code: def corr2_coeff(AB, msk, myrad, bcast_var):
      if not np.all(msk):
          return None
      A, B = (AB[0], AB[1])
      A = A.reshape((-1, A.shape[-1]))
      B = B.reshape((-1, B.shape[-1]))
      corrAB = np.corrcoef(A.T, B.T)[16:, :16]
      classical_within = np.mean(corrAB[0:8, 0:8])
      jazz_within = np.mean(corrAB[8:16, 8:16])
      classJazz_between = np.mean(corrAB[8:16, 0:8])
      jazzClass_between = np.mean(corrAB[0:8, 8:16])
      within_genre = np.mean([classical_within, jazz_within])
      between_genre = np.mean([classJazz_between, jazzClass_between])
      diff = within_genre - between_genre
      return diff
  
file_path: brainiak/examples/searchlight/genre_searchlight_example.py
imports: import numpy
  import time
  from mpi4py import MPI
  from nilearn.image import load_img
  import sys
  from brainiak.searchlight.searchlight import Searchlight
  from scipy import stats
  from scipy.sparse import random
  import os
label_desc: Use image node_id 1 for calling a global function with example usage: corr2_coeff(AB, msk, myrad, bcast_var) and returns: diff, None