class_docstr: Tripod objective function.
  
  This class defines the Tripod [1]_ global optimization problem. This
  is a multimodal minimization problem defined as follows:
  
  .. math::
  
      f_{\text{Tripod}}(x) = p(x_2) \left[1 + p(x_1) \right] +
                             \lvert x_1 + 50p(x_2) \left[1 - 2p(x_1) \right]
                             \rvert + \lvert x_2 + 50\left[1 - 2p(x_2)\right]
                             \rvert
  
  with :math:`x_i \in [-100, 100]` for :math:`i = 1, 2`.
  
  *Global optimum*: :math:`f(x) = 0` for :math:`x = [0, -50]`
  
  .. [1] Jamil, M. & Yang, X.-S. A Literature Survey of Benchmark Functions
  For Global Optimization Problems Int. Journal of Mathematical Modelling
  and Numerical Optimisation, 2013, 4, 150-194.
code: def fun(self, x, *args):
      self.nfev += 1
  
      p1 = float(x[0] >= 0)
      p2 = float(x[1] >= 0)
  
      return (
          p2 * (1.0 + p1)
          + abs(x[0] + 50.0 * p2 * (1.0 - 2.0 * p1))
          + abs(x[1] + 50.0 * (1.0 - 2.0 * p2))
      )
  
imports: from numpy import abs, asarray, cos, exp, arange, pi, sin, sum, atleast_2d
  from .go_benchmark import Benchmark
label_desc: Use image node_id 2 for calling the Tripod obj's underlying member method code with example usage: obj.fun(x) and returns: unknown