61 lines
1.5 KiB
Go
61 lines
1.5 KiB
Go
package core
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import (
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"encoding/json"
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)
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type Tray struct {
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InstID string `json:"instId,string"`
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Period string `json:"period,string"`
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Count int `json:"count,number"`
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Scale float64 `json:"scale,number"`
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LastUpdateTime int64 `json:"lastUpdateTime,number"`
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// SeriesMap map[string]*Series `json:"seriesMap"`
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}
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type PixelSeries struct {
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Count int64 `json:"count"`
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Section int64 `json:"section"`
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List []*Pixel `json:"list"`
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}
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func (tr *Tray) Init(instId string) {
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tr.InstID = instId
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tr.Count = 24
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tr.Scale = float64(0.005)
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// tr.SeriesMap = make(map[string]*Series)
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}
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func (tr *Tray) SetToKey(cr *Core) error {
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js, _ := json.Marshal(tr)
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keyName := tr.InstID + "|" + tr.Period + "|tray"
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_, err := cr.RedisLocalCli.Set(keyName, string(js), 0).Result()
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// fmt.Println(utils.GetFuncName(), "tray SetToKey:", string(js))
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return err
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}
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// 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
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// 单维度下的分析结果中包含以下信息：
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// 1.
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func (tr *Tray) Analytics(cr *Core) {
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go func() {
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}()
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}
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// TODO 实例化一个series
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// func (tr *Tray) NewSeries(cr *Core, period string) (*Series, error) {
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// sr := Series{
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// InstID: tr.InstID,
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// Period: period,
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// Count: tr.Count,
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// Scale: tr.Scale,
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// CandleSeries: &PixelList{},
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// Ma7Series: &PixelList{},
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// Ma30Series: &PixelList{},
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// }
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// // 自我更新
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// err := sr.Refresh(cr)
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// tr.SeriesMap["period"+period] = &sr
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// return &sr, err
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// }
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