DXC
2261b4b30e
- 9 个面板（step1~step6/step8_ml_train/step8_qaa/step9_ml_predict/step10）单步执行按钮从 parent 链上溯改为 global_event_bus.publish('RequestRunSingleStep')
- PipelineExecutor 新增 _on_request_run_single_step 订阅
- 新增 Handler: step8_ml_train / step9_ml_predict / step10_qaa_inversion / step11_concentration / step12_kriging / step13_visualization / step14_report
- 删除旧 water_quality_inversion_pipeline_GUI.py（上帝类已肢解完毕）
509 lines
20 KiB
Python
509 lines
20 KiB
Python
#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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"""
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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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import sys
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from pathlib import Path
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# 路径归一化 helper（与 pipeline.get_step_output_dir 互为表里）
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_HERE = os.path.dirname(os.path.abspath(__file__))
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if _HERE not in sys.path:
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sys.path.insert(0, _HERE)
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from _step_path_resolver import get_step_output_path, resolve_step_widget, resolve_subdir
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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, QRadioButton, QListWidget, QAbstractItemView, QHBoxLayout,
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QListWidgetItem,
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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 Step9MlPredictPanel(QWidget):
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"""步骤9：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.external_models_dict = {} # {subdir_name: model_obj, ...}
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self.external_model_dir = "" # 母文件夹路径（隐藏）
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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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# -------- 模型来源选择（单选按钮组） --------
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source_group = QGroupBox("模型来源")
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source_layout = QVBoxLayout()
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self.use_trained_model = QRadioButton("使用当前训练流程的模型")
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self.use_external_model = QRadioButton("导入本地预训练模型 (.joblib)")
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self.use_trained_model.setChecked(True)
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source_layout.addWidget(self.use_trained_model)
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source_layout.addWidget(self.use_external_model)
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self.use_trained_model.toggled.connect(self._on_model_source_changed)
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self.use_external_model.toggled.connect(self._on_model_source_changed)
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source_group.setStyleSheet("""
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QRadioButton {
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font-size: 13px;
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spacing: 8px;
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}
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QRadioButton::indicator {
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width: 16px;
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height: 16px;
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border-radius: 9px;
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border: 2px solid #A0A0A0;
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background-color: #FFFFFF;
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}
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QRadioButton::indicator:hover {
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border: 2px solid #0078D7;
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}
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QRadioButton::indicator:checked {
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background-color: #0078D7;
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border: 2px solid #0078D7;
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}
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""")
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source_group.setLayout(source_layout)
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layout.addWidget(source_group)
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# -------- 外部模型文件选择（条件显示） --------
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self.external_model_widget = FileSelectWidget(
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"模型母文件夹:",
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"Directories"
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)
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self.external_model_widget.browse_btn.clicked.disconnect()
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self.external_model_widget.browse_btn.clicked.connect(self._scan_external_model_dir)
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self.external_model_widget.setVisible(False)
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layout.addWidget(self.external_model_widget)
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# -------- 已扫描模型列表（条件显示） --------
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self.model_list_group = QGroupBox("选择参与预测的模型")
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self.model_list_group.setVisible(False)
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model_list_layout = QVBoxLayout()
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self.model_list = QListWidget()
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self.model_list.setMaximumHeight(130)
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self.model_list.setSelectionMode(QAbstractItemView.NoSelection)
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self.model_list.setStyleSheet("""
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QListWidget {
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border: 1px solid #C0C0C0;
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border-radius: 4px;
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background-color: #FFFFFF;
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font-size: 12px;
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}
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QListWidget::item {
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padding: 4px 6px;
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border-bottom: 1px solid #F0F0F0;
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}
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QListWidget::item:selected {
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background-color: transparent;
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}
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""")
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model_list_layout.addWidget(self.model_list)
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btn_row = QHBoxLayout()
