Changes goodput calculation.

plot_transmission_timeline.py

 
     print(transmission_df)
 
-    # create timedelta range with maximum timedelta
-    #time_range = pd.date_range(transmission_df.index.min(), transmission_df.index.max(), freq="{}s".format(args.interval))
-
-    # create bins by pd.cut, aggregate sum
-    #transmission_df["goodput"] = transmission_df.groupby(pd.cut(transmission_df.index, bins=time_range, labels=time_range[:-1]))["payload_size"].sum().reset_index()["payload_size"]
-
-
-
-
-    transmission_df["goodput"] = transmission_df["payload_size"].rolling("{}s".format(args.interval)).sum()
+    # key for columns and level for index
+    transmission_df["goodput"] = transmission_df.groupby(pd.Grouper(level="datetime", freq="{}s".format(args.interval))).sum()
+    #transmission_df["goodput"] = transmission_df["payload_size"].rolling("{}s".format(args.interval)).sum()
     transmission_df["goodput"] = transmission_df["goodput"].apply(
         lambda x: ((x * 8) / args.interval) / 10**6
     )
     if args.save:
         plt.savefig("{}{}_cdf_plot.pdf".format(args.save, "goodput"))
     else:
-        plt.show()
+        plt.show()
+
+    print(transmission_df)