core/internal/models/tray.go

package models

import (
	"encoding/json"
)

type Tray struct {
	InstID         string             `json:"instId,string"`
	Period         string             `json:"period,string"`
	Count          int                `json:"count,number"`
	Scale          float64            `json:"scale,number"`
	LastUpdateTime int64              `json:"lastUpdateTime,number"`
	SeriesMap      map[string]*Series `json:"seriesMap"`
}

type PixelSeries struct {
	Count   int64    `json:"count"`
	Section int64    `json:"section"`
	List    []*analysis/Pixel `json:"list"`
}

func (tr *Tray) Init(instId string) {
	tr.InstID = instId
	tr.Count = 24
	tr.Scale = float64(0.005)
	// tr.SeriesMap = make(map[string]*Series)
}
func (tr *Tray) SetToKey(cr *Core) error {
	js, _ := json.Marshal(tr)
	keyName := tr.InstID + "|" + tr.Period + "|tray"
	_, err := cr.RedisLocalCli.Set(keyName, string(js), 0).Result()
	// fmt.Println(utils.GetFuncName(), "tray SetToKey:", string(js))
	return err
}

// TODO 执行单维度分析，相对应的是跨维度的分析,那个还没想好
// 单维度下的分析结果中包含以下信息：
// 1.
func (tr *Tray) Analytics(cr *Core) {
	go func() {

	}()
}

// TODO 实例化一个series
func (tr *Tray) NewSeries(cr *Core, period string) (*Series, error) {
	sr := Series{
		InstID:       tr.InstID,
		Period:       period,
		Count:        tr.Count,
		Scale:        tr.Scale,
		CandleSeries: &PixelList{},
		Ma7Series:    &PixelList{},
		Ma30Series:   &PixelList{},
	}
	// 自我更新
	err := sr.Refresh(cr)
	tr.SeriesMap["period"+period] = &sr
	return &sr, err
}