def test_integer_to_binary2(self):
"""Test integer to binary variables 2"""
mod = QuadraticProgram()
mod.integer_var(name="x", lowerbound=0, upperbound=1)
mod.integer_var(name="y", lowerbound=0, upperbound=1)
mod.minimize(1, {"x": 1}, {("x", "y"): 2})
mod.linear_constraint({"x": 1}, "==", 1)
mod.quadratic_constraint({"x": 1}, {("x", "y"): 2}, "==", 1)
mod2 = IntegerToBinary().convert(mod)
self.assertListEqual([e.name + "@0" for e in mod.variables],
[e.name for e in mod2.variables])
self.assertDictEqual(mod.objective.linear.to_dict(),
mod2.objective.linear.to_dict())
self.assertDictEqual(mod.objective.quadratic.to_dict(),
mod2.objective.quadratic.to_dict())
self.assertEqual(mod.get_num_linear_constraints(),
mod2.get_num_linear_constraints())
for cst, cst2 in zip(mod.linear_constraints, mod2.linear_constraints):
self.assertDictEqual(cst.linear.to_dict(), cst2.linear.to_dict())
self.assertEqual(mod.get_num_quadratic_constraints(),
mod2.get_num_quadratic_constraints())
for cst, cst2 in zip(mod.quadratic_constraints,
mod2.quadratic_constraints):
self.assertDictEqual(cst.linear.to_dict(), cst2.linear.to_dict())
self.assertDictEqual(cst.quadratic.to_dict(),
cst2.quadratic.to_dict())
def test_binary_to_integer(self):
"""Test binary to integer"""
op = QuadraticProgram()
for i in range(0, 2):
op.binary_var(name="x{}".format(i))
op.integer_var(name="x2", lowerbound=0, upperbound=5)
linear = {"x0": 1, "x1": 2, "x2": 1}
op.maximize(0, linear, {})
linear = {}
for x in op.variables:
linear[x.name] = 1
op.linear_constraint(linear, Constraint.Sense.EQ, 6, "x0x1x2")
conv = IntegerToBinary()
_ = conv.convert(op)
new_x = conv.interpret([0, 1, 1, 1, 1])
np.testing.assert_array_almost_equal(new_x, [0, 1, 5])
def test_converter_list(self):
"""Test converter list"""
op = QuadraticProgram()
op.integer_var(0, 3, "x")
op.binary_var('y')
op.maximize(linear={'x': 1, 'y': 2})
op.linear_constraint(linear={'x': 1, 'y': 1}, sense='LE', rhs=3, name='xy_leq')
min_eigen_solver = NumPyMinimumEigensolver()
# a single converter
qp2qubo = QuadraticProgramToQubo()
min_eigen_optimizer = MinimumEigenOptimizer(min_eigen_solver, converters=qp2qubo)
result = min_eigen_optimizer.solve(op)
self.assertEqual(result.fval, 4)
# a list of converters
ineq2eq = InequalityToEquality()
int2bin = IntegerToBinary()
penalize = LinearEqualityToPenalty()
converters = [ineq2eq, int2bin, penalize]
min_eigen_optimizer = MinimumEigenOptimizer(min_eigen_solver, converters=converters)
result = min_eigen_optimizer.solve(op)
self.assertEqual(result.fval, 4)
with self.assertRaises(TypeError):
invalid = [qp2qubo, "invalid converter"]
MinimumEigenOptimizer(min_eigen_solver,
converters=invalid)
def test_converter_list(self):
"""Test converters list"""
# Input.
model = Model()
x_0 = model.binary_var(name='x0')
x_1 = model.binary_var(name='x1')
model.maximize(-x_0+2*x_1)
op = QuadraticProgram()
op.from_docplex(model)
