def lum(
num,
data,
kappa,
z,
BC_fac,
cent,
campos,
IMF='Chabrier_300',
filters=('FAKE.TH.FUV', ),
Type='Total',
log10t_BC=7.,
extinction='default',
):
kinp = np.load(
'/cosma7/data/dp004/dc-payy1/my_files/'
'los/kernel_sph-anarchy.npz',
allow_pickle=True)
lkernel = kinp['kernel']
header = kinp['header']
kbins = header.item()['bins']
S_mass_ini = data.stars.initial_masses.value
S_Z = data.stars.metal_mass_fractions.value
S_age = util.calc_ages(z, data.stars.birth_scale_factors.value)
G_Z = data.gas.metal_mass_fractions.value
S_sml = data.stars.smoothing_lengths.value
G_sml = data.gas.smoothing_lengths.value
G_mass = data.gas.masses.value * 10**10
S_coords = data.stars.coordinates.value - cent
G_coords = data.gas.coordinates.value - cent
S_mass = data.stars.masses.value * 10**10
if S_sml.max() == 0.0:
print("Ill-defined smoothing lengths")
last_snap = "%04d" % (num - 1)
# Define path
path = '/cosma/home/dp004/dc-rope1/cosma7/SWIFT/hydro_1380_data/ani_hydro_' + last_snap + ".hdf5"
olddata = load(path)
old_hsmls = olddata.stars.smoothing_lengths.value
S_sml[:old_hsmls.size] = old_hsmls
S_sml[old_hsmls.size:] = np.median(old_hsmls)
Lums = {f: np.zeros(len(S_mass), dtype=np.float64) for f in filters}
model = models.define_model(
F'BPASSv2.2.1.binary/{IMF}') # DEFINE SED GRID -
if extinction == 'default':
model.dust_ISM = ('simple', {
'slope': -1.
}) # Define dust curve for ISM
model.dust_BC = ('simple', {
'slope': -1.
}) # Define dust curve for birth cloud component
elif extinction == 'Calzetti':
model.dust_ISM = ('Starburst_Calzetti2000', {''})
model.dust_BC = ('Starburst_Calzetti2000', {''})
elif extinction == 'SMC':
model.dust_ISM = ('SMC_Pei92', {''})
model.dust_BC = ('SMC_Pei92', {''})
elif extinction == 'MW':
model.dust_ISM = ('MW_Pei92', {''})
model.dust_BC = ('MW_Pei92', {''})
elif extinction == 'N18':
model.dust_ISM = ('MW_N18', {''})
model.dust_BC = ('MW_N18', {''})
else:
ValueError("Extinction type not recognised")
# Convert coordinates to physical
S_coords = S_coords / (1 + z)
G_coords = G_coords / (1 + z)
# --- create rest-frame luminosities
F = FLARE.filters.add_filters(filters, new_lam=model.lam)
model.create_Lnu_grid(
F) # --- create new L grid for each filter. In units of erg/s/Hz
okinds = G_coords[:, 2] * (1 + z) < campos
MetSurfaceDensities = util.get_Z_LOS(S_coords, G_coords[okinds, :],
G_mass[okinds], G_Z[okinds],
G_sml[okinds], (0, 1, 2), lkernel,
kbins)
Mage = np.nansum(S_mass_ini * S_age) / np.nansum(S_mass_ini)
Z = np.nanmean(G_Z[okinds])
MetSurfaceDensities = DTM_fit(Z, Mage) * MetSurfaceDensities
if Type == 'Total':
# --- calculate V-band (550nm) optical depth for each star particle
tauVs_ISM = kappa * MetSurfaceDensities
tauVs_BC = BC_fac * (S_Z / 0.01)
fesc = 0.0
elif Type == 'Pure-stellar':
tauVs_ISM = np.zeros(len(S_mass_ini))
tauVs_BC = np.zeros(len(S_mass_ini))
fesc = 1.0
elif Type == 'Intrinsic':
tauVs_ISM = np.zeros(len(S_mass_ini))
tauVs_BC = np.zeros(len(S_mass_ini))
fesc = 0.0
elif Type == 'Only-BC':
tauVs_ISM = np.zeros(len(S_mass_ini))
