def dust_massfn(files, z, snapnum, i):
"""
Outputs the dust mass function for input files of a particular redshift, for a given volume
"""
add = sims[i]
snap = snapnum[i][np.where(redshift == str(z))[0][0]]
Mstar = (get_.get_var(files[i], 'StellarMass', snap) * 1e10) / h
Type = get_.get_var(files[i], 'Type', snap)
Mdust1 = get_.get_var(files[i], 'DustColdGasDiff_elements', snap)
Mdust2 = get_.get_var(files[i], 'DustColdGasClouds_elements', snap)
Mdust1 = np.nansum(Mdust1, axis=1)
Mdust2 = np.nansum(Mdust2, axis=1)
Mdust = Mdust1 + Mdust2
#Mdust = get_.get_var(files[i], 'ColdGasDiff_elements', snap)[:,0]
SFR = get_.get_var(files[i], 'Sfr', snap)
sSFR = SFR / Mstar
ok = np.logical_and(Mdust > 0.0, Type == 0)
#ok = np.logical_and(sSFR < get_.sSFR_cut(z), np.logical_and(Mdust > 0.0, Type == 0))
out = outputs(Mstar[ok], Mdust[ok], sSFR[ok], Type[ok], z)
dbins = np.arange(
np.log10(min(out)) - 0.05,
np.log10(max(out)) + 0.05, 0.2)
#dbins = np.arange(7, 12, 0.2)
bins, edges = np.histogram(np.log10(out), dbins)
xx = (edges[1:] + edges[:-1]) / 2
binsize = edges[1:] - edges[:-1]
yy = bins / (vol[i] * binsize)
return xx, yy
def dust_prod_rate_redshift(files, z, snap, i):
Mstar = (get_.get_var(files[i], 'StellarMass', snap) * 1e10) / h
Type = get_.get_var(files[i], 'Type', snap)
Mdust1 = get_.get_var(files[i], 'DustColdGasDiff_elements', snap)
Mdust2 = get_.get_var(files[i], 'DustColdGasClouds_elements', snap)
Mdust = Mdust1 + Mdust2
SFR = get_.get_var(files[i], 'Sfr', snap)
sSFR = SFR / Mstar
dustrates = get_.get_var(files[i], 'DustColdGasRates', snap)
Mcg1 = get_.get_var(files[i], 'ColdGasDiff_elements', snap)
Mcg2 = get_.get_var(files[i], 'ColdGasClouds_elements', snap)
Mcg = Mcg1 + Mcg2
Z = (Mcg[:, 4] - Mdust[:, 4]) / (15.9994 * (Mcg[:, 0])) #O/H ratio
#Z = np.nansum(Mcg[:,2:], axis = 1)/np.nansum(Mcg, axis = 1)
Mdust = np.nansum(Mdust, axis=1)
Mcg = np.nansum(Mcg, axis=1)
if inp == 0:
ok = np.logical_and(Mdust > 0, Type == 0)
else:
ok = np.logical_and(sSFR > get_.sSFR_cut(z),
np.logical_and(Mcg > 1e6, Type == 0))
dustrates = dustrates[ok]
SFR = SFR[ok]
Mstar = Mstar[ok]
Z = Z[ok]
return dustrates, Mstar, SFR, Z
def get_vals(files, z, snapnum, i, on):
snap = snapnum[i][np.where(redshift == str(z))[0][0]]
Mstar = (get_.get_var(files[i], 'StellarMass', snap) * 1e10) / h
if on and i == 0:
ok = np.where(Mstar >= 10**9.0)[0]
elif on and i == 1:
ok = np.logical_and(Mstar > 10**7.4, Mstar < 10**9.0)
else:
ok = np.where(Mstar >= 10**6.9)[0]
Mstar = Mstar[ok]
Type = get_.get_var(files[i], 'Type', snap)[ok]
Age = get_.get_var(files[i], 'MassWeightAge', snap)[ok]
Mcg = get_.get_var(files[i],
'ColdGasDiff_elements', snap)[ok] + get_.get_var(
files[i], 'ColdGasClouds_elements', snap)[ok]
Mmet = np.nansum(Mcg[:, 2:], axis=1) #Total metal mass in cold gas
Z = Mmet / np.nansum(Mcg, axis=1)
Mdust1 = get_.get_var(files[i], 'DustColdGasDiff_elements', snap)[ok]
Mdust2 = get_.get_var(files[i], 'DustColdGasClouds_elements', snap)[ok]
Mdust = Mdust1 + Mdust2
Mdust = np.nansum(Mdust, axis=1) #Total dust mass
Mratio = Mdust / (Mmet) #Dust-to-total metal mass ratio. Dimensionless.
ok = np.where(np.nansum(Mcg, axis=1) > 1e6)
return Mstar[ok], Mratio[ok], Type[ok], Age[ok], Mcg[ok], Mmet[ok]
def get_vals(files, z, axs, snapnum, i, on):
snap = snapnum[i][np.where(redshift == str(z))[0][0]]
Mstar = (get_.get_var(files[i], 'StellarMass', snap) * 1e10) / h
if on and i == 0:
ok = np.where(Mstar >= 10**9.0)[0]
elif on and i == 1:
ok = np.logical_and(Mstar > 10**7.0, Mstar < 10**9.0)
else:
ok = np.array([True] * len(Mstar))
Mstar = Mstar[ok]
Type = get_.get_var(files[i], 'Type', snap)[ok]
Age = get_.get_var(files[i], 'MassWeightAge', snap)[ok]
Mcg1 = get_.get_var(files[i], 'ColdGasDiff_elements', snap)[ok]
Mcg2 = get_.get_var(files[i], 'ColdGasClouds_elements', snap)[ok]
Mcg = Mcg1 + Mcg2
Mcg = np.nansum(Mcg, axis=1) #Total cold gas mass
Mdust1 = get_.get_var(files[i], 'DustColdGasDiff_elements', snap)[ok]
Mdust2 = get_.get_var(files[i], 'DustColdGasClouds_elements', snap)[ok]
Mdust = Mdust1 + Mdust2
Mdust = np.nansum(Mdust, axis=1) #Total dust mass
Mratio = Mdust / Mcg #Dust-to-total cold gas mass ratio. Dimensionless.
ok = np.where(
Mcg > 1e6
) #Only selecting galaxies with cold gas mass above this value, so the galaxies we are looking at are realistic for the dust content usually seen
return Mstar[ok], Mratio[ok], Type[ok], Age[ok]
def plot_Mstar_dep(files, z, axs, snaps, i, on):
add = sims[i]
snap = snaps[i][np.where(redshift == str(z))[0][0]]
Mstar = (get_.get_var(files[i], 'StellarMass', snap) * 1e10) / 0.673
if on and i == 0:
ok = np.where(Mstar >= 10**9.0)[0]
elif on and i == 1:
ok = np.logical_and(Mstar > 10**7.2, Mstar < 10**9.0)
else:
ok = np.array([True] * len(Mstar))
Mstar = Mstar[ok]
Type = get_.get_var(files[i], 'Type', snap)[ok]
Mdust1 = get_.get_var(files[i], 'DustColdGasDiff_elements', snap)[ok]
Mdust2 = get_.get_var(files[i], 'DustColdGasClouds_elements', snap)[ok]
Mdust = Mdust1 + Mdust2
Mcg1 = get_.get_var(files[i], 'ColdGasDiff_elements', snap)[ok]
Mcg2 = get_.get_var(files[i], 'ColdGasClouds_elements', snap)[ok]
Mcg = Mcg1 + Mcg2
SFR = get_.get_var(files[i], 'Sfr', snap)[ok]
sSFR = SFR / Mstar
ok = np.where(np.nansum(Mcg, axis=1) > 1e6)
plot_figure(Mstar[ok], Mcg[ok], Mdust[ok], sSFR[ok], Type[ok], z, axs)
axs.set_xlim((7.5, 11.6))
axs.set_xticks([8, 9, 10, 11])
return add
def get_DTM(z):
files = '../Dust_output/MR/SA_output_*'
snap = snapnumMR[np.where(redshift == str(z))[0][0]]
Mstar = (get_.get_var(files, 'StellarMass', snap) * 1e10) / 0.673
Mdust1 = get_.get_var(files, 'DustColdGasDiff_elements', snap)
Mdust2 = get_.get_var(files, 'DustColdGasClouds_elements', snap)
Mdust1 = np.nansum(Mdust1, axis=1)
Mdust2 = np.nansum(Mdust2, axis=1)
Mdust = Mdust1 + Mdust2
ok = np.logical_and(Mstar > 10**9.0, Mdust > 0)
Mstar = Mstar[ok]
Mdust = Mdust[ok]
Mcg1 = get_.get_var(files, 'ColdGasDiff_elements', snap)[ok]
Mcg2 = get_.get_var(files, 'ColdGasClouds_elements', snap)[ok]
Mcg = Mcg1 + Mcg2
Mmet = np.nansum(Mcg[:, 2:], axis=1)
snap = snapnumMRII[np.where(redshift == str(z))[0][0]]
files = '../Dust_output/MRII/SA_output_*'
tmp = (get_.get_var(files, 'StellarMass', snap) * 1e10) / 0.673
Mdust1 = get_.get_var(files, 'DustColdGasDiff_elements', snap)
Mdust2 = get_.get_var(files, 'DustColdGasClouds_elements', snap)
Mdust1 = np.nansum(Mdust1, axis=1)
Mdust2 = np.nansum(Mdust2, axis=1)
tmp1 = Mdust1 + Mdust2
