Memory usage with matplotlib

Steve Chaplin: I read the link about memory management you

    > indicated. It is very good and you are right in pointing
    > the differences between "collecting" and "freeing"
    > memory. Anyway, let me try to expose the problem once more
    > (sorry for the length).

So on reading this is does not appear that you have a memory leak, but
that you are using too much memory, ie the total memory consumed by
your 15 open figures is dragging your system down. But when you close
the figures, the memory usage cycles back down. Eg you started and
ended cycle 1 with about 70M consumed, and peaked around 150M.

Is this an accurate description of your problem?

There are definitely areas where we can and should improve memory use,
but this would have to be handled on a case by case basis and would in
some cases be backend dependent.

JDH

John,
As I've said before, since I don't understand the internals
of Python and MPL, I can only describe the "external effect"
(as seen by a novice user) of the problem which
is the large memory usage observed (which drags the system down).
The other "external effect" is that the memory doesn't seem
to be fully recovered at the end of the process. I'm not sufficiently
qualified to state that there exist a memory leak.
Thanks,
Clovis

···

    > Steve Chaplin: I read the link about memory management you
    > indicated. It is very good and you are right in pointing
    > the differences between "collecting" and "freeing"
    > memory. Anyway, let me try to expose the problem once more
    > (sorry for the length).

So on reading this is does not appear that you have a memory leak, but
that you are using too much memory, ie the total memory consumed by
your 15 open figures is dragging your system down. But when you close
the figures, the memory usage cycles back down. Eg you started and
ended cycle 1 with about 70M consumed, and peaked around 150M.

Is this an accurate description of your problem?

There are definitely areas where we can and should improve memory use,
but this would have to be handled on a case by case basis and would in
some cases be backend dependent.

JDH

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