Merge pull request #8 from kngwyu/no-reward-room

No reward envs, web-based visualizer, and so on

.github/workflows/main.yml

@@ -26,7 +26,7 @@ jobs:
       - name: Install Poetry
         run: pip install poetry
       - name: Install Mujoco Dependencies
-        run: sudo apt install libosmesa6-dev libglfw3 libglew-dev patchelf libgl1-mesa-glx -y
+        run: sudo apt update && sudo apt install libosmesa6-dev libglfw3 libglew-dev patchelf libgl1-mesa-glx -y
       - name: Install Mujoco
         run: |
           mkdir ~/.mujoco

MANIFEST.in

@@ -0,0 +1,2 @@
+include mujoco-maze/static/favicon.ico
+include mujoco-maze/templates/index.html

README.md

@@ -9,14 +9,15 @@ and [openai gym][gym].
 Thankfully, this project is based on the code from  [rllab] and
 [tensorflow/models][models].
 
-Note that [d4rl][d4rl] and [dm_control][dm_control] have similar maze
+Note that [d4rl] and [dm_control] have similar maze
 environments, and you can also check them.
 But, if you want more customizable or minimal one, I recommend this.
 
 ## Usage
 
-Importing `mujoco_maze` registers environments and environments listed
+Importing `mujoco_maze` registers environments and you can load
-below are available via `gym.make`.
+environments by `gym.make`.
+All available environments listed are listed in [Environments] section.
 
 E.g.,:
 ```python
@@ -116,7 +117,7 @@ not tested well.
 
 ## License
 This project is licensed under Apache License, Version 2.0
-([LICENSE-APACHE](LICENSE) or http://www.apache.org/licenses/LICENSE-2.0).
+([LICENSE](LICENSE) or http://www.apache.org/licenses/LICENSE-2.0).
 
 [d4rl]: https://github.com/rail-berkeley/d4rl
 [dm_control]: https://github.com/deepmind/dm_control

mujoco_maze/agent_model.py

@@ -11,7 +11,7 @@ from gym.utils import EzPickle
 class AgentModel(ABC, MujocoEnv, EzPickle):
     FILE: str
     MANUAL_COLLISION: bool
-    ORI_IND: int
+    ORI_IND: Optional[int] = None
     RADIUS: Optional[float] = None
 
     def __init__(self, file_path: str, frame_skip: int) -> None:
@@ -27,16 +27,13 @@ class AgentModel(ABC, MujocoEnv, EzPickle):
 
     @abstractmethod
     def _get_obs(self) -> np.ndarray:
-        """Returns the observation from the model.
+        """Returns the observation from the model."""
-        """
         pass
 
     def get_xy(self) -> np.ndarray:
-        """Returns the coordinate of the agent.
+        """Returns the coordinate of the agent."""
-        """
         pass
 
     def set_xy(self, xy: np.ndarray) -> None:
-        """Set the coordinate of the agent.
+        """Set the coordinate of the agent."""
-        """
         pass

mujoco_maze/ant.py

@@ -82,7 +82,9 @@ class AntEnv(AgentModel):
 
     def reset_model(self):
         qpos = self.init_qpos + self.np_random.uniform(
-            size=self.model.nq, low=-0.1, high=0.1,
+            size=self.model.nq,
+            low=-0.1,
+            high=0.1,
         )
         qvel = self.init_qvel + self.np_random.randn(self.model.nv) * 0.1
 

mujoco_maze/maze_env.py

@@ -10,7 +10,7 @@ import itertools as it
 import os
 import tempfile
 import xml.etree.ElementTree as ET
-from typing import List, Tuple, Type
+from typing import Any, List, Optional, Tuple, Type
 
 import gym
 import numpy as np
@@ -27,25 +27,20 @@ class MazeEnv(gym.Env):
         self,
         model_cls: Type[AgentModel],
         maze_task: Type[maze_task.MazeTask] = maze_task.MazeTask,
-        top_down_view: float = False,
+        include_position: bool = True,
         maze_height: float = 0.5,
         maze_size_scaling: float = 4.0,
         inner_reward_scaling: float = 1.0,
         restitution_coef: float = 0.8,
         task_kwargs: dict = {},
-        *args,
+        websock_port: Optional[int] = None,
         **kwargs,
     ) -> None:
+        self.t = 0  # time steps
         self._task = maze_task(maze_size_scaling, **task_kwargs)
-
-        xml_path = os.path.join(MODEL_DIR, model_cls.FILE)
-        tree = ET.parse(xml_path)
-        worldbody = tree.find(".//worldbody")
-
         self._maze_height = height = maze_height
         self._maze_size_scaling = size_scaling = maze_size_scaling
         self._inner_reward_scaling = inner_reward_scaling
-        self.t = 0  # time steps
         self._observe_blocks = self._task.OBSERVE_BLOCKS
         self._put_spin_near_agent = self._task.PUT_SPIN_NEAR_AGENT
         # Observe other objectives
@@ -70,11 +65,19 @@ class MazeEnv(gym.Env):
             if model_cls.RADIUS is None:
                 raise ValueError("Manual collision needs radius of the model")
             self._collision = maze_env_utils.CollisionDetector(
-                structure, size_scaling, torso_x, torso_y, model_cls.RADIUS,
+                structure,
+                size_scaling,
+                torso_x,
+                torso_y,
+                model_cls.RADIUS,
             )
             # Now all object balls have size=1.0
             self._objball_collision = maze_env_utils.CollisionDetector(
-                structure, size_scaling, torso_x, torso_y, self._task.OBJECT_BALL_SIZE,
+                structure,
+                size_scaling,
+                torso_x,
+                torso_y,
+                self._task.OBJECT_BALL_SIZE,
             )
         else:
             self._collision = None
@@ -86,6 +89,11 @@ class MazeEnv(gym.Env):
         # walls (immovable), chasms (fall), movable blocks
         self._view = np.zeros([5, 5, 3])
 
+        # Let's create MuJoCo XML
+        xml_path = os.path.join(MODEL_DIR, model_cls.FILE)
+        tree = ET.parse(xml_path)
+        worldbody = tree.find(".//worldbody")
+
         height_offset = 0.0
         if self.elevated:
             # Increase initial z-pos of ant.
@@ -141,7 +149,15 @@ class MazeEnv(gym.Env):
                     # Movable block.
                     self.movable_blocks.append(f"movable_{i}_{j}")
                     _add_movable_block(
-                        worldbody, struct, i, j, size_scaling, x, y, h, height_offset,
+                        worldbody,
+                        struct,
+                        i,
+                        j,
+                        size_scaling,
+                        x,
+                        y,
+                        h,
+                        height_offset,
                     )
                 elif struct.is_object_ball():
                     # Movable Ball
@@ -173,8 +189,11 @@ class MazeEnv(gym.Env):
         _, file_path = tempfile.mkstemp(text=True, suffix=".xml")
         tree.write(file_path)
         self.world_tree = tree
-        self.wrapped_env = model_cls(*args, file_path=file_path, **kwargs)
+        self.wrapped_env = model_cls(file_path=file_path, **kwargs)
         self.observation_space = self._get_obs_space()
+        self._websock_port = websock_port
+        self._mj_offscreen_viewer = None
+        self._websock_server_pipe = None
 
     @property
     def has_extended_obs(self) -> bool:
@@ -337,11 +356,32 @@ class MazeEnv(gym.Env):
             self.data.site_xpos[idx][: len(goal.pos)] = goal.pos
 
     @property
-    def viewer(self):
+    def viewer(self) -> Any:
-        return self.wrapped_env.viewer
+        if self._websock_port is not None:
+            return self._mj_viewer
+        else:
+            return self.wrapped_env.viewer
 
-    def render(self, *args, **kwargs):
+    def _render_image(self) -> np.ndarray:
-        return self.wrapped_env.render(*args, **kwargs)
+        self._mj_offscreen_viewer._set_mujoco_buffers()
+        self._mj_offscreen_viewer.render(640, 480)
+        return np.asarray(
+            self._mj_offscreen_viewer.read_pixels(640, 480, depth=False)[::-1, :, :],
+            dtype=np.uint8,
+        )
+
+    def render(self, mode="human", **kwargs) -> Optional[np.ndarray]:
+        if mode == "human" and self._websock_port is not None:
+            if self._mj_offscreen_viewer is None:
+                from mujoco_py import MjRenderContextOffscreen as MjRCO
+
+                from mujoco_maze.websock_viewer import start_server
+
+                self._mj_offscreen_viewer = MjRCO(self.wrapped_env.sim)
+                self._websock_server_pipe = start_server(self._websock_port)
+            self._websock_server_pipe.send(self._render_image())
+        else:
+            return self.wrapped_env.render(mode, **kwargs)
 
     @property
     def action_space(self):
@@ -406,6 +446,8 @@ class MazeEnv(gym.Env):
 
     def close(self) -> None:
         self.wrapped_env.close()
+        if self._websock_server_pipe is not None:
+            self._websock_server_pipe.send(None)
 
 
 def _add_object_ball(
@@ -479,7 +521,10 @@ def _add_movable_block(
         shrink = 1.0
     size = size_scaling * 0.5 * shrink
     movable_body = ET.SubElement(
-        worldbody, "body", name=f"movable_{i}_{j}", pos=f"{x} {y} {h}",
+        worldbody,
+        "body",
+        name=f"movable_{i}_{j}",
+        pos=f"{x} {y} {h}",
     )
     ET.SubElement(
         movable_body,

mujoco_maze/maze_env_utils.py

@@ -13,7 +13,7 @@ from typing import Any, List, Optional, Sequence, Tuple, Union
 import numpy as np
 
 Self = Any
-Point = np.complex
+Point = complex
 
 
 class MazeCell(Enum):
@@ -83,13 +83,15 @@ class MazeCell(Enum):
 
 class Line:
     def __init__(
-        self, p1: Union[Sequence[float], Point], p2: Union[Sequence[float], Point],
+        self,
+        p1: Union[Sequence[float], Point],
+        p2: Union[Sequence[float], Point],
     ) -> None:
-        self.p1 = p1 if isinstance(p1, Point) else np.complex(*p1)
+        self.p1 = p1 if isinstance(p1, Point) else complex(*p1)
-        self.p2 = p2 if isinstance(p2, Point) else np.complex(*p2)
+        self.p2 = p2 if isinstance(p2, Point) else complex(*p2)
         self.v1 = self.p2 - self.p1
-        self.conj_v1 = np.conjugate(self.v1)
+        self.conj_v1 = self.v1.conjugate()
-        self.norm = np.absolute(self.v1)
+        self.norm = abs(self.v1)
 
     def _intersect(self, other: Self) -> bool:
         v2 = other.p1 - self.p1
@@ -98,15 +100,15 @@ class Line:
 
     def _projection(self, p: Point) -> Point:
         nv1 = -self.v1
-        nv1_norm = np.absolute(nv1) ** 2
+        nv1_norm = abs(nv1) ** 2
-        scale = np.real(np.conjugate(p - self.p1) * nv1) / nv1_norm
+        scale = ((p - self.p1).conjugate() * nv1).real / nv1_norm
         return self.p1 + nv1 * scale
 
     def reflection(self, p: Point) -> Point:
         return p + 2.0 * (self._projection(p) - p)
 
     def distance(self, p: Point) -> float:
-        return np.absolute(p - self._projection(p))
+        return abs(p - self._projection(p))
 
     def intersect(self, other: Self) -> Point:
         if self._intersect(other) and other._intersect(self):
@@ -141,8 +143,7 @@ class Collision:
 
 
 class CollisionDetector:
-    """For manual collision detection.
+    """For manual collision detection."""
-    """
 
     EPS: float = 0.05
     NEIGHBORS: List[Tuple[int, int]] = [[0, -1], [-1, 0], [0, 1], [1, 0]]
@@ -197,9 +198,9 @@ class CollisionDetector:
         if len(collisions) == 0:
             return None
         col = collisions[0]
-        dist = np.absolute(col._point - move.p1)
+        dist = abs(col._point - move.p1)
         for collision in collisions[1:]:
-            new_dist = np.absolute(collision._point - move.p1)
+            new_dist = abs(collision._point - move.p1)
             if new_dist < dist:
                 col, dist = collision, new_dist
         return col

mujoco_maze/maze_task.py

@@ -145,6 +145,37 @@ class DistRewardSimpleRoom(GoalRewardSimpleRoom, DistRewardMixIn):
     pass
 
 
+class GoalRewardSquareRoom(GoalRewardUMaze):
+    MAZE_SIZE_SCALING: Scaling = Scaling(4.0, 4.0, 2.0)
+
+    def __init__(self, scale: float, goal: Tuple[float, float] = (1.0, 0.0)) -> None:
+        super().__init__(scale)
+        self.goals = [MazeGoal(np.array(goal) * scale)]
+
+    @staticmethod
+    def create_maze() -> List[List[MazeCell]]:
+        E, B, R = MazeCell.EMPTY, MazeCell.BLOCK, MazeCell.ROBOT
+        return [
+            [B, B, B, B, B],
+            [B, E, E, E, B],
+            [B, E, R, E, B],
+            [B, E, E, E, B],
+            [B, B, B, B, B],
+        ]
+
+
+class NoRewardSquareRoom(GoalRewardSimpleRoom):
+    def __init__(self, scale: float) -> None:
+        super().__init__(scale)
+
+    def reward(self, _obs: np.ndarray) -> float:
+        return 0.0
+
+
+class DistRewardSquareRoom(GoalRewardSquareRoom, DistRewardMixIn):
+    pass
+
+
 class GoalRewardPush(GoalRewardUMaze):
     OBSERVE_BLOCKS: bool = True
 
@@ -329,6 +360,48 @@ class SubGoalTRoom(GoalRewardTRoom):
         )
 
 
+class NoRewardCorridor(MazeTask):
+    REWARD_THRESHOLD: float = 0.0
+    MAZE_SIZE_SCALING: Scaling = Scaling(4.0, 4.0, 1.0)
+
+    def reward(self, _obs: np.ndarray) -> float:
+        return 0.0
+
+    @staticmethod
+    def create_maze() -> List[List[MazeCell]]:
+        E, B, R = MazeCell.EMPTY, MazeCell.BLOCK, MazeCell.ROBOT
+        return [
+            [B, B, B, B, B, B, B, B, B],
+            [B, E, E, B, E, E, E, E, B],
+            [B, E, E, B, E, E, E, E, B],
+            [B, E, E, E, E, E, B, B, B],
+            [B, E, E, E, R, E, E, E, B],
+            [B, B, B, E, E, E, E, E, B],
+            [B, E, E, E, E, B, E, E, B],
+            [B, E, E, E, E, B, E, E, B],
+            [B, B, B, B, B, B, B, B, B],
+        ]
+
+
+class GoalRewardCorridor(NoRewardCorridor):
+    REWARD_THRESHOLD: float = 0.9
+    PENALTY: float = -0.0001
+
+    def __init__(self, scale: float, goal: Tuple[float, float] = (3.0, -3.0)) -> None:
+        super().__init__(scale)
+        self.goals.append(MazeGoal(np.array(goal) * scale))
+
+    def reward(self, obs: np.ndarray) -> float:
+        for goal in self.goals:
+            if goal.neighbor(obs):
+                return goal.reward_scale
+        return self.PENALTY
+
+
+class DistRewardCorridor(GoalRewardCorridor, DistRewardMixIn):
+    pass
+
+
 class GoalRewardBlockMaze(GoalRewardUMaze):
     MAZE_SIZE_SCALING: Scaling = Scaling(8.0, 4.0, None)
     OBSERVE_BLOCKS: bool = True
@@ -406,6 +479,14 @@ class DistRewardBilliard(GoalRewardBilliard):
         return -self.goals[0].euc_dist(obs[3:6]) / self.scale
 
 
+class NoRewardBilliard(GoalRewardBilliard):
+    def __init__(self, scale: float) -> None:
+        MazeTask.__init__(self, scale)
+
+    def reward(self, _obs: np.ndarray) -> float:
+        return 0.0
+
+
 class SubGoalBilliard(GoalRewardBilliard):
     def __init__(
         self,
@@ -453,6 +534,7 @@ class BanditBilliard(SubGoalBilliard):
 class TaskRegistry:
     REGISTRY: Dict[str, List[Type[MazeTask]]] = {
         "SimpleRoom": [DistRewardSimpleRoom, GoalRewardSimpleRoom],
+        "SquareRoom": [DistRewardSquareRoom, GoalRewardSquareRoom, NoRewardSquareRoom],
         "UMaze": [DistRewardUMaze, GoalRewardUMaze],
         "Push": [DistRewardPush, GoalRewardPush],
         "Fall": [DistRewardFall, GoalRewardFall],
@@ -460,11 +542,13 @@ class TaskRegistry:
         "4Rooms": [DistReward4Rooms, GoalReward4Rooms, SubGoal4Rooms],
         "TRoom": [DistRewardTRoom, GoalRewardTRoom, SubGoalTRoom],
         "BlockMaze": [DistRewardBlockMaze, GoalRewardBlockMaze],
+        "Corridor": [DistRewardCorridor, GoalRewardCorridor, NoRewardCorridor],
         "Billiard": [
-            DistRewardBilliard,
+            DistRewardBilliard,  # v0
-            GoalRewardBilliard,
+            GoalRewardBilliard,  # v1
-            SubGoalBilliard,
+            SubGoalBilliard,  # v2
-            BanditBilliard,
+            BanditBilliard,  # v3
+            NoRewardBilliard,  # v4
         ],
     }
 

mujoco_maze/point.py

@@ -22,7 +22,7 @@ class PointEnv(AgentModel):
 
     VELOCITY_LIMITS: float = 10.0
 
-    def __init__(self, file_path: Optional[str] = None):
+    def __init__(self, file_path: Optional[str] = None) -> None:
         super().__init__(file_path, 1)
         high = np.inf * np.ones(6, dtype=np.float32)
         high[3:] = self.VELOCITY_LIMITS * 1.2

mujoco_maze/reacher.py

@@ -1,7 +1,7 @@
 """
 Based on the reacher in `dm_control`_.
 
-.. _gym: https://github.com/openai/gym
+.. _dm_control: https://github.com/deepmind/dm_control
 """
 
 from typing import Tuple
@@ -54,10 +54,14 @@ class ReacherEnv(AgentModel):
 
     def reset_model(self) -> np.ndarray:
         qpos = self.init_qpos + self.np_random.uniform(
-            low=-0.1, high=0.1, size=self.model.nq,
+            low=-0.1,
+            high=0.1,
+            size=self.model.nq,
         )
         qvel = self.init_qvel + self.np_random.uniform(
-            low=-0.1, high=0.1, size=self.model.nv,
+            low=-0.1,
+            high=0.1,
+            size=self.model.nv,
         )
 
         self.set_state(qpos, qvel)

mujoco_maze/swimmer.py

@@ -37,7 +37,6 @@ class SwimmerEnv(AgentModel):
     def step(self, action: np.ndarray) -> Tuple[np.ndarray, float, bool, dict]:
         xy_pos_before = self.sim.data.qpos[:2].copy()
         self.do_simulation(action, self.frame_skip)
-
         forward_reward = self._forward_reward(xy_pos_before)
         ctrl_cost = self._ctrl_cost_weight * np.sum(np.square(action))
         return (
@@ -55,10 +54,14 @@ class SwimmerEnv(AgentModel):
 
     def reset_model(self) -> np.ndarray:
         qpos = self.init_qpos + self.np_random.uniform(
-            low=-0.1, high=0.1, size=self.model.nq,
+            low=-0.1,
+            high=0.1,
+            size=self.model.nq,
         )
         qvel = self.init_qvel + self.np_random.uniform(
-            low=-0.1, high=0.1, size=self.model.nv,
+            low=-0.1,
+            high=0.1,
+            size=self.model.nv,
         )
 
         self.set_state(qpos, qvel)

mujoco_maze/websock_viewer.py

@@ -0,0 +1,116 @@
+import asyncio
+import io
+import multiprocessing as mp
+
+import fastapi
+import uvicorn
+from PIL import Image
+
+
+HTML = """
+<!DOCTYPE html>
+<html>
+  <head>
+    <title>MuJoCo maze visualizer</title>
+  </head>
+  <body>
+    <h2>MuJoCo Maze Visualizer</h2>
+    <script>
+      var ws_image = new WebSocket('ws://127.0.0.1:{{port}}/ws');
+      ws_image.binaryType = "arraybuffer";
+      ws_image.onmessage = function(event) {
+          var canvas = document.getElementById('canvas');
+          var ctx = canvas.getContext('2d');
+          var blob = new Blob([event.data], {type:'image/png'});
+          var url = URL.createObjectURL(blob);
+          var image = new Image();
+          image.onload = function() {
+              ctx.drawImage(image, 0, 0);
+          }
+          console.log(url);
+          image.src = url;
+      }
+      function saveVideo() {
