code: def test_one_minus_pvalue():
      effect = np.ones((1, 3))
      variance = effect[0]
  
      contrast = Contrast(effect, variance, stat_type="t")
  
      assert np.allclose(contrast.one_minus_pvalue(), 0.84, 1)
      assert np.allclose(contrast.stat_, 1.0, 1)
  
imports: import numpy
  import pytest
  import scipy.stats
  from numpy.testing import assert_almost_equal
  from sklearn.datasets import make_regression
  from sklearn.linear_model import LinearRegression
  from nilearn.glm.contrasts import Contrast, _compute_fixed_effects_params, compute_contrast, compute_fixed_effect_contrast, expression_to_contrast_vector
  from nilearn.glm.first_level import run_glm
label_desc: Use image node_id 14 for calling a global function with example usage: test_one_minus_pvalue() without return types