scipy.linalg.blas.dgemm#

scipy.linalg.blas.dgemm(alpha, a, b, beta=0.0, c=None, trans_a=0, trans_b=0, overwrite_c=0) = <fblas function dgemm>#

Compute the matrix-matrix product c = alpha*op(a)@op(b) + beta*c (BLAS dgemm).

Parameters:
alphafloat

Scalar multiplier for the product.

andarray

First input matrix.

bndarray

Second input matrix.

betafloat, optional

Scalar multiplier for c. Default is 0.

cndarray, optional

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

trans_aint, optional

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

trans_bint, optional

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

overwrite_cint, optional

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

Returns:
cndarray

The matrix alpha*op(a)@op(b) + beta*c, where op(x) is x, x.T, or x.conj().T according to trans_a / trans_b.