class_docstr: Class for the complex Poincaré metric.
class_docstr_tok: ["Class","for","the","complex","Poincar\u00e9","metric","."]
docstr: Compute the coefficient tau.
  
  The coefficient tau is used to compute the distance
  between point_a and point_b; it is also used to
  compute the logarithm map between point_a and point_b.
  
  Parameters
  ----------
  point_a : array-like, shape=[..., 1]
      Point.
  point_b : array-like, shape=[..., 1]
      Point.
  atol : float
      Tolerance.
      Optional, default: backend atol.
  
  Returns
  -------
  tau : array-like, shape=[...]
      Coefficient tau.
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code: def _tau(point_a, point_b, atol=gs.atol):
      """Compute the coefficient tau.
  
      The coefficient tau is used to compute the distance
      between point_a and point_b; it is also used to
      compute the logarithm map between point_a and point_b.
  
      Parameters
      ----------
      point_a : array-like, shape=[..., 1]
          Point.
      point_b : array-like, shape=[..., 1]
          Point.
      atol : float
          Tolerance.
          Optional, default: backend atol.
  
      Returns
      -------
      tau : array-like, shape=[...]
          Coefficient tau.
      """
      num = gs.abs(point_a - point_b)
      den = gs.maximum(gs.abs(1 - point_a * gs.conj(point_b)), atol)
      delta = gs.squeeze(gs.minimum(num / den, 1 - atol), axis=-1)
      return (1 / 2) * gs.log((1 + delta) / (1 - delta))
  
file_path: geomstats/geomstats/geometry/complex_poincare_disk.py
imports: import geomstats.backend
  from geomstats.geometry.base import ComplexVectorSpaceOpenSet
  from geomstats.geometry.complex_riemannian_metric import ComplexRiemannianMetric
  from geomstats.geometry.hermitian import Hermitian
label_desc: Use image node_id 3 for calling the ComplexPoincareDiskMetric obj's underlying member method code with example usage: obj._tau(point_a, point_b, atol) and returns: unknown