diff --git a/swp2.py b/swp2.py
index 207021c..69e6a24 100644
--- a/swp2.py
+++ b/swp2.py
@@ -252,6 +252,7 @@ def save_all_epochs_thetafolder(folder_path, mu, tgen, title = "Title", theta_sc
     print(cpt, "theta file(s) have been scanned.")
     brkpt_lik = []
     top_plots = {}
+    best_scenario_for_epoch = {}
     for epoch, scenari in epochs.items():
         # sort starting by the smallest -log(Likelihood)
         best10_scenari = (sorted(list(scenari.keys())))[:10]
@@ -270,6 +271,7 @@ def save_all_epochs_thetafolder(folder_path, mu, tgen, title = "Title", theta_sc
                 y[i] = y[i]/N0
                 x[i] = x[i]/N0
         top_plots[greatest_likelihood] = x,y,epoch
+        best_scenario_for_epoch[epoch] = x,y,greatest_likelihood
     plots_likelihoods = list(top_plots.keys())
     for i in range(len(plots_likelihoods)):
         plots_likelihoods[i] = float(plots_likelihoods[i])
@@ -278,9 +280,16 @@ def save_all_epochs_thetafolder(folder_path, mu, tgen, title = "Title", theta_sc
     # store x,y,brks,likelihood
     plots['best'] = (top_plots[top_plot_lik][0], top_plots[top_plot_lik][1], str(top_plots[top_plot_lik][2]), top_plot_lik)
     plots['plots'] = []
-    for k, plot_Lk in enumerate(best10_plots[1:]):
-        plot_Lk = str(plot_Lk)
-        plots['plots'].append([top_plots[plot_Lk][0], top_plots[plot_Lk][1], str(top_plots[plot_Lk][2]), plot_Lk])
+    for k, epoch in enumerate(best_scenario_for_epoch.keys()):
+        plot_Lk = str(best_scenario_for_epoch[epoch][2])
+        x,y = best_scenario_for_epoch[epoch][0], best_scenario_for_epoch[epoch][1]
+        plots['plots'].append([x, y, str(epoch), plot_Lk])
+    plots['plots'] = sorted(plots['plots'], key=lambda x: float(x[3]))
+    plots['plots'] = plots['plots'][1:]
+    # Previous version. Was this correct????
+    # for k, plot_Lk in enumerate(best10_plots[1:]):
+    #     plot_Lk = str(plot_Lk)
+    #     plots['plots'].append([top_plots[plot_Lk][0], top_plots[plot_Lk][1], str(top_plots[plot_Lk][2]), plot_Lk])
     # plot likelihood against nb of breakpoints
     # best possible likelihood from SFS
     # Segregating sites