feat: expand alpha operator dispatch

tests/test_alpha_factors.py

@@ -9,6 +9,7 @@ import pytest
 from quant_engine.alpha_factors import (
     ALPHA158_REGISTRY,
     ALPHA158_PHASE1_OPERATOR_SPECS,
+    ALPHA158_PHASE2_OPERATOR_SPECS,
     alpha_001,
     alpha_002,
     alpha_003,
@@ -168,7 +169,9 @@ from quant_engine.alpha_factors import (
     alpha_157,
     alpha_158,
     evaluate_phase1_operator,
+    evaluate_phase2_operator,
     list_phase1_operators,
+    list_phase2_operators,
     correlation,
     covariance,
     decay_linear,
@@ -1328,3 +1331,135 @@ def test_phase1_dispatch_rejects_window_above_supported_limit():
 
     with pytest.raises(ValueError, match="maximum"):
         evaluate_phase1_operator("ts_mean", values, window=2**63)
+
+
+# ── v1.2.0 Phase 2: cumulative deterministic operator contract ─────────────
+
+
+def test_phase2_operator_catalog_is_cumulative_stable_and_serializable():
+    """Phase 2 exposes all existing building blocks without changing Phase 1."""
+    import json
+
+    phase1 = list_phase1_operators()
+    expected_phase2 = (
+        *phase1,
+        "ts_argmin",
+        "ts_argmax",
+        "product",
+        "returns",
+        "scale",
+        "signed_power",
+        "stddev",
+        "covariance",
+        "log",
+        "abs_series",
+        "sign",
+        "max_pair",
+        "min_pair",
+        "indneutralize",
+    )
+
+    assert list_phase2_operators() == expected_phase2
+    assert tuple(ALPHA158_PHASE2_OPERATOR_SPECS) == expected_phase2
+    assert tuple(ALPHA158_PHASE1_OPERATOR_SPECS) == phase1
+    json.dumps(ALPHA158_PHASE2_OPERATOR_SPECS)
+    for name, spec in ALPHA158_PHASE2_OPERATOR_SPECS.items():
+        assert spec["name"] == name
+        assert isinstance(spec["inputs"], list)
+        assert isinstance(spec["parameters"], list)
+        assert isinstance(spec["formula"], str)
+
+
+@pytest.mark.parametrize("name", ["ts_argmin", "ts_argmax", "product", "stddev"])
+def test_phase2_windowed_unary_dispatch_is_deterministic(name: str):
+    values = pd.Series([3.0, 1.0, 4.0, 2.0], index=["a", "b", "c", "d"])
+
+    first = evaluate_phase2_operator(name, values, window=3)
+    second = evaluate_phase2_operator(name, values, window=3)
+
+    pd.testing.assert_series_equal(first, second)
+    assert first.index.equals(values.index)
+    with pytest.raises(ValueError, match="window"):
+        evaluate_phase2_operator(name, values)
+
+
+@pytest.mark.parametrize("name", ["returns", "scale", "log", "abs_series", "sign"])
+def test_phase2_unary_dispatch_rejects_unused_arguments(name: str):
+    values = pd.Series([1.0, 2.0, 4.0], index=["a", "b", "c"])
+
+    result = evaluate_phase2_operator(name, values)
+
+    assert result.index.equals(values.index)
+    with pytest.raises(ValueError, match="window"):
+        evaluate_phase2_operator(name, values, window=2)
+    with pytest.raises(ValueError, match="secondary"):
+        evaluate_phase2_operator(name, values, secondary=values)
+
+
+@pytest.mark.parametrize(
+    ("name", "window"),
+    [("correlation", 2), ("covariance", 2), ("max_pair", None), ("min_pair", None)],
+)
+def test_phase2_binary_dispatch_requires_aligned_secondary(name: str, window: int | None):
+    values = pd.Series([1.0, 2.0, 3.0], index=["a", "b", "c"])
+    secondary = pd.Series([3.0, 2.0, 1.0], index=values.index)
+
+    result = evaluate_phase2_operator(name, values, secondary=secondary, window=window)
+
+    assert result.index.equals(values.index)
+    with pytest.raises(ValueError, match="secondary is required"):
+        evaluate_phase2_operator(name, values, window=window)
+    with pytest.raises(ValueError, match="secondary index"):
+        evaluate_phase2_operator(
+            name,
+            values,
+            secondary=secondary.rename(index={"c": "z"}),
+            window=window,
+        )
+
+
+def test_phase2_signed_power_requires_finite_numeric_exponent():
+    values = pd.Series([-4.0, 0.0, 9.0])
+
+    result = evaluate_phase2_operator("signed_power", values, exponent=0.5)
+
+    pd.testing.assert_series_equal(result, pd.Series([-2.0, 0.0, 3.0]))
+    for exponent in (None, True, float("inf"), float("nan"), "2"):
+        with pytest.raises(ValueError, match="exponent"):
+            evaluate_phase2_operator(  # type: ignore[arg-type]
+                "signed_power",
+                values,
+                exponent=exponent,
+            )
+
+
+def test_phase2_indneutralize_requires_aligned_groups():
+    values = pd.Series([1.0, 3.0, 10.0, 14.0], index=["a", "b", "c", "d"])
+    groups = pd.Series(["x", "x", "y", "y"], index=values.index)
+
+    result = evaluate_phase2_operator("indneutralize", values, groups=groups)
+
+    pd.testing.assert_series_equal(result, pd.Series([-1.0, 1.0, -2.0, 2.0], index=values.index))
+    with pytest.raises(ValueError, match="groups is required"):
+        evaluate_phase2_operator("indneutralize", values)
+    with pytest.raises(ValueError, match="groups index"):
+        evaluate_phase2_operator(
+            "indneutralize",
+            values,
+            groups=groups.rename(index={"d": "z"}),
+        )
+
+
+def test_phase2_dispatch_validates_primary_series_and_unused_parameters():
+    values = pd.Series([1.0, 2.0, 3.0])
+
+    with pytest.raises(TypeError, match="series must be a pandas Series"):
+        evaluate_phase2_operator("rank", [1.0, 2.0, 3.0])  # type: ignore[arg-type]
+    with pytest.raises(KeyError, match="not registered"):
+        evaluate_phase2_operator("unknown", values)
+    with pytest.raises(ValueError, match="exponent"):
+        evaluate_phase2_operator("rank", values, exponent=2.0)
+    with pytest.raises(ValueError, match="groups"):
+        evaluate_phase2_operator("rank", values, groups=pd.Series(["x", "x", "x"]))
+    with pytest.raises(ValueError, match="maximum"):
+        evaluate_phase2_operator("product", values, window=253)