From 38b7bf68ec7e80cf7c8cc4a2c4b340ba43c3389f Mon Sep 17 00:00:00 2001 From: Langspielplatte Date: Tue, 28 Feb 2023 08:47:40 +0100 Subject: [PATCH] Bugfixes --- cdf_compare.py | 32 ++++++++++++++++---------------- 1 file changed, 16 insertions(+), 16 deletions(-) diff --git a/cdf_compare.py b/cdf_compare.py index 158a56f..e8c17e4 100755 --- a/cdf_compare.py +++ b/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() + #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 = 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,