fix: PhysicalFeatureExtractor 修复 ndarray 输入时波长丢失问题

- SimpleImputer 把 DataFrame → ndarray，PhysicalFeatureExtractor.fit()
  收不到列名导致 ValueError: 必须在 __init__ 中提供 wavelengths
- get_preprocessing_transformer 新增 wavelengths 可选参数
- train_single_model 在 DualStream_MNF 时提取 X_raw 波长列表传入工厂
- PhysicalFeatureExtractor 已有 ndarray + wavelengths 参数的处理分支

src/core/modeling/modeling_batch.py

@@ -611,7 +611,11 @@ class WaterQualityModelingBatch:
             base_model.set_params(verbose=-1)
 
         # ============ 关键：把预处理器塞进 Pipeline ============
-        preproc = get_preprocessing_transformer(preprocess_method)
+        # DualStream_MNF 需要传入波长列表，供 PhysicalFeatureExtractor 定位波段
+        _wl_list = None
+        if preprocess_method == "DualStream_MNF":
+            _wl_list = self._extract_train_wavelengths(X_raw.columns)
+        preproc = get_preprocessing_transformer(preprocess_method, wavelengths=_wl_list)
         pipeline = Pipeline([
             ('imputer', SimpleImputer(strategy='median')),
             ('preproc', preproc),

src/preprocessing/spectral_Preprocessing.py

@@ -501,7 +501,7 @@ _PREPROCESSING_TRANSFORMERS = {
 }
 
 
-def get_preprocessing_transformer(method: str):
+def get_preprocessing_transformer(method: str, wavelengths=None):
     """根据预处理方法名返回 sklearn 兼容的 Transformer 实例。
 
     - method 为 "None" 或 None：返回 IdentityTransformer
@@ -512,6 +512,8 @@ def get_preprocessing_transformer(method: str):
 
     Args:
         method: 预处理方法名
+        wavelengths: DualStream_MNF 时需要传入波长列表(float)，
+                     供 PhysicalFeatureExtractor 定位波段列
 
     Returns:
         sklearn 兼容的 Transformer 实例（可直接放入 Pipeline）
@@ -521,7 +523,7 @@ def get_preprocessing_transformer(method: str):
     if method == "DualStream_MNF":
         from sklearn.pipeline import FeatureUnion
         return FeatureUnion([
-            ('physical', PhysicalFeatureExtractor()),
+            ('physical', PhysicalFeatureExtractor(wavelengths=wavelengths)),
             ('mnf',      MNFTransformer(n_components=10)),
         ])
     if method not in _PREPROCESSING_TRANSFORMERS: