class_docstr: A Dirichlet random variable.
class_docstr_tok: ["A","Dirichlet","random","variable","."]
code: def __init__(self, space):
      pdf = lambda x, point: dirichlet.pdf(gs.transpose(x), point)
      super().__init__(space, dirichlet.rvs, pdf)
  
imports: import math
  import numpy
  from scipy.optimize import minimize
  from scipy.stats import dirichlet
  import geomstats.backend
  from geomstats.algebra_utils import from_vector_to_diagonal_matrix
  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, ScipyMultivariateRandomVariable
  from geomstats.numerics.bvp import ScipySolveBVP
  from geomstats.numerics.geodesic import ExpODESolver, LogODESolver
  from geomstats.numerics.ivp import ScipySolveIVP
  from geomstats.vectorization import repeat_out
label_desc: Use image node_id 1 to create a new DirichletRandomVariable object from inherited base classes: ScipyMultivariateRandomVariable with example: obj = DirichletRandomVariable(space)