dimea

README

dimea

Calculate the distance support for Go language

Gopher image by Renee French, licensed under Creative Commons 3.0 Attributions license.

Install

$ go get github.com/yut-kt/dimea

Usage

See dimea_example_test.go for detailed Usage

Contribution

CONTRIBUTING.md

License

dimea is released under the MIT License.

Documentation

Index

• func Chebyshev(x, y []float64) (float64, error)
• func CosineSimilarity(x, y []float64) (float64, error)
• func Euclidean(x, y []float64) (float64, error)
• func Hamming(x, y interface{}) (int, error)
• func JaccardIndex(x, y []float64) (float64, error)
• func Manhattan(x, y []float64) (float64, error)
• func Minkowski(x, y []float64, p float64) (float64, error)
• func SquaredEuclidean(x, y []float64) (float64, error)
• type Levenshtein
  • func (l *Levenshtein) Distance(x, y string) int
  • func (l *Levenshtein) SetCosts(insert, delete, replace int) *Levenshtein
  • func (l *Levenshtein) SetDeleteCost(delete int) *Levenshtein
  • func (l *Levenshtein) SetInsertCost(insert int) *Levenshtein
  • func (l *Levenshtein) SetReplaceCost(replace int) *Levenshtein
  • func (l *Levenshtein) StdDistance(x, y string) float64

Examples

• Chebyshev
• CosineSimilarity
• Euclidean
• Hamming
• JaccardIndex
• Levenshtein.Distance
• Levenshtein.StdDistance
• Manhattan
• Minkowski
• SquaredEuclidean

Functions

func Chebyshev

func Chebyshev(x, y []float64) (float64, error)

Chebyshev distance is https://en.wikipedia.org/wiki/Chebyshev_distance

Example

package main

import (
	"fmt"

	"github.com/yut-kt/dimea"
)

func makeSliceXY() ([]float64, []float64) {
	return []float64{1, 2, 3, 4, 5}, []float64{5, 4, 3, 2, 1}
}

func main() {
	x, y := makeSliceXY()
	v, _ := dimea.Chebyshev(x, y)
	fmt.Println(v)
}

Output:

4

func CosineSimilarity

func CosineSimilarity(x, y []float64) (float64, error)

CosineSimilarity is https://en.wikipedia.org/wiki/Cosine_similarity

Example

package main

import (
	"fmt"

	"github.com/yut-kt/dimea"
)

func makeSliceXY() ([]float64, []float64) {
	return []float64{1, 2, 3, 4, 5}, []float64{5, 4, 3, 2, 1}
}

func main() {
	x, y := makeSliceXY()
	v, _ := dimea.CosineSimilarity(x, y)
	fmt.Println(v)
}

Output:

0.6363636363636364

func Euclidean

func Euclidean(x, y []float64) (float64, error)

Euclidean distance is https://en.wikipedia.org/wiki/Euclidean_distance

Example

package main

import (
	"fmt"

	"github.com/yut-kt/dimea"
)

func makeSliceXY() ([]float64, []float64) {
	return []float64{1, 2, 3, 4, 5}, []float64{5, 4, 3, 2, 1}
}

func main() {
	x, y := makeSliceXY()
	v, _ := dimea.Euclidean(x, y)
	fmt.Println(v)
}

Output:

6.324555320336759

func Hamming

func Hamming(x, y interface{}) (int, error)

Hamming distance is https://en.wikipedia.org/wiki/Hamming_distance

Example

package main

import (
	"fmt"

	"github.com/yut-kt/dimea"
)

func makeSliceXY() ([]float64, []float64) {
	return []float64{1, 2, 3, 4, 5}, []float64{5, 4, 3, 2, 1}
}

func main() {
	x, y := makeSliceXY()
	v, _ := dimea.Hamming(x, y)
	fmt.Println(v)
}

Output:

4

func JaccardIndex

func JaccardIndex(x, y []float64) (float64, error)

JaccardIndex is https://en.wikipedia.org/wiki/Jaccard_index

Example

package main

import (
	"fmt"

	"github.com/yut-kt/dimea"
)

func makeSliceXY() ([]float64, []float64) {
	return []float64{1, 2, 3, 4, 5}, []float64{5, 4, 3, 2, 1}
}

func main() {
	x, y := makeSliceXY()
	v, _ := dimea.JaccardIndex(x, y)
	fmt.Println(v)
}

Output:

1

func Manhattan

func Manhattan(x, y []float64) (float64, error)

Manhattan is https://en.wikipedia.org/wiki/Taxicab_geometry

Example

package main

import (
	"fmt"

	"github.com/yut-kt/dimea"
)

func makeSliceXY() ([]float64, []float64) {
	return []float64{1, 2, 3, 4, 5}, []float64{5, 4, 3, 2, 1}
}

func main() {
	x, y := makeSliceXY()
	v, _ := dimea.Manhattan(x, y)
	fmt.Println(v)
}

Output:

12

func Minkowski

func Minkowski(x, y []float64, p float64) (float64, error)

Minkowski is https://en.wikipedia.org/wiki/Minkowski_distance p is float, but truncates other than +inf

Example

package main

import (
	"fmt"
	"math"

	"github.com/yut-kt/dimea"
)

func makeSliceXY() ([]float64, []float64) {
	return []float64{1, 2, 3, 4, 5}, []float64{5, 4, 3, 2, 1}
}

func main() {
	x, y := makeSliceXY()
	pSlice := []float64{1, 2, math.Inf(1)}
	for _, p := range pSlice {
		v, _ := dimea.Minkowski(x, y, p)
		fmt.Println(v)
	}
	fmt.Println()
}

Output:

12
6.324555320336759
4

func SquaredEuclidean

func SquaredEuclidean(x, y []float64) (float64, error)

SquaredEuclidean distance is https://en.wikipedia.org/wiki/Euclidean_distance#Squared_Euclidean_distance

Example

package main

import (
	"fmt"

	"github.com/yut-kt/dimea"
)

func makeSliceXY() ([]float64, []float64) {
	return []float64{1, 2, 3, 4, 5}, []float64{5, 4, 3, 2, 1}
}

func main() {
	x, y := makeSliceXY()
	v, _ := dimea.SquaredEuclidean(x, y)
	fmt.Println(v)
}

Output:

40

Types

type Levenshtein

type Levenshtein struct {
	// contains filtered or unexported fields
}

func (*Levenshtein) Distance

func (l *Levenshtein) Distance(x, y string) int

Example

package main

import (
	"fmt"

	"github.com/yut-kt/dimea"
)

func main() {
	fmt.Println(new(dimea.Levenshtein).SetCosts(7, 7, 10).Distance("agent", "agency"))
}

Output:

17

func (*Levenshtein) SetCosts

func (l *Levenshtein) SetCosts(insert, delete, replace int) *Levenshtein

func (*Levenshtein) SetDeleteCost

func (l *Levenshtein) SetDeleteCost(delete int) *Levenshtein

func (*Levenshtein) SetInsertCost

func (l *Levenshtein) SetInsertCost(insert int) *Levenshtein

func (*Levenshtein) SetReplaceCost

func (l *Levenshtein) SetReplaceCost(replace int) *Levenshtein

func (*Levenshtein) StdDistance

func (l *Levenshtein) StdDistance(x, y string) float64

Example

package main

import (
	"fmt"

	"github.com/yut-kt/dimea"
)

func main() {
	fmt.Printf(
		"%f",
		new(dimea.Levenshtein).
			SetInsertCost(7).
			SetDeleteCost(7).
			SetReplaceCost(10).
			StdDistance("agent", "agency"),
	)
}

Output:

2.833333