feat(visualization+report): 接入 Step9 浓度反演数据至可视化面板与报告生成器

src/gui/panels/visualization_panel.py

@@ -359,6 +359,64 @@ class VisualizationWorkerThread(QThread):
                             parts.append("采样点图: 跳过(无CSV)")
                     else:
                         parts.append("采样点图: 跳过(无影像)")
+
+                if self.extra.get("gen_concentration"):
+                    conc_dir = wp / "9_Concentration"
+                    conc_csv = conc_dir / "final_concentrations.csv"
+                    if conc_csv.is_file():
+                        charts_dir = conc_dir / "charts"
+                        charts_dir.mkdir(parents=True, exist_ok=True)
+                        try:
+                            import pandas as pd
+                            df = pd.read_csv(conc_csv)
+                            exclude_kw = (
+                                "wavelength", "lon", "lat", "utm_x", "utm_y",
+                                "x", "y", "coord", "longitude", "latitude",
+                                "sample_id", "id", "index", "name", "pixel",
+                            )
+                            conc_cols = [
+                                c for c in df.select_dtypes(include=[np.number]).columns
+                                if not any(k in str(c).lower() for k in exclude_kw)
+                            ]
+                            if conc_cols:
+                                orig_out = viz.output_dir
+                                viz.output_dir = str(charts_dir)
+                                output_dict = viz.plot_statistical_charts(
+                                    csv_path=str(conc_csv),
+                                    parameter_columns=conc_cols,
+                                )
+                                viz.output_dir = orig_out
+                                count = len([v for v in output_dict.values() if v])
+                                parts.append(f"浓度统计图: {count} 个")
+                                stats_rows = []
+                                for col in conc_cols:
+                                    s = df[col].dropna()
+                                    if len(s) == 0:
+                                        continue
+                                    stats_rows.append({
+                                        "参数": col,
+                                        "点位数": len(s),
+                                        "最小值": round(float(s.min()), 4),
+                                        "最大值": round(float(s.max()), 4),
+                                        "均值": round(float(s.mean()), 4),
+                                        "中位数": round(float(s.median()), 4),
+                                        "标准差": round(float(s.std()), 4) if len(s) > 1 else 0.0,
+                                    })
+                                if stats_rows:
+                                    pd.DataFrame(stats_rows).to_csv(
+                                        conc_dir / "statistics_summary.csv",
+                                        index=False,
+                                        encoding="utf-8-sig",
+                                    )
+                                    parts.append("浓度统计表: 已生成")
+                                else:
+                                    parts.append("浓度统计表: 跳过(无可用列)")
+                            else:
+                                parts.append("浓度统计图: 跳过(无可用浓度列)")
+                        except Exception as e:
+                            parts.append(f"浓度统计图: 失败({e})")
+                    else:
+                        parts.append("浓度统计图: 跳过(无浓度CSV)")
                 self.finished_ok.emit({"task": "generate_all_selected", "parts": parts})
             else:
                 self.failed.emit(f"未知可视化任务: {self.task}")
@@ -568,6 +626,7 @@ class ImageCategoryTree(QTreeWidget):
         "output_dir": "输出目录",
         "8_spatial_inversion": "空间反演",
         "4_processed_data": "处理数据",
+        "9_Concentration": "物理反演浓度分布",
     }
 
     def __init__(self, parent=None):
@@ -767,6 +826,7 @@ class ImageCategoryTree(QTreeWidget):
                 self._work_path / "3_deglint",
                 self._work_path / "1_water_mask",
                 self._work_path / "9_water_quality_prediction",
+                self._work_path / "9_Concentration",
             ]
 
             # 只保留存在的目录，并补充工作根目录作为兜底