Merge pull request #74 from hh2564/master

Replace random.py with np_random

gym_miniworld/envs/hallway.py

@@ -58,7 +58,7 @@ def _gen_world(self):
 
         # Place the agent a random distance away from the goal
         self.place_agent(
-            dir=self.rand.float(-math.pi / 4, math.pi / 4), max_x=room.max_x - 2
+            dir=self.np_random.uniform(-math.pi / 4, math.pi / 4), max_x=room.max_x - 2
         )
 
     def step(self, action):

gym_miniworld/envs/maze.py

@@ -96,7 +96,14 @@ def visit(i, j):
             visited.add(room)
 
             # Reorder the neighbors to visit in a random order
-            neighbors = self.rand.subset([(0, 1), (0, -1), (-1, 0), (1, 0)], 4)
+            orders = [(0, 1), (0, -1), (-1, 0), (1, 0)]
+            assert 4 <= len(orders)
+            neighbors = []
+
+            while len(neighbors) < 4:
+                elem = orders[self.np_random.choice(len(orders))]
+                orders.remove(elem)
+                neighbors.append(elem)
 
             # For each possible neighbor
             for dj, di in neighbors:

gym_miniworld/envs/pickupobjs.py

@@ -1,6 +1,6 @@
 from gymnasium import spaces
 
-from gym_miniworld.entity import Ball, Box, Key
+from gym_miniworld.entity import COLOR_NAMES, Ball, Box, Key
 from gym_miniworld.miniworld import MiniWorldEnv
 
 
@@ -64,10 +64,11 @@ def _gen_world(self):
         )
 
         obj_types = [Ball, Box, Key]
+        colorlist = list(COLOR_NAMES)
 
         for obj in range(self.num_objs):
-            obj_type = self.rand.choice(obj_types)
-            color = self.rand.color()
+            obj_type = obj_types[self.np_random.choice(len(obj_types))]
+            color = colorlist[self.np_random.choice(len(colorlist))]
 
             if obj_type == Box:
                 self.place_entity(Box(color=color, size=0.9))

gym_miniworld/envs/putnext.py

@@ -52,7 +52,7 @@ def _gen_world(self):
         self.add_rect_room(min_x=0, max_x=self.size, min_z=0, max_z=self.size)
 
         for color in COLOR_NAMES:
-            box = Box(color=color, size=self.rand.float(0.6, 0.85))
+            box = Box(color=color, size=self.np_random.uniform(0.6, 0.85))
             self.place_entity(box)
 
             if box.color == "red":

gym_miniworld/envs/roomobjs.py

@@ -1,6 +1,6 @@
 import math
 
-from gym_miniworld.entity import Ball, Box, Key
+from gym_miniworld.entity import COLOR_NAMES, Ball, Box, Key
 from gym_miniworld.miniworld import MiniWorldEnv
 
 
@@ -64,10 +64,15 @@ def _gen_world(self):
 
         # Reduce chances that objects are too close to see
         self.agent.radius = 1.5
+        colorlist = list(COLOR_NAMES)
 
-        self.place_entity(Box(color=self.rand.color(), size=0.9))
-        self.place_entity(Ball(color=self.rand.color(), size=0.9))
-        self.place_entity(Key(color=self.rand.color()))
+        self.place_entity(
+            Box(color=colorlist[self.np_random.choice(len(colorlist))], size=0.9)
+        )
+        self.place_entity(
+            Ball(color=colorlist[self.np_random.choice(len(colorlist))], size=0.9)
+        )
+        self.place_entity(Key(color=colorlist[self.np_random.choice(len(colorlist))]))
 
         self.place_agent()
 

gym_miniworld/envs/simtorealgoto.py

@@ -61,32 +61,33 @@ def __init__(self, **kwargs):
 
     def _gen_world(self):
         # 1-2 meter wide rink
-        size = self.rand.float(1, 2)
+        size = self.np_random.uniform(1, 2)
 
-        wall_height = self.rand.float(0.20, 0.50)
+        wall_height = self.np_random.uniform(0.20, 0.50)
 
