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Great discussion.
I think this tangent indicates a need for a section to explain both the
history of pylab, matplotlib.pyplot, and how they relate. (I'm still
confused at what exactly the difference is.)
My perspective is that of a scientist doing numerical analysis who needs to
visualize computational results and compare it to experimental data. I
normally don't have time to get into the interesting computer science
essoterica: what I need are
- a toolkit of HOWTOs;
- a solid reference to the various classes and functions; and
- a comprehensive index.
I also echo the request for a consistency in style: e.g., always use the OO
style as a basis, *supplementing* (i.e., duplicating) with a MATLAB-style as
needed.
When doing dev and programming work in python, I find myself constantly
refering to Martelli's "Python in a Nutshell" (2nd ed., but often using the
index from the 1st ed. because it's soooooo much better). At times I also
find Martelli & Ascher's "Python Cookbook" invaluable. I think that a good
reference to functions with liberal use of code snippets, combined with a
chapter of short cookbook examples, would be most useful for the Matplotlib
book.
Tell the gent who floated you the proposal that I'm looking forward to
purchasing the book. Oh, and please hurry up with the publication! :-)
James
On Monday 05 January 2009 17:48:43 Christopher Barker wrote:
> Sandro Tosi wrote:
> > So you suggest to start from matplotlib.pyplot and not from pylab?
>
> actually, I think matpoltlib.pyplot still has all of pylab in it, just
> not all of numpy also. So yes, do that, but what I meant was to focus on
> using the OO interface, rather than the state machine interface:
>
> rather than 'gca', 'gcf', etc, store references to the figures and axis,
> etc:
>
> this kind of thing:
>
> fig = plt.Figure()
>
> ax = fig.add_subplot(111)
> ax.plot([1,2,3])
>
> ax.set_title('hi mom')
>
> ax.grid(True)
>
> ax.set_xlabel('time')
> ax.set_ylabel('volts')
>
> While we are at it, discourage the use of "import *" !
>
> -Chris
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