Ejemplo n.º 1
0
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)
Ejemplo n.º 2
0
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
Ejemplo n.º 3
0
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
Ejemplo n.º 4
0
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
Ejemplo n.º 5
0
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)
Ejemplo n.º 6
0
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)