fix: unicode获取AI预测模型图表

controllers/data_manage/chart_common.go

@@ -9,12 +9,15 @@ import (
 	"eta/eta_mobile/controllers/data_manage/line_feature"
 	"eta/eta_mobile/controllers/data_manage/range_analysis"
 	"eta/eta_mobile/models"
+	aiPredictModel "eta/eta_mobile/models/ai_predict_model"
 	"eta/eta_mobile/models/data_manage"
 	"eta/eta_mobile/models/system"
+	"eta/eta_mobile/services"
 	"eta/eta_mobile/services/data"
 	"eta/eta_mobile/services/data/excel"
 	"eta/eta_mobile/utils"
 	"fmt"
+	"strings"
 	"time"
 )
 
@@ -179,6 +182,29 @@ func (this *ChartInfoController) CommonChartInfoDetailFromUniqueCode() {
 		br.Success = true
 		br.Msg = "获取成功"
 		br.Data = resp
+	case utils.CHART_SOURCE_AI_PREDICT_MODEL_DAILY, utils.CHART_SOURCE_AI_PREDICT_MODEL_MONTHLY:
+		resp, isOk, msg, errMsg := GetAiPredictChartInfoDetailFromUniqueCode(chartInfo, isCache)
+		if !isOk {
+			if strings.Contains(errMsg, utils.ErrNoRow()) {
+				endInfoList := make([]*data_manage.ChartEdbInfoMapping, 0)
+				resp.EdbInfoList = endInfoList
+				resp.ChartInfo = chartInfo
+				resp.Status = false
+
+				br.Data = resp
+				br.Ret = 200
+				br.Success = true
+				br.Msg = "获取成功"
+				return
+			}
+			br.Msg = msg
+			br.ErrMsg = errMsg
+			return
+		}
+		br.Ret = 200
+		br.Success = true
+		br.Msg = "获取成功"
+		br.Data = resp
 	default:
 		br.Msg = "错误的图表"
 		br.ErrMsg = "错误的图表"
@@ -228,3 +254,112 @@ func getBalanceChartInfoDetailFromUniqueCode(chartInfo *data_manage.ChartInfoVie
 
