// Mul takes the matrix product of a and b, placing the result in the receiver.
//
// See the Muler interface for more information.
func (m *Dense) Mul(a, b Matrix) {
ar, ac := a.Dims()
br, bc := b.Dims()
if ac != br {
panic(ErrShape)
}
m.reuseAs(ar, bc)
var w *Dense
if m != a && m != b {
w = m
} else {
w = getWorkspace(ar, bc, false)
defer func() {
m.Copy(w)
putWorkspace(w)
}()
}
if a, ok := a.(RawMatrixer); ok {
if b, ok := b.(RawMatrixer); ok {
amat, bmat := a.RawMatrix(), b.RawMatrix()
blas64.Gemm(blas.NoTrans, blas.NoTrans, 1, amat, bmat, 0, w.mat)
return
}
}
if a, ok := a.(Vectorer); ok {
if b, ok := b.(Vectorer); ok {
row := make([]float64, ac)
col := make([]float64, br)
for r := 0; r < ar; r++ {
dataTmp := w.mat.Data[r*w.mat.Stride : r*w.mat.Stride+bc]
for c := 0; c < bc; c++ {
dataTmp[c] = blas64.Dot(ac,
blas64.Vector{Inc: 1, Data: a.Row(row, r)},
blas64.Vector{Inc: 1, Data: b.Col(col, c)},
)
}
}
return
}
}
row := make([]float64, ac)
for r := 0; r < ar; r++ {
for i := range row {
row[i] = a.At(r, i)
}
for c := 0; c < bc; c++ {
var v float64
for i, e := range row {
v += e * b.At(i, c)
}
w.mat.Data[r*w.mat.Stride+c] = v
}
}
}
// MulVec computes a * b if trans == false and a^T * b if trans == true. The
// result is stored into the receiver. MulVec panics if the number of columns in
// a does not equal the number of rows in b.
func (v *Vector) MulVec(a Matrix, trans bool, b *Vector) {
ar, ac := a.Dims()
br := b.Len()
if trans {
if ar != br {
panic(ErrShape)
}
} else {
if ac != br {
panic(ErrShape)
}
}
var w Vector
if v != a && v != b {
w = *v
}
if w.n == 0 {
if trans {
w.mat.Data = use(w.mat.Data, ac)
} else {
w.mat.Data = use(w.mat.Data, ar)
}
w.mat.Inc = 1
w.n = ar
if trans {
w.n = ac
}
} else {
if trans {
if ac != w.n {
panic(ErrShape)
}
} else {
if ar != w.n {
panic(ErrShape)
}
}
}
switch a := a.(type) {
case RawSymmetricer:
amat := a.RawSymmetric()
blas64.Symv(1, amat, b.mat, 0, w.mat)
case RawTriangular:
w.CopyVec(b)
amat := a.RawTriangular()
ta := blas.NoTrans
if trans {
ta = blas.Trans
}
blas64.Trmv(ta, amat, w.mat)
case RawMatrixer:
amat := a.RawMatrix()
t := blas.NoTrans
if trans {
t = blas.Trans
}
blas64.Gemv(t, 1, amat, b.mat, 0, w.mat)
case Vectorer:
if trans {
col := make([]float64, ar)
for c := 0; c < ac; c++ {
w.mat.Data[c*w.mat.Inc] = blas64.Dot(ar,
blas64.Vector{Inc: 1, Data: a.Col(col, c)},
b.mat,
)
}
} else {
row := make([]float64, ac)
for r := 0; r < ar; r++ {
w.mat.Data[r*w.mat.Inc] = blas64.Dot(ac,
blas64.Vector{Inc: 1, Data: a.Row(row, r)},
b.mat,
)
}
}
default:
if trans {
col := make([]float64, ar)
for c := 0; c < ac; c++ {
for i := range col {
col[i] = a.At(i, c)
}
var f float64
for i, e := range col {
f += e * b.mat.Data[i*b.mat.Inc]
}
w.mat.Data[c*w.mat.Inc] = f
}
} else {
row := make([]float64, ac)
for r := 0; r < ar; r++ {
for i := range row {
row[i] = a.At(r, i)
}
var f float64
for i, e := range row {
f += e * b.mat.Data[i*b.mat.Inc]
}
w.mat.Data[r*w.mat.Inc] = f
}
}
}
*v = w
}
// MulTrans takes the matrix product of a and b, optionally transposing each,
// and placing the result in the receiver.
