code: def naive_cac(I, L, excl_factor, custom_iac=None):
      n = I.shape[0]
      AC = np.zeros(n)
      CAC = np.zeros(n)
      AC = naive_nnmark(I)
      if custom_iac is not None:
          IAC = custom_iac
      else:
          IAC = naive_iac(n)
      CAC = np.minimum(AC / IAC, 1.0)
      CAC[: L * excl_factor] = 1.0
      CAC[-L * excl_factor :] = 1.0
  
      return CAC
  
imports: import functools
  import naive
  import numpy
  import numpy.testing
  import pytest
  from stumpy import aamp, core, floss, fluss, stump
  from stumpy.floss import _cac, _iac, _nnmark, _rea
label_desc: Use image node_id 3 for calling a global function with example usage: naive_cac(I, L, excl_factor, custom_iac) and returns: CAC