code: def test_t_score_with_covars_and_normalized_design_withcovar(rng):
      """Test t-scores computation with covariates."""
      # Normalized data
      n_samples = 50
  
      # generate data
      var1 = np.ones((n_samples, 1)) / np.sqrt(n_samples)  # normalized
      var2 = rng.standard_normal((n_samples, 1))
      var2 = var2 / np.sqrt(np.sum(var2**2, 0))  # normalize
      covars = np.eye(n_samples, 3)  # covars is orthogonal
      covars[3] = -1  # covars is orthogonal to var1
      covars = _utils.orthonormalize_matrix(covars)
  
      # nilearn t-score
      own_score = _utils.t_score_with_covars_and_normalized_design(
          var1,
          var2,
          covars,
      )
  
      # compute t-scores with linalg or statmodels
      ref_score = get_tvalue_with_alternative_library(
          var1, var2, covars
      )
      assert_array_almost_equal(own_score, ref_score)
  
imports: import math
  import numpy
  import pytest
  from numpy.testing import assert_array_almost_equal
  from scipy.ndimage import generate_binary_structure
  from nilearn.mass_univariate import _utils
  from nilearn.mass_univariate.tests._testing import get_tvalue_with_alternative_library
label_desc: Use image node_id 13 for calling a global function with example usage: test_t_score_with_covars_and_normalized_design_withcovar(rng) without return types