def compute_rp_tree(J, inds=None):
'''Build the recursive partition tree of the adjacency matrix J using the
Chlebikova heuristic BCP2 method'''
if inds is None:
inds = range(J.shape[0])
tree = {'inds': inds, 'children': []}
if J.shape[0] <= N_THRESH:
return tree
G = nx.Graph(J!=0)
for k in G:
G.node[k]['w'] = 1./len(G[k])**W_POW
try:
V1, V2 = chlebikova(G)
except AssertionError:
print('Chlebikova failed. The problem is likely disjoint.')
parts = [sorted(x) for x in [V1, V2]] # incidices in each partition
for part in parts:
sub_tree = compute_rp_tree(J[part,:][:,part], inds=part)
tree['children'].append(sub_tree)
return tree
def compute_rp_tree(J, inds=None):
'''Build the recursive partition tree of the adjacency matrix J using the
Chlebikova heuristic BCP2 method'''
if inds is None:
inds = range(J.shape[0])
tree = {'inds': inds, 'children': []}
if J.shape[0] <= N_THRESH:
return tree
G = nx.Graph(J != 0)
for k in G:
G.node[k]['w'] = 1. / len(G[k])**W_POW
try:
V1, V2 = chlebikova(G)
except AssertionError:
print('Chlebikova failed. The problem is likely disjoint.')
parts = [sorted(x) for x in [V1, V2]] # incidices in each partition
for part in parts:
sub_tree = compute_rp_tree(J[part, :][:, part], inds=part)
tree['children'].append(sub_tree)
return tree
def run_chlebikova(J):
''' '''
# print('Running chlebikova...')
G = nx.Graph(J!=0)
for k in G:
G.node[k]['w'] = 1./len(G[k])**W_POW
V1, V2 = chlebikova(G)
return [sorted(x) for x in [V1, V2]]