code: def test_with_higher_S0():
      """
      Test whether fitting works for S0 > 1.
      """
      # params for a single voxel
      S0_2 = 1000.0
      params2 = np.array([S0_2, f, D_star, D])
      mevals2 = np.array(([D_star, D_star, D_star], [D, D, D]))
      # This gives an isotropic signal.
      signal2 = multi_tensor(
          gtab,
          mevals2,
          snr=None,
          S0=S0_2,
          fractions=[f * 100, 100 * (1 - f)],
      )
      # Single voxel data
      data_single2 = signal2[0]
  
      ivim_fit = ivim_model_trr.fit(data_single2)
  
      est_signal = ivim_fit.predict(gtab)
      assert_array_equal(est_signal.shape, data_single2.shape)
      assert_array_almost_equal(est_signal, data_single2)
      assert_array_almost_equal(ivim_fit.model_params, params2)
  
imports: import warnings
  import numpy
  from numpy.testing import assert_array_equal, assert_array_almost_equal, assert_raises, assert_array_less, assert_, assert_equal
  from dipy.testing import assert_greater_equal
  import pytest
  from dipy.reconst.ivim import ivim_prediction, IvimModel
  from dipy.core.gradients import gradient_table, generate_bvecs
  from dipy.sims.voxel import multi_tensor
  from dipy.utils.optpkg import optional_package
label_desc: Use image node_id 7 for calling a global function with example usage: test_with_higher_S0() without return types