refactor(pipeline): 路径直接传输 — 统一 ctx 字段名/panel key/step 形参名

src/core/pipeline/runner.py

@@ -4,10 +4,8 @@ PipelineRunner：基于 StepSpec 声明式调度 14 个 step。
 
 设计要点：
   - StepSpec 声明 requires（ctx 字段名列表）+ produces（ctx 字段名列表）
-  - 默认约定：ctx 字段名去掉 `_path` 后缀 = step 方法形参名
-    例：ctx.water_mask_path → 形参 water_mask
-    例：ctx.raw_img_path → 形参 raw_img
-  - 可被 spec.parameter_map 覆盖
+  - 命名约定：ctx 字段名 == panel key 名 == step 形参名（全链路无翻译）
+  - 保留 spec.parameter_map 字段骨架供极少数特例覆盖（默认空 dict）
   - 调度顺序：按 PIPELINE_STEPS 列表顺序，requires 缺则 skip
   - 软取消：在每个 step 前检查 ctx.is_cancelled()
   - duck-typed pipeline：runner 只调 getattr(pipeline, method_name)，不强依赖类层级
@@ -48,101 +46,76 @@ class StepSpec:
 PIPELINE_STEPS: List[StepSpec] = [
     StepSpec(
         step_id="step1", method_name="step1_generate_water_mask",
-        requires=["raw_img_path"], produces=["water_mask_path"],
-        # ctx.raw_img_path → 形参 img_path（老 step1 形参名是 img_path，不是 raw_img）
-        parameter_map={"raw_img_path": "img_path"},
+        requires=["img_path"], produces=["water_mask_path"],
         description="水域掩膜生成（NDWI 或 SHP）",
     ),
     StepSpec(
         step_id="step2", method_name="step2_find_glint_area",
-        requires=["raw_img_path", "water_mask_path"], produces=["glint_mask_path"],
-        # raw_img_path→img_path；water_mask_path 不变
-        parameter_map={"raw_img_path": "img_path"},
+        requires=["img_path", "water_mask_path"], produces=["glint_mask_path"],
         description="耀斑区域检测",
     ),
     StepSpec(
         step_id="step3", method_name="step3_remove_glint",
-        requires=["deglint_img_path"], produces=["deglint_img_path"],
-        # deglint_img_path→img_path（老 step3 形参名是 img_path）
-        # 注意：glint_mask_path 不在 requires 中——step3 形参表无该参数，内部走 self.glint_mask_path 回退
-        parameter_map={"deglint_img_path": "img_path"},
+        requires=["img_path", "water_mask_path", "glint_mask_path"],
+        produces=["deglint_img_path"],
         description="耀斑去除",
     ),
     StepSpec(
         step_id="step4", method_name="step4_process_csv",
-        requires=["raw_csv_path"], produces=["processed_csv_path"],
-        # raw_csv_path→csv_path（老 step4 形参名是 csv_path）
-        parameter_map={"raw_csv_path": "csv_path"},
+        requires=["csv_path"], produces=["processed_csv_path"],
         description="CSV 异常值清洗",
     ),
     StepSpec(
         step_id="step5", method_name="step5_extract_training_spectra",
-        requires=["deglint_img_path", "processed_csv_path"], produces=["training_spectra_path"],
-        # processed_csv_path→csv_path（老 step5 形参名是 csv_path）；deglint_img_path 不变
-        parameter_map={"processed_csv_path": "csv_path"},
+        requires=["deglint_img_path", "csv_path", "boundary_path", "glint_mask_path"],
+        produces=["training_csv_path"],
         description="实测样本点光谱提取",
     ),
     StepSpec(
         step_id="step5_5", method_name="step5_5_calculate_water_quality_indices",
-        requires=["training_spectra_path"], produces=["indices_path"],
-        # 老 step5.5 形参是 training_spectra_path；ctx 字段同名，无需映射
-        parameter_map={},
+        requires=["training_csv_path"], produces=["indices_path"],
         description="水质光谱指数计算（optional）",
     ),
     StepSpec(
         step_id="step6", method_name="step6_train_models",
-        requires=["training_spectra_path"], produces=["models_dir"],
-        # training_spectra_path→training_csv_path（老 step6 形参名是 training_csv_path）
-        parameter_map={"training_spectra_path": "training_csv_path"},
+        requires=["training_csv_path"], produces=["models_dir"],
         description="ML 建模（GridSearchCV / AutoML）",
     ),
     StepSpec(
         step_id="step6_5", method_name="step6_5_non_empirical_modeling",
-        requires=["training_spectra_path"], produces=["models_dir"],
-        # training_spectra_path→csv_path（老 step6.5 形参名是 csv_path）
-        parameter_map={"training_spectra_path": "csv_path"},
+        requires=["training_csv_path"], produces=["models_dir"],
         description="非经验统计回归",
     ),
     StepSpec(
         step_id="step6_75", method_name="step6_75_custom_regression",
-        requires=["training_spectra_path"], produces=["models_dir"],
-        # training_spectra_path→csv_path（老 step6.75 形参名是 csv_path）
-        parameter_map={"training_spectra_path": "csv_path"},
+        requires=["training_csv_path"], produces=["models_dir"],
         description="自定义回归分析",
     ),
     StepSpec(
         step_id="step7", method_name="step7_generate_sampling_points",
         requires=["deglint_img_path", "water_mask_path"], produces=["sampling_csv_path"],
-        # 老 step7 形参是 deglint_img_path / water_mask_path；ctx 字段同名
-        parameter_map={},
         description="整景密集采样点生成 + 光谱提取",
     ),
     StepSpec(
         step_id="step8", method_name="step8_predict_water_quality",
         requires=["sampling_csv_path", "models_dir"], produces=["prediction_csv_path"],
-        parameter_map={},
         description="ML 模型预测（采样点）",
     ),
     StepSpec(
         step_id="step8_5", method_name="step8_5_predict_with_non_empirical_models",
-        requires=["sampling_csv_path"], produces=["prediction_dir"],
-        parameter_map={},
+        requires=["sampling_csv_path", "models_dir"], produces=["prediction_dir"],
         description="非经验模型预测",
     ),
     StepSpec(
         step_id="step8_75", method_name="step8_75_predict_with_custom_regression",
-        requires=["sampling_csv_path"], produces=["prediction_dir"],
-        parameter_map={},
+        requires=["sampling_csv_path", "models_dir", "formula_csv_path"],
+        produces=["prediction_dir"],
         description="自定义回归预测",
     ),
     StepSpec(
         step_id="step9", method_name="step9_generate_distribution_map",
-        requires=["prediction_csv_path"],
+        requires=["prediction_csv_path", "boundary_shp_path"],
         produces=["distribution_map_path"],
-        # 老 step9 形参是 prediction_csv_path / boundary_shp_path；ctx 字段同名
-        # 注意：sampling_csv_path / water_mask_path 不在 requires 中——step9 形参表无该参数，
-        # 内部走 self.sampling_csv_path / self.water_mask_path 回退
-        parameter_map={},
         description="克里金插值成图",
     ),
 ]
@@ -157,7 +130,7 @@ class PipelineRunner:
 
     用法：
         runner = PipelineRunner(pipeline_instance)
-        ctx = PipelineContext(raw_img_path=..., ...)
+        ctx = PipelineContext(img_path=..., ...)
         result_ctx = runner.run(ctx)
     """