code: def test_smt2_specific_cases():
      mdkiM = msdki.MeanDiffusionKurtosisModel(gtab_3s)
  
      # Check smt2 is specific cases with known g.t:
      # 1) Intrinsic diffusion is equal MSD for single Gaussian isotropic
      #     diffusion (i.e. awf=0)
      sig_gaussian = single_tensor(
          gtab_3s, evals=np.array([2e-3, 2e-3, 2e-3])
      )
      mdkiF = mdkiM.fit(sig_gaussian)
      assert_almost_equal(mdkiF.msk, 0.0)
      assert_almost_equal(mdkiF.msd, 2.0e-3)
      assert_almost_equal(mdkiF.smt2f, 0)
      assert_almost_equal(mdkiF.smt2di, 2.0e-3)
  
      # 2) Intrinsic diffusion is equal to MSD/3 for single powder-averaged stick
      #    compartment
      Da = 2.0e-3
      mevals = np.zeros((64, 3))
      mevals[:, 0] = Da
      fracs = np.ones(64) * 100 / 64
      signal_pa, dt_sph, kt_sph = multi_tensor_dki(
          gtab_3s,
          mevals,
          angles=bvecs[1:, :],
          fractions=fracs,
          snr=None,
      )
      mdkiF = mdkiM.fit(signal_pa)
      # decimal is set to 1 because of finite number of directions for powder
      # average calculation
      assert_almost_equal(mdkiF.msk, 2.4, decimal=1)
      assert_almost_equal(mdkiF.msd * 1000, Da / 3 * 1000, decimal=1)
      assert_almost_equal(mdkiF.smt2f, 1, decimal=1)
      assert_almost_equal(mdkiF.smt2di, mdkiF.msd * 3, decimal=1)
  
file_path: dipy/dipy/reconst/tests/test_msdki.py
imports: import numpy
  import random
  from numpy.testing import assert_array_almost_equal, assert_raises, assert_almost_equal, assert_
  from dipy.sims.voxel import single_tensor, multi_tensor_dki
  from dipy.io.gradients import read_bvals_bvecs
  from dipy.core.gradients import gradient_table, unique_bvals_magnitude, round_bvals
  from dipy.data import get_fnames
  import dipy.reconst.msdki
  from dipy.reconst.msdki import msk_from_awf, awf_from_msk
label_desc: Use image node_id 10 for calling a global function with example usage: test_smt2_specific_cases() without return types