def adjacent(self, x, y):
up = utils.up(x, y)
down = utils.down(x, y)
left = utils.left(x, y)
right = utils.right(x, y)
ret = []
for x, y in (up, down, left, right):
if x < 0 or x > self.width - 1:
continue
if y < 0 or y > self.height - 1:
continue
ret.append((x, y))
return ret
line_level = env_config["line_level"]
world_im_name = env_config["world_im_name"]
fps = env_config["fps"]
omega = env_config["omega"]
radius = env_config["radius"]
l1 = env_config["l1"]
l2 = env_config["l2"]
shoulder = [im_width//2, D+line_level]
color = tuple(env_config["color"])
thickness = env_config["thickness"]
### Setting objects:
objs = list(sample([(i,j) for i in range(margin, im_width-margin) for j in range(line_level//4, line_level)], N_objs))
theta_d = [atan((shoulder[1]-obj[1])/(obj[0]-shoulder[0]))+pi*int(obj[0]<=shoulder[0]) for obj in objs]
delta_theta_d = [(right(theta_d[idx], theta_d, epsilon), left(theta_d[idx], theta_d, epsilon)) for idx in range(len(theta_d))]
env_config['theta_d'] = theta_d
env_config['delta_theta_d'] = delta_theta_d
### Simulation class and methods:
def draw_world(objs, T, world) -> None:
# cv.line(world, (0, line_level), (im_width, line_level), [255, 255, 255], 1)
for idx, obj in enumerate(objs):
cv.line(world, (int(shoulder[0]+(shoulder[1]-obj[1])/tan(theta_d[idx]-T*delta_theta_d[idx][0])), obj[1]), (int(shoulder[0]+(shoulder[1]-obj[1])/tan(theta_d[idx]+T*delta_theta_d[idx][1])), obj[1]), [0, 0, 255], 1)
cv.circle(world, obj, radius, [0, 255, 0], -1)
class Robot(RetinaAndArm):
from utils import correct_it, game_over, right, wrong, welcome, get_tip
import data
points = 0
asks = 0
total_types = len(data.exercises)
if __name__ == '__main__':
welcome()
while True:
collection = data.exercises[randrange(total_types)]
questions = collection["questions"]
type_of_collection = collection["type"]
question, answers = questions[randrange(len(questions))]
print(question)
get_tip(collection["tip"])
your_answer = input()
if your_answer == "exit":
break
asks += 1
if correct_it(type_of_collection, question, your_answer, answers):
right()
points += 1
else:
wrong(type_of_collection, question, answers)
game_over(asks, points)
l1 = env_config["l1"]
l2 = env_config["l2"]
shoulder = [im_width // 2, D + line_level]
color = tuple(env_config["color"])
thickness = env_config["thickness"]
### Setting objects:
objs = list(
sample([(i, j) for i in range(margin, im_width - margin)
for j in range(line_level // 4, line_level)], N_objs))
theta_d = [
atan((shoulder[1] - obj[1]) / (obj[0] - shoulder[0])) +
pi * int(obj[0] <= shoulder[0]) for obj in objs
]
delta_theta_d = [(right(theta_d[idx], theta_d,
epsilon), left(theta_d[idx], theta_d, epsilon))
for idx in range(len(theta_d))]
env_config['theta_d'] = theta_d
env_config['delta_theta_d'] = delta_theta_d
fourcc = cv.VideoWriter_fourcc(*'XVID')
cap = cv.VideoCapture(0)
out = cv.VideoWriter('simulation_fixed_object.avi', fourcc, fps,
(im_width, im_height))
### Simulation class and methods:
def draw_world(objs, T, world) -> None:
# cv.line(world, (0, line_level), (im_width, line_level), [255, 255, 255], 1)