def main():
import optparse
parser = optparse.OptionParser(usage='Usage: %prog <gpw-file> [options]',
description=description)
add = parser.add_option
add('-e',
'--cut-off',
type=float,
default=100,
meta='ECUT',
help='Plane-wave cut off energy (eV) for polarization function.')
add('-b',
'--blocks',
type=int,
default=1,
meta='N',
help='Split polarization matrix in N blocks.')
opts, args = parser.parse_args()
if len(args) == 0:
parser.error('No gpw-file!')
if len(args) > 1:
parser.error('Too many arguments!')
name = args[0]
assert name.endswith('.gpw')
rpa = RPACorrelation(name,
txt=name[:-3] + 'rpa.txt',
wstc=True,
nblocks=opts.blocks)
rpa.calculate([opts.cut_off])
def __init__(self, calc, xc='RPA', filename=None,
skip_gamma=False, qsym=True, nlambda=8,
nfrequencies=16, frequency_max=800.0, frequency_scale=2.0,
frequencies=None, weights=None, density_cut=1.e-6,
wcomm=None, chicomm=None, world=mpi.world,
unit_cells=None, tag=None,
txt=sys.stdout):
RPACorrelation.__init__(self, calc, xc=xc, filename=filename,
skip_gamma=skip_gamma, qsym=qsym,
nfrequencies=nfrequencies, nlambda=nlambda,
frequency_max=frequency_max,
frequency_scale=frequency_scale,
frequencies=frequencies, weights=weights,
wcomm=wcomm, chicomm=chicomm, world=world,
txt=txt)
self.l_l, self.weight_l = p_roots(nlambda)
self.l_l = (self.l_l + 1.0) * 0.5
self.weight_l *= 0.5
self.xc = xc
self.density_cut = density_cut
if unit_cells is None:
unit_cells = self.calc.wfs.kd.N_c
self.unit_cells = unit_cells
if tag is None:
tag = self.calc.atoms.get_chemical_formula(mode='hill')
self.tag = tag
def calculate(self, ecut):
if self.xc != 'RPA':
if isinstance(ecut, (float, int)):
self.ecut_max = ecut
else:
self.ecut_max = max(ecut)
if not os.path.isfile('fhxc_%s_%s_%s_0.gpw' %
(self.tag, self.xc, self.ecut_max)):
kernel = Kernel(self.calc, self.xc, self.ibzq_qc, self.fd,
self.unit_cells, self.density_cut,
self.ecut_max, self.tag, self.timer)
kernel.calculate_fhxc()
del kernel
else:
prnt('%s kernel already calculated' % self.xc, file=self.fd)
prnt(file=self.fd)
if self.calc.wfs.nspins == 1:
spin = False
else:
spin = True
e = RPACorrelation.calculate(self, ecut, spin=spin)
return e
def calculate(self, ecut):
if self.xc != 'RPA':
if isinstance(ecut, (float, int)):
self.ecut_max = ecut
else:
self.ecut_max = max(ecut)
if not os.path.isfile('fhxc_%s_%s_%s_0.gpw'
% (self.tag, self.xc, self.ecut_max)):
kernel = Kernel(self.calc, self.xc, self.ibzq_qc,
self.fd, self.unit_cells, self.density_cut,
self.ecut_max, self.tag)
kernel.calculate_fhxc()
del kernel
else:
prnt('%s kernel already calculated' % self.xc, file=self.fd)
prnt(file=self.fd)
if self.calc.wfs.nspins == 1:
spin = False
else:
spin = True
e = RPACorrelation.calculate(self, ecut, spin=spin)
return e
def __init__(self,
calc,
xc='RPA',
filename=None,
skip_gamma=False,
qsym=True,
nlambda=8,
nfrequencies=16,
frequency_max=800.0,
frequency_scale=2.0,
frequencies=None,
weights=None,
density_cut=1.e-6,
world=mpi.world,
nblocks=1,
unit_cells=None,
tag=None,
txt=sys.stdout):
RPACorrelation.__init__(self,
calc,
xc=xc,
filename=filename,
skip_gamma=skip_gamma,
qsym=qsym,
nfrequencies=nfrequencies,
nlambda=nlambda,
frequency_max=frequency_max,
frequency_scale=frequency_scale,
frequencies=frequencies,
weights=weights,
world=world,
nblocks=nblocks,
txt=txt)
self.l_l, self.weight_l = p_roots(nlambda)
self.l_l = (self.l_l + 1.0) * 0.5
self.weight_l *= 0.5
self.xc = xc
self.density_cut = density_cut
if unit_cells is None:
unit_cells = self.calc.wfs.kd.N_c
self.unit_cells = unit_cells
if tag is None:
tag = self.calc.atoms.get_chemical_formula(mode='hill')
self.tag = tag
def rpa(filename, ecut=200.0, blocks=1, extrapolate=4):
"""Calculate RPA energy.
