code: def test_anisotropic_reduced_MSE(radial_order=0, time_order=0):
      gtab_4d = generate_gtab4D()
      l1, l2, l3 = [0.0015, 0.0003, 0.0003]
      S = generate_signal_crossing(gtab_4d, l1, l2, l3)
      qtdmri_mod_aniso = qtdmri.QtdmriModel(
          gtab_4d,
          radial_order=radial_order,
          time_order=time_order,
          cartesian=True,
          anisotropic_scaling=True,
      )
      qtdmri_mod_iso = qtdmri.QtdmriModel(
          gtab_4d,
          radial_order=radial_order,
          time_order=time_order,
          cartesian=True,
          anisotropic_scaling=False,
      )
      qtdmri_fit_aniso = qtdmri_mod_aniso.fit(S)
      qtdmri_fit_iso = qtdmri_mod_iso.fit(S)
      mse_aniso = np.mean((S - qtdmri_fit_aniso.fitted_signal()) ** 2)
      mse_iso = np.mean((S - qtdmri_fit_iso.fitted_signal()) ** 2)
      assert_(mse_aniso < mse_iso)
  
imports: import warnings
  import numpy
  import scipy.integrate
  from numpy.testing import assert_, assert_almost_equal, assert_array_almost_equal, assert_equal, assert_raises
  import pytest
  from dipy.core.gradients import gradient_table_from_qvals_bvecs
  from dipy.data import get_gtab_taiwan_dsi, get_sphere
  from dipy.reconst import qtdmri, mapmri
  from dipy.reconst.shm import descoteaux07_legacy_msg
  from dipy.sims.voxel import multi_tensor, add_noise
  from dipy.testing.decorators import set_random_number_generator
label_desc: Use image node_id 9 for calling a global function with example usage: test_anisotropic_reduced_MSE(radial_order, time_order) without return types