def test_power_deriv2_xy3(): x = AutoDiff(1, "x", H=True) y = AutoDiff(2, "y", H=True) f = ef.power(3, x * y) assert np.isclose(f.der2['xy'], 31.612591892639465)
def test_power_no_sec_derivative(): x = AutoDiff(4, "x") y = AutoDiff(3, "y") with pytest.raises(AttributeError): assert ef.power(x, y).der2['x']
def test_power_deriv2_x3(): x = AutoDiff(1, "x", H=True) y = AutoDiff(2, "y", H=True) f = ef.power(3, x * y) assert np.isclose(f.der2['x'], 43.450162589252955)
def test_power_deriv2_y3(): x = AutoDiff(1, "x", H=True) y = AutoDiff(2, "y", H=True) f = ef.power(3, x * y) assert np.isclose(f.der2['y'], 10.862540647313239)
def test_power_deriv_y(): x = AutoDiff(1, "x") y = AutoDiff(2, "y") f = ef.power(x * y, x * y) assert np.isclose(f.der['y'], 6.772588722239782)
def test_power_deriv_y3(): x = AutoDiff(1, "x") y = AutoDiff(2, "y") f = ef.power(3, x * y) assert np.isclose(f.der['y'], 9.887510598012987)
def test_power_deriv2_xy2(): x = AutoDiff(1, "x", H=True) y = AutoDiff(2, "y", H=True) f = ef.power(x * y, 3) assert np.isclose(f.der2['xy'], 36)
def test_power_numeric_value(): assert np.isclose(ef.power(4, 3), np.power(4, 3))
def test_power_val2(): x = AutoDiff(1, "x") y = AutoDiff(2, "y") f = ef.power(x * y, 3) assert np.isclose(f.val, 8)
def test_power_deriv_y2(): x = AutoDiff(1, "x") y = AutoDiff(2, "y") f = ef.power(x * y, 3) assert np.isclose(f.der['y'], 12)
def test_power_deriv2_xy(): x = AutoDiff(1, "x", H=True) y = AutoDiff(2, "y", H=True) f = ef.power(x * y, x * y) assert np.isclose(f.der2['xy'], 33.70656772254452)
def test_power_deriv2_y(): x = AutoDiff(1, "x", H=True) y = AutoDiff(2, "y", H=True) f = ef.power(x * y, x * y) assert np.isclose(f.der2['y'], 13.46698950015237)
def test_power_deriv2_x(): x = AutoDiff(1, "x", H=True) y = AutoDiff(2, "y", H=True) f = ef.power(x * y, x * y) assert np.isclose(f.der2['x'], 53.86795800060948)
def test_power_no_sec_derivative_xy(): x = AutoDiff(4, "x") y = AutoDiff(5, "y") with pytest.raises(AttributeError): assert ef.power(x * y, x * y).der2['xy']
def test_power_val3(): x = AutoDiff(1, "x") y = AutoDiff(2, "y") f = ef.power(3, x * y) assert np.isclose(f.val, 9)
def test_power_numeric_input_no_deriv(): with pytest.raises(AttributeError): assert ef.power(4, 5).der
def test_power_deriv_x3(): x = AutoDiff(1, "x") y = AutoDiff(2, "y") f = ef.power(3, x * y) assert np.isclose(f.der['x'], 19.775021196025975)
def test_autodiff_eq(): a = AutoDiff(2, "a") b = AutoDiff(4, "b") assert ef.power(a, 2).val == b.val
def test_power_deriv_x(): x = AutoDiff(1, "x") y = AutoDiff(2, "y") f = ef.power(x * y, x * y) assert np.isclose(f.der['x'], 13.545177444479563)