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

src/gui/panels/step10_watercolor_panel.py

@@ -567,17 +567,22 @@ class Step10WatercolorPanel(QWidget):
             )
 
         # 2. 回退：直接读 step4_sampling panel 的 output_file widget
+        #    2026-06-30：panel widget 可能含幽灵占位路径，仅当文件确实存在时才采纳
         if not sampling_path and main_window:
             step4_widget = getattr(main_window, 'step4_sampling', None)
             if step4_widget and hasattr(step4_widget, 'output_file'):
-                sampling_path = step4_widget.output_file.get_path()
-            else:
+                candidate = step4_widget.output_file.get_path()
+                if candidate and os.path.isfile(candidate):
+                    sampling_path = candidate
+            if not sampling_path:
                 # 通过 _panel_factory 懒加载查找
                 factory = getattr(main_window, '_panel_factory', None)
                 if factory:
                     step4_panel = factory.get_panel('step4_sampling')
                     if step4_panel and hasattr(step4_panel, 'output_file'):
-                        sampling_path = step4_panel.output_file.get_path()
+                        candidate = step4_panel.output_file.get_path()
+                        if candidate and os.path.isfile(candidate):
+                            sampling_path = candidate
 
         # 3. 终极回退：扫描 work_dir/4_sampling/sampling_spectra.csv
         if not sampling_path and self.work_dir:
@@ -593,14 +598,12 @@ class Step10WatercolorPanel(QWidget):
                 ).replace('\\', '/')
             self.sampling_csv_file.set_path(sampling_path)
 
-        # 自动填入输出目录（默认 work_dir/10_WaterIndex_CSV/）
-        if self.work_dir:
+        # 自动填入输出目录（仅在为空时填入默认路径，不创建目录）
+        if self.work_dir and not self.output_dir.get_path():
             out_dir = os.path.join(
                 self.work_dir, '10_WaterIndex_CSV'
             ).replace('\\', '/')
-            os.makedirs(out_dir, exist_ok=True)
-            if not self.output_dir.get_path():
-                self.output_dir.set_path(out_dir)
+            self.output_dir.set_path(out_dir)
 
     def _on_run_single_clicked(self):
         """通过 EventBus 发布单步执行请求（解耦面板与 PipelineExecutor）。"""

src/gui/panels/step11_map_panel.py

@@ -482,35 +482,32 @@ class Step11MapPanel(QWidget):
         factory = getattr(main_window, '_panel_factory', None) if main_window else None
         if not factory: return
 
-        # 1. 安全抓取 Step 9 的预测 CSV 目录
+        # 1. 安全抓取 Step 9 的预测 CSV 目录（仅当目录确实存在）
         step9_panel = factory.get_panel('step9_ml_predict')
         if step9_panel and hasattr(step9_panel, 'output_file'):
             path = step9_panel.output_file.get_path()
-            if path:
+            if path and os.path.isdir(path):
                 self.prediction_csv_dir_edit.setText(path)
                 self.batch_mode_combo.setCurrentIndex(1)
 
-        # 2. 安全抓取 Step 1 的真实掩膜文件（彻底拒绝瞎猜 roi.shp）
+        # 2. 安全抓取 Step 1 的真实掩膜文件（仅当文件确实存在）
         step1_panel = factory.get_panel('step1')
         if step1_panel:
             use_ndwi = step1_panel.use_ndwi_radio.isChecked()
-            # 根据用户在第1步的选择，拿真实的输出掩膜或导入的掩膜
             if use_ndwi and hasattr(step1_panel, 'output_file'):
                 path = step1_panel.output_file.get_path()
             elif not use_ndwi and hasattr(step1_panel, 'mask_file'):
                 path = step1_panel.mask_file.get_path()
             else:
                 path = ""
-            
+
             existing = self.boundary_file.get_path()
-            if path and not existing:
+            if path and not existing and os.path.exists(path):
                 self.boundary_file.set_path(path)
 
-        # 3. 生成第 11 步的绝对输出目录 (杜绝保存到相对路径)
-        if hasattr(self, 'work_dir') and self.work_dir:
-            import os
+        # 3. 生成第 11 步的输出目录（仅在为空时填入默认路径，不创建目录）
+        if hasattr(self, 'work_dir') and self.work_dir and not self.output_dir.get_path():
             out_dir = os.path.join(self.work_dir, "14_visualization").replace('\\', '/')
-            os.makedirs(out_dir, exist_ok=True)
             self.output_dir.set_path(out_dir)
 
     def browse_output_dir(self):

src/gui/panels/step12_viz_panel.py

@@ -1656,21 +1656,22 @@ class Step12VizPanel(QWidget):
                 self.image_viewer.load_image(str(image_files[0]))
 
