code: def test_t_output():
      # Check we get required outputs
      exp_t = RESULTS.t(0)
      exp_effect = RESULTS.theta[0]
      exp_sd = exp_effect / exp_t
  
      res = RESULTS.Tcontrast([1, 0])
  
      assert_array_almost_equal(res.t, exp_t)
      assert_array_almost_equal(res.effect, exp_effect)
      assert_array_almost_equal(res.sd, exp_sd)
  
      res = RESULTS.Tcontrast([1, 0], store=("effect",))
  
      assert res.t is None
      assert_array_almost_equal(res.effect, exp_effect)
      assert res.sd is None
  
      res = RESULTS.Tcontrast([1, 0], store=("t",))
  
      assert_array_almost_equal(res.t, exp_t)
      assert res.effect is None
      assert res.sd is None
  
      res = RESULTS.Tcontrast([1, 0], store=("sd",))
  
      assert res.t is None
      assert res.effect is None
      assert_array_almost_equal(res.sd, exp_sd)
  
      res = RESULTS.Tcontrast([1, 0], store=("effect", "sd"))
  
      assert res.t is None
      assert_array_almost_equal(res.effect, exp_effect)
      assert_array_almost_equal(res.sd, exp_sd)
  
file_path: nilearn/nilearn/glm/tests/test_model.py
imports: import numpy
  import pytest
  from numpy.testing import assert_array_almost_equal
  from nilearn.glm import OLSModel
label_desc: Use image node_id 4 for calling a global function with example usage: test_t_output() without return types