# Get the optimum key and value.
n_iter = 8
# a single converter.
qp2qubo = QuadraticProgramToQubo()
gmf = GroverOptimizer(4, num_iterations=n_iter, quantum_instance=self.sv_simulator,
converters=qp2qubo)
results = gmf.solve(op)
self.validate_results(op, results)
# a list of converters
ineq2eq = InequalityToEquality()
int2bin = IntegerToBinary()
penalize = LinearEqualityToPenalty()
converters = [ineq2eq, int2bin, penalize]
gmf = GroverOptimizer(4, num_iterations=n_iter, quantum_instance=self.sv_simulator,
converters=converters)
results = gmf.solve(op)
self.validate_results(op, results)
# invalid converters
with self.assertRaises(TypeError):
invalid = [qp2qubo, "invalid converter"]
GroverOptimizer(4, num_iterations=n_iter,
quantum_instance=self.sv_simulator,
converters=invalid)
def test_integer_to_binary(self):
""" Test integer to binary """
op = QuadraticProgram()
for i in range(0, 2):
op.binary_var(name='x{}'.format(i))
op.integer_var(name='x2', lowerbound=0, upperbound=5)
linear = {}
for i, x in enumerate(op.variables):
linear[x.name] = i + 1
op.maximize(0, linear, {})
conv = IntegerToBinary()
op2 = conv.convert(op)
self.assertEqual(op2.get_num_vars(), 5)
self.assertListEqual([x.vartype for x in op2.variables], [Variable.Type.BINARY] * 5)
self.assertListEqual([x.name for x in op2.variables], ['x0', 'x1', 'x2@0', 'x2@1', 'x2@2'])
dct = op2.objective.linear.to_dict()
self.assertEqual(dct[2], 3)
self.assertEqual(dct[3], 6)
self.assertEqual(dct[4], 6)
def test_empty_problem(self):
""" Test empty problem """
op = QuadraticProgram()
conv = InequalityToEquality()
op = conv.convert(op)
conv = IntegerToBinary()
op = conv.convert(op)
conv = LinearEqualityToPenalty()
op = conv.convert(op)
_, shift = op.to_ising()
self.assertEqual(shift, 0.0)
def test_continuous_variable_decode(self):
"""Test decode func of IntegerToBinaryConverter for continuous variables"""
mdl = Model("test_continuous_varable_decode")
c = mdl.continuous_var(lb=0, ub=10.9, name="c")
x = mdl.binary_var(name="x")
mdl.maximize(c + x * x)
op = from_docplex_mp(mdl)
converter = IntegerToBinary()
op = converter.convert(op)
admm_params = ADMMParameters()
qubo_optimizer = MinimumEigenOptimizer(NumPyMinimumEigensolver())
continuous_optimizer = CplexOptimizer()
solver = ADMMOptimizer(
qubo_optimizer=qubo_optimizer,
continuous_optimizer=continuous_optimizer,
params=admm_params,
)
result = solver.solve(op)
new_x = converter.interpret(result.x)
self.assertEqual(new_x[0], 10.9)
def test_continuous_variable_decode(self):
""" Test decode func of IntegerToBinaryConverter for continuous variables"""
try:
mdl = Model('test_continuous_varable_decode')
c = mdl.continuous_var(lb=0, ub=10.9, name='c')
x = mdl.binary_var(name='x')
mdl.maximize(c + x * x)
op = QuadraticProgram()
op.from_docplex(mdl)
converter = IntegerToBinary()
op = converter.convert(op)
admm_params = ADMMParameters()
qubo_optimizer = MinimumEigenOptimizer(NumPyMinimumEigensolver())
continuous_optimizer = CplexOptimizer()
solver = ADMMOptimizer(
qubo_optimizer=qubo_optimizer,
continuous_optimizer=continuous_optimizer,
params=admm_params,
)
result = solver.solve(op)
new_x = converter.interpret(result.x)
self.assertEqual(new_x[0], 10.9)
except MissingOptionalLibraryError as ex:
self.skipTest(str(ex))
def test_converter_list(self):
"""Test converter list"""
op = QuadraticProgram()
op.integer_var(0, 3, "x")
op.binary_var("y")
op.maximize(linear={"x": 1, "y": 2})
op.linear_constraint(linear={
"y": 1,
"x": 1
},
sense="LE",
rhs=3,
name="xy_leq")
# construct minimum eigen optimizer
min_eigen_solver = NumPyMinimumEigensolver()
min_eigen_optimizer = MinimumEigenOptimizer(min_eigen_solver)
# a single converter
qp2qubo = QuadraticProgramToQubo()
recursive_min_eigen_optimizer = RecursiveMinimumEigenOptimizer(
min_eigen_optimizer, min_num_vars=2, converters=qp2qubo)
result = recursive_min_eigen_optimizer.solve(op)
self.assertEqual(result.fval, 4)
# a list of converters
ineq2eq = InequalityToEquality()
int2bin = IntegerToBinary()
penalize = LinearEqualityToPenalty()
converters = [ineq2eq, int2bin, penalize]
recursive_min_eigen_optimizer = RecursiveMinimumEigenOptimizer(
min_eigen_optimizer, min_num_vars=2, converters=converters)
result = recursive_min_eigen_optimizer.solve(op)
self.assertEqual(result.fval, 4)
# invalid converters
with self.assertRaises(TypeError):
invalid = [qp2qubo, "invalid converter"]
RecursiveMinimumEigenOptimizer(min_eigen_optimizer,
min_num_vars=2,
converters=invalid)
def test_integer_to_binary_quadratic(self):
"""Test integer to binary variables with quadratic expressions"""
mod = QuadraticProgram()
mod.integer_var(name="x", lowerbound=10, upperbound=13)
mod.minimize(quadratic={("x", "x"): 1})
mod2 = IntegerToBinary().convert(mod)
self.assertListEqual([e.name for e in mod2.variables], ["x@0", "x@1"])
self.assertEqual(mod.get_num_linear_constraints(), 0)
self.assertEqual(mod.get_num_quadratic_constraints(), 0)
self.assertAlmostEqual(mod2.objective.constant, 100)
self.assertDictEqual(mod2.objective.linear.to_dict(use_name=True), {
"x@0": 20,
"x@1": 40
})
self.assertDictEqual(
mod2.objective.quadratic.to_dict(use_name=True),
{
("x@0", "x@0"): 1,
("x@1", "x@1"): 4,
("x@0", "x@1"): 4
},
)
def test_integer_to_binary_zero_range_variable(self):
"""Test integer to binary variables with zero range variables"""
with self.subTest(
"zero range variable in a linear expression of the objective"):
mod = QuadraticProgram()
mod.integer_var(name="x", lowerbound=10, upperbound=10)
mod.minimize(linear={"x": 1})
mod2 = IntegerToBinary().convert(mod)
self.assertListEqual([e.name for e in mod2.variables], ["x@0"])
self.assertEqual(mod.get_num_linear_constraints(), 0)
self.assertEqual(mod.get_num_quadratic_constraints(), 0)
self.assertAlmostEqual(mod2.objective.constant, 10)
self.assertDictEqual(mod2.objective.linear.to_dict(), {})
self.assertDictEqual(mod2.objective.quadratic.to_dict(), {})
with self.subTest(
"zero range variable in a quadratic expression of the objective"
):
mod = QuadraticProgram()
mod.integer_var(name="x", lowerbound=10, upperbound=10)
mod.minimize(quadratic={("x", "x"): 1})
mod2 = IntegerToBinary().convert(mod)
self.assertListEqual([e.name for e in mod2.variables], ["x@0"])
self.assertEqual(mod.get_num_linear_constraints(), 0)
self.assertEqual(mod.get_num_quadratic_constraints(), 0)
self.assertAlmostEqual(mod2.objective.constant, 100)
self.assertDictEqual(mod2.objective.linear.to_dict(), {})
self.assertDictEqual(mod2.objective.quadratic.to_dict(), {})
with self.subTest("zero range variable in a linear constraint"):
mod = QuadraticProgram()
mod.integer_var(name="x", lowerbound=10, upperbound=10)
mod.binary_var(name="y")
mod.linear_constraint({"x": 1, "y": 1}, "<=", 100)
mod2 = IntegerToBinary().convert(mod)
self.assertListEqual([e.name for e in mod2.variables],
["x@0", "y"])
self.assertEqual(mod.get_num_linear_constraints(), 1)
self.assertEqual(mod.get_num_quadratic_constraints(), 0)
self.assertAlmostEqual(mod2.objective.constant, 0)
self.assertDictEqual(mod2.objective.linear.to_dict(), {})
self.assertDictEqual(mod2.objective.quadratic.to_dict(), {})
cst = mod2.get_linear_constraint(0)
self.assertDictEqual(cst.linear.to_dict(use_name=True), {"y": 1})
self.assertEqual(cst.sense, Constraint.Sense.LE)
self.assertAlmostEqual(cst.rhs, 90)
self.assertEqual(cst.name, "c0")
with self.subTest("zero range variable in a quadratic constraint"):
mod = QuadraticProgram()
mod.integer_var(name="x", lowerbound=10, upperbound=10)
mod.binary_var(name="y")
mod.quadratic_constraint({"x": 1}, {
("x", "x"): 2,
("x", "y"): 3
}, ">=", 100)
mod2 = IntegerToBinary().convert(mod)
self.assertListEqual([e.name for e in mod2.variables],
["x@0", "y"])
self.assertEqual(mod.get_num_linear_constraints(), 0)
self.assertEqual(mod.get_num_quadratic_constraints(), 1)
self.assertAlmostEqual(mod2.objective.constant, 0)
self.assertDictEqual(mod2.objective.linear.to_dict(), {})
self.assertDictEqual(mod2.objective.quadratic.to_dict(), {})
cst = mod2.get_quadratic_constraint(0)
self.assertDictEqual(cst.linear.to_dict(use_name=True), {"y": 30})
self.assertEqual(cst.sense, Constraint.Sense.GE)
self.assertAlmostEqual(cst.rhs, -110)
self.assertEqual(cst.name, "q0")