     def _setup_prediction_output_dirs(self, work_path: Path):
-        """设置三个预测步骤的默认输出目录"""
+        """收集预测输出目录路径信息（不创建目录，仅用于日志/调试）。
+
+        2026-06-30 修复：移除 mkdir 调用，不再在未运行 pipeline 时创建空目录。
+        目录创建统一留给各 pipeline 步骤在实际执行时处理。
+        """
         try:
             base_prediction_dir = Path(resolve_subdir(str(work_path), 'prediction_dir'))
             ml_dir = Path(resolve_subdir(str(work_path), 'ml_prediction'))
             reg_dir = base_prediction_dir / "Regression_Model_Prediction"
             custom_dir = Path(resolve_subdir(str(work_path), 'custom_regression')) / "Custom_Regression_Prediction"
-            ml_dir.mkdir(parents=True, exist_ok=True)
-            reg_dir.mkdir(parents=True, exist_ok=True)
-            custom_dir.mkdir(parents=True, exist_ok=True)
-            # 旧的 self.step11_ml_panel/step11_panel/step12_panel 在 Step12VizPanel 上不存在，是死代码。
-            # 三个目录的真实默认值在用户首次浏览 / 自动填充时由各 panel 自己的 _get_default_work_dir 路径产出。
-            # 这里仅做目录创建 + 提示输出，便于用户在工作目录树中能看到预测输出位置。
-            print(f"预测输出目录已创建:\n  ML: {ml_dir}\n  Reg: {reg_dir}\n  Custom: {custom_dir}")
+            # 仅输出信息，不创建目录
+            existing = [str(d) for d in (ml_dir, reg_dir, custom_dir) if d.is_dir()]
+            if existing:
+                print(f"预测输出目录已存在: {existing}")
         except Exception as e:
-            print(f"设置预测输出目录失败: {e}")
+            print(f"读取预测输出目录信息失败: {e}")
 
     def on_tree_item_clicked(self, item, column):
         """目录树项点击事件"""

src/gui/panels/step1_panel.py

@@ -114,6 +114,9 @@ class Step1Panel(QWidget):
         config_group.setLayout(config_layout)
         main_layout.addWidget(config_group)
 
+        # ==========================================
+        # 卡片 3：输出与执行（与 Step8 对齐的现代化卡片风格）
+        # ==========================================
         output_group = QGroupBox("🚀 输出与执行")
         output_layout = QVBoxLayout()
         output_layout.setSpacing(16)
@@ -124,11 +127,10 @@ class Step1Panel(QWidget):
             "Mask Files (*.dat *.tif);;All Files (*.*)",
             mode="save"
         )
-        self.output_file.label.setMinimumWidth(100)
         self.output_file.line_edit.setPlaceholderText("water_mask.dat")
         output_layout.addWidget(self.output_file)
 
-        # 完美对齐的底部按钮栏（已移除多余的启用步骤选项）
+        # 完美对齐的底部按钮栏
         action_layout = QHBoxLayout()
         action_layout.addStretch()
 
@@ -140,6 +142,8 @@ class Step1Panel(QWidget):
 
         output_layout.addLayout(action_layout)
         output_group.setLayout(output_layout)
+
+        # 将打包好的输出卡片添加到主 layout 中
         main_layout.addWidget(output_group)
 
         self.use_existing_radio.toggled.connect(self.update_ui_state)
@@ -164,10 +168,12 @@ class Step1Panel(QWidget):
         self._auto_fill_output_path()
 
     def _auto_fill_output_path(self):
+        """仅在输出框为空时填入默认路径；不创建目录（留给 pipeline 执行时创建）。"""
         if not hasattr(self, 'work_dir') or not self.work_dir:
             return
+        if self.output_file.get_path():
+            return  # 用户已手动指定，不覆盖
         output_dir = resolve_subdir(self.work_dir, 'water_mask')
-        os.makedirs(output_dir, exist_ok=True)
         default_output_path = os.path.join(output_dir, "water_mask_out.dat").replace('\\', '/')
         self.output_file.set_path(default_output_path)
 

src/gui/panels/step2_panel.py

@@ -192,13 +192,15 @@ class Step2Panel(QWidget):
         if mask_path:
             if not os.path.isabs(mask_path):
                 mask_path = os.path.join(self.work_dir or '', mask_path).replace('\\', '/')
-            self.water_mask_file.set_path(mask_path)
+            # 仅当上游文件确实存在时才自动填入（防止幽灵路径级联扩散）
+            if os.path.exists(mask_path):
+                self.water_mask_file.set_path(mask_path)
 
