TST: Isolate function unit tests.

RocketPy-Team · Dec 2, 2023 · 2efb0b1 · 2efb0b1
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diff --git a/tests/test_function.py b/tests/test_function.py
@@ -189,119 +189,6 @@ def test_extrapolation_methods(linear_func):
     assert np.isclose(linear_func.get_value(-1), -1, atol=1e-6)
 
 
-@pytest.mark.parametrize("a", [-1, 0, 0.5, 1, 2, 2.5, 3.5, 4, 5])
-@pytest.mark.parametrize("b", [-1, 0, 0.5, 1, 2, 2.5, 3.5, 4, 5])
-def test_integral_linear_interpolation(linearly_interpolated_func, a, b):
-    """Test the integral method of the Function class.
-
-    Parameters
-    ----------
-    linear_func : rocketpy.Function
-        A Function object created from a list of values.
-    """
-    # Test integral
-    assert isinstance(linearly_interpolated_func.integral(a, b, numerical=True), float)
-    assert np.isclose(
-        linearly_interpolated_func.integral(a, b, numerical=False),
-        linearly_interpolated_func.integral(a, b, numerical=True),
-        atol=1e-3,
-    )
-
-
-@pytest.mark.parametrize("func", ["linear_func", "spline_interpolated_func"])
-@pytest.mark.parametrize("a", [-1, -0.5, 0, 0.5, 1, 2, 2.5, 3.5, 4, 5])
-@pytest.mark.parametrize("b", [-1, -0.5, 0, 0.5, 1, 2, 2.5, 3.5, 4, 5])
-def test_integral_spline_interpolation(request, func, a, b):
-    """Test the integral method of the Function class.
-
-    Parameters
-    ----------
-    spline_func : rocketpy.Function
-        A Function object created from a list of values.
-    a : float
-        Lower limit of the integral.
-    b : float
-        Upper limit of the integral.
-    """
-    # Test integral
-    # Get the function from the fixture
-    func = request.getfixturevalue(func)
-    assert np.isclose(
-        func.integral(a, b, numerical=False),
-        func.integral(a, b, numerical=True),
-        atol=1e-3,
-    )
-
-
-def test_differentiate():
-    """Tests the differentiation method of the Function class.
-    Both with respect to return instances and expected behaviour.
-    """
-    func = Function(1)
-    assert isinstance(func.differentiate(0), float)
-    assert np.isclose(func.differentiate(5), 0)
-
-    func_x = Function(lambda x: x)
-    assert isinstance(func_x.differentiate(0), float)
-    assert np.isclose(func_x.differentiate(0), 1)
-
-    f_square = Function(lambda x: x**2)
-    assert isinstance(f_square.differentiate(1), float)
-    assert np.isclose(f_square.differentiate(1), 2)
-
-
-def test_get_value():
-    """Tests the get_value method of the Function class.
-    Both with respect to return instances and expected behaviour.
-    """
-    func = Function(lambda x: 2 * x)
-    assert isinstance(func.get_value(1), int or float)
-
-
-def test_identity_function():
-    """Tests the identity_function method of the Function class.
-    Both with respect to return instances and expected behaviour.
-    """
-
-    func = Function(lambda x: x**2)
-    assert isinstance(func.identity_function(), Function)
-
-
-def test_derivative_function():
-    """Tests the derivative_function method of the Function class.
-    Both with respect to return instances and expected behaviour.
-    """
-    square = Function(lambda x: x**2)
-    assert isinstance(square.derivative_function(), Function)
-
-
-def test_integral():
-    """Tests the integral method of the Function class.
-    Both with respect to return instances and expected behaviour.
-    """
-
-    zero_func = Function(0)
-    assert isinstance(zero_func.integral(2, 4, numerical=True), float)
-    assert zero_func.integral(2, 4, numerical=True) == 0
-
-    square = Function(lambda x: x**2)
-    assert isinstance
-    assert square.integral(2, 4, numerical=True) == -square.integral(
-        4, 2, numerical=True
-    )
-    assert square.integral(2, 4, numerical=False) == -square.integral(
-        4, 2, numerical=False
-    )
-
-
-def test_integral_function():
-    """Tests the integral_function method of the Function class.
-    Both with respect to return instances and expected behaviour.
-    """
-    zero_func = Function(0)
-    assert isinstance(zero_func, Function)
-
-
 @pytest.mark.parametrize("a", [-1, 0, 1])
 @pytest.mark.parametrize("b", [-1, 0, 1])
 def test_multivariable_dataset(a, b):