def from_abundance(cls, abundance_dict, density, atom_data, time_explosion, nlte_config=None, saha_treatment='lte'):
"""
Initializing the abundances from the a dictionary like {'Si':0.5, 'Fe':0.5} and a density.
All other parameters are the same as the normal initializer
Parameters
----------
abundance_dict : `~dict`
A dictionary with the abundances for each element, e.g. {'Fe':0.5, 'Ni':0.5}
density : `~float`
density in g/cm^3
Returns
-------
`Baseplasma` object
"""
abundance_series = parse_abundance_dict_to_dataframe(abundance_dict, atom_data)
abundances = pd.DataFrame({0:abundance_series})
number_densities = abundances * density.to('g/cm^3').value
number_densities = number_densities.div(atom_data.atom_data.mass.ix[number_densities.index], axis=0)
atom_data.prepare_atom_data(number_densities.index.values)
return cls(number_densities, atom_data, time_explosion.to('s').value, nlte_config=nlte_config, saha_treatment=saha_treatment)
def setup(self):
atom_data = atomic.AtomData.from_hdf5(helium_test_db)
density = 1e-15 * u.Unit("g/cm3")
abundance = parse_abundance_dict_to_dataframe({"He": 1.0})
abundance = pd.DataFrame({0: abundance})
number_densities = abundance * density.to("g/cm^3").value
number_densities = number_densities.div(atom_data.atom_data.mass.ix[number_densities.index], axis=0)
self.plasma = LegacyPlasmaArray(
number_densities, atomic_data=atom_data, time_explosion=10 * u.day, ionization_mode="nebular"
)
def setup(self):
atom_data = atomic.AtomData.from_hdf5(helium_test_db)
density = 1e-15 * u.Unit('g/cm3')
abundance = parse_abundance_dict_to_dataframe({'He':1.0})
abundance = pd.DataFrame({0:abundance})
number_densities = abundance * density.to('g/cm^3').value
number_densities = number_densities.div(
atom_data.atom_data.mass.ix[number_densities.index], axis=0)
self.plasma = LegacyPlasmaArray(number_densities,
atomic_data=atom_data, time_explosion=10 * u.day,
ionization_mode='nebular')
def setup(self):
atom_data = atomic.AtomData.from_hdf5(helium_test_db)
density = 1e-15 * u.Unit('g/cm3')
abundance = parse_abundance_dict_to_dataframe({'He': 1.0})
abundance = pd.DataFrame({0: abundance})
atom_data.prepare_atom_data([2]) # FIXME: hardcoded, bad
number_densities = abundance * density.to('g/cm^3').value
number_densities = number_densities.div(
atom_data.atom_data.mass.ix[number_densities.index], axis=0)
self.plasma = LegacyPlasmaArray(
number_densities,
atomic_data=atom_data, time_explosion=10 * u.day,
ionization_mode='nebular')
def from_abundance(cls, abundance_dict, density, atom_data, time_explosion,
nlte_config=None, ionization_mode='lte',
excitation_mode='lte'):
"""
Initializing the abundances from the a dictionary like {'Si':0.5, 'Fe':0.5} and a density.
All other parameters are the same as the normal initializer
Parameters
----------
abundance_dict : `~dict`
A dictionary with the abundances for each element, e.g. {'Fe':0.5, 'Ni':0.5}
density : `~float`
density in g/cm^3
Returns
-------
`Baseplasma` object
"""
abundance_series = parse_abundance_dict_to_dataframe(abundance_dict)
abundances = pd.DataFrame({0:abundance_series})
number_densities = abundances * density.to('g/cm^3').value
number_densities = number_densities.div(atom_data.atom_data.mass.ix[number_densities.index], axis=0)
if nlte_config is not None:
nlte_species = nlte_config.species
else:
nlte_species = []
atom_data.prepare_atom_data(number_densities.index.values, nlte_species=nlte_species)
return cls(number_densities, atom_data, time_explosion.to('s').value,
nlte_config=nlte_config, ionization_mode=ionization_mode,
excitation_mode=excitation_mode)