Jae-Joon Lee wrote: > Doing this in a general way is quite difficult (if possible) because a > user can set an arbitrary transform for an artist. What we may try to > do is recycling artists whose transform is simple, e.g., transData, > rather than try to come up with a general solution.
Is even that worth the potential extra complexity, both in the code and in the documentation? What is the real benefit? Eric > > I'll see what I can do but I must admit that I'm not very kin to this > kind of feature and it may take a while. I recommend you to open a new > ticket in the feature requests tracker hoping that other developers > or contributors can take a look. > > http://sourceforge.net/tracker/?atid=560723&group_id=80706&func=browse > > Regards, > > -JJ > > > > On Mon, Mar 29, 2010 at 1:54 PM, Thomas Robitaille > <thomas.robitai...@gmail.com> wrote: >> Hi Jae-Joon, >> >> Thanks for your quick reply! Since for example LineCollections can be >> created independent of the Axes in which they are going to be plotted >> through the creation of a LineCollection instance, would it not be possible >> to have a method that allows one to retrieve an Axes-independent >> LineCollection from an Axes instance? (for example a get_collection method) >> This would then allow one to 'recycle' existing collections. >> >> Cheers, >> >> Thomas >> >> On Mar 29, 2010, at 1:40 PM, Jae-Joon Lee wrote: >> >>> As far as I can say, moving around artists from one axes to the other >>> is NOT recommended. And I encourage you to create separate artists for >>> each axes rather than try to reuse the existing ones. >>> >>> For your particular example, >>> >>> fig = mpl.figure() >>> ax2 = fig.add_subplot(1,1,1) >>> for c in ax1.collections: >>> c._transOffset=ax2.transData >>> ax2.add_collection(c) >>> >>> should work. >>> >>> Regards, >>> >>> -JJ >>> >>> >>> >>> >>> On Mon, Mar 29, 2010 at 12:24 PM, Thomas Robitaille >>> <thomas.robitai...@gmail.com> wrote: >>>> Hello, >>>> >>>> In the following example, I am trying to copy over existing collections >>>> from one plot to another: >>>> >>>> import matplotlib.pyplot as mpl >>>> >>>> fig = mpl.figure() >>>> ax1 = fig.add_subplot(1,1,1) >>>> ax1.scatter([0.5],[0.5]) >>>> fig.savefig('test1.png') >>>> >>>> fig = mpl.figure() >>>> ax2 = fig.add_subplot(1,1,1) >>>> for c in ax1.collections: >>>> ax2.add_collection(c) >>>> fig.savefig('test2.png') >>>> >>>> However, the circle appears in the wrong place in test2.png (close to 0.4, >>>> 0.4 instead of 0.5,0.5). Is it not possible/safe to copy over collections >>>> in this way? If not, then how should this be done? >>>> >>>> Thanks, >>>> >>>> Thomas >>>> ------------------------------------------------------------------------------ >>>> Download Intel® Parallel Studio Eval >>>> Try the new software tools for yourself. Speed compiling, find bugs >>>> proactively, and fine-tune applications for parallel performance. >>>> See why Intel Parallel Studio got high marks during beta. >>>> http://p.sf.net/sfu/intel-sw-dev >>>> _______________________________________________ >>>> Matplotlib-users mailing list >>>> Matplotlib-users@lists.sourceforge.net >>>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users >>>> >> >> ------------------------------------------------------------------------------ >> Download Intel® Parallel Studio Eval >> Try the new software tools for yourself. Speed compiling, find bugs >> proactively, and fine-tune applications for parallel performance. >> See why Intel Parallel Studio got high marks during beta. >> http://p.sf.net/sfu/intel-sw-dev >> _______________________________________________ >> Matplotlib-users mailing list >> Matplotlib-users@lists.sourceforge.net >> https://lists.sourceforge.net/lists/listinfo/matplotlib-users >> > > ------------------------------------------------------------------------------ > Download Intel® Parallel Studio Eval > Try the new software tools for yourself. Speed compiling, find bugs > proactively, and fine-tune applications for parallel performance. > See why Intel Parallel Studio got high marks during beta. > http://p.sf.net/sfu/intel-sw-dev > _______________________________________________ > Matplotlib-users mailing list > Matplotlib-users@lists.sourceforge.net > https://lists.sourceforge.net/lists/listinfo/matplotlib-users ------------------------------------------------------------------------------ Download Intel® Parallel Studio Eval Try the new software tools for yourself. Speed compiling, find bugs proactively, and fine-tune applications for parallel performance. See why Intel Parallel Studio got high marks during beta. http://p.sf.net/sfu/intel-sw-dev _______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
