class_docstr: Class for the manifold of binomial distributions.
  
  This is the parameter space of binomial distributions
  i.e. the half-line of positive reals.
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docstr: Project a point in ambient space to the parameter set.
  
  The parameter is floored to `gs.atol` if it is negative
  and to '1-gs.atol' if it is greater than 1.
  
  Parameters
  ----------
  point : array-like, shape=[..., 1]
      Point in ambient space.
  atol : float
      Tolerance to evaluate positivity.
  
  Returns
  -------
  projected : array-like, shape=[..., 1]
      Projected point.
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code: def projection(self, point, atol=gs.atol):
      """Project a point in ambient space to the parameter set.
  
      The parameter is floored to `gs.atol` if it is negative
      and to '1-gs.atol' if it is greater than 1.
  
      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(
          gs.logical_or(point < atol, point > 1 - atol),
          (1 - atol) * gs.cast(point > 1 - atol, point.dtype)
          + atol * gs.cast(point < atol, point.dtype),
          point,
      )
  
imports: from scipy.special import factorial
  from scipy.stats import binom
  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 BinomialDistributions obj's underlying member method code with example usage: obj.projection(point, atol) and returns: gs