def test_grtol():
paras = np.random.uniform(0.3, 0.4, size=2)
start = np.random.uniform(0.1, 0.2, size=2)
bounds = [[0, 0], [0.3, 0.3]]
num_agents = 10000
objective, x = set_up_test_2(paras, start, num_agents)
len_out = len(objective(x))
out = solve(objective,
x,
len_out,
tol={
"grtol": 10,
"gatol": 1,
"gttol": 1
},
bounds=bounds,
gatol=False,
gttol=False)
assert (out["conv"] == "grtol below critical value"
or out["conv"] == "step size small")
if out["conv"] == 4:
assert (out["sol"][2] / out["sol"][1] < 10)
def test_robustness_2():
# get random args
paras = np.random.uniform(size=2)
start = np.random.uniform(size=2)
# Simulate a sample
num_agents = 10000
objective, x, exog, endog = set_up_test_2_ols(paras, start, num_agents)
# Obtain result with Pounders
len_out = len(objective(x))
out = solve(objective, x, len_out), start, paras
# Obtain result via ols
X = np.concatenate(
(np.ones(len(exog)).reshape(len(exog), 1), exog.reshape(len(exog), 1)),
axis=1).reshape(len(exog), 2)
y = endog.reshape(len(endog), 1)
ols = np.linalg.lstsq(X, y)
# compare
np.testing.assert_almost_equal(ols[0],
np.array(out[0]["solution"]).reshape(2, 1),
decimal=1)
return out
def test_robustness_1():
# get random args
paras = np.random.uniform(size=3)
start = np.random.uniform(size=3)
num_agents = 10000
objective, x = set_up_test_1(paras, start, num_agents)
len_out = len(objective(x))
out = solve(objective, x, len_out), start, paras
return out
def test_box_constr():
paras = np.random.uniform(0.3, 0.4, size=2)
start = np.random.uniform(0.1, 0.2, size=2)
bounds = [[0, 0], [0.3, 0.3]]
num_agents = 10000
objective, x = set_up_test_2(paras, start, num_agents)
len_out = len(objective(x))
out = solve(objective, x, len_out, bounds=bounds)
assert 0 <= out["solution"][0] <= 0.3
assert 0 <= out["solution"][1] <= 0.3
def test_max_iters():
paras = np.random.uniform(0.3, 0.4, size=2)
start = np.random.uniform(0.1, 0.2, size=2)
bounds = [[0, 0], [0.3, 0.3]]
num_agents = 10000
objective, x = set_up_test_2(paras, start, num_agents)
len_out = len(objective(x))
out = solve(objective, x, len_out, bounds=bounds, max_iterations=25)
assert (out["conv"] == 8 or out["conv"] == 6)
if out["conv"] == 8:
assert (out["sol"][0] == 25)
def test_tol():
paras = np.random.uniform(0.3, 0.4, size=2)
start = np.random.uniform(0.1, 0.2, size=2)
bounds = [[0, 0], [0.3, 0.3]]
num_agents = 10000
objective, x = set_up_test_2(paras, start, num_agents)
len_out = len(objective(x))
out = solve(objective,
x,
len_out,
bounds=bounds,
tol={
"gatol": 0.00000001,
"grtol": 0.00000001,
"gttol": 0.0000000001
})
if out["conv"] == 3:
assert (out["sol"][2] < 0.00000001)
elif out["conv"] == 4:
assert (out["sol"][2] / out["sol"][1] < 0.00000001)