code: def poincare(u, v):
      r"""Poincare distance.
  
      ..math::
          \delta (u, v) = 2 \frac{ \lVert  u - v \rVert ^2 }{ ( 1 - \lVert  u \rVert ^2 ) ( 1 - \lVert  v \rVert ^2 ) }
          D(x, y) = \operatorname{arcosh} (1+\delta (u,v))
      """
      sq_u_norm = np.sum(u * u)
      sq_v_norm = np.sum(v * v)
      sq_dist = np.sum(np.power(u - v, 2))
      return np.arccosh(
          1 + 2 * (sq_dist / ((1 - sq_u_norm) * (1 - sq_v_norm)))
      )
  
imports: import numba
  import numpy
  import scipy.stats
  from sklearn.metrics import pairwise_distances
label_desc: Use image node_id 12 for calling a global function with example usage: poincare(u, v) and returns: np