detlaM = 0
imf = 'Sal'
if imf == 'Sal':
detlaM = 0.23
ifplot = False
#%%
for ii in range(1):
HSC = HSC_set(zs, core = True,imf = imf)
Horizon = Horizon_set(filename, HSC_Lbol_overall=HSC['HSC_Lbol_overall'], HSC_MBHs_overall=HSC['HSC_MBHs_overall'],
zs = zs, I_mag_break = I_mag_break, imf = imf)
#%%
comp_plot(Horizon['BH_Mass'], Horizon['Eddington_ratio'], 'BH_Mass', 'Eddington_ratio')
# plt.xlabel(r'log(M$_{\rm BH}$/M$_{\odot}$)',fontsize=30)
# plt.ylabel('AGN Eddington ratio', fontsize=25)
plt.tick_params(labelsize=25)
plt.xlim(5,10)
if ifplot == True:
plt.show()
else:
plt.close()
comp_plot(Horizon['logLbol_nois'], Horizon['BH_Mass_nois'], 'logLbol_nois', 'BH_Mass_nois', alpha = 0.2, label = 'Horizon')
plt.scatter(Horizon['logLbol_nois_sl'], Horizon['BH_Mass_nois_sl'], color = 'green',alpha=0.2, zorder = 1, label = 'selected Horizon')
plt.scatter(HSC['HSC_Lbol_overall'], HSC['HSC_MBHs_overall'],c='orange',alpha=0.2,zorder = 0.5, label = 'HSC QSO distribution')
plt.xlabel('AGN logLbol', fontsize=25)
plt.ylabel(r'log(M$_{\rm BH}$/M$_{\odot}$)',fontsize=30)
# plt.xlabel(r"log(M$_*$/M$_{\odot})$",fontsize=35)
# plt.ylabel(r'log(M$_{\rm BH}$/M$_{\odot}$)',fontsize=35)
# plt.title("HSC uniform sample",fontsize=35)
# plt.tick_params(labelsize=25)
# plt.xlim(9,12.5)
# plt.ylim(6.0,10.3)
# cbar = plt.colorbar()
# cbar.ax.tick_params(labelsize=20)
# cbar.ax.set_ylabel('Redshift', rotation=270, fontsize = 25, labelpad=25)
# if ifplot == True:
# plt.show()
# else:
# plt.close()
#%%
comp_plot(MBII['BH_Mass'], MBII['sdss_g_pointsource'], 'BH_Mass',
'sdss_g_pointsource')
# plt.xlabel(r'log(M$_{\rm BH}$/M$_{\odot}$)',fontsize=30)
# plt.ylabel('AGN abs magnitude rest-frame g band', fontsize=25)
plt.xlim(5, 10)
plt.ylim(-26, -14)
if ifplot == True:
plt.show()
else:
plt.close()
comp_plot(MBII['BH_Mass'], MBII['Eddington_ratio'], 'BH_Mass',
'Eddington_ratio')
# plt.xlabel(r'log(M$_{\rm BH}$/M$_{\odot}$)',fontsize=30)
# plt.ylabel('AGN Eddington ratio', fontsize=25)
plt.tick_params(labelsize=25)
plt.xlim(5, 10)
detlaM = 0
imf = 'Sal'
if imf == 'Sal':
detlaM = 0.23
ifplot = True
#%%
for ii in range(1):
HSC = HSC_set(zs, core = True,imf = imf)
EAGLE = EAGLE_set(filename, HSC_Lbol_overall=HSC['HSC_Lbol_overall'], HSC_MBHs_overall=HSC['HSC_MBHs_overall'],
zs = zs, I_mag_break = I_mag_break, imf = imf)
#%%
comp_plot(EAGLE['BH_Mass'], EAGLE['Eddington_ratio'], 'BH_Mass', 'Eddington_ratio')
# plt.xlabel(r'log(M$_{\rm BH}$/M$_{\odot}$)',fontsize=30)
# plt.ylabel('AGN Eddington ratio', fontsize=25)
plt.tick_params(labelsize=25)
plt.xlim(5,10)
if ifplot == True:
plt.show()
else:
plt.close()
comp_plot(EAGLE['logLbol_nois'], EAGLE['BH_Mass_nois'], 'logLbol_nois', 'BH_Mass_nois', alpha = 0.2, label = 'EAGLE')
plt.scatter(EAGLE['logLbol_nois_sl'], EAGLE['BH_Mass_nois_sl'], color = 'green',alpha=0.2, zorder = 1, label = 'selected EAGLE')
plt.scatter(HSC['HSC_Lbol_overall'], HSC['HSC_MBHs_overall'],c='orange',alpha=0.2,zorder = 0.5, label = 'HSC QSO distribution')
plt.xlabel('AGN logLbol', fontsize=25)
plt.ylabel(r'log(M$_{\rm BH}$/M$_{\odot}$)',fontsize=30)
plt.scatter(HSC['HSC_Mstar_overall'], HSC['HSC_MBHs_overall'],c=HSC['HSC_z_overall'],
zorder = 0.5, alpha=0.4, edgecolors='white', cmap=cmap_r)
plt.plot(xl, m_ml*xl+b_ml, color="k", linewidth=4.0,zorder=-0.5)
plt.xlabel(r"log(M$_*$/M$_{\odot})$",fontsize=35)
plt.ylabel(r'log(M$_{\rm BH}$/M$_{\odot}$)',fontsize=35)
plt.title("HSC uniform sample",fontsize=35)
plt.tick_params(labelsize=25)
plt.xlim(9,12.5)
plt.ylim(6.0,10.3)
cbar = plt.colorbar()
cbar.ax.tick_params(labelsize=20)
cbar.ax.set_ylabel('Redshift', rotation=270, fontsize = 25, labelpad=25)
plt.show()
#%%
comp_plot(Illustris['BH_Mass'], Illustris['sdss_g_pointsource'], 'BH_Mass', 'sdss_g_pointsource')
# plt.xlabel(r'log(M$_{\rm BH}$/M$_{\odot}$)',fontsize=30)
# plt.ylabel('AGN abs magnitude rest-frame g band', fontsize=25)
plt.xlim(5,10)
plt.ylim(-26, -14)
plt.show()
comp_plot(Illustris['BH_Mass'], Illustris['Eddington_ratio'], 'BH_Mass', 'Eddington_ratio')
# plt.xlabel(r'log(M$_{\rm BH}$/M$_{\odot}$)',fontsize=30)
# plt.ylabel('AGN Eddington ratio', fontsize=25)
plt.tick_params(labelsize=25)
plt.xlim(5,10)
plt.show()
# comp_plot(Illustris['logLbol'], Illustris['BH_Mass'], 'logLbol', 'BH_Mass')
comp_plot(Illustris['logLbol_nois'], Illustris['BH_Mass_nois'], 'logLbol', 'BH_Mass')