class_docstr: NearestNDInterpolator(x, y)
  
  Nearest-neighbour interpolation in N dimensions.
  
  .. versionadded:: 0.9
  
  Methods
  -------
  __call__
  
  Parameters
  ----------
  x : (Npoints, Ndims) ndarray of floats
      Data point coordinates.
  y : (Npoints,) ndarray of float or complex
      Data values.
  rescale : boolean, optional
      Rescale points to unit cube before performing interpolation.
      This is useful if some of the input dimensions have
      incommensurable units and differ by many orders of magnitude.
  
      .. versionadded:: 0.14.0
  tree_options : dict, optional
      Options passed to the underlying ``cKDTree``.
  
      .. versionadded:: 0.17.0
  
  
  Notes
  -----
  Uses ``scipy.spatial.cKDTree``
docstr: Evaluate interpolator at given points.
  
  Parameters
  ----------
  xi : ndarray of float, shape (..., ndim)
      Points where to interpolate data at.
docstr_tok: ["Evaluate","interpolator","at","given","points",".","Parameters","--","--","--","--","--","xi",":","ndarray","of","float",",","shape","(","...",",","ndim",")","Points","where","to","interpolate","data","at","."]
code: def __call__(self, *args):
      """
      Evaluate interpolator at given points.
  
      Parameters
      ----------
      xi : ndarray of float, shape (..., ndim)
          Points where to interpolate data at.
  
      """
      xi = _ndim_coords_from_arrays(args, ndim=self.points.shape[1])
      xi = self._check_call_shape(xi)
      xi = self._scale_x(xi)
      dist, i = self.tree.query(xi)
      return self.values[i]
  
file_path: catboost/contrib/python/scipy/py2/scipy/interpolate/ndgriddata.py
imports: from __future__ import division, print_function, absolute_import
  import numpy
  from .interpnd import LinearNDInterpolator, NDInterpolatorBase, CloughTocher2DInterpolator, _ndim_coords_from_arrays
  from scipy.spatial import cKDTree
label_desc: Use image node_id 2 for calling the NearestNDInterpolator obj's underlying member method code with example usage: obj.__call__() and returns: self