import time
import sys
import os
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
import flare
import flare.filters
import synthobs
from synthobs.sed import models
import synthobs.morph.images
import synthobs.morph.PSF
cosmo = flare.default_cosmo()
z = 8.
test = synthobs.test_data() # --- read in some test data
# --- calculate V-band (550nm) optical depth for each star particle
A = 5.2
test.tauVs = (10**A) * test.MetSurfaceDensities
model = models.define_model('BPASSv2.2.1.binary/ModSalpeter_300') # DEFINE SED GRID -
model.dust = {'slope': -1.0} # define dust curve
def m_to_lum(m, z, cosmo=flare.default_cosmo()):
return flux_to_L(m_to_flux(m), cosmo, z)
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import cm
import sys
import os
sys.path.insert(0,
os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
import flare
import flare.LF
from flare.LF import evo, lf_parameters, LF_plots, completeness
from flare.photom import m_to_flux
cosmo = flare.default_cosmo() # WMAP9
f_limit_deep = flare.photom.m_to_flux(26.)
area = 60. * 60. * 40.
print('area of Euclid deep: {0} arcmin2'.format(area))
# load in lf parameters
m = getattr(lf_parameters, 'FLARES')()
evo_model = evo.linear(
m) # initialises the linear evolution model with the FLARES parameters
bin_edges, bin_centres, N = evo_model.N(cosmo=cosmo,
redshift_limits=[8., 15.],
log10L_limits=[27., 30.],
def m_to_M(m, z, cosmo=flare.default_cosmo()):
return m - DM(z, cosmo=cosmo)
def M_to_m(M, z, cosmo=flare.default_cosmo()):
return M + DM(z, cosmo=cosmo)
def DM(z, cosmo=flare.default_cosmo()):
luminosity_distance = cosmo.luminosity_distance(z).to('pc').value
return 5 * np.log10(luminosity_distance / (np.sqrt(1. + z) * 10.))
def flux(sim,
kappa,
tag,
BC_fac,
inp='FLARES',
IMF='Chabrier_300',
filters=flare.filters.NIRCam_W,
Type='Total',
log10t_BC=7.,
extinction='default',
data_folder='data',
aperture='30'):
S_mass, S_Z, S_age, S_los, S_len, begin, end, S_ap, DTM = get_data(
sim, tag, inp, data_folder, aperture)
if np.isscalar(filters):
Fnus = np.zeros(len(begin), dtype=np.float64)
else:
Fnus = np.zeros((len(begin), len(filters)), dtype=np.float64)
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")
z = float(tag[5:].replace('p', '.'))
F = flare.filters.add_filters(filters, new_lam=model.lam * (1. + z))
cosmo = flare.default_cosmo()
model.create_Fnu_grid(
F, z, cosmo
) # --- create new Fnu grid for each filter. In units of nJy/M_sol
for jj in range(len(begin)):
Masses = S_mass[begin[jj]:end[jj]][S_ap[begin[jj]:end[jj]]]
Ages = S_age[begin[jj]:end[jj]][S_ap[begin[jj]:end[jj]]]
Metallicities = S_Z[begin[jj]:end[jj]][S_ap[begin[jj]:end[jj]]]
MetSurfaceDensities = S_los[begin[jj]:end[jj]][S_ap[begin[jj]:end[jj]]]
MetSurfaceDensities = DTM[jj] * MetSurfaceDensities
if Type == 'Total':
tauVs_ISM = kappa * MetSurfaceDensities # --- 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}")
Fnu = models.generate_Fnu(
model=model,
F=F,
Masses=Masses,
Ages=Ages,
Metallicities=Metallicities,
tauVs_ISM=tauVs_ISM,
tauVs_BC=tauVs_BC,
fesc=fesc,
log10t_BC=log10t_BC
) # --- calculate rest-frame flux of each object in nJy
Fnus[jj] = list(Fnu.values())
return Fnus
def flux(sim, kappa, tag, BC_fac, inp='FLARES', IMF='Chabrier_300',
filters=flare.filters.NIRCam_W, Type='Total', log10t_BC=7.,
extinction='default', orientation="sim"):
kinp = np.load('/cosma/home/dp004/dc-rope1/cosma7/FLARES/'
'flares/los_extinction/kernel_sph-anarchy.npz',
allow_pickle=True)
lkernel = kinp['kernel']
header = kinp['header']
kbins = header.item()['bins']
S_mass, S_Z, S_age, S_los, G_Z, S_len, \
G_len, G_sml, S_sml, G_mass, S_coords, G_coords, \
S_vels, G_vels, cops, \
begin, end, gbegin, gend = get_data(sim, tag, inp)
Fnus = {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")
z = float(tag[5:].replace('p', '.'))
