func main() {
showLU(mat.MakeDenseMatrixStacked([][]float64{
{1, 3, 5},
{2, 4, 7},
{1, 1, 0}}))
showLU(mat.MakeDenseMatrixStacked([][]float64{
{11, 9, 24, 2},
{1, 5, 2, 6},
{3, 17, 18, 1},
{2, 5, 7, 1}}))
}
func main() {
m := mat.MakeDenseMatrixStacked([][]float64{
{1, 2, 3},
{4, 5, 6},
})
fmt.Println("original:")
fmt.Println(m)
m = m.Transpose()
fmt.Println("transpose:")
fmt.Println(m)
}
func main() {
a := mat.MakeDenseMatrixStacked([][]float64{
{1, 2, 3, 4},
{5, 6, 7, 8},
})
b := mat.MakeDenseMatrixStacked([][]float64{
{1, 2, 3},
{4, 5, 6},
{7, 8, 9},
{10, 11, 12},
})
fmt.Printf("Matrix A:\n%v\n", a)
fmt.Printf("Matrix B:\n%v\n", b)
p, err := a.TimesDense(b)
if err != nil {
fmt.Println(err)
return
}
fmt.Printf("Product of A and B:\n%v\n", p)
}
func Wishart(n int, V *m.DenseMatrix) func() *m.DenseMatrix {
p := V.Rows()
zeros := m.Zeros(p, 1)
rowGen := MVNormal(zeros, V)
return func() *m.DenseMatrix {
x := make([][]float64, n)
for i := 0; i < n; i++ {
x[i] = rowGen().Array()
}
X := m.MakeDenseMatrixStacked(x)
S, _ := X.Transpose().TimesDense(X)
return S
}
}
func (eigen *EigenFace) computeEigenFaces() {
denseMat := gomat.MakeDenseMatrixStacked(eigen.covMatrix)
eigenVectors, _, _ := denseMat.Eigen()
imageCount := eigenVectors.Cols()
rank := eigenVectors.Rows()
for i := 0; i < rank; i++ {
sumSquare := 0.0
for j := 0; j < eigen.rowCount; j++ {
for k := 0; k < imageCount; k++ {
eigen.eigenMatrix[j][i] += eigen.diffMatrix[j][k] * eigenVectors.Get(i, k)
}
sumSquare += eigen.eigenMatrix[j][i] * eigen.eigenMatrix[j][i]
}
norm := math.Sqrt(float64(sumSquare))
for j := 0; j < eigen.rowCount; j++ {
eigen.eigenMatrix[j][i] /= norm
}
}
}