89 lines
2.5 KiB
Go
89 lines
2.5 KiB
Go
package stats
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import (
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"math"
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)
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// Validate data for distance calculation
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func validateData(dataPointX, dataPointY Float64Data) error {
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if len(dataPointX) == 0 || len(dataPointY) == 0 {
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return EmptyInputErr
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}
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if len(dataPointX) != len(dataPointY) {
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return SizeErr
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}
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return nil
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}
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// ChebyshevDistance computes the Chebyshev distance between two data sets
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func ChebyshevDistance(dataPointX, dataPointY Float64Data) (distance float64, err error) {
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err = validateData(dataPointX, dataPointY)
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if err != nil {
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return math.NaN(), err
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}
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var tempDistance float64
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for i := 0; i < len(dataPointY); i++ {
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tempDistance = math.Abs(dataPointX[i] - dataPointY[i])
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if distance < tempDistance {
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distance = tempDistance
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}
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}
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return distance, nil
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}
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// EuclideanDistance computes the Euclidean distance between two data sets
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func EuclideanDistance(dataPointX, dataPointY Float64Data) (distance float64, err error) {
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err = validateData(dataPointX, dataPointY)
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if err != nil {
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return math.NaN(), err
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}
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distance = 0
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for i := 0; i < len(dataPointX); i++ {
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distance = distance + ((dataPointX[i] - dataPointY[i]) * (dataPointX[i] - dataPointY[i]))
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}
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return math.Sqrt(distance), nil
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}
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// ManhattanDistance computes the Manhattan distance between two data sets
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func ManhattanDistance(dataPointX, dataPointY Float64Data) (distance float64, err error) {
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err = validateData(dataPointX, dataPointY)
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if err != nil {
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return math.NaN(), err
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}
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distance = 0
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for i := 0; i < len(dataPointX); i++ {
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distance = distance + math.Abs(dataPointX[i]-dataPointY[i])
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}
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return distance, nil
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}
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// MinkowskiDistance computes the Minkowski distance between two data sets
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//
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// Arguments:
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// dataPointX: First set of data points
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// dataPointY: Second set of data points. Length of both data
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// sets must be equal.
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// lambda: aka p or city blocks; With lambda = 1
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// returned distance is manhattan distance and
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// lambda = 2; it is euclidean distance. Lambda
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// reaching to infinite - distance would be chebysev
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// distance.
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// Return:
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// Distance or error
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func MinkowskiDistance(dataPointX, dataPointY Float64Data, lambda float64) (distance float64, err error) {
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err = validateData(dataPointX, dataPointY)
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if err != nil {
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return math.NaN(), err
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}
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for i := 0; i < len(dataPointY); i++ {
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distance = distance + math.Pow(math.Abs(dataPointX[i]-dataPointY[i]), lambda)
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}
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distance = math.Pow(distance, 1/lambda)
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if math.IsInf(distance, 1) {
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return math.NaN(), InfValue
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}
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return distance, nil
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}
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