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self.btn_select_all = QPushButton("全选")
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self.btn_select_all.setMaximumWidth(80)
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self.btn_select_all.setStyleSheet(ModernStylesheet.get_button_stylesheet('default'))
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self.btn_select_all.clicked.connect(self._select_all_models)
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self.btn_select_none = QPushButton("全不选")
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self.btn_select_none.setMaximumWidth(80)
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self.btn_select_none.setStyleSheet(ModernStylesheet.get_button_stylesheet('default'))
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self.btn_select_none.clicked.connect(self._select_none_models)
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btn_row.addWidget(self.btn_select_all)
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btn_row.addWidget(self.btn_select_none)
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btn_row.addStretch()
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model_list_layout.addLayout(btn_row)
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self.model_list_group.setLayout(model_list_layout)
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layout.addWidget(self.model_list_group)
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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._on_run_single_clicked)
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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 _on_model_source_changed(self, checked: bool):
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"""单选按钮切换：控制外部模型文件选择控件的显示/隐藏"""
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if not checked:
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return
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is_external = self.use_external_model.isChecked()
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self.external_model_widget.setVisible(is_external)
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self.model_list_group.setVisible(is_external)
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if not is_external:
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self.external_models_dict = {}
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self.external_model_dir = ""
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self._clear_model_list()
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def _scan_external_model_dir(self):
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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 = resolve_subdir(default, 'ml_prediction')
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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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default,
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)
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if not dir_path:
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return
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self.external_model_dir = dir_path
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models_found = {}
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errors = []
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try:
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import joblib
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for subentry in os.scandir(dir_path):
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if not subentry.is_dir():
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continue
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subdir_name = subentry.name
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joblib_files = [
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f for f in os.scandir(subentry.path)
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if f.is_file() and f.name.lower().endswith(".joblib")
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]
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if not joblib_files:
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continue
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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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if isinstance(loaded, dict) and "model" in loaded:
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model_obj = loaded["model"]
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elif hasattr(loaded, "predict"):
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model_obj = loaded
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else:
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errors.append(f"{subdir_name}: 无法识别的格式 {type(loaded).__name__}")
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continue
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models_found[subdir_name] = model_obj
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except Exception as e:
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errors.append(f"{subdir_name}: {type(e).__name__}: {e}")
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except Exception as e:
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QMessageBox.warning(
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self,
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"扫描失败",
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f"遍历模型目录时发生错误：\n{type(e).__name__}: {e}",
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)
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return
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if not models_found:
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QMessageBox.warning(
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self,
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"未找到模型",
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f"在「{dir_path}」的子目录中未发现任何 .joblib 文件。\n"
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"请确认每个水质参数对应一个子文件夹，内含 .joblib 模型文件。",
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)
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self.external_model_widget.set_path("")
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self.external_models_dict = {}
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self._clear_model_list()
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return
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self.external_models_dict = models_found
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self._populate_model_list(models_found)
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names = sorted(models_found.keys())
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display = f"已识别到 {len(names)} 个模型: {', '.join(names)}"
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self.external_model_widget.set_path(display)
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self.external_model_widget.line_edit.setStyleSheet("color: #0078D7; font-weight: bold;")
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err_lines = "\n".join(errors) if errors else "无"
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QMessageBox.information(
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self,
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"模型扫描完成",
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f"成功加载 {len(models_found)} 个模型：\n{display}\n\n"
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f"加载失败 {len(errors)} 个：\n{err_lines}",
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)
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def _populate_model_list(self, models_dict):
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"""将扫描到的模型填充到 QListWidget，每个条目可勾选，默认全选"""
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self.model_list.clear()
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for name in sorted(models_dict.keys()):
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item = QListWidgetItem(name)
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item.setFlags(item.flags() | Qt.ItemIsUserCheckable)
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item.setCheckState(Qt.Checked)
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self.model_list.addItem(item)
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def _clear_model_list(self):
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"""清空模型列表"""
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self.model_list.clear()
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def _select_all_models(self):
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"""全选：设置所有条目为 Checked"""
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for i in range(self.model_list.count()):
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self.model_list.item(i).setCheckState(Qt.Checked)
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def _select_none_models(self):
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"""全不选：设置所有条目为 Unchecked"""
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for i in range(self.model_list.count()):
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self.model_list.item(i).setCheckState(Qt.Unchecked)
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def _get_checked_models_dict(self):
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"""从列表中提取用户勾选的模型，组装成字典返回"""
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result = {}
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for i in range(self.model_list.count()):
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item = self.model_list.item(i)
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if item.checkState() == Qt.Checked:
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name = item.text()
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if name in self.external_models_dict:
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result[name] = self.external_models_dict[name]
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return result
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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 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 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(step4_output_path)
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# 2. 尝试从 Step8（监督建模）读取模型目录（修复张冠李戴：原代码 main_window.step9_panel 不存在）
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step8_models_dir = get_step_output_path(
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main_window, 'models_dir', work_dir=self.work_dir,
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widget_attr='output_dir', fallback_key='step8_ml_train',
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)
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if step8_models_dir:
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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(step8_models_dir)
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# 3. 自动填充输出路径（机器学习预测目录，归属 step9 → 9_ML_Prediction）
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# 注：9_ML_Prediction 是 prediction_dir 的子目录，用本地约定
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if self.work_dir:
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output_dir = resolve_subdir(self.work_dir, '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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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 = resolve_subdir(default, 'ml_prediction')
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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 _on_run_single_clicked(self):
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"""通过 EventBus 发布单步执行请求（解耦面板与 PipelineExecutor）。"""
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from src.gui.core.event_bus import global_event_bus
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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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return
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# 外部模型优先：用户选择了"导入本地预训练模型"
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if self.use_external_model.isChecked():
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if not self.external_models_dict:
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QMessageBox.warning(
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self,
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"模型未加载",
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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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checked_dict = self._get_checked_models_dict()
|
||
if not checked_dict:
|
||
QMessageBox.warning(
|
||
self,
|
||
"未选择模型",
|
||
"请至少勾选一个模型参与预测！",
|
||
)
|
||
return
|
||
config = {
|
||
'step9_ml_predict': self.get_config(),
|
||
'_external_models_dict': checked_dict,
|
||
'_external_model_dir': self.external_model_dir,
|
||
}
|
||
global_event_bus.publish('RequestRunSingleStep', {
|
||
'step_name': 'step9_ml_predict',
|
||
'config': config,
|
||
})
|
||
return
|
||
|
||
# 默认流程：使用模型目录
|
||
models_dir = self.models_dir_file.get_path()
|
||
if not models_dir:
|
||
QMessageBox.warning(self, "输入错误", "请选择模型目录！")
|
||
return
|
||
|
||
config = {'step9_ml_predict': self.get_config()}
|
||
global_event_bus.publish('RequestRunSingleStep', {
|
||
'step_name': 'step9_ml_predict',
|
||
'config': config,
|
||
})
|
||
|
||
def run_step(self):
|
||
"""独立运行步骤11（旧版 parent 链上溯方式，保留兼容）。"""
|
||
sampling_csv_path = self.sampling_csv_file.get_path()
|
||
if not sampling_csv_path:
|
||
QMessageBox.warning(self, "输入错误", "请选择采样光谱CSV文件！")
|
||
return
|
||
|
||
# 外部模型优先：用户选择了"导入本地预训练模型"
|
||
if self.use_external_model.isChecked():
|
||
if not self.external_models_dict:
|
||
QMessageBox.warning(
|
||
self,
|
||
"模型未加载",
|
||
"请先点击「浏览...」按钮选择模型母文件夹！",
|
||
)
|
||
return
|
||
checked_dict = self._get_checked_models_dict()
|
||
if not checked_dict:
|
||
QMessageBox.warning(
|
||
self,
|
||
"未选择模型",
|
||
"请至少勾选一个模型参与预测！",
|
||
)
|
||
return
|
||
main_window = self.window()
|
||
if hasattr(main_window, 'run_single_step'):
|
||
config = {
|
||
'step9_ml_predict': self.get_config(),
|
||
'_external_models_dict': checked_dict,
|
||
'_external_model_dir': self.external_model_dir,
|
||
}
|
||
main_window.run_single_step('step9_ml_predict', config)
|
||
return
|
||
|
||
# 默认流程：使用模型目录
|
||
models_dir = self.models_dir_file.get_path()
|
||
if not models_dir:
|
||
QMessageBox.warning(self, "输入错误", "请选择模型目录！")
|
||
return
|
||
|
||
main_window = self.window()
|
||
if hasattr(main_window, 'run_single_step'):
|
||
config = {'step9_ml_predict': self.get_config()}
|
||
main_window.run_single_step('step9_ml_predict', config) |