refactor(gui): 重命名面板序号 step4-11，采样点布设移至 step4，ML 建模移至 step9
This commit is contained in:
@ -20,13 +20,16 @@ from typing import Any, Dict, List, Optional, Set
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# ============================================================
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STEP_MAP_OLD_TO_NEW: Dict[str, str] = {
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"step5_5": "step8",
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"step5_5": "step7",
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"step6_5": "step8_non_empirical_modeling",
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"step6_75": "step9",
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"step8_5": "step11",
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"step8_75": "step12",
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"step7": "step10",
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"step7": "step8",
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"step8": "step7",
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"step9": "step14",
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"step10": "step4",
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"step11_ml": "step10",
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"step11": "step11",
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}
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STEP_MAP_NEW_TO_OLD: Dict[str, str] = {v: k for k, v in STEP_MAP_OLD_TO_NEW.items()}
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@ -115,14 +115,14 @@ PIPELINE_STEPS: List[StepSpec] = [
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description="实测样本点光谱提取",
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),
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StepSpec(
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step_id="step8", method_name="step8_water_quality_indices",
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step_id="step7", method_name="step7_water_quality_indices",
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requires=["training_csv_path"], produces=["indices_path", "trad_indices_dir"],
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required_input_files=["training_csv_path"],
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output_file="{work_dir}/6_water_quality_indices/training_spectra_indices.csv",
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description="水质光谱指数计算（双轨输出：A轨宽表 + B轨单文件）",
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description="水质参数指数计算（双轨输出：A轨宽表 + B轨单文件）",
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),
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StepSpec(
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step_id="step7", method_name="step7_ml_modeling",
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step_id="step8", method_name="step8_ml_modeling",
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requires=["training_csv_path"], produces=["models_dir"],
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required_input_files=["training_csv_path"],
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output_file="{work_dir}/7_Supervised_Model_Training/best_models.pkl",
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@ -138,18 +138,17 @@ PIPELINE_STEPS: List[StepSpec] = [
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description="非经验统计回归",
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),
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StepSpec(
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step_id="step9", method_name="step9_custom_regression",
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requires=["indices_path"], produces=["models_dir"],
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parameter_map={"indices_path": "csv_path"},
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required_input_files=["indices_path"],
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output_file="{work_dir}/9_Custom_Regression_Modeling/custom_regression_models.pkl",
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description="自定义回归分析",
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step_id="step9", method_name="step9_watercolor_inversion",
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requires=["deglint_img_path", "water_mask_path"], produces=["watercolor_index_dir"],
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required_input_files=["deglint_img_path"],
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output_file="{work_dir}/9_WaterColor_Index_Images",
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description="水色指数反演（BSQ 影像直接处理）",
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),
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StepSpec(
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step_id="step10", method_name="step10_sampling",
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requires=["deglint_img_path", "water_mask_path"], produces=["sampling_csv_path"],
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required_input_files=["deglint_img_path", "water_mask_path"],
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output_file="{work_dir}/10_sampling/sampling_spectra.csv",
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output_file="{work_dir}/4_sampling/sampling_spectra.csv",
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description="整景密集采样点生成 + 光谱提取",
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),
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StepSpec(
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@ -167,15 +166,6 @@ PIPELINE_STEPS: List[StepSpec] = [
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output_file="{work_dir}/11_12_13_predictions/non_empirical_predictions",
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description="非经验模型预测",
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),
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StepSpec(
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step_id="step12", method_name="step12_custom_regression_prediction",
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requires=["sampling_csv_path", "models_dir", "formula_csv_path"],
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produces=["prediction_dir"],
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parameter_map={"models_dir": "custom_regression_dir"},
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required_input_files=["sampling_csv_path", "models_dir", "formula_csv_path"],
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output_file="{work_dir}/11_12_13_predictions/custom_regression_predictions",
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description="自定义回归预测",
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),
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StepSpec(
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step_id="step14", method_name="step14_distribution_map",
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requires=["prediction_csv_path", "boundary_shp_path"],
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@ -59,14 +59,14 @@ class PreflightDialog(QDialog):
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"step3": ("耀斑去除", 2),
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"step4": ("数据清洗", 3),
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"step5": ("特征构建", 4),
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"step8": ("水质指数", 5),
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"step7": ("监督建模", 6),
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"step7": ("水质指数", 5),
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"step8": ("监督建模", 6),
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"step8_non_empirical_modeling": ("回归建模", 7),
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"step9": ("自定义回归建模", 8),
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"step10": ("采样点布设", 9),
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"step11_ml": ("监督预测", 10),
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"step11": ("回归预测", 11),
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"step12": ("自定义回归预测", 12),
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"step9": ("水色指数反演", 8),
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"step9_concentration": ("浓度反演", 9),
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"step10": ("采样点布设", 10),
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"step11_ml": ("监督预测", 11),
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"step11": ("回归预测", 12),
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"step14": ("专题图生成", 13),
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}
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@ -325,16 +325,15 @@ class WorkerThread(QThread):
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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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'step6': 'step6_water_quality_indices',
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'step7': 'step7_ml_modeling',
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'step7': 'step7_water_quality_indices',
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'step8': 'step8_ml_modeling',
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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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'step9': 'step9_custom_regression',
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'step10': 'step10_sampling',
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'step11_ml': 'step11_ml_prediction',
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'step11': 'step11_non_empirical_prediction',
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'step12': 'step12_custom_regression_prediction',
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'step14': 'step14_distribution_map'
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}
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@ -1,7 +1,7 @@
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#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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"""
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Step8 面板 - 机器学习预测
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Step11 面板 - 机器学习预测
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"""
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import os
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@ -19,7 +19,7 @@ from src.gui.components.custom_widgets import FileSelectWidget
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from src.gui.styles import ModernStylesheet
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class Step11MlPanel(QWidget):
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class Step10MlPanel(QWidget):
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"""步骤11：机器学习预测"""
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def __init__(self, parent=None):
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super().__init__(parent)
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@ -190,7 +190,7 @@ class Step11MlPanel(QWidget):
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"""浏览模型母文件夹，自动扫描子目录中的 .joblib 文件"""
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default = self._get_default_work_dir()
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if default:
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default = os.path.join(default, "7_Supervised_Model_Training")
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default = os.path.join(default, "9_supervised_modeling")
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dir_path = QFileDialog.getExistingDirectory(
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self,
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"选择模型母文件夹",
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@ -216,7 +216,6 @@ class Step11MlPanel(QWidget):
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]
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if not joblib_files:
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continue
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# 每个子目录只取第一个 .joblib 文件（与 batch 逻辑一致）
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joblib_path = joblib_files[0].path
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try:
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loaded = joblib.load(joblib_path)
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@ -319,43 +318,41 @@ class Step11MlPanel(QWidget):
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main_window = self.window()
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# 1. 尝试从 Step7 界面读取全湖采样点 CSV 路径
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if main_window and hasattr(main_window, 'step10_panel'):
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step7_widget = getattr(main_window.step10_panel, 'output_file', None)
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step7_output_path = ""
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if hasattr(step7_widget, 'get_path'):
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step7_output_path = step7_widget.get_path() or ""
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elif hasattr(step7_widget, 'text'):
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step7_output_path = step7_widget.text() or ""
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# 1. 尝试从 Step4（采样点布设）读取全湖采样点 CSV 路径
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if main_window and hasattr(main_window, 'step4_sampling_panel'):
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step4_widget = getattr(main_window.step4_sampling_panel, 'output_file', None)
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step4_output_path = ""
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if hasattr(step4_widget, 'get_path'):
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step4_output_path = step4_widget.get_path() or ""
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elif hasattr(step4_widget, 'text'):
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step4_output_path = step4_widget.text() or ""
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if step7_output_path:
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# 若为相对路径，使用 work_dir 合成为绝对路径
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if not os.path.isabs(step7_output_path):
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step7_output_path = os.path.join(self.work_dir or '', step7_output_path).replace('\\', '/')
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if step4_output_path:
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if not os.path.isabs(step4_output_path):
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step4_output_path = os.path.join(self.work_dir or '', step4_output_path).replace('\\', '/')
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existing = self.sampling_csv_file.get_path()
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if not existing or not existing.strip():
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self.sampling_csv_file.set_path(step7_output_path)
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self.sampling_csv_file.set_path(step4_output_path)
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# 2. 尝试从 Step6 界面读取监督模型目录
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if main_window and hasattr(main_window, 'step7_panel'):
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step6_widget = getattr(main_window.step7_panel, 'output_dir', None)
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step6_models_dir = ""
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if hasattr(step6_widget, 'get_path'):
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step6_models_dir = step6_widget.get_path() or ""
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elif hasattr(step6_widget, 'text'):
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step6_models_dir = step6_widget.text() or ""
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# 2. 尝试从 Step9（监督建模）读取模型目录
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if main_window and hasattr(main_window, 'step9_panel'):
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step9_widget = getattr(main_window.step9_panel, 'output_dir', None)
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step9_models_dir = ""
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if hasattr(step9_widget, 'get_path'):
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step9_models_dir = step9_widget.get_path() or ""
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elif hasattr(step9_widget, 'text'):
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step9_models_dir = step9_widget.text() or ""
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if step6_models_dir:
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# 若为相对路径，使用 work_dir 合成为绝对路径
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if not os.path.isabs(step6_models_dir):
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step6_models_dir = os.path.join(self.work_dir or '', step6_models_dir).replace('\\', '/')
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if step9_models_dir:
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if not os.path.isabs(step9_models_dir):
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step9_models_dir = os.path.join(self.work_dir or '', step9_models_dir).replace('\\', '/')
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existing_models = self.models_dir_file.get_path()
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if not existing_models or not existing_models.strip():
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self.models_dir_file.set_path(step6_models_dir)
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self.models_dir_file.set_path(step9_models_dir)
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# 3. 自动填充输出路径（机器学习预测目录）
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if self.work_dir:
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output_dir = os.path.join(self.work_dir, "11_12_13_predictions/Machine_Learning_Prediction")
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output_dir = os.path.join(self.work_dir, "11_ml_prediction")
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os.makedirs(output_dir, exist_ok=True)
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existing_out = self.output_file.get_path()
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if not existing_out or not existing_out.strip():
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@ -378,7 +375,7 @@ class Step11MlPanel(QWidget):
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"""浏览模型目录"""
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default = self._get_default_work_dir()
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if default:
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default = os.path.join(default, "7_Supervised_Model_Training")
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default = os.path.join(default, "9_supervised_modeling")
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dir_path = QFileDialog.getExistingDirectory(self, "选择模型目录", default)
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if dir_path:
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self.models_dir_file.set_path(dir_path)
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@ -416,7 +413,7 @@ class Step11MlPanel(QWidget):
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self.output_file.set_path(config['output_path'])
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def run_step(self):
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"""独立运行步骤8"""
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"""独立运行步骤11"""
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sampling_csv_path = self.sampling_csv_file.get_path()
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if not sampling_csv_path:
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QMessageBox.warning(self, "输入错误", "请选择采样光谱CSV文件！")
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@ -431,7 +428,6 @@ class Step11MlPanel(QWidget):
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"请先点击「浏览...」按钮选择模型母文件夹！",
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)
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return
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# 只传递用户勾选的模型
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checked_dict = self._get_checked_models_dict()
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if not checked_dict:
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QMessageBox.warning(
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@ -17,7 +17,7 @@ from src.gui.components.custom_widgets import FileSelectWidget
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from src.gui.styles import ModernStylesheet
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class Step11Panel(QWidget):
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class Step11NonEmpiricalPanel(QWidget):
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"""步骤11：非经验模型预测"""
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def __init__(self, parent=None):
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super().__init__(parent)
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@ -1,185 +0,0 @@
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#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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"""
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Step4 面板 - 数据预处理
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"""
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import os
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import pandas as pd
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from PyQt5.QtWidgets import (
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QWidget, QVBoxLayout, QGroupBox, QHBoxLayout, QLabel,
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QSpinBox, QPushButton, QCheckBox, QTableView,
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QAbstractItemView, QHeaderView, QMessageBox,
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)
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from PyQt5.QtCore import Qt
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from src.gui.components.custom_widgets import FileSelectWidget
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from src.gui.styles import ModernStylesheet
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class Step4Panel(QWidget):
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"""步骤4：数据预处理"""
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def __init__(self, parent=None):
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super().__init__(parent)
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self.init_ui()
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def init_ui(self):
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layout = QVBoxLayout()
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# 标题
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# CSV文件
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self.csv_file = FileSelectWidget(
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"水质参数文件:",
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"CSV Files (*.csv);;All Files (*.*)"
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)
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layout.addWidget(self.csv_file)
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hint = QLabel("提示: 处理CSV文件，筛选剔除异常值")
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hint.setStyleSheet("color: #666; font-size: 10px;")
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layout.addWidget(hint)
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preview_group = QGroupBox("CSV数据预览")
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preview_layout = QVBoxLayout()
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controls_layout = QHBoxLayout()
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controls_layout.addWidget(QLabel("预览行数:"))
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self.preview_rows_spin = QSpinBox()
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self.preview_rows_spin.setRange(1, 200)
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self.preview_rows_spin.setValue(10)
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controls_layout.addWidget(self.preview_rows_spin)
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self.preview_btn = QPushButton("刷新预览")
