Am 05.10.2012 11:13, schrieb Matthias BUSSONNIER:
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
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
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
On 10/4/12 2:16 AM, Fernando Perez wrote:
This would make for an awesome couple of examples for the gallery, the
mathematica solutions look really pretty cool:
http://mathematica.stackexchange.com/questions/11350/xkcd-style-graphs
The matlab and R version not quite so much, still for
Hi Fernando,
Le 04/10/2012 09:16, Fernando Perez a écrit :
This would make for an awesome couple of examples for the gallery, the
mathematica solutions look really pretty cool:
http://mathematica.stackexchange.com/questions/11350/xkcd-style-graphs
I've never used Mathematica so that it's
On Thu, Oct 4, 2012 at 10:44 AM, Damon McDougall
damon.mcdoug...@gmail.com wrote:
On Thu, Oct 4, 2012 at 10:02 AM, Pierre Haessig
pierre.haes...@crans.org wrote:
Hi Fernando,
Le 04/10/2012 09:16, Fernando Perez a écrit :
This would make for an awesome couple of examples for the gallery, the
Nice challenge Fernando!
Damon, I love the solution! I do wonder whether we could do some
quirky transform on the lines to achieve a similar result, rather than
manipulating the data before plotting it. The benefit is that
everything should then get randomly Xkcd-ed automatically - maybe I
will
Yes -- this would be a great application for the path filtering
infrastructure that matplotlib has.
Mike
On 10/04/2012 08:29 AM, Phil Elson wrote:
Nice challenge Fernando!
Damon, I love the solution! I do wonder whether we could do some
quirky transform on the lines to achieve a similar
On 10/4/12 4:02 AM, Pierre Haessig wrote:
Hi Fernando,
Le 04/10/2012 09:16, Fernando Perez a écrit :
This would make for an awesome couple of examples for the gallery, the
mathematica solutions look really pretty cool:
http://mathematica.stackexchange.com/questions/11350/xkcd-style-graphs
Le 04/10/2012 14:29, Phil Elson a écrit :
Damon, I love the solution! I do wonder whether we could do some
quirky transform on the lines to achieve a similar result, rather than
manipulating the data before plotting it. The benefit is that
everything should then get randomly Xkcd-ed
This is just too cool of an idea to pass up -- I'm going to see if I can
put together a PR that does this using the C++ path filtering stuff so
it would be available everywhere.
Mike
On 10/04/2012 10:11 AM, Michael Droettboom wrote:
Yes -- this would be a great application for the path
On Thu, Oct 4, 2012 at 10:11 AM, Michael Droettboom md...@stsci.edu wrote:
Yes -- this would be a great application for the path filtering
infrastructure that matplotlib has.
Mike
I agree with this idea. However, I don't think the code is set up to allow
for user-defined path filters.
Le 04/10/2012 16:03, Jason Grout a écrit :
f@r means f(r)
a~ImageConvolve~b means ImageConvolve(a,b) (~ treats an operator as infix)
Table[..., {2}] means [... for i in range(2)]
#+1 is a lambda function lambda x: x+1
So I think it goes something like:
def xkcdDistort(p):
r =
Le 04/10/2012 16:11, Michael Droettboom a écrit :
Yes -- this would be a great application for the path filtering
infrastructure that matplotlib has.
Sounds way cooler than post-processing a raster plot image !
I'm not aware of this path filtering infrastructure. I guess it's a
deeply buried
On 10/4/12 9:11 AM, Michael Droettboom wrote:
Yes -- this would be a great application for the path filtering
infrastructure that matplotlib has.
Is that the same as the path effects features, like
http://matplotlib.org/examples/pylab_examples/patheffect_demo.html ?
Thanks,
Jason
On Thu, Oct 4, 2012 at 10:39 AM, Pierre Haessig pierre.haes...@crans.orgwrote:
Le 04/10/2012 16:11, Michael Droettboom a écrit :
Yes -- this would be a great application for the path filtering
infrastructure that matplotlib has.
Sounds way cooler than post-processing a raster plot image !
On Thu, Oct 4, 2012 at 3:35 PM, Pierre Haessig pierre.haes...@crans.org wrote:
Le 04/10/2012 16:03, Jason Grout a écrit :
f@r means f(r)
a~ImageConvolve~b means ImageConvolve(a,b) (~ treats an operator as infix)
Table[..., {2}] means [... for i in range(2)]
#+1 is a lambda function lambda
On 10/04/2012 10:29 AM, Benjamin Root wrote:
On Thu, Oct 4, 2012 at 10:11 AM, Michael Droettboom md...@stsci.edu
mailto:md...@stsci.edu wrote:
Yes -- this would be a great application for the path filtering
infrastructure that matplotlib has.
Mike
I agree with this idea.
Le 04/10/2012 16:54, Damon McDougall a écrit :
Adding Gaussian noise to each point on a function doesn't look nice.
That's why I produced a random function in Fourier space first. That
way, random functions still have some sense of smoothness.
Mathematica code seems to use a Gaussian
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
On Thu, Oct 4, 2012 at 10:09 PM, Juergen Hasch pyt...@elbonia.de wrote:
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
Sweet! That should *defiintely* go into the mpl gallery, and honestly
I'd love for it to be cleaned up enough to be usable to style
generically any plot, much like the mathematica code I linked to
earlier does.
It would be a beautiful demonstration of matplotlib's capabilities,
and furthermore,
I've put up a PR adding this sketchy line drawing as a path filter.
This makes it work with almost anything that matplotlib draws.
https://github.com/matplotlib/matplotlib/pull/1329
Mike
On 10/04/2012 06:06 PM, Fernando Perez wrote:
Sweet! That should *defiintely* go into the mpl gallery,
23 matches
Mail list logo
