def load_rprocess_yields(self):
"""Load r-process element yields.
Cescutti et al. (2006) r-process Ba & Eu yields for M = 12, 15, 30
Msun that are metallicity independent.
"""
self.rprocess_yields = pickle_read(
join(self.path_rprocess, 'cescutti06_yields.pck'))
def load_rprocess_yields(self):
"""Load r-process element yields.
Cescutti et al. (2006) r-process Ba & Eu yields for M = 12, 15, 30
Msun that are metallicity independent.
"""
self.rprocess_yields = pickle_read(join(self.path_rprocess,
'cescutti06_yields.pck'))
def load_sprocess_yields(self, supersolar=False):
"""Load s-process element yields.
Busso et al. (2001) s-process Ba yields for M < 8 Msun & Z =
2e-4--4e-2 (twice solar and twice the maximum Limongi & Chieffi
metallicity).
supersolar: if True, use the yields that extend from solar (Z = 2e-2)
to twice solar (Z = 4e-2), otherwise only use the yields up to solar.
"""
if supersolar:
self.sprocess_z = pickle_read(join(self.path_sprocess,
'busso01ext_metallicity.pck'))
self.sprocess_yields = pickle_read(join(self.path_sprocess,
'busso01ext_yields.pck'))
else:
self.sprocess_yields = pickle_read(join(self.path_sprocess,
'busso01_yields.pck'))
def load_snii_yields(self):
"""Load SNII yields.
Limongi & Chieffi SN II Yields: 1001 metallicities, 92 masses from
8 to 100 msun, 293 isotopes.
WW95 yields are also on same metallicity--stellar mass--isotope grid.
"""
self.snii_z = pickle_read(join(self.path_yldgen, 'interp_metallicity.pck'))
self.snii_yields = pickle_read(join(self.path_snii, 'interp_yields.pck'))
self.snii_mej = pickle_read(join(self.path_snii, 'interp_meject.pck'))
self.snii_rem = pickle_read(join(self.path_snii, 'interp_mremnant.pck'))
self.snii_agb_z = copy.deepcopy(self.snii_z)
self.n_z = len(self.snii_agb_z)
# adjust for a different upper mass limit to the IMF
self.snii_yields = self.snii_yields[:, :self.n_bins_high, :]
self.snii_mej = self.snii_mej[:, :self.n_bins_high]
self.snii_rem = self.snii_rem[:, :self.n_bins_high]
def load_sprocess_yields(self, supersolar=False):
"""Load s-process element yields.
Busso et al. (2001) s-process Ba yields for M < 8 Msun & Z =
2e-4--4e-2 (twice solar and twice the maximum Limongi & Chieffi
metallicity).
supersolar: if True, use the yields that extend from solar (Z = 2e-2)
to twice solar (Z = 4e-2), otherwise only use the yields up to solar.
"""
if supersolar:
self.sprocess_z = pickle_read(
join(self.path_sprocess, 'busso01ext_metallicity.pck'))
self.sprocess_yields = pickle_read(
join(self.path_sprocess, 'busso01ext_yields.pck'))
else:
self.sprocess_yields = pickle_read(
join(self.path_sprocess, 'busso01_yields.pck'))
def concat_ncapture_yields(self, r_elements, s_elements):
"""Create an array of r- and s-process isotopic yields."""
nclib = pickle_read(self.path_yldgen + 'sneden08.pck')
# unique elements arranged by atomic number
elements = np.unique(r_elements + s_elements)
at_num = []
for item in elements:
at_num.append(nclib[item]['Z'])
at_num = np.array(at_num)
elements = elements[np.argsort(at_num)]
self.nc_sym = []
self.nc_sym_mass = []
for item in elements:
n_tmp = len(nclib[item]['Isotope'])
for i in range(n_tmp):
self.nc_sym.append(item + str(nclib[item]['Isotope'][i]))
self.nc_sym_mass.append(nclib[item]['Isotope'][i])
self.nc_sym = np.array(self.nc_sym)
self.nc_sym_mass = np.array(self.nc_sym_mass)
self.n_nc_sym = len(self.nc_sym)
u, indices = np.unique([item.rstrip('0123456789')
for item in self.nc_sym], return_index=True)
indices_s = np.argsort(indices)
self.nc_element = u[indices_s]
# project elemental yields onto relative isotopic abundances
self.nc_yields = np.zeros((self.n_z, self.n_bins, self.n_nc_sym))
cnt = 0
for i in range(len(elements)):
el = elements[i]
el_iso = len(nclib[el]['Isotope'])
if el in r_elements:
j = np.where(np.array(r_elements) == el)[0]
self.nc_yields[:, -self.n_bins_high:, cnt:cnt+el_iso] = \
(np.ones((self.n_z, self.n_bins_high, el_iso)) *
self.rprocess_yields[:, -self.n_bins_high:, j] *
nclib[el]['isotopic_fraction[r]'])
if el in s_elements:
j = np.where(np.array(s_elements) == el)[0]
self.nc_yields[:, :self.n_bins_low, cnt:cnt+el_iso] = \
(np.ones((self.n_z, self.n_bins_low, el_iso)) *
self.sprocess_yields[:, :, j] *
nclib[el]['isotopic_fraction[s]'])
cnt += el_iso
# update arrays
self.sym = np.append(self.snii_sym, self.nc_sym)
self.sym_mass = np.append(self.snii_sym_mass, self.nc_sym_mass)
self.n_sym = len(self.sym)
self.element = np.append(self.element, self.nc_element)
self.n_elements = len(self.element)
self.bbmf = np.append(self.bbmf, np.zeros(self.n_nc_sym))
self.snia_yields = np.append(self.snia_yields, np.zeros(self.n_nc_sym))
self.snii_yields = np.append(self.snii_yields,
self.nc_yields[:, self.ind8:], axis=2)
self.agb_yields = np.append(self.agb_yields,
self.nc_yields[:, :self.ind8], axis=2)
self.snii_agb_rem = np.concatenate((self.agb_rem, self.snii_rem),
axis=1)
def load_snii_yields(self):
"""Load SNII yields.
