Selecting specific (non-random) spikes for waveform calculations

[Sietse-k]

Hi,

I want to compare the waveforms of units in different periods of the recording. Basically, do the waveforms of the same unit look similar during optogenic stimulation periods vs. outside these windows.

Instead of selecting spikes "randomly" in the recording, is there a way to specify which spikes you want to select (based on time intervals)? Or would I always need to slice the recording first into a smaller "sub recording" and then select all spikes within this sub recording, and then use this to compute the waveforms?

analyzer.compute(
    "random_spikes",
    method="uniform",
    max_spikes_per_unit=500,
)
analyzer.compute("waveforms", ms_before=1.0, ms_after=2.0)
analyzer.compute("templates", operators=["average", "median", "std"])

Any help would be much appreciated,

Sietse

[samuelgarcia]

Hi,
the underlying method for "random_spike" is https://github.com/SpikeInterface/spikeinterface/blob/main/src/spikeinterface/core/sorting_tools.py#L156
The plan was to extand this to support many approach : traget specific period, ensure spread over time, explicit indices, ...
At the moment, as you can see, only "uniform" and "all" are implemented.

If you want to implement another method feel free to open a small PR to start discussion.
I known that @yger wanted also to improve this when he has time.