docstr: Query the index with new points.
  
  Finds k nearest neighbors from the training data to each row of the
  query data.
  
  Parameters
  ----------
  query: array_like
  k: int
  
  Returns
  -------
  indices: np.ndarray
  distances: np.ndarray
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code: def query(self, query, k):
      """Query the index with new points.
  
      Finds k nearest neighbors from the training data to each row of the
      query data.
  
      Parameters
      ----------
      query: array_like
      k: int
  
      Returns
      -------
      indices: np.ndarray
      distances: np.ndarray
  
      """
  
imports: import logging
  import os
  import warnings
  import numpy
  from scipy.spatial.distance import cdist
  from sklearn import neighbors
  from sklearn.utils import check_random_state
  from openTSNE import utils
label_desc: Use image node_id 3 for calling the KNNIndex obj's underlying member method code with example usage: obj.query(query, k) without return types