calculate fitness independet of tokens (#298)

transitions without incoming arcs can always fire, therefore the fitness can be 1 without any produced or consumed tokens.
this is now reflected in the code

pm4py/evaluation/replay_fitness/variants/token_replay.py

@@ -50,10 +50,11 @@ def evaluate(aligned_traces, parameters=None):
     total_c = sum([x["consumed_tokens"] for x in aligned_traces])
     total_r = sum([x["remaining_tokens"] for x in aligned_traces])
     total_p = sum([x["produced_tokens"] for x in aligned_traces])
-    if no_traces > 0 and total_c > 0 and total_p > 0:
+    if no_traces > 0:
         perc_fit_traces = float(100.0 * fit_traces) / float(no_traces)
         average_fitness = float(sum_of_fitness) / float(no_traces)
-        log_fitness = 0.5 * (1 - total_m / total_c) + 0.5 * (1 - total_r / total_p)
+        if total_c > 0 and total_p > 0:
+            log_fitness = 0.5 * (1 - total_m / total_c) + 0.5 * (1 - total_r / total_p)
     return {"perc_fit_traces": perc_fit_traces, "average_trace_fitness": average_fitness, "log_fitness": log_fitness,
             "percentage_of_fitting_traces": perc_fit_traces }