class_docstr: Rosenbrock subject to equality and inequality constraints.
  
  The following optimization problem:
      minimize sum(100.0*(x[1] - x[0]**2)**2.0 + (1 - x[0])**2)
      subject to: x[0] + 2 x[1] <= 1
                  2 x[0] + x[1] = 1
  
  Taken from matlab ``fimincon`` documentation.
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code: def __init__(self, random_state=0):
      Rosenbrock.__init__(self, 2, random_state)
      self.x0 = [-1, -0.5]
      self.x_opt = [0.41494, 0.17011]
      self.bounds = None
  
imports: from __future__ import division, print_function, absolute_import
  import numpy
  import pytest
  from scipy.linalg import block_diag
  from scipy.sparse import csc_matrix
  from numpy.testing import TestCase, assert_array_almost_equal, assert_array_less, assert_allclose, assert_
  from pytest import raises
  from scipy.optimize import NonlinearConstraint, LinearConstraint, Bounds, minimize, BFGS, SR1
  from scipy._lib._numpy_compat import suppress_warnings
label_desc: Use image node_id 1 to create a new EqIneqRosenbrock object from inherited base classes: Rosenbrock with example: obj = EqIneqRosenbrock(random_state)