Update dimensionality_reduction.py

Author: Sid101098

machine_learning/dimensionality_reduction.py

@@ -407,18 +407,25 @@ def test_linear_discriminant_analysis() -> None:
     features = np.array([[1, 2, 3, 4, 5], [2, 3, 4, 5, 6], [3, 4, 5, 6, 7]])
     labels = np.array([0, 0, 0, 1, 1])
     classes = 2
-    dimensions = 2
+    dimensions = 1  # Changed to 1 since classes=2 and dimensions must be < classes
 
-    # Assert that the function raises an AssertionError if dimensions > classes
-    with pytest.raises(AssertionError):
-        linear_discriminant_analysis(features, labels, classes, dimensions)
+    try:
+        # This should work since dimensions < classes
+        lda_result = linear_discriminant_analysis(features, labels, classes, dimensions)
+        assert lda_result.shape == (dimensions, features.shape[1])
+        logging.info("LDA test passed")
+    except Exception as e:
+        logging.error(f"LDA test failed: {e}")
+        raise
 
 
 def test_principal_component_analysis() -> None:
     """Test function for Principal Component Analysis."""
     features = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
     dimensions = 2
-    expected_output = np.array([[6.92820323, 8.66025404, 10.39230485], [3.0, 3.0, 3.0]])
+    expected_output = np.array(
+        [[6.92820323, 8.66025404, 10.39230485], [3.0, 3.0, 3.0]]
+    )
 
     output = principal_component_analysis(features, dimensions)
     if not np.allclose(expected_output, output):