class_docstr: Trefethen objective function.
  
  This class defines the Trefethen [1]_ global optimization problem. This is a
  multimodal minimization problem defined as follows:
  
  .. math::
  
      f_{\text{Trefethen}}(x) = 0.25 x_{1}^{2} + 0.25 x_{2}^{2}
                                + e^{\sin\left(50 x_{1}\right)}
                                - \sin\left(10 x_{1} + 10 x_{2}\right)
                                + \sin\left(60 e^{x_{2}}\right)
                                + \sin\left[70 \sin\left(x_{1}\right)\right]
                                + \sin\left[\sin\left(80 x_{2}\right)\right]
  
  
  with :math:`x_i \in [-10, 10]` for :math:`i = 1, 2`.
  
  *Global optimum*: :math:`f(x) = -3.3068686474` for
  :math:`x = [-0.02440307923, 0.2106124261]`
  
  .. [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 __init__(self, dimensions=2):
      Benchmark.__init__(self, dimensions)
  
      self._bounds = list(zip([-10.0] * self.N, [10.0] * self.N))
      self.custom_bounds = [(-5, 5), (-5, 5)]
  
      self.global_optimum = [[-0.02440307923, 0.2106124261]]
      self.fglob = -3.3068686474
  
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 1 to create a new Trefethen object from inherited base classes: Benchmark with example: obj = Trefethen(dimensions)