Truth reconstruction error

Show standard deviation error in text on plots produced from truth_reconstruction.py

benchmarks/dis/analysis/truth_reconstruction.py

@@ -224,13 +224,11 @@ for i in range(len(MC_list)): #Repeat the following steps for each variable (mom
             if i == 0:  # for momentum
                 ax1.set_ylim(1-(Y_error[0][4]*10),1+(Y_error[0][4]*10))
                 center = 1
-                shift = 0
             else:       # for angles
                 ax1.set_ylim(0-(Y_error[0][4]*10),0+(Y_error[0][4]*10))
                 center = 0
-                shift = 0.1
             for each_bin in range(len(Y_error[0][0])):
-                ax1.text(x=Y_error[0][0][each_bin]-shift,y=center + Y_error[0][4]*7, s= '\u03BC = %.3f\n\u03C3 = %.3f' % (Y_error[0][1][each_bin],Y_error[0][3][each_bin]),size=text_size)
+                ax1.text(x=Y_error[0][0][each_bin],y=center + Y_error[0][4]*7, s= '\u03BC = %.3f\n\u03C3 = %.3f' % (Y_error[0][1][each_bin],Y_error[0][3][each_bin]),size=text_size,horizontalalignment='center',verticalalignment='top')
 
             ax1.set_title('%s %s with error bars %s  %s events\n DETECTOR_CONFIG: %s'%(title_list[i],title,config,Nevents,Dconfig))
             plt.savefig(os.path.join(r_path, '%s_%s_error_%s.png' %  (title_list[i],title,config)))
@@ -294,7 +292,7 @@ for i in range(len(MC_list)): #Repeat the following steps for each variable (mom
                 ax1.set_ylim(0-(Y_error[0][4]*10),0+(Y_error[0][4]*10))
                 for each_bin in range(len(Y_error[0][0])):
                     ax1.text(x=Y_error[0][0][each_bin],y=0 + Y_error[0][4]*7,
-                        s= '\u03BC = %.3f\n\u03C3 = %.3f' % (Y_error[0][1][each_bin],Y_error[0][3][each_bin]),size=text_size)
+                        s= '\u03BC = %.3f\n\u03C3 = %.3f' % (Y_error[0][1][each_bin],Y_error[0][3][each_bin]),size=text_size,horizontalalignment='center',verticalalignment='top')
                 ax1.set_title('%s %s with error bars %s  %s events\n DETECTOR_CONFIG: %s'%(title_list[i],title,config,Nevents,Dconfig))
                 plt.savefig(os.path.join(r_path, '%s_difference_vs_momentum_error_%s.png' %  (title_list[i],config)))
             else:
@@ -398,13 +396,14 @@ def particle_plots(boolean_particle):
     ax2.errorbar(-Y_error[1][0], Y_error[1][1], yerr=Y_error[1][3], xerr=Y_error[1][2] ,fmt='None', ecolor = 'orange', elinewidth = 1)
     ax3.errorbar(-Y_error[0][0], Y_error[0][1], yerr=Y_error[0][3], xerr=Y_error[0][2] ,fmt='None', ecolor = 'orange', elinewidth = 1)
     ax4.errorbar(-Y_error[1][0], Y_error[1][1], yerr=Y_error[1][3], xerr=Y_error[1][2] ,fmt='None', ecolor = 'orange', elinewidth = 1)
+    y_limits = ax3.get_ylim()
     for each_bin in range(len(Y_error[0][0])):
         if not np.isnan(Y_error[0][1][each_bin]):
-            ax3.text(x=-Y_error[0][0][each_bin]-0.1,y=0 - Y_error[0][4]*50,
-                    s= '\u03BC = %.3f\n\u03C3 = %.3f' % (Y_error[0][1][each_bin],Y_error[0][3][each_bin]),size=text_size)
+            ax3.text(x=-Y_error[0][0][each_bin],y=y_limits[1],
+                    s= '\u03BC = %.3f\n\u03C3 = %.3f' % (Y_error[0][1][each_bin],Y_error[0][3][each_bin]),size=text_size,horizontalalignment='center',verticalalignment='top')
         if not np.isnan(Y_error[1][1][each_bin]):
-            ax4.text(x=-Y_error[1][0][each_bin]-0.1,y=0 - Y_error[1][4]*50,
-                    s= '\u03BC = %.3f\n\u03C3 = %.3f' % (Y_error[1][1][each_bin],Y_error[1][3][each_bin]),size=text_size)
+            ax4.text(x=-Y_error[1][0][each_bin],y=y_limits[1],
+                    s= '\u03BC = %.3f\n\u03C3 = %.3f' % (Y_error[1][1][each_bin],Y_error[1][3][each_bin]),size=text_size,horizontalalignment='center',verticalalignment='top')
     if not np.isnan(Y_error[0][4]):
         ax1.set_ylim(0-(Y_error[1][4]*10),0+(Y_error[1][4]*10))
         ax2.set_ylim(0-(Y_error[1][4]*10),0+(Y_error[1][4]*10))