code: def test_estimate_linear_fit():
      """
      Test the linear estimates considering a single exponential fit.
      """
      data_single_exponential_D = single_exponential(S0, D, gtab.bvals)
      assert_array_almost_equal(
          ivim_model_trr.estimate_linear_fit(
              data_single_exponential_D, split_b=500.0, less_than=False
          ),
          (S0, D),
      )
      data_single_exponential_D_star = single_exponential(
          S0, D_star, gtab.bvals
      )
      assert_array_almost_equal(
          ivim_model_trr.estimate_linear_fit(
              data_single_exponential_D_star,
              split_b=100.0,
              less_than=True,
          ),
          (S0, D_star),
      )
  
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 20 for calling a global function with example usage: test_estimate_linear_fit() without return types