chore(dev): update environment and tooling configuration

.envrc

@@ -2,11 +2,18 @@
 
 export DIRENV_WARN_TIMEOUT=20s
 
-eval "$(devenv direnvrc)"
+# 尝试加载 devenv 的 direnv 配置
+if command -v devenv >/dev/null 2>&1; then
+    # 如果存在 devenv
+    eval "$(devenv direnvrc)"
 
-# `use devenv` supports the same options as the `devenv shell` command.
-#
-# To silence all output, use `--quiet`.
-#
-# Example usage: use devenv --quiet --impure --option services.postgres.enable:bool true
-use devenv
+    # `use devenv` 支持和 `devenv shell` 相同的选项
+    # 示例：use devenv --quiet --impure --option services.postgres.enable:bool true
+    use devenv
+else
+    # 如果不存在 devenv，则加载自己的 fallback 配置
+    echo "devenv not found, loading fallback configuration..."
+
+    export UV_PROJECT_ENVIRONMENT="/workspace/envs/mini-nav"
+    export MY_DEV_ENV=1
+fi

.gitignore

@@ -227,3 +227,8 @@ devenv.local.yaml
 
 # pre-commit
 .pre-commit-config.yaml
+
+# syncthing
+.stversions/
+.stfolder/
+.backup/

.justfile

@@ -14,8 +14,40 @@ download:
     ial-jumper-ial-pangyg:/home/ial-pangyg/docker-workspace/projects/mini-nav/outputs .
 
 sync-pkgs:
+    # micromamba env create -f ./environment.yml
     export UV_PROJECT_ENVIRONMENT="/workspace/envs/mini-nav/" && uv sync --inexact
 
 sync-data:
     python -m habitat_sim.utils.datasets_download --uids habitat_test_scenes --data-path data/
     python -m habitat_sim.utils.datasets_download --uids habitat_example_objects --data-path data/
+
+ssh:
+    ssh \
+    -L 127.0.0.1:22001:127.0.0.1:22000 \
+    -R 127.0.0.1:22001:127.0.0.1:22000 \
+    -L 127.0.0.1:8385:127.0.0.1:8384 \
+    -L 127.0.0.1:2718:172.30.0.2:2718 \
+    ial-gpu_workstation_1
+
+docker:
+    docker exec -it docker-ial-pangyg bash
+
+marimo:
+    export UV_PROJECT_ENVIRONMENT="/workspace/envs/mini-nav/" \
+    && uv run marimo edit ./mini-nav/habitat/test.py --host 0.0.0.0 --port 2718
+
+add +packages:
+    uv add {{ packages }} --no-sync
+    just sync-pkgs
+
+remove +packages:
+    uv remove {{ packages }} --no-sync
+    just sync-pkgs
+
+add-dev +packages:
+    uv add {{ packages }} --group dev --no-sync
+    just sync-pkgs
+
+remove-dev +packages:
+    uv remove {{ packages }} --group dev --no-sync
+    just sync-pkgs

.stignore

@@ -0,0 +1,5 @@
+.git
+.jj
+.venv
+.pytest_cache
+.ruff_cache

environment.yml

@@ -2,8 +2,8 @@ name: mini-nav
 channels:
     - pytorch
     - nvidia
-    - conda-forge
     - aihabitat-nightly
+    - conda-forge
 dependencies:
     - python=3.10
     - pip
@@ -15,5 +15,4 @@ dependencies:
     # Toolsets
     - uv
     - just
-    - git
-    - git-lfs
+    - nodejs

mini-nav/habitat/test.py

@@ -1,57 +1,159 @@
-import habitat_sim
-import numpy as np
-import plotly.express as px
+import marimo
 
