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"""采集一组新的自建模拟器演练局（问题三全向源 / 问题四混合源）。
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为什么需要它：论文正文的定量论据取自自建模拟器演练局，但历史留档里混入了
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算法尚未优化完全时的局（例如一次演练出现 33 次失败清除、10 分钟虚拟时间
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仍只清 10/13 个源）。这类局不能代表当前实现，需要重新采一组。
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本脚本**不自己造数据、也不写评测机日志**：它启动评测机 ``referee``、
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调用 ``judge.start("q3_practice"|"q4_practice", seed=...)`` 开始一局演练，
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再用与 ``mcm26b.cli run`` 完全相同的生产策略对接接口。
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于是：
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- 真值与行为日志由评测机自己写进 ``<data-dir>/sessions/<案例编码>/``，
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与历史留档同源同格式，可直接被 ``scripts/build_practice_data.py`` 复算；
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- 策略端只看见 HTTP 响应，不存在"为了好看而改数据"的空间；
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- 每局由 ``--seed`` 决定，可重放。
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有效性判定沿用项目口径（与 ``scripts/run_suite.py`` 一致，不放宽）：
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``清完全部源 ∧ 无缺席误判 ∧ 主动 /exit ∧ 零异常 ∧ 零失败清除``。
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最后一项是刻意加严的：算法未优化完全时会出现"最终清完了，但中途大量 /clear
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打空"的局（本次复测就抓到 3~114 次失败清除）。这类局的总虚拟时间与检测次数
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被无效试探撑大，不能代表当前实现，必须排除。
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uv run python scripts/run_practice_episodes.py --problem 3 --counts 10,13,16 \
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--seeds 300-309 --out referee-data
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uv run python scripts/run_practice_episodes.py --problem 4 --counts 10,13 \
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--seeds 400-411
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"""
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from __future__ import annotations
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import argparse
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import json
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import socket
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import sys
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import time
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from pathlib import Path
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ROOT = Path(__file__).resolve().parents[1]
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sys.path.insert(0, str(ROOT / "src"))
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from mcm26b.config import ProblemConfig # noqa: E402
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from mcm26b.planner import DirectionalExtension # noqa: E402
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from mcm26b.planner.bayes_loop import BayesLoop # noqa: E402
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from mcm26b.protocol.client import SimulatorClient # noqa: E402
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STRATEGIES = {3: BayesLoop, 4: DirectionalExtension}
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DEFAULT_SEEDS = {3: (300, 309), 4: (400, 411)}
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def free_port() -> int:
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"""取一个空闲回环端口，评测机接口与 WebUI 都只用回环 [题面 附件2 1.5]。"""
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with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as probe:
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probe.bind(("127.0.0.1", 0))
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return probe.getsockname()[1]
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def parse_seeds(text: str | None, problem: int) -> list[int]:
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"""``300-309`` 或 ``300,301`` 形式的种子表。"""
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if not text:
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low, high = DEFAULT_SEEDS[problem]
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return list(range(low, high + 1))
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seeds: list[int] = []
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for chunk in text.split(","):
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chunk = chunk.strip()
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if not chunk:
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continue
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if "-" in chunk:
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low, high = (int(part) for part in chunk.split("-", 1))
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seeds.extend(range(low, high + 1))
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else:
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seeds.append(int(chunk))
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return seeds
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def build_config(base_url: str, margin_deg: float) -> ProblemConfig:
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"""与 ``mcm26b.cli run`` 相同的生产配置：默认关闭 persistent 复扫。"""
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from dataclasses import replace # noqa: PLC0415
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config = ProblemConfig()
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return replace(config,
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session=replace(config.session, base_url=base_url),
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search=replace(config.search,
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bearing_rounding_margin_deg=margin_deg,
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persistent_search=False))
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def run_episode(problem: int, count: int, seed: int, robot_id: str, data_dir: Path,
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margin_deg: float, countdown_s: float,
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directional: int) -> dict:
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"""跑一局演练；返回该局的核对结果（真值只在此处用于判定）。"""
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from referee import Referee # noqa: PLC0415
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from referee.server import ActionInterfaceServer # noqa: PLC0415
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port = free_port()
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judge = Referee(action_port=port, data_dir=data_dir)
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ActionInterfaceServer(judge)
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module = f"q{problem}_practice"
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session = judge.start(module, robot_id, seed=seed, source_count=count,
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directional_count=directional, countdown_s=countdown_s)
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deadline = time.monotonic() + session.countdown_s + 15.0
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while session.phase == "countdown" and time.monotonic() < deadline:
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time.sleep(0.02)
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result = {"problem": problem, "seed": seed, "count": count,
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"case_code": session.case_code}
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if session.phase != "open":
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judge.abort()
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result.update(valid=False, error="评测机未能开放接口")
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return result
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config = build_config(f"http://127.0.0.1:{port}", margin_deg)
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client = SimulatorClient(robot_id, config=config)
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started = time.perf_counter()
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try:
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summary = STRATEGIES[problem](client, config).run()
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result["strategy_error"] = None
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except Exception as exc: # pylint: disable=broad-except
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summary = {"cleared_channels": [], "absent_channels": [],
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"exit_reason": "technical_error", "anomalies": [str(exc)]}
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result["strategy_error"] = f"{type(exc).__name__}: {exc}"
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result["compute_wall_s"] = round(time.perf_counter() - started, 3)
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settle = time.monotonic() + 10.0
