def __draw_base_img(self):
self._base_img = draw_grid(self._grid_shape[0], self._grid_shape[1], cell_size=CELL_SIZE, fill='white')
for row in range(self._grid_shape[0]):
for col in range(self._grid_shape[1]):
if self.__wall_exists((row, col)):
fill_cell(self._base_img, (row, col), cell_size=CELL_SIZE, fill=WALL_COLOR)
for agent_i, pos in list(self.final_agent_pos.items())[:self.n_agents]:
row, col = pos[0], pos[1]
draw_cell_outline(self._base_img, (row, col), cell_size=CELL_SIZE, fill=AGENT_COLORS[agent_i])
def render(self, mode='human'):
img = copy.copy(self._base_img)
for agent_i in range(self.n_agents):
for neighbour in self.__get_neighbour_coordinates(
self.agent_pos[agent_i]):
fill_cell(img,
neighbour,
cell_size=CELL_SIZE,
fill=AGENT_NEIGHBORHOOD_COLOR,
margin=0.1)
fill_cell(img,
self.agent_pos[agent_i],
cell_size=CELL_SIZE,
fill=AGENT_NEIGHBORHOOD_COLOR,
margin=0.1)
for agent_i in range(self.n_agents):
draw_circle(img,
self.agent_pos[agent_i],
cell_size=CELL_SIZE,
fill=AGENT_COLOR)
write_cell_text(img,
text=str(agent_i + 1),
pos=self.agent_pos[agent_i],
cell_size=CELL_SIZE,
fill='white',
margin=0.4)
for prey_i in range(self.n_preys):
if self._prey_alive[prey_i]:
draw_circle(img,
self.prey_pos[prey_i],
cell_size=CELL_SIZE,
fill=PREY_COLOR)
write_cell_text(img,
text=str(prey_i + 1),
pos=self.prey_pos[prey_i],
cell_size=CELL_SIZE,
fill='white',
margin=0.4)
img = np.asarray(img)
if mode == 'rgb_array':
return img
elif mode == 'human':
from gym.envs.classic_control import rendering
if self.viewer is None:
self.viewer = rendering.SimpleImageViewer()
self.viewer.imshow(img)
return self.viewer.isopen
def render(self, mode='human'):
img = copy.copy(self._base_img)
for agent_i in range(self.n_agents):
for row in range(self.agent_pos[agent_i][0] - 2,
self.agent_pos[agent_i][0] + 3):
fill_cell(img, (row, self.agent_pos[agent_i][1]),
cell_size=CELL_SIZE,
fill=AGENT_COLORS[agent_i])
ball_cells = self.__ball_cells
fill_cell(img,
ball_cells[0],
cell_size=CELL_SIZE,
fill=BALL_HEAD_COLOR)
fill_cell(img,
ball_cells[1],
cell_size=CELL_SIZE,
fill=BALL_TAIL_COLOR)
fill_cell(img,
ball_cells[2],
cell_size=CELL_SIZE,
fill=BALL_TAIL_COLOR)
img = draw_border(img, border_width=2, fill='gray')
img = np.asarray(img)
if mode == 'rgb_array':
return img
elif mode == 'human':
from gym.envs.classic_control import rendering
if self.viewer is None:
self.viewer = rendering.SimpleImageViewer()
self.viewer.imshow(img)
return self.viewer.isopen
def __draw_base_img(self):
# create grid and make everything black
img = draw_grid(self._grid_shape[0],
self._grid_shape[1],
cell_size=CELL_SIZE,
fill=WALL_COLOR)
# draw tracks
for i, row in enumerate(self._full_obs):
for j, col in enumerate(row):
if col == PRE_IDS['empty']:
fill_cell(img, (i, j),
cell_size=CELL_SIZE,
fill='white',
margin=0.05)
return img
def render(self, mode='human'):
for agent_i in range(self.n_agents):
fill_cell(self._base_img, self.agent_pos[agent_i], cell_size=CELL_SIZE, fill='white', margin=0.05)
fill_cell(self._base_img, self.agent_prev_pos[agent_i], cell_size=CELL_SIZE, fill='white', margin=0.05)
draw_circle(self._base_img, self.agent_pos[agent_i], cell_size=CELL_SIZE, fill=AGENT_COLORS[agent_i])
write_cell_text(self._base_img, text=str(agent_i + 1), pos=self.agent_pos[agent_i], cell_size=CELL_SIZE,
fill='white', margin=0.4)
# adds a score board on top of the image
# img = draw_score_board(self._base_img, score=self._total_episode_reward)
# img = np.asarray(img)
img = np.asarray(self._base_img)
if mode == 'rgb_array':
return img
elif mode == 'human':
from gym.envs.classic_control import rendering
if self.viewer is None:
self.viewer = rendering.SimpleImageViewer()
self.viewer.imshow(img)
return self.viewer.isopen
def render(self, mode='human'):
img = copy.copy(self._base_img)
cell_size = (CELL_SIZE, CELL_SIZE / 2)
mask = (
slice(self._agent_view[0], self._agent_view[0] + self._grid_shape[0]),
slice(self._agent_view[1], self._agent_view[1] + self._grid_shape[1]),
)
# Iterate over all grid positions
for pos, agent_strength, tree_strength in self._view_generator(mask):
if tree_strength and agent_strength:
cell_size = (CELL_SIZE, CELL_SIZE / 2)
tree_pos = (pos[0], 2 * pos[1])
agent_pos = (pos[0], 2 * pos[1] + 1)
else:
cell_size = (CELL_SIZE, CELL_SIZE)
tree_pos = agent_pos = (pos[0], pos[1])
if tree_strength != 0:
fill_cell(img, pos=tree_pos, cell_size=cell_size, fill=TREE_COLOR, margin=0.1)
write_cell_text(img, text=str(tree_strength), pos=tree_pos,
cell_size=cell_size, fill='white', margin=0.4)
if agent_strength != 0:
draw_circle(img, pos=agent_pos, cell_size=cell_size, fill=AGENT_COLOR, radius=0.30)
write_cell_text(img, text=str(agent_strength), pos=agent_pos,
cell_size=cell_size, fill='white', margin=0.4)
img = np.asarray(img)
if mode == 'rgb_array':
return img
elif mode == 'human':
from gym.envs.classic_control import rendering
if self._viewer is None:
self._viewer = rendering.SimpleImageViewer()
self._viewer.imshow(img)
return self._viewer.isopen
def __draw_base_img(self):
self._base_img = draw_grid(self._grid_shape[0], self._grid_shape[1], cell_size=CELL_SIZE, fill='white')
for row in range(self._grid_shape[0]):
for col in range(self._grid_shape[1]):
if PRE_IDS['wall'] in self._full_obs[row][col]:
fill_cell(self._base_img, (row, col), cell_size=CELL_SIZE, fill=WALL_COLOR, margin=0.05)
elif PRE_IDS['lemon'] in self._full_obs[row][col]:
fill_cell(self._base_img, (row, col), cell_size=CELL_SIZE, fill=LEMON_COLOR, margin=0.05)
elif PRE_IDS['apple'] in self._full_obs[row][col]:
fill_cell(self._base_img, (row, col), cell_size=CELL_SIZE, fill=APPLE_COLOR, margin=0.05)