code: def test_nilearn_regress(
      tmp_path, test_strategy, param, fmriprep_version
  ):
      """Try regressing out all motion types without sample mask."""
      img_nii, _ = create_tmp_filepath(
          tmp_path,
          copy_confounds=True,
          copy_json=True,
          fmriprep_version=fmriprep_version,
      )
      if fmriprep_version == "21.x.x" and test_strategy == (
          "ica_aroma",
      ):
          return
      confounds, _ = load_confounds(
          img_nii, strategy=test_strategy, **param
      )
      _regression(confounds, tmp_path)
  
imports: import re
  import numpy
  import pandas
  import pytest
  from nibabel import Nifti1Image
  from scipy.stats import pearsonr
  from sklearn.preprocessing import scale
  from nilearn._utils.data_gen import create_fake_bids_dataset
  from nilearn._utils.fmriprep_confounds import to_camel_case
  from nilearn.conftest import _rng
  from nilearn.interfaces.bids import get_bids_files
  from nilearn.interfaces.fmriprep import load_confounds
  from nilearn.interfaces.fmriprep.load_confounds import _check_strategy, _load_single_confounds_file
  from nilearn.interfaces.fmriprep.tests._testing import create_tmp_filepath, get_legal_confound
  from nilearn.maskers import NiftiMasker
label_desc: Use image node_id 4 for calling a global function with example usage: test_nilearn_regress(tmp_path, test_strategy, param, fmriprep_version) without return types