feat(weight-evolver): run_simulation이 active W를 score_combination에 전달

lotto/app/generator.py

@@ -25,6 +25,7 @@ from .db import (
 )
 from .analyzer import build_analysis_cache, build_number_weights, score_combination
 from .utils import weighted_sample_6
+from .weight_evolver import get_active_weight
 
 
 def run_simulation(
@@ -54,6 +55,7 @@ def run_simulation(
     # ── 1. 통계 캐시 및 가중치 구성 (시뮬레이션 전체에서 재사용) ────────────
     cache = build_analysis_cache(draws)
     weights = build_number_weights(cache)
+    active_weights = get_active_weight()  # None → analyzer uses fixed default
 
     # ── 2. 후보 생성 및 스코어링 ──────────────────────────────────────────────
     candidates: List[Dict[str, Any]] = []
@@ -69,7 +71,7 @@ def run_simulation(
             continue
         seen_keys.add(key)
 
-        scores = score_combination(nums, cache)
+        scores = score_combination(nums, cache, weights=active_weights)
         candidates.append({
             "numbers": sorted(nums),
             **scores,