class_docstr: Class for the manifold of binomial distributions.
  
  This is the parameter space of binomial distributions
  i.e. the half-line of positive reals.
class_docstr_tok: ["Class","for","the","manifold","of","binomial","distributions",".","This","is","the","parameter","space","of","binomial","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 BinomialMetric
  
imports: from scipy.special import factorial
  from scipy.stats import binom
  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 BinomialDistributions obj's underlying member method code with example usage: obj.default_metric() and returns: BinomialMetric