Thank you for your fast reply, you are right, AnchoredSizeBar has indeed almost all features I would like. Or it definitely has the most important ones. I have stumbled upon the page you refer, but I must have overlooked it. An actual documentation of the function wouldn't hurt Anyway, these features seem to be missing: - Bar styles (bar width, bar endings wouldn't hurt either). - Colors (bar, text, background). I would like to look into it, but it is usually more efficient if more experienced persons provide some pointers. So if you think that I should know something before attempting to add the functionality, please let me know. For instance, do you think that the enhancements I have proposed make sense and should be integrated into AnchoredSizeBar? Matej On 11/18/2012 06:32 PM, Joe Kington wrote: > Have you had a look at "AnchoredSizeBar" from > mpl_toolkits.axes_grid1.anchored_artists? > > http://matplotlib.org/1.1.1/mpl_toolkits/axes_grid/users/overview.html#anchoredartists > > It provides essentially all of the features you mention. I'd agree it > could use a few enhancements, but it's a good start on this. > > As a quick example of using it as you describe: > > import matplotlib.pyplot as plt > import numpy as np > from mpl_toolkits.axes_grid1.anchored_artists import AnchoredSizeBar > > fig, ax = plt.subplots() > ax.imshow(np.random.random((10,10))) > > bar = AnchoredSizeBar(ax.transData, 2, '2 Units', > pad=0.5, loc=8, sep=5, borderpad=0.5, frameon=True) > bar.patch.set(alpha=0.5, boxstyle='round') > ax.add_artist(bar) > > plt.show() > > > Note that this is very similar to your example. The main things it's > missing are ends on the scalebar. > > I'd certainly agree that it could use some enhancements (e.g. > different styles of scalebars and better documentation), but perhaps > it's best to start with AnchoredSizeBar instead of recreating it from > scratch? > > Just my thoughts, anyway. > -Joe > > > On Sun, Nov 18, 2012 at 8:16 AM, Matěj Týč <mat...@gm... > <mailto:mat...@gm...>> wrote: > > Dear developers, > I use Matplotlib to process and display images acquired by > microscopes. > It is quite common to indicate dimensions by displaying scale bar > in the > image rather than using axes with labels. Although axes enable you to > refer to specific location in the image, they take up space around the > image, so if you only need to show the scale, scale bar is better. > > What is needed: > - The scale bar of given dimension (data units), possibly with > bars at > its ends. > - Text (presumably centered under the bar), text size as well as > vertical offset in physical units (= units reflecting the actual image > size, like the font size) > - Semi-transparent rectangle, so the scale and label are more > readable > - Dark/bright theme might be a good idea. > I have made an svg file in Inkscape, so you can see what I mean. > > First of all, I tried to implement the stuff myself, but later I have > found out that there is something on github. I have forked it, > made some > minor modifications, and I think that it is "almost done". > https://gist.github.com/4100881 (the add_scalebar function there is > broken ATM) > I also attach the test code for your convenience. You need to run it > with scalebars.py in the same directory. > You are supposed to see a tiny bright scalebar at the bottom right > corner. > > There are some outstanding issues, though: > > - I have a feeling that bars at the end of the scale bar should be > related to the font size, as well as the actual width of the scale > bar. > How to achieve this? > - How to make the semi-transparent background for the bar and > label in > a smart way? > > Could you help me with those? I would like this to appear in > matplotlib > since it is IMO a useful feature, what needs to be done? > Regards, > Matěj Týč > > ------------------------------------------------------------------------------ > Monitor your physical, virtual and cloud infrastructure from a single > web console. Get in-depth insight into apps, servers, databases, > vmware, > SAP, cloud infrastructure, etc. Download 30-day Free Trial. > Pricing starts from 795ドル for 25 servers or applications! > http://p.sf.net/sfu/zoho_dev2dev_nov > _______________________________________________ > Matplotlib-devel mailing list > Mat...@li... > <mailto:Mat...@li...> > https://lists.sourceforge.net/lists/listinfo/matplotlib-devel > >