code: def test_pos_recipr():
      X = np.array([2, 1, -1, 0], dtype=np.int8)
      eX = np.array([0.5, 1, 0, 0])
      Y = positive_reciprocal(X)
  
      assert_array_almost_equal, Y, eX
      assert Y.dtype.type == np.float64
  
      X2 = X.reshape((2, 2))
      Y2 = positive_reciprocal(X2)
  
      assert_array_almost_equal, Y2, eX.reshape((2, 2))
  
      # check that lists have arrived
      XL = [0, 1, -1]
  
      assert_array_almost_equal(positive_reciprocal(XL), [0, 1, 0])
      # scalars
      assert positive_reciprocal(-1) == 0
      assert positive_reciprocal(0) == 0
      assert positive_reciprocal(2) == 0.5
  
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 10 for calling a global function with example usage: test_pos_recipr() without return types