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self.preview_btn.clicked.connect(self.load_csv_preview)
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controls_layout.addWidget(self.preview_btn)
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controls_layout.addStretch()
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self.preview_table = QTableView()
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self.preview_table.setEditTriggers(QAbstractItemView.NoEditTriggers)
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self.preview_table.setSelectionBehavior(QAbstractItemView.SelectRows)
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self.preview_table.setSelectionMode(QAbstractItemView.SingleSelection)
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self.preview_table.horizontalHeader().setSectionResizeMode(QHeaderView.Stretch)
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self.preview_table.verticalHeader().setVisible(False)
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self.preview_table.setMinimumHeight(200)
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self.preview_status_label = QLabel("请选择CSV文件并点击刷新预览")
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self.preview_status_label.setStyleSheet("color: #666; font-size: 11px;")
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preview_layout.addLayout(controls_layout)
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preview_layout.addWidget(self.preview_table)
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preview_layout.addWidget(self.preview_status_label)
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preview_group.setLayout(preview_layout)
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layout.addWidget(preview_group)
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# 输出文件路径
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self.output_file = FileSelectWidget(
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"输出处理后CSV:",
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"CSV Files (*.csv);;All Files (*.*)"
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)
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self.output_file.line_edit.setPlaceholderText("processed_data.csv")
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layout.addWidget(self.output_file)
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# 启用步骤
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self.enable_checkbox = QCheckBox("启用此步骤")
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self.enable_checkbox.setChecked(True)
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layout.addWidget(self.enable_checkbox)
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# 独立运行按钮
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self.run_btn = QPushButton("独立运行此步骤")
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self.run_btn.setStyleSheet(ModernStylesheet.get_button_stylesheet('success'))
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self.run_btn.clicked.connect(self.run_step)
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layout.addWidget(self.run_btn)
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layout.addStretch()
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self.setLayout(layout)
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self.reset_preview()
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def get_config(self):
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"""获取配置"""
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config = {
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'csv_path': self.csv_file.get_path(),
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}
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output_path = self.output_file.get_path()
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if output_path:
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config['output_path'] = output_path
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return config
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def set_config(self, config):
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"""设置配置"""
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if 'csv_path' in config:
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self.csv_file.set_path(config['csv_path'])
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self.load_csv_preview()
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if 'output_path' in config:
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self.output_file.set_path(config['output_path'])
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|
||||
def update_from_config(self, work_dir=None, pipeline=None):
|
||||
"""从全局配置自动填充输出路径
|
||||
|
||||
Args:
|
||||
work_dir: 工作目录路径
|
||||
pipeline: Pipeline 实例（未使用，保留接口兼容性）
|
||||
"""
|
||||
if work_dir:
|
||||
self.work_dir = work_dir
|
||||
elif hasattr(self, 'work_dir') and self.work_dir:
|
||||
pass
|
||||
else:
|
||||
self.work_dir = None
|
||||
|
||||
if self.work_dir:
|
||||
output_dir = os.path.join(self.work_dir, "4_processed_data")
|
||||
os.makedirs(output_dir, exist_ok=True)
|
||||
default_output_path = os.path.join(output_dir, "processed_data.csv").replace('\\', '/')
|
||||
self.output_file.set_path(default_output_path)
|
||||
else:
|
||||
self.output_file.set_path("")
|
||||
|
||||
def run_step(self):
|
||||
"""独立运行步骤4"""
|
||||
# 验证输入
|
||||
csv_path = self.csv_file.get_path()
|
||||
if not csv_path:
|
||||
QMessageBox.warning(self, "输入错误", "请选择水质参数文件！")
|
||||
return
|
||||
|
||||
# 获取主窗口并运行步骤
|
||||
main_window = self.window()
|
||||
if hasattr(main_window, 'run_single_step'):
|
||||
config = {'step4': self.get_config()}
|
||||
main_window.run_single_step('step4', config)
|
||||
|
||||
def reset_preview(self, message="请选择CSV文件并点击刷新预览"):
|
||||
"""重置预览表格"""
|
||||
from src.gui.water_quality_gui import PandasTableModel
|
||||
empty_model = PandasTableModel(pd.DataFrame())
|
||||
self.preview_table.setModel(empty_model)
|
||||
self.preview_status_label.setText(message)
|
||||
|
||||
def load_csv_preview(self):
|
||||
"""加载CSV预览数据"""
|
||||
from src.gui.water_quality_gui import PandasTableModel
|
||||
csv_path = self.csv_file.get_path()
|
||||
if not csv_path:
|
||||
self.reset_preview("请先选择CSV文件")
|
||||
return
|
||||
if not os.path.exists(csv_path):
|
||||
self.reset_preview("文件不存在，请检查路径")
|
||||
return
|
||||
|
||||
try:
|
||||
rows_to_preview = max(1, self.preview_rows_spin.value())
|
||||
# dtype=object 确保所有列以字符串读取，避免空值/混合类型导致 dtype 报错
|
||||
df = pd.read_csv(csv_path, nrows=rows_to_preview, dtype=object)
|
||||
# fillna 在 PandasTableModel.__init__ 中已执行，此处再次防御性处理
|
||||
df = df.fillna('')
|
||||
if df.empty:
|
||||
self.reset_preview("CSV文件为空")
|
||||
return
|
||||
|
||||
model = PandasTableModel(df)
|
||||
self.preview_table.setModel(model)
|
||||
self.preview_status_label.setText(
|
||||
f"预览 {len(df)} 行，{len(df.columns)} 列（总行数可能更多）"
|
||||
)
|
||||
except Exception as exc:
|
||||
self.reset_preview(f"加载失败: {exc}")
|
||||
@ -1,7 +1,7 @@
|
||||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
Step10 面板 - 采样点生成
|
||||
Step4 面板 - 采样点布设
|
||||
"""
|
||||
|
||||
import os
|
||||
@ -16,8 +16,8 @@ from src.gui.dialogs import SamplingViewerDialog
|
||||
from src.gui.styles import ModernStylesheet
|
||||
|
||||
|
||||
class Step10Panel(QWidget):
|
||||
"""步骤10：采样点生成"""
|
||||
class Step4SamplingPanel(QWidget):
|
||||
"""步骤4：采样点布设"""
|
||||
def __init__(self, parent=None):
|
||||
super().__init__(parent)
|
||||
self.init_ui()
|
||||
@ -71,7 +71,7 @@ class Step10Panel(QWidget):
|
||||
"输出采样点:",
|
||||
"CSV Files (*.csv);;All Files (*.*)"
|
||||
)
|
||||
self.output_file.line_edit.setPlaceholderText("sampling_points.csv")
|
||||
self.output_file.line_edit.setPlaceholderText("sampling_spectra.csv")
|
||||
layout.addWidget(self.output_file)
|
||||
|
||||
# 启用步骤
|
||||
@ -207,7 +207,7 @@ class Step10Panel(QWidget):
|
||||
|
||||
# 3. 自动填充输出路径（绝对路径）
|
||||
if self.work_dir:
|
||||
output_path = os.path.join(self.work_dir, "10_sampling", "sampling_spectra.csv")
|
||||
output_path = os.path.join(self.work_dir, "4_sampling", "sampling_spectra.csv")
|
||||
os.makedirs(os.path.dirname(output_path), exist_ok=True)
|
||||
self.output_file.set_path(output_path.replace('\\', '/'))
|
||||
|
||||
@ -215,7 +215,7 @@ class Step10Panel(QWidget):
|
||||
self._check_csv_exists()
|
||||
|
||||
def run_step(self):
|
||||
"""独立运行步骤10"""
|
||||
"""独立运行步骤4"""
|
||||
deglint_img_path = self.deglint_img_file.get_path()
|
||||
if not deglint_img_path:
|
||||
QMessageBox.warning(self, "输入错误", "请选择去耀斑影像文件！")
|
||||
@ -223,8 +223,8 @@ class Step10Panel(QWidget):
|
||||
|
||||
main_window = self.window()
|
||||
if hasattr(main_window, 'run_single_step'):
|
||||
config = {'step10': self.get_config()}
|
||||
main_window.run_single_step('step10', config)
|
||||
config = {'step4': self.get_config()}
|
||||
main_window.run_single_step('step4', config)
|
||||
|
||||
def _check_csv_exists(self):
|
||||
"""检查 output csv 是否存在，驱动预览按钮启停"""
|
||||
@ -243,7 +243,7 @@ class Step10Panel(QWidget):
|
||||
if not csv_path or not os.path.exists(csv_path):
|
||||
QMessageBox.warning(
|
||||
self, "文件不存在",
|
||||
f"采样点 CSV 文件不存在：{csv_path}\n请先运行步骤10生成数据。"
|
||||
f"采样点 CSV 文件不存在：{csv_path}\n请先运行步骤4生成数据。"
|
||||
)
|
||||
return
|
||||
dialog = SamplingViewerDialog(csv_path, self)
|
||||
@ -1,16 +1,17 @@
|
||||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
Step5 面板 - 光谱提取
|
||||
Step4 面板 - 数据预处理
|
||||
"""
|
||||
|
||||
import os
|
||||
|
||||
import pandas as pd
|
||||
from PyQt5.QtWidgets import (
|
||||
QWidget, QVBoxLayout, QGroupBox, QFormLayout, QLabel,
|
||||
QSpinBox, QPushButton, QCheckBox, QMessageBox,
|
||||
QWidget, QVBoxLayout, QGroupBox, QHBoxLayout, QLabel,
|
||||
QSpinBox, QPushButton, QCheckBox, QTableView,
|
||||
QAbstractItemView, QHeaderView, QMessageBox,
|
||||
)
|
||||
from PyQt5.QtGui import QFont
|
||||
from PyQt5.QtCore import Qt
|
||||
|
||||
from src.gui.components.custom_widgets import FileSelectWidget
|
||||
@ -18,7 +19,7 @@ from src.gui.styles import ModernStylesheet
|
||||
|
||||
|
||||
class Step5Panel(QWidget):
|
||||
"""步骤5：光谱提取"""
|
||||
"""步骤5：数据清洗"""
|
||||
def __init__(self, parent=None):
|
||||
super().__init__(parent)
|
||||
self.init_ui()
|
||||
@ -27,67 +28,55 @@ class Step5Panel(QWidget):
|
||||
layout = QVBoxLayout()
|
||||
|
||||
# 标题
|
||||
title = QLabel("步骤5：训练样本光谱提取")
|
||||
title.setFont(QFont("Arial", 12, QFont.Bold))
|
||||
layout.addWidget(title)
|
||||
|
||||
# 去耀斑影像文件（用于独立运行）
|
||||
self.deglint_img_file = FileSelectWidget(
|
||||
"去耀斑影像:",
|
||||
"Image Files (*.bsq *.dat *.tif);;All Files (*.*)"
|
||||
)
|
||||
layout.addWidget(self.deglint_img_file)
|
||||
|
||||
# 处理后的CSV文件（用于独立运行）
|
||||
# CSV文件
|
||||
self.csv_file = FileSelectWidget(
|
||||
"处理后CSV:",
|
||||
"水质参数文件:",
|
||||
"CSV Files (*.csv);;All Files (*.*)"
|
||||
)
|
||||
layout.addWidget(self.csv_file)
|
||||
|
||||
# 水体掩膜文件（可选，用于独立运行）
|
||||
self.water_mask_file = FileSelectWidget(
|
||||
"水体掩膜:",
|
||||
"Mask Files (*.dat *.tif);;All Files (*.*)"
|
||||
)
|
||||
self.water_mask_file.line_edit.setPlaceholderText("可选，如不选择则自动生成")
|
||||
layout.addWidget(self.water_mask_file)
|
||||
hint = QLabel("提示: 处理CSV文件，筛选剔除异常值")
|
||||
hint.setStyleSheet("color: #666; font-size: 10px;")
|
||||
layout.addWidget(hint)
|
||||
|
||||
self.glint_mask_file = FileSelectWidget(
|
||||
"耀斑掩膜:",
|
||||
"Mask Files (*.dat *.tif);;All Files (*.*)"
|
||||
)
|
||||
layout.addWidget(self.glint_mask_file)
|
||||
step5_glint_hint = QLabel(
|
||||
"提示：独立运行本步骤时必须选择耀斑掩膜（通常为步骤2输出的 severe_glint_area.dat），用于在采样时避开耀斑像元。"
|
||||
)
|
||||
step5_glint_hint.setWordWrap(True)
|
||||
step5_glint_hint.setStyleSheet("color: #666; font-size: 10px;")
|
||||
layout.addWidget(step5_glint_hint)
|
||||
preview_group = QGroupBox("CSV数据预览")
|
||||
preview_layout = QVBoxLayout()
|
||||
|
||||
# 参数设置
|
||||
params_group = QGroupBox("提取参数")
|
||||
params_layout = QFormLayout()
|
||||
controls_layout = QHBoxLayout()
|
||||
controls_layout.addWidget(QLabel("预览行数:"))
|
||||
self.preview_rows_spin = QSpinBox()
|
||||
self.preview_rows_spin.setRange(1, 200)
|
||||
self.preview_rows_spin.setValue(10)
|
||||
controls_layout.addWidget(self.preview_rows_spin)
|
||||
self.preview_btn = QPushButton("刷新预览")
|
||||
self.preview_btn.clicked.connect(self.load_csv_preview)
|
||||
controls_layout.addWidget(self.preview_btn)
|
||||
controls_layout.addStretch()
|
||||
|
||||
self.radius = QSpinBox()
|
||||
self.radius.setRange(1, 50)
|
||||
self.radius.setValue(5)
|
||||
params_layout.addRow("采样半径(像素):", self.radius)
|
||||
self.preview_table = QTableView()
|
||||
self.preview_table.setEditTriggers(QAbstractItemView.NoEditTriggers)
|
||||
self.preview_table.setSelectionBehavior(QAbstractItemView.SelectRows)
|
||||
self.preview_table.setSelectionMode(QAbstractItemView.SingleSelection)
|
||||
self.preview_table.horizontalHeader().setSectionResizeMode(QHeaderView.Stretch)
|
||||
self.preview_table.verticalHeader().setVisible(False)
|
||||
self.preview_table.setMinimumHeight(200)
|
||||
|
||||
self.source_epsg = QSpinBox()
|
||||
self.source_epsg.setRange(1000, 99999)
|
||||
self.source_epsg.setValue(4326)
|
||||
params_layout.addRow("源坐标系EPSG:", self.source_epsg)
|
||||
self.preview_status_label = QLabel("请选择CSV文件并点击刷新预览")
|
||||
self.preview_status_label.setStyleSheet("color: #666; font-size: 11px;")
|
||||
|
||||
params_group.setLayout(params_layout)
|
||||
layout.addWidget(params_group)
|
||||
preview_layout.addLayout(controls_layout)
|
||||
preview_layout.addWidget(self.preview_table)
|
||||
preview_layout.addWidget(self.preview_status_label)
|
||||
preview_group.setLayout(preview_layout)
|
||||
layout.addWidget(preview_group)
|
||||
|
||||
# 输出文件路径
|
||||
self.output_file = FileSelectWidget(
|
||||
"输出训练数据:",
|
||||
"输出处理后CSV:",
|
||||
"CSV Files (*.csv);;All Files (*.*)"
|
||||
)
|
||||
self.output_file.line_edit.setPlaceholderText("training_spectra.csv")
|
||||
self.output_file.line_edit.setPlaceholderText("processed_data.csv")
|
||||
layout.addWidget(self.output_file)
|
||||
|
||||
# 启用步骤
|
||||
@ -103,54 +92,33 @@ class Step5Panel(QWidget):
|
||||
|
||||
layout.addStretch()
|
||||
self.setLayout(layout)
|
||||
# 信号连接：影像文件路径变化时动态更新波段范围
|
||||
self.reset_preview()
|
||||
|
||||
def get_config(self):
|
||||
"""获取配置"""
|
||||
config = {
|
||||
'radius': self.radius.value(),
|
||||
'source_epsg': self.source_epsg.value(),
|
||||
'csv_path': self.csv_file.get_path(),
|
||||
}
|
||||
# 添加独立运行所需的文件路径
|
||||
deglint_img_path = self.deglint_img_file.get_path()
|
||||
if deglint_img_path:
|
||||
config['deglint_img_path'] = deglint_img_path
|
||||
csv_path = self.csv_file.get_path()
|
||||
if csv_path:
|
||||
config['csv_path'] = csv_path
|
||||
water_mask_path = self.water_mask_file.get_path()
|
||||
if water_mask_path:
|
||||
config['boundary_path'] = water_mask_path
|
||||
glint_mask_path = self.glint_mask_file.get_path()
|
||||
if glint_mask_path:
|
||||
config['glint_mask_path'] = glint_mask_path
|
||||
# 注意：step5_extract_training_spectra 不接受 output_path / training_csv_path
|
||||
# 参数，输出路径由 pipeline 内部根据 training_spectra_dir 自动生成。
|
||||
output_path = self.output_file.get_path()
|
||||
if output_path:
|
||||
config['output_path'] = output_path
|
||||
return config
|
||||
|
||||
def set_config(self, config):
|
||||
"""设置配置"""
|
||||
if 'radius' in config:
|
||||
self.radius.setValue(config['radius'])
|
||||
if 'source_epsg' in config:
|
||||
self.source_epsg.setValue(config['source_epsg'])
|
||||
if 'deglint_img_path' in config:
|
||||
self.deglint_img_file.set_path(config['deglint_img_path'])
|
||||
if 'csv_path' in config:
|
||||
self.csv_file.set_path(config['csv_path'])
|
||||
if 'boundary_path' in config:
|
||||
self.water_mask_file.set_path(config['boundary_path'])
|
||||
if 'glint_mask_path' in config:
|
||||
self.glint_mask_file.set_path(config['glint_mask_path'])
|
||||
self.load_csv_preview()
|
||||
if 'output_path' in config:
|
||||
self.output_file.set_path(config['output_path'])
|
||||
|
||||
def update_from_config(self, work_dir=None, pipeline=None):
|
||||
"""从全局配置/Pipeline 或 Step1Panel 自动填充路径，实现上下游数据流转
|
||||
"""从全局配置自动填充输出路径
|
||||
|
||||
Args:
|
||||
work_dir: 工作目录路径
|
||||
pipeline: Pipeline 实例，用于获取步骤1生成的水域掩膜路径
|
||||
pipeline: Pipeline 实例（未使用，保留接口兼容性）
|
||||
"""
|
||||
# 保存工作目录引用
|
||||
if work_dir:
|
||||
self.work_dir = work_dir
|
||||
elif hasattr(self, 'work_dir') and self.work_dir:
|
||||
@ -158,82 +126,60 @@ class Step5Panel(QWidget):
|
||||
else:
|
||||
self.work_dir = None
|
||||
|
||||
# 1. 尝试从 Pipeline 获取水体掩膜路径
|
||||
mask_path = None
|
||||
if pipeline and hasattr(pipeline, 'water_mask_path') and pipeline.water_mask_path:
|
||||
mask_path = pipeline.water_mask_path
|
||||
|
||||
# 2. 如果 Pipeline 中没有，则尝试直接从 Step1 界面读取
|
||||
main_window = self.window()
|
||||
if not mask_path and hasattr(main_window, 'step1_panel'):
|
||||
if main_window.step1_panel.use_ndwi_radio.isChecked():
|
||||
mask_path = main_window.step1_panel.output_file.get_path()
|
||||
else:
|
||||
mask_path = main_window.step1_panel.mask_file.get_path()
|
||||
# 若为相对路径，使用 work_dir 合成为绝对路径
|
||||
if mask_path and not os.path.isabs(mask_path):
|
||||
mask_path = os.path.join(self.work_dir or '', mask_path).replace('\\', '/')
|
||||
|
||||
# 填充水体掩膜路径
|
||||
if mask_path:
|
||||
# 若为相对路径，使用 work_dir 合成为绝对路径
|
||||
if not os.path.isabs(mask_path):
|
||||
mask_path = os.path.join(self.work_dir or '', mask_path).replace('\\', '/')
|
||||
self.water_mask_file.set_path(mask_path)
|
||||
|
||||
# 3. 尝试从 Step2 界面读取耀斑掩膜路径
|
||||
main_window = self.window()
|
||||
if hasattr(main_window, 'step2_panel'):
|
||||
glint_path = main_window.step2_panel.output_file.get_path()
|
||||
if glint_path:
|
||||
# 若为相对路径，使用 work_dir 合成为绝对路径
|
||||
if not os.path.isabs(glint_path):
|
||||
glint_path = os.path.join(self.work_dir or '', glint_path).replace('\\', '/')
|
||||
self.glint_mask_file.set_path(glint_path)
|
||||
|
||||
# 4. 自动填充输出路径（基于工作目录）
|
||||
if self.work_dir:
|
||||
output_dir = os.path.join(self.work_dir, "5_training_spectra")
|
||||
output_dir = os.path.join(self.work_dir, "4_processed_data")
|
||||
os.makedirs(output_dir, exist_ok=True)
|
||||
default_output_path = os.path.join(output_dir, "training_spectra.csv").replace('\\', '/')
|
||||
default_output_path = os.path.join(output_dir, "processed_data.csv").replace('\\', '/')
|
||||
self.output_file.set_path(default_output_path)
|
||||
else:
|
||||
self.output_file.set_path("")
|
||||
|
||||
# 5. 尝试从 Step4 界面读取已处理的水质参数 CSV 路径，自动填入本面板
|
||||
main_window = self.window()
|
||||
if main_window and hasattr(main_window, 'step4_panel'):
|
||||
step4_output_path = main_window.step4_panel.output_file.get_path()
|
||||
if step4_output_path:
|
||||
# 若为相对路径，使用 work_dir 合成为绝对路径
|
||||
if not os.path.isabs(step4_output_path):
|
||||
step4_output_path = os.path.join(self.work_dir or '', step4_output_path).replace('\\', '/')
|
||||
existing_csv = self.csv_file.get_path()
|
||||
if not existing_csv or not existing_csv.strip():
|
||||
self.csv_file.set_path(step4_output_path)
|
||||
|
||||
def run_step(self):
|
||||
"""独立运行步骤5"""
|
||||
"""独立运行步骤4"""
|
||||
# 验证输入
|
||||
deglint_img_path = self.deglint_img_file.get_path()
|
||||
csv_path = self.csv_file.get_path()
|
||||
if not deglint_img_path:
|
||||
QMessageBox.warning(self, "输入错误", "请选择去耀斑影像文件！")
|
||||
return
|
||||
if not csv_path:
|
||||
QMessageBox.warning(self, "输入错误", "请选择处理后的CSV文件！")
|
||||
return
|
||||
if not self.glint_mask_file.get_path():
|
||||
QMessageBox.warning(
|
||||
self,
|
||||
"输入错误",
|
||||
"独立运行光谱特征提取时，必须选择耀斑掩膜文件。\n\n"
|
||||
"请提供与去耀斑影像对应的耀斑二值掩膜（一般为步骤2输出的 severe_glint_area.dat）。",
|
||||
)
|
||||
QMessageBox.warning(self, "输入错误", "请选择水质参数文件！")
|
||||
return
|
||||
|
||||
# 获取主窗口并运行步骤
|
||||
main_window = self.window()
|
||||
if hasattr(main_window, 'run_single_step'):
|
||||
config = {'step5': self.get_config()}
|
||||
main_window.run_single_step('step5', config)
|
||||
config = {'step4': self.get_config()}
|
||||
main_window.run_single_step('step4', config)
|
||||
|
||||
def reset_preview(self, message="请选择CSV文件并点击刷新预览"):
|
||||
"""重置预览表格"""
|
||||
from src.gui.water_quality_gui import PandasTableModel
|
||||
empty_model = PandasTableModel(pd.DataFrame())
|
||||
self.preview_table.setModel(empty_model)
|
||||
self.preview_status_label.setText(message)
|
||||
|
||||
def load_csv_preview(self):
|
||||
"""加载CSV预览数据"""
|
||||
from src.gui.water_quality_gui import PandasTableModel
|
||||
csv_path = self.csv_file.get_path()
|
||||
if not csv_path:
|
||||
self.reset_preview("请先选择CSV文件")
|
||||
return
|
||||
if not os.path.exists(csv_path):
|
||||
self.reset_preview("文件不存在，请检查路径")
|
||||
return
|
||||
|
||||
try:
|
||||
rows_to_preview = max(1, self.preview_rows_spin.value())
|
||||
# dtype=object 确保所有列以字符串读取，避免空值/混合类型导致 dtype 报错
|
||||
df = pd.read_csv(csv_path, nrows=rows_to_preview, dtype=object)
|
||||
# fillna 在 PandasTableModel.__init__ 中已执行，此处再次防御性处理
|
||||
df = df.fillna('')
|
||||
if df.empty:
|
||||
self.reset_preview("CSV文件为空")
|
||||
return
|
||||
|
||||
model = PandasTableModel(df)
|
||||
self.preview_table.setModel(model)
|
||||
self.preview_status_label.setText(
|
||||
f"预览 {len(df)} 行，{len(df.columns)} 列（总行数可能更多）"
|
||||
)
|
||||
except Exception as exc:
|
||||
self.reset_preview(f"加载失败: {exc}")
|
||||
|
||||
@ -1,423 +1,239 @@
|
||||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
Step5 面板 - 光谱提取
|
||||
"""
|
||||
|
||||
import os
|
||||
import sys
|
||||
import pandas as pd
|
||||
import numpy as np
|
||||
from pathlib import Path
|
||||
from typing import Dict, List, Optional, Tuple
|
||||
|
||||
from PyQt5.QtWidgets import (
|
||||
QWidget, QVBoxLayout, QGroupBox, QGridLayout,
|
||||
QHBoxLayout, QLabel, QCheckBox, QPushButton, QMessageBox,
|
||||
QScrollArea, QListWidget, QListWidgetItem, QAbstractItemView,
|
||||
QRadioButton, QButtonGroup
|
||||
QWidget, QVBoxLayout, QGroupBox, QFormLayout, QLabel,
|
||||
QSpinBox, QPushButton, QCheckBox, QMessageBox,
|
||||
)
|
||||
from PyQt5.QtGui import QFont
|
||||
from PyQt5.QtCore import Qt
|
||||
from PyQt5.QtGui import QColor, QBrush, QFont
|
||||
|
||||
from src.gui.components.custom_widgets import FileSelectWidget
|
||||
from src.gui.styles import ModernStylesheet
|
||||
|
||||
|
||||
def get_resource_path(relative_path: str) -> str:
|
||||
"""适配开发与 PyInstaller 环境的路径获取逻辑。"""
|
||||
if hasattr(sys, '_MEIPASS'):
|
||||
internal = os.path.join(sys._MEIPASS, '_internal', relative_path)
|
||||
if os.path.exists(internal):
|
||||
return internal
|
||||
return os.path.join(sys._MEIPASS, relative_path)
|
||||
|
||||
exe_dir = os.path.dirname(sys.executable)
|
||||
internal = os.path.join(exe_dir, '_internal', relative_path)
|
||||
if os.path.exists(internal):
|
||||
return internal
|
||||
|
||||
base_dir = Path(__file__).resolve().parent.parent / "model"
|
||||
return str(base_dir / os.path.basename(relative_path))
|
||||
|
||||
|
||||
class Step6Panel(QWidget):
|
||||
COLOR_RATIO = QColor(255, 255, 255)
|
||||
COLOR_CONCENTRATION = QColor(220, 240, 255)
|
||||
COLOR_HEADER = QColor(245, 245, 245)
|
||||
|
||||
"""步骤6：光谱特征"""
|
||||
def __init__(self, parent=None):
|
||||
super().__init__(parent)
|
||||
self.index_checkboxes: Dict[str, QListWidgetItem] = {}
|
||||
self.work_dir: Optional[str] = None
|
||||
self.builtin_formula_path = get_resource_path("waterindex.csv")
|
||||
self._formula_type_map: Dict[str, str] = {}
|
||||
self._formula_color_map: Dict[str, QColor] = {}
|
||||
self._formula_coef_map: Dict[str, List[float]] = {}
|
||||
|
||||
self.init_ui()
|
||||
self._auto_load_formulas()
|
||||
|
||||
def init_ui(self):
|
||||
main_layout = QVBoxLayout()
|
||||
main_layout.setContentsMargins(20, 20, 20, 20)
|
||||
main_layout.setSpacing(10)
|
||||
layout = QVBoxLayout()
|
||||
|
||||
# 1. 公式配置源 (只读)
|
||||
path_group = QGroupBox("公式配置源 (内置)")
|
||||
path_layout = QVBoxLayout()
|
||||
self.formula_csv_widget = FileSelectWidget("内置CSV路径:", "CSV Files (*.csv)")
|
||||
self.formula_csv_widget.set_path(self.builtin_formula_path)
|
||||
self.formula_csv_widget.set_read_only(True)
|
||||
self.formula_csv_widget.line_edit.setStyleSheet("background-color: #f0f0f0; color: #666;")
|
||||
path_layout.addWidget(self.formula_csv_widget)
|
||||
path_group.setLayout(path_layout)
|
||||
main_layout.addWidget(path_group)
|
||||
# 标题
|
||||
title = QLabel("步骤5：训练样本光谱提取")
|
||||
title.setFont(QFont("Arial", 12, QFont.Bold))
|
||||
layout.addWidget(title)
|
||||
|
||||
# 2. 训练数据输入
|
||||
input_group = QGroupBox("输入样本数据")
|
||||
input_layout = QVBoxLayout()
|
||||
self.training_data_widget = FileSelectWidget("特征提取CSV:", "CSV Files (*.csv)")
|
||||
input_layout.addWidget(self.training_data_widget)
|
||||
input_group.setLayout(input_layout)
|
||||
main_layout.addWidget(input_group)
|
||||
# 去耀斑影像文件（用于独立运行）
|
||||
