def estimate_memory(self, mem):
RealSpaceHamiltonian.estimate_memory(self, mem)
solvation = mem.subnode('Solvation')
for name, obj in [
('Cavity', self.cavity),
('Dielectric', self.dielectric),
] + [('Interaction: ' + ia.subscript, ia) for ia in self.interactions]:
obj.estimate_memory(solvation.subnode(name))
def __init__(
self,
# solvation related arguments:
cavity,
dielectric,
interactions,
# RealSpaceHamiltonian arguments:
gd,
finegd,
nspins,
collinear,
setups,
timer,
xc,
world,
redistributor,
vext=None,
psolver=None,
stencil=3):
"""Constructor of SolvationRealSpaceHamiltonian class.
Additional arguments not present in RealSpaceHamiltonian:
cavity -- A Cavity instance.
dielectric -- A Dielectric instance.
interactions -- A list of Interaction instances.
"""
self.cavity = cavity
self.dielectric = dielectric
self.interactions = interactions
cavity.set_grid_descriptor(finegd)
dielectric.set_grid_descriptor(finegd)
for ia in interactions:
ia.set_grid_descriptor(finegd)
if psolver is None:
psolver = WeightedFDPoissonSolver()
psolver.set_dielectric(self.dielectric)
self.gradient = None
RealSpaceHamiltonian.__init__(self,
gd,
finegd,
nspins,
collinear,
setups,
timer,
xc,
world,
vext=vext,
psolver=psolver,
stencil=stencil,
redistributor=redistributor)
for ia in interactions:
setattr(self, 'e_' + ia.subscript, None)
self.new_atoms = None
self.vt_ia_g = None
self.e_el_free = None
self.e_el_extrapolated = None
def initialize(self):
self.gradient = [
Gradient(self.finegd, i, 1.0, self.poisson.nn) for i in (0, 1, 2)
]
self.vt_ia_g = self.finegd.zeros()
self.cavity.allocate()
self.dielectric.allocate()
for ia in self.interactions:
ia.allocate()
RealSpaceHamiltonian.initialize(self)
def summary(self, fermilevel, log):
self.cavity.summary(log)
log()
log('Solvation Energy Contributions:')
for ia in self.interactions:
E = Hartree * getattr(self, 'e_' + ia.subscript)
log('%-14s %+11.6f' % (ia.subscript + ':', E))
E_el_free = Hartree * self.e_el_free
E_el_extrapolated = Hartree * self.e_el_extrapolated
log('%-14s %+11.6f' % ('el (free):', E_el_free))
log('%-14s %+11.6f' % ('el (extrpol.):', E_el_extrapolated))
log('el (free) is composed of:')
RealSpaceHamiltonian.summary(self, fermilevel, log)
class UTHamiltonianFunctionSetup(UTLocalizedFunctionSetup):
__doc__ = UTLocalizedFunctionSetup.__doc__ + """
Atomic hamiltonian matrices are distributed over domains."""
def setUp(self):
UTLocalizedFunctionSetup.setUp(self)
self.finegd = self.gd.refine()
self.hamiltonian = RealSpaceHamiltonian(
self.gd, self.finegd, self.nspins,
self.setups, self.timer,
xc, p.external, True,
p.poissonsolver, p.stencils[1])
self.hamiltonian.dH_asp = {}
self.hamiltonian.rank_a = self.rank0_a
self.allocate(self.hamiltonian.dH_asp, self.hamiltonian.rank_a)
assert self.allocated
for a, dH_sp in self.hamiltonian.dH_asp.items():
ni = self.setups[a].ni
for s, dH_p in enumerate(dH_sp):
dH_p[:] = 1e9 * self.kd_old.comm.rank + 1e6 * self.bd.comm.rank \
+ 1e3 * s + np.arange(ni * (ni + 1) // 2, dtype=float)
def tearDown(self):
del self.hamiltonian
UTLocalizedFunctionSetup.tearDown(self)
# =================================
def test_initial_consistency(self):
self.update_references(self.hamiltonian.dH_asp, self.hamiltonian.rank_a)
self.check_values(self.hamiltonian.dH_asp, self.hamiltonian.rank_a)
def test_redistribution_to_domains(self):
self.update_references(self.hamiltonian.dH_asp, self.hamiltonian.rank_a)
spos_ac = self.atoms.get_scaled_positions() % 1.0
rank_a = self.gd.get_ranks_from_positions(spos_ac)
self.hamiltonian.set_positions(spos_ac, rank_a)
self.check_values(self.hamiltonian.dH_asp, self.hamiltonian.rank_a)
def test_redistribution_to_same(self):
self.update_references(self.hamiltonian.dH_asp, self.hamiltonian.rank_a)
spos_ac = self.atoms.get_scaled_positions() % 1.0
rank_a = self.gd.get_ranks_from_positions(spos_ac)
self.hamiltonian.set_positions(spos_ac, rank_a)
self.hamiltonian.set_positions(spos_ac, rank_a)
self.check_values(self.hamiltonian.dH_asp, self.hamiltonian.rank_a)
def update_pseudo_potential(self, density):
ret = RealSpaceHamiltonian.update_pseudo_potential(self, density)
if not self.cavity.depends_on_el_density:
return ret
del_g_del_n_g = self.cavity.del_g_del_n_g
# XXX optimize numerics
del_eps_del_g_g = self.dielectric.del_eps_del_g_g
Veps = -1. / (8. * np.pi) * del_eps_del_g_g * del_g_del_n_g
Veps *= self.grad_squared(self.vHt_g)
for vt_g in self.vt_sg:
vt_g += Veps
return ret
def create_hamiltonian(self, realspace, mode, xc):
dens = self.density
kwargs = dict(gd=dens.gd,
finegd=dens.finegd,
nspins=dens.nspins,
collinear=dens.collinear,
setups=dens.setups,
timer=self.timer,
xc=xc,
world=self.world,
redistributor=dens.redistributor,
vext=self.parameters.external,
psolver=self.parameters.poissonsolver)
if realspace:
self.hamiltonian = RealSpaceHamiltonian(stencil=mode.interpolation,
**kwargs)
xc.set_grid_descriptor(self.hamiltonian.finegd)
else:
# This code will work if dens.redistributor uses
# ordinary density.gd as aux_gd
gd = dens.finegd
xc_redist = None
if self.parallel['augment_grids']:
from gpaw.grid_descriptor import BadGridError
try:
aux_gd = gd.new_descriptor(comm=self.world)
except BadGridError as err:
import warnings
warnings.warn('Ignoring augment_grids: {}'.format(err))
else:
bcast_comm = dens.redistributor.broadcast_comm
xc_redist = GridRedistributor(self.world, bcast_comm, gd,
aux_gd)
self.hamiltonian = pw.ReciprocalSpaceHamiltonian(
pd2=dens.pd2,
pd3=dens.pd3,
realpbc_c=self.atoms.pbc,
xc_redistributor=xc_redist,
**kwargs)
xc.set_grid_descriptor(self.hamiltonian.xc_gd)
self.hamiltonian.soc = self.parameters.experimental.get('soc')
self.log(self.hamiltonian, '\n')
def calculate_forces(self, dens, F_av):
# XXX reorganize
self.el_force_correction(dens, F_av)
for ia in self.interactions:
if self.cavity.depends_on_atomic_positions:
for a, F_v in enumerate(F_av):
del_g_del_r_vg = self.cavity.get_del_r_vg(a, dens)
for v in (0, 1, 2):
F_v[v] -= self.finegd.integrate(ia.delta_E_delta_g_g *
del_g_del_r_vg[v],
global_integral=False)
if ia.depends_on_atomic_positions:
for a, F_v in enumerate(F_av):
del_E_del_r_vg = ia.get_del_r_vg(a, dens)
for v in (0, 1, 2):
F_v[v] -= self.finegd.integrate(del_E_del_r_vg[v],
global_integral=False)
return RealSpaceHamiltonian.calculate_forces(self, dens, F_av)
def setUp(self):
UTLocalizedFunctionSetup.setUp(self)
self.finegd = self.gd.refine()
self.hamiltonian = RealSpaceHamiltonian(
self.gd, self.finegd, self.nspins,
self.setups, self.timer,
xc, p.external, True,
p.poissonsolver, p.stencils[1])
self.hamiltonian.dH_asp = {}
self.hamiltonian.rank_a = self.rank0_a
self.allocate(self.hamiltonian.dH_asp, self.hamiltonian.rank_a)
assert self.allocated
for a, dH_sp in self.hamiltonian.dH_asp.items():
ni = self.setups[a].ni
for s, dH_p in enumerate(dH_sp):
dH_p[:] = 1e9 * self.kd_old.comm.rank + 1e6 * self.bd.comm.rank \
+ 1e3 * s + np.arange(ni * (ni + 1) // 2, dtype=float)
def create_hamiltonian(self, realspace, mode, xc):
dens = self.density
kwargs = dict(gd=dens.gd,
finegd=dens.finegd,
nspins=dens.nspins,
setups=dens.setups,
timer=self.timer,
xc=xc,
world=self.world,
redistributor=dens.redistributor,
vext=self.parameters.external,
psolver=self.parameters.poissonsolver)
if realspace:
self.hamiltonian = RealSpaceHamiltonian(stencil=mode.interpolation,
**kwargs)
xc.set_grid_descriptor(self.hamiltonian.finegd) # XXX
else:
self.hamiltonian = pw.ReciprocalSpaceHamiltonian(
pd2=dens.pd2, pd3=dens.pd3, realpbc_c=self.atoms.pbc, **kwargs)
xc.set_grid_descriptor(dens.xc_redistributor.aux_gd) # XXX
self.log(self.hamiltonian, '\n')
def __str__(self):
s = RealSpaceHamiltonian.__str__(self) + '\n'
s += ' Solvation:\n'
components = [self.cavity, self.dielectric] + self.interactions
s += ''.join([indent(str(c), 2) for c in components])
return s
class PAW(PAWTextOutput):
"""This is the main calculation object for doing a PAW calculation."""
def __init__(self,
filename=None,
timer=None,
read_projections=True,
**kwargs):
"""ASE-calculator interface.
The following parameters can be used: nbands, xc, kpts,
spinpol, gpts, h, charge, symmetry, width, mixer,
hund, lmax, fixdensity, convergence, txt, parallel,
communicator, dtype, softgauss and stencils.
If you don't specify any parameters, you will get:
Defaults: neutrally charged, LDA, gamma-point calculation, a
reasonable grid-spacing, zero Kelvin electronic temperature,
and the number of bands will be equal to the number of atomic
orbitals present in the setups. Only occupied bands are used
in the convergence decision. The calculation will be
spin-polarized if and only if one or more of the atoms have
non-zero magnetic moments. Text output will be written to
standard output.
For a non-gamma point calculation, the electronic temperature
will be 0.1 eV (energies are extrapolated to zero Kelvin) and
all symmetries will be used to reduce the number of
**k**-points."""
PAWTextOutput.__init__(self)
self.grid_descriptor_class = GridDescriptor
self.input_parameters = InputParameters()
if timer is None:
self.timer = Timer()
else:
self.timer = timer
self.scf = None
self.forces = ForceCalculator(self.timer)
self.stress_vv = None
self.dipole_v = None
self.magmom_av = None
self.wfs = EmptyWaveFunctions()
self.occupations = None
self.density = None
self.hamiltonian = None
self.atoms = None
self.iter = 0
self.initialized = False
self.nbands_parallelization_adjustment = None # Somehow avoid this?
# Possibly read GPAW keyword arguments from file:
if filename is not None and filename.endswith('.gkw'):
from gpaw.utilities.kwargs import load
parameters = load(filename)
parameters.update(kwargs)
kwargs = parameters
filename = None # XXX
if filename is not None:
comm = kwargs.get('communicator', mpi.world)
reader = gpaw.io.open(filename, 'r', comm)
self.atoms = gpaw.io.read_atoms(reader)
par = self.input_parameters
par.read(reader)
# _changed_keywords contains those keywords that have been
# changed by set() since last time initialize() was called.
self._changed_keywords = set()
self.set(**kwargs)
# Here in the beginning, effectively every keyword has been changed.
self._changed_keywords.update(self.input_parameters)
if filename is not None:
# Setups are not saved in the file if the setups were not loaded
# *from* files in the first place
if par.setups is None:
if par.idiotproof:
raise RuntimeError('Setups not specified in file. Use '
'idiotproof=False to proceed anyway.')
else:
par.setups = {None: 'paw'}
if par.basis is None:
if par.idiotproof:
raise RuntimeError('Basis not specified in file. Use '
'idiotproof=False to proceed anyway.')
else:
par.basis = {}
self.initialize()
self.read(reader, read_projections)
if self.hamiltonian.xc.type == 'GLLB':
self.occupations.calculate(self.wfs)
self.print_cell_and_parameters()
self.observers = []
def read(self, reader, read_projections=True):
gpaw.io.read(self, reader, read_projections)
def set(self, **kwargs):
"""Change parameters for calculator.
