code: def test_cluster_centroid_assign():
      centroid = np.zeros(features_shape)
      cluster = ClusterCentroid(centroid)
  
      indices = []
      centroid = np.zeros(features_shape, dtype=dtype)
      for idx in range(1, 10):
          cluster.assign(idx, (idx + 1) * features)
          cluster.update()
          indices.append(idx)
          centroid = (centroid * (idx - 1) + (idx + 1) * features) / idx
          assert_equal(len(cluster), idx)
          assert_equal(type(cluster.indices), list)
          assert_array_equal(cluster.indices, indices)
          assert_equal(type(cluster.centroid), np.ndarray)
          assert_array_equal(cluster.centroid, centroid)
  
imports: import copy
  import itertools
  import numpy
  from numpy.testing import assert_array_equal, assert_raises, assert_equal
  from dipy.segment.clustering import Cluster, ClusterCentroid
  from dipy.segment.clustering import ClusterMap, ClusterMapCentroid
  from dipy.segment.clustering import Clustering
  from dipy.testing import assert_true, assert_false, assert_arrays_equal
  from dipy.testing.decorators import set_random_number_generator
label_desc: Use image node_id 7 for calling a global function with example usage: test_cluster_centroid_assign() without return types