optimise for memory for very large all by all NBLAST

[jefferis]

• 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