class_docstr: Class for the manifold of multinomial 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 multinomial
  distribution, i.e. gives the probabilities of $n$ different outcomes
  in a single experiment.
  
  Attributes
  ----------
  dim : int
      Dimension of the parameter manifold of multinomial distributions.
      The number of outcomes is dim + 1.
  embedding_manifold : Manifold
      Embedding manifold.
docstr: Sample from the multinomial distribution.
  
  Sample from the multinomial distribution with parameters provided by
  point. This gives samples in the simplex.
  
  Parameters
  ----------
  point : array-like, shape=[..., dim + 1]
      Parameters of a multinomial distribution, i.e. probabilities
      associated to dim + 1 outcomes.
  n_samples : int
      Number of points to sample with each set of parameters in point.
      Optional, default: 1.
  
  Returns
  -------
  samples : array-like, shape=[..., n_samples, dim + 1]
      Samples from multinomial distributions.
      Note that this can be of shape [n_points, n_samples, dim + 1] if
      several points and several samples are provided as inputs.
docstr_tok: ["Sample","from","the","multinomial","distribution",".","Sample","from","the","multinomial","distribution","with","parameters","provided","by","point",".","This","gives","samples","in","the","simplex",".","Parameters","--","--","--","--","--","point",":","array-like",",","shape=","[","...",",","dim","+","1","]","Parameters","of","a","multinomial","distribution",",","i.e",".","probabilities","associated","to","dim","+","1","outcomes",".","n_samples",":","int","Number","of","points","to","sample","with","each","set","of","parameters","in","point",".","Optional",",","default",":","1",".","Returns","--","--","--","-","samples",":","array-like",",","shape=","[","...",",","n_samples",",","dim","+","1","]","Samples","from","multinomial","distributions",".","Note","that","this","can","be","of","shape","[","n_points",",","n_samples",",","dim","+","1","]","if","several","points","and","several","samples","are","provided","as","inputs","."]
code: def sample(self, point, n_samples=1):
      """Sample from the multinomial distribution.
  
      Sample from the multinomial distribution with parameters provided by
      point. This gives samples in the simplex.
  
      Parameters
      ----------
      point : array-like, shape=[..., dim + 1]
          Parameters of a multinomial distribution, i.e. probabilities
          associated to dim + 1 outcomes.
      n_samples : int
          Number of points to sample with each set of parameters in point.
          Optional, default: 1.
  
      Returns
      -------
      samples : array-like, shape=[..., n_samples, dim + 1]
          Samples from multinomial distributions.
          Note that this can be of shape [n_points, n_samples, dim + 1] if
          several points and several samples are provided as inputs.
      """
      return self._scp_rv.rvs(point, n_samples)
  
imports: from scipy.stats import dirichlet, multinomial
  import geomstats.backend
  from geomstats.algebra_utils import from_vector_to_diagonal_matrix
  from geomstats.geometry.base import LevelSet
  from geomstats.geometry.euclidean import Euclidean
  from geomstats.geometry.hypersphere import Hypersphere
  from geomstats.geometry.riemannian_metric import RiemannianMetric
  from geomstats.information_geometry.base import InformationManifoldMixin, ScipyMultivariateRandomVariable
  from geomstats.vectorization import repeat_out
label_desc: Use image node_id 9 for calling the MultinomialDistributions obj's underlying member method code with example usage: obj.sample(point, n_samples) and returns: self