 	return
 }
+
+// GetAiPredictChartInfoDetailFromUniqueCode 根据编码获取AI预测模型图表详情
+func GetAiPredictChartInfoDetailFromUniqueCode(chartInfo *data_manage.ChartInfoView, isCache bool) (resp *data_manage.ChartInfoDetailFromUniqueCodeResp, isOk bool, msg, errMsg string) {
+	var err error
+	msg = "获取成功"
+	defer func() {
+		if err != nil {
+			tips := fmt.Sprintf("UniqueCode获取图表详情失败, %v", err)
+			msg = "获取失败"
+			errMsg = fmt.Sprintf(tips)
+			utils.FileLog.Info(tips)
+		}
+	}()
+	if chartInfo == nil {
+		err = fmt.Errorf("图表信息不存在")
+		return
+	}
+	if chartInfo.Source != utils.CHART_SOURCE_AI_PREDICT_MODEL_DAILY && chartInfo.Source != utils.CHART_SOURCE_AI_PREDICT_MODEL_MONTHLY {
+		err = fmt.Errorf("图表来源有误, Source: %d", chartInfo.Source)
+		return
+	}
+	resp = new(data_manage.ChartInfoDetailFromUniqueCodeResp)
+
+	// 获取图表标的
+	edbMappings, e := data_manage.GetChartEdbMappingsByChartInfoId(chartInfo.ChartInfoId)
+	if e != nil {
+		err = fmt.Errorf("获取图表指标关联失败, %v", e)
+		return
+	}
+	if len(edbMappings) == 0 {
+		err = fmt.Errorf("图表指标关联不存在, %v", e)
+		return
+	}
+	indexId := edbMappings[0].EdbInfoId
+	if indexId <= 0 {
+		err = fmt.Errorf("图表标的有误")
+		return
+	}
+	indexOb := new(aiPredictModel.AiPredictModelIndex)
+	indexItem, e := indexOb.GetItemById(indexId)
+	if e != nil {
+		err = fmt.Errorf("获取图表标的失败, %v", e)
+		return
+	}
+	if indexItem != nil && indexItem.AiPredictModelIndexId <= 0 {
+		err = fmt.Errorf("图表标的不存在, IndexId: %d", indexId)
+		return
+	}
+
+	// 获取标的数据
+	indexData := make([]*aiPredictModel.AiPredictModelData, 0)
+	dataSource := aiPredictModel.ModelDataSourceDaily
+	if chartInfo.Source == utils.CHART_SOURCE_AI_PREDICT_MODEL_MONTHLY {
+		dataSource = aiPredictModel.ModelDataSourceMonthly
+	}
+	dataOb := new(aiPredictModel.AiPredictModelData)
+	dataCond := fmt.Sprintf(` AND %s = ?`, dataOb.Cols().IndexCode)
+	dataPars := make([]interface{}, 0)
+	dataPars = append(dataPars, indexItem.IndexCode)
+	list, e := dataOb.GetItemsByCondition(dataCond, dataPars, []string{}, fmt.Sprintf("%s DESC", dataOb.Cols().DataTime))
+	if e != nil {
+		err = fmt.Errorf("获取标的数据失败, %v", e)
+		return
+	}
+	for _, v := range list {
+		if v.Source == dataSource {
+			indexData = append(indexData, v)
+			continue
+		}
+	}
+
+	//判断是否存在缓存，如果存在缓存，那么直接从缓存中获取
+	key := data.GetChartInfoDataKey(chartInfo.ChartInfoId)
+	if utils.Re == nil && isCache {
+		if utils.Re == nil && utils.Rc.IsExist(key) {
+			if chartData, e := utils.Rc.RedisBytes(key); e == nil {
+				e = json.Unmarshal(chartData, &resp)
+				if e != nil || resp == nil {
+					return
+				}
+				isOk = true
+				return
+			}
+		}
+	}
+
+	// 图表详情
+	chartDetail, e := services.GetAiPredictChartDetailByData(indexItem, indexData, dataSource)
+	if e != nil {
+		err = fmt.Errorf("获取图表详情失败, %v", e)
+		return
+	}
+	resp.ChartInfo = chartDetail.ChartInfo
+	resp.EdbInfoList = chartDetail.EdbInfoList
+	resp.XEdbIdValue = chartDetail.XEdbIdValue
+	resp.YDataList = chartDetail.YDataList
+	resp.XDataList = chartDetail.XDataList
+	resp.BarChartInfo = chartDetail.BarChartInfo
+	resp.CorrelationChartInfo = chartDetail.CorrelationChartInfo
+	resp.DataResp = chartDetail.DataResp
+	resp.Status = true
+
+	if utils.Re == nil {
+		jsonData, _ := json.Marshal(resp)
+		_ = utils.Rc.Put(key, jsonData, 10*time.Minute)
+	}
+	isOk = true
+	return
+}

