Bugfixes

cdf_compare.py

@@ -14,7 +14,7 @@ from mpl_toolkits.axes_grid1 import host_subplot
 
 
 
-def csv_to_dataframe(csv_list, dummy):
+def csv_to_dataframe(csv_list, folder, dummy):
 
     global n
     global frame_list
@@ -23,7 +23,7 @@ def csv_to_dataframe(csv_list, dummy):
 
     for csv in csv_list:
         tmp_df = pd.read_csv(
-            "{}{}".format(args.pcap_csv_folder, csv),
+            "{}{}".format(folder, csv),
             dtype=dict(is_retranmission=bool, is_dup_ack=bool),
         )
         tmp_df["datetime"] = pd.to_datetime(tmp_df["datetime"]) - pd.Timedelta(hours=1)
@@ -97,14 +97,14 @@ if __name__ == "__main__":
 
         # load all pcap csv into one dataframe
         pcap_csv_list = list()
-        for filename in os.listdir(args.pcap_csv_folder):
+        for filename in os.listdir(f):
             if filename.endswith(".csv") and "tcp" in filename:
                 pcap_csv_list.append(filename)
 
         parts = chunk(pcap_csv_list, ceil(len(pcap_csv_list) / args.cores))
         print("Start processing with {} jobs.".format(args.cores))
         for p in parts:
-            process = multiprocessing.Process(target=csv_to_dataframe, args=(p, "dummy"))
+            process = multiprocessing.Process(target=csv_to_dataframe, args=(p, f, "dummy"))
             jobs.append(process)
 
         for j in jobs:
@@ -165,19 +165,19 @@ if __name__ == "__main__":
         transmission_direction = transmission_df["direction"].iloc[0]
 
         # read serial csv
-        serial_df = pd.read_csv(args.serial_file)
-        serial_df["datetime"] = pd.to_datetime(serial_df["datetime"]) - pd.Timedelta(hours=1)
-        serial_df = serial_df.set_index("datetime")
-        serial_df.index = pd.to_datetime(serial_df.index)
-        serial_df.sort_index()
-
-        transmission_df = pd.merge_asof(
-            transmission_df,
-            serial_df,
-            tolerance=pd.Timedelta("1s"),
-            right_index=True,
-            left_index=True,
-        )
+        #serial_df = pd.read_csv(args.serial_file)
+        #serial_df["datetime"] = pd.to_datetime(serial_df["datetime"]) - pd.Timedelta(hours=1)
+        #serial_df = serial_df.set_index("datetime")
+        #serial_df.index = pd.to_datetime(serial_df.index)
+        #serial_df.sort_index()
+
+        #transmission_df = pd.merge_asof(
+        #    transmission_df,
+        #    serial_df,
+        #    tolerance=pd.Timedelta("1s"),
+        #    right_index=True,
+        #    left_index=True,
+        #)
 
         transmission_df_list.append(dict(
             df=transmission_df,