Hi, On 2005年8月30日, Ken McIvor wrote: > On Aug 30, 2005, at 10:45 AM, Arnd Baecker wrote: > > I would have thought so as well. However I get: > <snip> > > A search for wxPython.h on > > http://www.debian.org/distrib/packages#search_packages > > gives no hits. > > Sorry, due to a lack of coffee this morning I misread "wxPython.h" as > "wxWidgets.h" or something daft, yielding the kneejerk "install the > -dev package" response. > > I wasn't aware of this situation, but it has the potential to be a big > problem for me at work, where we primarily run Debian. I have emailed > Ron Lee, the wxgtk2.4 package maintainer, about the situation. We'll > see what he has to say on the matter. Excellent - I was thinking about doing the same. > > I agree. I wonder if anything improved with wx2.6? (for our > > PlottingCanvas > > we even dared to keep drawing DCs around, and it works without > > problems...) > > What PlottingCanvas is this? I'd be interested in seeing what > optimizations you guys performed, if the source is available. http://www.physik.tu-dresden.de/~baecker/python/plot.html One of our main goals was to plot many points quickly, in such a way that one appears after another to get a "dynamic" appearance. See http://www.physik.tu-dresden.de/~baecker/python/StandardMap.py as an example. (note that it still uses the old wx style...) [...] > > However, we are currently investigating to use > > matplotlib for > > a computational physics course (which will be next summer) and many of > > the > > students have *much* slower machines. So we need maximum speed but > > with a > > minimum of coding hassle (around 30% of the students have never > > programmed > > before ...). > > Just leveling the playing field between WXAgg and GtkAgg is exciting > for me, because that means that future efforts at general optimization > will net a bigger speed improvement for WXAgg. > > I'd imagine the plotting speed will be good enough for something along > the lines of interactive plotting with iPython or visualizing results > with pylab. We have just finished the conversion of all exercices of our course from scipy.xplt (aka pygist) to matplotlib. Unfortunately, quite a few are prohibitively slow, even on our fast machines. But we have some ideas on possible improvements (both on the side of our code and on the side of matplotlib) - this is going to be separate thread though ;-) > Speaking as a recent survivor of a computational physics > class, I expect you to see a huge benefit from using Python as the > language and matplotlib as the visualization, especially if you have > students who have never programmed before. I absolutely agree - we have been running our course now for the third year, so far with scipy and scipy.xplt as plotting programm. We had very positive feedback (of course, those who never programmed before, had to work harder ;-). Just in case: http://www.comp-phys.tu-dresden.de/cp2005/, however the material (apart from the FAQ) is in German. Best, Arnd