fsps_time = maxage - t
#### calculate SFR at each t
sfr = mformed / dt
sfrout = np.zeros_like(t)
sfrout[::2] = sfr
sfrout[1::2] = sfr # * (1+epsilon)
return (fsps_time / 1e9)[::-1], sfrout[::-1], maxage / 1e9
##############
#####SET SIM#####
specz = 1.25
sim2 = Gen_spec('GND', 21156, 1.25257,
g102_lims=[8300, 11288], g141_lims=[11288, 16500],mdl_err = False,
phot_errterm = 0.0, decontam = False)
sp = fsps.StellarPopulation(imf_type = 2, tpagb_norm_type=0, zcontinuous = 1, logzsol = np.log10(1), sfh = 4, tau=0.1, dust_type = 1)
sp.params['dust2'] =0.2
sp.params['dust1'] =0.2
sp.params['tau'] =0.3
sp.params['logzsol'] = np.log10(0.8)
wave2, flux2 = sp.get_spectrum(tage = 4.25, peraa = True)
mass_perc2 = sp.stellar_mass
D_l = cosmo.luminosity_distance(specz).value # in Mpc
conv = 3.086E24
lsol_to_fsol = 3.839E33
sp.set_tabular_sfh(LBT,np.array([t1, t2, t3, t4, t5, t6]))
wave, flux = sp.get_spectrum(tage = a, peraa = True)
Gmfl, Pmfl = Full_forward_model(Gs, wave, flux, specz)
PC= Full_scale(Gs, Pmfl)
Gchi, Pchi = Full_fit(Gs, PC * Gmfl, PC * Pmfl)
return -0.5 * (Gchi + Pchi)
############## ############
############## redshift run ############
sp = fsps.StellarPopulation(imf_type = 2, tpagb_norm_type=0, zcontinuous = 1, logzsol = np.log10(1), sfh = 4, tau = 0.1)
Gs = Gen_spec(field, galaxy, 1, g102_lims=[8300, 11288], g141_lims=[11288, 16500],mdl_err = False,
phot_errterm = 0.03, decontam = True)
wvs, flxs, errs, beams, trans = Gather_grism_data(Gs)
zsampler = dynesty.NestedSampler( rshift_loglikelihood, rshift_prior, ndim = 5, sample = 'rwalk', bound = 'balls')
zsampler.run_nested(print_progress=False)
zres = zsampler.results
t,pt = Get_posterior(zres.samples[:,3 ],zres.logwt,zres.logz)
specz = t[pt == max(pt)][0]
agelim = Oldest_galaxy(specz)
LBT = Time_bins(agelim)
############## ############
############## bestfit run ############
sfr = mformed / dt
sfrout = np.zeros_like(t)
sfrout[::2] = sfr
sfrout[1::2] = sfr # * (1+epsilon)
return (fsps_time / 1e9)[::-1], sfrout[::-1], maxage / 1e9
##############
specz = 1.25
sim1 = Gen_spec('GND',
21156,
1.25257,
g102_lims=[8300, 11288],
g141_lims=[11288, 16500],
mdl_err=False,
phot_errterm=0.0,
decontam=False)
sp = fsps.StellarPopulation(imf_type=2,
tpagb_norm_type=0,
zcontinuous=1,
logzsol=np.log10(0.8),
sfh=3,
dust_type=1)
sp.params['dust2'] = 0.2
sp.params['dust1'] = 0.2
tab_masses = np.array(
[0.00, 0.00, 0.000, 0.0000, 0.0001, 0.0001, 0.001, 0.025, 0.3, 0.9])
def PLOT(field, galaxy, DF, savefig=True):
grow = DF.query('id == {0}'.format(galaxy))
flist = glob('../data/posteriors/{}_{}_*_Pm.npy'.format(field, galaxy))
for f in flist:
ext = re.split('{}_{}_'.format(field, galaxy),
re.split('_Pm.npy', os.path.basename(f))[0])[1]
if ext == 'tabfit':
Gs = Gen_spec(field,
galaxy,
grow.zgrism.values[0],
phot_errterm=0.04,
irac_err=0.08)
Flam = Posterior_spec(field, galaxy)
break
if ext in 'SFfit_p1':
Gs = Gen_SF_spec(field,
galaxy,
grow.z_grizli.values[0],
phot_errterm=0.04,
irac_err=0.08)
Flam = Posterior_SF_spec(field, galaxy, grow.z_grizli.values[0])
break
x, px = np.load('../data/posteriors/{}_{}_{}_Pbp1.npy'.format(
field, galaxy, ext))
bp1 = x[px == max(px)][0]
x, px = np.load('../data/posteriors/{}_{}_{}_Prp1.npy'.format(
field, galaxy, ext))
rp1 = x[px == max(px)][0]
Gs.Best_fit_scale_flam(Flam.wave, Flam.SPEC, Flam.rshift, bp1, rp1)
with open('../data/SFH/{}_{}.pkl'.format(field, galaxy), 'rb') as sfh_file:
sfh = pickle.load(sfh_file)
gs = GridSpec(3, 5, hspace=0.3, wspace=0.35)
plt.figure(figsize=[19, 15])
###############plot tab##################
plt.subplot(gs[0, :3])
if Gs.g102:
plt.errorbar(np.log10(Gs.Bwv_rf),
Gs.Bfl * 1E18,
Gs.Ber * 1E18,
linestyle='None',
marker='o',
markersize=3,
color='#36787A',
zorder=2)
plt.plot(np.log10(Gs.Bwv_rf), Gs.Bmfl * 1E18, 'k', zorder=4)
IDB = [U for U in range(len(Flam.wave)) if Flam.wave[U] < Gs.Bwv_rf[0]]
else:
IDB = [U for U in range(len(Flam.wave)) if Flam.wave[U] < Gs.Rwv_rf[0]]
if Gs.g141:
plt.errorbar(np.log10(Gs.Rwv_rf),
Gs.Rfl * 1E18,
Gs.Rer * 1E18,
linestyle='None',
marker='o',
markersize=3,
color='#EA2E3B',
zorder=2)
plt.plot(np.log10(Gs.Rwv_rf), Gs.Rmfl * 1E18, 'k', zorder=4)
IDR = [
U for U in range(len(Flam.wave)) if Flam.wave[U] > Gs.Rwv_rf[-1]
]
else:
IDR = [
U for U in range(len(Flam.wave)) if Flam.wave[U] > Gs.Bwv_rf[-1]
]
plt.errorbar(np.log10(Gs.Pwv_rf),
Gs.Pflx * 1E18,
Gs.Perr * 1E18,
linestyle='None',
marker='o',
markersize=10,
markerfacecolor='#B5677D',
zorder=1,
markeredgecolor='#685877',
markeredgewidth=1)
plt.plot(np.log10(Flam.wave)[IDB],
Flam.SPEC[IDB] * 1E18,
'k',
alpha=1,
label='Model',
zorder=5)
plt.plot(np.log10(Flam.wave)[IDR], Flam.SPEC[IDR] * 1E18, 'k', alpha=1)
plt.xlim(np.log10(min(Gs.Pwv_rf) * 0.95), np.log10(max(Gs.Pwv_rf) * 1.05))
plt.xticks(np.log10([2500, 5000, 7500, 10000, 25000]),
[2500, 5000, 7500, 10000, 25000])
plt.title(galaxy, fontsize=25)
plt.xlabel(r'Wavelength ($\rm \AA$)', fontsize=20)
plt.ylabel(r'F$_\lambda$ ($10^{-18}$ $erg/s/cm^{2}/ \rm \AA $)',
fontsize=20)
plt.tick_params(axis='both', which='major', labelsize=15)
###############sfh plot################
isfhl = interp1d(sfh.LBT, sfh.SFH_16)
isfhh = interp1d(sfh.LBT, sfh.SFH_84)
ax1 = plt.subplot(gs[0, 3:5])
ax2 = ax1.twiny()
ax1.plot(sfh.fulltimes,
sfh.sfr_grid.T[:1000],
color='#532436',
alpha=.075,
linewidth=0.5)
ax1.plot(sfh.LBT, sfh.SFH, color='#C1253C', linewidth=3, zorder=9)
ax1.plot(sfh.LBT, sfh.SFH_16, 'k', linewidth=2)
ax1.plot(sfh.LBT, sfh.SFH_84, 'k', linewidth=2)
max_lbt = np.round(sfh.fulltimes[-1])
max_age = max_lbt + cosmo.lookback_time(grow.zgrism.values[0]).value
age_at_z = cosmo.lookback_time(grow.zgrism.values[0]).value
if ext == 'tabfit':
zarray = [np.round(grow.zgrism.values[0], 2)]
else:
zarray = [np.round(grow.z_grizli.values[0], 2)]
idx = 0
while cosmo.lookback_time(np.array(zarray[idx])).value < 13:
zarray.append(int(zarray[idx]) + 1)
idx += 1
tarray = cosmo.lookback_time(np.array(zarray)).value - cosmo.lookback_time(
np.array(zarray)).value[0]
ax2.set_xlim(ax1.get_xlim())
ax2.set_xticks(tarray)
ax2.set_xticklabels(zarray)
ax2.xaxis.set_ticks_position('top')
