Michael Droettboom wrote: > Sorry to repeat myself, but please reduce this to a short, self contained > example, that is absolutely minimal to demonstrate the problem. > http://sscce.org/ should help better explain what I'm after. I don't want to > find the needle in the haystack here -- there is code in your example that > doesn't even run, for example. > > That said, are you really after creating a legend entry for each of the dots? > (See below). That just isn't going to work, and I'm not surprised it eats > up excessive amounts of memory. I think you want (and can) reduce this to a > single scatter call. > > _series = [_ax1.scatter(_x, _y, color=_c, s=objsize, label=_l, hatch='.') for > _x, _y, _c, _l in izip(mydata_x, mydata_y, colors, legends)] # returns > PathCollection object
Are you sure? I think it was concluded on this list that scatter cannot (or does not) take nested lists of lists with series like histogram and piechart do. I cannot find the thread but maybe you are more lucky. I even think that I already opened a bugreport/feature requested in the past for this. But maybe not. Martin > > Mike > > On 10/12/2013 12:57 PM, Martin MOKREJŠ wrote: >> Hi, >> so here is some quick but working example. I added there are 2-3 functions >> (unused) >> as a bonus, you can easily call them from the main function using same API >> (except the piechart). I hope this shows what I lack in matplotlib - a >> general API >> so that I could easily switch form scatter plot to piechart or barchart >> without altering >> much the function arguments. Messing with return objects line2D, >> PathCollection, Rectangle >> is awkward and I would like to stay away from matplotlib's internals. ;) >> Some can be sliced, >> so not, you will see in the code. >> >> This eatmem.py will take easily all your memory. Drawing 300000 dots is >> not feasible >> with 16GB of RAM. While the example is for sure inefficient in many places >> generating the data >> in python does not eat RAM. That happens afterwards. >> >> I would really like to hear whether matplotlib could be adjusted instead. ;) >> I already mentioned >> in this thread that it is awkward to pre-create colors before passing all >> data to a drawing >> function. I think we could all save a lot if matplotlib could dynamically >> fetch colors >> on the fly from user-created generator, same for legends descriptions. I >> think my example >> code shows the inefficient approach here. Would I have more time I would >> randomize a bit >> more the sublist of each series so that the numbers in legends would be more >> variable >> but that is a cosmetic issue. >> Probably due to my ignorance you will see that figures with legends have >> different font >> sizes, axes are rescaled and the figure. Of course I wanted to have the >> drawing same via both >> approaches but failed badly. The files/figures with legends should be just >> accompanied by the >> legend "table" underneath but the drawing itself should be same. Maybe an >> issue with DPI settings >> but not only. >> >> I placed some comments in the code, please don't take them in person. ;) >> Of course >> I am glad for the existing work and am happy to contribute my crap. I am >> fine if you rewamp >> this ugly code into matplotlib testsuite, provide similar function (the API >> mentioned above) >> so that I could use your code directly. That would be great. I just tried to >> show multiple >> issues at once, notably that is why I included those unused functions. You >> will for sure find >> a way to use them. >> >> Regarding the "unnecessary" del() calls etc., I think I have to use keep >> some, Ben, because >> the function is not always left soon enough. I could drop some, you are >> right, but for some >> I don't think so. Matplotlib cannot recycle the memory until me (upstream) >> deletes the reference >> so ... go and test this lousy code. Now you have a testcase. ;) Same with >> the gc.collect() calls. >> Actually, the main loop with 10 iteration is there just to show why I always >> want to clear >> a figure when entering a function and while leaving it as well. It happened >> too many times that >> I drawed over an old figure, and this was posted also few times on this list >> by others. That is >> a weird behavior in my opinion. We, users, are just forced to use too >> low-level functions. >> >> So, have fun eating your memory! :)) >> Martin > > > -- > _ > |\/|o _|_ _. _ | | \.__ __|__|_|_ _ _ ._ _ > | ||(_| |(_|(/_| |_/|(_)(/_|_ |_|_)(_)(_)| | | > > http://www.droettboom.com > -- Martin Mokrejs, Ph.D. Bioinformatics Donovalska 1658 149 00 Prague Czech Republic http://www.iresite.org http://www.iresite.org/~mmokrejs ------------------------------------------------------------------------------ October Webinars: Code for Performance Free Intel webinars can help you accelerate application performance. Explore tips for MPI, OpenMP, advanced profiling, and more. Get the most from the latest Intel processors and coprocessors. See abstracts and register > http://pubads.g.doubleclick.net/gampad/clk?id=60135031&iu=/4140/ostg.clktrk _______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
