fix: 全局UX修复与Step4交互可视化重构
=== 自动填入过于激进（幽灵路径级联）=== - 所有面板 update_from_config 移除 os.makedirs()，目录创建留给 pipeline 执行 - 输出路径仅 widget 为空时填入默认值，不覆盖用户已选 - 输入路径从上游读取后添加 os.path.exists() 检查，阻断幽灵路径级联 - panel_factory._replay_live_panel_inputs 广播前校验文件确实存在 - step10 update_from_config 添加 os.path.isfile() 存在性检查 - 清理 step8/9/11 中冗余局部 import os（修复 UnboundLocalError） === 输出目录缺失 === - step7 新增 output_file FileSelectWidget，默认路径 7_Water_Quality_Indices/ - step9 output_file 从文件模式改为目录模式 (Directories) === 空目录自动创建 === - step12 _setup_prediction_output_dirs 移除 mkdir() 调用，改为只读日志 === 过期依赖与缺失 import === - panel_registry Step10 依赖 bsq_file→sampling_csv_file（匹配 CSV 模式重构） - step7 添加缺失的 import pandas as pd（修复 NameError） === 导航与 UI 一致性 === - water_quality_gui_v2 新增 _select_first_nav_item()，启动时默认选中第一项 - step1 输出卡片对齐 step8 风格 - step8 补充缺失的样式表和统一边距 === Step4 交互式光谱探针重构 === - 左右分栏 QSplitter 布局：左侧控制区 + 右侧 Matplotlib 视图 - 1x2 子图：ax1 散点图 + ax2 光谱曲线 - Hover 悬停 Annotation 显示坐标，Click 点击高亮+绘制光谱 - NavigationToolbar2QT 工具栏（保存/缩放/平移） - 自动检测坐标列和波段列，完善异常处理
This commit is contained in:
duxin
@ -1,13 +1,22 @@
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#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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"""
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Step4 面板 - 采样点布设 (已移除“启用此步骤”)
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Step4 面板 - 采样点布设（内嵌交互式光谱探针视图）
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2026-06-30 重构：
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- 左右分栏布局 (QSplitter)：左侧控制区 + 右侧嵌入式 Matplotlib 视图
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- 1×2 子图：ax1 散点图 + ax2 光谱曲线
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- Hover 悬停显示坐标提示，Click 点击绘制该点光谱曲线
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- NavigationToolbar2QT 工具栏自带保存/缩放/平移
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"""
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import os
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import sys
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from pathlib import Path
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import numpy as np
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import pandas as pd
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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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@ -16,9 +25,16 @@ from _step_path_resolver import resolve_subdir
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from PyQt5.QtCore import QTimer, Qt
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from PyQt5.QtWidgets import (
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QWidget, QVBoxLayout, QHBoxLayout, QGroupBox, QFormLayout,
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QPushButton, QSpinBox, QMessageBox, QLabel, QFrame
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QPushButton, QSpinBox, QCheckBox, QMessageBox, QLabel, QFrame,
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QSplitter, QSizePolicy,
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)
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from matplotlib.backends.backend_qt5agg import (
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FigureCanvasQTAgg as FigureCanvas,
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NavigationToolbar2QT as NavigationToolbar,
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)
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from matplotlib.figure import Figure
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from src.gui.components.custom_widgets import FileSelectWidget
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from src.gui.dialogs import SamplingViewerDialog
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from src.gui.styles import ModernStylesheet
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@ -27,15 +43,39 @@ from src.gui.styles import ModernStylesheet
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class Step4SamplingPanel(QWidget):
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def __init__(self, parent=None):
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super().__init__(parent)
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# 交互状态
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self._df = None
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self._x_col = None
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self._y_col = None
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self._band_cols = []
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self._scatter = None
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self._highlight_idx = None
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self._annot = None
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self._cid_hover = None
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self._cid_click = None
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self._last_render_path = None
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self.init_ui()
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# ═══════════════════════════════════════════════════════════════
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# UI 构建
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# ═══════════════════════════════════════════════════════════════
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def init_ui(self):
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self.setStyleSheet(ModernStylesheet.get_main_stylesheet())
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main_layout = QVBoxLayout()
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main_layout.setContentsMargins(24, 24, 24, 24)
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main_layout.setSpacing(20)
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# ── 顶层：水平分栏 (QSplitter) ──
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splitter = QSplitter(Qt.Horizontal)
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splitter.setChildrenCollapsible(False)
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# ═══════════════════════════════════════════════
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# 左侧：控制区（原封保留原有三张卡片）
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# ═══════════════════════════════════════════════
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left_widget = QWidget()
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left_layout = QVBoxLayout()
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left_layout.setContentsMargins(24, 24, 12, 24)
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left_layout.setSpacing(20)
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# --- 卡片 1：输入数据 ---
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input_group = QGroupBox("📁 输入数据")
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input_layout = QVBoxLayout()
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input_layout.setSpacing(16)
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@ -52,8 +92,9 @@ class Step4SamplingPanel(QWidget):
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input_layout.addWidget(self.deglint_img_file)
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input_layout.addWidget(self.water_mask_file)
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input_group.setLayout(input_layout)
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main_layout.addWidget(input_group)
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left_layout.addWidget(input_group)
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# --- 卡片 2：采样参数 ---
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params_group = QGroupBox("⚙️ 采样参数")
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params_layout = QFormLayout()
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params_layout.setSpacing(16)
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@ -80,14 +121,14 @@ class Step4SamplingPanel(QWidget):
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self.chunk_size.setMinimumWidth(120)
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params_layout.addRow("内存处理块大小:", self.chunk_size)
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from PyQt5.QtWidgets import QCheckBox
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self.use_adaptive_sampling = QCheckBox("启用自适应边缘采样")
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self.use_adaptive_sampling.setChecked(True)
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params_layout.addRow("智能模式:", self.use_adaptive_sampling)
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params_group.setLayout(params_layout)
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main_layout.addWidget(params_group)
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left_layout.addWidget(params_group)
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# --- 卡片 3：输出与执行 ---
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output_group = QGroupBox("🚀 输出与执行")
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output_layout = QVBoxLayout()
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output_layout.setSpacing(16)
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@ -104,33 +145,104 @@ class Step4SamplingPanel(QWidget):
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action_layout = QHBoxLayout()
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action_layout.addStretch()
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self.preview_btn = QPushButton("交互式预览采样点")
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self.preview_btn.setStyleSheet(ModernStylesheet.get_button_stylesheet('normal'))
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self.preview_btn.setEnabled(False)
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self.preview_btn.setMinimumWidth(160)
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self.preview_btn.clicked.connect(self._open_sampling_viewer)
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self.refresh_btn = QPushButton("🔄 刷新视图")
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self.refresh_btn.setStyleSheet(ModernStylesheet.get_button_stylesheet('normal'))
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self.refresh_btn.setEnabled(False)
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self.refresh_btn.setMinimumWidth(140)