+          var xhr = new XMLHttpRequest();
+          xhr.open('GET', 'https://via.placeholder.com/150', true);
+          xhr.responseType = 'blob';
+          xhr.onerror = err => {
+              alert('Video is not ready');
+          };
+          xhr.send();
+       }
+    </script>
+    <div>
+      <canvas id="canvas" width="600" height="480"></canvas>
+    </div>
+    <a href="video">Video</a>
+  </body>
+</html>
+"""
+
+
+class _ServerWorker(mp.Process):
+    def __init__(self, pipe: mp.connection.Pipe, port: int) -> None:
+        super().__init__()
+        self.pipe = pipe
+        self.port = port
+        self.video_frames = []
+
+    def _run_server(self) -> None:
+
+        app = fastapi.FastAPI()
+        html = HTML.replace("{{port}}", str(self.port))
+
+        @app.get("/")
+        async def root():
+            return fastapi.responses.HTMLResponse(html)
+
+        server = None
+
+        @app.websocket("/ws")
+        async def ws(websocket: fastapi.WebSocket):
+            await websocket.accept()
+            loop = asyncio.get_running_loop()
+            while True:
+                image_array = await loop.run_in_executor(None, self.pipe.recv)
+                if image_array is None:
+                    break
+                self.video_frames.append(image_array)
+                image = Image.fromarray(image_array)
+                with io.BytesIO() as stream:
+                    image.save(stream, format="png")
+                    res = stream.getvalue()
+                    await websocket.send_bytes(res)
+            await websocket.close()
+            server.should_exit = True
+
+        @app.get("/video")
+        async def video():
+            import imageio
+
+            writer = imageio.get_writer("/tmp/mujoco-maze-video.mp4")
+            for frame in self.video_frames:
+                writer.append_data(frame)
+            writer.close()
+            video = open("/tmp/mujoco-maze-video.mp4", mode="rb")
+            return fastapi.responses.StreamingResponse(video, media_type="video/mp4")
+
+        config = uvicorn.Config(app, port=self.port)
+        server = uvicorn.Server(config)
+        server.run()
+
+    def run(self) -> None:
+        try:
+            self._run_server()
+        except KeyboardInterrupt:
+            pass
+        except Exception as e:
+            print("Exception in websocket server")
+            raise e
+
+
+def start_server(port: int) -> mp.connection.Connection:
+    mainproc_pipe, server_pipe = mp.Pipe()
+    worker = _ServerWorker(server_pipe, port)
+    worker.start()
+    return mainproc_pipe

poetry.lock

@@ -1,117 +1,109 @@
 [[package]]
-category = "dev"
-description = "Atomic file writes."
 name = "atomicwrites"
+version = "1.4.0"
+description = "Atomic file writes."
+category = "dev"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
-version = "1.4.0"
 
 [[package]]
-category = "dev"
-description = "Classes Without Boilerplate"
 name = "attrs"
+version = "21.2.0"
+description = "Classes Without Boilerplate"
+category = "dev"
 optional = false
-python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
-version = "20.2.0"
 
 [package.extras]
-dev = ["coverage (>=5.0.2)", "hypothesis", "pympler", "pytest (>=4.3.0)", "six", "zope.interface", "sphinx", "sphinx-rtd-theme", "pre-commit"]
+dev = ["coverage[toml] (>=5.0.2)", "hypothesis", "pympler", "pytest (>=4.3.0)", "six", "mypy", "pytest-mypy-plugins", "zope.interface", "furo", "sphinx", "sphinx-notfound-page", "pre-commit"]
-docs = ["sphinx", "sphinx-rtd-theme", "zope.interface"]
+docs = ["furo", "sphinx", "zope.interface", "sphinx-notfound-page"]
-tests = ["coverage (>=5.0.2)", "hypothesis", "pympler", "pytest (>=4.3.0)", "six", "zope.interface"]
+tests = ["coverage[toml] (>=5.0.2)", "hypothesis", "pympler", "pytest (>=4.3.0)", "six", "mypy", "pytest-mypy-plugins", "zope.interface"]
-tests_no_zope = ["coverage (>=5.0.2)", "hypothesis", "pympler", "pytest (>=4.3.0)", "six"]
+tests_no_zope = ["coverage[toml] (>=5.0.2)", "hypothesis", "pympler", "pytest (>=4.3.0)", "six", "mypy", "pytest-mypy-plugins"]
 
 [[package]]
-category = "main"
-description = "Foreign Function Interface for Python calling C code."
 name = "cffi"
+version = "1.14.5"
+description = "Foreign Function Interface for Python calling C code."
