Loading src/scripts/plots/plot_mbh_mstar.py +12 −6 Original line number Diff line number Diff line Loading @@ -21,8 +21,8 @@ mpl.style.use("etc/agile.mplstyle") log_mstar = np.linspace(8.5, 12.5, 401) dlog_mstar = 0.10 dz = 1.0 lw1 = 3.0 lw2 = 3.0 lw1 = 2.5 lw2 = 2.5 lw3 = 1.5 alpha = 0.80 cmap = mpl.colormaps["gist_heat"] Loading @@ -37,12 +37,18 @@ def main(): fig, axes = plt.subplots(1, 2, figsize=(8.3, 5.85 / 1.5), sharex=True, sharey=True, dpi=300) # Left panel: Plots the redshift evolution of the Con Eq for z in [0.0, 1.0, 2.0, 3.0, 4.0, 5.0]: for z in [0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 5.5]: # log_mbh = mbh.get_log_mbh_continuity(log_mstar, z) # log_mbh = mbh.get_log_mbh_continuity_new(log_mstar, z) ls = "solid" if z < 4 else "dotted" ls = "solid" if z < 4 else "dashed" if z < 5.5: log_mbh = mbh.get_log_mbh_continuity_new2(log_mstar, np.full_like(log_mstar, z)) axes[0].plot(log_mstar, log_mbh, color=cmap(norm(z)), lw=lw1, label=f"$z = {z:.0f}$", ls=ls) else: # Plot IC log_mbh = mbh.get_log_mbh_reines_volonteri2015(log_mstar) axes[0].plot(log_mstar, log_mbh, color="C2", lw=lw1, label="IC (R&V15)", ls="dotted") # Right panel: Plots the local Con Eq against literature # log_mbh = mbh.get_log_mbh_continuity(log_mstar, 0.0) Loading Loading
src/scripts/plots/plot_mbh_mstar.py +12 −6 Original line number Diff line number Diff line Loading @@ -21,8 +21,8 @@ mpl.style.use("etc/agile.mplstyle") log_mstar = np.linspace(8.5, 12.5, 401) dlog_mstar = 0.10 dz = 1.0 lw1 = 3.0 lw2 = 3.0 lw1 = 2.5 lw2 = 2.5 lw3 = 1.5 alpha = 0.80 cmap = mpl.colormaps["gist_heat"] Loading @@ -37,12 +37,18 @@ def main(): fig, axes = plt.subplots(1, 2, figsize=(8.3, 5.85 / 1.5), sharex=True, sharey=True, dpi=300) # Left panel: Plots the redshift evolution of the Con Eq for z in [0.0, 1.0, 2.0, 3.0, 4.0, 5.0]: for z in [0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 5.5]: # log_mbh = mbh.get_log_mbh_continuity(log_mstar, z) # log_mbh = mbh.get_log_mbh_continuity_new(log_mstar, z) ls = "solid" if z < 4 else "dotted" ls = "solid" if z < 4 else "dashed" if z < 5.5: log_mbh = mbh.get_log_mbh_continuity_new2(log_mstar, np.full_like(log_mstar, z)) axes[0].plot(log_mstar, log_mbh, color=cmap(norm(z)), lw=lw1, label=f"$z = {z:.0f}$", ls=ls) else: # Plot IC log_mbh = mbh.get_log_mbh_reines_volonteri2015(log_mstar) axes[0].plot(log_mstar, log_mbh, color="C2", lw=lw1, label="IC (R&V15)", ls="dotted") # Right panel: Plots the local Con Eq against literature # log_mbh = mbh.get_log_mbh_continuity(log_mstar, 0.0) Loading