feat(analyzer): score_combination에 weights 파라미터 추가 (None=기존 fixed)

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

lotto/tests/test_analyzer_weighted.py

@@ -0,0 +1,45 @@
+import sys
+import os
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..", "app"))
+
+import pytest
+from analyzer import score_combination, build_analysis_cache
+
+
+@pytest.fixture
+def cache():
+    # build_analysis_cache expects [(drw_no, [n1,n2,n3,n4,n5,n6]), ...] tuples
+    fake_draws = [
+        (1, [1, 2, 3, 4, 5, 6]),
+        (2, [7, 8, 9, 10, 11, 12]),
+    ]
+    return build_analysis_cache(fake_draws)
+
+
+def test_score_default_uses_fixed_weights(cache):
+    """weights=None은 기존 fixed [0.25, 0.30, 0.20, 0.15, 0.10]과 동등."""
+    s = score_combination([1, 2, 3, 4, 5, 6], cache)
+    assert "score_total" in s
+    assert 0.0 <= s["score_total"] <= 2.0
+    for k in ("score_frequency", "score_fingerprint", "score_gap",
+              "score_cooccur", "score_diversity"):
+        assert k in s
+
+
+def test_score_with_custom_weights_sums_correctly(cache):
+    """weights=[1,0,0,0,0]은 score_total == score_frequency."""
+    s = score_combination([1, 2, 3, 4, 5, 6], cache, weights=[1.0, 0.0, 0.0, 0.0, 0.0])
+    assert s["score_total"] == pytest.approx(s["score_frequency"], rel=1e-3)
+
+
+def test_score_with_uniform_weights(cache):
+    """weights=[0.2]*5는 단순 평균."""
+    s = score_combination([1, 2, 3, 4, 5, 6], cache, weights=[0.2] * 5)
+    expected = 0.2 * (s["score_frequency"] + s["score_fingerprint"]
+                      + s["score_gap"] + s["score_cooccur"] + s["score_diversity"])
+    assert s["score_total"] == pytest.approx(expected, rel=1e-3)
+
+
+def test_score_weights_wrong_length_raises(cache):
+    with pytest.raises((ValueError, AssertionError)):
+        score_combination([1, 2, 3, 4, 5, 6], cache, weights=[0.5, 0.5])