def test_equality(self):
self.assertEqual(Binary("a"), Binary("a"))
self.assertNotEqual(Binary("a"), Binary("b"))
exp1 = Binary("a") + 2
exp2 = Binary("a") + 2
exp3 = Binary("b") + 2
self.assertEqual(exp1, exp2)
self.assertNotEqual(exp1, exp3)
mul1 = Placeholder("p") * Binary("b")
mul2 = Placeholder("p") * Binary("b")
mul3 = Placeholder("p") * Binary("a")
self.assertEqual(mul1, mul2)
self.assertNotEqual(mul1, mul3)
class CustomPenalty(WithPenalty):
def __init__(self, hamiltonian, penalty, label="label"):
super().__init__(hamiltonian, penalty, label)
a, b = Binary("a"), Binary("b")
p1 = 1 + CustomPenalty(a + b, a * b)
p2 = 1 + CustomPenalty(a + b, a * b)
p3 = 1 + CustomPenalty(a * b, a + b)
self.assertEqual(p1, p2)
self.assertNotEqual(p1, p3)
subh1 = SubH(a + b, label="c1")
subh2 = SubH(a + b, label="c1")
subh3 = SubH(a + b, label="c2")
self.assertEqual(subh1, subh2)
self.assertNotEqual(subh1, subh3)
def test_namespaces(self):
s1, s2, s3 = Spin("s1"), Spin("s2"), Spin("s3")
H = (SubH(2 * s1 + 4 * s2, "n1") + SubH(6 * s3 + s2, "n2"))**2
model = H.compile()
self.assertTrue(model.namespaces[0]['n1'] == {'s1', 's2'})
self.assertTrue(model.namespaces[0]['n2'] == {'s2', 's3'})
def test_or_from_vars(self):
a, b, c = Binary("a"), Binary("b"), Binary("c")
exp = (SubH(a + b, 'n1') + SubH(b + c, 'n2'))**2
model = exp.compile()
set_x = VarSetFromVarLabels([a, b])
set_y = VarSetFromVarLabels([b, c])
set_z = OrVars(set_x, set_y)
self.assertTrue(set_x.var_names(model) == {'a', 'b'})
self.assertTrue(set_y.var_names(model) == {'b', 'c'})
self.assertTrue(set_z.var_names(model) == {'a', 'b', 'c'})
def test_and_from_model(self):
a, b, c = Binary("a"), Binary("b"), Binary("c")
exp = (SubH(a + b, 'n1') + SubH(b + c, 'n2'))**2
model = exp.compile()
set_x = VarSetFromSubH('n1')
set_y = VarSetFromSubH('n2')
set_z = AndVars(set_x, set_y)
self.assertTrue(set_x.var_names(model) == {'a', 'b'})
self.assertTrue(set_y.var_names(model) == {'b', 'c'})
self.assertTrue(set_z.var_names(model) == {'b'})
def test_compile_subh(self):
a, b = Binary("a"), Binary("b")
p = Placeholder("p")
exp = p * SubH((a + b - 1)**2, label="subh") + a * b
expected_qubo = {('a', 'a'): -3.0, ('a', 'b'): 7.0, ('b', 'b'): -3.0}
expected_offset = 3
feed_dict = {"p": 3}
self.compile_check(exp, expected_qubo, expected_offset, feed_dict)
def __init__(self, label, value_range, strength):
lower, upper = value_range
assert upper > lower, "upper value should be larger than lower value"
assert isinstance(lower, int)
assert isinstance(upper, int)
assert isinstance(strength, int) or isinstance(strength, float) or\
isinstance(strength, Placeholder)
self._num_variables = (upper - lower + 1)
self.array = Array.create(label, shape=self._num_variables, vartype='BINARY')
self.constraint = Constraint((sum(self.array)-1)**2, label=label+"_const", condition=lambda x: x==0)
express = SubH(lower + sum(i*x for i, x in enumerate(self.array)), label=label)
penalty = self.constraint * strength
super().__init__(
label=label,
value_range=value_range,
express=express,
penalty=penalty)
def test_decode_sample(self):
x = Array.create("x", (2, 2), vartype="BINARY")
exp = SubH((x[1, 1] + x[0, 1] + x[0, 0] - 1)**2, label="const")
model = exp.compile()
# type of solution is dict[label, int]
## vartype = BINARY
sample = {'x[0][1]': 1, 'x[1][1]': 1, 'x[0][0]': 0}
decoded_sample = model.decode_sample(sample, vartype="BINARY")
self.assertTrue(decoded_sample.sample == sample)
self.assertTrue(
len([
label for label, energy in decoded_sample.subh.items()
if energy > 0
]) == 1)
self.assertTrue(decoded_sample.energy == 1)
self.assertTrue(decoded_sample.array("x", (0, 0)) == 0)
self.assertTrue(decoded_sample.array("x", (0, 1)) == 1)
self.assertTrue(decoded_sample.array("x", (1, 1)) == 1)
sample = {'x[0][1]': 1, 'x[1][1]': 0, 'x[0][0]': 0}
decoded_sample = model.decode_sample(sample, vartype="BINARY")
self.assertTrue(decoded_sample.sample == sample)
self.assertTrue(
len([
label for label, energy in decoded_sample.subh.items()
if energy > 0
]) == 0)
self.assertTrue(decoded_sample.energy == 0)
self.assertTrue(decoded_sample.array("x", (0, 0)) == 0)
self.assertTrue(decoded_sample.array("x", (0, 1)) == 1)
self.assertTrue(decoded_sample.array("x", (1, 1)) == 0)
## vartype = SPIN
sample = {'x[0][1]': 1, 'x[1][1]': 1, 'x[0][0]': -1}
decoded_sample = model.decode_sample(sample, vartype="SPIN")
self.assertTrue(decoded_sample.sample == sample)
self.assertTrue(
len([
label for label, energy in decoded_sample.subh.items()
if energy > 0
]) == 1)
self.assertTrue(decoded_sample.energy == 1)
self.assertTrue(decoded_sample.array("x", (0, 0)) == -1)
self.assertTrue(decoded_sample.array("x", (0, 1)) == 1)
self.assertTrue(decoded_sample.array("x", (1, 1)) == 1)
sample = {'x[0][1]': 1, 'x[1][1]': -1, 'x[0][0]': -1}
decoded_sample = model.decode_sample(sample, vartype="SPIN")
self.assertTrue(decoded_sample.sample == sample)
self.assertTrue(
len([
label for label, energy in decoded_sample.subh.items()
if energy > 0
]) == 0)
self.assertTrue(decoded_sample.energy == 0)
self.assertTrue(decoded_sample.array("x", (0, 0)) == -1)
self.assertTrue(decoded_sample.array("x", (0, 1)) == 1)
self.assertTrue(decoded_sample.array("x", (1, 1)) == -1)
# type of solution is list[int]
## vartype = BINARY
sample = {'x[0][1]': 1, 'x[1][1]': 0, 'x[0][0]': 1}
list_sample = [sample[v] for v in model.variables]
decoded_sample = model.decode_sample(list_sample, vartype="BINARY")
self.assertTrue(decoded_sample.sample == sample)
self.assertTrue(
len([
label for label, energy in decoded_sample.subh.items()
if energy > 0
]) == 1)
self.assertTrue(decoded_sample.energy == 1)
self.assertTrue(decoded_sample.array("x", (0, 0)) == 1)
self.assertTrue(decoded_sample.array("x", (0, 1)) == 1)
self.assertTrue(decoded_sample.array("x", (1, 1)) == 0)
sample = {'x[0][1]': 1, 'x[1][1]': 0, 'x[0][0]': 0}
list_sample = [sample[v] for v in model.variables]
decoded_sample = model.decode_sample(list_sample, vartype="BINARY")
self.assertTrue(decoded_sample.sample == sample)
self.assertTrue(
len([
label for label, energy in decoded_sample.subh.items()
if energy > 0
]) == 0)
self.assertTrue(decoded_sample.energy == 0)
self.assertTrue(decoded_sample.array("x", (0, 0)) == 0)
self.assertTrue(decoded_sample.array("x", (0, 1)) == 1)
self.assertTrue(decoded_sample.array("x", (1, 1)) == 0)
## vartype = SPIN
sample = {'x[0][1]': 1, 'x[1][1]': 1, 'x[0][0]': -1}
list_sample = [sample[v] for v in model.variables]
decoded_sample = model.decode_sample(list_sample, vartype="SPIN")
self.assertTrue(decoded_sample.sample == sample)
self.assertTrue(
len([
label for label, energy in decoded_sample.subh.items()
if energy > 0
]) == 1)
