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)