376 lines
11 KiB
Python
376 lines
11 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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r"""
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CM95 / CM93 助航 relation20 全 AOI 审计 v1
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用途
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====
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验证选定 PBF AOI（默认 z10/914/385）中 CM93 助航对象的
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`_cm93_relation20_raw` 是否可以作为 CM95→NavSea `navigation_marks`
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的稳定合成键。
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重点检查：
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- LIGHTS 与 BCNLAT / BCNSPP / BOYSPP / RTPBCN / TOWERS / _extgn 等是否共享 relation20；
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- 同一 relation20 组的坐标是否一致；
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- 是否存在一个 relation20 对应多个不相干坐标；
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- LIGHTS 中有多少可以安全合并，有多少必须独立输出；
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- relation20 缺失情况；
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- 跨 Cell 不合并。
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本脚本只读 MySQL，不修改 importer/schema。
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默认 AOI：
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z10/914/385
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lon 141.328125 .. 141.6796875
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lat 40.44694705960049 .. 40.71395582628604
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"""
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from __future__ import annotations
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import argparse
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import csv
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import getpass
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import json
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import math
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from collections import Counter, defaultdict
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from datetime import datetime
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from pathlib import Path
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import pymysql
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from pymysql.cursors import DictCursor
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NAV_CLASSES = {
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"LIGHTS",
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"BCNLAT",
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"BCNSPP",
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"BOYSPP",
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"RTPBCN",
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"TOWERS",
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"_extgn",
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"SISTAT",
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"SISTAW",
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}
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BASE_CLASSES = {
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"BCNLAT",
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"BCNSPP",
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"BOYSPP",
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"RTPBCN",
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"TOWERS",
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"_extgn",
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"SISTAT",
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"SISTAW",
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}
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def parse_args():
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p = argparse.ArgumentParser()
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p.add_argument("--host", default="127.0.0.1")
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p.add_argument("--port", type=int, default=3306)
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p.add_argument("--user", default="root")
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p.add_argument("--password", default=None)
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p.add_argument("--database", default="cm93_chart")
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p.add_argument("--dataset-id", type=int, default=1)
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p.add_argument("--min-lon", type=float, default=141.328125)
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p.add_argument("--min-lat", type=float, default=40.44694705960049)
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p.add_argument("--max-lon", type=float, default=141.6796875)
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p.add_argument("--max-lat", type=float, default=40.71395582628604)
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p.add_argument(
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"--coord-tolerance-deg",
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type=float,
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default=1e-7,
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help="同 relation20 组坐标最大容差，默认约厘米级～十米级以下的严格检查",
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)
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p.add_argument("--output-dir", default=".")
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return p.parse_args()
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def rel20(attrs):
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if not isinstance(attrs, dict):
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return None
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v = attrs.get("_cm93_relation20_raw")
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if v is None:
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return None
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try:
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return int(v)
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except Exception:
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return str(v)
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def coord_distance_deg(a, b):
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return math.hypot(a[0] - b[0], a[1] - b[1])
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def write_csv(path, rows):
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rows = list(rows)
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if not rows:
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path.write_text("", encoding="utf-8-sig")
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return
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keys = []
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seen = set()
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for row in rows:
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for k in row:
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if k not in seen:
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seen.add(k)
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keys.append(k)
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with path.open("w", encoding="utf-8-sig", newline="") as f:
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w = csv.DictWriter(f, fieldnames=keys)
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w.writeheader()
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for row in rows:
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out = {}
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for k in keys:
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v = row.get(k)
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if isinstance(v, (list, dict, tuple)):
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v = json.dumps(v, ensure_ascii=False, default=str)
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out[k] = v
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w.writerow(out)
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def main():
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a = parse_args()
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if a.password is None:
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a.password = getpass.getpass("MySQL password: ")
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outdir = Path(a.output_dir).resolve()
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outdir.mkdir(parents=True, exist_ok=True)
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conn = pymysql.connect(
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host=a.host,
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port=a.port,
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user=a.user,
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password=a.password,
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database=a.database,
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charset="utf8mb4",
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cursorclass=DictCursor,
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autocommit=False,
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connect_timeout=20,
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read_timeout=900,
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)
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rows = []
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try:
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with conn.cursor() as cur:
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try:
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cur.execute("SET SESSION TRANSACTION READ ONLY")
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except Exception:
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pass
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try:
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cur.execute("START TRANSACTION READ ONLY")
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except Exception:
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cur.execute("START TRANSACTION")
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placeholders = ",".join(["%s"] * len(NAV_CLASSES))
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sql = f"""
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SELECT
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f.id AS feature_id,
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f.cell_id,
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c.source_relative_path,
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f.source_record_index,
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f.object_class,
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f.native_scale,
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f.bbox_min_lon,
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f.bbox_min_lat,
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f.attributes_json
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FROM chart_feature f
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JOIN chart_cell c ON c.id=f.cell_id
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WHERE f.dataset_id=%s
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AND f.geometry_type='POINT'
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AND f.object_class IN ({placeholders})
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AND f.bbox_min_lon BETWEEN %s AND %s
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AND f.bbox_min_lat BETWEEN %s AND %s
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ORDER BY
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f.cell_id,
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f.native_scale,
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f.object_class,
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f.source_record_index
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"""
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params = [
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a.dataset_id,
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*sorted(NAV_CLASSES),
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a.min_lon,
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a.max_lon,
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a.min_lat,
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a.max_lat,
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]
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cur.execute(sql, params)
