code: def test_final_parameter_values():
      model = LinearModel()
      params = model.make_params()
      params["intercept"].set(value=-1, min=-20, max=0)
      params["slope"].set(value=1, min=-100, max=400)
  
      np.random.seed(78281)
      x = np.linspace(0, 9, 10)
      y = x * 1.34 - 4.5 + np.random.normal(scale=0.05, size=x.size)
  
      result = model.fit(y, x=x, method="nelder", params=params)
  
      assert_almost_equal(result.chisqr, 0.014625543, decimal=6)
      assert_almost_equal(
          result.params["intercept"].value, -4.511087126, decimal=6
      )
      assert_almost_equal(
          result.params["slope"].value, 1.339685514, decimal=6
      )
  
file_path: lmfit-py/tests/test_covariance_matrix.py
imports: import os
  import numpy
  from numpy import pi
  from numpy.testing import assert_allclose, assert_almost_equal
  import pytest
  from lmfit import Parameters, minimize
  from lmfit.lineshapes import exponential
  from lmfit.models import ExponentialModel, LinearModel, VoigtModel
label_desc: Use image node_id 7 for calling a global function with example usage: test_final_parameter_values() without return types