def generate_noisy_eulerian_circuit_data(options):
"""
This is a noisy version of the eularian circuit problem.
"""
while True:
num_nodes = options["num_entities"]
g = nx.random_regular_graph(2, num_nodes)
try:
path = list(nxalg.eulerian_circuit(g))
except:
continue
break
edges = g.edges()
# generate another misleading cycle
num_confusing = options["num_confusing"]
if num_confusing > 0:
g_confusing = nx.random_regular_graph(2, num_confusing)
for e in g_confusing.edges():
edges.append((e[0] + num_nodes, e[1] + num_nodes))
random.shuffle(edges)
# randomize index
idx = _generate_random_node_index(num_nodes + num_confusing)
new_edges = _relabel_nodes_in_edges(edges, idx)
new_path = _relabel_nodes_in_edges(path, idx)
for edge in new_edges:
print "%s connected-to %s" % (edge[0], edge[1])
print "%s connected-to %s" % (edge[1], edge[0])
first_edge = new_path[0]
node_list = [str(edge[0]) for edge in new_path]
print "eval eulerian-circuit %s %s\t%s" % (first_edge[0], first_edge[1],
",".join(node_list))
def generate_noisy_eulerian_circuit_data(options):
"""
This is a noisy version of the eularian circuit problem.
"""
while True:
num_nodes = options["num_entities"]
g = nx.random_regular_graph(2, num_nodes)
try:
path = list(nxalg.eulerian_circuit(g))
except:
continue
break
edges = g.edges()
# generate another misleading cycle
num_confusing = options["num_confusing"]
if num_confusing > 0:
g_confusing = nx.random_regular_graph(2, num_confusing)
for e in g_confusing.edges():
edges.append((e[0] + num_nodes, e[1] + num_nodes))
random.shuffle(edges)
# randomize index
idx = _generate_random_node_index(num_nodes + num_confusing)
new_edges = _relabel_nodes_in_edges(edges, idx)
new_path = _relabel_nodes_in_edges(path, idx)
for edge in new_edges:
print "%s connected-to %s" % (edge[0], edge[1])
print "%s connected-to %s" % (edge[1], edge[0])
first_edge = new_path[0]
node_list = [str(edge[0]) for edge in new_path]
print "eval eulerian-circuit %s %s\t%s" % (first_edge[0], first_edge[1],
",".join(node_list))
def generate_eulerian_circuit_data(options):
while True:
num_nodes = options["num_entities"]
g = nx.random_regular_graph(2, num_nodes)
try:
path = list(nxalg.eulerian_circuit(g))
except:
continue
# print path
break
for edge in g.edges():
print "%s connected-to %s" % (edge[0], edge[1])
print "%s connected-to %s" % (edge[1], edge[0])
first_edge = path[0]
node_list = [str(edge[0]) for edge in path]
print "eval eulerian-circuit %s %s\t%s" % (first_edge[0], first_edge[1],
",".join(node_list))
def generate_eulerian_circuit_data(options):
while True:
num_nodes = options["num_entities"]
g = nx.random_regular_graph(2, num_nodes)
try:
path = list(nxalg.eulerian_circuit(g))
except:
continue
# print path
break
for edge in g.edges():
print "%s connected-to %s" % (edge[0], edge[1])
print "%s connected-to %s" % (edge[1], edge[0])
first_edge = path[0]
node_list = [str(edge[0]) for edge in path]
print "eval eulerian-circuit %s %s\t%s" % (first_edge[0], first_edge[1],
",".join(node_list))
