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_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_scaling_hubo(self):
linear = {'a': -4.0, 'b': -4.0}
quadratic = {('a', 'b', 'c'): 3.2}
offset = 5
ignored_variables = None
ignored_interactions = None
ignored_variables, ignored_interactions = _check_params(
ignored_variables, ignored_interactions)
hnew, jnew, offsetnew = _scaled_hubo(linear, quadratic, offset, None,
2, None, ignored_variables,
ignored_interactions, False)
sc = 2.
hsc = {
k: v / sc if k not in ignored_variables else v
for k, v in linear.items()
}
self.assertEqual(hsc, hnew)
Jsc = {
k: v / sc if k not in ignored_interactions else v
for k, v in quadratic.items()
}
self.assertEqual(Jsc, jnew)
self.assertEqual(offsetnew, offset / sc)
hnew, jnew, offsetnew = _scaled_hubo(linear, quadratic, offset, None,
2, None, ignored_variables,
ignored_interactions, True)
sc = 2.
hsc = {
k: v / sc if k not in ignored_variables else v
for k, v in linear.items()
}
self.assertEqual(hsc, hnew)
Jsc = {
k: v / sc if k not in ignored_interactions else v
for k, v in quadratic.items()
}
self.assertEqual(Jsc, jnew)
self.assertEqual(offsetnew, offset)
hnew, jnew, offsetnew = _scaled_hubo(linear, quadratic, offset, None,
1, (-1, 0.4), ignored_variables,
ignored_interactions, False)
sc = 3.2 / 0.4
hsc = {
k: v / sc if k not in ignored_variables else v
for k, v in linear.items()
}
self.assertEqual(hsc, hnew)
Jsc = {
k: v / sc if k not in ignored_interactions else v
for k, v in quadratic.items()
}
self.assertEqual(Jsc, jnew)
self.assertEqual(offsetnew, offset / sc)
ignored_variables = ['a', 'b']
ignored_interactions = None
ignored_variables, ignored_interactions = _check_params(
ignored_variables, ignored_interactions)
hnew, jnew, offsetnew = _scaled_hubo(linear, quadratic, offset, None,
(-2, 2), None, ignored_variables,
ignored_interactions, False)
sc = 3.2 / 2.
hsc = {
k: v / sc if k not in ignored_variables else v
for k, v in linear.items()
}
self.assertEqual(hsc, hnew)
Jsc = {
k: v / sc if k not in ignored_interactions else v
for k, v in quadratic.items()
}
self.assertEqual(Jsc, jnew)
self.assertEqual(offsetnew, offset / sc)
ignored_variables = None
ignored_interactions = [('a', 'b', 'c')]
ignored_variables, ignored_interactions = _check_params(
ignored_variables, ignored_interactions)
hnew, jnew, offsetnew = _scaled_hubo(linear, quadratic, offset, None,
1, 0.5, ignored_variables,
ignored_interactions, False)
sc = 4.
hsc = {
k: v / sc if k not in ignored_variables else v
for k, v in linear.items()
}
self.assertEqual(hsc, hnew)
Jsc = {
k: v / sc if k not in ignored_interactions else v
for k, v in quadratic.items()
}
self.assertEqual(Jsc, jnew)
self.assertEqual(offsetnew, offset / sc)
def test_scaling_bqm(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, offset=5.0)
scalar = None
quadratic_range = None
ignore_offset = False
bqm_new = _scaled_bqm(bqm, scalar, 2, quadratic_range,
ignored_variables, ignored_interactions,
ignore_offset)
sc = 2.
hsc = {
k: v / sc if k not in ignored_variables else v
for k, v in linear.items()
}
Jsc = {
k: v / sc if k not in ignored_interactions else v
for k, v in quadratic.items()
}
bqm_scaled = BinaryQuadraticModel.from_ising(hsc, Jsc, offset=5.0 / 2.)
self.assertEqual(bqm_scaled, bqm_new)
ignored_variables, ignored_interactions = _check_params(None, None)
bqm = BinaryQuadraticModel.from_ising(linear, quadratic, offset=5.0)
bqm_new = _scaled_bqm(bqm, scalar, 2, quadratic_range,
ignored_variables, ignored_interactions, True)
sc = 2.
hsc = {
k: v / sc if k not in ignored_variables else v
for k, v in linear.items()
}
Jsc = {
k: v / sc if k not in ignored_interactions else v
for k, v in quadratic.items()
}
bqm_scaled = BinaryQuadraticModel.from_ising(hsc, Jsc, offset=5.0)
self.assertEqual(bqm_scaled, bqm_new)
bqm_new = _scaled_bqm(bqm, scalar, 1, (-1, 0.4), ignored_variables,
ignored_interactions, ignore_offset)
sc = 3.2 / 0.4
hsc = {
k: v / sc if k not in ignored_variables else v
for k, v in linear.items()
}
Jsc = {
k: v / sc if k not in ignored_interactions else v
for k, v in quadratic.items()
}
bqm_scaled = BinaryQuadraticModel.from_ising(hsc, Jsc, offset=5.0 / sc)
self.assertEqual(bqm_scaled, bqm_new)
ignored_variables = ['a', 'b']
ignored_interactions = None
ignored_variables, ignored_interactions = _check_params(
ignored_variables, ignored_interactions)
bqm = BinaryQuadraticModel.from_ising(linear, quadratic)
bqm_new = _scaled_bqm(bqm, scalar, (2, 2), quadratic_range,
ignored_variables, ignored_interactions,
ignore_offset)
sc = 3.2 / 2.
hsc = {
k: v / sc if k not in ignored_variables else v
for k, v in linear.items()
}
Jsc = {
k: v / sc if k not in ignored_interactions else v
for k, v in quadratic.items()
}
bqm_scaled = BinaryQuadraticModel.from_ising(hsc, Jsc, offset=0)
self.assertEqual(bqm_scaled, bqm_new)
ignored_variables = None
ignored_interactions = [('a', 'b')]
ignored_variables, ignored_interactions = _check_params(
ignored_variables, ignored_interactions)
bqm = BinaryQuadraticModel.from_ising(linear, quadratic)
bqm_new = _scaled_bqm(bqm, scalar, 1, 0.5, ignored_variables,
ignored_interactions, ignore_offset)
sc = 4.
hsc = {
k: v / sc if k not in ignored_variables else v
for k, v in linear.items()
}
Jsc = {
k: v / sc if k not in ignored_interactions else v
for k, v in quadratic.items()
}
bqm_scaled = BinaryQuadraticModel.from_ising(hsc, Jsc, offset=0)
self.assertEqual(bqm_scaled, bqm_new)