self.deglint_img_file = FileSelectWidget(
|
||||
"去耀斑影像:",
|
||||
"Image Files (*.bsq *.dat *.tif);;All Files (*.*)"
|
||||
)
|
||||
layout.addWidget(self.deglint_img_file)
|
||||
|
||||
# 3. 公式选择区 (分组 ListWidget)
|
||||
self.formula_group = QGroupBox("待计算水质指数勾选")
|
||||
formula_outer_layout = QVBoxLayout()
|
||||
# 处理后的CSV文件（用于独立运行）
|
||||
self.csv_file = FileSelectWidget(
|
||||
"处理后CSV:",
|
||||
"CSV Files (*.csv);;All Files (*.*)"
|
||||
)
|
||||
layout.addWidget(self.csv_file)
|
||||
|
||||
btn_layout = QHBoxLayout()
|
||||
self.select_all_btn = QPushButton("全选")
|
||||
self.deselect_all_btn = QPushButton("清空")
|
||||
self.select_ratio_btn = QPushButton("仅选比值型")
|
||||
self.select_conc_btn = QPushButton("仅选浓度型")
|
||||
self.select_all_btn.clicked.connect(self.select_all_formulas)
|
||||
self.deselect_all_btn.clicked.connect(self.deselect_all_formulas)
|
||||
self.select_ratio_btn.clicked.connect(self._select_ratio_only)
|
||||
self.select_conc_btn.clicked.connect(self._select_conc_only)
|
||||
btn_layout.addWidget(self.select_all_btn)
|
||||
btn_layout.addWidget(self.deselect_all_btn)
|
||||
btn_layout.addWidget(self.select_ratio_btn)
|
||||
btn_layout.addWidget(self.select_conc_btn)
|
||||
btn_layout.addStretch()
|
||||
# 水体掩膜文件（可选，用于独立运行）
|
||||
self.water_mask_file = FileSelectWidget(
|
||||
"水体掩膜:",
|
||||
"Mask Files (*.dat *.tif);;All Files (*.*)"
|
||||
)
|
||||
self.water_mask_file.line_edit.setPlaceholderText("可选，如不选择则自动生成")
|
||||
layout.addWidget(self.water_mask_file)
|
||||
|
||||
self.refresh_button = QPushButton("重新加载")
|
||||
self.refresh_button.clicked.connect(lambda: self.refresh_formulas(silent=False))
|
||||
btn_layout.addWidget(self.refresh_button)
|
||||
self.glint_mask_file = FileSelectWidget(
|
||||
"耀斑掩膜:",
|
||||
"Mask Files (*.dat *.tif);;All Files (*.*)"
|
||||
)
|
||||
layout.addWidget(self.glint_mask_file)
|
||||
step5_glint_hint = QLabel(
|
||||
"提示：独立运行本步骤时必须选择耀斑掩膜（通常为步骤2输出的 severe_glint_area.dat），用于在采样时避开耀斑像元。"
|
||||
)
|
||||
step5_glint_hint.setWordWrap(True)
|
||||
step5_glint_hint.setStyleSheet("color: #666; font-size: 10px;")
|
||||
layout.addWidget(step5_glint_hint)
|
||||
|
||||
formula_outer_layout.addLayout(btn_layout)
|
||||
# 参数设置
|
||||
params_group = QGroupBox("提取参数")
|
||||
params_layout = QFormLayout()
|
||||
|
||||
scroll = QScrollArea()
|
||||
scroll.setWidgetResizable(True)
|
||||
scroll.setMinimumHeight(280)
|
||||
self.scroll_content = QWidget()
|
||||
self.formula_layout = QVBoxLayout(self.scroll_content)
|
||||
self.formula_layout.setContentsMargins(4, 4, 4, 4)
|
||||
self.formula_layout.setSpacing(2)
|
||||
self.formula_layout.setAlignment(Qt.AlignTop)
|
||||
self.radius = QSpinBox()
|
||||
self.radius.setRange(1, 50)
|
||||
self.radius.setValue(5)
|
||||
params_layout.addRow("采样半径(像素):", self.radius)
|
||||
|
||||
self.formula_list = QListWidget()
|
||||
self.formula_list.setSelectionMode(QAbstractItemView.MultiSelection)
|
||||
self.formula_list.itemChanged.connect(self._on_item_changed)
|
||||
self.formula_layout.addWidget(self.formula_list)
|
||||
self.source_epsg = QSpinBox()
|
||||
self.source_epsg.setRange(1000, 99999)
|
||||
self.source_epsg.setValue(4326)
|
||||
params_layout.addRow("源坐标系EPSG:", self.source_epsg)
|
||||
|
||||
scroll.setWidget(self.scroll_content)
|
||||
formula_outer_layout.addWidget(scroll)
|
||||
params_group.setLayout(params_layout)
|
||||
layout.addWidget(params_group)
|
||||
|
||||
self.formula_group.setLayout(formula_outer_layout)
|
||||
main_layout.addWidget(self.formula_group)
|
||||
# 输出文件路径
|
||||
self.output_file = FileSelectWidget(
|
||||
"输出训练数据:",
|
||||
"CSV Files (*.csv);;All Files (*.*)"
|
||||
)
|
||||
self.output_file.line_edit.setPlaceholderText("training_spectra.csv")
|
||||
layout.addWidget(self.output_file)
|
||||
|
||||
# 4. 输出选项
|
||||
output_group = QGroupBox("输出模式")
|
||||
output_layout = QVBoxLayout()
|
||||
|
||||
mode_layout = QHBoxLayout()
|
||||
self.mode_group = QButtonGroup()
|
||||
self.radio_both = QRadioButton("两者皆出")
|
||||
self.radio_wide = QRadioButton("仅宽表")
|
||||
self.radio_single = QRadioButton("仅单文件")
|
||||
self.mode_group.addButton(self.radio_both, 0)
|
||||
self.mode_group.addButton(self.radio_wide, 1)
|
||||
self.mode_group.addButton(self.radio_single, 2)
|
||||
self.radio_both.setChecked(True)
|
||||
mode_layout.addWidget(self.radio_both)
|
||||
mode_layout.addWidget(self.radio_wide)
|
||||
mode_layout.addWidget(self.radio_single)
|
||||
mode_layout.addStretch()
|
||||
output_layout.addLayout(mode_layout)
|
||||
|
||||
self.enable_checkbox = QCheckBox("启用计算流程")
|
||||
# 启用步骤
|
||||
self.enable_checkbox = QCheckBox("启用此步骤")
|
||||
self.enable_checkbox.setChecked(True)
|
||||
output_layout.addWidget(self.enable_checkbox)
|
||||
layout.addWidget(self.enable_checkbox)
|
||||
|
||||
output_group.setLayout(output_layout)
|
||||
main_layout.addWidget(output_group)
|
||||
# 独立运行按钮
|
||||
self.run_btn = QPushButton("独立运行此步骤")
|
||||
self.run_btn.setStyleSheet(ModernStylesheet.get_button_stylesheet('success'))
|
||||
self.run_btn.clicked.connect(self.run_step)
|
||||
layout.addWidget(self.run_btn)
|
||||
|
||||
# 5. 运行按钮
|
||||
self.run_button = QPushButton("立即执行计算")
|
||||
self.run_button.setStyleSheet(ModernStylesheet.get_button_stylesheet('success'))
|
||||
self.run_button.setMinimumHeight(40)
|
||||
self.run_button.clicked.connect(self.run_step)
|
||||
main_layout.addWidget(self.run_button)
|
||||
layout.addStretch()
|
||||
self.setLayout(layout)
|
||||
# 信号连接：影像文件路径变化时动态更新波段范围
|
||||
|
||||
self.setLayout(main_layout)
|
||||
|
||||
def _on_item_changed(self, item: QListWidgetItem):
|
||||
if item.checkState() == Qt.Checked:
|
||||
bg_color = self.COLOR_RATIO
|
||||
for name, ref_item in self.index_checkboxes.items():
|
||||
if ref_item is item:
|
||||
bg_color = self._formula_color_map.get(name, self.COLOR_RATIO)
|
||||
break
|
||||
item.setBackground(QBrush(bg_color))
|
||||
else:
|
||||
item.setBackground(QBrush(self.COLOR_RATIO))
|
||||
|
||||
def _auto_load_formulas(self):
|
||||
if os.path.exists(self.builtin_formula_path):
|
||||
self.refresh_formulas(silent=True)
|
||||
else:
|
||||
print(f"DEBUG: 自动加载失败，路径不存在: {self.builtin_formula_path}")
|
||||
|
||||
def refresh_formulas(self, silent=False):
|
||||
path = self.builtin_formula_path
|
||||
if not os.path.exists(path):
|
||||
if not silent:
|
||||
QMessageBox.warning(self, "错误", f"找不到内置公式文件:\n{path}")
|
||||
return
|
||||
|
||||
try:
|
||||
df = None
|
||||
for enc in ('utf-8', 'gbk', 'utf-8-sig'):
|
||||
try:
|
||||
df = pd.read_csv(path, encoding=enc)
|
||||
if 'Formula_Name' in df.columns:
|
||||
break
|
||||
except Exception:
|
||||
continue
|
||||
|
||||
if df is None or 'Formula_Name' not in df.columns:
|
||||
if not silent:
|
||||
QMessageBox.critical(self, "错误", "CSV缺少 'Formula_Name' 列")
|
||||
return
|
||||
|
||||
self._formula_type_map.clear()
|
||||
self._formula_coef_map.clear()
|
||||
for _, row in df.iterrows():
|
||||
name = str(row['Formula_Name']).strip()
|
||||
if not name:
|
||||
continue
|
||||
ftype = str(row.get('Formula_Type', 'ratio')).strip().lower()
|
||||
self._formula_type_map[name] = ftype
|
||||
|
||||
# Parse Coefficient for concentration formulas
|
||||
coef_str = str(row.get('Coefficient', '')).strip()
|
||||
if coef_str:
|
||||
try:
|
||||
coeffs = [float(c.strip()) for c in coef_str.split(',') if c.strip()]
|
||||
self._formula_coef_map[name] = coeffs
|
||||
except Exception:
|
||||
self._formula_coef_map[name] = []
|
||||
else:
|
||||
self._formula_coef_map[name] = []
|
||||
|
||||
self.formula_list.clear()
|
||||
self.index_checkboxes.clear()
|
||||
|
||||
self._formula_color_map.clear()
|
||||
for name, ftype in self._formula_type_map.items():
|
||||
item = QListWidgetItem(name, self.formula_list)
|
||||
item.setCheckState(Qt.Checked)
|
||||
if ftype == 'concentration':
|
||||
bg_color = QColor(220, 240, 255)
|
||||
else:
|
||||
bg_color = self.COLOR_RATIO
|
||||
self._formula_color_map[name] = bg_color
|
||||
item.setBackground(QBrush(bg_color))
|
||||
self.index_checkboxes[name] = item
|
||||
|
||||
self.formula_list.adjustSize()
|
||||
print(f"✅ 加载 {len(self.index_checkboxes)} 个公式")
|
||||
|
||||
except Exception as e:
|
||||
if not silent:
|
||||
QMessageBox.critical(self, "加载失败", f"原因: {str(e)}")
|
||||
|
||||
def _select_ratio_only(self):
|
||||
for name, item in self.index_checkboxes.items():
|
||||
ftype = self._formula_type_map.get(name, 'ratio')
|
||||
item.setCheckState(Qt.Checked if ftype == 'ratio' else Qt.Unchecked)
|
||||
|
||||
def _select_conc_only(self):
|
||||
for name, item in self.index_checkboxes.items():
|
||||
ftype = self._formula_type_map.get(name, 'ratio')
|
||||
item.setCheckState(Qt.Checked if ftype == 'concentration' else Qt.Unchecked)
|
||||
|
||||
def select_all_formulas(self):
|
||||
for item in self.index_checkboxes.values():
|
||||
item.setCheckState(Qt.Checked)
|
||||
|
||||
def deselect_all_formulas(self):
|
||||
for item in self.index_checkboxes.values():
|
||||
item.setCheckState(Qt.Unchecked)
|
||||
|
||||
def get_config(self) -> Dict:
|
||||
selected = [
|
||||
name for name, item in self.index_checkboxes.items()
|
||||
if item.checkState() == Qt.Checked
|
||||
]
|
||||
# Build coefficient dict for selected formulas
|
||||
formula_coefficients = {
|
||||
name: self._formula_coef_map.get(name, [])
|
||||
for name in selected
|
||||
}
|
||||
return {
|
||||
'training_csv_path': self.training_data_widget.get_path(),
|
||||
'formula_csv_file': self.builtin_formula_path,
|
||||
'formula_names': selected,
|
||||
'formula_coefficients': formula_coefficients,
|
||||
'enabled': self.enable_checkbox.isChecked(),
|
||||
'output_mode': self.mode_group.checkedId(),
|
||||
def get_config(self):
|
||||
"""获取配置"""
|
||||
config = {
|
||||
'radius': self.radius.value(),
|
||||
'source_epsg': self.source_epsg.value(),
|
||||
}
|
||||
# 添加独立运行所需的文件路径
|
||||
deglint_img_path = self.deglint_img_file.get_path()
|
||||
if deglint_img_path:
|
||||
config['deglint_img_path'] = deglint_img_path
|
||||
csv_path = self.csv_file.get_path()
|
||||
if csv_path:
|
||||
config['csv_path'] = csv_path
|
||||
water_mask_path = self.water_mask_file.get_path()
|
||||
if water_mask_path:
|
||||
config['boundary_path'] = water_mask_path
|
||||
glint_mask_path = self.glint_mask_file.get_path()
|
||||
if glint_mask_path:
|
||||
config['glint_mask_path'] = glint_mask_path
|
||||
# 注意：step5_extract_training_spectra 不接受 output_path / training_csv_path
|
||||
# 参数，输出路径由 pipeline 内部根据 training_spectra_dir 自动生成。
|
||||
return config
|
||||
|
||||
def set_config(self, config: Dict):
|
||||
if 'training_csv_path' in config:
|
||||
self.training_data_widget.set_path(config['training_csv_path'])
|
||||
if 'formula_names' in config:
|
||||
sel = set(config['formula_names'])
|
||||
for name, item in self.index_checkboxes.items():
|
||||
item.setCheckState(Qt.Checked if name in sel else Qt.Unchecked)
|
||||
self.enable_checkbox.setChecked(config.get('enabled', True))
|
||||
if 'output_mode' in config:
|
||||
btn = self.mode_group.button(config['output_mode'])
|
||||
if btn:
|
||||
btn.setChecked(True)
|
||||
def set_config(self, config):
|
||||
"""设置配置"""
|
||||
if 'radius' in config:
|
||||
self.radius.setValue(config['radius'])
|
||||
if 'source_epsg' in config:
|
||||
self.source_epsg.setValue(config['source_epsg'])
|
||||
if 'deglint_img_path' in config:
|
||||
self.deglint_img_file.set_path(config['deglint_img_path'])
|
||||
if 'csv_path' in config:
|
||||
self.csv_file.set_path(config['csv_path'])
|
||||
if 'boundary_path' in config:
|
||||
self.water_mask_file.set_path(config['boundary_path'])
|
||||
if 'glint_mask_path' in config:
|
||||
self.glint_mask_file.set_path(config['glint_mask_path'])
|
||||
|
||||
def update_from_config(self, work_dir=None, pipeline=None):
|
||||
"""从全局配置/Pipeline 或 Step1Panel 自动填充路径，实现上下游数据流转
|
||||
|
||||
Args:
|
||||
work_dir: 工作目录路径
|
||||
pipeline: Pipeline 实例，用于获取步骤1生成的水域掩膜路径
|
||||
"""
|
||||
# 保存工作目录引用
|
||||
if work_dir:
|
||||
self.work_dir = work_dir
|
||||
main = self.window()
|
||||
if hasattr(main, 'step5_panel'):
|
||||
p5 = main.step5_panel.output_file.get_path()
|
||||
if p5:
|
||||
if not os.path.isabs(p5):
|
||||
p5 = os.path.join(self.work_dir or '', p5)
|
||||
p5 = p5.replace('\\', '/')
|
||||
self.training_data_widget.set_path(p5)
|
||||
elif hasattr(self, 'work_dir') and self.work_dir:
|
||||
pass
|
||||
else:
|
||||
self.work_dir = None
|
||||
|
||||
def _get_work_dir(self) -> Optional[str]:
|
||||
# 1. 尝试从 Pipeline 获取水体掩膜路径
|
||||
mask_path = None
|
||||
if pipeline and hasattr(pipeline, 'water_mask_path') and pipeline.water_mask_path:
|
||||
mask_path = pipeline.water_mask_path
|
||||
|
||||
# 2. 如果 Pipeline 中没有，则尝试直接从 Step1 界面读取
|
||||
main_window = self.window()
|
||||
if not mask_path and hasattr(main_window, 'step1_panel'):
|
||||
if main_window.step1_panel.use_ndwi_radio.isChecked():
|
||||
mask_path = main_window.step1_panel.output_file.get_path()
|
||||
else:
|
||||
mask_path = main_window.step1_panel.mask_file.get_path()
|
||||
# 若为相对路径，使用 work_dir 合成为绝对路径
|
||||
if mask_path and not os.path.isabs(mask_path):
|
||||
mask_path = os.path.join(self.work_dir or '', mask_path).replace('\\', '/')
|
||||
|
||||
# 填充水体掩膜路径
|
||||
if mask_path:
|
||||
# 若为相对路径，使用 work_dir 合成为绝对路径
|
||||
if not os.path.isabs(mask_path):
|
||||
mask_path = os.path.join(self.work_dir or '', mask_path).replace('\\', '/')
|
||||
self.water_mask_file.set_path(mask_path)
|
||||
|
||||
# 3. 尝试从 Step2 界面读取耀斑掩膜路径
|
||||
main_window = self.window()
|
||||
if hasattr(main_window, 'step2_panel'):
|
||||
glint_path = main_window.step2_panel.output_file.get_path()
|
||||
if glint_path:
|
||||
# 若为相对路径，使用 work_dir 合成为绝对路径
|
||||
if not os.path.isabs(glint_path):
|
||||
glint_path = os.path.join(self.work_dir or '', glint_path).replace('\\', '/')
|
||||
self.glint_mask_file.set_path(glint_path)
|
||||
|
||||
# 4. 自动填充输出路径（基于工作目录）
|
||||
if self.work_dir:
|
||||
return self.work_dir
|
||||
main = self.window()
|
||||
if hasattr(main, 'work_dir') and main.work_dir:
|
||||
return main.work_dir
|
||||
return None
|
||||
output_dir = os.path.join(self.work_dir, "5_training_spectra")
|
||||
os.makedirs(output_dir, exist_ok=True)
|
||||
default_output_path = os.path.join(output_dir, "training_spectra.csv").replace('\\', '/')
|
||||
self.output_file.set_path(default_output_path)
|
||||
else:
|
||||
self.output_file.set_path("")
|
||||
|
||||
def _get_coord_cols(self, df: pd.DataFrame) -> Tuple[str, str]:
|
||||
coord_candidates = ['lon', 'lng', 'longitude', '经度', 'x', 'lon_utm', 'utm_x', 'pixel_x']
|
||||
lat_candidates = ['lat', 'latitude', '纬度', 'y', 'lat_utm', 'utm_y', 'pixel_y']
|
||||
|
||||
x_col, y_col = None, None
|
||||
for col in df.columns:
|
||||
cl = col.lower()
|
||||
if x_col is None and any(c in cl for c in coord_candidates):
|
||||
x_col = col
|
||||
if y_col is None and any(c in cl for c in lat_candidates):
|
||||
y_col = col
|
||||
|
||||
if x_col is None and len(df.columns) >= 2:
|
||||
x_col = df.columns[0]
|
||||
if y_col is None and len(df.columns) >= 2:
|
||||
y_col = df.columns[1]
|
||||
|
||||
return x_col or 'x_coord', y_col or 'y_coord'
|
||||
# 5. 尝试从 Step4 界面读取已处理的水质参数 CSV 路径，自动填入本面板
|
||||
main_window = self.window()
|
||||
if main_window and hasattr(main_window, 'step5_panel'):
|
||||
step4_output_path = main_window.step5_panel.output_file.get_path()
|
||||
if step4_output_path:
|
||||
# 若为相对路径，使用 work_dir 合成为绝对路径
|
||||
if not os.path.isabs(step4_output_path):
|
||||
step4_output_path = os.path.join(self.work_dir or '', step4_output_path).replace('\\', '/')
|
||||
existing_csv = self.csv_file.get_path()
|
||||
if not existing_csv or not existing_csv.strip():
|
||||
self.csv_file.set_path(step4_output_path)
|
||||
|
||||
def run_step(self):
|
||||
config = self.get_config()
|
||||
|
||||
if not config['enabled']:
|
||||
QMessageBox.information(self, "提示", "已禁用计算流程（启用计算流程未勾选）")
|
||||
"""独立运行步骤5"""
|
||||
# 验证输入
|
||||
deglint_img_path = self.deglint_img_file.get_path()
|
||||
csv_path = self.csv_file.get_path()
|
||||
if not deglint_img_path:
|
||||
QMessageBox.warning(self, "输入错误", "请选择去耀斑影像文件！")
|
||||
return
|
||||
|
||||
training_path = config['training_csv_path']
|
||||
if not training_path or not os.path.exists(training_path):
|
||||
QMessageBox.warning(self, "提示", "请先选择输入特征提取CSV文件")
|
||||
if not csv_path:
|
||||
QMessageBox.warning(self, "输入错误", "请选择处理后的CSV文件！")
|
||||
return
|
||||
|
||||
formula_names = config['formula_names']
|
||||
if not formula_names:
|
||||
QMessageBox.warning(self, "提示", "请至少勾选一个公式")
|
||||
return
|
||||
|
||||
output_mode = config['output_mode']
|
||||
|
||||
try:
|
||||
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)
|
||||
|
||||
# 构建 formula_csv_path（使用内置 waterindex.csv）
|
||||
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(),
|
||||
if not self.glint_mask_file.get_path():
|
||||
QMessageBox.warning(
|
||||
self,
|
||||
"输入错误",
|
||||
"独立运行光谱特征提取时，必须选择耀斑掩膜文件。\n\n"
|
||||
"请提供与去耀斑影像对应的耀斑二值掩膜（一般为步骤2输出的 severe_glint_area.dat）。",
|
||||
)
|
||||
return
|
||||
|
||||
# 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
|
||||
|
||||
if output_mode in (0, 1):
|
||||
track_a_dir = os.path.join(work_dir, "6_water_quality_indices") if work_dir else "6_water_quality_indices"
|
||||
os.makedirs(track_a_dir, exist_ok=True)
|
||||
track_a_path = os.path.join(track_a_dir, "training_spectra_indices.csv")
|
||||
|
||||
if output_mode in (0, 2):
|
||||
track_b_dir = os.path.join(work_dir, "11_12_13_predictions", "Traditional_Indices") if work_dir else "11_12_13_predictions/Traditional_Indices"
|
||||
os.makedirs(track_b_dir, exist_ok=True)
|
||||
|
||||
saved = []
|
||||
if output_mode in (0, 1):
|
||||
output_df.to_csv(track_a_path, index=False, float_format='%.6f')
|
||||
saved.append(f"宽表: {track_a_path}")
|
||||
|
||||
if output_mode in (0, 2):
|
||||
coord_x = spec_df[x_col].values if x_col in spec_df.columns else np.arange(len(spec_df))
|
||||
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 output_df.columns:
|
||||
continue
|
||||
single_df = pd.DataFrame({
|
||||
'x_coord': coord_x,
|
||||
'y_coord': coord_y,
|
||||
'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")
|
||||
single_df.to_csv(out_path, index=False, float_format='%.6f')
|
||||
saved.append(f"单文件目录: {track_b_dir}")
|
||||
|
||||
QMessageBox.information(
|
||||
self, "计算完成",
|
||||
f"已保存 {len(saved)} 个输出目标:\n" + "\n".join(saved)
|
||||
)
|
||||
|
||||
except ImportError as 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()}")
|
||||
# 获取主窗口并运行步骤
|
||||
main_window = self.window()
|
||||
if hasattr(main_window, 'run_single_step'):
|
||||
config = {'step5': self.get_config()}
|
||||
main_window.run_single_step('step5', config)
|
||||
|
||||
@ -1,415 +1,423 @@
|
||||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
Step7 面板 - 机器学习建模
|
||||
"""
|
||||
|
||||
import os
|
||||
import sys
|
||||
import pandas as pd
|
||||
import numpy as np
|
||||
from pathlib import Path
|
||||
from typing import Dict, List, Optional, Tuple
|
||||
|
||||
from PyQt5.QtWidgets import (
|
||||
QWidget, QVBoxLayout, QGroupBox, QFormLayout, QGridLayout,
|
||||
QHBoxLayout, QLabel, QLineEdit, QSpinBox, QCheckBox,
|
||||
QPushButton, QFileDialog, QMessageBox,
|
||||
QWidget, QVBoxLayout, QGroupBox, QGridLayout,
|
||||
QHBoxLayout, QLabel, QCheckBox, QPushButton, QMessageBox,
|
||||
QScrollArea, QListWidget, QListWidgetItem, QAbstractItemView,
|
||||
QRadioButton, QButtonGroup
|
||||
)
|
||||
from PyQt5.QtCore import Qt
|
||||
from PyQt5.QtGui import QColor, QBrush, QFont
|
||||
|
||||
from src.gui.components.custom_widgets import FileSelectWidget
|
||||
from src.gui.styles import ModernStylesheet
|
||||
|
||||
|
||||
# ============================================================
|
||||
# 中文映射表（内部键名 -> 显示文本）
|
||||
# ============================================================
|
||||
def get_resource_path(relative_path: str) -> str:
|
||||
"""适配开发与 PyInstaller 环境的路径获取逻辑。"""
|
||||
if hasattr(sys, '_MEIPASS'):
|
||||
internal = os.path.join(sys._MEIPASS, '_internal', relative_path)
|
||||
if os.path.exists(internal):
|
||||
return internal
|
||||
return os.path.join(sys._MEIPASS, relative_path)
|
||||
|
||||
# 预处理方法：内部键 -> 显示文本
|
||||
PREPROC_CHINESE = {
|
||||
'None': '无 (None)',
|
||||
'MMS': '最小-最大归一化 (MMS)',
|
||||
'SS': '标度化 (SS)',
|
||||
'SNV': '标准正态变换 (SNV)',
|
||||
'MA': '移动平均 (MA)',
|
||||
'SG': 'Savitzky-Golay (SG)',
|
||||
'MSC': '多元散射校正 (MSC)',
|
||||
'D1': '一阶导数 (D1)',
|
||||
'D2': '二阶导数 (D2)',
|
||||
'DT': '去趋势 (DT)',
|
||||
'CT': '中心化 (CT)',
|
||||
}
|
||||
exe_dir = os.path.dirname(sys.executable)
|
||||
internal = os.path.join(exe_dir, '_internal', relative_path)
|
||||
if os.path.exists(internal):
|
||||
return internal
|
||||
|
||||
# 模型类型：内部键 -> 显示文本
|
||||
MODEL_CHINESE = {
|
||||
# 线性模型
|
||||
'LinearRegression': '多元线性回归 (MLR)',
|
||||
'Ridge': '岭回归 (Ridge)',
|
||||
'Lasso': '套索回归 (Lasso)',
|
||||
'ElasticNet': '弹性网络 (ElasticNet)',
|
||||
'PLS': '偏最小二乘 (PLSR)',
|
||||
# 树模型
|
||||
'DecisionTree': '决策树 (CART)',
|
||||
'RF': '随机森林 (RF)',
|
||||
'ExtraTrees': '极端随机树 (ET)',
|
||||
'XGBoost': '极值梯度提升 (XGBoost)',
|
||||
'LightGBM': '轻量梯度提升 (LightGBM)',
|
||||
'CatBoost': '类别梯度提升 (CatBoost)',
|
||||
# 集成学习
|
||||
'GradientBoosting': '梯度提升树 (GBDT)',
|
||||
'AdaBoost': '自适应提升 (AdaBoost)',
|
||||
# 其他模型
|
||||
'SVR': '支持向量回归 (SVR)',
|
||||
'KNN': 'K近邻回归 (KNN)',
|
||||
'MLP': '多层感知机 (BP神经网络)',
|
||||
}
|
||||
|
||||
# 数据划分方法：内部键 -> 显示文本
|
||||
SPLIT_CHINESE = {
|
||||
'spxy': 'SPXY 算法 (考量X-Y空间)',
|
||||
'ks': 'KS 算法 (考量X空间)',
|
||||
'random': '随机划分 (Random)',
|
||||
}
|
||||
base_dir = Path(__file__).resolve().parent.parent / "model"
|
||||
return str(base_dir / os.path.basename(relative_path))
|
||||
|
||||
|
||||
class Step7Panel(QWidget):
|
||||
"""步骤7：机器学习建模"""
|
||||
COLOR_RATIO = QColor(255, 255, 255)
|
||||
COLOR_CONCENTRATION = QColor(220, 240, 255)
|
||||
COLOR_HEADER = QColor(245, 245, 245)
|
||||
|
||||
def __init__(self, parent=None):
|
||||
super().__init__(parent)
|
||||
self.index_checkboxes: Dict[str, QListWidgetItem] = {}
|
||||
self.work_dir: Optional[str] = None
|
||||
self.builtin_formula_path = get_resource_path("waterindex.csv")
|
||||
self._formula_type_map: Dict[str, str] = {}
|
||||
self._formula_color_map: Dict[str, QColor] = {}
|
||||
self._formula_coef_map: Dict[str, List[float]] = {}
|
||||
|
||||
self.init_ui()
|
||||
self._auto_load_formulas()
|
||||
|
||||
def init_ui(self):
|
||||
layout = QVBoxLayout()
|
||||
main_layout = QVBoxLayout()
|
||||
main_layout.setContentsMargins(20, 20, 20, 20)
|
||||
main_layout.setSpacing(10)
|
||||
|
||||
# 标题
|
||||
# 1. 公式配置源 (只读)
|
||||
path_group = QGroupBox("公式配置源 (内置)")
|
||||
path_layout = QVBoxLayout()
|
||||
self.formula_csv_widget = FileSelectWidget("内置CSV路径:", "CSV Files (*.csv)")
|
||||
self.formula_csv_widget.set_path(self.builtin_formula_path)
|
||||
self.formula_csv_widget.set_read_only(True)
|
||||
self.formula_csv_widget.line_edit.setStyleSheet("background-color: #f0f0f0; color: #666;")
|
||||
path_layout.addWidget(self.formula_csv_widget)
|
||||
path_group.setLayout(path_layout)
|
||||
main_layout.addWidget(path_group)
|
||||
|
||||
# 2. 训练数据输入
|
||||
input_group = QGroupBox("输入样本数据")
|
||||
input_layout = QVBoxLayout()
|
||||
self.training_data_widget = FileSelectWidget("特征提取CSV:", "CSV Files (*.csv)")
|
||||
input_layout.addWidget(self.training_data_widget)
|
||||
input_group.setLayout(input_layout)
|
||||
main_layout.addWidget(input_group)
|
||||
|
||||
# 训练数据文件（用于独立运行）
|
||||
self.training_csv_file = FileSelectWidget(
|
||||
"训练数据:",
|
||||
"CSV Files (*.csv);;All Files (*.*)"
|
||||
)
|
||||
layout.addWidget(self.training_csv_file)
|
||||
# 3. 公式选择区 (分组 ListWidget)
|
||||
self.formula_group = QGroupBox("待计算水质指数勾选")
|
||||
formula_outer_layout = QVBoxLayout()
|
||||
|
||||
# 机器学习模型页面
|
||||
self.ml_page = QWidget()
|
||||
self.create_ml_page()
|
||||
layout.addWidget(self.ml_page)
|
||||
btn_layout = QHBoxLayout()
|
||||
self.select_all_btn = QPushButton("全选")
|
||||
self.deselect_all_btn = QPushButton("清空")
|
||||
self.select_ratio_btn = QPushButton("仅选比值型")
|
||||
self.select_conc_btn = QPushButton("仅选浓度型")
|
||||
self.select_all_btn.clicked.connect(self.select_all_formulas)
|
||||
self.deselect_all_btn.clicked.connect(self.deselect_all_formulas)
|
||||
self.select_ratio_btn.clicked.connect(self._select_ratio_only)
|
||||
self.select_conc_btn.clicked.connect(self._select_conc_only)
|
||||
btn_layout.addWidget(self.select_all_btn)
|
||||
btn_layout.addWidget(self.deselect_all_btn)
|
||||
btn_layout.addWidget(self.select_ratio_btn)
|
||||
btn_layout.addWidget(self.select_conc_btn)
|
||||
btn_layout.addStretch()
|
||||
|
||||
# 输出文件路径
|
||||
self.output_path = FileSelectWidget(
|
||||
"输出文件:",
|
||||
"CSV Files (*.csv);;All Files (*.*)",
|
||||
mode="save"
|
||||
)
|
||||
self.output_path.line_edit.setPlaceholderText("自动生成，或手动指定输出文件路径...")
|
||||
self.output_path.browse_btn.clicked.disconnect()
|
||||
self.output_path.browse_btn.clicked.connect(self.browse_output_path)
|
||||
layout.addWidget(self.output_path)
|
||||
self.refresh_button = QPushButton("重新加载")
|
||||
self.refresh_button.clicked.connect(lambda: self.refresh_formulas(silent=False))
|
||||
btn_layout.addWidget(self.refresh_button)
|
||||
|
||||
# 启用步骤
|
||||
self.enable_checkbox = QCheckBox("启用此步骤")
|
||||
self.enable_checkbox.setChecked(False)
|
||||
layout.addWidget(self.enable_checkbox)
|
||||
formula_outer_layout.addLayout(btn_layout)
|
||||
|
||||
# 独立运行按钮
|
||||
self.run_btn = QPushButton("独立运行此步骤")
|
||||
self.run_btn.setStyleSheet(ModernStylesheet.get_button_stylesheet('success'))
|
||||
self.run_btn.clicked.connect(self.run_step)
|
||||
layout.addWidget(self.run_btn)
|
||||
scroll = QScrollArea()
|
||||
scroll.setWidgetResizable(True)
|
||||
scroll.setMinimumHeight(280)
|
||||
self.scroll_content = QWidget()
|
||||
self.formula_layout = QVBoxLayout(self.scroll_content)
|
||||
self.formula_layout.setContentsMargins(4, 4, 4, 4)
|
||||
self.formula_layout.setSpacing(2)
|
||||
self.formula_layout.setAlignment(Qt.AlignTop)
|
||||
|
||||
layout.addStretch()
|
||||
self.setLayout(layout)
|
||||
self.formula_list = QListWidget()
|
||||
self.formula_list.setSelectionMode(QAbstractItemView.MultiSelection)
|
||||
self.formula_list.itemChanged.connect(self._on_item_changed)
|
||||
self.formula_layout.addWidget(self.formula_list)
|
||||
|
||||
def create_ml_page(self):
|
||||
"""创建机器学习模型页面"""
|
||||
layout = QVBoxLayout()
|
||||
scroll.setWidget(self.scroll_content)
|
||||
formula_outer_layout.addWidget(scroll)
|
||||
|
||||
# 参数设置
|
||||
params_group = QGroupBox("训练参数")
|
||||
params_layout = QFormLayout()
|
||||
self.formula_group.setLayout(formula_outer_layout)
|
||||
main_layout.addWidget(self.formula_group)
|
||||
|
||||
self.feature_start = QLineEdit()
|
||||
self.feature_start.setText("374.285004")
|
||||
params_layout.addRow("特征起始列:", self.feature_start)
|
||||
# 4. 输出选项
|
||||
output_group = QGroupBox("输出模式")
|
||||
output_layout = QVBoxLayout()
|
||||
|
||||
self.cv_folds = QSpinBox()
|
||||
self.cv_folds.setRange(2, 10)
|
||||
self.cv_folds.setValue(3)
|
||||
params_layout.addRow("交叉验证折数:", self.cv_folds)
|
||||
mode_layout = QHBoxLayout()
|
||||
self.mode_group = QButtonGroup()
|
||||
self.radio_both = QRadioButton("两者皆出")
|
||||
self.radio_wide = QRadioButton("仅宽表")
|
||||
self.radio_single = QRadioButton("仅单文件")
|
||||
self.mode_group.addButton(self.radio_both, 0)
|
||||
self.mode_group.addButton(self.radio_wide, 1)
|
||||
self.mode_group.addButton(self.radio_single, 2)
|
||||
self.radio_both.setChecked(True)
|
||||
mode_layout.addWidget(self.radio_both)
|
||||
mode_layout.addWidget(self.radio_wide)
|
||||
mode_layout.addWidget(self.radio_single)
|
||||
mode_layout.addStretch()
|
||||
output_layout.addLayout(mode_layout)
|
||||
|
||||
params_group.setLayout(params_layout)
|
||||
layout.addWidget(params_group)
|
||||
self.enable_checkbox = QCheckBox("启用计算流程")
|
||||
self.enable_checkbox.setChecked(True)
|
||||
output_layout.addWidget(self.enable_checkbox)
|
||||
|
||||
# 预处理方法 - 多选
|
||||
preproc_group = QGroupBox("预处理方法 (可多选)")
|
||||
preproc_layout = QVBoxLayout()
|
||||
output_group.setLayout(output_layout)
|
||||
main_layout.addWidget(output_group)
|
||||
|
||||
preproc_grid = QGridLayout()
|
||||
self.preproc_checkboxes = {}
|
||||
preproc_methods = ['None', 'MMS', 'SS', 'SNV', 'MA', 'SG', 'MSC', 'D1', 'D2', 'DT', 'CT']
|
||||
# 5. 运行按钮
|
||||
self.run_button = QPushButton("立即执行计算")
|
||||
self.run_button.setStyleSheet(ModernStylesheet.get_button_stylesheet('success'))
|
||||
self.run_button.setMinimumHeight(40)
|
||||
self.run_button.clicked.connect(self.run_step)
|
||||
main_layout.addWidget(self.run_button)
|
||||
|
||||
for i, method in enumerate(preproc_methods):
|
||||
checkbox = QCheckBox(PREPROC_CHINESE.get(method, method))
|
||||
checkbox.setChecked(False)
|
||||
self.preproc_checkboxes[method] = checkbox
|
||||
preproc_grid.addWidget(checkbox, i // 4, i % 4)
|
||||
self.setLayout(main_layout)
|
||||
|
||||
button_layout = QHBoxLayout()
|
||||
select_all_btn = QPushButton("全选")
|
||||
deselect_all_btn = QPushButton("全不选")
|
||||
select_all_btn.clicked.connect(lambda: self._toggle_checkboxes(self.preproc_checkboxes, True))
|
||||
deselect_all_btn.clicked.connect(lambda: self._toggle_checkboxes(self.preproc_checkboxes, False))
|
||||
button_layout.addWidget(select_all_btn)
|
||||
button_layout.addWidget(deselect_all_btn)
|
||||
button_layout.addStretch()
|
||||
|
||||
preproc_layout.addLayout(preproc_grid)
|
||||
preproc_layout.addLayout(button_layout)
|
||||
preproc_group.setLayout(preproc_layout)
|
||||
layout.addWidget(preproc_group)
|
||||
|
||||
# 模型选择 - 多选
|
||||
model_group = QGroupBox("模型类型 (可多选)")
|
||||
model_layout = QVBoxLayout()
|
||||
|
||||
model_grid = QGridLayout()
|
||||
self.model_checkboxes = {}
|
||||
|
||||
model_groups = [
|
||||
("【线性模型】", ['LinearRegression', 'Ridge', 'Lasso', 'ElasticNet', 'PLS']),
|
||||
("【树模型】", ['DecisionTree', 'RF', 'ExtraTrees', 'XGBoost', 'LightGBM', 'CatBoost']),
|
||||
("【集成学习】", ['GradientBoosting', 'AdaBoost']),
|
||||
("【其他模型】", ['SVR', 'KNN', 'MLP'])
|
||||
]
|
||||
|
||||
row = 0
|
||||
for group_name, models in model_groups:
|
||||
group_label = QLabel(f"<b>{group_name}</b>")
|
||||
group_label.setStyleSheet(
|
||||
f"background-color: {ModernStylesheet.COLORS['hover']}; "
|
||||
f"padding: 5px; border: 1px solid {ModernStylesheet.COLORS['border_light']}; "
|
||||
f"border-radius: 3px;"
|
||||
)
|
||||
model_grid.addWidget(group_label, row, 0, 1, 4)
|
||||
row += 1
|
||||
|
||||
for i, model in enumerate(models):
|
||||
checkbox = QCheckBox(MODEL_CHINESE.get(model, model))
|
||||
checkbox.setChecked(False)
|
||||
self.model_checkboxes[model] = checkbox
|
||||
model_grid.addWidget(checkbox, row, i % 4)
|
||||
if (i + 1) % 4 == 0:
|
||||
row += 1
|
||||
|
||||
row += 1
|
||||
|
||||
model_button_layout = QHBoxLayout()
|
||||
model_select_all = QPushButton("全选")
|
||||
model_deselect_all = QPushButton("全不选")
|
||||
model_select_all.clicked.connect(lambda: self._toggle_checkboxes(self.model_checkboxes, True))
|
||||
model_deselect_all.clicked.connect(lambda: self._toggle_checkboxes(self.model_checkboxes, False))
|
||||
model_button_layout.addWidget(model_select_all)
|
||||
model_button_layout.addWidget(model_deselect_all)
|
||||
model_button_layout.addStretch()
|
||||
|
||||
model_layout.addLayout(model_grid)
|
||||
model_layout.addLayout(model_button_layout)
|
||||
model_group.setLayout(model_layout)
|
||||
layout.addWidget(model_group)
|
||||
|
||||
# 数据划分方法 - 多选
|
||||
split_group = QGroupBox("数据划分方法 (可多选)")
|
||||
split_layout = QVBoxLayout()
|
||||
|
||||
split_grid = QGridLayout()
|
||||
self.split_checkboxes = {}
|
||||
split_methods = ['spxy', 'ks', 'random']
|
||||
|
||||
for i, method in enumerate(split_methods):
|
||||
checkbox = QCheckBox(SPLIT_CHINESE.get(method, method))
|
||||
checkbox.setChecked(False)
|
||||
self.split_checkboxes[method] = checkbox
|
||||
split_grid.addWidget(checkbox, 0, i)
|
||||
|
||||
split_button_layout = QHBoxLayout()
|
||||
split_select_all = QPushButton("全选")
|
||||
split_deselect_all = QPushButton("全不选")
|
||||
split_select_all.clicked.connect(lambda: self._toggle_checkboxes(self.split_checkboxes, True))
|
||||
split_deselect_all.clicked.connect(lambda: self._toggle_checkboxes(self.split_checkboxes, False))
|
||||
split_button_layout.addWidget(split_select_all)
|
||||
split_button_layout.addWidget(split_deselect_all)
|
||||
split_button_layout.addStretch()
|
||||
|
||||
split_layout.addLayout(split_grid)
|
||||
split_layout.addLayout(split_button_layout)
|
||||
split_group.setLayout(split_layout)
|
||||
layout.addWidget(split_group)
|
||||
|
||||
self.ml_page.setLayout(layout)
|
||||
|
||||
def _toggle_checkboxes(self, checkboxes_dict, checked):
|
||||
"""统一设置checkbox状态"""
|
||||
for checkbox in checkboxes_dict.values():
|
||||
checkbox.setChecked(checked)
|
||||
|
||||
def _get_default_work_dir(self):
|
||||
"""获取 work_dir，优先用 panel 自身缓存的，否则尝试从主窗口取"""
|
||||
if hasattr(self, 'work_dir') and self.work_dir:
|
||||
return str(self.work_dir)
|
||||
mw = self.window()
|
||||
if mw and hasattr(mw, 'work_dir') and mw.work_dir:
|
||||
return str(mw.work_dir)
|
||||
return ""
|
||||
|
||||
def browse_output_path(self):
|
||||
"""浏览输出文件路径（保存对话框）"""
|
||||
current = self.output_path.get_path().strip()
|
||||
if current:
|
||||
initial_dir = os.path.dirname(current)
|
||||
initial_file = os.path.basename(current)
|
||||
def _on_item_changed(self, item: QListWidgetItem):
|
||||
if item.checkState() == Qt.Checked:
|
||||
bg_color = self.COLOR_RATIO
|
||||
for name, ref_item in self.index_checkboxes.items():
|
||||
if ref_item is item:
|
||||
bg_color = self._formula_color_map.get(name, self.COLOR_RATIO)
|
||||
break
|
||||
item.setBackground(QBrush(bg_color))
|
||||
else:
|
||||
initial_dir = ""
|
||||
initial_file = ""
|
||||
item.setBackground(QBrush(self.COLOR_RATIO))
|
||||
|
||||
if not initial_dir or not os.path.isdir(initial_dir):
|
||||
# 默认定位到 indices 目录
|
||||
work_dir = self._get_default_work_dir()
|
||||
initial_dir = os.path.join(work_dir, "6_water_quality_indices") if work_dir else ""
|
||||
if initial_dir and not os.path.isdir(initial_dir):
|
||||
os.makedirs(initial_dir, exist_ok=True)
|
||||
|
||||
file_path, _ = QFileDialog.getSaveFileName(
|
||||
self, "保存输出文件", os.path.join(initial_dir, initial_file) if initial_file else initial_dir,
|
||||
"CSV Files (*.csv);;All Files (*.*)"
|
||||
)
|
||||
if file_path:
|
||||
self.output_path.set_path(file_path)
|
||||
|
||||
def get_config(self):
|
||||
"""获取配置"""
|
||||
preprocessing_methods = [
|
||||
method for method, checkbox in self.preproc_checkboxes.items()
|
||||
if checkbox.isChecked()
|
||||
]
|
||||
model_names = [
|
||||
model for model, checkbox in self.model_checkboxes.items()
|
||||
if checkbox.isChecked()
|
||||
]
|
||||
split_methods = [
|
||||
method for method, checkbox in self.split_checkboxes.items()
|
||||
if checkbox.isChecked()
|
||||
]
|
||||
|
||||
config = {
|
||||
'feature_start_column': self.feature_start.text(),
|
||||
'preprocessing_methods': preprocessing_methods if preprocessing_methods else ['None'],
|
||||
'model_names': model_names if model_names else ['SVR'],
|
||||
'split_methods': split_methods if split_methods else ['random'],
|
||||
'cv_folds': self.cv_folds.value()
|
||||
}
|
||||
training_csv_path = self.training_csv_file.get_path()
|
||||
if training_csv_path:
|
||||
config['training_csv_path'] = training_csv_path
|
||||
output_path = self.output_path.get_path()
|
||||
if output_path:
|
||||
config['output_path'] = output_path
|
||||
return config
|
||||
|
||||
def set_config(self, config):
|
||||
"""设置配置"""
|
||||
if 'feature_start_column' in config:
|
||||
self.feature_start.setText(str(config['feature_start_column']))
|
||||
if 'cv_folds' in config:
|
||||
self.cv_folds.setValue(config['cv_folds'])
|
||||
if 'preprocessing_methods' in config:
|
||||
methods = config['preprocessing_methods']
|
||||
for method, checkbox in self.preproc_checkboxes.items():
|
||||
checkbox.setChecked(method in methods)
|
||||
if 'model_names' in config:
|
||||
models = config['model_names']
|
||||
for model, checkbox in self.model_checkboxes.items():
|
||||
checkbox.setChecked(model in models)
|
||||
if 'split_methods' in config:
|
||||
methods = config['split_methods']
|
||||
for method, checkbox in self.split_checkboxes.items():
|
||||
checkbox.setChecked(method in methods)
|
||||
if 'training_csv_path' in config:
|
||||
self.training_csv_file.set_path(config['training_csv_path'])
|
||||
if 'output_path' in config:
|
||||
self.output_path.set_path(config['output_path'])
|
||||
|
||||
def update_from_config(self, work_dir=None, pipeline=None):
|
||||
"""从全局配置自动填充训练数据和输出路径
|
||||
|
||||
Args:
|
||||
work_dir: 工作目录路径
|
||||
pipeline: Pipeline 实例（未使用，保留接口兼容性）
|
||||
"""
|
||||
if work_dir:
|
||||
self.work_dir = work_dir
|
||||
elif hasattr(self, 'work_dir') and self.work_dir:
|
||||
pass
|
||||
def _auto_load_formulas(self):
|
||||
if os.path.exists(self.builtin_formula_path):
|
||||
self.refresh_formulas(silent=True)
|
||||
else:
|
||||
self.work_dir = None
|
||||
print(f"DEBUG: 自动加载失败，路径不存在: {self.builtin_formula_path}")
|
||||
|
||||
# 1. 尝试从 Step5 界面读取训练数据路径，并确保为绝对路径
|
||||
main_window = self.window()
|
||||
if hasattr(main_window, 'step5_panel'):
|
||||
# 优先直接从 Step5 的输出 widget 读取
|
||||
step5_output = main_window.step5_panel.output_file.get_path()
|
||||
if step5_output:
|
||||
# 若为相对路径，使用 work_dir 合成为绝对路径
|
||||
if not os.path.isabs(step5_output):
|
||||
step5_output = os.path.join(self.work_dir or '', step5_output).replace('\\', '/')
|
||||
self.training_csv_file.set_path(step5_output)
|
||||
elif hasattr(main_window, 'step5_panel') and hasattr(main_window.step5_panel, 'get_config'):
|
||||
# 回退：从 Step5 的 config 字典中查找可能的键名
|
||||
step5_cfg = main_window.step5_panel.get_config()
|
||||
step5_csv = (
|
||||
step5_cfg.get('training_csv_path')
|
||||
or step5_cfg.get('output_file')
|
||||
or step5_cfg.get('csv_path')
|
||||
or step5_cfg.get('output_csv')
|
||||
)
|
||||
if step5_csv:
|
||||
# 若为相对路径，使用 work_dir 合成为绝对路径
|
||||
if not os.path.isabs(step5_csv):
|
||||
step5_csv = os.path.join(self.work_dir or '', step5_csv).replace('\\', '/')
|
||||
self.training_csv_file.set_path(step5_csv)
|
||||
|
||||
# 2. 自动填充输出文件路径（基于工作目录和输入文件名）
|
||||
# 输入是 training_spectra.csv → 输出 {work_dir}/6_water_quality_indices/training_spectra_indices.csv
|
||||
# 输入是 sampling_spectra.csv → 输出 {work_dir}/6_water_quality_indices/sampling_spectra_indices.csv
|
||||
if self.work_dir:
|
||||
indices_dir = os.path.join(self.work_dir, "6_water_quality_indices")
|
||||
os.makedirs(indices_dir, exist_ok=True)
|
||||
training_csv = self.training_csv_file.get_path()
|
||||
if training_csv:
|
||||
basename = os.path.splitext(os.path.basename(training_csv))[0]
|
||||
output_file = f"{basename}_indices.csv"
|
||||
else:
|
||||
output_file = "water_quality_indices.csv"
|
||||
output_path = os.path.join(indices_dir, output_file).replace('\\', '/')
|
||||
self.output_path.set_path(output_path)
|
||||
else:
|
||||
self.output_path.set_path("")
|
||||
|
||||
def run_step(self):
|
||||
"""独立运行步骤7"""
|
||||
training_csv_path = self.training_csv_file.get_path()
|
||||
if not training_csv_path:
|
||||
QMessageBox.warning(self, "输入错误", "请选择训练数据CSV文件！")
|
||||
def refresh_formulas(self, silent=False):
|
||||
path = self.builtin_formula_path
|
||||
if not os.path.exists(path):
|
||||
if not silent:
|
||||
QMessageBox.warning(self, "错误", f"找不到内置公式文件:\n{path}")
|
||||
return
|
||||
|
||||
main_window = self.window()
|
||||
if hasattr(main_window, 'run_single_step'):
|
||||
config = {'step7': self.get_config()}
|
||||
main_window.run_single_step('step7', config)
|
||||
try:
|
||||
df = None
|
||||
for enc in ('utf-8', 'gbk', 'utf-8-sig'):
|
||||
try:
|
||||
df = pd.read_csv(path, encoding=enc)
|
||||
if 'Formula_Name' in df.columns:
|
||||
break
|
||||
except Exception:
|
||||
continue
|
||||
|
||||
def get_training_params(self):
|
||||
"""获取模型训练参数"""
|
||||
return {
|
||||
'pipeline_type': 'machine_learning',
|
||||
'feature_start': float(self.feature_start.text()),
|
||||
'cv_folds': self.cv_folds.value(),
|
||||
'preprocess_methods': [method for method, cb in self.preproc_checkboxes.items() if cb.isChecked()],
|
||||
'model_types': [model for model, cb in self.model_checkboxes.items() if cb.isChecked()],
|
||||
'split_methods': [method for method, cb in self.split_checkboxes.items() if cb.isChecked()]
|
||||
if df is None or 'Formula_Name' not in df.columns:
|
||||
if not silent:
|
||||
QMessageBox.critical(self, "错误", "CSV缺少 'Formula_Name' 列")
|
||||
return
|
||||
|
||||
self._formula_type_map.clear()
|
||||
self._formula_coef_map.clear()
|
||||
for _, row in df.iterrows():
|
||||
name = str(row['Formula_Name']).strip()
|
||||
if not name:
|
||||
continue
|
||||
ftype = str(row.get('Formula_Type', 'ratio')).strip().lower()
|
||||
self._formula_type_map[name] = ftype
|
||||
|
||||
# Parse Coefficient for concentration formulas
|
||||
coef_str = str(row.get('Coefficient', '')).strip()
|
||||
if coef_str:
|
||||
try:
|
||||
coeffs = [float(c.strip()) for c in coef_str.split(',') if c.strip()]
|
||||
self._formula_coef_map[name] = coeffs
|
||||
except Exception:
|
||||
self._formula_coef_map[name] = []
|
||||
else:
|
||||
self._formula_coef_map[name] = []
|
||||
|
||||
self.formula_list.clear()
|
||||
self.index_checkboxes.clear()
|
||||
|
||||
self._formula_color_map.clear()
|
||||
for name, ftype in self._formula_type_map.items():
|
||||
item = QListWidgetItem(name, self.formula_list)
|
||||
item.setCheckState(Qt.Checked)
|
||||
if ftype == 'concentration':
|
||||
bg_color = QColor(220, 240, 255)
|
||||
else:
|
||||
bg_color = self.COLOR_RATIO
|
||||
self._formula_color_map[name] = bg_color
|
||||
item.setBackground(QBrush(bg_color))
|
||||
self.index_checkboxes[name] = item
|
||||
|
||||
self.formula_list.adjustSize()
|
||||
print(f"✅ 加载 {len(self.index_checkboxes)} 个公式")
|
||||
|
||||
except Exception as e:
|
||||
if not silent:
|
||||
QMessageBox.critical(self, "加载失败", f"原因: {str(e)}")
|
||||
|
||||
def _select_ratio_only(self):
|
||||
for name, item in self.index_checkboxes.items():
|
||||
ftype = self._formula_type_map.get(name, 'ratio')
|
||||
item.setCheckState(Qt.Checked if ftype == 'ratio' else Qt.Unchecked)
|
||||
|
||||
def _select_conc_only(self):
|
||||
for name, item in self.index_checkboxes.items():
|
||||
ftype = self._formula_type_map.get(name, 'ratio')
|
||||
item.setCheckState(Qt.Checked if ftype == 'concentration' else Qt.Unchecked)
|
||||
|
||||
def select_all_formulas(self):
|
||||
for item in self.index_checkboxes.values():
|
||||
item.setCheckState(Qt.Checked)
|
||||
|
||||
def deselect_all_formulas(self):
|
||||
for item in self.index_checkboxes.values():
|
||||
item.setCheckState(Qt.Unchecked)
|
||||
|
||||
def get_config(self) -> Dict:
|
||||
selected = [
|
||||
name for name, item in self.index_checkboxes.items()
|
||||
if item.checkState() == Qt.Checked
|
||||
]
|
||||
# Build coefficient dict for selected formulas
|
||||
formula_coefficients = {
|
||||
name: self._formula_coef_map.get(name, [])
|
||||
for name in selected
|
||||
}
|
||||
return {
|
||||
'training_csv_path': self.training_data_widget.get_path(),
|
||||
'formula_csv_file': self.builtin_formula_path,
|
||||
'formula_names': selected,
|
||||
'formula_coefficients': formula_coefficients,
|
||||
'enabled': self.enable_checkbox.isChecked(),
|
||||
'output_mode': self.mode_group.checkedId(),
|
||||
}
|
||||
|
||||
def set_config(self, config: Dict):
|
||||
if 'training_csv_path' in config:
|
||||
self.training_data_widget.set_path(config['training_csv_path'])
|
||||
if 'formula_names' in config:
|
||||
sel = set(config['formula_names'])
|
||||
for name, item in self.index_checkboxes.items():
