code: def corr2_coeff(A, B):
      """
      Compute correlation coefficients and return as a np array
      """
      A, B = np.array(A), np.array(B)
      # Rowwise mean of input arrays & subtract from input arrays themeselves
      A_mA = A - A.mean(1)[:, None]
      B_mB = B - B.mean(1)[:, None]
  
      # Sum of squares across rows
      ssA = (A_mA**2).sum(1)
      ssB = (B_mB**2).sum(1)
  
      # Finally get corr coeff
      return np.dot(A_mA, B_mB.T) / np.sqrt(
          np.dot(ssA[:, None], ssB[None])
      )
  
imports: import matplotlib.pyplot
  import numpy
  import pandas
  from mlxtend.externals.adjust_text import adjust_text
  from mlxtend.feature_extraction import PrincipalComponentAnalysis
label_desc: Use image node_id 1 for calling a global function with example usage: corr2_coeff(A, B) and returns: unknown