docs: def sweep_channels_slow(self, sampling_window_ms, n_sampling_windows,
                              delay_between_windows_ms, interleave_samples,
                              use_rms, channel_mask):
          '''
          Measure voltage across load of each of the following control board
          feedback circuits:
  
           - Reference _(i.e., attenuated high-voltage amplifier output)_.
           - Load _(i.e., voltage across DMF device)_.
  
          For each channel in the channel mask. The measured voltage _(i.e.,
          ``V2``)_ can be used to compute the impedance of the measured load, the
          input voltage _(i.e., ``V1``)_, etc.
  
          **N.B.,** Use one firmware call per channel, as opposed to scanning all
          channels with a single firmware call as in :meth:`sweep_channels`
          method.
  
          Returns
          -------
          pandas.DataFrame
              Table containing one actuation RMS measurement and one device load
              impedance measurement per row and the columns ``frequency``,
              ``voltage``, ``channel_i``, ``V_actuation``, ``capacitance``, and
              ``impedance``.
  
              Rows are indexed by time since first measurement in frame.
          '''
          channel_count = len(channel_mask)
          scan_count = sum(channel_mask)
  
          frames = []
  
          print ''
          scan_count_i = 0
          # Iterate through channel mask, measuring impedance for each selected
          # channel in the mask.
          for channel_i, state_i in enumerate(channel_mask):
              if state_i:
                  scan_count_i += 1
                  print '\rMeasure impedance: {} ({}/{})'.format(channel_i,
                                                                 scan_count_i,
                                                                 scan_count),
                  channel_states_i = [0] * channel_count
                  channel_states_i[channel_i] = 1
                  start_time_i = datetime.utcnow()
                  feedback_results_i = \
                      self.measure_impedance(sampling_window_ms,
                                             n_sampling_windows,
                                             delay_between_windows_ms,
                                             interleave_samples, use_rms,
                                             channel_states_i)
                  # Convert custom feedback results object into a
                  # `pandas.DataFrame`.
                  df_result_i =\
                      feedback_results_to_impedance_frame(feedback_results_i)
                  df_result_i.insert(2, 'channel_i', channel_i)
                  df_result_i.insert(0, 'utc_start', start_time_i)
                  frames.append(df_result_i)
          print ''
  
          if not frames:
              df_result = pd.DataFrame(None, columns=['utc_start', 'seconds',
                                                      'channel_i', 'frequency',
                                                      'V_actuation',
                                                      'capacitance',
                                                      'impedance'])
          else:
              df_result = pd.concat(frames)
          return df_result