Python dimod.SPIN屬性代碼示例

# 需要導入模塊: import dimod [as 別名]
# 或者: from dimod import SPIN [as 別名]
def random_sample_seq(size, vartype):
    """Return a random sample.

    Args:
        size (int):
            Sample size (number of variables).

        vartype (:class:`dimod.Vartype`):
            Variable type; for example, `Vartype.SPIN`, `BINARY`, or `{-1, 1}`.

    Returns:
        dict: Random sample of `size` in length, with values from `vartype`.

    Examples:
        >>> random_sample_seq(4, dimod.BINARY)      # doctest: +SKIP
        {0: 0, 1: 1, 2: 0, 3: 0}

    """
    values = list(vartype.value)
    return {i: random.choice(values) for i in range(size)} 

# 需要導入模塊: import dimod [as 別名]
# 或者: from dimod import SPIN [as 別名]
def test_vstack(self):
        a = SampleSet.from_samples(
                [{'a': 1, 'b': 0, 'c': 0}, {'a': 0, 'b': 1, 'c': 0}], vartype='BINARY', energy=[3, 1])
        b = SampleSet.from_samples(
                [{'a': 0, 'b': 0, 'c': 1}, {'a': 1, 'b': 0, 'c': 1}], vartype='BINARY', energy=[2, 0])
        c = SampleSet.from_samples(
                [{'a': -1, 'b': 1, 'c': -1}], vartype='SPIN', energy=4)

        m = a.vstack(b, c)

        self.assertEqual(len(m), 5)
        self.assertEqual(
            list(m.samples()),
            [
                {'a': 1, 'b': 0, 'c': 1},   # b[1], en=0
                {'a': 0, 'b': 1, 'c': 0},   # a[1], en=1
                {'a': 0, 'b': 0, 'c': 1},   # b[0], en=2
                {'a': 1, 'b': 0, 'c': 0},   # a[0], en=3
                {'a': 0, 'b': 1, 'c': 0}    # c[0] in BINARY, en=4
            ]
        ) 

# 需要導入模塊: import dimod [as 別名]
# 或者: from dimod import SPIN [as 別名]
def test_updated(self):
        a = SampleSet.from_samples([1,0,1], 'SPIN', 0)
        b = SampleSet.from_samples([0,1,0], 'SPIN', 0)
        s1 = State(samples=a)
        s2 = State(samples=b, emb={'a': {'b': 1}}, debug={'x': 1})
        s3 = State(debug={'x': {'y': {'z': [1]}}})

        # test simple replace
        self.assertDictEqual(s1.updated(), s1)
        self.assertDictEqual(s1.updated(samples=b), State(samples=b))
        self.assertDictEqual(s2.updated(emb={'b': 1}).emb, {'b': 1})
        self.assertDictEqual(s1.updated(samples=b, debug=dict(x=1), emb={'a': {'b': 1}}), s2)

        # test recursive merge of `debug`
        self.assertDictEqual(s1.updated(debug=dict(x=1)).debug, {'x': 1})
        self.assertDictEqual(s2.updated(debug=dict(x=2)).debug, {'x': 2})
        self.assertDictEqual(s2.updated(debug=dict(y=2)).debug, {'x': 1, 'y': 2})
        self.assertDictEqual(s2.updated(debug=dict(y=2)).debug, {'x': 1, 'y': 2})

        self.assertDictEqual(s3.updated(debug={'x': {'y': {'z': [2]}}}).debug, {'x': {'y': {'z': [2]}}})
        self.assertDictEqual(s3.updated(debug={'x': {'y': {'w': 2}}}).debug, {'x': {'y': {'z': [1], 'w': 2}}})

        # test clear
        self.assertEqual(s2.updated(emb=None).emb, None)
        self.assertEqual(s2.updated(debug=None).debug, None) 

# 需要導入模塊: import dimod [as 別名]
# 或者: from dimod import SPIN [as 別名]
def test_pfs_on_impactful_far_subproblem(self):
        # problem graph has two components, each one is 4-node cycle graph
        # variable flip energy gains order variables: a, h..b
        edges = {'ab': 1, 'bc': 1, 'cd': 1, 'da': 1,
                 'ef': 1, 'fg': 1, 'gh': 1, 'he': 1,
                 'de': 0}
        biases = dict(zip(string.ascii_letters, range(8)))
        biases['a'] += 10
        bqm = dimod.BinaryQuadraticModel(biases, edges, 0.0, 'SPIN')
        sample = {i: -1 for i in bqm.variables}

        state = State.from_sample(sample, bqm)
        eid = EnergyImpactDecomposer(size=5, traversal='pfs')
        result = eid.run(state).result()

        # move towards second cluster and pick the highest energy variables from there
        self.assertEqual(set(result.subproblem.variables), set('adehg')) 

# 需要導入模塊: import dimod [as 別名]
# 或者: from dimod import SPIN [as 別名]
def test_typical_construction(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)
        rcd.init(state=State.from_sample(min_sample(bqm), bqm))

        # check that the graph is complete
        G = rcd.constraint_graph
        for i in range(len(constraints)):
            self.assertIn(i, G.nodes) 

# 需要導入模塊: import dimod [as 別名]
# 或者: from dimod import SPIN [as 別名]
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 

# 需要導入模塊: import dimod [as 別名]
# 或者: from dimod import SPIN [as 別名]
def test_spread(self):
        energies = [1, 2]
        occurrences = [3, 2]
        sampleset = dimod.SampleSet.from_samples(
            [{'a': 1}, {'a': 2}], dimod.SPIN,
            energy=energies, num_occurrences=occurrences)
        state = State(samples=sampleset)

        result = AggregatedSamples(aggregate=False).run(state).result()

        # we'll have n=5 samples
        n = sum(occurrences)
        self.assertEqual(len(result.samples), n)

        # samples, energies and num_occurrences must be expanded
        np.testing.assert_array_equal(result.samples.record.sample,
                                      np.array([[1], [1], [1], [2], [2]]))
        np.testing.assert_array_equal(result.samples.record.energy,
                                      np.array([1, 1, 1, 2, 2]))
        np.testing.assert_array_equal(result.samples.record.num_occurrences,
                                      np.ones(n))

        # variables should stay the same
        self.assertEqual(list(sampleset.variables), list(result.samples.variables)) 

# 需要導入模塊: import dimod [as 別名]
# 或者: from dimod import SPIN [as 別名]
def test_energy_threshold_termination(self):
        class ExactSolver(Runnable):
            def next(self, state):
                return state.updated(
                    samples=dimod.ExactSolver().sample(state.problem))

        bqm = dimod.BinaryQuadraticModel({'a': 1}, {}, 0, dimod.SPIN)
        state = State.from_sample({'a': 1}, bqm)

        w = LoopUntilNoImprovement(ExactSolver(),
                                   key=operator.attrgetter('samples.first.energy'),
                                   terminate=partial(operator.ge, -1))
        s = w.run(state).result()
        self.assertEqual(s.samples.first.energy, -1)

        w = LoopUntilNoImprovement(ExactSolver(),
                                   key='samples.first.energy',
                                   terminate=partial(operator.ge, -1))
        s = w.run(state).result()
        self.assertEqual(s.samples.first.energy, -1)

        w = LoopUntilNoImprovement(ExactSolver(),
                                   terminate=partial(operator.ge, -1))
        s = w.run(state).result()
        self.assertEqual(s.samples.first.energy, -1) 

# 需要導入模塊: import dimod [as 別名]
# 或者: from dimod import SPIN [as 別名]
def test_beta_use(self):
        ss = dimod.SampleSet.from_samples([{'a': 0}], energy=[0], vartype='SPIN')
        state = hybrid.State(samples=ss)

        # beta not given at all
        with self.assertRaises(ValueError):
            res = EnergyWeightedResampler().run(state).result()

        # beta given on construction
        res = EnergyWeightedResampler(beta=0).run(state).result()
        self.assertEqual(res.samples.info['beta'], 0)

        # beta given on runtime, to run method
        res = EnergyWeightedResampler().run(state, beta=1).result()
        self.assertEqual(res.samples.info['beta'], 1)

        # beta given in state
        state.beta = 2
        res = EnergyWeightedResampler().run(state).result()
        self.assertEqual(res.samples.info['beta'], 2) 

# 需要導入模塊: import dimod [as 別名]
# 或者: from dimod import SPIN [as 別名]
def test_all_three_functional(self):
        builtin = [0, 'a', [0, 'a']]

        num_variables = 100
        num_samples = 100
        samples = 2*np.triu(np.ones((num_samples, num_variables)), -4) - 1
        bqm = dimod.BinaryQuadraticModel.from_ising({v: .1*v for v in range(num_variables)}, {})
        sampleset = dimod.SampleSet.from_samples_bqm(samples, bqm)

        linear = {'a': -1, 4: 1, ('a', "complex key"): 3}
        quadratic = {('a', 'c'): 3, ('b', 'c'): -3., ('a', 3): -1}
        bqm = dimod.BinaryQuadraticModel(linear, quadratic, 3, dimod.SPIN)

        obj = [builtin, sampleset, bqm]

        # no encoder, uses ._asdict
        new = simplejson.loads(simplejson.dumps(obj), object_hook=dimod_object_hook)
        self.assertEqual(obj, new) 

# 需要導入模塊: import dimod [as 別名]
# 或者: from dimod import SPIN [as 別名]
def test_x_vartype(self):
        samples = {'a': -1, 'b': 1}
        bqm = dimod.BQM.from_qubo({'ab': 1})

        init = Initialized().parse_initial_states(
            bqm=bqm, initial_states=samples, num_reads=10)

        self.assertIs(init.initial_states.vartype, dimod.BINARY)
        arr = init.initial_states.record.sample
        self.assertTrue(((arr == 1) ^ (arr == 0)).all())

        samples = {'a': 0, 'b': 1}
        bqm = dimod.BQM.from_ising({}, {'ab': 1})

        init = Initialized().parse_initial_states(
            bqm=bqm, initial_states=samples, num_reads=10)

        self.assertIs(init.initial_states.vartype, dimod.SPIN)
        arr = init.initial_states.record.sample
        self.assertTrue(((arr == 1) ^ (arr == -1)).all()) 

# 需要導入模塊: import dimod [as 別名]
# 或者: from dimod import SPIN [as 別名]
def test_contains(self, name, BQM):
        bqm = BQM({0: 1.0}, {(0, 1): 2.0, (2, 1): 0.4}, 0.0, dimod.SPIN)

        self.assertIn(0, bqm.adj[1])
        self.assertEqual(2.0, bqm.adj[1][0])
        self.assertIn(1, bqm.adj[0])
        self.assertEqual(2.0, bqm.adj[0][1])

        self.assertIn(2, bqm.adj[1])
        self.assertEqual(.4, bqm.adj[1][2])
        self.assertIn(1, bqm.adj[2])
        self.assertEqual(.4, bqm.adj[2][1])

        self.assertNotIn(2, bqm.adj[0])
        with self.assertRaises(KeyError):
            bqm.adj[0][2]
        self.assertNotIn(0, bqm.adj[2])
        with self.assertRaises(KeyError):
            bqm.adj[2][0] 

# 需要導入模塊: import dimod [as 別名]
# 或者: from dimod import SPIN [as 別名]
def test_bqm_binary_to_spin(self):
        linear = {'a': -1, 'b': 1, 0: 1.5}
        quadratic = {(0, 1): -1, (0, 0): 1, (1, 2): 1.5, (2, 2): 4, (4, 5): 7}
        offset = 0
        vartype = dimod.BINARY
        for source, target in itertools.product(BQM_SUBCLASSES, repeat=2):
            with self.subTest(source=source, target=target):
                bqm = source(linear, quadratic, offset, vartype)
                new = target(bqm, vartype=dimod.SPIN)

                self.assertIsInstance(new, target)
                assert_consistent_bqm(new)
                self.assertEqual(new.vartype, dimod.SPIN)

                # change back for equality check
                new.change_vartype(dimod.BINARY)
                self.assertEqual(bqm.adj, new.adj)
                self.assertEqual(bqm.offset, new.offset)
                self.assertEqual(bqm.vartype, new.vartype) 

# 需要導入模塊: import dimod [as 別名]
# 或者: from dimod import SPIN [as 別名]
def test_bqm_spin_to_binary(self):
        linear = {'a': -1, 'b': 1, 0: 1.5}
        quadratic = {(0, 1): -1, (0, 0): 1, (1, 2): 1.5, (2, 2): 4, (4, 5): 7}
        offset = 0
        vartype = dimod.SPIN
        for source, target in itertools.product(BQM_SUBCLASSES, repeat=2):
            with self.subTest(source=source, target=target):
                bqm = source(linear, quadratic, offset, vartype)
                new = target(bqm, vartype=dimod.BINARY)

                self.assertIsInstance(new, target)
                assert_consistent_bqm(new)
                self.assertEqual(new.vartype, dimod.BINARY)

                # change back for equality check
                new.change_vartype(dimod.SPIN)
                self.assertEqual(bqm.adj, new.adj)
                self.assertEqual(bqm.offset, new.offset)
                self.assertEqual(bqm.vartype, new.vartype) 

# 需要導入模塊: import dimod [as 別名]
# 或者: from dimod import SPIN [as 別名]
def test_vartype(self, name, BQM):
        bqm = BQM('SPIN')
        self.assertEqual(bqm.vartype, dimod.SPIN)

        bqm = BQM(dimod.SPIN)
        self.assertEqual(bqm.vartype, dimod.SPIN)

        bqm = BQM((-1, 1))
        self.assertEqual(bqm.vartype, dimod.SPIN)

        bqm = BQM('BINARY')
        self.assertEqual(bqm.vartype, dimod.BINARY)

        bqm = BQM(dimod.BINARY)
        self.assertEqual(bqm.vartype, dimod.BINARY)

        bqm = BQM((0, 1))
        self.assertEqual(bqm.vartype, dimod.BINARY)