filename: str
Name of restart-file.
ecut: float
Plane-wave cutoff.
blocks: int
Split polarizability matrix in this many blocks.
extrapolate: int
Number of cutoff energies to use for extrapolation.
"""
name, ext = filename.rsplit('.', 1)
assert ext == 'gpw'
from gpaw.xc.rpa import RPACorrelation
rpa = RPACorrelation(name, name + '-rpa.dat',
nblocks=blocks,
txt=name + '-rpa.txt')
rpa.calculate(ecut=ecut * (1 + 0.5 * np.arange(extrapolate))**(-2 / 3))
def rpa(filename, ecut=200.0, blocks=1, extrapolate=4):
"""Calculate RPA energy.
filename: str
Name of restart-file.
ecut: float
Plane-wave cutoff.
blocks: int
Split polarizability matrix in this many blocks.
extrapolate: int
Number of cutoff energies to use for extrapolation.
"""
name, ext = filename.rsplit('.', 1)
assert ext == 'gpw'
from gpaw.xc.rpa import RPACorrelation
rpa = RPACorrelation(name, name + '-rpa.dat',
nblocks=blocks,
wstc=True,
txt=name + '-rpa.txt')
rpa.calculate(ecut=ecut * (1 + 0.5 * np.arange(extrapolate))**(-2 / 3))
def main():
import optparse
parser = optparse.OptionParser(usage='Usage: %prog <gpw-file> [options]',
description=description)
add = parser.add_option
add('-e', '--cut-off', type=float, default=100, meta='ECUT',
help='Plane-wave cut off energy (eV) for polarization function.')
add('-b', '--blocks', type=int, default=1, meta='N',
help='Split polarization matrix in N blocks.')
opts, args = parser.parse_args()
if len(args) == 0:
parser.error('No gpw-file!')
if len(args) > 1:
parser.error('Too many arguments!')
name = args[0]
assert name.endswith('.gpw')
rpa = RPACorrelation(name,
txt=name[:-3] + 'rpa.txt',
wstc=True, nblocks=opts.blocks)
rpa.calculate([opts.cut_off])
from gpaw.mpi import serial_comm
from gpaw.test import equal
from gpaw.xc.rpa import RPACorrelation
import numpy as np
a0 = 5.43
cell = bulk('Si', 'fcc', a=a0).get_cell()
Si = Atoms('Si2', cell=cell, pbc=True,
scaled_positions=((0,0,0), (0.25,0.25,0.25)))
kpts = monkhorst_pack((2,2,2))
kpts += np.array([1/4., 1/4., 1/4.])
calc = GPAW(mode='pw',
kpts=kpts,
occupations=FermiDirac(0.001),
communicator=serial_comm)
Si.set_calculator(calc)
E = Si.get_potential_energy()
calc.diagonalize_full_hamiltonian(nbands=50)
ecut = 50
rpa = RPACorrelation(calc, qsym=False, nfrequencies=8)
E_rpa_noqsym = rpa.calculate(ecut=[ecut])
rpa = RPACorrelation(calc, qsym=True, nfrequencies=8)
E_rpa_qsym = rpa.calculate(ecut=[ecut])
equal(E_rpa_qsym, E_rpa_noqsym, 0.001)
equal(E_rpa_qsym, -12.61, 0.01)
from ase.build import bulk
from gpaw import GPAW, FermiDirac
from gpaw.mpi import serial_comm
from gpaw.test import equal
from gpaw.xc.rpa import RPACorrelation
a0 = 5.43
Si = bulk('Si', a=a0)
calc = GPAW(mode='pw',
kpts={
'size': (2, 2, 2),
'gamma': True
},
occupations=FermiDirac(0.001),
communicator=serial_comm)
Si.set_calculator(calc)
E = Si.get_potential_energy()
calc.diagonalize_full_hamiltonian(nbands=50)
ecut = 50
rpa = RPACorrelation(calc, qsym=False, nfrequencies=8)
E_rpa_noqsym = rpa.calculate(ecut=[ecut])
rpa = RPACorrelation(calc, qsym=True, nfrequencies=8)
E_rpa_qsym = rpa.calculate(ecut=[ecut])
print(E_rpa_qsym, E_rpa_noqsym, 0.001)
equal(E_rpa_qsym, -12.61, 0.01)
from __future__ import print_function
from ase.parallel import paropen
from ase.units import Hartree
from gpaw.xc.rpa import RPACorrelation
from gpaw.xc.fxc import FXCCorrelation
from gpaw.mpi import world
fxc0 = FXCCorrelation('CO.ralda.pbe_wfcs_CO.gpw',
xc='rAPBE',
txt='CO.ralda_02_CO_rapbe.txt',
wcomm=world.size)
E0_i = fxc0.calculate(ecut=400)
f = paropen('CO.ralda_rapbe_CO.dat', 'w')
for ecut, E0 in zip(fxc0.ecut_i, E0_i):
print(ecut * Hartree, E0, file=f)
f.close()
rpa0 = RPACorrelation('CO.ralda.pbe_wfcs_CO.gpw',
txt='CO.ralda_02_CO_rpa.txt',
wcomm=world.size)
E0_i = rpa0.calculate(ecut=400)
f = paropen('CO.ralda_rpa_CO.dat', 'w')
for ecut, E0 in zip(rpa0.ecut_i, E0_i):
print(ecut * Hartree, E0, file=f)
f.close()
from gpaw.xc.rpa import RPACorrelation
rpa = RPACorrelation('H.ralda.pbe_wfcs.gpw',
txt='H.ralda_05_rpa_at_pbe.output.txt')
rpa.calculate(ecut=300)
from __future__ import print_function
from ase.parallel import paropen
from ase.units import Hartree
from gpaw.xc.rpa import RPACorrelation
f = paropen('con_freq.dat', 'w')
for N in [4, 6, 8, 12, 16, 24, 32]:
rpa = RPACorrelation('N2.gpw',
txt='rpa_N2_frequencies.txt',
nfrequencies=N)
E = rpa.calculate(ecut=[50])
print(N, E[0], file=f)
if N == 16:
f16 = paropen('frequency_gauss16.dat', 'w')
for w, e in zip(rpa.omega_w, rpa.E_w):
print(w * Hartree, e, file=f16)
f16.close()
f.close()
from ase.build import bulk
from gpaw import GPAW, FermiDirac
from gpaw.mpi import serial_comm
from gpaw.test import equal
from gpaw.xc.rpa import RPACorrelation
from gpaw.xc.fxc import FXCCorrelation
a0 = 5.43
Ni = bulk('Ni', 'fcc')
Ni.set_initial_magnetic_moments([0.7])
calc = GPAW(mode='pw',
kpts=(3, 3, 3),
occupations=FermiDirac(0.001),
setups={'Ni': '10'},
communicator=serial_comm)
Ni.set_calculator(calc)
E = Ni.get_potential_energy()
calc.diagonalize_full_hamiltonian(nbands=50)
rpa = RPACorrelation(calc, nfrequencies=8, skip_gamma=True)
E_rpa = rpa.calculate(ecut=[50])
fxc = FXCCorrelation(calc, nlambda=16, nfrequencies=8, skip_gamma=True)
E_fxc = fxc.calculate(ecut=[50])
equal(E_rpa, -7.826, 0.01)
equal(E_fxc, -7.826, 0.01)
calc = GPAW(mode=PW(force_complex_dtype=True),
xc='PBE',
parallel={'domain': 1},
eigensolver='rmm-diis')
N2.set_calculator(calc)
E_n2_pbe = N2.get_potential_energy()
calc.diagonalize_full_hamiltonian(nbands=104, scalapack=True)
calc.write('N2.gpw', mode='all')
exx = EXX('N2.gpw')
exx.calculate()
E_n2_hf = exx.get_total_energy()
rpa = RPACorrelation('N2.gpw', nfrequencies=8)
E_n2_rpa = rpa.calculate(ecut=[ecut])
N = molecule('N')
N.set_cell(N2.cell)
calc = GPAW(mode=PW(force_complex_dtype=True),
xc='PBE',
parallel={'domain': 1},
eigensolver='rmm-diis')
N.set_calculator(calc)
E_n_pbe = N.get_potential_energy()
calc.diagonalize_full_hamiltonian(nbands=104, scalapack=True)
calc.write('N.gpw', mode='all')
from __future__ import print_function
from ase.parallel import paropen
from gpaw.xc.rpa import RPACorrelation
ds = [1.75, 2.0, 2.25, 2.5, 2.75, 3.0, 3.25, 3.5, 3.75, 4.0, 5.0, 6.0, 10.0]
for d in ds:
rpa = RPACorrelation('gs_%s.gpw' % d, txt='rpa_%s_%s.txt' % (ecut, d))
E_rpa = rpa.calculate(ecut=[200],
frequency_scale=2.5,
skip_gamma=True,
filename='restart_%s_%s.txt' % (ecut, d))
f = paropen('rpa_%s.dat' % ecut, 'a')
print(d, E_rpa, file=f)
f.close()
def run(args):
assert args.gpw.endswith('.gpw')
rpa = RPACorrelation(args.gpw,
txt=args.gpw[:-3] + 'rpa.txt',
nblocks=args.blocks)
rpa.calculate([args.cut_off])
from gpaw.xc.rpa import RPACorrelation
rpa1 = RPACorrelation('bulk.all.gpw', txt='si.rpa.rpa_output.txt')
E1_i = rpa1.calculate(ecut=[164.0, 140.0, 120.0, 100.0, 80.0])
from gpaw.xc.rpa import RPACorrelation
rpa = RPACorrelation('H.ralda.lda_wfcs.gpw',
txt='H.ralda_02_rpa_at_lda.output.txt')
rpa.calculate(ecut=300)
cell = bulk('Si', 'fcc', a=a0).get_cell()
Si = Atoms('Si2', cell=cell, pbc=True,
scaled_positions=((0,0,0), (0.25,0.25,0.25)))
kpts = monkhorst_pack((2,2,2))
kpts += np.array([1/4., 1/4., 1/4.])
