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feat(gui): 全流程面板合并 + 一键式运行 GUI 入口集成

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DXC
2026-06-09 11:30:42 +08:00
parent aefc9d5aac
commit 28394f2eda
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src/gui/panels/step14_panel.py Normal file
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Step14 面板 - 分布图生成
"""
import os
import traceback
from pathlib import Path
from typing import List, Optional
from PyQt5.QtCore import Qt, QThread, pyqtSignal
from PyQt5.QtWidgets import (
QWidget, QVBoxLayout, QGroupBox, QFormLayout, QHBoxLayout,
QLabel, QCheckBox, QPushButton, QLineEdit, QDoubleSpinBox,
QRadioButton, QButtonGroup, QMessageBox, QFileDialog,
)
from src.gui.components.custom_widgets import FileSelectWidget
from src.gui.styles import ModernStylesheet
# Pipeline 可用性（与 core/worker_thread.py 保持一致）
try:
from src.core.water_quality_inversion_pipeline_GUI import WaterQualityInversionPipeline
PIPELINE_AVAILABLE = True
except ImportError:
PIPELINE_AVAILABLE = False
class Step14BatchThread(QThread):
"""专题图：按文件夹内多个预测 CSV 批量生成分布图。"""
finished_ok = pyqtSignal(int)
failed = pyqtSignal(str)
log_message = pyqtSignal(str, str)
def __init__(self, work_dir: str, csv_paths: List[str], step14_kwargs: dict, output_dir_optional: Optional[str]):
super().__init__()
self.work_dir = work_dir
self.csv_paths = csv_paths
self.step14_kwargs = step14_kwargs
self.output_dir_optional = (output_dir_optional or "").strip() or None
def run(self):
mpl_prev = None
try:
import matplotlib
mpl_prev = matplotlib.get_backend()
except Exception:
pass
try:
import matplotlib.pyplot as plt
plt.switch_backend("Agg")
except Exception:
mpl_prev = None
try:
from src.core.water_quality_inversion_pipeline_GUI import WaterQualityInversionPipeline
pipeline = WaterQualityInversionPipeline(work_dir=self.work_dir)
n = len(self.csv_paths)
for i, csv_p in enumerate(self.csv_paths):
self.log_message.emit(f"专题图 [{i + 1}/{n}] {csv_p}", "info")
kw = {**self.step14_kwargs, "prediction_csv_path": csv_p, "skip_dependency_check": True}
if self.output_dir_optional:
stem = Path(csv_p).stem
kw["output_image_path"] = str(Path(self.output_dir_optional) / f"{stem}_distribution.png")
else:
kw["output_image_path"] = None
pipeline.step9_generate_distribution_map(**kw)
self.finished_ok.emit(n)
except Exception as e:
self.failed.emit(f"{e}\n{traceback.format_exc()}")
finally:
if mpl_prev:
try:
import matplotlib.pyplot as plt
plt.switch_backend(mpl_prev)
except Exception:
pass
class Step14Panel(QWidget):
"""步骤14：分布图生成"""
def __init__(self, parent=None):
super().__init__(parent)
self._batch_thread = None
self.init_ui()
def init_ui(self):
layout = QVBoxLayout()
hint = QLabel(
"独立运行：可选「单个 CSV」或「文件夹批量」（扫描目录下所有 .csv）。"
"完整流程中预测 CSV 由步骤11、12、13 自动传入，无需在此选择。"
)
hint.setWordWrap(True)
hint.setStyleSheet(
f"color: {ModernStylesheet.COLORS.get('text_secondary', '#666')};"
)
layout.addWidget(hint)
mode_row = QHBoxLayout()
self.mode_single_rb = QRadioButton("单个 CSV 文件")
self.mode_folder_rb = QRadioButton("文件夹批量")
self._mode_group = QButtonGroup(self)
self._mode_group.addButton(self.mode_single_rb, 0)
self._mode_group.addButton(self.mode_folder_rb, 1)
mode_row.addWidget(self.mode_single_rb)
mode_row.addWidget(self.mode_folder_rb)
mode_row.addStretch()
layout.addLayout(mode_row)
# ---------- RadioButton 美化样式（选中状态为方形实心块，贴合主界面风格） ----------
radio_style = """
QRadioButton {
font-size: 14px;
spacing: 8px;
color: #333333;
}
QRadioButton::indicator {
width: 16px;
height: 16px;
border: 2px solid #999999;
border-radius: 3px;
background-color: white;
}
QRadioButton::indicator:checked {
border: 2px solid #0078d4;
background-color: #0078d4;
image: none;
}
QRadioButton::indicator:hover {
border: 2px solid #005a9e;
}
"""
self.mode_single_rb.setStyleSheet(radio_style)
self.mode_folder_rb.setStyleSheet(radio_style)
self.prediction_csv_file = FileSelectWidget(
"预测结果CSV:",
"CSV Files (*.csv);;All Files (*.*)"
)
layout.addWidget(self.prediction_csv_file)
folder_row = QHBoxLayout()
self.prediction_csv_dir_label = QLabel("预测CSV目录:")
self.prediction_csv_dir_label.setMinimumWidth(120)
self.prediction_csv_dir_edit = QLineEdit()
self.prediction_csv_dir_edit.setPlaceholderText("选择含多个预测结果 CSV 的文件夹…")
pred_dir_btn = QPushButton("浏览…")
pred_dir_btn.setMaximumWidth(80)
pred_dir_btn.clicked.connect(self.browse_prediction_csv_dir)
folder_row.addWidget(self.prediction_csv_dir_label)
folder_row.addWidget(self.prediction_csv_dir_edit, 1)
folder_row.addWidget(pred_dir_btn)
self._folder_row_widget = QWidget()
self._folder_row_widget.setLayout(folder_row)
layout.addWidget(self._folder_row_widget)
self.recursive_csv_cb = QCheckBox("包含子文件夹（递归扫描 *.csv）")
layout.addWidget(self.recursive_csv_cb)
self.boundary_file = FileSelectWidget(
"边界文件:",
"Shapefiles (*.shp);;All Files (*.*)"
)
layout.addWidget(self.boundary_file)
# 参数设置
params_group = QGroupBox("生成参数")
params_layout = QFormLayout()
self.resolution = QDoubleSpinBox()
self.resolution.setRange(1, 1000)
self.resolution.setValue(30)
params_layout.addRow("分辨率(米):", self.resolution)
self.input_crs = QLineEdit()
self.input_crs.setText("EPSG:32651")
params_layout.addRow("输入坐标系:", self.input_crs)
self.output_crs = QLineEdit()
self.output_crs.setText("EPSG:4326")
params_layout.addRow("输出坐标系:", self.output_crs)
self.show_points = QCheckBox("显示采样点")
params_layout.addRow("", self.show_points)
self.use_diffusion = QCheckBox("启用距离扩散")
self.use_diffusion.setChecked(True)
params_layout.addRow("", self.use_diffusion)
params_group.setLayout(params_layout)
layout.addWidget(params_group)
# 输出目录
self.output_dir = FileSelectWidget(
"输出分布图目录:",
"Directories;;All Files (*.*)"
)
self.output_dir.line_edit.setPlaceholderText("留空→工作目录/14_visualization")
self.output_dir.browse_btn.clicked.disconnect()
self.output_dir.browse_btn.clicked.connect(self.browse_output_dir)
layout.addWidget(self.output_dir)
# 启用步骤
self.enable_checkbox = QCheckBox("启用此步骤")
self.enable_checkbox.setChecked(True)
layout.addWidget(self.enable_checkbox)
# 独立运行按钮
self.run_button = QPushButton("独立运行此步骤")
self.run_button.setStyleSheet(ModernStylesheet.get_button_stylesheet('success'))
self.run_button.clicked.connect(self.run_step)
layout.addWidget(self.run_button)
layout.addStretch()
self.setLayout(layout)
# 信号绑定与初始状态
self.mode_single_rb.toggled.connect(self._toggle_input_mode)
self.mode_folder_rb.toggled.connect(self._toggle_input_mode)
self.mode_single_rb.setChecked(True) # 默认选中"单个 CSV"
self._toggle_input_mode() # 根据默认值设置初始显示状态
def _toggle_input_mode(self):
"""槽函数：根据单选框状态动态显示/隐藏对应的输入组件。"""
folder_mode = self.mode_folder_rb.isChecked()
# 单个 CSV 模式：显示单文件选择，隐藏文件夹选择
self.prediction_csv_file.setVisible(not folder_mode)
# 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
self._folder_row_widget.setVisible(folder_mode)
self.recursive_csv_cb.setVisible(folder_mode)
def _get_default_work_dir(self):
"""获取 work_dir，优先用 panel 自身缓存的，否则尝试从主窗口取"""
if hasattr(self, 'work_dir') and self.work_dir:
return str(self.work_dir)
mw = self.window()
if mw and hasattr(mw, 'work_dir') and mw.work_dir:
return str(mw.work_dir)
return ""
def browse_prediction_csv_dir(self):
default = self._get_default_work_dir()
if default:
default = os.path.join(default, "11_12_13_predictions")
d = QFileDialog.getExistingDirectory(self, "选择预测结果 CSV 所在文件夹", default)
if d:
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 []
root = Path(folder)
if self.recursive_csv_cb.isChecked():
files = sorted(root.rglob("*.csv"))
else:
files = sorted(root.glob("*.csv"))
return [str(p) for p in 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()
config = {
'step14_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(),
}
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)
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))
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)
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:
# 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
# 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:
# 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。")
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_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.run_button.setEnabled(False)
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)
self._batch_thread.log_message.connect(_batch_log, 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), 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('step14', {'step14': config})
def _on_step14_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_step14_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")