//
// See the MulTranser interface for more information.
func (m *Dense) MulTrans(a Matrix, aTrans bool, b Matrix, bTrans bool) {
ar, ac := a.Dims()
if aTrans {
ar, ac = ac, ar
}
br, bc := b.Dims()
if bTrans {
br, bc = bc, br
}
if ac != br {
panic(ErrShape)
}
m.reuseAs(ar, bc)
var w *Dense
if m != a && m != b {
w = m
} else {
w = getWorkspace(ar, bc, false)
defer func() {
m.Copy(w)
putWorkspace(w)
}()
}
if a, ok := a.(RawMatrixer); ok {
if b, ok := b.(RawMatrixer); ok {
amat := a.RawMatrix()
if a == b && aTrans != bTrans {
var op blas.Transpose
if aTrans {
op = blas.Trans
} else {
op = blas.NoTrans
}
blas64.Syrk(op, 1, amat, 0, blas64.Symmetric{N: w.mat.Rows, Stride: w.mat.Stride, Data: w.mat.Data, Uplo: blas.Upper})
// Fill lower matrix with result.
// TODO(kortschak): Investigate whether using blas64.Copy improves the performance of this significantly.
for i := 0; i < w.mat.Rows; i++ {
for j := i + 1; j < w.mat.Cols; j++ {
w.set(j, i, w.at(i, j))
}
}
} else {
var aOp, bOp blas.Transpose
if aTrans {
aOp = blas.Trans
} else {
aOp = blas.NoTrans
}
if bTrans {
bOp = blas.Trans
} else {
bOp = blas.NoTrans
}
bmat := b.RawMatrix()
blas64.Gemm(aOp, bOp, 1, amat, bmat, 0, w.mat)
}
return
}
}
if a, ok := a.(Vectorer); ok {
if b, ok := b.(Vectorer); ok {
row := make([]float64, ac)
col := make([]float64, br)
if aTrans {
if bTrans {
for r := 0; r < ar; r++ {
dataTmp := w.mat.Data[r*w.mat.Stride : r*w.mat.Stride+bc]
for c := 0; c < bc; c++ {
dataTmp[c] = blas64.Dot(ac,
blas64.Vector{Inc: 1, Data: a.Col(row, r)},
blas64.Vector{Inc: 1, Data: b.Row(col, c)},
)
}
}
return
}
// TODO(jonlawlor): determine if (b*a)' is more efficient
for r := 0; r < ar; r++ {
dataTmp := w.mat.Data[r*w.mat.Stride : r*w.mat.Stride+bc]
for c := 0; c < bc; c++ {
dataTmp[c] = blas64.Dot(ac,
blas64.Vector{Inc: 1, Data: a.Col(row, r)},
blas64.Vector{Inc: 1, Data: b.Col(col, c)},
)
}
}
return
}
if bTrans {
for r := 0; r < ar; r++ {
dataTmp := w.mat.Data[r*w.mat.Stride : r*w.mat.Stride+bc]
for c := 0; c < bc; c++ {
dataTmp[c] = blas64.Dot(ac,
blas64.Vector{Inc: 1, Data: a.Row(row, r)},
blas64.Vector{Inc: 1, Data: b.Row(col, c)},
)
}
}
return
}
for r := 0; r < ar; r++ {
dataTmp := w.mat.Data[r*w.mat.Stride : r*w.mat.Stride+bc]
for c := 0; c < bc; c++ {
dataTmp[c] = blas64.Dot(ac,
blas64.Vector{Inc: 1, Data: a.Row(row, r)},
blas64.Vector{Inc: 1, Data: b.Col(col, c)},
)
}
}
return
}
}
row := make([]float64, ac)
if aTrans {
if bTrans {
for r := 0; r < ar; r++ {
dataTmp := w.mat.Data[r*w.mat.Stride : r*w.mat.Stride+bc]
for i := range row {
row[i] = a.At(i, r)
}
for c := 0; c < bc; c++ {
var v float64
for i, e := range row {
v += e * b.At(c, i)
}
dataTmp[c] = v
}
}
return
}
for r := 0; r < ar; r++ {
dataTmp := w.mat.Data[r*w.mat.Stride : r*w.mat.Stride+bc]
for i := range row {
row[i] = a.At(i, r)
}
for c := 0; c < bc; c++ {
var v float64
for i, e := range row {
v += e * b.At(i, c)
}
dataTmp[c] = v
}
}
return
}
if bTrans {
for r := 0; r < ar; r++ {
dataTmp := w.mat.Data[r*w.mat.Stride : r*w.mat.Stride+bc]
for i := range row {
row[i] = a.At(r, i)
}
for c := 0; c < bc; c++ {
var v float64
for i, e := range row {
v += e * b.At(c, i)
}
dataTmp[c] = v
}
}
return
}
for r := 0; r < ar; r++ {
dataTmp := w.mat.Data[r*w.mat.Stride : r*w.mat.Stride+bc]
for i := range row {
row[i] = a.At(r, i)
}
for c := 0; c < bc; c++ {
var v float64
for i, e := range row {
v += e * b.At(i, c)
}
dataTmp[c] = v
}
}
}
