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52 lines
1.5 KiB
Go
52 lines
1.5 KiB
Go
package timedata
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import (
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"math"
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"sort"
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"time"
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log "github.com/sirupsen/logrus"
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)
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// Resample the [timestamp,value] data given to numsteps between start-end (returns numSteps+1 points).
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// If the data does not extend past start/end then there will likely be NaN in the output data.
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func ResampleTimeSeriesData(data [][]float64, start float64, end float64, numSteps int) [][]float64 {
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var newData [][]float64
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l := len(data)
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step := (end - start) / float64(numSteps)
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for pos := start; pos <= end; pos += step {
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idx := sort.Search(l, func(i int) bool { return data[i][0] >= pos })
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var val float64
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if idx == 0 {
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val = math.NaN() // off the left
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} else if idx == l {
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val = math.NaN() // off the right
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} else {
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// between two points - linear interpolation
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left := data[idx-1]
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right := data[idx]
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dvdt := (right[1] - left[1]) / (right[0] - left[0])
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val = left[1] + (pos-left[0])*dvdt
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}
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newData = append(newData, []float64{pos, val})
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}
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return newData
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}
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// Assuming that the [timestamp,value] data provided is roughly evenly spaced, calculate that interval.
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func CalculateTimeQuantum(data [][]float64) time.Duration {
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if len(data) > 1 {
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minTime := time.UnixMilli(int64(data[0][0]))
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maxTime := time.UnixMilli(int64(data[len(data)-1][0]))
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return time.Duration(int64(maxTime.Sub(minTime)) / int64(len(data)-1))
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}
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return 0
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}
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// Print out all the [timestamp,value] data provided
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func DebugLogPriceData(data [][]float64) {
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for i := range data {
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log.Debugf("%s %.2f", time.Unix(int64(data[i][0]/1000), 0), data[i][1])
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}
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}
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