class_docstr: Class for the complex Poincaré metric.
class_docstr_tok: ["Class","for","the","complex","Poincar\u00e9","metric","."]
docstr: Compute the complex Poincaré disk squared distance.
  
  Compute the Riemannian squared distance between point_a and point_b.
  
  Parameters
  ----------
  point_a : array-like, shape=[..., 1]
      Point.
  point_b : array-like, shape=[..., 1]
      Point.
  
  Returns
  -------
  squared_dist : array-like, shape=[...]
      Riemannian squared distance.
docstr_tok: ["Compute","the","complex","Poincar\u00e9","disk","squared","distance",".","Compute","the","Riemannian","squared","distance","between","point_a","and","point_b",".","Parameters","--","--","--","--","--","point_a",":","array-like",",","shape=","[","...",",","1","]","Point",".","point_b",":","array-like",",","shape=","[","...",",","1","]","Point",".","Returns","--","--","--","-","squared_dist",":","array-like",",","shape=","[","...","]","Riemannian","squared","distance","."]
code: def squared_dist(self, point_a, point_b, atol=gs.atol):
      """Compute the complex Poincaré disk squared distance.
  
      Compute the Riemannian squared distance between point_a and point_b.
  
      Parameters
      ----------
      point_a : array-like, shape=[..., 1]
          Point.
      point_b : array-like, shape=[..., 1]
          Point.
  
      Returns
      -------
      squared_dist : array-like, shape=[...]
          Riemannian squared distance.
      """
      dist = self._tau(point_a, point_b, atol=atol)
      return gs.power(dist, 2)
  
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 5 for calling the ComplexPoincareDiskMetric obj's underlying member method code with example usage: obj.squared_dist(point_a, point_b, atol) and returns: gs