code: def test_seeds_from_mask(rng):
      mask = rng.integers(0, 1, size=(10, 10, 10))
      seeds = seeds_from_mask(mask, np.eye(4), density=1)
      npt.assert_equal(mask.sum(), len(seeds))
      npt.assert_array_equal(np.argwhere(mask), seeds)
  
      mask[:] = False
      mask[3, 3, 3] = True
      seeds = seeds_from_mask(mask, np.eye(4), density=[3, 4, 5])
      npt.assert_equal(len(seeds), 3 * 4 * 5)
      assert_true(np.all((seeds > 2.5) & (seeds < 3.5)))
  
      mask[4, 4, 4] = True
      seeds = seeds_from_mask(mask, np.eye(4), density=[3, 4, 5])
      npt.assert_equal(len(seeds), 2 * 3 * 4 * 5)
      assert_true(np.all((seeds > 2.5) & (seeds < 4.5)))
      in_333 = ((seeds > 2.5) & (seeds < 3.5)).all(1)
      npt.assert_equal(in_333.sum(), 3 * 4 * 5)
      in_444 = ((seeds > 3.5) & (seeds < 4.5)).all(1)
      npt.assert_equal(in_444.sum(), 3 * 4 * 5)
  
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 14 for calling a global function with example usage: test_seeds_from_mask(rng) without return types