def move_head(direction):
global head, tail, head_x, head_y, facing, opposite, snake_head_img
if direction == opposite:
direction = head['facing']
if facing != direction:
snake_head_img = orientate_snake(snake_head_img, head, direction.value)
if direction == Directions.UP:
head['rect'].top -= SEG_DIM
head['facing'] = Directions.UP
opposite = Directions.get_opposite(direction)
elif direction == Directions.RIGHT:
head['rect'].left += SEG_DIM
head['facing'] = Directions.RIGHT
opposite = Directions.get_opposite(direction)
elif direction == Directions.DOWN:
head['rect'].top += SEG_DIM
head['facing'] = Directions.DOWN
opposite = Directions.get_opposite(direction)
elif direction == Directions.LEFT:
head['rect'].left -= SEG_DIM
head['facing'] = Directions.LEFT
opposite = Directions.get_opposite(direction)
class DirectionResponseParser(object):
@classmethod
def parse(klass, response):
parser = DirectionResponseParser(response)
return parser._parse()
def __init__(self, response):
self.response = response
self.json_dict = json.loads(response.read())
self.directions = Directions()
def _parse(self):
if self.response_valid():
self.set_timeline()
self.build_steps()
return self.directions
else:
return None
def response_valid(self):
return self.response.status == 200
def set_timeline(self):
route = self.json_dict['routes'][0]['legs'][0]
if 'arrival_time' in route.keys() and 'departure_time' in route.keys():
arrival = route['arrival_time']['text']
departure = route['departure_time']['text']
self.directions.set_timeline(arrival, departure)
def build_steps(self):
steps = self.json_dict['routes'][0]['legs'][0]['steps']
for step in steps:
self.directions.add_step(DirectionStep(step))
def act(self, state):
head_pos = state[0]
apple_pos = state[1]
step_size = state[2]
facing = state[3]
tail = state[4]
shortest = None
action = action_space[0]
for i in range(0, len(action_space)):
if Directions.get_opposite(facing) == directions[i]:
continue
direction = directions[i]
opposite = Directions.get_opposite(direction)
x, y = self.pred_position(head_pos.left, head_pos.top, direction,
opposite, step_size)
if not self.will_avoid_oneself(x, y, tail):
continue
distance = math.sqrt((apple_pos.top - y)**2 +
(apple_pos.left - x)**2)
if shortest == None or distance < shortest:
shortest = distance
action = action_space[i]
return action
def __init__(self, unique_id, model, pos, exp, directions):
self.unique_id = unique_id
self.model = model
self.pos = pos
self.traversable = True
self.trip_lengths = powerlaw.Power_Law(
xmin=7, parameters=[exp]) #1.5-2.0 #xmin 17?
self.direction_range = 3
self.directions = Directions(self.direction_range)
self.current_direction = 0
self.remaining_steps = 0
self.start = None
self.end_point = None
def selectProcess(command, authkeys):
commandList = command.lower().split()
command = command.lower()
google_authkeys = authkeys["google"]
yelp_authkeys = authkeys["yelp"]
if (directionCommand(commandList)):
return (Directions(command, google_authkeys))
elif (dictionaryCommand(commandList)):
return (dictionary(command))
elif (yelpCommand(commandList)):
return (Yelp(command, yelp_authkeys))
elif (wikiCommand(commandList)):
return (SearchWiki(command))
elif (placesCommand(commandList)):
return (GooglePlace(command, google_authkeys))
elif (helpCommand(commandList)):
return (printHelp())
else:
return ("We didn't understand your search, see if this helps:\n" +
printHelp())
def __init__(self, N, height, width, exponent, steps):
self.number_of_agents = N
self.height = height
self.width = width
self.exponent = exponent
#self.x_locs = np.zeros((N, steps))
#self.y_locs = np.zeros((N))
self.direction_range=3
self.directions = Directions(self.direction_range)
self.current_step_contacts=[]
self.adjacency_matrix = np.zeros((N, N))
self.grid = MultiGrid(self.width, self.height, torus=False)
self.schedule = BaseScheduler(self)
self.current_step = 0
# Add N pedestrians to model (schedule, grid)
for i in range(self.number_of_agents):
x = self.random.randrange(1, self.grid.width-1)
y = self.random.randrange(1, self.grid.height-1)
pos = (x, y)
new_human = Pedestrian(i, self, pos, self.exponent, self.directions)
self.schedule.add(new_human)
self.grid.place_agent(new_human, pos)
self.data_collector=DataCollector()
self.running=True
self.data_collector.collect(self)
def reset(settings, first_play=False):
global head, tail, facing, opposite, direction, apple, snake_head_img, snake_body_img
direction = settings['starting_direction']
opposite = Directions.get_opposite(facing)