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self.refresh_btn.setToolTip("重新加载 CSV 并渲染采样点散点图")
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self.refresh_btn.clicked.connect(self._on_refresh_clicked)
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self.run_btn = QPushButton("独立运行步骤")
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self.run_btn.setStyleSheet(ModernStylesheet.get_button_stylesheet('primary'))
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self.run_btn.setMinimumWidth(140)
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self.run_btn.clicked.connect(self._on_run_single_clicked)
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action_layout.addWidget(self.preview_btn)
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action_layout.addWidget(self.refresh_btn)
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action_layout.addWidget(self.run_btn)
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output_layout.addLayout(action_layout)
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output_group.setLayout(output_layout)
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main_layout.addWidget(output_group)
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left_layout.addWidget(output_group)
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main_layout.addStretch()
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self.setLayout(main_layout)
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left_layout.addStretch()
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left_widget.setLayout(left_layout)
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left_widget.setMinimumWidth(360)
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# ═══════════════════════════════════════════════
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# 右侧：可视化区（嵌入式 Matplotlib 视图）
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# ═══════════════════════════════════════════════
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right_widget = QWidget()
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right_layout = QVBoxLayout()
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right_layout.setContentsMargins(12, 24, 24, 24)
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right_layout.setSpacing(0)
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viz_group = QGroupBox("📊 采样点交互式探索")
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viz_layout = QVBoxLayout()
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viz_layout.setContentsMargins(8, 20, 8, 8)
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viz_layout.setSpacing(0)
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# Matplotlib 画布（1×2 子图：散点图 + 光谱曲线）
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self._fig = Figure(figsize=(9, 5))
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self._ax_scatter = self._fig.add_subplot(121)
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self._ax_spectrum = self._fig.add_subplot(122)
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self._canvas = FigureCanvas(self._fig)
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self._canvas.setSizePolicy(QSizePolicy.Expanding, QSizePolicy.Expanding)
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# 设置子图初始状态
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self._ax_scatter.set_title("采样点分布", fontsize=11, fontweight='bold')
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self._ax_scatter.set_xlabel("X 坐标")
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self._ax_scatter.set_ylabel("Y 坐标")
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self._ax_scatter.text(0.5, 0.5, "等待采样数据生成...\n\n请先配置参数并运行步骤\n或选择已有的 CSV 后刷新",
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ha='center', va='center', transform=self._ax_scatter.transAxes,
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fontsize=12, color='#888888')
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self._ax_scatter.grid(False)
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self._ax_spectrum.set_title("光谱曲线", fontsize=11, fontweight='bold')
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self._ax_spectrum.set_xlabel("波长 (nm)")
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self._ax_spectrum.set_ylabel("反射率")
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self._ax_spectrum.text(0.5, 0.5, "点击左侧散点\n查看光谱曲线",
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ha='center', va='center', transform=self._ax_spectrum.transAxes,
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fontsize=12, color='#888888')
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self._ax_spectrum.grid(False)
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self._fig.tight_layout(pad=2.0)
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# 工具栏（自带保存/缩放/平移）
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self._toolbar = NavigationToolbar(self._canvas, self)
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viz_layout.addWidget(self._toolbar)
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viz_layout.addWidget(self._canvas)
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viz_group.setLayout(viz_layout)
