From 6d49e80c7e9176b5aabc79e67278dd4223ecaf0c Mon Sep 17 00:00:00 2001
From: dxc <duxingchen@iris-rs.cn>
Date: Tue, 9 Jun 2026 13:38:28 +0800
Subject: [PATCH] =?UTF-8?q?fix(gui):=20step8=5Fpanel=E6=94=B9=E7=94=A8Data?=
 =?UTF-8?q?PreparationStep=E8=AE=A1=E7=AE=97=E6=B0=B4=E8=B4=A8=E6=8C=87?=
 =?UTF-8?q?=E6=95=B0=EF=BC=8C=E7=BB=9F=E4=B8=80pipeline=E4=B8=8E=E9=9D=A2?=
 =?UTF-8?q?=E6=9D=BF=E7=8B=AC=E7=AB=8B=E8=BF=90=E8=A1=8C=E8=B7=AF=E5=BE=84?=
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---
 src/gui/panels/step8_panel.py | 37 +++++++++++++++++++++++++++--------
 1 file changed, 29 insertions(+), 8 deletions(-)

diff --git a/src/gui/panels/step8_panel.py b/src/gui/panels/step8_panel.py
index 74a084a..092f59b 100644
--- a/src/gui/panels/step8_panel.py
+++ b/src/gui/panels/step8_panel.py
@@ -346,17 +346,38 @@ class Step8Panel(QWidget):
         output_mode = config['output_mode']
 
         try:
-            from src.utils.water_index import WaterQualityIndexCalculator
-
-            calculator = WaterQualityIndexCalculator(self.builtin_formula_path)
+            from src.core.steps.data_preparation_step import DataPreparationStep
 
             spec_df = pd.read_csv(training_path)
             x_col, y_col = self._get_coord_cols(spec_df)
 
-            results_df = calculator.calculate_many(formula_names, spec_df)
-            output_df = pd.concat([spec_df, results_df], axis=1)
+            # 构建 formula_csv_path（使用内置 waterindex.csv）
+            import os
+            formula_csv_path = self.builtin_formula_path
+            if not formula_csv_path or not os.path.exists(formula_csv_path):
+                # 尝试从 src/gui/model/ 目录找
+                possible_path = os.path.join(os.path.dirname(os.path.dirname(os.path.dirname(__file__))), 'gui', 'model', 'waterindex.csv')
+                if os.path.exists(possible_path):
+                    formula_csv_path = possible_path
 
             work_dir = self._get_work_dir()
+
+            # 调用 DataPreparationStep 的静态方法计算水质指数（宽表输出）
+            indices_csv_path = DataPreparationStep.calculate_water_quality_indices(
+                training_csv_path=training_path,
+                formula_csv_file=formula_csv_path,
+                formula_names=formula_names,
+                output_file=None,  # 不在此处指定输出，由下面的双轨输出逻辑接管
+                enabled=True,
+                output_dir=work_dir if work_dir else os.getcwd(),
+            )
+
+            # 读取计算结果（宽表）
+            if indices_csv_path and os.path.exists(indices_csv_path):
+                output_df = pd.read_csv(indices_csv_path)
+            else:
+                output_df = spec_df  # fallback
+
             track_a_path = None
             track_b_dir = None
 
@@ -379,12 +400,12 @@ class Step8Panel(QWidget):
                 coord_y = spec_df[y_col].values if y_col in spec_df.columns else np.zeros(len(spec_df))
 
                 for formula_name in formula_names:
-                    if formula_name not in results_df.columns:
+                    if formula_name not in output_df.columns:
                         continue
                     single_df = pd.DataFrame({
                         'x_coord': coord_x,
                         'y_coord': coord_y,
-                        'value': results_df[formula_name].values,
+                        'value': output_df[formula_name].values,
                     })
                     safe_name = formula_name.replace('/', '_').replace(' ', '_')
                     out_path = os.path.join(track_b_dir, f"{safe_name}_prediction.csv")
@@ -397,7 +418,7 @@ class Step8Panel(QWidget):
             )
 
         except ImportError as e:
-            QMessageBox.critical(self, "依赖错误", f"无法导入 WaterQualityIndexCalculator:\n{e}")
+            QMessageBox.critical(self, "依赖错误", f"无法导入模块:\n{e}")
         except Exception as e:
             import traceback
             QMessageBox.critical(self, "计算失败", f"原因: {str(e)}\n{traceback.format_exc()}")
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