Limongi & Chieffi SN II Yields: 1001 metallicities, 92 masses from
8 to 100 msun, 293 isotopes.
WW95 yields are also on same metallicity--stellar mass--isotope grid.
"""
self.snii_z = pickle_read(
join(self.path_yldgen, 'interp_metallicity.pck'))
self.snii_yields = pickle_read(
join(self.path_snii, 'interp_yields.pck'))
self.snii_mej = pickle_read(join(self.path_snii, 'interp_meject.pck'))
self.snii_rem = pickle_read(join(self.path_snii,
'interp_mremnant.pck'))
self.snii_agb_z = copy.deepcopy(self.snii_z)
self.n_z = len(self.snii_agb_z)
# adjust for a different upper mass limit to the IMF
self.snii_yields = self.snii_yields[:, :self.n_bins_high, :]
self.snii_mej = self.snii_mej[:, :self.n_bins_high]
self.snii_rem = self.snii_rem[:, :self.n_bins_high]
def load_agb_yields(self):
"""Load AGB yields.
Karakas AGB Yields: 1001 metallicities, 79 masses from 0.1 to 8
msun, 70 isotopes.
Only works for Karakas et al. (2010) AGB yields.
B8, O14, Ne19, and Si33 are not in the LC yields. The latter three K10
yields are always 0 and the B8 yield is essentially zero (<1e-17), so I
have removed those from agb_sym, agb_yields_in, and agb_yields.
"""
self._check_yield_grids(self.path_agb)
agb_sym = pd.read_csv(join(self.path_agb, 'species.txt'),
delim_whitespace=True,
skiprows=1,
usecols=[1],
names=['name'])
self.agb_sym = np.array(agb_sym['name'])
self.agb_z = pickle_read(
join(self.path_yldgen, 'interp_metallicity.pck'))
agb_yields_in = pickle_read(join(self.path_agb, 'interp_yields.pck'))
# remove isotopes not in the LC06 yields
agb_yields_in = np.delete(agb_yields_in, np.s_[6, 13, 23, 47], axis=2)
self.agb_mej = pickle_read(join(self.path_agb, 'interp_meject.pck'))
self.agb_rem = pickle_read(join(self.path_agb, 'interp_mremnant.pck'))
# Create an array with the same elements as the Limongi & Chieffi
# (2006) SNII yields.
self.agb_yields = np.zeros(
(agb_yields_in.shape[0], agb_yields_in.shape[1],
self.snii_yields.shape[2]))
ind_agb = np.array([], dtype=int)
for i in range(len(self.agb_sym)):
tmp = np.where(self.agb_sym[i] == self.snii_sym)[0]
ind_agb = np.append(ind_agb, tmp)
self.agb_yields[:, :, ind_agb] = copy.deepcopy(agb_yields_in)
if self.mlow == 0.2:
self.agb_mej = self.agb_mej[:, 1:]
self.agb_rem = self.agb_rem[:, 1:]
self.agb_yields = self.agb_yields[:, 1:]
def load_snia_yields(self, model):
"""Load SNIa yields.
Iwamoto et al. (1999) models\:
cdd1\: CDD1
cdd2\: CDD2
w7\: single-degenerate model from Nomoto et al. (1984)
w70\: zero-metallicity version of W7
wdd1\: WDD1
wdd2\: WDD2
wdd3\: WDD3
"""
self.snia_yields = pickle_read(self.path_snia + model + '_yields.pck')
def load_snia_yields(self, model):
"""Load SNIa yields.
Iwamoto et al. (1999) models\:
cdd1\: CDD1
cdd2\: CDD2
w7\: single-degenerate model from Nomoto et al. (1984)
w70\: zero-metallicity version of W7
wdd1\: WDD1
wdd2\: WDD2
wdd3\: WDD3
"""
self.snia_yields = pickle_read(
join(self.path_snia, model + '_yields.pck'))
def load_agb_yields(self):
"""Load AGB yields.
Karakas AGB Yields: 1001 metallicities, 79 masses from 0.1 to 8
msun, 70 isotopes.
