class_docstr: Test SLSQP algorithm using Example 14.4 from Numerical Methods for
  Engineers by Steven Chapra and Raymond Canale.
  This example maximizes the function f(x) = 2*x*y + 2*x - x**2 - 2*y**2,
  which has a maximum at x=2, y=1.
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code: def test_regression_5743(self):
      # SLSQP must not indicate success for this problem,
      # which is infeasible.
      x = [1, 2]
      sol = minimize(
          lambda x: x[0] ** 2 + x[1] ** 2,
          x,
          constraints=(
              {"type": "eq", "fun": lambda x: x[0] + x[1] - 1},
              {"type": "ineq", "fun": lambda x: x[0] - 2},
          ),
          bounds=((0, None), (0, None)),
          method="SLSQP",
      )
      assert_(not sol.success, sol)
  
imports: from numpy.testing import assert_, assert_array_almost_equal, assert_allclose, assert_equal
  from pytest import raises
  import pytest
  import numpy
  from scipy.optimize import fmin_slsqp, minimize, Bounds, NonlinearConstraint
label_desc: Use image node_id 39 for calling the TestSLSQP obj's underlying member method code with example usage: obj.test_regression_5743() without return types