I am trying to automate the generation of scatterplots in matplotlib. The problem of where to put the labels is known as 'point-feature labeling' (a main application is in cartography, where cities and such are known as 'point features'). In general the problem is not easy. Some references:
http://www.merl.com/reports/docs/TR96-04.pdf http://www.eecs.harvard.edu/shieber/Biblio/Papers/tog-final.pdf If anyone knows of any canned python algorithms to do this, please direct me to them. If not, I will need to implement one. My problem is not that hard, as I will not have more than 20 labels to place. As I see it, the steps that need to be taken are: 1. locate the points 2. compute the size of the text boxes for the labels 3. minimize a loss function reflecting one of the algorithms discussed in the papers cited to determine the optimal placement of the labels At the moment I was wondering if any matplotlib experts (I am a bit of a novice) could suggest a good way to accomplish 2. I have tried to do something like In [1]: from pylab import * In [2]: plot([0.5],[0.5],'bo') In [3]: axis([0,1,0,1]) In [4]: t = text(0.50,0.51,'Test') In [5]: t._get_layout(t._renderer)[1][0][1] Out[5]: (20.0, 6.0) Then I have tried to use t._transform to convert these dimensions back into axis coordinates. Unfortunately this method seems to require that the plot be rendered to be able to get the dimensions, which is not too efficient. I'm sure there is a better way to do this; does anyone have any ideas? -- http://mail.python.org/mailman/listinfo/python-list
