code: def mtFeatureExtractionToFile(fileName, midTermSize, midTermStep, shortTermSize, shortTermStep, outPutFile,
                                storeStFeatures=False, storeToCSV=False, PLOT=False):
      
      [fs, x] = audioBasicIO.readAudioFile(fileName)
      x = audioBasicIO.stereo2mono(x)
      if storeStFeatures:
          [mtF, stF, _] = mtFeatureExtraction(x, fs,
                                           round(fs * midTermSize),
                                           round(fs * midTermStep),
                                           round(fs * shortTermSize),
                                           round(fs * shortTermStep))
      else:
          [mtF, _, _] = mtFeatureExtraction(x, fs, round(fs*midTermSize),
                                         round(fs * midTermStep),
                                         round(fs * shortTermSize),
                                         round(fs * shortTermStep))
      # save mt features to numpy file
      numpy.save(outPutFile, mtF)
      if PLOT:
          print("Mid-term numpy file: " + outPutFile + ".npy saved")
      if storeToCSV:
          numpy.savetxt(outPutFile+".csv", mtF.T, delimiter=",")
          if PLOT:
              print("Mid-term CSV file: " + outPutFile + ".csv saved")
  
      if storeStFeatures:
          # save st features to numpy file
          numpy.save(outPutFile+"_st", stF)
          if PLOT:
              print("Short-term numpy file: " + outPutFile + "_st.npy saved")
          if storeToCSV:
              # store st features to CSV file
              numpy.savetxt(outPutFile+"_st.csv", stF.T, delimiter=",")
              if PLOT:
                  print("Short-term CSV file: " + outPutFile + "_st.csv saved")
docs: This function is used as a wrapper to:
      a) read the content of a WAV file
      b) perform mid-term feature extraction on that signal
      c) write the mid-term feature sequences to a numpy file