code: def test_similarity_real_bundles():
      bundle_initial = fornix_streamlines()
      bundle_initial, shift = center_streamlines(bundle_initial)
      bundle = bundle_initial[:20]
      xgold = [0, 0, 10, 0, 0, 0, 1.5]
      mat = compose_matrix44(xgold)
      bundle2 = transform_streamlines(bundle_initial[:20], mat)
  
      metric = BundleMinDistanceMatrixMetric()
      x0 = np.array([0, 0, 0, 0, 0, 0, 1], "f8")
  
      slr = StreamlineLinearRegistration(
          metric=metric,
          x0=x0,
          method="Powell",
          bounds=None,
          verbose=False,
      )
  
      slm = slr.optimize(bundle, bundle2)
      new_bundle2 = slm.transform(bundle2)
      evaluate_convergence(bundle, new_bundle2)
  
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 16 for calling a global function with example usage: test_similarity_real_bundles() without return types