To fit steps into these intensity vs time plots, the concept of "moving average absolute deviation (MAD)" was used. It calculates the absolute difference between a datapoint and the mean of a set of following datapoints (n=30), this gives insights about step movement in the data. As steps were translated to peaks, and to find the peaks automatically, the scipy toolkit "signal.find_peaks" was used. Next, the step height was filtered, to ensure only relevant steps were considered. For this, a threshold was set to a minimal step height of 75% the RMSF (root mean square fluctuation) of the dataset. This procedure resulted in time stems for steps. Finishing, the mean value in between all timesteps was calculated .