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"""Compressed Sparse graph algorithms"""
# Backported from scipy 0.9: scipy.sparse.csgraph
# Some compatibility fixes for scipy 0.6
# Fabian Pedregosa, October 2010
__docformat__ = "restructuredtext en"
__all__ = ['cs_graph_components']
import numpy as np
from .sparsetools import cs_graph_components as _cs_graph_components
from scipy.sparse import csr_matrix
from scipy.sparse import isspmatrix
_msg0 = 'x must be a symmetric square matrix!'
_msg1 = _msg0 + '(has shape %s)'
def cs_graph_components(x):
"""
Determine connected compoments of a graph stored as a compressed sparse row
or column matrix. For speed reasons, the symmetry of the matrix x is not
checked.
Parameters
----------
x: ndarray-like, 2 dimensions, or sparse matrix
The adjacency matrix of the graph. Only the upper triangular part
is used.
Returns
-------
n_components: int
The number of connected components.
label: ndarray (ints, 1 dimension):
The label array of each connected component (-2 is used to
indicate empty rows: 0 everywhere, including diagonal).
Notes
-----
The matrix is assumed to be symmetric and the upper triangular part
of the matrix is used. The matrix is converted to a CSR matrix unless
it is already a CSR.
Examples
--------
>>> from scipy.sparse import cs_graph_components
>>> import numpy as np
>>> D = np.eye(4)
>>> D[0,1] = D[1,0] = 1
>>> cs_graph_components(D)
(3, array([0, 0, 1, 2]))
>>> from scipy.sparse import dok_matrix
>>> cs_graph_components(dok_matrix(D))
(3, array([0, 0, 1, 2]))
"""
try:
shape = x.shape
except AttributeError:
raise ValueError(_msg0)
if not ((len(x.shape) == 2) and (x.shape[0] == x.shape[1])):
raise ValueError(_msg1 % x.shape)
if isspmatrix(x):
x = x.tocsr()
else:
x = csr_matrix(x)
label = np.empty((shape[0],), dtype=x.indptr.dtype)
n_components = _cs_graph_components(shape[0], x.indptr, x.indices, label)
return n_components, label
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