Analysis of truth/reconstruction associations

Correlation and ratio plots to study truth (mc) reconstruction.

benchmarks/dis/analysis/truth_reconstruction.py

@@ -6,32 +6,19 @@ import matplotlib.pyplot as plt
 import matplotlib as mpl
 import mplhep 
 import argparse
-#
 
 parser = argparse.ArgumentParser()
 parser.add_argument('--rec_file', type=str, help='Reconstructed track file.')
 parser.add_argument('--config', type=str, help='Momentum configuration.')
-parser.add_argument('--ebeam', type=float, help='Electron beam energy.')
-parser.add_argument('--pbeam', type=float, help='Proton (or ion) beam energy.')
-parser.add_argument('--minq2', type=float, help='Minimum four-momentum transfer squared Q2.')
 parser.add_argument('--nevents', type=float, help='Number of events to process.')
-parser.add_argument('-o', dest='outdir', default='results/', help='Output directory.')
-parser.add_argument('--benchmark_tag', type=str, help='Single or dis benchmarks')
+parser.add_argument('--result_path', type=str, help='Output directory.')
 args = parser.parse_args()
 kwargs = vars(args)
 
 rec_file = args.rec_file
 config = args.config
-minq2 = int(args.minq2)
-k = int(args.ebeam)
-p = int(args.pbeam)
 Nevents = int(args.nevents)
-benchmark_tag = args.benchmark_tag
-
-r_path = dis_path = 'dis/%gon%g/minQ2=%g/truth_reconstruction/'
-single_path = 'single/truth_reconstruction/'
-if benchmark_tag == 'single':
-     r_path = single_path
+r_path = os.path.join(args.result_path, '/truth_reconstruction/')
 
 for array in ur.iterate(rec_file + ':events',['MCParticles/MCParticles.generatorStatus',
                                           'MCParticles/MCParticles.mass',
@@ -226,8 +213,12 @@ for i in range(len(MC_list)):
     ax4.set_title('Electrons')
     ax5.set_title('Neutrons')
     ax6.set_title('Photons')
-    ax5.set_xlabel('%s'%(title_list[i]))
-    ax6.set_xlabel('%s'%(title_list[i]))
+    if i == 1:
+        ax5.set_xlabel('- %s'%(title_list[i]))
+        ax6.set_xlabel('- %s'%(title_list[i]))
+    else:
+        ax5.set_xlabel('%s'%(title_list[i]))
+        ax6.set_xlabel('%s'%(title_list[i]))
     fig.set_figwidth(20)
     fig.set_figheight(10)
     ax1.set_title('%s %s  %s  %s events'%(title_list[i],tratio,config,Nevents))
@@ -347,8 +338,8 @@ ax1.set_ylabel('rc-mc')
 ax2.set_ylabel('rc-mc')
 ax3.set_ylabel('Phi mc')
 ax4.set_ylabel('Phi rc')
-ax3.set_xlabel('Theta mc')
-ax4.set_xlabel('Theta rc')
+ax3.set_xlabel('- Theta mc')
+ax4.set_xlabel('- Theta rc')
 fig.set_figwidth(20)
 fig.set_figheight(10)