code: def test_random_seed_initialization(rng):
      """Test that the random generator can be initialized correctly with the
      tracking seeds.
      """
      sphere = HemiSphere.from_sphere(unit_octahedron)
      pmf = np.zeros((4, 4, 4, 3))
      x = np.array([0.0, 0, 0, 57.421434502602544])
      y = np.array([0.0, 1, 2, 21.566539227085478])
      z = np.array([1.0, 1, 1, 51.67881720942744])
  
      seeds = np.row_stack(
          [np.column_stack([x, y, z]), rng.random((10, 3))]
      )
      sc = BinaryStoppingCriterion(np.ones((4, 4, 4)))
      dg = ProbabilisticDirectionGetter.from_pmf(pmf, 60, sphere)
  
      randoms_seeds = (
          [None, 0, 1, -1, np.iinfo(np.uint32).max + 1]
          + list(rng.random(10))
          + list(rng.integers(0, np.iinfo(np.int32).max, 10))
      )
  
      for rdm_seed in randoms_seeds:
          _ = Streamlines(
              LocalTracking(
                  direction_getter=dg,
                  stopping_criterion=sc,
                  seeds=seeds,
                  affine=np.eye(4),
                  step_size=1.0,
                  random_seed=rdm_seed,
              )
          )
  
imports: from logging import warn
  import warnings
  import nibabel
  import numpy
  import numpy.testing
  from dipy.core.gradients import gradient_table
  from dipy.core.sphere import HemiSphere, unit_octahedron
  from dipy.data import get_fnames, get_sphere
  from dipy.direction import BootDirectionGetter, ClosestPeakDirectionGetter, DeterministicMaximumDirectionGetter, PeaksAndMetrics, ProbabilisticDirectionGetter, PTTDirectionGetter
  from dipy.reconst.csdeconv import ConstrainedSphericalDeconvModel
  from dipy.reconst.shm import descoteaux07_legacy_msg
  from dipy.tracking.local_tracking import LocalTracking, ParticleFilteringTracking
  from dipy.tracking.streamline import Streamlines
  from dipy.tracking.stopping_criterion import ActStoppingCriterion, BinaryStoppingCriterion, ThresholdStoppingCriterion, StreamlineStatus
  from dipy.tracking.utils import random_seeds_from_mask, seeds_from_mask
  from dipy.sims.voxel import single_tensor, multi_tensor
  from dipy.testing.decorators import set_random_number_generator
label_desc: Use image node_id 12 for calling a global function with example usage: test_random_seed_initialization(rng) without return types