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src/s/c/scipy-0.13.3/scipy/sparse/linalg/matfuncs.py   scipy(Download)
from scipy.linalg.basic import solve, solve_triangular, inv
 
from scipy.sparse.base import isspmatrix
from scipy.sparse.construct import eye as speye
from scipy.sparse.linalg import spsolve
def _count_nonzero(A):
    # A compatibility function which should eventually disappear.
    #XXX There should be a better way to do this when A is sparse
    #    in the traditional sense.
    if isspmatrix(A):
def _is_upper_triangular(A):
    # This function could possibly be of wider interest.
    if isspmatrix(A):
        lower_part = scipy.sparse.tril(A, -1)
        if lower_part.nnz == 0:
    P = U + V
    Q = -U + V
    if isspmatrix(U):
        return spsolve(Q, P)
    elif structure is None:

src/s/c/scipy-0.13.3/scipy/sparse/csgraph/_components.py   scipy(Download)
 
from scipy.sparse.csr import csr_matrix
from scipy.sparse.base import isspmatrix
 
_msg0 = 'x must be a symmetric square matrix!'
        raise ValueError(_msg1 % x.shape)
 
    if isspmatrix(x):
        x = x.tocsr()
    else:

src/s/c/scipy-HEAD/scipy/sparse/linalg/matfuncs.py   scipy(Download)
from scipy.linalg.basic import solve, inv
 
from scipy.sparse.base import isspmatrix
from scipy.sparse.construct import eye as speye
from scipy.sparse.linalg import spsolve
    """
    n_squarings = 0
    Aissparse = isspmatrix(A)
 
    if Aissparse:

src/s/c/scipy-HEAD/scipy/sparse/csgraph/_components.py   scipy(Download)
 
from scipy.sparse.csr import csr_matrix
from scipy.sparse.base import isspmatrix
 
_msg0 = 'x must be a symmetric square matrix!'
        raise ValueError(_msg1 % x.shape)
 
    if isspmatrix(x):
        x = x.tocsr()
    else: