class_docstr: Class for the Fisher information metric on Dirichlet distributions.
class_docstr_tok: ["Class","for","the","Fisher","information","metric","on","Dirichlet","distributions","."]
docstr: Compute the radius of the injectivity domain.
  
  This is is the supremum of radii r for which the exponential map is a
  diffeomorphism from the open ball of radius r centered at the base point onto
  its image.
  In the case of the hyperbolic space, it does not depend on the base point and
  is infinite everywhere, because of the negative curvature.
  
  Parameters
  ----------
  base_point : array-like, shape=[..., dim]
      Point on the manifold.
  
  Returns
  -------
  radius : array-like, shape=[...,]
      Injectivity radius.
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code: def injectivity_radius(self, base_point):
      """Compute the radius of the injectivity domain.
  
      This is is the supremum of radii r for which the exponential map is a
      diffeomorphism from the open ball of radius r centered at the base point onto
      its image.
      In the case of the hyperbolic space, it does not depend on the base point and
      is infinite everywhere, because of the negative curvature.
  
      Parameters
      ----------
      base_point : array-like, shape=[..., dim]
          Point on the manifold.
  
      Returns
      -------
      radius : array-like, shape=[...,]
          Injectivity radius.
      """
      radius = gs.array(math.inf)
      return repeat_out(self._space.point_ndim, radius, base_point)
  
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 5 for calling the DirichletMetric obj's underlying member method code with example usage: obj.injectivity_radius(base_point) and returns: repeat_out