344e+00, 5.98746725e+00],
[-4.50657119e-03, -1.16906911e+00, 5.98934273e+00],
[3.73678498e+00, 1.55157272e-01, 8.27155126e+00],
[3.73119434e+00, 1.47879860e-01, 3.69345547e+00],
])
lattice = np.array([
[1.13437228e+01, -1.84405404e-03, 1.33836685e-05],
[-3.78300868e+00, 1.06992286e+01, -1.04202175e-03],
[-3.78025723e+00, -5.34955718e+00, 9.26593601e+00],
])
periodic = np.array([True, True, True])
# GFN2-xTB does not support periodic boundary conditions,
# yet the constructor should not flag this error to keep the interface uniform
calc = Calculator(Param.GFN2xTB,
numbers,
positions,
lattice=lattice,
periodic=periodic)
res = Results(calc)
with raises(XTBException, match="Single point calculation failed"):
calc.singlepoint(res)
def run(self, geom, multiplicity, state, verbose=False):
#print('running!')
#sys.stdout.flush()
coords = manage_xyz.xyz_to_np(geom)
# convert to bohr
positions = coords * units.ANGSTROM_TO_AU
calc = Calculator(get_method("GFN2-xTB"),
self.numbers,
positions,
charge=self.charge)
calc.set_output('lot_jobs_{}.txt'.format(self.node_id))
res = calc.singlepoint() # energy printed is only the electronic part
calc.release_output()
# energy in hartree
self._Energies[(multiplicity,
state)] = self.Energy(res.get_energy(), 'Hartree')
# grad in Hatree/Bohr
self._Gradients[(multiplicity,
state)] = self.Gradient(res.get_gradient(),
'Hartree/Bohr')
# write E to scratch
self.write_E_to_file()
self.hasRanForCurrentCoords = True
return res
def run(self, coords, multiplicity, state, verbose=False):
#print('running!')
#sys.stdout.flush()
self.E = []
self.grada = []
# convert to angstrom
positions = coords * units.ANGSTROM_TO_AU
calc = Calculator(get_method("GFN2-xTB"), self.numbers, positions)
calc.set_output('lot_jobs_{}.txt'.format(self.node_id))
res = calc.singlepoint() # energy printed is only the electronic part
calc.release_output()
# energy in hartree
self.E.append((multiplicity, state, res.get_energy()))
# grad in Hatree/Bohr
self.grada.append((multiplicity, state, res.get_gradient()))
# write E to scratch
with open('scratch/E_{}.txt'.format(self.node_id), 'w') as f:
for E in self.E:
f.write('{} {:9.7f}\n'.format(E[0], E[2]))
self.hasRanForCurrentCoords = True
return res
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 test_gfn1xtb_external_charges():
"""Test external charge potentials together with the GFN1-xTB method"""
thr = 1.0e-8
numbers = np.array([7, 1, 1, 6, 1, 1, 1])
positions1 = np.array([
[-2.74753712457143, 0.37784000250000, -1.43187391300000],
[-1.18171822157143, -0.72737292050000, -1.52700665300000],
[-3.99820987557143, -0.35850981350000, -2.67576139800000],
[-3.80581663657143, 0.22757315950000, 1.11430154300000],
[-5.49538086757143, 1.39513306450000, 1.22999226200000],
[-4.30486812157143, -1.67583868950000, 1.75209463100000],
[-2.44826907957143, 0.99721383450000, 2.45438316600000],
])
positions2 = np.array([
[ 2.99257143742857, -1.37287306250000, -1.14373597500000],
[ 3.55243804342857, -0.85407196950000, -2.89737380800000],
[ 4.17090944942857, -2.78580288550000, -0.62369309000000],
[ 3.29536218742857, 0.77236389950000, 0.58285999400000],
[ 2.78477654742857, 0.17767510450000, 2.48326881100000],
