code: def test_most_similar_mam():
      xyz1 = np.array(
          [[0, 0, 0], [1, 0, 0], [2, 0, 0], [3, 0, 0]], dtype="float32"
      )
      xyz2 = np.array(
          [[0, 1, 1], [1, 0, 1], [2, 3, -2]], dtype="float32"
      )
      xyz3 = np.array(
          [[-1, 0, 0], [2, 0, 0], [2, 3, 0], [3, 0, 0]], dtype="float32"
      )
      tracks = [xyz1, xyz2, xyz3]
      for metric in ("avg", "min", "max"):
          # pf should be much faster and the results equivalent
          pf.most_similar_track_mam(tracks, metric=metric)
  
file_path: dipy/dipy/tracking/tests/test_distances.py
imports: import warnings
  import numpy
  from numpy.testing import assert_array_almost_equal, assert_equal, assert_almost_equal, assert_array_equal
  from dipy.testing import assert_true
  from dipy.testing.decorators import set_random_number_generator
  from dipy.tracking import distances
  from dipy.tracking.streamline import set_number_of_points
  from dipy.data import get_fnames
  from dipy.io.streamline import load_tractogram
label_desc: Use image node_id 10 for calling a global function with example usage: test_most_similar_mam() without return types