def test_workflow_runs(self):
bqm = dimod.BinaryQuadraticModel.from_ising({'a': 1}, {})
sampler = HybridSampler(TabuProblemSampler())
ss = sampler.sample(bqm)
self.assertEqual(list(ss.samples()), [{'a': -1}])
self.assertNotIn('state', ss.info)
def test_return_state(self):
bqm = dimod.BinaryQuadraticModel.from_ising({'a': 1}, {})
sampler = HybridSampler(TabuProblemSampler())
ss = sampler.sample(bqm, return_state=True)
self.assertEqual(list(ss.samples()), [{'a': -1}])
self.assertIn('state', ss.info)
self.assertEqual(ss.info['state'].problem, bqm)
def test_simple(self):
bqm = dimod.BinaryQuadraticModel({}, {
'ab': 1,
'bc': 1,
'ca': -1
}, 0, dimod.SPIN)
sampler = HybridSampler(TabuProblemSampler())
response = sampler.sample(bqm)
self.assertEqual(response.record[0].energy, -3.0)
def test_sampling_params(self):
# a simple runnable that optionally resets the output samples
class Workflow(Runnable):
def next(self, state, reset=False):
if reset:
return state.updated(samples=hybrid.SampleSet.empty())
return state
bqm = dimod.BinaryQuadraticModel.from_ising({'a': 1}, {})
sampler = HybridSampler(Workflow())
# control run
ss = sampler.sample(bqm)
self.assertEqual(len(list(ss.samples())), 1)
# test runopts propagation
ss = sampler.sample(bqm, reset=True)
self.assertEqual(len(list(ss.samples())), 0)