Docs and linter update

examples/demo_pedestrian.py

@@ -1,6 +1,4 @@
 """Simulate the trained robot and a trained pedestrian."""
-import os
-from pathlib import Path
 
 from stable_baselines3 import PPO
 import loguru

robot_sf/gym_env/reward.py

@@ -52,6 +52,10 @@ def simple_ped_reward(meta: dict, max_episode_step_discount: float=-0.1,
     Parameters:
     meta (dict): Metadata containing information about the pedestrian's current state.
     max_episode_step_discount (float): Discount factor for each step in the episode.
+    ped_coll_penalty (float): Penalty for colliding with a pedestrian.
+    obst_coll_penalty (float): Penalty for colliding with an obstacle.
+    robot_coll_reward (float): Reward for colliding with a robot.
+    robot_at_goal_penalty (float): Penalty if the robot reaches his goal.
 
     Returns:
     float: The calculated reward.
@@ -76,6 +80,7 @@ def simple_ped_reward(meta: dict, max_episode_step_discount: float=-0.1,
     if meta["is_robot_collision"]:
         reward += robot_coll_reward
 
+    # If the robot has reached its goal, apply penalty
     if meta["is_robot_at_goal"]:
         reward += robot_at_goal_penalty
 

robot_sf/nav/occupancy.py

@@ -232,6 +232,35 @@ def is_in_bounds(self, world_x: float, world_y: float) -> bool:
 
 @dataclass
 class EgoPedContinuousOccupancy(ContinuousOccupancy):
+    """
+    A class, which extends the continuous occupancy for the ego pedestrian.
+
+    Attributes
+    ----------
+    width : float
+        The width of the occupancy.
+    height : float
+        The height of the occupancy.
+    get_agent_coords : Callable[[], Vec2D]
+        A function to get the agent coordinates.
+    get_goal_coords : Callable[[], Vec2D]
+        A function to get the goal coordinates.
+    get_obstacle_coords : Callable[[], np.ndarray]
+        A function to get the obstacle coordinates.
+    get_pedestrian_coords : Callable[[], np.ndarray]
+        A function to get the pedestrian coordinates.
+    agent_radius : float, optional
+        The robot radius, by default 1.0.
+    ped_radius : float, optional
+        The pedestrian radius, by default 0.4.
+    goal_radius : float, optional
+        The goal radius, by default 1.0.
+    get_enemy_coords : Optional[Callable[[], Vec2D]]
+        The coordinates of the opposing agent.
+    enemy_radius : optional, float=1.0
+        The radius of the opposing agent.
+    """
+
     get_enemy_coords: Optional[Callable[[], Vec2D]] = None
     enemy_radius: float=1.0
 

robot_sf/render/sim_view.py

@@ -234,7 +234,7 @@ def render(self, state: VisualizableSimState):
         # static objects
         if self.map_def.obstacles:
             self._draw_obstacles()
-        
+
         # debugging objects
         # if self.map_def.robot_routes:
         #     self._draw_robot_routes()
@@ -296,7 +296,7 @@ def _draw_robot(self, pose: RobotPose):
             ROBOT_COLOR,
             self._scale_tuple(pose[0]),
             self.robot_radius * self.scaling)
-        
+
     def _draw_ego_ped(self, pose: PedPose):
         # TODO: display robot with an image instead of a circle
         pygame.draw.circle(
@@ -468,16 +468,16 @@ def _add_text(self, timestep: int, state: VisualizableSimState):
         for i, text in enumerate(text_lines):
             text_render = self.font.render(text, True, TEXT_COLOR)
             text_outline = self.font.render(text, True, TEXT_OUTLINE_COLOR)
-            
+
             pos = (5, i * self.font.get_linesize() + 5)
-            
+
             # Draw text outline
             for dx, dy in [(-1, -1), (-1, 1), (1, -1), (1, 1)]:
                 text_surface.blit(text_outline, (pos[0] + dx, pos[1] + dy))
-            
+
             # Draw main text
             text_surface.blit(text_render, pos)
-        
+
         self.screen.blit(text_surface, self._timestep_text_pos)
 
     def _add_help_text(self):
@@ -496,7 +496,6 @@ def _add_help_text(self):
 
         # Determine max width of the text
         text_surface = self.font.render(text_lines[1], False, TEXT_COLOR)
-        width = text_surface.get_width() + 10
 
         max_width = max(self.font.size(line)[0] for line in text_lines)
         text_height = len(text_lines) * self.font.get_linesize()
@@ -506,13 +505,13 @@ def _add_help_text(self):
         for i, text in enumerate(text_lines):
             text_render = self.font.render(text, True, TEXT_COLOR)
             text_outline = self.font.render(text, True, TEXT_OUTLINE_COLOR)
-            
+
             pos = (5, i * self.font.get_linesize() + 5)
-            
+
             # Draw text outline
             for dx, dy in [(-1, -1), (-1, 1), (1, -1), (1, 1)]:
                 text_surface.blit(text_outline, (pos[0] + dx, pos[1] + dy))
-            
+
             # Draw main text
             text_surface.blit(text_render, pos)
 

robot_sf/sim/simulator.py

@@ -177,6 +177,13 @@ def init_simulators(
 
 @dataclass
 class PedSimulator(Simulator):
+    """
+    A pedestrian simulator, whic extends the base simulator.
+
+    Args:
+        ego_ped (UnicycleDrivePedestrian): The ego pedestrian in the environment.
+
+    """
     ego_ped: UnicycleDrivePedestrian
 
     @property
@@ -246,7 +253,7 @@ def get_proximity_point(self, fixed_point: Tuple[float, float],
 
     def is_obstacle_collision(self, x: float, y: float) -> bool:
         """
-        TODO: copy from occupancy.py
+        TODO: this method is copied from occupancy.py
         """
         if not (0 <= x <= self.map_def.width and 0 <= y <= self.map_def.height):
             return True

scripts/debug_ped_discrete.py

@@ -1,7 +1,4 @@
 """Simulate a hardcoded deterministic policy with four actions."""
-import os
-from pathlib import Path
-from math import pi
 
 from stable_baselines3 import PPO
 import loguru