class_docstr: Use a precomputed affinity matrix.
  
  Parameters
  ----------
  affinities: scipy.sparse.csr_matrix, np.ndarray
      An N x N matrix containing the affinities.
  normalize: bool
      Normalize the affinity matrix to sum to 1. Default is True.
class_docstr_tok: ["Use","a","precomputed","affinity","matrix",".","Parameters","--","--","--","--","--","affinities",":","scipy.sparse.csr_matrix",",","np.ndarray","An","N","x","N","matrix","containing","the","affinities",".","normalize",":","bool","Normalize","the","affinity","matrix","to","sum","to","1",".","Default","is","True","."]
code: def to_new(self, data, return_distances=False):
      raise RuntimeError(
          "Precomputed affinity matrices cannot be queried."
      )
  
imports: import logging
  import numbers
  import operator
  from functools import reduce
  import numpy
  import scipy.sparse
  from openTSNE import _tsne
  from openTSNE import nearest_neighbors
  from openTSNE import utils
  from openTSNE.utils import is_package_installed
  import warnings
label_desc: Use image node_id 2 for calling the PrecomputedAffinities obj's underlying member method code with example usage: obj.to_new(data, return_distances) without return types