"""
evolution/auto_iterator.py — 策略自动迭代
健康度低时生成参数变体，跑回测，记录结果
"""
import sys, os, json, sqlite3, copy
from datetime import datetime

sys.path.insert(0, '/home/hmo/MoFin')
import strategy_lab as lab

DB = '/home/hmo/MoFin/data/mofin.db'

# 可迭代的参数空间
PARAM_SPACE = {
    'max_hold_days': [40, 60, 80, 100, 120],
    'reentry_days': [5, 10, 15, 20],
    'sl_atr': [1.0, 1.5, 2.0, 2.5],
}


def get_current_health(version='v_next4', days=7):
    """获取当前策略健康度"""
    conn = sqlite3.connect(DB)
    conn.row_factory = sqlite3.Row
    rows = conn.execute("""
        SELECT health_score, date FROM strategy_health 
        WHERE strategy_version=? ORDER BY date DESC LIMIT ?
    """, (version, days)).fetchall()
    conn.close()
    if not rows:
        return 50  # 无数据，中性
    return round(sum(r['health_score'] for r in rows) / len(rows), 1)


def propose_variants(parent_version, health):
    """根据健康度生成变体参数建议"""
    if health >= 70:
        print(f"健康度{health}≥70，无需迭代", flush=True)
        return []
    
    variants = []
    severity = 'minor' if health >= 50 else 'major'
    
    if severity == 'minor':
        # 小幅调参
        variants.append({
            'parent': parent_version,
            'params': {'max_hold_days': 80, 'reentry_days': 15, 'sl_atr': 1.5},
            'description': '微调：确保当前最优参数',
        })
    else:
        # 大幅调参（扫参数网格）
        base_hold = 60
        base_reentry = 10
        for hold in PARAM_SPACE['max_hold_days']:
            for reentry in PARAM_SPACE['reentry_days']:
                variants.append({
                    'parent': parent_version,
                    'params': {'max_hold_days': hold, 'reentry_days': reentry, 'sl_atr': 1.5},
                    'description': f'网格扫描: h{hold}/r{reentry}',
                })
    
    return variants


def test_variant(variant):
    """测试单个变体"""
    name = f"auto_h{variant['params']['max_hold_days']}_r{variant['params']['reentry_days']}"
    # 克隆基座配置
    base = lab.STRATEGIES.get(variant['parent'])
    if not base:
        return None
    cfg = copy.deepcopy(base)
    cfg['version'] = name
    cfg['name'] = f"自进化-{variant['description']}"
    for k, v in variant['params'].items():
        cfg['config']['exit'][k] = v
    lab.STRATEGIES[name] = cfg
    
    results = {}
    for tag, start, end in [('5y', '2021-07-01', '2026-07-24')]:
        r = lab.run_backtest(name, start, end, 913000, save=False, universe='a', period_tag=tag)
        pf = r['summary'].get('portfolio_full', {})
        results[tag] = {
            'full': pf.get('total_return_pct'),
            'cagr': pf.get('cagr_pct'),
            'dd': pf.get('portfolio_max_dd_pct'),
        }
    return {'name': name, 'description': variant['description'], 'results': results}


def run_iteration(version='v_next4'):
    """执行一次迭代检查"""
    health = get_current_health(version)
    print(f"{version} 健康度: {health}", flush=True)
    
    variants = propose_variants(version, health)
    if not variants:
        return []
    
    conn = sqlite3.connect(DB)
    results = []
    for v in variants[:3]:  # 最多测3个
        print(f"测试: {v['description']}", flush=True)
        r = test_variant(v)
        if r:
            results.append(r)
            # 记录到 evolution 表
            conn.execute("""
                INSERT INTO strategy_evolution (parent_version, child_version, change_description, backtest_result, promoted)
                VALUES (?, ?, ?, ?, 0)
            """, (version, r['name'], r['description'], json.dumps(r['results'], ensure_ascii=False)))
            conn.commit()
    
    # 打印对比
    for r in results:
        rs = r['results'].get('5y', {})
        print(f"  {r['name']}: full={rs.get('full')}% cagr={rs.get('cagr')}% dd={rs.get('dd')}%", flush=True)
    
    conn.close()
    return results


if __name__ == '__main__':
    run_iteration()