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

def suggest_channel(data):
    """
    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
           
    
    
    """
#    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