Unit-Stärken präzisiert: Stat-Proxy-Multiplikatoren + gelernte Unit-Gewichte

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

backend/tests/test_learn.py

@@ -50,3 +50,15 @@ def test_empty_rows():
     assert learned["traits"] == {}
     assert learned["pairs"] == {}
     assert learned["n_boards"] == 0
+
+
+def test_unit_multipliers_learned():
+    def row(placement, unit):
+        units = [{"character_id": unit, "tier": 2, "itemNames": []}]
+        return (placement, json.dumps(units), json.dumps([]), json.dumps([]))
+
+    rows = [row(1, "TFT17_Strong") for _ in range(150)]
+    rows += [row(8, "TFT17_Weak") for _ in range(150)]
+    learned = learn(rows)
+    assert learned["units"]["TFT17_Strong"] > 1.05
+    assert learned["units"]["TFT17_Weak"] < 0.95