Hi, On Fri, 14 Oct 2005, Stuart Prescott wrote:
> Hi again, > > thanks for your responses so far -- some interesting ideas > > I had a play with PyX some more yesterday and piped the data through the > aspline utility (package: spline) to get an interpolated smooth curve. > That worked quite nicely for me (using the python pipes object to stream > in the data). I'm quite liking pyx as a concept, although I'm still not > convinced that it's a sustainable approach in the long run. > > But I did realise that it's not particularly efficient to be trying to > do this in python (which I will have to learn to use PyX) instead of > perl (which I am quite comfortable in). Anyone know of a perl graphing > module with the power of PyX? Learning python is not that hard. It takes about half a day to get (more than) the basics: See e.g. - for a quick 6 page start - instant python: http://www.hetland.org/python/instant-python.php - More is offered in the python tutorial http://docs.python.org/tut/tut.html And even more links of course on the docs page of python http://docs.python.org/tut/tut.html This one http://www.hackdiary.com/slides/lpw2004/ discusses python for perl programmers, maybe this helps as well. Personally I even think that you don't have to go through the above, but just learn while creating the graphics. PyX (http://pyx.sourceforge.net/) comes with *many* examples, see e.g. http://pyx.sourceforge.net/examples/graphs/index.html ranging from simple to very sophisticated. Especially, when the data are in files, you just have to do from pyx import * g = graph.graphxy(width=5) g.plot(graph.data.file("two_column_data.dat", x=1, y=2)) g.writeEPSfile("simple") And that's it ;-). The quality, accuracy, and the excellent (La)TeX embedding for the fonts makes it my number 1 choice for real publication quality graphs. (I used to use gnuplot for all my plots, but converted recently. For example all the plots in http://www.physik.tu-dresden.de/~baecker/pub21.html were generated with PyX). Also I should mention that the developers of PyX are very open to questions/suggestions (for example I forwarded the evaluation and they already started to think about the spline interpolation!). Let me bring in another one, matplotlib: http://matplotlib.sourceforge.net/ See the examples at http://matplotlib.sourceforge.net/screenshots.html It is also based on python and together with - ipython http://ipython.scipy.org/ - Numeric (soon to be superseeded by scipy core http://numeric.scipy.org/) - scipy http://www.scipy.org/ one gets an excellent framework for scientific computing in python (quite similar in many respects with matlab). Best, Arnd -- To UNSUBSCRIBE, email to [EMAIL PROTECTED] with a subject of "unsubscribe". Trouble? Contact [EMAIL PROTECTED]
