Rename pipeline method names to match step numbers (Step4)
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@ -323,18 +323,17 @@ class WorkerThread(QThread):
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'step1': 'step1_generate_water_mask',
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'step2': 'step2_find_glint_area',
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'step3': 'step3_remove_glint',
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'step4': 'step4_process_csv',
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'step5': 'step5_extract_training_spectra',
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'step7': 'step7_water_quality_indices',
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'step8': 'step8_ml_modeling',
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'step4': 'step5_process_csv',
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'step5': 'step6_extract_spectra',
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'step7': 'step7_calc_indices',
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'step8': 'step8_train_ml',
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'step8_non_empirical_modeling': 'step8_non_empirical_modeling',
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'step8_qaa': 'step8_qaa_inversion',
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'step9': 'step9_watercolor_inversion',
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'step9_concentration': 'step9_concentration_inversion',
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'step10': 'step10_sampling',
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'step11_ml': 'step11_ml_prediction',
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'step10': 'step4_sampling',
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'step11_ml': 'step9_predict_ml',
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'step11': 'step11_non_empirical_prediction',
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'step14': 'step14_distribution_map'
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'step14': 'step10_map'
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}
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if step_name not in step_method_map:
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@ -350,12 +349,6 @@ class WorkerThread(QThread):
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result = method(**config)
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return result
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# step9_concentration_inversion 同理,必须透传完整 config dict
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if step_name == 'step9_concentration':
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method = getattr(self.pipeline, method_name)
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result = method(**config)
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return result
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# 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)
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# 非空才覆盖(遵循 feedback_never_overwrite_with_empty 原则)
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for key in ('_external_model', '_external_model_path',
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@ -68,7 +68,7 @@ class Step14BatchThread(QThread):
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kw["output_image_path"] = str(Path(self.output_dir_optional) / f"{stem}_distribution.png")
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else:
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kw["output_image_path"] = None
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pipeline.step14_distribution_map(**kw)
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pipeline.step10_map(**kw)
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self.finished_ok.emit(n)
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except Exception as e:
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self.failed.emit(f"{e}\n{traceback.format_exc()}")
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@ -124,7 +124,7 @@ class Step6FeaturePanel(QWidget):
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glint_mask_path = self.glint_mask_file.get_path()
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if glint_mask_path:
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config['glint_mask_path'] = glint_mask_path
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# 注意:step5_extract_training_spectra 不接受 output_path / training_csv_path
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# 注意:step6_extract_spectra 不接受 output_path / training_csv_path
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# 参数,输出路径由 pipeline 内部根据 training_spectra_dir 自动生成。
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return config
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