tauVs_BC = BC_fac * (S_Z / 0.01)
fesc = 0.0
else:
tauVs_ISM = None
tauVs_BC = None
fesc = None
ValueError(F"Undefined Type {Type}")
# --- calculate rest-frame Luminosity. In units of erg/s/Hz
for f in filters:
Lnu = models.generate_Lnu_array(model,
S_mass_ini,
S_age,
S_Z,
tauVs_ISM,
tauVs_BC,
F,
f,
fesc=fesc,
log10t_BC=log10t_BC)
Lums[f] = Lnu
return Lums
import sys
import os
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
import SynthObs
from SynthObs.SED import models
import FLARE
import FLARE.filters
import matplotlib.pyplot as plt
model = models.define_model('BPASSv2.2.1.binary/ModSalpeter_300') # DEFINE SED GRID -
model.dust = {'A': 5.2, 'slope': -1.0} # DEFINE DUST MODEL - these are the calibrated z=8 values for the dust model
# --- read in test data
test = SynthObs.test_data() # --- read in some test data
# --- create rest-frame luminosities
filters = ['FAKE.FAKE.'+f for f in ['1500','2500']] # --- define the filters. FAKE.FAKE are just top-hat filters using for extracting rest-frame quantities.
F = FLARE.filters.add_filters(filters, new_lam = model.lam)
def lum_from_stars(MetSurfaceDensities,
Masses,
Ages,
Metallicities,
DTM,
kappa=0.0795,
BC_fac=1.0,
IMF='Chabrier_300',
filters=['FAKE.TH.FUV'],
Type='Total',
log10t_BC=7.,
extinction='default'):
model = models.define_model(
F'BPASSv2.2.1.binary/{IMF}') # DEFINE SED GRID -
if extinction == 'default':
model.dust_ISM = ('simple', {'slope': -1.}) #Define dust curve for ISM
model.dust_BC = ('simple', {
'slope': -1.
}) #Define dust curve for birth cloud component
elif extinction == 'Calzetti':
model.dust_ISM = ('Starburst_Calzetti2000', {''})
model.dust_BC = ('Starburst_Calzetti2000', {''})
elif extinction == 'SMC':
model.dust_ISM = ('SMC_Pei92', {''})
model.dust_BC = ('SMC_Pei92', {''})
elif extinction == 'MW':
model.dust_ISM = ('MW_Pei92', {''})
model.dust_BC = ('MW_Pei92', {''})
elif extinction == 'N18':
model.dust_ISM = ('MW_N18', {''})
model.dust_BC = ('MW_N18', {''})
else:
ValueError("Extinction type not recognised")
# --- create rest-frame luminosities
F = FLARE.filters.add_filters(filters, new_lam=model.lam)
model.create_Lnu_grid(
F) # --- create new L grid for each filter. In units of erg/s/Hz
DustSurfaceDensities = DTM * MetSurfaceDensities
if Type == 'Total':
tauVs_ISM = kappa * DustSurfaceDensities # --- calculate V-band (550nm) optical depth for each star particle
tauVs_BC = BC_fac * (Metallicities / 0.01)
fesc = 0.0
elif Type == 'Pure-stellar':
tauVs_ISM = np.zeros(len(Masses))
tauVs_BC = np.zeros(len(Masses))
fesc = 1.0
elif Type == 'Intrinsic':
tauVs_ISM = np.zeros(len(Masses))
tauVs_BC = np.zeros(len(Masses))
fesc = 0.0
elif Type == 'Only-BC':
tauVs_ISM = np.zeros(len(Masses))
tauVs_BC = BC_fac * (Metallicities / 0.01)
fesc = 0.0
else:
ValueError(F"Undefined Type {Type}")
Lnu = {
f: models.generate_Lnu_array(model,
Masses,
Ages,
Metallicities,
tauVs_ISM,
tauVs_BC,
F,
f,
fesc=fesc)
for f in filters
} # --- calculate rest-frame Luminosity. In units of erg/s/Hz
Lums = list(Lnu.values())
return Lums