|
||||
item.setCheckState(Qt.Checked if name in sel else Qt.Unchecked)
|
||||
self.enable_checkbox.setChecked(config.get('enabled', True))
|
||||
if 'output_mode' in config:
|
||||
btn = self.mode_group.button(config['output_mode'])
|
||||
if btn:
|
||||
btn.setChecked(True)
|
||||
|
||||
def update_from_config(self, work_dir=None, pipeline=None):
|
||||
if work_dir:
|
||||
self.work_dir = work_dir
|
||||
main = self.window()
|
||||
if hasattr(main, 'step6_panel'):
|
||||
p5 = main.step6_panel.output_file.get_path()
|
||||
if p5:
|
||||
if not os.path.isabs(p5):
|
||||
p5 = os.path.join(self.work_dir or '', p5)
|
||||
p5 = p5.replace('\\', '/')
|
||||
self.training_data_widget.set_path(p5)
|
||||
|
||||
def _get_work_dir(self) -> Optional[str]:
|
||||
if self.work_dir:
|
||||
return self.work_dir
|
||||
main = self.window()
|
||||
if hasattr(main, 'work_dir') and main.work_dir:
|
||||
return main.work_dir
|
||||
return None
|
||||
|
||||
def _get_coord_cols(self, df: pd.DataFrame) -> Tuple[str, str]:
|
||||
coord_candidates = ['lon', 'lng', 'longitude', '经度', 'x', 'lon_utm', 'utm_x', 'pixel_x']
|
||||
lat_candidates = ['lat', 'latitude', '纬度', 'y', 'lat_utm', 'utm_y', 'pixel_y']
|
||||
|
||||
x_col, y_col = None, None
|
||||
for col in df.columns:
|
||||
cl = col.lower()
|
||||
if x_col is None and any(c in cl for c in coord_candidates):
|
||||
x_col = col
|
||||
if y_col is None and any(c in cl for c in lat_candidates):
|
||||
y_col = col
|
||||
|
||||
if x_col is None and len(df.columns) >= 2:
|
||||
x_col = df.columns[0]
|
||||
if y_col is None and len(df.columns) >= 2:
|
||||
y_col = df.columns[1]
|
||||
|
||||
return x_col or 'x_coord', y_col or 'y_coord'
|
||||
|
||||
def run_step(self):
|
||||
config = self.get_config()
|
||||
|
||||
if not config['enabled']:
|
||||
QMessageBox.information(self, "提示", "已禁用计算流程（启用计算流程未勾选）")
|
||||
return
|
||||
|
||||
training_path = config['training_csv_path']
|
||||
if not training_path or not os.path.exists(training_path):
|
||||
QMessageBox.warning(self, "提示", "请先选择输入特征提取CSV文件")
|
||||
return
|
||||
|
||||
formula_names = config['formula_names']
|
||||
if not formula_names:
|
||||
QMessageBox.warning(self, "提示", "请至少勾选一个公式")
|
||||
return
|
||||
|
||||
output_mode = config['output_mode']
|
||||
|
||||
try:
|
||||
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)
|
||||
|
||||
# 构建 formula_csv_path（使用内置 waterindex.csv）
|
||||
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
|
||||
|
||||
if output_mode in (0, 1):
|
||||
track_a_dir = os.path.join(work_dir, "6_water_quality_indices") if work_dir else "6_water_quality_indices"
|
||||
os.makedirs(track_a_dir, exist_ok=True)
|
||||
track_a_path = os.path.join(track_a_dir, "training_spectra_indices.csv")
|
||||
|
||||
if output_mode in (0, 2):
|
||||
track_b_dir = os.path.join(work_dir, "11_12_13_predictions", "Traditional_Indices") if work_dir else "11_12_13_predictions/Traditional_Indices"
|
||||
os.makedirs(track_b_dir, exist_ok=True)
|
||||
|
||||
saved = []
|
||||
if output_mode in (0, 1):
|
||||
output_df.to_csv(track_a_path, index=False, float_format='%.6f')
|
||||
saved.append(f"宽表: {track_a_path}")
|
||||
|
||||
if output_mode in (0, 2):
|
||||
coord_x = spec_df[x_col].values if x_col in spec_df.columns else np.arange(len(spec_df))
|
||||
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 output_df.columns:
|
||||
continue
|
||||
single_df = pd.DataFrame({
|
||||
'x_coord': coord_x,
|
||||
'y_coord': coord_y,
|
||||
'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")
|
||||
single_df.to_csv(out_path, index=False, float_format='%.6f')
|
||||
saved.append(f"单文件目录: {track_b_dir}")
|
||||
|
||||
QMessageBox.information(
|
||||
self, "计算完成",
|
||||
f"已保存 {len(saved)} 个输出目标:\n" + "\n".join(saved)
|
||||
)
|
||||
|
||||
except ImportError as 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()}")
|
||||
@ -1,424 +1,415 @@
|
||||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
Step7 面板 - 机器学习建模
|
||||
"""
|
||||
|
||||
import os
|
||||
import sys
|
||||
import pandas as pd
|
||||
import numpy as np
|
||||
from pathlib import Path
|
||||
from typing import Dict, List, Optional, Tuple
|
||||
|
||||
from PyQt5.QtWidgets import (
|
||||
QWidget, QVBoxLayout, QGroupBox, QGridLayout,
|
||||
QHBoxLayout, QLabel, QCheckBox, QPushButton, QMessageBox,
|
||||
QScrollArea, QListWidget, QListWidgetItem, QAbstractItemView,
|
||||
QRadioButton, QButtonGroup
|
||||
QWidget, QVBoxLayout, QGroupBox, QFormLayout, QGridLayout,
|
||||
QHBoxLayout, QLabel, QLineEdit, QSpinBox, QCheckBox,
|
||||
QPushButton, QFileDialog, QMessageBox,
|
||||
)
|
||||
from PyQt5.QtCore import Qt
|
||||
from PyQt5.QtGui import QColor, QBrush, QFont
|
||||
|
||||
from src.gui.components.custom_widgets import FileSelectWidget
|
||||
from src.gui.styles import ModernStylesheet
|
||||
|
||||
|
||||
def get_resource_path(relative_path: str) -> str:
|
||||
"""适配开发与 PyInstaller 环境的路径获取逻辑。"""
|
||||
if hasattr(sys, '_MEIPASS'):
|
||||
internal = os.path.join(sys._MEIPASS, '_internal', relative_path)
|
||||
if os.path.exists(internal):
|
||||
return internal
|
||||
return os.path.join(sys._MEIPASS, relative_path)
|
||||
# ============================================================
|
||||
# 中文映射表（内部键名 -> 显示文本）
|
||||
# ============================================================
|
||||
|
||||
exe_dir = os.path.dirname(sys.executable)
|
||||
internal = os.path.join(exe_dir, '_internal', relative_path)
|
||||
if os.path.exists(internal):
|
||||
return internal
|
||||
# 预处理方法：内部键 -> 显示文本
|
||||
PREPROC_CHINESE = {
|
||||
'None': '无 (None)',
|
||||
'MMS': '最小-最大归一化 (MMS)',
|
||||
'SS': '标度化 (SS)',
|
||||
'SNV': '标准正态变换 (SNV)',
|
||||
'MA': '移动平均 (MA)',
|
||||
'SG': 'Savitzky-Golay (SG)',
|
||||
'MSC': '多元散射校正 (MSC)',
|
||||
'D1': '一阶导数 (D1)',
|
||||
'D2': '二阶导数 (D2)',
|
||||
'DT': '去趋势 (DT)',
|
||||
'CT': '中心化 (CT)',
|
||||
}
|
||||
|
||||
base_dir = Path(__file__).resolve().parent.parent / "model"
|
||||
return str(base_dir / os.path.basename(relative_path))
|
||||
# 模型类型：内部键 -> 显示文本
|
||||
MODEL_CHINESE = {
|
||||
# 线性模型
|
||||
'LinearRegression': '多元线性回归 (MLR)',
|
||||
'Ridge': '岭回归 (Ridge)',
|
||||
'Lasso': '套索回归 (Lasso)',
|
||||
'ElasticNet': '弹性网络 (ElasticNet)',
|
||||
'PLS': '偏最小二乘 (PLSR)',
|
||||
# 树模型
|
||||
'DecisionTree': '决策树 (CART)',
|
||||
'RF': '随机森林 (RF)',
|
||||
'ExtraTrees': '极端随机树 (ET)',
|
||||
'XGBoost': '极值梯度提升 (XGBoost)',
|
||||
'LightGBM': '轻量梯度提升 (LightGBM)',
|
||||
'CatBoost': '类别梯度提升 (CatBoost)',
|
||||
# 集成学习
|
||||
'GradientBoosting': '梯度提升树 (GBDT)',
|
||||
'AdaBoost': '自适应提升 (AdaBoost)',
|
||||
# 其他模型
|
||||
'SVR': '支持向量回归 (SVR)',
|
||||
'KNN': 'K近邻回归 (KNN)',
|
||||
'MLP': '多层感知机 (BP神经网络)',
|
||||
}
|
||||
|
||||
# 数据划分方法：内部键 -> 显示文本
|
||||
SPLIT_CHINESE = {
|
||||
'spxy': 'SPXY 算法 (考量X-Y空间)',
|
||||
'ks': 'KS 算法 (考量X空间)',
|
||||
'random': '随机划分 (Random)',
|
||||
}
|
||||
|
||||
|
||||
class Step8Panel(QWidget):
|
||||
COLOR_RATIO = QColor(255, 255, 255)
|
||||
COLOR_CONCENTRATION = QColor(220, 240, 255)
|
||||
COLOR_HEADER = QColor(245, 245, 245)
|
||||
|
||||
"""步骤8：水质参数指数计算"""
|
||||
def __init__(self, parent=None):
|
||||
super().__init__(parent)
|
||||
self.index_checkboxes: Dict[str, QListWidgetItem] = {}
|
||||
self.work_dir: Optional[str] = None
|
||||
self.builtin_formula_path = get_resource_path("waterindex.csv")
|
||||
self._formula_type_map: Dict[str, str] = {}
|
||||
self._formula_color_map: Dict[str, QColor] = {}
|
||||
self._formula_coef_map: Dict[str, List[float]] = {}
|
||||
|
||||
self.init_ui()
|
||||
self._auto_load_formulas()
|
||||
|
||||
def init_ui(self):
|
||||
main_layout = QVBoxLayout()
|
||||
main_layout.setContentsMargins(20, 20, 20, 20)
|
||||
main_layout.setSpacing(10)
|
||||
layout = QVBoxLayout()
|
||||
|
||||
# 1. 公式配置源 (只读)
|
||||
path_group = QGroupBox("公式配置源 (内置)")
|
||||
path_layout = QVBoxLayout()
|
||||
self.formula_csv_widget = FileSelectWidget("内置CSV路径:", "CSV Files (*.csv)")
|
||||
self.formula_csv_widget.set_path(self.builtin_formula_path)
|
||||
self.formula_csv_widget.set_read_only(True)
|
||||
self.formula_csv_widget.line_edit.setStyleSheet("background-color: #f0f0f0; color: #666;")
|
||||
path_layout.addWidget(self.formula_csv_widget)
|
||||
path_group.setLayout(path_layout)
|
||||
main_layout.addWidget(path_group)
|
||||
# 标题
|
||||
|
||||
# 2. 训练数据输入
|
||||
input_group = QGroupBox("输入样本数据")
|
||||
input_layout = QVBoxLayout()
|
||||
self.training_data_widget = FileSelectWidget("特征提取CSV:", "CSV Files (*.csv)")
|
||||
input_layout.addWidget(self.training_data_widget)
|
||||
input_group.setLayout(input_layout)
|
||||
main_layout.addWidget(input_group)
|
||||
|
||||
# 3. 公式选择区 (分组 ListWidget)
|
||||
self.formula_group = QGroupBox("待计算水质指数勾选")
|
||||
formula_outer_layout = QVBoxLayout()
|
||||
# 训练数据文件（用于独立运行）
|
||||
self.training_csv_file = FileSelectWidget(
|
||||
"训练数据:",
|
||||
"CSV Files (*.csv);;All Files (*.*)"
|
||||
)
|
||||
layout.addWidget(self.training_csv_file)
|
||||
|
||||
btn_layout = QHBoxLayout()
|
||||
self.select_all_btn = QPushButton("全选")
|
||||
self.deselect_all_btn = QPushButton("清空")
|
||||
self.select_ratio_btn = QPushButton("仅选比值型")
|
||||
self.select_conc_btn = QPushButton("仅选浓度型")
|
||||
self.select_all_btn.clicked.connect(self.select_all_formulas)
|
||||
self.deselect_all_btn.clicked.connect(self.deselect_all_formulas)
|
||||
self.select_ratio_btn.clicked.connect(self._select_ratio_only)
|
||||
self.select_conc_btn.clicked.connect(self._select_conc_only)
|
||||
btn_layout.addWidget(self.select_all_btn)
|
||||
btn_layout.addWidget(self.deselect_all_btn)
|
||||
btn_layout.addWidget(self.select_ratio_btn)
|
||||
btn_layout.addWidget(self.select_conc_btn)
|
||||
btn_layout.addStretch()
|
||||
# 机器学习模型页面
|
||||
self.ml_page = QWidget()
|
||||
self.create_ml_page()
|
||||
layout.addWidget(self.ml_page)
|
||||
|
||||
self.refresh_button = QPushButton("重新加载")
|
||||
self.refresh_button.clicked.connect(lambda: self.refresh_formulas(silent=False))
|
||||
btn_layout.addWidget(self.refresh_button)
|
||||
# 输出文件路径
|
||||
self.output_path = FileSelectWidget(
|
||||
"输出文件:",
|
||||
"CSV Files (*.csv);;All Files (*.*)",
|
||||
mode="save"
|
||||
)
|
||||
self.output_path.line_edit.setPlaceholderText("自动生成，或手动指定输出文件路径...")
|
||||
self.output_path.browse_btn.clicked.disconnect()
|
||||
self.output_path.browse_btn.clicked.connect(self.browse_output_path)
|
||||
layout.addWidget(self.output_path)
|
||||
|
||||
formula_outer_layout.addLayout(btn_layout)
|
||||
# 启用步骤
|
||||
self.enable_checkbox = QCheckBox("启用此步骤")
|
||||
self.enable_checkbox.setChecked(False)
|
||||
layout.addWidget(self.enable_checkbox)
|
||||
|
||||
scroll = QScrollArea()
|
||||
scroll.setWidgetResizable(True)
|
||||
scroll.setMinimumHeight(280)
|
||||
self.scroll_content = QWidget()
|
||||
self.formula_layout = QVBoxLayout(self.scroll_content)
|
||||
self.formula_layout.setContentsMargins(4, 4, 4, 4)
|
||||
self.formula_layout.setSpacing(2)
|
||||
self.formula_layout.setAlignment(Qt.AlignTop)
|
||||
# 独立运行按钮
|
||||
self.run_btn = QPushButton("独立运行此步骤")
|
||||
self.run_btn.setStyleSheet(ModernStylesheet.get_button_stylesheet('success'))
|
||||
self.run_btn.clicked.connect(self.run_step)
|
||||
layout.addWidget(self.run_btn)
|
||||
|
||||
self.formula_list = QListWidget()
|
||||
self.formula_list.setSelectionMode(QAbstractItemView.MultiSelection)
|
||||
self.formula_list.itemChanged.connect(self._on_item_changed)
|
||||
self.formula_layout.addWidget(self.formula_list)
|
||||
layout.addStretch()
|
||||
self.setLayout(layout)
|
||||
|
||||
scroll.setWidget(self.scroll_content)
|
||||
formula_outer_layout.addWidget(scroll)
|
||||
def create_ml_page(self):
|
||||
"""创建机器学习模型页面"""
|
||||
layout = QVBoxLayout()
|
||||
|
||||
self.formula_group.setLayout(formula_outer_layout)
|
||||
main_layout.addWidget(self.formula_group)
|
||||
# 参数设置
|
||||
params_group = QGroupBox("训练参数")
|
||||
params_layout = QFormLayout()
|
||||
|
||||
# 4. 输出选项
|
||||
output_group = QGroupBox("输出模式")
|
||||
output_layout = QVBoxLayout()
|
||||
self.feature_start = QLineEdit()
|
||||
self.feature_start.setText("374.285004")
|
||||
params_layout.addRow("特征起始列:", self.feature_start)
|
||||
|
||||
mode_layout = QHBoxLayout()
|
||||
self.mode_group = QButtonGroup()
|
||||
self.radio_both = QRadioButton("两者皆出")
|
||||
self.radio_wide = QRadioButton("仅宽表")
|
||||
self.radio_single = QRadioButton("仅单文件")
|
||||
self.mode_group.addButton(self.radio_both, 0)
|
||||
self.mode_group.addButton(self.radio_wide, 1)
|
||||
self.mode_group.addButton(self.radio_single, 2)
|
||||
self.radio_both.setChecked(True)
|
||||
mode_layout.addWidget(self.radio_both)
|
||||
mode_layout.addWidget(self.radio_wide)
|
||||
mode_layout.addWidget(self.radio_single)
|
||||
mode_layout.addStretch()
|
||||
output_layout.addLayout(mode_layout)
|
||||
self.cv_folds = QSpinBox()
|
||||
self.cv_folds.setRange(2, 10)
|
||||
self.cv_folds.setValue(3)
|
||||
params_layout.addRow("交叉验证折数:", self.cv_folds)
|
||||
|
||||
self.enable_checkbox = QCheckBox("启用计算流程")
|
||||
self.enable_checkbox.setChecked(True)
|
||||
output_layout.addWidget(self.enable_checkbox)
|
||||
params_group.setLayout(params_layout)
|
||||
layout.addWidget(params_group)
|
||||
|
||||
output_group.setLayout(output_layout)
|
||||
main_layout.addWidget(output_group)
|
||||
# 预处理方法 - 多选
|
||||
preproc_group = QGroupBox("预处理方法 (可多选)")
|
||||
preproc_layout = QVBoxLayout()
|
||||
|
||||
# 5. 运行按钮
|
||||
self.run_button = QPushButton("立即执行计算")
|
||||
self.run_button.setStyleSheet(ModernStylesheet.get_button_stylesheet('success'))
|
||||
self.run_button.setMinimumHeight(40)
|
||||
self.run_button.clicked.connect(self.run_step)
|
||||
main_layout.addWidget(self.run_button)
|
||||
preproc_grid = QGridLayout()
|
||||
self.preproc_checkboxes = {}
|
||||
preproc_methods = ['None', 'MMS', 'SS', 'SNV', 'MA', 'SG', 'MSC', 'D1', 'D2', 'DT', 'CT']
|
||||
|
||||
self.setLayout(main_layout)
|
||||
for i, method in enumerate(preproc_methods):
|
||||
checkbox = QCheckBox(PREPROC_CHINESE.get(method, method))
|
||||
checkbox.setChecked(False)
|
||||
self.preproc_checkboxes[method] = checkbox
|
||||
preproc_grid.addWidget(checkbox, i // 4, i % 4)
|
||||
|
||||
def _on_item_changed(self, item: QListWidgetItem):
|
||||
if item.checkState() == Qt.Checked:
|
||||
bg_color = self.COLOR_RATIO
|
||||
for name, ref_item in self.index_checkboxes.items():
|
||||
if ref_item is item:
|
||||
bg_color = self._formula_color_map.get(name, self.COLOR_RATIO)
|
||||
break
|
||||
item.setBackground(QBrush(bg_color))
|
||||
else:
|
||||
item.setBackground(QBrush(self.COLOR_RATIO))
|
||||
button_layout = QHBoxLayout()
|
||||
select_all_btn = QPushButton("全选")
|
||||
deselect_all_btn = QPushButton("全不选")
|
||||
select_all_btn.clicked.connect(lambda: self._toggle_checkboxes(self.preproc_checkboxes, True))
|
||||
deselect_all_btn.clicked.connect(lambda: self._toggle_checkboxes(self.preproc_checkboxes, False))
|
||||
button_layout.addWidget(select_all_btn)
|
||||
button_layout.addWidget(deselect_all_btn)
|
||||
button_layout.addStretch()
|
||||
|
||||
def _auto_load_formulas(self):
|
||||
if os.path.exists(self.builtin_formula_path):
|
||||
self.refresh_formulas(silent=True)
|
||||
else:
|
||||
print(f"DEBUG: 自动加载失败，路径不存在: {self.builtin_formula_path}")
|
||||
preproc_layout.addLayout(preproc_grid)
|
||||
preproc_layout.addLayout(button_layout)
|
||||
preproc_group.setLayout(preproc_layout)
|
||||
layout.addWidget(preproc_group)
|
||||
|
||||
def refresh_formulas(self, silent=False):
|
||||
path = self.builtin_formula_path
|
||||
if not os.path.exists(path):
|
||||
if not silent:
|
||||
QMessageBox.warning(self, "错误", f"找不到内置公式文件:\n{path}")
|
||||
return
|
||||
# 模型选择 - 多选
|
||||
model_group = QGroupBox("模型类型 (可多选)")
|
||||
model_layout = QVBoxLayout()
|
||||
|
||||
try:
|
||||
df = None
|
||||
for enc in ('utf-8', 'gbk', 'utf-8-sig'):
|
||||
try:
|
||||
df = pd.read_csv(path, encoding=enc)
|
||||
if 'Formula_Name' in df.columns:
|
||||
break
|
||||
except Exception:
|
||||
continue
|
||||
model_grid = QGridLayout()
|
||||
self.model_checkboxes = {}
|
||||
|
||||
if df is None or 'Formula_Name' not in df.columns:
|
||||
if not silent:
|
||||
QMessageBox.critical(self, "错误", "CSV缺少 'Formula_Name' 列")
|
||||
return
|
||||
|
||||
self._formula_type_map.clear()
|
||||
self._formula_coef_map.clear()
|
||||
for _, row in df.iterrows():
|
||||
name = str(row['Formula_Name']).strip()
|
||||
if not name:
|
||||
continue
|
||||
ftype = str(row.get('Formula_Type', 'ratio')).strip().lower()
|
||||
self._formula_type_map[name] = ftype
|
||||
|
||||
# Parse Coefficient for concentration formulas
|
||||
coef_str = str(row.get('Coefficient', '')).strip()
|
||||
if coef_str:
|
||||
try:
|
||||
coeffs = [float(c.strip()) for c in coef_str.split(',') if c.strip()]
|
||||
self._formula_coef_map[name] = coeffs
|
||||
except Exception:
|
||||
self._formula_coef_map[name] = []
|
||||
else:
|
||||
self._formula_coef_map[name] = []
|
||||
|
||||
self.formula_list.clear()
|
||||
self.index_checkboxes.clear()
|
||||
|
||||
self._formula_color_map.clear()
|
||||
for name, ftype in self._formula_type_map.items():
|
||||
item = QListWidgetItem(name, self.formula_list)
|
||||
item.setCheckState(Qt.Checked)
|
||||
if ftype == 'concentration':
|
||||
bg_color = QColor(220, 240, 255)
|
||||
else:
|
||||
bg_color = self.COLOR_RATIO
|
||||
self._formula_color_map[name] = bg_color
|
||||
item.setBackground(QBrush(bg_color))
|
||||
self.index_checkboxes[name] = item
|
||||
|
||||
self.formula_list.adjustSize()
|
||||
print(f"✅ 加载 {len(self.index_checkboxes)} 个公式")
|
||||
|
||||
except Exception as e:
|
||||
if not silent:
|
||||
QMessageBox.critical(self, "加载失败", f"原因: {str(e)}")
|
||||
|
||||
def _select_ratio_only(self):
|
||||
for name, item in self.index_checkboxes.items():
|
||||
ftype = self._formula_type_map.get(name, 'ratio')
|
||||
item.setCheckState(Qt.Checked if ftype == 'ratio' else Qt.Unchecked)
|
||||
|
||||
def _select_conc_only(self):
|
||||
for name, item in self.index_checkboxes.items():
|
||||
ftype = self._formula_type_map.get(name, 'ratio')
|
||||
item.setCheckState(Qt.Checked if ftype == 'concentration' else Qt.Unchecked)
|
||||
|
||||
def select_all_formulas(self):
|
||||
for item in self.index_checkboxes.values():
|
||||
item.setCheckState(Qt.Checked)
|
||||
|
||||
def deselect_all_formulas(self):
|
||||
for item in self.index_checkboxes.values():
|
||||
item.setCheckState(Qt.Unchecked)
|
||||
|
||||
def get_config(self) -> Dict:
|
||||
selected = [
|
||||
name for name, item in self.index_checkboxes.items()
|
||||
if item.checkState() == Qt.Checked
|
||||
model_groups = [
|
||||
("【线性模型】", ['LinearRegression', 'Ridge', 'Lasso', 'ElasticNet', 'PLS']),
|
||||
("【树模型】", ['DecisionTree', 'RF', 'ExtraTrees', 'XGBoost', 'LightGBM', 'CatBoost']),
|
||||
("【集成学习】", ['GradientBoosting', 'AdaBoost']),
|
||||
("【其他模型】", ['SVR', 'KNN', 'MLP'])
|
||||
]
|
||||
# Build coefficient dict for selected formulas
|
||||
