| @@ -2,6 +2,7 @@ | |||
| import multiprocessing | |||
| import os | |||
| from argparse import ArgumentParser | |||
| from datetime import datetime | |||
| from math import ceil | |||
| from time import sleep | |||
| @@ -53,6 +54,7 @@ if __name__ == "__main__": | |||
| parser.add_argument("--save", default=None, help="Location to save pdf file.") | |||
| parser.add_argument("--time_offset", default=0, type=int, help="Minutes added to GPS datetime.") | |||
| parser.add_argument("--neg_offset", default=False, action="store_true", help="Subtract GPS time offset.") | |||
| parser.add_argument("--auto_offset", default=False, action="store_true", help="Calculate GPS time offset.") | |||
| parser.add_argument( | |||
| "-c", | |||
| "--cores", | |||
| @@ -132,13 +134,24 @@ if __name__ == "__main__": | |||
| # load dataframe an put it into geopandas | |||
| df = pd.read_csv(args.gps_file) | |||
| df["kmh"] = df["speed (knots)"].apply(lambda x: x * 1.852) | |||
| if args.time_offset > 0: | |||
| if not args.auto_offset and args.time_offset > 0: | |||
| if args.neg_offset: | |||
| df["datetime"] = pd.to_datetime(df["datetime"]) - pd.Timedelta(minutes=args.time_offset) | |||
| else: | |||
| df["datetime"] = pd.to_datetime(df["datetime"]) + pd.Timedelta(minutes=args.time_offset) | |||
| elif args.auto_offset: | |||
| gps_first = datetime.strptime(df["datetime"].iloc[0], "%Y-%m-%d %H:%M:%S.%f") | |||
| pcap_first = datetime.strptime(transmission_df["datetime"].iloc[0], "%Y-%m-%d %H:%M:%S.%f") | |||
| calc_offset = gps_first - pcap_first | |||
| if gps_first > pcap_first: | |||
| time_offset = gps_first - pcap_first | |||
| df["datetime"] = pd.to_datetime(df["datetime"]) - time_offset | |||
| else: | |||
| time_offset = pcap_first - gps_first | |||
| df["datetime"] = pd.to_datetime(df["datetime"]) + time_offset | |||
| else: | |||
| df["datetime"] = pd.to_datetime(df["datetime"]) | |||
| df = df.set_index("datetime") | |||
| df.index = pd.to_datetime(df.index) | |||