scipy.linalg.blas.get_blas_funcs#

scipy.linalg.blas.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'