13 Nov
2012
13 Nov
'12
6:52 a.m.
On Tue, Nov 13, 2012 at 2:27 AM, Austin Bingham
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