Examples::
calc.set(xc='PBE')
calc.set(nbands=20, kpts=(4, 1, 1))
"""
p = self.input_parameters
self._changed_keywords.update(kwargs)
if (kwargs.get('h') is not None) and (kwargs.get('gpts') is not None):
raise TypeError("""You can't use both "gpts" and "h"!""")
if 'h' in kwargs:
p['gpts'] = None
if 'gpts' in kwargs:
p['h'] = None
# Special treatment for dictionary parameters:
for name in ['convergence', 'parallel']:
if kwargs.get(name) is not None:
tmp = p[name]
for key in kwargs[name]:
if key not in tmp:
raise KeyError('Unknown subparameter "%s" in '
'dictionary parameter "%s"' %
(key, name))
tmp.update(kwargs[name])
kwargs[name] = tmp
self.initialized = False
for key in kwargs:
if key == 'basis' and str(p['mode']) == 'fd': # umm what about PW?
# The second criterion seems buggy, will not touch it. -Ask
continue
if key == 'eigensolver':
self.wfs.set_eigensolver(None)
if key in [
'fixmom', 'mixer', 'verbose', 'txt', 'hund', 'random',
'eigensolver', 'idiotproof', 'notify'
]:
continue
if key in ['convergence', 'fixdensity', 'maxiter']:
self.scf = None
continue
# More drastic changes:
self.scf = None
self.wfs.set_orthonormalized(False)
if key in [
'lmax', 'width', 'stencils', 'external', 'xc',
'poissonsolver'
]:
self.hamiltonian = None
self.occupations = None
elif key in ['occupations']:
self.occupations = None
elif key in ['charge']:
self.hamiltonian = None
self.density = None
self.wfs = EmptyWaveFunctions()
self.occupations = None
elif key in ['kpts', 'nbands', 'usesymm', 'symmetry']:
self.wfs = EmptyWaveFunctions()
self.occupations = None
elif key in [
'h', 'gpts', 'setups', 'spinpol', 'realspace', 'parallel',
'communicator', 'dtype', 'mode'
]:
self.density = None
self.occupations = None
self.hamiltonian = None
self.wfs = EmptyWaveFunctions()
elif key in ['basis']:
self.wfs = EmptyWaveFunctions()
elif key in ['parsize', 'parsize_bands', 'parstride_bands']:
name = {
'parsize': 'domain',
'parsize_bands': 'band',
'parstride_bands': 'stridebands'
}[key]
raise DeprecationWarning(
'Keyword argument has been moved ' +
"to the 'parallel' dictionary keyword under '%s'." % name)
else:
raise TypeError("Unknown keyword argument: '%s'" % key)
p.update(kwargs)
def calculate(self,
atoms=None,
converge=False,
force_call_to_set_positions=False):
"""Update PAW calculaton if needed.
Returns True/False whether a calculation was performed or not."""
self.timer.start('Initialization')
if atoms is None:
atoms = self.atoms
if self.atoms is None:
# First time:
self.initialize(atoms)
self.set_positions(atoms)
elif (len(atoms) != len(self.atoms)
or (atoms.get_atomic_numbers() !=
self.atoms.get_atomic_numbers()).any()
or (atoms.get_initial_magnetic_moments() !=
self.atoms.get_initial_magnetic_moments()).any()
or (atoms.get_cell() != self.atoms.get_cell()).any()
or (atoms.get_pbc() != self.atoms.get_pbc()).any()):
# Drastic changes:
self.wfs = EmptyWaveFunctions()
self.occupations = None
self.density = None
self.hamiltonian = None
self.scf = None
self.initialize(atoms)
self.set_positions(atoms)
elif not self.initialized:
self.initialize(atoms)
self.set_positions(atoms)
elif (atoms.get_positions() != self.atoms.get_positions()).any():
self.density.reset()
self.set_positions(atoms)
elif not self.scf.converged:
# Do not call scf.check_convergence() here as it overwrites
# scf.converged, and setting scf.converged is the only
# 'practical' way for a user to force the calculation to proceed
self.set_positions(atoms)
elif force_call_to_set_positions:
self.set_positions(atoms)
self.timer.stop('Initialization')
if self.scf.converged:
return False
else:
self.print_cell_and_parameters()
self.timer.start('SCF-cycle')
for iter in self.scf.run(self.wfs, self.hamiltonian, self.density,
self.occupations, self.forces):
self.iter = iter
self.call_observers(iter)
self.print_iteration(iter)
self.timer.stop('SCF-cycle')
if self.scf.converged:
self.call_observers(iter, final=True)
self.print_converged(iter)
elif converge:
self.txt.write(oops)
raise KohnShamConvergenceError(
'Did not converge! See text output for help.')
return True
def initialize_positions(self, atoms=None):
"""Update the positions of the atoms."""
if atoms is None:
atoms = self.atoms
else:
# Save the state of the atoms:
self.atoms = atoms.copy()
self.check_atoms()
spos_ac = atoms.get_scaled_positions() % 1.0
self.wfs.set_positions(spos_ac)
self.density.set_positions(spos_ac, self.wfs.rank_a)
self.hamiltonian.set_positions(spos_ac, self.wfs.rank_a)
return spos_ac
def set_positions(self, atoms=None):
"""Update the positions of the atoms and initialize wave functions."""
spos_ac = self.initialize_positions(atoms)
self.wfs.initialize(self.density, self.hamiltonian, spos_ac)
self.wfs.eigensolver.reset()
self.scf.reset()
self.forces.reset()
self.stress_vv = None
self.dipole_v = None
self.magmom_av = None
self.print_positions()
def initialize(self, atoms=None):
"""Inexpensive initialization."""
if atoms is None:
atoms = self.atoms
else:
# Save the state of the atoms:
self.atoms = atoms.copy()
par = self.input_parameters
world = par.communicator
if world is None:
world = mpi.world
elif hasattr(world, 'new_communicator'):
# Check for whether object has correct type already
#
# Using isinstance() is complicated because of all the
# combinations, serial/parallel/debug...
pass
else:
# world should be a list of ranks:
world = mpi.world.new_communicator(np.asarray(world))
self.wfs.world = world
if 'txt' in self._changed_keywords:
self.set_txt(par.txt)
self.verbose = par.verbose
natoms = len(atoms)
cell_cv = atoms.get_cell() / Bohr
pbc_c = atoms.get_pbc()
Z_a = atoms.get_atomic_numbers()
magmom_av = atoms.get_initial_magnetic_moments()
self.check_atoms()
# Generate new xc functional only when it is reset by set
# XXX sounds like this should use the _changed_keywords dictionary.
if self.hamiltonian is None or self.hamiltonian.xc is None:
if isinstance(par.xc, str):
xc = XC(par.xc)
else:
xc = par.xc
else:
xc = self.hamiltonian.xc
mode = par.mode
if mode == 'fd':
mode = FD()
elif mode == 'pw':
mode = pw.PW()
elif mode == 'lcao':
mode = LCAO()
else:
assert hasattr(mode, 'name'), str(mode)
if xc.orbital_dependent and mode.name == 'lcao':
raise NotImplementedError('LCAO mode does not support '
'orbital-dependent XC functionals.')
if par.realspace is None:
realspace = (mode.name != 'pw')
else:
realspace = par.realspace
if mode.name == 'pw':
assert not realspace
if par.filter is None and mode.name != 'pw':
gamma = 1.6
if par.gpts is not None:
h = ((np.linalg.inv(cell_cv)**2).sum(0)**-0.5 / par.gpts).max()
else:
h = (par.h or 0.2) / Bohr
def filter(rgd, rcut, f_r, l=0):
gcut = np.pi / h - 2 / rcut / gamma
f_r[:] = rgd.filter(f_r, rcut * gamma, gcut, l)
else:
filter = par.filter
setups = Setups(Z_a, par.setups, par.basis, par.lmax, xc, filter,
world)
if magmom_av.ndim == 1:
collinear = True
magmom_av, magmom_a = np.zeros((natoms, 3)), magmom_av
magmom_av[:, 2] = magmom_a
else:
collinear = False
magnetic = magmom_av.any()
spinpol = par.spinpol
if par.hund:
if natoms != 1:
raise ValueError('hund=True arg only valid for single atoms!')
spinpol = True
magmom_av[0] = (0, 0, setups[0].get_hunds_rule_moment(par.charge))
if spinpol is None:
spinpol = magnetic
elif magnetic and not spinpol:
raise ValueError('Non-zero initial magnetic moment for a ' +
'spin-paired calculation!')
if collinear:
nspins = 1 + int(spinpol)
ncomp = 1
else:
nspins = 1
ncomp = 2
if par.usesymm != 'default':
warnings.warn('Use "symmetry" keyword instead of ' +
'"usesymm" keyword')
par.symmetry = usesymm2symmetry(par.usesymm)
symm = par.symmetry
if symm == 'off':
symm = {'point_group': False, 'time_reversal': False}
bzkpts_kc = kpts2ndarray(par.kpts, self.atoms)
kd = KPointDescriptor(bzkpts_kc, nspins, collinear)
m_av = magmom_av.round(decimals=3) # round off
id_a = zip(setups.id_a, *m_av.T)
symmetry = Symmetry(id_a, cell_cv, atoms.pbc, **symm)
kd.set_symmetry(atoms, symmetry, comm=world)
setups.set_symmetry(symmetry)
if par.gpts is not None:
N_c = np.array(par.gpts)
else:
h = par.h
if h is not None:
h /= Bohr
N_c = get_number_of_grid_points(cell_cv, h, mode, realspace,
kd.symmetry)
symmetry.check_grid(N_c)
width = par.width
if width is None:
if pbc_c.any():
width = 0.1 # eV
else:
width = 0.0
else:
assert par.occupations is None
if hasattr(self, 'time') or par.dtype == complex:
dtype = complex
else:
if kd.gamma:
dtype = float
else:
dtype = complex
nao = setups.nao
nvalence = setups.nvalence - par.charge
M_v = magmom_av.sum(0)
M = np.dot(M_v, M_v)**0.5
nbands = par.nbands
orbital_free = any(setup.orbital_free for setup in setups)
if orbital_free:
nbands = 1
if isinstance(nbands, basestring):
if nbands[-1] == '%':
basebands = int(nvalence + M + 0.5) // 2
nbands = int((float(nbands[:-1]) / 100) * basebands)
else:
raise ValueError('Integer Expected: Only use a string '
'if giving a percentage of occupied bands')
if nbands is None:
nbands = 0
for setup in setups:
nbands_from_atom = setup.get_default_nbands()
# Any obscure setup errors?
if nbands_from_atom < -(-setup.Nv // 2):
raise ValueError('Bad setup: This setup requests %d'
' bands but has %d electrons.' %
(nbands_from_atom, setup.Nv))
nbands += nbands_from_atom
nbands = min(nao, nbands)
elif nbands > nao and mode.name == 'lcao':
raise ValueError('Too many bands for LCAO calculation: '
'%d bands and only %d atomic orbitals!' %
(nbands, nao))
if nvalence < 0:
raise ValueError(
'Charge %f is not possible - not enough valence electrons' %
par.charge)
if nbands <= 0:
nbands = int(nvalence + M + 0.5) // 2 + (-nbands)
if nvalence > 2 * nbands and not orbital_free:
raise ValueError('Too few bands! Electrons: %f, bands: %d' %
(nvalence, nbands))
nbands *= ncomp
if par.width is not None:
self.text('**NOTE**: please start using '
'occupations=FermiDirac(width).')
if par.fixmom:
self.text('**NOTE**: please start using '
'occupations=FermiDirac(width, fixmagmom=True).')
if self.occupations is None:
if par.occupations is None:
# Create object for occupation numbers:
if orbital_free:
width = 0.0 # even for PBC
self.occupations = occupations.TFOccupations(
width, par.fixmom)
else:
self.occupations = occupations.FermiDirac(
width, par.fixmom)
else:
self.occupations = par.occupations
# If occupation numbers are changed, and we have wave functions,
# recalculate the occupation numbers
if self.wfs is not None and not isinstance(self.wfs,
EmptyWaveFunctions):
self.occupations.calculate(self.wfs)
self.occupations.magmom = M_v[2]
cc = par.convergence
if mode.name == 'lcao':
niter_fixdensity = 0
else:
niter_fixdensity = None
if self.scf is None:
force_crit = cc['forces']
if force_crit is not None:
force_crit /= Hartree / Bohr
self.scf = SCFLoop(cc['eigenstates'] / Hartree**2 * nvalence,
cc['energy'] / Hartree * max(nvalence, 1),
cc['density'] * nvalence, par.maxiter,
par.fixdensity, niter_fixdensity, force_crit)
parsize_kpt = par.parallel['kpt']
parsize_domain = par.parallel['domain']
parsize_bands = par.parallel['band']
if not realspace:
pbc_c = np.ones(3, bool)
if not self.wfs:
if parsize_domain == 'domain only': # XXX this was silly!
