Function for visualising time series attribution

🚀 Feature

Function for visualising time series along with attribution values, just like captum.attr.visualization.visualize_image_attr does for images.

Motivation

Working with time series a lot, I often copy the same plotting function around between projects, so I think it would be great to have a basic 1D plotting method built-in. Since 1D attributions are prepared the same way as for images (normalisation and choice of sign), it would fit in nicely with the existing code. I would be happy to submit a PR with my own (adapted) plotting function, but probably best to first discuss the scope and need.

Pitch

A built-in plotting function would simplify and speed up the model development cycle. But besides convenience, it could also be valuable to new users, since the applicability of Captum to time series is somewhat undercommunicated 😄

Alternatives

Users write their own custom plotting functions. This is likely to happen anyway because of the big variation in different time series’ length, number of channels, etc., but in that case, a built-in function is a good starting point.

Additional context

[smaeland]

Hi @ic085908, here is the script I used to produce the plots shown in #980: visualize_synthetic_data.py (data is randomly generated, so it won’t look exactly identical). Let me know if you run into any problems or find things that could be improved

[smaeland]

Great! I’ll close this then, since the corresponding PR is merged now.