code: def test_pad_contrast(rng, val, stat_type):
      """Check padding of vector contrasts."""
      theta = rng.random((4, 1))
      con_val = np.array([val])
      padded_contrast = pad_contrast(
          con_val, theta, stat_type=stat_type
      )
      assert_array_equal(padded_contrast, [[1, 0, 0, 0]])
  
imports: import numpy
  import pytest
  import scipy.linalg
  import scipy.stats
  from numpy.testing import assert_almost_equal, assert_array_almost_equal, assert_array_equal
  from scipy.stats import norm
  from nilearn._utils.data_gen import generate_fake_fmri
  from nilearn.glm._utils import full_rank, multiple_fast_inverse, multiple_mahalanobis, pad_contrast, positive_reciprocal, z_score
  from nilearn.glm.first_level import FirstLevelModel, make_first_level_design_matrix
  from nilearn.maskers import NiftiMasker
label_desc: Use image node_id 11 for calling a global function with example usage: test_pad_contrast(rng, val, stat_type) without return types