test+fix: 自动化测试18条全过 + 量比基准排除当日 + 截面打分最低有效因子数修正

tests/test_anomaly.py

@@ -0,0 +1,52 @@
+# -*- coding: utf-8 -*-
+"""异常检测规则单测"""
+import sys, os, warnings
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..'))
+warnings.filterwarnings('ignore')
+
+import numpy as np
+import pandas as pd
+import pytest
+from tests.helpers import gen_kline
+
+from src.analysis.anomaly_detect import detect_anomalies
+
+
+class TestAnomalyRules:
+
+    def test_volume_spike_detected(self):
+        """天量应被检出（放大到 15 倍均量确保触发）"""
+        k = gen_kline(50, vol_pct=0.003, seed=1)
+        base_vol = k['volume'].iloc[-20:-1].mean()
+        k.loc[k.index[-1], 'volume'] = base_vol * 15   # 15 倍天量
+        found = detect_anomalies('test', '测试股', k)
+        types = [a['type'] for a in found]
+        assert '天量' in types, f'天量未检出，检出: {types}'
+
+    def test_big_swing_detected(self):
+        """单日大涨 8% 应被检出"""
+        k = gen_kline(40, vol_pct=0.005, seed=2)
+        k.loc[k.index[-1], 'close'] = k['close'].iloc[-2] * 1.08
+        found = detect_anomalies('test', '测试股', k)
+        types = [a['type'] for a in found]
+        assert '大幅波动' in types, f'大幅波动未检出，检出: {types}'
+
+    def test_no_anomaly_in_quiet_market(self):
+        """平静市场不应大量误报"""
+        k = gen_kline(40, base=10, trend=0.0001, vol_pct=0.003, seed=3)
+        found = detect_anomalies('test', '测试股', k)
+        assert len(found) <= 1, f'平静市场不应大量报异常，实际 {len(found)} 条'
+
+    def test_output_format(self):
+        """输出包含必要字段"""
+        k = gen_kline(40, vol_pct=0.02, seed=4)
+        found = detect_anomalies('test', '测试股', k)
+        for a in found:
+            assert 'code' in a and 'type' in a and 'severity' in a and 'desc' in a
+
+    def test_severity_range(self):
+        """severity 在 1-5 范围内"""
+        k = gen_kline(40, vol_pct=0.05, seed=5)
+        found = detect_anomalies('test', '测试股', k)
+        for a in found:
+            assert 1 <= a['severity'] <= 5