code: def test_sfm_stick():
      fdata, fbvals, fbvecs = dpd.get_fnames()
      data = load_nifti_data(fdata)
      gtab = grad.gradient_table(fbvals, fbvecs)
      sfmodel = sfm.SparseFascicleModel(
          gtab, solver="NNLS", response=[0.001, 0, 0]
      )
      sffit1 = sfmodel.fit(data[0, 0, 0])
      sphere = dpd.get_sphere()
      sffit1.odf(sphere)
      sffit1.predict(gtab)
  
      SNR = 1000
      S0 = 100
      mevals = np.array(([0.001, 0, 0], [0.001, 0, 0]))
      angles = [(0, 0), (60, 0)]
      S, sticks = sims.multi_tensor(
          gtab, mevals, S0, angles=angles, fractions=[50, 50], snr=SNR
      )
  
      sfmodel = sfm.SparseFascicleModel(
          gtab, solver="NNLS", response=[0.001, 0, 0]
      )
      sffit = sfmodel.fit(S)
      pred = sffit.predict()
      npt.assert_(xval.coeff_of_determination(pred, S) > 96)
  
file_path: dipy/dipy/reconst/tests/test_sfm.py
imports: import warnings
  import numpy
  import numpy.testing
  import pytest
  import dipy.reconst.sfm
  import dipy.data
  import dipy.core.gradients
  import dipy.sims.voxel
  import dipy.core.optimize
  import dipy.reconst.cross_validation
  from dipy.io.gradients import read_bvals_bvecs
  from dipy.io.image import load_nifti_data
  from dipy.utils.optpkg import optional_package
label_desc: Use image node_id 5 for calling a global function with example usage: test_sfm_stick() without return types