fixed bugs in n events

atlas-outreach-data-tools · Nov 4, 2024 · b15f415 · b15f415
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diff --git a/03_analyses.py b/03_analyses.py
@@ -430,8 +430,7 @@ def toggle_hint():
     # Steep 5: invariant mass plot
     if (st.session_state.leptoncharge_cut_applied and not st.session_state.is_higgs) or (st.session_state.is_higgs and st.session_state.leptonpt_cut_applied):
         st.markdown("## Unveiling Particles with Invariant Mass")
-        st.markdown("The *invariant mass* is a key tool in particle physics. It allows us to reconstruct the mass of particles that are produced in collisions, even if we don't observe them directly. By analyzing the energy and momentum of the leptons in the final state, we can calculate their combined *invariant mass*.")
-        st.markdown('This quantity is particularly useful because it is the same in all reference frames—it "remembers" the mass of the particle that decayed into the leptons.')
+        st.markdown("The *invariant mass* is a important tool in particle physics. It allows us to reconstruct the mass of particles that are produced in collisions, even if we don't observe them directly. By analyzing the energy and momentum of the leptons in the final state, we can calculate their combined *invariant mass*.")
         st.markdown("When plotted, the invariant mass distribution often shows peaks where particles like the Z boson or Higgs boson appear. These peaks reveal the characteristic mass of the particle, allowing us to \"see\" it even though it's long gone by the time we're analyzing the data.")
         st.markdown("By calculating and plotting the invariant mass, you will be able to observe these peaks and potentially discover particles for yourself!")
 

diff --git a/analyses/.__afsC80F b/analyses/.__afsC80F
diff --git a/analyses/.analysis.swp b/analyses/.analysis.swp
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diff --git a/analyses/36_Higgs__data_backgrounds_signal_dark.png b/analyses/36_Higgs__data_backgrounds_signal_dark.png
diff --git a/analyses/36_Higgs__data_backgrounds_signal_light.png b/analyses/36_Higgs__data_backgrounds_signal_light.png
diff --git a/analyses/36_Higgs__data_only_dark.png b/analyses/36_Higgs__data_only_dark.png
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diff --git a/analyses/analysis.py b/analyses/analysis.py
@@ -24,15 +24,14 @@
     # Samples to use for the analysis
 SAMPLES = {
     'data': {
-        'list' : ['data15_periodD','data15_periodF',
-                'data15_periodH','data16_periodA',
-                'data16_periodC','data16_periodE',
-                'data16_periodG','data16_periodK',
-                'data15_periodE','data15_periodG',
-                'data15_periodJ','data16_periodB',
-                'data16_periodD','data16_periodF',
-                'data16_PeriodI','data16_periodL'],
-        #'list' : ['data15','data16'],
+        'list' : ['data15_periodD','data15_periodE',
+                'data15_periodF','data15_periodG',
+                'data15_periodH','data15_periodJ',
+                'data16_periodA','data16_periodB',
+                'data16_periodC','data16_periodD',
+                'data16_periodE','data16_periodF',
+                'data16_periodG','data16_PeriodI',
+                'data16_periodK','data16_periodL'],
     },
 
     r'Background $Z,t\bar{t},t\bar{t}+V,VVV$' : { # Z+t+vvv
@@ -199,10 +198,9 @@ def read_file(path,sample, lumi_used, n_leptons, flavor, charge_pair, bin_edges,
     with uproot.open(path + ":analysis") as tree:
         numevents = tree.num_entries # number of events
         #if 'data' not in sample: xsec_weight = get_xsec_weight(sample) # get cross-section weight
-        for data in tree.iterate(['lep_n','lep_pt','lep_eta','lep_phi','lep_z0','lep_d0',
-                                  'lep_e','lep_charge','lep_type', 'lep_isTightID','lep_topoetcone20',
-                                  'lep_ptvarcone30', 'lep_isLooseID','lep_isMediumID',
-                                  'lep_isLooseIso','lep_isTightIso',
+        for data in tree.iterate(['lep_n','lep_pt','lep_eta','lep_phi','lep_e','lep_charge','lep_type', 
+                                  'lep_isTightID', 'lep_isLooseID','lep_isMediumID','lep_isLooseIso',
+                                  'lep_isTightIso',
                                   #'lep_isLooseID','lep_isMediumID',
                                   # add more variables here if you make cuts on them 
                                   'mcWeight','ScaleFactor_PILEUP',
@@ -219,8 +217,7 @@ def read_file(path,sample, lumi_used, n_leptons, flavor, charge_pair, bin_edges,
             if 'data' in sample:
                 # Update the initial event count
                 event_counts['initial_events'] += nIn
-
-
+
             # N_leptons cut
             data = data[data['lep_n'] == n_leptons]
 