[ 5.19909163542857, 1.56940602550000, 0.65272644000000],
[ 1.98665062642857, 2.25726425050000, 0.02981799000000],
])
ext_charges1 = np.array([-0.49337941, 0.19159242, 0.18562205, 0.06205481,
0.01529955, 0.00541236, 0.01570019])
ext_charges2 = np.array([-0.48186275, 0.19166815, 0.19110522, 0.05778421,
0.02072806, 0.00885202, 0.02942314])
charges1 = np.array([
-0.4893542979011367, 0.20004214919138275, 0.1869926298627577,
0.0615170739008161, 0.01681197840166056, 0.0066754441219079,
0.0173150224226123,
])
charges2 = np.array([
-0.4920274542173372, 0.18970771261324710, 0.1885460472894940,
0.0588378643836063, 0.01936872263252927, 0.0072127270460456,
0.0283543802524126,
])
calc = Calculator(Param.GFN1xTB, numbers, positions1)
res = calc.singlepoint()
assert approx(res.get_energy(), thr) == -8.008992383435352
calc.set_external_charges(numbers, ext_charges2, positions2)
res = calc.singlepoint(res)
assert approx(res.get_energy(), thr) == -8.009880136017214
assert approx(res.get_charges(), thr) == charges1
calc.update(positions2)
calc.set_external_charges(numbers, ext_charges1, positions1)
res = calc.singlepoint()
assert approx(res.get_energy(), thr) == -8.009764296271317
assert approx(res.get_charges(), thr) == charges2
calc.release_external_charges()
res = calc.singlepoint(res)
assert approx(res.get_energy(), thr) == -8.008980959176283
with raises(ValueError):
calc.set_external_charges(numbers, ext_charges2, np.zeros(9))
with raises(ValueError):
calc.set_external_charges(numbers, np.zeros(4), positions2)
# Try to circumvent the wrapper to actually trip off an API error
with raises(XTBException):
calc.set_external_charges(np.zeros(0), np.zeros(0), np.zeros(0))
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
def test_gfn1_xtb_3d():
"""Test GFN1-xTB for periodic input"""
thr = 1.0e-7
thr2 = 1.0e-6
numbers = np.array(
[6, 6, 6, 6, 6, 6, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 7, 7, 7, 7]
)
positions = np.array([
[ 9.77104501e-01, 1.24925555e-01, 8.22139769e+00],
[ 8.37995371e-01, 8.23489051e+00, 3.74893761e+00],
[ 4.62693404e+00, -2.45721089e+00, 8.22052352e+00],
[ 4.62532610e+00, 1.41051267e+00, 5.97940016e+00],
[ 9.71618351e-01, 1.17570237e-01, 3.75065164e+00],
[-2.80917006e+00, 6.94865315e+00, 5.99166085e+00],
[ 4.06610161e+00, 4.51252077e+00, 6.46827038e-01],
[ 2.76223056e-01, -8.50055887e-01, 2.06420987e+00],
[ 2.84806942e-01, 2.07039689e+00, 8.22836360e+00],
[ 2.90284064e+00, 8.22939158e+00, 3.73820878e+00],
[ 6.69188274e+00, -2.46191735e+00, 8.22593771e+00],
[ 6.69035555e+00, 1.41863696e+00, 5.97712614e+00],
[ 7.73011343e+00, 1.91963880e+00, 6.45533278e-01],
[ 3.94842571e+00, 3.36121142e+00, 5.97668593e+00],
[-3.49960564e+00, 5.97197638e+00, 7.67502785e+00],
[ 2.79250975e-01, 2.06298102e+00, 3.73907675e+00],
[-3.50586965e+00, 5.96534053e+00, 4.31491171e+00],
[ 1.56432603e-01, 7.25773353e+00, 2.06229892e+00],
[-4.98732693e-02, 6.88619344e+00, 5.98746725e+00],
[-4.50657119e-03, -1.16906911e+00, 5.98934273e+00],
[ 3.73678498e+00, 1.55157272e-01, 8.27155126e+00],
[ 3.73119434e+00, 1.47879860e-01, 3.69345547e+00],
])
lattice = np.array([
[ 1.13437228e+01, -1.84405404e-03, 1.33836685e-05],
