167 lines
5.5 KiB
Python
167 lines
5.5 KiB
Python
from collections import defaultdict, deque
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from functools import lru_cache
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import time
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from typing import Any
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from app.services.tjnetwork import (
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get_network_link_nodes,
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is_node,
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get_link_properties,
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)
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VALVE_LINK_TYPE = "valve"
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def _parse_link_entry(link_entry: str) -> tuple[str, str, str, str]:
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parts = link_entry.split(":", 3)
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if len(parts) != 4:
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raise ValueError(f"Invalid link entry format: {link_entry}")
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return parts[0], parts[1], parts[2], parts[3]
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@lru_cache(maxsize=16)
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def _get_network_topology(network: str):
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"""
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解析并缓存网络拓扑，大幅减少重复的 API 调用和字符串解析开销。
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返回:
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- pipe_adj: 永久连通的管道/泵邻接表 (dict[str, set])
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- all_valves: 所有阀门字典 {id: (n1, n2)}
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- link_lookup: 链路快速查表 {id: (n1, n2, type)} 用于快速定位事故点
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- node_set: 所有已知节点集合
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"""
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pipe_adj = defaultdict(set)
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all_valves = {}
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link_lookup = {}
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node_set = set()
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# 此处假设 get_network_link_nodes 获取全网数据
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for link_entry in get_network_link_nodes(network):
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link_id, link_type, node1, node2 = _parse_link_entry(link_entry)
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link_type_name = str(link_type).lower()
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link_lookup[link_id] = (node1, node2, link_type_name)
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node_set.add(node1)
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node_set.add(node2)
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if link_type_name == VALVE_LINK_TYPE:
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all_valves[link_id] = (node1, node2)
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else:
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# 只有非阀门（管道/泵）才进入永久连通图
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pipe_adj[node1].add(node2)
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pipe_adj[node2].add(node1)
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return pipe_adj, all_valves, link_lookup, node_set
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def valve_isolation_analysis(
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network: str, accident_elements: str | list[str], disabled_valves: list[str] = None
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) -> dict[str, Any]:
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"""
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关阀搜索/分析：基于拓扑结构确定事故隔离所需关阀。
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:param network: 模型名称
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:param accident_elements: 事故点（节点或管道/泵/阀门ID），可以是单个ID字符串或ID列表
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:param disabled_valves: 故障/无法关闭的阀门ID列表
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:return: dict，包含受影响节点、必须关闭阀门、可选阀门等信息
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"""
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if disabled_valves is None:
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disabled_valves_set = set()
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else:
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disabled_valves_set = set(disabled_valves)
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if isinstance(accident_elements, str):
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target_elements = [accident_elements]
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else:
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target_elements = accident_elements
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# 1. 获取缓存拓扑 (极快，无 IO)
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pipe_adj, all_valves, link_lookup, node_set = _get_network_topology(network)
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# 2. 确定起点，优先查表避免 API 调用
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start_nodes = set()
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for element in target_elements:
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if element in node_set:
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start_nodes.add(element)
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elif element in link_lookup:
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n1, n2, _ = link_lookup[element]
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start_nodes.add(n1)
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start_nodes.add(n2)
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else:
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# 仅当缓存中没找到时（极少见），才回退到慢速 API
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if is_node(network, element):
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start_nodes.add(element)
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else:
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props = get_link_properties(network, element)
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n1, n2 = props.get("node1"), props.get("node2")
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if n1 and n2:
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start_nodes.add(n1)
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start_nodes.add(n2)
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else:
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raise ValueError(
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f"Accident element {element} invalid or missing endpoints"
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)
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# 3. 处理故障阀门 (构建临时增量图)
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# 我们不修改 cached pipe_adj，而是建立一个 extra_adj
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extra_adj = defaultdict(list)
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boundary_valves = {} # 当前有效的边界阀门
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for vid, (n1, n2) in all_valves.items():
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if vid in disabled_valves_set:
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# 故障阀门：视为连通管道
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extra_adj[n1].append(n2)
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extra_adj[n2].append(n1)
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else:
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# 正常阀门：视为潜在边界
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boundary_valves[vid] = (n1, n2)
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# 4. BFS 搜索 (叠加 pipe_adj 和 extra_adj)
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affected_nodes: set[str] = set()
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queue = deque(start_nodes)
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while queue:
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node = queue.popleft()
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if node in affected_nodes:
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continue
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affected_nodes.add(node)
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# 遍历永久管道邻居
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if node in pipe_adj:
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for neighbor in pipe_adj[node]:
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if neighbor not in affected_nodes:
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queue.append(neighbor)
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# 遍历故障阀门带来的额外邻居
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if node in extra_adj:
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for neighbor in extra_adj[node]:
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if neighbor not in affected_nodes:
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queue.append(neighbor)
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# 5. 结果聚合
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must_close_valves: list[str] = []
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optional_valves: list[str] = []
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for valve_id, (n1, n2) in boundary_valves.items():
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in_n1 = n1 in affected_nodes
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in_n2 = n2 in affected_nodes
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if in_n1 and in_n2:
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optional_valves.append(valve_id)
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elif in_n1 or in_n2:
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must_close_valves.append(valve_id)
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must_close_valves.sort()
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optional_valves.sort()
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result = {
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"accident_elements": target_elements,
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"disabled_valves": disabled_valves,
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"affected_nodes": sorted(affected_nodes),
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"must_close_valves": must_close_valves,
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"optional_valves": optional_valves,
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"isolatable": len(must_close_valves) > 0,
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}
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if len(target_elements) == 1:
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result["accident_element"] = target_elements[0]
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return result
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