@@ -230,17 +227,11 @@ def read_file(path,sample, lumi_used, n_leptons, flavor, charge_pair, bin_edges,
                 data[f'lep_looseID{i+1}'] = data['lep_isLooseID'][:,i]
                 data[f'lep_mediumID{i+1}'] = data['lep_isMediumID'][:,i]
                 data[f'lep_looseIso{i+1}'] = data['lep_isLooseIso'][:,i]
-                data[f'lep_topoetcone20{i+1}'] = data['lep_topoetcone20'][:,i]/data['lep_pt'][:,i]
-                data[f'lep_ptvarcone30{i+1}'] = data['lep_ptvarcone30'][:,i]/data['lep_pt'][:,i]
                 data[f'lep_type{i+1}'] = data['lep_type'][:,i]
-                data[f'lep_z0sintheta{i+1}'] = data['lep_z0'][:,i]*np.sin(2*np.arctan(np.exp(-1.0*data["lep_eta"][:,i])))
-                data[f'lep_d0{i+1}'] = data['lep_d0'][:,i]
 
             # Apply trigger
             data = data[data['trigE'] | data['trigM']]
 
-            logging.info("Cut : After trg        : %i"%len(data['lep_n']))
-
             for i in range(0,n_leptons):
                 # Keep events where all four leptons pass the loose isolation criteria.
                 data = data[data[f'lep_looseIso{i+1}']]
@@ -250,27 +241,27 @@ def read_file(path,sample, lumi_used, n_leptons, flavor, charge_pair, bin_edges,
 
             if 'data' in sample:
                 # Update the event count after cleaning leptons
-                event_counts['after_cleaning_leptons'] += len(data['lep_n'])
+                event_counts['after_cleaning_leptons'] += len(data)
 
-            logging.info("Cut : After cleaning leptons       : %i"%len(data['lep_n'])) ####----> Save this as the initial number of events
+            logging.info("Cut : After cleaning leptons       : %i"%len(data)) 
 
             # Cut on lepton charge using the function cut_lep_charge defined above
             mask_lep_type = lepton_type_cut(data.lep_type, n_leptons, flavor)
             data = data[mask_lep_type]
 
             if 'data' in sample:
                 # Update the event count after lepton type cut
-                event_counts['after_lepton_type_cut'] += len(data['lep_n'])
-            logging.info(f"Cut : After lepton_type_cut : {len(data['lep_n'])}")
+                event_counts['after_lepton_type_cut'] += len(data)
+            logging.info(f"Cut : After lepton_type_cut : {len(data)}")
 
             # cut on lepton type using the function cut_lep_type defined above
             mask_lep_charge = lepton_charge_cut(data.lep_charge, n_leptons, charge_pair)
             data = data[mask_lep_charge]
 
             if 'data' in sample:
                 # Update the event count after lepton charge cut
-                event_counts['after_lepton_charge_cut'] += len(data['lep_n'])
-            logging.info(f"Cut : After lepton_charge_cut : {len(data['lep_n'])}")
+                event_counts['after_lepton_charge_cut'] += len(data)
+            logging.info(f"Cut : After lepton_charge_cut : {len(data)}")
 
             if lumi_weights: #mening it is higgs
                 # pT cuts
@@ -280,9 +271,9 @@ def read_file(path,sample, lumi_used, n_leptons, flavor, charge_pair, bin_edges,
 
                 if 'data' in sample:
                     # Update the event count after lepton charge cut
-                    event_counts['after_leptonpt_cut'] += len(data['lep_n'])
+                    event_counts['after_leptonpt_cut'] += len(data)
 