calc = GPAW(mode='pw',
kpts=kpts,
occupations=FermiDirac(0.001),
communicator=serial_comm)
Si.set_calculator(calc)
E = Si.get_potential_energy()
calc.diagonalize_full_hamiltonian(nbands=50)
rpa = RPACorrelation(calc)
E_rpa1 = rpa.calculate(ecut=[25, 50])
fxc = FXCCorrelation(calc, xc='RPA', nlambda=16)
E_rpa2 = fxc.calculate(ecut=[25, 50])
fxc = FXCCorrelation(calc, xc='rALDA', unit_cells=[1,1,2])
E_ralda = fxc.calculate(ecut=[25, 50])
fxc = FXCCorrelation(calc, xc='rAPBE', unit_cells=[1,1,2])
E_rapbe = fxc.calculate(ecut=[25, 50])
equal(E_rpa1[-1], E_rpa2[-1], 0.01)
equal(E_rpa2[-1], -12.6495, 0.001)
equal(E_ralda[-1], -11.3817, 0.001)
equal(E_rapbe[-1], -11.1640, 0.001)
from ase.parallel import paropen
from gpaw.xc.rpa import RPACorrelation
import numpy as np
dw = 0.5
frequencies = np.array([dw * i for i in range(2000)])
weights = len(frequencies) * [dw]
weights[0] /= 2
weights[-1] /= 2
weights = np.array(weights)
rpa = RPACorrelation('N2.gpw',
txt='frequency_equidistant.txt',
frequencies=frequencies,
weights=weights)
Es = rpa.calculate(ecut=[50])
Es_w = rpa.E_w
f = paropen('frequency_equidistant.dat', 'w')
for w, E in zip(frequencies, Es_w):
print >> f, w, E.real
f.close()
from gpaw.xc.rpa import RPACorrelation
#This calculation is too heavy to run as an exercise!!
rpa1 = RPACorrelation('si_isolated.gpw', txt='rpa_output.txt')
E1_i = rpa1.calculate(ecut=400.0)
from ase.lattice import bulk
from gpaw import GPAW, FermiDirac
from gpaw.mpi import serial_comm
from gpaw.test import equal
from gpaw.xc.rpa import RPACorrelation
from gpaw.xc.fxc import FXCCorrelation
a0 = 5.43
Ni = bulk("Ni", "fcc")
Ni.set_initial_magnetic_moments([0.7])
calc = GPAW(mode="pw", kpts=(3, 3, 3), occupations=FermiDirac(0.001), setups={"Ni": "10"}, communicator=serial_comm)
Ni.set_calculator(calc)
E = Ni.get_potential_energy()
calc.diagonalize_full_hamiltonian(nbands=50)
rpa = RPACorrelation(calc, nfrequencies=8, skip_gamma=True)
E_rpa = rpa.calculate(ecut=[50])
fxc = FXCCorrelation(calc, nlambda=16, nfrequencies=8, skip_gamma=True)
E_fxc = fxc.calculate(ecut=[50])
equal(E_rpa, -7.826, 0.01)
equal(E_fxc, -7.826, 0.01)
from __future__ import print_function
from ase.parallel import paropen
from gpaw.xc.rpa import RPACorrelation
import numpy as np
dw = 0.5
frequencies = np.array([dw * i for i in range(2000)])
weights = len(frequencies) * [dw]
weights[0] /= 2
weights[-1] /= 2
weights = np.array(weights)
rpa = RPACorrelation('N2.gpw',
txt='frequency_equidistant.txt',
frequencies=frequencies,
weights=weights)
Es = rpa.calculate(ecut=[50])
Es_w = rpa.E_w
f = paropen('frequency_equidistant.dat', 'w')
for w, E in zip(frequencies, Es_w):
print(w, E.real, file=f)
f.close()
from __future__ import print_function
from ase.parallel import paropen
from ase.units import Hartree