ok = np.logical_and(tmp > 10**7.0, np.logical_and(tmp < 10**9.0, tmp1 > 0))
Mstar = np.append(Mstar, tmp[ok])
Mdust = np.append(Mdust, tmp1[ok])
Mcg1 = get_.get_var(files,
'ColdGasDiff_elements', snap)[ok] + get_.get_var(
files, 'ColdGasClouds_elements', snap)[ok]
Mmet = np.append(Mmet, np.nansum(Mcg1[:, 2:], axis=1))
Mcg = np.append(Mcg, Mcg1, axis=0)
DTM = Mdust / (Mmet)
ok = np.where(Mcg > 1e6)[0]
return DTM[ok]
def plot_Mstar_Mdust(fil, z, axs, snapnum, i, on, k, label):
add = sims[i]
snap = snapnum[i][np.where(redshift == str(z))[0][0]]
print(fil[i])
Mstar = (get_.get_var(fil[i], 'StellarMass', snap) * 1e10) / 0.673
if on and i == 0:
ok = np.where(Mstar >= 10**8.9)[0]
elif on and i == 1:
ok = np.logical_and(Mstar > 10**7.5, Mstar < 10**8.9)
else:
ok = np.array([True] * len(Mstar))
Mstar = Mstar[ok]
Type = get_.get_var(fil[i], 'Type', snap)[ok]
Mdust1 = get_.get_var(fil[i], 'DustColdGasDiff_elements', snap)[ok]
Mdust2 = get_.get_var(fil[i], 'DustColdGasClouds_elements', snap)[ok]
Mdust1 = np.nansum(Mdust1, axis=1)
Mdust2 = np.nansum(Mdust2, axis=1)
Mdust = Mdust1 + Mdust2
SFR = get_.get_var(fil[i], 'Sfr', snap)[ok]
sSFR = SFR / Mstar
xx, yy, yy_up, yy_low = outputs(Mstar, Mdust, sSFR, Type, z)
xx = np.log10(xx)
yy = np.log10(yy)
yy_up = np.log10(yy_up)
yy_low = np.log10(yy_low)
plot_figure(axs, z, xx, yy, yy_up, yy_low, k, label)
xlim = [7.5, 11.7]
ylim = [1.5, 10.5]
xticks = [8, 9, 10, 11]
axs.set_xlim(xlim)
axs.set_ylim(ylim)
axs.set_xticks(xticks)
return add
def get_vals(files, z, axs, snapnum, i, on):
snap = snapnum[i][np.where(redshift == str(z))[0][0]]
Mstar = (get_.get_var(files[i], 'StellarMass', snap) * 1e10) / h
if on and i == 0:
ok = np.where(Mstar >= 10**9.0)[0]
elif on and i == 1:
ok = np.logical_and(Mstar > 10**7.0, Mstar < 10**9.0)
else:
ok = np.array([True] * len(Mstar))
Mstar = Mstar[ok]
Type = get_.get_var(files[i], 'Type', snap)[ok]
Age = get_.get_var(files[i], 'MassWeightAge', snap)[ok]
Mcg = get_.get_var(files[i],
'ColdGasDiff_elements', snap)[ok] + get_.get_var(
files[i], 'ColdGasClouds_elements', snap)[ok]
Mmet = np.nansum(Mcg[:, 2:], axis=1)
Mcg = np.nansum(Mcg, axis=1)
Z = Mmet / Mcg
tacc = get_.get_var(files[i], 't_acc', snap)[ok]
ok = np.where(
Mcg > 1e6
) #Only selecting galaxies with cold gas mass above this value, so the galaxies we are looking at are realistic for the dust content usually seen
return Mstar[ok], tacc[ok], Type[ok], Age[ok], Z[ok]
def mu_Krumholz(files, z, snapnum, i):
add = sims[i]
snap = snapnum[i][np.where(redshift == str(z))[0][0]]
Z_sun = 0.0134
cgas = get_.get_var(files[i], 'ColdGas', snap)
ok = np.logical_not(cgas == 0.)
Z_cgas = np.sum(get_.get_var(files[i], 'MetalsColdGas', snap),
axis=1) / cgas
Z_fraction = Z_cgas / Z_sun
Z_fraction[~ok] = 0.
Z_fraction[Z_fraction < 0.01] = 0.01
chi = 3.1 * (1.0 + 3.1 * np.power(Z_fraction, 0.365)) / 4.1
GasDiskRadius = get_.get_var(files[i], 'GasDiskRadius', snap)
Sigma_gas = (1.0e10 *
(cgas / h)) / (np.pi *
((((GasDiskRadius * 1.0e6) / h) / 3.0) *
(((GasDiskRadius * 1.0e6) / h) / 3.0)))
ok = np.where(Z_fraction < 1.)[0]
c_f = np.ones(len(cgas))
c_f[ok] = (Z_fraction[ok])**(-0.7)
Sigma_comp = c_f * Sigma_gas
tau_c = 0.066 * Sigma_comp * Z_fraction
s = np.log(1.0 + 0.6 * chi + 0.01 * chi * chi) / (0.6 * tau_c)
f_h2 = np.zeros(len(cgas))
ok = np.where(s < 2.)
