def test_sample_hising_quadratic_range(self): linear = {'a': -4.0, 'b': -4.0, 'c': -4.0} quadratic = {('a', 'b', 'c'): 3.2} offset = 5 ignored_variables, ignored_interactions = _check_params(None, None) comp_parameters = dict(ignored_interactions=ignored_interactions, ignored_variables=ignored_variables, penalty_strength=5., quadratic_range=(-1, 2) ) sampler = ScaleComposite( ScalingChecker(HigherOrderComposite(ExactSolver()), h=linear, J=quadratic, offset=offset, **comp_parameters)) response = sampler.sample_ising(linear, quadratic, offset=offset, **comp_parameters) self.assertAlmostEqual(response.first.energy, -3.8) comp_parameters = dict(ignored_interactions=ignored_interactions, ignored_variables=ignored_variables, penalty_strength=5., quadratic_range=(-1, 0.4) ) sampler = ScaleComposite( ScalingChecker(HigherOrderComposite(ExactSolver()), h=linear, J=quadratic, offset=offset, **comp_parameters)) response = sampler.sample_ising(linear, quadratic, offset=offset, **comp_parameters) self.assertAlmostEqual(response.first.energy, -3.8)
def test_quadratic(self): sampler = HigherOrderComposite(self.tracker) Q = {(0, 0): 1, (0, 1): 2} sampleset = sampler.sample_hubo(Q, initial_state={0: 1, 1: 1}) # nothing should change self.assertEqual(self.tracker.input['initial_state'], {0: 1, 1: 1})
def test_discard(self): linear = {0: -0.5, 1: -0.3, 2: -0.8} quadratic = {(0, 1, 2): -1.7} sampler = HigherOrderComposite(ExactSolver()) response = sampler.sample_ising(linear, quadratic, penalty_strength=10, discard_unsatisfied=True) self.assertEqual(response.first.sample, {0: 1, 1: 1, 2: 1}) self.assertAlmostEqual(response.first.energy, -3.3) self.assertTrue(np.prod(response.record.penalty_satisfaction))
def test_already_qubo_2(self): linear = {0: -0.5, 1: -0.3} quadratic = {(0, 1): -1.7} sampler = HigherOrderComposite(ExactSolver()) response = sampler.sample_ising(linear, quadratic, penalty_strength=10, keep_penalty_variables=True, discard_unsatisfied=True) self.assertEqual(response.first.sample, {0: 1, 1: 1}) self.assertAlmostEqual(response.first.energy, -2.5) self.assertTrue(response.first.penalty_satisfaction)
def test_penalty_variables(self): linear = {0: -0.5, 1: -0.3, 2: -0.8} quadratic = {(0, 1, 2): -1.7} sampler = HigherOrderComposite(ExactSolver()) response = sampler.sample_ising(linear, quadratic, penalty_strength=10, keep_penalty_variables=True, discard_unsatisfied=True) self.assertEqual(len(response.first.sample), 5) self.assertAlmostEqual(response.first.energy, -3.3) self.assertTrue(response.first.penalty_satisfaction)
def test_higherorder_binary(self): sampler = HigherOrderComposite(self.tracker) Q = {'abc': -1, 'ab': 1} sampleset = sampler.sample_hubo(Q, initial_state={ 'a': 1, 'b': 1, 'c': 0 }) initial_state = self.tracker.input['initial_state'] self.assertIn(initial_state, [ { 'a': 1, 'b': 1, 'c': 0, 'a*b': 1 }, { 'a': 1, 'b': 1, 'c': 0, 'a*c': 0 }, { 'a': 1, 'b': 1, 'c': 0, 'b*c': 0 }, { 'a': 1, 'b': 1, 'c': 0, 'b*a': 1 }, { 'a': 1, 'b': 1, 'c': 0, 'c*a': 0 }, { 'a': 1, 'b': 1, 'c': 0, 'c*b': 0 }, ])
