feat(gui): 全流程面板合并 + 一键式运行 GUI 入口集成
This commit is contained in:
@ -1,206 +1,158 @@
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#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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"""
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Step9 面板 - 分布图生成
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Step9 面板 - 自定义回归分析
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"""
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import os
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import traceback
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from pathlib import Path
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from typing import List, Optional
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from typing import Dict
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from PyQt5.QtCore import Qt, QThread, pyqtSignal
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import pandas as pd
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from PyQt5.QtWidgets import (
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QWidget, QVBoxLayout, QGroupBox, QFormLayout, QHBoxLayout,
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QLabel, QCheckBox, QPushButton, QLineEdit, QDoubleSpinBox,
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QRadioButton, QButtonGroup, QMessageBox, QFileDialog,
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QWidget, QVBoxLayout, QGroupBox, QFormLayout, QGridLayout,
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QHBoxLayout, QLabel, QLineEdit, QCheckBox, QPushButton,
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QScrollArea, QMessageBox,
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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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# Pipeline 可用性（与 core/worker_thread.py 保持一致）
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try:
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from src.core.water_quality_inversion_pipeline_GUI import WaterQualityInversionPipeline
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PIPELINE_AVAILABLE = True
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except ImportError:
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PIPELINE_AVAILABLE = False
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class Step9BatchThread(QThread):
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"""专题图：按文件夹内多个预测 CSV 批量生成分布图。"""
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finished_ok = pyqtSignal(int)
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failed = pyqtSignal(str)
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log_message = pyqtSignal(str, str)
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def __init__(self, work_dir: str, csv_paths: List[str], step9_kwargs: dict, output_dir_optional: Optional[str]):
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super().__init__()
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self.work_dir = work_dir
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self.csv_paths = csv_paths
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self.step9_kwargs = step9_kwargs
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self.output_dir_optional = (output_dir_optional or "").strip() or None
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def run(self):
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mpl_prev = None
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try:
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import matplotlib
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mpl_prev = matplotlib.get_backend()
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except Exception:
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pass
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try:
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import matplotlib.pyplot as plt
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plt.switch_backend("Agg")
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except Exception:
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mpl_prev = None
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try:
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from src.core.water_quality_inversion_pipeline_GUI import WaterQualityInversionPipeline
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pipeline = WaterQualityInversionPipeline(work_dir=self.work_dir)
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n = len(self.csv_paths)
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for i, csv_p in enumerate(self.csv_paths):
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self.log_message.emit(f"专题图 [{i + 1}/{n}] {csv_p}", "info")
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kw = {**self.step9_kwargs, "prediction_csv_path": csv_p, "skip_dependency_check": True}
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if self.output_dir_optional:
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stem = Path(csv_p).stem
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kw["output_image_path"] = str(Path(self.output_dir_optional) / f"{stem}_distribution.png")
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else:
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kw["output_image_path"] = None
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pipeline.step9_generate_distribution_map(**kw)
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self.finished_ok.emit(n)
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except Exception as e:
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self.failed.emit(f"{e}\n{traceback.format_exc()}")
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finally:
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if mpl_prev:
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try:
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import matplotlib.pyplot as plt
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plt.switch_backend(mpl_prev)
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except Exception:
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pass
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class Step9Panel(QWidget):
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"""步骤9：分布图生成"""
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"""步骤9：自定义回归分析"""
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def __init__(self, parent=None):
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super().__init__(parent)
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self._batch_thread = None
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self.x_column_checkboxes: Dict[str, QCheckBox] = {}
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self.y_column_checkboxes: Dict[str, QCheckBox] = {}
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self.method_checkboxes: Dict[str, QCheckBox] = {}
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self.csv_columns = []
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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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hint = QLabel(
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"独立运行：可选「单个 CSV」或「文件夹批量」（扫描目录下所有 .csv）。"
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"完整流程中预测 CSV 由步骤11、12、13 自动传入，无需在此选择。"
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)
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hint.setWordWrap(True)
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hint.setStyleSheet(
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f"color: {ModernStylesheet.COLORS.get('text_secondary', '#666')};"
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)
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hint = QLabel("指定自变量与因变量列，批量尝试不同回归方法")
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hint.setStyleSheet("color: #666; font-size: 11px;")
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layout.addWidget(hint)
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mode_row = QHBoxLayout()
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self.mode_single_rb = QRadioButton("单个 CSV 文件")
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self.mode_folder_rb = QRadioButton("文件夹批量")
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self._mode_group = QButtonGroup(self)
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self._mode_group.addButton(self.mode_single_rb, 0)
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self._mode_group.addButton(self.mode_folder_rb, 1)
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mode_row.addWidget(self.mode_single_rb)
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mode_row.addWidget(self.mode_folder_rb)
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mode_row.addStretch()
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layout.addLayout(mode_row)
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# CSV文件选择
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csv_group = QGroupBox("数据文件")
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csv_layout = QVBoxLayout()
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# ---------- RadioButton 美化样式（选中状态为方形实心块，贴合主界面风格） ----------
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radio_style = """
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QRadioButton {
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font-size: 14px;
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spacing: 8px;
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color: #333333;
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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: 2px solid #999999;
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border-radius: 3px;
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background-color: white;
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}
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QRadioButton::indicator:checked {
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border: 2px solid #0078d4;
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background-color: #0078d4;
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image: none;
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}
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QRadioButton::indicator:hover {
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border: 2px solid #005a9e;
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}
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"""
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self.mode_single_rb.setStyleSheet(radio_style)
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self.mode_folder_rb.setStyleSheet(radio_style)
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self.prediction_csv_file = FileSelectWidget(
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"预测结果CSV:",
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self.csv_file = FileSelectWidget(
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"输入CSV文件:",
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"CSV Files (*.csv);;All Files (*.*)"
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)
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layout.addWidget(self.prediction_csv_file)
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self.csv_file.line_edit.textChanged.connect(self.on_csv_file_changed)
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csv_layout.addWidget(self.csv_file)
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folder_row = QHBoxLayout()
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self.prediction_csv_dir_label = QLabel("预测CSV目录:")
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self.prediction_csv_dir_label.setMinimumWidth(120)
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self.prediction_csv_dir_edit = QLineEdit()
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self.prediction_csv_dir_edit.setPlaceholderText("选择含多个预测结果 CSV 的文件夹…")
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pred_dir_btn = QPushButton("浏览…")
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pred_dir_btn.setMaximumWidth(80)
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pred_dir_btn.clicked.connect(self.browse_prediction_csv_dir)
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folder_row.addWidget(self.prediction_csv_dir_label)
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folder_row.addWidget(self.prediction_csv_dir_edit, 1)
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folder_row.addWidget(pred_dir_btn)
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self._folder_row_widget = QWidget()
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self._folder_row_widget.setLayout(folder_row)
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layout.addWidget(self._folder_row_widget)
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self.refresh_btn = QPushButton("刷新列信息")
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self.refresh_btn.clicked.connect(self.refresh_csv_columns)
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csv_layout.addWidget(self.refresh_btn)
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self.recursive_csv_cb = QCheckBox("包含子文件夹（递归扫描 *.csv）")
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layout.addWidget(self.recursive_csv_cb)
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csv_group.setLayout(csv_layout)
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layout.addWidget(csv_group)
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self.boundary_file = FileSelectWidget(
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"边界文件:",
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"Shapefiles (*.shp);;All Files (*.*)"
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)
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layout.addWidget(self.boundary_file)
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# 自变量选择
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x_group = QGroupBox("自变量列选择 (可多选)")
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x_layout = QVBoxLayout()
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# 参数设置
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params_group = QGroupBox("生成参数")
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params_layout = QFormLayout()
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x_scroll = QScrollArea()
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x_scroll.setWidgetResizable(True)
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x_scroll.setMinimumHeight(250)
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x_scroll.setMaximumHeight(350)
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self.resolution = QDoubleSpinBox()
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self.resolution.setRange(1, 1000)
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self.resolution.setValue(30)
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params_layout.addRow("分辨率(米):", self.resolution)
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x_widget = QWidget()
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self.x_columns_layout = QGridLayout()
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x_widget.setLayout(self.x_columns_layout)
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self.input_crs = QLineEdit()
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self.input_crs.setText("EPSG:32651")
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params_layout.addRow("输入坐标系:", self.input_crs)
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x_scroll.setWidget(x_widget)
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x_layout.addWidget(x_scroll)
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self.output_crs = QLineEdit()
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self.output_crs.setText("EPSG:4326")
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params_layout.addRow("输出坐标系:", self.output_crs)
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x_btn_layout = QHBoxLayout()
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self.x_select_all = QPushButton("全选")
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self.x_deselect_all = QPushButton("全不选")
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self.x_select_all.clicked.connect(lambda: self.toggle_checkboxes(self.x_column_checkboxes, True))
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self.x_deselect_all.clicked.connect(lambda: self.toggle_checkboxes(self.x_column_checkboxes, False))
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x_btn_layout.addWidget(self.x_select_all)
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x_btn_layout.addWidget(self.x_deselect_all)
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x_btn_layout.addStretch()
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x_layout.addLayout(x_btn_layout)
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self.show_points = QCheckBox("显示采样点")
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params_layout.addRow("", self.show_points)
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x_group.setLayout(x_layout)
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layout.addWidget(x_group)
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self.use_diffusion = QCheckBox("启用距离扩散")
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self.use_diffusion.setChecked(True)
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params_layout.addRow("", self.use_diffusion)
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# 因变量选择
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y_group = QGroupBox("因变量列选择 (可多选)")
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y_layout = QVBoxLayout()
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params_group.setLayout(params_layout)
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layout.addWidget(params_group)
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y_scroll = QScrollArea()
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y_scroll.setWidgetResizable(True)
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y_scroll.setMinimumHeight(200)
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y_scroll.setMaximumHeight(300)
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y_widget = QWidget()
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self.y_columns_layout = QGridLayout()
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y_widget.setLayout(self.y_columns_layout)
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y_scroll.setWidget(y_widget)
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y_layout.addWidget(y_scroll)
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y_btn_layout = QHBoxLayout()
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self.y_select_all = QPushButton("全选")
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self.y_deselect_all = QPushButton("全不选")
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self.y_select_all.clicked.connect(lambda: self.toggle_checkboxes(self.y_column_checkboxes, True))
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self.y_deselect_all.clicked.connect(lambda: self.toggle_checkboxes(self.y_column_checkboxes, False))
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y_btn_layout.addWidget(self.y_select_all)
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y_btn_layout.addWidget(self.y_deselect_all)
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y_btn_layout.addStretch()
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y_layout.addLayout(y_btn_layout)
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y_group.setLayout(y_layout)
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layout.addWidget(y_group)
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# 回归方法选择
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method_group = QGroupBox("回归方法选择 (可多选)")
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method_layout = QVBoxLayout()
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method_grid = QGridLayout()
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regression_methods = [
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'linear', 'exponential', 'power', 'logarithmic',
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'polynomial', 'hyperbolic', 'sigmoidal'
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]
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for i, method in enumerate(regression_methods):
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checkbox = QCheckBox(method)
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if method in ['linear', 'exponential', 'power', 'logarithmic']:
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checkbox.setChecked(True)
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self.method_checkboxes[method] = checkbox
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method_grid.addWidget(checkbox, i // 3, i % 3)
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method_layout.addLayout(method_grid)
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method_btn_layout = QHBoxLayout()
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self.method_select_all = QPushButton("全选")
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self.method_deselect_all = QPushButton("全不选")
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self.method_select_all.clicked.connect(lambda: self.toggle_checkboxes(self.method_checkboxes, True))
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self.method_deselect_all.clicked.connect(lambda: self.toggle_checkboxes(self.method_checkboxes, False))
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method_btn_layout.addWidget(self.method_select_all)
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method_btn_layout.addWidget(self.method_deselect_all)
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method_btn_layout.addStretch()
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method_layout.addLayout(method_btn_layout)
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method_group.setLayout(method_layout)
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layout.addWidget(method_group)
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# 输出目录
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self.output_dir = FileSelectWidget(
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"输出分布图目录:",
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"Directories;;All Files (*.*)"
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)
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self.output_dir.line_edit.setPlaceholderText("留空→工作目录/14_visualization")
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self.output_dir.browse_btn.clicked.disconnect()
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self.output_dir.browse_btn.clicked.connect(self.browse_output_dir)
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layout.addWidget(self.output_dir)
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output_group = QGroupBox("输出设置")
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output_layout = QFormLayout()
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self.output_dir = QLineEdit()
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self.output_dir.setText("") # 路径由 update_from_config 根据 work_dir 自动填充
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output_layout.addRow("输出目录名:", self.output_dir)
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output_group.setLayout(output_layout)
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layout.addWidget(output_group)
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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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@ -216,119 +168,120 @@ class Step9Panel(QWidget):
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layout.addStretch()
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self.setLayout(layout)
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# 信号绑定与初始状态
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self.mode_single_rb.toggled.connect(self._toggle_input_mode)
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self.mode_folder_rb.toggled.connect(self._toggle_input_mode)
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self.mode_single_rb.setChecked(True) # 默认选中"单个 CSV"
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self._toggle_input_mode() # 根据默认值设置初始显示状态
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def toggle_checkboxes(self, checkboxes_dict, checked):
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"""统一设置checkbox状态"""
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for checkbox in checkboxes_dict.values():
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checkbox.setChecked(checked)
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def _toggle_input_mode(self):
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"""槽函数：根据单选框状态动态显示/隐藏对应的输入组件。"""
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folder_mode = self.mode_folder_rb.isChecked()
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# 单个 CSV 模式：显示单文件选择，隐藏文件夹选择
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self.prediction_csv_file.setVisible(not folder_mode)
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# 文件夹批量模式：显示文件夹选择 + 递归选项，隐藏单文件选择
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self._folder_row_widget.setVisible(folder_mode)
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self.recursive_csv_cb.setVisible(folder_mode)
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def on_csv_file_changed(self):
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"""CSV文件改变时自动刷新列信息"""
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self.refresh_csv_columns()
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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 refresh_csv_columns(self):
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"""刷新CSV文件的列信息"""
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csv_path = self.csv_file.get_path()
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if not csv_path or not os.path.exists(csv_path):
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self.csv_columns = []
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self.update_column_widgets()
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return
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def browse_prediction_csv_dir(self):
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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, "11_12_13_predictions")
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d = QFileDialog.getExistingDirectory(self, "选择预测结果 CSV 所在文件夹", default)
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if d:
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self.prediction_csv_dir_edit.setText(d)
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try:
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df = pd.read_csv(csv_path, nrows=0)
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self.csv_columns = list(df.columns)
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self.update_column_widgets()
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except Exception as e:
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self.csv_columns = []
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self.update_column_widgets()
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print(f"读取CSV列信息失败: {e}")
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def _collect_csv_paths_from_folder(self) -> List[str]:
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folder = (self.prediction_csv_dir_edit.text() or "").strip()
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if not folder or not os.path.isdir(folder):
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return []
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root = Path(folder)
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if self.recursive_csv_cb.isChecked():
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files = sorted(root.rglob("*.csv"))
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else:
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files = sorted(root.glob("*.csv"))
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return [str(p) for p in files if p.is_file()]
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def update_column_widgets(self):
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"""更新列选择组件"""
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for checkbox in self.x_column_checkboxes.values():
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checkbox.setParent(None)
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self.x_column_checkboxes.clear()
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def _step9_base_pipeline_kwargs(self) -> dict:
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return {
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'boundary_shp_path': self.boundary_file.get_path(),
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'resolution': self.resolution.value(),
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'input_crs': self.input_crs.text(),
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'output_crs': self.output_crs.text(),
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'show_sample_points': self.show_points.isChecked(),
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'use_distance_diffusion': self.use_diffusion.isChecked(),
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}
|
||||
for checkbox in self.y_column_checkboxes.values():
|
||||
checkbox.setParent(None)
|
||||
self.y_column_checkboxes.clear()
|
||||
|
||||
if not self.csv_columns:
|
||||
return
|
||||
|
||||
for i, col in enumerate(self.csv_columns):
|
||||
checkbox = QCheckBox(col)
|
||||
if any(keyword in col.lower() for keyword in ['index', 'ratio', 'normalized', 'nd', 'b']):
|
||||
checkbox.setChecked(True)
|
||||
self.x_column_checkboxes[col] = checkbox
|
||||
self.x_columns_layout.addWidget(checkbox, i // 3, i % 3)
|
||||
|
||||
for i, col in enumerate(self.csv_columns):
|
||||
checkbox = QCheckBox(col)
|
||||
if any(keyword in col.lower() for keyword in ['chl', 'tn', 'tp', 'turbidity', 'do', 'ph', 'conductivity']):
|
||||
checkbox.setChecked(True)
|
||||
self.y_column_checkboxes[col] = checkbox
|
||||
self.y_columns_layout.addWidget(checkbox, i // 2, i % 2)
|
||||
|
||||
self.x_columns_layout.update()
|
||||
self.y_columns_layout.update()
|
||||
|
||||
def get_config(self):
|
||||
pred_csv = (self.prediction_csv_file.get_path() or "").strip()
|
||||
folder_mode = self.mode_folder_rb.isChecked()
|
||||
pred_dir = (self.prediction_csv_dir_edit.text() or "").strip()
|
||||
config = {
|
||||
'step9_batch_mode': 'folder' if folder_mode else 'single',
|
||||
'prediction_csv_dir': pred_dir if pred_dir else None,
|
||||
'recursive_csv_scan': self.recursive_csv_cb.isChecked(),
|
||||
'prediction_csv_path': None if folder_mode else (pred_csv if pred_csv else None),
|
||||
'boundary_shp_path': self.boundary_file.get_path(),
|
||||
'resolution': self.resolution.value(),
|
||||
'input_crs': self.input_crs.text(),
|
||||
'output_crs': self.output_crs.text(),
|
||||
'show_sample_points': self.show_points.isChecked(),
|
||||
'use_distance_diffusion': self.use_diffusion.isChecked(),
|
||||
selected_x_columns = [
|
||||
col for col, checkbox in self.x_column_checkboxes.items()
|
||||
if checkbox.isChecked()
|
||||
]
|
||||
selected_y_columns = [
|
||||
col for col, checkbox in self.y_column_checkboxes.items()
|
||||
if checkbox.isChecked()
|
||||
]
|
||||
selected_methods = [
|
||||
method for method, checkbox in self.method_checkboxes.items()
|
||||
if checkbox.isChecked()
|
||||
]
|
||||
if not selected_methods:
|
||||
selected_methods = 'all'
|
||||
|
||||
return {
|
||||
'csv_path': self.csv_file.get_path() or None,
|
||||
'x_columns': selected_x_columns,
|
||||
'y_columns': selected_y_columns,
|
||||
'methods': selected_methods,
|
||||
'output_dir': self.output_dir.text().strip() or None,
|
||||
'enabled': self.enable_checkbox.isChecked()
|
||||
}
|
||||
out_dir = (self.output_dir.get_path() or "").strip()
|
||||
if not folder_mode and pred_csv and out_dir:
|
||||
stem = Path(pred_csv).stem
|
||||
config['output_image_path'] = str(Path(out_dir) / f"{stem}_distribution.png")
|
||||
else:
|
||||
config['output_image_path'] = None
|
||||
return config
|
||||
|
||||
def set_config(self, config):
|
||||
mode = config.get('step9_batch_mode', 'single')
|
||||
if mode == 'folder':
|
||||
self.mode_folder_rb.setChecked(True)
|
||||
else:
|
||||
self.mode_single_rb.setChecked(True)
|
||||
if config.get('prediction_csv_dir'):
|
||||
self.prediction_csv_dir_edit.setText(str(config['prediction_csv_dir']))
|
||||
if 'recursive_csv_scan' in config:
|
||||
self.recursive_csv_cb.setChecked(bool(config['recursive_csv_scan']))
|
||||
if 'prediction_csv_path' in config and config['prediction_csv_path']:
|
||||
self.prediction_csv_file.set_path(str(config['prediction_csv_path']))
|
||||
if 'boundary_shp_path' in config:
|
||||
self.boundary_file.set_path(config['boundary_shp_path'])
|
||||
if 'resolution' in config:
|
||||
self.resolution.setValue(config['resolution'])
|
||||
if 'input_crs' in config:
|
||||
self.input_crs.setText(config['input_crs'])
|
||||
if 'output_crs' in config:
|
||||
self.output_crs.setText(config['output_crs'])
|
||||
if 'show_sample_points' in config:
|
||||
self.show_points.setChecked(config['show_sample_points'])
|
||||
if 'use_distance_diffusion' in config:
|
||||
self.use_diffusion.setChecked(config['use_distance_diffusion'])
|
||||
if 'output_dir' in config and config['output_dir']:
|
||||
self.output_dir.set_path(str(config['output_dir']))
|
||||
elif config.get('output_image_path'):
|
||||
p = Path(str(config['output_image_path']))
|
||||
if p.parent and str(p.parent) != '.':
|
||||
self.output_dir.set_path(str(p.parent))
|
||||
if 'csv_path' in config:
|
||||
self.csv_file.set_path(config['csv_path'])
|
||||
self.refresh_csv_columns()
|
||||
|
||||
if 'x_columns' in config:
|
||||
selected_x = set(config['x_columns']) if isinstance(config['x_columns'], list) else set()
|
||||
for col, checkbox in self.x_column_checkboxes.items():
|
||||
checkbox.setChecked(col in selected_x)
|
||||
|
||||
if 'y_columns' in config:
|
||||
selected_y = set(config['y_columns']) if isinstance(config['y_columns'], list) else set()
|
||||
for col, checkbox in self.y_column_checkboxes.items():
|
||||
checkbox.setChecked(col in selected_y)
|
||||
|
||||
if 'methods' in config:
|
||||
methods = config['methods']
|
||||
if isinstance(methods, list):
|
||||
selected_methods = set(methods)
|
||||
elif methods == 'all':
|
||||
selected_methods = set(self.method_checkboxes.keys())
|
||||
else:
|
||||
selected_methods = set()
|
||||
for method, checkbox in self.method_checkboxes.items():
|
||||
checkbox.setChecked(method in selected_methods)
|
||||
|
||||
if 'output_dir' in config:
|
||||
self.output_dir.setText(config['output_dir'] or "9_Custom_Regression_Modeling")
|
||||
if 'enabled' in config:
|
||||
self.enable_checkbox.setChecked(config['enabled'])
|
||||
|
||||
def update_from_config(self, work_dir=None, pipeline=None):
|
||||
"""从全局配置自动填充预测结果目录
|
||||
|
||||
优先使用 Step8（机器学习预测）的输出目录作为待预测 CSV 目录；
|
||||
其次回退到 Step8.5（回归预测）或 Step8.75（自定义回归预测）的输出目录。
|
||||
"""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
|
||||
@ -344,190 +297,78 @@ class Step9Panel(QWidget):
|
||||
else:
|
||||
self.work_dir = None
|
||||
|
||||
# 1. 尝试从 Step5 界面读取训练光谱 CSV 路径
|
||||
main_window = self.window()
|
||||
if not main_window:
|
||||
return
|
||||
if main_window and hasattr(main_window, 'step5_panel'):
|
||||
step5_widget = getattr(main_window.step5_panel, 'output_file', None)
|
||||
step5_output_path = ""
|
||||
if hasattr(step5_widget, 'get_path'):
|
||||
step5_output_path = step5_widget.get_path() or ""
|
||||
elif hasattr(step5_widget, 'text'):
|
||||
step5_output_path = step5_widget.text() or ""
|
||||
|
||||
# 1. 尝试从 Step8 界面读取机器学习预测输出目录（最优先）
|
||||
pred_dir = None
|
||||
if hasattr(main_window, 'step8_panel'):
|
||||
step8_widget = getattr(main_window.step8_panel, 'output_file', None)
|
||||
step8_output = ""
|
||||
if hasattr(step8_widget, 'get_path'):
|
||||
step8_output = step8_widget.get_path() or ""
|
||||
elif hasattr(step8_widget, 'text'):
|
||||
step8_output = step8_widget.text() or ""
|
||||
|
||||
if step8_output:
|
||||
if step5_output_path:
|
||||
# 若为相对路径，使用 work_dir 合成为绝对路径
|
||||
if not os.path.isabs(step8_output):
|
||||
step8_output = os.path.join(self.work_dir or '', step8_output).replace('\\', '/')
|
||||
# 提取父目录后追加 Machine_Learning_Prediction（最底层真实子目录）
|
||||
base_pred_dir = str(Path(step8_output).parent)
|
||||
ml_pred_dir = Path(base_pred_dir) / "Machine_Learning_Prediction"
|
||||
pred_dir = str(ml_pred_dir) if ml_pred_dir.exists() else base_pred_dir
|
||||
if not os.path.isabs(step5_output_path):
|
||||
step5_output_path = os.path.join(self.work_dir or '', step5_output_path).replace('\\', '/')
|
||||
existing = self.csv_file.get_path()
|
||||
if not existing or not existing.strip():
|
||||
self.csv_file.set_path(step5_output_path)
|
||||
|
||||
# 2. 备选：从 Step8.5 界面读取非经验预测输出目录
|
||||
if not pred_dir and hasattr(main_window, 'step8_5_panel'):
|
||||
step8_5_widget = getattr(main_window.step8_5_panel, 'output_file', None)
|
||||
step8_5_output = ""
|
||||
if hasattr(step8_5_widget, 'get_path'):
|
||||
step8_5_output = step8_5_widget.get_path() or ""
|
||||
elif hasattr(step8_5_widget, 'text'):
|
||||
step8_5_output = step8_5_widget.text() or ""
|
||||
|
||||
if step8_5_output:
|
||||
# 若为相对路径，使用 work_dir 合成为绝对路径
|
||||
if not os.path.isabs(step8_5_output):
|
||||
step8_5_output = os.path.join(self.work_dir or '', step8_5_output).replace('\\', '/')
|
||||
pred_dir = str(Path(step8_5_output).parent)
|
||||
|
||||
# 3. 备选：从 Step8.75 界面读取自定义回归预测输出目录
|
||||
if not pred_dir and hasattr(main_window, 'step8_75_panel'):
|
||||
step8_75_widget = getattr(main_window.step8_75_panel, 'output_dir_widget', None)
|
||||
step8_75_output = ""
|
||||
if hasattr(step8_75_widget, 'get_path'):
|
||||
step8_75_output = step8_75_widget.get_path() or ""
|
||||
elif hasattr(step8_75_widget, 'text'):
|
||||
step8_75_output = step8_75_widget.text() or ""
|
||||
|
||||
if step8_75_output:
|
||||
pred_dir = step8_75_output
|
||||
|
||||
# 自动填入"预测CSV目录"（文件夹批量模式）
|
||||
if pred_dir:
|
||||
existing_dir = (self.prediction_csv_dir_edit.text() or "").strip()
|
||||
if not existing_dir:
|
||||
self.prediction_csv_dir_edit.setText(pred_dir)
|
||||
# 切换到文件夹批量模式
|
||||
self.mode_folder_rb.setChecked(True)
|
||||
|
||||
# 4. 自动填充输出目录（14_visualization）
|
||||
# 2. 自动填充输出目录（9_Custom_Regression_Modeling）
|
||||
if self.work_dir:
|
||||
output_dir = os.path.join(self.work_dir, "14_visualization")
|
||||
output_dir = os.path.join(self.work_dir, "9_Custom_Regression_Modeling")
|
||||
os.makedirs(output_dir, exist_ok=True)
|
||||
existing_out = self.output_dir.get_path()
|
||||
if not existing_out or not existing_out.strip():
|
||||
self.output_dir.set_path(output_dir)
|
||||
|
||||
# 5. 自动探测原始矢量边界文件（.shp）作为专题图底图
|
||||
# 优先回溯 input-test/roi.shp，geopandas.read_file 仅支持矢量格式
|
||||
if self.work_dir:
|
||||
possible_shp = None
|
||||
candidates = [
|
||||
Path(self.work_dir).parent / "input-test" / "roi.shp",
|
||||
Path(self.work_dir) / "roi.shp",
|
||||
Path(self.work_dir).parent / "roi.shp",
|
||||
]
|
||||
for candidate in candidates:
|
||||
if candidate.exists() and candidate.suffix.lower() == ".shp":
|
||||
possible_shp = candidate
|
||||
break
|
||||
|
||||
existing_boundary = (self.boundary_file.get_path() or "").strip()
|
||||
if not existing_boundary and possible_shp:
|
||||
self.boundary_file.set_path(str(possible_shp))
|
||||
elif not existing_boundary:
|
||||
# 未找到 .shp 时清空并提示用户手动选择矢量文件
|
||||
self.boundary_file.set_path("")
|
||||
print("⚠️ 提示：专题图生成模块需传入标准矢量边界文件 (.shp)，请手动选择。")
|
||||
existing_out = self.output_dir.text().strip()
|
||||
if not existing_out:
|
||||
self.output_dir.setText(output_dir)
|
||||
except Exception as e:
|
||||
import traceback
|
||||
print(f"【{self.__class__.__name__}】自动填充失败，跳过: {e}")
|
||||
traceback.print_exc()
|
||||
|
||||
def browse_output_dir(self):
|
||||
"""浏览输出目录"""
|
||||
default = self._get_default_work_dir()
|
||||
if default:
|
||||
default = os.path.join(default, "14_visualization")
|
||||
dir_path = QFileDialog.getExistingDirectory(self, "选择输出分布图目录", default)
|
||||
if dir_path:
|
||||
self.output_dir.set_path(dir_path)
|
||||
|
||||
def run_step(self):
|
||||
"""独立运行步骤9"""
|
||||
if self._batch_thread and self._batch_thread.isRunning():
|
||||
QMessageBox.information(self, "提示", "批量任务正在运行，请稍候。")
|
||||
csv_path = self.csv_file.get_path()
|
||||
|
||||
if not csv_path:
|
||||
QMessageBox.warning(self, "输入验证失败", "请选择输入CSV文件")
|
||||
return
|
||||
if not os.path.exists(csv_path):
|
||||
QMessageBox.warning(self, "输入验证失败", "输入CSV文件不存在")
|
||||
return
|
||||
|
||||
boundary_shp_path = self.boundary_file.get_path()
|
||||
if not boundary_shp_path:
|
||||
QMessageBox.warning(self, "输入验证失败", "请选择边界文件")
|
||||
selected_x_columns = [
|
||||
col for col, checkbox in self.x_column_checkboxes.items()
|
||||
if checkbox.isChecked()
|
||||
]
|
||||
if not selected_x_columns:
|
||||
QMessageBox.warning(self, "输入验证失败", "请至少选择一个自变量列")
|
||||
return
|
||||
if not os.path.exists(boundary_shp_path):
|
||||
QMessageBox.warning(self, "输入验证失败", "边界文件不存在")
|
||||
|
||||
selected_y_columns = [
|
||||
col for col, checkbox in self.y_column_checkboxes.items()
|
||||
if checkbox.isChecked()
|
||||
]
|
||||
if not selected_y_columns:
|
||||
QMessageBox.warning(self, "输入验证失败", "请至少选择一个因变量列")
|
||||
return
|
||||
|
||||
selected_methods = [
|
||||
method for method, checkbox in self.method_checkboxes.items()
|
||||
if checkbox.isChecked()
|
||||
]
|
||||
if not selected_methods:
|
||||
QMessageBox.warning(self, "输入验证失败", "请至少选择一种回归方法")
|
||||
return
|
||||
|
||||
config = self.get_config()
|
||||
|
||||
parent = self.parent()
|
||||
while parent and not hasattr(parent, 'run_single_step'):
|
||||
parent = parent.parent()
|
||||
|
||||
if not parent or not hasattr(parent, 'run_single_step'):
|
||||
if parent and hasattr(parent, 'run_single_step'):
|
||||
parent.run_single_step('step9', {'step9': config})
|
||||
else:
|
||||
QMessageBox.critical(self, "错误", "无法找到父级GUI对象")
|
||||
return
|
||||
|
||||
if self.mode_folder_rb.isChecked():
|
||||
csv_list = self._collect_csv_paths_from_folder()
|
||||
if not csv_list:
|
||||
QMessageBox.warning(
|
||||
self,
|
||||
"输入验证失败",
|
||||
"所选文件夹中未找到 .csv 文件，或目录无效。\n"
|
||||
"可勾选「包含子文件夹」以递归扫描。",
|
||||
)
|
||||
return
|
||||
if not PIPELINE_AVAILABLE:
|
||||
QMessageBox.critical(self, "错误", "Pipeline 模块不可用，无法批量生成专题图。")
|
||||
return
|
||||
work_dir = getattr(parent, "work_dir", None) or "./work_dir"
|
||||
work_dir = str(work_dir)
|
||||
base_kw = self._step9_base_pipeline_kwargs()
|
||||
out_dir_opt = (self.output_dir.get_path() or "").strip() or None
|
||||
self.run_button.setEnabled(False)
|
||||
self._batch_thread = Step9BatchThread(work_dir, csv_list, base_kw, out_dir_opt)
|
||||
main_win = parent
|
||||
|
||||
def _batch_log(msg, lvl):
|
||||
if hasattr(main_win, "log_message"):
|
||||
main_win.log_message(msg, lvl)
|
||||
|
||||
self._batch_thread.log_message.connect(_batch_log, Qt.QueuedConnection)
|
||||
self._batch_thread.finished_ok.connect(self._on_step9_batch_ok, Qt.QueuedConnection)
|
||||
self._batch_thread.failed.connect(self._on_step9_batch_fail, Qt.QueuedConnection)
|
||||
self._batch_thread.finished.connect(lambda: self.run_button.setEnabled(True), Qt.QueuedConnection)
|
||||
self._batch_thread.start()
|
||||
if hasattr(parent, "log_message"):
|
||||
parent.log_message(f"专题图批量：共 {len(csv_list)} 个 CSV，工作目录 {work_dir}", "info")
|
||||
return
|
||||
|
||||
prediction_csv_path = (self.prediction_csv_file.get_path() or "").strip()
|
||||
if not prediction_csv_path:
|
||||
QMessageBox.warning(
|
||||
self,
|
||||
"输入验证失败",
|
||||
"请选择「预测结果 CSV」文件，或切换到「文件夹批量」。",
|
||||
)
|
||||
return
|
||||
if not os.path.isfile(prediction_csv_path):
|
||||
QMessageBox.warning(self, "输入验证失败", "预测结果 CSV 不存在或不是文件")
|
||||
return
|
||||
|
||||
config = self.get_config()
|
||||
parent.run_single_step('step9', {'step9': config})
|
||||
|
||||
def _on_step9_batch_ok(self, n: int):
|
||||
QMessageBox.information(self, "完成", f"已批量生成 {n} 个分布图。")
|
||||
parent = self.parent()
|
||||
while parent and not hasattr(parent, "log_message"):
|
||||
parent = parent.parent()
|
||||
if parent and hasattr(parent, "log_message"):
|
||||
parent.log_message(f"专题图批量完成，共 {n} 个文件。", "info")
|
||||
|
||||
def _on_step9_batch_fail(self, err: str):
|
||||
QMessageBox.critical(self, "失败", f"批量生成中断：\n{err[:900]}")
|
||||
parent = self.parent()
|
||||
while parent and not hasattr(parent, "log_message"):
|
||||
parent = parent.parent()
|
||||
if parent and hasattr(parent, "log_message"):
|
||||
parent.log_message(err, "error")
|
||||
|
||||
Reference in New Issue
Block a user