Merge d252e1174b1ba554833ebde97fff6d25f3d28310 into 74ae077eafb245fa3bdca0288854b6d51f97fe60

knn/knn.go

@@ -7,7 +7,6 @@ import (
 	"errors"
 	"fmt"
 
-	"github.com/gonum/matrix"
 	"github.com/sjwhitworth/golearn/base"
 	"github.com/sjwhitworth/golearn/kdtree"
 	"github.com/sjwhitworth/golearn/metrics/pairwise"
@@ -430,7 +429,7 @@ func NewKnnRegressor(distfunc string) *KNNRegressor {
 
 func (KNN *KNNRegressor) Fit(values []float64, numbers []float64, rows int, cols int) {
 	if rows != len(values) {
-		panic(matrix.ErrShape)
+		panic(mat.ErrShape)
 	}
 
 	KNN.Data = mat.NewDense(rows, cols, numbers)

linear_models/linear_regression.go

@@ -6,7 +6,7 @@ import (
 	"github.com/sjwhitworth/golearn/base"
 
 	"fmt"
-	_ "github.com/gonum/blas"
+	_ "gonum.org/v1/gonum/blas"
 	"gonum.org/v1/gonum/mat"
 )
 

metrics/pairwise/chebyshev.go

@@ -3,7 +3,6 @@ package pairwise
 import (
 	"math"
 
-	"github.com/gonum/matrix"
 	"gonum.org/v1/gonum/mat"
 )
 
@@ -17,7 +16,7 @@ func (c *Chebyshev) Distance(vectorX *mat.Dense, vectorY *mat.Dense) float64 {
 	r1, c1 := vectorX.Dims()
 	r2, c2 := vectorY.Dims()
 	if r1 != r2 || c1 != c2 {
-		panic(matrix.ErrShape)
+		panic(mat.ErrShape)
 	}
 
 	max := float64(0)

metrics/pairwise/cranberra.go

@@ -3,7 +3,6 @@ package pairwise
 import (
 	"math"
 
-	"github.com/gonum/matrix"
 	"gonum.org/v1/gonum/mat"
 )
 
@@ -24,7 +23,7 @@ func (c *Cranberra) Distance(vectorX *mat.Dense, vectorY *mat.Dense) float64 {
 	r1, c1 := vectorX.Dims()
 	r2, c2 := vectorY.Dims()
 	if r1 != r2 || c1 != c2 {
-		panic(matrix.ErrShape)
+		panic(mat.ErrShape)
 	}
 
 	sum := .0

metrics/pairwise/manhattan.go

@@ -3,7 +3,6 @@ package pairwise
 import (
 	"math"
 
-	"github.com/gonum/matrix"
 	"gonum.org/v1/gonum/mat"
 )
 
@@ -19,7 +18,7 @@ func (m *Manhattan) Distance(vectorX *mat.Dense, vectorY *mat.Dense) float64 {
 	r1, c1 := vectorX.Dims()
 	r2, c2 := vectorY.Dims()
 	if r1 != r2 || c1 != c2 {
-		panic(matrix.ErrShape)
+		panic(mat.ErrShape)
 	}
 
 	result := .0