WIP: Allow Dredge AP to use online motion resolution method - #4746
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chrishalcrow wants to merge 7 commits into
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WIP: Allow Dredge AP to use online motion resolution method#4746chrishalcrow wants to merge 7 commits into
chrishalcrow wants to merge 7 commits into
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This is amazing! I'll take a look at the code. |
cwindolf
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Sep 2, 2026
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Can't see any issues here, this is great!
| **xcorr_kw, | ||
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| if resolution_mode == "simultaneous": |
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I'd call this "batch" or "offline"? (Just because those are more standard terms in optimization literature for this kind of thing)
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Do you think "resolution_mode" is the right terminology. I struggled with this language.
| bin_s=1 / lfp_recording.sampling_frequency, # only relevant for time_horizon_s | ||
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| P_online = compute_displacement_online( |
| if isinstance(lfp_recording, BaseRecording): | ||
| traces0 = lfp_recording.get_traces(start_frame=t0, end_frame=t1) | ||
| else: | ||
| traces0 = lfp_recording[:, t0:t1].T |
chrishalcrow
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Sep 3, 2026
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The motion correction algorithms in SpikeInterface have two steps. You first compute many histograms-in-depth (using e.g. peak detection or LFP) over time. Second, you compare the histograms at different times to extract a time vector.
In the current implementation, if you use peak detection the comparison part of the algorithm compares ALL histograms against all others. This is fine if you have a standard recording, but fills up RAM quickly if you get towards one day long recordings. If you use LFP there is an "online" method to compare the histograms. This only compares histograms which are nearby in time, meaning that you don't need to load them all into memory. Hence, this can be used for very long recordings.
This PR refactors the "all at once" and "online" methods to extract motion vectors from histograms, allowing either method to be used regardless of histogram-construction method. Most of the pain is in how parameters are dealt with - they were packaged a bit differently for the two algorithms. We attempt to unify the arguments in the two methods as much as possible, and abstract some language.
Docs, tests, etc incoming.
I spent a while understanding the parameters and all the kwarg dicts. Here's a summary:
Parameters
User can give
dredge_apanddredge_online_lpfthe following dicts:thomas_kw: passed to
thomas_solvexcorr_kw: passed to
xcorr_windowsInside the functions, we set the following kwarg dicts:
full_xcorr_kw
weights_kw (passed to
weight_correlation_matrixin AP, just used to getmincorrin LFP)threshold_kw (passed to
threshold_correlation_matrix). We set: