def getRandomDriverTrips(self, numtrips, numNotDrivers, feat):
#get list of drivers and shuffle
notDrivers = os.listdir("../drivers/")
copy = notDrivers[1:]
random.shuffle(copy)
notDrivers[1:] = copy
#process number of 'other' drivers
if numNotDrivers == 0 or numNotDrivers >= len(notDrivers):
numNotDrivers = len(notDrivers) - 1
#if we are comparing to only one driver and that driver is the same as
#the original driver
if numNotDrivers == 1:
while notDrivers[1] == self.name:
copy = notDrivers[1:]
random.shuffle(copy)
notDrivers[1:] = copy
#sample trips and output desired features
tripList = []
for i in range(numtrips):
dnum = notDrivers[random.randint(
1, numNotDrivers)] #sample a random driver
#print self.name + " " + dnum
while dnum == self.name: #don't sample from self
dnum = notDrivers[random.randint(1, numNotDrivers)]
tnum = random.randint(1, 200) #sample a random trip
t = Trip("../drivers/" + str(dnum) + "/" + str(tnum) + ".csv",
feat)
tripList.append(t.printFeatures())
return tripList
def export_gtfs(cls, directory):
Agency.write_agencies(directory)
Calendar.write_calendars(directory)
Stop.write_stops(directory)
Route.write_routes(directory)
Trip.write_trips(directory)
Frequency.write_frequencies(directory)
Path.write_paths(directory)
def import_gtfs(cls, directory):
Agency.import_agencies(directory)
Calendar.import_calendars(directory)
Stop.import_stops(directory)
Path.import_paths(directory)
Route.import_routes(directory)
Trip.import_trips(directory)
Frequency.import_frequencies(directory)
def writeCSV(self, numTrips=training_self):
g = open ("driver_stats/"+str(self.name)+"_trips.csv", "w")
#a header and then the features for each trip
g.write("advSpeed,tripDist\n")
for i in range (1, numTrips+1):
t = Trip("../drivers/"+str(self.name)+"/"+str(i)+".csv")
g.write(t.printFeatures())
g.close()
def initRoutingDay(self):
routingDay = RoutingDay(self.instance)
for request in self.scheduleDay.deliveries:
trip = Trip(self.instance, request)
routingDay.addTrip(trip)
for request in self.scheduleDay.pickups:
trip = Trip(self.instance, request)
routingDay.addTrip(trip)
return routingDay
def add_trip(self):
trip = Trip('', self, self.calendar)
# add the stops
for stop in self._stops:
trip.add_trip_stop(TripStop(stop))
self.trips.append(trip)
return trip
def writeCSV_test(self):
g = open("driver_stats/" + str(self.name) + "_test.csv", "w")
#first trips from this driver
for i in range(num_selfTrips + 1, num_selfTrips + num_testTrips + 1):
t = Trip("../drivers/" + str(self.name) + "/" + str(i) + ".csv")
g.write(t.printFeatures())
#trips from other drivers
tripList = self.getRandomDriverTrips(num_testTrips)
for other in tripList:
g.write(other)
g.close()
def writeCSV_notDriver(self, numTrips = training_others):
#list other drivers in directory, since their numbers skip around
notDrivers = os.listdir("../drivers/")
g = open ("driver_stats/"+str(self.name)+"_NOTtrips.csv", "w")
for i in range(numTrips):
dnum = notDrivers[random.randint(1, len(notDrivers))] #sample a random driver
while dnum == self.name: #don't sample from self
dnum = notDrivers[random.randint(1, len(notDrivers))]
tnum = random.randint(1,201)#sample a random trip
t = Trip("../drivers/"+str(dnum)+"/"+str(tnum)+".csv")
g.write(t.printFeatures())
g.close()
def writeCSV_training(self):
g = open("driver_stats/" + str(self.name) + "_training.csv", "w")
#a header and then the features for each trip
#g.write("advSpeed,tripDist\n")
#first trips from this driver
for i in range(1, num_selfTrips + 1):
t = Trip("../drivers/" + str(self.name) + "/" + str(i) + ".csv")
g.write(t.printFeatures())
#trips from other drivers
tripList = self.getRandomDriverTrips(num_NOTselfTrips)
