class_docstr: Rosenbrock function.
  
  The following optimization problem:
      minimize sum(100.0*(x[1:] - x[:-1]**2.0)**2.0 + (1 - x[:-1])**2.0)
class_docstr_tok: ["Rosenbrock","function",".","The","following","optimization","problem",":","minimize","sum","(","100.0","*","(","x","[","1",":","]","-","x","[",":","-1","]","*","*","2.0",")","*","*","2.0","+","(","1","-","x","[",":","-1","]",")","*","*","2.0",")"]
code: def fun(self, x):
      x = np.asarray(x)
      r = np.sum(
          100.0 * (x[1:] - x[:-1] ** 2.0) ** 2.0 + (1 - x[:-1]) ** 2.0,
          axis=0,
      )
      return r
  
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 2 for calling the Rosenbrock obj's underlying member method code with example usage: obj.fun(x) and returns: r