diff --git a/tools/plotting/fastnnlo_runtime.py b/tools/plotting/fastnnlo_runtime.py
index 642336937d52631be753d46cbd42b974243c703c..ff535542d5d2da795ee02146d8cd075aea0673b2 100755
--- a/tools/plotting/fastnnlo_runtime.py
+++ b/tools/plotting/fastnnlo_runtime.py
@@ -173,26 +173,22 @@ def get_files(files):
 
 def get_loginformation(files):
 
+    # always in hours for simplicity
     runtimes = []
+    unit = 'hours'
 
     for file in files:
         runtimes_temp = []
 
         with open(file) as origin:
             for line in origin:
-                # extract elapsed time with time unit
+                # extract elapsed time in hours
                 if 'Time elapsed' in line:
                     line = line.split(':')
                     hours = float(line[1])
                     minutes = float(line[2])
                     seconds = float(line[3])
-
-                    if hours != 0.:
-                        runtimes_temp.append(hours + minutes/60 + seconds/360)
-                        unit = 'hours'
-                    else:
-                        runtimes_temp.append(minutes + seconds/60)
-                        unit = 'minutes'
+                    runtimes_temp.append(hours + minutes/60 + seconds/3600)
 
         runtimes.append(runtimes_temp[-1])
 
@@ -235,7 +231,7 @@ def get_runinformation(files):
 def plot_elapsed_time(infodict, out_path, out_name, formats):
 
     times = infodict['runtime']
-    unit = infodict['runtime_unit']
+    unit  = infodict['runtime_unit']
     channels = infodict['channels']
     events   = infodict['events']
 
@@ -252,7 +248,7 @@ def plot_elapsed_time(infodict, out_path, out_name, formats):
     median = np.median(times)
     iqd = np.subtract(*np.percentile(times, [75, 25], interpolation='linear'))/2.
 
-    CPUtime = np.sum(times) / (1 if unit == 'hours' else 60)
+    CPUtime = np.sum(times)
 
     # set figure
     fig = plt.figure(figsize=(16, 12))
@@ -314,10 +310,7 @@ def plot_events_per_hour(infodict, out_path, out_name, formats):
         exit(11)
     eph = []
     for i, time in enumerate(times):
-        if unit == 'hours':
-            eph.append(float(events[i])/time)
-        else:
-            eph.append(float(events[i])/(time/60))
+        eph.append(float(events[i])/time)
     ephchn = []
     for i, val in enumerate(eph):
         for j, chn in enumerate(_channels):
@@ -336,7 +329,7 @@ def plot_events_per_hour(infodict, out_path, out_name, formats):
     ephmin  = np.min(eph)
     ephmax  = np.max(eph)
     logbins = np.geomspace(ephmin, ephmax, 100)
-    CPUtime = np.sum(times) / (1 if unit == 'hours' else 60)
+    CPUtime = np.sum(times)
 
     # create figure
     fig = plt.figure(figsize=(16, 12))
@@ -344,11 +337,9 @@ def plot_events_per_hour(infodict, out_path, out_name, formats):
 
     # plot (multistack-)histogram
     evrs = []
-    lastch = 'LO'
     for chn in _channels:
         if chn in unique_channels:
             evrs.append(ephchn[masks[_channel_number[chn]]][:,0])
-            lastch = chn
     if len(unique_channels) == 1:
 
         # plot each unique number in different color
@@ -362,9 +353,10 @@ def plot_events_per_hour(infodict, out_path, out_name, formats):
     else:
         chnlab = []
         chncol = []
-        for chn in unique_channels:
-            chnlab.append(chn)
-            chncol.append(_channel_colors[_channel_number[chn]])
+        for chn in _channels:
+            if chn in unique_channels:
+                chnlab.append(chn)
+                chncol.append(_channel_colors[_channel_number[chn]])
         n, batches, _ = ax.hist(evrs, histtype='barstacked', log=True, stacked=True, bins=logbins, edgecolor='black', color=chncol, label=chnlab)
         ax.set_xlim(0.9*ephmin, 1.1*ephmax)
         ax.set_xscale('log')