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package stats
import (
"math"
)
// Validate data for distance calculation
func validateData(dataPointX, dataPointY Float64Data) error {
if len(dataPointX) == 0 || len(dataPointY) == 0 {
return EmptyInputErr
}
if len(dataPointX) != len(dataPointY) {
return SizeErr
}
return nil
}
// ChebyshevDistance computes the Chebyshev distance between two data sets
func ChebyshevDistance(dataPointX, dataPointY Float64Data) (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
}
// EuclideanDistance computes the Euclidean distance between two data sets
func EuclideanDistance(dataPointX, dataPointY Float64Data) (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
}
// ManhattanDistance computes the Manhattan distance between two data sets
func ManhattanDistance(dataPointX, dataPointY Float64Data) (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
}
// MinkowskiDistance computes the Minkowski distance between two data sets
//
// Arguments:
//
// 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.
//
// Return:
//
// Distance or error
func MinkowskiDistance(dataPointX, dataPointY Float64Data, 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, 1/lambda)
if math.IsInf(distance, 1) {
return math.NaN(), InfValue
}
return distance, nil
}
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