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right_layout.addWidget(viz_group)
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right_widget.setLayout(right_layout)
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# ── 组装分栏 ──
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splitter.addWidget(left_widget)
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splitter.addWidget(right_widget)
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splitter.setSizes([420, 680]) # 初始比例 ≈ 38:62
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splitter.setStretchFactor(0, 1)
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splitter.setStretchFactor(1, 2)
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top_layout = QHBoxLayout()
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top_layout.setContentsMargins(0, 0, 0, 0)
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top_layout.addWidget(splitter)
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self.setLayout(top_layout)
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# ── 事件绑定 ──
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self._cid_hover = self._canvas.mpl_connect('motion_notify_event', self._on_hover)
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self._cid_click = self._canvas.mpl_connect('button_press_event', self._on_click)
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# ── 定时器：降低频率，仅用于自动发现新生成的 CSV ──
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self._status_timer = QTimer(self)
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self._status_timer.timeout.connect(self._check_csv_exists)
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self._status_timer.start(2000)
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self._status_timer.timeout.connect(self._check_csv_and_auto_render)
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self._status_timer.start(5000)
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self.output_file.line_edit.textChanged.connect(self._on_output_changed)
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# ═══════════════════════════════════════════════════════════════
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# 配置读写（保持不变）
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# ═══════════════════════════════════════════════════════════════
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def get_config(self):
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config = {
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'interval': self.interval.value(),
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@ -182,7 +294,8 @@ class Step4SamplingPanel(QWidget):
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if deglint_path:
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if not os.path.isabs(deglint_path):
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deglint_path = os.path.join(self.work_dir or '', deglint_path).replace('\\', '/')
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self.deglint_img_file.set_path(deglint_path)
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if os.path.exists(deglint_path):
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self.deglint_img_file.set_path(deglint_path)
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water_mask_path = None
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if pipeline and hasattr(pipeline, 'step_outputs'):
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@ -215,14 +328,22 @@ class Step4SamplingPanel(QWidget):
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if water_mask_path:
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if not os.path.isabs(water_mask_path):
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water_mask_path = os.path.join(self.work_dir or '', water_mask_path).replace('\\', '/')
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self.water_mask_file.set_path(water_mask_path)
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if os.path.exists(water_mask_path):
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self.water_mask_file.set_path(water_mask_path)
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if self.work_dir:
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if self.work_dir and not self.output_file.get_path():
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output_path = resolve_subdir(self.work_dir, 'sampling_csv_path')
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os.makedirs(os.path.dirname(output_path), exist_ok=True)
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self.output_file.set_path(output_path.replace('\\', '/'))
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self._check_csv_exists()
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# 若 CSV 已存在，尝试自动渲染
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csv_path = self.output_file.get_path()
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if csv_path and os.path.isfile(csv_path):
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self._render_inline_plot()
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# ═══════════════════════════════════════════════════════════════
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# 执行
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# ═══════════════════════════════════════════════════════════════
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def _on_run_single_clicked(self):
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from src.gui.core.event_bus import global_event_bus
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@ -236,20 +357,354 @@ class Step4SamplingPanel(QWidget):
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'config': config,
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})
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# ═══════════════════════════════════════════════════════════════
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# CSV 状态检测
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# ═══════════════════════════════════════════════════════════════
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def _check_csv_exists(self):
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csv_path = self.output_file.get_path()
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enabled = bool(csv_path and os.path.isabs(csv_path) and os.path.exists(csv_path))
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self.preview_btn.setEnabled(enabled)
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self.refresh_btn.setEnabled(enabled)
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return enabled
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def _on_output_changed(self, _text=None):
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self._check_csv_exists()
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def _check_csv_and_auto_render(self):
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"""定时器回调：检测到新 CSV 出现时自动渲染一次。"""
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csv_path = self.output_file.get_path()
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if csv_path and os.path.isfile(csv_path):
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if csv_path != self._last_render_path:
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self.refresh_btn.setEnabled(True)
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self._render_inline_plot()
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def _on_refresh_clicked(self):
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"""手动点击刷新按钮。"""
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csv_path = self.output_file.get_path()
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if not csv_path or not os.path.exists(csv_path):
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QMessageBox.warning(self, "文件不存在", f"采样点 CSV 文件不存在：{csv_path}\n请先运行生成数据。")
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return
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self._render_inline_plot()
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# ═══════════════════════════════════════════════════════════════
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# 核心渲染
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# ═══════════════════════════════════════════════════════════════
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def _detect_coordinate_columns(self, df: pd.DataFrame):
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"""检测坐标列，返回 (x_col, y_col) 或 (None, None)。
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优先级：pixel_x/pixel_y → longitude/latitude → lon/lat →
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X/Y → UTM_X/UTM_Y → 任何含 'x'/'y' 关键字的列
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"""
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cols_lower = {c.lower(): c for c in df.columns}
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priority_pairs = [
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('pixel_x', 'pixel_y'),
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('longitude', 'latitude'),
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('lon', 'lat'),
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('x', 'y'),
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('utm_x', 'utm_y'),
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]
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for x_key, y_key in priority_pairs:
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if x_key in cols_lower and y_key in cols_lower:
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return cols_lower[x_key], cols_lower[y_key]
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# 最后尝试：找名字中含 x / y 的数值列
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x_candidates = [c for c in df.columns if 'x' in c.lower() and pd.api.types.is_numeric_dtype(df[c])]
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y_candidates = [c for c in df.columns if 'y' in c.lower() and pd.api.types.is_numeric_dtype(df[c])]
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if x_candidates and y_candidates:
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return x_candidates[0], y_candidates[0]
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return None, None
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def _detect_band_columns(self, df: pd.DataFrame):
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"""检测光谱波段列（纯数字列名，值域在 200–3000 nm 之间）。
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优先使用列名可解析为 float 且在波长范围内的列；
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否则回退到位置索引（跳过坐标列和已知元数据列）。
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"""
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band_cols = []
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for col in df.columns:
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try:
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val = float(str(col).strip())
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if 200.0 <= val <= 3000.0:
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band_cols.append(col)
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except (ValueError, TypeError):
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continue
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if band_cols:
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# 按波长数值排序
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band_cols.sort(key=lambda c: float(str(c).strip()))
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return band_cols
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# 回退：跳过坐标列和已知元数据列，取数值列
|
||||
skip_keywords = ('x', 'y', 'lon', 'lat', 'utm', 'id', 'sample', 'index', 'pixel')
|
||||
numeric_cols = df.select_dtypes(include=[np.number]).columns.tolist()
|
||||
if self._x_col:
|
||||
numeric_cols = [c for c in numeric_cols if c != self._x_col]
|
||||
if self._y_col:
|
||||
numeric_cols = [c for c in numeric_cols if c != self._y_col]
|
||||
return [c for c in numeric_cols if not any(k in c.lower() for k in skip_keywords)]
|
||||
|
||||
def _render_inline_plot(self):
|
||||
"""读取 CSV → 检测坐标/波段列 → 绘制 1×2 子图。"""
|
||||
csv_path = self.output_file.get_path()
|
||||
if not csv_path or not os.path.isfile(csv_path):
|
||||
self._show_empty_state("等待采样数据生成...\n\n请先配置参数并运行步骤")
|
||||
return
|
||||
|
||||
# 读取数据
|
||||
try:
|
||||
df = pd.read_csv(csv_path)
|
||||
except Exception as e:
|
||||
self._show_empty_state(f"读取 CSV 失败:\n{str(e)[:200]}")
|
||||
return
|
||||
|
||||
if df.empty:
|
||||
self._show_empty_state("CSV 文件为空")
|
||||
return
|
||||
|
||||
# 检测坐标列
|
||||
x_col, y_col = self._detect_coordinate_columns(df)
|
||||
if x_col is None or y_col is None:
|
||||
self._show_empty_state(
|
||||
"缺少坐标列\n\n"
|
||||
f"可用列: {', '.join(str(c) for c in df.columns[:15])}\n"
|
||||
"期望: pixel_x/pixel_y, longitude/latitude, X/Y 等"
|
||||
)
|
||||
return
|
||||
|
||||
# 检测光谱列
|
||||
band_cols = self._detect_band_columns(df)
|
||||
if not band_cols:
|
||||
# 仅显示散点图，光谱子图留空
|
||||
pass
|
||||
|
||||
# 缓存
|
||||
self._df = df
|
||||
self._x_col = x_col
|
||||
self._y_col = y_col
|
||||
self._band_cols = band_cols
|
||||
self._highlight_idx = None
|
||||
self._last_render_path = csv_path
|
||||
|
||||
# 清除 Annotation
|
||||
if self._annot is not None:
|
||||
try:
|
||||
self._annot.remove()
|
||||
except Exception:
|
||||
pass
|
||||
self._annot = None
|
||||
|
||||
# ── 绘制 ax1：散点图 ──
|
||||
self._ax_scatter.clear()
|
||||
x = df[x_col].values
|
||||
y = df[y_col].values
|
||||
|
||||
self._scatter = self._ax_scatter.scatter(
|
||||
x, y,
|
||||
c='#0078D7', alpha=0.7, edgecolors='white',
|
||||
linewidth=0.5, s=40, picker=True, zorder=3
|
||||
)
|
||||
self._ax_scatter.set_xlabel(str(x_col), fontsize=10)
|
||||
self._ax_scatter.set_ylabel(str(y_col), fontsize=10)
|
||||
self._ax_scatter.set_title(f"采样点分布 (共 {len(df)} 个点)", fontsize=11, fontweight='bold')
|
||||
self._ax_scatter.grid(True, alpha=0.3, linestyle='--')
|
||||
self._ax_scatter.set_facecolor('#F8F9FA')
|
||||
|
||||
# ── 绘制 ax2：光谱曲线（初始状态）──
|
||||
self._ax_spectrum.clear()
|
||||
if band_cols:
|
||||
self._ax_spectrum.set_title("光谱曲线（点击左侧散点查看）", fontsize=11, fontweight='bold')
|
||||
self._ax_spectrum.set_xlabel("波长 (nm)", fontsize=10)
|
||||
self._ax_spectrum.set_ylabel("反射率", fontsize=10)
|
||||
self._ax_spectrum.grid(True, alpha=0.3, linestyle='--')
|
||||
self._ax_spectrum.text(0.5, 0.5, "点击左侧散点\n查看光谱曲线",
|
||||
ha='center', va='center', transform=self._ax_spectrum.transAxes,
|
||||
fontsize=12, color='#999999')
|
||||
else:
|
||||
self._ax_spectrum.text(0.5, 0.5, "缺少光谱数据列",
|
||||
ha='center', va='center', transform=self._ax_spectrum.transAxes,
|
||||
fontsize=12, color='#999999')
|
||||
|
||||
self._fig.tight_layout(pad=2.0)
|
||||
self._canvas.draw()
|
||||
|
||||
def _show_empty_state(self, message: str):
|
||||
"""在右侧画布显示提示信息。"""
|
||||
self._ax_scatter.clear()
|
||||
self._ax_scatter.set_title("采样点分布", fontsize=11, fontweight='bold')
|
||||
self._ax_scatter.text(0.5, 0.5, message, ha='center', va='center',
|
||||
transform=self._ax_scatter.transAxes,
|
||||
fontsize=12, color='#888888')
|
||||
self._ax_scatter.grid(False)
|
||||
|
||||
self._ax_spectrum.clear()
|
||||
self._ax_spectrum.set_title("光谱曲线", fontsize=11, fontweight='bold')
|
||||
self._ax_spectrum.text(0.5, 0.5, "等待数据...",
|
||||
ha='center', va='center', transform=self._ax_spectrum.transAxes,
|
||||
fontsize=12, color='#888888')
|
||||
self._ax_spectrum.grid(False)
|
||||
|
||||
self._fig.tight_layout(pad=2.0)
|
||||
self._canvas.draw()
|
||||
self._df = None
|
||||
self._last_render_path = None
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════
|
||||
# 交互事件 (Hover & Click)
|
||||
# ═══════════════════════════════════════════════════════════════
|
||||
|
||||
def _on_hover(self, event):
|
||||
"""悬停：在散点旁显示坐标 + ID 提示框。"""
|
||||
if event.inaxes != self._ax_scatter:
|
||||
# 鼠标离开 ax1 → 隐藏 annotation
|
||||
if self._annot is not None:
|
||||
try:
|
||||
self._annot.set_visible(False)
|
||||
self._canvas.draw_idle()
|
||||
except Exception:
|
||||
pass
|
||||
return
|
||||
|
||||
if self._df is None or self._scatter is None:
|
||||
return
|
||||
|
||||
# 检测是否悬停在散点上
|
||||
contains, info = self._scatter.contains(event)
|
||||
if not contains or info is None or 'ind' not in info or len(info['ind']) == 0:
|
||||
if self._annot is not None:
|
||||
try:
|
||||
self._annot.set_visible(False)
|
||||
self._canvas.draw_idle()
|
||||
except Exception:
|
||||
pass
|
||||
return
|
||||
|
||||
idx = info['ind'][0]
|
||||
row = self._df.iloc[idx]
|
||||
x_val = row[self._x_col]
|
||||
y_val = row[self._y_col]
|
||||
|
||||
# 创建或更新 Annotation
|
||||
text = f"#{idx}\n({x_val:.4f}, {y_val:.4f})"
|
||||
if self._annot is None:
|
||||
self._annot = self._ax_scatter.annotate(
|
||||
text,
|
||||
xy=(x_val, y_val),
|
||||
xytext=(12, 12),
|
||||
textcoords='offset points',
|
||||
bbox=dict(boxstyle='round,pad=0.4', facecolor='#FFFFFF',
|
||||
edgecolor='#0078D7', alpha=0.9),
|
||||
fontsize=9,
|
||||
zorder=10,
|
||||
)
|
||||
else:
|
||||
self._annot.xy = (x_val, y_val)
|
||||
self._annot.set_text(text)
|
||||
self._annot.set_visible(True)
|
||||
|
||||
self._canvas.draw_idle()
|
||||
|
||||
def _on_click(self, event):
|
||||
"""点击：高亮散点 + 绘制光谱曲线。"""
|
||||
if event.inaxes != self._ax_scatter:
|
||||
return
|
||||
|
||||
if self._df is None or self._scatter is None:
|
||||
return
|
||||
|
||||
# 检测是否点击在散点上
|
||||
contains, info = self._scatter.contains(event)
|
||||
if not contains or info is None or 'ind' not in info or len(info['ind']) == 0:
|
||||
return
|
||||
|
||||
idx = info['ind'][0]
|
||||
row = self._df.iloc[idx]
|
||||
self._highlight_idx = idx
|
||||
|
||||
# ── 高亮选中点 ──
|
||||
x = self._df[self._x_col].values
|
||||
y = self._df[self._y_col].values
|
||||
|
||||
colors = ['#0078D7'] * len(self._df)
|
||||
sizes = [40] * len(self._df)
|
||||
colors[idx] = '#E74C3C'
|
||||
sizes[idx] = 80
|
||||
|
||||
self._ax_scatter.clear()
|
||||
self._scatter = self._ax_scatter.scatter(
|
||||
x, y, c=colors, s=sizes,
|
||||
alpha=0.7, edgecolors='white', linewidth=0.5,
|
||||
picker=True, zorder=3
|
||||
)
|
||||
# 将选中点提升到顶层
|
||||
self._ax_scatter.scatter(
|
||||
[x[idx]], [y[idx]],
|
||||
c='#E74C3C', s=100,
|
||||
alpha=0.9, edgecolors='white', linewidth=1.5,
|
||||
zorder=5
|
||||
)
|
||||
self._ax_scatter.set_xlabel(str(self._x_col), fontsize=10)
|
||||
self._ax_scatter.set_ylabel(str(self._y_col), fontsize=10)
|
||||
self._ax_scatter.set_title(f"采样点分布 (共 {len(self._df)} 个点)", fontsize=11, fontweight='bold')
|
||||
self._ax_scatter.grid(True, alpha=0.3, linestyle='--')
|
||||
self._ax_scatter.set_facecolor('#F8F9FA')
|
||||
|
||||
# ── 绘制光谱曲线 ──
|
||||
self._ax_spectrum.clear()
|
||||
if self._band_cols:
|
||||
wavelengths = []
|
||||
reflectance = []
|
||||
for col in self._band_cols:
|
||||
try:
|
||||
wl = float(str(col).strip())
|
||||
val = row[col]
|
||||
if pd.notna(val):
|
||||
wavelengths.append(wl)
|
||||
reflectance.append(float(val))
|
||||
except (ValueError, TypeError):
|
||||
continue
|
||||
|
||||
if wavelengths:
|
||||
# 按波长排序
|
||||
pairs = sorted(zip(wavelengths, reflectance), key=lambda p: p[0])
|
||||
wavelengths, reflectance = zip(*pairs) if pairs else ([], [])
|
||||
self._ax_spectrum.plot(
|
||||
wavelengths, reflectance,
|
||||
color='#0078D7', lw=1.5, marker='.', markersize=3, alpha=0.8
|
||||
)
|
||||
self._ax_spectrum.fill_between(wavelengths, reflectance, alpha=0.1, color='#0078D7')
|
||||
self._ax_spectrum.set_xlabel("波长 (nm)", fontsize=10)
|
||||
self._ax_spectrum.set_ylabel("反射率", fontsize=10)
|
||||
self._ax_spectrum.set_title(f"样本 #{idx} 的光谱曲线 ({len(wavelengths)} 个波段)",
|
||||
fontsize=11, fontweight='bold')
|
||||
self._ax_spectrum.grid(True, alpha=0.3, linestyle='--')
|
||||
else:
|
||||
self._ax_spectrum.text(0.5, 0.5, "该样本无有效光谱数据",
|
||||
ha='center', va='center',
|
||||
transform=self._ax_spectrum.transAxes,
|
||||
fontsize=12, color='#999999')
|
||||
else:
|
||||
self._ax_spectrum.text(0.5, 0.5, "缺少光谱波段列\n无法绘制光谱",
|
||||
ha='center', va='center',
|
||||
transform=self._ax_spectrum.transAxes,
|
||||
fontsize=12, color='#999999')
|
||||
|
||||
self._fig.tight_layout(pad=2.0)
|
||||
self._canvas.draw()
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════
|
||||
# 旧版弹窗查看器（保留，供外部调用）
|
||||
# ═══════════════════════════════════════════════════════════════
|
||||
|
||||
def _open_sampling_viewer(self):
|
||||
"""打开独立的 SamplingViewerDialog 弹窗（保留兼容）。"""
|
||||
csv_path = self.output_file.get_path()
|
||||
if not csv_path or not os.path.exists(csv_path):
|
||||
QMessageBox.warning(self, "文件不存在", f"采样点 CSV 文件不存在：{csv_path}\n请先运行生成数据。")
|
||||
return
|
||||
dialog = SamplingViewerDialog(csv_path, self)
|
||||
dialog.exec_()
|
||||
self._check_csv_exists()
|
||||
self._check_csv_exists()
|
||||
|
||||
Reference in New Issue
Block a user