from gpaw.xc.rpa import RPACorrelation
rpa = RPACorrelation('N.gpw',
nblocks=8,
truncation='wigner-seitz',
txt='rpa_N.txt')
E1_i = rpa.calculate(ecut=400)
rpa = RPACorrelation('N2.gpw',
nblocks=8,
truncation='wigner-seitz',
txt='rpa_N2.txt')
E2_i = rpa.calculate(ecut=400)
ecut_i = rpa.ecut_i
f = paropen('rpa_N2.dat', 'w')
for ecut, E1, E2 in zip(ecut_i, E1_i, E2_i):
print(ecut * Hartree, E2 - 2 * E1, file=f)
f.close()
from gpaw.xc.rpa import RPACorrelation
from gpaw.test import equal
bulk = bulk("Na", "bcc", a=4.23)
ecut = 350
calc = GPAW(
mode=PW(ecut),
dtype=complex,
basis="dzp",
kpts={"size": (4, 4, 4), "gamma": True},
parallel={"domain": 1},
txt="gs_occ_pw.txt",
nbands=4,
occupations=FermiDirac(0.01),
setups={"Na": "1"},
)
bulk.set_calculator(calc)
bulk.get_potential_energy()
calc.write("gs_occ_pw.gpw")
calc = GPAW("gs_occ_pw.gpw", txt="gs_pw.txt", parallel={"band": 1})
calc.diagonalize_full_hamiltonian(nbands=520)
calc.write("gs_pw.gpw", "all")
ecut = 120
calc = GPAW("gs_pw.gpw", communicator=serial_comm, txt=None)
rpa = RPACorrelation(calc, txt="rpa_%s.txt" % ecut)
E = rpa.calculate(ecut=[ecut])
equal(E, -1.106, 0.005)
from gpaw.xc.rpa import RPACorrelation
rpa1 = RPACorrelation('bulk.gpw', txt='si.rpa.rpa_output.txt')
E1_i = rpa1.calculate(ecut=[164.0, 140.0, 120.0, 100.0, 80.0])
calc = GPAW(mode=PW(300),
hund=True,
dtype=complex,
xc='LDA')
H.set_calculator(calc)
E_lda = H.get_potential_energy()
E_c_lda = -calc.get_xc_difference('LDA_X')
print 'LDA correlation: ', E_c_lda, 'eV'
print
calc.diagonalize_full_hamiltonian()
calc.write('H_lda.gpw', mode='all')
rpa = RPACorrelation('H_lda.gpw')
rpa.calculate(ecut=300)
fxc = FXCCorrelation('H_lda.gpw', xc='rALDA')
fxc.calculate(ecut=300)
# PBE --------------------------------------
H = Atoms('H', [(0, 0, 0)])
H.set_pbc(True)
H.center(vacuum=2.0)
calc = GPAW(mode=PW(300),
hund=True,
dtype=complex,
xc='PBE')
from __future__ import print_function
from ase.parallel import paropen
from ase.units import Hartree
from gpaw.xc.rpa import RPACorrelation
rpa1 = RPACorrelation('N.gpw', nblocks=8, wstc=True, txt='rpa_N.txt')
rpa2 = RPACorrelation('N2.gpw', nblocks=8, wstc=True, txt='rpa_N2.txt')
E1_i = rpa1.calculate(ecut=400)
E2_i = rpa2.calculate(ecut=400)
f = paropen('rpa_N2.dat', 'w')
for ecut, E1, E2 in zip(rpa1.ecut_i, E1_i, E2_i):
print(ecut * Hartree, E2 - 2 * E1, file=f)
f.close()
N2 = molecule("N2")
N2.center(vacuum=2.0)
calc = GPAW(mode="pw", dtype=complex, xc="PBE", eigensolver="rmm-diis")
N2.set_calculator(calc)
E_n2_pbe = N2.get_potential_energy()
calc.diagonalize_full_hamiltonian(nbands=104, scalapack=True)
calc.write("N2.gpw", mode="all")
exx = EXX("N2.gpw")
exx.calculate()
E_n2_hf = exx.get_total_energy()
rpa = RPACorrelation("N2.gpw", nfrequencies=8)
E_n2_rpa = rpa.calculate(ecut=[ecut])
