construct kinematic coverage plot and include Sigma and eSigma correlation in kinematics_correlation.py

include Sigma and eSigma and Kinematic Coverage script in benchmarks/dis/analysis/kinematics_correlations.py

benchmarks/dis/analysis/kinematics_correlations.py

@@ -88,7 +88,7 @@ def Q2correlation(minq2,method): #minq2 can be 1,10,100, or 1000; method can be
     fig.set_figheight(11)
     plt.xlabel('$Q^2$ [$GeV^2$] Truth')
     plt.ylabel('$Q^2$ [$GeV^2$] {}'.format(method_dict['{}'.format(method)]))
-    plt.title('{}   $Q^2$ correlation   {}x{}   $minQ^2=${}$GeV^2$'.format(method_dict['{}'.format(method)],k,p,minq2))
+    plt.title('{}   $Q^2$ correlation   {}x{}   $minQ^2=${}$GeV^2$\n  {} events  DETECTOR_CONFIG: {} '.format(method_dict['{}'.format(method)],k,p,minq2,Nevents,Dconfig))
     plt.savefig(os.path.join(r_path, 'Q2_correlation_%s_%s.png' %(method,config)))
 
 
@@ -146,7 +146,7 @@ def Xcorrelation(minq2,method): #minq2 can be 1,10,100, or 1000; method can be '
     fig.set_figheight(11)
     plt.xlabel('x Truth')
     plt.ylabel('$x$   {}'.format(method_dict['{}'.format(method)]))
-    plt.title('{}   $x$ correlation   {}x{}   $minQ^2=${}$GeV^2$'.format(method_dict['{}'.format(method)],k,p,minq2))
+    plt.title('{}   $x$ correlation   {}x{}   $minQ^2=${}$GeV^2$\n  {} events  DETECTOR_CONFIG: {} '.format(method_dict['{}'.format(method)],k,p,minq2,Nevents,Dconfig))
     plt.savefig(os.path.join(r_path, 'x_correlation_%s_%s.png' %(method,config)))
 
 
@@ -223,7 +223,7 @@ ax6.set_title('Jacquet Blondel')
 fig.set_figwidth(30)
 fig.set_figheight(20)
 
-plt.title('Kinematic Coverage  {}x{}   $minQ^2=${}$GeV^2$'.format(k,p,minq2))
-plt.savefig(os.path.join(r_path, 'kinematic_coverage_%s.png' %(method,config)))
+plt.title('Kinematic Coverage  {}x{}   $minQ^2=${}$GeV^2$\n  {} events  DETECTOR_CONFIG: {} '.format(k,p,minq2,Nevents,Dconfig))
+plt.savefig(os.path.join(r_path, 'kinematic_coverage_%s.png' %(config)))