models/ai_predict_model/ai_predict_model_data.go

@@ -0,0 +1,81 @@
+package data_manage
+
+import (
+	"database/sql"
+	"fmt"
+	"github.com/beego/beego/v2/client/orm"
+	"strings"
+	"time"
+)
+
+const (
+	ModelDataSourceMonthly = 1 // 月度预测数据
+	ModelDataSourceDaily   = 2 // 日度预测数据
+)
+
+// AiPredictModelData AI预测模型标的数据
+type AiPredictModelData struct {
+	AiPredictModelDataId  int             `orm:"column(ai_predict_model_data_id);pk" gorm:"primaryKey"`
+	AiPredictModelIndexId int             `description:"标的ID"`
+	IndexCode             string          `description:"标的编码"`
+	DataTime              time.Time       `description:"数据日期"`
+	Value                 sql.NullFloat64 `description:"实际值"`
+	PredictValue          sql.NullFloat64 `description:"预测值"`
+	Direction             string          `description:"方向"`
+	DeviationRate         string          `description:"偏差率"`
+	CreateTime            time.Time       `description:"创建时间"`
+	ModifyTime            time.Time       `description:"修改时间"`
+	DataTimestamp         int64           `description:"数据日期时间戳"`
+	Source                int             `description:"来源：1-月度预测（默认）；2-日度预测"`
+}
+
+func (m *AiPredictModelData) TableName() string {
+	return "ai_predict_model_data"
+}
+
+type AiPredictModelDataCols struct {
+	PrimaryId             string
+	AiPredictModelIndexId string
+	IndexCode             string
+	DataTime              string
+	Value                 string
+	PredictValue          string
+	Direction             string
+	DeviationRate         string
+	CreateTime            string
+	ModifyTime            string
+	DataTimestamp         string
+	Source                string
+}
+
+func (m *AiPredictModelData) Cols() AiPredictModelDataCols {
+	return AiPredictModelDataCols{
+		PrimaryId:             "ai_predict_model_data_id",
+		AiPredictModelIndexId: "ai_predict_model_index_id",
+		IndexCode:             "index_code",
+		DataTime:              "data_time",
+		Value:                 "value",
+		PredictValue:          "predict_value",
+		Direction:             "direction",
+		DeviationRate:         "deviation_rate",
+		CreateTime:            "create_time",
+		ModifyTime:            "modify_time",
+		DataTimestamp:         "data_timestamp",
+		Source:                "source",
+	}
+}
+
+func (m *AiPredictModelData) GetItemsByCondition(condition string, pars []interface{}, fieldArr []string, orderRule string) (items []*AiPredictModelData, err error) {
+	o := orm.NewOrmUsingDB("data")
+	fields := strings.Join(fieldArr, ",")
+	if len(fieldArr) == 0 {
+		fields = `*`
+	}
+	order := fmt.Sprintf(`ORDER BY %s DESC`, m.Cols().CreateTime)
+	if orderRule != "" {
+		order = ` ORDER BY ` + orderRule
+	}
+	sqlRun := fmt.Sprintf(`SELECT %s FROM %s WHERE 1=1 %s %s`, fields, m.TableName(), condition, order)
+	_, err = o.Raw(sqlRun, pars...).QueryRows(&items)
+	return
+}

models/ai_predict_model/ai_predict_model_index.go

@@ -0,0 +1,96 @@
+package data_manage
+
+import (
+	"fmt"
+	"github.com/beego/beego/v2/client/orm"
+	"time"
+)
+
+// AiPredictModelIndex AI预测模型标的
+type AiPredictModelIndex struct {
+	AiPredictModelIndexId int       `orm:"column(ai_predict_model_index_id);pk" gorm:"primaryKey"`
+	IndexName             string    `description:"标的名称"`
+	IndexCode             string    `description:"自生成的指标编码"`
+	ClassifyId            int       `description:"分类ID"`
+	ModelFramework        string    `description:"模型框架"`
+	PredictDate           time.Time `description:"预测日期"`
+	PredictValue          float64   `description:"预测值"`
+	PredictFrequency      string    `description:"预测频度"`
+	DirectionAccuracy     string    `description:"方向准确度"`
+	AbsoluteDeviation     string    `description:"绝对偏差"`
+	ExtraConfig           string    `description:"模型参数"`
+	Sort                  int       `description:"排序"`
+	SysUserId             int       `description:"创建人ID"`
+	SysUserRealName       string    `description:"创建人姓名"`
+	LeftMin               string    `description:"图表左侧最小值"`
+	LeftMax               string    `description:"图表左侧最大值"`
+	CreateTime            time.Time `description:"创建时间"`
+	ModifyTime            time.Time `description:"修改时间"`
+}
+
+func (m *AiPredictModelIndex) TableName() string {
+	return "ai_predict_model_index"
+}
+
+type AiPredictModelIndexCols struct {
+	PrimaryId         string
+	IndexName         string
+	IndexCode         string
+	ClassifyId        string
+	ModelFramework    string
+	PredictDate       string
+	PredictValue      string
+	DirectionAccuracy string
+	AbsoluteDeviation string
+	ExtraConfig       string
+	Sort              string
+	SysUserId         string
+	SysUserRealName   string
+	LeftMin           string
+	LeftMax           string
+	CreateTime        string
+	ModifyTime        string
+}
+
+func (m *AiPredictModelIndex) Cols() AiPredictModelIndexCols {
+	return AiPredictModelIndexCols{
+		PrimaryId:         "ai_predict_model_index_id",
+		IndexName:         "index_name",
+		IndexCode:         "index_code",
+		ClassifyId:        "classify_id",
+		ModelFramework:    "model_framework",
+		PredictDate:       "predict_date",
+		PredictValue:      "predict_value",
+		DirectionAccuracy: "direction_accuracy",
+		AbsoluteDeviation: "absolute_deviation",
+		ExtraConfig:       "extra_config",
+		Sort:              "sort",
+		SysUserId:         "sys_user_id",
+		SysUserRealName:   "sys_user_real_name",
+		LeftMin:           "left_min",
+		LeftMax:           "left_max",
+		CreateTime:        "create_time",
+		ModifyTime:        "modify_time",
+	}
+}
+
+func (m *AiPredictModelIndex) GetItemById(id int) (item *AiPredictModelIndex, err error) {
+	o := orm.NewOrmUsingDB("data")
+	sql := fmt.Sprintf(`SELECT * FROM %s WHERE %s = ? LIMIT 1`, m.TableName(), m.Cols().PrimaryId)
+	err = o.Raw(sql, id).QueryRow(&item)
+	return
+}
+
+type AiPredictModelIndexExtraConfig struct {
+	MonthlyChart struct {
+		LeftMin string `description:"图表左侧最小值"`
+		LeftMax string `description:"图表左侧最大值"`
+		Unit    string `description:"单位"`
+	}
+	DailyChart struct {
+		LeftMin           string `description:"图表左侧最小值"`
+		LeftMax           string `description:"图表左侧最大值"`
+		Unit              string `description:"单位"`
+		PredictLegendName string `description:"预测图例的名称（通常为Predicted）"`
+	}
+}