f_h2[ok] = 1. - (0.75) * (s[ok]) / (1. + 0.25 * s[ok])
return f_h2, cgas
def get_vals(files, z, axs, snapnum, i, on):
snap = snapnum[i][np.where(redshift == str(z))[0][0]]
Mstar = (get_.get_var(files[i], 'StellarMass', snap) * 1e10) / h
if on and i == 0:
ok = np.where(Mstar >= 10**9.0)[0]
elif on and i == 1:
ok = np.logical_and(Mstar > 10**7.0, Mstar < 10**9.0)
else:
ok = np.array([True] * len(Mstar))
Mstar = Mstar[ok]
Type = get_.get_var(files[i], 'Type', snap)[ok]
Mdust1 = get_.get_var(files[i], 'DustColdGasDiff_elements', snap)[ok]
Mdust2 = get_.get_var(files[i], 'DustColdGasClouds_elements', snap)[ok]
Mdust1 = np.nansum(Mdust1, axis=1)
Mdust2 = np.nansum(Mdust2, axis=1)
#Mdust = np.nansum(get_.get_var(files[i], 'DustEjectedMass_elements', snap)[ok], axis = 1)# + np.nansum(get_.get_var(files[i], 'DustEjectedMass_elements', snap)[ok], axis = 1) + np.nansum(get_.get_var(files[i], 'DustICM_elements', snap)[ok], axis = 1)#
Mdust = Mdust1 + Mdust2
Mcg = get_.get_var(files[i],
'ColdGasDiff_elements', snap)[ok] + get_.get_var(
files[i], 'ColdGasClouds_elements', snap)[ok]
Mdust_sat = Mcg[:,
2] * 0.7 + Mcg[:,
4] * 0.2 + Mcg[:,
6] + Mcg[:,
7] + Mcg[:,
9] + Mcg[:,
10]
Mcg = np.nansum(Mcg, axis=1)
ok = np.where(
Mcg > 1e6
) #Only selecting galaxies with cold gas mass above this value, so the galaxies we are looking at are realistic for the dust content usually seen
Mstar = Mstar[ok]
Mdust = Mdust[ok]
Type = Type[ok]
Mdust_sat = Mdust_sat[ok]
"""
if z > 4:
bins = 10**(np.linspace(min(np.log10(Mstar)), max(np.log10(Mstar)), num = 10, endpoint = True))
xx = yy = np.array([])
for k in range(0, len(bins)-1):
ok = np.logical_and(Mstar>=bins[k], Mstar<bins[k+1])
if np.sum(ok)>5:
xx = np.append(xx, np.nanmax(Mstar[ok]))
yy = np.append(yy, np.nanmax(Mdust_sat[ok]))
axs.plot(np.log10(xx), np.log10(yy), ls = 'dotted', lw = 3, color = 'red')
"""
return Mstar, Mdust, Type
figsize=(10, 8),
sharex=False,
sharey=True,
facecolor='w',
edgecolor='k')
axs = axs.ravel()
color = [
'red', 'green', 'blue', 'orange', 'violet', 'indigo', 'violet', 'brown',
'yellow'
]
for j, k in enumerate(range(6, 7)):
i = 0
z = 6
snap = snapnum[i][np.where(redshift == str(z))[0][0]]
Mstar = (get_.get_var(files[i], 'StellarMass', snap) * 1e10) / 0.673
ok = np.where(Mstar >= 10**8.85)[0]
Mstar = Mstar[ok]
Type = get_.get_var(files[i], 'Type', snap)[ok]
dustrates = get_.get_var(files[i], 'DustColdGasRates', snap)[ok]
Mcg1 = get_.get_var(files[i], 'ColdGasDiff_elements', snap)[ok]
Mcg2 = get_.get_var(files[i], 'ColdGasClouds_elements', snap)[ok]
Mcg = Mcg1 + Mcg2
Mdust1 = get_.get_var(files[i], 'DustColdGasDiff_elements', snap)[ok]
Mdust2 = get_.get_var(files[i], 'DustColdGasClouds_elements', snap)[ok]
Mdust = Mdust1 + Mdust2
met = (Mcg[:, 4] - Mdust[:, 4]) / (15.9994 * (Mcg[:, 0])) #O/H ratio
Mcg = np.sum(Mcg[:, 2:], axis=1) #Total cold gas mass
def get_vals(files, z, axs, snapnum, i, on):
if on:
i = 0
snap = snapnum[i][np.where(redshift == str(z))[0][0]]
Mstar = (get_.get_var(files[i], 'StellarMass', snap)*1e10)/0.673
Mdust1 = get_.get_var(files[i], 'DustColdGasDiff_elements', snap)
Mdust2 = get_.get_var(files[i], 'DustColdGasClouds_elements', snap)
Mdust = Mdust1 + Mdust2
ok = np.logical_and(Mstar >= 10**9.0, Mdust > 0.)[0]
Mstar = Mstar[ok]
Mdust = Mdust[ok]
Type = get_.get_var(files[i], 'Type', snap)[ok]
Age = get_.get_var(files[i], 'MassWeightAge', snap)[ok]
Mcg = get_.get_var(files[i], 'ColdGasDiff_elements', snap)[ok] + get_.get_var(files[i], 'ColdGasClouds_elements', snap)[ok]
met = (Mcg[:,4]-Mdust[:,4])/(15.9994*(Mcg[:,0])) #O/H ratio
tacc = get_.get_var(files[i], 't_acc', snap)[ok]
i = 1
snap = snapnum[i][np.where(redshift == str(z))[0][0]]
tmp = (get_.get_var(files[i], 'StellarMass', snap)*1e10)/0.673
Mdust1 = get_.get_var(files[i], 'DustColdGasDiff_elements', snap)
Mdust2 = get_.get_var(files[i], 'DustColdGasClouds_elements', snap)
Mdust = Mdust1 + Mdust2
ok = np.logical_and(tmp > 10**7.0, np.logical_and(tmp < 10**9.0, Mdust > 0))
Mstar = np.append(Mstar, tmp[ok])
Type = np.append(Type, get_.get_var(files[i], 'Type', snap)[ok])
Age = np.append(Age, get_.get_var(files[i], 'MassWeightAge', snap)[ok])
Mcg1 = get_.get_var(files[i], 'ColdGasDiff_elements', snap)[ok] + get_.get_var(files[i], 'ColdGasClouds_elements', snap)[ok]
met = np.append(met, (Mcg1[:,4]-Mdust[:,4])/(15.9994*(Mcg1[:,0])))
Mcg = np.append(np.nansum(Mcg, axis = 1), np.nansum(Mcg1, axis = 1))
tacc = np.append(tacc, get_.get_var(files[i], 't_acc', snap)[ok])
ok = np.logical_and(Mcg > 1e6, 12.+np.log10(met) > 6.) #Only selecting galaxies with cold gas mass above this value, so the galaxies we are looking at are realistic for the dust content usually seen
add = 'MR_MRII'
else:
add = sims[i]
snap = snapnum[i][np.where(redshift == str(z))[0][0]]
Mstar = (get_.get_var(files[i], 'StellarMass', snap)*1e10)/0.673
Type = get_.get_var(files[i], 'Type', snap)
Mcg = get_.get_var(files[i], 'ColdGasDiff_elements', snap)[ok] + get_.get_var(files[i], 'ColdGasClouds_elements', snap)[ok]
met = (Mcg[:,4])/(15.9994*(Mcg[:,0])) #O/H ratio
Mcg = np.nansum(Mcg, axis = 1)
tacc = get_.get_var(files[i], 't_acc', snap)
ok = np.logical_and(Mcg > 1e6, 12.+np.log10(met) > 6.) #Only selecting galaxies with cold gas mass above this value, so the galaxies we are looking at are realistic for the dust content usually seen
return add, met[ok], tacc[ok], Type[ok], Age[ok]
def plot_Mstar_Mdust_age(files, z, axs, snapnum, i, on):
add = sims[i]
snap = snapnum[i][np.where(redshift == str(z))[0][0]]
try:
data = np.load('data/Mstar_{}_snap_{}.npz'.format(add, snap))
Mstar = data['Mstar']
data = np.load('data/Type_{}_snap_{}.npz'.format(add, snap))
Type = data['Type']
data = np.load('data/Age_{}_snap_{}.npz'.format(add, snap))
Age = data['Age']
data = np.load('data/DustColdGasDiff_elements_{}_snap_{}.npz'.format(
add, snap))
Mdust1 = data['DustColdGasDiff_elements']
data = np.load('data/DustColdGasClouds_elements_{}_snap_{}.npz'.format(
add, snap))
Mdust2 = data['DustColdGasClouds_elements']
except:
Mstar = (get_.get_var(files[i], 'StellarMass', snap) * 1e10) / h
if on and i == 0:
ok = np.where(Mstar >= 10**8.9)[0]
elif on and i == 1:
ok = np.logical_and(Mstar > 10**7.5, Mstar < 10**8.9)
else:
ok = np.array([True] * len(Mstar))
Mstar = Mstar[ok]
np.savez_compressed('data/Mstar_{}_snap_{}'.format(add, snap),
Mstar=Mstar)
Type = get_.get_var(files[i], 'Type', snap)[ok]
np.savez_compressed('data/Type_{}_snap_{}'.format(add, snap),
Type=Type)
Age = get_.get_var(files[i], 'MassWeightAge', snap)[ok]
np.savez_compressed('data/Age_{}_snap_{}'.format(add, snap), Age=Age)
Mdust1 = get_.get_var(files[i], 'DustColdGasDiff_elements', snap)[ok]
np.savez_compressed('data/DustColdGasDiff_elements_{}_snap_{}'.format(
add, snap),
DustColdGasDiff_elements=Mdust1)
Mdust2 = get_.get_var(files[i], 'DustColdGasClouds_elements', snap)[ok]
np.savez_compressed(
'data/DustColdGasClouds_elements_{}_snap_{}'.format(add, snap),
DustColdGasClouds_elements=Mdust2)
Mdust1 = np.nansum(Mdust1, axis=1)
Mdust2 = np.nansum(Mdust2, axis=1)
Mdust = Mdust1 + Mdust2
x, y, xx, yy, yy_up, yy_low, den = create_out.out_age(
Mstar, Mdust, Type, Age, z)
x = np.log10(x)
y = np.log10(y)
xx = np.log10(xx)
yy = np.log10(yy)
yy_up = np.log10(yy_up)
yy_low = np.log10(yy_low)
p = make_fig.fig_age(axs, z, x, y, xx, yy, yy_up, yy_low, den)
xlim = [7.5, 11.9]
ylim = [1.5, 10.8]
xticks = [8, 9, 10, 11]
axs.set_xlim(xlim)
axs.set_ylim(ylim)
axs.set_xticks(xticks)
return add, p, den
def get_vals(z):
snap = snapnumMR[np.where(redshift == str(z))[0][0]]
files = '../Dust_output/MR/SA_output_*'
Mstar = (get_.get_var(files, 'StellarMass', snap) * 1e10) / h
Mdust1 = get_.get_var(files, 'DustColdGasDiff_elements', snap)
Mdust2 = get_.get_var(files, 'DustColdGasClouds_elements', snap)
Mdust1 = np.nansum(Mdust1, axis=1)
Mdust2 = np.nansum(Mdust2, axis=1)
Mdust = Mdust1 + Mdust2
ok = np.logical_and(Mstar > 10**9.0, Mdust > 0)
Mstar = Mstar[ok]
Mdust = Mdust[ok]
Age = get_.get_var(files, 'MassWeightAge', snap)[ok]
mu = get_.get_var(files, 'mu_gas', snap)[ok]
Type = get_.get_var(files, 'Type', snap)[ok]
Mcg1 = get_.get_var(files, 'ColdGasDiff_elements', snap)[ok]
