[Matplotlib-users] Development advice needed

[Jianbao T. <jia...@gm...>]

Dear all,

As some of you might have noticed, I am asking questions frequently
recently, most of which are naive ones. The reason for this is that I
recently decided to develop a  satellite data viewer with matplotlib, and I
am new to both python and matplotlib.

Here is a little background of this decision. I am a postdoc in the space
physics field, where a lot of people watch and analyze satellite data for a
living. The data are time-series data by nature. As for now, a lot of
people use packages based on IDL to navigate their data. I myself is one of
them too. For now. :-) One big problem with IDL is that it is very
expensive because it doesn't have a broad enough user base to drive their
cost down. Another big problem is that the company that is developing IDL
doesn't seem to work in the right direction. For example, more than 99% of
the time of more than 99% of the IDL users use the so-called direct
graphics system in IDL, but IDL hasn't upgraded this system since, I don't
know, maybe early 90s. Compared to what matplotlib can offer, the on-screen
graphics quality of the IDL direct graphics is simply "ugly", which is a
big reason why I want to switch to matplotlib. There are also some other
frequently-used nice features in matplotlib that IDL doesn't have.

After reading the matplotlib documents and trying out several little
examples for a few days, I now have a feeling that matplotlib at least has
most of the infrastructure ready for my purposes. One thing that bothers me
a little bit is that the plotting speed seems to be a little slow. But IDL
had the same problem in the first place too. As computers became faster and
faster, that problem just became less and less important. I expect the same
thing will happen to matplotlib too.

Now let me turn to technical stuff. What I want is a time-series plotting
system like the following. First, it manages all the figure windows it
generates, including the positions and looks of the figure windows. A
common use case for such a system would be that the user is also analyzing
the data while watching the time-series data,and hence the user likely
needs to plot some temporary results, such as a snapshot of particle
distribution function, but doesn't want to screw up the time-series plot.
Therefore, it will be nice that the plotting windows of the time-series
data are managed particularly. Second, it should come with a navigation
toolbar that facilitates the data navigation. The current navigation
toolbar widget is nice and probably suit more than 50% percent of my needs,
but it's not sufficient. Third, the system should have minimal dependencies
for the sake of portability and installation easiness. As for now, I don't
want any dependencies beyond numpy, scipy, and matplotlib. Ipython would be
a highly recommended tool, but the system should be just fine without it.

After weighing all the options, I sense that I will probably be better off
to use the matplotlib library directly, rather than the convenient
utilities provided by pyplot. However, I am having a hard time to find good
instructions for using the matplotlib infrastructure. So, I would like to
hear some references on that. I also would like to hear general advice
about how to construct such a system so that its structure is consistent
with matplotlib conventions. Other comments and advice are warmly welcome
too. :-)

Thank you very much for reading this far.

Jianbao