def test_ignored_interactions(self):
bqm = dimod.BQM.from_ising({
'a': -4.0,
'b': -4.0
}, {
('a', 'b'): 3.2,
('b', 'c'): 1
}, 1.5)
with self.assertWarns(DeprecationWarning):
sampler = ScaleComposite(
dimod.TrackingComposite(dimod.ExactSolver()))
sampleset = sampler.sample(bqm,
scalar=.5,
ignored_interactions=[('b', 'c')])
# check that everything was restored properly
dimod.testing.assert_sampleset_energies(sampleset, bqm)
self.assertEqual(
sampler.child.input['bqm'],
dimod.BQM.from_ising({
'a': -2.0,
'b': -2.0
}, {
'ab': 1.6,
'bc': 1
}, .75))
def test_sample_bias_range(self):
linear = {'a': -4.0, 'b': -4.0}
quadratic = {('a', 'b'): 3.2}
ignored_variables, ignored_interactions = _check_params(None, None)
bqm = BinaryQuadraticModel.from_ising(linear, quadratic)
comp_parameters = dict(ignored_interactions=ignored_interactions,
ignored_variables=ignored_variables,
bias_range=2.)
sampler = ScaleComposite(
ScalingChecker(ExactSolver(), bqm=bqm, **comp_parameters))
response = sampler.sample(bqm, **comp_parameters)
self.assertAlmostEqual(response.first.energy, -4.8)
def test_sample_ising_quadratic(self):
linear = {'a': -4.0, 'b': -4.0}
quadratic = {('a', 'b'): 3.2}
offset = 5
ignored_variables, ignored_interactions = _check_params(None, None)
comp_parameters = dict(ignored_interactions=ignored_interactions,
ignored_variables=ignored_variables)
sampler = ScaleComposite(ScalingChecker(ExactSolver(), h=linear,
J=quadratic, offset=offset,
**comp_parameters))
response = sampler.sample_ising(linear, quadratic,
offset=offset)
self.assertAlmostEqual(response.first.energy, 0.2)
def test_sample_ignore_variables(self):
linear = {'a': -4.0, 'b': -4.0}
quadratic = {('a', 'b'): 3.2}
offset = 5
bqm = BinaryQuadraticModel.from_ising(linear, quadratic, offset=offset)
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(ExactSolver(), h=linear,
J=quadratic, offset=offset,
**comp_parameters))
response = sampler.sample(bqm, **comp_parameters)
self.assertAlmostEqual(response.first.energy, 0.2)
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_ignored_offset(self):
bqm = dimod.BQM.from_ising({
'a': -4.0,
'b': -4.0
}, {('a', 'b'): 3.2}, 1.5)
sampler = ScaleComposite(dimod.TrackingComposite(dimod.ExactSolver()))
sampleset = sampler.sample(bqm, scalar=.5, ignore_offset=True)
# check that everything was restored properly
dimod.testing.assert_sampleset_energies(sampleset, bqm)
self.assertEqual(
sampler.child.input['bqm'],
dimod.BQM.from_ising({
'a': -2.0,
'b': -2.0
}, {('a', 'b'): 1.6}, 1.5))
def test_sample_hising_ranges(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, 10),
bias_range=(-8.0, 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_bias_range(self):
bqm = dimod.BQM.from_ising({
'a': -4.0,
'b': -4.0
}, {('a', 'b'): 3.2}, 1.5)
with self.assertWarns(DeprecationWarning):
sampler = ScaleComposite(
dimod.TrackingComposite(dimod.ExactSolver()))
sampleset = sampler.sample(bqm, bias_range=[-2, 2])
# check that everything was restored properly
dimod.testing.assert_sampleset_energies(sampleset, bqm)
self.assertEqual(
sampler.child.input['bqm'],
dimod.BQM.from_ising({
'a': -2.0,
'b': -2.0
}, {('a', 'b'): 1.6}, .75))
def test_instantiation_smoketest(self):
sampler = ScaleComposite(ExactSolver())
dtest.assert_sampler_api(sampler)
def test_api(self):
with self.assertWarns(DeprecationWarning):
sampler = ScaleComposite(dimod.ExactSolver())
dimod.testing.assert_sampler_api(sampler)
#
import unittest
import dimod
from dimod import ScaleComposite
try:
import dwave.preprocessing as preprocessing
except ImportError:
preprocessing = False
if preprocessing:
@dimod.testing.load_sampler_bqm_tests(ScaleComposite(dimod.ExactSolver()))
@dimod.testing.load_sampler_bqm_tests(ScaleComposite(dimod.NullSampler()))
class TestScaleComposite(unittest.TestCase):
def test_api(self):
with self.assertWarns(DeprecationWarning):
sampler = ScaleComposite(dimod.ExactSolver())
dimod.testing.assert_sampler_api(sampler)
def test_bias_range(self):
bqm = dimod.BQM.from_ising({
'a': -4.0,
'b': -4.0
}, {('a', 'b'): 3.2}, 1.5)
with self.assertWarns(DeprecationWarning):
sampler = ScaleComposite(
def test_api(self):
sampler = ScaleComposite(dimod.ExactSolver())
dimod.testing.assert_sampler_api(sampler)
