feat(step9): 新增浓度反演模块及 GUI 面板

src/gui/core/worker_thread.py

@@ -325,9 +325,11 @@ class WorkerThread(QThread):
             'step3': 'step3_remove_glint',
             'step4': 'step4_process_csv',
             'step5': 'step5_extract_training_spectra',
-            'step8': 'step8_water_quality_indices',
+            'step6': 'step6_water_quality_indices',
             'step7': 'step7_ml_modeling',
             'step8_non_empirical_modeling': 'step8_non_empirical_modeling',
+            'step8_qaa': 'step8_qaa_inversion',
+            'step9_concentration': 'step9_concentration_inversion',
             'step9': 'step9_custom_regression',
             'step10': 'step10_sampling',
             'step11_ml': 'step11_ml_prediction',
@@ -342,6 +344,19 @@ class WorkerThread(QThread):
         method_name = step_method_map[step_name]
         step_config = dict(config.get(step_name, {}))
 
+        # step8_qaa_inversion 内部使用 config.get('step8_qaa', {}) 读取内层，
+        # 必须透传完整 config dict（含外层 step_name key）
+        if step_name == 'step8_qaa':
+            method = getattr(self.pipeline, method_name)
+            result = method(**config)
+            return result
+
+        # step9_concentration_inversion 同理，必须透传完整 config dict
+        if step_name == 'step9_concentration':
+            method = getattr(self.pipeline, method_name)
+            result = method(**config)
+            return result
+
         # 透传面板顶层传入的外部预训练模型（GUI step11_prediction_panel 通过 config['_external_model'] 传入）
         # 非空才覆盖（遵循 feedback_never_overwrite_with_empty 原则）
         for key in ('_external_model', '_external_model_path',
@@ -449,12 +464,12 @@ class WorkerThread(QThread):
                 "    → 请确认「流程步骤-阶段五」中已填写有效的边界 shp 路径。"
             )
 
-        # ── 步骤8（水质指数）：训练光谱 CSV ──
-        step8_cfg = config.get('step8', {})
-        training_csv = step8_cfg.get('training_csv_path')
+        # ── 步骤6（水质光谱指数）：训练光谱 CSV ──
+        step6_cfg = config.get('step6', {})
+        training_csv = step6_cfg.get('training_csv_path')
         if training_csv and not os.path.isfile(training_csv):
             errors.append(
-                f"步骤 8（水质指数）：训练光谱文件不存在：\n    {training_csv}\n"
+                f"步骤 6（水质光谱指数）：训练光谱文件不存在：\n    {training_csv}\n"
                 "    → 请确认步骤 5 已成功运行并生成了训练光谱。"
             )