def dscf_load_band(filename, paw, molecule=None):
"""Load and distribute all information for a band from a tar file."""
if not paw.wfs:
paw.initialize()
world, bd, gd, kd = paw.wfs.world, paw.wfs.bd, paw.wfs.gd, \
KPointDescriptor(paw.wfs.nspins, paw.wfs.nibzkpts, paw.wfs.kpt_comm, \
paw.wfs.gamma, paw.wfs.dtype)
if bd.comm.size != 1:
raise NotImplementedError('Undefined action for band parallelization.')
r = Reader(filename)
assert (r.dimension('nspins') == kd.nspins and \
r.dimension('nibzkpts') == kd.nibzkpts), 'Incompatible spin/kpoints.'
# Read wave function for every spin/kpoint owned by this rank
psit_uG = gd.empty(kd.mynks, kd.dtype)
for myu, psit_G in enumerate(psit_uG):
u = kd.global_index(myu)
s, k = kd.what_is(u)
if gd.comm.rank == 0:
big_psit_G = np.array(r.get('PseudoWaveFunction', s, k), kd.dtype)
else:
big_psit_G = None
gd.distribute(big_psit_G, psit_G)
# Find domain ranks for each atom
atoms = paw.get_atoms()
spos_ac = atoms.get_scaled_positions() % 1.0
rank_a = gd.get_ranks_from_positions(spos_ac)
#my_atom_indices = np.argwhere(rank_a == gd.comm.rank).ravel()
#assert np.all(my_atom_indices == paw.wfs.pt.my_atom_indices)
assert r.dimension('nproj') == sum([setup.ni for setup in paw.wfs.setups])
if molecule is None:
molecule = range(len(atoms))
# Read projections for every spin/kpoint and atom owned by this rank
P_uai = [{}] * kd.mynks #[paw.wfs.pt.dict() for myu in range(kd.mynks)]
for myu, P_ai in enumerate(P_uai):
u = kd.global_index(myu)
s, k = kd.what_is(u)
P_i = r.get('Projection', s, k)
i1 = 0
for a in molecule:
setup = paw.wfs.setups[a]
i2 = i1 + setup.ni
if gd.comm.rank == rank_a[a]:
P_ai[a] = np.array(P_i[i1:i2], kd.dtype)
i1 = i2
return psit_uG, P_uai
def dscf_load_band(filename, paw, molecule=None):
"""Load and distribute all information for a band from a tar file."""
if not paw.wfs:
paw.initialize()
world, bd, gd, kd = paw.wfs.world, paw.wfs.bd, paw.wfs.gd, \
KPointDescriptor(paw.wfs.nspins, paw.wfs.nibzkpts, paw.wfs.kpt_comm, \
paw.wfs.gamma, paw.wfs.dtype)
if bd.comm.size != 1:
raise NotImplementedError('Undefined action for band parallelization.')
r = Reader(filename)
assert (r.dimension('nspins') == kd.nspins and \
r.dimension('nibzkpts') == kd.nibzkpts), 'Incompatible spin/kpoints.'
# Read wave function for every spin/kpoint owned by this rank
psit_uG = gd.empty(kd.mynks, kd.dtype)
for myu, psit_G in enumerate(psit_uG):
u = kd.global_index(myu)
s, k = kd.what_is(u)
if gd.comm.rank == 0:
big_psit_G = np.array(r.get('PseudoWaveFunction', s, k), kd.dtype)
else:
big_psit_G = None
gd.distribute(big_psit_G, psit_G)
# Find domain ranks for each atom
atoms = paw.get_atoms()
spos_ac = atoms.get_scaled_positions() % 1.0
rank_a = gd.get_ranks_from_positions(spos_ac)
#my_atom_indices = np.argwhere(rank_a == gd.comm.rank).ravel()
#assert np.all(my_atom_indices == paw.wfs.pt.my_atom_indices)
assert r.dimension('nproj') == sum([setup.ni for setup in paw.wfs.setups])
if molecule is None:
molecule = range(len(atoms))
# Read projections for every spin/kpoint and atom owned by this rank
P_uai = [{}] * kd.mynks #[paw.wfs.pt.dict() for myu in range(kd.mynks)]
for myu, P_ai in enumerate(P_uai):
u = kd.global_index(myu)
s, k = kd.what_is(u)
P_i = r.get('Projection', s, k)
i1 = 0
for a in molecule:
setup = paw.wfs.setups[a]
i2 = i1 + setup.ni
if gd.comm.rank == rank_a[a]:
P_ai[a] = np.array(P_i[i1:i2], kd.dtype)
i1 = i2
return psit_uG, P_uai
def read(self, filename, mode='', ws='all', idiotproof=True):
if idiotproof and not filename.endswith('.ind'):
raise IOError('Filename must end with `.ind`.')
reads = self._parse_readwritemode(mode)
# Open reader (handles masters)
tar = Reader(filename)
# Actual read
self.nw = tar.dimension('nw')
if ws == 'all':
ws = range(self.nw)
self.nw = len(ws)
self._read(tar, reads, ws)
# Close
tar.close()
self.world.barrier()
def read(self, filename, idiotproof=True):
if idiotproof and not filename.endswith('.ftd'):
raise IOError('Filename must end with `.ftd`.')
tar = Reader(filename)
# Test data type
dtype = {'Float':float, 'Complex':complex}[tar['DataType']]
if dtype != self.dtype:
raise IOError('Data is an incompatible type.')
# Test time
time = tar['Time']
if idiotproof and abs(time-self.time) >= 1e-9:
raise IOError('Timestamp is incompatible with calculator.')
# Test timestep (non-critical)
timestep = tar['TimeStep']
if abs(timestep - self.timestep) > 1e-12:
print 'Warning: Time-step has been altered. (%lf -> %lf)' \
% (self.timestep, timestep)
self.timestep = timestep
# Test dimensions
nw = tar.dimension('nw')
nspins = tar.dimension('nspins')
ng = (tar.dimension('ngptsx'), tar.dimension('ngptsy'), \
tar.dimension('ngptsz'),)
if (nw != self.nw or nspins != self.nspins or
(ng != self.gd.get_size_of_global_array()).any()):
raise IOError('Data has incompatible shapes.')
# Test width (non-critical)
sigma = tar['Width']
if ((sigma is None)!=(self.sigma is None) or # float <-> None
(sigma is not None and self.sigma is not None and \
abs(sigma - self.sigma) > 1e-12)): # float -> float
print 'Warning: Width has been altered. (%s -> %s)' \
% (self.sigma, sigma)
self.sigma = sigma
# Read frequencies
self.omega_w[:] = tar.get('Frequency')
# Read cumulative phase factors
self.gamma_w[:] = tar.get('PhaseFactor')
# Read average densities on master and distribute
for s in range(self.nspins):
all_Ant_G = tar.get('Average', s)
self.gd.distribute(all_Ant_G, self.Ant_sG[s])
# Read fourier transforms on master and distribute
for w in range(self.nw):
for s in range(self.nspins):
all_Fnt_G = tar.get('FourierTransform', w, s)
self.gd.distribute(all_Fnt_G, self.Fnt_wsG[w,s])
# Close for good measure
tar.close()
def read(self, filename, idiotproof=True):
if idiotproof and not filename.endswith('.ftd'):
raise IOError('Filename must end with `.ftd`.')
tar = Reader(filename)
# Test data type
dtype = {'Float': float, 'Complex': complex}[tar['DataType']]
if dtype != self.dtype:
raise IOError('Data is an incompatible type.')
# Test time
time = tar['Time']
if idiotproof and abs(time - self.time) >= 1e-9:
raise IOError('Timestamp is incompatible with calculator.')
# Test timestep (non-critical)
timestep = tar['TimeStep']
if abs(timestep - self.timestep) > 1e-12:
print('Warning: Time-step has been altered. (%lf -> %lf)' \
% (self.timestep, timestep))
self.timestep = timestep
# Test dimensions
nw = tar.dimension('nw')
nspins = tar.dimension('nspins')
ng = (tar.dimension('ngptsx'), tar.dimension('ngptsy'), \
tar.dimension('ngptsz'),)
if (nw != self.nw or nspins != self.nspins
or (ng != self.gd.get_size_of_global_array()).any()):
raise IOError('Data has incompatible shapes.')
# Test width (non-critical)
sigma = tar['Width']
if ((sigma is None)!=(self.sigma is None) or # float <-> None
(sigma is not None and self.sigma is not None and \
abs(sigma - self.sigma) > 1e-12)): # float -> float
print('Warning: Width has been altered. (%s -> %s)' \
% (self.sigma, sigma))
self.sigma = sigma
# Read frequencies
self.omega_w[:] = tar.get('Frequency')
# Read cumulative phase factors
self.gamma_w[:] = tar.get('PhaseFactor')
# Read average densities on master and distribute
for s in range(self.nspins):
all_Ant_G = tar.get('Average', s)
self.gd.distribute(all_Ant_G, self.Ant_sG[s])
# Read fourier transforms on master and distribute
for w in range(self.nw):
for s in range(self.nspins):
all_Fnt_G = tar.get('FourierTransform', w, s)
self.gd.distribute(all_Fnt_G, self.Fnt_wsG[w, s])
# Close for good measure
tar.close()
def wrap_old_gpw_reader(filename):
warnings.warn('You are reading an old-style gpw-file. Please check '
'the results carefully!')
r = Reader(filename)
data = {
'version': -1,
'gpaw_version': '1.0',
'ha': Ha,
'bohr': Bohr,
'scf.': {
'converged': True
},
'atoms.': {},
'wave_functions.': {}
}
class DictBackend:
def write(self, **kwargs):
data['atoms.'].update(kwargs)
write_atoms(DictBackend(), read_atoms(r))
e_total_extrapolated = r.get('PotentialEnergy').item() * Ha
magmom_a = r.get('MagneticMoments')
data['results.'] = {
'energy': e_total_extrapolated,
'magmoms': magmom_a,
'magmom': magmom_a.sum()
}
if r.has_array('CartesianForces'):
data['results.']['forces'] = r.get('CartesianForces') * Ha / Bohr
p = data['parameters.'] = {}
p['xc'] = r['XCFunctional']
p['nbands'] = r.dimension('nbands')
p['spinpol'] = (r.dimension('nspins') == 2)
bzk_kc = r.get('BZKPoints', broadcast=True)
if r.has_array('NBZKPoints'):
p['kpts'] = r.get('NBZKPoints', broadcast=True)
if r.has_array('MonkhorstPackOffset'):
offset_c = r.get('MonkhorstPackOffset', broadcast=True)
if offset_c.any():
p['kpts'] = monkhorst_pack(p['kpts']) + offset_c
else:
p['kpts'] = bzk_kc
if r['version'] < 4:
usesymm = r['UseSymmetry']
if usesymm is None:
p['symmetry'] = {'time_reversal': False, 'point_group': False}
elif usesymm:
p['symmetry'] = {'time_reversal': True, 'point_group': True}
else:
p['symmetry'] = {'time_reversal': True, 'point_group': False}
else:
p['symmetry'] = {
'point_group': r['SymmetryOnSwitch'],
'symmorphic': r['SymmetrySymmorphicSwitch'],
'time_reversal': r['SymmetryTimeReversalSwitch'],
'tolerance': r['SymmetryToleranceCriterion']
}
p['basis'] = r['BasisSet']
try:
h = r['GridSpacing']
except KeyError: # CMR can't handle None!
h = None
if h is not None:
p['h'] = Bohr * h
if r.has_array('GridPoints'):
p['gpts'] = r.get('GridPoints')
p['lmax'] = r['MaximumAngularMomentum']
p['setups'] = r['SetupTypes']
p['fixdensity'] = r['FixDensity']
nbtc = r['NumberOfBandsToConverge']
if not isinstance(nbtc, (int, str)):
# The string 'all' was eval'ed to the all() function!
nbtc = 'all'
p['convergence'] = {
'density': r['DensityConvergenceCriterion'],
'energy': r['EnergyConvergenceCriterion'] * Ha,
'eigenstates': r['EigenstatesConvergenceCriterion'],
'bands': nbtc
}
mixer = r['MixClass']
weight = r['MixWeight']
for key in ['basis', 'setups']:
dct = p[key]
if isinstance(dct, dict) and None in dct:
dct['default'] = dct.pop(None)
if mixer == 'Mixer':
from gpaw.mixer import Mixer
elif mixer == 'MixerSum':
from gpaw.mixer import MixerSum as Mixer
elif mixer == 'MixerSum2':
from gpaw.mixer import MixerSum2 as Mixer
elif mixer == 'MixerDif':
from gpaw.mixer import MixerDif as Mixer
elif mixer == 'DummyMixer':
from gpaw.mixer import DummyMixer as Mixer
else:
Mixer = None
if Mixer is None:
p['mixer'] = None
else:
p['mixer'] = Mixer(r['MixBeta'], r['MixOld'], weight)
p['stencils'] = (r['KohnShamStencil'], r['InterpolationStencil'])
vt_sG = r.get('PseudoPotential') * Ha
ps = r['PoissonStencil']
if isinstance(ps, int) or ps == 'M':
poisson = {'name': 'fd'}
poisson['nn'] = ps
if data['atoms.']['pbc'] == [1, 1, 0]:
v1, v2 = vt_sG[0, :, :, [0, -1]].mean(axis=(1, 2))
if abs(v1 - v2) > 0.01:
warnings.warn('I am guessing that this calculation was done '
'with a dipole-layer correction?')
poisson['dipolelayer'] = 'xy'
p['poissonsolver'] = poisson
p['charge'] = r['Charge']
fixmom = r['FixMagneticMoment']
p['occupations'] = FermiDirac(r['FermiWidth'] * Ha, fixmagmom=fixmom)
p['mode'] = r['Mode']
if p['mode'] == 'pw':
p['mode'] = PW(ecut=r['PlaneWaveCutoff'] * Ha)
if len(bzk_kc) == 1 and not bzk_kc[0].any():
# Gamma point only:
if r['DataType'] == 'Complex':
p['dtype'] = complex
data['occupations.'] = {
'fermilevel': r['FermiLevel'] * Ha,
'split': r.parameters.get('FermiSplit', 0) * Ha,
'h**o': np.nan,
'lumo': np.nan
}
data['density.'] = {
'density': r.get('PseudoElectronDensity') * Bohr**-3,
'atomic_density_matrices': r.get('AtomicDensityMatrices')
}
data['hamiltonian.'] = {
'e_coulomb': r['Epot'] * Ha,
'e_entropy': -r['S'] * Ha,
'e_external': r['Eext'] * Ha,
'e_kinetic': r['Ekin'] * Ha,
'e_total_extrapolated': e_total_extrapolated,
'e_xc': r['Exc'] * Ha,
'e_zero': r['Ebar'] * Ha,
'potential': vt_sG,
'atomic_hamiltonian_matrices': r.get('NonLocalPartOfHamiltonian') * Ha
}
data['hamiltonian.']['e_total_free'] = (sum(
data['hamiltonian.'][e] for e in [
'e_coulomb', 'e_entropy', 'e_external', 'e_kinetic', 'e_xc',
'e_zero'
]))
if r.has_array('GLLBPseudoResponsePotential'):
data['hamiltonian.']['xc.'] = {
'gllb_pseudo_response_potential':
r.get('GLLBPseudoResponsePotential') * Ha,
'gllb_dxc_pseudo_response_potential':
r.get('GLLBDxcPseudoResponsePotential') * Ha / Bohr,
'gllb_atomic_density_matrices':
r.get('GLLBAtomicDensityMatrices'),
