def test_mse(): x = [1, 2, 2, 3] y = [3, 4, 5, 6] model = lsrl(x, y) assert mse(x, y, model, rounding=3) == 0.25 x = [6, 7, 7, 8, 10, 10, 11, 12, 14, 15, 16] y = [55, 40, 50, 41, 35, 28, 38, 32, 28, 18, 13] model = lsrl(x, y) assert round(math.sqrt(mse(x, y, model)), 2) == 5.01
def test_lsrl(): x = [1, 2, 2, 3] y = [3, 4, 5, 6] model = lsrl(x, y) assert isinstance(model, LinearRegression) assert round(model.intercept_, 2) == 1.5 assert round(model.coef_[0], 2) == 1.5 x = [6, 7, 7, 8, 10, 10, 11, 12, 14, 15, 16] y = [55, 40, 50, 41, 35, 28, 38, 32, 28, 18, 13] model = lsrl(x, y) assert isinstance(model, LinearRegression) assert round(model.intercept_, 2) == 70.16 assert round(model.coef_[0], 2) == -3.39
def test_lsrl_summarize(): x = [6, 7, 7, 8, 10, 10, 11, 12, 14, 15, 16] y = [55, 40, 50, 41, 35, 28, 38, 32, 28, 18, 13] assert lsrl( x, y, summarize=True, rounding=2) == {'intercept': 70.16, 'slope': -3.39}
def test_t_conf_y(): x = [6, 7, 7, 8, 10, 10, 11, 12, 14, 15, 16] y = [55, 40, 50, 41, 35, 28, 38, 32, 28, 18, 13] k = 1 model = lsrl(x, y) s_2 = mse(x, y, model) df = len(x) - (k + 1) res = t_conf_y(x, 13, s_2, model, df, rounding=3) assert res == (21.754, 30.311)
def test_t_pred_y(): x = [6, 7, 7, 8, 10, 10, 11, 12, 14, 15, 16] y = [55, 40, 50, 41, 35, 28, 38, 32, 28, 18, 13] k = 1 model = lsrl(x, y) s_2 = mse(x, y, model) df = len(x) - (k + 1) res = t_pred_y(x, 13, s_2, model, df, rounding=3) assert res == (13.919, 38.146)
def test_residuals(): x = [1, 2, 2, 3] y = [3, 4, 5, 6] model = lsrl(x, y) assert residuals(x, y, model, 3) == [0.0, -0.5, 0.5, 0.0]