def initialize(config):
if not config['color']:
config['state'] = np.zeros((config['width'], config['height']))
else:
config['state'] = np.zeros((config['width'], config['height'], 3))
if not config['start']:
if not config['color']:
config['start'] = utils.spawn_random_point(
np.zeros((config['width'], config['height'])))
else:
config['start'] = utils.spawn_random_point(
np.zeros((config['width'], config['height'], 3)))
if not config['target_start']:
if not config['color']:
config['target_start'] = utils.spawn_random_point(
np.zeros((config['width'], config['height'])))
else:
config['target_start'] = utils.spawn_random_point(
np.zeros((config['width'], config['height'], 3)))
state = config['state']
pt = config['start']
if config['color']:
state[pt[0], pt[1], :] = [1, 0, 0]
else:
state[pt[0], pt[1]] = 1
config['state'] = state
return config
def main():
width = 250
height = 250
field = np.zeros((width, height, 3))
n_rabbits = 100
n_predators = 1
start = []
rabbits = []
# Populate the field with rabbits
for rabbit in range(n_rabbits):
[x, y] = utils.spawn_random_point(np.zeros((width, height)))
field[x, y, :] = [1, 1, 1]
rabbits.append([x, y])
# Optionally, give predators a start:
if n_predators == 1:
start = [int(width / 2), int(height / 2)]
field[start[0] - 2:start[0], start[1] - 2:start[1], :] = [1, 0, 0]
# If not assign predator random start
if len(start) <= 1:
start = utils.spawn_random_point(field)
f = plt.figure()
# Determine direction to head, and define
# how many steps before checking fov
simulation = []
[pxs, pys] = np.array(field[:, :, 1]).nonzero()
steps = 0
while n_rabbits > (n_rabbits / 2) and steps < 10:
for position in rabbits:
directions = {
1: [position[0] - 1, position[1] - 1],
2: [position[0], position[1] - 1],
3: [position[0] + 1, position[1] - 1],
4: [position[0] - 1, position[1]],
5: position,
6: [position[0] + 1, position[1]],
7: [position[0] - 1, position[1] + 1],
8: [position[0], position[1] + 1],
9: [position[0] + 1, position[1] + 1]
}
steps += 1
simulation.append([plt.imshow(field)])
a = animation.ArtistAnimation(f,
simulation,
interval=190,
blit=True,
repeat_delay=900)
plt.show()
def initialize(self, config):
self.state = config['map']
if 'start' not in config.keys():
self.point = point(utils.spawn_random_point(self.state))
else:
self.point = point(config['start'])
self.state[self.point.x, self.point.y] = 2
def initialize(config):
n_points = config['n_obstacles']
if config['color']:
state = utils.add_random_points_color(
np.zeros((config['width'], config['height'], 3)), n_points, 'r')
if config['start'] == []:
start = utils.spawn_random_point(
np.zeros((config['width'], config['height'])))
state[start[0], start[1], :] = [0, 0, 1]
else:
state = utils.add_random_points(
np.zeros((config['width'], config['height'])), n_points)
if config['start'] == []:
start = utils.spawn_random_point(
np.zeros((config['width'], config['height'])))
state[start[0], start[1]] = -1
config['initial_state'] = state
if config['start'] == []:
config['start'] = np.array(
utils.spawn_random_point(config['initial_state']))
config['steps'] = utils.spawn_random_walk(config['start'],
config['n_steps'])
return high_speed_crawler(config)
def build_map(config):
state = np.zeros((config['width'], config['height']))
for point in range(config['n_obstacles']):
pt = utils.spawn_random_point(state)
state[pt[0], pt[1]] = 1
return state
def init(config):
c = config
c['state'] = build_map(config)
if config['start'] == []:
c['start'] = np.array(utils.spawn_random_point(c['initial_state']))
return c