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Within half the filtering window of a nan-value, the speed is set to 0. Since immobility is often used as a parameter in behavioral analysis, I think it would be better to have the speed set to np.nan instead.
Additionally, I found that if a dataset has multiple scorers that have the same bodypart, it also produces interesting intermediate result and throws an error. I know this rarely happens, but it should be easy to fix.
Within half the filtering window of a nan-value, the speed is set to 0. Since immobility is often used as a parameter in behavioral analysis, I think it would be better to have the speed set to np.nan instead.
Additionally, I found that if a dataset has multiple scorers that have the same bodypart, it also produces interesting intermediate result and throws an error. I know this rarely happens, but it should be easy to fix.
I visualized both issues in a jupyter notebook that I used for testing
I think I have a solution for both (see jupyter notebook) and would be happy to contribute!
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