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Device registry port (#49)
* Update README and MQTTClient for installation instructions and code improvements * feat: 支持local_config启动 add: 增加对crt path的说明，为传入config.py的相对路径 move: web component * add: registry description * add 3d visualization * 完成在main中启动设备可视化 完成在main中启动设备可视化，并输出物料ID：mesh的对应关系resource_model 添加物料模型管理类，遍历物料与resource_model，完成TF数据收集 * 完成TF发布 * 修改模型方向，在yaml中添加变换属性 * 添加物料tf变化时，发送topic到前端 另外修改了物料初始化的方法，防止在tf还未发布时提前建立物料模型与发布话题 * 添加关节发布节点与物料可视化节点进入unilab * 使用json启动plr与3D模型仿真 * feat: node_info_update srv fix: OTDeck cant create * close #12 feat: slave node registry * feat: show machine name fix: host node registry not uploaded * feat: add hplc registry * feat: add hplc registry * fix: hplc status typo * fix: devices/ * 完成启动OT并联动rviz * add 3d visualization * 完成在main中启动设备可视化 完成在main中启动设备可视化，并输出物料ID：mesh的对应关系resource_model 添加物料模型管理类，遍历物料与resource_model，完成TF数据收集 * 完成TF发布 * 修改模型方向，在yaml中添加变换属性 * 添加物料tf变化时，发送topic到前端 另外修改了物料初始化的方法，防止在tf还未发布时提前建立物料模型与发布话题 * 添加关节发布节点与物料可视化节点进入unilab * 使用json启动plr与3D模型仿真 * 完成启动OT并联动rviz * fix: device.class possible null * fix: HPLC additions with online service * fix: slave mode spin not working * fix: slave mode spin not working * 修复rviz位置问题, 修复rviz位置问题, 在无tf变动时减缓发送频率 在backend中添加物料跟随方法 * feat: 多ProtocolNode 允许子设备ID相同 feat: 上报发现的ActionClient feat: Host重启动，通过discover机制要求slaveNode重新注册，实现信息及时上报 * feat: 支持env设置config * fix: running logic * fix: running logic * fix: missing ot * 在main中直接初始化republisher和物料的mesh节点 * 将joint_republisher和resource_mesh_manager添加进 main_slave_run.py中 * Device visualization (#14) * add 3d visualization * 完成在main中启动设备可视化 完成在main中启动设备可视化，并输出物料ID：mesh的对应关系resource_model 添加物料模型管理类，遍历物料与resource_model，完成TF数据收集 * 完成TF发布 * 修改模型方向，在yaml中添加变换属性 * 添加物料tf变化时，发送topic到前端 另外修改了物料初始化的方法，防止在tf还未发布时提前建立物料模型与发布话题 * 添加关节发布节点与物料可视化节点进入unilab * 使用json启动plr与3D模型仿真 * 完成启动OT并联动rviz * add 3d visualization * 完成在main中启动设备可视化 完成在main中启动设备可视化，并输出物料ID：mesh的对应关系resource_model 添加物料模型管理类，遍历物料与resource_model，完成TF数据收集 * 完成TF发布 * 修改模型方向，在yaml中添加变换属性 * 添加物料tf变化时，发送topic到前端 另外修改了物料初始化的方法，防止在tf还未发布时提前建立物料模型与发布话题 * 添加关节发布节点与物料可视化节点进入unilab * 使用json启动plr与3D模型仿真 * 完成启动OT并联动rviz * 修复rviz位置问题, 修复rviz位置问题, 在无tf变动时减缓发送频率 在backend中添加物料跟随方法 * fix: running logic * fix: running logic * fix: missing ot * 在main中直接初始化republisher和物料的mesh节点 * 将joint_republisher和resource_mesh_manager添加进 main_slave_run.py中 --------- Co-authored-by: zhangshixiang <@zhangshixiang> Co-authored-by: wznln <18435084+Xuwznln@users.noreply.github.com> * fix: missing hostname in devices_names fix: upload_file for model file * fix: missing paho-mqtt package bump version to 0.9.0 * fix startup add ResourceCreateFromOuter.action * fix type hint * update actions * update actions * host node add_resource_from_outer fix cmake list * pass device config to device class * add: bind_parent_ids to resource create action fix: message convert string * fix: host node should not be re_discovered * feat: resource tracker support dict * feat: add more necessary params * feat: fix boolean null in registry action data * feat: add outer resource * 编写mesh添加action * feat: append resource * add action * feat: vis 2d for plr * fix * fix: browser on rviz * fix: cloud bridge error fallback to local * fix: salve auto run rviz * 初始化两个plate * Device visualization (#22) * add 3d visualization * 完成在main中启动设备可视化 完成在main中启动设备可视化，并输出物料ID：mesh的对应关系resource_model 添加物料模型管理类，遍历物料与resource_model，完成TF数据收集 * 完成TF发布 * 修改模型方向，在yaml中添加变换属性 * 添加物料tf变化时，发送topic到前端 另外修改了物料初始化的方法，防止在tf还未发布时提前建立物料模型与发布话题 * 添加关节发布节点与物料可视化节点进入unilab * 使用json启动plr与3D模型仿真 * 完成启动OT并联动rviz * add 3d visualization * 完成在main中启动设备可视化 完成在main中启动设备可视化，并输出物料ID：mesh的对应关系resource_model 添加物料模型管理类，遍历物料与resource_model，完成TF数据收集 * 完成TF发布 * 修改模型方向，在yaml中添加变换属性 * 添加物料tf变化时，发送topic到前端 另外修改了物料初始化的方法，防止在tf还未发布时提前建立物料模型与发布话题 * 添加关节发布节点与物料可视化节点进入unilab * 使用json启动plr与3D模型仿真 * 完成启动OT并联动rviz * 修复rviz位置问题, 修复rviz位置问题, 在无tf变动时减缓发送频率 在backend中添加物料跟随方法 * fix: running logic * fix: running logic * fix: missing ot * 在main中直接初始化republisher和物料的mesh节点 * 将joint_republisher和resource_mesh_manager添加进 main_slave_run.py中 * 编写mesh添加action * add action * fix * fix: browser on rviz * fix: cloud bridge error fallback to local * fix: salve auto run rviz * 初始化两个plate --------- Co-authored-by: zhangshixiang <@zhangshixiang> Co-authored-by: wznln <18435084+Xuwznln@users.noreply.github.com> * fix: multi channel * fix: aspirate * fix: aspirate * fix: aspirate * fix: aspirate * 提交 * fix: jobadd * fix: jobadd * fix: msg converter * tijiao * add resource creat easy action * identify debug msg * mq client id * unify liquid_handler definition * Update virtual_device.yaml * 更正了stir和heater的连接方式 * 区分了虚拟仪器中的八通阀和电磁阀，添加了两个阀门的驱动 * 修改了add protocol * 修复了阀门更新版的bug * 修复了添加protocol前缀导致的不能启动的bug * Fix handles * bump version to 0.9.6 * add resource edge upload * update container registry and handles * add virtual_separator virtual_rotavap fix transfer_pump * fix container value add parent_name to edge device id * 大图的问题都修复好了，添加了gassource和vacuum pump的驱动以及注册表 * default resource upload mode is false * 添加了icon的文件名在注册表里面 * 修改了json图中link的格式 * fix resource and edge upload * fix device ports * Fix edge id * 移除device的父节点关联 * separate registry sync and resource_add * 默认不进行注册表报送，通过命令unilabos-register或者增加启动参数 * 完善tip * protocol node不再嵌套显示 * bump version to 0.9.7 新增一个测试PumpTransferProtocol的teststation，亲测可以运行，将八通阀们和转移泵与pump_protocol适配 * protocol node 执行action不应携带自身device id * 添加了一套简易双八通阀工作站JSON，亲测能跑 * 修复了很多protocol，亲测能跑 * 添加了run column和filter through的protocol，亲测能跑 * fix mock_reactor * 修改了大图和小图的json，但是在前端上没看到改变 --------- Co-authored-by: Harvey Que <Q-Query@outlook.com> Co-authored-by: wznln <18435084+Xuwznln@users.noreply.github.com> Co-authored-by: zhangshixiang <@zhangshixiang> Co-authored-by: q434343 <73513873+q434343@users.noreply.github.com> Co-authored-by: Junhan Chang <changjh@pku.edu.cn>
This commit is contained in:
Kongchang Feng
GitHub
@@ -1,5 +1,59 @@
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from typing import List, Dict, Any
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import networkx as nx
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from .pump_protocol import generate_pump_protocol
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def get_vessel_liquid_volume(G: nx.DiGraph, vessel: str) -> float:
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"""
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获取容器中的液体体积
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"""
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if vessel not in G.nodes():
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return 0.0
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vessel_data = G.nodes[vessel].get('data', {})
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liquids = vessel_data.get('liquid', [])
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total_volume = 0.0
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for liquid in liquids:
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if isinstance(liquid, dict) and 'liquid_volume' in liquid:
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total_volume += liquid['liquid_volume']
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return total_volume
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def find_centrifuge_device(G: nx.DiGraph) -> str:
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"""
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查找离心机设备
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"""
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centrifuge_nodes = [node for node in G.nodes()
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if (G.nodes[node].get('class') or '') == 'virtual_centrifuge']
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if centrifuge_nodes:
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return centrifuge_nodes[0]
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raise ValueError("系统中未找到离心机设备")
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def find_centrifuge_vessel(G: nx.DiGraph) -> str:
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"""
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查找离心机专用容器
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"""
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possible_names = [
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"centrifuge_tube",
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"centrifuge_vessel",
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"tube_centrifuge",
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"vessel_centrifuge",
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"centrifuge",
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"tube_15ml",
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"tube_50ml"
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]
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for vessel_name in possible_names:
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if vessel_name in G.nodes():
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return vessel_name
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raise ValueError(f"未找到离心机容器。尝试了以下名称: {possible_names}")
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def generate_centrifuge_protocol(
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G: nx.DiGraph,
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@@ -9,115 +63,223 @@ def generate_centrifuge_protocol(
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temp: float = 25.0
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) -> List[Dict[str, Any]]:
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"""
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生成离心操作的协议序列
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生成离心操作的协议序列，复用 pump_protocol 的成熟算法
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离心流程：
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1. 液体转移：将待离心溶液从源容器转移到离心机容器
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2. 离心操作：执行离心分离
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3. 上清液转移：将离心后的上清液转移回原容器或新容器
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4. 沉淀处理：处理离心沉淀（可选）
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Args:
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G: 有向图，节点为设备和容器
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vessel: 离心容器名称
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G: 有向图，节点为设备和容器，边为流体管道
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vessel: 包含待离心溶液的容器名称
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speed: 离心速度 (rpm)
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time: 离心时间 (秒)
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temp: 温度 (摄氏度，可选)
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temp: 离心温度 (°C)，默认25°C
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Returns:
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List[Dict[str, Any]]: 离心操作的动作序列
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Raises:
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ValueError: 当找不到离心机设备时抛出异常
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ValueError: 当找不到必要的设备时抛出异常
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Examples:
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centrifuge_protocol = generate_centrifuge_protocol(G, "reactor", 5000, 300, 4.0)
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centrifuge_actions = generate_centrifuge_protocol(G, "reaction_mixture", 5000, 600, 4.0)
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"""
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action_sequence = []
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# 查找离心机设备
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centrifuge_nodes = [node for node in G.nodes()
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if G.nodes[node].get('class') == 'virtual_centrifuge']
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print(f"CENTRIFUGE: 开始生成离心协议")
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print(f" - 源容器: {vessel}")
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print(f" - 离心速度: {speed} rpm")
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print(f" - 离心时间: {time}s ({time/60:.1f}分钟)")
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print(f" - 离心温度: {temp}°C")
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if not centrifuge_nodes:
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raise ValueError("没有找到可用的离心机设备")
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# 使用第一个可用的离心机
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centrifuge_id = centrifuge_nodes[0]
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# 验证容器是否存在
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# 验证源容器存在
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if vessel not in G.nodes():
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raise ValueError(f"容器 {vessel} 不存在于图中")
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raise ValueError(f"源容器 '{vessel}' 不存在于系统中")
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# 执行离心操作
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action_sequence.append({
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# 获取源容器中的液体体积
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source_volume = get_vessel_liquid_volume(G, vessel)
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print(f"CENTRIFUGE: 源容器 {vessel} 中有 {source_volume} mL 液体")
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# 查找离心机设备
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try:
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centrifuge_id = find_centrifuge_device(G)
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print(f"CENTRIFUGE: 找到离心机: {centrifuge_id}")
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except ValueError as e:
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raise ValueError(f"无法找到离心机: {str(e)}")
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# 查找离心机容器
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try:
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centrifuge_vessel = find_centrifuge_vessel(G)
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print(f"CENTRIFUGE: 找到离心机容器: {centrifuge_vessel}")
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except ValueError as e:
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raise ValueError(f"无法找到离心机容器: {str(e)}")
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# === 简化的体积计算策略 ===
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if source_volume > 0:
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# 如果能检测到液体体积，使用实际体积的大部分
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transfer_volume = min(source_volume * 0.9, 15.0) # 90%或最多15mL（离心管通常较小）
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print(f"CENTRIFUGE: 检测到液体体积，将转移 {transfer_volume} mL")
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else:
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# 如果检测不到液体体积，默认转移标准量
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transfer_volume = 10.0 # 标准离心管体积
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print(f"CENTRIFUGE: 未检测到液体体积，默认转移 {transfer_volume} mL")
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# === 第一步：将待离心溶液转移到离心机容器 ===
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print(f"CENTRIFUGE: 将 {transfer_volume} mL 溶液从 {vessel} 转移到 {centrifuge_vessel}")
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try:
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# 使用成熟的 pump_protocol 算法进行液体转移
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transfer_to_centrifuge_actions = generate_pump_protocol(
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G=G,
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from_vessel=vessel,
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to_vessel=centrifuge_vessel,
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volume=transfer_volume,
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flowrate=1.0, # 离心转移用慢速，避免气泡
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transfer_flowrate=1.0
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)
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action_sequence.extend(transfer_to_centrifuge_actions)
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except Exception as e:
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raise ValueError(f"无法将溶液转移到离心机: {str(e)}")
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# 转移后等待
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wait_action = {
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"action_name": "wait",
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"action_kwargs": {"time": 5}
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}
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action_sequence.append(wait_action)
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# === 第二步：执行离心操作 ===
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print(f"CENTRIFUGE: 执行离心操作")
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centrifuge_action = {
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"device_id": centrifuge_id,
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"action_name": "centrifuge",
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"action_kwargs": {
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"vessel": vessel,
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"vessel": centrifuge_vessel,
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"speed": speed,
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"time": time,
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"temp": temp
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}
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})
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}
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action_sequence.append(centrifuge_action)
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# 离心后等待系统稳定
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wait_action = {
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"action_name": "wait",
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"action_kwargs": {"time": 10} # 离心后等待稍长，让沉淀稳定
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}
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action_sequence.append(wait_action)
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# === 第三步：将上清液转移回原容器 ===
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print(f"CENTRIFUGE: 将上清液从离心机转移回 {vessel}")
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try:
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# 估算上清液体积（约为转移体积的80% - 假设20%成为沉淀）
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supernatant_volume = transfer_volume * 0.8
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print(f"CENTRIFUGE: 预计上清液体积 {supernatant_volume} mL")
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transfer_back_actions = generate_pump_protocol(
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G=G,
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from_vessel=centrifuge_vessel,
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to_vessel=vessel,
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volume=supernatant_volume,
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flowrate=0.5, # 上清液转移更慢，避免扰动沉淀
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transfer_flowrate=0.5
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)
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action_sequence.extend(transfer_back_actions)
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except Exception as e:
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print(f"CENTRIFUGE: 将上清液转移回容器失败: {str(e)}")
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# === 第四步：清洗离心机容器 ===
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print(f"CENTRIFUGE: 清洗离心机容器")
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try:
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# 查找清洗溶剂
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cleaning_solvent = None
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for solvent in ["flask_water", "flask_ethanol", "flask_acetone"]:
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if solvent in G.nodes():
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cleaning_solvent = solvent
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break
