扩展指标

2026-07-09 05:08:16 +08:00
commit 308c46ab9a
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+"""Unit tests for ferro_ta.indicators.price_transform"""
+
+import numpy as np
+
+from ferro_ta.indicators.price_transform import AVGPRICE, MEDPRICE, TYPPRICE, WCLPRICE
+
+# ---------------------------------------------------------------------------
+# Shared fixtures
+# ---------------------------------------------------------------------------
+
+O = np.array([10.0, 11.0, 12.0, 13.0])
+H = np.array([12.0, 13.0, 14.0, 15.0])
+L = np.array([9.0, 10.0, 11.0, 12.0])
+C = np.array([11.0, 12.0, 13.0, 14.0])
+
+
+# ---------------------------------------------------------------------------
+# AVGPRICE
+# ---------------------------------------------------------------------------
+
+
+class TestAVGPRICE:
+    def test_known_formula(self):
+        result = AVGPRICE(O, H, L, C)
+        expected = (O + H + L + C) / 4.0
+        np.testing.assert_allclose(result, expected, rtol=1e-10)
+
+    def test_first_bar(self):
+        result = AVGPRICE(O, H, L, C)
+        np.testing.assert_allclose(result[0], (10 + 12 + 9 + 11) / 4.0, rtol=1e-10)
+
+    def test_no_nan(self):
+        result = AVGPRICE(O, H, L, C)
+        assert np.all(np.isfinite(result))
+
+    def test_length(self):
+        assert len(AVGPRICE(O, H, L, C)) == len(O)
+
+
+# ---------------------------------------------------------------------------
+# MEDPRICE
+# ---------------------------------------------------------------------------
+
+
+class TestMEDPRICE:
+    def test_known_formula(self):
+        result = MEDPRICE(H, L)
+        expected = (H + L) / 2.0
+        np.testing.assert_allclose(result, expected, rtol=1e-10)
+
+    def test_first_bar(self):
+        result = MEDPRICE(H, L)
+        np.testing.assert_allclose(result[0], (12 + 9) / 2.0, rtol=1e-10)
+
+    def test_no_nan(self):
+        result = MEDPRICE(H, L)
+        assert np.all(np.isfinite(result))
+
+    def test_length(self):
+        assert len(MEDPRICE(H, L)) == len(H)
+
+
+# ---------------------------------------------------------------------------
+# TYPPRICE
+# ---------------------------------------------------------------------------
+
+
+class TestTYPPRICE:
+    def test_known_formula(self):
+        result = TYPPRICE(H, L, C)
+        expected = (H + L + C) / 3.0
+        np.testing.assert_allclose(result, expected, rtol=1e-10)
+
+    def test_first_bar(self):
+        result = TYPPRICE(H, L, C)
+        np.testing.assert_allclose(result[0], (12 + 9 + 11) / 3.0, rtol=1e-10)
+
+    def test_no_nan(self):
+        result = TYPPRICE(H, L, C)
+        assert np.all(np.isfinite(result))
+
+    def test_length(self):
+        assert len(TYPPRICE(H, L, C)) == len(H)
+
+
+# ---------------------------------------------------------------------------
+# WCLPRICE
+# ---------------------------------------------------------------------------
+
+
+class TestWCLPRICE:
+    def test_known_formula(self):
+        result = WCLPRICE(H, L, C)
+        expected = (H + L + 2.0 * C) / 4.0
+        np.testing.assert_allclose(result, expected, rtol=1e-10)
+
+    def test_first_bar(self):
+        result = WCLPRICE(H, L, C)
+        np.testing.assert_allclose(result[0], (12 + 9 + 2 * 11) / 4.0, rtol=1e-10)
+
+    def test_no_nan(self):
+        result = WCLPRICE(H, L, C)
+        assert np.all(np.isfinite(result))
+
+    def test_close_weight_double(self):
+        # WCLPRICE weights close twice vs TYPPRICE
+        wcl = WCLPRICE(H, L, C)
+        # On a rising series (H > L > 0), WCLPRICE > TYPPRICE when C > (H+L)/2
+        # Just verify formula correctness already done above
+        assert np.all(np.isfinite(wcl))
+
+    def test_length(self):
+        assert len(WCLPRICE(H, L, C)) == len(H)