def test_exact_cover_vqe(self):
        algorithm_cfg = {
            'name': 'VQE',
            'operator_mode': 'matrix',
            'max_evals_grouped': 2
        }

        optimizer_cfg = {
            'name': 'COBYLA'
        }

        var_form_cfg = {
            'name': 'RYRZ',
            'depth': 5
        }

        params = {
            'problem': {'name': 'ising', 'random_seed': 10598},
            'algorithm': algorithm_cfg,
            'optimizer': optimizer_cfg,
            'variational_form': var_form_cfg
        }
        backend = BasicAer.get_backend('statevector_simulator')
        result = run_algorithm(params, self.algo_input, backend=backend)
        x = exact_cover.sample_most_likely(len(self.list_of_subsets), result['eigvecs'][0])
        ising_sol = exact_cover.get_solution(x)
        oracle = self.brute_force()
        self.assertEqual(exact_cover.check_solution_satisfiability(ising_sol, self.list_of_subsets), oracle)
 def test_exact_cover_direct(self):
     algo = ExactEigensolver(self.algo_input.qubit_op, k=1, aux_operators=[])
     result = algo.run()
     x = exact_cover.sample_most_likely(len(self.list_of_subsets), result['eigvecs'][0])
     ising_sol = exact_cover.get_solution(x)
     np.testing.assert_array_equal(ising_sol, [0, 1, 1, 0])
     oracle = self.brute_force()
     self.assertEqual(exact_cover.check_solution_satisfiability(ising_sol, self.list_of_subsets), oracle)
 def test_exact_cover(self):
     params = {
         'problem': {'name': 'ising'},
         'algorithm': {'name': 'ExactEigensolver'}
     }
     result = run_algorithm(params, self.algo_input)
     x = exact_cover.sample_most_likely(len(self.list_of_subsets), result['eigvecs'][0])
     ising_sol = exact_cover.get_solution(x)
     np.testing.assert_array_equal(ising_sol, [0, 1, 1, 0])
     oracle = self.brute_force()
     self.assertEqual(exact_cover.check_solution_satisfiability(ising_sol, self.list_of_subsets), oracle)