Riku
2025-10-21 ce17d42203a17120736d796d0e83b3742c4ec441
src/views/historymode/component/MissionReport.vue
@@ -14,6 +14,21 @@
        ></OptionLocation2>
      </el-form-item>
      <OptionTime v-model="formObj.timeArray"></OptionTime>
      <el-form-item label="区县筛选" prop="removeOtherDistrict">
        <el-checkbox v-model="formObj.removeOtherDistrict"
          >移除其他区县</el-checkbox
        >
      </el-form-item>
      <el-form-item label="污染源筛选" prop="removeNoPollutedSource">
        <el-checkbox v-model="formObj.removeNoPollutedSource"
          >移除未发现污染源的线索</el-checkbox
        >
      </el-form-item>
      <el-form-item label="隐患区域" prop="showPollutedArea">
        <el-checkbox v-model="formObj.showPollutedArea"
          >将典型隐患区域表格作为附件展示</el-checkbox
        >
      </el-form-item>
      <el-form-item>
        <el-button
          type="primary"
@@ -23,6 +38,36 @@
        >
          下载报告
        </el-button>
        <!-- <el-button
          type="primary"
          class="el-button-custom"
          @click="handleGenerateImg"
          :loading="docLoading"
        >
          生成图片
        </el-button> -->
      </el-form-item>
      <!-- <el-form-item>
        <el-image :src="base64Url" fit="fill" :preview-src-list="[base64Url]" />
      </el-form-item> -->
      <el-form-item>
        <el-button
          type="primary"
          class="el-button-custom"
          @click="handleMixClick"
          :loading="docLoading"
        >
          生成网格图片
        </el-button>
        <el-form-item>
          <el-form-item>
            <el-image
              :src="gridBase64Url"
              fit="fill"
              :preview-src-list="[gridBase64Url]"
            />
          </el-form-item>
        </el-form-item>
      </el-form-item>
    </el-form>
  </CardDialog>
@@ -31,14 +76,39 @@
import { computed, ref } from 'vue';
import moment from 'moment';
import dataAnalysisApi from '@/api/dataAnalysisApi';
import gridApi from '@/api/gridApi';
import { exportDocx } from '@/utils/doc';
import { radioOptions } from '@/constant/radio-options';
import { TYPE0 } from '@/constant/device-type';
import { FactorDatas } from '@/model/FactorDatas';
import factorDataParser from '@/utils/chart/factor-data-parser';
import chartToImg from '@/utils/chart/chart-to-img';
import chartMap from '@/utils/chart/chart-map';
import chartMapAmap from '@/utils/chart/chart-map-amap';
import { Legend } from '@/model/Legend';
import { getHexColor, getColorBetweenTwoColors } from '@/utils/color';
import { getGridDataDetailFactorValue } from '@/model/GridDataDetail';
import { factorName } from '@/constant/factor-name';
// 借用卫星遥测模块中的100米网格
const props = defineProps({
  groupId: {
    type: Number,
    default: import.meta.env.VITE_DATA_MODE == 'jingan' ? 2 : 3
  }
});
const formObj = ref({
  timeArray: [new Date('2025-07-01T00:00:00'), new Date('2025-08-31T23:59:59')],
  timeArray: [new Date('2025-07-01T00:00:00'), new Date('2025-09-30T23:59:59')],
  location: {}
});
const docLoading = ref(false);
const base64Url = ref(null);
const gridBase64Url = ref(null);
const gridCellList = ref([]);
const params = computed(() => {
  return {
@@ -53,7 +123,10 @@
      cityName: formObj.value.location.cName,
      districtCode: formObj.value.location.dCode,
      districtName: formObj.value.location.dName
    }
    },
    removeOtherDistrict: formObj.value.removeOtherDistrict,
    removeNoPollutedSource: formObj.value.removeNoPollutedSource,
    factorTypes: radioOptions(TYPE0).map((e) => e.name)
  };
});
@@ -68,6 +141,7 @@
  srySceneCount: 5,
  sryProbByFactor:
    '颗粒物(PM)相关X处,占比 %,主要涉及工地扬尘污染问题、道路扬尘污染问题等;VOC相关X处,占比 %,主要涉及加油站油气泄露、餐饮油烟污染等',
  sryFocusRegion: '聚焦区域',
  missionInfoList: [
    {
      missionCode: '',
@@ -76,31 +150,102 @@
      _airQulity: 'AQI:30(优)',
      mainFactor: '',
      _abnormalFactors: '',
      sceneCount: 0
      sceneCount: 0,
      _kilometres: '1000',
      _keyScene: '1个国控点(静安监测站)和2个市控点(和田中学、市北高新)',
      exceptionCount: 0,
