def degrees_und(*args): return _bct.degrees_und(*args)
def degrees_und(*args):
return _bct.degrees_und(*args)
def degrees_und(*args): """degrees_und(gsl_matrix CIJ) -> gsl_vector""" return _bct.degrees_und(*args)
def degree(cmatrix, directed):
""" In an undirected graph, the degree is the number of connections
for individual nodes.
In a directed graph, the indegree (outdegree) is the number of incoming
(outgoing) connections for individual nodes. The degree is the sum of
indegree and outdegree.Connection weights are ignored.
Parameters
----------
cmatrix : ndarray (N,N)
Connection/Adjacency matrix
directed : boolean
Is the network directed?
Returns
-------
directed == True:
deg : ndarray
Degree for all vertices
deg_in : ndarray
In-Degree for all vertices
deg_out : ndarray
Out-Degree for all vertices
Computes the and degree (indegree + outdegree) for a
directed binary matrix. Weights are discarded.
Note: Inputs of CIJ are assumed to be on the columns of the matrix.
Olaf Sporns, Indiana University, 2002/2006/2008
directed == False:
deg : ndarray
Degree for all vertices
deg_in : ndarray
In-Degree for all vertices
deg_out : ndarray
Out-Degree for all vertices
Computes the degree for a nondirected binary matrix. Weights are
discarded.
Olaf Sporns, Indiana University, 2002/2006/2008
"""
if directed:
m = bct.to_gslm(cmatrix.tolist())
deg, deg_in, deg_out = bct.degrees_dir(m)
rdeg = bct.from_gsl(deg)
rdeg_in = bct.from_gsl(deg)
rdeg_out = bct.from_gsl(deg)
bct.gsl_free(m)
bct.gsl_free(deg)
bct.gsl_free(deg_in)
bct.gsl_free(deg_out)
return (rdeg, rdeg_in, rdeg_out)
else:
m = bct.to_gslm(cmatrix.tolist())
deg = bct.degrees_und(m)
rdeg = bct.from_gsl(deg)
bct.gsl_free(m)
bct.gsl_free(deg)
return rdeg
def degrees_und(*args):
"""degrees_und(gsl_matrix CIJ) -> gsl_vector"""
return _bct.degrees_und(*args)
def degree(cmatrix, directed):
""" In an undirected graph, the degree is the number of connections
for individual nodes.
In a directed graph, the indegree (outdegree) is the number of incoming
(outgoing) connections for individual nodes. The degree is the sum of
indegree and outdegree.Connection weights are ignored.
Parameters
----------
cmatrix : ndarray (N,N)
Connection/Adjacency matrix
directed : boolean
Is the network directed?
Returns
-------
directed == True:
deg : ndarray
Degree for all vertices
deg_in : ndarray
In-Degree for all vertices
deg_out : ndarray
Out-Degree for all vertices
Computes the and degree (indegree + outdegree) for a
directed binary matrix. Weights are discarded.
Note: Inputs of CIJ are assumed to be on the columns of the matrix.
Olaf Sporns, Indiana University, 2002/2006/2008
directed == False:
deg : ndarray
Degree for all vertices
deg_in : ndarray
In-Degree for all vertices
deg_out : ndarray
Out-Degree for all vertices
Computes the degree for a nondirected binary matrix. Weights are
discarded.
Olaf Sporns, Indiana University, 2002/2006/2008
"""
if directed:
m = bct.to_gslm(cmatrix.tolist())
deg, deg_in, deg_out = bct.degrees_dir(m)
rdeg = bct.from_gsl(deg)
rdeg_in = bct.from_gsl(deg)
rdeg_out = bct.from_gsl(deg)
bct.gsl_free(m)
bct.gsl_free(deg)
bct.gsl_free(deg_in)
bct.gsl_free(deg_out)
return (rdeg, rdeg_in, rdeg_out)
else:
m = bct.to_gslm(cmatrix.tolist())
deg = bct.degrees_und(m)
rdeg = bct.from_gsl(deg)
bct.gsl_free(m)
bct.gsl_free(deg)
return rdeg