class_docstr: Class for the manifold of exponential distributions.
  
  This is the parameter space of exponential distributions
  i.e. the half-line of positive reals.
class_docstr_tok: ["Class","for","the","manifold","of","exponential","distributions",".","This","is","the","parameter","space","of","exponential","distributions","i.e",".","the","half-line","of","positive","reals","."]
code: def __init__(self, equip=True):
      super().__init__(
          dim=1,
          embedding_space=Euclidean(dim=1, equip=False),
          support_shape=(),
          equip=equip,
      )
      self._scp_rv = ExponentialDistributionsRandomVariable(self)
  
imports: from scipy.stats import expon
  import geomstats.backend
  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
label_desc: Use image node_id 1 to create a new ExponentialDistributions object from inherited base classes: InformationManifoldMixin, VectorSpaceOpenSet with example: obj = ExponentialDistributions(equip)