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 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