matplotlib-users Mailing List for matplotlib

Yes, sorry about that. I hope this now works.

Tanim Islam

On Mon, 30 Apr 2012, Benjamin Root wrote:

> 
> 
> On Mon, Apr 30, 2012 at 2:02 PM, Tanim Islam <tan...@gm...> wrote:
>       Apologies, but attached to this email are the 2 python scripts I have neglected to attach to the previous email.
> Tanim Islam
> 
> 
> Tanim,
> 
> Could you try that again?  No python scripts came with that email.
> 
> Ben Root
> 
> 
>

On Mon, Apr 30, 2012 at 2:02 PM, Tanim Islam <tan...@gm...> wrote:

> Apologies, but attached to this email are the 2 python scripts I have
> neglected to attach to the previous email.
>
> Tanim Islam
>
>
Tanim,

Could you try that again?  No python scripts came with that email.

Ben Root

Apologies, but attached to this email are the 2 python scripts I have
neglected to attach to the previous email.

Tanim Islam

Hello:

I believe I may have uncovered some unusual behavior wrt to Axes3D.scatter.


   - When I run the attached and self-contained problem,
   "demo_colorbar_3d.py," I am able to create a colorbar and the 3d scatter
   points are normally created.
   - However, in the attached python script "demo_data_3d.py," when I read
   a set of XYZ data from a file and place into separate XYZ arrays, I am able
   to create the appropriately limited and colored colorbar, but all the
   scatter points appear black.

The data input for "demo_data_3d.py," "data_output.txt," and png
screenshots "demo_colorbar_3d.pdf" and "demo_data_3d.pdf," are located in a
the following public Dropbox links are here:

   - demo_data_3d.pdf <http://dl.dropbox.com/u/7140790/demo_data_3d.pdf>
   - data_output.txt <http://dl.dropbox.com/u/7140790/data_output.txt>
   - demo_colorbar_3d.pdf<http://dl.dropbox.com/u/7140790/demo_colorbar_3d.pdf>


Thank you,

Tanim Islam

On 30/04/12 02:15, Benjamin Root wrote:
> Use pcolormesh().  *much* faster if you can assume certain things about
> the domain.
> 
> Ben Root 

Thank you very much!

Ignas

On Sunday, April 29, 2012, Ignas Anikevičius wrote:

> Hello everybody,
>
> On 28 April 2012 12:13, julien tayon <ju...@ta... <javascript:_e({},
> 'cvml', 'ju...@ta...');>> wrote:
>
>> First cpp stands for C Pre Processor, this tool usually does macro
>> substitution in c, objective c, c++. Hence Cpp in the object is pretty
>> much confusing when it seems to be talking about C++.
>>
>
> Sorry for my ignorance, will know it in the future
>
>
>> There is another simpler solution however :
>> Do everything in python : python is a very powerfull gluing langage,
>> the GIL ensuring that non thread-safe code is thread safe, it is very
>> forgiving with code not design for concurrency.
>>
>
> I wanted to write in Python as much code as possible, it is just some plot
> commands are quite slow in matplotlib. For example, I want to work in polar
> coordinate system to plot a function of 2 variables. For that I want to use
> the np.meshgrid function and the plot the results with the pcolor command
> from pyplot. The problem is that with a lot of data points it becomes very
> slow, which is not acceptable if one wants to draw a lot of plots using
> this function. Because the array is not ordered and points in space are at
> irregular intervals, I could not use imshow,  which is much much faster. So
> I was thinking if there is some internal C++ API which I could use and
> maybe speed up the plotting itself a bit.
>
> It would actually be very nice if I could do that as most of the toolkits,
> which can interface with C/C++ do not have LaTeX capabilites. Gnuplot can
> be used in C/C++, but as far as I remember it is not the most elegant way
> of doing it...
>
> Going back to the topic, is there any potential to speed up some commands
> (e.g. pcolor) by rewriting/extending them in Cython or C++? If yes, then
> maybe I might tinker with the code at some point, when I have more free
> time.
>
> Anyway, thanks for such detailed answers.
>
> All best,
> Ignas A.
>



Use pcolormesh().  *much* faster if you can assume certain things about the
domain.

Ben Root

Hello everybody,

On 28 April 2012 12:13, julien tayon <ju...@ta...> wrote:

> First cpp stands for C Pre Processor, this tool usually does macro
> substitution in c, objective c, c++. Hence Cpp in the object is pretty
> much confusing when it seems to be talking about C++.
>

Sorry for my ignorance, will know it in the future


> There is another simpler solution however :
> Do everything in python : python is a very powerfull gluing langage,
> the GIL ensuring that non thread-safe code is thread safe, it is very
> forgiving with code not design for concurrency.
>

I wanted to write in Python as much code as possible, it is just some plot
commands are quite slow in matplotlib. For example, I want to work in polar
coordinate system to plot a function of 2 variables. For that I want to use
the np.meshgrid function and the plot the results with the pcolor command
from pyplot. The problem is that with a lot of data points it becomes very
slow, which is not acceptable if one wants to draw a lot of plots using
this function. Because the array is not ordered and points in space are at
irregular intervals, I could not use imshow,  which is much much faster. So
I was thinking if there is some internal C++ API which I could use and
maybe speed up the plotting itself a bit.

It would actually be very nice if I could do that as most of the toolkits,
which can interface with C/C++ do not have LaTeX capabilites. Gnuplot can
be used in C/C++, but as far as I remember it is not the most elegant way
of doing it...

Going back to the topic, is there any potential to speed up some commands
(e.g. pcolor) by rewriting/extending them in Cython or C++? If yes, then
maybe I might tinker with the code at some point, when I have more free
time.

Anyway, thanks for such detailed answers.

All best,
Ignas A.