Mcg2 = get_.get_var(files, 'ColdGasClouds_elements', snap)[ok]
Mcg = Mcg1 + Mcg2
Mmet = np.nansum(Mcg[:, 2:], axis=1)
Mcg = np.nansum(Mcg, axis=1)
snap = snapnumMRII[np.where(redshift == str(z))[0][0]]
files = '../Dust_output/MRII/SA_output_*'
tmp = (get_.get_var(files, 'StellarMass', snap) * 1e10) / h
Mdust1 = get_.get_var(files, 'DustColdGasDiff_elements', snap)
Mdust2 = get_.get_var(files, 'DustColdGasClouds_elements', snap)
Mdust1 = np.nansum(Mdust1, axis=1)
Mdust2 = np.nansum(Mdust2, axis=1)
tmp1 = Mdust1 + Mdust2
ok = np.logical_and(tmp > 10**7.4, np.logical_and(tmp < 10**9.0, tmp1 > 0))
Mstar = np.append(Mstar, tmp[ok])
Mdust = np.append(Mdust, tmp1[ok])
Age = np.append(Age, get_.get_var(files, 'MassWeightAge', snap)[ok])
mu = np.append(mu, get_.get_var(files, 'mu_gas', snap)[ok])
Mcg1 = get_.get_var(files, 'ColdGasDiff_elements', snap)[ok]
Mcg2 = get_.get_var(files, 'ColdGasClouds_elements', snap)[ok]
Type = np.append(Type, get_.get_var(files, 'Type', snap)[ok])
Mmet = np.append(Mmet, np.nansum(Mcg1[:, 2:] + Mcg2[:, 2:], axis=1))
Mcg = np.append(Mcg, np.nansum(Mcg1 + Mcg2, axis=1))
Z = Mmet / Mcg
DTM = Mdust / (Mmet)
ok = np.where(Mcg > 1e6)
Mdust = Mdust[ok]
DTM = DTM[ok]
Z = Z[ok]
Mstar = Mstar[ok]
Age = Age[ok]
Type = Type[ok]
mu = mu[ok]
out = get_.remove_(np.array([Mdust, DTM, Z, Mstar, Age, Type, mu]),
np.array([5]))
out = out[(out[5] == 0)]
out = np.array(out).T
return out[0], out[1], out[2], out[3], out[4], out[5]
def get_vals(tacc, z):
snap = snapnumMR[np.where(redshift == str(z))[0][0]]
files = '../test_rmol/def_{}/MR/SA_output_*'.format(tacc)
Mstar = (get_.get_var(files, 'StellarMass', snap) * 1e10) / 0.673
Mdust1 = get_.get_var(files, 'DustColdGasDiff_elements', snap)
Mdust2 = get_.get_var(files, 'DustColdGasClouds_elements', snap)
Mdust1 = np.nansum(Mdust1, axis=1)
Mdust2 = np.nansum(Mdust2, axis=1)
Mdust = Mdust1 + Mdust2
ok = np.logical_and(Mstar >= 10**9, Mdust > 0)
Mstar = Mstar[ok]
Mdust = Mdust[ok]
Age = get_.get_var(files, 'MassWeightAge', snap)[ok]
Mcg1 = get_.get_var(files, 'ColdGasDiff_elements', snap)[ok]
Mcg2 = get_.get_var(files, 'ColdGasClouds_elements', snap)[ok]
Mcg = Mcg1 + Mcg2
Mmet = np.nansum(Mcg[:, 2:], axis=1)
Mcg = np.nansum(Mcg, axis=1)
snap = snapnumMRII[np.where(redshift == str(z))[0][0]]
files = '../test_rmol/def_{}/MRII/SA_output_*'.format(tacc)
tmp = (get_.get_var(files, 'StellarMass', snap) * 1e10) / 0.673
Mdust1 = get_.get_var(files, 'DustColdGasDiff_elements', snap)
Mdust2 = get_.get_var(files, 'DustColdGasClouds_elements', snap)
Mdust1 = np.nansum(Mdust1, axis=1)
Mdust2 = np.nansum(Mdust2, axis=1)
tmp1 = Mdust1 + Mdust2
ok = np.logical_and(tmp > 10**7.5, np.logical_and(tmp < 10**9, tmp1 > 0))
Mstar = np.append(Mstar, tmp[ok])
Mdust = np.append(Mdust, tmp1[ok])
Age = np.append(Age, get_.get_var(files, 'MassWeightAge', snap)[ok])
Mcg1 = get_.get_var(files, 'ColdGasDiff_elements', snap)[ok]
Mcg2 = get_.get_var(files, 'ColdGasClouds_elements', snap)[ok]
Mmet = np.append(Mmet, np.nansum(Mcg1[:, 2:] + Mcg2[:, 2:], axis=1))
Mcg = np.append(Mcg, np.nansum(Mcg1 + Mcg2, axis=1))
Z = Mmet / Mcg
DTM = Mdust / (Mmet)
ok = np.where(Mcg > 1e6)
return Mdust[ok], DTM[ok], Z[ok], Mstar[ok], Age[ok]
def get_vals(files, z, axs, snapnum, i, on):
if on:
i = 0
snap = snapnum[i][np.where(redshift == str(z))[0][0]]
Mstar = (get_.get_var(files[i], 'StellarMass', snap)*1e10)/h
ok = np.where(Mstar >= 10**9)[0]
Mstar = Mstar[ok]
Type = get_.get_var(files[i], 'Type', snap)[ok]
Age = get_.get_var(files[i], 'MassWeightAge', snap)[ok]
Mcg = get_.get_var(files[i], 'ColdGasDiff_elements', snap)[ok] + get_.get_var(files[i], 'ColdGasClouds_elements', snap)[ok]
met = (Mcg[:,4])/(15.9994*(Mcg[:,0])) #O/H ratio
Mdust1 = get_.get_var(files[i], 'DustColdGasDiff_elements', snap)[ok]
Mdust2 = get_.get_var(files[i], 'DustColdGasClouds_elements', snap)[ok]
Mdust = Mdust1 + Mdust2
met = met - (Mdust[:,4])/(15.9994*(Mcg[:,0]))
Mcg = np.sum(Mcg, axis = 1) #Total cold gas mass
Mdust = np.nansum(Mdust, axis = 1)
Mratio = Mdust/Mcg #Dust-to-total cold gas mass ratio. Dimensionless.
