code: def test_fit_method_error():
      bval, bvec = read_bvals_bvecs(*get_fnames("55dir_grad"))
      gtab = grad.gradient_table_from_bvals_bvecs(bval, bvec)
  
      # This should work (smoke-testing!):
      TensorModel(gtab, fit_method="WLS")
  
      # This should raise an error because there is no such fit_method
      npt.assert_raises(
          ValueError, TensorModel, gtab, min_signal=1e-9, fit_method="s"
      )
  
imports: import warnings
  import numpy
  import numpy.testing
  import scipy.optimize
  import dipy.reconst.dti
  from dipy.io.gradients import read_bvals_bvecs
  from dipy.reconst.dti import ols_resort_msg, axial_diffusivity, color_fa, fractional_anisotropy, from_lower_triangular, geodesic_anisotropy, lower_triangular, mean_diffusivity, radial_diffusivity, TensorModel, trace, linearity, planarity, sphericity, decompose_tensor, _decompose_tensor_nan
  from dipy.io.image import load_nifti_data
  from dipy.data import get_fnames, dsi_voxels, get_sphere
  from dipy.core.subdivide_octahedron import create_unit_sphere
  import dipy.core.gradients
  import dipy.core.sphere
  from dipy.sims.voxel import single_tensor
  from dipy.testing.decorators import set_random_number_generator
label_desc: Use image node_id 12 for calling a global function with example usage: test_fit_method_error() without return types