code: def median(embedding, neighbors, verbose=False):
      """Initialize points onto an existing embedding by placing them in the
      median position of their nearest neighbors on the reference embedding.
  
      Parameters
      ----------
      embedding: TSNEEmbedding
      neighbors: np.ndarray
      verbose: bool
  
      Returns
      -------
      np.ndarray
  
      """
      with utils.Timer(
          "Calculating meadian initialization...", verbose
      ):
          embedding = np.median(embedding[neighbors], axis=1)
      return np.ascontiguousarray(embedding)
  
file_path: openTSNE/openTSNE/initialization.py
imports: import numpy
  import scipy.sparse
  from sklearn.decomposition import PCA
  from sklearn.utils import check_random_state
  from openTSNE import utils
label_desc: Use image node_id 7 for calling a global function with example usage: median(embedding, neighbors, verbose) and returns: np