def test_next_on_different_sized_constraints(self):
bqm = dimod.BinaryQuadraticModel.empty(dimod.SPIN)
variables = list('abcdefg')
fixed_variables = list('abc')
size = 3
constraints = []
# Set BQM and constraints of varying lengths
for triplet in itertools.combinations(variables, size):
for u, v in itertools.combinations(triplet, 2):
bqm.add_interaction(u, v, -1)
non_fixed_variables = set(triplet) - set(fixed_variables)
constraints.append(non_fixed_variables)
for fixed_variable in fixed_variables:
bqm.fix_variable(fixed_variable, 1)
# Get new state
rcd = RandomConstraintDecomposer(size, constraints)
state = State.from_sample(min_sample(bqm), bqm)
newstate = rcd.run(state).result()
self.assertIn('subproblem', newstate)
self.assertTrue(len(newstate.subproblem) <= size) # correct size
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_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
def test_next(self):
bqm = dimod.BinaryQuadraticModel.empty(dimod.SPIN)
variables = list('abcdefg')
constraints = []
for triplet in itertools.combinations(variables, 3):
for u, v in itertools.combinations(triplet, 2):
bqm.add_interaction(u, v, -1)
constraints.append(triplet)
rcd = RandomConstraintDecomposer(3, constraints)
state = State.from_sample(min_sample(bqm), bqm)
newstate = rcd.run(state).result()
self.assertIn('subproblem', newstate)
self.assertTrue(len(newstate.subproblem) <= 3) # correct size
