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@@ -0,0 +1,349 @@
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+package line_feature
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+
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+import (
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+ "errors"
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+ "github.com/shopspring/decimal"
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+ "hongze/hongze_chart_lib/models"
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+ "hongze/hongze_chart_lib/models/data_manage/line_feature/response"
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+ "hongze/hongze_chart_lib/services/data"
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+ "hongze/hongze_chart_lib/utils"
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+ "time"
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+)
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+
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+// GetStandardDeviationData 获取标准差图表的指标数据
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+func GetStandardDeviationData(chartInfoId int, mappingInfo *models.ChartEdbInfoMapping, calculateValue int) (edbList []*models.ChartEdbInfoMapping, dataResp response.LineFeatureDataResp, err error, errMsg string) {
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+ edbList = make([]*models.ChartEdbInfoMapping, 0)
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+
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+ // 指标对应的所有数据
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+ _, edbList, err = data.GetEdbDataMapList(chartInfoId, 1, `公历`, ``, ``, []*models.ChartEdbInfoMapping{mappingInfo})
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+ if err != nil {
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+ return
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+ }
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+
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+ if len(edbList) != 1 {
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+ errMsg = `指标异常`
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+ err = errors.New(errMsg)
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+ return
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+ }
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+
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+ edb := edbList[0]
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+ dataList := edb.DataList.([]*models.EdbDataList)
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+ newDataList := make([]models.EdbDataList, 0)
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+ lenData := len(dataList)
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+
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+ var minVal, maxVal float64
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+ if lenData >= calculateValue {
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+ tmpDataList := make([]float64, 0)
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+ for _, tmpData := range dataList {
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+ tmpDataList = append(tmpDataList, tmpData.Value)
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+ }
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+ for i := calculateValue; i <= lenData; i++ {
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+ tmpV := utils.CalculateStandardDeviation(tmpDataList[i-calculateValue : i])
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+ tmpV, _ = decimal.NewFromFloat(tmpV).Round(4).Float64()
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+ newDataList = append(newDataList, models.EdbDataList{
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+ EdbDataId: i,
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+ EdbInfoId: edb.EdbInfoId,
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+ DataTime: dataList[i-1].DataTime,
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+ DataTimestamp: dataList[i-1].DataTimestamp,
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+ Value: tmpV,
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+ })
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+ if tmpV > maxVal {
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+ maxVal = tmpV
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+ }
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+ if tmpV < minVal {
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+ minVal = tmpV
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+ }
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+ }
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+ }
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+
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+ dataResp = response.LineFeatureDataResp{
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+ MaxData: maxVal,
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+ MinData: minVal,
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+ LatestDate: edb.LatestDate,
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+ EdbInfoCategoryType: edb.EdbInfoCategoryType,
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+ ChartColor: `#00F`,
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+ ChartStyle: `spline`,
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+ PredictChartColor: `#00F`,
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+ ChartType: 0,
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+ ChartWidth: 3,
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+ EdbName: "标准差",
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+ EdbNameEn: "standard deviation",
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+ Unit: edb.Unit,
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+ UnitEn: edb.UnitEn,
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+ IsAxis: 1,
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+ DataList: newDataList,
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+ }
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+
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+ return
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+}
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+
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+// GetPercentileData 获取百分位图表的指标数据
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+func GetPercentileData(chartInfoId int, mappingInfo *models.ChartEdbInfoMapping, calculateValue int, calculateUnit string) (edbList []*models.ChartEdbInfoMapping, dataResp response.LineFeatureDataResp, err error, errMsg string) {
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+ edbList = make([]*models.ChartEdbInfoMapping, 0)
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+ moveUnitDays, ok := utils.FrequencyDaysMap[calculateUnit]
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+ if !ok {
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+ errMsg = `错误的周期`
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+ err = errors.New(errMsg)
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+ return
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+ }
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+ calculateDay := calculateValue * moveUnitDays
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+ // 指标对应的所有数据
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+ _, edbList, err = data.GetEdbDataMapList(chartInfoId, 1, `公历`, ``, ``, []*models.ChartEdbInfoMapping{mappingInfo})
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+ if err != nil {
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+ return
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+ }
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+
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+ if len(edbList) != 1 {
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+ errMsg = `指标异常`
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+ err = errors.New(errMsg)
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+ return
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+ }
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+
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+ edb := edbList[0]
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+ dataList := edb.DataList.([]*models.EdbDataList)
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+ newDataList := make([]models.EdbDataList, 0)
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+
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+ var edbMinVal, edbMaxVal float64
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+ dataMap := make(map[time.Time]float64, 0)
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+ for _, tmpData := range dataList {
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+ currDateTime, _ := time.ParseInLocation(utils.FormatDate, tmpData.DataTime, time.Local)
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+ dataMap[currDateTime] = tmpData.Value
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+ }
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+
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+ //百分位：对所选指标滚动地取对应时间长度的数据值，取最大值Max，最小值Min，计算Max-Min，百分位=(现值-Min)/(Max-Min)，Max=Min时不予计算。
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+ for i, tmpData := range dataList {
