scipy.linalg.get_blas_funcs#

scipy.linalg.get_blas_funcs(names, arrays=(), dtype=None, ilp64=False)[source]#

Return available BLAS function objects from names.

Arrays are used to determine the optimal prefix of BLAS routines.

Parameters:
namesstr or sequence of str

Name(s) of BLAS functions without type prefix.

arrayssequence of ndarrays, optional

Arrays can be given to determine optimal prefix of BLAS routines. If not given, double-precision routines will be used, otherwise the most generic type in arrays will be used.

dtypestr or dtype, optional

Data-type specifier. Not used if arrays is non-empty.

ilp64{True, False, ‘preferred’}, optional

Whether to return ILP64 routine variant. Choosing ‘preferred’ returns ILP64 routine if available, and otherwise the 32-bit routine. Default: False

Returns:
funcslist

List containing the found function(s).

Notes

This routine automatically chooses between Fortran/C interfaces. Fortran code is used whenever possible for arrays with column major order. In all other cases, C code is preferred.

In BLAS, the naming convention is that all functions start with a type prefix, which depends on the type of the principal matrix. These can be one of {‘s’, ‘d’, ‘c’, ‘z’} for the NumPy types {float32, float64, complex64, complex128} respectively. The code and the dtype are stored in attributes typecode and dtype of the returned functions.

Examples

>>> import numpy as np
>>> import scipy.linalg as LA
>>> rng = np.random.default_rng()
>>> a = rng.random((3,2))
>>> x_gemv = LA.get_blas_funcs('gemv', (a,))
>>> x_gemv.typecode
'd'
>>> x_gemv = LA.get_blas_funcs('gemv',(a*1j,))
>>> x_gemv.typecode
'z'