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Hey Travis,
I was trying your code out and found that I had to first convert the input data to Float64
to avoid an a type error with gemm
. It might be nice to add some more methods that can take care of this.
I needed to install StatsBase to run this code on Julia v0.6 (not sure about v0.5).
I hope you don't mind these issues I am opening up. The exact DMD function is pretty slow for me because my data is about 15000 samples with 2500 features. I did some profiling and the lines involving transpose
are the most expensive steps. I think julia arrays are memory-contiguous along the columns, so one solution would be to assume that the data is already given with time as the second index. Most datasets I have worked with are stored on disk in this way anyway.
I am not sure what the best choice is in terms of memory layout for the optimized DMD solvers though.
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