      _focusScene: ''
    }
  ],
  missionDetailList: [
    {
      _index: 1,
      missionCode: '',
      _startTime: '2025年07月29日',
      _time: '09:00至14:30',
      _kilometres: '1000',
      _keyScene: '1个国控点(静安监测站)和2个市控点(和田中学、市北高新)',
      _dataStat:
        'PM₂.₅(范围30–35 μg/m³,均值35.51 μg/m³)、PM₁₀(范围25–68 μg/m³,均值38 μg/m³)、NO₂(范围22–54 μg/m³,均值32 μg/m³)、CO(范围2.08–6.39 mg/m³,均值3.398 mg/m³)和NO(范围1–106 μg/m³,均值20.97 μg/m³)',
      _dataStatistics: [
        {
          factor: 'PM10',
          minValue: 25,
          maxValue: 68,
          avgValue: 38
        }
      ],
      _airQulity: 'AQI:30(优)',
      aqi: 30,
      pollutionDegree: '优'
    }
  ],
  clueByAreaList: [
    {
      _index: 1,
      _area: '某某区域周边',
      clueByFactorList: [
        {
          factor: 'PM₂.₅',
          clues: [
            {
              _factorNames: 'PM2.5',
              _time: '10:22:28 - 10:22:34',
              _riskRegion: '长宁区清溪路可乐东路',
              _exceptionType: '快速上升',
              _chart: '',
              _conclusion:
                '在10:22:28至10:22:34之间,出现快速上升,VOC最低值为135.95μg/m³,最高值为135.95μg/m³,均值为135.95μg/m³,发现3个风险源,包含2个加油站,1个汽修。',
              _scenes:
                '1.上海依德汽车维修有限公司,汽修企业,位于上海市长宁区北虹路1079号,距仙霞站1887米。\r\n……'
            }
          ]
        }
      ]
    }
  ],
  gridFusionByAQIList: [
    {
      pollutionDegree: '优',
      _areaDes: '走航区域大小',
      _gridDes: '100米正方形网格',
      _missionDes: '20250729、20250730两次',
      highRiskGridList: [
        {
          index: 1,
          factor: 'PM2.5',
          // 标准色网格图
          gridImgUrl1: '',
          // 对比色网格图
          gridImgUrl2: '',
          factorValue: 20,
          // 四至范围,顺序为最小经度,最大经度,最小纬度,最大纬度
          bounds: [121.4945, 121.4955, 31.2304, 31.2314],
          _boundsDes: '四至范围',
          // 涉及街镇
          town: '',
          _scenesDes: '涉及的污染场景'
        }
      ]
    }
  ]
};
const handleClick = () => {
  generateMissionSummary(params.value).then((res) => {
    // generateDocx();
    generateMissionList(params.value).then((res) => {
      generateMissionDetail(params.value).then((res) => {
        //     generateClueByRiskArea(params.value).then((res) => {});
  docLoading.value = true;
  generateMissionSummary(params.value).then(() => {
    generateMissionList(params.value).then(() => {
      generateMissionDetail(params.value).then(() => {
        generateClueByRiskArea(params.value).then(() => {
          generateGridFusion(params.value).then(() => {
            generateDocx();
          });
        });
      });
    });
  });
};
const handleGenerateImg = () => {
  generateClueByRiskArea(params.value).then(() => {
    generateDocx();
  });
};
@@ -110,6 +255,10 @@
      new Date(res.data.startTime),
      new Date(res.data.endTime)
    );
    templateParam.subTitle =
      templateParam.sryTime.indexOf('季度') !== -1
        ? templateParam.sryTime.replace(/(.*)/, '')
        : templateParam.sryTime;
    templateParam.sryArea = res.data.area.districtName;
    templateParam.sryCount = res.data.count;
    templateParam.sryKm = Math.round(res.data.kilometres / 1000);
@@ -127,6 +276,7 @@
        return `${item.first}相关${item.second}处,占比 ${Math.round(item.third * 1000) / 10}%,主要涉及${getPollutingProblemTypes(item.first)}等`;
      })
      .join(';');
    templateParam.sryFocusRegion = res.data.focusRegion.join('、');
  });
}
@@ -134,21 +284,10 @@
  return dataAnalysisApi.fetchMissionList(param).then((res) => {
    templateParam.missionInfoList = res.data.map((item) => {
      item._time = formatDateTimeRange(item.startTime, item.endTime);
      item._airQulity = `AQI:${item.aqi}(${item.pollutionDegree})`;
      item._airQulity = `${item.aqi}(${item.pollutionDegree})`;
      item._abnormalFactors = item.abnormalFactors
        .map((factor) => factor.des)
        .map((factor) => factorName[factor])
        .join('、');
      return item;
    });
  });
}
function generateMissionDetail(param) {
  return dataAnalysisApi.fetchMissionDetail(param).then((res) => {
    templateParam.missionDetailList = res.data.map((item) => {
      const t = formatDateTimeRange(item.startTime, item.endTime).split(' ');
      item._startTime = t[0];
      item._time = t[1];
      item._kilometres = Math.round(item.kilometres / 1000);
      const keySceneMap = new Map();
@@ -156,7 +295,7 @@
        if (!keySceneMap.has(e.type)) {
          keySceneMap.set(e.type, { scenes: [], count: 0 });
        }
        keySceneMap.get(e.type).scenes.push(e.scene);
        keySceneMap.get(e.type).scenes.push(e);
        keySceneMap.get(e.type).count++;
      });
      item._keyScene = [...keySceneMap]
@@ -165,12 +304,36 @@
            `${info.count}个${type}(${info.scenes.map((s) => s.name).join('、')})`
        )
        .join('、');
      item._dataStat = item.dataStatistic
        .map(
          (e) =>
            `${e.factor.des}(范围${e.minValue}–${e.maxValue}μg/m³,均值${e.avgValue}μg/m³)`
        )
        .join('、');
      item._focusScene =
        item.scenes.length > 0
          ? item.scenes.map((s) => s.name).join('、')
          : '道路交通密集区和部分施工周边';
      return item;
    });
  });
}
function generateMissionDetail(param) {
  return dataAnalysisApi.fetchMissionDetail(param).then((res) => {
    templateParam.missionDetailList = res.data.map((item, index) => {
      const t = formatDateTimeRange(item.startTime, item.endTime).split(' ');
      item._index = index + 1;
      item._startTime = t[0];
      item._time = t[1];
      item._kilometres = Math.round(item.kilometres / 1000);
      item._airQulity = `${item.aqi}(${item.pollutionDegree})`;
      const factorNames = radioOptions(TYPE0).map((e) => e.name);
      item._dataStatistics = item.dataStatistics.filter((e) => {
        return factorNames.indexOf(e.factor) != -1;
      });
      radioOptions(TYPE0).forEach((f) => {
        const _factor = item.dataStatistics.find((e) => e.factor == f.name);
        item[`avgValue_${f.name}`] = _factor?.avgValue.toFixed(0) ?? '-';
        item[`maxValue_${f.name}`] = _factor?.maxValue.toFixed(0) ?? '-';
        item[`minValue_${f.name}`] = _factor?.minValue.toFixed(0) ?? '-';
      });
      return item;
    });
@@ -178,19 +341,349 @@
}
function generateClueByRiskArea(param) {
  return dataAnalysisApi.fetchClueByRiskArea(param).then((res) => {});
  const _param = {
    area: param.area,
    startTime: param.startTime,
    endTime: param.endTime,
    removeOtherDistrict: param.removeOtherDistrict,
    removeNoPollutedSource: param.removeNoPollutedSource
  };
  return dataAnalysisApi.fetchClueByRiskArea(_param).then((res) => {
    templateParam.showPollutedArea = formObj.value.showPollutedArea;
    templateParam.clueByAreaList = res.data
      .groupBy((e) => e.township)
      .map((item, index) => {
        const { key: township, values: clues } = item;
        return {
          _index: index + 1,
          // _area: `${item.sceneInfo.type}${item.sceneInfo.name}周边`,
          _area: `${township}`,
          clueByFactorList: clues
            .groupBy((e) => e.factorTag)
            .map((item2, index2) => {
              const { key: factorTag, values: clues2 } = item2;
              const factorNames = [...new Set(clues2.flatMap((e) => e.factors))]
                .map((e) => factorName[e])
                .join('、');
              return {
                index: index2 + 1,
                factor: factorNames,
                clues: clues2.map((item3, index3) => {
                  const clue = item3.clue;
                  let _riskRegion = '';
                  if (
                    parseInt(clue.pollutedArea.distance) <
                    parseInt(clue.pollutedArea.distance2)
                  ) {
                    if (
                      clue.pollutedArea.address.indexOf(
                        clue.pollutedArea.streetNumber
                      ) == -1
                    ) {
                      _riskRegion +=
                        (clue.pollutedArea.address ?? '') +
