code: def test_single_transforms():
      moving = subset_b0
      static = subset_b0
      moving_affine = static_affine = np.eye(4)
  
      reg_methods = [
          center_of_mass,
          translation,
          rigid_isoscaling,
          rigid_scaling,
          rigid,
          affine,
      ]
  
      for func in reg_methods:
          xformed, affine_mat = func(
              moving,
              static,
              moving_affine,
              static_affine,
              level_iters=[5, 5],
              sigmas=[3, 1],
              factors=[2, 1],
          )
          # We don't ask for much:
          npt.assert_almost_equal(
              affine_mat[:3, :3], np.eye(3), decimal=1
          )
  
imports: import os.path
  import pytest
  from tempfile import TemporaryDirectory
  import numpy
  import numpy.testing
  import nibabel
  import dipy.data
  import dipy.core.gradients
  from dipy.align import syn_registration, register_series, register_dwi_series, center_of_mass, translation, rigid_isoscaling, rigid_scaling, rigid, affine, motion_correction, affine_registration, streamline_registration, write_mapping, read_mapping, register_dwi_to_template
  from dipy.align.imwarp import DiffeomorphicMap
  from dipy.tracking.utils import transform_tracking_output
  from dipy.io.streamline import save_trk
  from dipy.io.stateful_tractogram import StatefulTractogram, Space
  from dipy.io.gradients import read_bvals_bvecs
  from dipy.io.image import load_nifti
  from dipy.testing.decorators import set_random_number_generator
label_desc: Use image node_id 5 for calling a global function with example usage: test_single_transforms() without return types