         if self.work_dir:
-            output_dir = resolve_subdir(self.work_dir, 'glint_detection')
-            os.makedirs(output_dir, exist_ok=True)
-            default_output_path = os.path.join(output_dir, "severe_glint_area.dat").replace('\\', '/')
-            self.output_file.set_path(default_output_path)
+            if not self.output_file.get_path():
+                output_dir = resolve_subdir(self.work_dir, 'glint_detection')
+                default_output_path = os.path.join(output_dir, "severe_glint_area.dat").replace('\\', '/')
+                self.output_file.set_path(default_output_path)
         else:
             self.output_file.set_path("")
 

src/gui/panels/step3_panel.py

@@ -317,13 +317,15 @@ class Step3Panel(QWidget):
             if mask_path:
                 if not os.path.isabs(mask_path):
                     mask_path = os.path.join(self.work_dir or '', mask_path).replace('\\', '/')
-                self.water_mask_file.set_path(mask_path)
+                # 仅当上游文件确实存在时才自动填入（防止幽灵路径级联扩散）
+                if os.path.exists(mask_path):
+                    self.water_mask_file.set_path(mask_path)
 
         if self.work_dir:
-            output_dir = resolve_subdir(self.work_dir, 'deglint')
-            os.makedirs(output_dir, exist_ok=True)
-            default_output_path = os.path.join(output_dir, "deglint_image.bsq").replace('\\', '/')
-            self.output_file.set_path(default_output_path)
+            if not self.output_file.get_path():
+                output_dir = resolve_subdir(self.work_dir, 'deglint')
+                default_output_path = os.path.join(output_dir, "deglint_image.bsq").replace('\\', '/')
+                self.output_file.set_path(default_output_path)
         else:
             self.output_file.set_path("")
 

src/gui/panels/step4_sampling_panel.py

@@ -1,13 +1,22 @@
 #!/usr/bin/env python
 # -*- coding: utf-8 -*-
 """
-Step4 面板 - 采样点布设 (已移除“启用此步骤”)
+Step4 面板 - 采样点布设（内嵌交互式光谱探针视图）
+
+2026-06-30 重构：
+  - 左右分栏布局 (QSplitter)：左侧控制区 + 右侧嵌入式 Matplotlib 视图
+  - 1×2 子图：ax1 散点图 + ax2 光谱曲线
+  - Hover 悬停显示坐标提示，Click 点击绘制该点光谱曲线
+  - NavigationToolbar2QT 工具栏自带保存/缩放/平移
 """
 
 import os
 import sys
 from pathlib import Path
 
+import numpy as np
+import pandas as pd
+
 _HERE = os.path.dirname(os.path.abspath(__file__))
 if _HERE not in sys.path:
     sys.path.insert(0, _HERE)
@@ -16,9 +25,16 @@ from _step_path_resolver import resolve_subdir
 from PyQt5.QtCore import QTimer, Qt
 from PyQt5.QtWidgets import (
     QWidget, QVBoxLayout, QHBoxLayout, QGroupBox, QFormLayout,
-    QPushButton, QSpinBox, QMessageBox, QLabel, QFrame
+    QPushButton, QSpinBox, QCheckBox, QMessageBox, QLabel, QFrame,
+    QSplitter, QSizePolicy,
 )
 
+from matplotlib.backends.backend_qt5agg import (
+    FigureCanvasQTAgg as FigureCanvas,
+    NavigationToolbar2QT as NavigationToolbar,
+)
+from matplotlib.figure import Figure
+
 from src.gui.components.custom_widgets import FileSelectWidget
 from src.gui.dialogs import SamplingViewerDialog
 from src.gui.styles import ModernStylesheet
@@ -27,15 +43,39 @@ from src.gui.styles import ModernStylesheet
 class Step4SamplingPanel(QWidget):
     def __init__(self, parent=None):
         super().__init__(parent)
+        # 交互状态
+        self._df = None
+        self._x_col = None
+        self._y_col = None
+        self._band_cols = []
+        self._scatter = None
+        self._highlight_idx = None
+        self._annot = None
+        self._cid_hover = None
+        self._cid_click = None
+        self._last_render_path = None
         self.init_ui()
 
+    # ═══════════════════════════════════════════════════════════════
+    # UI 构建
+    # ═══════════════════════════════════════════════════════════════
+
     def init_ui(self):
         self.setStyleSheet(ModernStylesheet.get_main_stylesheet())
 
-        main_layout = QVBoxLayout()
-        main_layout.setContentsMargins(24, 24, 24, 24)
-        main_layout.setSpacing(20)
+        # ── 顶层：水平分栏 (QSplitter) ──
+        splitter = QSplitter(Qt.Horizontal)
+        splitter.setChildrenCollapsible(False)
 
+        # ═══════════════════════════════════════════════
+        # 左侧：控制区（原封保留原有三张卡片）
+        # ═══════════════════════════════════════════════
+        left_widget = QWidget()
+        left_layout = QVBoxLayout()
+        left_layout.setContentsMargins(24, 24, 12, 24)
+        left_layout.setSpacing(20)
+
+        # --- 卡片 1：输入数据 ---
         input_group = QGroupBox("📁 输入数据")
         input_layout = QVBoxLayout()
         input_layout.setSpacing(16)
@@ -52,8 +92,9 @@ class Step4SamplingPanel(QWidget):
         input_layout.addWidget(self.deglint_img_file)
         input_layout.addWidget(self.water_mask_file)
         input_group.setLayout(input_layout)
-        main_layout.addWidget(input_group)
+        left_layout.addWidget(input_group)
 
+        # --- 卡片 2：采样参数 ---
         params_group = QGroupBox("⚙️ 采样参数")
         params_layout = QFormLayout()
         params_layout.setSpacing(16)
@@ -80,14 +121,14 @@ class Step4SamplingPanel(QWidget):
         self.chunk_size.setMinimumWidth(120)
         params_layout.addRow("内存处理块大小:", self.chunk_size)
 
-        from PyQt5.QtWidgets import QCheckBox
         self.use_adaptive_sampling = QCheckBox("启用自适应边缘采样")
         self.use_adaptive_sampling.setChecked(True)
         params_layout.addRow("智能模式:", self.use_adaptive_sampling)
 
         params_group.setLayout(params_layout)
-        main_layout.addWidget(params_group)
+        left_layout.addWidget(params_group)
 
+        # --- 卡片 3：输出与执行 ---
         output_group = QGroupBox("🚀 输出与执行")
         output_layout = QVBoxLayout()
         output_layout.setSpacing(16)
@@ -104,33 +145,104 @@ class Step4SamplingPanel(QWidget):
         action_layout = QHBoxLayout()
         action_layout.addStretch()
 
-        self.preview_btn = QPushButton("交互式预览采样点")
-        self.preview_btn.setStyleSheet(ModernStylesheet.get_button_stylesheet('normal'))
-        self.preview_btn.setEnabled(False)
-        self.preview_btn.setMinimumWidth(160)
-        self.preview_btn.clicked.connect(self._open_sampling_viewer)
+        self.refresh_btn = QPushButton("🔄 刷新视图")
+        self.refresh_btn.setStyleSheet(ModernStylesheet.get_button_stylesheet('normal'))
+        self.refresh_btn.setEnabled(False)
+        self.refresh_btn.setMinimumWidth(140)
+        self.refresh_btn.setToolTip("重新加载 CSV 并渲染采样点散点图")
+        self.refresh_btn.clicked.connect(self._on_refresh_clicked)
 
         self.run_btn = QPushButton("独立运行步骤")
         self.run_btn.setStyleSheet(ModernStylesheet.get_button_stylesheet('primary'))
         self.run_btn.setMinimumWidth(140)
         self.run_btn.clicked.connect(self._on_run_single_clicked)
 
-        action_layout.addWidget(self.preview_btn)
+        action_layout.addWidget(self.refresh_btn)
         action_layout.addWidget(self.run_btn)
 
         output_layout.addLayout(action_layout)
         output_group.setLayout(output_layout)
-        main_layout.addWidget(output_group)
+        left_layout.addWidget(output_group)
 
-        main_layout.addStretch()
-        self.setLayout(main_layout)
+        left_layout.addStretch()
+        left_widget.setLayout(left_layout)
+        left_widget.setMinimumWidth(360)
 
