code: def test_tensor_algebra(rng):
      # Test that the computation of tensor determinant and norm is correct
      test_arr = rng.random((10, 3, 3))
      t_det = dti.determinant(test_arr)
      t_norm = dti.norm(test_arr)
      for i, x in enumerate(test_arr):
          npt.assert_almost_equal(np.linalg.det(x), t_det[i])
          npt.assert_almost_equal(np.linalg.norm(x), t_norm[i])
  
imports: import warnings
  import numpy
  import numpy.testing
  import scipy.optimize
  import dipy.reconst.dti
  from dipy.io.gradients import read_bvals_bvecs
  from dipy.reconst.dti import ols_resort_msg, axial_diffusivity, color_fa, fractional_anisotropy, from_lower_triangular, geodesic_anisotropy, lower_triangular, mean_diffusivity, radial_diffusivity, TensorModel, trace, linearity, planarity, sphericity, decompose_tensor, _decompose_tensor_nan
  from dipy.io.image import load_nifti_data
  from dipy.data import get_fnames, dsi_voxels, get_sphere
  from dipy.core.subdivide_octahedron import create_unit_sphere
  import dipy.core.gradients
  import dipy.core.sphere
  from dipy.sims.voxel import single_tensor
  from dipy.testing.decorators import set_random_number_generator
label_desc: Use image node_id 2 for calling a global function with example usage: test_tensor_algebra(rng) without return types