formula_coefficients = {
|
||||
name: self._formula_coef_map.get(name, [])
|
||||
for name in selected
|
||||
}
|
||||
return {
|
||||
'training_csv_path': self.training_data_widget.get_path(),
|
||||
'formula_csv_file': self.builtin_formula_path,
|
||||
'formula_names': selected,
|
||||
'formula_coefficients': formula_coefficients,
|
||||
'enabled': self.enable_checkbox.isChecked(),
|
||||
'output_mode': self.mode_group.checkedId(),
|
||||
}
|
||||
|
||||
def set_config(self, config: Dict):
|
||||
row = 0
|
||||
for group_name, models in model_groups:
|
||||
group_label = QLabel(f"<b>{group_name}</b>")
|
||||
group_label.setStyleSheet(
|
||||
f"background-color: {ModernStylesheet.COLORS['hover']}; "
|
||||
f"padding: 5px; border: 1px solid {ModernStylesheet.COLORS['border_light']}; "
|
||||
f"border-radius: 3px;"
|
||||
)
|
||||
model_grid.addWidget(group_label, row, 0, 1, 4)
|
||||
row += 1
|
||||
|
||||
for i, model in enumerate(models):
|
||||
checkbox = QCheckBox(MODEL_CHINESE.get(model, model))
|
||||
checkbox.setChecked(False)
|
||||
self.model_checkboxes[model] = checkbox
|
||||
model_grid.addWidget(checkbox, row, i % 4)
|
||||
if (i + 1) % 4 == 0:
|
||||
row += 1
|
||||
|
||||
row += 1
|
||||
|
||||
model_button_layout = QHBoxLayout()
|
||||
model_select_all = QPushButton("全选")
|
||||
model_deselect_all = QPushButton("全不选")
|
||||
model_select_all.clicked.connect(lambda: self._toggle_checkboxes(self.model_checkboxes, True))
|
||||
model_deselect_all.clicked.connect(lambda: self._toggle_checkboxes(self.model_checkboxes, False))
|
||||
model_button_layout.addWidget(model_select_all)
|
||||
model_button_layout.addWidget(model_deselect_all)
|
||||
model_button_layout.addStretch()
|
||||
|
||||
model_layout.addLayout(model_grid)
|
||||
model_layout.addLayout(model_button_layout)
|
||||
model_group.setLayout(model_layout)
|
||||
layout.addWidget(model_group)
|
||||
|
||||
# 数据划分方法 - 多选
|
||||
split_group = QGroupBox("数据划分方法 (可多选)")
|
||||
split_layout = QVBoxLayout()
|
||||
|
||||
split_grid = QGridLayout()
|
||||
self.split_checkboxes = {}
|
||||
split_methods = ['spxy', 'ks', 'random']
|
||||
|
||||
for i, method in enumerate(split_methods):
|
||||
checkbox = QCheckBox(SPLIT_CHINESE.get(method, method))
|
||||
checkbox.setChecked(False)
|
||||
self.split_checkboxes[method] = checkbox
|
||||
split_grid.addWidget(checkbox, 0, i)
|
||||
|
||||
split_button_layout = QHBoxLayout()
|
||||
split_select_all = QPushButton("全选")
|
||||
split_deselect_all = QPushButton("全不选")
|
||||
split_select_all.clicked.connect(lambda: self._toggle_checkboxes(self.split_checkboxes, True))
|
||||
split_deselect_all.clicked.connect(lambda: self._toggle_checkboxes(self.split_checkboxes, False))
|
||||
split_button_layout.addWidget(split_select_all)
|
||||
split_button_layout.addWidget(split_deselect_all)
|
||||
split_button_layout.addStretch()
|
||||
|
||||
split_layout.addLayout(split_grid)
|
||||
split_layout.addLayout(split_button_layout)
|
||||
split_group.setLayout(split_layout)
|
||||
layout.addWidget(split_group)
|
||||
|
||||
self.ml_page.setLayout(layout)
|
||||
|
||||
def _toggle_checkboxes(self, checkboxes_dict, checked):
|
||||
"""统一设置checkbox状态"""
|
||||
for checkbox in checkboxes_dict.values():
|
||||
checkbox.setChecked(checked)
|
||||
|
||||
def _get_default_work_dir(self):
|
||||
"""获取 work_dir，优先用 panel 自身缓存的，否则尝试从主窗口取"""
|
||||
if hasattr(self, 'work_dir') and self.work_dir:
|
||||
return str(self.work_dir)
|
||||
mw = self.window()
|
||||
if mw and hasattr(mw, 'work_dir') and mw.work_dir:
|
||||
return str(mw.work_dir)
|
||||
return ""
|
||||
|
||||
def browse_output_path(self):
|
||||
"""浏览输出文件路径（保存对话框）"""
|
||||
current = self.output_path.get_path().strip()
|
||||
if current:
|
||||
initial_dir = os.path.dirname(current)
|
||||
initial_file = os.path.basename(current)
|
||||
else:
|
||||
initial_dir = ""
|
||||
initial_file = ""
|
||||
|
||||
if not initial_dir or not os.path.isdir(initial_dir):
|
||||
# 默认定位到 indices 目录
|
||||
work_dir = self._get_default_work_dir()
|
||||
initial_dir = os.path.join(work_dir, "6_water_quality_indices") if work_dir else ""
|
||||
if initial_dir and not os.path.isdir(initial_dir):
|
||||
os.makedirs(initial_dir, exist_ok=True)
|
||||
|
||||
file_path, _ = QFileDialog.getSaveFileName(
|
||||
self, "保存输出文件", os.path.join(initial_dir, initial_file) if initial_file else initial_dir,
|
||||
"CSV Files (*.csv);;All Files (*.*)"
|
||||
)
|
||||
if file_path:
|
||||
self.output_path.set_path(file_path)
|
||||
|
||||
def get_config(self):
|
||||
"""获取配置"""
|
||||
preprocessing_methods = [
|
||||
method for method, checkbox in self.preproc_checkboxes.items()
|
||||
if checkbox.isChecked()
|
||||
]
|
||||
model_names = [
|
||||
model for model, checkbox in self.model_checkboxes.items()
|
||||
if checkbox.isChecked()
|
||||
]
|
||||
split_methods = [
|
||||
method for method, checkbox in self.split_checkboxes.items()
|
||||
if checkbox.isChecked()
|
||||
]
|
||||
|
||||
config = {
|
||||
'feature_start_column': self.feature_start.text(),
|
||||
'preprocessing_methods': preprocessing_methods if preprocessing_methods else ['None'],
|
||||
'model_names': model_names if model_names else ['SVR'],
|
||||
'split_methods': split_methods if split_methods else ['random'],
|
||||
'cv_folds': self.cv_folds.value()
|
||||
}
|
||||
training_csv_path = self.training_csv_file.get_path()
|
||||
if training_csv_path:
|
||||
config['training_csv_path'] = training_csv_path
|
||||
output_path = self.output_path.get_path()
|
||||
if output_path:
|
||||
config['output_path'] = output_path
|
||||
return config
|
||||
|
||||
def set_config(self, config):
|
||||
"""设置配置"""
|
||||
if 'feature_start_column' in config:
|
||||
self.feature_start.setText(str(config['feature_start_column']))
|
||||
if 'cv_folds' in config:
|
||||
self.cv_folds.setValue(config['cv_folds'])
|
||||
if 'preprocessing_methods' in config:
|
||||
methods = config['preprocessing_methods']
|
||||
for method, checkbox in self.preproc_checkboxes.items():
|
||||
checkbox.setChecked(method in methods)
|
||||
if 'model_names' in config:
|
||||
models = config['model_names']
|
||||
for model, checkbox in self.model_checkboxes.items():
|
||||
checkbox.setChecked(model in models)
|
||||
if 'split_methods' in config:
|
||||
methods = config['split_methods']
|
||||
for method, checkbox in self.split_checkboxes.items():
|
||||
checkbox.setChecked(method in methods)
|
||||
if 'training_csv_path' in config:
|
||||
self.training_data_widget.set_path(config['training_csv_path'])
|
||||
if 'formula_names' in config:
|
||||
sel = set(config['formula_names'])
|
||||
for name, item in self.index_checkboxes.items():
|
||||
item.setCheckState(Qt.Checked if name in sel else Qt.Unchecked)
|
||||
self.enable_checkbox.setChecked(config.get('enabled', True))
|
||||
if 'output_mode' in config:
|
||||
btn = self.mode_group.button(config['output_mode'])
|
||||
if btn:
|
||||
btn.setChecked(True)
|
||||
self.training_csv_file.set_path(config['training_csv_path'])
|
||||
if 'output_path' in config:
|
||||
self.output_path.set_path(config['output_path'])
|
||||
|
||||
def update_from_config(self, work_dir=None, pipeline=None):
|
||||
"""从全局配置自动填充训练数据和输出路径
|
||||
|
||||
Args:
|
||||
work_dir: 工作目录路径
|
||||
pipeline: Pipeline 实例（未使用，保留接口兼容性）
|
||||
"""
|
||||
if work_dir:
|
||||
self.work_dir = work_dir
|
||||
main = self.window()
|
||||
if hasattr(main, 'step5_panel'):
|
||||
p5 = main.step5_panel.output_file.get_path()
|
||||
if p5:
|
||||
if not os.path.isabs(p5):
|
||||
p5 = os.path.join(self.work_dir or '', p5)
|
||||
p5 = p5.replace('\\', '/')
|
||||
self.training_data_widget.set_path(p5)
|
||||
elif hasattr(self, 'work_dir') and self.work_dir:
|
||||
pass
|
||||
else:
|
||||
self.work_dir = None
|
||||
|
||||
def _get_work_dir(self) -> Optional[str]:
|
||||
# 1. 尝试从 Step6 界面读取训练数据路径，并确保为绝对路径
|
||||
main_window = self.window()
|
||||
if hasattr(main_window, 'step6_panel'):
|
||||
# 优先直接从 Step6 的输出 widget 读取
|
||||
step5_output = main_window.step6_panel.output_file.get_path()
|
||||
if step5_output:
|
||||
# 若为相对路径，使用 work_dir 合成为绝对路径
|
||||
if not os.path.isabs(step5_output):
|
||||
step5_output = os.path.join(self.work_dir or '', step5_output).replace('\\', '/')
|
||||
self.training_csv_file.set_path(step5_output)
|
||||
elif hasattr(main_window, 'step6_panel') and hasattr(main_window.step6_panel, 'get_config'):
|
||||
# 回退：从 Step6 的 config 字典中查找可能的键名
|
||||
step6_cfg = main_window.step6_panel.get_config()
|
||||
step6_csv = (
|
||||
step6_cfg.get('training_csv_path')
|
||||
or step6_cfg.get('output_file')
|
||||
or step6_cfg.get('csv_path')
|
||||
or step6_cfg.get('output_csv')
|
||||
)
|
||||
if step6_csv:
|
||||
# 若为相对路径，使用 work_dir 合成为绝对路径
|
||||
if not os.path.isabs(step6_csv):
|
||||
step6_csv = os.path.join(self.work_dir or '', step6_csv).replace('\\', '/')
|
||||
self.training_csv_file.set_path(step6_csv)
|
||||
|
||||
# 2. 自动填充输出文件路径（基于工作目录和输入文件名）
|
||||
# 输入是 training_spectra.csv → 输出 {work_dir}/6_water_quality_indices/training_spectra_indices.csv
|
||||
# 输入是 sampling_spectra.csv → 输出 {work_dir}/6_water_quality_indices/sampling_spectra_indices.csv
|
||||
if self.work_dir:
|
||||
return self.work_dir
|
||||
main = self.window()
|
||||
if hasattr(main, 'work_dir') and main.work_dir:
|
||||
return main.work_dir
|
||||
return None
|
||||
|
||||
def _get_coord_cols(self, df: pd.DataFrame) -> Tuple[str, str]:
|
||||
coord_candidates = ['lon', 'lng', 'longitude', '经度', 'x', 'lon_utm', 'utm_x', 'pixel_x']
|
||||
lat_candidates = ['lat', 'latitude', '纬度', 'y', 'lat_utm', 'utm_y', 'pixel_y']
|
||||
|
||||
x_col, y_col = None, None
|
||||
for col in df.columns:
|
||||
cl = col.lower()
|
||||
if x_col is None and any(c in cl for c in coord_candidates):
|
||||
x_col = col
|
||||
if y_col is None and any(c in cl for c in lat_candidates):
|
||||
y_col = col
|
||||
|
||||
if x_col is None and len(df.columns) >= 2:
|
||||
x_col = df.columns[0]
|
||||
if y_col is None and len(df.columns) >= 2:
|
||||
y_col = df.columns[1]
|
||||
|
||||
return x_col or 'x_coord', y_col or 'y_coord'
|
||||
indices_dir = os.path.join(self.work_dir, "6_water_quality_indices")
|
||||
os.makedirs(indices_dir, exist_ok=True)
|
||||
training_csv = self.training_csv_file.get_path()
|
||||
if training_csv:
|
||||
basename = os.path.splitext(os.path.basename(training_csv))[0]
|
||||
output_file = f"{basename}_indices.csv"
|
||||
else:
|
||||
output_file = "water_quality_indices.csv"
|
||||
output_path = os.path.join(indices_dir, output_file).replace('\\', '/')
|
||||
self.output_path.set_path(output_path)
|
||||
else:
|
||||
self.output_path.set_path("")
|
||||
|
||||
def run_step(self):
|
||||
config = self.get_config()
|
||||
|
||||
if not config['enabled']:
|
||||
QMessageBox.information(self, "提示", "已禁用计算流程（启用计算流程未勾选）")
|
||||
"""独立运行步骤7"""
|
||||
training_csv_path = self.training_csv_file.get_path()
|
||||
if not training_csv_path:
|
||||
QMessageBox.warning(self, "输入错误", "请选择训练数据CSV文件！")
|
||||
return
|
||||
|
||||
training_path = config['training_csv_path']
|
||||
if not training_path or not os.path.exists(training_path):
|
||||
QMessageBox.warning(self, "提示", "请先选择输入特征提取CSV文件")
|
||||
return
|
||||
main_window = self.window()
|
||||
if hasattr(main_window, 'run_single_step'):
|
||||
config = {'step7': self.get_config()}
|
||||
main_window.run_single_step('step7', config)
|
||||
|
||||
formula_names = config['formula_names']
|
||||
if not formula_names:
|
||||
QMessageBox.warning(self, "提示", "请至少勾选一个公式")
|
||||
return
|
||||
|
||||
output_mode = config['output_mode']
|
||||
|
||||
try:
|
||||
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)
|
||||
|
||||
# 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
|
||||
|
||||
if output_mode in (0, 1):
|
||||
track_a_dir = os.path.join(work_dir, "6_water_quality_indices") if work_dir else "6_water_quality_indices"
|
||||
os.makedirs(track_a_dir, exist_ok=True)
|
||||
track_a_path = os.path.join(track_a_dir, "training_spectra_indices.csv")
|
||||
|
||||
if output_mode in (0, 2):
|
||||
track_b_dir = os.path.join(work_dir, "11_12_13_predictions", "Traditional_Indices") if work_dir else "11_12_13_predictions/Traditional_Indices"
|
||||
os.makedirs(track_b_dir, exist_ok=True)
|
||||
|
||||
saved = []
|
||||
if output_mode in (0, 1):
|
||||
output_df.to_csv(track_a_path, index=False, float_format='%.6f')
|
||||
saved.append(f"宽表: {track_a_path}")
|
||||
|
||||
if output_mode in (0, 2):
|
||||
coord_x = spec_df[x_col].values if x_col in spec_df.columns else np.arange(len(spec_df))
|
||||
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 output_df.columns:
|
||||
continue
|
||||
single_df = pd.DataFrame({
|
||||
'x_coord': coord_x,
|
||||
'y_coord': coord_y,
|
||||
'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")
|
||||
single_df.to_csv(out_path, index=False, float_format='%.6f')
|
||||
saved.append(f"单文件目录: {track_b_dir}")
|
||||
|
||||
QMessageBox.information(
|
||||
self, "计算完成",
|
||||
f"已保存 {len(saved)} 个输出目标:\n" + "\n".join(saved)
|
||||
)
|
||||
|
||||
except ImportError as 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()}")
|
||||
def get_training_params(self):
|
||||
"""获取模型训练参数"""
|
||||
return {
|
||||
'pipeline_type': 'machine_learning',
|
||||
'feature_start': float(self.feature_start.text()),
|
||||
'cv_folds': self.cv_folds.value(),
|
||||
'preprocess_methods': [method for method, cb in self.preproc_checkboxes.items() if cb.isChecked()],
|
||||
'model_types': [model for model, cb in self.model_checkboxes.items() if cb.isChecked()],
|
||||
'split_methods': [method for method, cb in self.split_checkboxes.items() if cb.isChecked()]
|
||||
}
|
||||
|
||||
@ -1,7 +1,7 @@
|
||||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
Step8 面板 - 水色指数反演（直接处理去耀斑 BSQ 影像）
|
||||
Step9 面板 - 水色指数反演（直接处理去耀斑 BSQ 影像）
|
||||
|
||||
将 waterindex.csv 中的公式直接应用于去耀斑高光谱影像，
|
||||
输出各水质参数指数的 GeoTIFF 栅格图像。
|
||||
@ -98,8 +98,8 @@ class WaterIndexWorker(QThread):
|
||||
self.progress.emit(msg, pct)
|
||||
|
||||
|
||||
class Step8WaterIndexPanel(QWidget):
|
||||
"""步骤8：水色指数反演（直接处理 BSQ 影像）"""
|
||||
class Step9WaterColorPanel(QWidget):
|
||||
"""步骤9：水色指数反演（直接处理 BSQ 影像）"""
|
||||
|
||||
def __init__(self, parent=None):
|
||||
super().__init__(parent)
|
||||
@ -115,7 +115,7 @@ class Step8WaterIndexPanel(QWidget):
|
||||
layout = QVBoxLayout()
|
||||
|
||||
# ---- 标题 ----
|
||||
title = QLabel("步骤8：水色指数反演（高光谱影像直接处理）")
|
||||
title = QLabel("步骤9：水色指数反演（高光谱影像直接处理）")
|
||||
title.setFont(QFont("Arial", 12, QFont.Bold))
|
||||
layout.addWidget(title)
|
||||
|
||||
|
||||
@ -1,7 +1,7 @@
|
||||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
Step9 面板 - 浓度反演（基于 QAA 物理反演的二次反演）
|
||||
Step10 面板 - 浓度反演（基于 QAA 物理反演的二次反演）
|
||||
"""
|
||||
|
||||
import os
|
||||
@ -18,8 +18,8 @@ from src.gui.components.custom_widgets import FileSelectWidget
|
||||
from src.gui.styles import ModernStylesheet
|
||||
|
||||
|
||||
class Step9ConcentrationPanel(QWidget):
|
||||
"""步骤9：浓度反演（物理模型二次反演）"""
|
||||
class Step10ConcentrationPanel(QWidget):
|
||||
"""步骤10：浓度反演（物理模型二次反演）"""
|
||||
def __init__(self, parent=None):
|
||||
super().__init__(parent)
|
||||
self.init_ui()
|
||||
@ -27,7 +27,7 @@ class Step9ConcentrationPanel(QWidget):
|
||||
def init_ui(self):
|
||||
layout = QVBoxLayout()
|
||||
|
||||
title = QLabel("步骤9：浓度反演（物理模型二次反演）")
|
||||
title = QLabel("步骤10：浓度反演（物理模型二次反演）")
|
||||
title.setFont(QFont("Arial", 12, QFont.Bold))
|
||||
layout.addWidget(title)
|
||||
|
||||
|
||||
@ -1,400 +1,424 @@
|
||||
#!/usr/bin/env python
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
Step9 面板 - 自定义回归分析
|
||||
Step9 面板 - 机器学习建模
|
||||
"""
|
||||
|
||||
import os
|
||||
from typing import Dict
|
||||
|
||||
import sys
|
||||
import pandas as pd
|
||||
import numpy as np
|
||||
from pathlib import Path
|
||||
from typing import Dict, List, Optional, Tuple
|
||||
|
||||
from PyQt5.QtWidgets import (
|
||||
QWidget, QVBoxLayout, QGroupBox, QFormLayout, QGridLayout,
|
||||
QHBoxLayout, QLabel, QLineEdit, QCheckBox, QPushButton,
|
||||
QScrollArea, QMessageBox,
|
||||
QWidget, QVBoxLayout, QGroupBox, QGridLayout,
|
||||
QHBoxLayout, QLabel, QCheckBox, QPushButton, QMessageBox,
|
||||
QScrollArea, QListWidget, QListWidgetItem, QAbstractItemView,
|
||||
QRadioButton, QButtonGroup
|
||||
)
|
||||
from PyQt5.QtCore import Qt
|
||||
from PyQt5.QtGui import QColor, QBrush, QFont
|
||||
|
||||
from src.gui.components.custom_widgets import FileSelectWidget
|
||||
from src.gui.styles import ModernStylesheet
|
||||
|
||||
|
||||
def get_resource_path(relative_path: str) -> str:
|
||||
"""适配开发与 PyInstaller 环境的路径获取逻辑。"""
|
||||
if hasattr(sys, '_MEIPASS'):
|
||||
internal = os.path.join(sys._MEIPASS, '_internal', relative_path)
|
||||
if os.path.exists(internal):
|
||||
return internal
|
||||
return os.path.join(sys._MEIPASS, relative_path)
|
||||
|
||||
exe_dir = os.path.dirname(sys.executable)
|
||||
internal = os.path.join(exe_dir, '_internal', relative_path)
|
||||
if os.path.exists(internal):
|
||||
return internal
|
||||
|
||||
base_dir = Path(__file__).resolve().parent.parent / "model"
|
||||
return str(base_dir / os.path.basename(relative_path))
|
||||
|
||||
|
||||
class Step9Panel(QWidget):
|
||||
"""步骤9：自定义回归分析"""
|
||||
"""步骤9：机器学习建模"""
|
||||
COLOR_RATIO = QColor(255, 255, 255)
|
||||
COLOR_CONCENTRATION = QColor(220, 240, 255)
|
||||
COLOR_HEADER = QColor(245, 245, 245)
|
||||
|
||||
def __init__(self, parent=None):
|
||||
super().__init__(parent)
|
||||
self.x_column_checkboxes: Dict[str, QCheckBox] = {}
|
||||
self.y_column_checkboxes: Dict[str, QCheckBox] = {}
|
||||
self.method_checkboxes: Dict[str, QCheckBox] = {}
|
||||
self.csv_columns = []
|
||||
self.index_checkboxes: Dict[str, QListWidgetItem] = {}
|
||||
self.work_dir: Optional[str] = None
|
||||
self.builtin_formula_path = get_resource_path("waterindex.csv")
|
||||
self._formula_type_map: Dict[str, str] = {}
|
||||
self._formula_color_map: Dict[str, QColor] = {}
|
||||
self._formula_coef_map: Dict[str, List[float]] = {}
|
||||
|
||||
self.init_ui()
|
||||
self._auto_load_formulas()
|
||||
|
||||
def init_ui(self):
|
||||
layout = QVBoxLayout()
|
||||
main_layout = QVBoxLayout()
|
||||
main_layout.setContentsMargins(20, 20, 20, 20)
|
||||
main_layout.setSpacing(10)
|
||||
|
||||
hint = QLabel("指定自变量与因变量列，批量尝试不同回归方法")
|
||||
hint.setStyleSheet("color: #666; font-size: 11px;")
|
||||
layout.addWidget(hint)
|
||||
# 1. 公式配置源 (只读)
|
||||
path_group = QGroupBox("公式配置源 (内置)")
|
||||
path_layout = QVBoxLayout()
|
||||
self.formula_csv_widget = FileSelectWidget("内置CSV路径:", "CSV Files (*.csv)")
|
||||
self.formula_csv_widget.set_path(self.builtin_formula_path)
|
||||
self.formula_csv_widget.set_read_only(True)
|
||||
self.formula_csv_widget.line_edit.setStyleSheet("background-color: #f0f0f0; color: #666;")
|
||||
path_layout.addWidget(self.formula_csv_widget)
|
||||
path_group.setLayout(path_layout)
|
||||
main_layout.addWidget(path_group)
|
||||
|
||||
# CSV文件选择
|
||||
