2025.10.18 修改嫉妒报告生成逻辑

feiyu02

2025-10-20 eb4111e0fd7110e5aa6a00608da2da9af21a3035

 src/views/historymode/component/MissionReport.vue

@@ -277,7 +277,7 @@
      item._time = formatDateTimeRange(item.startTime, item.endTime);
      item._airQulity = `AQI：${item.aqi}（${item.pollutionDegree}）`;
      item._abnormalFactors = item.abnormalFactors
        .map((factor) => factor)
        .map((factor) => factorName[factor])
        .join('、');
      item._kilometres = Math.round(item.kilometres / 1000);

@@ -321,9 +321,9 @@

      radioOptions(TYPE0).forEach((f) => {
        const _factor = item.dataStatistics.find((e) => e.factor == f.name);
        item[`avgValue_${f.name}`] = _factor?.avgValue ?? '-';
        item[`maxValue_${f.name}`] = _factor?.maxValue ?? '-';
        item[`minValue_${f.name}`] = _factor?.minValue ?? '-';
        item[`avgValue_${f.name}`] = _factor?.avgValue.toFixed(0) ?? '-';
        item[`maxValue_${f.name}`] = _factor?.maxValue.toFixed(0) ?? '-';
        item[`minValue_${f.name}`] = _factor?.minValue.toFixed(0) ?? '-';
      });

      return item;
@@ -350,14 +350,15 @@
          _area: `${township}`,
          clueByFactorList: clues
            .groupBy((e) => e.factorTag)
            .map((item2) => {
            .map((item2, index2) => {
              const { key: factorTag, values: clues2 } = item2;
              const factorNames = [...new Set(clues2.flatMap((e) => e.factors))]
                .map((e) => factorName(e))
                .map((e) => factorName[e])
                .join('、');
              return {
                index: index2 + 1,
                factor: factorNames,
                clues: clues2.map((clue) => {
                clues: clues2.map((item3, index3) => {
                  // const _riskRegion = [];
                  // if (clue.pollutedArea.address) {
                  //   _riskRegion.push(clue.pollutedArea.address);
@@ -368,13 +369,15 @@
                  // if (clue.pollutedArea.roadinter) {
                  //   _riskRegion.push(clue.pollutedArea.roadinter);
                  // }
                  const clue = item3.clue
                  return {
                    index: index3+1,
                    _title:
                      (clue.pollutedArea.street ?? '') +
                      (clue.pollutedArea.streetNumber ?? '') +
                      (clue.pollutedArea.direction ?? ''),
                    _factorNames: Object.keys(clue.pollutedData.statisticMap)
                      .map((e) => factorName(e))
                      .map((e) => factorName[e])
                      .join('、'),
                    _time:
                      moment(clue.pollutedData.startTime).format(
@@ -468,14 +471,14 @@

        const infoDes = item.highRiskGridMap[key].map((e) => {
          return {
            factorValue: g.factorValue,
            factorValue: e.factorValue,
            // 四至范围，顺序为最小经度，最大经度，最小纬度，最大纬度
            _boundsDes: `经度${g.bounds[0]}至${g.bounds[1]}，纬度${g.bounds[2]}至${g.bounds[3]}`,
            _boundsDes: `经度${e.bounds[0]}至${e.bounds[1]}，纬度${e.bounds[2]}至${e.bounds[3]}`,
            // 涉及街镇
            town: g.town,
            town: e.town,
            _scenesDes:
              g.highRiskScenes.length > 0
                ? `涉及的污染场景包括${g.highRiskScenes.map((s) => s.name).join('、')}`
              e.highRiskScenes.length > 0
                ? `涉及的污染场景包括${e.highRiskScenes.map((s) => s.name).join('、')}`
                : '网格内可能存在隐藏风险源'
          };
        });
@@ -488,7 +491,7 @@
            const { url1, url2 } = url;
            _highRiskGridList.push({
              index: i + 1,
              factor: factorName(g.factorType),
              factor: factorName[g.factorType],
              // 标准色网格图
              gridImgUrl1: url1,
              // 对比色网格图