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rows = list(cur.fetchall())
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conn.rollback()
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finally:
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conn.close()
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for row in rows:
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attrs = row.get("attributes_json")
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if isinstance(attrs, str):
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try:
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attrs = json.loads(attrs)
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except Exception:
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attrs = {}
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elif attrs is None:
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attrs = {}
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row["attributes"] = attrs
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row["relation20"] = rel20(attrs)
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row["lon"] = float(row["bbox_min_lon"])
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row["lat"] = float(row["bbox_min_lat"])
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row.pop("attributes_json", None)
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groups = defaultdict(list)
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no_relation = []
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for row in rows:
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rel = row["relation20"]
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if rel is None:
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no_relation.append(row)
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else:
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groups[(int(row["cell_id"]), rel)].append(row)
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group_rows = []
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light_total = 0
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light_with_relation = 0
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light_mergeable = 0
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light_relation_without_base = 0
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coord_conflict_groups = 0
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for row in rows:
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if row["object_class"] == "LIGHTS":
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light_total += 1
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if row["relation20"] is not None:
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light_with_relation += 1
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for (cell_id, relation20), members in sorted(groups.items()):
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classes = Counter(m["object_class"] for m in members)
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coords = [(m["lon"], m["lat"]) for m in members]
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base = coords[0]
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max_spread = max(coord_distance_deg(base, c) for c in coords)
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has_light = classes["LIGHTS"] > 0
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base_members = [
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m for m in members
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if m["object_class"] in BASE_CLASSES
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]
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has_base = bool(base_members)
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if max_spread > a.coord_tolerance_deg:
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coord_conflict_groups += 1
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if has_light and has_base and max_spread <= a.coord_tolerance_deg:
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light_mergeable += classes["LIGHTS"]
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elif has_light and not has_base:
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light_relation_without_base += classes["LIGHTS"]
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group_rows.append({
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"cell_id": cell_id,
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"relation20": relation20,
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"member_count": len(members),
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"classes": dict(classes),
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"has_light": has_light,
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"has_base_component": has_base,
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"base_classes": sorted(
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set(m["object_class"] for m in base_members)
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),
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"max_coord_spread_deg": max_spread,
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"coord_ok": max_spread <= a.coord_tolerance_deg,
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"members": [
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{
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"feature_id": m["feature_id"],
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"source_record_index": m["source_record_index"],
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"object_class": m["object_class"],
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"native_scale": m["native_scale"],
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"lon": m["lon"],
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"lat": m["lat"],
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"attributes": m["attributes"],
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}
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for m in members
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],
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})
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no_relation_counts = Counter(
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r["object_class"] for r in no_relation
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)
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standalone_lights = [
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r for r in rows
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if r["object_class"] == "LIGHTS"
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and (
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r["relation20"] is None
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or not any(
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g["cell_id"] == r["cell_id"]
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and g["relation20"] == r["relation20"]
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and g["has_base_component"]
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and g["coord_ok"]
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for g in group_rows
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)
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)
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]
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report = {
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"version": "v1",
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"generated_at": datetime.now().isoformat(timespec="seconds"),
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"dataset_id": a.dataset_id,
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"aoi_bbox": [
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a.min_lon, a.min_lat, a.max_lon, a.max_lat
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],
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"coord_tolerance_deg": a.coord_tolerance_deg,
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"counts": {
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"nav_point_rows": len(rows),
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"relation_groups": len(groups),
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"rows_without_relation20": len(no_relation),
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"coord_conflict_groups": coord_conflict_groups,
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"light_total": light_total,
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"light_with_relation20": light_with_relation,
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"light_mergeable_by_relation20": light_mergeable,
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"light_relation_without_base": light_relation_without_base,
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"light_standalone_required": len(standalone_lights),
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},
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"no_relation_by_class": dict(no_relation_counts),
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"groups": group_rows,
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"standalone_lights": standalone_lights,
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"decision": (
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"PASS_RELATION20_PRIMARY_KEY"
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if light_total > 0
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and light_mergeable > 0
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and coord_conflict_groups == 0
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else "REVIEW_RELATION20"
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),
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}
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json_path = outdir / "cm95_nav_aid_relation_audit_v1.json"
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csv_path = outdir / "cm95_nav_aid_relation_groups_v1.csv"
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txt_path = outdir / "cm95_nav_aid_relation_audit_v1.txt"
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json_path.write_text(
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json.dumps(report, ensure_ascii=False, indent=2, default=str),
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encoding="utf-8",
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)
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write_csv(csv_path, group_rows)
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lines = [
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"CM95 / CM93 助航 relation20 全 AOI 审计 v1",
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"=" * 76,
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f"NAV point rows : {len(rows)}",
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f"Relation groups : {len(groups)}",
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f"Rows without relation20 : {len(no_relation)}",
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f"Coordinate conflict groups : {coord_conflict_groups}",
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"",
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f"LIGHTS total : {light_total}",
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f"LIGHTS with relation20 : {light_with_relation}",
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f"LIGHTS mergeable : {light_mergeable}",
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f"LIGHTS relation no base : {light_relation_without_base}",
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f"LIGHTS standalone required : {len(standalone_lights)}",
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"",
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f"DECISION : {report['decision']}",
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]
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txt_path.write_text("\n".join(lines), encoding="utf-8")
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print("\n".join(lines))
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print("")
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print("输出:")
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print(json_path)
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print(csv_path)
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print(txt_path)
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if __name__ == "__main__":
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main()
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