def test_build_mega_stops(self):
stops = [Stop(1, 0, 90), Stop(2, 10, 45)]
groups = {0: [0, 1]}
_ = MegaStopFac(0)
mega_stops = _.build_mega_stops(groups, stops)
self.assertEqual(mega_stops[0].id, "M0")
self.assertEqual(mega_stops[0].lat, 0)
self.assertEqual(mega_stops[0].lon, 90)
def get_rail_stops(self, train_dict):
"""
:return:
"""
train_routes = list(train_dict.keys())
mega_fac = MegaStopFac(700)
curr = train_dict[train_routes[0]]
for r in train_routes[1:]:
curr = mega_fac.get_train_mega_stops(curr, train_dict[r])
else:
for i in range(4):
inbound, outbound = self.duplicate(curr)
curr = mega_fac.get_train_mega_stops(inbound, outbound)
return mega_fac.get_train_mega_stops(inbound, outbound)
def preprocess_gtsf(self, day):
"""
@document
:param day:
:return:
"""
self.MegaStopFactory = MegaStopFac(700)
self.scheduler = schedule.ScheduleMaker(self.gtsf['trips'],
self.gtsf['calendar'],
self.gtsf['stop_times'],
self.gtsf['stops'],
self.gtsf['routes'])
self.scheduler.build_daily_table(day)
routes, train_dict = self.scheduler.get_routes()
route_ms = {}
for route in routes.keys():
_ = self.MegaStopFactory.get_mega_stops(routes[route][0],
routes[route][1])
route_ms[route] = _
rsf = RailStopFac(700, self.MegaStopFactory.count)
route_ms["RAIL"] = rsf.get_rail_stops(train_dict)
self.megas = route_ms
return route_ms
def test_build_ball_tree(self):
odx = ODX(0, 1)
odx.load_gtsf()
day = dt.datetime.strptime("01/30/18 00:00", "%m/%d/%y %H:%M")
odx.preprocess_gtsf(day)
fac = MegaStopFac(700)
def test_process_query_results(self):
mega_fac = MegaStopFac(100)
result = ([[1], [1], [1]], [[1], [2], [3]])
dist, ind = mega_fac.process_query_results(result)
self.assertEqual(dist, [mega_fac.R, mega_fac.R, mega_fac.R])
self.assertEqual(ind, [1, 2, 3])
def test_union_find(self):
partners = [0, 1, 3, 2]
_ = MegaStopFac(0)
self.assertListEqual(_.union_find(partners), [0, 1, 2, 2])
partners = [0, 1, 2, 3]
self.assertListEqual(_.union_find(partners), partners)
def test_stop_2_tup(self):
stops = [Stop(1, 0, 90)]
_ = MegaStopFac(0)
tup = _.stop_2_tup(stops)[0]
self.assertAlmostEqual(tup[0], 0)
self.assertAlmostEqual(tup[1], 1.5707, places=3)
def test_get_groups(self):
partners = [0, 1, 3, 2]
_ = MegaStopFac(0)
groups = _.union_find(partners)
self.assertDictEqual(_.get_groups(groups), {0: [0], 1: [1], 2: [2, 3]})
def test_correct_outbound_matches(self):
fac = MegaStopFac(10)
in_dist = [20, 20, 4, 4]
matches = [1, 0, 3, 2]
out = fac.correct_outboud_matches(in_dist, matches, 4)
self.assertEqual([4, 5, 3, 2], out)
def test_correct_inbound_matches(self):
fac = MegaStopFac(10)
in_dist = [20, 20, 4, 4]
matches = [1, 0, 3, 2]
out = fac.correct_inbound_matches(in_dist, matches)
self.assertEqual([0, 1, 7, 6], out)
class ODX:
"""
This is the odx class which has the main
"""
def __init__(self, start, end, **kwargs):
"""
:param start: string, with time of the period that starts
:param end: string, with time of the period that starts
:param kwargs:
"""
self.start = dt.datetime.strptime("01/30/18 00:00", "%m/%d/%y %H:%M")
self.end = dt.datetime.strptime("01/31/18 00:00", "%m/%d/%y %H:%M")
fileDir = os.path.realpath('__file__').split('/code')[0]
self.data_path = os.path.join(fileDir, 'Data')
self.megas = None
def load_gtsf(self):
"""
build a documents search tree for this so we can get the correct days data
function loads all of the gtsf tables Exclusively
:param gtsf_path: path to the gtsf
:return:
"""
gtsf_path = os.path.join(self.data_path, 'gtsf')
trips = pd.read_csv(os.path.join(gtsf_path, 'trips.txt'))
stops = pd.read_csv(os.path.join(gtsf_path, 'stops.txt'))
stop_times = pd.read_csv(os.path.join(gtsf_path, "stop_times.txt"))
routes = pd.read_csv(os.path.join(gtsf_path, 'routes.txt'))
cal = pd.read_csv(os.path.join(gtsf_path, 'calendar.txt'))
self.gtsf = {
"trips": trips,
'stops': stops,
"stop_times": stop_times,
"routes": routes,
'calendar': cal
}
def load_apc(self, apc_path):
"""
Need to build a script to break these apart and store in seperate data buckets.
Need to implement the search tree to find the given file containing the precompiled daily data
@document apc function
@test functionality
:param apc_path:
:return:
"""
self.apc = pd.read_pickle(os.path.join(self.data_path, 'apc.pick'))
def load_breeze(self, breeze_path):
"""
Need to build a script to break these apart and store in seperate data buckets.
Need to implement the search tree to find the given file containing the precompiled daily data
@document breeze function
@test functionality
:param breeze_path:
:return:
"""
self.breeze = pd.read_pickle(
os.path.join(self.data_path, 'breeze.pick'))
def preprocess_gtsf(self, day):
"""
@document
:param day:
:return:
"""
self.MegaStopFactory = MegaStopFac(700)
self.scheduler = schedule.ScheduleMaker(self.gtsf['trips'],
self.gtsf['calendar'],
self.gtsf['stop_times'],
self.gtsf['stops'],
self.gtsf['routes'])
self.scheduler.build_daily_table(day)
routes, train_dict = self.scheduler.get_routes()
route_ms = {}
for route in routes.keys():
_ = self.MegaStopFactory.get_mega_stops(routes[route][0],
routes[route][1])
route_ms[route] = _
rsf = RailStopFac(700, self.MegaStopFactory.count)
route_ms["RAIL"] = rsf.get_rail_stops(train_dict)
self.megas = route_ms
return route_ms
def export_megas(self, path_out):
"""
This file exports the megastops to a specific file for analysis
:param path_out:
:return:
"""
with open(path_out, 'w') as fout:
import csv
writer = csv.writer(fout)
writer.writerow(["ROUTE", 'MEGA_STOP_ID', "LAT", "LON"])
for route, mega in self.megas.items():
for stop in mega:
writer.writerow([route] + list(stop.to_csv()))
def build_network(self, trans_limit, id=1):
"""
:return:
"""
if self.megas is not None:
self.network = Network(self.megas, id, 700)
def preprocess_apc(self, day):
"""
@create function to preprocess apc data
@document
@test
:param day:
:return:
"""
pass
def preprocess_breeze(self, day):
"""
@create function to preprocess apc data
@document
@test
:param day:
:return:
"""
pass
def trip_chain(self):
"""
@create function to preprocess apc data
@document
@test
:return:
"""
pass
def __call__(self):
"""
This funciton
:return:
"""
pass
