class_docstr: Base class for crossovers.
  
  A crossover operation is used by :class:`~optuna.samplers.NSGAIISampler`
  to create new parameter combination from parameters of ``n`` parent individuals.
  
  .. note::
      Concrete implementations of this class are expected to only accept parameters
      from numerical distributions. At the moment, only crossover operation for categorical
      parameters (uniform crossover) is built-in into :class:`~optuna.samplers.NSGAIISampler`.
code: def __str__(self) -> str:
      return self.__class__.__name__
  
file_path: optuna/optuna/samplers/nsgaii/_crossovers/_base.py
imports: import abc
  import numpy
  from optuna.study import Study
label_desc: Use image node_id 1 for calling the BaseCrossover obj's underlying member method code with example usage: obj.__str__() and returns: self