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standard_deviation.go
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/*
Copyright 2020 Binh Nguyen
Licensed under terms of MIT license (see LICENSE)
*/
package tago
import (
"fmt"
"math"
)
/*
StandardDeviation returns the standard deviation of the last n values.
# Formula
Where:
* _σ_ - value of standard deviation for N given probes.
* _N_ - number of probes in observation.
* _x<sub>i</sub>_ - i-th observed value from N elements observation.
# Parameters
* _n_ - number of periods (integer greater than 0)
# Example
```
sd, _ := NewStandardDeviation(4)
sd.Next(10.)
sd.Next(20.)
sd.Next(30.)
sd.Next(20.)
sd.Next(10.)
```
*/
type StandardDeviation struct {
// number of periods (must be an integer greater than 0)
n int
// internal parameters for calculations
index int
count int
m float64
m2 float64
// slice of data needed for calculation
data []float64
}
// NewStandardDeviation creates a new StandardDeviation with the given number of periods
// Example: NewStandardDeviation(9)
func NewStandardDeviation(n int) (*StandardDeviation, error) {
if n <= 0 {
return nil, ErrInvalidParameters
}
return &StandardDeviation{
n: n,
index: 0,
count: 0,
m: 0,
m2: 0,
data: make([]float64, n),
}, nil
}
// Next takes the next input and returns the next StandardDeviation value
func (sd *StandardDeviation) Next(input float64) float64 {
// add input to data
sd.index = (sd.index + 1) % sd.n
oldValue := sd.data[sd.index]
sd.data[sd.index] = input
if sd.count < sd.n {
// not enough data for n periods yet
sd.count++
delta := input - sd.m
sd.m += delta / float64(sd.count)
delta2 := input - sd.m
sd.m2 += delta * delta2
} else {
oldM := sd.m
delta := input - oldValue
sd.m += delta / float64(sd.n)
delta2 := input - sd.m + oldValue - oldM
sd.m2 += delta * delta2
}
return math.Sqrt(sd.m2 / float64(sd.count))
}
// Reset resets the indicators to a clean state
func (sd *StandardDeviation) Reset() {
sd.index = 0
sd.count = 0
sd.m = 0
sd.m2 = 0
sd.data = make([]float64, sd.n)
}
func (sd *StandardDeviation) String() string {
return fmt.Sprintf("SD(%d)", sd.n)
}