I'm trying to find the optimal compression for 2- and 3-dimensional
matrices of recorded data. These data sets contain data that doesn't
change much over time (and time is being used as the first axis). I
thought that by using shuffle, I might get better compression, but
instead the resulting files were larger than without shuffle.
Is shuffle meant to work with compound types? Are there things I need
to be considering in the organization of the axes of the data set in
order to better encourage compression?
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