def init_first(self):
AnalysisHook.init_first(self)
if self.outg is not None:
self.outg.create_dataset('amps', (self.ssize,), float)
self.outg.create_dataset('freqs', (self.ssize,), float)
self.outg.create_dataset('ac', (self.ssize,), float)
self.outg.create_dataset('time', (self.ssize,), float)
def init_first(self):
# update the shape if select is present
if self.select is not None:
self.shape = (len(self.select), ) + self.shape[1:]
# compute the number of dimensions, i.e. 3 for atoms
self.ndim = 1
for s in self.shape[1:]:
self.ndim *= s
# allocate working arrays
self.last_poss = [
np.zeros(self.shape, float) for i in range(self.mult)
]
self.pos = np.zeros(self.shape, float)
# prepare the hdf5 output file, if present.
AnalysisHook.init_first(self)
if self.outg is not None:
for m in range(self.mult):
self.outg.create_dataset('msd%03i' % (m + 1),
shape=(0, ),
maxshape=(None, ),
dtype=float)
self.outg.create_dataset('msdsums', data=self.msdsums)
self.outg.create_dataset('msdcounters', data=self.msdcounters)
self.outg.create_dataset('pars', shape=(2, ), dtype=float)
self.outg.create_dataset('pars_error', shape=(2, ), dtype=float)
def init_first(self):
'''Setup some work arrays'''
# determine the number of atoms
if self.select0 is None:
self.natom0 = self.natom
else:
self.natom0 = len(self.select0)
self.pos0 = np.zeros((self.natom0, 3), float)
# the number of pairs
if self.select1 is None:
self.npair = (self.natom0 * (self.natom0 - 1)) // 2
self.pos1 = None
else:
self.natom1 = len(self.select1)
self.pos1 = np.zeros((self.natom1, 3), float)
self.npair = self.natom0 * self.natom1
# multiply the number of pairs by all images
self.npair *= (1 + 2 * self.nimage)**3
# Prepare the output
self.work = np.zeros(self.npair, float)
AnalysisHook.init_first(self)
if self.outg is not None:
self.outg.create_dataset('rdf', (self.nbin, ), float)
self.outg.create_dataset('CN', (self.nbin, ), float)
self.outg['d'] = self.d
if self.pairs_sr is not None:
self.outg.create_dataset('rdf_sr', (self.nbin, ), float)
def init_first(self):
AnalysisHook.init_first(self)
if self.outg is not None:
self.outg.create_dataset("amps", (self.ssize,), float)
self.outg.create_dataset("freqs", (self.ssize,), float)
self.outg.create_dataset("ac", (self.ssize,), float)
self.outg.create_dataset("time", (self.ssize,), float)
def init_first(self):
AnalysisHook.init_first(self)
if self.outg is not None:
self.outg.create_dataset('amps', (self.ssize, ), float)
self.outg.create_dataset('freqs', (self.ssize, ), float)
self.outg.create_dataset('ac', (self.ssize, ), float)
self.outg.create_dataset('time', (self.ssize, ), float)
def init_first(self):
'''Setup some work arrays'''
# determine the number of atoms
if self.select0 is None:
self.natom0 = self.natom
else:
self.natom0 = len(self.select0)
self.pos0 = np.zeros((self.natom0, 3), float)
# the number of pairs
if self.select1 is None:
self.npair = (self.natom0*(self.natom0-1))/2
self.pos1 = None
else:
self.natom1 = len(self.select1)
self.pos1 = np.zeros((self.natom1, 3), float)
self.npair = self.natom0*self.natom1
# multiply the number of pairs by all images
self.npair *= (1 + 2*self.nimage)**3
# Prepare the output
self.work = np.zeros(self.npair, float)
AnalysisHook.init_first(self)
if self.outg is not None:
self.outg.create_dataset('rdf', (self.nbin,), float)
self.outg['d'] = self.d
if self.pairs_sr is not None:
self.outg.create_dataset('rdf_sr', (self.nbin,), float)
def init_first(self):
# update the shape if select is present
if self.select is not None:
self.shape = (len(self.select),) + self.shape[1:]
# compute the number of dimensions, i.e. 3 for atoms
self.ndim = 1
for s in self.shape[1:]:
self.ndim *= s
# allocate working arrays
self.last_poss = [np.zeros(self.shape, float) for i in range(self.mult)]
self.pos = np.zeros(self.shape, float)
# prepare the hdf5 output file, if present.
AnalysisHook.init_first(self)
if self.outg is not None:
for m in range(self.mult):
self.outg.create_dataset('msd%03i' % (m+1), shape=(0,), maxshape=(None,), dtype=float)
self.outg.create_dataset('msdsums', data=self.msdsums)
self.outg.create_dataset('msdcounters', data=self.msdcounters)
self.outg.create_dataset('pars', shape=(2,), dtype=float)
self.outg.create_dataset('pars_error', shape=(2,), dtype=float)
