code: def find_peakset(dataset, basecolumn=-1, method='', where=None):
      
      peakset = []
      where_i = None
      for data in dataset:
          base = data[basecolumn]
          base = maidenhair.statistics.average(base)
          # limit data points
          if where:
              adata = [maidenhair.statistics.average(x) for x in data]
              where_i = np.where(where(adata))
              base = base[where_i]
          # find peak index
          index = getattr(np, method, np.argmax)(base)
          # create peakset
          for a, axis in enumerate(data):
              if len(peakset) <= a:
                  peakset.append([])
              if where_i:
                  axis = axis[where_i]
              peakset[a].append(axis[index])
      peakset = np.array(peakset)
      return peakset
docs: Find peakset from the dataset
  
      Parameters
      -----------
      dataset : list
          A list of data
      basecolumn : int
          An index of column for finding peaks
      method : str
          A method name of numpy for finding peaks
      where : function
          A function which recieve ``data`` and return numpy indexing list
  
      Returns
      -------
      list
          A list of peaks of each axis (list)