code: def find_closest_point_index(self, x, y, return_distance=False):
          
          ia.do_assert(len(self.exterior) > 0)
          distances = []
          for x2, y2 in self.exterior:
              d = (x2 - x) ** 2 + (y2 - y) ** 2
              distances.append(d)
          distances = np.sqrt(distances)
          closest_idx = np.argmin(distances)
          if return_distance:
              return closest_idx, distances[closest_idx]
          return closest_idx
docs: Find the index of the point within the exterior that is closest to the given coordinates.
  
          "Closeness" is here defined based on euclidean distance.
          This method will raise an AssertionError if the exterior contains no points.
  
          Parameters
          ----------
          x : number
              X-coordinate around which to search for close points.
  
          y : number
              Y-coordinate around which to search for close points.
  
          return_distance : bool, optional
              Whether to also return the distance of the closest point.
  
          Returns
          -------
          int
              Index of the closest point.
  
          number
              Euclidean distance to the closest point.
              This value is only returned if `return_distance` was set to True.