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while judge.session.phase != "finished" and time.monotonic() < settle:
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time.sleep(0.02)
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if judge.session.phase != "finished":
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judge.abort()
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state = judge.snapshot()
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truth = sorted(source.channel for source in session.sources)
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cleared = sorted(summary.get("cleared_channels", []))
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absent = sorted(summary.get("absent_channels", []))
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# 失败清除次数从评测机行为日志里数，而不是策略自报，避免口径分歧。
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clear_calls = clear_failures = 0
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log_path = data_dir / "sessions" / session.case_code / "log.jsonl"
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if log_path.exists():
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for line in log_path.read_text(encoding="utf-8").splitlines():
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if '"path": "/clear"' not in line:
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continue
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event = json.loads(line)
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if (event.get("event") != "action"
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or (event.get("response") or {}).get("accepted") is not True):
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continue
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clear_calls += 1
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if (event["response"].get("clear_result")) != "success":
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clear_failures += 1
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result.update(
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end_reason=state.get("end_reason"),
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cleared_channels=cleared,
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cleared_count=len(cleared),
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truth_channels=truth,
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source_count=len(truth),
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directional_count=sum(1 for s in session.sources if s.directional),
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absent_misjudged=sorted(set(absent) & set(truth)),
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anomalies=len(summary.get("anomalies", [])),
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virtual_time_s=state.get("virtual_time_s"),
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clear_calls=clear_calls,
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clear_failures=clear_failures,
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measurements=len([s for s in summary.get("steps", [])
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if s.get("action") == "measure"]),
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valid=(bool(truth) and cleared == truth and not (set(absent) & set(truth))
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and summary.get("exit_reason") == "user_exit"
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and not summary.get("anomalies")
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and clear_failures == 0
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and result["strategy_error"] is None))
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return result
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def main() -> int:
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parser = argparse.ArgumentParser(description=__doc__.splitlines()[0])
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parser.add_argument("--problem", type=int, choices=(3, 4), required=True)
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parser.add_argument("--counts", default="10,13,16",
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help="每局的源数量表（逗号分隔），逐局循环取用")
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parser.add_argument("--seeds", default=None,
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help="种子表，支持 300-309 或 300,301；缺省用内置区间")
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parser.add_argument("--directional", type=int, default=3,
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help="问题四每局定向源个数（题面未规定，自建模拟器默认为 3）")
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parser.add_argument("--directional-cycle", default=None,
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help="问题四定向源个数循环表，如 3,6,8；给定时覆盖 --directional，"
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"用于让演练局的定向占比也覆盖题面的不确定性")
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parser.add_argument("--robot-id", default="2026001")
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parser.add_argument("--data-dir", type=Path, default=ROOT / "referee-data")
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parser.add_argument("--margin-deg", type=float, default=0.005)
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parser.add_argument("--countdown-s", type=float, default=0.2)
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parser.add_argument("--out", type=Path, default=None,
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help="逐局核对结果的 JSON 输出路径")
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args = parser.parse_args()
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counts = [int(item) for item in args.counts.split(",") if item.strip()]
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directional_cycle = ([int(item) for item in args.directional_cycle.split(",")
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if item.strip()]
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if args.directional_cycle else [args.directional])
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seeds = parse_seeds(args.seeds, args.problem)
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print(f"问题{args.problem}：{len(seeds)} 局，源数循环 {counts}，"
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f"定向源循环 {directional_cycle}，数据目录 {args.data_dir}", flush=True)
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results = []
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for index, seed in enumerate(seeds):
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outcome = run_episode(args.problem, counts[index % len(counts)], seed,
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args.robot_id, args.data_dir, args.margin_deg,
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args.countdown_s,
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directional_cycle[index % len(directional_cycle)])
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results.append(outcome)
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verdict = "有效" if outcome.get("valid") else "无效"
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print(f" [{index + 1:2d}/{len(seeds)}] seed={seed:5d} n={outcome['count']:2d} "
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f"{outcome['case_code']} 清除 {outcome['cleared_count']}/{outcome['source_count']} "
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f"T={outcome.get('virtual_time_s') or 0:9.1f}s 墙钟={outcome['compute_wall_s']:6.2f}s "
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f"失败清除={outcome['clear_failures']} 缺席误判={len(outcome['absent_misjudged'])} "
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f"异常={outcome['anomalies']} {outcome['end_reason']} -> {verdict}", flush=True)
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valid = [row for row in results if row.get("valid")]
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print(f"\n有效 {len(valid)}/{len(results)} 局；"
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f"无效局的种子：{[r['seed'] for r in results if not r.get('valid')]}")
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if args.out:
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args.out.parent.mkdir(parents=True, exist_ok=True)
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args.out.write_text(json.dumps({"problem": args.problem,
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"counts": counts, "seeds": seeds,
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"directional": args.directional,
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"results": results},
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ensure_ascii=False, indent=2) + "\n",
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encoding="utf-8")
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print(f"核对结果已写入 {args.out}")
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return 0 if valid else 1
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if __name__ == "__main__":
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raise SystemExit(main())
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