forked from golang/hotime
95 lines
2.5 KiB
Go
95 lines
2.5 KiB
Go
package stats
|
|
|
|
import (
|
|
"math"
|
|
)
|
|
|
|
// Validate data for distance calculation
|
|
func validateData(dataPointX, dataPointY []float64) error {
|
|
if len(dataPointX) == 0 || len(dataPointY) == 0 {
|
|
return EmptyInput
|
|
}
|
|
|
|
if len(dataPointX) != len(dataPointY) {
|
|
return SizeErr
|
|
}
|
|
return nil
|
|
}
|
|
|
|
// Computes Chebyshev distance between two data sets
|
|
func ChebyshevDistance(dataPointX, dataPointY []float64) (distance float64, err error) {
|
|
err = validateData(dataPointX, dataPointY)
|
|
if err != nil {
|
|
return math.NaN(), err
|
|
}
|
|
var tempDistance float64
|
|
for i := 0; i < len(dataPointY); i++ {
|
|
tempDistance = math.Abs(dataPointX[i] - dataPointY[i])
|
|
if distance < tempDistance {
|
|
distance = tempDistance
|
|
}
|
|
}
|
|
return distance, nil
|
|
}
|
|
|
|
//
|
|
// Computes Euclidean distance between two data sets
|
|
//
|
|
func EuclideanDistance(dataPointX, dataPointY []float64) (distance float64, err error) {
|
|
|
|
err = validateData(dataPointX, dataPointY)
|
|
if err != nil {
|
|
return math.NaN(), err
|
|
}
|
|
distance = 0
|
|
for i := 0; i < len(dataPointX); i++ {
|
|
distance = distance + ((dataPointX[i] - dataPointY[i]) * (dataPointX[i] - dataPointY[i]))
|
|
}
|
|
return math.Sqrt(distance), nil
|
|
}
|
|
|
|
//
|
|
// Computes Manhattan distance between two data sets
|
|
//
|
|
func ManhattanDistance(dataPointX, dataPointY []float64) (distance float64, err error) {
|
|
err = validateData(dataPointX, dataPointY)
|
|
if err != nil {
|
|
return math.NaN(), err
|
|
}
|
|
distance = 0
|
|
for i := 0; i < len(dataPointX); i++ {
|
|
distance = distance + math.Abs(dataPointX[i]-dataPointY[i])
|
|
}
|
|
return distance, nil
|
|
}
|
|
|
|
//
|
|
// Computes minkowski distance between two data sets.
|
|
//
|
|
// Input:
|
|
// dataPointX: First set of data points
|
|
// dataPointY: Second set of data points. Length of both data
|
|
// sets must be equal.
|
|
// lambda: aka p or city blocks; With lambda = 1
|
|
// returned distance is manhattan distance and
|
|
// lambda = 2; it is euclidean distance. Lambda
|
|
// reaching to infinite - distance would be chebysev
|
|
// distance.
|
|
// Output:
|
|
// Distance or error
|
|
//
|
|
func MinkowskiDistance(dataPointX, dataPointY []float64, lambda float64) (distance float64, err error) {
|
|
err = validateData(dataPointX, dataPointY)
|
|
if err != nil {
|
|
return math.NaN(), err
|
|
}
|
|
for i := 0; i < len(dataPointY); i++ {
|
|
distance = distance + math.Pow(math.Abs(dataPointX[i]-dataPointY[i]), lambda)
|
|
}
|
|
distance = math.Pow(distance, float64(1/lambda))
|
|
if math.IsInf(distance, 1) == true {
|
|
return math.NaN(), InfValue
|
|
}
|
|
return distance, nil
|
|
}
|