结构修改，后端文件跟前端内容进行适配
This commit is contained in:
@ -5,345 +5,411 @@ Step8 面板 - 机器学习建模
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"""
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import os
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import sys
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import pandas as pd
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import numpy as np
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from pathlib import Path
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from typing import Dict, List, Optional, Tuple
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from PyQt5.QtWidgets import (
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QWidget, QVBoxLayout, QGroupBox, QGridLayout,
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QHBoxLayout, QLabel, QCheckBox, QPushButton, QMessageBox,
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QScrollArea, QListWidget, QListWidgetItem, QAbstractItemView,
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QRadioButton, QButtonGroup
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QWidget, QVBoxLayout, QGroupBox, QFormLayout, QGridLayout,
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QHBoxLayout, QLabel, QLineEdit, QSpinBox, QCheckBox,
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QPushButton, QFileDialog, QMessageBox,
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)
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from PyQt5.QtCore import Qt
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from PyQt5.QtGui import QColor, QBrush, QFont
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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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def get_resource_path(relative_path: str) -> str:
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"""适配开发与 PyInstaller 环境的路径获取逻辑。"""
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if hasattr(sys, '_MEIPASS'):
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internal = os.path.join(sys._MEIPASS, '_internal', relative_path)
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if os.path.exists(internal):
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return internal
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return os.path.join(sys._MEIPASS, relative_path)
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# ============================================================
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# 中文映射表（内部键名 -> 显示文本）
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# ============================================================
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exe_dir = os.path.dirname(sys.executable)
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internal = os.path.join(exe_dir, '_internal', relative_path)
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if os.path.exists(internal):
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return internal
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# 预处理方法：内部键 -> 显示文本
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PREPROC_CHINESE = {
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'None': '无 (None)',
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'MMS': '最小-最大归一化 (MMS)',
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'SS': '标度化 (SS)',
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'SNV': '标准正态变换 (SNV)',
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'MA': '移动平均 (MA)',
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'SG': 'Savitzky-Golay (SG)',
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'MSC': '多元散射校正 (MSC)',
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'D1': '一阶导数 (D1)',
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'D2': '二阶导数 (D2)',
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'DT': '去趋势 (DT)',
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'CT': '中心化 (CT)',
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}
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base_dir = Path(__file__).resolve().parent.parent / "model"
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return str(base_dir / os.path.basename(relative_path))
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# 模型类型：内部键 -> 显示文本
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MODEL_CHINESE = {
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# 线性模型
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'LinearRegression': '多元线性回归 (MLR)',
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'Ridge': '岭回归 (Ridge)',
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'Lasso': '套索回归 (Lasso)',
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'ElasticNet': '弹性网络 (ElasticNet)',
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'PLS': '偏最小二乘 (PLSR)',
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# 树模型
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'DecisionTree': '决策树 (CART)',
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'RF': '随机森林 (RF)',
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'ExtraTrees': '极端随机树 (ET)',
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'XGBoost': '极值梯度提升 (XGBoost)',
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'LightGBM': '轻量梯度提升 (LightGBM)',
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'CatBoost': '类别梯度提升 (CatBoost)',
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# 集成学习
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'GradientBoosting': '梯度提升树 (GBDT)',
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'AdaBoost': '自适应提升 (AdaBoost)',
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# 其他模型
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'SVR': '支持向量回归 (SVR)',
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'KNN': 'K近邻回归 (KNN)',
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'MLP': '多层感知机 (BP神经网络)',
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}
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# 数据划分方法：内部键 -> 显示文本
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SPLIT_CHINESE = {
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'spxy': 'SPXY 算法 (考量X-Y空间)',
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'ks': 'KS 算法 (考量X空间)',
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'random': '随机划分 (Random)',
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}
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class Step8MlTrainPanel(QWidget):
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"""步骤8：机器学习建模"""
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COLOR_RATIO = QColor(255, 255, 255)
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COLOR_CONCENTRATION = QColor(220, 240, 255)
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COLOR_HEADER = QColor(245, 245, 245)
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def __init__(self, parent=None):
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super().__init__(parent)
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self.index_checkboxes: Dict[str, QListWidgetItem] = {}
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self.work_dir: Optional[str] = None
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self.builtin_formula_path = get_resource_path("waterindex.csv")
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self._formula_type_map: Dict[str, str] = {}
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self._formula_color_map: Dict[str, QColor] = {}
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self._formula_coef_map: Dict[str, List[float]] = {}
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self.init_ui()
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self._auto_load_formulas()
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def init_ui(self):
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main_layout = QVBoxLayout()
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main_layout.setContentsMargins(20, 20, 20, 20)
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main_layout.setSpacing(10)
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layout = QVBoxLayout()
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# 1. 公式配置源 (只读)
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path_group = QGroupBox("公式配置源 (内置)")
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path_layout = QVBoxLayout()
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self.formula_csv_widget = FileSelectWidget("内置CSV路径:", "CSV Files (*.csv)")
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self.formula_csv_widget.set_path(self.builtin_formula_path)
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self.formula_csv_widget.set_read_only(True)
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self.formula_csv_widget.line_edit.setStyleSheet("background-color: #f0f0f0; color: #666;")
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path_layout.addWidget(self.formula_csv_widget)
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path_group.setLayout(path_layout)
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main_layout.addWidget(path_group)
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# 标题
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# 2. 训练数据输入
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input_group = QGroupBox("输入样本数据")
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input_layout = QVBoxLayout()
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self.training_data_widget = FileSelectWidget("特征提取CSV:", "CSV Files (*.csv)")
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input_layout.addWidget(self.training_data_widget)
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input_group.setLayout(input_layout)
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main_layout.addWidget(input_group)
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# 3. 公式选择区 (分组 ListWidget)
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self.formula_group = QGroupBox("待计算水质指数勾选")
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formula_outer_layout = QVBoxLayout()
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# 训练数据文件（用于独立运行）
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self.training_csv_file = FileSelectWidget(
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"训练数据:",
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"CSV Files (*.csv);;All Files (*.*)"
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)
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layout.addWidget(self.training_csv_file)
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btn_layout = QHBoxLayout()
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self.select_all_btn = QPushButton("全选")
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self.deselect_all_btn = QPushButton("清空")
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self.select_ratio_btn = QPushButton("仅选比值型")
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self.select_conc_btn = QPushButton("仅选浓度型")
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self.select_all_btn.clicked.connect(self.select_all_formulas)
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self.deselect_all_btn.clicked.connect(self.deselect_all_formulas)
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self.select_ratio_btn.clicked.connect(self._select_ratio_only)
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self.select_conc_btn.clicked.connect(self._select_conc_only)
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btn_layout.addWidget(self.select_all_btn)
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btn_layout.addWidget(self.deselect_all_btn)
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btn_layout.addWidget(self.select_ratio_btn)
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btn_layout.addWidget(self.select_conc_btn)
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btn_layout.addStretch()
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# 机器学习模型页面
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self.ml_page = QWidget()
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self.create_ml_page()
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layout.addWidget(self.ml_page)
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self.refresh_button = QPushButton("重新加载")
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self.refresh_button.clicked.connect(lambda: self.refresh_formulas(silent=False))
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btn_layout.addWidget(self.refresh_button)
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# 输出文件路径
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self.output_path = FileSelectWidget(
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"输出文件:",
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"CSV Files (*.csv);;All Files (*.*)",
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mode="save"
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)
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self.output_path.line_edit.setPlaceholderText("自动生成，或手动指定输出文件路径...")
