figure tweaks

overplot_corner.py

@@ -5,64 +5,94 @@
 
 # read in the nested sampling posteriors & make some nice corner plots
 
-def combine_teff_hilow(fitname='sinfoni', model='bt-settl-cifist'):
+
+def combine_teff_hilow(fitname="sinfoni", model="bt-settl-cifist"):
     """
     A couple of the runs are done by setting a low prior on Teff, then re-running
-    with a higher prior on Teff. This method combines them, making sure the 
+    with a higher prior on Teff. This method combines them, making sure the
     relative likelihoods are weighted correctly
     """
 
-    if 'nosphereGP' in fitname:
-        names = ['Teff', 'logg','R','plx']
-        labels=['T$_{{\\mathrm{{eff}}}}$ [K]', '$\\log{{g}}$','R [R$_J$]','$\pi$ [mas]']
+    if "nosphereGP" in fitname:
+        names = ["Teff", "logg", "R", "plx"]
+        labels = [
+            "T$_{{\\mathrm{{eff}}}}$ [K]",
+            "$\\log{{g}}$",
+            "R [R$_J$]",
+            "$\pi$ [mas]",
+        ]
     else:
-        names = ['Teff', 'logg','R','plx','gp_len','gp_amp']
-        labels=['T$_{{\\mathrm{{eff}}}}$ [K]', '$\\log{{g}}$','R [R$_J$]','$\pi$ [mas]', '$\\log{{l_{{SPHERE_IFU}}}}$', '$A_{{SPHERE_IFU}}$']
-    if 'sinfoni' in fitname:
-        names += ['rv_sinfoni']
+        names = ["Teff", "logg", "R", "plx", "gp_len", "gp_amp"]
+        labels = [
+            "T$_{{\\mathrm{{eff}}}}$ [K]",
+            "$\\log{{g}}$",
+            "R [R$_J$]",
+            "$\pi$ [mas]",
+            "$\\log{{l_{{SPHERE_IFU}}}}$",
+            "$A_{{SPHERE_IFU}}$",
+        ]
+    if "sinfoni" in fitname:
+        names += ["rv_sinfoni"]
 
-    names += ['']
-    chain_name = 'results/{}_tefflo_{}/multinest/post_equal_weights.dat'.format(fitname, model)
-    print(chain_name)
-    loteff_post = pd.read_csv(
-        chain_name,
-        delim_whitespace=True,
-        names = names
+    names += [""]
+    chain_name = "results/{}_tefflo_{}/multinest/post_equal_weights.dat".format(
+        fitname, model
     )
-
-    chain_name = 'results/{}_teffhi_{}/multinest/post_equal_weights.dat'.format(fitname, model)
     print(chain_name)
-    hiteff_post = pd.read_csv(
-        chain_name,
-        delim_whitespace=True,
-        names = names
+    loteff_post = pd.read_csv(chain_name, delim_whitespace=True, names=names)
+
+    chain_name = "results/{}_teffhi_{}/multinest/post_equal_weights.dat".format(
+        fitname, model
     )
+    print(chain_name)
+    hiteff_post = pd.read_csv(chain_name, delim_whitespace=True, names=names)
 
     return pd.concat([loteff_post, hiteff_post]), labels
 
+
 sphereGP = True
-jwst=True
+jwst = True
 
-fitname = 'sinfoni'
+fitname = "sinfoni"
 if jwst:
-    fitname += '_jwst'
+    fitname += "_jwst"
 if not sphereGP:
-    fitname += '_nosphereGP'
+    fitname += "_nosphereGP"
 sinfoni_fit, labels = combine_teff_hilow(fitname=fitname)
 
-fitname = 'gravity'
+fitname = "gravity"
 if jwst:
-    fitname += '_jwst'
+    fitname += "_jwst"
 if not sphereGP:
-    fitname += '_nosphereGP'
+    fitname += "_nosphereGP"
 gravity_fit, labels = combine_teff_hilow(fitname=fitname)
 
 fig = corner.corner(
-    sinfoni_fit[sinfoni_fit.keys()[:-2]], 
-    bins=25, labels=labels, plot_datapoints=False, color='hotpink', plot_density=False, weights=np.ones(len(sinfoni_fit)) / len(sinfoni_fit), 
+    sinfoni_fit[sinfoni_fit.keys()[:-2]],
+    bins=25,
+    labels=labels,
+    plot_datapoints=False,
+    color="hotpink",
+    plot_density=False,
+    weights=np.ones(len(sinfoni_fit)) / len(sinfoni_fit),
 )
 corner.corner(
-    gravity_fit[gravity_fit.keys()[:-1]], fig=fig,
-    bins=25, labels=labels, plot_datapoints=False, color='purple', plot_density=False, weights=np.ones(len(gravity_fit)) / len(gravity_fit), 
+    gravity_fit[gravity_fit.keys()[:-1]],
+    fig=fig,
+    bins=25,
+    labels=labels,
+    plot_datapoints=False,
+    color="purple",
+    plot_density=False,
+    weights=np.ones(len(gravity_fit)) / len(gravity_fit),
+)
+
+for ax in fig.get_axes():
+    ax.tick_params(axis="both", labelsize=14)
+    ax.set_xlabel(ax.get_xlabel(), fontsize=14)
+    ax.set_ylabel(ax.get_ylabel(), fontsize=14)
+    ax.set_title(ax.get_title(), fontsize=14)
+ax.set_xlabel(ax.get_xlabel(), fontsize=14)
+plt.savefig(
+    "results/plots/sinfoni_gravity_corner_sphereGP{}.png".format(sphereGP), dpi=250
 )
-plt.savefig('results/plots/sinfoni_gravity_corner_sphereGP{}.png'.format(sphereGP), dpi=250)