code: def test_openmp_locks(rng):
      static = []
      moving = []
      pts = 20
  
      for i in range(1000):
          s = rng.random((pts, 3))
          static.append(s)
          moving.append(s + 2)
  
      moving = moving[2:]
  
      points, offsets = unlist_streamlines(static)
      points2, offsets2 = unlist_streamlines(moving)
  
      D = np.zeros((len(offsets), len(offsets2)), dtype="f8")
  
      _bundle_minimum_distance_matrix(
          points, points2, len(offsets), len(offsets2), pts, D
      )
  
      dist1 = (
          0.25
          * (
              np.sum(np.min(D, axis=0)) / float(D.shape[1])
              + np.sum(np.min(D, axis=1)) / float(D.shape[0])
          )
          ** 2
      )
  
      dist2 = _bundle_minimum_distance(
          points, points2, len(offsets), len(offsets2), pts
      )
  
      assert_almost_equal(dist1, dist2, 6)
  
imports: import numpy
  from numpy.testing import assert_, assert_equal, assert_almost_equal, assert_array_almost_equal, assert_raises
  from dipy.align.streamlinear import compose_matrix44, decompose_matrix44, BundleSumDistanceMatrixMetric, BundleMinDistanceMatrixMetric, BundleMinDistanceMetric, StreamlineLinearRegistration, StreamlineDistanceMetric, groupwise_slr, get_unique_pairs
  from dipy.tracking.streamline import center_streamlines, unlist_streamlines, relist_streamlines, transform_streamlines, set_number_of_points, Streamlines
  from dipy.io.streamline import load_tractogram
  from dipy.core.geometry import compose_matrix
  from dipy.data import get_fnames, two_cingulum_bundles, read_five_af_bundles
  from dipy.align.bundlemin import _bundle_minimum_distance_matrix, _bundle_minimum_distance, distance_matrix_mdf
  from dipy.testing.decorators import set_random_number_generator
label_desc: Use image node_id 11 for calling a global function with example usage: test_openmp_locks(rng) without return types