code: def test_L6(self):
      # Lampinen ([5]) test problem 6
      def f(x):
          x = np.hstack(([0], x))  # 1-indexed to match reference
          fun = (x[1] - 10) ** 3 + (x[2] - 20) ** 3
          return fun
  
      def c1(x):
          x = np.hstack(([0], x))  # 1-indexed to match reference
          return [
              (x[1] - 5) ** 2 + (x[2] - 5) ** 2 - 100,
              -((x[1] - 6) ** 2) - (x[2] - 5) ** 2 + 82.81,
          ]
  
      N = NonlinearConstraint(c1, 0, np.inf)
      bounds = [(13, 100), (0, 100)]
      constraints = N
      res = differential_evolution(
          f,
          bounds,
          strategy="rand1bin",
          seed=1234,
          constraints=constraints,
          tol=1e-7,
      )
      x_opt = (14.095, 0.84296)
      f_opt = -6961.814744
  
      assert_allclose(f(x_opt), f_opt, atol=1e-6)
      assert_allclose(res.fun, f_opt, atol=0.001)
      assert_allclose(res.x, x_opt, atol=1e-4)
      assert res.success
      assert_(np.all(np.array(c1(res.x)) >= 0))
      assert_(np.all(res.x >= np.array(bounds)[:, 0]))
      assert_(np.all(res.x <= np.array(bounds)[:, 1]))
  
imports: import multiprocessing
  import platform
  from scipy.optimize._differentialevolution import DifferentialEvolutionSolver, _ConstraintWrapper
  from scipy.optimize import differential_evolution
  from scipy.optimize._constraints import Bounds, NonlinearConstraint, LinearConstraint
  from scipy.optimize import rosen
  from scipy.sparse import csr_matrix
  from scipy._lib._pep440 import Version
  import numpy
  from numpy.testing import assert_equal, assert_allclose, assert_almost_equal, assert_array_equal, assert_string_equal, assert_, suppress_warnings
  from pytest import raises, warns
  import pytest
label_desc: Use image node_id 52 for calling the TestDifferentialEvolutionSolver obj's underlying member method code with example usage: obj.test_L6() and returns: fun, list