DXC
2261b4b30e
- 9 个面板（step1~step6/step8_ml_train/step8_qaa/step9_ml_predict/step10）单步执行按钮从 parent 链上溯改为 global_event_bus.publish('RequestRunSingleStep')
- PipelineExecutor 新增 _on_request_run_single_step 订阅
- 新增 Handler: step8_ml_train / step9_ml_predict / step10_qaa_inversion / step11_concentration / step12_kriging / step13_visualization / step14_report
- 删除旧 water_quality_inversion_pipeline_GUI.py（上帝类已肢解完毕）
337 lines
12 KiB
Python
337 lines
12 KiB
Python
#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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"""
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Step8 面板 - QAA 物理反演（非经验模型）
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"""
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import os
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import sys
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# 路径归一化 helper（与 pipeline.get_step_output_dir 互为表里）
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_HERE = os.path.dirname(os.path.abspath(__file__))
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if _HERE not in sys.path:
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sys.path.insert(0, _HERE)
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from _step_path_resolver import resolve_subdir
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from PyQt5.QtWidgets import (
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QWidget, QVBoxLayout, QGroupBox, QFormLayout, QGridLayout,
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QHBoxLayout, QLabel, QLineEdit, QComboBox, QCheckBox,
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QPushButton, QFileDialog, QMessageBox,
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)
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from PyQt5.QtGui import QFont
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from PyQt5.QtCore import Qt
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from src.gui.components.custom_widgets import FileSelectWidget
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from src.gui.styles import ModernStylesheet
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from src.utils.water_owt_config import (
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get_all_lake_names,
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get_lake_config,
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get_lambda_0,
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get_default_lake,
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)
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from src.core.algorithms.qaa import QAABaselineSolver
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class Step8QAAPanel(QWidget):
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"""步骤8：QAA 物理反演（非经验模型）"""
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def __init__(self, parent=None):
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super().__init__(parent)
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self.init_ui()
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def init_ui(self):
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layout = QVBoxLayout()
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title = QLabel("步骤8：QAA 物理反演（非经验模型）")
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title.setFont(QFont("Arial", 12, QFont.Bold))
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layout.addWidget(title)
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# 光谱 CSV 文件输入
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self.spectrum_csv_file = FileSelectWidget(
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"光谱 CSV 文件:",
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"CSV Files (*.csv);;All Files (*.*)"
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)
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self.spectrum_csv_file.line_edit.setPlaceholderText(
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"选择实测光谱或采样点光谱 CSV（含波长列）"
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)
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layout.addWidget(self.spectrum_csv_file)
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# 水域类型选择
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lake_group = QGroupBox("水域类型配置")
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lake_layout = QFormLayout()
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self.lake_combo = QComboBox()
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lake_names = get_all_lake_names()
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self.lake_combo.addItems(lake_names)
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default_lake = get_default_lake()
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if default_lake in lake_names:
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self.lake_combo.setCurrentText(default_lake)
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self.lake_combo.currentTextChanged.connect(self._on_lake_changed)
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lake_layout.addRow("水域选择:", self.lake_combo)
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# 参考波长显示
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self.lambda_0_label = QLabel()
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self.lambda_0_label.setStyleSheet(
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f"color: {ModernStylesheet.COLORS['accent']}; "
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f"font-weight: bold;"
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)
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lake_layout.addRow("参考波长 λ₀:", self.lambda_0_label)
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# 算法提示
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self.hint_label = QLabel()
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self.hint_label.setWordWrap(True)
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self.hint_label.setStyleSheet(
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f"color: {ModernStylesheet.COLORS['text_secondary']}; "
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"font-size: 12px;"
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)
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lake_layout.addRow("算法提示:", self.hint_label)
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lake_group.setLayout(lake_layout)
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layout.addWidget(lake_group)
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# 输出路径
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self.output_path = FileSelectWidget(
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"输出文件:",
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"CSV Files (*.csv);;All Files (*.*)",
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mode="save"
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)
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self.output_path.line_edit.setPlaceholderText(
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"自动生成到 8_QAA_Inversion，或手动指定..."
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)
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self.output_path.browse_btn.clicked.disconnect()
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self.output_path.browse_btn.clicked.connect(self.browse_output_path)
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layout.addWidget(self.output_path)
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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(False)
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layout.addWidget(self.enable_checkbox)
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# 独立运行按钮
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self.run_btn = QPushButton("执行 QAA 反演")
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self.run_btn.setStyleSheet(ModernStylesheet.get_button_stylesheet('success'))
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self.run_btn.clicked.connect(self._on_run_single_clicked)
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layout.addWidget(self.run_btn)
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layout.addStretch()
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self.setLayout(layout)
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self._on_lake_changed(self.lake_combo.currentText())
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def _on_lake_changed(self, lake_name: str):
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"""当用户切换水域时更新显示"""
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cfg = get_lake_config(lake_name)
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if cfg:
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self.lambda_0_label.setText(
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f"{cfg['lambda_0']} nm（{cfg['qaa_version']}）"
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)
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self.hint_label.setText(cfg.get('notes', ''))
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else:
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self.lambda_0_label.setText("—")
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self.hint_label.setText("")
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def _get_default_work_dir(self) -> str:
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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_output_path(self):
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"""浏览输出文件路径"""
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current = self.output_path.get_path().strip()
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if current:
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initial_dir = os.path.dirname(current)
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initial_file = os.path.basename(current)
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else:
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initial_dir = ""
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initial_file = ""
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if not initial_dir or not os.path.isdir(initial_dir):
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work_dir = self._get_default_work_dir()
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initial_dir = resolve_subdir(work_dir, 'qaa_inversion') if work_dir else ""
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if initial_dir and not os.path.isdir(initial_dir):
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os.makedirs(initial_dir, exist_ok=True)
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file_path, _ = QFileDialog.getSaveFileName(
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self, "保存输出文件",
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os.path.join(initial_dir, initial_file) if initial_file else initial_dir,
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"CSV Files (*.csv);;All Files (*.*)"
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)
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if file_path:
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self.output_path.set_path(file_path)
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def get_config(self) -> dict:
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"""获取面板配置"""
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config = {
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'lake_name': self.lake_combo.currentText(),
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'lambda_0': get_lambda_0(self.lake_combo.currentText()),
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'spectrum_csv_path': self.spectrum_csv_file.get_path(),
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}
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output_path = self.output_path.get_path()
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if output_path:
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config['output_path'] = output_path
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return config
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def set_config(self, config: dict):
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"""设置面板配置"""
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if 'lake_name' in config:
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lake_name = config['lake_name']
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idx = self.lake_combo.findText(lake_name)
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if idx >= 0:
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self.lake_combo.setCurrentIndex(idx)
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if 'spectrum_csv_path' in config:
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self.spectrum_csv_file.set_path(config['spectrum_csv_path'])
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if 'output_path' in config:
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self.output_path.set_path(config['output_path'])
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def update_from_config(self, work_dir=None, pipeline=None):
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"""从全局配置自动填充训练数据和输出路径"""
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if work_dir:
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self.work_dir = work_dir
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elif hasattr(self, 'work_dir') and self.work_dir:
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pass
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else:
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self.work_dir = None
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main_window = self.window()
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if main_window and hasattr(main_window, 'step5_panel'):
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step5_output = main_window.step5_panel.output_file.get_path()
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if step5_output:
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if not os.path.isabs(step5_output):
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step5_output = os.path.join(self.work_dir or '', step5_output).replace('\\', '/')
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self.spectrum_csv_file.set_path(step5_output)
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if self.work_dir:
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qaa_dir = resolve_subdir(self.work_dir, 'qaa_inversion')
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os.makedirs(qaa_dir, exist_ok=True)
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output_path = os.path.join(qaa_dir, "a_lambda_results.csv").replace('\\', '/')
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self.output_path.set_path(output_path)
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else:
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self.output_path.set_path("")
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def _on_run_single_clicked(self):
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"""通过 EventBus 发布单步执行请求（解耦面板与 PipelineExecutor）。"""
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from src.gui.core.event_bus import global_event_bus
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spectrum_path = self.spectrum_csv_file.get_path()
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if not spectrum_path:
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QMessageBox.warning(self, "输入错误", "请选择光谱 CSV 文件！")
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return
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config = {'step8_qaa': self.get_config()}
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global_event_bus.publish('RequestRunSingleStep', {
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'step_name': 'step8_qaa',
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'config': config,
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})
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def run_step(self):
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"""独立运行 QAA 反演（旧版 parent 链上溯方式，保留兼容）。"""
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spectrum_path = self.spectrum_csv_file.get_path()
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if not spectrum_path:
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QMessageBox.warning(self, "输入错误", "请选择光谱 CSV 文件！")
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return
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main_window = self.window()
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if hasattr(main_window, 'run_single_step'):
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config = {'step8_qaa': self.get_config()}
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main_window.run_single_step('step8_qaa', config)
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else:
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self._run_qaa_direct()
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def _run_qaa_direct(self):
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"""直接执行 QAA 反演（不依赖主窗口流水线）"""
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spectrum_path = self.spectrum_csv_file.get_path()
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output_path = self.output_path.get_path()
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lake_name = self.lake_combo.currentText()
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lambda_0 = get_lambda_0(lake_name)
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if not output_path:
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work_dir = self._get_default_work_dir()
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qaa_dir = resolve_subdir(work_dir, 'qaa_inversion') if work_dir else ""
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if qaa_dir and not os.path.isdir(qaa_dir):
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os.makedirs(qaa_dir, exist_ok=True)
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output_path = os.path.join(qaa_dir, "a_lambda_results.csv").replace('\\', '/')
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try:
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import numpy as np
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import pandas as pd
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df = pd.read_csv(spectrum_path, encoding="utf-8-sig")
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col_names = df.columns.tolist()
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wavelength_col_idx = None
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for i, col in enumerate(col_names):
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try:
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float(col)
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wavelength_col_idx = i
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break
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except (ValueError, TypeError):
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pass
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if wavelength_col_idx is None:
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QMessageBox.warning(
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self, "解析错误",
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"无法从 CSV 列名中识别波长信息，请确保列名包含数值型波长（nm）"
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)
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return
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wavelengths = np.array(
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[float(c) for c in col_names[wavelength_col_idx:]], dtype=np.float64
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)
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data_matrix = df.iloc[:, wavelength_col_idx:].values.astype(np.float64)
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if data_matrix.ndim == 1:
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data_matrix = data_matrix[np.newaxis, :]
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solver = QAABaselineSolver()
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raw_result = solver.run_inversion(wavelengths, data_matrix, lambda_0)
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# run_inversion 返回：单样本 → dict，多样本 → list[dict]
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if isinstance(raw_result, list):
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sample_results = raw_result
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aw_0 = raw_result[0].get('aw_0', 0)
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bbw_0 = raw_result[0].get('bbw_0', 0)
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else:
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sample_results = [raw_result]
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aw_0 = raw_result.get('aw_0', 0)
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bbw_0 = raw_result.get('bbw_0', 0)
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rows_out = []
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for i, sample_result in enumerate(sample_results):
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wl_arr = wavelengths
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a_arr = sample_result['a_lambda']
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bb_arr = sample_result['bb_lambda']
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for j, wl in enumerate(wl_arr):
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rows_out.append({
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'sample_id': f"sample_{i}",
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'Wavelength': wl,
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'a_lambda': a_arr[j],
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'bb_lambda': bb_arr[j],
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})
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result_df = pd.DataFrame(rows_out)
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os.makedirs(os.path.dirname(output_path) or '.', exist_ok=True)
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result_df.to_csv(output_path, index=False, float_format='%.8f')
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QMessageBox.information(
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self, "执行成功",
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f"QAA 反演完成！\n"
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f"水域: {lake_name}\n"
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f"参考波长 λ₀: {lambda_0} nm\n"
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f"λ₀ 处 aw: {aw_0:.6f} m⁻¹\n"
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f"λ₀ 处 bbw: {bbw_0:.6f} m⁻¹\n"
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f"结果已保存到:\n{output_path}"
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)
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except Exception as e:
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QMessageBox.critical(self, "执行错误", f"QAA 反演失败:\n{str(e)}")
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def get_training_params(self) -> dict:
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"""获取反演参数"""
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return {
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'pipeline_type': 'qaa_non_empirical',
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'lake_name': self.lake_combo.currentText(),
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'lambda_0': get_lambda_0(self.lake_combo.currentText()),
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} |