                        '(' +
                        (clue.pollutedArea.street ?? '') +
                        (clue.pollutedArea.streetNumber ?? '') +
                        (clue.pollutedArea.direction ?? '') +
                        ')';
                    } else {
                      _riskRegion = clue.pollutedArea.address;
                    }
                  } else {
                    _riskRegion +=
                      (clue.pollutedArea.address ?? '') +
                      '(' +
                      (clue.pollutedArea.street ?? '') +
                      (clue.pollutedArea.roadinter ?? '') +
                      ')';
                  }
                  return {
                    index: index3 + 1 + '',
                    showPollutedArea: formObj.value.showPollutedArea,
                    _title:
                      // (clue.pollutedArea.street ?? '') +
                      // (clue.pollutedArea.streetNumber ?? '') +
                      // (clue.pollutedArea.direction ?? ''),
                      clue.pollutedArea.address ?? '',
                    _factorNames: Object.keys(clue.pollutedData.statisticMap)
                      .map((e) => factorName[e])
                      .join('、'),
                    _time:
                      moment(clue.pollutedData.startTime).format(
                        'YYYY-MM-DD HH:mm:ss'
                      ) +
                      ' - ' +
                      moment(clue.pollutedData.endTime).format('HH:mm:ss'),
                    _riskRegion: _riskRegion,
                    _exceptionType: clue.pollutedData.exception,
                    _images: generateChartImg(clue.pollutedData),
                    _conclusion: clue.pollutedSource.conclusion,
                    _hasScene: clue.pollutedSource.sceneList.length > 0,
                    // _scenes:
                    //   clue.pollutedSource.sceneList.length > 0
                    //     ? clue.pollutedSource.sceneList
                    //         .map(
                    //           (s, index) =>
                    //             `${index + 1}. ${s.name},${s.type},位于${s.location},距${s.closestStation.name}${parseInt(s.length)}米;`
                    //         )
                    //         .join('\r\n')
                    //     : '无',
                    _scenes: clue.pollutedSource.sceneList.map((s, index) => {
                      return {
                        des: `${index + 1}. ${s.name},${s.type},位于${s.location},距${s.closestStation.name}${parseInt(s.length)}米;`
                      };
                    })
                  };
                })
              };
            })
        };
      });
  });
}
function generateChartImg(pollutedData) {
  const exceptionIndexArr = [];
  pollutedData.dataVoList.forEach((e) => {
    const i = pollutedData.historyDataList.findIndex((v) => v.time == e.time);
    exceptionIndexArr.push([i - 1 < 0 ? 0 : i - 1, i]);
  });
  const factorDatas = new FactorDatas();
  const images = [];
  factorDatas.setData(pollutedData.historyDataList, 0, () => {
    for (const key in pollutedData.statisticMap) {
      const value = pollutedData.statisticMap[key];
      const _chartOptions = factorDataParser.parseData(
        factorDatas,
        [
          {
            label: value.factorName,
            name: value.factorName,
            value: value.factorId + ''
          }
        ],
        false
      );
      _chartOptions.forEach((o) => {
        images.push({
          url: chartToImg.generateEchartsImage(o, exceptionIndexArr, 20)
        });
      });
      if (base64Url.value == null) {
        base64Url.value = images[0].url;
      }
    }
  });
  return images;
}
function generateGridFusion(param) {
  return dataAnalysisApi.fetchGridFusion(param).then((res) => {
    const promiseList = [];
    templateParam.gridFusionByAQIList = [];
    res.data.forEach((item) => {
      const scenes = [];