for other in tripList:
g.write(other)
g.close()
def close(self):
self._is_open = False
self._dbname = None
# clear everything
Agency.clear()
Calendar.clear()
Stop.clear()
Path.clear()
Route.clear()
TripRoute.clear()
Trip.clear()
Frequency.clear()
Picture.clear()
def getRandomDriverTrips(self, numtrips):
notDrivers = os.listdir("../drivers/")
numNotDrivers = len(
notDrivers) #change this parameter to consider a different number
tripList = []
for i in range(numtrips):
dnum = notDrivers[random.randint(1,
len(notDrivers) -
1)] #sample a random driver
while dnum == self.name: #don't sample from self
dnum = notDrivers[random.randint(1, numNotDrivers - 1)]
tnum = random.randint(1, 200) #sample a random trip
t = Trip("../drivers/" + str(dnum) + "/" + str(tnum) + ".csv")
tripList.append(t.printFeatures())
return tripList
def request(self, rider_id, lat, lng):
minDistance, minDriverId = float('inf'), None
for dId, loc in self.driver2Location.items():
curDistance = Helper.get_distance(lat, lng, loc[0], loc[1])
if minDistance > curDistance:
minDistance, minDriverId = curDistance, dId
trip = Trip(rider_id, lat, lng)
trip.driver_id = minDriverId
if minDriverId:
self.driver2Trip[minDriverId] = trip
del self.driver2Location[minDriverId]
return trip
def __get_trip(self, trip):
"""
Gets the trip information out of the json returned from ITA
This should only be called if the caller understands the json returned by ITA
"""
price = float(trip['ext']['price'][3:])
ppm = float(trip['ext']['pricePerMile'][3:])
ppm = round(ppm, 4)
itin = trip['itinerary']
distance = int(itin['distance']['value'])
flights = []
#get the flights out of the itinerary
for flight in itin['slices']:
stops = []
layovers = flight.get('stops')
if not layovers is None:
for layover in layovers:
stops.append(layover['code'])
fl = Flight(flight['origin']['code'],
flight['destination']['code'], flight['departure'],
flight['arrival'], flight['duration'], stops)
flights.append(fl)
return Trip(flights[0], flights[1], ppm, price, distance)
def import_frequencies(cls, directory):
from Trip import Trip
try:
f = open(os.path.join(directory, 'frequencies.txt'), 'rb')
reader = csv.reader(f)
mappings = {'trip_id': ('trip_route', lambda x: Trip.get_by_gtfs_id(x).trip_route),
'start_time': ('start', lambda x: x),
'end_time': ('end', lambda x: x),
'headway_secs': ('headway', lambda x: x),
}
# create a headers with an index
headers = reader.next()
r_headers = dict([(x, i) for i, x in enumerate(headers)])
for l2 in reader:
if len(l2) != len(headers):
print >> sys.stderr, 'Invalid line', l2, headers
continue
kw = {}
for i, a in enumerate(l2):
key = headers[i]
if key in mappings:
kw[mappings[key][0]] = mappings[key][1](BaseObject.unquote(a))
# create the frequency
frequency = Frequency(**kw)
trip_route = frequency.trip_route.frequencies.append(frequency)
except IOError, e:
print >> sys.stderr, 'Unable to open frequencies.txt:', e
def request(self, rider_id, lat, lng):
# Write your code here
dist = -1
driver = -1
for key, value in self.locs.items():
td = Helper.get_distance(value[0], value[1], lat, lng)
if dist == -1 or td < dist:
dist = td
driver = key
trip = Trip(rider_id, lat, lng)
trip.driver_id = driver
if dist != -1:
del self.locs[driver]
self.trips[driver] = trip
return trip
def trip_for_stopnames(self, stopnames=[]):
"""
:param: stopnames: array that hold name of the stops
:return: Object of Trip
"""
matching_stations = [self.stations_by_name[name] for name in stopnames]
return Trip(matching_stations)
def test_order_hotel():
flights_data = flight_general.get_all_updated_data()
data_in_range = [
flight for flight in flights_data
