// Compute
// Y = alpha*A*X + beta*Y
// Y = alpha*A.T*X + beta*Y ; flags = TRANSA
//
// A is M*N or N*M generic matrix,
// X is row or column vector of length N
// Y is row or column vector of legth M.
//
// MVMult is vector orientation agnostic. It does not matter if Y, X are row or
// column vectors, they are always handled as if they were column vectors.
func MVMult(Y, A, X *matrix.FloatMatrix, alpha, beta float64, flags Flags) error {
if A.Rows() == 0 || A.Cols() == 0 {
return nil
}
if Y.Rows() != 1 && Y.Cols() != 1 {
return errors.New("Y not a vector.")
}
if X.Rows() != 1 && X.Cols() != 1 {
return errors.New("X not a vector.")
}
Ar := A.FloatArray()
ldA := A.LeadingIndex()
Yr := Y.FloatArray()
incY := 1
lenY := Y.NumElements()
if Y.Rows() == 1 {
// row vector
incY = Y.LeadingIndex()
}
Xr := X.FloatArray()
incX := 1
lenX := X.NumElements()
if X.Rows() == 1 {
// row vector
incX = X.LeadingIndex()
}
// NOTE: This could diveded to parallel tasks by rows.
calgo.DMultMV(Yr, Ar, Xr, alpha, beta, calgo.Flags(flags), incY, ldA, incX,
0, lenX, 0, lenY, vpLen, mB)
return nil
}
// Y = alpha*A.T*X + beta*Y
func MVMultTransA(Y, A, X *matrix.FloatMatrix, alpha, beta float64) error {
if Y.Rows() != 1 && Y.Cols() != 1 {
return errors.New("Y not a vector.")
}
if X.Rows() != 1 && X.Cols() != 1 {
return errors.New("X not a vector.")
}
Ar := A.FloatArray()
ldA := A.LeadingIndex()
Yr := Y.FloatArray()
incY := 1
lenY := Y.Rows()
if Y.Rows() == 1 {
// row vector
incY = Y.LeadingIndex()
lenY = Y.Cols()
}
Xr := X.FloatArray()
incX := 1
lenX := X.Rows()
if X.Rows() == 1 {
// row vector
incX = X.LeadingIndex()
lenX = X.Cols()
}
calgo.DMultMV(Yr, Ar, Xr, alpha, beta, calgo.TRANSA, incY, ldA, incX,
0, lenX, 0, lenY, vpLen, mB)
return nil
}