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ad77c0dc7e
Previously, Manhattan distance measure was only able to calculate vector distances. Now, it's possible to calculate distances on matrices, too, without unnecessary overhead of copying vectors, doing an in-place lookups.
35 lines
595 B
Go
35 lines
595 B
Go
package pairwise
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import (
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"math"
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"github.com/gonum/matrix/mat64"
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)
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type Chebyshev struct{}
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func NewChebyshev() *Chebyshev {
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return &Chebyshev{}
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}
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func (self *Chebyshev) Distance(vectorX *mat64.Dense, vectorY *mat64.Dense) float64 {
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r1, c1 := vectorX.Dims()
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r2, c2 := vectorY.Dims()
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if r1 != r2 || c1 != c2 {
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panic(mat64.ErrShape)
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}
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subVector := mat64.NewDense(0, 0, nil)
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subVector.Sub(vectorX, vectorY)
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max := float64(0)
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for i := 0; i < r1; i++ {
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for j := 0; j < c1; j++ {
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max = math.Max(max, math.Abs(vectorX.At(i, j) - vectorY.At(i, j)))
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}
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}
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return max
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}
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