if (4 <= flight.days <= 6) and flight.destination_value == 10 and (
flight.label == 4 or flight.label == 3) and datetime.strptime(
flight.return_date, '%Y-%m-%d') < datetime(2021, 5, 1)
]
data_in_range.sort()
trip_list = []
time_start = time.time()
i = 0
j = 0
my_set = set()
while i < 2:
flight = data_in_range[j]
if flight.destination.city not in my_set:
trip_list.append(Trip(flight))
my_set.update([flight.destination.city])
i += 1
j = j + 1
for trip in trip_list:
trip.get_hotel_for_trip()
trip_list.sort(reverse=True)
for trip in trip_list:
print(trip)
time_end = time.time()
print((time_end - time_start) / 60)
def writeCSV(self, order, numNotDrivers, feat):
g = open("driver_stats/" + str(self.name) + "_training.csv", "w")
#first trips from this driver
for i in range(0, num_selfTrips + num_testTrips):
#print i
t = Trip(
"../drivers/" + str(self.name) + "/" + str(order[i]) + ".csv",
feat)
g.write(t.printFeatures())
#trips from other drivers
tripList = self.getRandomDriverTrips(num_NOTselfTrips + num_testTrips,
numNotDrivers, feat)
for other in tripList:
g.write(other)
g.close()
def test_order_hotel():
flights_data = flight_general.get_all_updated_data()
data_in_range = [
flight for flight in flights_data
if (flight.days == 5 or flight.days == 6) and flight.destination_value
< 25 and (flight.label == 4 or flight.label == 3)
]
data_in_range.sort()
trip_list = []
for i in range(0, 3):
flight = data_in_range[i]
trip = Trip(flight)
trip.get_hotel_for_trip()
trip_list.append(trip)
trip_list.sort(reverse=True)
return trip_list
def request(self, rider_id, lat, lng):
trip = Trip(rider_id, lat, lng)
distance, driver_id = -1, -1
for key, value in self.driver2Location.items():
dis = Helper.get_distance(value.lat, value.lng, lat, lng)
if distance < 0 or distance > dis:
driver_id = key
distance = dis
if driver_id != -1:
del self.driver2Location[driver_id]
trip.driver_id = driver_id
self.driver2Trip[driver_id] = trip
return trip
def request(self, rider_id, lat, lng):
# Write your code here
minD = sys.maxsize
closestD = None
for driver in self.driverLocation.keys():
if driver in self.trip:
continue
lat1, lng1 = self.driverLocation[driver]
dis = Helper.get_distance(lat1, lng1, lat, lng)
if dis < minD:
minD = dis
closestD = driver
trip = Trip(rider_id, lat, lng)
trip.driver_id = closestD
self.trip[closestD] = trip
return trip
def request(self, rider_id, lat, lng):
trip = Trip(rider_id, lat, lng)
min_dist = float('inf')
closest_driver_id = -1
for driver_id, driver in self.drivers.items():
dist = Helper.get_distance(lat, lng, driver.lat, driver.lng)
if dist < min_dist:
min_dist = dist
closest_driver_id = driver_id
print(dist, closest_driver_id)
trip.driver_id = closest_driver_id
self.trip_serial_id += 1
self.trips[self.trip_serial_id] = trip
self.drivers[closest_driver_id].trip_id = self.trip_serial_id
return trip
def _generate_all_combinations(self):
logging.info("Generating trip candidates with {0} cities each".format(
self.cities_per_trip_candidate))
if self.total_cities < self.cities_per_trip_candidate:
only_trip = self.requested_cities.keys()
trip_votes = self._get_trip_total_votes(only_trip)
trip_votees = self._get_trip_total_votees(only_trip)
self.all_combinations = [Trip(only_trip, trip_votes, trip_votees)]
candidate_list = list(
combinations(self.requested_cities.keys(),
self.cities_per_trip_candidate))
self.all_combinations = [
Trip(trip_cities, self._get_trip_total_votes(trip_cities),
self._get_trip_total_votees(trip_cities))
for trip_cities in candidate_list
]
def request(self, rider_id, lat, lng):
# create a trip first
# find the closest available driver from self.driver2Location
# if no driver return none, if yes, fill in trip driver_id,
# remove from driver2Location, add to driver2Trip
trip = Trip(rider_id, lat, lng)
