class_docstr: Class for the manifold of Poisson distributions.
  
  This is the parameter space of Poisson distributions
  i.e. [the half-line of positive reals].
class_docstr_tok: ["Class","for","the","manifold","of","Poisson","distributions",".","This","is","the","parameter","space","of","Poisson","distributions","i.e",".","[","the","half-line","of","positive","reals","]","."]
docstr: Metric to equip the space with if equip is True.
docstr_tok: ["Metric","to","equip","the","space","with","if","equip","is","True","."]
code: def default_metric():
      """Metric to equip the space with if equip is True."""
      return PoissonMetric
  
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 PoissonDistributions obj's underlying member method code with example usage: obj.default_metric() and returns: PoissonMetric