def test_benzene_gradients(benzene_dimer):
coords, species, vol_ratios = benzene_dimer[0]
ene, gradients = MBDGeom(coords).mbd_energy_species(species,
vol_ratios,
0.83,
force=True)
with MBDGeom(coords) as geom:
num_gradients = numerical_gradients(geom, 'mbd_energy_species',
species, vol_ratios, 0.83)
for i in range(len(coords)):
assert gradients[i] == approx(num_gradients[i], rel=1e-10, abs=1e-10)
def test_benzene_rpa():
coords, species, vol_ratios = benzene_dimer[0]
alpha_0, C6, R_vdw = from_volumes(species, vol_ratios)
ene = MBDGeom(coords, do_rpa=True).mbd_energy(
alpha_0, C6, R_vdw, 0.83, variant='plain'
)
assert ene == approx(-0.007002398506090302, rel=1e-9)
def test_lithium():
with pytest.raises(MBDFortranException):
[
MBDGeom(coords, lattice,
k_grid).mbd_energy_species(species, vol_ratios, 0.83)
for coords, lattice, k_grid, species, vol_ratios in bulk_lithium
]
def test_ethylcarbamate():
enes = [
MBDGeom(coords, lattice, k_grid).mbd_energy_species(species, vol_ratios, 0.83)
for coords, lattice, k_grid, species, vol_ratios in ethylcarbamate
]
ene_int = enes[0] - 2 * enes[1]
assert ene_int == approx(-0.037040868610822564, rel=1e-10)
def test_argon_dimer_plain():
ene = MBDGeom([(0, 0, 0),
(0, 0, 4 * ang)]).mbd_energy([11, 11], [63.525, 63.525],
[3.55, 3.55],
0.83,
variant='plain')
assert ene == approx(-0.00024329110270970844, rel=1e-10)
def test_ethylcarbamate_ts():
enes = [
MBDGeom(coords, lattice).ts_energy_species(species, vol_ratios, 0.83)
for coords, lattice, _, species, vol_ratios in ethylcarbamate
]
ene_int = enes[0] - 2 * enes[1]
assert ene_int == approx(-0.05218213230219945, rel=1e-10)
def test_argon_crystal_gradients():
coords, lattice, k_grid, species, vol_ratios = argon_crystal
ene, gradients, latt_gradients = MBDGeom(
coords, lattice, k_grid
).mbd_energy_species(species, vol_ratios, 0.83, force=True)
with MBDGeom(coords, lattice, k_grid) as geom:
num_gradients = numerical_gradients(
geom, 'mbd_energy_species', species, vol_ratios, 0.83
)
for i in range(len(coords)):
assert gradients[i] == approx(num_gradients[i], rel=1e-10, abs=1e-10)
with MBDGeom(coords, lattice, k_grid) as geom:
num_latt_gradients = numerical_latt_gradients(
geom, 'mbd_energy_species', species, vol_ratios, 0.83
)
for i in range(3):
assert latt_gradients[i] == approx(num_latt_gradients[i], rel=1e-10, abs=1e-10)
def test_argon_crystal_rpa():
coords, lattice, k_grid, species, vol_ratios = argon_crystal
ene = MBDGeom(coords, lattice, k_grid,
do_rpa=True).mbd_energy_species(species,
vol_ratios,
0.83,
variant='plain')
assert ene == approx(-0.0021036969146744147, rel=1e-10)
def test_mbd_coulomb():
a = 14.4
beta = 2.0
enes = []
for coords, species, vol_ratios in peptide_meoh:
geom = MBDGeom(coords, get_spectrum=True)
_, eigs, C = geom.mbd_energy_species(species, vol_ratios, beta=0.83)
omega_t = np.sqrt(eigs)
alpha_0, C6, R_vdw = from_volumes(species, vol_ratios)
omega = 4 * C6 / (3 * alpha_0 ** 2)
charges = np.ones_like(alpha_0)
masses = 1 / (alpha_0 * omega ** 2)
ecoul = geom.coulomb_energy(
charges, masses, omega_t, 'fermi', R_vdw, beta, a, C
)
edip = geom.dipole_energy(
alpha_0, omega, omega_t, 'fermi,dip', R_vdw, beta, a, C
)
C = np.identity(len(omega_t))
omega_non = np.repeat(omega, 3)
ecoul_non = geom.coulomb_energy(
charges, masses, omega_non, 'fermi', R_vdw, beta, a, C
)
edip_non = geom.dipole_energy(
alpha_0, omega, omega_t, 'fermi,dip', R_vdw, beta, a, C
)
enes.append(ecoul - edip - (ecoul_non - edip_non))
ene_int = enes[2] - enes[0] - enes[1]
assert ene_int == approx(0.0002460638172163822 / 627.503, rel=1e-10)
def test_benzene_dimer_python():
mon1, mon2 = benzene_dimer
dim = (np.vstack((mon1[0], mon2[0])), mon1[1] + mon2[1], mon1[2] + mon2[2])
enes = [
MBDGeom(coords).mbd_energy_species(species, vol_ratios, 0.83)
for coords, species, vol_ratios in (mon1, mon2, dim)
]
ene_int = enes[2] - enes[1] - enes[0]
assert ene_int == approx(-0.006312323931302544, rel=1e-10)
def test_ethylcarbamate_scs():
enes = [
MBDGeom(coords, lattice, k_grid).mbd_energy_species(
species, vol_ratios, 1, a=2.56, variant='scs'
)
for coords, lattice, k_grid, species, vol_ratios in ethylcarbamate
]
ene_int = enes[0] - 2 * enes[1]
assert ene_int == approx(-0.03633331132194684, rel=1e-10)
def test_benzene_dimer_ts():
mon1, mon2 = benzene_dimer
dim = (np.vstack((mon1[0], mon2[0])), mon1[1] + mon2[1], mon1[2] + mon2[2])
enes = [
MBDGeom(coords).ts_energy_species(species, vol_ratios, 0.94)
for coords, species, vol_ratios in (mon1, mon2, dim)
]
ene_int = enes[2] - enes[1] - enes[0]
assert ene_int == approx(-0.008490052683234028, rel=1e-10)
def _run_MBD_f(self):
"""
Run MBD calculation via FORTRAN implementation.
"""
MBD = MBDcalc_F(self.xyz,
lattice=self.UC,
k_grid=self.kgrid,
n_freq=self.n_omega_SCS,
get_spectrum=self.get_MBD_spectrum)
res = MBD.mbd_energy(self.alpha0_TS,
self.C6_TS,
self.RvdW_TS,
self.beta,
force=self.calc_forces)
if self.periodic and self.get_MBD_spectrum and self.calc_forces: # all
((self.results['energy'], self.MBDevals, self.MBDmodes), \
self.results['forces'], self.results['stress']) = res
self.results['forces'] *= -1. * Hartree / Bohr
self.results['stress'] *= -1. * Hartree / Bohr
elif self.periodic and self.get_MBD_spectrum: # no forces
(self.results['energy'], self.MBDevals, self.MBDmodes) = res
elif self.periodic and self.calc_forces: # no spectrum
(self.results['energy'], self.results['forces'], \
self.results['stress']) = res
self.results['forces'] *= -1. * Hartree / Bohr
self.results['stress'] *= -1. * Hartree / Bohr
elif self.get_MBD_spectrum and self.calc_forces: # no PBC
((self.results['energy'], self.MBDevals, self.MBDmodes), \
self.results['forces']) = res
self.results['forces'] *= -1. * Hartree / Bohr
elif self.get_MBD_spectrum: # no forces and no PBC
(self.results['energy'], self.MBDevals, self.MBDmodes) = res
elif self.calc_forces: # no spectrum and no PBC
(self.results['energy'], self.results['forces']) = res
self.results['forces'] *= -1. * Hartree / Bohr
else: # only energy (with and without PBC)
