"bwaha" <[EMAIL PROTECTED]> wrote in message news:[EMAIL PROTECTED] > Has anyone figured out how to get a legend for each line in a > matplotlib.collections.LineCollection instance? > After frigging around for hours I finally tracked down the real cause of the plotting speed problem which led me to use LineCollections in the first place. Its the 'best' option in the legend location and setting it to default in my application!
When I first put in the LineCollection code I cut out my legend code to keep things simple. And sure enough LineCollections plotted really fast. Then, since legends didn't work for LineCollection lines individually I figured I'd fudge it by creating dummy lines from the collection, adding labels and calling legend(). This worked with only a small speed penalty. But I kept getting a stackdump when I added the location argument. Finally realised it was due to having a default of 'best' location in my code which meant it went searching for intersection with lines that don't exist (outside of the LineCollection). So I disabled the 'best' location option. Then I figured, since I'd cleaned up my code a bit, I'd reinstate my earlier pylab.plot based line drawing code to see if the clean up made any difference to what was previously abysmal performance. The lines plotted faster than the LineCollection code! When I removed the legend hack for LineCollections there was virtually no difference. (Story is not finshed yet). So I figured after all that that I'd reinstate my pylab.plot based code since I could plot a greater range of symbols than with LineCollections with no speed loss. And I thought why not go the whole hog and reinstate the 'best' location option too. Boom! Plotting performance was abysmal again. Finally I realised that enabling 'best' and having it as the default meant that as I added new data to plot, the search time for a good place to put the legend increased dramtically, and probably became more difficult with more and more lines filling the canvas. Anyway now I'm a lot happier than when I started because I've retained my original range of plot styles and I got much faster plotting. Hopefully this lesson can help someone else. -- http://mail.python.org/mailman/listinfo/python-list