driver_id, distance = -1, -1
for id, loc in self.driver2Location.items():
dis = Helper.get_distance(lat, lng, loc.lat, loc.lng)
if distance == -1 or dis < distance:
distance = dis
driver_id = id
if driver_id == -1:
print("No available drivers")
return None
trip.driver_id = driver_id
self.driver2Trip[driver_id] = trip
del self.driver2Location[driver_id]
return trip
def request(self, rider_id, lat, lng):
# Write your code here
t = Trip(rider_id, lat, lng)
min_diff = sys.maxint
match_driver = []
for driver in self.driver_id_to_location:
driver_tuple = self.driver_id_to_location[driver]
diff = Helper.get_distance(lat, lng, driver_tuple[0], driver_tuple[1])
if diff < min_diff:
min_diff = diff
match_driver = [driver, driver_tuple[0], driver_tuple[1]]
if len(match_driver) != 0:
del self.driver_id_to_location[match_driver[0]]
t.driver_id = match_driver[0]
self.driver_id_to_trip[match_driver[0]] = t
return t
else:
return None
def request(self, rider_id, lat, lng):
the_dvr_id = None
min_distance = float("inf")
for dvr_id, dvr in self.drivers.items():
if dvr[2]:
continue
distance = Helper.get_distance(lat, lng, dvr[0], dvr[1])
if distance < min_distance:
min_distance = distance
the_dvr_id = dvr_id
if not the_dvr_id:
return None
trip = Trip(rider_id, lat, lng)
trip.driver_id = the_dvr_id
self.drivers[the_dvr_id][2] = trip
return trip
def load_trips(filename, limit=float('inf')):
trips = []
with open(filename, "r") as f:
reader = csv.reader(f)
reader.next()
for line in reader:
trips.append(Trip(line))
if (len(trips) >= limit):
break
return trips
def request(self, rider_id, lat, lng):
if not rider_id:
return
trip = Trip(rider_id, lat, lng)
_distance = distance = self.INFINITY
driver_id = -1
for _driver_id, _loc in self.driver_to_locs.items():
_distance = Helper.get_distance(_loc['lat'], _loc['lng'], lat, lng)
if _distance < distance:
driver_id = _driver_id
distance = _distance
if driver_id == -1:
return trip
trip.driver_id = driver_id
self.driver_to_trip[driver_id] = trip
del self.driver_to_locs[driver_id]
return trip
def plot_unique_trips():
from matplotlib import pyplot as plt
trip_lookup = {}
print("Loading map")
road_map = Map("nyc_map4/nodes.csv", "nyc_map4/links.csv")
print("Matching nodes")
sizes = []
with open("sample.csv", "r") as f:
reader = csv.reader(f)
reader.next()
for line in reader:
trip = Trip(line)
trip.num_occurrences = 1
trip.origin_node = road_map.get_nearest_node(
trip.fromLat, trip.fromLon)
trip.dest_node = road_map.get_nearest_node(trip.toLat, trip.toLon)
if ((trip.origin_node, trip.dest_node) in trip_lookup):
#Already seen this trip at least once
trip_lookup[trip.origin_node,
trip.dest_node].num_occurrences += 1
elif trip.origin_node != None and trip.dest_node != None:
#Never seen this trip before
trip_lookup[trip.origin_node, trip.dest_node] = trip
sizes.append(len(trip_lookup))
plt.plot(range(len(sizes)), sizes)
plt.xlabel("Inner Loop Iteration")
plt.ylabel("L1 Error (sec)")
fig = plt.gcf()
fig.set_size_inches(20, 10)
fig.savefig('test2png.png', dpi=100)
#Make unique trips into a list and return
new_trips = [trip_lookup[key] for key in trip_lookup]
return new_trips
def request(self, rider_id, lat, lng):
# @param rider_id an integer
# @param lat, lng rider's location
# return a trip
# find a closest driver
closest_driver, closest_dist = None, sys.maxsize
for driver, location in self.drivers2location.items():
distance = Helper.get_distance(lat, lng, location[0], location[1])
if distance < closest_dist:
closest_driver = driver
closest_dist = distance
# create a trip with rider's information.
trip = Trip(rider_id, lat, lng)
