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import pandas as pd
import numpy as np
import time
# List of all filenames
od_fns = ["./DataForUConn/201407OD/201407.gz/part-m-{x}".format(x=str(x).rjust(5,"0")) for x in range(12)]
gps_fns = ["./DataForUConn/201407GPS/part-r-{x}".format(x=str(x).rjust(5,"0")) for x in range(2)]
od_headers = ["id", "ptime", "dtime", "plon", "plat", "dlon", "dlat"]
gps_headers = ["id", "color", "lon", "lat", "time", "speed", "noMeaning"]
# Time formatter function; string --> unix timestamp.
# (Timezone data is lost, but shouldn't matter, assuming each string comes from the same timezone.)
formattime = lambda timestr: int(time.mktime(time.strptime(timestr, "%Y-%m-%dT%H:%M:%S.000Z")))
for od_id, od_fn in enumerate(od_fns):
print(f"Opening OD {od_id}...")
with open(od_fn) as f:
odlines = [line.split(",") for line in f.read().strip().split("\n")]
print(f"Processing OD {od_id}...")
oddf = pd.DataFrame(odlines, columns=od_headers)
oddf["ptime"] = oddf["ptime"].apply(formattime)
oddf["dtime"] = oddf["dtime"].apply(formattime)
oddf["plon"] = oddf["plon"].astype(np.float32)
oddf["plat"] = oddf["plat"].astype(np.float32)
oddf["dlon"] = oddf["dlon"].astype(np.float32)
oddf["dlat"] = oddf["dlat"].astype(np.float32)
print(f"Saving OD {od_id} pickle...")
oddf.to_pickle("./data/od_part-m-{x}.pkl".format(x=str(od_id).rjust(3,"0")),
compression=None)
for gps_id, gps_fn in enumerate(gps_fns):
print(f"Opening GPS {gps_id}...")
with open(gps_fn) as f:
gpslines = [line.split(",") for line in f.read().strip().split("\n")]
print(f"Processing GPS {gps_id}...")
gpsdf = pd.DataFrame(gpslines, columns=gps_headers)
gpsdf["time"] = gpsdf["time"].apply(formattime)
gpsdf["lon"] = gpsdf["lon"].astype(np.float32)
gpsdf["lat"] = gpsdf["lat"].astype(np.float32)
gpsdf["speed"] = gpsdf["speed"].astype(int)
print(f"Saving GPS {gps_id} pickle...")
gpsdf.to_pickle("./data/gps_part-r-{x}.pkl".format(x=str(gps_id).rjust(3,"0")),
compression=None)