self.assertTrue(decoded_sample.energy == 1)
self.assertTrue(decoded_sample.array("x", (0, 0)) == -1)
self.assertTrue(decoded_sample.array("x", (0, 1)) == 1)
self.assertTrue(decoded_sample.array("x", (1, 1)) == 1)
sample = {'x[0][1]': 1, 'x[1][1]': -1, 'x[0][0]': -1}
list_sample = [sample[v] for v in model.variables]
decoded_sample = model.decode_sample(list_sample, vartype="SPIN")
self.assertTrue(decoded_sample.sample == sample)
self.assertTrue(
len([
label for label, energy in decoded_sample.subh.items()
if energy > 0
]) == 0)
self.assertTrue(decoded_sample.energy == 0)
self.assertTrue(decoded_sample.array("x", (0, 0)) == -1)
self.assertTrue(decoded_sample.array("x", (0, 1)) == 1)
self.assertTrue(decoded_sample.array("x", (1, 1)) == -1)
# type of solution is dict[index_label(int), bit]
## vartype = BINARY
sample = {'x[0][1]': 1, 'x[1][1]': 0, 'x[0][0]': 1}
sample_index = {v: sample[v] for v in model.variables}
decoded_sample = model.decode_sample(sample_index, vartype="BINARY")
self.assertTrue(decoded_sample.sample == sample)
self.assertTrue(
len([
label for label, energy in decoded_sample.subh.items()
if energy > 0
]) == 1)
self.assertTrue(decoded_sample.energy == 1)
self.assertTrue(decoded_sample.array("x", (0, 0)) == 1)
self.assertTrue(decoded_sample.array("x", (0, 1)) == 1)
self.assertTrue(decoded_sample.array("x", (1, 1)) == 0)
sample = {'x[0][1]': 1, 'x[1][1]': 0, 'x[0][0]': 0}
sample_index = {v: sample[v] for v in model.variables}
decoded_sample = model.decode_sample(sample_index, vartype="BINARY")
self.assertTrue(decoded_sample.sample == sample)
self.assertTrue(
len([
label for label, energy in decoded_sample.subh.items()
if energy > 0
]) == 0)
self.assertTrue(decoded_sample.energy == 0)
self.assertTrue(decoded_sample.array("x", (0, 0)) == 0)
self.assertTrue(decoded_sample.array("x", (0, 1)) == 1)
self.assertTrue(decoded_sample.array("x", (1, 1)) == 0)
## vartype = SPIN
sample = {'x[0][1]': 1, 'x[1][1]': 1, 'x[0][0]': -1}
sample_index = {v: sample[v] for v in model.variables}
decoded_sample = model.decode_sample(sample_index, vartype="SPIN")
self.assertTrue(decoded_sample.sample == sample)
self.assertTrue(
len([
label for label, energy in decoded_sample.subh.items()
if energy > 0
]) == 1)
self.assertTrue(decoded_sample.energy == 1)
self.assertTrue(decoded_sample.array("x", (0, 0)) == -1)
self.assertTrue(decoded_sample.array("x", (0, 1)) == 1)
self.assertTrue(decoded_sample.array("x", (1, 1)) == 1)
sample = {'x[0][1]': 1, 'x[1][1]': -1, 'x[0][0]': -1}
sample_index = {v: sample[v] for v in model.variables}
decoded_sample = model.decode_sample(sample_index, vartype="SPIN")
self.assertTrue(decoded_sample.sample == sample)
self.assertTrue(
len([
label for label, energy in decoded_sample.subh.items()
if energy > 0
]) == 0)
self.assertTrue(decoded_sample.energy == 0)
self.assertTrue(decoded_sample.array("x", (0, 0)) == -1)
self.assertTrue(decoded_sample.array("x", (0, 1)) == 1)
self.assertTrue(decoded_sample.array("x", (1, 1)) == -1)
# invalid solution
self.assertRaises(
ValueError,
lambda: model.decode_sample([1, 1, 1, 1], vartype="BINARY"))
qubo = model.to_qubo()
self.assertRaises(
ValueError, lambda: model.decode_sample(
{
'x[0][2]': 1,
'x[1][1]': 0,
'x[0][0]': 1
}, vartype="BINARY"))
self.assertRaises(
TypeError, lambda: model.decode_sample((1, 1), vartype="BINARY"))