      item.missionList.forEach((m) => {
        m.keyScene.map((s) => {
          if (scenes.indexOf(s.name) == -1) {
            scenes.push(s.name);
          }
        });
      });
      const gfbAQI = {
        pollutionDegree: item.pollutionDegree,
        _areaDes: `走航区域经过${scenes.join('、')}`,
        _gridDes: `${item.gridLen}米正方形网格`,
        _missionDes: `${item.missionList.map((m) => m.missionCode).join('、')}共${item.missionList.length}次`
      };
      const _highRiskGridList = [];
      Object.keys(item.highRiskGridMap).forEach((key, i) => {
        const g = item.highRiskGridMap[key][0];
        const infoDes = item.highRiskGridMap[key].map((e) => {
          return {
            factorValue: e.factorValue,
            // 四至范围,顺序为最小经度,最大经度,最小纬度,最大纬度
            _boundsDes: `经度${e.bounds[0]}至${e.bounds[1]},纬度${e.bounds[2]}至${e.bounds[3]}`,
            // 涉及街镇
            town: e.town,
            _scenesDes:
              e.highRiskScenes.length > 0
                ? `涉及的污染场景包括${e.highRiskScenes.map((s) => s.name).join('、')}`
                : '网格内可能存在隐藏风险源'
          };
        });
        const infoDes2 = item.highRiskGridMap2[key].map((e) => {
          return {
            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${e.bounds[0]}至${e.bounds[1]},纬度${e.bounds[2]}至${e.bounds[3]}`,
            // 涉及街镇
            town: e.town,
            _scenesDes:
              e.highRiskScenes.length > 0
                ? `涉及的污染场景包括${e.highRiskScenes.map((s) => s.name).join('、')}`
                : '网格内可能存在隐藏风险源'
          };
        });
        // })
        // item.highRiskGridList.forEach((g, i) => {
        // const g = item.highRiskGridList[0];
        // const i = 0;
        const p = generateGridFusionImg(g.factorType, item.gridFusionList).then(
          (url) => {
            const { url1, url2 } = url;
            _highRiskGridList.push({
              index: i + 1,
              factor: factorName[g.factorType],
              // 标准色网格图
              gridImgUrl1: url1,
              // 对比色网格图
              gridImgUrl2: url2,
              infoDes: infoDes,
              infoDes2: infoDes2
            });
          }
        );
        promiseList.push(p);
      });
      gfbAQI.highRiskGridList = _highRiskGridList;
      templateParam.gridFusionByAQIList.push(gfbAQI);
    });
    return Promise.all(promiseList).then(() => {
      return templateParam.gridFusionByAQIList;
    });
    // templateParam.gridFusionByAQIList = res.data.map((item) => {
    //   const scenes = [];
    //   item.missionList.forEach((m) => {
    //     m.keyScene.map((s) => {
    //       if (scenes.indexOf(s.name) == -1) {
    //         scenes.push(s.name);
    //       }
    //     });
    //   });
    //   return {
    //     pollutionDegree: item.pollutionDegree,
    //     _areaDes: `走航区域经过${scenes.join('、')}`,
    //     _gridDes: `${item.gridLen}米正方形网格`,
    //     _missionDes: `${item.missionList.map((m) => m.missioncode).join('、')}${item.missionList.length}次`,
    //     highRiskGridList: item.highRiskGridList.map(async (g, i) => {
    //       const { url1, url2 } = await generateGridFusionImg(
    //         g.factorType,
    //         item.gridFusionList
    //       );
    //       return {
    //         index: i + 1,
    //         factor: g.factorType,
    //         // 标准色网格图
    //         gridImgUrl1: url1,
    //         // 对比色网格图
    //         gridImgUrl2: url2,
    //         factorValue: g.factorValue,
    //         // 四至范围,顺序为最小经度,最大经度,最小纬度,最大纬度
    //         _boundsDes: `经度${g.bounds[0]}至${g.bounds[1]},纬度${g.bounds[2]}至${g.bounds[3]}`,
    //         // 涉及街镇
    //         town: g.town,
    //         _scenesDes: g.highRiskScenes.map((s) => s.name).join('、')
    //       };
    //     })
    //   };
    // });
  });
}
async function generateGridFusionImg(factorName, dataList) {
  let min = 1000000;
  let max = 0;
  dataList.forEach((v) => {
    min = Math.min(min, getGridDataDetailFactorValue(v.data, factorName));
