Updated tests

Author: Diegomangasco

Diff for: machine_learning/dimensionality_reduction.py

@@ -164,24 +164,13 @@ def linear_discriminant_analysis(
 def test_linear_discriminant_analysis() -> None:
     # Create dummy dataset with 2 classes and 3 features
     features = np.array([[1, 2, 3, 4, 5], [2, 3, 4, 5, 6], [3, 4, 5, 6, 7]])
-    labels = np.array([0, 2, 0, 1, 1])
-    classes = 3
+    labels = np.array([0, 0, 0, 1, 1])
+    classes = 2
     dimensions = 2
 
-    projected_data = linear_discriminant_analysis(features, labels, classes, dimensions)
-
-    # Assert that the shape of the projected data is correct
-    assert projected_data.shape == (dimensions, features.shape[1])
-
-    # Assert that the projected data is a numpy array
-    assert isinstance(projected_data, np.ndarray)
-
-    # Assert that the projected data is not empty
-    assert projected_data.any()
-
     # Assert that the function raises an AssertionError if dimensions > classes
     with pytest.raises(AssertionError) as error_info:
-        projected_data = linear_discriminant_analysis(features, labels, classes, 3)
+        projected_data = linear_discriminant_analysis(features, labels, classes, dimensions)
         if isinstance(projected_data, np.ndarray):
             raise AssertionError(
                 "Did not raise AssertionError for dimensions > classes"