head['rect'] = get_segment()
head['facing'] = settings['starting_direction']
apple = spawn_apple()
snake_head_img = pygame.image.load("snake head.png")
snake_head_img = pygame.transform.scale(snake_head_img, (settings['block_dim'], settings['block_dim']))
snake_body_img = pygame.image.load("snake body.png")
snake_body_img = pygame.transform.scale(snake_body_img, (settings['block_dim'], settings['block_dim']))
if settings['autostart']:
direction = facing
if first_play:
if settings['walls_on']:
generate_walls()
if settings['tunnels_on']:
generate_tunnels()
else:
tail = []
for _ in range(settings['starting_tail']):
move_head(head['facing'])
tail.append(get_segment())
class Wonsz():
'''Wonsz class'''
def __init__(self, board):
'''object creation'''
self.directions = Directions()
self.direction = self.directions.get_random_direction()
self.board = board
self.body = [(self.board.rows // 2, self.board.cols // 2)]
def __init__(self, screen_size, earth, events):
self.screen_size = screen_size
self.earth_origin = earth.origin
self.earth_radius = earth.earth_radius
self.weapons = []
# Gun parts
self.gun_cooldown = Cooldown(GameData.WEAPON_GUN_COOLDOWN)
self.multigun_cooldown = Cooldown(GameData.WEAPON_MULTIGUN_COOLDOWN)
self.gun_factory = GunFactory(Directions(1.0))
self.missile_cooldown = Cooldown(GameData.WEAPON_MISSILE_COOLDOWN)
self.missile_factory = MissileFactory(Directions(1.0))
self.multimissile_cooldown = Cooldown(
GameData.WEAPON_MULTIMISSILE_COOLDOWN)
self.multimissile_factory = MultiMissileFactory(Directions(1.0))
#Events
self.events = events
self.watch_game_events()
def __init__(self, unique_id, model, pos, exp, x_min, seed=None):
self.unique_id = unique_id
self.model = model
self.pos = pos
self.area_traversed = np.zeros((model.width, model.height))
self.traversable = True
self.trip_lengths = powerlaw.Power_Law(
xmin=x_min, parameters=[exp]) #1.5-2.0 #xmin 17?
self.direction_range = 3
self.directions = Directions(self.direction_range)
self.trip_lengths_covered = []
self.steps_covered = []
self.area_traversed[self.pos[0], self.pos[1]] = 1
self.on_trip = False
self.current_direction = 0
self.remaining_steps = 0
def ajax_quick_search():
origin = request.form.get('origin')
destination = request.form.get('destination')
max_travel_duration = int(request.form.get('max-travel-duration'))*3600
budget = int(request.form.get('budget'))
max_hotel_price = settings.HOTEL_THRESHOLDS.get(budget)
directions = Directions.generate_from_google(origin, destination)
corridors = directions.get_corridors(max_travel_duration, settings.DEFAULT_CORRIDOR_DURATION)
for corridor in corridors:
corridor.generate_hotels(Hotel, max_hotel_price, settings.DEFAULT_EARLY_WEIGHT, settings.DEFAULT_DETOUR_WEIGHT)
if len(corridor.hotels) >= settings.NUMBER_OF_HOTELS_RETURNED:
corridor.hotels = corridor.hotels[:settings.NUMBER_OF_HOTELS_RETURNED]
return render_template("quick_search_results.html", directions=directions, corridors=corridors)
def solve(self, seq_a, seq_b):
score_mat = self._get_score_matrix((len(seq_a) + 1, len(seq_b) + 1))
directions = Directions(score_mat.shape)
for i in range(1, score_mat.shape[0]):
for j in range(1, score_mat.shape[1]):
from_up = score_mat[i - 1][j] + self.gap_penalty
from_left = score_mat[i][j - 1] + self.gap_penalty
if seq_a[i - 1] == seq_b[j - 1]:
from_diag = score_mat[i - 1][j - 1] + self.same
else:
from_diag = score_mat[i - 1][j - 1] + self.diff
best_score = max(from_up, from_left, from_diag)
score_mat[i][j] = best_score
is_left = from_left == best_score
is_up = from_up == best_score
is_diag = from_diag == best_score
directions.set_directions(i, j, is_left, is_up, is_diag)
return score_mat, directions, self._get_final_score_from_score_mat(
score_mat)
def generate_test():
origin = 'Boston'
destination = 'Boulder'
max_travel_duration = 10*3600
budget = 3
max_hotel_price = settings.HOTEL_THRESHOLDS.get(budget)
directions = Directions.generate_from_google(origin, destination)
corridors = directions.get_corridors(max_travel_duration, settings.DEFAULT_CORRIDOR_DURATION)
for corridor in corridors:
corridor.generate_hotels(Hotel, max_hotel_price, settings.DEFAULT_EARLY_WEIGHT, settings.DEFAULT_DETOUR_WEIGHT)
if len(corridor.hotels) >= settings.NUMBER_OF_HOTELS_RETURNED:
corridor.hotels = corridor.hotels[:settings.NUMBER_OF_HOTELS_RETURNED]
with open('data/test.pk', 'wb') as output:
pickle.dump(directions, output, pickle.HIGHEST_PROTOCOL)
pickle.dump(corridors, output, pickle.HIGHEST_PROTOCOL)
return "Success."