models/data_manage/chart_edb_mapping.go

@@ -331,3 +331,9 @@ func GetChartMappingList(chartInfoId int) (list []*ChartEdbMapping, err error) {
 	_, err = o.Raw(sql, chartInfoId).QueryRows(&list)
 	return
 }
+
+func GetChartEdbMappingsByChartInfoId(chartInfoId int) (list []*ChartEdbInfoMapping, err error) {
+	sql := ` SELECT * FROM chart_edb_mapping AS a WHERE chart_info_id = ? ORDER BY chart_edb_mapping_id ASC`
+	_, err = orm.NewOrmUsingDB("data").Raw(sql, chartInfoId).QueryRows(&list)
+	return
+}

models/data_manage/chart_info.go

@@ -2766,3 +2766,12 @@ type ExcelChartEdbView struct {
 	DataSequenceStr string `description:"数据序列选区"`
 	FromTag         string `description:"标签"`
 }
+
+// GetAiPredictChartInfoByIndexId 获取AI预测模型图表
+func GetAiPredictChartInfoByIndexId(source, indexId int) (item *ChartInfo, err error) {
+	sql := `SELECT * FROM chart_info WHERE chart_info_id = (
+		  SELECT chart_info_id FROM chart_edb_mapping WHERE source = ? AND edb_info_id = ?
+		) LIMIT 1`
+	err = orm.NewOrmUsingDB("data").Raw(sql, source, indexId).QueryRow(&item)
+	return
+}

