@@ -110,8 +110,9 @@ def cli(filenames, cut_level, debug, output, layout, event_type):
110110
111111 if event_type > 0 :
112112 logging .info (f"Number of events within event_type file: { len (event_types )} " )
113+ ratio = np .sum (event_types == - 1 ) / len (event_types )
113114 logging .info (
114- f"Ratio of training to simulated events: { np . sum ( event_types == - 1 ) / len ( event_types ) } "
115+ f"Ratio of training to simulated events: { ratio } "
115116 )
116117 logging .info (f"len(data_mask): { len (data_mask )} " )
117118 data_mask [data_mask ] = event_types == event_type
@@ -121,6 +122,7 @@ def cli(filenames, cut_level, debug, output, layout, event_type):
121122
122123 else :
123124 logging .info (f"Surviving events: { np .count_nonzero (data_mask )} (cut level { cut_level } )" )
125+ ratio = 0
124126
125127 # columns readable without transformation
126128 EVENTS_COLUMNS = {
@@ -187,7 +189,10 @@ def cli(filenames, cut_level, debug, output, layout, event_type):
187189 # Store the histogram of simulated events vs MC_ENERGY
188190 energy_low = u .Quantity (10 ** bin_edges [:- 1 ], u .TeV , copy = False )
189191 energy_high = u .Quantity (10 ** bin_edges [1 :], u .TeV , copy = False )
190- num_events = bin_content
192+ # If there are events used in the event-types training, that proportion must be
193+ # excluded from the number of events in the simulation, so the IRFs can be
194+ # then computed properly
195+ num_events = bin_content * (1 - ratio )
191196
192197 simulated_events = Table ()
193198 simulated_events ["MC_ENERG_LO" ] = energy_low
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