If your immediate need is to analyze data and produce plots, take a look at
the R statistical language or the Gri plotting system. Both are shorter paths
to a solution of analyzed and plotted data.
I switched to Python just because I need more than simply this. What I
described is the *main* thing my application must do, but we need an
integrated app that, for example, loads and converts data from the
instrument application file format, can save it in another format, can
save data stats, produce illustrations, interface with the operating
system and so on. I'm sure other packages can deal with it, but I feel
Python has a much cleaner and complete interface for this all. Our data
analysis is quite complex and requires automatization of a lot of tasks.
We must deal with a LOT of data and keep them and their results
automatically organized. We even need a basic plugin architecture,
probably (quite complex here to explain why). We were used to solve it
all with a bunch of Matlab scripts but they quickly become unmanageable.
I could rewrite them in Matlab (I wouldn't like it for license reasons,
but I can deal with it...) (or Octave, or Scilab) but (1)Matlab is very
good at math/plots, and has excellent interactivity but s**ks when
applied to other needs (2)I am quite comfortable with Python, although
it's a lot I don't seriuosly code in it; I would have to learn R or Gri
or Scilab basics instead (3)We need elegant, readable code that can be
used and extended by many: me and most of my collegues know or at least
can easily learn Python, and figuring out Python is really easy.
Nevertheless, I promise I'll have a look to R and Gri, but I tested
scipy and matplotlib these days, and I'm pretty convinced they are the
way to go. Note that, despite I like Python very much, I was really
skeptical before actually trying these two packages, so it's not fanboying.
University of Bologna
Department of Biochemistry "G.Moruzzi"
Via Irnerio 48, 40126 Bologna, Italy