def test_get_betas_Y():
actual = linear_modeling.get_betas_Y(X, data)[0]
expected = np.array([[-0.85496183, -0.11450382, -0.01526718],
[6.91603053, 2.90839695, 6.58778626]])
assert_almost_equal(expected, actual)
actual = linear_modeling.get_betas_Y(X, data)[1]
expected = np.array([[1, 1, 3], [0, 0, 7], [7, 4, 9], [0, 4, 7]])
assert_almost_equal(expected, actual)
def test_get_betas_Y():
actual = linear_modeling.get_betas_Y(X, data)[0]
expected = np.array([[-0.85496183, -0.11450382, -0.01526718],
[6.91603053, 2.90839695, 6.58778626]])
assert_almost_equal(expected, actual)
actual = linear_modeling.get_betas_Y(X, data)[1]
expected = np.array([[1, 1, 3], [0, 0, 7], [7, 4, 9], [0, 4, 7]])
assert_almost_equal(expected, actual)
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_get_betas_4d():
actual = linear_modeling.get_betas_4d(
linear_modeling.get_betas_Y(X, data)[0], data)
expected = np.array([[[-0.85496183, 6.91603053], [-0.11450382, 2.90839695],
[-0.01526718, 6.58778626]]])
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)
def test_get_betas_4d():
actual = linear_modeling.get_betas_4d(
linear_modeling.get_betas_Y(X, data)[0], data)
expected = np.array([[[-0.85496183, 6.91603053], [-0.11450382, 2.90839695],
[-0.01526718, 6.58778626]]])
assert_almost_equal(expected, actual)