# fill driver_id into this trip.
trip.driver_id = closest_driver
# mark this driver not available.
del self.drivers2location[closest_driver]
self.drivers2trip[closest_driver] = trip
return trip
def plot_unique_trips():
from matplotlib import pyplot as plt
trip_lookup = {}
print("Loading map")
road_map = Map("nyc_map4/nodes.csv", "nyc_map4/links.csv")
print("Matching nodes")
sizes = []
with open("sample.csv", "r") as f:
reader = csv.reader(f)
reader.next()
for line in reader:
trip = Trip(line)
trip.num_occurrences = 1
trip.origin_node = road_map.get_nearest_node(trip.fromLat, trip.fromLon)
trip.dest_node = road_map.get_nearest_node(trip.toLat, trip.toLon)
if((trip.origin_node, trip.dest_node) in trip_lookup):
#Already seen this trip at least once
trip_lookup[trip.origin_node, trip.dest_node].num_occurrences += 1
elif trip.origin_node !=None and trip.dest_node != None:
#Never seen this trip before
trip_lookup[trip.origin_node, trip.dest_node] = trip
sizes.append(len(trip_lookup))
plt.plot(range(len(sizes)), sizes)
plt.xlabel("Inner Loop Iteration")
plt.ylabel("L1 Error (sec)")
fig = plt.gcf()
fig.set_size_inches(20,10)
fig.savefig('test2png.png',dpi=100)
#Make unique trips into a list and return
new_trips = [trip_lookup[key] for key in trip_lookup]
return new_trips
def GetFeatures(driverID,j):
driverDir = '/home/user1/Desktop/Share2Windows/Kaggle/DriversCleaned/'+str(driverID)
tripFiles = range(1,201)
cacc = pd.DataFrame(np.zeros((1,51)))
for index,tripID in enumerate(tripFiles):
trip = Trip(driverID,tripID,pd.read_csv(driverDir+'_' + str(tripID) + '.csv'))
trip.getSpeed()
trip.getRadius()
trip.getCacc()
cacc.loc[index] = asarray(trip.Quantiles(trip.cacc.val))
cacc.to_csv('/home/user1/Desktop/Share2Windows/Kaggle/FeaturesCleaned/CaccQuantiles/' + str(driverID) + '.csv', index=False)
del cacc
return 0
def GetProba(drive,driverID,tripInd):
driverDir = '/home/user1/Desktop/SharedFolder/Kaggle/DriversCleaned/'+str(driverID)
df = pd.read_csv(driverDir+'_' + str(tripInd)+'.csv')
trip = Trip(driverID,tripInd,df)
trip.getSpeed()
trip.getAcc()
#trip.getRadius()
#trip.getCacc()
trip.getFeatures()
X=trip.features[['v','acc']]
probas = np.zeros((X.shape[0],drive.shape[0]))
for i in range(drive.shape[0]):
probas[:,i]=multivariate_normal.pdf(X, mean=array(drive.ix[i,:2]), cov=[array(drive.ix[i,2:4]),array(drive.ix[i,4:])])
probas=np.max(probas,axis=1)
return probas.mean()
def GetProba(clf,driverID,tripID):
#print driverID,tripID
driverDir = '/home/user1/Desktop/SharedFolder/Kaggle/DriversCleaned/'+str(driverID)
df = pd.read_csv(driverDir+'_' + str(tripInd)+'.csv')
trip = Trip(driverID,tripInd,df)
trip.getSpeed()
trip.getAcc()
#trip.getRadius()
#trip.getCacc()
trip.getFeatures()
X=trip.features[['v','acc']]
probas = np.zeros(X.shape[0])
for i in range(X.shape[0]):
probas[i]=clf.score(X.loc[i])
print probas.mean()
return probas.mean()
def GetFeatures(driverID,j):
driverDir = '/home/user1/Desktop/SharedFolder/Kaggle/DriversCleaned/'+str(driverID)
tripFiles = range(1,201)
X = pd.DataFrame(columns=selectedCols)
for index,tripID in enumerate(tripFiles):
#print index,tripID
trip = Trip(driverID,tripID,pd.read_csv(driverDir+'_' + str(tripID) + '.csv'))
trip.getSpeed()
trip.getAcc()
#trip.getRadius()
#trip.getCacc()
trip.getFeatures()
'''z=array(list(set(np.asarray([range(x-5,x+5) for x in (trip.features.v<vlim[0]).nonzero()[0]]).flatten())))
z=z[z<trip.features.shape[0]]
z=z[z>=0]
#z=array(list(set(range(trip.features.shape[0]))-set(z)))
Xz=trip.features.loc[z]
Xz=Xz.reset_index(drop=True)
Xz=Xz.loc[Xz.v!=0]
Xz=Xz.reset_index(drop=True)
