code: def test_min_signal_alone():
      fdata, fbvals, fbvecs = get_fnames()
      data = load_nifti_data(fdata)
      gtab = grad.gradient_table(fbvals, fbvecs)
  
      idx = tuple(np.array(np.where(data == np.min(data)))[:-1, 0])
      ten_model = dti.TensorModel(gtab)
      fit_alone = ten_model.fit(data[idx])
      fit_together = ten_model.fit(data)
      npt.assert_array_almost_equal(
          fit_together.model_params[idx],
          fit_alone.model_params,
          decimal=12,
      )
  
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 24 for calling a global function with example usage: test_min_signal_alone() without return types