def _init_propars(self):
IterativeProatomMixin._init_propars(self)
charges = self.cache.load('charges',
alloc=self._system.natom,
tags='o')[0]
self.cache.dump('propars', charges, tags='o')
return charges
def _init_propars(self):
IterativeProatomMixin._init_propars(self)
self._ranges = [0]
self._nshells = []
for iatom in xrange(self.natom):
nshell = _get_nshell(self.numbers[iatom])
self._ranges.append(self._ranges[-1]+2*nshell)
self._nshells.append(nshell)
ntotal = self._ranges[-1]
propars = self.cache.load('propars', alloc=ntotal, tags='o')[0]
for iatom in xrange(self.natom):
propars[self._ranges[iatom]:self._ranges[iatom+1]] = _get_initial_mbis_propars(self.numbers[iatom])
return propars
def _init_propars(self):
IterativeProatomMixin._init_propars(self)
self._ranges = [0]
self._nshells = []
for iatom in xrange(self.natom):
nshell = _get_nshell(self.numbers[iatom])
self._ranges.append(self._ranges[-1] + 2 * nshell)
self._nshells.append(nshell)
ntotal = self._ranges[-1]
propars = self.cache.load('propars', alloc=ntotal, tags='o')[0]
for iatom in xrange(self.natom):
propars[self._ranges[iatom]:self.
_ranges[iatom + 1]] = _get_initial_mbis_propars(
self.numbers[iatom])
return propars
def _finalize_propars(self):
IterativeProatomMixin._finalize_propars(self)
propars = self.cache.load('propars')
core_charges = []
valence_charges = []
valence_widths = []
for iatom in xrange(self.natom):
my_propars = propars[self._ranges[iatom]:self._ranges[iatom+1]]
valence_charges.append(-my_propars[-2])
valence_widths.append(1.0/my_propars[-1])
valence_charges = np.array(valence_charges)
valence_widths = np.array(valence_widths)
core_charges = self._cache.load('charges') - valence_charges
self.cache.dump('core_charges', core_charges, tags='o')
self.cache.dump('valence_charges', valence_charges, tags='o')
self.cache.dump('valence_widths', valence_widths, tags='o')
def _finalize_propars(self):
IterativeProatomMixin._finalize_propars(self)
propars = self.cache.load('propars')
core_charges = []
valence_charges = []
valence_widths = []
for iatom in xrange(self.natom):
my_propars = propars[self._ranges[iatom]:self._ranges[iatom + 1]]
valence_charges.append(-my_propars[-2])
valence_widths.append(1.0 / my_propars[-1])
valence_charges = np.array(valence_charges)
valence_widths = np.array(valence_widths)
core_charges = self._cache.load('charges') - valence_charges
self.cache.dump('core_charges', core_charges, tags='o')
self.cache.dump('valence_charges', valence_charges, tags='o')
self.cache.dump('valence_widths', valence_widths, tags='o')
def _init_propars(self):
IterativeProatomMixin._init_propars(self)
charges = self.cache.load('charges', alloc=self.natom, tags='o')[0]
self.cache.dump('propars', charges, tags='o')
return charges
