def test_sample_CONSTRAINED_MIXED(self):
# Using various Vartypes, including the `add_discrete` method
cqm = dimod.ConstrainedQuadraticModel()
x = {(u, v): dimod.Binary((u, v))
for u, v in product(['u1', 'u2'], range(3))}
cqm.add_discrete([('u1', v) for v in range(3)], label='u1')
cqm.add_discrete([('u2', v) for v in range(3)], label='u2')
y, z = dimod.Spin('y'), dimod.Integer('z',
lower_bound=1,
upper_bound=3)
obj1 = x[('u1', 0)] * y - x[('u2', 1)] * y
obj2 = x[('u1', 0)] * z + 2 * x[('u1', 2)] * x[('u2', 2)]
cqm.set_objective(obj1 + obj2)
cqm.add_constraint(z == 2)
response = dimod.ExactCQMSolver().sample_cqm(cqm)
# every possible combination should be present, respecting the discrete constraints
self.assertEqual(len(response), 54)
self.assertEqual(response.record.sample.shape,
(54, len(cqm.variables)))
# only 18 samples should be feasible
feasible_responses = response.filter(lambda d: d.is_feasible)
self.assertEqual(len(feasible_responses), 18)
dimod.testing.assert_sampleset_energies_cqm(response, cqm)
def test_kwargs(self):
bqm = dimod.BinaryQuadraticModel({}, {}, 0.0, dimod.SPIN)
with self.assertWarns(SamplerUnknownArgWarning):
sampleset = dimod.ExactSolver().sample(bqm, a=1, b="abc")
dqm = dimod.DiscreteQuadraticModel()
with self.assertWarns(SamplerUnknownArgWarning):
sampleset = dimod.ExactDQMSolver().sample_dqm(dqm, a=1, b="abc")
cqm = dimod.ConstrainedQuadraticModel()
with self.assertWarns(SamplerUnknownArgWarning):
sampleset = dimod.ExactCQMSolver().sample_cqm(cqm, a=1, b="abc")
def test_arbitrary_labels(self):
bqm = dimod.BQM.from_ising({}, {'ab': -1})
sampleset = dimod.ExactSolver().sample(bqm)
self.assertEqual(set(sampleset.variables), set(bqm.variables))
dqm = dimod.DQM.from_numpy_vectors([0], [-1], ([], [], []),
labels={'ab'})
sampleset = dimod.ExactDQMSolver().sample_dqm(dqm)
self.assertEqual(set(sampleset.variables), set(dqm.variables))
cqm = dimod.CQM.from_dqm(dqm)
sampleset = dimod.ExactCQMSolver().sample_cqm(cqm)
self.assertEqual(set(sampleset.variables), set(cqm.variables))
def test_sample_CONSTRAINED_SPIN(self):
# using Spin variables, with inequality constraint:
cqm = dimod.ConstrainedQuadraticModel()
x, y, z = dimod.Spin('x'), dimod.Spin('y'), dimod.Spin('z')
cqm.set_objective(x * y + 2 * y * z)
cqm.add_constraint(x * y <= 0)
response = dimod.ExactCQMSolver().sample_cqm(cqm)
# every possible combination should be present
self.assertEqual(len(response), 8)
self.assertEqual(response.record.sample.shape, (8, len(cqm.variables)))
# four samples should be feasible
feasible_responses = response.filter(lambda d: d.is_feasible)
self.assertEqual(len(feasible_responses), 4)
dimod.testing.assert_sampleset_energies_cqm(response, cqm)
def test_sample_CONSTRAINED_INTEGER(self):
# using Integer variables, with inequality constraint:
cqm = dimod.ConstrainedQuadraticModel()
x, y, z = dimod.Integer(
'x', lower_bound=1, upper_bound=3), dimod.Integer(
'y', lower_bound=4,
upper_bound=5), dimod.Integer('z',
lower_bound=-2,
upper_bound=1)
cqm.set_objective(x * y + 2 * y * z)
cqm.add_constraint(x * z >= 1)
response = dimod.ExactCQMSolver().sample_cqm(cqm)
# every possible combination should be present
self.assertEqual(len(response), 24)
self.assertEqual(response.record.sample.shape,
(24, len(cqm.variables)))
# only six samples should be feasible
feasible_responses = response.filter(lambda d: d.is_feasible)
self.assertEqual(len(feasible_responses), 6)
dimod.testing.assert_sampleset_energies_cqm(response, cqm)
def test_sample_CONSTRAINED_empty(self):
cqm = dimod.ConstrainedQuadraticModel()
response = dimod.ExactCQMSolver().sample_cqm(cqm)
self.assertEqual(response.record.sample.shape, (0, 0))