+        # ═══════════════════════════════════════════════
+        # 右侧：可视化区（嵌入式 Matplotlib 视图）
+        # ═══════════════════════════════════════════════
+        right_widget = QWidget()
+        right_layout = QVBoxLayout()
+        right_layout.setContentsMargins(12, 24, 24, 24)
+        right_layout.setSpacing(0)
+
+        viz_group = QGroupBox("📊 采样点交互式探索")
+        viz_layout = QVBoxLayout()
+        viz_layout.setContentsMargins(8, 20, 8, 8)
+        viz_layout.setSpacing(0)
+
+        # Matplotlib 画布（1×2 子图：散点图 + 光谱曲线）
+        self._fig = Figure(figsize=(9, 5))
+        self._ax_scatter = self._fig.add_subplot(121)
+        self._ax_spectrum = self._fig.add_subplot(122)
+        self._canvas = FigureCanvas(self._fig)
+        self._canvas.setSizePolicy(QSizePolicy.Expanding, QSizePolicy.Expanding)
+
+        # 设置子图初始状态
+        self._ax_scatter.set_title("采样点分布", fontsize=11, fontweight='bold')
+        self._ax_scatter.set_xlabel("X 坐标")
+        self._ax_scatter.set_ylabel("Y 坐标")
+        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",
+                              ha='center', va='center', transform=self._ax_scatter.transAxes,
+                              fontsize=12, color='#888888')
+        self._ax_scatter.grid(False)
+
+        self._ax_spectrum.set_title("光谱曲线", fontsize=11, fontweight='bold')
+        self._ax_spectrum.set_xlabel("波长 (nm)")
+        self._ax_spectrum.set_ylabel("反射率")
+        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='#888888')
+        self._ax_spectrum.grid(False)
+
+        self._fig.tight_layout(pad=2.0)
+
+        # 工具栏（自带保存/缩放/平移）
+        self._toolbar = NavigationToolbar(self._canvas, self)
+        viz_layout.addWidget(self._toolbar)
+        viz_layout.addWidget(self._canvas)
+
+        viz_group.setLayout(viz_layout)
+        right_layout.addWidget(viz_group)
+        right_widget.setLayout(right_layout)
+
+        # ── 组装分栏 ──
+        splitter.addWidget(left_widget)
+        splitter.addWidget(right_widget)
+        splitter.setSizes([420, 680])  # 初始比例 ≈ 38:62
+        splitter.setStretchFactor(0, 1)
+        splitter.setStretchFactor(1, 2)
+
+        top_layout = QHBoxLayout()
+        top_layout.setContentsMargins(0, 0, 0, 0)
+        top_layout.addWidget(splitter)
+        self.setLayout(top_layout)
+
+        # ── 事件绑定 ──
+        self._cid_hover = self._canvas.mpl_connect('motion_notify_event', self._on_hover)
+        self._cid_click = self._canvas.mpl_connect('button_press_event', self._on_click)
+
+        # ── 定时器：降低频率，仅用于自动发现新生成的 CSV ──
         self._status_timer = QTimer(self)
-        self._status_timer.timeout.connect(self._check_csv_exists)
-        self._status_timer.start(2000)
+        self._status_timer.timeout.connect(self._check_csv_and_auto_render)
+        self._status_timer.start(5000)
 
         self.output_file.line_edit.textChanged.connect(self._on_output_changed)
 
+    # ═══════════════════════════════════════════════════════════════
+    # 配置读写（保持不变）
+    # ═══════════════════════════════════════════════════════════════
+
     def get_config(self):
         config = {
             'interval': self.interval.value(),
@@ -182,7 +294,8 @@ class Step4SamplingPanel(QWidget):
         if deglint_path:
             if not os.path.isabs(deglint_path):
                 deglint_path = os.path.join(self.work_dir or '', deglint_path).replace('\\', '/')
-            self.deglint_img_file.set_path(deglint_path)
+            if os.path.exists(deglint_path):
+                self.deglint_img_file.set_path(deglint_path)
 
         water_mask_path = None
         if pipeline and hasattr(pipeline, 'step_outputs'):
@@ -215,14 +328,22 @@ class Step4SamplingPanel(QWidget):
         if water_mask_path:
             if not os.path.isabs(water_mask_path):
                 water_mask_path = os.path.join(self.work_dir or '', water_mask_path).replace('\\', '/')
-            self.water_mask_file.set_path(water_mask_path)
+            if os.path.exists(water_mask_path):
+                self.water_mask_file.set_path(water_mask_path)
 
-        if self.work_dir:
+        if self.work_dir and not self.output_file.get_path():
             output_path = resolve_subdir(self.work_dir, 'sampling_csv_path')
-            os.makedirs(os.path.dirname(output_path), exist_ok=True)
             self.output_file.set_path(output_path.replace('\\', '/'))
 
         self._check_csv_exists()
+        # 若 CSV 已存在，尝试自动渲染
+        csv_path = self.output_file.get_path()
+        if csv_path and os.path.isfile(csv_path):
+            self._render_inline_plot()
+
+    # ═══════════════════════════════════════════════════════════════
+    # 执行
+    # ═══════════════════════════════════════════════════════════════
 
     def _on_run_single_clicked(self):
         from src.gui.core.event_bus import global_event_bus
@@ -236,20 +357,354 @@ class Step4SamplingPanel(QWidget):
             'config': config,
         })
 
+    # ═══════════════════════════════════════════════════════════════
+    # CSV 状态检测
+    # ═══════════════════════════════════════════════════════════════
+
     def _check_csv_exists(self):
         csv_path = self.output_file.get_path()
         enabled = bool(csv_path and os.path.isabs(csv_path) and os.path.exists(csv_path))
-        self.preview_btn.setEnabled(enabled)
+        self.refresh_btn.setEnabled(enabled)
         return enabled
 
     def _on_output_changed(self, _text=None):
         self._check_csv_exists()
 