+category = "main"
 optional = false
 python-versions = "*"
-version = "1.14.3"
 
 [package.dependencies]
 pycparser = "*"
 
 [[package]]
-category = "main"
-description = "Extended pickling support for Python objects"
 name = "cloudpickle"
+version = "1.6.0"
+description = "Extended pickling support for Python objects"
+category = "main"
 optional = false
 python-versions = ">=3.5"
-version = "1.6.0"
 
 [[package]]
-category = "dev"
-description = "Cross-platform colored terminal text."
-marker = "sys_platform == \"win32\""
 name = "colorama"
+version = "0.4.4"
+description = "Cross-platform colored terminal text."
+category = "dev"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
-version = "0.4.3"
 
 [[package]]
-category = "main"
-description = "The Cython compiler for writing C extensions for the Python language."
 name = "cython"
+version = "0.29.23"
+description = "The Cython compiler for writing C extensions for the Python language."
+category = "main"
 optional = false
 python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*"
-version = "0.29.21"
 
 [[package]]
-category = "main"
-description = "A python package that provides useful locks."
 name = "fasteners"
+version = "0.16"
+description = "A python package that provides useful locks."
+category = "main"
 optional = false
 python-versions = "*"
-version = "0.15"
 
 [package.dependencies]
-monotonic = ">=0.1"
 six = "*"
 
 [[package]]
-category = "main"
-description = "Clean single-source support for Python 3 and 2"
-name = "future"
-optional = false
-python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*"
-version = "0.18.2"
-
-[[package]]
-category = "main"
-description = "A ctypes-based wrapper for GLFW3."
 name = "glfw"
+version = "2.1.0"
+description = "A ctypes-based wrapper for GLFW3."
+category = "main"
 optional = false
 python-versions = "*"
-version = "2.0.0"
 
 [[package]]
-category = "main"
-description = "The OpenAI Gym: A toolkit for developing and comparing your reinforcement learning agents."
 name = "gym"
+version = "0.18.3"
+description = "The OpenAI Gym: A toolkit for developing and comparing your reinforcement learning agents."
+category = "main"
 optional = false
-python-versions = ">=3.5"
+python-versions = ">=3.6"
-version = "0.17.3"
 
 [package.dependencies]
 cloudpickle = ">=1.2.0,<1.7.0"
 numpy = ">=1.10.4"
-pyglet = ">=1.4.0,<=1.5.0"
+Pillow = "<=8.2.0"
+pyglet = ">=1.4.0,<=1.5.15"
 scipy = "*"
 
 [package.extras]
-all = ["atari_py (>=0.2.0,<0.3.0)", "pillow", "opencv-python", "box2d-py (>=2.3.5,<2.4.0)", "mujoco_py (>=1.50,<2.0)", "imageio", "mujoco_py (>=1.50,<2.0)", "imageio"]
+all = ["box2d-py (>=2.3.5,<2.4.0)", "opencv-python (>=3)", "imageio", "atari_py (>=0.2.0,<0.3.0)", "mujoco_py (>=1.50,<2.0)"]
-atari = ["atari_py (>=0.2.0,<0.3.0)", "pillow", "opencv-python"]
+atari = ["atari_py (>=0.2.0,<0.3.0)", "opencv-python (>=3)"]
 box2d = ["box2d-py (>=2.3.5,<2.4.0)"]
 mujoco = ["mujoco_py (>=1.50,<2.0)", "imageio"]
+nomujoco = ["box2d-py (>=2.3.5,<2.4.0)", "opencv-python (>=3)", "atari_py (>=0.2.0,<0.3.0)"]
 robotics = ["mujoco_py (>=1.50,<2.0)", "imageio"]
 
 [[package]]
-category = "main"
-description = "Library for reading and writing a wide range of image, video, scientific, and volumetric data formats."
 name = "imageio"
+version = "2.9.0"
+description = "Library for reading and writing a wide range of image, video, scientific, and volumetric data formats."
