def test_sample_bqm(self, mock_client):
mock_client.from_config.side_effect = MockClient
bqm = dimod.BinaryQuadraticModel({'a': -1, 'b': 1, 'c': 1},
{'ab': -0.8, 'ac': -0.7, 'bc': -1}, 0, dimod.SPIN)
sampler = LeapHybridSampler()
response = sampler.sample(bqm)
rows, cols = response.record.sample.shape
self.assertEqual(cols, 3)
self.assertFalse(np.any(response.record.sample == 0))
self.assertIs(response.vartype, dimod.SPIN)
self.assertIn('num_occurrences', response.record.dtype.fields)
config = sigma_is_one_constraints(G.number_of_nodes())
for node in G.nodes():
variables = [str(node) + str(pos) for pos in G.nodes()]
csp.add_constraint(config, variables)
for pos in G.nodes():
variables = [str(node) + str(pos) for node in G.nodes()]
csp.add_constraint(config, variables)
bqm = dwavebinarycsp.stitch(csp, max_graph_size=15)
#%%
sampler = LeapHybridSampler()
response = sampler.sample(bqm)
# %%
from collections import defaultdict
data = create_tsp_data_model(5)
G = nx.from_numpy_matrix(data["distance_matrix_numpy"])
time_window = defaultdict(bool)
i = 0
for node in range(5):
i += 1
for pos in range(5):
if pos < i:
time_window[(4 - node, pos)] = True
else:
