matplotlib-devel Mailing List for matplotlib

On Fri, 8 Aug 2008 08:47:11 -0500
 "John Hunter" <jd...@gm...> wrote:
> On Fri, Aug 8, 2008 at 8:20 AM, Nils Wagner
> <nw...@ia...> wrote:
> 
>> I have installed matplotlib locally on a linux box
>> (without root access).
>> Is it possible for o t h e r users to use my local
>> matplotlib installation ? The problem is that show()
>> doesn't produce a result on the screen.
>>
>> Any pointer would be appreciated.
> 
> This is really a question for matplotlib-users, but, 
>there is no
> reason this shouldn't work. Some of my colleagues have 
>run out of my
> directory before.
> 
> * what backend are they using?
> 
> * what test script are they trying (I suggest
> examples/pylab_examples/simple_plot.py
> 
> * what is the output of --verbose-debug when the other 
>users run this script?
> 
> * does it help to try different backends, eg if they 
>run the script
> with -dTKAgg, -dWXAgg, -dQt4Agg or -dGTKAgg
> 
> * what are the permissions on your install directory -- 
>can the
> other uses see all the files?
> 
> * what version of matplotlib are you using? What 
>platform (you say
> linux, but when reporting problems it helps to include 
>as much detail
> as possible). Are the users running from the console or 
>an X11
> session?
> 
> JDH
 
Hi John,
I think it was a missing matplotlibrc in ~/.matplotlib
Now it works fine.
Thank you very much !
Next time I will post to matploblib-user. Sorry for that.
Nils

Hello everybody,
I have sent this message to the user group, but thinking of it, it may be more
relevant to the development mailing list...so here it is again.
We are looking for the best way to plot a waterfall diagram in
Matplotlib. The 2 functions which could be used 
to do that are (as far as I have found) imshow and pcolormesh. Here is a
small script that use both to compare the output:
-----------------
from pylab import *
delta = 0.2
x = arange(-3.0, 3.0, delta)
y = arange(-2.0, 2.0, delta)
X, Y = meshgrid(x, y)
Z1 = bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0)
Z2 = bivariate_normal(X, Y, 1.5, 0.5, 1, 1)
# difference of Gaussians
Z = 10.0 * (Z2 - Z1)
figure(1)
im = imshow(Z,extent=(-3,3,-2,2))
CS = contour(X, -Y, Z, 6,
 colors='k', # negative contours will be dashed by default
 )
clabel(CS, fontsize=9, inline=1)
title('Using imshow')
figure(2)
im = pcolormesh(X,-Y,Z)
CS = contour(X, -Y, Z, 6,
 colors='k', # negative contours will be dashed by default
 )
clabel(CS, fontsize=9, inline=1)
title('Using pcolormesh')
show()
---------------------
The problem is that we need some of the flexibility of pcolormesh (which
is able to map the matrix of value on any deformed mesh), while
we would like to use the interpolations available in imshow (which
explain why the imshow version is much "smoother" than the pcolormesh
one).
In fact, what would be needed is not the full flexibility of pcolormesh
(which can map the grid to any kind of shape), we "only" have to deal
with rectangular grids where x- and y- graduations are irregularly spaced.
Is there a drawing function in Matplotlib which would be able to work
with such a rectangular non-uniform grid?
And if not (and a quick look at the example and the code make me think 
that indeed the capability is currently not present),
what about an extension of imshow which would work as this:
 
im = imshow(Z,x_gridpos=x, y_gridpos=y) #specify the
position of the grid's nodes, instead of giving the extend and assuming
uniform spacing.
Longer term, would a pcolormesh accepting interpolation be possible? The
current behavior, averaging the color of the grids node to get a uniform
cell color, 
is quite rough except for a large number of cells...And even then, it
soon shows when you zoom in...
The best would be to allow the same interpolations as in imshow (or a
subset of it), and also allows to use interpolation before colormap
lookup (or after), 
like in Matlab. Indeed, Matlab allows to finely tune interpolation by
specifying Gouraud (interpolation after color
lookup)/Phong(interpolation before color lookup, i.e. for each pixel).
Phong is usually much better but also more CPU intensive. Phong is
especially when using discrete colormap, producing banded colors
equivalent to countour lines, while Gouraud does not work in those
cases.
Of course, the performance will be impacted by some of those
interpolation options, which would degrade performance in animations for
example.... but I think that having the different options available
would be very useful, it allows to have the highest map quality, or have
a "quick and dirty" map depending on situation (grid spacing, type of
map, animation or not, ...).
Best regards,
Greg.

On Fri, Aug 8, 2008 at 8:20 AM, Nils Wagner
<nw...@ia...> wrote:
> I have installed matplotlib locally on a linux box
> (without root access).
> Is it possible for o t h e r users to use my local
> matplotlib installation ? The problem is that show()
> doesn't produce a result on the screen.
>
> Any pointer would be appreciated.
This is really a question for matplotlib-users, but, there is no
reason this shouldn't work. Some of my colleagues have run out of my
directory before.
 * what backend are they using?
 * what test script are they trying (I suggest
examples/pylab_examples/simple_plot.py
 * what is the output of --verbose-debug when the other users run this script?
 * does it help to try different backends, eg if they run the script
with -dTKAgg, -dWXAgg, -dQt4Agg or -dGTKAgg
 * what are the permissions on your install directory -- can the
other uses see all the files?
 * what version of matplotlib are you using? What platform (you say
linux, but when reporting problems it helps to include as much detail
as possible). Are the users running from the console or an X11
session?
JDH

Hi all,
I have installed matplotlib locally on a linux box 
(without root access).
Is it possible for o t h e r users to use my local 
matplotlib installation ? The problem is that show() 
doesn't produce a result on the screen.
Any pointer would be appreciated.
 
Nils

John Hunter wrote:
> On Wed, Aug 6, 2008 at 8:51 AM, Manuel Metz <mm...@as...> wrote:
> 
>> I think the section Controlling axes properties of
>> http://matplotlib.sourceforge.net/tutorial.html needs to be updated, since
>>
>> frame = gca(gca(), 'frame')
>> setp(frame, 'linewidth', 2)
>>
>> doesn't work any more with mpl 0.98.x ...
> 
> Argg, the dreaded frame/patch rears it's ugly head. Eric, did you add
> the deprecation warning? It seems to me we could use set/get frame to
> set the frame attr and set/get patch to set the patch attr to support
> people used to the matlab idiom as in the tutorial above.
Uh, I just noticed that the example couldn't have worked before ;-)
 frame = gca(gca(), 'frame') # fails
--> frame = getp(gca(), 'frame') #
;-)