code: def getAvgBySweep(abf,feature,T0=None,T1=None):
      
      if T1 is None:
          T1=abf.sweepLength
      if T0 is None:
          T0=0
      data = [np.empty((0))]*abf.sweeps
      for AP in cm.dictFlat(cm.matrixToDicts(abf.APs)):
          if T0<AP['sweepT']<T1:
              val=AP[feature]
              data[int(AP['sweep'])]=np.concatenate((data[int(AP['sweep'])],[val]))
      for sweep in range(abf.sweeps):
          if len(data[sweep])>1 and np.any(data[sweep]):
              data[sweep]=np.nanmean(data[sweep])
          elif len(data[sweep])==1:
              data[sweep]=data[sweep][0]
          else:
              data[sweep]=np.nan
      return data
docs: return average of a feature divided by sweep.