class_docstr: Cola objective function.
  
  This class defines the Cola global optimization problem. The 17-dimensional
  function computes indirectly the formula :math:`f(n, u)` by setting
  :math:`x_0 = y_0, x_1 = u_0, x_i = u_{2(i2)}, y_i = u_{2(i2)+1}` :
  
  .. math::
  
      f_{\text{Cola}}(x) = \sum_{i<j}^{n} \left (r_{i,j} - d_{i,j} \right )^2
  
  
  Where :math:`r_{i, j}` is given by:
  
  .. math::
  
      r_{i, j} = \sqrt{(x_i - x_j)^2 + (y_i - y_j)^2}
  
  And :math:`d` is a symmetric matrix given by:
  
  .. math::
  
      \{d} = \left [ d_{ij} \right ] = \begin{pmatrix}
      1.27 &  &  &  &  &  &  &  & \\
      1.69 & 1.43 &  &  &  &  &  &  & \\
      2.04 & 2.35 & 2.43 &  &  &  &  &  & \\
      3.09 & 3.18 & 3.26 & 2.85  &  &  &  &  & \\
      3.20 & 3.22 & 3.27 & 2.88 & 1.55 &  &  &  & \\
      2.86 & 2.56 & 2.58 & 2.59 & 3.12 & 3.06  &  &  & \\
      3.17 & 3.18 & 3.18 & 3.12 & 1.31 & 1.64 & 3.00  & \\
      3.21 & 3.18 & 3.18 & 3.17 & 1.70 & 1.36 & 2.95 & 1.32  & \\
      2.38 & 2.31 & 2.42 & 1.94 & 2.85 & 2.81 & 2.56 & 2.91 & 2.97
      \end{pmatrix}
  
  
  This function has bounds :math:`x_0 \in [0, 4]` and :math:`x_i \in [-4, 4]`
  for :math:`i = 1, ..., n-1`.
  *Global optimum* 11.7464.
  
  .. [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
  
      xi = atleast_2d(asarray([0.0, x[0]] + list(x[1::2])))
      xj = repeat(xi, size(xi, 1), axis=0)
      xi = xi.T
  
      yi = atleast_2d(asarray([0.0, 0.0] + list(x[2::2])))
      yj = repeat(yi, size(yi, 1), axis=0)
      yi = yi.T
  
      inner = (sqrt((xi - xj) ** 2 + (yi - yj) ** 2) - self.d) ** 2
      inner = tril(inner, -1)
      return sum(sum(inner, axis=1))
  
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 2 for calling the Cola obj's underlying member method code with example usage: obj.fun(x) and returns: sum