827 lines
36 KiB
Python
827 lines
36 KiB
Python
#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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"""
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Step14 面板 - 分布图生成
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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 PyQt5.QtCore import Qt, QThread, pyqtSignal
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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, QComboBox,
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QProgressBar,
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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 Step14BatchThread(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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progress = pyqtSignal(int, int) # (current, total)
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def __init__(self, work_dir: str, csv_paths: List[str], step14_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.step14_kwargs = step14_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.progress.emit(i + 1, n)
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self.log_message.emit(f"专题图 [{i + 1}/{n}] {csv_p}", "info")
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kw = {**self.step14_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.step10_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 Step14GeoTIFFBatchThread(QThread):
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"""GeoTIFF 批量渲染：遍历文件夹下所有 .tif/.bsq 逐一渲染成分布图 PNG。"""
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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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progress = pyqtSignal(int, int) # (current, total)
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def __init__(
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self,
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tif_paths: List[str],
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output_dir: str,
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boundary_shp_path: Optional[str],
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input_crs: str,
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output_crs: str,
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):
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super().__init__()
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self.tif_paths = tif_paths
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self.output_dir = output_dir
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self.boundary_shp_path = boundary_shp_path
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self.input_crs = input_crs
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self.output_crs = output_crs
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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.postprocessing.map import ContentMapper
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mapper = ContentMapper()
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n = len(self.tif_paths)
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for i, tif_path in enumerate(self.tif_paths):
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self.progress.emit(i + 1, n)
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tif_stem = Path(tif_path).stem
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chinese_name = mapper._get_chinese_title(tif_stem)
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output_png = str(Path(self.output_dir) / f"{chinese_name}_专题图.png")
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self.log_message.emit(f"GeoTIFF 渲染 [{i + 1}/{n}] {tif_stem}", "info")
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try:
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mapper.visualize_raster(
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raster_tif_path=tif_path,
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output_file=output_png,
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boundary_shp_path=self.boundary_shp_path,
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nodata_value=-9999.0,
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figsize=(14, 10),
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alpha=0.9,
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)
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except Exception as vis_err:
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self.log_message.emit(f" ⚠️ 渲染失败，跳过: {vis_err}", "warning")
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continue
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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 Step14Panel(QWidget):
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"""步骤14：分布图生成"""
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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.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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"GeoTIFF 栅格模式下，亦支持批量渲染步骤8输出的所有水色指数 GeoTIFF 文件。"
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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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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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# ---------- 渲染模式选择器（CSV vs GeoTIFF） ----------
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render_row = QHBoxLayout()
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render_row.addWidget(QLabel("渲染模式:"))
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self.render_mode_combo = QComboBox()
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self.render_mode_combo.addItems(["CSV 插值模式", "GeoTIFF 栅格模式"])
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self.render_mode_combo.setMinimumWidth(180)
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self.render_mode_combo.currentTextChanged.connect(self._toggle_input_mode)
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render_row.addWidget(self.render_mode_combo)
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render_row.addStretch()
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layout.addLayout(render_row)
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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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"CSV Files (*.csv);;All Files (*.*)"
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)
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layout.addWidget(self.prediction_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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# ---------- GeoTIFF 栅格文件选择器 ----------
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self.geotiff_file = FileSelectWidget(
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"水色指数 GeoTIFF:",
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"GeoTIFF Files (*.tif);;All Files (*.*)"
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)
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self.geotiff_file.line_edit.setPlaceholderText("选择步骤8输出的水色指数 GeoTIFF 文件…")
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self.geotiff_file.setVisible(False)
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layout.addWidget(self.geotiff_file)
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# ---------- GeoTIFF 文件夹批量选择器（GeoTIFF + 文件夹模式时显示） ----------
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geotiff_dir_row = QHBoxLayout()
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self.geotiff_dir_label = QLabel("水色指数目录:")
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self.geotiff_dir_label.setMinimumWidth(120)
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self.geotiff_dir_edit = QLineEdit()
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self.geotiff_dir_edit.setPlaceholderText("选择 10_WaterIndex_Images 文件夹（批量渲染）…")
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geotiff_dir_btn = QPushButton("浏览…")
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geotiff_dir_btn.setMaximumWidth(80)
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geotiff_dir_btn.clicked.connect(self.browse_geotiff_dir)
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geotiff_dir_row.addWidget(self.geotiff_dir_label)
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geotiff_dir_row.addWidget(self.geotiff_dir_edit, 1)
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geotiff_dir_row.addWidget(geotiff_dir_btn)
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self._geotiff_dir_widget = QWidget()
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self._geotiff_dir_widget.setLayout(geotiff_dir_row)
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self._geotiff_dir_widget.setVisible(False)
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layout.addWidget(self._geotiff_dir_widget)
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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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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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# 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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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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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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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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self.show_points = QCheckBox("显示采样点")
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params_layout.addRow("", self.show_points)
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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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params_group.setLayout(params_layout)
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layout.addWidget(params_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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# 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_button = QPushButton("独立运行此步骤")
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self.run_button.setStyleSheet(ModernStylesheet.get_button_stylesheet('success'))
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self.run_button.clicked.connect(self.run_step)
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layout.addWidget(self.run_button)
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# 批量渲染进度条
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self.progress_bar = QProgressBar()
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self.progress_bar.setVisible(False)
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self.progress_bar.setMinimum(0)
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self.progress_bar.setMaximum(100)
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self.progress_bar.setValue(0)
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layout.addWidget(self.progress_bar)
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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_input_mode(self):
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"""槽函数：根据渲染模式和输入模式动态显示/隐藏对应的输入组件。"""
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geotiff_mode = self.render_mode_combo.currentText() == "GeoTIFF 栅格模式"
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folder_mode = self.mode_folder_rb.isChecked()
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# CSV 插值模式
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if not geotiff_mode:
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self.prediction_csv_file.setVisible(not folder_mode)
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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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self.geotiff_file.setVisible(False)
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self._geotiff_dir_widget.setVisible(False)
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# GeoTIFF 栅格模式
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else:
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self.prediction_csv_file.setVisible(False)
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self._folder_row_widget.setVisible(False)
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self.recursive_csv_cb.setVisible(False)
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||
# GeoTIFF + 文件夹批量 → 显示文件夹选择器；否则 → 显示单文件选择器
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self.geotiff_file.setVisible(not folder_mode)
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self._geotiff_dir_widget.setVisible(folder_mode)
|
||
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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_prediction_csv_dir(self):
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||
default = self._get_default_work_dir()
|
||
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)
|
||
if d:
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self.prediction_csv_dir_edit.setText(d)
|
||
|
||
def _collect_csv_paths_from_folder(self) -> List[str]:
|
||
folder = (self.prediction_csv_dir_edit.text() or "").strip()
|
||
if not folder or not os.path.isdir(folder):
|
||
return []
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||
root = Path(folder)
|
||
if self.recursive_csv_cb.isChecked():
|
||
files = sorted(root.rglob("*.csv"))
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||
else:
|
||
files = sorted(root.glob("*.csv"))
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||
return [str(p) for p in files if p.is_file()]
|
||
|
||
def browse_geotiff_dir(self):
|
||
"""浏览 GeoTIFF 文件夹（批量模式）"""
|
||
default = self._get_default_work_dir()
|
||
if default:
|
||
default = os.path.join(default, "10_WaterIndex_Images")
|
||
d = QFileDialog.getExistingDirectory(
|
||
self, "选择水色指数 GeoTIFF 文件夹", default
|
||
)
|
||
if d:
|
||
self.geotiff_dir_edit.setText(d)
|
||
|
||
def _collect_tif_paths_from_folder(self) -> List[str]:
|
||
"""扫描所选文件夹，收集所有 .tif 和 .bsq 文件路径"""
|
||
folder = (self.geotiff_dir_edit.text() or "").strip()
|
||
if not folder or not os.path.isdir(folder):
|
||
return []
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||
root = Path(folder)
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||
tif_files = sorted(root.glob("*.tif"))
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||
bsq_files = sorted(root.glob("*.bsq"))
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||
return [str(p) for p in tif_files + bsq_files if p.is_file()]
|
||
|
||
def _step14_base_pipeline_kwargs(self) -> dict:
|
||
return {
|
||
'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(),
|
||
}
|
||
|
||
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()
|
||
geotiff_path = (self.geotiff_file.get_path() or "").strip()
|
||
config = {
|
||
'step14_batch_mode': 'folder' if folder_mode else 'single',
|
||
'render_mode': self.render_mode_combo.currentText(),
|
||
'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),
|
||
'geotiff_path': geotiff_path if geotiff_path else None,
|
||
'geotiff_dir': (self.geotiff_dir_edit.text() or "").strip() or 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(),
|
||
}
|
||
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('step14_batch_mode', 'single')
|
||
if mode == 'folder':
|
||
self.mode_folder_rb.setChecked(True)
|
||
else:
|
||
self.mode_single_rb.setChecked(True)
|
||
render_mode = config.get('render_mode', 'CSV 插值模式')
|
||
idx = self.render_mode_combo.findText(render_mode)
|
||
if idx >= 0:
|
||
self.render_mode_combo.setCurrentIndex(idx)
|
||
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 'geotiff_path' in config and config['geotiff_path']:
|
||
self.geotiff_file.set_path(str(config['geotiff_path']))
|
||
if 'geotiff_dir' in config and config['geotiff_dir']:
|
||
self.geotiff_dir_edit.setText(str(config['geotiff_dir']))
|
||
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))
|
||
|
||
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。
|
||
|
||
Args:
|
||
work_dir: 工作目录路径
|
||
pipeline: Pipeline 实例（未使用，保留接口兼容性）
|
||
"""
|
||
try:
|
||
import traceback
|
||
|
||
if work_dir:
|
||
self.work_dir = work_dir
|
||
elif hasattr(self, 'work_dir') and self.work_dir:
|
||
pass
|
||
else:
|
||
self.work_dir = None
|
||
|
||
main_window = self.window()
|
||
if not main_window:
|
||
return
|
||
|
||
# 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, 'step11_prediction_panel'):
|
||
step8_widget = getattr(main_window.step11_prediction_panel, 'output_file', None)
|
||
step10_output = ""
|
||
if hasattr(step8_widget, 'get_path'):
|
||
step10_output = step8_widget.get_path() or ""
|
||
elif hasattr(step8_widget, 'text'):
|
||
step10_output = step8_widget.text() or ""
|
||
|
||
if step10_output:
|
||
# 若为相对路径，使用 work_dir 合成为绝对路径
|
||
if not os.path.isabs(step10_output):
|
||
step10_output = os.path.join(self.work_dir or '', step10_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(step10_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
|
||
|
||
# 2. 备选：从 Step11 界面读取非经验预测输出目录
|
||
if not pred_dir and hasattr(main_window, 'step11_panel'):
|
||
step8_5_widget = getattr(main_window.step11_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 Step12 界面读取自定义回归预测输出目录
|
||
if not pred_dir and hasattr(main_window, 'step12_panel'):
|
||
step8_75_widget = getattr(main_window.step12_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）
|
||
if self.work_dir:
|
||
output_dir = os.path.join(self.work_dir, "14_visualization")
|
||
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:
|
||
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。")
|
||
|
||
# 6. 自动探测 Step 8 输出的水色指数 GeoTIFF（GeoTIFF 渲染模式）
|
||
step10_out_dir = Path(self.work_dir) / "10_WaterIndex_Images" if self.work_dir else None
|
||
if step10_out_dir and step10_out_dir.is_dir():
|
||
# GeoTIFF 批量模式：填充目录供批量渲染
|
||
if not (self.geotiff_dir_edit.text() or "").strip():
|
||
self.geotiff_dir_edit.setText(str(step10_out_dir))
|
||
# GeoTIFF 单文件模式：默认选中第一个
|
||
tif_files = sorted(step10_out_dir.glob("*.tif"))
|
||
if tif_files and not (self.geotiff_file.get_path() or "").strip():
|
||
self.geotiff_file.set_path(str(tif_files[0]))
|
||
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 _start_batch_run(self, csv_list, work_dir, base_kw, out_dir_opt, parent):
|
||
"""封装 CSV 批量启动逻辑，统一处理信号连接和进度条"""
|
||
self.run_button.setEnabled(False)
|
||
self.progress_bar.setVisible(True)
|
||
self.progress_bar.setValue(0)
|
||
self._batch_thread = Step14BatchThread(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)
|
||
|
||
def _on_progress(cur, total):
|
||
if total > 0:
|
||
self.progress_bar.setMaximum(total)
|
||
self.progress_bar.setValue(cur)
|
||
self.progress_bar.setFormat(f"{cur}/{total} 张 (%p%)")
|
||
|
||
self._batch_thread.log_message.connect(_batch_log, Qt.QueuedConnection)
|
||
self._batch_thread.progress.connect(_on_progress, Qt.QueuedConnection)
|
||
self._batch_thread.finished_ok.connect(self._on_step14_batch_ok, Qt.QueuedConnection)
|
||
self._batch_thread.failed.connect(self._on_step14_batch_fail, Qt.QueuedConnection)
|
||
self._batch_thread.finished.connect(
|
||
lambda: (self.run_button.setEnabled(True), self.progress_bar.setVisible(False)),
|
||
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")
|
||
|
||
def run_step(self):
|
||
"""独立运行步骤14"""
|
||
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。")
|
||
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")
|
||
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")
|
||
return
|
||
|
||
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'):
|
||
QMessageBox.critical(self, "错误", "无法找到父级GUI对象")
|
||
return
|
||
|
||
if self.mode_folder_rb.isChecked():
|
||
# -------- CSV 插值批量 --------
|
||
if self.render_mode_combo.currentText() != "GeoTIFF 栅格模式":
|
||
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._step14_base_pipeline_kwargs()
|
||
out_dir_opt = (self.output_dir.get_path() or "").strip() or None
|
||
self._start_batch_run(csv_list, work_dir, base_kw, out_dir_opt, parent)
|
||
return
|
||
|
||
# -------- GeoTIFF 栅格批量 --------
|
||
tif_list = self._collect_tif_paths_from_folder()
|
||
if not tif_list:
|
||
QMessageBox.warning(
|
||
self,
|
||
"输入验证失败",
|
||
"所选文件夹中未找到 .tif / .bsq 文件，\n"
|
||
"请确认目录包含步骤8输出的水色指数 GeoTIFF 文件。",
|
||
)
|
||
return
|
||
|
||
out_dir = (self.output_dir.get_path() or "").strip()
|
||
if not out_dir:
|
||
out_dir = os.path.join(self._get_default_work_dir(), "14_visualization")
|
||
os.makedirs(out_dir, exist_ok=True)
|
||
|
||
self.run_button.setEnabled(False)
|
||
self.progress_bar.setVisible(True)
|
||
self.progress_bar.setValue(0)
|
||
self._batch_thread = Step14GeoTIFFBatchThread(
|
||
tif_paths=tif_list,
|
||
output_dir=out_dir,
|
||
boundary_shp_path=boundary_shp_path,
|
||
input_crs=self.input_crs.text(),
|
||
output_crs=self.output_crs.text(),
|
||
)
|
||
main_win = parent
|
||
|
||
def _batch_log(msg, lvl):
|
||
if hasattr(main_win, "log_message"):
|
||
main_win.log_message(msg, lvl)
|
||
|
||
def _on_progress(cur, total):
|
||
if total > 0:
|
||
pct = int(cur / total * 100)
|
||
self.progress_bar.setMaximum(total)
|
||
self.progress_bar.setValue(cur)
|
||
self.progress_bar.setFormat(f"{cur}/{total} 张 (%p%)")
|
||
|
||
self._batch_thread.log_message.connect(_batch_log, Qt.QueuedConnection)
|
||
self._batch_thread.progress.connect(_on_progress, Qt.QueuedConnection)
|
||
self._batch_thread.finished_ok.connect(self._on_step14_batch_ok, Qt.QueuedConnection)
|
||
self._batch_thread.failed.connect(self._on_step14_batch_fail, Qt.QueuedConnection)
|
||
self._batch_thread.finished.connect(
|
||
lambda: (self.run_button.setEnabled(True), self.progress_bar.setVisible(False)),
|
||
Qt.QueuedConnection,
|
||
)
|
||
self._batch_thread.start()
|
||
if hasattr(parent, "log_message"):
|
||
parent.log_message(f"GeoTIFF 批量渲染：共 {len(tif_list)} 个文件 → {out_dir}", "info")
|
||
return
|
||
|
||
# -------- GeoTIFF 栅格单文件模式 --------
|
||
if self.render_mode_combo.currentText() == "GeoTIFF 栅格模式":
|
||
geotiff_path = (self.geotiff_file.get_path() or "").strip()
|
||
if not geotiff_path:
|
||
QMessageBox.warning(self, "输入验证失败", "请选择水色指数 GeoTIFF 文件")
|
||
return
|
||
if not os.path.isfile(geotiff_path):
|
||
QMessageBox.warning(self, "输入验证失败", f"GeoTIFF 文件不存在:\n{geotiff_path}")
|
||
return
|
||
|
||
boundary_shp_path = self.boundary_file.get_path()
|
||
input_crs = self.input_crs.text()
|
||
output_crs = self.output_crs.text()
|
||
|
||
# 构造输出路径
|
||
out_dir = (self.output_dir.get_path() or "").strip()
|
||
if not out_dir:
|
||
out_dir = os.path.join(self._get_default_work_dir(), "14_visualization")
|
||
os.makedirs(out_dir, exist_ok=True)
|
||
tif_stem = Path(geotiff_path).stem
|
||
chinese_name = mapper._get_chinese_title(tif_stem)
|
||
output_png = os.path.join(out_dir, f"{chinese_name}_专题图.png")
|
||
|
||
self.run_button.setEnabled(False)
|
||
try:
|
||
from src.postprocessing.map import ContentMapper
|
||
mapper = ContentMapper()
|
||
result_path = mapper.visualize_raster(
|
||
raster_tif_path=geotiff_path,
|
||
output_file=output_png,
|
||
boundary_shp_path=boundary_shp_path if boundary_shp_path else None,
|
||
nodata_value=-9999.0,
|
||
figsize=(14, 10),
|
||
alpha=0.9,
|
||
)
|
||
self.run_button.setEnabled(True)
|
||
QMessageBox.information(
|
||
self, "完成",
|
||
f"GeoTIFF 栅格渲染完成！\n{result_path}"
|
||
)
|
||
if hasattr(parent, "log_message"):
|
||
parent.log_message(f"Step14 GeoTIFF 渲染完成 → {result_path}", "info")
|
||
except Exception as e:
|
||
self.run_button.setEnabled(True)
|
||
QMessageBox.critical(self, "渲染失败", f"{e}\n{traceback.format_exc()[:500]}")
|
||
if hasattr(parent, "log_message"):
|
||
parent.log_message(str(e), "error")
|
||
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('step14', {'step14': config})
|
||
|
||
def _on_step14_batch_ok(self, n: int):
|
||
self.progress_bar.setVisible(False)
|
||
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_step14_batch_fail(self, err: str):
|
||
self.progress_bar.setVisible(False)
|
||
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")
|