code: def test_labels_to_stc():
      """Test labels_to_stc."""
      pytest.importorskip("nibabel")
      labels = read_labels_from_annot(
          "sample", "aparc", subjects_dir=subjects_dir
      )
      values = np.random.RandomState(0).randn(len(labels))
      with pytest.raises(ValueError, match="1 or 2 dim"):
          labels_to_stc(labels, values[:, np.newaxis, np.newaxis])
      with pytest.raises(ValueError, match=r"values\.shape"):
          labels_to_stc(labels, values[np.newaxis])
      with pytest.raises(
          ValueError, match="multiple values of subject"
      ):
          labels_to_stc(labels, values, subject="foo")
      stc = labels_to_stc(labels, values)
      assert stc.subject == "sample"
      for value, label in zip(values, labels):
          stc_label = stc.in_label(label)
          assert (stc_label.data == value).all()
      stc = read_source_estimate(stc_fname, "sample")
  
imports: import glob
  import os
  import pickle
  import shutil
  from itertools import product
  from pathlib import Path
  import numpy
  import pytest
  from numpy.testing import assert_allclose, assert_array_almost_equal, assert_array_equal, assert_array_less, assert_equal
  from scipy import sparse
  from mne import grow_labels, labels_to_stc, morph_labels, random_parcellation, read_label, read_labels_from_annot, read_source_estimate, read_source_spaces, read_surface, spatial_tris_adjacency, split_label, stc_to_label, write_labels_to_annot
  from mne.datasets import testing
  from mne.label import Label, _blend_colors, _load_vert_pos, _n_colors, _read_annot, _read_annot_cands, label_sign_flip, select_sources
  from mne.source_estimate import mesh_edges
  from mne.source_space import SourceSpaces
  from mne.surface import _mesh_borders
  from mne.utils import _record_warnings, get_subjects_dir
label_desc: Use image node_id 12 for calling a global function with example usage: test_labels_to_stc() without return types