def test_get_top_32():
a = np.array([6, 4, 1, 2, 8, 8, 1, 9, 5, 2, 1, 9, 5, 4, 3, 6, 5, 3, 5, 8])
assert_equal(linear_modeling.get_top_32(a, .2), [11, 7, 19, 4])
actual = linear_modeling.get_top_32(
linear_modeling.t_stat(
linear_modeling.get_betas_Y(X, data)[1], X, [0, 1]), .5)
expected = np.array([0, 2])
assert_almost_equal(actual, expected)
def test_get_top_32():
a = np.array([6, 4, 1, 2, 8, 8, 1, 9, 5, 2, 1, 9, 5, 4, 3, 6, 5, 3, 5, 8])
assert_equal(linear_modeling.get_top_32(a, .2), [11, 7, 19, 4])
actual = linear_modeling.get_top_32(
linear_modeling.t_stat(
linear_modeling.get_betas_Y(X, data)[1], X, [0, 1]), .5)
expected = np.array([0, 2])
assert_almost_equal(actual, expected)
def test_t_stat():
actual = linear_modeling.t_stat(
linear_modeling.get_betas_Y(X, data)[1], X, [0, 1])
expected = np.array([2.7475368, 1.04410995, 1.90484058])
assert_almost_equal(expected, actual)
def test_t_stat():
actual = linear_modeling.t_stat(
linear_modeling.get_betas_Y(X, data)[1], X, [0, 1])
expected = np.array([2.7475368, 1.04410995, 1.90484058])
assert_almost_equal(expected, actual)
