ran go mod vendor on the whole project

vendor/github.com/montanaflynn/stats/data_set_distances.go

@@ -0,0 +1,94 @@
+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
+}