class_docstr: Class for the Siegel metric.
class_docstr_tok: ["Class","for","the","Siegel","metric","."]
docstr: Compute the Siegel exponential map.
  
  Compute the exponential map at base_point of tangent_vec.
  
  Parameters
  ----------
  tangent_vec : array-like, shape=[..., n, n]
      Tangent vector at base point.
  base_point : array-like, shape=[..., n, n]
      Point on the manifold.
  
  Returns
  -------
  exp : array-like, shape=[..., n, n]
      Point on the manifold.
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code: def exp(self, tangent_vec, base_point):
      """Compute the Siegel exponential map.
  
      Compute the exponential map at base_point of tangent_vec.
  
      Parameters
      ----------
      tangent_vec : array-like, shape=[..., n, n]
          Tangent vector at base point.
      base_point : array-like, shape=[..., n, n]
          Point on the manifold.
  
      Returns
      -------
      exp : array-like, shape=[..., n, n]
          Point on the manifold.
      """
      tangent_vec_at_zero = self.tangent_vec_from_base_point_to_zero(
          tangent_vec=tangent_vec, base_point=base_point
      )
  
      exp_zero = self.exp_at_zero(tangent_vec_at_zero)
  
      return self.isometry(point=exp_zero, point_to_zero=-base_point)
  
imports: import geomstats.backend
  from geomstats.geometry.base import ComplexVectorSpaceOpenSet
  from geomstats.geometry.complex_matrices import ComplexMatrices
  from geomstats.geometry.complex_riemannian_metric import ComplexRiemannianMetric
  from geomstats.geometry.hermitian_matrices import expmh, powermh
  from geomstats.geometry.matrices import Matrices
label_desc: Use image node_id 5 for calling the SiegelMetric obj's underlying member method code with example usage: obj.exp(tangent_vec, base_point) and returns: self