services/ai_predict_model_index.go

@@ -0,0 +1,221 @@
+package services
+
+import (
+	"encoding/json"
+	aiPredictModel "eta/eta_mobile/models/ai_predict_model"
+	"eta/eta_mobile/models/data_manage"
+	"eta/eta_mobile/services/data"
+	"eta/eta_mobile/utils"
+	"fmt"
+	"sort"
+	"time"
+)
+
+func GetAiPredictChartDetailByData(indexItem *aiPredictModel.AiPredictModelIndex, indexData []*aiPredictModel.AiPredictModelData, source int) (resp *data_manage.ChartInfoDetailResp, err error) {
+	resp = new(data_manage.ChartInfoDetailResp)
+
+	// 标的配置
+	var extraConfig aiPredictModel.AiPredictModelIndexExtraConfig
+	if indexItem.ExtraConfig != "" {
+		if e := json.Unmarshal([]byte(indexItem.ExtraConfig), &extraConfig); e != nil {
+			err = fmt.Errorf("标的额外配置解析失败, Config: %s, Err: %v", indexItem.ExtraConfig, e)
+			return
+		}
+	}
+
+	// 图表信息
+	var predictLegendName, confLeftMin, confLeftMax, unit string
+	if source == aiPredictModel.ModelDataSourceDaily {
+		predictLegendName = extraConfig.DailyChart.PredictLegendName
+		if predictLegendName == "" {
+			predictLegendName = "Predicted"
+		}
+		unit = extraConfig.DailyChart.Unit
+		confLeftMin = extraConfig.DailyChart.LeftMin
+		confLeftMax = extraConfig.DailyChart.LeftMax
+	}
+	if source == aiPredictModel.ModelDataSourceMonthly {
+		predictLegendName = "预测值"
+		unit = extraConfig.MonthlyChart.Unit
+		confLeftMin = extraConfig.MonthlyChart.LeftMin
+		confLeftMax = extraConfig.MonthlyChart.LeftMax
+	}
+	// 这里简单兼容下吧，暂时就不修数据了
+	if confLeftMin == "" {
+		confLeftMin = indexItem.LeftMin
+	}
+	if confLeftMax == "" {
+		confLeftMax = indexItem.LeftMax
+	}
+
+	// 获取指标对应的图表
+	chartSourceMapping := map[int]int{
+		aiPredictModel.ModelDataSourceMonthly: utils.CHART_SOURCE_AI_PREDICT_MODEL_MONTHLY,
+		aiPredictModel.ModelDataSourceDaily:   utils.CHART_SOURCE_AI_PREDICT_MODEL_DAILY,
+	}
+	chartInfo, e := data_manage.GetAiPredictChartInfoByIndexId(chartSourceMapping[source], indexItem.AiPredictModelIndexId)
+	if e != nil && e.Error() != utils.ErrNoRow() {
+		err = fmt.Errorf("获取标的图表失败, %v", e)
+		return
+	}
+
+	// 获取曲线图主题样式
+	chartView := new(data_manage.ChartInfoView)
+	if chartInfo != nil && chartInfo.ChartInfoId > 0 {
+		chartView.ChartInfoId = chartInfo.ChartInfoId
+		chartView.ChartName = chartInfo.ChartName
+		chartView.ChartNameEn = chartInfo.ChartNameEn
+		chartView.Source = chartInfo.Source
+		chartView.ChartImage = chartInfo.ChartImage
+	} else {
+		chartView.ChartName = indexItem.IndexName
+		chartView.ChartNameEn = indexItem.IndexName
+	}
+	chartView.ChartType = utils.CHART_SOURCE_DEFAULT
+	chartTheme, e := data.GetChartThemeConfig(0, chartView.ChartType, utils.CHART_TYPE_CURVE)
+	if e != nil {
+		err = fmt.Errorf("获取图表主题样式失败, %v", e)
+		return
+	}
+	chartView.ChartThemeStyle = chartTheme.Config
+	chartView.ChartThemeId = chartTheme.ChartThemeId
+
+	chartView.ChartName = indexItem.IndexName
+	chartView.ChartNameEn = indexItem.IndexName
+	chartView.DateType = 3
+	chartView.Calendar = "公历"
+	chartView.ChartSource = "AI预测模型"
+	chartView.ChartSourceEn = "AI预测模型"
+	chartView.Unit = unit
+	chartView.UnitEn = unit
+
+	// EdbList-固定一条为标的实际值、一条为预测值
+	edbList := make([]*data_manage.ChartEdbInfoMapping, 0)
+	edbActual, edbPredict := new(data_manage.ChartEdbInfoMapping), new(data_manage.ChartEdbInfoMapping)
+	edbActual.EdbName = indexItem.IndexName
+	edbActual.EdbNameEn = indexItem.IndexName
+	edbActual.IsAxis = 1
+	edbActual.Unit = unit
+	edbActual.UnitEn = unit
+
+	edbPredict.EdbName = predictLegendName
+	edbPredict.EdbNameEn = predictLegendName
+	edbPredict.IsAxis = 1
+	edbPredict.Unit = unit
+	edbPredict.UnitEn = unit
