E501 for build_kdtree.py, hypercube_points.py, nearest_neighbour_search.py

Author: Ramy-Badr-Ahmed

data_structures/kd_tree/build_kdtree.py

@@ -7,10 +7,12 @@ def build_kdtree(points: list[list[float]], depth: int = 0) -> KDNode | None:
 
     Args:
         points (list[list[float]]): The list of points to build the KD-Tree from.
-        depth (int): The current depth in the tree (used to determine axis for splitting).
+        depth (int): The current depth in the tree
+                     (used to determine axis for splitting).
 
     Returns:
-        KDNode | None: The root node of the KD-Tree, or None if no points are provided.
+        KDNode | None: The root node of the KD-Tree,
+                       or None if no points are provided.
     """
     if not points:
         return None

data_structures/kd_tree/example/hypercube_points.py

@@ -13,7 +13,8 @@ def hypercube_points(
         num_dimensions (int): Number of dimensions of the hypercube.
 
     Returns:
-        np.ndarray: An array of shape (num_points, num_dimensions) with generated points.
+        np.ndarray: An array of shape (num_points, num_dimensions)
+                    with generated points.
     """
     rng = np.random.default_rng()
     shape = (num_points, num_dimensions)

data_structures/kd_tree/nearest_neighbour_search.py

@@ -9,11 +9,13 @@ def nearest_neighbour_search(
 
     Args:
         root (KDNode | None): The root node of the KD-Tree.
-        query_point (list[float]): The point for which the nearest neighbor is being searched.
+        query_point (list[float]): The point for which the nearest neighbor
+                                    is being searched.
 
     Returns:
         tuple[list[float] | None, float, int]:
-            - The nearest point found in the KD-Tree to the query point, or None if no point is found.
+            - The nearest point found in the KD-Tree to the query point,
+              or None if no point is found.
             - The squared distance to the nearest point.
             - The number of nodes visited during the search.
     """