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Use a pattern of small (e.g. 100 x 100) blocks that might 10s of seconds / a few minutes to compute
this should work better than doing a whole row or column that might have 20-50k neurons.
need to implement an x by y nblast function instead of all by all NBLAST for each block (would current NBLAST be ok?)
inputs could be neuronlistfh and read in for each process. I suspect that read time will be trivial compared with search time so long as blocks take 10s of seconds to compute. This might work well for memory.
ideally we would parallelise across those blocks with progress
if doing mean scores, we might want to do forward and reverse scores at the same time since they use the same sets of neurons
we might wish to fill a sparse matrix with the results with a threshold
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The text was updated successfully, but these errors were encountered: