class_docstr: MultiModal objective function.
  
  This class defines the MultiModal global optimization problem. This
  is a multimodal minimization problem defined as follows:
  
  .. math::
  
     f_{\text{MultiModal}}(x) = \left( \sum_{i=1}^n \lvert x_i \rvert
     \right) \left( \prod_{i=1}^n \lvert x_i \rvert \right)
  
  
  Here, :math:`n` represents the number of dimensions and
  :math:`x_i \in [-10, 10]` for :math:`i = 1, ..., n`.
  
  *Global optimum*: :math:`f(x) = 0` for :math:`x_i = 0` for
  :math:`i = 1, ..., n`
  
  .. [1] Gavana, A. Global Optimization Benchmarks and AMPGO retrieved 2015
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code: def fun(self, x, *args):
      self.nfev += 1
  
      return sum(abs(x)) * prod(abs(x))
  
imports: from numpy import abs, asarray, cos, exp, log, arange, pi, prod, sin, sqrt, sum, tan
  from .go_benchmark import Benchmark, safe_import
label_desc: Use image node_id 2 for calling the MultiModal obj's underlying member method code with example usage: obj.fun(x) and returns: unknown