def test_dnx(self):
import dimod
import dwave_networkx as dnx
G = dnx.chimera_graph(1)
cut = dnx.maximum_cut(G, dimod.ExactSolver())
def test_edge_cases(self):
# get the empty graph
G = nx.Graph()
S = dnx.maximum_cut(G, ExactSolver())
self.assertTrue(len(S) == 0)
S = dnx.weighted_maximum_cut(G, ExactSolver())
self.assertTrue(len(S) == 0)
def test_typical_cases(self):
G = nx.complete_graph(10)
S = dnx.maximum_cut(G, ExactSolver())
self.assertTrue(len(S) == 5) # half of the nodes
with self.assertRaises(dnx.DWaveNetworkXException):
S = dnx.weighted_maximum_cut(G, ExactSolver())
nx.set_edge_attributes(G, 1, 'weight')
S = dnx.weighted_maximum_cut(G, ExactSolver())
self.assertTrue(len(S) == 5) # half of the nodes
G = nx.Graph()
G.add_edges_from([(0, 1), (0, 2), (1, 2), (1, 3), (3, 4), (2, 4)])
S = dnx.maximum_cut(G, ExactSolver())
self.assertTrue(len(S) in (2, 3))
def test_max_cut(self):
G = dnx.chimera_graph(2, 2, 4)
sampler = micro.EmbeddingComposite(micro.DWaveSampler())
cut = dnx.maximum_cut(G, sampler)
for u, v in G.edges:
self.assertTrue(u in cut or v in cut)
self.assertFalse(u in cut and v in cut)
# BusBar500kV, 31-Mar-2019
# D-Wave Challenge 10
import networkx as nx
import dwave_networkx as dnx
from dwave.system.composites import EmbeddingComposite
from dwave.system.samplers import DWaveSampler
problem10 = [(nx.florentine_families_graph(),
'families in Renaissance-era Florence'),
(nx.karate_club_graph(), 'Karate club'),
(nx.davis_southern_women_graph(), 'Davis Southern women graph')]
for G, text in problem10:
shots = 1000
number_of_rounds = 10
min_max_cut_set = []
for n in range(number_of_rounds):
sampler = EmbeddingComposite(DWaveSampler())
max_cut = dnx.maximum_cut(G, sampler, num_reads=shots)
min_max_cut_set.append(min(len(max_cut), len(set(G) - set(max_cut))))
print('Max Cut for %s graph is %s.' % (text, min(min_max_cut_set)))
import dwave_networkx as dnx
import networkx as nx
import dimod
# Use basic simulated annealer
sampler = dimod.SimulatedAnnealingSampler()
# Set up a Networkx Graph
G = nx.Graph()
G.add_edges_from([(0, 1), (0, 2), (1, 2), (1, 3), (2, 3), (1, 4), (2, 4),
(3, 4), (3, 5), (4, 5), (5, 2)])
# Get the max cut
candidate = dnx.maximum_cut(G, sampler)
if len(candidate) == 3:
print(candidate, " is the right length")
else:
print(candidate, " is not the right length")
def maximum_cut(graph, sampler, params=None):
res = dnx.maximum_cut(graph, sampler)
return list(res), 'node'
import networkx as nx
import dwave_networkx as dnx
import dimod
import matplotlib.pyplot as plt
from dwave.system.samplers import DWaveSampler
from dwave.system.composites import EmbeddingComposite
sampler = EmbeddingComposite(DWaveSampler(profile='cdl'))
G = nx.gnm_random_graph(12, 25)
cut = dnx.maximum_cut(G, sampler, num_reads=50)
print('Size of the nodes, for maximum edges cut', len(cut))
print('The nodes, for maximum edges cut', cut)
subG = G.subgraph(cut)
notG = list(set(G.nodes()) - set(cut))
other_subG = G.subgraph(notG)
pos = nx.circular_layout(G)
plt.figure()
nx.draw(G, pos=pos)
nx.draw(subG, pos=pos)
nx.draw(other_subG, pos=pos, node_color='b')
plt.show()