def test_sawatabi_solver_with_initial_states_reverse():
model = LogicalModel(mtype="ising")
x = model.variables("x", shape=(6,))
for i in range(6):
model.add_interaction(x[i], coefficient=10.0)
solver = SawatabiSolver()
initial_states = [
{
"x[0]": -1,
"x[1]": -1,
"x[2]": -1,
"x[3]": -1,
"x[4]": -1,
"x[5]": -1,
},
]
sampleset = solver.solve(
model.to_physical(),
num_reads=1,
num_sweeps=10,
initial_states=initial_states,
reverse_options={"reverse_period": 5, "reverse_temperature": 10.0},
seed=12345,
)
assert len(sampleset.record) == 1
# Check the ground state
assert np.array_equal(sampleset.record[0].sample, [1, 1, 1, 1, 1, 1])
assert sampleset.record[0].energy == -60.0
assert sampleset.record[0].num_occurrences == 1
def test_sawatabi_solver_with_initial_states_ising():
model = LogicalModel(mtype="ising")
x = model.variables("x", shape=(12,))
for i in range(12):
model.add_interaction(x[i], coefficient=-1.0)
solver = SawatabiSolver()
initial_states = [
{
"x[0]": 1,
"x[1]": -1,
"x[2]": -1,
"x[3]": -1,
"x[4]": -1,
"x[5]": -1,
"x[6]": -1,
"x[7]": -1,
"x[8]": -1,
"x[9]": -1,
"x[10]": -1,
"x[11]": -1,
},
]
sampleset = solver.solve(model.to_physical(), num_reads=1, num_sweeps=1, pickup_mode="sequential", initial_temperature=1e-9, initial_states=initial_states)
assert len(sampleset.record) == 1
# Check the ground state
assert np.array_equal(sampleset.record[0].sample, [-1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1])
assert sampleset.record[0].energy == -12.0
assert sampleset.record[0].num_occurrences == 1
def test_sawatabi_solver_with_initial_states_qubo():
model = LogicalModel(mtype="qubo")
x = model.variables("x", shape=(6,))
for i in range(6):
model.add_interaction(x[i], coefficient=-1.0)
solver = SawatabiSolver()
initial_states = [
{
"x[0]": 1,
"x[1]": 0,
"x[2]": 1,
"x[3]": 0,
"x[4]": 1,
"x[5]": 0,
},
]
sampleset = solver.solve(model.to_physical(), num_reads=1, num_sweeps=10, cooling_rate=0.5, initial_states=initial_states, seed=12345)
assert len(sampleset.record) == 1
# Check the ground state
assert np.array_equal(sampleset.record[0].sample, [0, 0, 0, 0, 0, 0])
assert sampleset.record[0].energy == 0.0
assert sampleset.record[0].num_occurrences == 1
def test_sawatabi_solver_invalid_pickup_mode():
model = LogicalModel(mtype="ising")
x = model.variables("x", shape=(2,))
for i in range(2):
model.add_interaction(x[i], coefficient=-1.0)
solver = SawatabiSolver()
with pytest.raises(ValueError):
solver.solve(model.to_physical(), pickup_mode="invalid")
def test_sawatabi_solver_with_initial_states_fails():
model = LogicalModel(mtype="ising")
x = model.variables("x", shape=(2,))
for i in range(2):
model.add_interaction(x[i], coefficient=-1.0)
solver = SawatabiSolver()
initial_states = [{"x[0]": 1, "x[1]": 1}]
with pytest.raises(ValueError):
solver.solve(model.to_physical(), num_reads=2, initial_states=initial_states)
def test_sawatabi_solver_with_stats():
model = LogicalModel(mtype="ising")
x = model.variables("x", shape=(2,))
for i in range(2):
model.add_interaction(x[i], coefficient=-1.0)
solver = SawatabiSolver()
sampleset, stats = solver.solve(model.to_physical(), num_reads=1, num_sweeps=10, cooling_rate=0.5, seed=12345, need_stats=True)
assert stats[0]["acceptance_history"][-1] == 0
assert stats[0]["energy_history"][-1] == -2.0
assert stats[0]["temperature_history"] == [100.0, 50.0, 25.0, 12.5, 6.25, 3.125, 1.5625, 0.78125, 0.390625, 0.1953125]
def test_sawatabi_solver_n_hot_ising_with_deleting(n, s, i):
# n out of (s - 1) variables should be 1
model = LogicalModel(mtype="ising")
x = model.variables("x", shape=(s,))
model.add_constraint(NHotConstraint(variables=x, n=n))
model.delete_variable(x[i])
solver = SawatabiSolver()
sampleset = solver.solve(model.to_physical(), seed=12345)
result = np.array(sampleset.record[0].sample)
assert np.count_nonzero(result == 1) == n
assert np.count_nonzero(result == -1) == s - n - 1
def test_sawatabi_solver_reuse_solver_instance():
model = LogicalModel(mtype="ising")
x = model.variables("x", shape=(2,))
for i in range(2):
model.add_interaction(x[i], coefficient=-1.0)
solver = SawatabiSolver()
sampleset_1 = solver.solve(model.to_physical(), num_reads=1, num_sweeps=10, cooling_rate=0.5, seed=12345)
assert np.array_equal(sampleset_1.record[0].sample, [-1, -1])
assert sampleset_1.record[0].energy == -2.0
sampleset_2 = solver.solve(model.to_physical(), num_reads=1, num_sweeps=10, cooling_rate=0.5, seed=12345)
assert np.array_equal(sampleset_2.record[0].sample, [-1, -1])
assert sampleset_2.record[0].energy == -2.0
def test_sawatabi_solver_n_hot_qubo(n, s):
# n out of s variables should be 1
model = LogicalModel(mtype="qubo")
x = model.variables("x", shape=(s,))
model.add_constraint(NHotConstraint(variables=x, n=n))
solver = SawatabiSolver()
sampleset = solver.solve(model.to_physical(), seed=12345)
result = np.array(sampleset.record[0].sample)
assert np.count_nonzero(result == 1) == n
assert np.count_nonzero(result == 0) == s - n
# Execution time should be within practical seconds (20 sec).
assert sampleset.info["timing"]["execution_sec"] <= 20.0
def test_sawatabi_solver_qubo():
model = LogicalModel(mtype="qubo")
x = model.variables("x", shape=(2,))
model.add_interaction(x[0], coefficient=1.0)
model.add_interaction(x[1], coefficient=2.0)
model.add_interaction((x[0], x[1]), coefficient=-5.0)
model.offset(10.0)
solver = SawatabiSolver()
sampleset = solver.solve(model.to_physical(), num_reads=1, num_sweeps=10, cooling_rate=0.55, seed=12345)
assert sampleset.variables == ["x[0]", "x[1]"]
assert len(sampleset.record) == 1
# Check the ground state
record = sorted(sampleset.record, key=lambda r: r.energy) # sort by energy
assert np.array_equal(record[0].sample, [0, 1])
assert record[0].energy == 8.0
def test_sawatabi_solver_ising():
model = LogicalModel(mtype="ising")
s = model.variables("s", shape=(2,))
model.add_interaction(s[0], coefficient=1.0)
model.add_interaction(s[1], coefficient=2.0)
model.add_interaction((s[0], s[1]), coefficient=-3.0)
model.offset(10.0)
solver = SawatabiSolver()
sampleset = solver.solve(model.to_physical(), num_reads=2, num_sweeps=10, cooling_rate=0.5, initial_temperature=10.0, seed=12345)
assert sampleset.variables == ["s[0]", "s[1]"]
assert len(sampleset.record) == 1
# Check the ground state
assert np.array_equal(sampleset.record[0].sample, [-1, 1])
assert sampleset.record[0].energy == 6.0
assert sampleset.record[0].num_occurrences == 2
def test_sawatabi_solver_qubo_without_active_var():
model = LogicalModel(mtype="qubo")
x = model.variables("x", shape=(2, 2))
model.add_interaction(x[0, 1], coefficient=1.0)
model.add_interaction((x[1, 0], x[1, 1]), coefficient=2.0)
physical = model.to_physical()
assert len(physical._label_to_index) == 3
assert len(physical._index_to_label) == 3
solver = SawatabiSolver()
sampleset = solver.solve(physical, seed=12345)
assert sampleset.variables == ["x[0][1]", "x[1][0]", "x[1][1]"]
assert len(sampleset.record) == 1
# Check the ground state
assert np.array_equal(sampleset.record[0].sample, [1, 1, 1])
assert sampleset.record[0].energy == -3.0
assert sampleset.record[0].num_occurrences == 1
def test_sawatabi_solver_ising_without_active_var():
model = LogicalModel(mtype="ising")
s = model.variables("s", shape=(2, 2))
model.add_interaction(s[0, 1], coefficient=1.0)
model.add_interaction((s[1, 0], s[1, 1]), coefficient=2.0)
physical = model.to_physical()
assert len(physical._label_to_index) == 3
assert len(physical._index_to_label) == 3
solver = SawatabiSolver()
sampleset = solver.solve(physical, num_reads=10, seed=12345)
assert sampleset.variables == ["s[0][1]", "s[1][0]", "s[1][1]"]
assert len(sampleset.record) == 2
# Check the ground state
assert np.array_equal(sampleset.record[0].sample, [1, -1, -1])
assert np.array_equal(sampleset.record[1].sample, [1, 1, 1])
assert sampleset.record[0].energy == -3
assert sampleset.record[1].energy == -3
assert sampleset.record[0].num_occurrences + sampleset.record[1].num_occurrences == 10
def test_sawatabi_solver_invalid_reverse_options():
model = LogicalModel(mtype="ising")
x = model.variables("x", shape=(2,))
for i in range(2):
model.add_interaction(x[i], coefficient=-1.0)
solver = SawatabiSolver()
with pytest.raises(ValueError):
solver.solve(model.to_physical(), reverse_options={"reverse_period": 5})
with pytest.raises(ValueError):
solver.solve(model.to_physical(), reverse_options={"reverse_temperature": 10.0})
def test_sawatabi_solver_with_empty_model_fails():
model = LogicalModel(mtype="ising")
physical = model.to_physical()
solver = SawatabiSolver()
with pytest.raises(ValueError):
solver.solve(physical, seed=12345)
def test_sawatabi_solver_with_logical_model_fails():
model = LogicalModel(mtype="ising")
solver = SawatabiSolver()
with pytest.raises(TypeError):
solver.solve(model, seed=12345)
