code: def test_da_scipy_vs_lmfit():
      """Test DA algorithm in lmfit versus SciPy."""
      bounds = [(-512, 512), (-512, 512)]
      result_scipy = scipy.optimize.dual_annealing(
          eggholder, bounds, seed=7
      )
  
      pars = lmfit.Parameters()
      pars.add_many(
          ("x0", 0, True, -512, 512), ("x1", 0, True, -512, 512)
      )
      mini = lmfit.Minimizer(eggholder_lmfit, pars)
      result = mini.minimize(method="dual_annealing", seed=7)
      out_x = np.array(
          [result.params["x0"].value, result.params["x1"].value]
      )
  
      assert_allclose(result_scipy.fun, result.residual)
      assert_allclose(result_scipy.x, out_x)
  
file_path: lmfit-py/tests/test_dual_annealing.py
imports: import numpy
  from numpy.testing import assert_allclose
  import scipy
  import lmfit
label_desc: Use image node_id 3 for calling a global function with example usage: test_da_scipy_vs_lmfit() without return types