feat: add Quant OS A-share baseline

tests/test_features.py

@@ -0,0 +1,83 @@
+import math
+import unittest
+from datetime import date
+
+from quant60.features import (
+    TrainOnlyFeaturePreprocessor,
+    build_executable_label,
+    compute_price_features,
+)
+from quant60.synthetic import generate_synthetic_bars
+
+
+class FeatureTests(unittest.TestCase):
+    def setUp(self):
+        self.bars = generate_synthetic_bars(
+            ["600000.XSHG"],
+            start_date="2024-01-02",
+            trading_days_count=150,
+            seed=7,
+            include_market_events=False,
+        )
+
+    def test_feature_as_of_does_not_change_when_future_bars_are_appended(self):
+        decision = self.bars[99].trading_date
+        early = compute_price_features(self.bars[:100], as_of=decision)
+        with_future = compute_price_features(self.bars, as_of=decision)
+        self.assertEqual(early.values, with_future.values)
+        self.assertEqual(early.history_end, decision)
+
+    def test_long_window_features_are_explicitly_missing(self):
+        snapshot = compute_price_features(self.bars[:30])
+        self.assertIsNone(snapshot.values["momentum_60"])
+        self.assertIsNotNone(snapshot.values["momentum_20"])
+
+    def test_preprocessor_uses_training_statistics_and_missing_indicator(self):
+        processor = TrainOnlyFeaturePreprocessor(winsor_fraction=0).fit(
+            [{"a": 1.0}, {"a": 2.0}, {"a": 3.0}]
+        )
+        transformed = processor.transform_one({"a": None})
+        self.assertEqual(transformed["a__missing"], 1.0)
+        self.assertAlmostEqual(transformed["a"], 0.0)
+        extreme = processor.transform_one({"a": 1_000_000.0})
+        expected = processor.transform_one({"a": 3.0})
+        self.assertEqual(extreme["a"], expected["a"])
+
+    def test_executable_label_uses_sessions_after_decision(self):
+        decision_index = 80
+        label = build_executable_label(
+            self.bars,
+            decision_date=self.bars[decision_index].trading_date,
+            horizon_sessions=5,
+        )
+        self.assertEqual(label.status, "OK")
+        self.assertEqual(
+            label.entry_date,
+            self.bars[decision_index + 1].trading_date,
+        )
+        self.assertEqual(
+            label.exit_date,
+            self.bars[decision_index + 6].trading_date,
+        )
+        self.assertTrue(math.isfinite(label.value))
+
+    def test_suspended_entry_is_censored_not_dropped(self):
+        bars = generate_synthetic_bars(
+            ["600000.XSHG"],
+            start_date=date(2024, 1, 2),
+            trading_days_count=40,
+            seed=7,
+            include_market_events=True,
+        )
+        decision = bars[10].trading_date
+        label = build_executable_label(
+            bars,
+            decision_date=decision,
+            horizon_sessions=5,
+        )
+        self.assertEqual(label.status, "NON_EXECUTABLE_CENSORED")
+        self.assertIsNone(label.value)
+
+
+if __name__ == "__main__":
+    unittest.main()