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Well, indeed, the second link relies on PR #263 which solves the issue. Here is the original notebook (using filterpy 1.4.5 from pypi). As you can see, the non handling of NaN causes problems and is not really compatible with a numpy approach.
Note that the PR has not been merged so the issue cannot be closed.
I want to switch from pykalman to filterpy because the later is not maintained anymore.
I try to reproduce a basic filtering and smoothing example that I did with pykalman (original code from Anton):
linear_case_pykalman.ipynb
However, I struggle to make it work with filterpy and I do not really get why... It has to do with missing values handing I guess.
linear_case_filterpy.ipynb
Thanks in advance for the help !
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