-# 配置场景
-scene_path = "data/scene_datasets/habitat-test-scenes/skokloster-castle.glb"
-
-sim_cfg = habitat_sim.SimulatorConfiguration()
-sim_cfg.scene_id = scene_path
-sim_cfg.enable_physics = False
-
-# 配置 agent
-agent_cfg = habitat_sim.agent.AgentConfiguration()
-rgb_sensor_spec = habitat_sim.CameraSensorSpec()
-rgb_sensor_spec.uuid = "color_sensor"
-rgb_sensor_spec.sensor_type = habitat_sim.SensorType.COLOR
-rgb_sensor_spec.resolution = [256, 256]
-rgb_sensor_spec.position = [0.0, 1.5, 0.0]
-
-agent_cfg.sensor_specifications = [rgb_sensor_spec]
-
-# 创建 simulator 实例
-cfg = habitat_sim.Configuration(sim_cfg, [agent_cfg])
-sim = habitat_sim.Simulator(cfg)
-
-# 初始化 agent
-agent = sim.initialize_agent(0)
-
-# 设置 agent 初始位置
-agent_state = habitat_sim.AgentState()
-agent_state.position = np.array([0.0, 0.0, 0.0])
-agent.set_state(agent_state)
-
-state = agent.get_state()
-print("位置:", state.position)
-print("旋转四元数:", state.rotation)
-
-observations = sim.get_sensor_observations()
-rgb_image = observations["color_sensor"]  # numpy array
-print("RGB shape:", rgb_image.shape)
+__generated_with = "0.21.1"
+app = marimo.App()
 
 
-# 假设 rgb_image 已经被定义（例如一个 numpy array 或 PIL Image）
-fig = px.imshow(rgb_image)
+@app.cell
+def _():
+    import habitat_sim
+    from habitat_sim import ShortestPath
+    import numpy as np
+    import plotly.express as px
+    from matplotlib import pyplot as plt
 
-# 隐藏坐标轴（等同于 plt.axis("off")）
-fig.update_xaxes(visible=False)
-fig.update_yaxes(visible=False)
+    return ShortestPath, habitat_sim, np, plt
 
-# 去除多余的边距，使图片填满画布
-fig.update_layout(
-    margin=dict(l=0, r=0, t=0, b=0),
-    coloraxis_showscale=False,  # 如果是灰度图或带colorbar，这行可以隐藏色条
-)
 