def test_sampleset_trim(self): h = {'a': -4.0, 'b': -4.0, 'c': 0} J = {('a', 'b'): 3.2} sampler = PolyTruncateComposite(HigherOrderComposite(ExactSolver()), 6) samples = sampler.sample_ising(h, J) self.assertEqual(len(samples), 6)
def test_sampleset_shorter(self): h = {'a': -4.0, 'b': -4.0, 'c': 0} J = {('a', 'b'): 3.2} sampler = PolyTruncateComposite(HigherOrderComposite(ExactSolver()), 10) with self.assertWarns(DeprecationWarning): samples = sampler.sample_ising(h, J) # we should see 2**n < 10 rows self.assertEqual(len(samples), 8)
def test_with_aggration(self): # this is actually just a smoke test, needs better testing in the # future... h = {'a': -4.0, 'b': -4.0, 'c': 0} J = {('a', 'b'): 3.2} sampler = PolyTruncateComposite(HigherOrderComposite(ExactSolver()), 6, aggregate=True) with self.assertWarns(DeprecationWarning): samples = sampler.sample_ising(h, J) self.assertEqual(len(samples), 6)
def test_higherorder_spin(self): sampler = HigherOrderComposite(self.tracker) J = {'abc': -1, 'ab': 1} sampleset = sampler.sample_hising({}, J, initial_state={ 'a': 1, 'b': 1, 'c': -1 }) bqm = self.tracker.input['bqm'] initial_state = self.tracker.input['initial_state'] samples = dimod.ExactSolver().sample(bqm).samples() # make sure that the initial-state is minimzed over the product/aux mask = (samples[:, ['a', 'b', 'c']] == [1, 1, -1]).all(axis=1) for v, val in initial_state.items(): if v in ['a', 'b', 'c']: continue self.assertTrue(samples[mask, [v]][0, 0], val)
def test_sample_hising_ignore_variables(self): linear = {'a': -4.0, 'b': -4.0, 'c': -4.0} quadratic = {('a', 'b', 'c'): 3.2} offset = 5 ignored_variables, ignored_interactions = _check_params( ['a'], None) comp_parameters = dict(ignored_interactions=ignored_interactions, ignored_variables=ignored_variables, ignore_offset=True, scalar=0.5) sampler = ScaleComposite(ScalingChecker(HigherOrderComposite( ExactSolver()), h=linear, J=quadratic, offset=offset, **comp_parameters)) response = sampler.sample_ising(linear, quadratic, offset=offset, **comp_parameters) self.assertAlmostEqual(response.first.energy, -3.8)
def test_all_energies(self): sampler = PolyScaleComposite(HigherOrderComposite(ExactSolver())) h = {'a': -1, 'b': 4} J = {'abc': -1, 'ab': 1, 'aaa': .5} sampleset = sampler.sample_hising(h, J, discard_unsatisfied=True) for sample, energy in sampleset.data(['sample', 'energy']): en = 0 for v, bias in h.items(): en += sample[v] * bias for term, bias in J.items(): val = bias for v in term: val *= sample[v] en += val self.assertAlmostEqual(energy, en)
def test_instantiation_smoketest(self): sampler = HigherOrderComposite(ExactSolver()) dtest.assert_sampler_api(sampler)
def test_0(self): with self.assertRaises(ValueError): PolyTruncateComposite(HigherOrderComposite(ExactSolver()), 0)
def test_10(self): sampler = PolyTruncateComposite(HigherOrderComposite(ExactSolver()), 10) dtest.assert_composite_api(sampler) self.assertEqual(sampler.parameters, sampler.child.parameters)
def test_typical(self): sampler = PolyScaleComposite(HigherOrderComposite(ExactSolver())) self.assertTrue(hasattr(sampler, 'sample_poly')) self.assertTrue(hasattr(sampler, 'sample_hising')) self.assertTrue(hasattr(sampler, 'sample_hubo'))