class_docstr: Cosine Mixture objective function.
  
  This class defines the Cosine Mixture global optimization problem. This
  is a multimodal minimization problem defined as follows:
  
  .. math::
  
      f_{\text{CosineMixture}}(x) = -0.1 \sum_{i=1}^n \cos(5 \pi x_i)
      - \sum_{i=1}^n x_i^2
  
  
  Here, :math:`n` represents the number of dimensions and :math:`x_i \in
  [-1, 1]` for :math:`i = 1, ..., N`.
  
  *Global optimum*: :math:`f(x) = -0.1N` for :math:`x_i = 0` for
  :math:`i = 1, ..., N`
  
  .. [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.
  
  TODO, Jamil #38 has wrong minimum and wrong fglob. I plotted it.
  -(x**2) term is always negative if x is negative.
   cos(5 * pi * x) is equal to -1 for x=-1.
code: def __init__(self, dimensions=2):
      Benchmark.__init__(self, dimensions)
  
      self.change_dimensionality = True
      self._bounds = list(zip([-1.0] * self.N, [1.0] * self.N))
  
      self.global_optimum = [[-1.0 for _ in range(self.N)]]
      self.fglob = -0.9 * self.N
  
imports: import numpy
  from numpy import abs, asarray, cos, exp, floor, pi, sign, sin, sqrt, sum, size, tril, isnan, atleast_2d, repeat
  from numpy.testing import assert_almost_equal
  from .go_benchmark import Benchmark
label_desc: Use image node_id 1 to create a new CosineMixture object from inherited base classes: Benchmark with example: obj = CosineMixture(dimensions)