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","."]
docstr: Project a point in ambient space to the open set.
  
  The last coordinate is floored to `gs.atol` if it is non-positive.
  
  Parameters
  ----------
  point : array-like, shape=[..., 1]
      Point in ambient space.
  atol : float
      Tolerance to evaluate positivity.
  
  Returns
  -------
  projected : array-like, shape=[..., 1]
      Projected point.
docstr_tok: ["Project","a","point","in","ambient","space","to","the","open","set",".","The","last","coordinate","is","floored","to","`","gs.atol","`","if","it","is","non-positive",".","Parameters","--","--","--","--","--","point",":","array-like",",","shape=","[","...",",","1","]","Point","in","ambient","space",".","atol",":","float","Tolerance","to","evaluate","positivity",".","Returns","--","--","--","-","projected",":","array-like",",","shape=","[","...",",","1","]","Projected","point","."]
code: def projection(self, point, atol=gs.atol):
      """Project a point in ambient space to the open set.
  
      The last coordinate is floored to `gs.atol` if it is non-positive.
  
      Parameters
      ----------
      point : array-like, shape=[..., 1]
          Point in ambient space.
      atol : float
          Tolerance to evaluate positivity.
  
      Returns
      -------
      projected : array-like, shape=[..., 1]
          Projected point.
      """
      return gs.where(point < atol, atol, point)
  
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 5 for calling the ExponentialDistributions obj's underlying member method code with example usage: obj.projection(point, atol) and returns: gs