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#!/usr/bin/env python
# Make a valid dataset by cutting the training set at specified timestamps
import os
import sys
import importlib
import h5py
import numpy
import data
from data.hdf5 import taxi_it
import sqlite3
def make_valid(outpath):
times = []
for i, line in enumerate(taxi_it('train')):
time = line['timestamp']
latitude = line['latitude']
if len(latitude) == 0:
continue
duration = 15 * (len(latitude) - 1)
times.append((i, int(time), int(time + duration)))
if i % 1000 == 0:
print times[-1]
with sqlite3.connect(outpath) as timedb:
c = timedb.cursor()
c.execute('''
CREATE TABLE trip_times
(trip INTEGER, begin INTEGER, end INTEGER)
''')
print "Adding data..."
c.executemany('INSERT INTO trip_times(trip, begin, end) VALUES(?, ?, ?)', times)
timedb.commit()
print "Creating index..."
c.execute('''CREATE INDEX trip_time_index ON trip_times (begin, end)''')
if __name__ == '__main__':
if len(sys.argv) < 1 or len(sys.argv) > 2:
print >> sys.stderr, 'Usage: %s [outfile]' % sys.argv[0]
sys.exit(1)
outpath = os.path.join(data.path, 'time_index.db') if len(sys.argv) < 2 else sys.argv[1]
make_valid(outpath)
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