def test_seed(self): sampler = Neal() num_vars = 40 h = {v: -1 for v in range(num_vars)} J = {(u, v): -1 for u in range(num_vars) for v in range(u, num_vars) if u != v} num_reads = 1000 # test seed exceptions for bad_seed in (3.5, float("inf"), "string", [], {}): self.assertRaises(TypeError, sampler.sample_ising, {}, {}, seed=bad_seed) for bad_seed in (-1, -100, 2**65): self.assertRaises(ValueError, sampler.sample_ising, {}, {}, seed=bad_seed) # make sure it can accept large seeds sampler.sample_ising(h, J, seed=2**63, num_reads=1, num_sweeps=1) # no need to do a bunch of sweeps, in fact the less we do the more # sure we can be that the same seed is returning the same result all_samples = [] for seed in (1, 25, 2352, 736145, 5682453, 923759283623): response0 = sampler.sample_ising(h, J, num_reads=num_reads, num_sweeps=10, seed=seed) response1 = sampler.sample_ising(h, J, num_reads=num_reads, num_sweeps=10, seed=seed) samples0 = response0.record.sample samples1 = response1.record.sample self.assertTrue(np.array_equal(samples0, samples1), "Same seed returned different results") for previous_sample in all_samples: self.assertFalse(np.array_equal(samples0, previous_sample), "Different seed returned same results") all_samples.append(samples0)
def test_initial_states(self): sampler = Neal() var_labels = ["a", "b", "c", "d"] num_vars = len(var_labels) h = {v: -1 for v in var_labels} J = {(u, v): 1 for u, v in itertools.combinations(var_labels, 2)} num_reads = 100 seed = 1234567890 np_rand = np.random.RandomState(seed) initial_state_array = 2 * np_rand.randint( 2, size=(num_reads, num_vars)) - 1 init_labels = dict(zip(var_labels, np_rand.permutation(num_vars))) resp = sampler.sample_ising(h, J, num_reads=num_reads, sweeps=0, seed=seed, initial_states=(initial_state_array, init_labels)) for v in var_labels: self.assertTrue( np.array_equal(resp.record.sample[:, resp.variables.index(v)], initial_state_array[:, init_labels[v]]), "Samples were not the same as initial states with " "no sweeps")
def test_basic_response(self): sampler = Neal() h = {'a': 0, 'b': -1} J = {('a', 'b'): -1} response = sampler.sample_ising(h, J) self.assertIsInstance(response, dimod.SampleSet, "Sampler returned an unexpected response type")
def test_cubic_lattice_with_geometric(self): # Set up all lattice edges in a cube. Each edge is labelled by a 3-D coordinate system def get_cubic_lattice_edges(N): for x, y, z in itertools.product(range(N), repeat=3): u = x, y, z yield u, ((x + 1) % N, y, z) yield u, (x, (y + 1) % N, z) yield u, (x, y, (z + 1) % N) # Add a J-bias to each edge np_rand = np.random.RandomState(128) J = {e: np_rand.choice((-1, 1)) for e in get_cubic_lattice_edges(12)} # Solve ising problem sampler = Neal() response = sampler.sample_ising({}, J, beta_schedule_type="geometric", num_reads=10) _, response_energy, _ = next(response.data()) # Note: lowest energy found was -3088 with a different benchmarking tool threshold = -3000 self.assertLess(response_energy, threshold, ("response_energy, {}, exceeds " "threshold").format(response_energy))
def test_geometric_schedule(self): sampler = Neal() num_vars = 40 h = {v: -1 for v in range(num_vars)} J = {(u, v): -1 for u in range(num_vars) for v in range(u, num_vars) if u != v} num_reads = 10 resp = sampler.sample_ising(h, J, num_reads=num_reads, beta_schedule_type='geometric') row, col = resp.record.sample.shape self.assertEqual(row, num_reads) self.assertEqual(col, num_vars) # should get back two variables self.assertIs(resp.vartype, dimod.SPIN) # should be ising with self.assertRaises(ValueError): sampler.sample_ising(h, J, num_reads=num_reads, beta_schedule_type='asd')
def test_num_reads(self): sampler = Neal() h = {} J = {('a', 'b'): .5, (0, 'a'): -1, (1, 'b'): 0.0} for num_reads in (1, 10, 100, 3223, 10352): response = sampler.sample_ising(h, J, num_reads=num_reads) row, col = response.record.sample.shape self.assertEqual(row, num_reads) self.assertEqual(col, 4) for bad_num_reads in (0, -1, -100): with self.assertRaises(ValueError): sampler.sample_ising(h, J, num_reads=bad_num_reads) for bad_num_reads in (3.5, float("inf"), "string", [], {}): with self.assertRaises(TypeError): sampler.sample_ising(h, J, num_reads=bad_num_reads)
def test_empty_problem(self): sampler = Neal() h = {'a': 0, 'b': -1} J = {('a', 'b'): -1} eh, eJ = {}, {} for h in (h, eh): for J in (J, eJ): _h = copy.deepcopy(h) _J = copy.deepcopy(J) r = sampler.sample_ising(_h, _J)
def test_interrupt_error(self): sampler = Neal() num_vars = 40 h = {v: -1 for v in range(num_vars)} J = {(u, v): -1 for u in range(num_vars) for v in range(u, num_vars) if u != v} num_reads = 100 def f(): raise NotImplementedError resp = sampler.sample_ising(h, J, num_reads=num_reads, interrupt_function=f) self.assertEqual(len(resp), 1)
def test_disconnected_problem(self): sampler = Neal() h = {} J = { # K_3 (0, 1): -1, (1, 2): -1, (0, 2): -1, # disonnected K_3 (3, 4): -1, (4, 5): -1, (3, 5): -1, } resp = sampler.sample_ising(h, J, sweeps=1000, num_reads=100) row, col = resp.record.sample.shape self.assertEqual(row, 100) self.assertEqual(col, 6) # should get back two variables self.assertIs(resp.vartype, dimod.SPIN) # should be ising