TST: Reorganizing testing modules into unit and integration tests

tests/integration/test_function.py

@@ -0,0 +1,179 @@
+import os
+from unittest.mock import patch
+
+import matplotlib as plt
+import numpy as np
+import pytest
+
+from rocketpy import Function
+
+plt.rcParams.update({"figure.max_open_warning": 0})
+
+
+@pytest.mark.parametrize(
+    "func",
+    [
+        "linearly_interpolated_func",
+        "spline_interpolated_func",
+        "func_2d_from_csv",
+        "lambda_quad_func",
+    ],
+)
+def test_savetxt(request, func):
+    """Test the savetxt method of various Function objects.
+
+    This test function verifies that the `savetxt` method correctly writes the
+    function's data to a CSV file and that a new function object created from
+    this file has the same data as the original function object.
+
+    Notes
+    -----
+    The test performs the following steps:
+    1. It invokes the `savetxt` method of the given function object.
+    2. It then reads this file to create a new function object.
+    3. The test asserts that the data of the new function matches the original.
+    4. Finally, the test cleans up by removing the created CSV file.
+
+    Raises
+    ------
+    AssertionError
+        If the `savetxt` method fails to save the file, or if the data of the
+        newly read function does not match the data of the original function.
+    """
+    func = request.getfixturevalue(func)
+    assert (
+        func.savetxt(
+            filename="test_func.csv",
+            lower=0,
+            upper=9,
+            samples=10,
+            fmt="%.6f",
+            delimiter=",",
+            newline="\n",
+            encoding=None,
+        )
+        is None
+    ), "Couldn't save the file using the Function.savetxt method."
+
+    read_func = Function(
+        "test_func.csv",
+        interpolation="linear" if func.get_domain_dim() == 1 else "shepard",
+        extrapolation="natural",
+    )
+    if callable(func.source):
+        source = np.column_stack(
+            (np.linspace(0, 9, 10), func.source(np.linspace(0, 9, 10)))
+        )
+        assert np.allclose(source, read_func.source)
+    else:
+        assert np.allclose(func.source, read_func.source)
+
+    # clean up the file
+    os.remove("test_func.csv")
+
+
+# Test Function creation from .csv file
+def test_function_from_csv(func_from_csv, func_2d_from_csv):
+    """Test the Function class creation from a .csv file.
+
+    Parameters
+    ----------
+    func_from_csv : rocketpy.Function
+        A Function object created from a .csv file.
+    func_2d_from_csv : rocketpy.Function
+        A Function object created from a .csv file with 2 inputs.
+    """
+    # Assert the function is zero at 0 but with a certain tolerance
+    assert np.isclose(func_from_csv(0), 0.0, atol=1e-6)
+    assert np.isclose(func_2d_from_csv(0, 0), 0.0, atol=1e-6)
+    # Check the __str__ method
+    assert func_from_csv.__str__() == "Function from R1 to R1 : (Scalar) → (Scalar)"
+    assert (
+        func_2d_from_csv.__str__()
+        == "Function from R2 to R1 : (Input 1, Input 2) → (Scalar)"
+    )
+    # Check the __repr__ method
+    assert func_from_csv.__repr__() == "'Function from R1 to R1 : (Scalar) → (Scalar)'"
+    assert (
+        func_2d_from_csv.__repr__()
+        == "'Function from R2 to R1 : (Input 1, Input 2) → (Scalar)'"
+    )
+
+
+@pytest.mark.parametrize(
+    "csv_file",
+    [
+        "tests/fixtures/function/1d_quotes.csv",
+        "tests/fixtures/function/1d_no_quotes.csv",
+    ],
+)
+def test_func_from_csv_with_header(csv_file):
+    """Tests if a Function can be created from a CSV file with a single header
+    line. It tests cases where the fields are separated by quotes and without
+    quotes."""
+    f = Function(csv_file)
+    assert f.__repr__() == "'Function from R1 to R1 : (time) → (value)'"
+    assert np.isclose(f(0), 100)
+    assert np.isclose(f(0) + f(1), 300), "Error summing the values of the function"
+
+
+@patch("matplotlib.pyplot.show")
+def test_plots(mock_show, func_from_csv, func_2d_from_csv):
+    """Test different plot methods of the Function class.
+
+    Parameters
+    ----------
+    mock_show : Mock
+        Mock of the matplotlib.pyplot.show method.
+    func_from_csv : rocketpy.Function
+        A Function object created from a .csv file.
+    """
+    # Test plot methods
+    assert func_from_csv.plot() == None
+    assert func_2d_from_csv.plot() == None
+    # Test plot methods with limits
+    assert func_from_csv.plot(-1, 1) == None
+    assert func_2d_from_csv.plot(-1, 1) == None
+    # Test compare_plots
+    func2 = Function(
+        source="tests/fixtures/airfoils/e473-10e6-degrees.csv",
+        inputs=["Scalar"],
+        outputs=["Scalar"],
+        interpolation="linear",
+        extrapolation="natural",
+    )
+    assert (
+        func_from_csv.compare_plots([func_from_csv, func2], return_object=False) == None
+    )
+
+
+@patch("matplotlib.pyplot.show")
+def test_multivariable_dataset_plot(mock_show):
+    """Test the plot method of the Function class with a multivariable dataset."""
+    # Test plane f(x,y) = x - y
+    source = [
+        (-1, -1, -1),
+        (-1, 0, -1),
+        (-1, 1, -2),
+        (0, 1, 1),
+        (0, 0, 0),
+        (0, 1, -1),
+        (1, -1, 2),
+        (1, 0, 1),
+        (1, 1, 0),
+    ]
+    func = Function(source=source, inputs=["x", "y"], outputs=["z"])
+
+    # Assert plot
+    assert func.plot() == None
+
+
+@patch("matplotlib.pyplot.show")
+def test_multivariable_function_plot(mock_show):
+    """Test the plot method of the Function class with a multivariable function."""
+    # Test plane f(x,y) = sin(x + y)
+    source = lambda x, y: np.sin(x * y)
+    func = Function(source=source, inputs=["x", "y"], outputs=["z"])
+
+    # Assert plot
+    assert func.plot() == None