class_docstr: Class for the Fisher information metric on binomial distributions.
  
  References
  ----------
  .. [AM1981] Atkinson, C., & Mitchell, A. F. (1981). Rao's distance measure.
      Sankhyā: The Indian Journal of Statistics, Series A, 345-365.
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docstr: Compute log map using a base point and an end point.
  
  Parameters
  ----------
  point : array-like, shape=[..., 1]
      End point.
  base_point : array-like, shape=[..., 1]
      Base point.
  
  Returns
  -------
  tangent_vec : array-like, shape=[..., 1]
      Initial velocity of the geodesic starting at base_point and
      reaching point at time 1.
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code: def log(self, point, base_point):
      """Compute log map using a base point and an end point.
  
      Parameters
      ----------
      point : array-like, shape=[..., 1]
          End point.
      base_point : array-like, shape=[..., 1]
          Base point.
  
      Returns
      -------
      tangent_vec : array-like, shape=[..., 1]
          Initial velocity of the geodesic starting at base_point and
          reaching point at time 1.
      """
      return (
          2
          * gs.sqrt(base_point)
          * gs.sqrt(1 - base_point)
          * (gs.arcsin(gs.sqrt(point)) - gs.arcsin(gs.sqrt(base_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 7 for calling the BinomialMetric obj's underlying member method code with example usage: obj.log(point, base_point) and returns: unknown