class_docstr: Class for the manifold of categorical distributions.
  
  This is the set of `n+1`-tuples of positive reals that sum up to one,
  i.e. the `n`-simplex. Each point is the parameter of a categorical
  distribution, i.e. gives the probabilities of $n$ different outcomes
  in a single experiment.
  
  Attributes
  ----------
  dim : int
      Dimension of the manifold of categorical distributions. The
      number of outcomes is dim + 1.
  embedding_manifold : Manifold
      Embedding manifold.
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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 CategoricalMetric
  
imports: from geomstats.information_geometry.multinomial import MultinomialDistributions, MultinomialMetric
label_desc: Use image node_id 2 for calling the CategoricalDistributions obj's underlying member method code with example usage: obj.default_metric() and returns: CategoricalMetric