parsize_domain = world.size
parallelization = mpi.Parallelization(world, nspins * kd.nibzkpts)
ndomains = None
if parsize_domain is not None:
ndomains = np.prod(parsize_domain)
if mode.name == 'pw':
if ndomains > 1:
raise ValueError('Planewave mode does not support '
'domain decomposition.')
ndomains = 1
parallelization.set(kpt=parsize_kpt,
domain=ndomains,
band=parsize_bands)
comms = parallelization.build_communicators()
domain_comm = comms['d']
kpt_comm = comms['k']
band_comm = comms['b']
kptband_comm = comms['D']
domainband_comm = comms['K']
self.comms = comms
kd.set_communicator(kpt_comm)
parstride_bands = par.parallel['stridebands']
# Unfortunately we need to remember that we adjusted the
# number of bands so we can print a warning if it differs
# from the number specified by the user. (The number can
# be inferred from the input parameters, but it's tricky
# because we allow negative numbers)
self.nbands_parallelization_adjustment = -nbands % band_comm.size
nbands += self.nbands_parallelization_adjustment
# I would like to give the following error message, but apparently
# there are cases, e.g. gpaw/test/gw_ppa.py, which involve
# nbands > nao and are supposed to work that way.
#if nbands > nao:
# raise ValueError('Number of bands %d adjusted for band '
# 'parallelization %d exceeds number of atomic '
# 'orbitals %d. This problem can be fixed '
# 'by reducing the number of bands a bit.'
# % (nbands, band_comm.size, nao))
bd = BandDescriptor(nbands, band_comm, parstride_bands)
if (self.density is not None
and self.density.gd.comm.size != domain_comm.size):
# Domain decomposition has changed, so we need to
# reinitialize density and hamiltonian:
if par.fixdensity:
raise RuntimeError(
'Density reinitialization conflict ' +
'with "fixdensity" - specify domain decomposition.')
self.density = None
self.hamiltonian = None
# Construct grid descriptor for coarse grids for wave functions:
gd = self.grid_descriptor_class(N_c, cell_cv, pbc_c, domain_comm,
parsize_domain)
# do k-point analysis here? XXX
args = (gd, nvalence, setups, bd, dtype, world, kd, kptband_comm,
self.timer)
if par.parallel['sl_auto']:
# Choose scalapack parallelization automatically
for key, val in par.parallel.items():
if (key.startswith('sl_') and key != 'sl_auto'
and val is not None):
raise ValueError("Cannot use 'sl_auto' together "
"with '%s'" % key)
max_scalapack_cpus = bd.comm.size * gd.comm.size
nprow = max_scalapack_cpus
npcol = 1
# Get a sort of reasonable number of columns/rows
while npcol < nprow and nprow % 2 == 0:
npcol *= 2
nprow //= 2
assert npcol * nprow == max_scalapack_cpus
# ScaLAPACK creates trouble if there aren't at least a few
# whole blocks; choose block size so there will always be
# several blocks. This will crash for small test systems,
# but so will ScaLAPACK in any case
blocksize = min(-(-nbands // 4), 64)
sl_default = (nprow, npcol, blocksize)
else:
sl_default = par.parallel['sl_default']
if mode.name == 'lcao':
# Layouts used for general diagonalizer
sl_lcao = par.parallel['sl_lcao']
if sl_lcao is None:
sl_lcao = sl_default
lcaoksl = get_KohnSham_layouts(sl_lcao,
'lcao',
gd,
bd,
domainband_comm,
dtype,
nao=nao,
timer=self.timer)
self.wfs = mode(collinear, lcaoksl, *args)
elif mode.name == 'fd' or mode.name == 'pw':
# buffer_size keyword only relevant for fdpw
buffer_size = par.parallel['buffer_size']
# Layouts used for diagonalizer
sl_diagonalize = par.parallel['sl_diagonalize']
if sl_diagonalize is None:
sl_diagonalize = sl_default
diagksl = get_KohnSham_layouts(
sl_diagonalize,
'fd', # XXX
# choice of key 'fd' not so nice
gd,
bd,
domainband_comm,
dtype,
buffer_size=buffer_size,
timer=self.timer)
# Layouts used for orthonormalizer
sl_inverse_cholesky = par.parallel['sl_inverse_cholesky']
if sl_inverse_cholesky is None:
sl_inverse_cholesky = sl_default
if sl_inverse_cholesky != sl_diagonalize:
message = 'sl_inverse_cholesky != sl_diagonalize ' \
'is not implemented.'
raise NotImplementedError(message)
orthoksl = get_KohnSham_layouts(sl_inverse_cholesky,
'fd',
gd,
bd,
domainband_comm,
dtype,
buffer_size=buffer_size,
timer=self.timer)
# Use (at most) all available LCAO for initialization
lcaonbands = min(nbands, nao)
try:
lcaobd = BandDescriptor(lcaonbands, band_comm,
parstride_bands)
except RuntimeError:
initksl = None
else:
# Layouts used for general diagonalizer
# (LCAO initialization)
sl_lcao = par.parallel['sl_lcao']
if sl_lcao is None:
sl_lcao = sl_default
initksl = get_KohnSham_layouts(sl_lcao,
'lcao',
gd,
lcaobd,
domainband_comm,
dtype,
nao=nao,
timer=self.timer)
if hasattr(self, 'time'):
assert mode.name == 'fd'
from gpaw.tddft import TimeDependentWaveFunctions
self.wfs = TimeDependentWaveFunctions(
par.stencils[0], diagksl, orthoksl, initksl, gd,
nvalence, setups, bd, world, kd, kptband_comm,
self.timer)
elif mode.name == 'fd':
self.wfs = mode(par.stencils[0], diagksl, orthoksl,
initksl, *args)
else:
assert mode.name == 'pw'
self.wfs = mode(diagksl, orthoksl, initksl, *args)
else:
self.wfs = mode(self, *args)
else:
self.wfs.set_setups(setups)
if not self.wfs.eigensolver:
# Number of bands to converge:
nbands_converge = cc['bands']
if nbands_converge == 'all':
nbands_converge = nbands
elif nbands_converge != 'occupied':
assert isinstance(nbands_converge, int)
if nbands_converge < 0:
nbands_converge += nbands
eigensolver = get_eigensolver(par.eigensolver, mode,
par.convergence)
eigensolver.nbands_converge = nbands_converge
# XXX Eigensolver class doesn't define an nbands_converge property
if isinstance(xc, SIC):
eigensolver.blocksize = 1
self.wfs.set_eigensolver(eigensolver)
if self.density is None:
gd = self.wfs.gd
if par.stencils[1] != 9:
# Construct grid descriptor for fine grids for densities
# and potentials:
finegd = gd.refine()
else:
# Special case (use only coarse grid):
finegd = gd
if realspace:
self.density = RealSpaceDensity(
gd, finegd, nspins, par.charge + setups.core_charge,
collinear, par.stencils[1])
else:
self.density = pw.ReciprocalSpaceDensity(
gd, finegd, nspins, par.charge + setups.core_charge,
collinear)
self.density.initialize(setups, self.timer, magmom_av, par.hund)
self.density.set_mixer(par.mixer)
if self.hamiltonian is None:
gd, finegd = self.density.gd, self.density.finegd
if realspace:
self.hamiltonian = RealSpaceHamiltonian(
gd, finegd, nspins, setups, self.timer, xc, world,
self.wfs.kptband_comm, par.external, collinear,
par.poissonsolver, par.stencils[1])
else:
self.hamiltonian = pw.ReciprocalSpaceHamiltonian(
gd, finegd, self.density.pd2, self.density.pd3, nspins,
setups, self.timer, xc, world, self.wfs.kptband_comm,
par.external, collinear)
xc.initialize(self.density, self.hamiltonian, self.wfs,
self.occupations)
self.text()
self.print_memory_estimate(self.txt, maxdepth=memory_estimate_depth)
self.txt.flush()
self.timer.print_info(self)
if dry_run:
self.dry_run()
if realspace and \
self.hamiltonian.poisson.get_description() == 'FDTD+TDDFT':
self.hamiltonian.poisson.set_density(self.density)
self.hamiltonian.poisson.print_messages(self.text)
self.txt.flush()
self.initialized = True
self._changed_keywords.clear()
def dry_run(self):
# Can be overridden like in gpaw.atom.atompaw
self.print_cell_and_parameters()
self.print_positions()
self.txt.flush()
raise SystemExit
def linearize_to_xc(self, newxc):
"""Linearize Hamiltonian to difference XC functional.
Used in real time TDDFT to perform calculations with various kernels.
"""
if isinstance(newxc, str):
newxc = XC(newxc)
self.txt.write('Linearizing xc-hamiltonian to ' + str(newxc))
newxc.initialize(self.density, self.hamiltonian, self.wfs,
self.occupations)
self.hamiltonian.linearize_to_xc(newxc, self.density)
def restore_state(self):
"""After restart, calculate fine density and poisson solution.
These are not initialized by default.
TODO: Is this really the most efficient way?
"""
spos_ac = self.atoms.get_scaled_positions() % 1.0
self.density.set_positions(spos_ac, self.wfs.rank_a)
self.density.interpolate_pseudo_density()
self.density.calculate_pseudo_charge()
self.hamiltonian.set_positions(spos_ac, self.wfs.rank_a)
self.hamiltonian.update(self.density)
def attach(self, function, n=1, *args, **kwargs):
"""Register observer function.
Call *function* using *args* and
*kwargs* as arguments.
If *n* is positive, then
*function* will be called every *n* iterations + the
final iteration if it would not be otherwise
If *n* is negative, then *function* will only be
called on iteration *abs(n)*.
If *n* is 0, then *function* will only be called
on convergence"""
try:
slf = function.im_self
except AttributeError:
pass
else:
if slf is self:
# function is a bound method of self. Store the name
# of the method and avoid circular reference:
function = function.im_func.func_name
self.observers.append((function, n, args, kwargs))
def call_observers(self, iter, final=False):
"""Call all registered callback functions."""
for function, n, args, kwargs in self.observers:
call = False
# Call every n iterations, including the last
if n > 0:
if ((iter % n) == 0) != final:
call = True
# Call only on iteration n
elif n < 0 and not final:
if iter == abs(n):
call = True
# Call only on convergence
elif n == 0 and final:
call = True
if call:
if isinstance(function, str):
function = getattr(self, function)
function(*args, **kwargs)
def get_reference_energy(self):
return self.wfs.setups.Eref * Hartree
def write(self, filename, mode='', cmr_params={}, **kwargs):
"""Write state to file.
use mode='all' to write the wave functions. cmr_params is a
dictionary that allows you to specify parameters for CMR
(Computational Materials Repository).
"""
self.timer.start('IO')
gpaw.io.write(self, filename, mode, cmr_params=cmr_params, **kwargs)
self.timer.stop('IO')
def get_myu(self, k, s):
"""Return my u corresponding to a certain kpoint and spin - or None"""
# very slow, but we are sure that we have it
for u in range(len(self.wfs.kpt_u)):
if self.wfs.kpt_u[u].k == k and self.wfs.kpt_u[u].s == s:
return u
return None
def get_homo_lumo(self):
"""Return H**O and LUMO eigenvalues."""
return self.occupations.get_homo_lumo(self.wfs) * Hartree
def estimate_memory(self, mem):
"""Estimate memory use of this object."""
for name, obj in [
('Density', self.density),
('Hamiltonian', self.hamiltonian),
('Wavefunctions', self.wfs),
]:
obj.estimate_memory(mem.subnode(name))
def print_memory_estimate(self, txt=None, maxdepth=-1):
"""Print estimated memory usage for PAW object and components.
maxdepth is the maximum nesting level of displayed components.
The PAW object must be initialize()'d, but needs not have large
arrays allocated."""
