code: def get_test_data(rng):
      gtab = get_3shell_gtab()
      evals_list = [
          np.array([1.7e-3, 0.4e-3, 0.4e-3]),
          np.array([6.0e-4, 4.0e-4, 4.0e-4]),
          np.array([3.0e-3, 3.0e-3, 3.0e-3]),
      ]
      s0 = [0.8, 1, 4]
      signals = [
          single_tensor(gtab, x[0], x[1]) for x in zip(s0, evals_list)
      ]
      tissues = [0, 0, 2, 0, 1, 0, 0, 1, 2]  # wm=0, gm=1, csf=2
      data = [
          add_noise(signals[tissue], 80, s0[0], rng=rng)
          for tissue in tissues
      ]
      data = np.asarray(data).reshape((3, 3, 1, len(signals[0])))
      tissues = np.asarray(tissues).reshape((3, 3, 1))
      masks = [np.where(tissues == x, 1, 0) for x in range(3)]
      responses = [
          np.concatenate((x[0], [x[1]])) for x in zip(evals_list, s0)
      ]
      return gtab, data, masks, responses
  
imports: import warnings
  from dipy.reconst.mcsd import mask_for_response_msmt, response_from_mask_msmt, auto_response_msmt
  from dipy.reconst.mcsd import MultiShellDeconvModel, multi_shell_fiber_response
  import numpy
  import numpy.testing
  import pytest
  from dipy.sims.voxel import single_tensor, multi_tensor, add_noise
  from dipy.reconst import shm
  from dipy.data import default_sphere, get_3shell_gtab
  from dipy.core.gradients import GradientTable
  from dipy.testing.decorators import set_random_number_generator
  from dipy.utils.optpkg import optional_package
label_desc: Use image node_id 1 for calling a global function with example usage: get_test_data(rng) and returns: gtab,  data,  masks,  responses