[IPython-dev] SVG figures status report

Zoltán Vörös zvoros@gmail....
Tue Jun 26 02:43:44 CDT 2012


Dear Fernando, and Bob,

I didn't want to bring up this issue before the new release, given that 
that has the higher priority, but since a new thread was opened along 
the same lines, I would like to respond to a couple of points raised 
here, and here: 
http://mail.scipy.org/pipermail/ipython-dev/2012-June/009476.html which 
I will quote here.

Based on these two threads, I have the feeling that the views on what an 
interactive plot should do are somewhat diverging, and we should first 
come to some consensus as to what we exactly want.

First, here are a couple of use cases for the notebook (From Fernando's 
comments)

> On Fri, Jun 8, 2012 at 8:49 AM, Bob McElrath<bob+ipython@mcelrath.org  <http://mail.scipy.org/mailman/listinfo/ipython-dev>>  wrote:
> >/  Well I'll just say that IPython and matplotlib have quickly become my primary
> />/  computational tool.  So I would not simply call it an "exploratory" tool.  I
> />/  could already do exploratory computing with the (i)python command line.  The
> />/  notebook allows me to save, repeat/reproduce, and communicate a computation.  In
> />/  particular it allows me to record how I produced the final version of a plot.
> /
> 1. Individual exploratory work: play with some code, some data, ...
> 2. Collaboration with colleagues.  ...
> 3. Parallel production work: ...
>
>   ... if your results do pan out, you'll want to publish them!...
>
> 4. The same notebook can then be exported to latex or html for
> publication.  We're not really at the point of the notebook being what
> you send to a journal, but the notebooks right now are perfect as
> supplementary materials that remain *executable*.

I think, implementing all of these in a single tool is too ambitious, 
and unrealistic, and the requirements are even conflicting. This would 
mean, e.g., that the notebook should be aware of LaTeX packages. But 
since at this point, it uses MathJaX, and since MathJaX does not 
implement the full LaTeX command set, I don't see how this could be 
pulled off. Even worse, many journals require the use of a specific 
stylesheet, and figures have to be submitted as separate files. So, one 
would have to implement at least two separate backends, one for 
interactive work, and one for PDFs...

Also, if executability is a requirement (I think, it is a reasonable 
one), then for plots we are left with js or SVG, that can work as a 
stand-alone figure, without relying on the ipython kernel. Another 
reason for decoupling the plot from the kernel is that in this way, one 
could explore plots in the notebook, while another calculation is 
running in the kernel.

I would like to quote Brian's comments "I would love to see that emerge 
out of matplotlib, rather than YAPL (yet another plotting library).". I 
couldn't agree more. But if this is the case, then there are some major 
modifications to be implemented in matplotlib itself. I think, we have 
already realised that we would have to have access to not only the 
canvas elements, but the underlying data. At this point, there is no 
easy way of exposing those in matplotlib. So, the bottom line is that, 
if this plotting tool is to emerge from matplotlib, then we have to work 
with the matplotlib developers, and we can't just piggyback on what is 
already there. In such a case, however, we would have to have a very 
clear idea as to what is needed, for otherwise, it will be quite hard to 
convince the matplotlib developers.

As I said earlier, after having played with the javascript backend, I 
could implement coordinate reporting, cross-hairs, and grid toggling in 
a standalone file, and more would most probably be not possible. If this 
is enough, then we should just go with that. If not, then the javascript 
backend is not an option, and SVG would not offer significantly more.
> 5. ... With the traditional approaches we've mostly used so far, each of the
> steps above typically required shifting tools completely.  That hurts
> productivity, kills reproducibility, and fundamentally impairs your
> ability to *iterate* on an idea...
In my view, this point is perhaps the most problematic: if the user
is capable of changing a figure significantly, then there's got to be
a mechanism for tracing those changes, otherwise, reproducibility will
be severely compromised, if at a different level. However, implementing
such a tracking mechanism is most certainly a huge undertaking.


On 06/26/2012 06:26 AM, Fernando Perez wrote:
> Hi Bob,
>
> In this spirit, have you had a chance to play with tools like this?
>
> http://paperjs.org/about/
>
> Since it goes directly to the canvas element and is not SVG, I wonder
> if interactive figures built upon it would fare any better than the
> SVG ones.
I have looked at quite a few of the examples, and it seems to me that 
this library is rather CPU-hungry. But it might just be an issue with 
firefox... However, this might be a problem, even if we start from 
matplotlib, and implement a javascript backend from scratch. Static 
plots certainly have the advantage that once produced, they don't 
require CPU resources anymore...
Cheers,
Zoltán

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