code: def test_target_lb():
      streamlines = [
          np.array([[0.0, 1.0, 1.0], [3.0, 1.0, 1.0]]),
          np.array([[0.0, 0.0, 0.0], [2.0, 2.0, 2.0]]),
          np.array([[1.0, 1.0, 1.0]]),
      ]  # Single-point streamline
      _target(
          target_line_based, streamlines, (1, 1, 1), (2, 1, 1), False
      )
  
imports: import warnings
  import numpy
  import pytest
  from dipy.tracking import metrics
  from dipy.tracking.streamline import transform_streamlines
  from dipy.tracking.utils import connectivity_matrix, density_map, length, ndbincount, reduce_labels, seeds_from_mask, random_seeds_from_mask, target, target_line_based, unique_rows, near_roi, reduce_rois, path_length, _min_at, max_angle_from_curvature, min_radius_curvature_from_angle
  from dipy.tracking._utils import _to_voxel_coordinates
  from dipy.tracking.vox2track import streamline_mapping
  import numpy.testing
  from dipy.testing import assert_true
  from dipy.testing.decorators import set_random_number_generator
label_desc: Use image node_id 8 for calling a global function with example usage: test_target_lb() without return types