def __init__(self,
stencil,
diagksl,
orthoksl,
initksl,
gd,
nvalence,
setups,
bd,
world,
kd,
kptband_comm,
timer=None):
FDWaveFunctions.__init__(self, stencil, diagksl, orthoksl, initksl, gd,
nvalence, setups, bd, complex, world, kd,
kptband_comm, timer)
def __init__(self, stencil, diagksl, orthoksl, initksl, gd, nvalence,
setups, bd, dtype, world, kd, kptband_comm, timer):
assert dtype == complex
FDWaveFunctions.__init__(self,
stencil,
diagksl,
orthoksl,
initksl,
gd,
nvalence,
setups,
bd,
dtype,
world,
kd,
kptband_comm,
timer=timer)
def __init__(self, stencil, parallel, initksl, gd, nvalence, collinear,
setups, bd, dtype, world, kd, kptband_comm, timer):
assert dtype == complex
FDWaveFunctions.__init__(self,
stencil,
parallel,
initksl,
gd,
nvalence,
setups,
bd,
dtype,
world,
kd,
kptband_comm,
collinear=collinear,
timer=timer)
self.overlap = self.make_overlap()
def setUp(self):
UTLocalizedFunctionSetup.setUp(self)
fdksl = get_KohnSham_layouts(None, 'fd', self.gd, self.bd, self.dtype)
lcaoksl = get_KohnSham_layouts(None,
'lcao',
self.gd,
self.bd,
self.dtype,
nao=self.setups.nao)
args = (self.gd, self.setups.nvalence, self.setups, self.bd,
self.dtype, world, self.kd)
self.wfs = FDWaveFunctions(p.stencils[0], fdksl, fdksl, lcaoksl, *args)
self.wfs.rank_a = self.rank0_a
self.allocate(self.wfs.kpt_u, self.wfs.rank_a)
assert self.allocated
for kpt in self.wfs.kpt_u:
for a, P_ni in kpt.P_ani.items():
for myn, P_i in enumerate(P_ni):
n = self.bd.global_index(myn)
P_i[:] = 1e12 * kpt.s + 1e9 * kpt.k + 1e6 * a + 1e3 * n \
+ np.arange(self.setups[a].ni, dtype=self.dtype)
def setUp(self):
UTLocalizedFunctionSetup.setUp(self)
fdksl = get_KohnSham_layouts(None, 'fd', self.gd, self.bd,
self.dtype)
lcaoksl = get_KohnSham_layouts(None, 'lcao', self.gd, self.bd,
self.dtype, nao=self.setups.nao)
args = (self.gd, self.setups.nvalence, self.setups,
self.bd, self.dtype, world, self.kd)
self.wfs = FDWaveFunctions(p.stencils[0], fdksl, fdksl, lcaoksl, *args)
self.wfs.rank_a = self.rank0_a
self.allocate(self.wfs.kpt_u, self.wfs.rank_a)
assert self.allocated
for kpt in self.wfs.kpt_u:
for a,P_ni in kpt.P_ani.items():
for myn,P_i in enumerate(P_ni):
n = self.bd.global_index(myn)
P_i[:] = 1e12 * kpt.s + 1e9 * kpt.k + 1e6 * a + 1e3 * n \
+ np.arange(self.setups[a].ni, dtype=self.dtype)
def __init__(self, stencil, diagksl, orthoksl, initksl, gd, nvalence, setups,
bd, world, kd, timer=None):
FDWaveFunctions.__init__(self, stencil, diagksl, orthoksl, initksl,
gd, nvalence, setups, bd, complex, world,
kd, timer)
def __init__(self, filename=None, **kwargs):
"""ASE-calculator interface.
The following parameters can be used: nbands, xc, kpts,
spinpol, gpts, h, charge, usesymm, 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()
self.timer = self.timer_class()
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)
self.set(**kwargs)
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)
self.print_cell_and_parameters()
self.observers = []
class PAW(PAWTextOutput):
"""This is the main calculation object for doing a PAW calculation."""
timer_class = Timer
def __init__(self, filename=None, **kwargs):
"""ASE-calculator interface.
The following parameters can be used: nbands, xc, kpts,
spinpol, gpts, h, charge, usesymm, 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()
self.timer = self.timer_class()
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)
self.set(**kwargs)
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)
self.print_cell_and_parameters()
self.observers = []
def read(self, reader):
gpaw.io.read(self, reader)
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
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 not key 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 p['mode'] == 'fd':
continue
if key == 'eigensolver':
self.wfs.set_eigensolver(None)
if key in ['fixmom', 'mixer',
'verbose', 'txt', 'hund', 'random',
'eigensolver', 'idiotproof', 'notify', 'usefractrans']:
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', 'occupations']:
self.hamiltonian = None
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']:
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.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)
if 'converged' in hooks:
hooks['converged'](self)
elif converge:
if 'not_converged' in hooks:
hooks['not_converged'](self)
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
self.set_text(par.txt, 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()
# Generate new xc functional only when it is reset by set
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 xc.orbital_dependent and mode == 'lcao':
raise NotImplementedError('LCAO mode does not support '
'orbital-dependent XC functionals.')
if mode == 'pw':
mode = PW()
if mode == 'fd' and par.usefractrans:
raise NotImplementedError('FD mode does not support '
'fractional translations.')
if mode == 'lcao' and par.usefractrans:
raise Warning('Fractional translations have not been tested '
'with LCAO mode. Use with care!')
if par.realspace is None:
realspace = not isinstance(mode, PW)
else:
realspace = par.realspace
if isinstance(mode, PW):
assert not realspace
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)
if par.filter is None and not isinstance(mode, PW):
gamma = 1.6
hmax = ((np.linalg.inv(cell_cv)**2).sum(0)**-0.5 / N_c).max()
def filter(rgd, rcut, f_r, l=0):
gcut = np.pi / hmax - 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
# K-point descriptor
bzkpts_kc = kpts2ndarray(par.kpts, self.atoms)
kd = KPointDescriptor(bzkpts_kc, nspins, collinear, par.usefractrans)
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
## rbw: If usefractrans=True, kd.set_symmetry might overwrite N_c.
## This is necessary, because N_c must be dividable by 1/(fractional translation),
## f.e. fractional translations of a grid point must land on a grid point.
N_c = kd.set_symmetry(atoms, setups, magmom_av, par.usesymm, N_c, world)
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
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 == '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:
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:
self.occupations = occupations.FermiDirac(width, par.fixmom)
else:
self.occupations = par.occupations
self.occupations.magmom = M_v[2]
cc = par.convergence
if mode == 'lcao':
niter_fixdensity = 0
else:
niter_fixdensity = None
if self.scf is None:
self.scf = SCFLoop(
cc['eigenstates'] / Hartree**2 * nvalence,
cc['energy'] / Hartree * max(nvalence, 1),
cc['density'] * nvalence,
par.maxiter, par.fixdensity,
niter_fixdensity)
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 isinstance(mode, 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)
domain_comm, kpt_comm, band_comm = \
parallelization.build_communicators()
#domain_comm, kpt_comm, band_comm = mpi.distribute_cpus(
# parsize_domain, parsize_bands,
# nspins, kd.nibzkpts, world, par.idiotproof, mode)
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, 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 == '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, dtype,
nao=nao, timer=self.timer)
if collinear:
self.wfs = LCAOWaveFunctions(lcaoksl, *args)
else:
from gpaw.xc.noncollinear import \
NonCollinearLCAOWaveFunctions
self.wfs = NonCollinearLCAOWaveFunctions(lcaoksl, *args)
elif mode == 'fd' or isinstance(mode, 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',
gd, bd, 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, 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, dtype,
nao=nao,
timer=self.timer)
if hasattr(self, 'time'):
assert mode == 'fd'
from gpaw.tddft import TimeDependentWaveFunctions
self.wfs = TimeDependentWaveFunctions(par.stencils[0],
diagksl, orthoksl, initksl, gd, nvalence, setups,
bd, world, kd, self.timer)
elif mode == 'fd':
self.wfs = FDWaveFunctions(par.stencils[0], diagksl,
orthoksl, initksl, *args)
else:
# Planewave basis:
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 = 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, par.external,
collinear, par.poissonsolver, par.stencils[1], world)
else:
self.hamiltonian = ReciprocalSpaceHamiltonian(
gd, finegd,
self.density.pd2, self.density.pd3,
nspins, setups, self.timer, xc, par.external,
collinear, world)
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()
self.initialized = True
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 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.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* every *n* iterations using *args* and
*kwargs* as arguments."""
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:
if ((iter % n) == 0) != final:
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, 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 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
self.set_text(par.txt, 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()
# Generate new xc functional only when it is reset by set
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 xc.orbital_dependent and mode == 'lcao':
raise NotImplementedError('LCAO mode does not support '
'orbital-dependent XC functionals.')
if mode == 'pw':
mode = PW()
if mode == 'fd' and par.usefractrans:
raise NotImplementedError('FD mode does not support '
'fractional translations.')
if mode == 'lcao' and par.usefractrans:
raise Warning('Fractional translations have not been tested '
'with LCAO mode. Use with care!')
if par.realspace is None:
realspace = not isinstance(mode, PW)
else:
realspace = par.realspace
if isinstance(mode, PW):
assert not realspace
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)
if par.filter is None and not isinstance(mode, PW):
gamma = 1.6
hmax = ((np.linalg.inv(cell_cv)**2).sum(0)**-0.5 / N_c).max()
def filter(rgd, rcut, f_r, l=0):
gcut = np.pi / hmax - 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
# K-point descriptor
bzkpts_kc = kpts2ndarray(par.kpts, self.atoms)
kd = KPointDescriptor(bzkpts_kc, nspins, collinear, par.usefractrans)
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
## rbw: If usefractrans=True, kd.set_symmetry might overwrite N_c.
## This is necessary, because N_c must be dividable by 1/(fractional translation),
## f.e. fractional translations of a grid point must land on a grid point.
N_c = kd.set_symmetry(atoms, setups, magmom_av, par.usesymm, N_c, world)
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
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 == '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:
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:
self.occupations = occupations.FermiDirac(width, par.fixmom)
else:
self.occupations = par.occupations
self.occupations.magmom = M_v[2]
cc = par.convergence
if mode == 'lcao':
niter_fixdensity = 0
else:
niter_fixdensity = None
if self.scf is None:
self.scf = SCFLoop(
cc['eigenstates'] / Hartree**2 * nvalence,
cc['energy'] / Hartree * max(nvalence, 1),
cc['density'] * nvalence,
par.maxiter, par.fixdensity,
niter_fixdensity)
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 isinstance(mode, 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)
domain_comm, kpt_comm, band_comm = \
parallelization.build_communicators()
#domain_comm, kpt_comm, band_comm = mpi.distribute_cpus(
# parsize_domain, parsize_bands,
# nspins, kd.nibzkpts, world, par.idiotproof, mode)
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, 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 == '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, dtype,
nao=nao, timer=self.timer)
if collinear:
self.wfs = LCAOWaveFunctions(lcaoksl, *args)
else:
from gpaw.xc.noncollinear import \
NonCollinearLCAOWaveFunctions
self.wfs = NonCollinearLCAOWaveFunctions(lcaoksl, *args)
elif mode == 'fd' or isinstance(mode, 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',
gd, bd, 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, 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, dtype,
nao=nao,
timer=self.timer)
if hasattr(self, 'time'):
assert mode == 'fd'
from gpaw.tddft import TimeDependentWaveFunctions
self.wfs = TimeDependentWaveFunctions(par.stencils[0],
diagksl, orthoksl, initksl, gd, nvalence, setups,
bd, world, kd, self.timer)
elif mode == 'fd':
self.wfs = FDWaveFunctions(par.stencils[0], diagksl,
orthoksl, initksl, *args)
else:
# Planewave basis:
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 = 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, par.external,
collinear, par.poissonsolver, par.stencils[1], world)
else:
self.hamiltonian = ReciprocalSpaceHamiltonian(
gd, finegd,
self.density.pd2, self.density.pd3,
nspins, setups, self.timer, xc, par.external,
collinear, world)
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()
self.initialized = True
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.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)
if 'converged' in hooks:
hooks['converged'](self)
elif converge:
if 'not_converged' in hooks:
hooks['not_converged'](self)
self.txt.write(oops)
raise KohnShamConvergenceError(
'Did not converge! See text output for help.')
return True
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
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 not key 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 p['mode'] == 'fd':
continue
if key == 'eigensolver':
self.wfs.set_eigensolver(None)
if key in ['fixmom', 'mixer',
'verbose', 'txt', 'hund', 'random',
'eigensolver', 'idiotproof', 'notify', 'usefractrans']:
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', 'occupations']:
self.hamiltonian = None
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']:
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)
class UTProjectorFunctionSetup(UTLocalizedFunctionSetup):
__doc__ = UTDomainParallelSetup.__doc__ + """
Projection expansion coefficients are distributed over domains."""
def setUp(self):
UTLocalizedFunctionSetup.setUp(self)
fdksl = get_KohnSham_layouts(None, 'fd', self.gd, self.bd, self.dtype)
lcaoksl = get_KohnSham_layouts(None,
'lcao',
self.gd,
self.bd,
self.dtype,
nao=self.setups.nao)
args = (self.gd, self.setups.nvalence, self.setups, self.bd,
self.dtype, world, self.kd)
self.wfs = FDWaveFunctions(p.stencils[0], fdksl, fdksl, lcaoksl, *args)
self.wfs.rank_a = self.rank0_a
self.allocate(self.wfs.kpt_u, self.wfs.rank_a)
assert self.allocated
for kpt in self.wfs.kpt_u:
for a, P_ni in kpt.P_ani.items():
for myn, P_i in enumerate(P_ni):
n = self.bd.global_index(myn)
P_i[:] = 1e12 * kpt.s + 1e9 * kpt.k + 1e6 * a + 1e3 * n \
+ np.arange(self.setups[a].ni, dtype=self.dtype)
def tearDown(self):
del self.wfs
UTLocalizedFunctionSetup.tearDown(self)
def allocate(self, kpt_u, rank_a):
if self.allocated:
raise RuntimeError('Already allocated!')
my_atom_indices = np.argwhere(rank_a == self.gd.comm.rank).ravel()
self.holm_nielsen_check(my_atom_indices)
self.wfs.allocate_arrays_for_projections(my_atom_indices) #XXX
self.chk_una = np.zeros((self.kd_old.nks, self.bd.nbands, self.natoms),
dtype=np.int64)
self.allocated = True
def update_references(self, kpt_u, rank_a):
requests = []
kpt_comm, band_comm, domain_comm = self.kd_old.comm, self.bd.comm, self.gd.comm
for u in range(self.kd_old.nks):
kpt_rank, myu = self.kd_old.who_has(u)
for n in range(self.bd.nbands):
band_rank, myn = self.bd.who_has(n)
for a in range(self.natoms):
domain_rank = rank_a[a]
if kpt_comm.rank == kpt_rank and \
band_comm.rank == band_rank and \
domain_comm.rank == domain_rank:
kpt = kpt_u[myu]
chk = md5_array(kpt.P_ani[a][myn], numeric=True)
if world.rank == 0:
self.chk_una[u, n, a] = chk
else:
requests.append(world.send(np.array([chk], \
dtype=np.int64), 0, 1303+a, block=False))
elif world.rank == 0:
world_rank = rank_a[a] + \
band_rank * domain_comm.size + \
kpt_rank * domain_comm.size * band_comm.size
chk = self.chk_una[u, n,
a:a + 1] #XXX hack to get pointer
requests.append(world.receive(chk, world_rank, \
1303+a, block=False))
world.waitall(requests)
world.broadcast(self.chk_una, 0)
def check_values(self, kpt_u, rank_a):
for kpt in kpt_u:
self.holm_nielsen_check(kpt.P_ani.keys())
# Compare to reference checksums
ret = True
kpt_comm, band_comm, domain_comm = self.kd_old.comm, self.bd.comm, self.gd.comm
for u in range(self.kd_old.nks):
kpt_rank, myu = self.kd_old.who_has(u)
for n in range(self.bd.nbands):
band_rank, myn = self.bd.who_has(n)
for a in range(self.natoms):
domain_rank = rank_a[a]
if kpt_comm.rank == kpt_rank and \
band_comm.rank == band_rank and \
domain_comm.rank == domain_rank:
kpt = kpt_u[myu]
chk = md5_array(kpt.P_ani[a][myn], numeric=True)
ret &= (chk == self.chk_una[u, n, a])
self.assertTrue(ret)
# =================================
def test_initial_consistency(self):
self.update_references(self.wfs.kpt_u, self.wfs.rank_a)
self.check_values(self.wfs.kpt_u, self.wfs.rank_a)
def test_redistribution_to_domains(self):
self.update_references(self.wfs.kpt_u, self.wfs.rank_a)
spos_ac = self.atoms.get_scaled_positions() % 1.0
self.wfs.set_positions(spos_ac)
self.check_values(self.wfs.kpt_u, self.wfs.rank_a)
def test_redistribution_to_same(self):
self.update_references(self.wfs.kpt_u, self.wfs.rank_a)
spos_ac = self.atoms.get_scaled_positions() % 1.0
self.wfs.set_positions(spos_ac)
self.wfs.set_positions(spos_ac)
self.check_values(self.wfs.kpt_u, self.wfs.rank_a)
class UTProjectorFunctionSetup(UTLocalizedFunctionSetup):
__doc__ = UTDomainParallelSetup.__doc__ + """
Projection expansion coefficients are distributed over domains."""
def setUp(self):
UTLocalizedFunctionSetup.setUp(self)
fdksl = get_KohnSham_layouts(None, 'fd', self.gd, self.bd,
self.dtype)
lcaoksl = get_KohnSham_layouts(None, 'lcao', self.gd, self.bd,
self.dtype, nao=self.setups.nao)
args = (self.gd, self.setups.nvalence, self.setups,
self.bd, self.dtype, world, self.kd)
self.wfs = FDWaveFunctions(p.stencils[0], fdksl, fdksl, lcaoksl, *args)
self.wfs.rank_a = self.rank0_a
self.allocate(self.wfs.kpt_u, self.wfs.rank_a)
assert self.allocated
for kpt in self.wfs.kpt_u:
for a,P_ni in kpt.P_ani.items():
for myn,P_i in enumerate(P_ni):
n = self.bd.global_index(myn)
P_i[:] = 1e12 * kpt.s + 1e9 * kpt.k + 1e6 * a + 1e3 * n \
+ np.arange(self.setups[a].ni, dtype=self.dtype)
def tearDown(self):
del self.wfs
UTLocalizedFunctionSetup.tearDown(self)
def allocate(self, kpt_u, rank_a):
if self.allocated:
raise RuntimeError('Already allocated!')
my_atom_indices = np.argwhere(rank_a == self.gd.comm.rank).ravel()
self.holm_nielsen_check(my_atom_indices)
self.wfs.allocate_arrays_for_projections(my_atom_indices) #XXX
self.chk_una = np.zeros((self.kd_old.nks, self.bd.nbands,
self.natoms), dtype=np.int64)
self.allocated = True
def update_references(self, kpt_u, rank_a):
requests = []
kpt_comm, band_comm, domain_comm = self.kd_old.comm, self.bd.comm, self.gd.comm
for u in range(self.kd_old.nks):
kpt_rank, myu = self.kd_old.who_has(u)
for n in range(self.bd.nbands):
band_rank, myn = self.bd.who_has(n)
for a in range(self.natoms):
domain_rank = rank_a[a]
if kpt_comm.rank == kpt_rank and \
band_comm.rank == band_rank and \
domain_comm.rank == domain_rank:
kpt = kpt_u[myu]
chk = md5_array(kpt.P_ani[a][myn], numeric=True)
if world.rank == 0:
self.chk_una[u,n,a] = chk
else:
requests.append(world.send(np.array([chk], \
dtype=np.int64), 0, 1303+a, block=False))
elif world.rank == 0:
world_rank = rank_a[a] + \
band_rank * domain_comm.size + \
kpt_rank * domain_comm.size * band_comm.size
chk = self.chk_una[u,n,a:a+1] #XXX hack to get pointer
requests.append(world.receive(chk, world_rank, \
1303+a, block=False))
world.waitall(requests)
world.broadcast(self.chk_una, 0)
def check_values(self, kpt_u, rank_a):
for kpt in kpt_u:
self.holm_nielsen_check(kpt.P_ani.keys())
# Compare to reference checksums
ret = True
kpt_comm, band_comm, domain_comm = self.kd_old.comm, self.bd.comm, self.gd.comm
for u in range(self.kd_old.nks):
kpt_rank, myu = self.kd_old.who_has(u)
for n in range(self.bd.nbands):
band_rank, myn = self.bd.who_has(n)
for a in range(self.natoms):
domain_rank = rank_a[a]
if kpt_comm.rank == kpt_rank and \
band_comm.rank == band_rank and \
domain_comm.rank == domain_rank:
kpt = kpt_u[myu]
chk = md5_array(kpt.P_ani[a][myn], numeric=True)
ret &= (chk == self.chk_una[u,n,a])
self.assertTrue(ret)
# =================================
def test_initial_consistency(self):
self.update_references(self.wfs.kpt_u, self.wfs.rank_a)
self.check_values(self.wfs.kpt_u, self.wfs.rank_a)
def test_redistribution_to_domains(self):
self.update_references(self.wfs.kpt_u, self.wfs.rank_a)
spos_ac = self.atoms.get_scaled_positions() % 1.0
self.wfs.set_positions(spos_ac)
self.check_values(self.wfs.kpt_u, self.wfs.rank_a)
def test_redistribution_to_same(self):
self.update_references(self.wfs.kpt_u, self.wfs.rank_a)
spos_ac = self.atoms.get_scaled_positions() % 1.0
self.wfs.set_positions(spos_ac)
self.wfs.set_positions(spos_ac)
self.check_values(self.wfs.kpt_u, self.wfs.rank_a)
def set(self, **kwargs):
p = self.input_parameters
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 not key 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 p["mode"] == "fd":
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", "occupations"]:
self.hamiltonian = None
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"]:
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)
class PAW(PAWTextOutput):
"""This is the main calculation object for doing a PAW calculation."""
timer_class = Timer
def __init__(self, filename=None, **kwargs):
"""ASE-calculator interface.
The following parameters can be used: `nbands`, `xc`, `kpts`,
`spinpol`, `gpts`, `h`, `charge`, `usesymm`, `width`, `mixer`,
`hund`, `lmax`, `fixdensity`, `convergence`, `txt`, `parallel`,
`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()
self.timer = self.timer_class()
self.scf = None
self.forces = ForceCalculator(self.timer)
self.wfs = EmptyWaveFunctions()
self.occupations = None
self.density = None
self.hamiltonian = None
self.atoms = None
self.initialized = False
# 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)
self.set(**kwargs)
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)
self.print_cell_and_parameters()
self.observers = []
def read(self, reader):
gpaw.io.read(self, reader)
def set(self, **kwargs):
p = self.input_parameters
# Prune input for things that didn't change
for key, value in kwargs.items():
if key == 'kpts':
oldbzk_kc = kpts2ndarray(p.kpts)
newbzk_kc = kpts2ndarray(value)
if (len(oldbzk_kc) == len(newbzk_kc) and
(oldbzk_kc == newbzk_kc).all()):
kwargs.pop('kpts')
elif np.all(p[key] == value):
kwargs.pop(key)
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]
tmp.update(kwargs[name])
kwargs[name] = tmp
self.initialized = False
for key in kwargs:
if key == 'basis' and p['mode'] == 'fd':
continue
if key == 'eigensolver':
self.wfs.set_eigensolver(None)
if key in ['fixmom', 'mixer',
'verbose', 'txt', 'hund', 'random',
'eigensolver', 'poissonsolver', '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',
'occupations']:
self.hamiltonian = None
self.occupations = None
elif key in ['charge']:
self.hamiltonian = None
self.density = None
self.wfs = EmptyWaveFunctions()
self.occupations = None
elif key in ['kpts', 'nbands']:
self.wfs = EmptyWaveFunctions()
self.occupations = None
elif key in ['h', 'gpts', 'setups', 'spinpol', 'usesymm',
'parallel', 'communicator', 'dtype']:
self.density = None
self.occupations = None
self.hamiltonian = None
self.wfs = EmptyWaveFunctions()
elif key in ['mode', '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."""
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
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.call_observers(iter)
self.print_iteration(iter)
self.iter = iter
self.timer.stop('SCF-cycle')
if self.scf.converged:
self.call_observers(iter, final=True)
self.print_converged(iter)
if 'converged' in hooks:
hooks['converged'](self)
elif converge:
if 'not_converged' in hooks:
hooks['not_converged'](self)
raise KohnShamConvergenceError('Did not converge!')
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.scf.reset()
self.forces.reset()
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
self.set_text(par.txt, par.verbose)
natoms = len(atoms)
pos_av = atoms.get_positions() / Bohr
cell_cv = atoms.get_cell()
pbc_c = atoms.get_pbc()
Z_a = atoms.get_atomic_numbers()
magmom_a = atoms.get_initial_magnetic_moments()
magnetic = magmom_a.any()
spinpol = par.spinpol
if par.hund:
if natoms != 1:
raise ValueError('hund=True arg only valid for single atoms!')
spinpol = True
if spinpol is None:
spinpol = magnetic
elif magnetic and not spinpol:
raise ValueError('Non-zero initial magnetic moment for a '
'spin-paired calculation!')
nspins = 1 + int(spinpol)
if isinstance(par.xc, str):
xc = XC(par.xc)
else:
xc = par.xc
setups = Setups(Z_a, par.setups, par.basis, par.lmax, xc, world)
# K-point descriptor
kd = KPointDescriptor(par.kpts, nspins)
width = par.width
if width is None:
if kd.gamma:
width = 0.0
else:
width = 0.1 # eV
else:
assert par.occupations is None
if par.gpts is not None and par.h is None:
N_c = np.array(par.gpts)
else:
if par.h is None:
self.text('Using default value for grid spacing.')
h = 0.2
else:
h = par.h
N_c = h2gpts(h, cell_cv)
cell_cv /= Bohr
if hasattr(self, 'time') or par.dtype==complex:
dtype = complex
else:
if kd.gamma:
dtype = float
else:
dtype = complex
kd.set_symmetry(atoms, setups, par.usesymm, N_c)
nao = setups.nao
nvalence = setups.nvalence - par.charge
nbands = par.nbands
if nbands is None:
nbands = nao
elif nbands > nao and par.mode == '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)
M = magmom_a.sum()
if par.hund:
f_si = setups[0].calculate_initial_occupation_numbers(
magmom=0, hund=True, charge=par.charge, nspins=nspins)
Mh = f_si[0].sum() - f_si[1].sum()
if magnetic and M != Mh:
raise RuntimeError('You specified a magmom that does not'
'agree with hunds rule!')
else:
M = Mh
if nbands <= 0:
nbands = int(nvalence + M + 0.5) // 2 + (-nbands)
if nvalence > 2 * nbands:
raise ValueError('Too few bands! Electrons: %d, bands: %d'
% (nvalence, nbands))
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:
self.occupations = occupations.FermiDirac(width, par.fixmom)
else:
self.occupations = par.occupations
self.occupations.magmom = M
cc = par.convergence
if par.mode == 'lcao':
niter_fixdensity = 0
else:
niter_fixdensity = None
if self.scf is None:
self.scf = SCFLoop(
cc['eigenstates'] * nvalence,
cc['energy'] / Hartree * max(nvalence, 1),
cc['density'] * nvalence,
par.maxiter, par.fixdensity,
niter_fixdensity)
parsize, parsize_bands = par.parallel['domain'], par.parallel['band']
if parsize_bands is None:
parsize_bands = 1
# TODO delete/restructure so all checks are in BandDescriptor
if nbands % parsize_bands != 0:
raise RuntimeError('Cannot distribute %d bands to %d processors' %
(nbands, parsize_bands))
if not self.wfs:
if parsize == 'domain only': #XXX this was silly!
parsize = world.size
domain_comm, kpt_comm, band_comm = mpi.distribute_cpus(parsize,
parsize_bands, nspins, kd.nibzkpts, world, par.idiotproof)
kd.set_communicator(kpt_comm)
parstride_bands = par.parallel['stridebands']
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("I'm confused - please specify parsize."
)
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)
# do k-point analysis here? XXX
args = (gd, nvalence, setups, bd, dtype, world, kd, self.timer)
if par.mode == 'lcao':
# Layouts used for general diagonalizer
sl_lcao = par.parallel['sl_lcao']
if sl_lcao is None:
sl_lcao = par.parallel['sl_default']
lcaoksl = get_KohnSham_layouts(sl_lcao, 'lcao',
gd, bd, dtype,
nao=nao, timer=self.timer)
self.wfs = LCAOWaveFunctions(lcaoksl, *args)
elif par.mode == 'fd' or isinstance(par.mode, 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 = par.parallel['sl_default']
diagksl = get_KohnSham_layouts(sl_diagonalize, 'fd',
gd, bd, 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 = par.parallel['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, dtype,
buffer_size=buffer_size,
timer=self.timer)
# Use (at most) all available LCAO for initialization
lcaonbands = min(nbands, nao)
lcaobd = BandDescriptor(lcaonbands, band_comm, parstride_bands)
assert nbands <= nao or bd.comm.size == 1
assert lcaobd.mynbands == min(bd.mynbands, nao) #XXX
# Layouts used for general diagonalizer (LCAO initialization)
sl_lcao = par.parallel['sl_lcao']
if sl_lcao is None:
sl_lcao = par.parallel['sl_default']
initksl = get_KohnSham_layouts(sl_lcao, 'lcao',
gd, lcaobd, dtype,
nao=nao,
timer=self.timer)
if par.mode == 'fd':
self.wfs = FDWaveFunctions(par.stencils[0], diagksl,
orthoksl, initksl, *args)
else:
# Planewave basis:
self.wfs = par.mode(diagksl, orthoksl, initksl,
gd, nvalence, setups, bd,
world, kd, self.timer)
else:
self.wfs = par.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, par.mode,
par.convergence)
eigensolver.nbands_converge = nbands_converge
# XXX Eigensolver class doesn't define an nbands_converge property
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
self.density = Density(gd, finegd, nspins,
par.charge + setups.core_charge)
self.density.initialize(setups, par.stencils[1], self.timer,
magmom_a, par.hund)
self.density.set_mixer(par.mixer)
if self.hamiltonian is None:
gd, finegd = self.density.gd, self.density.finegd
self.hamiltonian = Hamiltonian(gd, finegd, nspins,
setups, par.stencils[1], self.timer,
xc, par.poissonsolver,
par.external)
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()
if dry_run:
self.dry_run()
self.initialized = True
def dry_run(self):
# Can be overridden like in gpaw.atom.atompaw
self.print_cell_and_parameters()
self.txt.flush()
raise SystemExit
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.nct.set_positions(spos_ac)
self.density.ghat.set_positions(spos_ac)
self.density.nct_G = self.density.gd.zeros()
self.density.nct.add(self.density.nct_G, 1.0 / self.density.nspins)
self.density.interpolate()
self.density.calculate_pseudo_charge(0)
self.hamiltonian.set_positions(spos_ac, self.wfs.rank_a)
self.hamiltonian.update(self.density)
def attach(self, function, n, *args, **kwargs):
"""Register observer function.
Call *function* every *n* iterations using *args* and
*kwargs* as arguments."""
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:
if ((iter % n) == 0) != final:
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."""
mem_init = maxrss() # XXX initial overhead includes part of Hamiltonian
mem.subnode('Initial overhead', mem_init)
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
print >> txt, 'Memory estimate'
print >> txt, '---------------'
mem = MemNode('Calculator', 0)
try:
self.estimate_memory(mem)
except AttributeError, m:
print >> txt, 'Attribute error:', m
print >> txt, 'Some object probably lacks estimate_memory() method'
print >> txt, 'Memory breakdown may be incomplete'
totalsize = mem.calculate_size()
mem.write(txt, maxdepth=maxdepth)
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
self.set_text(par.txt, par.verbose)
natoms = len(atoms)
pos_av = atoms.get_positions() / Bohr
cell_cv = atoms.get_cell()
pbc_c = atoms.get_pbc()
Z_a = atoms.get_atomic_numbers()
magmom_a = atoms.get_initial_magnetic_moments()
magnetic = magmom_a.any()
spinpol = par.spinpol
if par.hund:
if natoms != 1:
raise ValueError('hund=True arg only valid for single atoms!')
spinpol = True
if spinpol is None:
spinpol = magnetic
elif magnetic and not spinpol:
raise ValueError('Non-zero initial magnetic moment for a '
'spin-paired calculation!')
nspins = 1 + int(spinpol)
if isinstance(par.xc, str):
xc = XC(par.xc)
else:
xc = par.xc
setups = Setups(Z_a, par.setups, par.basis, par.lmax, xc, world)
# K-point descriptor
kd = KPointDescriptor(par.kpts, nspins)
width = par.width
if width is None:
if kd.gamma:
width = 0.0
else:
width = 0.1 # eV
else:
assert par.occupations is None
if par.gpts is not None and par.h is None:
N_c = np.array(par.gpts)
else:
if par.h is None:
self.text('Using default value for grid spacing.')
h = 0.2
else:
h = par.h
N_c = h2gpts(h, cell_cv)
cell_cv /= Bohr
if hasattr(self, 'time') or par.dtype==complex:
dtype = complex
else:
if kd.gamma:
dtype = float
else:
dtype = complex
kd.set_symmetry(atoms, setups, par.usesymm, N_c)
nao = setups.nao
nvalence = setups.nvalence - par.charge
nbands = par.nbands
if nbands is None:
nbands = nao
elif nbands > nao and par.mode == '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)
M = magmom_a.sum()
if par.hund:
f_si = setups[0].calculate_initial_occupation_numbers(
magmom=0, hund=True, charge=par.charge, nspins=nspins)
Mh = f_si[0].sum() - f_si[1].sum()
if magnetic and M != Mh:
raise RuntimeError('You specified a magmom that does not'
'agree with hunds rule!')