-        box_size = self.rand.float(0.07, 0.12)
+        box_size = self.np_random.uniform(0.07, 0.12)
 
         self.agent.radius = 0.11
 
-        floor_tex = self.rand.choice(
-            [
-                "cardboard",
-                "wood",
-                "wood_planks",
-            ]
-        )
-
-        wall_tex = self.rand.choice(
-            [
-                "drywall",
-                "stucco",
-                "cardboard",
-                # Chosen because they have visible lines/seams
-                "concrete_tiles",
-                "ceiling_tiles",
-            ]
-        )
+        # Randomly choosing floor_tex and wall_tex
+        floor_tex_list = [
+            "cardboard",
+            "wood",
+            "wood_planks",
+        ]
+
+        wall_tex_list = [
+            "drywall",
+            "stucco",
+            "cardboard",
+            # Chosen because they have visible lines/seams
+            "concrete_tiles",
+            "ceiling_tiles",
+        ]
+
+        floor_tex = self.np_random.choice(floor_tex_list)
+
+        wall_tex = self.np_random.choice(wall_tex_list)
 
         # Create a long rectangular room
         self.add_rect_room(

gym_miniworld/envs/simtorealpush.py

@@ -65,31 +65,32 @@ def __init__(self, **kwargs):
 
     def _gen_world(self):
         # Size of the rink the robot is placed in
-        size = self.rand.float(1.6, 1.7)
-        wall_height = self.rand.float(0.42, 0.50)
+        size = self.np_random.uniform(1.6, 1.7)
+        wall_height = self.np_random.uniform(0.42, 0.50)
 
-        box1_size = self.rand.float(0.075, 0.090)
-        box2_size = self.rand.float(0.075, 0.090)
+        box1_size = self.np_random.uniform(0.075, 0.090)
+        box2_size = self.np_random.uniform(0.075, 0.090)
 
         self.agent.radius = 0.11
 
-        floor_tex = self.rand.choice(
-            [
-                "cardboard",
-                "wood",
-                "wood_planks",
-            ]
-        )
-
-        wall_tex = self.rand.choice(
-            [
-                "drywall",
-                "stucco",
-                # Materials chosen because they have visible lines/seams
-                "concrete_tiles",
-                "ceiling_tiles",
-            ]
-        )
+        # Randomly choosing floor_tex and wall_tex
+        floor_tex_list = [
+            "cardboard",
+            "wood",
+            "wood_planks",
+        ]
+
+        wall_tex_list = [
+            "drywall",
+            "stucco",
+            "cardboard",
+            # Chosen because they have visible lines/seams
+            "concrete_tiles",
+            "ceiling_tiles",
+        ]
+        floor_tex = self.np_random.choice(floor_tex_list)
+
+        wall_tex = self.np_random.choice(wall_tex_list)
 
         # Create a long rectangular room
         self.add_rect_room(
@@ -154,7 +155,7 @@ def step(self, action):
                     next_box_pos = box.pos + vec
                     if not self.intersect(box, next_box_pos, box.radius):
                         box.pos = next_box_pos
-                        box.dir += self.rand.float(-math.pi / 5, math.pi / 5)
+                        box.dir += self.np_random.uniform(-math.pi / 5, math.pi / 5)
 
         obs, reward, termination, truncation, info = super().step(action)
 

gym_miniworld/envs/tmaze.py

@@ -66,13 +66,15 @@ def _gen_world(self):
                 max_z=self.goal_pos[2],
             )
         else:
-            if self.rand.bool():
+            if self.np_random.integers(0, 2) == 0:
                 self.place_entity(self.box, room=room2, max_z=room2.min_z + 2)
             else:
                 self.place_entity(self.box, room=room2, min_z=room2.max_z - 2)
 
         # Choose a random room and position to spawn at
-        self.place_agent(dir=self.rand.float(-math.pi / 4, math.pi / 4), room=room1)
+        self.place_agent(
+            dir=self.np_random.uniform(-math.pi / 4, math.pi / 4), room=room1
+        )
 
     def step(self, action):
         obs, reward, termination, truncation, info = super().step(action)

gym_miniworld/envs/ymaze.py

@@ -101,13 +101,15 @@ def _gen_world(self):
                 max_z=self.goal_pos[2],
             )
         else:
-            if self.rand.bool():
+            if self.np_random.integers(0, 2) == 0:
                 self.place_entity(self.box, room=left_arm, max_z=left_arm.min_z + 2.5)
             else:
                 self.place_entity(self.box, room=right_arm, min_z=right_arm.max_z - 2.5)
 
