def assign_cores_to_communities(graph):
""""""
num_comm = max([graph.nodes[n]['community'] for n in graph.nodes])
community_coreness_be = {i: 0 for i in range(num_comm)}
community_coreness_rb = {i: 0 for i in range(num_comm)}
for i in range(num_comm+1):
community = [n for n in graph.nodes if graph.nodes[n]['community']==i]
subgraph = graph.subgraph(community).copy()
matrix = nx.convert_matrix.to_numpy_array(subgraph)
if (matrix.size>1) & (np.sum(matrix)>0):
# borgatti-everett
be = bct.core_periphery_dir(matrix)
# rombach
rb = cpa.Rombach()
rb.detect(subgraph)
# assign
community_coreness_be[i] = be[1]
community_coreness_rb[i] = rb.score()[0]
cp_rb = rb.get_coreness()
for j, node in enumerate(subgraph.nodes):
graph.nodes[node]['community_core_be'] = be[0][j]
graph.nodes[node]['community_core_rb'] = cp_rb[node]
else:
community_coreness_be[i] = 0
community_coreness_rb[i] = 0
for j, node in enumerate(subgraph.nodes):
graph.nodes[node]['community_core_be'] = 1
graph.nodes[node]['community_core_rb'] = 1
graph.graph['community_coreness_be'] = community_coreness_be
graph.graph['community_coreness_rb'] = community_coreness_rb
def assign_core_periphery(graph):
""" Compute core-periphery of ``graph`` (``nx.DiGraph``;
converted to symmetric ``nx.Graph``).
Assign ``core`` as ``1`` or ``0`` to each node.
Assign ``coreness`` to ``graph``.
See ``core_periphery_dir()`` in ``bctpy``.
"""
# borgatti-everett
be = bct.core_periphery_dir(nx.convert_matrix.to_numpy_array(graph))
for i, node in enumerate(graph.nodes):
graph.nodes[node]['core_be'] = be[0][i]
graph.graph['coreness_be'] = be[1]
def assign_core_periphery(graph):
""" Compute core-periphery of ``graph`` (``nx.DiGraph``;
converted to symmetric ``nx.Graph``).
Assign ``core`` as ``1`` or ``0`` to each node.
Assign ``coreness`` to ``graph``.
See ``core_periphery_dir()`` in ``bctpy``.
"""
# borgatti-everett
be = bct.core_periphery_dir(nx.convert_matrix.to_numpy_array(graph))
for i, node in enumerate(graph.nodes):
graph.nodes[node]['core_be'] = be[0][i]
graph.graph['coreness_be'] = be[1]
# rombach
rb = cpa.Rombach()
rb.detect(graph)
if rb.get_coreness() != 0:
for node, coreness in rb.get_coreness().items():
graph.nodes[node]['core_rb'] = coreness
graph.graph['coreness_rb'] = rb.score()[0]
else:
for node in graph.nodes:
graph.nodes[node]['core_rb'] = 0
graph.graph['coreness_rb'] = 0
def core_periphery_analysis(network0):
network0 /= np.sum(network0)
C, Q_core = bct.core_periphery_dir(network0)
per_nodes = []
for i in range(len(C)):
if C[i] == 0:
per_nodes.append(i)
G = nx.from_numpy_matrix(network0)
G_per = G.subgraph(per_nodes)
per_network = np.array(nx.to_numpy_matrix(G_per))
M_per, Q_comm_per = bct.community_louvain(per_network)
print(Q_comm_per, "Q")
# print(M_per, Q_comm_per)
per_comm_assignments = {}
for i in range(len(per_nodes)):
per_comm_assignments[per_nodes[i]] = M_per[i]
classifications = [
[], [], []
] # index 0 means periphery-periphery edge, 1 means periphery-core, 2 means core-core
for i in range(len(network0) - 1):
for j in range(i + 1, len(network0)):
if network0[i][j] > 0:
classifications[C[i] + C[j]].append((i, j))
return classifications, per_comm_assignments, G_per, M_per
def test_core_periphery_dir():
x = load_sample(thres=.1)
c, q = bct.core_periphery_dir(x)
assert np.sum(c) == 57
assert np.sum(np.cumsum(c)) == 4170
assert np.allclose(q, .3086, atol=.0001)
def test_core_periphery_dir():
x = load_sample(thres=.1)
c, q = bct.core_periphery_dir(x)
assert np.sum(c) == 57
assert np.sum(np.cumsum(c)) == 4170
assert np.allclose(q, .3086, atol=.0001)