删除env.local；新增漏损区域识别功能

app/services/__init__.py

@@ -15,6 +15,7 @@ from app.services.simulation_ops import (
     scheduling_simulation,
     daily_scheduling_simulation,
 )
+from app.services.leakage_identifier import run_leakage_identification
 
 __all__ = [
     "network_update",
@@ -31,4 +32,5 @@ __all__ = [
     "scheduling_simulation",
     "daily_scheduling_simulation",
     "analyze_valve_isolation",
+    "run_leakage_identification",
 ]

app/services/leakage_identifier.py

@@ -0,0 +1,104 @@
+import os
+from typing import Any
+
+import pandas as pd
+
+from app.algorithms.leakage_identifier import LeakageIdentifier
+from app.services.tjnetwork import (
+    PARTITION_TYPE_KWAY,
+    calculate_district_metering_area_for_nodes,
+    dump_inp,
+    get_all_scada_info,
+    get_network_node_coords,
+)
+
+
+def run_leakage_identification(
+    network: str,
+    observed_pressure_data: str | pd.DataFrame | dict[str, list[Any]] | list[dict[str, Any]],
+    start_time: float = 0,
+    duration: float = 24,
+    timestep: float = 5,
+    q_sum: float = 0.2,
+    q_sum_unit: str = "m3/s",
+    output_dir: str = "Results",
+    pop_size: int = 50,
+    max_gen: int = 100,
+    output_flow_unit: str = "m3/s",
+) -> dict[str, Any]:
+    os.makedirs(output_dir, exist_ok=True)
+    inp_path = os.path.join(output_dir, f"{network}.leakage.inp")
+    dump_inp(network, inp_path, "2")
+    sensor_nodes = _get_pressure_sensor_nodes(network)
+    area_map = _build_area_map_by_spectral_partition(network, sensor_nodes)
+
+    q_sum_m3s = LeakageIdentifier._flow_to_m3s(q_sum, q_sum_unit)
+    identifier = LeakageIdentifier(
+        inp_path=inp_path,
+        sensor_nodes=sensor_nodes,
+        area_map=area_map,
+        start_time=start_time,
+        duration=duration,
+        timestep=timestep,
+        q_sum=q_sum_m3s,
+    )
+    result_df = identifier.run_identification(
+        observed_pressure_data=observed_pressure_data,
+        output_dir=output_dir,
+        pop_size=pop_size,
+        max_gen=max_gen,
+        output_flow_unit=output_flow_unit,
+        save_result=False,
+    )
+    return {
+        "result_path": result_df.attrs.get("result_path"),
+        "sensor_nodes": sensor_nodes,
+        "area_count": len(set(area_map.values())),
+        "rows": result_df.to_dict(orient="records"),
+    }
+
+
+def _get_pressure_sensor_nodes(network: str) -> list[str]:
+    scada_info = get_all_scada_info(network)
+    sensor_nodes: list[str] = []
+    for item in scada_info:
+        if item.get("type") != "pressure":
+            continue
+        node_id = item.get("associated_element_id")
+        if isinstance(node_id, str) and node_id:
+            sensor_nodes.append(node_id)
+    sensor_nodes = list(dict.fromkeys(sensor_nodes))
+    if not sensor_nodes:
+        raise ValueError("未找到压力传感器对应节点（scada_info.type=pressure）。")
+    return sensor_nodes
+
+
+def _build_area_map_by_spectral_partition(
+    network: str, sensor_nodes: list[str]
+) -> dict[str, str]:
+    node_coords = get_network_node_coords(network)
+    all_nodes = list(node_coords.keys())
+    if not all_nodes:
+        raise ValueError("管网中未获取到可分区节点。")
+
+    part_count = min(len(sensor_nodes), len(all_nodes))
+    if part_count <= 0:
+        raise ValueError("无可用压力传感器，无法生成虚拟分区。")
+
+    groups = calculate_district_metering_area_for_nodes(
+        network,
+        all_nodes,
+        part_count=part_count,
+        part_type=PARTITION_TYPE_KWAY,
+    )
+    if not groups:
+        raise ValueError("虚拟分区计算失败，未返回分区结果。")
+
+    area_map: dict[str, str] = {}
+    for idx, group_nodes in enumerate(groups, start=1):
+        area_id = str(idx)
+        for node_id in group_nodes:
+            area_map[node_id] = area_id
+    if not area_map:
+        raise ValueError("虚拟分区结果为空，无法生成节点区域映射。")
+    return area_map