class Pedestrian(Agent):
DIRECTION_DEGREES = 15
#NR_OF_DIRECTIONS = 24
def __init__(self, unique_id, model, pos, exp, seed=None):
self.unique_id = unique_id
self.model = model
self.pos = pos
self.traversable = False
self.area_traversed = np.zeros((model.width, model.height))
self.traversable = True
self.trip_lengths = powerlaw.Power_Law(
xmin=7, parameters=[exp]) #1.5-2.0 #xmin 17?
self.direction_range = 3
self.directions = Directions(self.direction_range)
self.trip_lengths_covered = []
self.steps_covered = []
self.area_traversed[self.pos[0], self.pos[1]] = 1
self.on_trip = False
self.current_direction = 0
self.remaining_steps = 0
def plan_trip(self):
'''
Plan new tip:
i. Determine trip length
ii. Determine new direction based on current direction (correlated RW)
'''
# Direction
if self.current_direction == 0: # first trip
direction = random.choice(self.directions.directions)
self.current_direction = Direction(direction, self.direction_range)
else: # correlated random walk
radians = np.random.vonmises(0, kappa=4)
degrees = math.degrees(radians)
jumps = math.floor(degrees / Pedestrian.DIRECTION_DEGREES)
self.current_direction = self.directions.correlated(
self.current_direction, jumps)
# Trip length
length_of_trip = int(self.trip_lengths.generate_random(1)
[0]) #generate_random ignores xmax
self.remaining_steps = self.current_direction.calculate_steps(
length_of_trip)
self.trip_lengths_covered.append(length_of_trip)
self.steps_covered.append(self.remaining_steps)
def contact(self):
'''
Find all other agents within range (radius = 5) and update contacts.
'''
neighbors_in_contact = self.model.grid.get_neighbors(self.pos,
moore=True,
radius=5)
if len(neighbors_in_contact) > 0:
for neighbor in neighbors_in_contact:
if neighbor.unique_id != self.unique_id:
self.model.contact_update(
(self.unique_id, neighbor.unique_id))
def check_if_traversable(self, coordinate):
'''
Check if location is traversable.
'''
traversable = True
if (0 <= coordinate[0] < self.model.width) and (0 <= coordinate[1] <
self.model.height):
contents = self.model.grid.get_cell_list_contents(coordinate)
for content in contents:
if not content.traversable:
traversable = False
else:
traversable = False
return traversable
def move(self):
'''
Move pedestrian one step
'''
# Plan new trip, if current trip length reached
if self.remaining_steps == 0:
self.plan_trip()
# Determine move based on current direction
shift = self.current_direction.move()
move = (self.pos[0] + shift[0], self.pos[1] + shift[1])
# Check if move is possible (can't traverse walls)
if self.check_if_traversable(move):
new_position = move
self.model.grid.move_agent(self, new_position)
self.remaining_steps -= 1
else:
'''
If not traversable, determine the two alternative moves (i. bounce
of vertical wall, ii. bounce of horizontal wall). Determine
which bouncing move works, then move and update direction accordingly
'''
# Bouncing moves
alternative_shifts = [[-shift[0], shift[1]], [shift[0], -shift[1]],
[-shift[0], -shift[1]]]
# If bouncing move possible --> move and update direction
# TODO: Possible bias for objects??? Always checks vertical wall shift first
for bounce_shift in alternative_shifts:
move = (self.pos[0] + bounce_shift[0],
self.pos[1] + bounce_shift[1])
if self.check_if_traversable(move):
# Bounce: move + new direction
new_position = move
self.model.grid.move_agent(self, new_position)
self.remaining_steps -= 1
self.current_direction.change(bounce_shift)
break
def step(self):
self.move()
from directions import Directions
if __name__ == '__main__':
# Calculate values from input
results = Directions('input.txt')
at_least_one_present = str(results.houses_at_least_one_present)
# Print out results
print "The amount of houses that received at least one present: " + at_least_one_present
def __init__(self, response):
self.response = response
self.json_dict = json.loads(response.read())
self.directions = Directions()
