def middleout_explore(G, alg, c, ignore=[]):
# c: start as a single edge e.g. (0,1) and every recursion adds a
# neighbour to it
# Reaches the base case when the maximum size clique is found
if len(c) == alg.max:
return
else:
# Get all the connected neighbour vertex of the edge
V = set(graph.neighborhood(c, G))
for v in V:
# If the edge c does not contain the vertex
if v not in c:
if canonical.canonical_r2(c, v, G, ignore=ignore):
c.append(v)
LOG.debug('%s %s' % (str(c), 'F'))
# Check if the neighor is connected to any sides of the edge
if alg.filter(c, G, v):
# For cliques, we find a n-d clique
alg.process(c, G)
# Keep going to find a larger clique
middleout_explore(G, alg, c, ignore=ignore)
c.pop()
else:
LOG.debug('%s %s' % (str(c), 'R'))
def backwards_explore(G, alg, c, last_v=None):
if not canonical.canonical_r2_all(c, G):
LOG.debug('%s %s' % (str(c), 'R2'))
return
elif not canonical.canonical_r1_all(c):
LOG.debug('%s %s' % (str(c), 'R1'))
else:
LOG.debug('%s %s' % (str(c), 'F'))
if alg.filter(c, G, last_v):
alg.process(c, G)
else:
return
if len(c) > alg.max:
return
else:
V = set(
filter(lambda v: last_v is None or True, graph.neighborhood(c, G)))
for v in V:
if v not in c:
for i in range(0, len(c) + 1):
c.insert(i, v)
if graph.is_connected(v, c, G):
backwards_explore(G, alg, c, v)
c.pop(i)
def forwards_explore(G, alg, c):
if len(c) == alg.max:
return
else:
V = set(graph.neighborhood(c, G))
for v in V:
if v not in c:
if canonical.canonical(c, v, G):
c.append(v)
LOG.debug('%s %s' %(str(c), 'F'))
if alg.filter(c, G, v):
alg.process(c, G)
forwards_explore(G, alg, c)
c.pop()
else:
LOG.debug('%s %s' %(str(c), 'R'))
def middleout_explore(G, alg, c, ignore=[]):
if len(c) == alg.max:
return
else:
V = set(graph.neighborhood(c, G))
for v in V:
if v not in c:
if canonical.canonical_r2(c, v, G, ignore=ignore):
c.append(v)
LOG.debug('%s %s' %(str(c), 'F'))
if alg.filter(c, G, v):
alg.process(c, G)
middleout_explore(G, alg, c, ignore=ignore)
c.pop()
else:
LOG.debug('%s %s' %(str(c), 'R'))
def canonicalize(e, G):
if len(e) <= 1:
return e
else:
e = sorted(e)
e_c = [e[0]]
e = e[1:]
while len(e) > 0:
V = graph.neighborhood(e_c, G)
for i, u in enumerate(e):
if u in V:
e_c.append(u)
e.pop(i)
break
return e_c