On 2012/09/09 8:50 AM, Benjamin Root wrote:
>
>
> On Wed, Aug 15, 2012 at 5:40 AM, Jesper Larsen <jes...@gm...
> <mailto:jes...@gm...>> wrote:
>
> Hi Matplotlib users
>
> I have an application where performance is critical and matplotlib is
> the performance bottleneck. I am making a lot of figures using the
> same basic setup of the figure. And from my profiling I can see that
> this basic setup accounts for most of the CPU time. Let us say that I
> make a given figure including some axes. My questions are:
>
> 1. Can I make a copy of this figure including axes (copy.deepcopy does
> not work on Figure objects) and use the copy for plotting on?
>
> 2. And how? Should I use the frozen method somehow?
>
> I did do something similar some years back. But at the time I removed
> the stuff I had drawn on the figure. I would like to avoid this for
> two reasons: 1) Thread safety, I must be able to draw figures in
> several simultaneous threads and 2) I really had to go into some
> low-level details in matplotlib (not a show-stopper, but for
> maintenance reasons I would like to keep the code as clear as
> possible).
>
> Best regards,
> Jesper
>
>
> Jesper,
>
> An experimental feature that will be available in the upcoming v1.2.0
> release will be pickling support. It is marked as experimental as there
> are plenty of untested edge cases, but it should be a huge step in the
> right direction for the feature that you and many others have asked
> for. We certainly will welcome any and all feedback on what does and
> does not pickle well.
>
> Cheers!
> Ben Root
Some benchmarking would be useful as well. Pickling/unpickling can be
very slow.
Eric
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