Your files do not seem to be readable:
http://atmos.uwyo.edu/~gsever/data/matplotlib/test_speed.py http://atmos.uwyo.edu/~gsever/data/matplotlib/test_speed.pdf Nicolas On Jul 4, 2012, at 19:17 , Gökhan Sever wrote: > Hello, > > I am working on creating some distribution plots to analyze cloud droplet and > drop features. You can see one such plot at > http://atmos.uwyo.edu/~gsever/data/rf06_1second/rf06_belowcloud_SurfaceArea_1second.pdf > This file contains 38 pages and each page has 16 panels created via MPL's > AxesGrid toolkit. I am using PdfPages from pdf backend profile to construct > this multi-page plot. The original code that is used to create this plot is > in > http://code.google.com/p/ccnworks/source/browse/trunk/parcel_drizzle/rf06_moments.py > > The problem I am reporting is due to the lengthier plot creation times. It > takes about 4 minutes to create such plot in my laptop. To better demonstrate > the issue I created a sample script which you can use to reproduce my timing > results --well based on pseudo/random data points. All my data points in the > original script are float64 so I use float64 in the sample script as well. > > The script is at http://atmos.uwyo.edu/~gsever/data/matplotlib/test_speed.py > I also included 2 pages output running the script with nums=2 setting > http://atmos.uwyo.edu/~gsever/data/matplotlib/test_speed.pdf > Comparing my original output, indeed cloud particles are not from a normal > distribution :) > > Joke aside, running with nums=2 for 2 pages > > time run test_speed.py > CPU times: user 12.39 s, sys: 0.10 s, total: 12.49 s > Wall time: 12.84 s > > when nums=38, just like my original script, then I get similar timing to my > original run > > time run test.py > CPU times: user 227.39 s, sys: 1.74 s, total: 229.13 s > Wall time: 234.87 s > > In addition to these longer plot creation times, 38 pages plot creation > consumes about 3 GB memory. I am wondering if there are tricks to improve > plot creation times as well as more efficiently using the memory. Attempting > to create two such distributions blocks my machine eating 6 GB of ram space. > > Using Python 2.7, NumPy 2.0.0.dev-7e202a2, IPython 0.13.beta1, matplotlib > 1.1.1rc on Fedora 16 (x86_64) > > Thanks. > > -- > Gökhan > ------------------------------------------------------------------------------ > Live Security Virtual Conference > Exclusive live event will cover all the ways today's security and > threat landscape has changed and how IT managers can respond. Discussions > will include endpoint security, mobile security and the latest in malware > threats. > http://www.accelacomm.com/jaw/sfrnl04242012/114/50122263/_______________________________________________ > Matplotlib-users mailing list > Matplotlib-users@lists.sourceforge.net > https://lists.sourceforge.net/lists/listinfo/matplotlib-users ------------------------------------------------------------------------------ Live Security Virtual Conference Exclusive live event will cover all the ways today's security and threat landscape has changed and how IT managers can respond. Discussions will include endpoint security, mobile security and the latest in malware threats. http://www.accelacomm.com/jaw/sfrnl04242012/114/50122263/ _______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
