Merge pull request #4 from TracyYXChen/master

replace random with np random

car_dreamer/carla_four_lane_env.py

@@ -1,5 +1,5 @@
 import numpy as np
-import random
+#import random
 import carla
 
 from .carla_wpt_env import CarlaWptEnv
@@ -20,7 +20,7 @@ class CarlaFourLaneEnv(CarlaWptEnv):
     """
 
     def on_reset(self) -> None:
-        self.ego_src = self._config.lane_start_points[random.randint(0, len(self._config.lane_start_points) - 1)]
+        self.ego_src = self._config.lane_start_points[np.random.randint(0, len(self._config.lane_start_points) - 1)]
         ego_transform = carla.Transform(carla.Location(
             x=self.ego_src[0], y=self.ego_src[1], z=self.ego_src[2]), carla.Rotation(yaw=-90))
         self.ego = self._world.spawn_actor(transform=ego_transform)

car_dreamer/carla_overtake_env.py

@@ -1,6 +1,6 @@
 import carla
 import numpy as np
-import random
+#import random
 import math
 
 from .carla_wpt_env import CarlaWptEnv
@@ -27,10 +27,10 @@ class CarlaOvertakeEnv(CarlaWptEnv):
 
     """
     def on_reset(self) -> None:
-        self.nonego_spawn_point = self._config.nonego_spawn_points[random.randint(0, len(self._config.nonego_spawn_points) - 1)]
+        self.nonego_spawn_point = self._config.nonego_spawn_points[np.random.randint(0, len(self._config.nonego_spawn_points) - 1)]
         nonego_transform = carla.Transform(carla.Location(*self.nonego_spawn_point[:3]), carla.Rotation(*self.nonego_spawn_point[-3:]))
         self.nonego = self._world.spawn_actor(transform=nonego_transform)
-        self.ego_src = self._config.lane_start_points[random.randint(0, len(self._config.lane_start_points) - 1)]
+        self.ego_src = self._config.lane_start_points[np.random.randint(0, len(self._config.lane_start_points) - 1)]
         ego_transform = carla.Transform(carla.Location(x=self.nonego_spawn_point[0], y=self.ego_src[1], z=self.ego_src[2]), carla.Rotation(yaw=-90)) # set x that always behind nonego
         self.ego = self._world.spawn_actor(transform=ego_transform)
 

car_dreamer/carla_stop_sign_env.py

@@ -1,5 +1,5 @@
 import carla
-import random
+#import random
 import time
 import numpy as np
 from .carla_wpt_fixed_env import CarlaWptFixedEnv
@@ -15,8 +15,8 @@ def __init__(self, config):
         super().__init__(config)
 
     def on_reset(self) -> None:
-        random.seed(time.time())
-        random_index = random.randint(0, len(self._config.lane_start_point) - 1)
+        np.random.seed(time.time())
+        random_index = np.random.randint(0, len(self._config.lane_start_point) - 1)
         self.ego_src = self._config.lane_start_point[random_index]
         ego_transform = carla.Transform(carla.Location(*self.ego_src[:3]), carla.Rotation(yaw=self.ego_src[3]))
         self.ego = self._world.spawn_actor(transform=ego_transform)

car_dreamer/carla_traffic_lights_env.py

@@ -1,5 +1,6 @@
 import carla
-import random
+import numpy as np
+#import random
 import time
 from .carla_wpt_fixed_env import CarlaWptFixedEnv
 from .toolkit import FixedPathPlanner
@@ -14,8 +15,8 @@ def __init__(self, config):
         super().__init__(config)
 
     def on_reset(self) -> None:
-        random.seed(time.time())
-        random_index = random.randint(0, len(self._config.lane_start_point) - 1)
+        np.random.seed(time.time())
+        random_index = np.random.randint(0, len(self._config.lane_start_point) - 1)
         self.ego_src = self._config.lane_start_point[random_index]
         ego_transform = carla.Transform(carla.Location(*self.ego_src[:3]), carla.Rotation(yaw=self.ego_src[3]))
         self.ego = self._world.spawn_actor(transform=ego_transform)
@@ -28,8 +29,8 @@ def on_reset(self) -> None:
         traffic_location = carla.Location(*self._config.traffic_locations)
         self.traffic_light = self.find_traffic_light_by_location(traffic_location)
         self.traffic_light.set_state(carla.TrafficLightState.Red)
-        self.red_duration = random.randint(self._config.red_duration[0], self._config.red_duration[1])
-        self.green_duration = random.randint(self._config.green_duration[0], self._config.green_duration[1])
+        self.red_duration = np.random.randint(self._config.red_duration[0], self._config.red_duration[1])
+        self.green_duration = np.random.randint(self._config.green_duration[0], self._config.green_duration[1])
         self.yellow_duration = 10
         self.total_duration = self.red_duration + self.green_duration + self.yellow_duration
 

car_dreamer/carla_wpt_fixed_env.py

@@ -1,5 +1,5 @@
 import carla
-import random
+#import random
 import numpy as np
 from collections import deque
 
@@ -48,7 +48,7 @@ def on_step(self) -> None:
             else:
                 spawn_location = np.array(self._config.flow_spawn_point[:2])
                 nearest_car_location = np.array(get_vehicle_pos(self.actor_flow[-1]))
-                flow_dist = random.uniform(self._config.min_flow_dist,self._config.max_flow_dist)
+                flow_dist = np.random.uniform(self._config.min_flow_dist,self._config.max_flow_dist)
                 if get_location_distance(spawn_location, nearest_car_location) >= flow_dist:
                     spawn = True
         if spawn:

car_dreamer/toolkit/planner/agents/navigation/behavior_agent.py

@@ -8,7 +8,7 @@
 waypoints and avoiding other vehicles. The agent also responds to traffic lights,
 traffic signs, and has different possible configurations. """
 
-import random
+#import random
 import numpy as np
 import carla
 from .basic_agent import BasicAgent

car_dreamer/toolkit/planner/agents/navigation/local_planner.py

@@ -7,8 +7,8 @@
 
 from enum import IntEnum
 from collections import deque
-import random
-
+#import random
+import numpy as np
 import carla
 from .controller import VehiclePIDController
 from ..tools.misc import draw_waypoints, get_speed
@@ -183,7 +183,7 @@ def _compute_next_waypoints(self, k=1):
                 # random choice between the possible options
                 road_options_list = _retrieve_options(
                     next_waypoints, last_waypoint)
-                road_option = random.choice(road_options_list)
+                road_option = np.random.choice(road_options_list)
                 next_waypoint = next_waypoints[road_options_list.index(
                     road_option)]