部分暴雨灾害链报告产出，部分内容待完善

src/main/java/com/gis/xian/service/impl/IReportOutputServiceImpl.java

@@ -102,16 +102,18 @@ public class IReportOutputServiceImpl implements ReportOutputService {
 
         // 获取降雨概况
         List<RainfallDistrictSummaryResponseDTO> rainData = fetchRainData();
-        List<String> districtNames = top3DistrictNames(rainData);
+        List<String> allDistricts = allDistrictNames(rainData);
+        List<String> top3Districts = top3DistrictNames(rainData);
 
         // 获取风险统计
-        int riskCount = sumCount(riskSpotsMapper.queryRiskNumberByDistrictName(districtNames));
+        int riskCount = sumCount(riskSpotsMapper.queryRiskNumberByDistrictName(top3Districts));
-        int hiddenCount = sumCount(hiddenDangerSpotsMapper.queryHiddenDangerNumberByDistrictName(districtNames));
+        int hiddenCount = sumCount(hiddenDangerSpotsMapper.queryHiddenDangerNumberByDistrictName(top3Districts));
-        int predictPointNum = inferenceResultMapper.getTheNumberOfPredictedPoints();
+        int predictPointNum = sumCount(riskSpotsMapper.queryRiskNumberByDistrictName(allDistricts))
+                + sumCount(hiddenDangerSpotsMapper.queryHiddenDangerNumberByDistrictName(allDistricts));
 
         // 构建模板数据模型
         Map<String, Object> model = buildTemplateModel(sim, disasterDataList, rainData,
-                districtNames, riskCount, hiddenCount, predictPointNum);
+                allDistricts, top3Districts, riskCount, hiddenCount, predictPointNum);
 
         // 渲染输出
         return renderReport(
@@ -144,6 +146,16 @@ public class IReportOutputServiceImpl implements ReportOutputService {
         return resp != null ? resp.getData() : Collections.emptyList();
     }
 
+    /**
+     * 全部行政区名称
+     */
+    private List<String> allDistrictNames(List<RainfallDistrictSummaryResponseDTO> rainData) {
+        return rainData.stream()
+                .filter(d -> d.getDistrictName() != null && !d.getDistrictName().isEmpty())
+                .map(RainfallDistrictSummaryResponseDTO::getDistrictName)
+                .collect(Collectors.toList());
+    }
+
     /**
      * 降雨量前3行政区
      */
@@ -195,7 +207,7 @@ public class IReportOutputServiceImpl implements ReportOutputService {
                     .map(spot -> {
                         Double prob = probabilities.get(spot.getId() + "_1");
                         if (prob == null) return null;
-                        String level = prob >= 0.70 ? "高" : "中";
+                        String level = prob >= 70 ? "高" : "中";
                         return new DisasterRiskData.SpotRisk()
                                 .setPosition(spot.getPosition())
                                 .setProbability(prob)
@@ -242,7 +254,8 @@ public class IReportOutputServiceImpl implements ReportOutputService {
      * @param sim              模拟结果
      * @param disasterDataList 灾害数据
      * @param rainData         降雨数据
-     * @param districtNames    灾害名称
+     * @param allDistricts     所有灾害名称
+     * @param top3Districts    top3灾害名称
      * @param riskCount        灾害数量
      * @param hiddenCount      隐患数量
      * @param predictPointNum  预测点数
@@ -252,7 +265,8 @@ public class IReportOutputServiceImpl implements ReportOutputService {
             XianInferenceResult sim,
             List<DisasterRiskData> disasterDataList,
             List<RainfallDistrictSummaryResponseDTO> rainData,
-            List<String> districtNames,
+            List<String> allDistricts,
+            List<String> top3Districts,
             int riskCount,
             int hiddenCount,
             int predictPointNum) {
@@ -263,10 +277,10 @@ public class IReportOutputServiceImpl implements ReportOutputService {
         // 基础文本
         m.put("报告时间", DateTimeUtils.datetimeFormat(sim.getOccurredTime(), "MM月dd日HH时mm分"));
         m.put("降雨时间", DateTimeUtils.datetimeFormat(sim.getOccurredTime(), "yyyy年MM月dd日HH时"));
-        m.put("降雨地区", String.join("、", districtNames));
+        m.put("降雨地区", String.join("、", allDistricts));
         m.put("持续时间", cond.getDuration() == null ? 72 : cond.getDuration());
-        m.put("降雨量", buildRainfallStr(rainData, districtNames));
+        m.put("降雨量", buildRainfallStr(rainData, allDistricts));
-        m.put("降雨集中区域", districtNames.isEmpty() ? "" : districtNames.get(0));
+        m.put("降雨集中区域", String.join("、", top3Districts));
         m.put("风险区数量", riskCount);
         m.put("隐患点数量", hiddenCount);
         m.put("致灾因子", String.join("、", reportProperties.getDisasterCausingFactors().getRainfall().getType()) + "等");

src/main/java/com/gis/xian/utils/ReportTableBuilder.java

@@ -15,7 +15,7 @@ import java.util.concurrent.atomic.AtomicInteger;
  */
 public class ReportTableBuilder {
 
-    private static final DecimalFormat PCT_FMT = new DecimalFormat("0.00%");
+    private static final DecimalFormat PCT_FMT = new DecimalFormat("0.00");
 
     /**
      * 构建灾害风险表（四列：序号、位置、发生概率、灾害等级）
@@ -34,7 +34,7 @@ public class ReportTableBuilder {
             builder.addRow(Rows.of(
                     String.valueOf(idx.getAndIncrement()),
                     spot.getPosition(),
-                    PCT_FMT.format(spot.getProbability()),
+                    PCT_FMT.format(spot.getProbability()) + "%",
                     spot.getRiskLevel()
             ).center().create());
         }