    max = Math.max(max, getGridDataDetailFactorValue(v.data, factorName));
  });
  const gridDataStand = [];
  const gridDataCustom = [];
  dataList.forEach((v) => {
    const data = getGridDataDetailFactorValue(v.data, factorName);
    const grid = v.cell;
    // 标准色
    const {
      color: color1,
      nextColor: nextColor1,
      range: range1,
      nextRange: nextRange1
    } = Legend.getStandardColorAndNext(factorName, data);
    const ratio1 = (data - range1) / (nextRange1 - range1);
    const _color1 = getColorBetweenTwoColors(
      color1.map((v) => v * 255),
      nextColor1.map((v) => v * 255),
      ratio1
    );
    // 对比色
    const { color, nextColor, range, nextRange } = Legend.getCustomColorAndNext(
      data,
      min,
      max
    );
    const ratio = (data - range) / (nextRange - range);
    const _color = getColorBetweenTwoColors(
      color.map((v) => v * 255),
      nextColor.map((v) => v * 255),
      ratio
    );
    gridDataStand.push({
      centerLng: grid.longitude,
      centerLat: grid.latitude,
      value: _color1,
      coordinates: [
        [grid.point1Lon, grid.point1Lat],
        [grid.point2Lon, grid.point2Lat],
        [grid.point3Lon, grid.point3Lat],
        [grid.point4Lon, grid.point4Lat]
      ]
    });
    gridDataCustom.push({
      centerLng: grid.longitude,
      centerLat: grid.latitude,
      value: _color,
      coordinates: [
        [grid.point1Lon, grid.point1Lat],
        [grid.point2Lon, grid.point2Lat],
        [grid.point3Lon, grid.point3Lat],
        [grid.point4Lon, grid.point4Lat]
      ]
    });
  });
  const url1 = await chartMap.generateGridMap(gridDataStand);
  const url2 = await chartMap.generateGridMap(gridDataCustom);
  if (gridBase64Url.value == null) {
    gridBase64Url.value = url1;
  }
  return {
    url1,
    url2
  };
}
function handleMixClick({ tags = [10, 11], factorName = 'PM25' }) {
  generateGridFusion(params.value).then(() => {});
}
function generateDocx() {
  docLoading.value = true;
  exportDocx(
    '/underway_season_report.docx',
    templateParam,
    `走航季度报告.docx`,
    {
      horizontalHeight: 368,
      verticalWidth: 266,
      scale: 1.367
      horizontalHeight: 250,
      verticalWidth: 568,
      scale: 2
    }
  ).finally(() => (docLoading.value = false));
}
@@ -233,19 +726,28 @@
  // 不是季度第一天则返回具体日期范围
  if (!quarter) {
    return `${startYear}年${startMonth + 1}月${startDate}日-${endYear}年${endMonth + 1}月${endDate}日`;
    // return `${startYear}年${startMonth + 1}月${startDate}日-${endYear}年${endMonth + 1}月${endDate}日`;
    return startYear == endYear
      ? `${startYear}年${startMonth + 1}月-${endMonth + 1}月`
      : `${startYear}年${startMonth + 1}月-${endYear}年${endMonth + 1}月`;
  }
  // 验证是否为对应季度最后一个月
  const expectedEndMonth = quarter * 3 - 1; // Q1:2(3月), Q2:5(6月), Q3:8(9月), Q4:11(12月)
  if (endMonth !== expectedEndMonth) {
    return `${startYear}年${startMonth + 1}月${startDate}日-${endYear}年${endMonth + 1}月${endDate}日`;
    // return `${startYear}年${startMonth + 1}月${startDate}日-${endYear}年${endMonth + 1}月${endDate}日`;
    return startYear == endYear
      ? `${startYear}年${startMonth + 1}月-${endMonth + 1}月`
      : `${startYear}年${startMonth + 1}月-${endYear}年${endMonth + 1}月`;
  }
  // 验证是否为季度最后一天
  const lastDayOfEndMonth = new Date(endYear, endMonth + 1, 0).getDate();
  if (endDate !== lastDayOfEndMonth) {
    return `${startYear}年${startMonth + 1}月${startDate}日-${endYear}年${endMonth + 1}月${endDate}日`;
    // return `${startYear}年${startMonth + 1}月${startDate}日-${endYear}年${endMonth + 1}月${endDate}日`;
    return startYear == endYear
      ? `${startYear}年${startMonth + 1}月-${endMonth + 1}月`
      : `${startYear}年${startMonth + 1}月-${endYear}年${endMonth + 1}月`;
  }
  const quarterNames = ['', '第一季度', '第二季度', '第三季度', '第四季度'];
@@ -312,3 +814,8 @@
  return `${datePart} ${startTimePart}至${endTimePart}`;
}
</script>
<style scoped>
.el-checkbox {
  --el-checkbox-text-color: white;
}
</style>