def test_inconsistent_shapes_for_best_index(self):
"""An error is raised when parameters have inconsistent shapes."""
objective_vector = np.array([1, 2, 3])
constraints_matrix = np.array([[1, 5], [2, 6], [3, 7], [4, 8]])
with self.assertRaises(ValueError):
_ = candidates.find_best_candidate_index(objective_vector,
constraints_matrix)
def test_best_index_rank_objectives_true_max_constraints_true(self):
"""Index should match known solution."""
# To see why the expected answer is 0, notice that:
# self._objective_vector ranks = [2, 1, 4, 3].
# self._constraints_matrix maximum ranks = [2, 3, 4, 1]
index = candidates.find_best_candidate_index(self._objective_vector,
self._constraints_matrix,
rank_objectives=True,
max_constraints=True)
self.assertEqual(0, index)
def test_best_index_rank_objectives_false_max_constraints_false(self):
"""Index should match known solution."""
# To see why the expected answer is 3, notice that:
# self._objective_vector ranks = [2, 1, 4, 3].
# self._constraints_matrix ranks = [[1, 4], [3, 1], [4, 1], [1, 1]].
# Maximum ranks = [4, 3, 4, 1].
index = candidates.find_best_candidate_index(self._objective_vector,
self._constraints_matrix,
rank_objectives=False,
max_constraints=False)
self.assertEqual(3, index)