langspielplatte/measurement-scripts
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Bugfixes

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langspielplatte
2023-02-28 08:47:40 +01:00
parent 8004c74acf
commit 38b7bf68ec
1 changed files with 16 additions and 16 deletions
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32
cdf_compare.py
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@@ -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 n
global frame_list global frame_list
@@ -23,7 +23,7 @@ def csv_to_dataframe(csv_list, dummy):
for csv in csv_list: for csv in csv_list:
tmp_df = pd.read_csv( tmp_df = pd.read_csv(
"{}{}".format(args.pcap_csv_folder, csv), "{}{}".format(folder, csv),
dtype=dict(is_retranmission=bool, is_dup_ack=bool), dtype=dict(is_retranmission=bool, is_dup_ack=bool),
) )
tmp_df["datetime"] = pd.to_datetime(tmp_df["datetime"]) - pd.Timedelta(hours=1) 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 # load all pcap csv into one dataframe
pcap_csv_list = list() 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: if filename.endswith(".csv") and "tcp" in filename:
pcap_csv_list.append(filename) pcap_csv_list.append(filename)
parts = chunk(pcap_csv_list, ceil(len(pcap_csv_list) / args.cores)) parts = chunk(pcap_csv_list, ceil(len(pcap_csv_list) / args.cores))
print("Start processing with {} jobs.".format(args.cores)) print("Start processing with {} jobs.".format(args.cores))
for p in parts: 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) jobs.append(process)
for j in jobs: for j in jobs:
@@ -165,19 +165,19 @@ if __name__ == "__main__":
transmission_direction = transmission_df["direction"].iloc[0] transmission_direction = transmission_df["direction"].iloc[0]
# read serial csv # read serial csv
serial_df = pd.read_csv(args.serial_file) #serial_df = pd.read_csv(args.serial_file)
serial_df["datetime"] = pd.to_datetime(serial_df["datetime"]) - pd.Timedelta(hours=1) #serial_df["datetime"] = pd.to_datetime(serial_df["datetime"]) - pd.Timedelta(hours=1)
serial_df = serial_df.set_index("datetime") #serial_df = serial_df.set_index("datetime")
serial_df.index = pd.to_datetime(serial_df.index) #serial_df.index = pd.to_datetime(serial_df.index)
serial_df.sort_index() #serial_df.sort_index()
transmission_df = pd.merge_asof( #transmission_df = pd.merge_asof(
transmission_df, # transmission_df,
serial_df, # serial_df,
tolerance=pd.Timedelta("1s"), # tolerance=pd.Timedelta("1s"),
right_index=True, # right_index=True,
left_index=True, # left_index=True,
) #)
transmission_df_list.append(dict( transmission_df_list.append(dict(
df=transmission_df, df=transmission_df,