code: def test_output_F():
      # Test output_F convenience function
      rng = np.random.RandomState(ord("F"))
      Y = rng.normal(size=(10, 1)) * 10 + 100
      X = np.c_[rng.normal(size=(10, 3)), np.ones((N,))]
      c1 = np.zeros((X.shape[1],))
      c1[0] = 1
      model = OLSModel(X)
      results = model.fit(Y)
      # Check we get required outputs
      exp_f = results.t(0) ** 2
      assert_array_almost_equal(exp_f, output_F(results, c1))
  
imports: import numpy
  from numpy.testing import assert_array_almost_equal
  from nipy.algorithms.statistics.api import OLSModel
  from ..outputters import output_F, output_T
label_desc: Use image node_id 3 for calling a global function with example usage: test_output_F() without return types