feat(data): parse 3-agency PDF transition matrices to CSV #task-290

- New: data/parse_pdf_matrices.py (KR/NICE/SCI PDF parser)
  - KR: text-based parser (space-separated numbers + dashes)
  - NICE: text-based parser (clean numeric format)
  - SCI: pdfplumber table extraction (column-position-aware)
  - WR redistribution, B이하→B mapping, CCC extrapolation from PD patterns
- Modified: data/transition_matrices.py (added source='real' loader)
- Modified: config.yaml (data.transition_source: 'real')
- Modified: main.py (reads transition source from config)
- Output: 112 CSV files (KR/NICE/SCI/AVG × 28 years)

data/transition_matrices.py

@@ -181,6 +181,9 @@ def load_transition_matrices(
     if source == "builtin":
         return _build_sample_matrices()
     
+    elif source == "real":
+        return _load_real_matrices(data_dir)
+    
     elif source == "csv":
         if data_dir is None:
             raise ValueError("CSV 로딩시 data_dir를 지정해야 합니다.")
@@ -195,6 +198,43 @@ def load_transition_matrices(
         raise ValueError(f"지원하지 않는 소스: {source}")
 
 
+def _load_real_matrices(data_dir: Optional[str] = None) -> Dict[int, np.ndarray]:
+    """
+    실제 3사 전이행렬 로딩 (data/real/AVG_YYYY.csv)
+    
+    parse_pdf_matrices.py 로 생성된 3사 평균 CSV 사용.
+    """
+    if data_dir is None:
+        data_dir = str(Path(__file__).parent / "real")
+    real_dir = Path(data_dir)
+    
+    if not real_dir.exists():
+        raise FileNotFoundError(
+            f"실제 전이행렬 디렉토리가 없습니다: {real_dir}\n"
+            "먼저 python data/parse_pdf_matrices.py 를 실행하세요."
+        )
+    
+    matrices = {}
+    for csv_file in sorted(real_dir.glob("AVG_*.csv")):
+        year = _extract_year_from_filename(csv_file.name)
+        if year is not None:
+            df = pd.read_csv(csv_file, index_col=0)
+            tm = df.values.astype(float)
+            for i in range(tm.shape[0]):
+                row_sum = tm[i].sum()
+                if row_sum > 0:
+                    tm[i] /= row_sum
+            matrices[year] = tm
+    
+    if not matrices:
+        raise FileNotFoundError(
+            f"AVG_*.csv 파일이 없습니다: {real_dir}\n"
+            "먼저 python data/parse_pdf_matrices.py 를 실행하세요."
+        )
+    
+    return matrices
+
+
 def _load_from_csv(data_dir: Path, pattern: str) -> Dict[int, np.ndarray]:
     """CSV 파일에서 전이행렬 로딩 (파일명에 연도 포함 예상)"""
     matrices = {}