csv_group = QGroupBox("数据文件")
|
||||
csv_layout = QVBoxLayout()
|
||||
# 2. 训练数据输入
|
||||
input_group = QGroupBox("输入样本数据")
|
||||
input_layout = QVBoxLayout()
|
||||
self.training_data_widget = FileSelectWidget("特征提取CSV:", "CSV Files (*.csv)")
|
||||
input_layout.addWidget(self.training_data_widget)
|
||||
input_group.setLayout(input_layout)
|
||||
main_layout.addWidget(input_group)
|
||||
|
||||
self.csv_file = FileSelectWidget(
|
||||
"输入CSV文件:",
|
||||
"CSV Files (*.csv);;All Files (*.*)"
|
||||
)
|
||||
self.csv_file.line_edit.textChanged.connect(self.on_csv_file_changed)
|
||||
csv_layout.addWidget(self.csv_file)
|
||||
# 3. 公式选择区 (分组 ListWidget)
|
||||
self.formula_group = QGroupBox("待计算水质指数勾选")
|
||||
formula_outer_layout = QVBoxLayout()
|
||||
|
||||
self.refresh_btn = QPushButton("刷新列信息")
|
||||
self.refresh_btn.clicked.connect(self.refresh_csv_columns)
|
||||
csv_layout.addWidget(self.refresh_btn)
|
||||
btn_layout = QHBoxLayout()
|
||||
self.select_all_btn = QPushButton("全选")
|
||||
self.deselect_all_btn = QPushButton("清空")
|
||||
self.select_ratio_btn = QPushButton("仅选比值型")
|
||||
self.select_conc_btn = QPushButton("仅选浓度型")
|
||||
self.select_all_btn.clicked.connect(self.select_all_formulas)
|
||||
self.deselect_all_btn.clicked.connect(self.deselect_all_formulas)
|
||||
self.select_ratio_btn.clicked.connect(self._select_ratio_only)
|
||||
self.select_conc_btn.clicked.connect(self._select_conc_only)
|
||||
btn_layout.addWidget(self.select_all_btn)
|
||||
btn_layout.addWidget(self.deselect_all_btn)
|
||||
btn_layout.addWidget(self.select_ratio_btn)
|
||||
btn_layout.addWidget(self.select_conc_btn)
|
||||
btn_layout.addStretch()
|
||||
|
||||
csv_group.setLayout(csv_layout)
|
||||
layout.addWidget(csv_group)
|
||||
self.refresh_button = QPushButton("重新加载")
|
||||
self.refresh_button.clicked.connect(lambda: self.refresh_formulas(silent=False))
|
||||
btn_layout.addWidget(self.refresh_button)
|
||||
|
||||
# 自变量选择
|
||||
x_group = QGroupBox("自变量列选择 (可多选)")
|
||||
x_layout = QVBoxLayout()
|
||||
formula_outer_layout.addLayout(btn_layout)
|
||||
|
||||
x_scroll = QScrollArea()
|
||||
x_scroll.setWidgetResizable(True)
|
||||
x_scroll.setMinimumHeight(250)
|
||||
x_scroll.setMaximumHeight(350)
|
||||
scroll = QScrollArea()
|
||||
scroll.setWidgetResizable(True)
|
||||
scroll.setMinimumHeight(280)
|
||||
self.scroll_content = QWidget()
|
||||
self.formula_layout = QVBoxLayout(self.scroll_content)
|
||||
self.formula_layout.setContentsMargins(4, 4, 4, 4)
|
||||
self.formula_layout.setSpacing(2)
|
||||
self.formula_layout.setAlignment(Qt.AlignTop)
|
||||
|
||||
x_widget = QWidget()
|
||||
self.x_columns_layout = QGridLayout()
|
||||
x_widget.setLayout(self.x_columns_layout)
|
||||
self.formula_list = QListWidget()
|
||||
self.formula_list.setSelectionMode(QAbstractItemView.MultiSelection)
|
||||
self.formula_list.itemChanged.connect(self._on_item_changed)
|
||||
self.formula_layout.addWidget(self.formula_list)
|
||||
|
||||
x_scroll.setWidget(x_widget)
|
||||
x_layout.addWidget(x_scroll)
|
||||
scroll.setWidget(self.scroll_content)
|
||||
formula_outer_layout.addWidget(scroll)
|
||||
|
||||
x_btn_layout = QHBoxLayout()
|
||||
self.x_select_all = QPushButton("全选")
|
||||
self.x_deselect_all = QPushButton("全不选")
|
||||
self.x_select_all.clicked.connect(lambda: self.toggle_checkboxes(self.x_column_checkboxes, True))
|
||||
self.x_deselect_all.clicked.connect(lambda: self.toggle_checkboxes(self.x_column_checkboxes, False))
|
||||
x_btn_layout.addWidget(self.x_select_all)
|
||||
x_btn_layout.addWidget(self.x_deselect_all)
|
||||
x_btn_layout.addStretch()
|
||||
x_layout.addLayout(x_btn_layout)
|
||||
self.formula_group.setLayout(formula_outer_layout)
|
||||
main_layout.addWidget(self.formula_group)
|
||||
|
||||
x_group.setLayout(x_layout)
|
||||
layout.addWidget(x_group)
|
||||
# 4. 输出选项
|
||||
output_group = QGroupBox("输出模式")
|
||||
output_layout = QVBoxLayout()
|
||||
|
||||
# 因变量选择
|
||||
y_group = QGroupBox("因变量列选择 (可多选)")
|
||||
y_layout = QVBoxLayout()
|
||||
mode_layout = QHBoxLayout()
|
||||
self.mode_group = QButtonGroup()
|
||||
self.radio_both = QRadioButton("两者皆出")
|
||||
self.radio_wide = QRadioButton("仅宽表")
|
||||
self.radio_single = QRadioButton("仅单文件")
|
||||
self.mode_group.addButton(self.radio_both, 0)
|
||||
self.mode_group.addButton(self.radio_wide, 1)
|
||||
self.mode_group.addButton(self.radio_single, 2)
|
||||
self.radio_both.setChecked(True)
|
||||
mode_layout.addWidget(self.radio_both)
|
||||
mode_layout.addWidget(self.radio_wide)
|
||||
mode_layout.addWidget(self.radio_single)
|
||||
mode_layout.addStretch()
|
||||
output_layout.addLayout(mode_layout)
|
||||
|
||||
y_scroll = QScrollArea()
|
||||
y_scroll.setWidgetResizable(True)
|
||||
y_scroll.setMinimumHeight(200)
|
||||
y_scroll.setMaximumHeight(300)
|
||||
|
||||
y_widget = QWidget()
|
||||
self.y_columns_layout = QGridLayout()
|
||||
y_widget.setLayout(self.y_columns_layout)
|
||||
|
||||
y_scroll.setWidget(y_widget)
|
||||
y_layout.addWidget(y_scroll)
|
||||
|
||||
y_btn_layout = QHBoxLayout()
|
||||
self.y_select_all = QPushButton("全选")
|
||||
self.y_deselect_all = QPushButton("全不选")
|
||||
self.y_select_all.clicked.connect(lambda: self.toggle_checkboxes(self.y_column_checkboxes, True))
|
||||
self.y_deselect_all.clicked.connect(lambda: self.toggle_checkboxes(self.y_column_checkboxes, False))
|
||||
y_btn_layout.addWidget(self.y_select_all)
|
||||
y_btn_layout.addWidget(self.y_deselect_all)
|
||||
y_btn_layout.addStretch()
|
||||
y_layout.addLayout(y_btn_layout)
|
||||
|
||||
y_group.setLayout(y_layout)
|
||||
layout.addWidget(y_group)
|
||||
|
||||
# 回归方法选择
|
||||
method_group = QGroupBox("回归方法选择 (可多选)")
|
||||
method_layout = QVBoxLayout()
|
||||
|
||||
method_grid = QGridLayout()
|
||||
regression_methods = [
|
||||
'linear', 'exponential', 'power', 'logarithmic',
|
||||
'polynomial', 'hyperbolic', 'sigmoidal'
|
||||
]
|
||||
|
||||
for i, method in enumerate(regression_methods):
|
||||
checkbox = QCheckBox(method)
|
||||
if method in ['linear', 'exponential', 'power', 'logarithmic']:
|
||||
checkbox.setChecked(True)
|
||||
self.method_checkboxes[method] = checkbox
|
||||
method_grid.addWidget(checkbox, i // 3, i % 3)
|
||||
|
||||
method_layout.addLayout(method_grid)
|
||||
|
||||
method_btn_layout = QHBoxLayout()
|
||||
self.method_select_all = QPushButton("全选")
|
||||
self.method_deselect_all = QPushButton("全不选")
|
||||
self.method_select_all.clicked.connect(lambda: self.toggle_checkboxes(self.method_checkboxes, True))
|
||||
self.method_deselect_all.clicked.connect(lambda: self.toggle_checkboxes(self.method_checkboxes, False))
|
||||
method_btn_layout.addWidget(self.method_select_all)
|
||||
method_btn_layout.addWidget(self.method_deselect_all)
|
||||
method_btn_layout.addStretch()
|
||||
method_layout.addLayout(method_btn_layout)
|
||||
|
||||
method_group.setLayout(method_layout)
|
||||
layout.addWidget(method_group)
|
||||
|
||||
# 输出目录
|
||||
output_group = QGroupBox("输出设置")
|
||||
output_layout = QFormLayout()
|
||||
|
||||
self.output_dir = QLineEdit()
|
||||
self.output_dir.setText("") # 路径由 update_from_config 根据 work_dir 自动填充
|
||||
output_layout.addRow("输出目录名:", self.output_dir)
|
||||
self.enable_checkbox = QCheckBox("启用计算流程")
|
||||
self.enable_checkbox.setChecked(True)
|
||||
output_layout.addWidget(self.enable_checkbox)
|
||||
|
||||
output_group.setLayout(output_layout)
|
||||
layout.addWidget(output_group)
|
||||
main_layout.addWidget(output_group)
|
||||
|
||||
# 启用步骤
|
||||
self.enable_checkbox = QCheckBox("启用此步骤")
|
||||
self.enable_checkbox.setChecked(True)
|
||||
layout.addWidget(self.enable_checkbox)
|
||||
|
||||
# 独立运行按钮
|
||||
self.run_button = QPushButton("独立运行此步骤")
|
||||
# 5. 运行按钮
|
||||
self.run_button = QPushButton("立即执行计算")
|
||||
self.run_button.setStyleSheet(ModernStylesheet.get_button_stylesheet('success'))
|
||||
self.run_button.setMinimumHeight(40)
|
||||
self.run_button.clicked.connect(self.run_step)
|
||||
layout.addWidget(self.run_button)
|
||||
main_layout.addWidget(self.run_button)
|
||||
|
||||
layout.addStretch()
|
||||
self.setLayout(layout)
|
||||
self.setLayout(main_layout)
|
||||
|
||||
def toggle_checkboxes(self, checkboxes_dict, checked):
|
||||
"""统一设置checkbox状态"""
|
||||
for checkbox in checkboxes_dict.values():
|
||||
checkbox.setChecked(checked)
|
||||
def _on_item_changed(self, item: QListWidgetItem):
|
||||
if item.checkState() == Qt.Checked:
|
||||
bg_color = self.COLOR_RATIO
|
||||
for name, ref_item in self.index_checkboxes.items():
|
||||
if ref_item is item:
|
||||
bg_color = self._formula_color_map.get(name, self.COLOR_RATIO)
|
||||
break
|
||||
item.setBackground(QBrush(bg_color))
|
||||
else:
|
||||
item.setBackground(QBrush(self.COLOR_RATIO))
|
||||
|
||||
def on_csv_file_changed(self):
|
||||
"""CSV文件改变时自动刷新列信息"""
|
||||
self.refresh_csv_columns()
|
||||
def _auto_load_formulas(self):
|
||||
if os.path.exists(self.builtin_formula_path):
|
||||
self.refresh_formulas(silent=True)
|
||||
else:
|
||||
print(f"DEBUG: 自动加载失败，路径不存在: {self.builtin_formula_path}")
|
||||
|
||||
def refresh_csv_columns(self):
|
||||
"""刷新CSV文件的列信息"""
|
||||
csv_path = self.csv_file.get_path()
|
||||
if not csv_path or not os.path.exists(csv_path):
|
||||
self.csv_columns = []
|
||||
self.update_column_widgets()
|
||||
def refresh_formulas(self, silent=False):
|
||||
path = self.builtin_formula_path
|
||||
if not os.path.exists(path):
|
||||
if not silent:
|
||||
QMessageBox.warning(self, "错误", f"找不到内置公式文件:\n{path}")
|
||||
return
|
||||
|
||||
try:
|
||||
df = pd.read_csv(csv_path, nrows=0)
|
||||
self.csv_columns = list(df.columns)
|
||||
self.update_column_widgets()
|
||||
df = None
|
||||
for enc in ('utf-8', 'gbk', 'utf-8-sig'):
|
||||
try:
|
||||
df = pd.read_csv(path, encoding=enc)
|
||||
if 'Formula_Name' in df.columns:
|
||||
break
|
||||
except Exception:
|
||||
continue
|
||||
|
||||
if df is None or 'Formula_Name' not in df.columns:
|
||||
if not silent:
|
||||
QMessageBox.critical(self, "错误", "CSV缺少 'Formula_Name' 列")
|
||||
return
|
||||
|
||||
self._formula_type_map.clear()
|
||||
self._formula_coef_map.clear()
|
||||
for _, row in df.iterrows():
|
||||
name = str(row['Formula_Name']).strip()
|
||||
if not name:
|
||||
continue
|
||||
ftype = str(row.get('Formula_Type', 'ratio')).strip().lower()
|
||||
self._formula_type_map[name] = ftype
|
||||
|
||||
coef_str = str(row.get('Coefficient', '')).strip()
|
||||
if coef_str:
|
||||
try:
|
||||
coeffs = [float(c.strip()) for c in coef_str.split(',') if c.strip()]
|
||||
self._formula_coef_map[name] = coeffs
|
||||
except Exception:
|
||||
self._formula_coef_map[name] = []
|
||||
else:
|
||||
self._formula_coef_map[name] = []
|
||||
|
||||
self.formula_list.clear()
|
||||
self.index_checkboxes.clear()
|
||||
|
||||
self._formula_color_map.clear()
|
||||
for name, ftype in self._formula_type_map.items():
|
||||
item = QListWidgetItem(name, self.formula_list)
|
||||
item.setCheckState(Qt.Checked)
|
||||
if ftype == 'concentration':
|
||||
bg_color = QColor(220, 240, 255)
|
||||
else:
|
||||
bg_color = self.COLOR_RATIO
|
||||
self._formula_color_map[name] = bg_color
|
||||
item.setBackground(QBrush(bg_color))
|
||||
self.index_checkboxes[name] = item
|
||||
|
||||
self.formula_list.adjustSize()
|
||||
print(f"✅ 加载 {len(self.index_checkboxes)} 个公式")
|
||||
|
||||
except Exception as e:
|
||||
self.csv_columns = []
|
||||
self.update_column_widgets()
|
||||
print(f"读取CSV列信息失败: {e}")
|
||||
if not silent:
|
||||
QMessageBox.critical(self, "加载失败", f"原因: {str(e)}")
|
||||
|
||||
def update_column_widgets(self):
|
||||
"""更新列选择组件"""
|
||||
for checkbox in self.x_column_checkboxes.values():
|
||||
checkbox.setParent(None)
|
||||
self.x_column_checkboxes.clear()
|
||||
def _select_ratio_only(self):
|
||||
for name, item in self.index_checkboxes.items():
|
||||
ftype = self._formula_type_map.get(name, 'ratio')
|
||||
item.setCheckState(Qt.Checked if ftype == 'ratio' else Qt.Unchecked)
|
||||
|
||||
for checkbox in self.y_column_checkboxes.values():
|
||||
checkbox.setParent(None)
|
||||
self.y_column_checkboxes.clear()
|
||||
def _select_conc_only(self):
|
||||
for name, item in self.index_checkboxes.items():
|
||||
ftype = self._formula_type_map.get(name, 'ratio')
|
||||
item.setCheckState(Qt.Checked if ftype == 'concentration' else Qt.Unchecked)
|
||||
|
||||
if not self.csv_columns:
|
||||
return
|
||||
def select_all_formulas(self):
|
||||
for item in self.index_checkboxes.values():
|
||||
item.setCheckState(Qt.Checked)
|
||||
|
||||
for i, col in enumerate(self.csv_columns):
|
||||
checkbox = QCheckBox(col)
|
||||
if any(keyword in col.lower() for keyword in ['index', 'ratio', 'normalized', 'nd', 'b']):
|
||||
checkbox.setChecked(True)
|
||||
self.x_column_checkboxes[col] = checkbox
|
||||
self.x_columns_layout.addWidget(checkbox, i // 3, i % 3)
|
||||
def deselect_all_formulas(self):
|
||||
for item in self.index_checkboxes.values():
|
||||
item.setCheckState(Qt.Unchecked)
|
||||
|
||||
for i, col in enumerate(self.csv_columns):
|
||||
checkbox = QCheckBox(col)
|
||||
if any(keyword in col.lower() for keyword in ['chl', 'tn', 'tp', 'turbidity', 'do', 'ph', 'conductivity']):
|
||||
checkbox.setChecked(True)
|
||||
self.y_column_checkboxes[col] = checkbox
|
||||
self.y_columns_layout.addWidget(checkbox, i // 2, i % 2)
|
||||
|
||||
self.x_columns_layout.update()
|
||||
self.y_columns_layout.update()
|
||||
|
||||
def get_config(self):
|
||||
selected_x_columns = [
|
||||
col for col, checkbox in self.x_column_checkboxes.items()
|
||||
if checkbox.isChecked()
|
||||
def get_config(self) -> Dict:
|
||||
selected = [
|
||||
name for name, item in self.index_checkboxes.items()
|
||||
if item.checkState() == Qt.Checked
|
||||
]
|
||||
selected_y_columns = [
|
||||
col for col, checkbox in self.y_column_checkboxes.items()
|
||||
if checkbox.isChecked()
|
||||
]
|
||||
selected_methods = [
|
||||
method for method, checkbox in self.method_checkboxes.items()
|
||||
if checkbox.isChecked()
|
||||
]
|
||||
if not selected_methods:
|
||||
selected_methods = 'all'
|
||||
|
||||
formula_coefficients = {
|
||||
name: self._formula_coef_map.get(name, [])
|
||||
for name in selected
|
||||
}
|
||||
return {
|
||||
'csv_path': self.csv_file.get_path() or None,
|
||||
'x_columns': selected_x_columns,
|
||||
'y_columns': selected_y_columns,
|
||||
'methods': selected_methods,
|
||||
'output_dir': self.output_dir.text().strip() or None,
|
||||
'enabled': self.enable_checkbox.isChecked()
|
||||
'training_csv_path': self.training_data_widget.get_path(),
|
||||
'formula_csv_file': self.builtin_formula_path,
|
||||
'formula_names': selected,
|
||||
'formula_coefficients': formula_coefficients,
|
||||
'enabled': self.enable_checkbox.isChecked(),
|
||||
'output_mode': self.mode_group.checkedId(),
|
||||
}
|
||||
|
||||
def set_config(self, config):
|
||||
if 'csv_path' in config:
|
||||
self.csv_file.set_path(config['csv_path'])
|
||||
self.refresh_csv_columns()
|
||||
|
||||
if 'x_columns' in config:
|
||||
selected_x = set(config['x_columns']) if isinstance(config['x_columns'], list) else set()
|
||||
for col, checkbox in self.x_column_checkboxes.items():
|
||||
checkbox.setChecked(col in selected_x)
|
||||
|
||||
if 'y_columns' in config:
|
||||
selected_y = set(config['y_columns']) if isinstance(config['y_columns'], list) else set()
|
||||
for col, checkbox in self.y_column_checkboxes.items():
|
||||
checkbox.setChecked(col in selected_y)
|
||||
|
||||
if 'methods' in config:
|
||||
methods = config['methods']
|
||||
if isinstance(methods, list):
|
||||
selected_methods = set(methods)
|
||||
elif methods == 'all':
|
||||
selected_methods = set(self.method_checkboxes.keys())
|
||||
else:
|
||||
selected_methods = set()
|
||||
for method, checkbox in self.method_checkboxes.items():
|
||||
checkbox.setChecked(method in selected_methods)
|
||||
|
||||
if 'output_dir' in config:
|
||||
self.output_dir.setText(config['output_dir'] or "9_Custom_Regression_Modeling")
|
||||
if 'enabled' in config:
|
||||
self.enable_checkbox.setChecked(config['enabled'])
|
||||
def set_config(self, config: Dict):
|
||||
if 'training_csv_path' in config:
|
||||
self.training_data_widget.set_path(config['training_csv_path'])
|
||||
if 'formula_names' in config:
|
||||
sel = set(config['formula_names'])
|
||||
for name, item in self.index_checkboxes.items():
|
||||
item.setCheckState(Qt.Checked if name in sel else Qt.Unchecked)
|
||||
self.enable_checkbox.setChecked(config.get('enabled', True))
|
||||
if 'output_mode' in config:
|
||||
btn = self.mode_group.button(config['output_mode'])
|
||||
if btn:
|
||||
btn.setChecked(True)
|
||||
|
||||
def update_from_config(self, work_dir=None, pipeline=None):
|
||||
"""从全局配置自动填充训练数据和输出路径
|
||||
if work_dir:
|
||||
self.work_dir = work_dir
|
||||
main = self.window()
|
||||
if hasattr(main, 'step5_panel'):
|
||||
p5 = main.step5_panel.output_file.get_path()
|
||||
if p5:
|
||||
if not os.path.isabs(p5):
|
||||
p5 = os.path.join(self.work_dir or '', p5)
|
||||
p5 = p5.replace('\\', '/')
|
||||
self.training_data_widget.set_path(p5)
|
||||
|
||||
Args:
|
||||
work_dir: 工作目录路径
|
||||
pipeline: Pipeline 实例（未使用，保留接口兼容性）
|
||||
"""
|
||||
try:
|
||||
import traceback
|
||||
def _get_work_dir(self) -> Optional[str]:
|
||||
if self.work_dir:
|
||||
return self.work_dir
|
||||
main = self.window()
|
||||
if hasattr(main, 'work_dir') and main.work_dir:
|
||||
return main.work_dir
|
||||
return None
|
||||
|
||||
if work_dir:
|
||||
self.work_dir = work_dir
|
||||
elif hasattr(self, 'work_dir') and self.work_dir:
|
||||
pass
|
||||
else:
|
||||
self.work_dir = None
|
||||
def _get_coord_cols(self, df: pd.DataFrame) -> Tuple[str, str]:
|
||||
coord_candidates = ['lon', 'lng', 'longitude', '经度', 'x', 'lon_utm', 'utm_x', 'pixel_x']
|
||||
lat_candidates = ['lat', 'latitude', '纬度', 'y', 'lat_utc', 'utm_y', 'pixel_y']
|
||||
|
||||
# 1. 尝试从 Step8 界面读取训练光谱 CSV 路径
|
||||
main_window = self.window()
|
||||
if main_window and hasattr(main_window, 'step8_panel'):
|
||||
step8_widget = main_window.step8_panel.training_data_widget
|
||||
step8_output_path = ""
|
||||
if hasattr(step8_widget, 'get_path'):
|
||||
step8_output_path = step8_widget.get_path() or ""
|
||||
x_col, y_col = None, None
|
||||
for col in df.columns:
|
||||
cl = col.lower()
|
||||
if x_col is None and any(c in cl for c in coord_candidates):
|
||||
x_col = col
|
||||
if y_col is None and any(c in cl for c in lat_candidates):
|
||||
y_col = col
|
||||
|
||||
if step8_output_path:
|
||||
if not os.path.isabs(step8_output_path):
|
||||
step8_output_path = os.path.join(self.work_dir or '', step8_output_path).replace('\\', '/')
|
||||
existing = self.csv_file.get_path()
|
||||
if not existing or not existing.strip():
|
||||
self.csv_file.set_path(step8_output_path)
|
||||
if x_col is None and len(df.columns) >= 2:
|
||||
x_col = df.columns[0]
|
||||
if y_col is None and len(df.columns) >= 2:
|
||||
y_col = df.columns[1]
|
||||
|
||||