ax1.set_xlabel('Look-back time (Gyr)', fontsize=21)
ax1.set_ylabel('SFR ($M_\odot$ / yr)', fontsize=21)
ax2.set_xlabel('Redshift (z)', fontsize=21)
ax1.tick_params(axis='both', which='major', labelsize=17)
ax2.tick_params(axis='both', which='major', labelsize=17)
ax1.vlines(grow.t_50.values[0],
isfhl(grow.t_50.values[0]),
isfhh(grow.t_50.values[0]),
color='#ED2D39',
linewidth=2,
zorder=11)
ax1.vlines(grow.t_50.values[0],
isfhl(grow.t_50.values[0]),
isfhh(grow.t_50.values[0]),
color='k',
linewidth=4,
zorder=10)
hdr = np.linspace(grow.t_50_hci.values[0][0], grow.t_50_hci.values[0][1])
ax1.fill_between(hdr,
isfhh(hdr),
isfhl(hdr),
color='#4E7577',
alpha=0.75,
zorder=8)
ax1.vlines(grow.t_50_hci.values[0][0],
isfhl(grow.t_50_hci.values[0][0]),
isfhh(grow.t_50_hci.values[0][0]),
color='k',
linewidth=1,
zorder=8)
ax1.vlines(grow.t_50_hci.values[0][1],
isfhl(grow.t_50_hci.values[0][1]),
isfhh(grow.t_50_hci.values[0][1]),
color='k',
linewidth=1,
zorder=8)
###############plot zoom tab##################
plt.subplot(gs[1, :3])
if Gs.g102:
plt.errorbar(Gs.Bwv_rf,
Gs.Bfl * 1E18,
Gs.Ber * 1E18,
linestyle='None',
marker='o',
markersize=3,
color='#36787A',
zorder=2)
plt.plot(Gs.Bwv_rf, Gs.Bmfl * 1E18, 'k', zorder=4)
if Gs.g141:
plt.errorbar(Gs.Rwv_rf,
Gs.Rfl * 1E18,
Gs.Rer * 1E18,
linestyle='None',
marker='o',
markersize=3,
color='#EA2E3B',
zorder=2)
plt.plot(Gs.Rwv_rf, Gs.Rmfl * 1E18, 'k', zorder=4)
plt.xlabel(r'Wavelength ($\rm \AA$)', fontsize=20)
plt.ylabel(r'F$_\lambda$ ($10^{-18}$ $erg/s/cm^{2}/ \rm \AA $)',
fontsize=20)
plt.tick_params(axis='both', which='major', labelsize=15)
#################plot uvj###################
plt.subplot(gs[1, 3:5])
plt.scatter(Bdb.VJ, Bdb.UV)
plt.scatter(grow.VJ.values, grow.UV.values, marker='*', color='r', s=100)
if grow.AGN.values == 'AGN':
plt.scatter(grow.VJ.values,
grow.UV.values,
marker='o',
s=500,
linewidth=5,
color='None',
edgecolor='g')
plt.plot([0, .9], [1.382, 1.382], 'k', lw=1.2)
plt.plot([1.65, 1.65], [2.05, 2.5], 'k', lw=1.2)
plt.plot([.9, 1.65], [0.88 * .9 + 0.59, 0.88 * 1.65 + 0.59], 'k', lw=1.2)
plt.xlabel('(V-J)', fontsize=21)
plt.ylabel('(U-V)', fontsize=21)
plt.tick_params(axis='both', which='major', labelsize=17)
###############P(Z)################
plt.subplot(gs[2, 0])
plot_posterior(field, galaxy, 'm', ext, 'Z', 'Z / Z$_\odot$',
'Z / Z$_\odot$', Bdb)
###############P(lwa)################
plt.subplot(gs[2, 1])
plot_posterior(field, galaxy, 'lwa', ext, 'lwa', 'LWA (Gyr)', 'LWA', Bdb)
###############P(z)################
plt.subplot(gs[2, 2])
if ext == 'tabfit':
plot_posterior(field,
galaxy,
'z',
ext,
'zgrism',
'Redshift (z)',
'z',
Bdb,
roundto=4)
###############P(d)################
plt.subplot(gs[2, 3])
plot_posterior(field, galaxy, 'd', ext, 'Av', 'Dust (Av)', 'Av', Bdb)
###############P(lmass)################
plt.subplot(gs[2, 4])
plot_posterior(field, galaxy, 'lm', ext, 'lmass', 'log(M/M$_\odot$)',
'log(M/M$_\odot$)', Bdb)
if savefig:
plt.savefig('../plots/bulgefits/all_data_{0}_{1}.png'.format(
field, galaxy),
bbox_inches='tight')