+category = "main"
 optional = false
 python-versions = ">=3.5"
-version = "2.9.0"
 
 [package.dependencies]
 numpy = "*"
@@ -125,165 +117,191 @@ gdal = ["gdal"]
 itk = ["itk"]
 
 [[package]]
-category = "dev"
-description = "Read metadata from Python packages"
-marker = "python_version < \"3.8\""
 name = "importlib-metadata"
+version = "4.4.0"
+description = "Read metadata from Python packages"
+category = "dev"
 optional = false
-python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,>=2.7"
+python-versions = ">=3.6"
-version = "2.0.0"
 
 [package.dependencies]
+typing-extensions = {version = ">=3.6.4", markers = "python_version < \"3.8\""}
 zipp = ">=0.5"
 
 [package.extras]
-docs = ["sphinx", "rst.linker"]
+docs = ["sphinx", "jaraco.packaging (>=8.2)", "rst.linker (>=1.9)"]
-testing = ["packaging", "pep517", "importlib-resources (>=1.3)"]
+testing = ["pytest (>=4.6)", "pytest-checkdocs (>=2.4)", "pytest-flake8", "pytest-cov", "pytest-enabler (>=1.0.1)", "packaging", "pep517", "pyfakefs", "flufl.flake8", "pytest-black (>=0.3.7)", "pytest-mypy", "importlib-resources (>=1.3)"]
 
 [[package]]
-category = "main"
+name = "iniconfig"
-description = "An implementation of time.monotonic() for Python 2 & < 3.3"
+version = "1.1.1"
-name = "monotonic"
+description = "iniconfig: brain-dead simple config-ini parsing"
+category = "dev"
 optional = false
 python-versions = "*"
-version = "1.5"
 
 [[package]]
-category = "dev"
-description = "More routines for operating on iterables, beyond itertools"
-name = "more-itertools"
-optional = false
-python-versions = ">=3.5"
-version = "8.5.0"
-
-[[package]]
-category = "main"
-description = ""
 name = "mujoco-py"
+version = "2.0.2.13"
+description = ""
+category = "main"
 optional = false
 python-versions = ">=3.6"
-version = "2.0.2.13"
 
 [package.dependencies]
-Cython = ">=0.27.2"
 cffi = ">=1.10"
+Cython = ">=0.27.2"
 fasteners = ">=0.15,<1.0"
 glfw = ">=1.4.0"
 imageio = ">=2.1.2"
 numpy = ">=1.11"
 
 [[package]]
-category = "main"
-description = "NumPy is the fundamental package for array computing with Python."
 name = "numpy"
+version = "1.19.5"
+description = "NumPy is the fundamental package for array computing with Python."
+category = "main"
 optional = false
 python-versions = ">=3.6"
-version = "1.19.2"
-
-[[package]]
-category = "main"
-description = "Python Imaging Library (Fork)"
-name = "pillow"
-optional = false
-python-versions = ">=3.5"
-version = "7.2.0"
 
 [[package]]
+name = "packaging"
+version = "20.9"
+description = "Core utilities for Python packages"
 category = "dev"
-description = "plugin and hook calling mechanisms for python"
-name = "pluggy"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
-version = "0.13.1"
 
 [package.dependencies]
-[package.dependencies.importlib-metadata]
+pyparsing = ">=2.0.2"
-python = "<3.8"
+
-version = ">=0.12"
+[[package]]
+name = "pillow"
+version = "8.2.0"
+description = "Python Imaging Library (Fork)"
+category = "main"
+optional = false
+python-versions = ">=3.6"
+
+[[package]]
+name = "pluggy"
+version = "0.13.1"
+description = "plugin and hook calling mechanisms for python"
+category = "dev"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
+
+[package.dependencies]
+importlib-metadata = {version = ">=0.12", markers = "python_version < \"3.8\""}
 
 [package.extras]
 dev = ["pre-commit", "tox"]
 
 [[package]]
-category = "dev"
-description = "library with cross-python path, ini-parsing, io, code, log facilities"
 name = "py"
+version = "1.10.0"
+description = "library with cross-python path, ini-parsing, io, code, log facilities"
+category = "dev"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
-version = "1.9.0"
 
 [[package]]
-category = "main"
-description = "C parser in Python"
 name = "pycparser"
+version = "2.20"
+description = "C parser in Python"
+category = "main"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
-version = "2.20"
 
 [[package]]
-category = "main"
-description = "Cross-platform windowing and multimedia library"
 name = "pyglet"
+version = "1.5.15"
+description = "Cross-platform windowing and multimedia library"
+category = "main"
 optional = false
 python-versions = "*"
-version = "1.5.0"
-
-[package.dependencies]
-future = "*"
 
 [[package]]
+name = "pyparsing"
+version = "2.4.7"
+description = "Python parsing module"
 category = "dev"
-description = "pytest: simple powerful testing with Python"
-name = "pytest"
 optional = false
-python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
+python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*"
-version = "3.10.1"
-
-[package.dependencies]
-atomicwrites = ">=1.0"
