class_docstr: A Poisson random variable.
class_docstr_tok: ["A","Poisson","random","variable","."]
code: def _flatten_params(point, pre_flat_shape):
      flat_point = gs.reshape(
          gs.broadcast_to(point, pre_flat_shape), (-1,)
      )
      return {"mu": flat_point}
  
imports: from scipy.special import factorial
  from scipy.stats import poisson
  import geomstats.backend
  from geomstats.geometry.base import VectorSpaceOpenSet
  from geomstats.geometry.euclidean import Euclidean
  from geomstats.geometry.riemannian_metric import RiemannianMetric
  from geomstats.information_geometry.base import InformationManifoldMixin, ScipyUnivariateRandomVariable
label_desc: Use image node_id 2 for calling the PoissonDistributionsRandomVariable obj's underlying member method code with example usage: obj._flatten_params(point, pre_flat_shape) and returns: dict