class_docstr: An abstract red-blue ensemble move with parallelization as described in
  `Foreman-Mackey et al. (2013) <https://arxiv.org/abs/1202.3665>`_.
  
  Args:
      nsplits (Optional[int]): The number of sub-ensembles to use. Each
          sub-ensemble is updated in parallel using the other sets as the
          complementary ensemble. The default value is ``2`` and you
          probably won't need to change that.
  
      randomize_split (Optional[bool]): Randomly shuffle walkers between
          sub-ensembles. The same number of walkers will be assigned to
          each sub-ensemble on each iteration. By default, this is ``True``.
  
      live_dangerously (Optional[bool]): By default, an update will fail with
          a ``RuntimeError`` if the number of walkers is smaller than twice
          the dimension of the problem because the walkers would then be
          stuck on a low dimensional subspace. This can be avoided by
          switching between the stretch move and, for example, a
          Metropolis-Hastings step. If you want to do this and suppress the
          error, set ``live_dangerously = True``. Thanks goes (once again)
          to @dstndstn for this wonderful terminology.
code: def setup(self, coords):
      pass
  
file_path: emcee/src/emcee/moves/red_blue.py
imports: import numpy
  from ..state import State
  from .move import Move
label_desc: Use image node_id 2 for calling the RedBlueMove obj's underlying member method code with example usage: obj.setup(coords) without return types