#!/usr/bin/env python3
"""
本地最小验证：5 个交易日，验证 pipeline 正确性。

用法：
  python scripts/run_local_test.py
"""

import os
import sys
from pathlib import Path

# 保证项目根在 path 里
sys.path.insert(0, str(Path(__file__).resolve().parent.parent))

from src.data.loader import load_l2_day, BLACKLIST_DATES
from src.features.passive_orders import (
    compute_vwap,
    extract_passive_orders,
    prepare_features,
    select_candidates,
)
from src.clustering.daily_cluster import cluster_candidates
from src.matching.cross_day_match import match_clusters, match_multi_window
from src.tracking.entity_tracker import EntityTracker

# 测试日期：2024年3月第二周（避开黑名单）
TEST_DATES = [20240311, 20240312, 20240313, 20240314, 20240315]

OUTPUT_DIR = os.path.join(
    os.path.dirname(__file__), "..", "outputs", "local_test"
)


def main():
    os.makedirs(OUTPUT_DIR, exist_ok=True)
    print(f"本地测试: {len(TEST_DATES)} 天, 输出目录: {OUTPUT_DIR}\n")

    tracker = EntityTracker(inactive_threshold=5)
    recent_history = {}

    for i, date in enumerate(TEST_DATES):
        print(f"--- {date} ---")

        # 1. 加载
        try:
            data = load_l2_day(date)
        except Exception as e:
            print(f"  SKIP: 加载失败 ({e})")
            continue

        trades = data["trades"]
        orders = data["orders"]
        if "is_cancellation" in trades.columns:
            trades = trades[~trades["is_cancellation"]]

        print(f"  trades={len(trades):,}, orders={len(orders):,}")

        # 2. VWAP + 被动单
        vwap = compute_vwap(trades)
        passive = extract_passive_orders(trades, vwap)
        candidates = select_candidates(passive, top_n=150)
        print(f"  passive_orders={len(passive):,}, candidates={len(candidates)}")
        print(f"  VWAP={vwap:.2f}, bid_candidates={len(candidates[candidates['side']=='bid'])}, ask_candidates={len(candidates[candidates['side']=='ask'])}")

        if candidates.empty:
            recent_history[date] = {}
            continue

        # 3. 聚类
        feats = prepare_features(candidates)
        labeled, centroids = cluster_candidates(candidates, feats)
        n_clusters = len(centroids)
        n_noise = (labeled["cluster_id"] == -1).sum()
        print(f"  clusters={n_clusters}, noise={n_noise}")

        # 4. 跨日匹配
        prev_dates = sorted(
            [d for d in recent_history.keys() if d < date]
        )[-2:]
        prev_c_for_match = {}
        for pd_ in prev_dates:
            if recent_history.get(pd_):
                prev_c_for_match[pd_] = recent_history[pd_]

        matches = match_multi_window(date, centroids, prev_c_for_match)
        print(f"  matches={len(matches)}")
        for m in matches:
            print(f"    {m[0]} c{m[1]} → {m[2]} cost={m[3]:.3f}")

        # 5. 实体追踪
        cid_to_eid = tracker.process_day(date, centroids, matches)
        print(f"  entity mapping: {cid_to_eid}")

        # 6. 仓位推断
        signal = tracker.compute_position_signal(date)
        print(f"  signal: score={signal['score']:.4f}, bid_entities={signal['bid_entities']}, ask_entities={signal['ask_entities']}")

        recent_history[date] = centroids

    # ---- 导出 ----
    print("\n===== 导出 =====")

    entity_df = tracker.get_entity_timeline()
    print(f"实体总数: {len(entity_df)}")
    print(entity_df.to_string())

    entity_path = os.path.join(OUTPUT_DIR, "entity_timeline.parquet")
    entity_df.to_parquet(entity_path)
    print(f"实体表 → {entity_path}")

    signals_df = tracker.get_daily_signals()
    signals_path = os.path.join(OUTPUT_DIR, "position_signal_daily.parquet")
    signals_df.to_parquet(signals_path)
    print(f"信号表 → {signals_path}")
    print(signals_df[["date", "score", "score_z", "n_active_entities"]].to_string())

    # 被动单样本（第一天）
    passive_path = os.path.join(OUTPUT_DIR, "sample_passive_orders.parquet")
    passive.to_parquet(passive_path)
    print(f"被动单样本 → {passive_path}")

    # 聚类样本
    cluster_path = os.path.join(OUTPUT_DIR, "sample_clusters.parquet")
    labeled.to_parquet(cluster_path)
    print(f"聚类样本 → {cluster_path}")

    print("\n===== 本地验证完成 =====")


if __name__ == "__main__":
    main()