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

src/postprocessing/report_word.py

@@ -834,7 +834,12 @@ class WaterQualityReportGenerator:
             figure_counter = self._add_result_analysis_section(
                 doc, vis_dir, figure_counter, all_image_analyses, progress=progress
             )
-            
+
+            # 物理模型反演浓度统计与分析（第4.1节）
+            figure_counter = self._add_physical_inversion_section(
+                doc, self.work_dir, figure_counter, all_image_analyses, progress=progress
+            )
+
             # 设置页眉和页码（从正文开始）
             self._setup_header_and_footer(section)
             
@@ -1747,6 +1752,90 @@ class WaterQualityReportGenerator:
         doc.add_page_break()
         return start_figure_num + (1 if heatmap_path.exists() else 0)
 
+    def _add_physical_inversion_section(
+        self,
+        doc: Document,
+        work_dir: Path,
+        start_figure_num: int = 1,
+        all_image_analyses: Optional[List[Dict[str, Any]]] = None,
+        progress=None,
+    ) -> int:
+        """新增章节：物理模型反演浓度统计与分析（第4节之后）"""
+        conc_dir = work_dir / "9_Concentration"
+        if not conc_dir.is_dir():
+            doc.add_paragraph("[物理反演浓度章节：9_Concentration 目录不存在，已跳过]")
+            return start_figure_num
+
+        stats_csv = conc_dir / "statistics_summary.csv"
+        charts_dir = conc_dir / "charts"
+
+        h = doc.add_heading("4.1 物理模型反演浓度统计与分析", level=2)
+        self._style_heading(h, level=2)
+
+        fig_num = start_figure_num
+
+        if stats_csv.is_file():
+            try:
+                stats_df = pd.read_csv(stats_csv)
+                table = doc.add_table(rows=1, cols=len(stats_df.columns))
+                table.style = "Table Grid"
+                hdr_cells = table.rows[0].cells
+                for i, col_name in enumerate(stats_df.columns):
+                    hdr_cells[i].text = str(col_name)
+                    for run in hdr_cells[i].paragraphs[0].runs:
+                        run.font.name = self.chinese_font
+                        run.font.size = Pt(10)
+                        run.font.bold = True
+                        run._element.rPr.rFonts.set(qn('w:eastAsia'), self.chinese_font)
+                for _, row_data in stats_df.iterrows():
+                    row_cells = table.add_row().cells
+                    for i, val in enumerate(row_data):
+                        row_cells[i].text = str(val)
+                        for run in row_cells[i].paragraphs[0].runs:
+                            run.font.name = self.chinese_font
+                            run.font.size = Pt(10)
+                            run._element.rPr.rFonts.set(qn('w:eastAsia'), self.chinese_font)
+                doc.add_paragraph()
+            except Exception as e:
+                doc.add_paragraph(f"[浓度统计表插入失败: {e}]")
+        else:
+            doc.add_paragraph("[浓度统计表不存在: statistics_summary.csv]")
+
+        if charts_dir.is_dir():
+            image_extensions = ['*.png', '*.jpg', '*.jpeg', '*.tif', '*.tiff']
+            chart_files: List[Path] = []
+            for ext in image_extensions:
+                chart_files.extend(sorted(charts_dir.glob(ext)))
+            for chart_file in chart_files:
+                caption_text = f"图{fig_num} {chart_file.stem} 分布图"
+                if self._add_image_with_caption(doc, str(chart_file), caption_text, width=Inches(5.5)):
+                    if all_image_analyses is not None:
+                        image_type = "boxplot" if "boxplot" in chart_file.stem.lower() else "distribution"
+                        analysis_text = self._analyze_and_cache_image(
+                            image_path=chart_file,
+                            image_type=image_type,
+                            param=chart_file.stem,
+                            figure_num=fig_num,
+                        )
+                        self._add_ai_analysis_paragraph(doc, analysis_text)
+                        all_image_analyses.append({
+                            "figure_num": fig_num,
+                            "param": chart_file.stem,
+                            "image_type": image_type,
+                            "image_name": chart_file.name,
+                            "analysis": analysis_text,
+                        })
+                    fig_num += 1
+                try:
+                    if progress is not None:
+                        progress.update(1)
+                except Exception:
+                    pass
+        else:
+            doc.add_paragraph("[浓度图表目录不存在: 9_Concentration/charts/]")
+
+        return fig_num
+
 # ==================== 使用示例 ====================
 
 def generate_full_water_quality_report(