On 11/13/12 10:27 AM, Austin Bingham 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!
Profiling memory can be tricky because the operating system may not return memory *immediately* as requested, and it might mislead you in some situations. So do not trust too much in memory profilers to be too exact and rather focus on the big picture (i.e. my app is reclaiming a lot of memory for a large amount o time? if yes, then start worrying, but not before). -- Francesc Alted