def test_step(self):
a = Taxi()
a._drift_prob = 0.0
(r, ns, terminal) = a.step(np.array([1, 0, 0, 0]), 0)
self.assertEqual((r, ns.tolist(), terminal), (-1, [1, 0, 0, 0], False))
(r, ns, terminal) = a.step(np.array([1, 0, 0, 0]), 1)
self.assertEqual((r, ns.tolist(), terminal), (-1, [1, 0, 1, 0], False))
(r, ns, terminal) = a.step(np.array([1, 0, 0, 0]), 2)
self.assertEqual((r, ns.tolist(), terminal), (-1, [1, 0, 0, 0], False))
(r, ns, terminal) = a.step(np.array([1, 0, 0, 0]), 3)
self.assertEqual((r, ns.tolist(), terminal), (-1, [1, 0, 0, 1], False))
(r, ns, terminal) = a.step(np.array([2, 0, 0, 0]), 4)
self.assertEqual((r, ns.tolist(), terminal), (-1, [2, 4, 0, 0], False))
(r, ns, terminal) = a.step(np.array([0, 4, 1, 1]), 4)
self.assertEqual((r, ns.tolist(), terminal), (-10, [0, 4, 1, 1], False))
(r, ns, terminal) = a.step(np.array([0, 4, 1, 0]), 5)
self.assertEqual((r, ns.tolist(), terminal), (-10, [0, 4, 1, 0], False))
(r, ns, terminal) = a.step(np.array([0, 4, 0, 0]), 5)
self.assertEqual((r, ns.tolist(), terminal), (20, [0, 0, 0, 0], True))
def main():
mytaxi = Taxi("Crown Victoria", 100)
mytaxi.drive(40)
print("Taxi Information\n {}\n Current Fare: ${}".format(
mytaxi, mytaxi.get_fare()))
mytaxi.start_fare()
print("Taxi Information\n {}\n Current Fare: ${}".format(
mytaxi, mytaxi.get_fare()))
def init_taxis(self):
taxis = []
taxi_types = len(self.capacities)
for capacity in self.capacities:
for x in range(round(self.n_taxi / taxi_types)):
taxis.append(Taxi(x, self, capacity))
return taxis
def test_can_move(self):
a = Taxi()
self.assertFalse(a.can_move([0, 1], [0, 2]))
self.assertFalse(a.can_move([0, 2], [0, 1]))
self.assertFalse(a.can_move([1, 1], [1, 2]))
self.assertFalse(a.can_move([1, 2], [1, 1]))
self.assertFalse(a.can_move([3, 0], [3, 1]))
self.assertFalse(a.can_move([3, 1], [3, 0]))
self.assertFalse(a.can_move([4, 0], [4, 1]))
self.assertFalse(a.can_move([4, 1], [4, 0]))
self.assertFalse(a.can_move([3, 2], [3, 3]))
self.assertFalse(a.can_move([3, 3], [3, 2]))
self.assertFalse(a.can_move([4, 2], [4, 3]))
self.assertFalse(a.can_move([4, 3], [4, 2]))
def main():
taxi_list = [
Taxi("Prius", 100),
SilverServiceTaxi("Limo", 100, 2),
SilverServiceTaxi("Hummer", 200, 4)
]
my_taxi = None
totalbill = 0
flag = True
print("Let's drive!")
while flag:
print("Menu:")
print("q) quit")
print("c) choose taxi")
print("d) drive)")
menuoption = input(">>>")
if (menuoption == "D" or menuoption == "d"):
if not (my_taxi in taxi_list):
my_taxi = taxi_list[0]
print(my_taxi)
curr_trip_distance = int(input("Drive how far?"))
my_taxi.start_fare()
curr_distance_driven = my_taxi.drive(curr_trip_distance)
totalbill += my_taxi.get_fare()
print("Your {} trip cost you ${:.2f}".format(
my_taxi.name, my_taxi.get_fare()))
print("Bill to date : ${:.2f}".format(totalbill))
elif (menuoption == "c" or menuoption == "C"):
print("Taxis available:")
for i in range(len(taxi_list)):
print(taxi_list[i])
taxioption = int(input("Choose Taxi: "))
my_taxi = taxi_list[taxioption]
print("Bill to date: ${:.2f}".format(totalbill))
second_flag = True
while second_flag:
if not (0 <= taxioption < len(taxi_list)):
print("Invalid Option Try Again..!!")
else:
my_taxi = taxi_list[taxioption]
second_flag = False
elif (menuoption == "q" or menuoption == "Q"):
print("Total Trip Cost: ${:.2f}".format(totalbill))
flag = False
else:
print("Invalid Menu Choice")
def test_can_move(self):
a = Taxi()
self.assertFalse(a.can_move([0, 1], [0, 2]))
self.assertFalse(a.can_move([0, 2], [0, 1]))
self.assertFalse(a.can_move([1, 1], [1, 2]))
self.assertFalse(a.can_move([1, 2], [1, 1]))
self.assertFalse(a.can_move([3, 0], [3, 1]))
self.assertFalse(a.can_move([3, 1], [3, 0]))
self.assertFalse(a.can_move([4, 0], [4, 1]))
self.assertFalse(a.can_move([4, 1], [4, 0]))
self.assertFalse(a.can_move([3, 2], [3, 3]))
self.assertFalse(a.can_move([3, 3], [3, 2]))
self.assertFalse(a.can_move([4, 2], [4, 3]))
self.assertFalse(a.can_move([4, 3], [4, 2]))
def system_init():
print('type: {}'.format(type(osm_map)))
# sub_graph = osm_map.subgraph([4548141057, 4548141062, 4548141067, 1457872913, 4548141073])
# E = list(sub_graph.nodes)
# print(E)
# input()
print('System Initiating...')
taxi_table = pd.read_csv('./data/taxi_info_list.csv')
df = pd.read_csv('./data/node_list_with_cluster.csv')
for indexs in df.index:
tmp = df.loc[indexs]
node_list.append(
Node(tmp['real_id'], tmp['lon'], tmp['lat'], int(tmp['cluster_id'])))
# .里面包含的内容是每个partition的landmark的经纬度.其下标与partition_list的下标一一对应
landmark_table = pd.read_csv('./data/landmark.csv')
global landmark_list
landmark_list = list(
zip(landmark_table.loc[:, 'lon'], landmark_table.loc[:, 'lat'], landmark_table.loc[:, 'landmark_node_id']))
global partition_list
partition_list = [None] * (max(df.loc[:, 'cluster_id']) + 1)
# 初始化所有partition实例
for node_it in node_list:
cid = node_it.cluster_id_belongto
if partition_list[cid] is None:
partition_list[cid] = Partition(cid, node_list=[], taxi_list=[])
partition_list[cid].node_list.append(int(node_it.node_id))
else:
partition_list[cid].node_list.append(int(node_it.node_id))
global taxi_list
for taxi_it in taxi_table.index:
tmp = taxi_table.loc[taxi_it]
taxi_in_which_partition = check_in_which_partition(
tmp['init_lon'], tmp['init_lat'])
taxi_list.append(
Taxi(int(tmp['taxi_id']), tmp['init_lon'], tmp['init_lat'], SYSTEM_INIT_TIME - TIME_OFFSET, partition_id_belongto=taxi_in_which_partition, seat_left=3))
partition_list[taxi_in_which_partition].taxi_list.append(
int(tmp['taxi_id']))
# 初始化邻接矩阵
global node_distance_matrix
node_distance_matrix = copy.copy(node_distance.values)
def create( spec, scheme = 'none', count = 20, *args ):
"""
@spec - Specification (size, endpoints, barriers); either exactly
specified in a file, or with numeric values in a list
@option_scheme - none|manual|optimal|small-world|random|ozgur's betweenness|ozgur's randomness|end
@n_actions - Number of steps that need to taken
comment : optimal(shortest path to destination)??|random|ozgur's betweenness|ozgur's randomness
"""
env = Taxi.create( spec )
# Percentage
if isinstance(count,str):
count = int(count[:-1])
count = count*env.S/100
# Add options for all the optimal states
O = []
if scheme == "none":
pass
elif scheme == "random-node":
O = OptionGenerator.optimal_options_from_random_nodes( env, count, *args )
elif scheme == "random-path":
O = OptionGenerator.optimal_options_from_random_paths( env, count, *args )
elif scheme == "betweenness":
O = OptionGenerator.optimal_options_from_betweenness( env, count, *args )
elif scheme == "small-world":
O = OptionGenerator.optimal_options_from_small_world( env, count, *args )
elif scheme == "betweenness+small-world":
O = OptionEnvironment.optimal_options_from_betweenness( env, count )
count_ = count - len( O )
O += OptionEnvironment.optimal_options_from_small_world( env, count_, *args )
elif scheme == "load":
O = OptionGenerator.options_from_file( *args )[:count]
else:
raise NotImplemented()
return OptionEnvironment( TaxiOptions, env.S, env.A, env.P, env.R, env.R_bias, env.start_set, env.end_set, O )
def create( spec, scheme = 'none', count = 20, *args ):
"""
@spec - Specification (size, endpoints, barriers); either exactly
specified in a file, or with numeric values in a list
@option_scheme - none|manual|optimal|small-world|random|ozgur's betweenness|ozgur's randomness|end
