On Sun, Nov 16, 2008 at 10:03 AM, mhampton <[EMAIL PROTECTED]> wrote:
>
> I think this sounds great, I give a hearty +1.
>
> I've gotten frustrated in the past by the plotting code. Being "more
> closely tied to matplotlib" would be nice for lots of reasons.
I as well support utilizing matplotlib way more. I wrote a lot of that plotting
code almost 3 years ago and in the meantime have watched matplotlib
continually get
better and better. Their code is far better the (naive) stuff I wrote
way back then.
A big +1 for going with matplotlib as much as possible.
-Alex
The
> matplotlib documentation is pretty good, and maybe some of what we do
> could find its way upstream in Mike's approach. Its a similar
> situation to how I feel about the preparser and leaving python types
> alone - its a good thing to stay as close to python as possible.
>
> Many cheers for working on this!
>
> -Marshall
>
> On Nov 17, 11:23 am, "Mike Hansen" <[EMAIL PROTECTED]> wrote:
>> Hello,
>>
>>
>>
>> On Sat, Nov 15, 2008 at 11:06 AM, Ronan Paixão <[EMAIL PROTECTED]> wrote:
>>
>> > Em Sex, 2008-11-14 às 16:22 -0200, Ronan Paixão escreveu:
>> >> I recently thought about implementing more functions used by non-math
>> >> people (I'm an Electronic Engineering student).
>>
>> >> I started by trying to make a Bode plot, but after a lot of digging to
>> >> find how to make subplots and how to use logarithmic scale in plot(), I
>> >> found that if applying that kind of scale can turn plot() unusable.
>>
>> >> The first problem is that the adaptive choosing of points just considers
>> >> linear scale, so the points get too much spaced apart in the beginning
>> >> of the plot and too close in the end.
>>
>> >> The second problem relates to the axis, which, for the same reason,
>> >> isn't located right.
>>
>> >> to test it, one can try:
>>
>> >> p=plot(x,marker='.')
>> >> f=pylab.figure()
>> >> f.gca().set_xscale('log')
>> >> p.save(figure=f)
>>
>> >> So, I intend to implement the changes in plot() to support it.
>> >> For that, I ask YOU (uncle sam pointing finger) sage gurus how to better
>> >> implement that: would it be better to try check if the user used a
>> >> custom figure() with different axis or would it be better to add another
>> >> kwarg like log="xy" where "x" would make the x axis logarithmic and "y"
>> >> likewise for the y axis, avoiding the need for the user to deal with
>> >> matplotlib's figure()?
>>
>> After thinking about this (and the plotting code in general), I think
>> our best bet is to scrap the custom axes code written in
>> sage/plot/axes.py and to let matplotlib handle axes, ticks, etc.
>> They've thought about and worked on this problem and have developed a
>> fairly robust solution. Most of the axes code hasn't been touched in
>> over 2 years despite complaints (
>> seehttp://groups.google.com/group/sage-devel/browse_thread/thread/394b2f...
>> ). If we want custom axes, then we should do so by properly
>> subclassing matplotlibs Axes class.
>>
>> Additionally, I think the Graphics wrapper should not be nearly as
>> heavy as it is. In particular, there's no way to get at and modify
>> the matplotlib subplot object. For example, I have some preliminary
>> code that would let one do this:
>>
>> sage: p = plot(e^x, 1, 5)
>> sage: p.subplot.set_xlabel('Mike')
>> <matplotlib.text.Text object at 0x46b8350>
>> sage: p.subplot.set_title('A plot')
>> <matplotlib.text.Text object at 0x46badd0>
>> sage: p.subplot.set_ylabel("Sage")
>> <matplotlib.text.Text object at 0x46ba090>
>> sage: p.save('plot1.png')
>> sage: p.subplot.set_yscale('log')
>> sage: p.save('plot2.png')
>>
>> to produce the following images:
>>
>> http://sage.math.washington.edu/home/mhansen/plot1.pnghttp://sage.math.washington.edu/home/mhansen/plot2.png
>>
>> While this would mean being more closely tied to matplotlib as a
>> backed, I think the benefits are worth it. I don't envision anybody
>> working on another backend for Graphics anytime in the near future.
>>
>> --Mike
> >
>
--
Alex Clemesha
clemesha.org
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