F = flare.filters.add_filters(filters, new_lam=model.lam * (1. + z))
cosmo = flare.default_cosmo()
# --- create new Fnu grid for each filter. In units of nJy/M_sol
model.create_Fnu_grid(F, z, cosmo)
for jj in range(len(begin)):
# Extract values for this galaxy
Masses = S_mass[begin[jj]: end[jj]]
Ages = S_age[begin[jj]: end[jj]]
Metallicities = S_Z[begin[jj]: end[jj]]
gasMetallicities = G_Z[begin[jj]: end[jj]]
gasSML = G_sml[begin[jj]: end[jj]]
gasMasses = G_mass[begin[jj]: end[jj]]
if orientation == "sim":
starCoords = S_coords[:, begin[jj]: end[jj]].T - cops[:, jj]
S_coords[:, begin[jj]: end[jj]] = starCoords.T
MetSurfaceDensities = S_los[begin[jj]:end[jj]]
elif orientation == "face-on":
starCoords = S_coords[:, begin[jj]: end[jj]].T - cops[:, jj]
gasCoords = G_coords[:, begin[jj]: end[jj]].T - cops[:, jj]
gasVels = G_vels[:, begin[jj]: end[jj]].T
# Get angular momentum vector
ang_vec = util.ang_mom_vector(gasMasses, gasCoords, gasVels)
# Rotate positions
starCoords = util.get_rotated_coords(ang_vec, starCoords)
gasCoords = util.get_rotated_coords(ang_vec, gasCoords)
S_coords[:, begin[jj]: end[jj]] = starCoords.T
MetSurfaceDensities = util.get_Z_LOS(starCoords, gasCoords,
gasMasses, gasMetallicities,
gasSML, (0, 1, 2),
lkernel, kbins)
elif orientation == "side-on":
starCoords = S_coords[:, begin[jj]: end[jj]].T - cops[:, jj]
gasCoords = G_coords[:, begin[jj]: end[jj]].T - cops[:, jj]
gasVels = G_vels[:, begin[jj]: end[jj]].T
# Get angular momentum vector
ang_vec = util.ang_mom_vector(gasMasses, gasCoords, gasVels)
# Rotate positions
starCoords = util.get_rotated_coords(ang_vec, starCoords)
gasCoords = util.get_rotated_coords(ang_vec, gasCoords)
S_coords[:, begin[jj]: end[jj]] = starCoords.T
MetSurfaceDensities = util.get_Z_LOS(starCoords, gasCoords,
gasMasses, gasMetallicities,
gasSML, (2, 0, 1),
lkernel, kbins)
else:
MetSurfaceDensities = None
print(orientation,
"is not an recognised orientation. "
"Accepted types are 'sim', 'face-on', or 'side-on'")
Mage = np.nansum(Masses * Ages) / np.nansum(Masses)
Z = np.nanmean(gasMetallicities)
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 * (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:
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:
# --- calculate rest-frame flux of each object in nJy
Fnu = models.generate_Fnu_array(model, Masses, Ages, Metallicities,
tauVs_ISM, tauVs_BC, F, f,
fesc=fesc, log10t_BC=log10t_BC)
Fnus[f][begin[jj]: end[jj]] = Fnu
Fnus["coords"] = S_coords
Fnus["smls"] = S_sml
Fnus["begin"] = begin
Fnus["end"] = end
return Fnus