Only works for Karakas et al. (2010) AGB yields.
B8, O14, Ne19, and Si33 are not in the LC yields. The latter three K10
yields are always 0 and the B8 yield is essentially zero (<1e-17), so I
have removed those from agb_sym, agb_yields_in, and agb_yields.
"""
self._check_yield_grids(self.path_agb)
agb_sym = pd.read_csv(join(self.path_agb, 'species.txt'),
delim_whitespace=True, skiprows=1, usecols=[1],
names=['name'])
self.agb_sym = np.array(agb_sym['name'])
self.agb_z = pickle_read(join(self.path_yldgen, 'interp_metallicity.pck'))
agb_yields_in = pickle_read(join(self.path_agb, 'interp_yields.pck'))
# remove isotopes not in the LC06 yields
agb_yields_in = np.delete(agb_yields_in, np.s_[6, 13, 23, 47], axis=2)
self.agb_mej = pickle_read(join(self.path_agb, 'interp_meject.pck'))
self.agb_rem = pickle_read(join(self.path_agb, 'interp_mremnant.pck'))
# Create an array with the same elements as the Limongi & Chieffi
# (2006) SNII yields.
self.agb_yields = np.zeros((agb_yields_in.shape[0],
agb_yields_in.shape[1],
self.snii_yields.shape[2]))
ind_agb = np.array([], dtype=int)
for i in range(len(self.agb_sym)):
tmp = np.where(self.agb_sym[i] == self.snii_sym)[0]
ind_agb = np.append(ind_agb, tmp)
self.agb_yields[:, :, ind_agb] = copy.deepcopy(agb_yields_in)
if self.mlow == 0.2:
self.agb_mej = self.agb_mej[:, 1:]
self.agb_rem = self.agb_rem[:, 1:]
self.agb_yields = self.agb_yields[:, 1:]
def concat_ncapture_yields(self, r_elements, s_elements):
"""Create an array of r- and s-process isotopic yields."""
nclib = pickle_read(join(self.path_yldgen, 'sneden08.pck'))
# unique elements arranged by atomic number
elements = np.unique(r_elements + s_elements)
at_num = []
for item in elements:
at_num.append(nclib[item]['Z'])
at_num = np.array(at_num)
elements = elements[np.argsort(at_num)]
self.nc_sym = []
self.nc_sym_mass = []
for item in elements:
n_tmp = len(nclib[item]['Isotope'])
for i in range(n_tmp):
self.nc_sym.append(item + str(nclib[item]['Isotope'][i]))
self.nc_sym_mass.append(nclib[item]['Isotope'][i])
self.nc_sym = np.array(self.nc_sym)
self.nc_sym_mass = np.array(self.nc_sym_mass)
self.n_nc_sym = len(self.nc_sym)
u, indices = np.unique(
[item.rstrip('0123456789') for item in self.nc_sym],
return_index=True)
indices_s = np.argsort(indices)
self.nc_element = u[indices_s]
# project elemental yields onto relative isotopic abundances
self.nc_yields = np.zeros((self.n_z, self.n_bins, self.n_nc_sym))
cnt = 0
for i in range(len(elements)):
el = elements[i]
el_iso = len(nclib[el]['Isotope'])
if el in r_elements:
j = np.where(np.array(r_elements) == el)[0]
self.nc_yields[:, -self.n_bins_high:, cnt:cnt+el_iso] = \
(np.ones((self.n_z, self.n_bins_high, el_iso)) *
self.rprocess_yields[:, -self.n_bins_high:, j] *
nclib[el]['isotopic_fraction[r]'])
if el in s_elements:
j = np.where(np.array(s_elements) == el)[0]
self.nc_yields[:, :self.n_bins_low, cnt:cnt+el_iso] = \
(np.ones((self.n_z, self.n_bins_low, el_iso)) *
self.sprocess_yields[:, :, j] *
nclib[el]['isotopic_fraction[s]'])
cnt += el_iso
# update arrays
self.sym = np.append(self.snii_sym, self.nc_sym)
self.sym_mass = np.append(self.snii_sym_mass, self.nc_sym_mass)
self.n_sym = len(self.sym)
self.element = np.append(self.element, self.nc_element)
self.n_elements = len(self.element)
self.bbmf = np.append(self.bbmf, np.zeros(self.n_nc_sym))
if len(self.snia_yields.shape) == 1:
# metallicity-independent SNIa yields
self.snia_yields = np.append(self.snia_yields,
np.zeros(self.n_nc_sym))
elif len(self.snia_yields.shape) == 2:
# metallicity-dependent SNIa yields
self.snia_yields = np.append(self.snia_yields,
np.zeros((self.nc_yields.shape[0],
self.nc_yields.shape[2])),
axis=1)
self.snii_yields = np.append(self.snii_yields,
self.nc_yields[:, self.ind8:],
axis=2)
self.agb_yields = np.append(self.agb_yields,
self.nc_yields[:, :self.ind8],
axis=2)
self.snii_agb_rem = np.concatenate((self.agb_rem, self.snii_rem),
axis=1)