code: def test_permuted_ols_with_multiple_constants_and_covars_warnings(
      design,
  ):
      target_var, tested_var, *_ = design
  
      # Multiple intercepts should raise a warning
      # In confounding vars
      with pytest.warns(UserWarning, match="Multiple columns across"):
          confounding_vars = np.ones([N_SAMPLES, 2])
          permuted_ols(
              tested_var,
              target_var,
              confounding_vars,
              n_perm=0,
              random_state=0,
          )
  
      # Across tested vars and confounding vars
      with pytest.warns(UserWarning, match="Multiple columns across"):
          confounding_vars = np.ones([N_SAMPLES, 1])
          tested_var = np.ones([N_SAMPLES, 1])
          permuted_ols(
              tested_var,
              target_var,
              confounding_vars,
              n_perm=0,
              random_state=0,
          )
  
imports: import nibabel
  import numpy
  import pytest
  from numpy.testing import assert_array_almost_equal, assert_array_less, assert_equal
  from scipy import stats
  from nilearn.conftest import _rng
  from nilearn.maskers import NiftiMasker
  from nilearn.mass_univariate import permuted_ols
label_desc: Use image node_id 28 for calling a global function with example usage: test_permuted_ols_with_multiple_constants_and_covars_warnings(design) without return types