# Unsynchronized time series visualization

I would like to visualize a large amount of events composed of time serie windows. A typical event would be:

Problem is, my events are not synchronized, and so if I plot them all, it would look like:

Question
Is there any way to visualize all my events so I can see their original/"typical" shape (preferably in the time domain) despite their unsynchronization ?

What I have tried so far:

• Visualize features: approach is good but I have to guess what I am looking for.
• Synchronized events: in the example above it might be possible, but for some other cases it won't be. (such as multiple peaks spaced with different time lapses)
• Use statistical values to visualize: that was my first shot, to plot not all events but only their mean, median, p95,... Problem is, using this approach gives a deformed rendering of the data because of the unsynchronization:

The main problem of applying the mean, p95 or whatever statistical function is that it is applied along an axis that is not synchronized between events. I don't know if it exists or if it is even feasible, but I was thinking about an approach that would display those statistical values checking their temporal neighbors ? I know Dynamic Time Warping deals with this unsynchronization but I am not sure if and how I could use it to plot my events in the way I'd like.
An idea of a possible output could be (any other output idea is welcomed!):

Any help, idea, would be greatly appreciated ! Thanks

– WBM
Feb 26 '21 at 10:39
• Thanks @WBM, how would you do use DTW to display a graph like the last one ? Have you seen raw data visualization based on DTW ? Feb 26 '21 at 10:43
• So you use DTW to cluster the clips in time (or warp them so they're aligned) and then you create an average of those clusters which would be your ideal_sig in the final image
– WBM
Feb 26 '21 at 10:46
• Thanks, I think I see your point, I will dig into it and try to build a function that does that Feb 26 '21 at 11:20