fixed df indexing

bind/G4Calo.py

@@ -322,6 +322,8 @@ def _run_mini_batch(
     from  G4Calo import __G4System
     G4System = __G4System()
     seed = int(batch_seed + counter)
+    #truncate to 32 bit, lower 32 bit are used in G4
+    seed = seed & 0xFFFFFFFF
     G4System.init(cw, seed) #counter gives random seed offset
 
     df = G4System.run_batch(nEvents, particleSpec, minEnergy_GeV, maxEnergy_GeV,"")
@@ -357,8 +359,6 @@ def run_batch(
     nevents = [nEventsPerCore if i < nCores - 1 else nEventsLastCore for i in range(nCores)]
 
     batch_seed = int(time.time()*1000)
-    #truncate to 32 bit, lower 32 bit are used in G4
-    batch_seed = batch_seed & 0xFFFFFFFF
 
     print(f"Batch seed: {batch_seed}")
     #use a multiprocessing pool to run the mini batches in parallel
@@ -366,6 +366,7 @@ def run_batch(
         dfs = pool.starmap(_run_mini_batch_silent, [(gd, nevents[i], particleSpec, minEnergy_GeV, maxEnergy_GeV, batch_seed, i) for i in range(nCores)])
 
     alldf = pd.concat(dfs)
+    alldf.reset_index(drop=True, inplace=True)
     #convert alldf['total_dep_energy'] to numpy array and check if all non-zero entries are unique
     non_zero = alldf['total_dep_energy'][alldf['total_dep_energy'] != 0.]
     n_unique = np.unique(non_zero.to_numpy()).shape[0]