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receiver name should be a reflection of its identity; dont use generic names such as "me", "this", or "self"

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This commit is contained in:
Niclas Jern 2014-07-18 13:58:07 +03:00
parent e714470814
commit 716bddc46a
6 changed files with 12 additions and 12 deletions
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2
metrics/pairwise/chebyshev.go
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@ -12,7 +12,7 @@ func NewChebyshev() *Chebyshev {
return &Chebyshev{}
}
func (self *Chebyshev) Distance(vectorX *mat64.Dense, vectorY *mat64.Dense) float64 {
func (c *Chebyshev) Distance(vectorX *mat64.Dense, vectorY *mat64.Dense) float64 {
r1, c1 := vectorX.Dims()
r2, c2 := vectorY.Dims()
if r1 != r2 || c1 != c2 {

2
metrics/pairwise/cranberra.go
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@ -19,7 +19,7 @@ func cranberraDistanceStep(num float64, denom float64) float64 {
return num / denom
}
func (self *Cranberra) Distance(vectorX *mat64.Dense, vectorY *mat64.Dense) float64 {
func (c *Cranberra) Distance(vectorX *mat64.Dense, vectorY *mat64.Dense) float64 {
r1, c1 := vectorX.Dims()
r2, c2 := vectorY.Dims()
if r1 != r2 || c1 != c2 {

6
metrics/pairwise/euclidean.go
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@ -13,18 +13,18 @@ func NewEuclidean() *Euclidean {
}
// InnerProduct computes a Eucledian inner product.
func (self *Euclidean) InnerProduct(vectorX *mat64.Dense, vectorY *mat64.Dense) float64 {
func (e *Euclidean) InnerProduct(vectorX *mat64.Dense, vectorY *mat64.Dense) float64 {
result := vectorX.Dot(vectorY)
return result
}
// Distance computes Euclidean distance (also known as L2 distance).
func (self *Euclidean) Distance(vectorX *mat64.Dense, vectorY *mat64.Dense) float64 {
func (e *Euclidean) Distance(vectorX *mat64.Dense, vectorY *mat64.Dense) float64 {
subVector := mat64.NewDense(0, 0, nil)
subVector.Sub(vectorX, vectorY)
result := self.InnerProduct(subVector, subVector)
result := e.InnerProduct(subVector, subVector)
return math.Sqrt(result)
}

2
metrics/pairwise/manhattan.go
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@ -14,7 +14,7 @@ func NewManhattan() *Manhattan {
// Distance computes the Manhattan distance, also known as L1 distance.
// == the sum of the absolute values of elements.
func (self *Manhattan) Distance(vectorX *mat64.Dense, vectorY *mat64.Dense) float64 {
func (m *Manhattan) Distance(vectorX *mat64.Dense, vectorY *mat64.Dense) float64 {
r1, c1 := vectorX.Dims()
r2, c2 := vectorY.Dims()
if r1 != r2 || c1 != c2 {

8
metrics/pairwise/poly_kernel.go
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@ -17,18 +17,18 @@ func NewPolyKernel(degree int) *PolyKernel {
// InnerProduct computes the inner product through a kernel trick
// K(x, y) = (x^T y + 1)^d
func (self *PolyKernel) InnerProduct(vectorX *mat64.Dense, vectorY *mat64.Dense) float64 {
func (p *PolyKernel) InnerProduct(vectorX *mat64.Dense, vectorY *mat64.Dense) float64 {
result := vectorX.Dot(vectorY)
result = math.Pow(result+1, float64(self.degree))
result = math.Pow(result+1, float64(p.degree))
return result
}
// Distance computes distance under the polynomial kernel (maybe not needed?)
func (self *PolyKernel) Distance(vectorX *mat64.Dense, vectorY *mat64.Dense) float64 {
func (p *PolyKernel) Distance(vectorX *mat64.Dense, vectorY *mat64.Dense) float64 {
subVector := mat64.NewDense(0, 0, nil)
subVector.Sub(vectorX, vectorY)
result := self.InnerProduct(subVector, subVector)
result := p.InnerProduct(subVector, subVector)
return math.Sqrt(result)
}

4
metrics/pairwise/rbf_kernel.go
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@ -17,11 +17,11 @@ func NewRBFKernel(gamma float64) *RBFKernel {
// InnerProduct computes the inner product through a kernel trick
// K(x, y) = exp(-gamma * ||x - y||^2)
func (self *RBFKernel) InnerProduct(vectorX *mat64.Dense, vectorY *mat64.Dense) float64 {
func (r *RBFKernel) InnerProduct(vectorX *mat64.Dense, vectorY *mat64.Dense) float64 {
euclidean := NewEuclidean()
distance := euclidean.Distance(vectorX, vectorY)
result := math.Exp(-self.gamma * math.Pow(distance, 2))
result := math.Exp(-r.gamma * math.Pow(distance, 2))
return result
}