else:
M = Mh
if nbands <= 0:
nbands = int(nvalence + M + 0.5) // 2 + (-nbands)
if nvalence > 2 * nbands:
raise ValueError('Too few bands! Electrons: %d, bands: %d'
% (nvalence, nbands))
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:
self.occupations = occupations.FermiDirac(width, par.fixmom)
else:
self.occupations = par.occupations
self.occupations.magmom = M
cc = par.convergence
if par.mode == 'lcao':
niter_fixdensity = 0
else:
niter_fixdensity = None
if self.scf is None:
self.scf = SCFLoop(
cc['eigenstates'] * nvalence,
cc['energy'] / Hartree * max(nvalence, 1),
cc['density'] * nvalence,
par.maxiter, par.fixdensity,
niter_fixdensity)
parsize, parsize_bands = par.parallel['domain'], par.parallel['band']
if parsize_bands is None:
parsize_bands = 1
# TODO delete/restructure so all checks are in BandDescriptor
if nbands % parsize_bands != 0:
raise RuntimeError('Cannot distribute %d bands to %d processors' %
(nbands, parsize_bands))
if not self.wfs:
if parsize == 'domain only': #XXX this was silly!
parsize = world.size
domain_comm, kpt_comm, band_comm = mpi.distribute_cpus(parsize,
parsize_bands, nspins, kd.nibzkpts, world, par.idiotproof)
kd.set_communicator(kpt_comm)
parstride_bands = par.parallel['stridebands']
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("I'm confused - please specify parsize."
)
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)
# do k-point analysis here? XXX
args = (gd, nvalence, setups, bd, dtype, world, kd, self.timer)
if par.mode == 'lcao':
# Layouts used for general diagonalizer
sl_lcao = par.parallel['sl_lcao']
if sl_lcao is None:
sl_lcao = par.parallel['sl_default']
lcaoksl = get_KohnSham_layouts(sl_lcao, 'lcao',
gd, bd, dtype,
nao=nao, timer=self.timer)
self.wfs = LCAOWaveFunctions(lcaoksl, *args)
elif par.mode == 'fd' or isinstance(par.mode, 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 = par.parallel['sl_default']
diagksl = get_KohnSham_layouts(sl_diagonalize, 'fd',
gd, bd, 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 = par.parallel['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, dtype,
buffer_size=buffer_size,
timer=self.timer)
# Use (at most) all available LCAO for initialization
lcaonbands = min(nbands, nao)
lcaobd = BandDescriptor(lcaonbands, band_comm, parstride_bands)
assert nbands <= nao or bd.comm.size == 1
assert lcaobd.mynbands == min(bd.mynbands, nao) #XXX
# Layouts used for general diagonalizer (LCAO initialization)
sl_lcao = par.parallel['sl_lcao']
if sl_lcao is None:
sl_lcao = par.parallel['sl_default']
initksl = get_KohnSham_layouts(sl_lcao, 'lcao',
gd, lcaobd, dtype,
nao=nao,
timer=self.timer)
if par.mode == 'fd':
self.wfs = FDWaveFunctions(par.stencils[0], diagksl,
orthoksl, initksl, *args)
else:
# Planewave basis:
self.wfs = par.mode(diagksl, orthoksl, initksl,
gd, nvalence, setups, bd,
world, kd, self.timer)
else:
self.wfs = par.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, par.mode,
par.convergence)
eigensolver.nbands_converge = nbands_converge
# XXX Eigensolver class doesn't define an nbands_converge property
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
self.density = Density(gd, finegd, nspins,
par.charge + setups.core_charge)
self.density.initialize(setups, par.stencils[1], self.timer,
magmom_a, par.hund)
self.density.set_mixer(par.mixer)
if self.hamiltonian is None:
gd, finegd = self.density.gd, self.density.finegd
self.hamiltonian = Hamiltonian(gd, finegd, nspins,
setups, par.stencils[1], self.timer,
xc, par.poissonsolver,
par.external)
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()
if dry_run:
self.dry_run()
self.initialized = True
def set(self, **kwargs):
p = self.input_parameters
# Prune input for things that didn't change
for key, value in kwargs.items():
if key == 'kpts':
oldbzk_kc = kpts2ndarray(p.kpts)
newbzk_kc = kpts2ndarray(value)
if (len(oldbzk_kc) == len(newbzk_kc) and
(oldbzk_kc == newbzk_kc).all()):
kwargs.pop('kpts')
elif np.all(p[key] == value):
kwargs.pop(key)
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]
tmp.update(kwargs[name])
kwargs[name] = tmp
self.initialized = False
for key in kwargs:
if key == 'basis' and p['mode'] == 'fd':
continue
if key == 'eigensolver':
self.wfs.set_eigensolver(None)
if key in ['fixmom', 'mixer',
'verbose', 'txt', 'hund', 'random',
'eigensolver', 'poissonsolver', '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',
'occupations']:
self.hamiltonian = None
self.occupations = None
elif key in ['charge']:
self.hamiltonian = None
self.density = None
self.wfs = EmptyWaveFunctions()
self.occupations = None
elif key in ['kpts', 'nbands']:
self.wfs = EmptyWaveFunctions()
self.occupations = None
elif key in ['h', 'gpts', 'setups', 'spinpol', 'usesymm',
'parallel', 'communicator', 'dtype']:
self.density = None
self.occupations = None
self.hamiltonian = None
self.wfs = EmptyWaveFunctions()
elif key in ['mode', '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)