Re: [Matplotlib-users] Bug when zooming on multiple lines separated by None

[Eric F. <ef...@ha...>]

On 2012/10/03 8:11 AM, Charleux Ludovic wrote:
> Thanks for your multiple answers. I'll try the same manipulation with
> the 1.2 version as soon as possible. Concerning the debate between the
> use of None and numpy.nan, I tryed both methods before posting and they
> both lead to the same bug on my version. I'm using the None/numpy.nan
> trick to plot finite element 2D meshes (Matplotlib  allows very neat
> vectorial plots) and I often adjust xlim/ylim to magnify interesting
> zones and so this bug is everywhere. I'm not totally sure but I think
> the bug was not present in the 1.0.x versions I tested before.

Please--there is *no* None trick. This is not a debate. Please do *not* 
use None.  Use np.nan or a masked array.  Unless you go into the lower 
levels of the api, mpl will convert a floating-point array with nans 
into a masked array for operations such as auto-scaling.

If you must use an object array (e.g., as Ben notes, if you are using 
datetime objects--it must be something for which there is a registered 
converter, because at the plotting level mpl works with floats), then 
make it a masked array if you need to put gaps in it.  If that does not 
work, then it is a bug in the conversion process.  Masked arrays should 
work for any input type supported by mpl.

Eric

>
> Regards.
>
> Ludovic Charleux
>
> 2012/10/3 Benjamin Root <ben...@ou... <mailto:ben...@ou...>>
>
>
>
>     On Wed, Oct 3, 2012 at 1:02 PM, Phil Elson <pel...@gm...
>     <mailto:pel...@gm...>> wrote:
>
>         I don't get this on matplotlib/master (and therefore probably
>         not on 1.2rc2).
>
>         I'm pretty sure masked array line plotting was fixed at some
>         point this release cycle (I cannot find the appropriate github
>         issue to link to), so I suggest this is a known bug with 1.1.1
>         and fixed in 1.2. Just to be clear, I am using the TkAgg
>         backend, and there is a remote possiblity that this bug is
>         backend dependent. Is there any chance you could test this with
>         the latest release candidate?
>
>         Many Thanks,
>
>
>     This issue may be dependent upon which version of Numpy one is
>     using.  As Eric pointed out, one should be getting an object array
>     if you have a None in the list.  On top of that, I wouldn't be
>     surprised if the different backends handled this object array
>     differently.
>
>     As far as I am concerned, using None in the list is the bug and is
>     not only unsupported, but should be actively discouraged.  Use NaNs
>     or masked arrays instead.
>
>     (and to ward off the inevitable question, I would advise against
>     explicitly checking for object arrays because there are times when
>     it is correct to have such arrays, i.e., python decimal or datetime
>     objects).
>
>     Cheers!
>     Ben Root
>
>
>
>
>
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