'gllb_atomic_response_matrices':
r.get('GLLBAtomicResponseMatrices'),
'gllb_dxc_atomic_density_matrices':
r.get('GLLBDxcAtomicDensityMatrices'),
'gllb_dxc_atomic_response_matrices':
r.get('GLLBDxcAtomicResponseMatrices')
}
special = [('eigenvalues', 'Eigenvalues'),
('occupations', 'OccupationNumbers'),
('projections', 'Projections')]
if r['Mode'] == 'pw':
special.append(('coefficients', 'PseudoWaveFunctions'))
try:
data['wave_functions.']['indices'] = r.get('PlaneWaveIndices')
except KeyError:
pass
elif r['Mode'] == 'fd':
special.append(('values', 'PseudoWaveFunctions'))
else:
special.append(('coefficients', 'WaveFunctionCoefficients'))
for name, old in special:
try:
fd, shape, size, dtype = r.get_file_object(old, ())
except KeyError:
continue
offset = fd
data['wave_functions.'][name + '.'] = {
'ndarray': (shape, dtype.name, offset)
}
new = ulm.Reader(devnull,
data=data,
little_endian=r.byteswap ^ np.little_endian)
for ref in new._data['wave_functions']._data.values():
try:
ref.fd = ref.offset
except AttributeError:
continue
ref.offset = 0
return new
def read_data(filename, keys=None, ws='all'):
"""
Read data arrays for post processing.
Not parallel safe. No GridDescriptor, only numpy arrays.
Parameters
----------
filename: string
File to be read.
keys: list of strings
Keys to be read.
ws: list of ints
Indices of frequencies to be read.
"""
key_to_tarname = {
'n0t_sG': 'n0t_sG',
'Fnt_wsG': 'Fnt_wsG',
'Frho_wg': 'Frho_wg',
'Fphi_wg': 'Fphi_wg',
'Fef_wvg': 'Fef_wvg',
'Ffe_wg': 'Ffe_wg',
'eps0_G': 'eps0_G'
}
print('Reading %s' % (filename))
if keys is None:
keys = key_to_tarname.keys() # all keys
tar = Reader(filename)
omega_w = tar.get('omega_w')
if ws == 'all':
ws = range(len(omega_w))
else:
omega_w = omega_w[ws]
freq_w = omega_w * aufrequency_to_eV
try:
nspins = tar.dimension('nspins')
except KeyError:
nspins = None
na = tar['na']
try:
atomnum_a = tar.get('atomnum_a')
atompos_av = tar.get('atompos_a')
atomcell_cv = tar.get('atomcell_cv')
Fbgef_v = tar.get('Fbgef_v')
atom_a = []
for a in range(na):
atom_a.append({'atom': atomnum_a[a], 'pos': atompos_av[a]})
except KeyError:
atom_a = None
atomcell_cv = None
Fbgef_v = None
print('no atoms')
data = dict()
data['freq_w'] = freq_w
data['nspins'] = nspins
data['na'] = na
data['atom_a'] = atom_a
data['cell_cv'] = atomcell_cv
data['Fbgef_v'] = Fbgef_v
try:
data['corner1_v'] = tar.get('corner1_v')
data['corner2_v'] = tar.get('corner2_v')
except:
print('no corners')
try:
FD_awsp = {}
D0_asp = {}
for a in range(na):
FD_awsp[a] = tar.get('FD_%dwsp' % a)
D0_asp[a] = tar.get('D0_%dsp' % a)
data['FD_awsp'] = FD_awsp
data['D0_asp'] = D0_asp
except KeyError:
print('no FD_awsp')
for key in keys:
try:
if '_w' in key:
tmp = zero_pad(tar.get(key_to_tarname[key], ws[0]))
data[key] = np.empty((len(ws), ) + tmp.shape, tmp.dtype)
data[key][0] = tmp
for w, wread in enumerate(ws[1:], 1):
data[key][w] = zero_pad(tar.get(key_to_tarname[key],
wread))
else:
data[key] = zero_pad(tar.get(key_to_tarname[key]))
except KeyError:
print('no %s' % key)
pass
tar.close()
return data
