code: def _self_join_or_not_preprocess(tsA, tsB, m):
      """
      Core method for determining if a self join is occuring and returns appropriate
      profile and index numpy arrays with correct dimensions as all np.nan values.
  
      Parameters
      ----------
      tsA: Time series containing the queries for which to calculate the Matrix Profile.
      tsB: Time series to compare the query against. Note that, if no value is provided, ts_b = ts_a by default.
      m: Length of subsequence to compare.
      """
      n = len(tsA)
      if tsB is not None:
          n = len(tsB)
  
      shape = n - m + 1
  
      return (np.full(shape, np.inf), np.full(shape, np.inf))
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  from .None import distanceProfile
  from .None import order
  from .utils import mass, movmeanstd
  import numpy
  import multiprocessing
  from functools import partial
  import math
  from .scrimp import scrimp_plus_plus
label_desc: Use image node_id 4 for calling a global function with example usage: _self_join_or_not_preprocess(tsA, tsB, m) and returns: np,  np