code: def test_signals_extraction_with_labels_without_mask(
      signals, labels_data, labels_img, shape_3d_default, tmp_path
  ):
      """Test conversion between signals and images \
      using regions defined by labels."""
      data_img = signals_to_img_labels(
          signals=signals, labels_img=labels_img
      )
  
      assert data_img.shape == (shape_3d_default + (N_TIMEPOINTS,))
      data = get_data(data_img)
      assert np.all(data.std(axis=-1) > 0)
      # There must be non-zero data (safety net)
      assert abs(data).max() > 1e-9
  
      _all_voxel_of_each_region_have_same_values(
          data, labels_data, N_REGIONS, signals
      )
  
      # and back
      signals_r, labels_r = img_to_signals_labels(
          imgs=data_img, labels_img=labels_img
      )
  
      assert_almost_equal(signals_r, signals)
      assert labels_r == list(range(1, 9))
  
      filenames = write_imgs_to_path(data_img, file_path=tmp_path)
      signals_r, labels_r = img_to_signals_labels(
          imgs=filenames, labels_img=labels_img
      )
  
      assert_almost_equal(signals_r, signals)
      assert labels_r == list(range(1, 9))
  
imports: import warnings
  import numpy
  import pytest
  from nibabel import Nifti1Image
  from numpy.testing import assert_almost_equal, assert_equal
  from nilearn._utils.data_gen import generate_fake_fmri, generate_labeled_regions, generate_maps, generate_timeseries
  from nilearn._utils.exceptions import DimensionError
  from nilearn._utils.testing import write_imgs_to_path
  from nilearn.conftest import _affine_eye, _shape_3d_default
  from nilearn.image import get_data, new_img_like
  from nilearn.maskers import NiftiLabelsMasker
  from nilearn.regions.signal_extraction import _check_shape_and_affine_compatibility, _trim_maps, img_to_signals_labels, img_to_signals_maps, signals_to_img_labels, signals_to_img_maps
label_desc: Use image node_id 23 for calling a global function with example usage: test_signals_extraction_with_labels_without_mask(signals, labels_data, labels_img, shape_3d_default, tmp_path) without return types