[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

Author: pre-commit-ci[bot]

Diff for: machine_learning/dimensionality_reduction.py

@@ -29,7 +29,7 @@ def column_reshape(input_array: np.ndarray) -> np.ndarray:
 
 
 def covariance_within_classes(
-        features: np.ndarray, labels: np.ndarray, classes: int
+    features: np.ndarray, labels: np.ndarray, classes: int
 ) -> np.ndarray:
     """Function to compute the covariance matrix inside each class.
     >>> features = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
@@ -57,7 +57,7 @@ def covariance_within_classes(
 
 
 def covariance_between_classes(
-        features: np.ndarray, labels: np.ndarray, classes: int
+    features: np.ndarray, labels: np.ndarray, classes: int
 ) -> np.ndarray:
     """Function to compute the covariance matrix between multiple classes
     >>> features = np.array([[9, 2, 3], [4, 3, 6], [1, 8, 9]])
@@ -121,7 +121,7 @@ def principal_component_analysis(features: np.ndarray, dimensions: int) -> np.nd
 
 
 def linear_discriminant_analysis(
-        features: np.ndarray, labels: np.ndarray, classes: int, dimensions: int
+    features: np.ndarray, labels: np.ndarray, classes: int, dimensions: int
 ) -> np.ndarray:
     """
     Linear Discriminant Analysis.
@@ -186,9 +186,11 @@ def test_linear_discriminant_analysis() -> None:
 def test_principal_component_analysis() -> None:
     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., 3., 3.]])
+    expected_output = np.array([[6.92820323, 8.66025404, 10.39230485], [3.0, 3.0, 3.0]])
     output = principal_component_analysis(features, dimensions)
-    assert np.allclose(expected_output, output), f"Expected {expected_output}, but got {output}"
+    assert np.allclose(
+        expected_output, output
+    ), f"Expected {expected_output}, but got {output}"
 
 
 if __name__ == "__main__":