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+ currDateTime, _ := time.ParseInLocation(utils.FormatDate, tmpData.DataTime, time.Local)
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+ maxVal := tmpData.Value
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+ minVal := tmpData.Value
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+ for k := 0; k < calculateDay; k++ {
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+ preVal, ok2 := dataMap[currDateTime.AddDate(0, 0, -k)]
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+ if ok2 {
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+ if preVal > maxVal {
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+ maxVal = preVal
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+ }
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+ if preVal < minVal {
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+ minVal = preVal
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+ }
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+ }
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+ }
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+
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+ if maxVal == minVal {
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+ continue
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+ }
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+ //百分位=(现值-Min)/(Max-Min)
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+ tmpV := (tmpData.Value - minVal) / (maxVal - minVal) * 100
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+ tmpV, _ = decimal.NewFromFloat(tmpV).Round(4).Float64()
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+ newDataList = append(newDataList, models.EdbDataList{
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+ EdbDataId: i,
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+ EdbInfoId: edb.EdbInfoId,
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+ DataTime: dataList[i].DataTime,
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+ DataTimestamp: dataList[i].DataTimestamp,
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+ Value: tmpV,
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+ })
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+
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+ if tmpV < edbMinVal {
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+ edbMinVal = tmpV
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+ }
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+ if tmpV > edbMaxVal {
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+ edbMaxVal = tmpV
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+ }
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+ }
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+
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+ dataResp = response.LineFeatureDataResp{
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+ MaxData: edbMaxVal,
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+ MinData: edbMinVal,
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+ LatestDate: edb.LatestDate,
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+ EdbInfoCategoryType: edb.EdbInfoCategoryType,
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+ ChartColor: `#00F`,
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+ ChartStyle: `spline`,
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+ PredictChartColor: `#00F`,
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+ ChartType: 0,
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+ ChartWidth: 3,
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+ EdbName: "百分位",
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+ EdbNameEn: "percentile",
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+ Unit: "%",
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+ UnitEn: "%",
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+ IsAxis: 1,
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+ DataList: newDataList,
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+ }
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+
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+ return
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+}
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+
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+// GetFrequencyDistributionData 获取频率分布的图表数据
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+func GetFrequencyDistributionData(chartInfoId int, mappingInfo *models.ChartEdbInfoMapping, dateType, stepVal int, startDate, endDate string) (edbList []*models.ChartEdbInfoMapping, dataResp response.FrequencyDistributionResp, err error, errMsg string) {
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+ XDataList := make([]float64, 0)
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+ // 频度
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+ Y1DataList := make([]response.FrequencyDistributionYData, 0)
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+ // 累计频率
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+ Y2DataList := make([]response.FrequencyDistributionYData, 0)
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+ edbList = make([]*models.ChartEdbInfoMapping, 0)
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+
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+ // 指标对应的所有数据
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+ _, edbList, err = data.GetEdbDataMapList(chartInfoId, 1, `公历`, startDate, endDate, []*models.ChartEdbInfoMapping{mappingInfo})
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+ if err != nil {
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+ return
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+ }
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+ if len(edbList) != 1 {
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+ err = errors.New("指标异常")
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+ return
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+ }
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+ startDateTime, _ := time.ParseInLocation(utils.FormatDate, startDate, time.Local)
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+ var endDateTime time.Time
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+ if endDate != `` {
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+ endDateTime, _ = time.ParseInLocation(utils.FormatDate, endDate, time.Local)
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+ }
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+
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+ edb := edbList[0]
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+ dataList := edb.DataList.([]*models.EdbDataList)
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+ if len(dataList) <= 0 {
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+ return
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+ }
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+
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+ // 非自定义
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+ if dateType != 8 {
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+ endDate = dataList[len(dataList)-1].DataTime
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+ endDateTime, err = time.ParseInLocation(utils.FormatDate, endDate, time.Local)
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+ if err != nil {
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+ return
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+ }
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+ //日期类型:1:最近3月；2:最近6月；3:最近1年；4:最近2年；5:最近3年；6:最近5年；7:最近10年，8:自定义时间
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+ startDateTime = utils.GetDateByDateType2(dateType, endDateTime)
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+ startDate = startDateTime.Format(utils.FormatDate)
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+
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+ newDataList := make([]*models.EdbDataList, 0)
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+ for _, v := range dataList {
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+ tmpDataTime, tmpErr := time.ParseInLocation(utils.FormatDate, v.DataTime, time.Local)
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+ if tmpErr != nil {
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+ err = tmpErr
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+ return
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+ }
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+ if tmpDataTime.Equal(startDateTime) || tmpDataTime.After(startDateTime) {
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+ newDataList = append(newDataList, v)
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+ }
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+
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+ }
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+ dataList = newDataList
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+ }
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+
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+ maxVal := dataList[0].Value
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+ minVal := dataList[0].Value
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+ dataValMap := make(map[float64]int)
