[Numpy-discussion] Managing Rolling Data
Wed Feb 21 16:20:25 CST 2007
If none of the suggested methods turn out to be efficient enough due to
copying overhead, here's a way to reduce the copying overhead by trading
memory (and a bit of complexity) for copying overhead. The general thrust is
to allocate M extra slices of memory and then shift the data every M time
slices instead of every time slice.
First you would allocate a block of memory N*P*(H+M) in size.
>>> buffer = zeros([H+M,N,P], float)
Then you'd look at the first H time slices.
>>> data = buffer[:H]
Top pop one piece of data off the stack you'd simply shift data to look at a
different place in the buffer. The first time, you'd have something like
>>> data = buffer[1:1+H]
Every M time steps you need to recopy the data. I expect that this should
reduce your copying overhead a bunch since your not copying as frequently.
It's pretty tunable too. You'd want to wrap some convenience functions
around stuff to automate the copying and popping, but that should be easy
I haven't tried this though, so caveat emptor.
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