code: def test_csd_superres():
      """Check the quality of csdfit with high SH order."""
      _, fbvals, fbvecs = get_fnames("small_64D")
      bvals, bvecs = read_bvals_bvecs(fbvals, fbvecs)
      gtab = gradient_table(bvals, bvecs)
  
      # img, gtab = read_stanford_hardi()
      evals = np.array([[1.5, 0.3, 0.3]]) * [[1.0], [1.0]] / 1000.0
      S, sticks = multi_tensor(
          gtab, evals, snr=None, fractions=[55.0, 45.0]
      )
  
      with warnings.catch_warnings(record=True) as w:
          warnings.filterwarnings(
              action="always",
              message="Number of parameters required.*",
              category=UserWarning,
          )
          warnings.filterwarnings(
              "ignore",
              message=descoteaux07_legacy_msg,
              category=PendingDeprecationWarning,
          )
          model16 = ConstrainedSphericalDeconvModel(
              gtab, (evals[0], 3.0), sh_order=16
          )
          assert_greater_equal(len(w), 1)
          npt.assert_(issubclass(w[0].category, UserWarning))
  
      fit16 = model16.fit(S)
  
      sphere = HemiSphere.from_sphere(get_sphere("symmetric724"))
      # print local_maxima(fit16.odf(default_sphere), default_sphere.edges)
      with warnings.catch_warnings():
          warnings.filterwarnings(
              "ignore",
              message=descoteaux07_legacy_msg,
              category=PendingDeprecationWarning,
          )
          d, v, ind = peak_directions(
              fit16.odf(sphere),
              sphere,
              relative_peak_threshold=0.2,
              min_separation_angle=0,
          )
  
      # Check that there are two peaks
      assert_equal(len(d), 2)
  
      # Check that peaks line up with sticks
      cos_sim = abs((d * sticks).sum(1)) ** 0.5
      assert_(all(cos_sim > 0.99))
  
imports: import warnings
  import numpy
  import numpy.testing
  from numpy.testing import assert_, assert_equal, assert_almost_equal, assert_array_almost_equal, assert_array_equal
  from dipy.testing import assert_greater, assert_greater_equal
  from dipy.data import get_sphere, get_fnames, default_sphere, small_sphere
  from dipy.sims.voxel import multi_tensor, single_tensor, multi_tensor_odf, all_tensor_evecs, single_tensor_odf
  from dipy.core.gradients import gradient_table
  from dipy.core.sphere import Sphere, HemiSphere
  from dipy.core.sphere_stats import angular_similarity
  from dipy.reconst.csdeconv import ConstrainedSphericalDeconvModel, ConstrainedSDTModel, forward_sdeconv_mat, odf_deconv, odf_sh_to_sharp, mask_for_response_ssst, response_from_mask_ssst, response_from_mask, auto_response_ssst, auto_response, recursive_response
  from dipy.direction.peaks import peak_directions
  from dipy.reconst.dti import TensorModel, fractional_anisotropy
  from dipy.reconst.shm import descoteaux07_legacy_msg, QballModel, sf_to_sh, sh_to_sf, real_sh_descoteaux, sph_harm_ind_list
  from dipy.reconst.shm import lazy_index
  from dipy.utils.deprecator import ExpiredDeprecationError
  from dipy.io.gradients import read_bvals_bvecs
  from dipy.testing.decorators import set_random_number_generator
label_desc: Use image node_id 18 for calling a global function with example usage: test_csd_superres() without return types