+    def _check_csv_and_auto_render(self):
+        """定时器回调：检测到新 CSV 出现时自动渲染一次。"""
+        csv_path = self.output_file.get_path()
+        if csv_path and os.path.isfile(csv_path):
+            if csv_path != self._last_render_path:
+                self.refresh_btn.setEnabled(True)
+                self._render_inline_plot()
+
+    def _on_refresh_clicked(self):
+        """手动点击刷新按钮。"""
+        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
+        self._render_inline_plot()
+
+    # ═══════════════════════════════════════════════════════════════
+    # 核心渲染
+    # ═══════════════════════════════════════════════════════════════
+
+    def _detect_coordinate_columns(self, df: pd.DataFrame):
+        """检测坐标列，返回 (x_col, y_col) 或 (None, None)。
+
+        优先级：pixel_x/pixel_y → longitude/latitude → lon/lat →
+                X/Y → UTM_X/UTM_Y → 任何含 'x'/'y' 关键字的列
+        """
+        cols_lower = {c.lower(): c for c in df.columns}
+
+        priority_pairs = [
+            ('pixel_x', 'pixel_y'),
+            ('longitude', 'latitude'),
+            ('lon', 'lat'),
+            ('x', 'y'),
+            ('utm_x', 'utm_y'),
+        ]
+
+        for x_key, y_key in priority_pairs:
+            if x_key in cols_lower and y_key in cols_lower:
+                return cols_lower[x_key], cols_lower[y_key]
+
+        # 最后尝试：找名字中含 x / y 的数值列
+        x_candidates = [c for c in df.columns if 'x' in c.lower() and pd.api.types.is_numeric_dtype(df[c])]
+        y_candidates = [c for c in df.columns if 'y' in c.lower() and pd.api.types.is_numeric_dtype(df[c])]
+        if x_candidates and y_candidates:
+            return x_candidates[0], y_candidates[0]
+
+        return None, None
+
+    def _detect_band_columns(self, df: pd.DataFrame):
+        """检测光谱波段列（纯数字列名，值域在 200–3000 nm 之间）。
+
+        优先使用列名可解析为 float 且在波长范围内的列；
+        否则回退到位置索引（跳过坐标列和已知元数据列）。
+        """
+        band_cols = []
+        for col in df.columns:
+            try:
+                val = float(str(col).strip())
+                if 200.0 <= val <= 3000.0:
+                    band_cols.append(col)
+            except (ValueError, TypeError):
+                continue
+
+        if band_cols:
+            # 按波长数值排序
+            band_cols.sort(key=lambda c: float(str(c).strip()))
+            return band_cols
+
+        # 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()

src/gui/panels/step5_clean_panel.py

@@ -190,12 +190,11 @@ class Step5CleanPanel(QWidget):
         else:
             self.work_dir = None
 
-        if self.work_dir:
+        if self.work_dir and not self.output_file.get_path():
             output_dir = resolve_subdir(self.work_dir, 'data_cleaning')
-            os.makedirs(output_dir, exist_ok=True)
             default_output_path = os.path.join(output_dir, "processed_data.csv").replace('\\', '/')
             self.output_file.set_path(default_output_path)
-        else:
+        elif not self.work_dir:
             self.output_file.set_path("")
 
     def _on_run_single_clicked(self):

src/gui/panels/step6_feature_panel.py

@@ -234,14 +234,16 @@ class Step6FeaturePanel(QWidget):
         if mask_path:
             if not os.path.isabs(mask_path):
                 mask_path = os.path.join(self.work_dir or '', mask_path).replace('\\', '/')
-            self.water_mask_file.set_path(mask_path)
+            if os.path.exists(mask_path):
+                self.water_mask_file.set_path(mask_path)
 
         if hasattr(main_window, 'step2_panel'):
             glint_path = main_window.step2_panel.output_file.get_path()
             if glint_path:
                 if not os.path.isabs(glint_path):
                     glint_path = os.path.join(self.work_dir or '', glint_path).replace('\\', '/')
-                self.glint_mask_file.set_path(glint_path)
+                if os.path.exists(glint_path):
+                    self.glint_mask_file.set_path(glint_path)
 
         deglint_path = None
         if pipeline and hasattr(pipeline, 'step_outputs'):
@@ -273,15 +275,14 @@ class Step6FeaturePanel(QWidget):
             if not os.path.isabs(deglint_path):
                 deglint_path = os.path.join(self.work_dir or '', deglint_path).replace('\\', '/')
             existing_deglint = self.deglint_img_file.get_path()
-            if not existing_deglint or not existing_deglint.strip():
+            if (not existing_deglint or not existing_deglint.strip()) and os.path.exists(deglint_path):
                 self.deglint_img_file.set_path(deglint_path)
 
