class_docstr: Hypervolume computation based on variant 3 of the algorithm in the paper:
  C. M. Fonseca, L. Paquete, and M. Lopez-Ibanez. An improved dimension-sweep
  algorithm for the hypervolume indicator. In IEEE Congress on Evolutionary
  Computation, pages 1157-1163, Vancouver, Canada, July 2006.
  
  Minimization is implicitly assumed here!
class_docstr_tok: ["Hypervolume","computation","based","on","variant","3","of","the","algorithm","in","the","paper",":","C.","M.","Fonseca",",","L.","Paquete",",","and","M.","Lopez-Ibanez",".","An","improved","dimension-sweep","algorithm","for","the","hypervolume","indicator",".","In","IEEE","Congress","on","Evolutionary","Computation",",","pages","1157-1163",",","Vancouver",",","Canada",",","July","2006",".","Minimization","is","implicitly","assumed","here","!"]
docstr: Sets up the list data structure needed for calculation.
docstr_tok: ["Sets","up","the","list","data","structure","needed","for","calculation","."]
code: def preProcess(self, front):
      """Sets up the list data structure needed for calculation."""
      dimensions = len(self.referencePoint)
      nodeList = _MultiList(dimensions)
      nodes = [_MultiList.Node(dimensions, point) for point in front]
      for i in range(dimensions):
          self.sortByDimension(nodes, i)
          nodeList.extend(nodes, i)
      self.list = nodeList
  
file_path: deap/deap/tools/_hypervolume/pyhv.py
imports: import warnings
  import numpy
label_desc: Use image node_id 4 for calling the _HyperVolume obj's underlying member method code with example usage: obj.preProcess(front) without return types