`scipy.linalg.blas:get_blas_funcs`

source: /scipy/linalg/blas.py:430

Signature

def get_blas_funcs(names, arrays = (), dtype = None, ilp64 = preferred)

Summary

Return available BLAS function objects from names.

Extended Summary

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

Parameters

names : str or sequence of str: Name(s) of BLAS functions without type prefix.
arrays : sequence 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.
dtype : str 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 (LP64) routine. Default: 'preferred'.

Returns

funcs : list: List containing the found function(s).

Raises

: RuntimeError: If the requested LP64/ILP64 variant is not available.

Notes

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,))

✓

Note that ``x_gemv`` string representation shows the exact BLAS function with the prefix (here, ``d-`` because ``a`` is double precision real):

x_gemv

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<fortran function dgemv>

The BLAS variant information is also available from the ``typecode`` attribute:

x_gemv.typecode

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'd'

For double precision complex arrays, we select the ``z-`` variant, ``zgemv``

x_gemv = LA.get_blas_funcs('gemv', (a*1j,))
x_gemv.typecode

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'z'

If you want to select a specific BLAS variant instead of relying on array types, use the ``dtype=`` argument:

LA.get_blas_funcs('gemv', dtype=np.float32)

✓

<fortran function sgemv>

The ``int_dtype`` attribute stores whether the routine is ILP64 (integer arguments and outputs are 64-bit) or LP64 (integer arguments and outputs are 32-bit):

x_gemv.int_dtype

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dtype('int32')

Aliases

scipy.linalg.get_blas_funcs