Add whitening_seed parameter to MountainSort5#4600
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MountainSort5 whitens the recording before sorting, and the whitening matrix is estimated from randomly-selected data chunks (spikeinterface.preprocessing.whiten -> get_random_data_chunks). Without control of the seed, sorting isn't reproducible, even on identical input. Added a `whitening_seed` parameter (default None, preserves current behavior) that is forwarded to whiten(seed=...). There is still some very small residual indeterminism (on my test recording: 100% of units match, but ~0.04% of spikes differ) between runs with identical input. Not sure where it comes from -- maybe BLAS multithreading?
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Looks good, thanks! |
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MountainSort5 whitens the recording before sorting, and the whitening matrix is estimated from randomly-selected data chunks (
spikeinterface.preprocessing.whiten->get_random_data_chunks).Without control of the seed, sorting isn't reproducible, even on identical input.
Added a
whitening_seedparameter (defaultNone, preserves current behavior) that is forwarded towhiten(seed=...).There is still some very, very small residual indeterminism (on my test recording: 100% of units match, but ~0.04% of spikes differ) between runs with identical input. Not sure where it comes from -- maybe BLAS multithreading? Not worried about it.
Looks okay @magland ?
(The reason I'm trying to get deterministic output is so that I can evaluate whether the lossy
WavPack(bps=2.25)compression that has negligible impact on Neuropixel sortings is also safe for some tetrode recordings. @alejoe91 )