code: def _loadedges(self) -> typing.Tuple[np.ndarray, np.ndarray, np.ndarray, float, np.ndarray]:
          
          data = sco.loadmat(self.filename)
          datakeys = [k for k in data.keys()
                      if ('right' in k) or ('left' in k) or ('edge' in k)]
          averagedata = ((data[datakeys[0]] + data[datakeys[1]]) / 2)
  
          try:
              times = (data['times'] - data['times'].min())[0]
          except KeyError:
              times = np.arange(len(data[datakeys[0]][0]))
  
          try:
              accept = data['accept']
          except KeyError:
              accept = np.zeros(len(times))
  
          try:
              ratio = data['ratio']
          except KeyError:
              ratio = 1
  
          try:
              viscosity = data['viscosity']
          except KeyError:
              viscosity = np.ones(len(times))
          return averagedata, times, accept, ratio, viscosity
docs: Attempts to intelligently load the .mat file and take average of left and right edges
  
          :return: left and right averages
          :return: times for each column
          :return: accept/reject for each column
          :return: pixel-inch ratio