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#
# Author: Pearu Peterson, March 2002
# refactoring by Fabian Pedregosa, March 2010
#
__all__ = ['get_blas_funcs']
import numpy as np
# The following ensures that possibly missing flavor (C or Fortran) is
# replaced with the available one. If none is available, exception
# is raised at the first attempt to use the resources.
from scipy.linalg import cblas, fblas
if hasattr(cblas,'empty_module'):
cblas = fblas
elif hasattr(fblas,'empty_module'):
fblas = cblas
# 'd' will be default for 'i',..
_type_conv = {'f':'s', 'd':'d', 'F':'c', 'D':'z', 'G':'z'}
# some convenience alias for complex functions
_blas_alias = {'cnrm2' : 'scnrm2', 'znrm2' : 'dznrm2',
'cdot' : 'cdotc', 'zdot' : 'zdotc',
'cger' : 'cgerc', 'zger' : 'zgerc',
'sdotc': 'sdot', 'sdotu': 'sdot',
'ddotc': 'ddot', 'ddotu': 'ddot'}
def get_blas_funcs(names, arrays=(), dtype=None):
"""Return available BLAS function objects from names.
Arrays are used to determine the optimal prefix of BLAS routines.
Parameters
----------
names : str or sequence of str
Name(s) of BLAS functions withouth type prefix.
arrays : sequency of ndarrays, optional
Arrays can be given to determine optiomal 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.
Returns
-------
funcs : list
List containing the found function(s).
Notes
-----
This routines 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} respectevely, and
are stored in attribute `typecode` of the returned functions.
"""
blas_funcs = []
unpack = False
dtype = np.dtype(dtype)
module1 = (cblas, 'cblas')
module2 = (fblas, 'fblas')
if isinstance(names, str):
names = (names,)
unpack = True
if arrays:
# use the most generic type in arrays
dtype, index = max(
[(ar.dtype, i) for i, ar in enumerate(arrays)])
if arrays[index].flags['FORTRAN']:
# prefer Fortran for leading array with column major order
module1, module2 = module2, module1
prefix = _type_conv.get(dtype.char, 'd')
for i, name in enumerate(names):
func_name = prefix + name
func_name = _blas_alias.get(func_name, func_name)
func = getattr(module1[0], func_name, None)
module_name = module1[1]
if func is None:
func = getattr(module2[0], func_name, None)
module_name = module2[1]
if func is None:
raise ValueError(
'BLAS function %s could not be found' % func_name)
func.module_name, func.typecode = module_name, prefix
blas_funcs.append(func)
if unpack:
return blas_funcs[0]
else:
return blas_funcs
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