// dgemmSerial where both are transposed
func dgemmSerialTransTrans(a, b, c general64, alpha float64) {
if debug {
if a.rows != b.cols {
panic("inner dimension mismatch")
}
if a.cols != c.rows {
panic("outer dimension mismatch")
}
if b.rows != c.cols {
panic("outer dimension mismatch")
}
}
// This style is used instead of the literal [i*stride +j]) is used because
// approximately 5 times faster as of go 1.3.
for l := 0; l < a.rows; l++ {
for i, v := range a.data[l*a.stride : l*a.stride+a.cols] {
ctmp := c.data[i*c.stride : i*c.stride+c.cols]
if v != 0 {
tmp := alpha * v
if tmp != 0 {
asm.DaxpyInc(tmp, b.data[l:], ctmp, uintptr(b.rows), uintptr(b.stride), 1, 0, 0)
}
}
}
}
}
// Dger performs the rank-one operation
// A += alpha * x * y^T
// where A is an m×n dense matrix, x and y are vectors, and alpha is a scalar.
func (Implementation) Dger(m, n int, alpha float64, x []float64, incX int, y []float64, incY int, a []float64, lda int) {
// Check inputs
if m < 0 {
panic("m < 0")
}
if n < 0 {
panic(negativeN)
}
if incX == 0 {
panic(zeroIncX)
}
if incY == 0 {
panic(zeroIncY)
}
if lda < max(1, n) {
panic(badLdA)
}
// Quick return if possible
if m == 0 || n == 0 || alpha == 0 {
return
}
var ky, kx int
if incY > 0 {
ky = 0
} else {
ky = -(n - 1) * incY
}
if incX > 0 {
kx = 0
} else {
kx = -(m - 1) * incX
}
if incX == 1 && incY == 1 {
x = x[:m]
y = y[:n]
for i, xv := range x {
tmp := alpha * xv
if tmp != 0 {
atmp := a[i*lda : i*lda+n]
asm.DaxpyUnitary(tmp, y, atmp, atmp)
}
}
return
}
ix := kx
for i := 0; i < m; i++ {
tmp := alpha * x[ix]
if tmp != 0 {
asm.DaxpyInc(tmp, y, a[i*lda:i*lda+n], uintptr(n), uintptr(incY), 1, uintptr(ky), 0)
}
ix += incX
}
}
// dgemmSerial where both are transposed
func dgemmSerialTransTrans(m, n, k int, a []float64, lda int, b []float64, ldb int, c []float64, ldc int, alpha float64) {
// This style is used instead of the literal [i*stride +j]) is used because
// approximately 5 times faster as of go 1.3.
for l := 0; l < k; l++ {
for i, v := range a[l*lda : l*lda+m] {
tmp := alpha * v
if tmp != 0 {
ctmp := c[i*ldc : i*ldc+n]
asm.DaxpyInc(tmp, b[l:], ctmp, uintptr(n), uintptr(ldb), 1, 0, 0)
}
}
}
}
// Daxpy adds alpha times x to y
// y[i] += alpha * x[i] for all i
func (Implementation) Daxpy(n int, alpha float64, x []float64, incX int, y []float64, incY int) {
if n < 1 {
if n == 0 {
return
}
panic(negativeN)
}
if incX == 0 {
panic(zeroIncX)
}
if incY == 0 {
panic(zeroIncY)
}
if (incX > 0 && (n-1)*incX >= len(x)) || (incX < 0 && (1-n)*incX >= len(x)) {
panic(badX)
}
if (incY > 0 && (n-1)*incY >= len(y)) || (incY < 0 && (1-n)*incY >= len(y)) {
panic(badY)
}
if alpha == 0 {
return
}
if incX == 1 && incY == 1 {
if len(x) < n {
panic(badLenX)
}
if len(y) < n {
panic(badLenY)
}
asm.DaxpyUnitary(alpha, x[:n], y, y)
return
}
var ix, iy int
if incX < 0 {
ix = (-n + 1) * incX
}
if incY < 0 {
iy = (-n + 1) * incY
}
if ix >= len(x) || ix+(n-1)*incX >= len(x) {
panic(badLenX)
}
if iy >= len(y) || iy+(n-1)*incY >= len(y) {
panic(badLenY)
}
asm.DaxpyInc(alpha, x, y, uintptr(n), uintptr(incX), uintptr(incY), uintptr(ix), uintptr(iy))
}
// AddScaledVec adds the vectors a and alpha*b, placing the result in the receiver.
func (v *Vector) AddScaledVec(a *Vector, alpha float64, b *Vector) {
if alpha == 1 {
v.AddVec(a, b)
return
}
if alpha == -1 {
v.SubVec(a, b)
return
}
ar := a.Len()
br := b.Len()
if ar != br {
panic(matrix.ErrShape)
}
v.reuseAs(ar)
switch {
case alpha == 0: // v <- a
v.CopyVec(a)
case v == a && v == b: // v <- v + alpha * v = (alpha + 1) * v
blas64.Scal(ar, alpha+1, v.mat)
case v == a && v != b: // v <- v + alpha * b
if v.mat.Inc == 1 && b.mat.Inc == 1 {
// Fast path for a common case.
asm.DaxpyUnitaryTo(v.mat.Data, alpha, b.mat.Data, a.mat.Data)
} else {
asm.DaxpyInc(alpha, b.mat.Data, v.mat.Data,
uintptr(ar), uintptr(b.mat.Inc), uintptr(v.mat.Inc), 0, 0)
}
default: // v <- a + alpha * b or v <- a + alpha * v
if v.mat.Inc == 1 && a.mat.Inc == 1 && b.mat.Inc == 1 {
// Fast path for a common case.
asm.DaxpyUnitaryTo(v.mat.Data, alpha, b.mat.Data, a.mat.Data)
} else {
asm.DaxpyIncTo(v.mat.Data, uintptr(v.mat.Inc), 0,
alpha, b.mat.Data, a.mat.Data,
uintptr(ar), uintptr(b.mat.Inc), uintptr(a.mat.Inc), 0, 0)
}
}
}
// Dgemv computes
// y = alpha * a * x + beta * y if tA = blas.NoTrans
// y = alpha * A^T * x + beta * y if tA = blas.Trans or blas.ConjTrans
// where A is an m×n dense matrix, x and y are vectors, and alpha is a scalar.
func (Implementation) Dgemv(tA blas.Transpose, m, n int, alpha float64, a []float64, lda int, x []float64, incX int, beta float64, y []float64, incY int) {
if tA != blas.NoTrans && tA != blas.Trans && tA != blas.ConjTrans {
panic(badTranspose)
}
if m < 0 {
panic(mLT0)
}
if n < 0 {
panic(nLT0)
}
if lda < max(1, n) {
panic(badLdA)
}
if incX == 0 {
panic(zeroIncX)
}
if incY == 0 {
panic(zeroIncY)
}
// Quick return if possible
if m == 0 || n == 0 || (alpha == 0 && beta == 1) {
return
}
// Set up indexes
lenX := m
lenY := n
if tA == blas.NoTrans {
lenX = n
lenY = m
}
var kx, ky int
if incX > 0 {
kx = 0
} else {
kx = -(lenX - 1) * incX
}
if incY > 0 {
ky = 0
} else {
ky = -(lenY - 1) * incY
}
// First form y := beta * y
if incY > 0 {
Implementation{}.Dscal(lenY, beta, y, incY)
} else {
Implementation{}.Dscal(lenY, beta, y, -incY)
}
if alpha == 0 {
return
}
// Form y := alpha * A * x + y
if tA == blas.NoTrans {
if incX == 1 {
for i := 0; i < m; i++ {
y[i] += alpha * asm.DdotUnitary(a[lda*i:lda*i+n], x)
}
return
}
iy := ky
for i := 0; i < m; i++ {
y[iy] += alpha * asm.DdotInc(x, a[lda*i:lda*i+n], uintptr(n), uintptr(incX), 1, uintptr(kx), 0)
iy += incY
}
return
}
// Cases where a is not transposed.
if incX == 1 {
for i := 0; i < m; i++ {
tmp := alpha * x[i]
if tmp != 0 {
asm.DaxpyUnitary(tmp, a[lda*i:lda*i+n], y, y)
}
}
return
}
ix := kx
for i := 0; i < m; i++ {
tmp := alpha * x[ix]
if tmp != 0 {
asm.DaxpyInc(tmp, a[lda*i:lda*i+n], y, uintptr(n), 1, uintptr(incY), 0, uintptr(ky))
}
ix += incX
}
}