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')