# NOTE. This should work with --dry-run=N
#
# However, the initial overhead estimate is wrong if this method
# is called within a real mpirun/gpaw-python context.
if txt is None:
txt = self.txt
txt.write('Memory estimate\n')
txt.write('---------------\n')
mem_init = maxrss() # initial overhead includes part of Hamiltonian!
txt.write('Process memory now: %.2f MiB\n' % (mem_init / 1024.0**2))
mem = MemNode('Calculator', 0)
try:
self.estimate_memory(mem)
except AttributeError as m:
txt.write('Attribute error: %r' % m)
txt.write('Some object probably lacks estimate_memory() method')
txt.write('Memory breakdown may be incomplete')
mem.calculate_size()
mem.write(txt, maxdepth=maxdepth)
def converge_wave_functions(self):
"""Converge the wave-functions if not present."""
if not self.wfs or not self.scf:
self.initialize()
else:
self.wfs.initialize_wave_functions_from_restart_file()
spos_ac = self.atoms.get_scaled_positions() % 1.0
self.wfs.set_positions(spos_ac)
no_wave_functions = (self.wfs.kpt_u[0].psit_nG is None)
converged = self.scf.check_convergence(self.density,
self.wfs.eigensolver, self.wfs,
self.hamiltonian, self.forces)
if no_wave_functions or not converged:
self.wfs.eigensolver.error = np.inf
self.scf.converged = False
# is the density ok ?
error = self.density.mixer.get_charge_sloshing()
criterion = (self.input_parameters['convergence']['density'] *
self.wfs.nvalence)
if error < criterion and not self.hamiltonian.xc.orbital_dependent:
self.scf.fix_density()
self.calculate()
def diagonalize_full_hamiltonian(self,
nbands=None,
scalapack=None,
expert=False):
self.wfs.diagonalize_full_hamiltonian(self.hamiltonian, self.atoms,
self.occupations, self.txt,
nbands, scalapack, expert)
def check_atoms(self):
"""Check that atoms objects are identical on all processors."""
if not mpi.compare_atoms(self.atoms, comm=self.wfs.world):
raise RuntimeError('Atoms objects on different processors ' +
'are not identical!')
def initialize(self, atoms=None):
"""Inexpensive initialization."""
if atoms is None:
atoms = self.atoms
else:
# Save the state of the atoms:
self.atoms = atoms.copy()
par = self.input_parameters
world = par.communicator
if world is None:
world = mpi.world
elif hasattr(world, 'new_communicator'):
# Check for whether object has correct type already
#
# Using isinstance() is complicated because of all the
# combinations, serial/parallel/debug...
pass
else:
# world should be a list of ranks:
world = mpi.world.new_communicator(np.asarray(world))
self.wfs.world = world
if 'txt' in self._changed_keywords:
self.set_txt(par.txt)
self.verbose = par.verbose
natoms = len(atoms)
cell_cv = atoms.get_cell() / Bohr
pbc_c = atoms.get_pbc()
Z_a = atoms.get_atomic_numbers()
magmom_av = atoms.get_initial_magnetic_moments()
self.check_atoms()
# Generate new xc functional only when it is reset by set
# XXX sounds like this should use the _changed_keywords dictionary.
if self.hamiltonian is None or self.hamiltonian.xc is None:
if isinstance(par.xc, str):
xc = XC(par.xc)
else:
xc = par.xc
else:
xc = self.hamiltonian.xc
mode = par.mode
if mode == 'fd':
mode = FD()
elif mode == 'pw':
mode = pw.PW()
elif mode == 'lcao':
mode = LCAO()
else:
assert hasattr(mode, 'name'), str(mode)
if xc.orbital_dependent and mode.name == 'lcao':
raise NotImplementedError('LCAO mode does not support '
'orbital-dependent XC functionals.')
if par.realspace is None:
realspace = (mode.name != 'pw')
else:
realspace = par.realspace
if mode.name == 'pw':
assert not realspace
if par.filter is None and mode.name != 'pw':
gamma = 1.6
if par.gpts is not None:
h = ((np.linalg.inv(cell_cv)**2).sum(0)**-0.5 / par.gpts).max()
else:
h = (par.h or 0.2) / Bohr
def filter(rgd, rcut, f_r, l=0):
gcut = np.pi / h - 2 / rcut / gamma
f_r[:] = rgd.filter(f_r, rcut * gamma, gcut, l)
else:
filter = par.filter
setups = Setups(Z_a, par.setups, par.basis, par.lmax, xc, filter,
world)
if magmom_av.ndim == 1:
collinear = True
magmom_av, magmom_a = np.zeros((natoms, 3)), magmom_av
magmom_av[:, 2] = magmom_a
else:
collinear = False
magnetic = magmom_av.any()
spinpol = par.spinpol
if par.hund:
if natoms != 1:
raise ValueError('hund=True arg only valid for single atoms!')
spinpol = True
magmom_av[0] = (0, 0, setups[0].get_hunds_rule_moment(par.charge))
if spinpol is None:
spinpol = magnetic
elif magnetic and not spinpol:
raise ValueError('Non-zero initial magnetic moment for a ' +
'spin-paired calculation!')
if collinear:
nspins = 1 + int(spinpol)
ncomp = 1
else:
nspins = 1
ncomp = 2
if par.usesymm != 'default':
warnings.warn('Use "symmetry" keyword instead of ' +
'"usesymm" keyword')
par.symmetry = usesymm2symmetry(par.usesymm)
symm = par.symmetry
if symm == 'off':
symm = {'point_group': False, 'time_reversal': False}
bzkpts_kc = kpts2ndarray(par.kpts, self.atoms)
kd = KPointDescriptor(bzkpts_kc, nspins, collinear)
m_av = magmom_av.round(decimals=3) # round off
id_a = zip(setups.id_a, *m_av.T)
symmetry = Symmetry(id_a, cell_cv, atoms.pbc, **symm)
kd.set_symmetry(atoms, symmetry, comm=world)
setups.set_symmetry(symmetry)
if par.gpts is not None:
N_c = np.array(par.gpts)
else:
h = par.h
if h is not None:
h /= Bohr
N_c = get_number_of_grid_points(cell_cv, h, mode, realspace,
kd.symmetry)
symmetry.check_grid(N_c)
width = par.width
if width is None:
if pbc_c.any():
width = 0.1 # eV
else:
width = 0.0
else:
assert par.occupations is None
if hasattr(self, 'time') or par.dtype == complex:
dtype = complex
else:
if kd.gamma:
dtype = float
else:
dtype = complex
nao = setups.nao
nvalence = setups.nvalence - par.charge
M_v = magmom_av.sum(0)
M = np.dot(M_v, M_v)**0.5
nbands = par.nbands
orbital_free = any(setup.orbital_free for setup in setups)
if orbital_free:
nbands = 1
if isinstance(nbands, basestring):
if nbands[-1] == '%':
basebands = int(nvalence + M + 0.5) // 2
nbands = int((float(nbands[:-1]) / 100) * basebands)
else:
raise ValueError('Integer Expected: Only use a string '
'if giving a percentage of occupied bands')
if nbands is None:
nbands = 0
for setup in setups:
nbands_from_atom = setup.get_default_nbands()
# Any obscure setup errors?
if nbands_from_atom < -(-setup.Nv // 2):
raise ValueError('Bad setup: This setup requests %d'
' bands but has %d electrons.' %
(nbands_from_atom, setup.Nv))
nbands += nbands_from_atom
nbands = min(nao, nbands)
elif nbands > nao and mode.name == 'lcao':
raise ValueError('Too many bands for LCAO calculation: '
'%d bands and only %d atomic orbitals!' %
(nbands, nao))
if nvalence < 0:
raise ValueError(
'Charge %f is not possible - not enough valence electrons' %
par.charge)
if nbands <= 0:
nbands = int(nvalence + M + 0.5) // 2 + (-nbands)
if nvalence > 2 * nbands and not orbital_free:
raise ValueError('Too few bands! Electrons: %f, bands: %d' %
(nvalence, nbands))
nbands *= ncomp
if par.width is not None:
self.text('**NOTE**: please start using '
'occupations=FermiDirac(width).')
if par.fixmom:
self.text('**NOTE**: please start using '
'occupations=FermiDirac(width, fixmagmom=True).')
if self.occupations is None:
if par.occupations is None:
# Create object for occupation numbers:
if orbital_free:
width = 0.0 # even for PBC
self.occupations = occupations.TFOccupations(
width, par.fixmom)
else:
self.occupations = occupations.FermiDirac(
width, par.fixmom)
else:
self.occupations = par.occupations
# If occupation numbers are changed, and we have wave functions,
# recalculate the occupation numbers
if self.wfs is not None and not isinstance(self.wfs,
EmptyWaveFunctions):
self.occupations.calculate(self.wfs)
self.occupations.magmom = M_v[2]
cc = par.convergence
if mode.name == 'lcao':
niter_fixdensity = 0
else:
niter_fixdensity = None
if self.scf is None:
force_crit = cc['forces']
if force_crit is not None:
force_crit /= Hartree / Bohr
self.scf = SCFLoop(cc['eigenstates'] / Hartree**2 * nvalence,
cc['energy'] / Hartree * max(nvalence, 1),
cc['density'] * nvalence, par.maxiter,
par.fixdensity, niter_fixdensity, force_crit)
parsize_kpt = par.parallel['kpt']
parsize_domain = par.parallel['domain']
parsize_bands = par.parallel['band']
if not realspace:
pbc_c = np.ones(3, bool)
if not self.wfs:
if parsize_domain == 'domain only': # XXX this was silly!
parsize_domain = world.size
parallelization = mpi.Parallelization(world, nspins * kd.nibzkpts)
ndomains = None
if parsize_domain is not None:
ndomains = np.prod(parsize_domain)
if mode.name == 'pw':
if ndomains > 1:
raise ValueError('Planewave mode does not support '
'domain decomposition.')
ndomains = 1
parallelization.set(kpt=parsize_kpt,
domain=ndomains,
band=parsize_bands)
comms = parallelization.build_communicators()
domain_comm = comms['d']
kpt_comm = comms['k']
band_comm = comms['b']
kptband_comm = comms['D']
domainband_comm = comms['K']
self.comms = comms
kd.set_communicator(kpt_comm)
parstride_bands = par.parallel['stridebands']
# Unfortunately we need to remember that we adjusted the
# number of bands so we can print a warning if it differs
# from the number specified by the user. (The number can
# be inferred from the input parameters, but it's tricky
# because we allow negative numbers)
self.nbands_parallelization_adjustment = -nbands % band_comm.size
nbands += self.nbands_parallelization_adjustment
# I would like to give the following error message, but apparently
# there are cases, e.g. gpaw/test/gw_ppa.py, which involve
# nbands > nao and are supposed to work that way.
#if nbands > nao:
# raise ValueError('Number of bands %d adjusted for band '
# 'parallelization %d exceeds number of atomic '
# 'orbitals %d. This problem can be fixed '
# 'by reducing the number of bands a bit.'
# % (nbands, band_comm.size, nao))
bd = BandDescriptor(nbands, band_comm, parstride_bands)
if (self.density is not None
and self.density.gd.comm.size != domain_comm.size):
# Domain decomposition has changed, so we need to
# reinitialize density and hamiltonian:
if par.fixdensity:
raise RuntimeError(
'Density reinitialization conflict ' +
'with "fixdensity" - specify domain decomposition.')
self.density = None
self.hamiltonian = None
# Construct grid descriptor for coarse grids for wave functions:
gd = self.grid_descriptor_class(N_c, cell_cv, pbc_c, domain_comm,
parsize_domain)
# do k-point analysis here? XXX
args = (gd, nvalence, setups, bd, dtype, world, kd, kptband_comm,
self.timer)
if par.parallel['sl_auto']:
# Choose scalapack parallelization automatically
for key, val in par.parallel.items():
if (key.startswith('sl_') and key != 'sl_auto'
and val is not None):
raise ValueError("Cannot use 'sl_auto' together "
"with '%s'" % key)
max_scalapack_cpus = bd.comm.size * gd.comm.size
nprow = max_scalapack_cpus
npcol = 1
# Get a sort of reasonable number of columns/rows
while npcol < nprow and nprow % 2 == 0:
npcol *= 2
nprow //= 2
assert npcol * nprow == max_scalapack_cpus
# ScaLAPACK creates trouble if there aren't at least a few
# whole blocks; choose block size so there will always be
# several blocks. This will crash for small test systems,
# but so will ScaLAPACK in any case
blocksize = min(-(-nbands // 4), 64)
sl_default = (nprow, npcol, blocksize)
else:
sl_default = par.parallel['sl_default']
if mode.name == 'lcao':
# Layouts used for general diagonalizer
sl_lcao = par.parallel['sl_lcao']
if sl_lcao is None:
sl_lcao = sl_default
lcaoksl = get_KohnSham_layouts(sl_lcao,
'lcao',
gd,
bd,
domainband_comm,
dtype,
nao=nao,
timer=self.timer)
self.wfs = mode(collinear, lcaoksl, *args)
elif mode.name == 'fd' or mode.name == 'pw':
# buffer_size keyword only relevant for fdpw
buffer_size = par.parallel['buffer_size']
# Layouts used for diagonalizer
sl_diagonalize = par.parallel['sl_diagonalize']
if sl_diagonalize is None:
sl_diagonalize = sl_default
diagksl = get_KohnSham_layouts(
sl_diagonalize,
'fd', # XXX
# choice of key 'fd' not so nice
gd,
bd,
domainband_comm,
dtype,
buffer_size=buffer_size,
timer=self.timer)
# Layouts used for orthonormalizer
sl_inverse_cholesky = par.parallel['sl_inverse_cholesky']
if sl_inverse_cholesky is None:
sl_inverse_cholesky = sl_default
if sl_inverse_cholesky != sl_diagonalize:
message = 'sl_inverse_cholesky != sl_diagonalize ' \
'is not implemented.'
raise NotImplementedError(message)
orthoksl = get_KohnSham_layouts(sl_inverse_cholesky,
'fd',
gd,
bd,
domainband_comm,
dtype,
buffer_size=buffer_size,
timer=self.timer)
# Use (at most) all available LCAO for initialization
lcaonbands = min(nbands, nao)
try:
lcaobd = BandDescriptor(lcaonbands, band_comm,
parstride_bands)
except RuntimeError:
initksl = None
else:
# Layouts used for general diagonalizer
# (LCAO initialization)
sl_lcao = par.parallel['sl_lcao']
if sl_lcao is None:
sl_lcao = sl_default
initksl = get_KohnSham_layouts(sl_lcao,
'lcao',
gd,
lcaobd,
domainband_comm,
dtype,
nao=nao,
timer=self.timer)
if hasattr(self, 'time'):
assert mode.name == 'fd'
from gpaw.tddft import TimeDependentWaveFunctions
self.wfs = TimeDependentWaveFunctions(
par.stencils[0], diagksl, orthoksl, initksl, gd,
nvalence, setups, bd, world, kd, kptband_comm,
self.timer)
elif mode.name == 'fd':
self.wfs = mode(par.stencils[0], diagksl, orthoksl,
initksl, *args)
else:
assert mode.name == 'pw'
self.wfs = mode(diagksl, orthoksl, initksl, *args)
else:
self.wfs = mode(self, *args)
else:
self.wfs.set_setups(setups)
if not self.wfs.eigensolver:
# Number of bands to converge:
nbands_converge = cc['bands']
if nbands_converge == 'all':
nbands_converge = nbands
elif nbands_converge != 'occupied':
assert isinstance(nbands_converge, int)
if nbands_converge < 0:
nbands_converge += nbands
eigensolver = get_eigensolver(par.eigensolver, mode,
par.convergence)
eigensolver.nbands_converge = nbands_converge
# XXX Eigensolver class doesn't define an nbands_converge property
if isinstance(xc, SIC):
eigensolver.blocksize = 1
self.wfs.set_eigensolver(eigensolver)
if self.density is None:
gd = self.wfs.gd
if par.stencils[1] != 9:
# Construct grid descriptor for fine grids for densities
# and potentials:
finegd = gd.refine()
else:
# Special case (use only coarse grid):
finegd = gd
if realspace:
self.density = RealSpaceDensity(
gd, finegd, nspins, par.charge + setups.core_charge,
collinear, par.stencils[1])
else:
self.density = pw.ReciprocalSpaceDensity(
gd, finegd, nspins, par.charge + setups.core_charge,
collinear)
self.density.initialize(setups, self.timer, magmom_av, par.hund)
self.density.set_mixer(par.mixer)
if self.hamiltonian is None:
gd, finegd = self.density.gd, self.density.finegd
if realspace:
self.hamiltonian = RealSpaceHamiltonian(
gd, finegd, nspins, setups, self.timer, xc, world,
self.wfs.kptband_comm, par.external, collinear,
par.poissonsolver, par.stencils[1])
else:
self.hamiltonian = pw.ReciprocalSpaceHamiltonian(
gd, finegd, self.density.pd2, self.density.pd3, nspins,
setups, self.timer, xc, world, self.wfs.kptband_comm,
par.external, collinear)
xc.initialize(self.density, self.hamiltonian, self.wfs,
self.occupations)
self.text()
self.print_memory_estimate(self.txt, maxdepth=memory_estimate_depth)
self.txt.flush()
self.timer.print_info(self)
if dry_run:
self.dry_run()
if realspace and \
self.hamiltonian.poisson.get_description() == 'FDTD+TDDFT':
self.hamiltonian.poisson.set_density(self.density)
self.hamiltonian.poisson.print_messages(self.text)
self.txt.flush()
self.initialized = True
self._changed_keywords.clear()
def __init__(self,
cavity,
dielectric,
interactions,
gd,
finegd,
nspins,
setups,
timer,
xc,
world,
redistributor,
vext=None,
psolver=None,
stencil=3,
collinear=None):
"""Constructor of SJM_RealSpaceHamiltonian class.
Notes
-----
The only difference to SolvationRealSpaceHamiltonian is the
possibility to perform a dipole correction
"""
self.cavity = cavity
self.dielectric = dielectric
self.interactions = interactions
cavity.set_grid_descriptor(finegd)
dielectric.set_grid_descriptor(finegd)
for ia in interactions:
ia.set_grid_descriptor(finegd)
if psolver is None:
psolver = WeightedFDPoissonSolver()
self.dipcorr = False
elif isinstance(psolver, dict):
psolver = SJMDipoleCorrection(WeightedFDPoissonSolver(),
psolver['dipolelayer'])
self.dipcorr = True
if self.dipcorr:
psolver.poissonsolver.set_dielectric(self.dielectric)
else:
psolver.set_dielectric(self.dielectric)
self.gradient = None
RealSpaceHamiltonian.__init__(self,
gd,
finegd,
nspins,
collinear,
setups,
timer,
xc,
world,
vext=vext,
psolver=psolver,
stencil=stencil,
redistributor=redistributor)
for ia in interactions:
setattr(self, 'e_' + ia.subscript, None)
self.new_atoms = None
self.vt_ia_g = None
self.e_el_free = None
self.e_el_extrapolated = None
class PAW(PAWTextOutput):
"""This is the main calculation object for doing a PAW calculation."""
def __init__(self, filename=None, timer=None,
read_projections=True, **kwargs):
"""ASE-calculator interface.
The following parameters can be used: nbands, xc, kpts,
spinpol, gpts, h, charge, symmetry, width, mixer,
hund, lmax, fixdensity, convergence, txt, parallel,
communicator, dtype, softgauss and stencils.
If you don't specify any parameters, you will get:
Defaults: neutrally charged, LDA, gamma-point calculation, a
reasonable grid-spacing, zero Kelvin electronic temperature,
and the number of bands will be equal to the number of atomic
orbitals present in the setups. Only occupied bands are used
in the convergence decision. The calculation will be
spin-polarized if and only if one or more of the atoms have
non-zero magnetic moments. Text output will be written to
standard output.
For a non-gamma point calculation, the electronic temperature
will be 0.1 eV (energies are extrapolated to zero Kelvin) and
all symmetries will be used to reduce the number of
**k**-points."""
PAWTextOutput.__init__(self)
self.grid_descriptor_class = GridDescriptor
self.input_parameters = InputParameters()
if timer is None:
self.timer = Timer()
else:
self.timer = timer
self.scf = None
self.forces = ForceCalculator(self.timer)
self.stress_vv = None
self.dipole_v = None
self.magmom_av = None
self.wfs = EmptyWaveFunctions()
self.occupations = None
self.density = None
self.hamiltonian = None
self.atoms = None
self.iter = 0
self.initialized = False
self.nbands_parallelization_adjustment = None # Somehow avoid this?
# Possibly read GPAW keyword arguments from file:
if filename is not None and filename.endswith('.gkw'):
from gpaw.utilities.kwargs import load
parameters = load(filename)
parameters.update(kwargs)
kwargs = parameters
filename = None # XXX
if filename is not None:
comm = kwargs.get('communicator', mpi.world)
reader = gpaw.io.open(filename, 'r', comm)
self.atoms = gpaw.io.read_atoms(reader)
par = self.input_parameters
par.read(reader)
# _changed_keywords contains those keywords that have been
# changed by set() since last time initialize() was called.
self._changed_keywords = set()
self.set(**kwargs)
# Here in the beginning, effectively every keyword has been changed.
self._changed_keywords.update(self.input_parameters)
if filename is not None:
# Setups are not saved in the file if the setups were not loaded
# *from* files in the first place
if par.setups is None:
if par.idiotproof:
raise RuntimeError('Setups not specified in file. Use '
'idiotproof=False to proceed anyway.')
else:
par.setups = {None: 'paw'}
if par.basis is None:
if par.idiotproof:
raise RuntimeError('Basis not specified in file. Use '
'idiotproof=False to proceed anyway.')
else:
par.basis = {}
self.initialize()
self.read(reader, read_projections)
if self.hamiltonian.xc.type == 'GLLB':
self.occupations.calculate(self.wfs)
self.print_cell_and_parameters()
self.observers = []
def read(self, reader, read_projections=True):
gpaw.io.read(self, reader, read_projections)
def set(self, **kwargs):
"""Change parameters for calculator.
Examples::
calc.set(xc='PBE')
calc.set(nbands=20, kpts=(4, 1, 1))
"""
p = self.input_parameters
self._changed_keywords.update(kwargs)
if (kwargs.get('h') is not None) and (kwargs.get('gpts') is not None):
raise TypeError("""You can't use both "gpts" and "h"!""")
if 'h' in kwargs:
p['gpts'] = None
if 'gpts' in kwargs:
p['h'] = None
# Special treatment for dictionary parameters:
for name in ['convergence', 'parallel']:
if kwargs.get(name) is not None:
tmp = p[name]
for key in kwargs[name]:
if key not in tmp:
raise KeyError('Unknown subparameter "%s" in '
'dictionary parameter "%s"' % (key,
name))
tmp.update(kwargs[name])
kwargs[name] = tmp
self.initialized = False
for key in kwargs:
if key == 'basis' and str(p['mode']) == 'fd': # umm what about PW?
# The second criterion seems buggy, will not touch it. -Ask
continue
if key == 'eigensolver':
self.wfs.set_eigensolver(None)
if key in ['fixmom', 'mixer',
'verbose', 'txt', 'hund', 'random',
'eigensolver', 'idiotproof', 'notify']:
continue
if key in ['convergence', 'fixdensity', 'maxiter']:
self.scf = None
continue
# More drastic changes:
self.scf = None
self.wfs.set_orthonormalized(False)
if key in ['lmax', 'width', 'stencils', 'external', 'xc',
'poissonsolver']:
self.hamiltonian = None
self.occupations = None
elif key in ['occupations']:
self.occupations = None
elif key in ['charge']:
self.hamiltonian = None
self.density = None
self.wfs = EmptyWaveFunctions()
self.occupations = None
elif key in ['kpts', 'nbands', 'usesymm', 'symmetry']:
self.wfs = EmptyWaveFunctions()
self.occupations = None
elif key in ['h', 'gpts', 'setups', 'spinpol', 'realspace',
'parallel', 'communicator', 'dtype', 'mode']:
self.density = None
self.occupations = None
self.hamiltonian = None
self.wfs = EmptyWaveFunctions()
elif key in ['basis']:
self.wfs = EmptyWaveFunctions()
elif key in ['parsize', 'parsize_bands', 'parstride_bands']:
name = {'parsize': 'domain',
'parsize_bands': 'band',
'parstride_bands': 'stridebands'}[key]
raise DeprecationWarning(
'Keyword argument has been moved ' +
"to the 'parallel' dictionary keyword under '%s'." % name)
else:
raise TypeError("Unknown keyword argument: '%s'" % key)
p.update(kwargs)
def calculate(self, atoms=None, converge=False,
force_call_to_set_positions=False):
"""Update PAW calculaton if needed.
Returns True/False whether a calculation was performed or not."""
self.timer.start('Initialization')
if atoms is None:
atoms = self.atoms
if self.atoms is None:
# First time:
self.initialize(atoms)
self.set_positions(atoms)
elif (len(atoms) != len(self.atoms) or
(atoms.get_atomic_numbers() !=
self.atoms.get_atomic_numbers()).any() or
(atoms.get_initial_magnetic_moments() !=
self.atoms.get_initial_magnetic_moments()).any() or
(atoms.get_cell() != self.atoms.get_cell()).any() or
(atoms.get_pbc() != self.atoms.get_pbc()).any()):
# Drastic changes:
self.wfs = EmptyWaveFunctions()
self.occupations = None
self.density = None
self.hamiltonian = None
self.scf = None
self.initialize(atoms)
self.set_positions(atoms)
elif not self.initialized:
self.initialize(atoms)
self.set_positions(atoms)
elif (atoms.get_positions() != self.atoms.get_positions()).any():
self.density.reset()
self.set_positions(atoms)
elif not self.scf.converged:
# Do not call scf.check_convergence() here as it overwrites
# scf.converged, and setting scf.converged is the only
# 'practical' way for a user to force the calculation to proceed
self.set_positions(atoms)
elif force_call_to_set_positions:
self.set_positions(atoms)
self.timer.stop('Initialization')
if self.scf.converged:
return False
else:
self.print_cell_and_parameters()
self.timer.start('SCF-cycle')
for iter in self.scf.run(self.wfs, self.hamiltonian, self.density,
self.occupations, self.forces):
self.iter = iter
self.call_observers(iter)
self.print_iteration(iter)
self.timer.stop('SCF-cycle')
if self.scf.converged:
self.call_observers(iter, final=True)
self.print_converged(iter)
elif converge:
self.txt.write(oops)
raise KohnShamConvergenceError(
'Did not converge! See text output for help.')
return True
def initialize_positions(self, atoms=None):
"""Update the positions of the atoms."""
if atoms is None:
atoms = self.atoms
else:
# Save the state of the atoms:
self.atoms = atoms.copy()
self.check_atoms()
spos_ac = atoms.get_scaled_positions() % 1.0
self.wfs.set_positions(spos_ac)
self.density.set_positions(spos_ac, self.wfs.rank_a)
self.hamiltonian.set_positions(spos_ac, self.wfs.rank_a)
return spos_ac
def set_positions(self, atoms=None):
"""Update the positions of the atoms and initialize wave functions."""
spos_ac = self.initialize_positions(atoms)
self.wfs.initialize(self.density, self.hamiltonian, spos_ac)
self.wfs.eigensolver.reset()
self.scf.reset()
self.forces.reset()
self.stress_vv = None
self.dipole_v = None
self.magmom_av = None
self.print_positions()
def initialize(self, atoms=None):
"""Inexpensive initialization."""
if atoms is None:
atoms = self.atoms
else:
# Save the state of the atoms:
self.atoms = atoms.copy()
par = self.input_parameters
world = par.communicator
if world is None:
world = mpi.world
elif hasattr(world, 'new_communicator'):
# Check for whether object has correct type already
#
# Using isinstance() is complicated because of all the
# combinations, serial/parallel/debug...
pass
else:
# world should be a list of ranks:
world = mpi.world.new_communicator(np.asarray(world))
self.wfs.world = world
if 'txt' in self._changed_keywords:
self.set_txt(par.txt)
self.verbose = par.verbose
natoms = len(atoms)
cell_cv = atoms.get_cell() / Bohr
pbc_c = atoms.get_pbc()
Z_a = atoms.get_atomic_numbers()
magmom_av = atoms.get_initial_magnetic_moments()
self.check_atoms()
# Generate new xc functional only when it is reset by set
# XXX sounds like this should use the _changed_keywords dictionary.
if self.hamiltonian is None or self.hamiltonian.xc is None:
if isinstance(par.xc, str):
xc = XC(par.xc)
else:
xc = par.xc
else:
xc = self.hamiltonian.xc
mode = par.mode
if mode == 'fd':
mode = FD()
elif mode == 'pw':
mode = pw.PW()
elif mode == 'lcao':
mode = LCAO()
else:
assert hasattr(mode, 'name'), str(mode)
if xc.orbital_dependent and mode.name == 'lcao':
raise NotImplementedError('LCAO mode does not support '
'orbital-dependent XC functionals.')
if par.realspace is None:
realspace = (mode.name != 'pw')
else:
realspace = par.realspace
if mode.name == 'pw':
assert not realspace
if par.filter is None and mode.name != 'pw':
gamma = 1.6
if par.gpts is not None:
h = ((np.linalg.inv(cell_cv)**2).sum(0)**-0.5
/ par.gpts).max()
else:
h = (par.h or 0.2) / Bohr
def filter(rgd, rcut, f_r, l=0):
gcut = np.pi / h - 2 / rcut / gamma
f_r[:] = rgd.filter(f_r, rcut * gamma, gcut, l)
else:
filter = par.filter
setups = Setups(Z_a, par.setups, par.basis, par.lmax, xc,
filter, world)
if magmom_av.ndim == 1:
collinear = True
magmom_av, magmom_a = np.zeros((natoms, 3)), magmom_av
magmom_av[:, 2] = magmom_a
else:
collinear = False
magnetic = magmom_av.any()
spinpol = par.spinpol
if par.hund:
if natoms != 1:
raise ValueError('hund=True arg only valid for single atoms!')
spinpol = True
magmom_av[0] = (0, 0, setups[0].get_hunds_rule_moment(par.charge))
if spinpol is None:
spinpol = magnetic
elif magnetic and not spinpol:
raise ValueError('Non-zero initial magnetic moment for a ' +
'spin-paired calculation!')
if collinear:
nspins = 1 + int(spinpol)
ncomp = 1
else:
nspins = 1
ncomp = 2
if par.usesymm != 'default':
warnings.warn('Use "symmetry" keyword instead of ' +
'"usesymm" keyword')
par.symmetry = usesymm2symmetry(par.usesymm)
symm = par.symmetry
if symm == 'off':
symm = {'point_group': False, 'time_reversal': False}
bzkpts_kc = kpts2ndarray(par.kpts, self.atoms)
kd = KPointDescriptor(bzkpts_kc, nspins, collinear)
m_av = magmom_av.round(decimals=3) # round off
id_a = zip(setups.id_a, *m_av.T)
symmetry = Symmetry(id_a, cell_cv, atoms.pbc, **symm)
kd.set_symmetry(atoms, symmetry, comm=world)
setups.set_symmetry(symmetry)
if par.gpts is not None:
N_c = np.array(par.gpts)
else:
h = par.h
if h is not None:
h /= Bohr
N_c = get_number_of_grid_points(cell_cv, h, mode, realspace,
kd.symmetry)
symmetry.check_grid(N_c)
width = par.width
if width is None:
if pbc_c.any():
width = 0.1 # eV
else:
width = 0.0
else:
assert par.occupations is None
if hasattr(self, 'time') or par.dtype == complex:
dtype = complex
else:
if kd.gamma:
dtype = float
else:
dtype = complex
nao = setups.nao
nvalence = setups.nvalence - par.charge
M_v = magmom_av.sum(0)
M = np.dot(M_v, M_v) ** 0.5
nbands = par.nbands
orbital_free = any(setup.orbital_free for setup in setups)
if orbital_free:
nbands = 1
if isinstance(nbands, basestring):
if nbands[-1] == '%':
basebands = int(nvalence + M + 0.5) // 2
nbands = int((float(nbands[:-1]) / 100) * basebands)
else:
raise ValueError('Integer Expected: Only use a string '
'if giving a percentage of occupied bands')
if nbands is None:
nbands = 0
for setup in setups:
nbands_from_atom = setup.get_default_nbands()
# Any obscure setup errors?
if nbands_from_atom < -(-setup.Nv // 2):
raise ValueError('Bad setup: This setup requests %d'
' bands but has %d electrons.'
% (nbands_from_atom, setup.Nv))
nbands += nbands_from_atom
nbands = min(nao, nbands)
elif nbands > nao and mode.name == 'lcao':
raise ValueError('Too many bands for LCAO calculation: '
'%d bands and only %d atomic orbitals!' %
(nbands, nao))
if nvalence < 0:
raise ValueError(
'Charge %f is not possible - not enough valence electrons' %
par.charge)
if nbands <= 0:
nbands = int(nvalence + M + 0.5) // 2 + (-nbands)
if nvalence > 2 * nbands and not orbital_free:
raise ValueError('Too few bands! Electrons: %f, bands: %d'
% (nvalence, nbands))
nbands *= ncomp
if par.width is not None:
self.text('**NOTE**: please start using '
'occupations=FermiDirac(width).')
if par.fixmom:
self.text('**NOTE**: please start using '
'occupations=FermiDirac(width, fixmagmom=True).')
if self.occupations is None:
if par.occupations is None:
# Create object for occupation numbers:
if orbital_free:
width = 0.0 # even for PBC
self.occupations = occupations.TFOccupations(width,
par.fixmom)
else:
self.occupations = occupations.FermiDirac(width,
par.fixmom)
else:
self.occupations = par.occupations
# If occupation numbers are changed, and we have wave functions,
# recalculate the occupation numbers
if self.wfs is not None and not isinstance(
self.wfs,
EmptyWaveFunctions):
self.occupations.calculate(self.wfs)
self.occupations.magmom = M_v[2]
cc = par.convergence
if mode.name == 'lcao':
niter_fixdensity = 0
else:
niter_fixdensity = None
if self.scf is None:
force_crit = cc['forces']
if force_crit is not None:
force_crit /= Hartree / Bohr
self.scf = SCFLoop(
cc['eigenstates'] / Hartree**2 * nvalence,
cc['energy'] / Hartree * max(nvalence, 1),
cc['density'] * nvalence,
par.maxiter, par.fixdensity,
niter_fixdensity,
force_crit)
parsize_kpt = par.parallel['kpt']
parsize_domain = par.parallel['domain']
parsize_bands = par.parallel['band']
if not realspace:
pbc_c = np.ones(3, bool)
if not self.wfs:
if parsize_domain == 'domain only': # XXX this was silly!
parsize_domain = world.size
parallelization = mpi.Parallelization(world,
nspins * kd.nibzkpts)
ndomains = None
if parsize_domain is not None:
ndomains = np.prod(parsize_domain)
if mode.name == 'pw':
if ndomains > 1:
raise ValueError('Planewave mode does not support '
'domain decomposition.')
ndomains = 1
parallelization.set(kpt=parsize_kpt,
domain=ndomains,
band=parsize_bands)
comms = parallelization.build_communicators()
domain_comm = comms['d']
kpt_comm = comms['k']
band_comm = comms['b']
kptband_comm = comms['D']
domainband_comm = comms['K']
self.comms = comms
kd.set_communicator(kpt_comm)
parstride_bands = par.parallel['stridebands']
# Unfortunately we need to remember that we adjusted the
# number of bands so we can print a warning if it differs
# from the number specified by the user. (The number can
# be inferred from the input parameters, but it's tricky
# because we allow negative numbers)
self.nbands_parallelization_adjustment = -nbands % band_comm.size
nbands += self.nbands_parallelization_adjustment
# I would like to give the following error message, but apparently
# there are cases, e.g. gpaw/test/gw_ppa.py, which involve
# nbands > nao and are supposed to work that way.
#if nbands > nao:
# raise ValueError('Number of bands %d adjusted for band '
# 'parallelization %d exceeds number of atomic '
# 'orbitals %d. This problem can be fixed '
# 'by reducing the number of bands a bit.'
# % (nbands, band_comm.size, nao))
bd = BandDescriptor(nbands, band_comm, parstride_bands)
if (self.density is not None and
self.density.gd.comm.size != domain_comm.size):
# Domain decomposition has changed, so we need to
# reinitialize density and hamiltonian:
if par.fixdensity:
raise RuntimeError(
'Density reinitialization conflict ' +
'with "fixdensity" - specify domain decomposition.')
self.density = None
self.hamiltonian = None
# Construct grid descriptor for coarse grids for wave functions:
gd = self.grid_descriptor_class(N_c, cell_cv, pbc_c,
domain_comm, parsize_domain)
# do k-point analysis here? XXX
args = (gd, nvalence, setups, bd, dtype, world, kd,
kptband_comm, self.timer)
if par.parallel['sl_auto']:
# Choose scalapack parallelization automatically
for key, val in par.parallel.items():
if (key.startswith('sl_') and key != 'sl_auto'
and val is not None):
raise ValueError("Cannot use 'sl_auto' together "
"with '%s'" % key)
max_scalapack_cpus = bd.comm.size * gd.comm.size
nprow = max_scalapack_cpus
npcol = 1
# Get a sort of reasonable number of columns/rows
while npcol < nprow and nprow % 2 == 0:
npcol *= 2
nprow //= 2
assert npcol * nprow == max_scalapack_cpus
# ScaLAPACK creates trouble if there aren't at least a few
# whole blocks; choose block size so there will always be
# several blocks. This will crash for small test systems,
# but so will ScaLAPACK in any case
blocksize = min(-(-nbands // 4), 64)
sl_default = (nprow, npcol, blocksize)
else:
sl_default = par.parallel['sl_default']
if mode.name == 'lcao':
# Layouts used for general diagonalizer
sl_lcao = par.parallel['sl_lcao']
if sl_lcao is None:
sl_lcao = sl_default
lcaoksl = get_KohnSham_layouts(sl_lcao, 'lcao',
gd, bd, domainband_comm, dtype,
nao=nao, timer=self.timer)
self.wfs = mode(collinear, lcaoksl, *args)
elif mode.name == 'fd' or mode.name == 'pw':
# buffer_size keyword only relevant for fdpw
buffer_size = par.parallel['buffer_size']
# Layouts used for diagonalizer
sl_diagonalize = par.parallel['sl_diagonalize']
if sl_diagonalize is None:
sl_diagonalize = sl_default
diagksl = get_KohnSham_layouts(sl_diagonalize, 'fd', # XXX
# choice of key 'fd' not so nice
gd, bd, domainband_comm, dtype,
buffer_size=buffer_size,
timer=self.timer)
# Layouts used for orthonormalizer
sl_inverse_cholesky = par.parallel['sl_inverse_cholesky']
if sl_inverse_cholesky is None:
sl_inverse_cholesky = sl_default
if sl_inverse_cholesky != sl_diagonalize:
message = 'sl_inverse_cholesky != sl_diagonalize ' \
'is not implemented.'