[-3.78300868e+00, 1.06992286e+01, -1.04202175e-03],
[-3.78025723e+00, -5.34955718e+00, 9.26593601e+00],
])
periodic = np.array([True, True, True])
gradient = np.array([
[ 5.46952312e-03, -3.12525543e-03, -6.52896786e-03],
[-5.71285287e-03, 4.38725269e-03, 6.32349907e-03],
[-5.02173630e-03, 4.34885633e-03, -7.00803496e-03],
[-4.87551596e-03, -7.09454257e-03, 3.77244368e-04],
[ 5.02630829e-03, -3.79620239e-03, 6.30421751e-03],
[ 4.91374216e-03, 8.09631816e-03, -3.68676539e-04],
[-7.28717739e-05, 1.30568980e-03, -6.38908884e-04],
[ 9.79695284e-05, 1.46129903e-03, 1.04762274e-03],
[ 7.73360338e-05, -1.75682759e-03, 7.51987006e-04],
[-1.23628606e-03, -4.69633640e-04, -7.39566395e-04],
[-1.91940111e-03, -4.73100704e-04, 6.08278469e-04],
[-1.77181502e-03, 7.83050332e-04, -4.59767804e-06],
[ 1.17661172e-03, 2.89377463e-04, -9.14361241e-04],
[ 1.34273926e-03, -1.27328012e-03, -1.21190000e-04],
[ 7.78894324e-05, -2.90779544e-05, -1.64479354e-03],
[ 2.01000804e-04, -1.68099958e-03, -7.42723431e-04],
[-6.00020414e-05, 2.71877066e-05, 1.56139664e-03],
[ 1.25834445e-03, 4.52585494e-04, 7.01094853e-04],
[-1.59037639e-03, 6.66092068e-03, 1.53044955e-03],
[ 6.42180919e-03, -6.01295157e-04, -1.95941235e-04],
[-1.85390467e-03, -4.18967639e-03, -5.23581022e-03],
[-1.94851179e-03, -3.32264614e-03, 4.93778178e-03],
])
charges = np.array([
0.06182382, 0.06099432, 0.03885390, 0.06788916, 0.06428087,
0.05876764, 0.03243010, 0.02574899, 0.02339485, 0.03323515,
0.02257734, 0.02147826, 0.03444456, 0.02614362, 0.03103734,
0.02593346, 0.03068062, 0.03220337, -0.16214463, -0.17714762,
-0.17554024, -0.17708487,
])
calc = Calculator(
Param.GFN1xTB, numbers, positions, lattice=lattice, periodic=periodic
)
res = Results(calc)
# Start calculation by restarting with result, since we are working with
# a pointer under the hood, we don't have to catch the return value to
# access the results
calc.singlepoint(res)
assert approx(res.get_energy(), abs=thr) == -31.906084801853034
assert approx(res.get_gradient(), abs=thr) == gradient
assert approx(res.get_charges(), abs=thr2) == charges
def test_gfn1_xtb_0d():
"""check if the GFN1-xTB interface is working correctly."""
thr = 1.0e-7
thr2 = 1.0e-6
numbers = np.array(
[6, 7, 6, 7, 6, 6, 6, 8, 7, 6, 8, 7, 6, 6, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]
)
positions = np.array(
[
[ 2.02799738646442, 0.09231312124713,-0.14310895950963],
[ 4.75011007621000, 0.02373496014051,-0.14324124033844],
[ 6.33434307654413, 2.07098865582721,-0.14235306905930],
[ 8.72860718071825, 1.38002919517619,-0.14265542523943],
[ 8.65318821103610,-1.19324866489847,-0.14231527453678],
[ 6.23857175648671,-2.08353643730276,-0.14218299370797],
[ 5.63266886875962,-4.69950321056008,-0.13940509630299],
[ 3.44931709749015,-5.48092386085491,-0.14318454855466],
[ 7.77508917214346,-6.24427872938674,-0.13107140408805],
[10.30229550927022,-5.39739796609292,-0.13672168520430],
[12.07410272485492,-6.91573621641911,-0.13666499342053],
[10.70038521493902,-2.79078533715849,-0.14148379504141],
[13.24597858727017,-1.76969072232377,-0.14218299370797],
[ 7.40891694074004,-8.95905928176407,-0.11636933482904],
[ 1.38702118184179, 2.05575746325296,-0.14178615122154],