i = 1
snap = snapnum[i][np.where(redshift == str(z))[0][0]]
tmp = (get_.get_var(files[i], 'StellarMass', snap)*1e10)/h
ok = np.logical_and(tmp > 10**7.5, tmp < 10**8.98)
Mstar = np.append(Mstar, tmp[ok])
Type = np.append(Type, get_.get_var(files[i], 'Type', snap)[ok])
Age = np.append(Age, get_.get_var(files[i], 'MassWeightAge', snap)[ok])
tmp1 = get_.get_var(files[i], 'ColdGasDiff_elements', snap)[ok] + get_.get_var(files[i], 'ColdGasClouds_elements', snap)[ok]
Mdust1 = get_.get_var(files[i], 'DustColdGasDiff_elements', snap)[ok]
Mdust2 = get_.get_var(files[i], 'DustColdGasClouds_elements', snap)[ok]
tmp2 = Mdust1 + Mdust2
met = np.append(met, (tmp1[:,4]-tmp2[:,4])/(15.9994*(tmp1[:,0])))
tmp1 = np.nansum(tmp1, axis = 1)
tmp2 = np.nansum(Mdust1 + Mdust2, axis = 1)
Mdust = np.append(Mdust, tmp2)
Mratio = np.append(Mratio, tmp2/tmp1)
Mcg = np.append(Mcg, tmp1)
ok = np.logical_and(Mcg > 1e6, 12.+np.log10(met) > 6.) #Only selecting galaxies with cold gas mass above this value, so the galaxies we are looking at are realistic for the dust content usually seen
add = 'MR_MRII'
else:
add = sims[i]
snap = snapnum[i][np.where(redshift == str(z))[0][0]]
Mstar = (get_.get_var(files[i], 'StellarMass', snap)*1e10)/h
Type = get_.get_var(files[i], 'Type', snap)
Age = get_.get_var(files[i], 'MassWeightAge', snap)
Mcg = get_.get_var(files[i], 'ColdGas_elements', snap)
met = (Mcg[:,4])/(15.9994*(Mcg[:,0])) #O/H ratio
Mcg = np.nansum(Mcg, axis = 1) #Total cold gas mass
Mdust1 = get_.get_var(files[i], 'DustColdGasDiff_elements', snap)
Mdust2 = get_.get_var(files[i], 'DustColdGasClouds_elements', snap)
Mdust1 = np.nansum(Mdust1, axis = 1)
Mdust2 = np.nansum(Mdust2, axis = 1)
Mdust = Mdust1 + Mdust2
Mratio = Mdust/Mcg #Dust-to-total cold gas mass ratio. Dimensionless.
ok = np.logical_and(Mcg > 1e6, 12.+np.log10(met) > 6.) #Only selecting galaxies with cold gas mass above this value, so the galaxies we are looking at are realistic for the dust content usually seen
return add, met[ok], Mratio[ok], Type[ok], Age[ok]
def get_vals(files, z, axs, snapnum, i, on):
if on == False:
add = sims[i]
snap = snapnum[i][np.where(redshift == str(z))[0][0]]
Mstar = (get_.get_var(files[i], 'StellarMass', snap) * 1e10) / h
Age = get_.get_var(files[i], 'MassWeightAge', snap)
Type = get_.get_var(files[i], 'Type', snap)
Mcg = get_.get_var(files[i],
'ColdGasDiff_elements', snap) + get_.get_var(
files[i], 'ColdGasClouds_elements', snap)
met = Mcg[:, 4] / (15.9994 * Mcg[:, 0]) #O/H ratio
Mdust1 = get_.get_var(files[i], 'DustColdGasDiff_elements', snap)
Mdust2 = get_.get_var(files[i], 'DustColdGasClouds_elements', snap)
Mdust = Mdust1 + Mdust2
met = met - Mdust[:, 4] / (15.9994 * Mcg[:, 0])
Mdust = np.nansum(Mdust, axis=1)
ok = np.logical_and(Mcg > 1e6, 12. + np.log10(met) > 6.)
