def test_from_problem(self):
sample = {0: 1, 1: 0}
bqm = dimod.BinaryQuadraticModel({0: 1, 1: 2}, {}, 0.0, 'BINARY')
self.assertEqual(State.from_problem(bqm).samples.first.energy, 0.0)
self.assertEqual(State.from_problem(bqm, beta=0.5).beta, 0.5)
self.assertEqual(State.from_problem(bqm, samples=hybrid.utils.max_sample).samples.first.energy, 3.0)
self.assertEqual(State.from_problem(bqm, samples=sample), State.from_samples(sample, bqm))
self.assertEqual(State.from_problem(bqm, samples=[sample]), State.from_samples([sample], bqm))
def test_large_sparse(self):
"Total energy is preserved after ICM on random samples over random graph."
# random Erdős-Rényi sparse graph with 100 nodes and 10% density
graph = nx.generators.fast_gnp_random_graph(n=100, p=0.1)
bqm = dimod.generators.uniform(graph=graph, vartype=dimod.SPIN)
nodes = sorted(bqm.variables)
# random input samples
s1 = State.from_problem(bqm, samples=random_sample)
s2 = State.from_problem(bqm, samples=random_sample)
inp = States(s1, s2)
icm = IsoenergeticClusterMove()
res = icm.run(inp).result()
self.assertAlmostEqual(self.total_energy(inp), self.total_energy(res))
def test_completely_disconnected_constraints(self):
bqm = dimod.BinaryQuadraticModel.from_ising({}, {'ab': 1, 'bc': 1, 'ca': 1})
size = 2
constraints = ['a', 'b']
with self.assertRaises(ValueError):
rcd = RandomConstraintDecomposer(size, constraints)
state = State.from_problem(bqm)
_ = rcd.run(state).result()
def test_dtype(self):
bqm = dimod.BQM.from_ising({'a': 0}, {})
init = State.from_problem(bqm)
state = init.updated(subsamples=init.samples)
nextstate = SplatComposer().next(state)
init_dtype = state.samples.record.sample.dtype
next_dtype = nextstate.samples.record.sample.dtype
self.assertEqual(init_dtype, next_dtype)
def test_partially_disconnected_constraints(self):
bqm = dimod.BinaryQuadraticModel.from_ising({}, {'ab': 1, 'bc': 1, 'ca': 1})
size = 2
constraints = ['a', 'b', 'cb']
rcd = RandomConstraintDecomposer(size, constraints)
state = State.from_problem(bqm)
newstate = rcd.run(state).result()
self.assertIn('subproblem', newstate)
self.assertTrue(len(newstate.subproblem) <= size) # correct size
