On Fri, Oct 5, 2012 at 10:13 AM, Matthias BUSSONNIER <bussonniermatth...@gmail.com> wrote: > > Le 4 oct. 2012 à 23:09, Juergen Hasch a écrit : > >> Here is my take on it as an IPython notebook, based on Damon's code: >> http://nbviewer.ipython.org/3835181/ >> >> I took the engineering approach and filtered the random function instead of >> doing some fft/ifft magic. >> Also, X and Y of the functions are affected now, giving them a more >> "natural" look in the slopes. >> >> Juergen > > If anyone have time to make some examples and a right side thumbnail > I can make it as featured notebook in the front page of nbviewer. > > You can even make a direct PR agains nbviewer and I would then just have > to merge and deploy. > > To be fair, notebook should also give some explanation of the code, > link to this discussion, maybe show one "original" xkcd graph. > > Please take your time, and if there is several submission, > we'll sort out how to choose the best(s). > > -- > Matthias > >> >> >> Am 04.10.2012 18:09, schrieb Pierre Haessig: >>> Le 04/10/2012 16:35, Pierre Haessig a écrit : >>>> So I think this code indeed resamples the rastered plot image on a >>>> shaken coordinate grid. I kind of understand that the noise on >>>> coordinates is spatially smoothed by a 10px Gaussian Point Spread >>>> Function (if I understand correctly...) >>> I've implemented this processing in a tiny "image_shake" script. >>> https://gist.github.com/3834536 >>> A nice occasion to learn how to use some scipy image processing functions... >>> >>> I've attached the before/after images because I didn't manage to put >>> them in the Gist (it's not a plot image but gives the idea of line shaking). >>> >>> Now, I think it's unfortunately outside the frame of Fernando's >>> challenge, because this script uses zero matplotlib methods!! >>> >>> Best, >>> Pierre
This thread has made my week. -- Damon McDougall http://www.damon-is-a-geek.com B2.39 Mathematics Institute University of Warwick Coventry West Midlands CV4 7AL United Kingdom ------------------------------------------------------------------------------ Don't let slow site performance ruin your business. Deploy New Relic APM Deploy New Relic app performance management and know exactly what is happening inside your Ruby, Python, PHP, Java, and .NET app Try New Relic at no cost today and get our sweet Data Nerd shirt too! http://p.sf.net/sfu/newrelic-dev2dev _______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
