using spike_vector on core/check_sortings_equal test
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alejoe91
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Dec 23, 2025
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| def _sorted_spike_vector(SX): | ||
| spikes = SX.to_spike_vector() | ||
| order = np.lexsort((spikes["sample_index"], spikes["unit_index"], spikes["segment_index"])) | ||
| return spikes[order] |
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I don't think we need this, since to_spike_vector should already return spikes sorted by segment_index + sample_index. Or did you add this to add the sorting by unit_index?
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Pure inattention from me ! I remove it.
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oups. this was needed put it back!!
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vacations will do me good XD
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@tayheau I think we actually needed the unit_index lex sort after all! The reason is that before we were testing spiketrain-by-spiketrain, so the order didn't matter if we had synchronous spikes. Now with the spike vector representation we need to ensure unit_index is sorted too! Sorry about that! :) |
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