-        if self.work_dir:
+        if self.work_dir and not self.output_file.get_path():
             output_dir = resolve_subdir(self.work_dir, 'spectral_feature')
-            os.makedirs(output_dir, exist_ok=True)
             default_output_path = os.path.join(output_dir, "training_spectra.csv").replace('\\', '/')
             self.output_file.set_path(default_output_path)
-        else:
+        elif not self.work_dir:
             self.output_file.set_path("")
 
         if main_window and hasattr(main_window, 'step5_clean_panel'):
@@ -292,7 +293,7 @@ class Step6FeaturePanel(QWidget):
                         self.work_dir or '', step5_clean_output_path
                     ).replace('\\', '/')
                 existing_csv = self.csv_file.get_path()
-                if not existing_csv or not existing_csv.strip():
+                if (not existing_csv or not existing_csv.strip()) and os.path.exists(step5_clean_output_path):
                     self.csv_file.set_path(step5_clean_output_path)
 
     def _on_run_single_clicked(self):

src/gui/panels/step7_inversion_panel.py

@@ -9,6 +9,8 @@ import sys
 import csv
 from pathlib import Path
 
+import pandas as pd
+
 from PyQt5.QtWidgets import (
     QVBoxLayout, QHBoxLayout, QGroupBox, QFormLayout,
     QLabel, QPushButton, QMessageBox, QListWidget,
@@ -263,7 +265,15 @@ class Step7InversionPanel(QWidget):
         output_layout.setSpacing(16)
         output_layout.setContentsMargins(20, 24, 20, 20)
 
-        # 这里不需要输出文件选择框，因为服务层会直接覆盖原 CSV，但保留执行按钮
+        self.output_file = FileSelectWidget(
+            "结果保存至:",
+            "CSV Files (*.csv);;All Files (*.*)",
+            mode="save"
+        )
+        self.output_file.label.setMinimumWidth(120)
+        self.output_file.line_edit.setPlaceholderText("training_spectra_indices.csv")
+        output_layout.addWidget(self.output_file)
+
         action_layout = QHBoxLayout()
         action_layout.addStretch()
 
@@ -328,6 +338,9 @@ class Step7InversionPanel(QWidget):
             'formula_names': selected_names,
             'enabled': True  # 默认启用
         }
+        output_path = self.output_file.get_path()
+        if output_path:
+            config['output_path'] = output_path
         return config
 
     def set_config(self, config: dict):
@@ -347,6 +360,9 @@ class Step7InversionPanel(QWidget):
                 item.setCheckState(state)
             self.formula_list.blockSignals(False)
 
+        if 'output_path' in config:
+            self.output_file.set_path(config['output_path'])
+
     def _load_formulas_from_csv(self):
         """解析公式 CSV 文件并填充列表框"""
         csv_path = self.formula_file.get_path()
@@ -439,7 +455,7 @@ class Step7InversionPanel(QWidget):
         """从全局配置/Pipeline 同步工作目录。
 
         step6 的训练数据已由 PANEL_REGISTRY 的 dependencies 自动通过 set_config
-        注入到 self.training_data_widget；此处仅缓存 work_dir，
+        注入到 self.training_data_widget；此处仅缓存 work_dir 并填入默认输出路径，
         不重复拉取，避免与 panel_factory 注入路径冲突。
         """
         if work_dir:
@@ -448,3 +464,11 @@ class Step7InversionPanel(QWidget):
             pass
         else:
             self.work_dir = None
+
+        # 仅在输出框为空时填入默认路径（不创建目录，留给 pipeline 执行时创建）
+        if self.work_dir and not self.output_file.get_path():
+            output_dir = os.path.join(self.work_dir, "7_Water_Quality_Indices")
+            default_path = os.path.join(output_dir, "training_spectra_indices.csv").replace('\\', '/')
+            self.output_file.set_path(default_path)
+        elif not self.work_dir:
+            self.output_file.set_path("")

src/gui/panels/step8_ml_train_panel.py

@@ -85,10 +85,11 @@ class Step8MlTrainPanel(QWidget):
         self.init_ui()
 
     def init_ui(self):
+        self.setStyleSheet(ModernStylesheet.get_main_stylesheet())
+
         layout = QVBoxLayout()
-
-        # 标题
-
+        layout.setContentsMargins(24, 24, 24, 24)
+        layout.setSpacing(20)
 
