No thoughts on optimizing memory, but that indexing error probably comes from np.mean producing float results. An astype call shoulder that work.

-CHB

Sent from my iPhone

On Sep 15, 2017, at 5:51 PM, Robert McLeod <robbmcleod@gmail.com> wrote:


On Fri, Sep 15, 2017 at 2:37 PM, Elliot Hallmark <Permafacture@gmail.com> wrote:

Nope. Numpy only works on in memory arrays. You can determine your own chunking strategy using hdf5, or something like dask can figure that strategy out for you. With numpy you might worry about not accidentally making duplicates or intermediate arrays, but that's the extent of memory optimization you can do in numpy itself.


NumPy does have it's own memory map variant on ndarray:

https://docs.scipy.org/doc/numpy/reference/generated/numpy.memmap.html



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