fix(factor): 因子管线真数据跑通（注册因子 + close 时区 + 多 symbol + smoke 真断言）

端到端修复因子分析在真实 A 股数据上的多层问题：
- __init__ 引入 library 触发 _register_all（ma5 等内置因子注册）
- read_db_daily 用裸 symbol（600000 非 600000.SSE），匹配 DB 存储
- analyzer 单独读 close 价格 + tz_localize Asia/Shanghai 对齐 factor_df aware 日期
- smoke 用 >=2 symbol（alphalens IC 是横截面分析，单 symbol 分位为空 -> concat 报错）
- smoke 真断言 IC 非空（杀掉之前的假阳性 PASS）
- 修 status 引用未定义的 use_cumsum_fallback

验证：容器 smoke 6/6 PASS，real tears 出真 IC
（ma5: 1D mean=-0.122/icir=-0.22, 5D mean=-0.276, 10D mean=-0.265, count=49）
容器 68 tests passed。

scripts/smoke_phase3a.py

@@ -251,11 +251,11 @@ async def test_real_factor_tears_pipeline():
             print("  === SKIP: database config not found ===")
             return
 
-        # Run on a SMALL real slice to avoid overwhelming the 2-core NAS
-        symbols = ["600000.SSE"]  # Just one symbol
+        # ≥2 symbols: alphalens IC is cross-sectional (1 symbol → empty bins → fails)
+        symbols = ["600000", "000001", "300750"]  # BARE symbols (no .EXCHANGE suffix) for DB lookup
         factor_names = ["ma5"]   # Simple factor
         start = "2024-01-01"
-        end = "2024-01-31"     # Just one month to reduce load
+        end = "2024-06-30"     # Use longer range for reliable IC (Phase 1 confirmed 541 bars)
 
         print(f"  Running factor analysis: {symbols}, {factor_names}, {start} to {end}")
         print("  This will test the multiprocessing pipeline...")
@@ -278,6 +278,12 @@ async def test_real_factor_tears_pipeline():
         assert result is not None, "Result is None"
         assert len(result.factor_names) > 0, "No factors processed"
 
+        # CRITICAL: Verify IC is non-empty (Root cause C fix)
+        assert result.ic_summary, "ic_summary empty - no IC computed"
+        assert "ma5" in result.ic_summary, "ma5 not in ic_summary"
+        assert result.ic_summary["ma5"].get("ic"), "no IC data for ma5"
+        print(f"  ✓ IC computed: {result.ic_summary['ma5']['ic']}")
+
         # Check if any reports were generated
         if result.report_paths:
             print(f"  Tears report generated: {result.report_paths}")