Ok likelihood swp2

swp2.py

         plt.title(title)
         plt.savefig(title+'_b'+str(breaks)+'.pdf')
     # plot likelihood against nb of breakpoints
-
     # best possible likelihood from SFS
     # Segregating sites
     S = sum(SFS_stored)
         for i in range(0, len(x)):
             T += y[i] / (x[i]*(x[i]-1))
             x_2.append(T)
-    # Plotting (fig 2)
-    plt.plot(x_2, y, 'o', linestyle="dotted", alpha=0.75, lw=2, label = str(epoch)+' brks')
-    plt.xlabel("# breaks")
-    plt.ylabel("theta")
-    plt.legend(loc='upper right')
-    plt.savefig(title+'_test'+str(k)+'.pdf')
-
-    # Plotting (fig 3) which is the same but log scale for x
-    plt.plot(x_2, y, 'o', linestyle="dotted", alpha=0.75, lw=2, label = str(epoch)+' brks')
-    plt.xscale('log')
-    plt.xlabel("# breaks")
-    plt.ylabel("theta")
-    plt.legend(loc='upper right')
-    plt.savefig(title+'_test'+str(k)+'_log.pdf')
+        # Plotting (fig 2)
+        plt.plot(x_2, y, 'o', linestyle="dotted", alpha=0.75, lw=2, label = str(epoch)+' brks')
+        plt.xlabel("# breaks")
+        plt.ylabel("theta")
+        plt.legend(loc='upper right')
+        plt.savefig(title+'_test'+str(k)+'.pdf')
+        # Plotting (fig 3) which is the same but log scale for x
+        plt.plot(x_2, y, 'o', linestyle="dotted", alpha=0.75, lw=2, label = str(epoch)+' brks')
+        plt.xscale('log')
+        plt.xlabel("# breaks")
+        plt.ylabel("theta")
+        plt.legend(loc='upper right')
+        plt.savefig(title+'_test'+str(k)+'_log.pdf')
 
 def save_multi_image(filename):
     pp = PdfPages(filename)