后端服务将通过tjwater-cli形式访问
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#!/usr/bin/env python3
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"""
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compute_service_areas.py — 水源服务范围分析核心脚本
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输入：
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sim_result.json — runprojectreturndict 的水力模拟结果
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pipes.json — getallpipeproperties 的管道属性列表
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reservoirs.json — getallreservoirproperties 的水库属性列表
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输出：
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service_area_result.json — 包含 node_area_map 和统计信息
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算法：
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1. 从 pipes 构建无向拓扑图 (node1 <-> node2)
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2. 从 sim link_results 确定流向，生成有向图
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3. 从 reservoirs 获取所有水源节点
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4. 多源 BFS 下游遍历，首次访问即归属性
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5. 生成渲染数据与统计
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用法:
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python compute_service_areas.py sim_result.json pipes.json reservoirs.json \
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--output service_area_result.json --network tjwater
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"""
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import argparse
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import json
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import os
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import sys
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from collections import deque
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# ── 高区分度 20 色调色板 ──────────────────────────────────────────
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PALETTE = [
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"#1f77b4", "#ff7f0e", "#2ca02c", "#d62728", "#9467bd",
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"#8c564b", "#e377c2", "#7f7f7f", "#bcbd22", "#17becf",
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"#aec7e8", "#ffbb78", "#98df8a", "#ff9896", "#c5b0d5",
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"#c49c94", "#f7b6d2", "#c7c7c7", "#dbdb8d", "#9edae5",
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]
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def load_json(path: str) -> dict | list:
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"""加载 JSON 文件，支持引用格式（含 result_ref 字段）或列表。"""
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with open(path, "r", encoding="utf-8") as f:
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data = json.load(f)
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# 如果顶层是引用包装，展开到内部的列表
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if isinstance(data, dict) and "data" in data:
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data = data["data"]
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if isinstance(data, dict) and "items" in data:
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data = data["items"]
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return data
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def build_undirected_graph(pipes: list) -> tuple[dict, dict]:
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"""
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从管道列表构建无向拓扑图。
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返回:
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adj: { node_id: set(neighbor_node_ids) }
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edge_map: { (node1, node2): pipe_id } 用于查找管道 ID
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"""
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adj = {}
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edge_map = {}
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for p in pipes:
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pipe_id = str(p.get("id", p.get("pipe_id", p.get("name", ""))))
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n1 = str(p.get("node1", ""))
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n2 = str(p.get("node2", ""))
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if not n1 or not n2:
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continue
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adj.setdefault(n1, set()).add(n2)
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adj.setdefault(n2, set()).add(n1)
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edge_map[(n1, n2)] = pipe_id
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edge_map[(n2, n1)] = pipe_id
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return adj, edge_map
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def build_directed_graph(adj: dict, edge_map: dict, link_results: list) -> dict:
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"""
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基于模拟流向构建有向图。
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link_results 中每条记录含 link_id, flow, status。
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流向判定:
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flow > 0 → node1 → node2
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flow < 0 → node2 → node1
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flow ≈ 0 或 status != "Open" → 忽略（视为断连）
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注意: link_results 中没有 node1/node2，需要通过 link_id 反查 edge_map。
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由于 edge_map 只有 (node1,node2) → pipe_id 的映射，
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这里需要先建立 pipe_id → (node1, node2) 的反向索引。
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"""
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# 建立 pipe_id → (node1, node2) 反向索引
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# 注意：edge_map 含有 (n1,n2) 和 (n2,n1) 两个方向，只保留第一个以避免反向覆写
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pipe_to_nodes = {}
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for (n1, n2), pid in edge_map.items():
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if pid not in pipe_to_nodes:
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pipe_to_nodes[pid] = (n1, n2)
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digraph = {}
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missing = 0
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closed_or_zero = 0
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for link in link_results:
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lid = str(link.get("link_id", link.get("id", "")))
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flow = link.get("flow", 0)
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status = str(link.get("status", "Open"))
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# 忽略非 Open 管段和零流量管段（大小写不敏感）
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if status.upper() != "OPEN":
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closed_or_zero += 1
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continue
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if abs(flow) < 1e-6:
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closed_or_zero += 1
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continue
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# 查找管段对应的节点对
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pair = pipe_to_nodes.get(lid)
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if pair is None:
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missing += 1
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continue
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n1, n2 = pair
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if flow > 0:
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digraph.setdefault(n1, set()).add(n2)
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else:
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digraph.setdefault(n2, set()).add(n1)
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if missing > 0:
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print(f"[WARN] {missing} 条模拟管段未在管道拓扑中找到对应节点对", file=sys.stderr)
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if closed_or_zero > 0:
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print(f"[INFO] 忽略 {closed_or_zero} 条 Closed/零流量管段", file=sys.stderr)
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return digraph
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def bfs_from_sources(sources: list, digraph: dict) -> dict:
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"""
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多水源 BFS 下游遍历。首次访问的节点归属到对应水源。
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返回: { node_id: source_id }
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"""
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node_area = {}
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queue = deque()
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# 初始化：所有水源入队，归属自身
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for src in sources:
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node_area[src] = src
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queue.append(src)
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while queue:
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cur = queue.popleft()
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cur_source = node_area[cur]
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for nb in digraph.get(cur, set()):
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if nb not in node_area:
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node_area[nb] = cur_source
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queue.append(nb)
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return node_area
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def generate_render_data(node_area: dict, sources: list) -> dict:
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"""
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生成 render_junctions 所需的渲染数据。
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返回:
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node_area_map: { node_id: area_id }
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area_ids: 水源 ID 列表
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area_colors: { area_id: color_hex }
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"""
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# 为每个水源分配颜色
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area_colors = {}
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for i, src in enumerate(sources):
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area_colors[src] = PALETTE[i % len(PALETTE)]
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return {
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"node_area_map": node_area,
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"area_ids": sources,
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"area_colors": area_colors,
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}
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def compute_stats(node_area: dict, sources: list, all_nodes: set) -> dict:
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"""计算各水源服务节点数和覆盖率统计。"""
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source_counts = {}
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for src in sources:
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source_counts[src] = sum(1 for v in node_area.values() if v == src)
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total = len(all_nodes)
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assigned = len(node_area)
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unassigned = total - assigned
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coverage = (assigned / total * 100) if total > 0 else 0
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return {
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"total_nodes": total,
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"assigned_nodes": assigned,
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"unassigned_nodes": unassigned,
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"coverage_pct": round(coverage, 2),
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"source_counts": source_counts,
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}
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def main():
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parser = argparse.ArgumentParser(
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description="水源服务范围分析 — 基于水力模拟流向的多源 BFS 分区"
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)
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parser.add_argument("sim_file", help="runprojectreturndict 模拟结果 JSON")
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parser.add_argument("pipes_file", help="getallpipeproperties 管道属性 JSON")
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parser.add_argument("reservoirs_file", help="getallreservoirproperties 水库属性 JSON")
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parser.add_argument("--output", "-o", default="/tmp/opencode/service_area_result.json",
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help="输出 JSON 文件路径")
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parser.add_argument("--network", "-n", default="tjwater",
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help="管网名称（仅用于报告标注）")
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args = parser.parse_args()
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# ── 1. 加载数据 ──
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print(f"[INFO] 加载模拟结果: {args.sim_file}")
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sim_data = load_json(args.sim_file)
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link_results = sim_data.get("link_results", [])
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print(f"[INFO] 加载管道属性: {args.pipes_file}")
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pipes = load_json(args.pipes_file)
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print(f"[INFO] 加载水库列表: {args.reservoirs_file}")
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reservoirs = load_json(args.reservoirs_file)
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# 提取水源 ID 列表
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sources = []
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if isinstance(reservoirs, list):
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sources = [str(r.get("id", r.get("name", ""))) for r in reservoirs if r.get("id") or r.get("name")]
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elif isinstance(reservoirs, dict):
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# 可能是 { data: [...] } 格式
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for key in ["data", "items", "reservoirs"]:
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if key in reservoirs and isinstance(reservoirs[key], list):
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sources = [str(r.get("id", r.get("name", ""))) for r in reservoirs[key] if r.get("id") or r.get("name")]
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break
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if not sources:
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# 也可能是 { "551656": {...}, ... } 格式
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sources = [str(k) for k in reservoirs if isinstance(reservoirs[k], dict)]
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if not sources:
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print("[ERROR] 未能从水库数据中提取水源 ID 列表", file=sys.stderr)
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sys.exit(1)
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print(f"[INFO] 水源数: {len(sources)}")
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print(f"[INFO] 水源列表: {sources}")
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# ── 2. 构建无向图 ──
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adj, edge_map = build_undirected_graph(pipes)
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all_nodes = set(adj.keys())
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# ── 3. 构建有向图 ──
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digraph = build_directed_graph(adj, edge_map, link_results)
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# ── 4. BFS 下游遍历 ──
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print("[INFO] 执行多源 BFS 下游遍历...")
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node_area = bfs_from_sources(sources, digraph)
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# ── 5. 统计 ──
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stats = compute_stats(node_area, sources, all_nodes)
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print(f"[INFO] 总节点数: {stats['total_nodes']}")
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print(f"[INFO] 已分配: {stats['assigned_nodes']} ({stats['coverage_pct']:.1f}%)")
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print(f"[INFO] 未分配: {stats['unassigned_nodes']}")
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print("\n各水源服务节点数 (按数量降序):")
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for src, count in sorted(stats["source_counts"].items(), key=lambda x: -x[1]):
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pct = (count / stats["assigned_nodes"] * 100) if stats["assigned_nodes"] > 0 else 0
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print(f" {src}: {count} ({pct:.1f}%)")
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# ── 6. 生成渲染数据 ──
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render = generate_render_data(node_area, sources)
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# ── 7. 输出 ──
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output = {
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"network": args.network,
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"stats": stats,
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"render": render,
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"sources": sources,
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}
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os.makedirs(os.path.dirname(args.output) or ".", exist_ok=True)
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with open(args.output, "w", encoding="utf-8") as f:
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json.dump(output, f, ensure_ascii=False, indent=2)
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print(f"\n[OK] 结果已写入: {args.output}")
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if __name__ == "__main__":
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main()
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