-attrs = ">=17.4.0"
-colorama = "*"
-more-itertools = ">=4.0.0"
-pluggy = ">=0.7"
-py = ">=1.5.0"
-setuptools = "*"
-six = ">=1.10.0"
 
 [[package]]
-category = "main"
+name = "pytest"
-description = "SciPy: Scientific Library for Python"
+version = "6.2.4"
-name = "scipy"
+description = "pytest: simple powerful testing with Python"
+category = "dev"
+optional = false
+python-versions = ">=3.6"
+
+[package.dependencies]
+atomicwrites = {version = ">=1.0", markers = "sys_platform == \"win32\""}
+attrs = ">=19.2.0"
+colorama = {version = "*", markers = "sys_platform == \"win32\""}
+importlib-metadata = {version = ">=0.12", markers = "python_version < \"3.8\""}
+iniconfig = "*"
+packaging = "*"
+pluggy = ">=0.12,<1.0.0a1"
+py = ">=1.8.2"
+toml = "*"
+
+[package.extras]
+testing = ["argcomplete", "hypothesis (>=3.56)", "mock", "nose", "requests", "xmlschema"]
+
+[[package]]
+name = "scipy"
+version = "1.5.4"
+description = "SciPy: Scientific Library for Python"
+category = "main"
 optional = false
 python-versions = ">=3.6"
-version = "1.5.2"
 
 [package.dependencies]
 numpy = ">=1.14.5"
 
 [[package]]
-category = "main"
-description = "Python 2 and 3 compatibility utilities"
 name = "six"
+version = "1.16.0"
+description = "Python 2 and 3 compatibility utilities"
+category = "main"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*"
-version = "1.15.0"
 
 [[package]]
+name = "toml"
+version = "0.10.2"
+description = "Python Library for Tom's Obvious, Minimal Language"
 category = "dev"
-description = "Backport of pathlib-compatible object wrapper for zip files"
+optional = false
-marker = "python_version < \"3.8\""
+python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*"
+
+[[package]]
+name = "typing-extensions"
+version = "3.10.0.0"
+description = "Backported and Experimental Type Hints for Python 3.5+"
+category = "dev"
+optional = false
+python-versions = "*"
+
+[[package]]
 name = "zipp"
+version = "3.4.1"
+description = "Backport of pathlib-compatible object wrapper for zip files"
+category = "dev"
 optional = false
 python-versions = ">=3.6"
-version = "3.3.0"
 
 [package.extras]
-docs = ["sphinx", "jaraco.packaging (>=3.2)", "rst.linker (>=1.9)"]
+docs = ["sphinx", "jaraco.packaging (>=8.2)", "rst.linker (>=1.9)"]
-testing = ["pytest (>=3.5,<3.7.3 || >3.7.3)", "pytest-checkdocs (>=1.2.3)", "pytest-flake8", "pytest-cov", "jaraco.test (>=3.2.0)", "jaraco.itertools", "func-timeout", "pytest-black (>=0.3.7)", "pytest-mypy"]
+testing = ["pytest (>=4.6)", "pytest-checkdocs (>=1.2.3)", "pytest-flake8", "pytest-cov", "pytest-enabler", "jaraco.itertools", "func-timeout", "pytest-black (>=0.3.7)", "pytest-mypy"]
 
 [metadata]
-content-hash = "7ae1ca698619b46069b373d39e9b71110d4d71c3d9b4b97b7e22f6a80abe47f6"
+lock-version = "1.1"
-python-versions = "^3.6"  # Compatible python versions must be declared here
+python-versions = ">=3.6"  # Compatible python versions must be declared here
+content-hash = "7ee84c79fcf3f786abecf596c63f654e3b635b34a139b01835b0e503983fdbd5"
 
 [metadata.files]
 atomicwrites = [
@@ -291,229 +309,277 @@ atomicwrites = [
     {file = "atomicwrites-1.4.0.tar.gz", hash = "sha256:ae70396ad1a434f9c7046fd2dd196fc04b12f9e91ffb859164193be8b6168a7a"},
 ]
 attrs = [
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+    {file = "attrs-21.2.0-py2.py3-none-any.whl", hash = "sha256:149e90d6d8ac20db7a955ad60cf0e6881a3f20d37096140088356da6c716b0b1"},
-    {file = "attrs-20.2.0.tar.gz", hash = "sha256:26b54ddbbb9ee1d34d5d3668dd37d6cf74990ab23c828c2888dccdceee395594"},
+    {file = "attrs-21.2.0.tar.gz", hash = "sha256:ef6aaac3ca6cd92904cdd0d83f629a15f18053ec84e6432106f7a4d04ae4f5fb"},
 ]
 cffi = [
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+    {file = "cffi-1.14.5-cp27-cp27m-macosx_10_9_x86_64.whl", hash = "sha256:bb89f306e5da99f4d922728ddcd6f7fcebb3241fc40edebcb7284d7514741991"},
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pyproject.toml

@@ -10,12 +10,12 @@ repository = "https://github.com/kngwyu/mujoco-maze"
 homepage = "https://github.com/kngwyu/mujoco-maze"
 
 [tool.poetry.dependencies]
-python = ">=3.6.1"  # Compatible python versions must be declared here
+python = ">=3.6"  # Compatible python versions must be declared here
 gym = ">=0.16"
 mujoco-py = ">=1.5"
 
 [tool.poetry.dev-dependencies]
-pytest = "^3.0"
+pytest = "^6.2"
 
 [tool.poetry.scripts]
 test = "pytest:main"

tests/test_intersect.py

@@ -13,7 +13,7 @@ from mujoco_maze.maze_env_utils import Line
 )
 def test_distance(l1, l2, p, ans):
     line = Line(l1, l2)
-    point = np.complex(*p)
+    point = complex(*p)
     assert abs(line.distance(point) - ans) <= 1e-8