On Tue, Nov 13, 2012 at 2:27 AM, Austin Bingham <[email protected]>wrote:
> OK, if numpy is just subject to Python's behavior then what I'm seeing > must be due to the vagaries of Python. I've noticed that things like > removing a particular line of code or reordering seemingly unrelated calls > (unrelated to the memory issue, that is) can affect when memory is reported > as free. I'll just assume that everything is in order and carry on. Thanks! > > If you are running interactively in IPython, references will be kept to return values. That can eventually eat up memory if you are working with a lot of big arrays. <snip> Chuck
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