def assortativity(cmatrix, directed=False):
""" Assortativity coefficient. Essentially, the assortativity is a
correlation coefficient for the degrees of linked nodes. A positive
assortativity coefficient indicates that nodes tend to link to other
nodes with the same or similar degree.
The function accepts weighted networks, but the connection weights
are ignored.
Parameters
----------
cmatrix : ndarray (N,N)
Connection/Adjacency matrix
directed : boolean
Is the network directed?
Returns
-------
r : array_like
Assortativity
Computed after Newman (2003)
Note
----
Weights are discarded, no edges on main diagonal.
Olaf Sporns, Indiana University, 2007/2008
Vassilis Tsiaras, University of Crete, 2009
"""
if not directed:
m = bct.to_gslm(cmatrix.tolist())
ass = bct.assortativity_und(m)
r = bct.from_gsl(ass)
if np.isnan(ass):
return 0
bct.gsl_free(m)
bct.gsl_free(ass)
return r
else:
m = bct.to_gslm(cmatrix.tolist())
ass = bct.assortativity_dir(m)
if np.isnan(ass):
return 0
r = bct.from_gsl(ass)
bct.gsl_free(m)
bct.gsl_free(ass)
return r
def assortativity(cmatrix, directed = False):
""" Assortativity coefficient. Essentially, the assortativity is a
correlation coefficient for the degrees of linked nodes. A positive
assortativity coefficient indicates that nodes tend to link to other
nodes with the same or similar degree.
The function accepts weighted networks, but the connection weights
are ignored.
Parameters
----------
cmatrix : ndarray (N,N)
Connection/Adjacency matrix
directed : boolean
Is the network directed?
Returns
-------
r : array_like
Assortativity
Computed after Newman (2003)
Note
----
Weights are discarded, no edges on main diagonal.
Olaf Sporns, Indiana University, 2007/2008
Vassilis Tsiaras, University of Crete, 2009
"""
if not directed:
m = bct.to_gslm(cmatrix.tolist())
ass = bct.assortativity_und(m)
r = bct.from_gsl(ass)
if np.isnan(ass):
return 0
bct.gsl_free(m)
bct.gsl_free(ass)
return r
else:
m = bct.to_gslm(cmatrix.tolist())
ass = bct.assortativity_dir(m)
if np.isnan(ass):
return 0
r = bct.from_gsl(ass)
bct.gsl_free(m)
bct.gsl_free(ass)
return r
def assortativity_und(*args): return _bct.assortativity_und(*args)
def assortativity_und(*args):
return _bct.assortativity_und(*args)
def assortativity_und(*args): """assortativity_und(gsl_matrix CIJ) -> double""" return _bct.assortativity_und(*args)
def assortativity_und(*args):
"""assortativity_und(gsl_matrix CIJ) -> double"""
return _bct.assortativity_und(*args)