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self.output_path.browse_btn.clicked.disconnect()
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self.output_path.browse_btn.clicked.connect(self.browse_output_path)
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layout.addWidget(self.output_path)
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formula_outer_layout.addLayout(btn_layout)
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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(False)
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layout.addWidget(self.enable_checkbox)
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scroll = QScrollArea()
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scroll.setWidgetResizable(True)
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scroll.setMinimumHeight(280)
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self.scroll_content = QWidget()
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self.formula_layout = QVBoxLayout(self.scroll_content)
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self.formula_layout.setContentsMargins(4, 4, 4, 4)
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self.formula_layout.setSpacing(2)
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self.formula_layout.setAlignment(Qt.AlignTop)
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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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self.formula_list = QListWidget()
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self.formula_list.setSelectionMode(QAbstractItemView.MultiSelection)
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self.formula_list.itemChanged.connect(self._on_item_changed)
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self.formula_layout.addWidget(self.formula_list)
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layout.addStretch()
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self.setLayout(layout)
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scroll.setWidget(self.scroll_content)
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formula_outer_layout.addWidget(scroll)
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def create_ml_page(self):
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"""创建机器学习模型页面"""
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layout = QVBoxLayout()
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self.formula_group.setLayout(formula_outer_layout)
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main_layout.addWidget(self.formula_group)
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# 参数设置
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params_group = QGroupBox("训练参数")
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params_layout = QFormLayout()
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# 4. 输出选项
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output_group = QGroupBox("输出模式")
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output_layout = QVBoxLayout()
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self.feature_start = QLineEdit()
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self.feature_start.setText("374.285004")
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params_layout.addRow("特征起始列:", self.feature_start)
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mode_layout = QHBoxLayout()
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self.mode_group = QButtonGroup()
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self.radio_both = QRadioButton("两者皆出")
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self.radio_wide = QRadioButton("仅宽表")
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self.radio_single = QRadioButton("仅单文件")
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self.mode_group.addButton(self.radio_both, 0)
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self.mode_group.addButton(self.radio_wide, 1)
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self.mode_group.addButton(self.radio_single, 2)
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self.radio_both.setChecked(True)
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mode_layout.addWidget(self.radio_both)
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mode_layout.addWidget(self.radio_wide)
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mode_layout.addWidget(self.radio_single)
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mode_layout.addStretch()
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output_layout.addLayout(mode_layout)
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self.cv_folds = QSpinBox()
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self.cv_folds.setRange(2, 10)
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self.cv_folds.setValue(3)
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params_layout.addRow("交叉验证折数:", self.cv_folds)
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self.enable_checkbox = QCheckBox("启用计算流程")
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self.enable_checkbox.setChecked(True)
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output_layout.addWidget(self.enable_checkbox)
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params_group.setLayout(params_layout)
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layout.addWidget(params_group)
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output_group.setLayout(output_layout)
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main_layout.addWidget(output_group)
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# 预处理方法 - 多选
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preproc_group = QGroupBox("预处理方法 (可多选)")
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preproc_layout = QVBoxLayout()
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# 5. 运行按钮
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self.run_button = QPushButton("立即执行计算")
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self.run_button.setStyleSheet(ModernStylesheet.get_button_stylesheet('success'))
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self.run_button.setMinimumHeight(40)
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self.run_button.clicked.connect(self.run_step)
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main_layout.addWidget(self.run_button)
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preproc_grid = QGridLayout()
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self.preproc_checkboxes = {}
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preproc_methods = ['None', 'MMS', 'SS', 'SNV', 'MA', 'SG', 'MSC', 'D1', 'D2', 'DT', 'CT']
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self.setLayout(main_layout)
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for i, method in enumerate(preproc_methods):
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checkbox = QCheckBox(PREPROC_CHINESE.get(method, method))
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checkbox.setChecked(False)
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self.preproc_checkboxes[method] = checkbox
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preproc_grid.addWidget(checkbox, i // 4, i % 4)
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def _on_item_changed(self, item: QListWidgetItem):
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if item.checkState() == Qt.Checked:
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bg_color = self.COLOR_RATIO
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for name, ref_item in self.index_checkboxes.items():
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if ref_item is item:
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bg_color = self._formula_color_map.get(name, self.COLOR_RATIO)
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break
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item.setBackground(QBrush(bg_color))
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else:
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item.setBackground(QBrush(self.COLOR_RATIO))
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button_layout = QHBoxLayout()
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select_all_btn = QPushButton("全选")
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deselect_all_btn = QPushButton("全不选")
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select_all_btn.clicked.connect(lambda: self._toggle_checkboxes(self.preproc_checkboxes, True))
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deselect_all_btn.clicked.connect(lambda: self._toggle_checkboxes(self.preproc_checkboxes, False))
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button_layout.addWidget(select_all_btn)
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button_layout.addWidget(deselect_all_btn)
