We use compressed spectral array (CSA) as a representation of the resting-state electroencephalogram (rs-EEG) data. Thus, CSA shows super-imposing linear plots of successive epochs of time on each other. The latter generates a 3-dimensional ‘hills and valleys’ display of the power density in a single channel. Of note, as successive epochs are added to the display, information can become hidden behind ‘hills’ of increased power at particular frequencies [1].
In order to overcome the above limitation, an alpha=0.5 transparency parameter is available, as well as a t = np.sqrt(abs(delta))/1.5 tuning parameter to control the height of the peaks.
This Jupyter Notebook includes an implementation of Luc Kuster's Matplotlib-based waterfall plot adapted by @yjmantilla and @alberto-jj for EEG data.
CSA can be plotted in B&W as well as using matplotlib colormaps
[1] Whyte SD, Booker PD. Monitoring depth of anaesthesia by EEG. British Journal of Anaesthesia. 2003; 3(4): 103-10.