Changes

src/core/modeling/modeling_batch.py

@@ -19,7 +19,6 @@ from sklearn.cross_decomposition import PLSRegression
 from sklearn.ensemble import GradientBoostingRegressor, AdaBoostRegressor, ExtraTreesRegressor
 from sklearn.tree import DecisionTreeRegressor
 from sklearn.neural_network import MLPRegressor
-from joblib import parallel_backend
 # 第三方模型导入
 # try:
 #     import lightgbm as lgb
@@ -43,6 +42,11 @@ import os
 from src.preprocessing.spectral_Preprocessing import Preprocessing
 
 
+def _sklearn_parallel_n_jobs() -> int:
+    """PyInstaller 等打包环境下，joblib loky 会再次启动当前 exe，出现多个同名进程。"""
+    return 1 if getattr(sys, "frozen", False) else -1
+
+
 class WaterQualityModelingBatch:
     """水质参数反演批量建模类"""
 
@@ -638,25 +642,26 @@ class WaterQualityModelingBatch:
         # 网格搜索 - 使用KFold代替StratifiedKFold
         cv_strategy = KFold(n_splits=cv_folds, shuffle=True, random_state=random_state)
 
+        _n_jobs = _sklearn_parallel_n_jobs()
         grid_search = GridSearchCV(
             base_model,
             config['params'],
             cv=cv_strategy,
             scoring=scoring,
-            n_jobs=-1,
+            n_jobs=_n_jobs,
             verbose=1
         )
 
         # 在训练集上训练模型
-        # with parallel_backend("threading", n_jobs=-1):
-        #     grid_search.fit(X_train, y_train)
         grid_search.fit(X_train, y_train)
         
         # 获取最佳模型
         best_model = grid_search.best_estimator_
 
         # 交叉验证评估（在训练集上）
-        cv_scores = cross_val_score(best_model, X_train, y_train, cv=cv_strategy, scoring=scoring)
+        cv_scores = cross_val_score(
+            best_model, X_train, y_train, cv=cv_strategy, scoring=scoring, n_jobs=_n_jobs
+        )
 
         # 计算训练集上的回归指标
         y_train_pred = best_model.predict(X_train)

src/gui/water_quality_gui.py

@@ -2263,7 +2263,7 @@ class Step6Panel(QWidget):
         
         for i, method in enumerate(preproc_methods):
             checkbox = QCheckBox(method)
-            checkbox.setChecked(True)  # 默认全选
+            checkbox.setChecked(method == 'SNV') # 默认全选
             self.preproc_checkboxes[method] = checkbox
             preproc_grid.addWidget(checkbox, i // 4, i % 4)
         
@@ -2344,7 +2344,7 @@ class Step6Panel(QWidget):
         
         for i, method in enumerate(split_methods):
             checkbox = QCheckBox(method)
-            checkbox.setChecked(True)  # 默认全选
+            checkbox.setChecked(method == 'spxy')  # 默认全选
             self.split_checkboxes[method] = checkbox
             split_grid.addWidget(checkbox, 0, i)
         
@@ -4812,7 +4812,7 @@ class Step6_5Panel(QWidget):
 
         for i, method in enumerate(preproc_methods):
             checkbox = QCheckBox(method)
-            checkbox.setChecked(True)
+            checkbox.setChecked(method == 'SNV')
             self.preproc_checkboxes[method] = checkbox
             preproc_grid.addWidget(checkbox, i // 4, i % 4)
 
@@ -4843,7 +4843,7 @@ class Step6_5Panel(QWidget):
             row_layout = QHBoxLayout()
             row_layout.setContentsMargins(0, 0, 0, 0)
             checkbox = QCheckBox(algorithm)
-            checkbox.setChecked(True)
+            checkbox.setChecked(algorithm == 'chl_a')
             spinbox = QSpinBox()
             spinbox.setRange(0, 500)
             spinbox.setValue(0)
@@ -5144,7 +5144,7 @@ class Step6_75Panel(QWidget):
         for i, method in enumerate(regression_methods):
             checkbox = QCheckBox(method)
             # 默认选择常用的方法
-            if method in ['linear', 'exponential', 'power', 'logarithmic']:
+            if method in ['linear', 'exponential', 'power']:
                 checkbox.setChecked(True)
             self.method_checkboxes[method] = checkbox
             method_grid.addWidget(checkbox, i // 3, i % 3)
@@ -5251,7 +5251,7 @@ class Step6_75Panel(QWidget):
         for i, col in enumerate(self.csv_columns):
             checkbox = QCheckBox(col)
             # 默认选择一些常见的指数列
-            if any(keyword in col.lower() for keyword in ['index', 'ratio', 'normalized', 'nd', 'b']):
+            if any(keyword in col.lower() for keyword in ['index', 'ratio', 'normalized', 'nd','BGA_','Chl_','Turb_']):
                 checkbox.setChecked(True)
             self.x_column_checkboxes[col] = checkbox
             self.x_columns_layout.addWidget(checkbox, i // 3, i % 3)
@@ -5260,7 +5260,8 @@ class Step6_75Panel(QWidget):
         for i, col in enumerate(self.csv_columns):
             checkbox = QCheckBox(col)
             # 默认选择一些常见的水质参数列
-            if any(keyword in col.lower() for keyword in ['chl', 'tn', 'tp', 'turbidity', 'do', 'ph', 'conductivity']):
+            target_keywords = ['Chlorophyll', 'COD', 'DO', 'PH', 'Temperature', 'spCond', 'Turbidity', 'TDS', 'Cl-', 'NO3-N', 'NH3-N', 'BGA', 'TT']
+            if any(keyword.lower() in col.lower() for keyword in target_keywords):
                 checkbox.setChecked(True)
             self.y_column_checkboxes[col] = checkbox
             self.y_columns_layout.addWidget(checkbox, i // 2, i % 2)
@@ -6990,7 +6991,6 @@ def main():
 
 
 if __name__ == "__main__":
-    #冻结，只显示1个exe
+    multiprocessing.freeze_support()
-    # multiprocessing.freeze_support()
     main()