[ 1.34622199478497,-0.86356704498496, 1.55590600570783],
[ 1.34624089204623,-0.86133716815647,-1.84340893849267],
[ 5.65596919189118, 4.00172183859480,-0.14131371969009],
[14.67430918222276,-3.26230980007732,-0.14344911021228],
[13.50897177220290,-0.60815166181684, 1.54898960808727],
[13.50780014200488,-0.60614855212345,-1.83214617078268],
[ 5.41408424778406,-9.49239668625902,-0.11022772492007],
[ 8.31919801555568,-9.74947502841788, 1.56539243085954],
[ 8.31511620712388,-9.76854236502758,-1.79108242206824],
]
)
gradient = np.array(
[
[ 3.87497169e-03, 1.05883022e-03, 4.01012413e-06],
[-6.82002304e-03,-2.54686427e-02,-4.74713878e-05],
[ 1.06489319e-02, 8.83656933e-03, 4.79964506e-05],
[ 3.19138203e-04, 7.42440606e-03,-2.84972366e-05],
[-2.62085234e-02,-9.01316371e-03,-3.86695635e-05],
[-1.75094079e-03, 3.66993588e-03, 3.41186057e-05],
[ 1.94850127e-02, 4.74199522e-03, 4.04729092e-05],
[-1.17234487e-02, 7.48238018e-03,-1.16123385e-04],
[-1.22410371e-03,-1.91329992e-02, 1.24615909e-04],
[-1.67669061e-02, 1.21039811e-02,-3.45753133e-05],
[ 2.48445184e-02,-1.92875717e-02,-4.91970983e-05],
[ 1.10842561e-02, 1.70041879e-02,-3.22098294e-06],
[-6.45913430e-03,-4.28606740e-03,-4.08606798e-06],
[-6.58997261e-03, 1.32209050e-02,-9.01648028e-05],
[-1.32693744e-03, 2.12474694e-03, 4.09305030e-06],
[ 1.72269615e-03, 1.17167501e-03, 2.68453033e-03],
[ 1.72536326e-03, 1.17100604e-03,-2.68802212e-03],
[-1.55002130e-03, 3.93152833e-03, 2.52250090e-05],
[ 6.35716726e-03, 2.28982657e-03, 3.48062215e-06],
[ 5.17423565e-04,-5.06087446e-04, 1.94245792e-03],
[ 5.40636707e-04,-4.85737643e-04,-1.94565875e-03],
[-1.26772106e-03,-7.65879097e-03, 8.49174054e-05],
[ 2.77976049e-04,-1.82969944e-04, 1.40041971e-03],
[ 2.89640303e-04,-2.09943109e-04,-1.35065134e-03],
]
)
dipole = np.array([-0.81941935, 1.60912848, 0.00564382])
calc = Calculator(Param.GFN1xTB, numbers, positions)
res = Results(calc)
# check if we cannot retrieve properties from the unallocated result
with raises(XTBException, match="Energy is not available"):
res.get_energy()
with raises(XTBException, match="Gradient is not available"):
res.get_gradient()
with raises(XTBException, match="Virial is not available"):
res.get_virial()
with raises(XTBException, match="Partial charges are not available"):
res.get_charges()
with raises(XTBException, match="Dipole moment is not available"):
res.get_dipole()
with raises(XTBException, match="Bond orders are not available"):
res.get_bond_orders()
assert res.get_number_of_orbitals() == 0
with raises(XTBException, match="Orbital eigenvalues are not available"):
res.get_orbital_eigenvalues()
with raises(XTBException, match="Occupation numbers are not available"):
res.get_orbital_occupations()
with raises(XTBException, match="Orbital coefficients are not available"):
res.get_orbital_coefficients()
# Start calculation by restarting with result
res = calc.singlepoint(res)
assert approx(res.get_energy(), abs=thr) == -44.509702418208896
assert approx(res.get_gradient(), abs=thr2) == gradient
assert approx(res.get_dipole(), abs=thr2) == dipole
def test_gfn2_xtb_0d():
"""check if the GFN2-xTB interface is working correctly."""
thr = 1.0e-7
thr2 = 1.0e-6
numbers = np.array(
[6, 7, 6, 7, 6, 6, 6, 8, 7, 6, 8, 7, 6, 6, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]
)
positions = np.array(
[
[ 2.02799738646442, 0.09231312124713,-0.14310895950963],
[ 4.75011007621000, 0.02373496014051,-0.14324124033844],
[ 6.33434307654413, 2.07098865582721,-0.14235306905930],
[ 8.72860718071825, 1.38002919517619,-0.14265542523943],
[ 8.65318821103610,-1.19324866489847,-0.14231527453678],
[ 6.23857175648671,-2.08353643730276,-0.14218299370797],
[ 5.63266886875962,-4.69950321056008,-0.13940509630299],
[ 3.44931709749015,-5.48092386085491,-0.14318454855466],
[ 7.77508917214346,-6.24427872938674,-0.13107140408805],
[10.30229550927022,-5.39739796609292,-0.13672168520430],
[12.07410272485492,-6.91573621641911,-0.13666499342053],
[10.70038521493902,-2.79078533715849,-0.14148379504141],
[13.24597858727017,-1.76969072232377,-0.14218299370797],
[ 7.40891694074004,-8.95905928176407,-0.11636933482904],
[ 1.38702118184179, 2.05575746325296,-0.14178615122154],
[ 1.34622199478497,-0.86356704498496, 1.55590600570783],
[ 1.34624089204623,-0.86133716815647,-1.84340893849267],
[ 5.65596919189118, 4.00172183859480,-0.14131371969009],
[14.67430918222276,-3.26230980007732,-0.14344911021228],
[13.50897177220290,-0.60815166181684, 1.54898960808727],
[13.50780014200488,-0.60614855212345,-1.83214617078268],
[ 5.41408424778406,-9.49239668625902,-0.11022772492007],
[ 8.31919801555568,-9.74947502841788, 1.56539243085954],
[ 8.31511620712388,-9.76854236502758,-1.79108242206824],
],
order="F",
)
gradient = np.array(
[
[-4.48702270e-03,-7.11501681e-04, 4.42250727e-06],
[ 5.63520998e-03,-2.63277841e-02,-5.47551032e-05],
[ 4.94394513e-03, 1.91697172e-02, 5.20296937e-05],
[ 4.14320227e-03, 3.78985927e-03,-3.26124506e-05],
[-3.44924840e-02,-8.30763633e-03,-3.85476373e-05],
[ 6.09858493e-03,-4.02776651e-03, 3.46142461e-05],
[ 1.74698961e-02, 7.91501928e-03, 3.75246600e-05],
[-1.44268345e-02, 7.07857171e-03,-1.12175048e-04],
[-5.07088926e-04,-1.13149559e-02, 7.28999985e-05],
[-1.55778036e-02, 1.26994854e-02,-2.82633017e-05],
[ 2.84123935e-02,-2.38401320e-02,-3.96858051e-05],
[ 2.52730535e-03, 1.36557434e-02,-1.07970323e-05],
[-1.61957397e-03,-2.96924390e-03, 2.89329075e-06],
[-6.51526117e-03, 7.90714240e-03,-5.83689564e-05],
[-1.45365262e-03, 2.78387473e-03, 4.39889933e-06],
[ 2.59676642e-03, 9.07269292e-04, 3.98184821e-03],
[ 2.59860253e-03, 9.08300767e-04,-3.98462262e-03],
[-3.77425616e-03, 8.36833530e-03, 2.89789639e-05],
[ 7.86820850e-03, 2.13957196e-03, 7.31459251e-07],
[ 9.32145702e-04,-1.65668033e-04, 3.24917573e-03],
[ 9.57211265e-04,-1.41846051e-04,-3.25368821e-03],
[-2.06937754e-03,-9.28913451e-03, 1.03587348e-04],
[ 3.58598494e-04,-9.82977790e-05, 2.38378001e-03],
[ 3.81284918e-04,-1.28923994e-04,-2.34336886e-03],
]
)
charges = np.array([
-0.05445590, -0.00457526, 0.08391889, -0.27870751, 0.11914924,
