Thank you so much Jae-Joon and Tony. You saved me so much time ! The whole transforms system was very obscure (to me !).
>> trans = (ax.transScale + ax.transLimits).inverted() ---- barspace = 0.32 #inches barstep = abscissa[1] - abscissa[0] trans = (ax.transScale + ax.transLimits).inverted() barspacedata = trans.transform([barspace,0.0]) barwidth = barstep - barspacedata[0] ---- Works great ! > I just wanted to add a little bit to Jae-Joon's example. I feel like I have > to relearn the axes transformations every time I deal with them. Your email > reminded me to write things down, and I thought I'd share it, in case others > find it useful. Let me know if anything is wrong/unclear. Everything is very clear now. Thanks for taking the time to detail everything, it's priceless. > It's important to note that these are two **very different** approaches. The > first point (red dot) above is always referenced to axes space and will > remain > in the center of the plot, even if you change the axes limits (try panning > in > interactive mode). > > On the other hand, the second point (green square) is referenced to the data > space and will move with the data if the axes limits are changed. > > I really liked your small example. I wish we could publish it on scipy or something. Best regards. Mat. ------------------------------------------------------------------------- This SF.Net email is sponsored by the Moblin Your Move Developer's challenge Build the coolest Linux based applications with Moblin SDK & win great prizes Grand prize is a trip for two to an Open Source event anywhere in the world http://moblin-contest.org/redirect.php?banner_id=100&url=/ _______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
