TST: fixes warnings in problematic tests

tests/fixtures/monte_carlo/monte_carlo_fixtures.py

@@ -32,3 +32,20 @@ def monte_carlo_calisto(stochastic_environment, stochastic_calisto, stochastic_f
         rocket=stochastic_calisto,
         flight=stochastic_flight,
     )
+
+
+@pytest.fixture
+def monte_carlo_calisto_pre_loaded(
+    stochastic_environment, stochastic_calisto, stochastic_flight
+):
+    """Creates a MonteCarlo object with some already imported simulations."""
+    monte_carlo = MonteCarlo(
+        filename="monte_carlo_test",
+        environment=stochastic_environment,
+        rocket=stochastic_calisto,
+        flight=stochastic_flight,
+    )
+    monte_carlo.import_results(
+        filename="tests/fixtures/monte_carlo/example.outputs.txt"
+    )
+    return monte_carlo

tests/test_environment.py

@@ -166,6 +166,7 @@ def test_gefs_atmosphere(mock_show, example_spaceport_env):
     assert example_spaceport_env.all_info() == None
 
 
+@pytest.mark.skip(reason="legacy tests")  # deprecated method
 @patch("matplotlib.pyplot.show")
 def test_info_returns(mock_show, example_plain_env):
     """Tests the all_info_returned() all_plot_info_returned() and methods of the

tests/test_function.py

@@ -101,8 +101,7 @@ def test_setters(func_from_csv, func_2d_from_csv):
     assert func_2d_from_csv.get_outputs() == ["Scalar3"]
     func_2d_from_csv.set_interpolation("shepard")
     assert func_2d_from_csv.get_interpolation_method() == "shepard"
-    func_2d_from_csv.set_extrapolation("zero")
-    # 2d functions do not support zero extrapolation, must change to natural
+    func_2d_from_csv.set_extrapolation("natural")
     assert func_2d_from_csv.get_extrapolation_method() == "natural"
 
 

tests/test_monte_carlo.py

@@ -107,7 +107,7 @@ def test_monte_carlo_set_inputs_log(monte_carlo_calisto):
     """
     monte_carlo_calisto.input_file = "tests/fixtures/monte_carlo/example.inputs.txt"
     monte_carlo_calisto.set_inputs_log()
-    assert len(monte_carlo_calisto.inputs_log) == 10
+    assert len(monte_carlo_calisto.inputs_log) == 100
     assert all(isinstance(item, dict) for item in monte_carlo_calisto.inputs_log)
     assert all(
         "gravity" in item and "elevation" in item
@@ -125,7 +125,7 @@ def test_monte_carlo_set_outputs_log(monte_carlo_calisto):
     """
     monte_carlo_calisto.output_file = "tests/fixtures/monte_carlo/example.outputs.txt"
     monte_carlo_calisto.set_outputs_log()
-    assert len(monte_carlo_calisto.outputs_log) == 10
+    assert len(monte_carlo_calisto.outputs_log) == 100
     assert all(isinstance(item, dict) for item in monte_carlo_calisto.outputs_log)
     assert all(
         "apogee" in item and "impact_velocity" in item
@@ -145,24 +145,24 @@ def test_monte_carlo_prints(monte_carlo_calisto):
 
 
 @patch("matplotlib.pyplot.show")
-def test_monte_carlo_plots(mock_show, monte_carlo_calisto):
+def test_monte_carlo_plots(mock_show, monte_carlo_calisto_pre_loaded):
     """Tests the plots methods of the MonteCarlo class."""
-    assert monte_carlo_calisto.all_info() is None
+    assert monte_carlo_calisto_pre_loaded.all_info() is None
 
 
-def test_monte_carlo_export_ellipses_to_kml(monte_carlo_calisto):
+def test_monte_carlo_export_ellipses_to_kml(monte_carlo_calisto_pre_loaded):
     """Tests the export_ellipses_to_kml method of the MonteCarlo class.
 
     Parameters
     ----------
-    monte_carlo_calisto : MonteCarlo
+    monte_carlo_calisto_pre_loaded : MonteCarlo
         The MonteCarlo object, this is a pytest fixture.
     """
     assert (
-        monte_carlo_calisto.export_ellipses_to_kml(
+        monte_carlo_calisto_pre_loaded.export_ellipses_to_kml(
             filename="monte_carlo_class_example.kml",
-            origin_lat=32,
-            origin_lon=-104,
+            origin_lat=32.990254,
+            origin_lon=-106.974998,
             type="impact",
         )
         is None

tests/unit/test_function.py

@@ -243,7 +243,9 @@ def test_savetxt(request, func):
     ), "Couldn't save the file using the Function.savetxt method."
 
     read_func = Function(
-        "test_func.csv", interpolation="linear", extrapolation="natural"
+        "test_func.csv",
+        interpolation="linear" if func.get_domain_dim() == 1 else "shepard",
+        extrapolation="natural",
     )
     if callable(func.source):
         source = np.column_stack(