code: def _regression(confounds, tmp_path):
      """Simple regression with NiftiMasker."""
      # Simulate data
      img, mask_conf, _, _, _ = _simu_img(tmp_path, demean=False)
      confounds = _handle_non_steady(confounds)
      # Do the regression
      masker = NiftiMasker(mask_img=mask_conf, standardize=True)
      tseries_clean = masker.fit_transform(
          img, confounds=confounds, sample_mask=None
      )
      assert tseries_clean.shape[0] == confounds.shape[0]
  
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 3 for calling a global function with example usage: _regression(confounds, tmp_path) without return types