X = X.append(Xz)'''
X = X.append(trip.features)
X=X.reset_index(drop=True)
X=X[(X.v<vlim[1]) & (X.v>vlim[0])]
X=X[(X.acc<clim[1]) & (X.acc>clim[0])]
X=X.reset_index(drop=True)
clf=GetGmm(np.asanyarray(X[['v','acc']]))
cos = SaveGmm(clf)
cos.to_csv('/home/user1/Desktop/SharedFolder/Kaggle/FeaturesCleaned/GMM/All/' + str(driverID) + '.csv', index=False)
#del cos
return 0
def algorithm(self):
self.routingDay = self.initRoutingDay()
for pair, saving in self.savings:
trip1 = self.routingDay.tripContainingRequest(pair[0], True)
trip2 = self.routingDay.tripContainingRequest(pair[1], True)
if trip1 and trip2:
if not trip1.equals(trip2):
newTrip = Trip(self.instance)
newTrip.concatenateTrips(trip2, trip1, pair)
if newTrip.isValid():
validChange = True
benefit = True
for toolID, tool in self.instance.tools.items():
if self.inventory[toolID] < 0:
benefit = False
newInventory = newTrip.inventoryChange()
inventory1 = trip1.inventoryChange()
inventory2 = trip2.inventoryChange()
for toolID, tool in self.instance.tools.items():
change = newInventory[toolID] - inventory1[
toolID] - inventory2[toolID]
if change < 0 and self.inventory[
toolID] + change < 0:
validChange = False
break
if self.inventory[toolID] < 0 and change > 0:
benefit = True
if validChange and benefit:
self.routingDay.addTrip(newTrip)
self.routingDay.deleteTrip(trip1)
self.routingDay.deleteTrip(trip2)
for toolID, tool in self.instance.tools.items():
change = newInventory[toolID] - inventory1[
toolID] - inventory2[toolID]
self.inventory[
toolID] = self.inventory[toolID] + change
def writeCSV_selfDriver(self):
g = open("driver_stats/" + str(self.name) + "_selfTrips.csv", "w")
for i in range(1, 201): #get features for all driver trips
t = Trip("../drivers/" + str(self.name) + "/" + str(i) + ".csv")
g.write(t.printFeatures())
g.close()
from Trip import Trip
from MaxMileageException import MaxMileageException
try:
miles = int(input("How many miles to your destination? \n"))
trip = Trip()
trip.setMiles(miles)
hours = miles / 65
print("The trip will be {} hours.".format(hours))
trip.stop_for_food(hours)
trip.rest_for_day(hours)
# print(miles)
loop = 0
while miles > 0:
if loop == 350:
print("You are getting low on gas. Please fill up.")
loop += 1
# print(miles)
miles -= 1
except MaxMileageException:
print("You must not go on a trip over 500 miles.")
import itertools
from scipy import linalg
import matplotlib.pyplot as plt
import matplotlib as mpl
from sklearn.mixture import GMM
from sklearn.neighbors import KernelDensity as kde
from scipy.stats import multivariate_normal
from scipy.spatial.distance import mahalanobis
# <codecell>
driverID = 1
driverDir = '/home/user1/Desktop/SharedFolder/Kaggle/DriversCleaned/'+str(driverID)
tripInd = 1
df = pd.read_csv(driverDir+'_' + str(tripInd)+'.csv')
trip = Trip(driverID,tripInd,df)
trip.getSpeed()
trip.getAcc()
#trip.getRadius()
#trip.getCacc()
trip.getFeatures()
X=trip.features[['v','acc']]
# <codecell>
def GetProba(drive,driverID,tripInd):
driverDir = '/home/user1/Desktop/SharedFolder/Kaggle/DriversCleaned/'+str(driverID)
df = pd.read_csv(driverDir+'_' + str(tripInd)+'.csv')
trip = Trip(driverID,tripInd,df)
trip.getSpeed()
trip.getAcc()
def get_trips() -> List[Trip]:
conn = get_db()
res = conn.execute(
'SELECT * FROM position ORDER BY Timestamp').fetchall()
trips = []
if len(res) > 1:
start = res[0]
end = res[1]
tr = Trip()
#res = list(map(dict,res))
for x in range(0, len(res) - 2):
next_el = res[x + 2]
if end["mileage"] - start["mileage"] == 0 or \
(end["Timestamp"] - start["Timestamp"]).total_seconds() / 3600 > 3:
start = end
tr = Trip()
else:
distance = next_el["mileage"] - end["mileage"] # km
duration = (next_el["Timestamp"] -
end["Timestamp"]).total_seconds() / 3600
if (
distance == 0 and duration > 0.08
) or duration > 2: # check the speed to handle missing point
tr.distance = end["mileage"] - start["mileage"] # km
if tr.distance > 0:
tr.start_at = start["Timestamp"]
tr.end_at = end["Timestamp"]
tr.add_points(end["longitude"], end["latitude"])
tr.duration = (
end["Timestamp"] -
start["Timestamp"]).total_seconds() / 3600
tr.speed_average = tr.distance / tr.duration
diff_level = start["level"] - end["level"]
tr.consumption = diff_level / 100 * BATTERY_POWER # kw
tr.consumption_km = 100 * tr.consumption / tr.distance # kw/100 km
# logger.debug(
# f"Trip: {start['Timestamp']} {tr.distance:.1f}km {tr.duration:.2f}h {tr.speed_average:.2f} km/h {tr.consumption:.2f} kw {tr.consumption_km:.2f}kw/100km")
# filter bad value
if tr.consumption_km < 70:
trips.append(tr)
start = next_el
tr = Trip()
else:
tr.add_points(end["longitude"], end["latitude"])
end = next_el
return trips
result_dict['schedule'].append({
"job":
j.job_id,
"delivery time":
j.find_delivery_time().strftime("%m/%d/%Y, %H:%M:%S"),
"user company":
j.user_company,
"location":
j.vessel_loading_location,
"pick up":
j.check_pickup_time(),
"items":
j.process_items(),
"terminal":
j.terminal
})
pp = pprint.PrettyPrinter(indent=4)
unassigned_jobs_list.sort(key=lambda x: x.find_delivery_time())
for i in range(len(unassigned_jobs_list) - 1):
j = unassigned_jobs_list[i]
for k in range(1, len(unassigned_jobs_list) - i):
o = unassigned_jobs_list[i + k]
print(
str(j.job_id) + " and " + str(o.job_id) + ": " +
str(j.use_same_truck(o)))
if (j.use_same_truck(o)):
trip = Trip(j, o)
print(trip.get_truck())
pp.pprint(sorted(result_dict['schedule'], key=lambda x: x['delivery time']))
stop_id = stop_node.get('id')
stop = Stop.get(int(stop_id))
tr.add_stop(stop)
# trips
trips_node = trip_route_node.find('Trips')
for trip_node in trips_node.findall('Trip'):
trip_id = trip_node.get('id')
trip = tr.add_trip()
trip.trip_id = int(trip_id)
for trip_node in tree.getroot().findall('Trip'):
trip_id = trip_node.get('id', Trip.new_id())
gtfs_id = trip_node.get('gtfs_id', None)
name = trip_node.findtext('name')
calendar_id = trip_node.findtext('calendar_id')
route_id = trip_node.findtext('route_id')
route = Route.get(int(route_id))
trip = Trip.get(int(trip_id))
trip.name = name
trip.gtfs_id = gtfs_id
# trip stops
trip_stops_node = trip_node.find('TripStops')
for i, trip_stop_node in enumerate(trip_stops_node.findall('TripStop')):
stop_id = trip_stop_node.findtext('stop_id')
# Holds a set of random trips
all_trips = []
header = True
# Get 20000 trips
for t in trip_file:
if header:
# First row is just descriptions of data, not data at all
header = False
continue
if i > 20000:
break
i += 1
# This list is used to initialize a Trip object
new_trip_list = [t[0], t[8], t[9], float(t[10]), float(t[11]),
float(t[12]), float(t[13]), -1, -1, 1]
new_trip = Trip(new_trip_list)
all_trips.append(new_trip)
grid_arcs = get_correct_nodes(n, "speeds_per_hour/0_0",
"ArcFlags/20Regions0_0.csv")
grid_a_star = get_correct_nodes(n, "speeds_per_hour/0_0", None)
node_info = get_node_range(grid_a_star)
max_speed = 0
# Iterates through every edge to find te fastest speed
for column in grid_a_star:
for region in column:
for node in region.nodes:
for connection in node.speed_connections:
if node.speed_connections[connection] > max_speed:
max_speed = node.speed_connections[connection]
all_trips_arcs = []
all_trips_star = []
