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 = {}
linear['x0'] = 1
linear['x1'] = 2
linear['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.encode(op)
result = OptimizationResult(x=[0, 1, 1, 1, 1], fval=17)
new_result = conv.decode(result)
self.assertListEqual(new_result.x, [0, 1, 5])
self.assertEqual(new_result.fval, 17)
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.encode(op)
admm_params = ADMMParameters()
qubo_optimizer = MinimumEigenOptimizer(NumPyMinimumEigensolver())
continuous_optimizer = CplexOptimizer()
solver = ADMMOptimizer(
qubo_optimizer=qubo_optimizer,
continuous_optimizer=continuous_optimizer,
params=admm_params,
)
solution = solver.solve(op)
solution = converter.decode(solution)
self.assertEqual(solution.x[0], 10.9)
except NameError as ex:
self.skipTest(str(ex))