raise NotImplementedError(message)
orthoksl = get_KohnSham_layouts(sl_inverse_cholesky, 'fd',
gd, bd, domainband_comm, dtype,
buffer_size=buffer_size,
timer=self.timer)
# Use (at most) all available LCAO for initialization
lcaonbands = min(nbands, nao)
try:
lcaobd = BandDescriptor(lcaonbands, band_comm,
parstride_bands)
except RuntimeError:
initksl = None
else:
# Layouts used for general diagonalizer
# (LCAO initialization)
sl_lcao = par.parallel['sl_lcao']
if sl_lcao is None:
sl_lcao = sl_default
initksl = get_KohnSham_layouts(sl_lcao, 'lcao',
gd, lcaobd, domainband_comm,
dtype, nao=nao,
timer=self.timer)
if hasattr(self, 'time'):
assert mode.name == 'fd'
from gpaw.tddft import TimeDependentWaveFunctions
self.wfs = TimeDependentWaveFunctions(
par.stencils[0],
diagksl,
orthoksl,
initksl,
gd,
nvalence,
setups,
bd,
world,
kd,
kptband_comm,
self.timer)
elif mode.name == 'fd':
self.wfs = mode(par.stencils[0], diagksl,
orthoksl, initksl, *args)
else:
assert mode.name == 'pw'
self.wfs = mode(diagksl, orthoksl, initksl, *args)
else:
self.wfs = mode(self, *args)
else:
self.wfs.set_setups(setups)
if not self.wfs.eigensolver:
# Number of bands to converge:
nbands_converge = cc['bands']
if nbands_converge == 'all':
nbands_converge = nbands
elif nbands_converge != 'occupied':
assert isinstance(nbands_converge, int)
if nbands_converge < 0:
nbands_converge += nbands
eigensolver = get_eigensolver(par.eigensolver, mode,
par.convergence)
eigensolver.nbands_converge = nbands_converge
# XXX Eigensolver class doesn't define an nbands_converge property
if isinstance(xc, SIC):
eigensolver.blocksize = 1
self.wfs.set_eigensolver(eigensolver)
if self.density is None:
gd = self.wfs.gd
if par.stencils[1] != 9:
# Construct grid descriptor for fine grids for densities
# and potentials:
finegd = gd.refine()
else:
# Special case (use only coarse grid):
finegd = gd
if realspace:
self.density = RealSpaceDensity(
gd, finegd, nspins, par.charge + setups.core_charge,
collinear, par.stencils[1])
else:
self.density = pw.ReciprocalSpaceDensity(
gd, finegd, nspins, par.charge + setups.core_charge,
collinear)
self.density.initialize(setups, self.timer, magmom_av, par.hund)
self.density.set_mixer(par.mixer)
if self.hamiltonian is None:
gd, finegd = self.density.gd, self.density.finegd
if realspace:
self.hamiltonian = RealSpaceHamiltonian(
gd, finegd, nspins, setups, self.timer, xc,
world, self.wfs.kptband_comm, par.external,
collinear, par.poissonsolver, par.stencils[1])
else:
self.hamiltonian = pw.ReciprocalSpaceHamiltonian(
gd, finegd, self.density.pd2, self.density.pd3,
nspins, setups, self.timer, xc, world,
self.wfs.kptband_comm, par.external, collinear)
xc.initialize(self.density, self.hamiltonian, self.wfs,
self.occupations)
self.text()
self.print_memory_estimate(self.txt, maxdepth=memory_estimate_depth)
self.txt.flush()
self.timer.print_info(self)
if dry_run:
self.dry_run()
if realspace and \
self.hamiltonian.poisson.get_description() == 'FDTD+TDDFT':
self.hamiltonian.poisson.set_density(self.density)
self.hamiltonian.poisson.print_messages(self.text)
self.txt.flush()
self.initialized = True
self._changed_keywords.clear()
def dry_run(self):
# Can be overridden like in gpaw.atom.atompaw
self.print_cell_and_parameters()
self.print_positions()
self.txt.flush()
raise SystemExit
def linearize_to_xc(self, newxc):
"""Linearize Hamiltonian to difference XC functional.
Used in real time TDDFT to perform calculations with various kernels.
"""
if isinstance(newxc, str):
newxc = XC(newxc)
self.txt.write('Linearizing xc-hamiltonian to ' + str(newxc))
newxc.initialize(self.density, self.hamiltonian, self.wfs,
self.occupations)
self.hamiltonian.linearize_to_xc(newxc, self.density)
def restore_state(self):
"""After restart, calculate fine density and poisson solution.
These are not initialized by default.
TODO: Is this really the most efficient way?
"""
spos_ac = self.atoms.get_scaled_positions() % 1.0
self.density.set_positions(spos_ac, self.wfs.rank_a)
self.density.interpolate_pseudo_density()
self.density.calculate_pseudo_charge()
self.hamiltonian.set_positions(spos_ac, self.wfs.rank_a)
self.hamiltonian.update(self.density)
def attach(self, function, n=1, *args, **kwargs):
"""Register observer function.
Call *function* using *args* and
*kwargs* as arguments.
If *n* is positive, then
*function* will be called every *n* iterations + the
final iteration if it would not be otherwise
If *n* is negative, then *function* will only be
called on iteration *abs(n)*.
If *n* is 0, then *function* will only be called
on convergence"""
try:
slf = function.im_self
except AttributeError:
pass
else:
if slf is self:
# function is a bound method of self. Store the name
# of the method and avoid circular reference:
function = function.im_func.func_name
self.observers.append((function, n, args, kwargs))
def call_observers(self, iter, final=False):
"""Call all registered callback functions."""
for function, n, args, kwargs in self.observers:
call = False
# Call every n iterations, including the last
if n > 0:
if ((iter % n) == 0) != final:
call = True
# Call only on iteration n
elif n < 0 and not final:
if iter == abs(n):
call = True
# Call only on convergence
elif n == 0 and final:
call = True
if call:
if isinstance(function, str):
function = getattr(self, function)
function(*args, **kwargs)
def get_reference_energy(self):
return self.wfs.setups.Eref * Hartree
def write(self, filename, mode='', cmr_params={}, **kwargs):
"""Write state to file.
use mode='all' to write the wave functions. cmr_params is a
dictionary that allows you to specify parameters for CMR
(Computational Materials Repository).
"""
self.timer.start('IO')
gpaw.io.write(self, filename, mode, cmr_params=cmr_params, **kwargs)
self.timer.stop('IO')
def get_myu(self, k, s):
"""Return my u corresponding to a certain kpoint and spin - or None"""
# very slow, but we are sure that we have it
for u in range(len(self.wfs.kpt_u)):
if self.wfs.kpt_u[u].k == k and self.wfs.kpt_u[u].s == s:
return u
return None
def get_homo_lumo(self):
"""Return H**O and LUMO eigenvalues."""
return self.occupations.get_homo_lumo(self.wfs) * Hartree
def estimate_memory(self, mem):
"""Estimate memory use of this object."""
for name, obj in [('Density', self.density),
('Hamiltonian', self.hamiltonian),
('Wavefunctions', self.wfs),
]:
obj.estimate_memory(mem.subnode(name))
def print_memory_estimate(self, txt=None, maxdepth=-1):
"""Print estimated memory usage for PAW object and components.
maxdepth is the maximum nesting level of displayed components.
The PAW object must be initialize()'d, but needs not have large
arrays allocated."""
# NOTE. This should work with --dry-run=N
#
# However, the initial overhead estimate is wrong if this method
# is called within a real mpirun/gpaw-python context.
if txt is None:
txt = self.txt
txt.write('Memory estimate\n')
txt.write('---------------\n')
mem_init = maxrss() # initial overhead includes part of Hamiltonian!
txt.write('Process memory now: %.2f MiB\n' % (mem_init / 1024.0**2))
mem = MemNode('Calculator', 0)
try:
self.estimate_memory(mem)
except AttributeError as m:
txt.write('Attribute error: %r' % m)
txt.write('Some object probably lacks estimate_memory() method')
txt.write('Memory breakdown may be incomplete')
mem.calculate_size()
mem.write(txt, maxdepth=maxdepth)
def converge_wave_functions(self):
"""Converge the wave-functions if not present."""
if not self.wfs or not self.scf:
self.initialize()
else:
self.wfs.initialize_wave_functions_from_restart_file()
spos_ac = self.atoms.get_scaled_positions() % 1.0
self.wfs.set_positions(spos_ac)
no_wave_functions = (self.wfs.kpt_u[0].psit_nG is None)
converged = self.scf.check_convergence(self.density,
self.wfs.eigensolver, self.wfs,
self.hamiltonian, self.forces)
if no_wave_functions or not converged:
self.wfs.eigensolver.error = np.inf
self.scf.converged = False
# is the density ok ?
error = self.density.mixer.get_charge_sloshing()
criterion = (self.input_parameters['convergence']['density']
* self.wfs.nvalence)
if error < criterion and not self.hamiltonian.xc.orbital_dependent:
self.scf.fix_density()
self.calculate()
def diagonalize_full_hamiltonian(self, nbands=None, scalapack=None, expert=False):
self.wfs.diagonalize_full_hamiltonian(self.hamiltonian, self.atoms,
self.occupations, self.txt,
nbands, scalapack, expert)
def check_atoms(self):
"""Check that atoms objects are identical on all processors."""
if not mpi.compare_atoms(self.atoms, comm=self.wfs.world):
raise RuntimeError('Atoms objects on different processors ' +
'are not identical!')
def initialize(self, atoms=None):
"""Inexpensive initialization."""
if atoms is None:
atoms = self.atoms
else:
# Save the state of the atoms:
self.atoms = atoms.copy()
par = self.input_parameters
world = par.communicator
if world is None:
world = mpi.world
elif hasattr(world, 'new_communicator'):
# Check for whether object has correct type already
#
# Using isinstance() is complicated because of all the
# combinations, serial/parallel/debug...
pass
else:
# world should be a list of ranks:
world = mpi.world.new_communicator(np.asarray(world))
self.wfs.world = world
if 'txt' in self._changed_keywords:
self.set_txt(par.txt)
self.verbose = par.verbose
natoms = len(atoms)
cell_cv = atoms.get_cell() / Bohr
pbc_c = atoms.get_pbc()
Z_a = atoms.get_atomic_numbers()
magmom_av = atoms.get_initial_magnetic_moments()
self.check_atoms()
# Generate new xc functional only when it is reset by set
# XXX sounds like this should use the _changed_keywords dictionary.
if self.hamiltonian is None or self.hamiltonian.xc is None:
if isinstance(par.xc, str):
xc = XC(par.xc)
else:
xc = par.xc
else:
xc = self.hamiltonian.xc
mode = par.mode
if mode == 'fd':
mode = FD()
elif mode == 'pw':
mode = pw.PW()
elif mode == 'lcao':
mode = LCAO()
else:
assert hasattr(mode, 'name'), str(mode)
if xc.orbital_dependent and mode.name == 'lcao':
raise NotImplementedError('LCAO mode does not support '
'orbital-dependent XC functionals.')
if par.realspace is None:
realspace = (mode.name != 'pw')
else:
realspace = par.realspace
if mode.name == 'pw':
assert not realspace
if par.filter is None and mode.name != 'pw':
gamma = 1.6
if par.gpts is not None:
h = ((np.linalg.inv(cell_cv)**2).sum(0)**-0.5
/ par.gpts).max()
else:
h = (par.h or 0.2) / Bohr
def filter(rgd, rcut, f_r, l=0):
gcut = np.pi / h - 2 / rcut / gamma
f_r[:] = rgd.filter(f_r, rcut * gamma, gcut, l)
else:
filter = par.filter
setups = Setups(Z_a, par.setups, par.basis, par.lmax, xc,
filter, world)
if magmom_av.ndim == 1:
collinear = True
magmom_av, magmom_a = np.zeros((natoms, 3)), magmom_av
magmom_av[:, 2] = magmom_a
else:
collinear = False
magnetic = magmom_av.any()
spinpol = par.spinpol
if par.hund:
if natoms != 1:
raise ValueError('hund=True arg only valid for single atoms!')
spinpol = True
magmom_av[0] = (0, 0, setups[0].get_hunds_rule_moment(par.charge))
if spinpol is None:
spinpol = magnetic
elif magnetic and not spinpol:
raise ValueError('Non-zero initial magnetic moment for a ' +
'spin-paired calculation!')
if collinear:
nspins = 1 + int(spinpol)
ncomp = 1
else:
nspins = 1
ncomp = 2
if par.usesymm != 'default':
warnings.warn('Use "symmetry" keyword instead of ' +
'"usesymm" keyword')
par.symmetry = usesymm2symmetry(par.usesymm)
symm = par.symmetry
if symm == 'off':
symm = {'point_group': False, 'time_reversal': False}
bzkpts_kc = kpts2ndarray(par.kpts, self.atoms)
kd = KPointDescriptor(bzkpts_kc, nspins, collinear)
m_av = magmom_av.round(decimals=3) # round off
id_a = zip(setups.id_a, *m_av.T)
symmetry = Symmetry(id_a, cell_cv, atoms.pbc, **symm)
kd.set_symmetry(atoms, symmetry, comm=world)
setups.set_symmetry(symmetry)
if par.gpts is not None:
N_c = np.array(par.gpts)
else:
h = par.h
if h is not None:
h /= Bohr
N_c = get_number_of_grid_points(cell_cv, h, mode, realspace,
kd.symmetry)
symmetry.check_grid(N_c)
width = par.width
if width is None:
if pbc_c.any():
width = 0.1 # eV
else:
width = 0.0
else:
assert par.occupations is None
if hasattr(self, 'time') or par.dtype == complex:
dtype = complex
else:
if kd.gamma:
dtype = float
else:
dtype = complex
nao = setups.nao
nvalence = setups.nvalence - par.charge
M_v = magmom_av.sum(0)
M = np.dot(M_v, M_v) ** 0.5
nbands = par.nbands
orbital_free = any(setup.orbital_free for setup in setups)
if orbital_free:
nbands = 1
if isinstance(nbands, basestring):
if nbands[-1] == '%':
basebands = int(nvalence + M + 0.5) // 2
nbands = int((float(nbands[:-1]) / 100) * basebands)
else:
raise ValueError('Integer Expected: Only use a string '
'if giving a percentage of occupied bands')
if nbands is None:
nbands = 0
for setup in setups:
nbands_from_atom = setup.get_default_nbands()
# Any obscure setup errors?
if nbands_from_atom < -(-setup.Nv // 2):
raise ValueError('Bad setup: This setup requests %d'
' bands but has %d electrons.'
% (nbands_from_atom, setup.Nv))
nbands += nbands_from_atom
nbands = min(nao, nbands)
elif nbands > nao and mode.name == 'lcao':
raise ValueError('Too many bands for LCAO calculation: '
'%d bands and only %d atomic orbitals!' %
(nbands, nao))
if nvalence < 0:
raise ValueError(
'Charge %f is not possible - not enough valence electrons' %
par.charge)
if nbands <= 0:
nbands = int(nvalence + M + 0.5) // 2 + (-nbands)
if nvalence > 2 * nbands and not orbital_free:
raise ValueError('Too few bands! Electrons: %f, bands: %d'
% (nvalence, nbands))
nbands *= ncomp
if par.width is not None:
self.text('**NOTE**: please start using '
'occupations=FermiDirac(width).')
if par.fixmom:
self.text('**NOTE**: please start using '
'occupations=FermiDirac(width, fixmagmom=True).')
if self.occupations is None:
if par.occupations is None:
# Create object for occupation numbers:
if orbital_free:
width = 0.0 # even for PBC
self.occupations = occupations.TFOccupations(width,
par.fixmom)
else:
self.occupations = occupations.FermiDirac(width,
par.fixmom)
else:
self.occupations = par.occupations
# If occupation numbers are changed, and we have wave functions,
# recalculate the occupation numbers
if self.wfs is not None and not isinstance(
self.wfs,
EmptyWaveFunctions):
self.occupations.calculate(self.wfs)
self.occupations.magmom = M_v[2]
cc = par.convergence
if mode.name == 'lcao':
niter_fixdensity = 0
else:
niter_fixdensity = None
if self.scf is None:
force_crit = cc['forces']
if force_crit is not None:
force_crit /= Hartree / Bohr
self.scf = SCFLoop(
cc['eigenstates'] / Hartree**2 * nvalence,
cc['energy'] / Hartree * max(nvalence, 1),
cc['density'] * nvalence,
par.maxiter, par.fixdensity,
niter_fixdensity,
force_crit)
parsize_kpt = par.parallel['kpt']
parsize_domain = par.parallel['domain']
parsize_bands = par.parallel['band']
if not realspace:
pbc_c = np.ones(3, bool)
if not self.wfs:
if parsize_domain == 'domain only': # XXX this was silly!
parsize_domain = world.size
parallelization = mpi.Parallelization(world,
nspins * kd.nibzkpts)
ndomains = None
if parsize_domain is not None:
ndomains = np.prod(parsize_domain)
if mode.name == 'pw':
if ndomains > 1:
raise ValueError('Planewave mode does not support '
'domain decomposition.')
ndomains = 1
parallelization.set(kpt=parsize_kpt,
domain=ndomains,
band=parsize_bands)
comms = parallelization.build_communicators()
domain_comm = comms['d']
kpt_comm = comms['k']
band_comm = comms['b']
kptband_comm = comms['D']
domainband_comm = comms['K']
self.comms = comms
kd.set_communicator(kpt_comm)
parstride_bands = par.parallel['stridebands']
# Unfortunately we need to remember that we adjusted the
# number of bands so we can print a warning if it differs
# from the number specified by the user. (The number can
# be inferred from the input parameters, but it's tricky
# because we allow negative numbers)
self.nbands_parallelization_adjustment = -nbands % band_comm.size
nbands += self.nbands_parallelization_adjustment
# I would like to give the following error message, but apparently
# there are cases, e.g. gpaw/test/gw_ppa.py, which involve
# nbands > nao and are supposed to work that way.
#if nbands > nao:
# raise ValueError('Number of bands %d adjusted for band '
# 'parallelization %d exceeds number of atomic '
# 'orbitals %d. This problem can be fixed '
# 'by reducing the number of bands a bit.'
# % (nbands, band_comm.size, nao))
bd = BandDescriptor(nbands, band_comm, parstride_bands)
if (self.density is not None and
self.density.gd.comm.size != domain_comm.size):
# Domain decomposition has changed, so we need to
# reinitialize density and hamiltonian:
if par.fixdensity:
raise RuntimeError(
'Density reinitialization conflict ' +
'with "fixdensity" - specify domain decomposition.')
self.density = None
self.hamiltonian = None
# Construct grid descriptor for coarse grids for wave functions:
gd = self.grid_descriptor_class(N_c, cell_cv, pbc_c,
domain_comm, parsize_domain)
# do k-point analysis here? XXX
args = (gd, nvalence, setups, bd, dtype, world, kd,
kptband_comm, self.timer)
if par.parallel['sl_auto']:
# Choose scalapack parallelization automatically
for key, val in par.parallel.items():
if (key.startswith('sl_') and key != 'sl_auto'
and val is not None):
raise ValueError("Cannot use 'sl_auto' together "
"with '%s'" % key)
max_scalapack_cpus = bd.comm.size * gd.comm.size
nprow = max_scalapack_cpus
npcol = 1
# Get a sort of reasonable number of columns/rows
while npcol < nprow and nprow % 2 == 0:
npcol *= 2
nprow //= 2
assert npcol * nprow == max_scalapack_cpus
# ScaLAPACK creates trouble if there aren't at least a few
# whole blocks; choose block size so there will always be
# several blocks. This will crash for small test systems,
# but so will ScaLAPACK in any case
blocksize = min(-(-nbands // 4), 64)
sl_default = (nprow, npcol, blocksize)
else:
sl_default = par.parallel['sl_default']
if mode.name == 'lcao':
# Layouts used for general diagonalizer
sl_lcao = par.parallel['sl_lcao']
if sl_lcao is None:
sl_lcao = sl_default
lcaoksl = get_KohnSham_layouts(sl_lcao, 'lcao',
gd, bd, domainband_comm, dtype,
nao=nao, timer=self.timer)
self.wfs = mode(collinear, lcaoksl, *args)
elif mode.name == 'fd' or mode.name == 'pw':
# buffer_size keyword only relevant for fdpw
buffer_size = par.parallel['buffer_size']
# Layouts used for diagonalizer
sl_diagonalize = par.parallel['sl_diagonalize']
if sl_diagonalize is None:
sl_diagonalize = sl_default
diagksl = get_KohnSham_layouts(sl_diagonalize, 'fd', # XXX
# choice of key 'fd' not so nice
gd, bd, domainband_comm, dtype,
buffer_size=buffer_size,
timer=self.timer)
# Layouts used for orthonormalizer
sl_inverse_cholesky = par.parallel['sl_inverse_cholesky']
if sl_inverse_cholesky is None:
sl_inverse_cholesky = sl_default
if sl_inverse_cholesky != sl_diagonalize:
message = 'sl_inverse_cholesky != sl_diagonalize ' \
'is not implemented.'
raise NotImplementedError(message)
orthoksl = get_KohnSham_layouts(sl_inverse_cholesky, 'fd',
gd, bd, domainband_comm, dtype,
buffer_size=buffer_size,
timer=self.timer)
# Use (at most) all available LCAO for initialization
lcaonbands = min(nbands, nao)
try:
lcaobd = BandDescriptor(lcaonbands, band_comm,
parstride_bands)
except RuntimeError:
initksl = None
else:
# Layouts used for general diagonalizer
# (LCAO initialization)
sl_lcao = par.parallel['sl_lcao']
if sl_lcao is None:
sl_lcao = sl_default
initksl = get_KohnSham_layouts(sl_lcao, 'lcao',
gd, lcaobd, domainband_comm,
dtype, nao=nao,
timer=self.timer)
if hasattr(self, 'time'):
assert mode.name == 'fd'
from gpaw.tddft import TimeDependentWaveFunctions
self.wfs = TimeDependentWaveFunctions(
par.stencils[0],
diagksl,
orthoksl,
initksl,
gd,
nvalence,
setups,
bd,
world,
kd,
kptband_comm,
self.timer)
elif mode.name == 'fd':
self.wfs = mode(par.stencils[0], diagksl,
orthoksl, initksl, *args)
else:
assert mode.name == 'pw'
self.wfs = mode(diagksl, orthoksl, initksl, *args)
else:
self.wfs = mode(self, *args)
else:
self.wfs.set_setups(setups)
if not self.wfs.eigensolver:
# Number of bands to converge:
nbands_converge = cc['bands']
if nbands_converge == 'all':
nbands_converge = nbands
elif nbands_converge != 'occupied':
assert isinstance(nbands_converge, int)
if nbands_converge < 0:
nbands_converge += nbands
eigensolver = get_eigensolver(par.eigensolver, mode,
par.convergence)
eigensolver.nbands_converge = nbands_converge
# XXX Eigensolver class doesn't define an nbands_converge property
if isinstance(xc, SIC):
eigensolver.blocksize = 1
self.wfs.set_eigensolver(eigensolver)
if self.density is None:
gd = self.wfs.gd
if par.stencils[1] != 9:
# Construct grid descriptor for fine grids for densities
# and potentials:
finegd = gd.refine()
else:
# Special case (use only coarse grid):
finegd = gd
if realspace:
self.density = RealSpaceDensity(
gd, finegd, nspins, par.charge + setups.core_charge,
collinear, par.stencils[1])
else:
self.density = pw.ReciprocalSpaceDensity(
gd, finegd, nspins, par.charge + setups.core_charge,
collinear)
self.density.initialize(setups, self.timer, magmom_av, par.hund)
self.density.set_mixer(par.mixer)
if self.hamiltonian is None:
gd, finegd = self.density.gd, self.density.finegd
if realspace:
self.hamiltonian = RealSpaceHamiltonian(
gd, finegd, nspins, setups, self.timer, xc,
world, self.wfs.kptband_comm, par.external,
collinear, par.poissonsolver, par.stencils[1])
else:
self.hamiltonian = pw.ReciprocalSpaceHamiltonian(
gd, finegd, self.density.pd2, self.density.pd3,
nspins, setups, self.timer, xc, world,
self.wfs.kptband_comm, par.external, collinear)
xc.initialize(self.density, self.hamiltonian, self.wfs,
self.occupations)
self.text()
self.print_memory_estimate(self.txt, maxdepth=memory_estimate_depth)
self.txt.flush()
self.timer.print_info(self)
if dry_run:
self.dry_run()
if realspace and \
self.hamiltonian.poisson.get_description() == 'FDTD+TDDFT':
self.hamiltonian.poisson.set_density(self.density)
self.hamiltonian.poisson.print_messages(self.text)
self.txt.flush()
self.initialized = True
self._changed_keywords.clear()