def lu_factor(a, overwrite_a=False, check_finite=True):
 if check_finite:
  a1 = asarray_chkfinite(a)
 else:
  a1 = asarray(a)
 if ((len(a1.shape) != 2) or (a1.shape[0] != a1.shape[1])):
  raise ValueError('expected square matrix')
 overwrite_a = (overwrite_a or _datacopied(a1, a))
 (getrf,) = get_lapack_funcs(('getrf',), (a1,))
 (lu, piv, info) = getrf(a1, overwrite_a=overwrite_a)
 if (info < 0):
  raise ValueError(('illegal value in %d-th argument of internal getrf (lu_factor)' % (- info)))
 if (info > 0):
  warn(('Diagonal number %d is exactly zero. Singular matrix.' % info), RuntimeWarning)
 return (lu, piv)

def lu_factor ( a , overwrite_a = False , check_finite = True ) : if check_finite : a1 = asarray_chkfinite ( a ) else : a1 = asarray ( a ) if ( ( len ( a1 . shape ) != 2 ) or ( a1 . shape [ 0 ] != a1 . shape [ 1 ] ) ) : raise ValueError ( 'expected square matrix' ) overwrite_a = ( overwrite_a or _datacopied ( a1 , a ) ) ( getrf , ) = get_lapack_funcs ( ( 'getrf' , ) , ( a1 , ) ) ( lu , piv , info ) = getrf ( a1 , overwrite_a = overwrite_a ) if ( info < 0 ) : raise ValueError ( ( 'illegal value in %d-th argument of internal getrf (lu_factor)' % ( - info ) ) ) if ( info > 0 ) : warn ( ( 'Diagonal number %d is exactly zero. Singular matrix.' % info ) , RuntimeWarning ) return ( lu , piv )
compute pivoted lu decomposition of a matrix .