code: def test_t_score_with_covars_and_normalized_design_nocovar(rng):
      """Test t-scores computation without covariates."""
      # Normalized data
      n_samples = 50
  
      # generate data
      var1 = np.ones((n_samples, 1)) / np.sqrt(n_samples)
      var2 = rng.standard_normal((n_samples, 1))
      var2 = var2 / np.sqrt(np.sum(var2**2, 0))  # normalize
  
      # compute t-scores with nilearn routine
      t_val_own = _utils.t_score_with_covars_and_normalized_design(
          var1, var2
      )
  
      # compute t-scores with linalg or statsmodels
      t_val_alt = get_tvalue_with_alternative_library(var1, var2)
      assert_array_almost_equal(t_val_own, t_val_alt)
  
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 12 for calling a global function with example usage: test_t_score_with_covars_and_normalized_design_nocovar(rng) without return types