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if cleaning_solvent:
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# 用少量溶剂清洗离心管
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cleaning_volume = 5.0 # 5mL清洗
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print(f"CENTRIFUGE: 用 {cleaning_volume} mL {cleaning_solvent} 清洗")
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# 清洗溶剂加入
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cleaning_actions = generate_pump_protocol(
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G=G,
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from_vessel=cleaning_solvent,
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to_vessel=centrifuge_vessel,
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volume=cleaning_volume,
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flowrate=2.0,
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transfer_flowrate=2.0
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)
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action_sequence.extend(cleaning_actions)
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# 将清洗液转移到废液
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if "waste_workup" in G.nodes():
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waste_actions = generate_pump_protocol(
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G=G,
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from_vessel=centrifuge_vessel,
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to_vessel="waste_workup",
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volume=cleaning_volume,
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flowrate=2.0,
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||||
transfer_flowrate=2.0
|
||||
)
|
||||
action_sequence.extend(waste_actions)
|
||||
|
||||
except Exception as e:
|
||||
print(f"CENTRIFUGE: 清洗步骤失败: {str(e)}")
|
||||
|
||||
print(f"CENTRIFUGE: 生成了 {len(action_sequence)} 个动作")
|
||||
print(f"CENTRIFUGE: 离心协议生成完成")
|
||||
print(f"CENTRIFUGE: 总处理体积: {transfer_volume} mL")
|
||||
|
||||
return action_sequence
|
||||
|
||||
|
||||
def generate_multi_step_centrifuge_protocol(
|
||||
# 便捷函数：常用离心方案
|
||||
def generate_low_speed_centrifuge_protocol(
|
||||
G: nx.DiGraph,
|
||||
vessel: str,
|
||||
steps: List[Dict[str, Any]]
|
||||
time: float = 300.0 # 5分钟
|
||||
) -> List[Dict[str, Any]]:
|
||||
"""
|
||||
生成多步骤离心操作的协议序列
|
||||
|
||||
Args:
|
||||
G: 有向图，节点为设备和容器
|
||||
vessel: 离心容器名称
|
||||
steps: 离心步骤列表，每个步骤包含 speed, time, temp 参数
|
||||
|
||||
Returns:
|
||||
List[Dict[str, Any]]: 多步骤离心操作的动作序列
|
||||
|
||||
Examples:
|
||||
steps = [
|
||||
{"speed": 1000, "time": 60, "temp": 4.0}, # 低速预离心
|
||||
{"speed": 12000, "time": 600, "temp": 4.0} # 高速离心
|
||||
]
|
||||
protocol = generate_multi_step_centrifuge_protocol(G, "reactor", steps)
|
||||
"""
|
||||
action_sequence = []
|
||||
|
||||
# 查找离心机设备
|
||||
centrifuge_nodes = [node for node in G.nodes()
|
||||
if G.nodes[node].get('class') == 'virtual_centrifuge']
|
||||
|
||||
if not centrifuge_nodes:
|
||||
raise ValueError("没有找到可用的离心机设备")
|
||||
|
||||
centrifuge_id = centrifuge_nodes[0]
|
||||
|
||||
# 验证容器是否存在
|
||||
if vessel not in G.nodes():
|
||||
raise ValueError(f"容器 {vessel} 不存在于图中")
|
||||
|
||||
# 执行每个离心步骤
|
||||
for i, step in enumerate(steps):
|
||||
speed = step.get('speed', 5000)
|
||||
time = step.get('time', 300)
|
||||
temp = step.get('temp', 25.0)
|
||||
|
||||
action_sequence.append({
|
||||
"device_id": centrifuge_id,
|
||||
"action_name": "centrifuge",
|
||||
"action_kwargs": {
|
||||
"vessel": vessel,
|
||||
"speed": speed,
|
||||
"time": time,
|
||||
"temp": temp
|
||||
}
|
||||
})
|
||||
|
||||
# 步骤间等待时间（除了最后一步）
|
||||
if i < len(steps) - 1:
|
||||
action_sequence.append({
|
||||
"action_name": "wait",
|
||||
"action_kwargs": {"time": 3}
|
||||
})
|
||||
|
||||
return action_sequence
|
||||
"""低速离心：细胞分离或大颗粒沉淀"""
|
||||
return generate_centrifuge_protocol(G, vessel, 1000.0, time, 4.0)
|
||||
|
||||
|
||||
def generate_high_speed_centrifuge_protocol(
|
||||
G: nx.DiGraph,
|
||||
vessel: str,
|
||||
time: float = 600.0 # 10分钟
|
||||
) -> List[Dict[str, Any]]:
|
||||
"""高速离心：蛋白质沉淀或小颗粒分离"""
|
||||
return generate_centrifuge_protocol(G, vessel, 12000.0, time, 4.0)
|
||||
|
||||
|
||||
def generate_standard_centrifuge_protocol(
|
||||
G: nx.DiGraph,
|
||||
vessel: str,
|
||||
time: float = 600.0 # 10分钟
|
||||
) -> List[Dict[str, Any]]:
|
||||
"""标准离心：常规样品处理"""
|
||||
return generate_centrifuge_protocol(G, vessel, 5000.0, time, 25.0)
|
||||
|
||||
|
||||
def generate_cold_centrifuge_protocol(
|
||||
G: nx.DiGraph,
|
||||
vessel: str,
|
||||
speed: float = 5000.0,
|
||||
time: float = 600.0
|
||||
) -> List[Dict[str, Any]]:
|
||||
"""冷冻离心：热敏感样品处理"""
|
||||
return generate_centrifuge_protocol(G, vessel, speed, time, 4.0)
|
||||
|
||||
|
||||
def generate_ultra_centrifuge_protocol(
|
||||
G: nx.DiGraph,
|
||||
vessel: str,
|
||||
time: float = 1800.0 # 30分钟
|
||||
) -> List[Dict[str, Any]]:
|
||||
"""超高速离心：超细颗粒分离"""
|
||||
return generate_centrifuge_protocol(G, vessel, 15000.0, time, 4.0)
|
||||
Reference in New Issue
Block a user