-# 输出成 PNG 图片
-fig.write_html("outputs/output.html")
+@app.cell
+def _(habitat_sim):
+    # 配置场景
+    scene_path = "data/scene_datasets/habitat-test-scenes/skokloster-castle.glb"
+
+    sim_cfg = habitat_sim.SimulatorConfiguration()
+    sim_cfg.scene_id = scene_path
+    sim_cfg.enable_physics = False
+    return (sim_cfg,)
+
+
+@app.cell
+def _(habitat_sim, sim_cfg):
+    # 配置 agent
+    agent_cfg = habitat_sim.agent.AgentConfiguration()
+    rgb_sensor_spec = habitat_sim.CameraSensorSpec()
+    rgb_sensor_spec.uuid = "color_sensor"
+    rgb_sensor_spec.sensor_type = habitat_sim.SensorType.COLOR
+    rgb_sensor_spec.resolution = [256, 256]
+    rgb_sensor_spec.position = [0.0, 1.5, 0.0]
+
+    agent_cfg.sensor_specifications = [rgb_sensor_spec]
+
+    # 创建 simulator 实例
+    cfg = habitat_sim.Configuration(sim_cfg, [agent_cfg])
+    sim = habitat_sim.Simulator(cfg)
+    return (sim,)
+
+
+@app.cell
+def _(habitat_sim, plt, sim):
+    # 初始化 agent
+    agent = sim.initialize_agent(0)
+
+    # 设置 agent 初始位置：使用可导航点，而不是写死 [0,0,0]
+    agent_state = habitat_sim.AgentState()
+    agent_state.position = sim.pathfinder.get_random_navigable_point()
+    agent.set_state(agent_state)
+
+    state = agent.get_state()
+    print("位置:", state.position)
+    print("旋转四元数:", state.rotation)
+
+    observations = sim.get_sensor_observations()
+    rgb_image = observations["color_sensor"]
+    print("RGB shape:", rgb_image.shape)
+    print("RGB min/max:", rgb_image[..., :3].min(), rgb_image[..., :3].max())
+
+
+    plt.imshow(rgb_image)
+    plt.axis("off")
+    plt.show()
+    return (agent,)
+
+
+@app.cell
+def _(agent, plt, sim):
+    action_names = list(agent.agent_config.action_space.keys())
+    print("可用动作:", action_names)
+
+    # 进行一步移动
+    sim.step("move_forward")
+
+    import random
+    6
+    for i in range(5):
+        action = random.choice(action_names)
+        obs = sim.step(action)
+        rgb = obs["color_sensor"]
+        plt.imshow(rgb)
+        plt.axis("off")
+        plt.show()
+    return
+
+
+@app.cell
+def _(sim):
+    pathfinder = sim.pathfinder
+    print("NavMesh是否加载:", pathfinder.is_loaded)
+    print("可导航面积:", pathfinder.navigable_area)
+    print("场景边界:", pathfinder.get_bounds())
+
+    # 获取随机可导航点
+    rand_point = pathfinder.get_random_navigable_point()
+    print("随机可导航点:", rand_point)
+    return (pathfinder,)
+
+
+@app.cell
+def _(ShortestPath, pathfinder):
+    start = pathfinder.get_random_navigable_point()
+    end = pathfinder.get_random_navigable_point()
+
+    path = ShortestPath()
+    path.requested_start = start
+    path.requested_end = end
+
+    found = pathfinder.find_path(path)
+    print("是否找到路径:", found)
+    print("路径点:", path.points)
+    print("路径长度:", path.geodesic_distance)
+    return path, start
+
+
+@app.cell
+def _(path, pathfinder, plt, sim, start):
+    from habitat.utils.visualizations import maps
+
+    top_down_map = maps.get_topdown_map(
+        pathfinder, height=start[1], meters_per_pixel=0.05
+    )
+
+    # 绘制路径
+    trajectory = [
+        maps.to_grid(p[2], p[0], top_down_map.shape, pathfinder=sim.pathfinder)
+        for p in path.points
+    ]
+    maps.draw_path(top_down_map, trajectory)
+
+    plt.imshow(top_down_map)
+    plt.axis("off")
+    plt.show()
+    return
+
+
+@app.cell
+def _(habitat_sim, np):
+    # 高级控制：连续动作和滑动碰撞
+
+    vel_control = habitat_sim.physics.VelocityControl()
+    vel_control.controlling_lin_vel = True
+    vel_control.lin_vel_is_local = True
+    vel_control.controlling_ang_vel = True
+
+    # 设置线速度和角速度
+    vel_control.linear_velocity = np.array([0, 0, -1.0])  # forward
+    vel_control.angular_velocity = np.array([0, 0.1, 0])  # rotation
+    return
+
+
+if __name__ == "__main__":
+    app.run()

pyproject.toml

@@ -5,12 +5,17 @@ description = "Add your description here"
 readme = "README.md"
 requires-python = ">=3.10"
 dependencies = [
+    "altair>=6.0.0",
     "dash>=3.4.0",
     "dash-ag-grid>=33.3.3",
     "dash-mantine-components>=2.5.1",
     "datasets>=4.5.0",
+    "habitat-baselines>=0.3.320250127",
+    "habitat-lab>=0.3.320250127",
     "httpx[socks]>=0.28.1",
     "lancedb>=0.27.1",
+    "marimo>=0.21.1",
+    "matplotlib>=3.10.8",
     "polars[database,numpy,pandas,pydantic]>=1.37.1",
     "pyarrow>=23.0.0",
     "pydantic>=2.12.5",
@@ -25,6 +30,10 @@ dev = [
     "pip>=26.0.1",
     "pytest>=9.0.2",
     "pytest-mpi>=0.6",
+    "python-lsp-server>=1.14.0",
+    "ruff>=0.15.7",
+    "ty>=0.0.24",
+    "websockets>=16.0",
 ]
 
 [tool.ty.environment]