+	actualData, predictData := make([]*data_manage.EdbDataList, 0), make([]*data_manage.EdbDataList, 0)
+
+	var startDate, endDate time.Time
+	var actualValues, predictValues []float64
+	var actualNewest, predictNewest bool
+	var actualLatestTimestamp int64 // 实际值最后一天的时间戳，作为日度图表的分割线
+	for k, v := range indexData {
+		// 如果实际值和预测值都是null那么该日期无效直接忽略
+		if !v.Value.Valid && !v.PredictValue.Valid {
+			continue
+		}
+
+		// 将有效值加入[]float64，最后取极值
+		if v.Value.Valid {
+			actualValues = append(actualValues, v.Value.Float64)
+		}
+		if v.PredictValue.Valid {
+			predictValues = append(predictValues, v.PredictValue.Float64)
+		}
+
+		// 开始结束时间
+		if k == 0 {
+			startDate = v.DataTime
+			endDate = v.CreateTime
+		}
+		if v.DataTime.Before(startDate) {
+			startDate = v.DataTime
+		}
+		if v.DataTime.After(endDate) {
+			endDate = v.DataTime
+		}
+
+		// 指标数据
+		if v.Value.Valid {
+			if !actualNewest {
+				edbActual.LatestDate = v.DataTime.Format(utils.FormatDate)
+				edbActual.LatestValue = v.Value.Float64
+				actualLatestTimestamp = v.DataTime.UnixNano() / 1e6
+				actualNewest = true
+			}
+			actualData = append(actualData, &data_manage.EdbDataList{
+				DataTime:      v.DataTime.Format(utils.FormatDate),
+				Value:         v.Value.Float64,
+				DataTimestamp: v.DataTimestamp,
+			})
+		}
+		if v.PredictValue.Valid {
+			if !predictNewest {
+				edbPredict.LatestDate = v.DataTime.Format(utils.FormatDate)
+				edbPredict.LatestValue = v.Value.Float64
+				predictNewest = true
+			}
+			predictData = append(predictData, &data_manage.EdbDataList{
+				DataTime:      v.DataTime.Format(utils.FormatDate),
+				Value:         v.PredictValue.Float64,
+				DataTimestamp: v.DataTimestamp,
+			})
+		}
+	}
+
+	// 图表数据这里均做一个升序排序
+	sort.Slice(actualData, func(i, j int) bool {
+		return actualData[i].DataTimestamp < actualData[j].DataTimestamp
+	})
+	sort.Slice(predictData, func(i, j int) bool {
+		return predictData[i].DataTimestamp < predictData[j].DataTimestamp
+	})
+
+	// 极值
+	actualMin, actualMax := utils.FindMinMax(actualValues)
+	predictMin, predictMax := utils.FindMinMax(predictValues)
+	edbActual.MinData = actualMin
+	edbActual.MaxData = actualMax
+	edbPredict.MinData = predictMin
+	edbPredict.MaxData = predictMax
+
+	edbActual.DataList = actualData
+	edbPredict.DataList = predictData
+	edbList = append(edbList, edbActual, edbPredict)
+
+	// 上下限
+	if confLeftMin != "" {
+		chartView.LeftMin = confLeftMin
+	} else {
+		leftMin := actualMin
+		if leftMin > predictMin {
+			leftMin = predictMin
+		}
+		chartView.LeftMin = fmt.Sprint(leftMin)
+	}
+	if confLeftMax != "" {
+		chartView.LeftMax = confLeftMax
+	} else {
+		leftMax := actualMax
+		if leftMax < predictMax {
+			leftMax = predictMax
+		}
+		chartView.LeftMax = fmt.Sprint(leftMax)
+	}
+
+	chartView.StartDate = startDate.Format(utils.FormatDate)
+	chartView.EndDate = endDate.Format(utils.FormatDate)
+
+	// 日度图表的分割线日期
+	if source == aiPredictModel.ModelDataSourceDaily {
+		var dataResp struct {
+			ActualLatestTimestamp int64
+		}
+		dataResp.ActualLatestTimestamp = actualLatestTimestamp
+		resp.DataResp = dataResp
+	}
+
+	resp.ChartInfo = chartView
+	resp.EdbInfoList = edbList
+	return
+}

utils/common.go

@@ -2562,3 +2562,23 @@ func GetDuration(filePath string) (duration string, err error) {
 
 	return duration, nil
 }
+
+// FindMinMax 取出数组中的最小值和最大值
+func FindMinMax(numbers []float64) (min float64, max float64) {
+	if len(numbers) == 0 {
+		return 0, 0 // 如果切片为空，返回0, 0
+	}
+
+	min, max = numbers[0], numbers[0] // 初始化 min 和 max 为切片的第一个元素
+
+	for _, num := range numbers {
+		if num < min {
+			min = num
+		}
+		if num > max {
+			max = num
+		}
+	}
+
+	return min, max
+}