def test_basic_acv_optimizers_give_consistent_output(acv_optimizer, mocker):
exponents = [4, 3, 2, 1]
covariance = _monomial_model_covariance(exponents)
model_costs = _monomial_model_costs(exponents)
target_cost = 10
optimizer = Optimizer.get_algorithm(acv_optimizer)(model_costs,
covariance=covariance)
constraints = optimizer._get_constraints(target_cost)
np.random.seed(0)
for i in range(25):
valid_ratios = \
_generate_random_ratios_fulfilling_constraints(constraints,
model_costs)
mocker.patch.object(Optimizer.get_algorithm(acv_optimizer),
'_solve_opt_problem',
return_value=valid_ratios)
opt_result = optimizer.optimize(target_cost)
_assert_opt_result_is_consistent(covariance, model_costs, opt_result)
def test_acvmfmc_known_solution(cost_factor, covariance_factor, mocker):
covariance = np.array([[1, 0.5], [0.5, 1]]) * covariance_factor
model_costs = np.array([4800, 4])
optimizer = Optimizer(model_costs, covariance)
ratios_for_opt = np.array([20])
mocker.patch.object(Optimizer.get_algorithm("acvmfmc"),
'_solve_opt_problem',
return_value=ratios_for_opt)
cost_ref = 14640 * cost_factor
var_ref = 61 / 240 * covariance_factor / cost_factor
allocation_ref = np.array(
[[3 * cost_factor, 1, 1, 1], [57 * cost_factor, 0, 0, 1]], dtype=int)
target_cost = 14640 * cost_factor
opt_result = optimizer.optimize(algorithm="acvmfmc",
target_cost=target_cost)
assert_opt_result_equal(opt_result, cost_ref, var_ref, allocation_ref)
def test_acvmf_three_models_known_solution(cost_factor, covariance_factor,
mocker):
covariance = np.array([[1, 0.75, 0.25], [0.75, 1., 0.5], [0.25, 0.5, 1.]
]) * covariance_factor
model_costs = np.array([3, 2, 1])
optimizer = Optimizer(model_costs, covariance)
ratios_for_opt = np.array([1, 2])
mocker.patch.object(Optimizer.get_algorithm("wrdiff"),
'_solve_opt_problem',
return_value=ratios_for_opt)
cost_ref = 10. * cost_factor
var_ref = 0.6931818181818182 * covariance_factor / cost_factor
allocation_ref = np.array(
[[1 * cost_factor, 1, 1, 0, 0, 0], [1 * cost_factor, 0, 0, 1, 1, 0],
[2 * cost_factor, 0, 0, 0, 0, 1]],
dtype=int)
target_cost = 10 * cost_factor
opt_result = optimizer.optimize(algorithm="wrdiff",
target_cost=target_cost)
assert_opt_result_equal(opt_result, cost_ref, var_ref, allocation_ref)
