class_docstr: Powell objective function.
  
  This class defines the Powell [1]_ global optimization problem. This
  is a multimodal minimization problem defined as follows:
  
  .. math::
  
      f_{\text{Powell}}(x) = (x_3+10x_1)^2 + 5(x_2-x_4)^2 + (x_1-2x_2)^4
      + 10(x_3-x_4)^4
  
  
  Here, :math:`n` represents the number of dimensions and
  :math:`x_i \in [-4, 5]` for :math:`i = 1, ..., 4`.
  
  *Global optimum*: :math:`f(x) = 0` for :math:`x_i = 0` for
  :math:`i = 1, ..., 4`
  
  ..[1] Powell, M. An iterative method for finding stationary values of a
  function of several variables Computer Journal, 1962, 5, 147-151
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code: def fun(self, x, *args):
      self.nfev += 1
  
      return (
          (x[0] + 10 * x[1]) ** 2
          + 5 * (x[2] - x[3]) ** 2
          + (x[1] - 2 * x[2]) ** 4
          + 10 * (x[0] - x[3]) ** 4
      )
  
imports: from numpy import abs, sum, sin, cos, sqrt, log, prod, where, pi, exp, arange, floor, log10, atleast_2d, zeros
  from .go_benchmark import Benchmark
label_desc: Use image node_id 2 for calling the Powell obj's underlying member method code with example usage: obj.fun(x) and returns: unknown