else:
i = 0
snap = snapnum[i][np.where(redshift == str(z))[0][0]]
Mstar = (get_.get_var(files[i], 'StellarMass', snap) * 1e10) / h
ok = np.where(Mstar >= 10**9.0)[0]
Mstar = Mstar[ok]
Age = get_.get_var(files[i], 'MassWeightAge', snap)[ok]
Type = get_.get_var(files[i], 'Type', snap)[ok]
Mcg = get_.get_var(files[i],
'ColdGasDiff_elements', snap)[ok] + get_.get_var(
files[i], 'ColdGasClouds_elements', snap)[ok]
met = Mcg[:, 4] / (15.9994 * Mcg[:, 0]) #O/H ratio
Mdust1 = get_.get_var(files[i], 'DustColdGasDiff_elements', snap)[ok]
Mdust2 = get_.get_var(files[i], 'DustColdGasClouds_elements', snap)[ok]
Mdust = Mdust1 + Mdust2
met = met - Mdust[:, 4] / (15.9994 * Mcg[:, 0])
Mdust = np.nansum(Mdust, axis=1)
i = 1
snap = snapnum[i][np.where(redshift == str(z))[0][0]]
tmp = (get_.get_var(files[i], 'StellarMass', snap) * 1e10) / h
ok = np.logical_and(tmp > 10**7.0, tmp < 10**9.0)
Mstar = np.append(Mstar, tmp[ok])
Type = np.append(Type, get_.get_var(files[i], 'Type', snap)[ok])
Age = np.append(Age, get_.get_var(files[i], 'MassWeightAge', snap)[ok])
Mcg1 = get_.get_var(files[i],
'ColdGasDiff_elements', snap)[ok] + get_.get_var(
files[i], 'ColdGasClouds_elements', snap)[ok]
Mdust1 = get_.get_var(files[i], 'DustColdGasDiff_elements', snap)[ok]
Mdust2 = get_.get_var(files[i], 'DustColdGasClouds_elements', snap)[ok]
tmp = Mdust1 + Mdust2
met = np.append(met, (Mcg1[:, 4] - tmp[:, 4]) / (15.9994 * Mcg[:, 0]))
Mdust = np.append(Mdust, np.nansum(tmp, axis=1))
Mcg = np.append(np.nansum(Mcg, axis=1), np.nansum(Mcg1, axis=1))
ok = np.logical_and(Mcg > 1e6, 12. + np.log10(met) > 6.)
add = 'MR_MRII'
return add, met[ok], Mdust[ok], Type[ok], Age[ok]
def plot_Z_dep(files, z, axs, snaps, i, on):
if on:
add = sims[0] + '_' + sims[1]
snap = snaps[0][np.where(redshift == str(z))[0][0]]
Mstar = (get_.get_var(files[0], 'StellarMass', snap) * 1e10) / 0.673
ok = np.where(Mstar >= 1e9)
Mstar = Mstar[ok]
Type = get_.get_var(files[0], 'Type', snap)[ok]
Mdust1 = get_.get_var(files[0], 'DustColdGasDiff_elements', snap)[ok]
Mdust2 = get_.get_var(files[0], 'DustColdGasClouds_elements', snap)[ok]
Mdust = Mdust1 + Mdust2
Mcg1 = get_.get_var(files[0], 'ColdGasDiff_elements', snap)[ok]
Mcg2 = get_.get_var(files[0], 'ColdGasClouds_elements', snap)[ok]
Mcg = Mcg1 + Mcg2
SFR = get_.get_var(files[0], 'Sfr', snap)[ok]
snap = snaps[1][np.where(redshift == str(z))[0][0]]
tmp = (get_.get_var(files[1], 'StellarMass', snap) * 1e10) / 0.673
ok = np.logical_and(tmp > 1e7, tmp <= 1e9)
Mstar = np.append(Mstar, tmp[ok])
Type = np.append(Type, get_.get_var(files[1], 'Type', snap)[ok])
tmp1 = get_.get_var(files[1], 'DustColdGasDiff_elements', snap)[ok]
tmp2 = get_.get_var(files[1], 'DustColdGasClouds_elements', snap)[ok]
Mdust = np.append(Mdust, tmp1 + tmp2, axis=0)
tmp1 = get_.get_var(files[1], 'ColdGasDiff_elements', snap)[ok]
tmp2 = get_.get_var(files[1], 'ColdGasClouds_elements', snap)[ok]
Mcg = np.append(Mcg, tmp1 + tmp2, axis=0)
SFR = np.append(SFR, get_.get_var(files[1], 'Sfr', snap)[ok])
else:
add = sims[i]
snap = snaps[0][np.where(redshift == str(z))[0][0]]
Mstar = (get_.get_var(files[i], 'StellarMass', snap) * 1e10) / 0.673
if i == 0:
ok = np.where(Mstar >= 1e9)[0]
else:
ok = np.logical_and(Mstar > 1e7, Mstar <= 1e9)
Mstar = Mstar[ok]
Type = get_.get_var(files[i], 'Type', snap)[ok]
Mdust1 = get_.get_var(files[i], 'DustColdGasDiff_elements', snap)[ok]
Mdust2 = get_.get_var(files[i], 'DustColdGasClouds_elements', snap)[ok]
Mdust = Mdust1 + Mdust2
Mcg1 = get_.get_var(files[i], 'ColdGasDiff_elements', snap)[ok]
Mcg2 = get_.get_var(files[i], 'ColdGasClouds_elements', snap)[ok]
Mcg = Mcg1 + Mcg2
SFR = get_.get_var(files[i], 'Sfr', snap)[ok]
sSFR = SFR / Mstar
pltx = (Mcg[:, 4] - Mdust[:, 4]) / (15.9994 * (Mcg[:, 0]))
plot_figure(pltx, Mcg, Mdust, sSFR, Type, z, axs)
xlim = [6.8, 9.8]
xticks = [7, 7.5, 8, 8.5, 9, 9.5]
axs.set_xlim(xlim)
axs.set_xticks(xticks)
return add