code: def test_positive_evals():
      # Tested evals
      L1 = np.array([[1e-3, 1e-3, 2e-3], [0, 1e-3, 0]])
      L2 = np.array([[3e-3, 0, 2e-3], [1e-3, 1e-3, 0]])
      L3 = np.array([[4e-3, 1e-4, 0], [0, 1e-3, 0]])
      # only the first voxels have all eigenvalues larger than zero, thus:
      expected_ind = np.array(
          [[True, False, False], [False, True, False]], dtype=bool
      )
      # test function _positive_evals
      ind = _positive_evals(L1, L2, L3)
      assert_array_equal(ind, expected_ind)
  
imports: import numpy
  import random
  import dipy.reconst.dki
  import dipy.reconst.dti
  from numpy.testing import assert_array_almost_equal, assert_array_equal, assert_almost_equal, assert_raises
  from dipy.sims.voxel import multi_tensor_dki
  from dipy.io.gradients import read_bvals_bvecs
  from dipy.core.gradients import gradient_table
  from dipy.data import get_fnames
  from dipy.reconst.dti import from_lower_triangular, decompose_tensor
  from dipy.reconst.dki import mean_kurtosis, carlson_rf, carlson_rd, axial_kurtosis, radial_kurtosis, mean_kurtosis_tensor, _positive_evals, lower_triangular, kurtosis_fractional_anisotropy
  from dipy.core.sphere import Sphere
  from dipy.data import default_sphere
  from dipy.core.geometry import sphere2cart
  from dipy.utils.optpkg import optional_package
  from dipy.utils.tripwire import TripWireError
label_desc: Use image node_id 3 for calling a global function with example usage: test_positive_evals() without return types