         # 训练数据文件（用于独立运行）
         self.training_csv_file = FileSelectWidget(
@@ -547,13 +548,11 @@ class Step8MlTrainPanel(QWidget):
             if candidate:
                 self.training_csv_file.set_path(candidate)
 
-        # 2. 自动填充输出目录为 8_Machine_Learning_Models
-        if self.work_dir:
-            import os
+        # 2. 自动填充输出目录（仅在为空时填入默认路径，不创建目录）
+        if self.work_dir and not self.output_path.get_path():
             models_dir = os.path.join(self.work_dir, "8_Machine_Learning_Models").replace('\\', '/')
-            os.makedirs(models_dir, exist_ok=True)
             self.output_path.set_path(models_dir)
-        else:
+        elif not self.work_dir:
             self.output_path.set_path("")
 
     def _on_run_single_clicked(self):

src/gui/panels/step9_ml_predict_panel.py

@@ -183,11 +183,13 @@ class Step9MlPredictPanel(QWidget):
         output_layout.setSpacing(16)
         output_layout.setContentsMargins(20, 24, 20, 20)
 
-        # 输出文件路径
+        # 输出目录路径（目录模式：模型预测结果为多个 CSV 文件，存放到目录中）
         self.output_file = FileSelectWidget(
-            "输出路径:",
-            "CSV Files (*.csv);;All Files (*.*)"
+            "输出目录:",
+            "Directories"
         )
+        self.output_file.browse_btn.clicked.disconnect()
+        self.output_file.browse_btn.clicked.connect(self._browse_output_dir)
         output_layout.addWidget(self.output_file)
 
         # 完美对齐的底部按钮栏（已彻底移除多余的启用复选框）
@@ -400,31 +402,28 @@ class Step9MlPredictPanel(QWidget):
         factory = getattr(main_window, '_panel_factory', None) if main_window else None
 
         # 1. 智能挑选采样 CSV：优先"含 WQI 指数的测试集"（防止特征维度与训练时不匹配）
-        #    修复目标：用户在 Step 8 用 95 维 (50+45 WQI) 训练 → Step 9 默认读 50 维 raw sampling
-        #    时 inference_batch.preprocess_spectra 会触发"自动特征补全"逻辑；但若用户已经在
-        #    Step 10/手工把指数算到 CSV 里了，应该直接用那个文件（少走内存补全、避免 band 列顺序漂移）
         wqi_test_csv = self._resolve_latest_wqi_test_csv()
         if wqi_test_csv:
             self.sampling_csv_file.set_path(wqi_test_csv)
         elif factory:
-            # 兜底：拿第 4 步的纯原始采样光谱（旧行为保留）
+            # 兜底：拿第 4 步的纯原始采样光谱（仅当文件确实存在）
             step4_panel = factory.get_panel('step4_sampling')
             if step4_panel and hasattr(step4_panel, 'output_file'):
                 path = step4_panel.output_file.get_path()
-                if path: self.sampling_csv_file.set_path(path)
+                if path and os.path.exists(path):
+                    self.sampling_csv_file.set_path(path)
 
-        # 2. 拿第 8 步的模型目录
+        # 2. 拿第 8 步的模型目录（仅当目录确实存在）
         if factory:
             step8_panel = factory.get_panel('step8_ml_train')
             if step8_panel and hasattr(step8_panel, 'output_path'):
                 path = step8_panel.output_path.get_path()
-                if path: self.models_dir_file.set_path(path)
+                if path and os.path.isdir(path):
+                    self.models_dir_file.set_path(path)
 
-        # 3. 生成第 9 步的输出目录
-        if hasattr(self, 'work_dir') and self.work_dir:
-            import os
+        # 3. 生成第 9 步的输出目录（仅在为空时填入默认路径，不创建目录）
+        if hasattr(self, 'work_dir') and self.work_dir and not self.output_file.get_path():
             out_dir = os.path.join(self.work_dir, "9_ML_Prediction").replace('\\', '/')
-            os.makedirs(out_dir, exist_ok=True)
             self.output_file.set_path(out_dir)
 
     def _get_default_work_dir(self):
@@ -445,6 +444,15 @@ class Step9MlPredictPanel(QWidget):
         if dir_path:
             self.models_dir_file.set_path(dir_path)
 
+    def _browse_output_dir(self):
+        """浏览预测输出目录"""
+        default = self._get_default_work_dir()
+        if default:
+            default = os.path.join(default, '9_ML_Prediction')
+        dir_path = QFileDialog.getExistingDirectory(self, "选择预测输出目录", default)
+        if dir_path:
+            self.output_file.set_path(dir_path)
+
     def get_config(self):
         """获取配置"""
         config = {