# 1.2 尝试从 pipeline 读取 Step 8 宽表 indices_path（优先级最高）
|
||||
if pipeline and hasattr(pipeline, 'indices_path') and pipeline.indices_path:
|
||||
step8_indices_path = pipeline.indices_path
|
||||
if not os.path.isabs(step8_indices_path):
|
||||
step8_indices_path = os.path.join(self.work_dir or '', step8_indices_path).replace('\\', '/')
|
||||
current_path = self.csv_file.get_path()
|
||||
if not current_path or not current_path.strip():
|
||||
self.csv_file.set_path(step8_indices_path)
|
||||
print(f"✅ 从pipeline.indices_path回填Step8产出: {step8_indices_path}")
|
||||
|
||||
# 1.5 自动探测并回填 Step 8 双轨输出的 Traditional_Indices 目录
|
||||
if self.work_dir:
|
||||
trad_indices_dir = os.path.join(
|
||||
self.work_dir, "11_12_13_predictions", "Traditional_Indices"
|
||||
)
|
||||
if os.path.isdir(trad_indices_dir):
|
||||
csv_files = [
|
||||
f for f in os.listdir(trad_indices_dir)
|
||||
if f.lower().endswith('.csv')
|
||||
]
|
||||
if csv_files:
|
||||
csv_files.sort()
|
||||
first_csv = os.path.join(trad_indices_dir, csv_files[0])
|
||||
existing = self.csv_file.get_path()
|
||||
if not existing or not existing.strip():
|
||||
self.csv_file.set_path(first_csv)
|
||||
self.refresh_csv_columns()
|
||||
print(f"✅ 自动探测到 Traditional_Indices 目录，加载首个CSV: {csv_files[0]}")
|
||||
|
||||
# 2. 自动填充输出目录（9_Custom_Regression_Modeling）
|
||||
if self.work_dir:
|
||||
output_dir = os.path.join(self.work_dir, "9_Custom_Regression_Modeling")
|
||||
os.makedirs(output_dir, exist_ok=True)
|
||||
existing_out = self.output_dir.text().strip()
|
||||
if not existing_out:
|
||||
self.output_dir.setText(output_dir)
|
||||
except Exception as e:
|
||||
import traceback
|
||||
print(f"【{self.__class__.__name__}】自动填充失败，跳过: {e}")
|
||||
traceback.print_exc()
|
||||
return x_col or 'x_coord', y_col or 'y_coord'
|
||||
|
||||
def run_step(self):
|
||||
"""独立运行步骤9"""
|
||||
csv_path = self.csv_file.get_path()
|
||||
|
||||
if not csv_path:
|
||||
QMessageBox.warning(self, "输入验证失败", "请选择输入CSV文件")
|
||||
return
|
||||
if not os.path.exists(csv_path):
|
||||
QMessageBox.warning(self, "输入验证失败", "输入CSV文件不存在")
|
||||
return
|
||||
|
||||
selected_x_columns = [
|
||||
col for col, checkbox in self.x_column_checkboxes.items()
|
||||
if checkbox.isChecked()
|
||||
]
|
||||
if not selected_x_columns:
|
||||
QMessageBox.warning(self, "输入验证失败", "请至少选择一个自变量列")
|
||||
return
|
||||
|
||||
selected_y_columns = [
|
||||
col for col, checkbox in self.y_column_checkboxes.items()
|
||||
if checkbox.isChecked()
|
||||
]
|
||||
if not selected_y_columns:
|
||||
QMessageBox.warning(self, "输入验证失败", "请至少选择一个因变量列")
|
||||
return
|
||||
|
||||
selected_methods = [
|
||||
method for method, checkbox in self.method_checkboxes.items()
|
||||
if checkbox.isChecked()
|
||||
]
|
||||
if not selected_methods:
|
||||
QMessageBox.warning(self, "输入验证失败", "请至少选择一种回归方法")
|
||||
return
|
||||
|
||||
config = self.get_config()
|
||||
|
||||
parent = self.parent()
|
||||
while parent and not hasattr(parent, 'run_single_step'):
|
||||
parent = parent.parent()
|
||||
if not config['enabled']:
|
||||
QMessageBox.information(self, "提示", "已禁用计算流程（启用计算流程未勾选）")
|
||||
return
|
||||
|
||||
if parent and hasattr(parent, 'run_single_step'):
|
||||
parent.run_single_step('step9', {'step9': config})
|
||||
else:
|
||||
QMessageBox.critical(self, "错误", "无法找到父级GUI对象")
|
||||
training_path = config['training_csv_path']
|
||||
if not training_path or not os.path.exists(training_path):
|
||||
QMessageBox.warning(self, "提示", "请先选择输入特征提取CSV文件")
|
||||
return
|
||||
|
||||
formula_names = config['formula_names']
|
||||
if not formula_names:
|
||||
QMessageBox.warning(self, "提示", "请至少勾选一个公式")
|
||||
return
|
||||
|
||||
output_mode = config['output_mode']
|
||||
|
||||
try:
|
||||
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)
|
||||
|
||||
formula_csv_path = self.builtin_formula_path
|
||||
if not formula_csv_path or not os.path.exists(formula_csv_path):
|
||||
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()
|
||||
|
||||
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,
|
||||
enabled=True,
|
||||
output_dir=work_dir if work_dir else os.getcwd(),
|
||||
)
|
||||
|
||||
if indices_csv_path and os.path.exists(indices_csv_path):
|
||||
output_df = pd.read_csv(indices_csv_path)
|
||||
else:
|
||||
output_df = spec_df
|
||||
|
||||
track_a_path = None
|
||||
track_b_dir = None
|
||||
|
||||
if output_mode in (0, 1):
|
||||
track_a_dir = os.path.join(work_dir, "9_supervised_modeling") if work_dir else "9_supervised_modeling"
|
||||
os.makedirs(track_a_dir, exist_ok=True)
|
||||
track_a_path = os.path.join(track_a_dir, "training_spectra_indices.csv")
|
||||
|
||||
if output_mode in (0, 2):
|
||||
track_b_dir = os.path.join(work_dir, "11_12_13_predictions", "Traditional_Indices") if work_dir else "11_12_13_predictions/Traditional_Indices"
|
||||
os.makedirs(track_b_dir, exist_ok=True)
|
||||
|
||||
saved = []
|
||||
if output_mode in (0, 1):
|
||||
output_df.to_csv(track_a_path, index=False, float_format='%.6f')
|
||||
saved.append(f"宽表: {track_a_path}")
|
||||
|
||||
if output_mode in (0, 2):
|
||||
coord_x = spec_df[x_col].values if x_col in spec_df.columns else np.arange(len(spec_df))
|
||||
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 output_df.columns:
|
||||
continue
|
||||
single_df = pd.DataFrame({
|
||||
'x_coord': coord_x,
|
||||
'y_coord': coord_y,
|
||||
'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")
|
||||
single_df.to_csv(out_path, index=False, float_format='%.6f')
|
||||
saved.append(f"单文件目录: {track_b_dir}")
|
||||
|
||||
QMessageBox.information(
|
||||
self, "计算完成",
|
||||
f"已保存 {len(saved)} 个输出目标:\n" + "\n".join(saved)
|
||||
)
|
||||
|
||||
except ImportError as 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()}")
|
||||
@ -117,15 +117,17 @@ from src.gui.components.custom_widgets import FileSelectWidget
|
||||
from src.gui.panels.step1_panel import Step1Panel
|
||||
from src.gui.panels.step2_panel import Step2Panel
|
||||
from src.gui.panels.step3_panel import Step3Panel
|
||||
from src.gui.panels.step4_panel import Step4Panel
|
||||
from src.gui.panels.step5_panel import Step5Panel
|
||||
from src.gui.panels.step6_panel import Step6Panel # was step8_panel
|
||||
from src.gui.panels.step7_panel import Step7Panel # was step6_panel
|
||||
from src.gui.panels.step8_waterindex_panel import Step8WaterIndexPanel # 水色指数反演
|
||||
from src.gui.panels.step9_concentration_panel import Step9ConcentrationPanel # 浓度反演
|
||||
from src.gui.panels.step10_panel import Step10Panel # was step7_panel
|
||||
from src.gui.panels.step11_ml_panel import Step11MlPanel # ML prediction (step11_ml)
|
||||
from src.gui.panels.step14_panel import Step14Panel # was step9_panel
|
||||
from src.gui.panels.step4_sampling_panel import Step4SamplingPanel # 采样点布设（原step10→新step4）
|
||||
from src.gui.panels.step5_panel import Step5Panel # 数据清洗（原step4→新step5）
|
||||
from src.gui.panels.step6_panel import Step6Panel # 光谱特征（原step5→新step6）
|
||||
from src.gui.panels.step7_panel import Step7Panel # 水质光谱指数（原step6→新step7）
|
||||
from src.gui.panels.step8_panel import Step8Panel # 水质参数指数（原step7→新step8）
|
||||
from src.gui.panels.step8_waterindex_panel import Step9WaterColorPanel # 水色指数反演
|
||||
from src.gui.panels.step9_concentration_panel import Step10ConcentrationPanel # 浓度反演
|
||||
from src.gui.panels.step9_panel import Step9Panel # 机器学习建模（原step8→新step9）
|
||||
from src.gui.panels.step10_ml_panel import Step10MlPanel # 机器学习预测（原step11_ml→新step10）
|
||||
from src.gui.panels.step11_panel import Step11NonEmpiricalPanel # 非经验模型预测
|
||||
from src.gui.panels.step14_panel import Step14Panel
|
||||
from src.gui.dialogs import BandConfirmDialog, AISettingsDialog
|
||||
from src.gui.panels.visualization_panel import VisualizationPanel
|
||||
from src.gui.panels.report_generation_panel import ReportGenerationPanel
|
||||
@ -1846,23 +1848,22 @@ class WaterQualityGUI(QMainWindow):
|
||||
("step3", "3. 耀斑去除与修复"),
|
||||
],
|
||||
"阶段二：样本数据准备 ": [
|
||||
("step4", "4. 数据标准化处理"),
|
||||
("step5", "5. 光谱特征提取"),
|
||||
("step6", "6. 水质参数指数计算"),
|
||||
("step4", "4. 采样点布设"),
|
||||
("step5", "5. 数据清洗"),
|
||||
("step6", "6. 光谱特征"),
|
||||
("step7", "7. 水质光谱指数计算"),
|
||||
("step8", "8. 水质参数指数计算"),
|
||||
],
|
||||
"阶段三：模型构建与训练": [
|
||||
("step7", "7. 机器学习模型训练"),
|
||||
("step8_non_empirical_modeling", "8. 回归模型训练"),
|
||||
("step9", "9. 自定义回归模型训练"),
|
||||
("step9", "9. 机器学习建模"),
|
||||
("step8_non_empirical_modeling", "8b. 回归模型训练"),
|
||||
],
|
||||
"阶段四：预测与成果输出 ": [
|
||||
("step10", "10. 采样点布设"),
|
||||
("step11_ml", "11. 机器学习预测"),
|
||||
("step11", "12. 回归预测"),
|
||||
("step12", "13. 自定义回归预测"),
|
||||
("step14", "14. 专题图生成"),
|
||||
("step9_viz", "15. 可视化分析"),
|
||||
("step_report", "16. 分析报告生成"),
|
||||
("step10", "10. 机器学习预测"),
|
||||
("step11", "11. 回归预测"),
|
||||
("step14", "12. 专题图生成"),
|
||||
("step9_viz", "13. 可视化分析"),
|
||||
("step_report", "14. 分析报告生成"),
|
||||
]
|
||||
}
|
||||
|
||||
@ -1882,7 +1883,7 @@ class WaterQualityGUI(QMainWindow):
|
||||
self.step_list.addItem(stage_item)
|
||||
|
||||
# 添加该阶段的所有步骤
|
||||
HIDDEN_STEP_IDS = {"step8_non_empirical_modeling", "step9", "step11", "step12"}
|
||||
HIDDEN_STEP_IDS = {"step8_non_empirical_modeling"}
|
||||
for step_id, step_display in steps:
|
||||
if step_id in HIDDEN_STEP_IDS:
|
||||
continue
|
||||
@ -1956,29 +1957,35 @@ class WaterQualityGUI(QMainWindow):
|
||||
self.step3_panel = Step3Panel()
|
||||
self.step_stack.addTab(self.create_scroll_area(self.step3_panel), QIcon(self.get_icon_path("3.png")), "耀斑去除")
|
||||
|
||||
self.step4_panel = Step4Panel()
|
||||
self.step_stack.addTab(self.create_scroll_area(self.step4_panel), QIcon(self.get_icon_path("4.png")), "数据清洗")
|
||||
self.step4_panel = Step4SamplingPanel()
|
||||
self.step_stack.addTab(self.create_scroll_area(self.step4_panel), QIcon(self.get_icon_path("4.png")), "采样点布设")
|
||||
|
||||
self.step5_panel = Step5Panel()
|
||||
self.step_stack.addTab(self.create_scroll_area(self.step5_panel), QIcon(self.get_icon_path("5.png")), "特征构建")
|
||||
self.step_stack.addTab(self.create_scroll_area(self.step5_panel), QIcon(self.get_icon_path("5.png")), "数据清洗")
|
||||
|
||||
self.step6_panel = Step6Panel()
|
||||
self.step_stack.addTab(self.create_scroll_area(self.step6_panel), QIcon(self.get_icon_path("6.png")), "水质光谱指数计算")
|
||||
self.step_stack.addTab(self.create_scroll_area(self.step6_panel), QIcon(self.get_icon_path("6.png")), "光谱特征")
|
||||
|
||||
self.step7_panel = Step7Panel()
|
||||
self.step_stack.addTab(self.create_scroll_area(self.step7_panel), QIcon(self.get_icon_path("7.png")), "监督建模")
|
||||
self.step_stack.addTab(self.create_scroll_area(self.step7_panel), QIcon(self.get_icon_path("7.png")), "水质光谱指数计算")
|
||||
|
||||
self.step8_waterindex_panel = Step8WaterIndexPanel()
|
||||
self.step_stack.addTab(self.create_scroll_area(self.step8_waterindex_panel), QIcon(self.get_icon_path("6.png")), "水色指数反演")
|
||||
self.step8_panel = Step8Panel()
|
||||
self.step_stack.addTab(self.create_scroll_area(self.step8_panel), QIcon(self.get_icon_path("7.png")), "水质参数指数计算")
|
||||
|
||||
self.step9_concentration_panel = Step9ConcentrationPanel()
|
||||
self.step_stack.addTab(self.create_scroll_area(self.step9_concentration_panel), QIcon(self.get_icon_path("6.png")), "浓度反演")
|
||||
self.step9_panel = Step9Panel()
|
||||
self.step_stack.addTab(self.create_scroll_area(self.step9_panel), QIcon(self.get_icon_path("8.png")), "机器学习建模")
|
||||
|
||||
self.step10_panel = Step10Panel()
|
||||
self.step_stack.addTab(self.create_scroll_area(self.step10_panel), QIcon(self.get_icon_path("7.png")), "采样点布设")
|
||||
self.step8_waterindex_panel = Step9WaterColorPanel()
|
||||
self.step_stack.addTab(self.create_scroll_area(self.step8_waterindex_panel), QIcon(self.get_icon_path("8.png")), "水色指数反演")
|
||||
|
||||
self.step11_ml_panel = Step11MlPanel() # ML prediction panel (step11_ml)
|
||||
self.step_stack.addTab(self.create_scroll_area(self.step11_ml_panel), QIcon(self.get_icon_path("8.png")), "监督预测")
|
||||
self.step9_concentration_panel = Step10ConcentrationPanel()
|
||||
self.step_stack.addTab(self.create_scroll_area(self.step9_concentration_panel), QIcon(self.get_icon_path("9.png")), "浓度反演")
|
||||
|
||||
self.step10_ml_panel = Step10MlPanel()
|
||||
self.step_stack.addTab(self.create_scroll_area(self.step10_ml_panel), QIcon(self.get_icon_path("10.png")), "机器学习预测")
|
||||
|
||||
self.step11_non_empirical_panel = Step11NonEmpiricalPanel()
|
||||
self.step_stack.addTab(self.create_scroll_area(self.step11_non_empirical_panel), QIcon(self.get_icon_path("11.png")), "回归预测")
|
||||
|
||||
self.step14_panel = Step14Panel()
|
||||
self.step_stack.addTab(self.create_scroll_area(self.step14_panel), QIcon(self.get_icon_path("10.png")), "专题图生成")
|
||||
@ -2133,12 +2140,12 @@ class WaterQualityGUI(QMainWindow):
|
||||
'step5': 4,
|
||||
'step6': 5,
|
||||
'step7': 6,
|
||||
'step8_non_empirical_modeling': 7,
|
||||
'step8': 7,
|
||||
'step9': 8,
|
||||
'step10': 9,
|
||||
'step11_ml': 10,
|
||||
'step11': 11,
|
||||
'step12': 12,
|
||||
'step8_non_empirical_modeling': 9,
|
||||
'step9_concentration': 10,
|
||||
'step10': 11,
|
||||
'step11': 12,
|
||||
'step14': 13,
|
||||
'step9_viz': 14,
|
||||
'step_report': 15,
|
||||
@ -2164,12 +2171,12 @@ class WaterQualityGUI(QMainWindow):
|
||||
4: 'step5',
|
||||
5: 'step6',
|
||||
6: 'step7',
|
||||
7: 'step8_non_empirical_modeling',
|
||||
7: 'step8',
|
||||
8: 'step9',
|
||||
9: 'step10',
|
||||
10: 'step11_ml',
|
||||
11: 'step11',
|
||||
12: 'step12',
|
||||
9: 'step8_non_empirical_modeling',
|
||||
10: 'step9_concentration',
|
||||
11: 'step10',
|
||||
12: 'step11',
|
||||
13: 'step14',
|
||||
14: 'step9_viz',
|
||||
15: 'step_report',
|
||||
@ -2199,44 +2206,48 @@ class WaterQualityGUI(QMainWindow):
|
||||
elif index == 2:
|
||||
self.step3_panel.update_from_config(work_dir=self.work_dir)
|
||||
|
||||
# Step4 切换时自动填充输出路径
|
||||
# Step4（采样点布设）切换时自动填充输出路径
|
||||
elif index == 3:
|
||||
self.step4_panel.update_from_config(work_dir=self.work_dir)
|
||||
|
||||
# Step5 切换时自动填充数据流转路径
|
||||
# Step5（数据清洗）切换时自动填充数据流转路径
|
||||
elif index == 4:
|
||||
self.step5_panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline)
|
||||
|
||||
# Step6（水质光谱指数）切换时自动填充输出路径
|
||||
# Step6（光谱特征）切换时自动填充输出路径
|
||||
elif index == 5:
|
||||
self.step6_panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline)
|
||||
|
||||
# Step7（监督建模）切换时自动填充训练数据和输出路径
|
||||
# Step7（水质光谱指数计算）切换时自动填充水质参数 CSV
|
||||
elif index == 6:
|
||||
self.step7_panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline)
|
||||
|
||||
# Step8 水色指数反演切换时自动填充光谱数据和输出路径
|
||||
# Step8（水质参数指数计算）切换时自动填充水质参数 CSV
|
||||
elif index == 7:
|
||||
self.step8_panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline)
|
||||
|
||||
# Step9（机器学习建模）切换时自动填充训练数据和输出路径
|
||||
elif index == 8:
|
||||
self.step9_panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline)
|
||||
|
||||
# Step8b（水色指数反演）切换时自动填充光谱数据和输出路径
|
||||
elif index == 9:
|
||||
self.step8_waterindex_panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline)
|
||||
|
||||
# Step9 浓度反演切换时自动填充 QAA 结果和输出路径
|
||||
elif index == 8:
|
||||
# Step10（浓度反演）切换时自动填充 QAA 结果和输出路径
|
||||
elif index == 10:
|
||||
self.step9_concentration_panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline)
|
||||
|
||||
# Step10（采样点布设）切换时自动填充掩膜和输出路径
|
||||
elif index == 9:
|
||||
self.step10_panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline)
|
||||
|
||||
# Step11（机器学习预测）切换时自动填充采样光谱和模型目录
|
||||
elif index == 10:
|
||||
self.step11_ml_panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline)
|
||||
elif index == 11:
|
||||
self.step10_ml_panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline)
|
||||
|
||||
# Step14（专题图生成）切换时自动填充预测结果目录
|
||||
elif index == 11:
|
||||
elif index == 13:
|
||||
self.step14_panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline)
|
||||
|
||||
# 可视化分析面板切换时自动推断图像目录并加载目录树
|
||||
elif index == 12:
|
||||
elif index == 14:
|
||||
self.viz_panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline)
|
||||
|
||||
def apply_stylesheet(self):
|
||||
@ -2285,9 +2296,9 @@ class WaterQualityGUI(QMainWindow):
|
||||
if 'step7' in config:
|
||||
self.step7_panel.set_config(config['step7'])
|
||||
if 'step10' in config:
|
||||
self.step10_panel.set_config(config['step10'])
|
||||
self.step4_panel.set_config(config['step10'])
|
||||
if 'step11_ml' in config:
|
||||
self.step11_ml_panel.set_config(config['step11_ml'])
|
||||
self.step10_ml_panel.set_config(config['step11_ml'])
|
||||
if 'step14' in config:
|
||||
self.step14_panel.set_config(config['step14'])
|
||||
if 'visualization' in config:
|
||||
@ -2334,8 +2345,8 @@ class WaterQualityGUI(QMainWindow):
|
||||
'step5': self.step5_panel.get_config(),
|
||||
'step6': self.step6_panel.get_config(),
|
||||
'step7': self.step7_panel.get_config(),
|
||||
'step10': self.step10_panel.get_config(),
|
||||
'step11_ml': self.step11_ml_panel.get_config(),
|
||||
'step10': self.step4_panel.get_config(),
|
||||
'step11_ml': self.step10_ml_panel.get_config(),
|
||||
'step14': self.step14_panel.get_config(),
|
||||
'visualization': self.viz_panel.get_config(),
|
||||
'report_generation': self.report_panel.get_config(),
|
||||
@ -2389,8 +2400,8 @@ class WaterQualityGUI(QMainWindow):
|
||||
'step5': self.step5_panel,
|
||||
'step6': self.step6_panel,
|
||||
'step7': self.step7_panel,
|
||||
'step10': self.step10_panel,
|
||||
'step11_ml': self.step11_ml_panel,
|
||||
'step10': self.step4_panel,
|
||||
'step11_ml': self.step10_ml_panel,
|
||||
'step14': self.step14_panel,
|
||||
}
|
||||
return panel_map.get(step_id)
|
||||
@ -2591,8 +2602,8 @@ class WaterQualityGUI(QMainWindow):
|
||||
('step5', self.step5_panel),
|
||||
('step6', self.step6_panel),
|
||||
('step7', self.step7_panel),
|
||||
('step10', self.step10_panel),
|
||||
('step11_ml', self.step11_ml_panel),
|
||||
('step10', self.step4_panel),
|
||||
('step11_ml', self.step10_ml_panel),
|
||||
('step14', self.step14_panel)
|
||||
]
|
||||
|
||||
@ -3219,14 +3230,14 @@ class WaterQualityGUI(QMainWindow):
|
||||
def update_ui_for_training_mode(self):
|
||||
"""根据训练数据模式更新UI状态"""
|
||||
# 需要禁用的步骤ID（对应无训练数据模式下需要禁用的步骤）
|
||||
disabled_step_ids = ['step4', 'step5', 'step6', 'step7', 'step8_non_empirical_modeling', 'step9']
|
||||
disabled_step_ids = ['step4', 'step5', 'step6', 'step7', 'step8', 'step8_non_empirical_modeling', 'step9']
|
||||
|
||||
# 更新标签页的启用/禁用状态
|
||||
step_id_to_tab = {
|
||||
'step1': 0, 'step2': 1, 'step3': 2, 'step4': 3,
|
||||
'step5': 4, 'step6': 5, 'step7': 6, 'step8_non_empirical_modeling': 7,
|
||||
'step9': 8, 'step10': 9, 'step11_ml': 10, 'step11': 11,
|
||||
'step12': 12, 'step14': 13, 'step9_viz': 14
|
||||
'step5': 4, 'step6': 5, 'step7': 6, 'step8': 7,
|
||||
'step9': 8, 'step8_non_empirical_modeling': 9, 'step9_concentration': 10,
|
||||
'step10': 11, 'step11': 12, 'step14': 13, 'step9_viz': 14
|
||||
}
|
||||
|
||||
for step_id in disabled_step_ids:
|
||||
|
||||
Reference in New Issue
Block a user