code: def suggest_channel(data):
      
  #    c_idx = 0
  #    max_chan_mags = 1
      
      import numpy as np
      # Determine how many channels there are, based on the shape of the data channel index
      
      max_chan_mags = np.max(np.average(np.abs(data),axis=0),axis=1)    
      idx = np.argsort(max_chan_mags)
      c_idx = idx[-1]
     
      return c_idx, max_chan_mags
docs: If the use-case is plotting multiple averages collected from the same channel (coil)
      on the same axis, this function suggests a channel to use for plotting raw averages
      based on relative maximum magnitudes of the available channel data.
      
      Parameters
      ----------
      data : array_like
             Data array. Assumed to be formatted as [averages, channels, data_points]
      
      Returns
      -------
      c_idx : integer
              Index of suggested channel to plot
      max_chan_mags : array_like
                      Maximum values of the average
              stuff