class_docstr: Class for the Fisher information metric on Gamma distributions.
  
  References
  ----------
  .. [AD2008] Arwini, K. A., & Dodson, C. T. (2008).
      Information geometry (pp. 31-54). Springer Berlin Heidelberg.
class_docstr_tok: ["Class","for","the","Fisher","information","metric","on","Gamma","distributions",".","References","--","--","--","--","--","..","[","AD2008","]","Arwini",",","K.","A.",",","&","Dodson",",","C.","T.","(","2008",")",".","Information","geometry","(","pp",".","31-54",")",".","Springer","Berlin","Heidelberg","."]
code: def __init__(self, space):
      super().__init__(space=space)
  
      self.log_solver = LogODESolver(
          n_nodes=1000, integrator=ScipySolveBVP(max_nodes=1000)
      )
      self.exp_solver = ExpODESolver(
          integrator=ScipySolveIVP(method="LSODA")
      )
  
imports: from scipy.stats import gamma
  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, ScipyUnivariateRandomVariable
  from geomstats.numerics.bvp import ScipySolveBVP
  from geomstats.numerics.geodesic import ExpODESolver, LogODESolver
  from geomstats.numerics.ivp import ScipySolveIVP
  from geomstats.vectorization import check_is_batch
label_desc: Use image node_id 1 to create a new GammaMetric object from inherited base classes: RiemannianMetric with example: obj = GammaMetric(space)