56 lines
2.1 KiB
Python
56 lines
2.1 KiB
Python
from setuptools import setup, find_packages
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import os
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from glob import glob
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package_name = 'soft_arm_sim'
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setup(
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name=package_name,
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version='0.0.0',
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# 自动查找所有包含 __init__.py 的子包
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packages=find_packages(exclude=['test']),
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data_files=[
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('share/ament_index/resource_index/packages',
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['resource/' + package_name]),
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('share/' + package_name, ['package.xml']),
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# 1. 安装 launch 文件
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(os.path.join('share', package_name, 'launch'), glob('launch/*.launch.py')),
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# 2. 安装 urdf 文件 (非常重要，否则 robot_state_publisher 找不到模型)
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(os.path.join('share', package_name, 'urdf'), glob('urdf/*')),
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# 3. 配置文件安装
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(os.path.join('share', package_name, 'config'), glob('config/*.yaml')),
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],
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install_requires=['setuptools'],
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zip_safe=True,
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maintainer='mio',
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maintainer_email='user@todo.todo',
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description='Soft Robot Arm Simulation',
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license='TODO: License declaration',
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tests_require=['pytest'],
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entry_points={
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'console_scripts': [
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# 格式: '可执行文件名 = 包名.路径.文件名:函数名'
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# 仿真核心节点 (对应 base/simulation_node.py 中的 main 函数)
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'simulator = soft_arm_sim.base.simulation_node:main',
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# 测试控制器 (对应 control/test_controller.py 中的 main 函数)
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'sine_controller = soft_arm_sim.control.test_controller:main',
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# 数据生成
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'generate_data = soft_arm_sim.deeplearning.dataset_generator:main',
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# 训练脚本 (可选，一般直接用 python 跑也行)
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'train_model = soft_arm_sim.deeplearning.train:train_model',
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# 推理控制节点
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'pinn_controller = soft_arm_sim.deeplearning.inference_node:main',
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# 注意路径变化：soft_arm_sim.deeplearning.inference.inference_node
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'inference_node = soft_arm_sim.deeplearning.inference.inference_node:main',
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],
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},
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) |