-0.02621044, 0.26115960, -0.44071824, -0.10804747, 0.30411699,
-0.44083760, -0.07457706, -0.04790859, -0.03738239, 0.06457802,
0.08293905, 0.08296802, 0.05698136, 0.09025556, 0.07152988,
0.07159003, 0.08590674, 0.06906357, 0.06926350,
])
calc = Calculator(Param.GFN2xTB, numbers, positions)
calc.set_verbosity(VERBOSITY_MINIMAL)
assert calc.check() == 0
calc.set_accuracy(1.0)
calc.set_max_iterations(50)
calc.set_electronic_temperature(300.0)
res = calc.singlepoint()
assert approx(res.get_energy(), abs=thr) == -42.14746312757416
assert approx(res.get_gradient(), abs=thr2) == gradient
assert approx(res.get_charges(), abs=thr2) == charges
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_orbitals():
"""Try to access the GFN1-xTB wavefunction for a small molecule like water"""
thr = 1.0e-6
numbers = np.array([8, 1, 1])
positions = np.array([
[0.00000000000000, 0.00000000000000, -0.73578586109551],
[1.44183152868459, 0.00000000000000, 0.36789293054775],
[-1.44183152868459, 0.00000000000000, 0.36789293054775],
])
eigenvalues = np.array([
-0.75821687,
-0.61119872,
-0.54824272,
-0.50023252,
-0.15792833,
-0.05043755,
0.33342098,
0.45699087,
])
occupations = np.array([2.0, 2.0, 2.0, 2.0, 0.0, 0.0, 0.0, 0.0])
coefficients = np.array([
[
-7.96486314e-01,
1.91513472e-15,
-3.81069986e-01,
1.06627860e-15,
-3.85581374e-01,
-2.77555756e-16,
6.66133815e-16,
8.73808841e-01,
],
[
8.67361738e-16,
7.06326895e-01,
2.06085149e-15,
5.99181075e-17,
-2.35922393e-16,
9.10524298e-02,
-9.80328049e-01,
1.05471187e-15,
],
[
6.66133815e-16,
-2.22044605e-16,
2.27595720e-15,
1.00000000e+00,
-1.66533454e-16,
1.11022302e-16,
-2.77555756e-17,
1.38777878e-17,
],
[
-7.03752745e-02,
-2.35922393e-15,
8.51677843e-01,
-1.85493019e-15,
-1.38148603e-01,
4.02455846e-16,
7.77156117e-16,
7.23141261e-01,
],
[
-1.79427083e-01,
3.32421120e-01,
1.83354106e-01,
-2.70755099e-17,
3.63066743e-01,
-3.84174939e-01,
8.29758195e-01,
-7.50228671e-01,
],
[
-1.38489858e-02,
4.55724612e-02,
4.79829369e-02,
-2.77816056e-16,
-5.47923122e-01,
6.88051905e-01,
3.00554964e-01,
-4.79998559e-01,
],
[
-1.79427083e-01,
-3.32421120e-01,
1.83354106e-01,
-4.15348025e-16,
3.63066743e-01,
3.84174939e-01,
-8.29758195e-01,
-7.50228671e-01,
],
[
-1.38489858e-02,
-4.55724612e-02,
4.79829369e-02,
-1.37843421e-16,
-5.47923122e-01,
-6.88051905e-01,
-3.00554964e-01,
-4.79998559e-01,
],
],
order='F')
calc = Calculator(Param.GFN1xTB, numbers, positions)
res = calc.singlepoint()
assert res.get_number_of_orbitals() == 8
assert approx(res.get_orbital_eigenvalues(), thr) == eigenvalues
assert approx(res.get_orbital_occupations(), thr) == occupations
this_coefficients = res.get_orbital_coefficients()
# remember, signs of wavefunctions are tricky, better get this one right
for i in range(res.get_number_of_orbitals()):
assert approx(this_coefficients[i], thr) == +coefficients[i] \
or approx(this_coefficients[i], thr) == -coefficients[i]