         # Choose a random room and position to spawn at
-        self.place_agent(dir=self.rand.float(-math.pi / 4, math.pi / 4), room=main_arm)
+        self.place_agent(
+            dir=self.np_random.uniform(-math.pi / 4, math.pi / 4), room=main_arm
+        )
 
     def step(self, action):
         obs, reward, termination, truncation, info = super().step(action)

gym_miniworld/miniworld.py

@@ -71,7 +71,6 @@
 from gym_miniworld.math import Y_VEC, intersect_circle_segs
 from gym_miniworld.opengl import FrameBuffer, Texture, drawBox
 from gym_miniworld.params import DEFAULT_PARAMS
-from gym_miniworld.random import RandGen
 
 # Default wall height for room
 DEFAULT_WALL_HEIGHT = 2.74
@@ -550,7 +549,6 @@ def reset(
         This also randomizes many environment parameters (domain randomization)
         """
         super().reset(seed=seed)
-        self.rand = RandGen(seed)
 
         # Step count since episode start
         self.step_count = 0
@@ -572,7 +570,7 @@ def reset(
         self._gen_world()
 
         # Check if domain randomization is enabled or not
-        rand = self.rand if self.domain_rand else None
+        rand = self.np_random if self.domain_rand else None
 
         # Randomize elements of the world (domain randomization)
         self.params.sample_many(
@@ -676,7 +674,7 @@ def step(self, action):
 
         self.step_count += 1
 
-        rand = self.rand if self.domain_rand else None
+        rand = self.np_random if self.domain_rand else None
         fwd_step = self.params.sample(rand, "forward_step")
         fwd_drift = self.params.sample(rand, "forward_drift")
         turn_step = self.params.sample(rand, "turn_step")
@@ -863,22 +861,30 @@ def place_entity(
 
         # If an exact position if specified
         if pos is not None:
-            ent.dir = dir if dir is not None else self.rand.float(-math.pi, math.pi)
+            ent.dir = (
+                dir if dir is not None else self.np_random.uniform(-math.pi, math.pi)
+            )
             ent.pos = pos
             self.entities.append(ent)
             return ent
 
         # Keep retrying until we find a suitable position
         while True:
             # Pick a room, sample rooms proportionally to floor surface area
-            r = room if room else self.rand.choice(self.rooms, probs=self.room_probs)
+            r = (
+                room
+                if room
+                else list(self.rooms)[
+                    self.np_random.choice(len(list(self.rooms)), p=self.room_probs)
+                ]
+            )
 
             # Choose a random point within the square bounding box of the room
             lx = r.min_x if min_x is None else min_x
             hx = r.max_x if max_x is None else max_x
             lz = r.min_z if min_z is None else min_z
             hz = r.max_z if max_z is None else max_z
-            pos = self.rand.float(
+            pos = self.np_random.uniform(
                 low=[lx - ent.radius, 0, lz - ent.radius],
                 high=[hx + ent.radius, 0, hz + ent.radius],
             )
@@ -892,7 +898,7 @@ def place_entity(
                 continue
 
             # Pick a direction
-            d = dir if dir is not None else self.rand.float(-math.pi, math.pi)
+            d = dir if dir is not None else self.np_random.uniform(-math.pi, math.pi)
 
             ent.pos = pos
             ent.dir = d
@@ -965,7 +971,9 @@ def _load_tex(self, tex_name):
         Load a texture, with or without domain randomization
         """
 
-        rand = self.rand if self.params.sample(self.rand, "tex_rand") else None
+        rand = (
+            self.np_random if self.params.sample(self.np_random, "tex_rand") else None
+        )
         return Texture.get(tex_name, rand)
 
     def _gen_static_data(self):
@@ -975,7 +983,9 @@ def _gen_static_data(self):
 
         # Generate the static data for each room
         for room in self.rooms:
-            room._gen_static_data(self.params, self.rand if self.domain_rand else None)
+            room._gen_static_data(
+                self.params, self.np_random if self.domain_rand else None
+            )
 
         # Concatenate the wall segments
         self.wall_segs = np.concatenate([r.wall_segs for r in self.rooms])

gym_miniworld/opengl.py

@@ -134,7 +134,7 @@ def get(self, tex_name, rng=None):
 
         # If domain-randomization is to be used
         if rng:
-            path_idx = rng.int(0, len(paths))
+            path_idx = rng.integers(0, len(paths))
             path = paths[path_idx]
         else:
             path = paths[0]

gym_miniworld/params.py

@@ -93,9 +93,9 @@ def sample(self, rng, name):
             return p.default
 
         if p.type == "float":
-            return rng.float(p.min, p.max)
+            return rng.uniform(p.min, p.max)
         elif p.type == "int":
-            return rng.int(p.min, p.max + 1)
+            return rng.integers(p.min, p.max + 1)
 
         assert False