-                logging.info(f"Cut : After lepton pT cut : {len(data['lep_n'])}")
+                logging.info(f"Cut : After lepton pT cut : {len(data)}")
 
             # calculation of 4-lepton invariant mass using the function calc_mllll defined above
             data['mass'] = invariant_mass(data.lep_pt, data.lep_eta, data.lep_phi, data.lep_e, n_leptons)
@@ -330,6 +321,12 @@ def get_data_from_files(lumi_data, lumi_mc, n_leptons, flavor, charge_pair, bin_
         hist_mass_weights_squared_total = np.zeros(len(bin_edges) - 1)
 
         for val in SAMPLES[s]['list']:
+            period_event_counts = {'initial_events':0,
+                   'after_cleaning_leptons':0,
+                   'after_lepton_type_cut':0,
+                   'after_lepton_charge_cut':0,
+                   'after_leptonpt_cut':0}
+
             if s == 'data':
                 prefix = "Data/"
                 fileString = TUPLE_PATH + prefix + val + ".root"
@@ -343,27 +340,28 @@ def get_data_from_files(lumi_data, lumi_mc, n_leptons, flavor, charge_pair, bin_
 
             if process_mc:
                 if s == 'data':
-                    hist_mass, hist_mass_weights_squared, batch_event_counts = read_file(fileString, val, lumi_data, 
+                    hist_mass, hist_mass_weights_squared, period_event_counts = read_file(fileString, val, lumi_data, 
                                                                                      n_leptons, flavor, charge_pair, 
                                                                                      bin_edges, lumi_weights=lumi_data)
                 else:
+                    # period_event_counts should be just zeros here
                     hist_mass, hist_mass_weights_squared, _ = read_file(fileString, val, lumi_mc, 
                                                                                      n_leptons, flavor, charge_pair, 
                                                                                      bin_edges, lumi_weights=lumi_data)
 
             elif s == 'data':
-                hist_mass, hist_mass_weights_squared, batch_event_counts = read_file(fileString, val, lumi_data, 
+                hist_mass, hist_mass_weights_squared, period_event_counts = read_file(fileString, val, lumi_data, 
                                                                                      n_leptons, flavor, charge_pair, 
                                                                                      bin_edges)
 
             hist_mass_total += hist_mass
             hist_mass_weights_squared_total += hist_mass_weights_squared
-            
-            event_counts['initial_events'] += batch_event_counts['initial_events']
-            event_counts['after_cleaning_leptons'] += batch_event_counts['after_cleaning_leptons']
-            event_counts['after_lepton_type_cut'] += batch_event_counts['after_lepton_type_cut']
-            event_counts['after_lepton_charge_cut'] += batch_event_counts['after_lepton_charge_cut']
-            event_counts['after_leptonpt_cut'] += batch_event_counts['after_leptonpt_cut']
+
+            event_counts['initial_events'] += period_event_counts['initial_events']
+            event_counts['after_cleaning_leptons'] += period_event_counts['after_cleaning_leptons']
+            event_counts['after_lepton_type_cut'] += period_event_counts['after_lepton_type_cut']
+            event_counts['after_lepton_charge_cut'] += period_event_counts['after_lepton_charge_cut']
+            event_counts['after_leptonpt_cut'] += period_event_counts['after_leptonpt_cut']
 
         data[s] = hist_mass_total
         data_weights_squared[s] = hist_mass_weights_squared_total
@@ -481,7 +479,7 @@ def make_plot(data, data_weights_squared, lumi_used, bin_edges, background='ligh
 
     plt.tight_layout()
     filename = f'{lumi_used}_{filename_prefix}_{filename_suffix}_{background}.png'
-    plt.savefig(filename, transparent=True)
+    plt.savefig(filename, bbox_inches='tight', transparent=True)
     plt.close()
 
     return filename
@@ -659,7 +657,6 @@ def main():
                             results_json[lumi_key][nlep_key][flavor_key][charge_key][f'plot_{filename_suffix}_dark'] = plot_dark
 
 
-
     # Save the results to a JSON file after all configurations are processed
         with open('event_counts.json', 'w') as json_file:
             json.dump(results_json, json_file, indent=4)