self.results['energy'] = res
self.results['energy'] *= Hartree
def test_benzene_dimer_scs():
mon1, mon2 = benzene_dimer
dim = (np.vstack((mon1[0], mon2[0])), mon1[1] + mon2[1], mon1[2] + mon2[2])
enes = [
MBDGeom(coords).mbd_energy_species(
species, vol_ratios, 1, a=2.56, variant='scs'
)
for coords, species, vol_ratios in (mon1, mon2, dim)
]
ene_int = enes[2] - enes[1] - enes[0]
assert ene_int == approx(-0.007462380657774048, rel=1e-10)
def run(supercell, k_grid, finite, force, method, early_return, repeat):
if with_mpi:
from mpi4py import MPI
global RANK
RANK = MPI.COMM_WORLD.Get_rank()
_print('--------------')
coords, lattice, species, vol_ratios = make_supercell(
*unit_cell, supercell)
_print('number of atoms:', len(coords))
_print('Pymbd version:', '.'.join(map(str, _version)))
_print('Libmbd version:', '{}.{}.{}-{}'.format(*LIBMBD_VERSION))
_print('--------------')
if early_return:
return
geom = MBDGeom(coords) if finite else MBDGeom(coords, lattice, k_grid)
if method == 'mbd@rsscs':
func = geom.mbd_energy_species
elif method == 'mbd':
func = partial(geom.mbd_energy_species, variant='plain')
elif method == 'ts':
func = geom.ts_energy_species
with geom:
for _ in range(repeat):
res = func(species, vol_ratios, 0.83, force=force)
geom.print_timing()
if force:
ene, grad, *_ = res
else:
ene = res
ene = ene / len(coords)
_print('--------------')
_print('energy:', ene)
if force:
_print('grad[0]:', grad[0])
_print('--------------')
def test_argon_dimer_ts():
ene = MBDGeom([(0, 0, 0), (0, 0, 4 * ang)]).ts_energy(
[11, 11], [63.525, 63.525], [3.55, 3.55], 0.94
)
assert ene == approx(-0.000318123017869182, rel=1e-10)
def test_argon_crystal():
coords, lattice, k_grid, species, vol_ratios = argon_crystal
ene = MBDGeom(coords, lattice, k_grid).mbd_energy_species(species, vol_ratios, 0.83)
assert ene == approx(-0.0021037562496878173, rel=1e-10)
def test_argon_dimer_dipole_matrix():
dip = MBDGeom([(0, 0, 0), (0, 0, 4 * ang)]).dipole_matrix('bare')
assert (dip != 0).sum() == 6
def test_argon_dimer_rsscs():
ene = MBDGeom([(0, 0, 0), (0, 0, 4 * ang)]).mbd_energy_species(
['Ar', 'Ar'], [1, 1], 0.83
)
assert ene == approx(-0.0002462647623815428, rel=1e-10)
# This Source Code Form is subject to the terms of the Mozilla Public
# License, v. 2.0. If a copy of the MPL was not distributed with this
# file, You can obtain one at http://mozilla.org/MPL/2.0/.
import sys
from pymbd import ang
from pymbd.fortran import MBDGeom, with_mpi
ene_expected = -0.0002462647623815428
ene = MBDGeom([(0, 0, 0), (0, 0, 4 * ang)]).mbd_energy_species(['Ar', 'Ar'],
[1, 1], 0.83)
if with_mpi:
from mpi4py import MPI
rank = MPI.COMM_WORLD.Get_rank()
else:
rank = 0
if rank == 0:
print('Expected energy: {ene_expected}')
print('Calculated energy: {ene}')
if ene - ene_expected > 1e-10:
sys.exit(1)
def test_lithium(bulk_lithium):
coords, lattice, k_grid, species, vol_ratios = bulk_lithium
with pytest.raises(MBDFortranError):
MBDGeom(coords, lattice,
k_grid).mbd_energy_species(species, vol_ratios, 0.83)