# -------------------------------------------------------------------------
N = molecule("N")
N.set_cell(N2.cell)
calc = GPAW(mode="pw", dtype=complex, xc="PBE", eigensolver="rmm-diis")
N.set_calculator(calc)
E_n_pbe = N.get_potential_energy()
calc.diagonalize_full_hamiltonian(nbands=104, scalapack=True)
calc.write("N.gpw", mode="all")
exx = EXX("N.gpw")
bulk = bulk('Na', 'bcc', a=4.23)
ecut = 350
calc = GPAW(
mode=PW(ecut),
dtype=complex,
basis='dzp',
kpts={
'size': (4, 4, 4),
'gamma': True
},
parallel={'domain': 1},
txt='gs_occ_pw.txt',
nbands=4,
occupations=FermiDirac(0.01),
setups={'Na': '1'},
)
bulk.set_calculator(calc)
bulk.get_potential_energy()
calc.write('gs_occ_pw.gpw')
calc = GPAW('gs_occ_pw.gpw', txt='gs_pw.txt', parallel={'band': 1})
calc.diagonalize_full_hamiltonian(nbands=520)
calc.write('gs_pw.gpw', 'all')
ecut = 120
calc = GPAW('gs_pw.gpw', communicator=serial_comm, txt=None)
rpa = RPACorrelation(calc, txt='rpa_%s.txt' % ecut)
E = rpa.calculate(ecut=[ecut])
equal(E, -1.106, 0.005)
from __future__ import print_function
from ase.parallel import paropen
from ase.units import Hartree
from gpaw.xc.rpa import RPACorrelation
from gpaw.xc.fxc import FXCCorrelation
fxc = FXCCorrelation('diamond.ralda.pbe_wfcs.gpw', xc='rAPBE',
txt='diamond.ralda_02_rapbe.txt')
E_i = fxc.calculate(ecut=400)
f = paropen('diamond.ralda.rapbe.dat', 'w')
for ecut, E in zip(fxc.ecut_i, E_i):
print(ecut * Hartree, E, file=f)
f.close()
rpa = RPACorrelation('diamond.ralda.pbe_wfcs.gpw',
txt='diamond.ralda_02_rpa.txt')
E_i = rpa.calculate(ecut=400)
f = paropen('diamond.ralda.rpa.dat', 'w')
for ecut, E in zip(rpa.ecut_i, E_i):
print(ecut * Hartree, E, file=f)
f.close()
cell = bulk('Si', 'fcc', a=a0).get_cell()
Si = Atoms('Si2', cell=cell, pbc=True,
scaled_positions=((0,0,0), (0.25,0.25,0.25)))
kpts = monkhorst_pack((2,2,2))
kpts += np.array([1/4., 1/4., 1/4.])
calc = GPAW(mode='pw',
kpts=kpts,
occupations=FermiDirac(0.001),
communicator=serial_comm)
Si.set_calculator(calc)
E = Si.get_potential_energy()
calc.diagonalize_full_hamiltonian(nbands=50)
rpa = RPACorrelation(calc)
E_rpa1 = rpa.calculate(ecut=[25, 50])
fxc = FXCCorrelation(calc, xc='RPA', nlambda=16)
E_rpa2 = fxc.calculate(ecut=[25, 50])
fxc = FXCCorrelation(calc, xc='rALDA', unit_cells=[1,1,2])
E_ralda = fxc.calculate(ecut=[25, 50])
fxc = FXCCorrelation(calc, xc='rAPBE', unit_cells=[1,1,2])
E_rapbe = fxc.calculate(ecut=[25, 50])
fxc = FXCCorrelation(calc, xc='rALDA', av_scheme='wavevector')
E_raldawave = fxc.calculate(ecut=[25, 50])
fxc = FXCCorrelation(calc, xc='rAPBE', av_scheme='wavevector')
from gpaw.xc.rpa import RPACorrelation
#This calculation is too heavy to run as an exercise!!
rpa1 = RPACorrelation('si.rpa.isolated.gpw', txt='si.atom.rpa_output.txt')
E1_i = rpa1.calculate(ecut=400.0)
