self.move_towards(obj=self.target, n=10)
class Collectible(BaseCollectible):
def on_trigger(self, obj):
obj.score += 1
obj.target = None
#==================================================================================================
# SIMULATION
#==================================================================================================
# Setup agents
agent = Agent(1, 1, color=RED)
agent2 = Agent(75, 25, color=BLUE)
# Setup collectibles as random spawner
collectible_spawner = lambda x, y: Collectible(x, y, color=WHITE)
# Setup environment
env = GridEnvironment(80, 30, 10, objects=[agent, agent2])
env.spawn(collectible_spawner, 100)
env.render()
# Prepare simulation
sim = Simulation(env, fps=30, name="CollectiblesMultiplayer")
if __name__ == "__main__":
sim.run_episode(n_steps=1000, save=True)
class Agent(BaseGridAgent):
def step(self):
self.wander()
obstacle = BaseObstacle(10, 0, 1, 7, color=BLUE)
agent_spawner = lambda x, y: Agent(x, y, color=GREEN)
coll_spawner = lambda x, y: BaseCollectible(
x, y, color=WHITE, circle=True, radius=0.3)
agent1 = agent_spawner(1, 1)
# Setup grid
BOX_SIZE = 20
WIDTH = 20
HEIGHT = 10
env = GridEnvironment(WIDTH,
HEIGHT,
BOX_SIZE,
show_grid=True,
objects=[obstacle, agent1])
env.spawn(coll_spawner, 120)
env.render()
# Prepare simulation
sim = Simulation(env, fps=30, name="CollectiblesObstacle")
if __name__ == "__main__":
sim.run_episode(n_steps=200, save=True)
#==================================================================================================
# SIMULATION
#==================================================================================================
# Prepare layer
layer = BaseLayer(
img_filepath="examples/assets/layers/Layer_1590257407_boxsize=20.png",
img_transparency=(255, 255, 255))
# Prepare agents
agents = [
Agent(0, 0, color=RED),
WanderAgent(17, 7, color=BLUE, curiosity=20),
RandomAgent(10, 11, color=GREEN),
]
# Prepare environment
env = GridEnvironment(cell_size=20,
show_grid=True,
background_color=WHITE,
grid_color=(200, 200, 200),
objects=agents + [layer])
# Prepare simulation and run it
sim = Simulation(env, fps=30, name="LayerPathfindingMouse")
if __name__ == "__main__":
sim.run_episode(n_steps=200, save=True)
CONTACT_RISK = 6
RECOVERY_DURATION_RANGE = [20, 50]
spawner = lambda state: lambda x, y: SIRAgent(x,
y,
state=state,
contact_risk=CONTACT_RISK,
recovery_duration_range=
RECOVERY_DURATION_RANGE)
# Setup grid
CELL_SIZE = 20
WIDTH = 40
HEIGHT = 30
env = GridEnvironment(cell_size=CELL_SIZE,
width=WIDTH,
height=HEIGHT,
show_grid=False,
callbacks_step=[callback_logger])
env.spawn(spawner("S"), 100)
env.spawn(spawner("I"), 1)
# Prepare simulation and run it
sim = Simulation(env, fps=10, name="SimpleSIR")
if __name__ == "__main__":
sim.run_episode(n_steps=200, save=False)
logger.df[["S", "I", "R"]].plot()
plt.show()
from westworld.colors import *
obstacle = BaseObstacle(10, 0, 1, 7, color=RED)
agent_spawner = lambda x, y: CollectibleFinderAgent(
x, y, color=(0, 200, 255), search_radius=3, img_asset="blob")
coll_spawner = lambda x, y: BaseCollectible(
x,
y,
color=(220, 150, 50),
img_filepath="examples/assets/sprites/sprite_lemon.png")
# Setup grid
BOX_SIZE = 40
WIDTH = 20
HEIGHT = 10
env = GridEnvironment(WIDTH,
HEIGHT,
BOX_SIZE,
show_grid=True,
objects=[obstacle])
env.spawn(agent_spawner, 1)
env.spawn(coll_spawner, 20)
env.render()
env.get_img()
# Prepare simulation
sim = Simulation(env, fps=10, name="CollectiblesFinder")
if __name__ == "__main__":
sim.run_episode(n_steps=1000, save=False)
spawner = lambda state: lambda x, y: SIRQuarantineAgent(
x,
y,
state=state,
contact_risk=CONTACT_RISK,
recovery_duration_range=RECOVERY_DURATION_RANGE)
# Prepare layer
layer = BaseLayer(
img_filepath="examples/assets/layers/Layer_1590257407_boxsize=20.png",
img_transparency=(255, 255, 255))
# Prepare environment
env = GridEnvironment(cell_size=10,
show_grid=True,
background_color=WHITE,
grid_color=(200, 200, 200),
callbacks_step=[callback_logger],
objects=[layer])
env.spawn(spawner("S"), 100)
env.spawn(spawner("I"), 10)
# Prepare simulation and run it
sim = Simulation(env, fps=25, name="RoomSIR")
if __name__ == "__main__":
sim.run_episode(n_steps=500, save=True, save_format="video")
logger.df[["S", "I", "R"]].plot()
plt.show()
x, y = self.target
self.move_towards(x=x, y=y, n=15)
class PathfindingClickSimulation(Simulation):
def on_event(self, event):
if self.event_is_click(event):
x, y = self.get_mouse_pos()
obstacle = obstacle_spawner(x, y)
env.add_object(obstacle)
if self.event_is_rightclick(event):
new_target = self.get_mouse_pos()
for agent in self.env.objects:
agent.target = new_target
agent_spawner = lambda x, y: Agent(x, y)
obstacle_spawner = lambda x, y: BaseObstacle(x, y, 5, 5, color=GREEN)
# Setup grid
env = GridEnvironment(200, 100, 4)
env.spawn(agent_spawner, 100)
# Setup simulation
sim = PathfindingClickSimulation(env, fps=25)
sim.run_episode(n_steps=500, save=True)
from westworld.agents import BaseGridAgent
from westworld.objects import BaseObstacle, BaseTrigger, BaseCollectible
from westworld.simulation import Simulation
from westworld.colors import *
BOX_SIZE = 10
WIDTH = 50
HEIGHT = 30
N_ZONES = 10
TARGETS = list(
zip(np.random.randint(0, WIDTH, N_ZONES),
np.random.randint(0, HEIGHT, N_ZONES)))
class Agent(BaseGridAgent):
def init(self):
self.target = random.choice(TARGETS)
def step(self):
self.move_towards(*self.target, n=20)
agent_spawner = lambda x, y: Agent(x, y, color=GREEN)
# Setup grid
env = GridEnvironment(WIDTH, HEIGHT, BOX_SIZE)
env.spawn(agent_spawner, 100)
# Setup simulation
sim = Simulation(env, fps=30, name="PathfindingZonesSimulation")
sim.run_episode(n_steps=250, save=False)