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+ total := 0 // 数据总量
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+ for _, tmpData := range dataList {
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+ currDateTime, _ := time.ParseInLocation(utils.FormatDate, tmpData.DataTime, time.Local)
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+ if (currDateTime.Equal(startDateTime) || currDateTime.After(startDateTime)) && (endDateTime.IsZero() || currDateTime.Before(endDateTime)) {
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+ if maxVal < tmpData.Value {
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+ maxVal = tmpData.Value
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+ }
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+ if minVal > tmpData.Value {
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+ minVal = tmpData.Value
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+ }
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+
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+ num, ok := dataValMap[tmpData.Value]
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+ if ok {
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+ dataValMap[tmpData.Value] = num + 1
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+ } else {
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+ dataValMap[tmpData.Value] = 1
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+ }
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+ total++
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+ }
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+ }
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+
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+ if total <= 0 {
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+ errMsg = `没有数据`
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+ err = errors.New(errMsg)
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+ return
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+ }
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+
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+ // 最大最小值 向上/下取整
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+ minVal = utils.GetFloorNewNum(minVal, 2)
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+ maxVal = utils.GetCeilNewNum(maxVal, 2)
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+ //间距
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+ spacing, _ := (decimal.NewFromFloat(maxVal).Sub(decimal.NewFromFloat(minVal))).Div(decimal.NewFromInt(int64(stepVal))).Float64()
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+
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+ distributionDataNumMap := make(map[float64]int)
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+ for i := 1; i <= stepVal; i++ {
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+ tmpMinVal, _ := decimal.NewFromFloat(minVal).Add((decimal.NewFromFloat(spacing)).Mul(decimal.NewFromInt(int64(i - 1)))).Float64()
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+ tmpMaxVal, _ := decimal.NewFromFloat(minVal).Add((decimal.NewFromFloat(spacing)).Mul(decimal.NewFromInt(int64(i)))).Float64()
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+ XDataList = append(XDataList, tmpMinVal)
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+ distributionDataNumMap[tmpMinVal] = 0
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+ for tmpVal, num := range dataValMap {
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+ if tmpMinVal <= tmpVal {
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+ // 最后一期数据是要小于等于
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+ if i == stepVal {
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+ if tmpVal <= tmpMaxVal {
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+ distributionDataNumMap[tmpMinVal] += num
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+ }
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+ } else {
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+ if tmpVal < tmpMaxVal {
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+ distributionDataNumMap[tmpMinVal] += num
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+ }
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+ }
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+ }
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+ }
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+ }
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+
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+ var minFrequency, maxFrequency float64
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+ tmpNum := 0
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+ for k, tmpMinVal := range XDataList {
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+ // 数量
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+ frequencyYNum := distributionDataNumMap[tmpMinVal]
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+
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+ // 频率
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+ tmpFrequency, _ := decimal.NewFromInt(int64(frequencyYNum)).Div(decimal.NewFromInt(int64(total))).Mul(decimal.NewFromInt(100)).Round(4).Float64()
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+ Y1DataList = append(Y1DataList, response.FrequencyDistributionYData{
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+ X: tmpMinVal,
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+ Y: tmpFrequency,
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+ })
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+ if k == 0 {
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+ minFrequency = tmpFrequency
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+ maxFrequency = tmpFrequency
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+ } else {
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+ if tmpFrequency < minFrequency {
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+ minFrequency = tmpFrequency
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+ }
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+ if tmpFrequency > maxFrequency {
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+ maxFrequency = tmpFrequency
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+ }
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+ }
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+
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+ // 累计数
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+ tmpNum += frequencyYNum
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+ // 累计频率
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+ tmpTotalFrequency, _ := decimal.NewFromInt(int64(tmpNum)).Div(decimal.NewFromInt(int64(total))).Mul(decimal.NewFromInt(100)).Round(4).Float64()
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+ Y2DataList = append(Y2DataList, response.FrequencyDistributionYData{
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+ X: tmpMinVal,
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+ Y: tmpTotalFrequency,
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+ })
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+ }
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+
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+ newDataList := []response.FrequencyDistributionData{
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+ {
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+ Name: "频率",
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+ NameEn: "Frequency",
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+ Unit: "%",
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+ UnitEn: "%",
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+ Value: Y1DataList,
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+ Color: "#00F",
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+ IsAxis: 1,
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+ }, {
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+ Name: "累计频率",
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+ NameEn: "Total Frequency",
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+ Unit: "%",
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+ UnitEn: "%",
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+ Value: Y2DataList,
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+ Color: "#F00",
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+ IsAxis: 0,
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+ },
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+ }
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+ edbList[0].DataList = nil
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+ dataResp = response.FrequencyDistributionResp{
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+ LeftMinValue: minFrequency,
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+ LeftMaxValue: maxFrequency,
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+ RightMinValue: 0,
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+ RightMaxValue: 100,
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+ DataList: newDataList,
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+ }
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+ return
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+}
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