scipy.linalg.blas.dgbmv

scipy.linalg.blas.dgbmv(m, n, kl, ku, alpha, a, x, incx=1, offx=0, beta=0.0, y=None, incy=1, offy=0, trans=0, overwrite_y=0) = <fblas function dgbmv>

Compute y = alpha*op(a)@x + beta*y for a banded matrix a (BLAS dgbmv).

Parameters:

mint

Number of rows of the full matrix.

nint

Number of columns of the full matrix.

klint

Number of sub-diagonals.

kuint

Number of super-diagonals.

alphafloat

Scalar multiplier for the product.

andarray

Banded storage of the matrix, shape (kl + ku + 1, n).

xndarray

Input vector.

incxint, optional

Stride between successive elements of x. Default is 1.

offxint, optional

Index of the first element of x to use. Default is 0.

betafloat, optional

Scalar multiplier for y. Default is 0.

yndarray, optional

Input/output vector; if omitted a new zero vector is allocated. Default is None.

incyint, optional

Stride between successive elements of y. Default is 1.

offyint, optional

Index of the first element of y to use. Default is 0.

transint, optional

Operation on the matrix: 0 none, 1 transpose, 2 conjugate transpose. Default is 0.

overwrite_yint, optional

If nonzero, y may be overwritten in place. Default is 0.

Returns:

yndarray

The vector alpha*op(a)@x + beta*y.