@n_actions - Number of steps that need to taken
comment : optimal(shortest path to destination)??|random|ozgur's betweenness|ozgur's randomness
"""
env = Taxi.create( spec )
# Percentage
if isinstance(count,str):
count = int(count[:-1])
count = count*env.S/100
# Add options for all the optimal states
O = []
if scheme == "none":
pass
elif scheme == "random-node":
O = OptionGenerator.optimal_options_from_random_nodes( env, count, *args )
elif scheme == "random-path":
O = OptionGenerator.optimal_options_from_random_paths( env, count, *args )
elif scheme == "betweenness":
O = OptionGenerator.optimal_options_from_betweenness( env, count, *args )
elif scheme == "small-world":
O = OptionGenerator.optimal_options_from_small_world( env, count, *args )
elif scheme == "betweenness+small-world":
O = OptionEnvironment.optimal_options_from_betweenness( env, count )
count_ = count - len( O )
O += OptionEnvironment.optimal_options_from_small_world( env, count_, *args )
elif scheme == "load":
O = OptionGenerator.options_from_file( *args )[:count]
else:
raise NotImplemented()
return OptionEnvironment( TaxiOptions, env.S, env.A, env.P, env.R, env.R_bias, env.start_set, env.end_set, O )
from Transportation import Transportation
from Walk import Walk
from Taxi import Taxi
from Train import Train
if __name__ == '__main__':
travel_cost = 0
trip = [
Walk("KMITL", "KMITL SCB Bank", 0.6),
Taxi("KMITL SCB Bank", "Ladkrabang Station", 5),
Train("Ladkrabang Station", "Payathai Station", 40, 6),
Taxi("Payathai Station", "The British Council", 3)
]
for travel in trip:
travel_cost += travel.find_cost()
print(travel_cost)
#!/usr/bin/python from Demo import Demo from Swarm import Swarm from Taxi import Taxi swarm= Swarm(count=24) demo= Demo(swarm) while demo.is_open: demo.draw(Taxi(swarm)) if not demo.paused: swarm.move(demo.step)
from Taxi import Taxi
Taxi1 = Taxi("Prius 1", 100, 1.2)
print(Taxi1)
Taxi1.drive(50)
print(Taxi1)
Taxi2 = Taxi("Prius 2", 100, 1.2)
print(Taxi2)
Taxi2.drive(100)
print(Taxi2.get_fare())
print(Taxi2)
def test_step(self):
a = Taxi()
a._drift_prob = 0.0
(r, ns, terminal) = a.step(np.array([1, 0, 0, 0]), 0)
self.assertEqual((r, ns.tolist(), terminal), (-1, [1, 0, 0, 0], False))
(r, ns, terminal) = a.step(np.array([1, 0, 0, 0]), 1)
self.assertEqual((r, ns.tolist(), terminal), (-1, [1, 0, 1, 0], False))
(r, ns, terminal) = a.step(np.array([1, 0, 0, 0]), 2)
self.assertEqual((r, ns.tolist(), terminal), (-1, [1, 0, 0, 0], False))
(r, ns, terminal) = a.step(np.array([1, 0, 0, 0]), 3)
self.assertEqual((r, ns.tolist(), terminal), (-1, [1, 0, 0, 1], False))
(r, ns, terminal) = a.step(np.array([2, 0, 0, 0]), 4)
self.assertEqual((r, ns.tolist(), terminal), (-1, [2, 4, 0, 0], False))
(r, ns, terminal) = a.step(np.array([0, 4, 1, 1]), 4)
self.assertEqual((r, ns.tolist(), terminal),
(-10, [0, 4, 1, 1], False))
(r, ns, terminal) = a.step(np.array([0, 4, 1, 0]), 5)
self.assertEqual((r, ns.tolist(), terminal),
(-10, [0, 4, 1, 0], False))
(r, ns, terminal) = a.step(np.array([0, 4, 0, 0]), 5)
self.assertEqual((r, ns.tolist(), terminal), (20, [0, 0, 0, 0], True))
def test_is_terminal(self):
a = Taxi()
self.assertTrue(a.is_terminal(np.array([0, 0, 0, 0])))
self.assertTrue(a.is_terminal(np.array([1, 1, 0, 0])))
self.assertTrue(a.is_terminal(np.array([2, 2, 0, 0])))
self.assertTrue(a.is_terminal(np.array([3, 3, 0, 0])))
from Taxi import Taxi
Taxi1 = Taxi("Prius 1", 100, 1.2)
print(Taxi1)
Taxi1.drive(50)
print(Taxi1)
Taxi2 = Taxi("Prius 2", 100, 1.2)
print(Taxi2)
Taxi2.drive(100)
print(Taxi2.get_fare())
print(Taxi2)
def determine_travel_time(self):
if self.simulation.dist_indep:
return float('inf')
else:
distance = Taxi.distance(self.orig, self.dest)
return ((MAX_DISTANCE * 0.1) + (1.2 * distance)) / self.power
def determine_price(self):
if self.simulation.price_indep:
return float('inf')
else:
return Taxi.distance(self.orig, self.dest) * self.power
def test_is_terminal(self):
a = Taxi()
self.assertTrue(a.is_terminal(np.array([0, 0, 0, 0])))
self.assertTrue(a.is_terminal(np.array([1, 1, 0, 0])))
self.assertTrue(a.is_terminal(np.array([2, 2, 0, 0])))
self.assertTrue(a.is_terminal(np.array([3, 3, 0, 0])))
