212 lines
8.2 KiB
Python
212 lines
8.2 KiB
Python
#!/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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"""
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import os
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from pathlib import Path
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from PyQt5.QtWidgets import (
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QWidget, QVBoxLayout, QGroupBox, QFormLayout,
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QPushButton, QCheckBox, QComboBox, QLineEdit, QMessageBox,
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QFileDialog,
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)
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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 Step8Panel(QWidget):
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"""步骤8：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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self.init_ui()
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def init_ui(self):
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layout = QVBoxLayout()
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# 采样光谱CSV文件（用于独立运行）
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self.sampling_csv_file = FileSelectWidget(
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"采样光谱CSV:",
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"CSV Files (*.csv);;All Files (*.*)"
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)
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layout.addWidget(self.sampling_csv_file)
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# 模型目录（用于独立运行）
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self.models_dir_file = FileSelectWidget(
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"模型目录:",
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"Directories;;All Files (*.*)"
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)
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self.models_dir_file.label.setText("模型目录:")
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self.models_dir_file.browse_btn.clicked.disconnect()
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self.models_dir_file.browse_btn.clicked.connect(self.browse_models_dir)
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layout.addWidget(self.models_dir_file)
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# 参数设置
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params_group = QGroupBox("预测参数")
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params_layout = QFormLayout()
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self.metric = QComboBox()
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self.metric.addItems(['test_r2', 'test_rmse', 'test_mae'])
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params_layout.addRow("模型选择指标:", self.metric)
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self.prediction_column = QLineEdit()
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self.prediction_column.setText("prediction")
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params_layout.addRow("预测列名:", self.prediction_column)
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params_group.setLayout(params_layout)
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layout.addWidget(params_group)
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# 输出路径
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self.output_file = FileSelectWidget(
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"输出路径:",
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"CSV Files (*.csv);;All Files (*.*)"
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)
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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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def update_from_config(self, work_dir=None, pipeline=None):
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"""从全局配置自动填充采样光谱和模型目录
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Args:
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work_dir: 工作目录路径
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pipeline: Pipeline 实例（未使用，保留接口兼容性）
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"""
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try:
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import traceback
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if work_dir:
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self.work_dir = work_dir
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elif hasattr(self, 'work_dir') and self.work_dir:
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pass
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else:
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self.work_dir = None
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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, 'step7_panel'):
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step7_widget = getattr(main_window.step7_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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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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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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# 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, 'step6_panel'):
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step6_widget = getattr(main_window.step6_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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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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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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# 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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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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self.output_file.set_path(output_dir)
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except Exception as e:
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import traceback
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print(f"【{self.__class__.__name__}】自动填充失败，跳过: {e}")
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traceback.print_exc()
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def _get_default_work_dir(self):
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"""获取 work_dir，优先用 panel 自身缓存的，否则尝试从主窗口取"""
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if hasattr(self, 'work_dir') and self.work_dir:
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return str(self.work_dir)
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mw = self.window()
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if mw and hasattr(mw, 'work_dir') and mw.work_dir:
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return str(mw.work_dir)
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return ""
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def browse_models_dir(self):
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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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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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def get_config(self):
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"""获取配置"""
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config = {
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'metric': self.metric.currentText(),
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'prediction_column': self.prediction_column.text(),
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}
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sampling_csv_path = self.sampling_csv_file.get_path()
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if sampling_csv_path:
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config['sampling_csv_path'] = sampling_csv_path
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models_dir = self.models_dir_file.get_path()
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if models_dir:
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config['models_dir'] = models_dir
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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 'metric' in config:
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idx = self.metric.findText(config['metric'])
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if idx >= 0:
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self.metric.setCurrentIndex(idx)
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if 'prediction_column' in config:
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self.prediction_column.setText(config['prediction_column'])
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if 'sampling_csv_path' in config:
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self.sampling_csv_file.set_path(config['sampling_csv_path'])
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if 'models_dir' in config:
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self.models_dir_file.set_path(config['models_dir'])
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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 run_step(self):
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"""独立运行步骤8"""
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sampling_csv_path = self.sampling_csv_file.get_path()
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models_dir = self.models_dir_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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return
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if not models_dir:
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QMessageBox.warning(self, "输入错误", "请选择模型目录！")
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return
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main_window = self.window()
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if hasattr(main_window, 'run_single_step'):
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config = {'step8': self.get_config()}
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main_window.run_single_step('step8', config)
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