class_docstr: AbstractEnsembleSolver base class for mystic optimizers that are called within
  a parallel map.  This allows pseudo-global coverage of parameter space using
  non-global optimizers.
      
class_docstr_tok: ["AbstractEnsembleSolver","base","class","for","mystic","optimizers","that","are","called","within","a","parallel","map",".","This","allows","pseudo-global","coverage","of","parameter","space","using","non-global","optimizers","."]
docstr: Set Initial Points with Guess (``x0``)
  
  Args:
      x0 (list[float]): a sequence of length ``self.nDim``
      radius (float): generate random points within ``[-radius*x0, radius*x0]``
          for ``i!=0`` when a simplex-type initial guess is required
  
  Returns:
      None
  
  NOTE:
      *** this method must be overwritten ***
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code: def SetInitialPoints(self, x0, radius=0.05):
      """Set Initial Points with Guess (``x0``)
  
      Args:
          x0 (list[float]): a sequence of length ``self.nDim``
          radius (float): generate random points within ``[-radius*x0, radius*x0]``
              for ``i!=0`` when a simplex-type initial guess is required
  
      Returns:
          None
  
      NOTE:
          *** this method must be overwritten ***"""
      raise NotImplementedError("must be overwritten...")
  
imports: from mystic.monitors import Null
  from mystic.abstract_map_solver import AbstractMapSolver
  from mystic.tools import wrap_function
  from functools import reduce
label_desc: Use image node_id 10 for calling the AbstractEnsembleSolver obj's underlying member method code with example usage: obj.SetInitialPoints(x0, radius) without return types