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button_layout.addStretch()
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def _auto_load_formulas(self):
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if os.path.exists(self.builtin_formula_path):
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self.refresh_formulas(silent=True)
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else:
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print(f"DEBUG: 自动加载失败，路径不存在: {self.builtin_formula_path}")
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preproc_layout.addLayout(preproc_grid)
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preproc_layout.addLayout(button_layout)
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preproc_group.setLayout(preproc_layout)
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layout.addWidget(preproc_group)
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def refresh_formulas(self, silent=False):
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path = self.builtin_formula_path
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if not os.path.exists(path):
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if not silent:
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QMessageBox.warning(self, "错误", f"找不到内置公式文件:\n{path}")
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return
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# 模型选择 - 多选
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model_group = QGroupBox("模型类型 (可多选)")
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model_layout = QVBoxLayout()
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try:
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df = None
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for enc in ('utf-8', 'gbk', 'utf-8-sig'):
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try:
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df = pd.read_csv(path, encoding=enc)
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if 'Formula_Name' in df.columns:
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break
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except Exception:
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continue
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model_grid = QGridLayout()
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self.model_checkboxes = {}
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if df is None or 'Formula_Name' not in df.columns:
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if not silent:
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QMessageBox.critical(self, "错误", "CSV缺少 'Formula_Name' 列")
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return
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self._formula_type_map.clear()
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self._formula_coef_map.clear()
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for _, row in df.iterrows():
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name = str(row['Formula_Name']).strip()
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if not name:
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continue
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ftype = str(row.get('Formula_Type', 'ratio')).strip().lower()
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self._formula_type_map[name] = ftype
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coef_str = str(row.get('Coefficient', '')).strip()
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if coef_str:
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try:
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coeffs = [float(c.strip()) for c in coef_str.split(',') if c.strip()]
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self._formula_coef_map[name] = coeffs
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except Exception:
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self._formula_coef_map[name] = []
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else:
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self._formula_coef_map[name] = []
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self.formula_list.clear()
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self.index_checkboxes.clear()
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self._formula_color_map.clear()
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for name, ftype in self._formula_type_map.items():
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item = QListWidgetItem(name, self.formula_list)
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item.setCheckState(Qt.Checked)
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if ftype == 'concentration':
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bg_color = QColor(220, 240, 255)
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else:
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bg_color = self.COLOR_RATIO
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self._formula_color_map[name] = bg_color
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item.setBackground(QBrush(bg_color))
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self.index_checkboxes[name] = item
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self.formula_list.adjustSize()
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print(f"✅ 加载 {len(self.index_checkboxes)} 个公式")
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except Exception as e:
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if not silent:
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QMessageBox.critical(self, "加载失败", f"原因: {str(e)}")
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def _select_ratio_only(self):
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for name, item in self.index_checkboxes.items():
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ftype = self._formula_type_map.get(name, 'ratio')
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item.setCheckState(Qt.Checked if ftype == 'ratio' else Qt.Unchecked)
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def _select_conc_only(self):
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for name, item in self.index_checkboxes.items():
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ftype = self._formula_type_map.get(name, 'ratio')
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item.setCheckState(Qt.Checked if ftype == 'concentration' else Qt.Unchecked)
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def select_all_formulas(self):
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for item in self.index_checkboxes.values():
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item.setCheckState(Qt.Checked)
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def deselect_all_formulas(self):
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for item in self.index_checkboxes.values():
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item.setCheckState(Qt.Unchecked)
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def get_config(self) -> Dict:
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selected = [
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name for name, item in self.index_checkboxes.items()
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if item.checkState() == Qt.Checked
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model_groups = [
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("【线性模型】", ['LinearRegression', 'Ridge', 'Lasso', 'ElasticNet', 'PLS']),
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("【树模型】", ['DecisionTree', 'RF', 'ExtraTrees', 'XGBoost', 'LightGBM', 'CatBoost']),
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("【集成学习】", ['GradientBoosting', 'AdaBoost']),
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("【其他模型】", ['SVR', 'KNN', 'MLP'])
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]
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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 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:
|
||||
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_utc', '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）")
|
||||
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")
|
||||
"""独立运行步骤8"""
|
||||
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
|
||||
|
||||
main_window = self.window()
|
||||
if hasattr(main_window, 'run_single_step'):
|
||||
pipeline_config = {'step8_ml_train': config}
|
||||
main_window.run_single_step('step8_ml_train', pipeline_config)
|
||||
config = {'step8_ml_train': self.get_config()}
|
||||
main_window.run_single_step('step8_ml_train', config)
|
||||
|
||||
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()]
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user