code: def test_center_init(
      center_init_callable: Callable[[np.ndarray], np.ndarray]
  ):
      """Test center initialisation algorithms."""
      k = 5
      X, y = load_arrow_head(return_X_y=True)
      X_train, X_test, y_train, y_test = train_test_split(X, y)
      X_train = convert_to(X_train, "numpy3D")
      random_state = check_random_state(1)
      test_centers = center_init_callable(X_train, k, random_state)
      assert len(test_centers) == k
      assert len(np.unique(test_centers, axis=1)) == k
  
file_path: sktime/sktime/clustering/tests/test_lloyds.py
imports: from typing import Callable
  import numpy
  import pytest
  from sklearn.model_selection import train_test_split
  from sklearn.utils import check_random_state
  from sktime.clustering.partitioning._lloyds import TimeSeriesLloyds, _forgy_center_initializer, _kmeans_plus_plus, _random_center_initializer
  from sktime.datasets import load_arrow_head
  from sktime.datatypes import convert_to
  from sktime.distances.tests._utils import create_test_distance_numpy
label_desc: Use image node_id 2 for calling a global function with example usage: test_center_init(center_init_callable) without return types