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I'm not understanding facecolor and edgecolor.
In the code below (on Windows, with TkAgg)
I get the facecolor displayed but not the
edgecolor, and the saved figure shows *neither*.
Why? (version is 0.98.1)
Thanks,
Alan Isaac
import matplotlib.pyplot as plt
import numpy as np
fig1 = plt.figure(1)
fig1.set_frameon(True)
fig1.set_facecolor('r')
fig1.set_edgecolor('b')
ax1 = fig1.gca()
ax1.plot([1,2,3])
fig1.savefig('c:/temp/temp.eps')
plt.show()

jtamir wrote:
> Hello,
>
> Is it possible to have basemap plot in the usual way on a polar-projection
> subplot?
> 
No.
> I want to do something like this:
> fig = plt.figure(figsize)
> ax = fig.add_subplot(111, polar=True)
> m = Basemap(...)
> m.drawcoastlines(...)
> etc.
>
> The reason I want to have a polar-projection plot is because I want to add
> concentric circles to the subplot using rgrids.
>
> Thanks,
>
> jtamir
> 
You can draw lines of latitude with the drawparallels method - these are 
concentric circles on a polar projection. 
-Jeff
-- 
Jeffrey S. Whitaker Phone : (303)497-6313
Meteorologist FAX : (303)497-6449
NOAA/OAR/PSD R/PSD1 Email : Jef...@no...
325 Broadway Office : Skaggs Research Cntr 1D-113
Boulder, CO, USA 80303-3328 Web : http://tinyurl.com/5telg

Hello,
Is it possible to have basemap plot in the usual way on a polar-projection
subplot?
I want to do something like this:
fig = plt.figure(figsize)
ax = fig.add_subplot(111, polar=True)
m = Basemap(...)
m.drawcoastlines(...)
etc.
The reason I want to have a polar-projection plot is because I want to add
concentric circles to the subplot using rgrids.
Thanks,
jtamir
-- 
View this message in context: http://www.nabble.com/Basemap---plot-on-a-polar-figure-tp23377500p23377500.html
Sent from the matplotlib - users mailing list archive at Nabble.com.

On Mon, May 4, 2009 at 10:50 AM, Matthieu Brucher <
mat...@gm...> wrote:
> Just compile numpy on a system that doesn't have lapack3 installed.
>
Unfortunately, this is going to be difficult - our build process is very
automated (done every night) and we use these systems for other things too,
so I'm very reluctant to tinker with the installed software, and I doubt we
have spare boxes with suitable hardware. I will talk to our admin but my
guess is he'll say the same thing.
thanks,
Nat

Eric and Thomas,
Thanks for your help. I was able to get it plotting MUCH faster. Here's my
code:
#!/usr/bin/env python
from pylab import *
from scipy import *
ion()
img = standard_normal((50,100))
image = imshow(img,interpolation='nearest',animated=True,label="blah")
for k in range(1,100):
 img = standard_normal((100,100))
 image.set_data(img)
 draw()
Thanks again.
-Joey
On Sat, May 2, 2009 at 1:27 PM, Eric Firing <ef...@ha...> wrote:
> Thomas Robitaille wrote:
>
>> Not sure if this will help, but maybe you can do something like this?
>>
>> ---
>> #!/usr/bin/env python
>>
>> from pylab import *
>> from scipy import *
>>
>
> To run this as a standalone script, without ipython -pylab, you need to
> include:
>
> ion()
>
>
>> img = standard_normal((40,40))
>> image = imshow(img,interpolation='nearest',animated=True,label="blah")
>>
>> for k in range(1,10000):
>> img = standard_normal((40,40))
>> image.set_data(img)
>> show()
>>
>
> show() should never be called more than once for a given figure; what you
> want here is draw().
>
> Eric
>
>
>
> ---
>>
>> Note, interpolation='nearest' can be faster than interpolation=None if
>> your default interpolation is set to bicubic (which it probably is)
>>
>> Does this speed things up?
>>
>> Thomas
>>
>> On May 1, 2009, at 3:31 PM, Joey Wilson wrote:
>>
>> I am creating a script that generates images and displays them to the
>>> screen in real time. I created the following simple script:
>>>
>>> __________________________
>>>
>>> #!/usr/bin/env python
>>>
>>> from pylab import *
>>> from scipy import *
>>>
>>> for k in range(1,10000):
>>> img = standard_normal((40,40))
>>> imshow(img,interpolation=None,animated=True,label="blah")
>>> clf()
>>> show()
>>>
>>> __________________________
>>>
>>> Now, this script plots the image too slowly. I am forced to use the
>>> clf() function so that it doesn't slow down at each iteration of the for
>>> loop. Is there a way that I can plot this simple image faster? What's the
>>> best way to get imshow() to plot quickly? Thanks for your help.
>>>
>>> -Joey
>>>
>>>
>>> ------------------------------------------------------------------------------
>>> Register Now & Save for Velocity, the Web Performance & Operations
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>>>
>>
>>
>>
>> ------------------------------------------------------------------------------
>> Register Now & Save for Velocity, the Web Performance & Operations
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>> extra 15% before 5/3. http://p.sf.net/sfu/velocityconf
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>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>
>
>

Hi,
Just compile numpy on a system that doesn't have lapack3 installed.
Matthieu
2009年5月4日 Nathaniel Echols <nat...@gm...>:
> I need to distribute matplotlib as part of a large and somewhat
> heterogeneous package of Python-based software. On Macs, lapack is
> installed by default, and I can rely on the linking working regardless of
> which OS version it was compiled on (we use 10.4.11, but it runs fine on
> 10.5). On Linux, it's variable - the kernel 2.6-based OSes we use appear to
> have it, but not the older 2.4-based systems. For the older systems this is
> not a problem - it results in this:
>
> nat@linux2.4> ldd lapack_lite.so
>     linux-gate.so.1 => (0xffffe000)
>     libc.so.6 => /lib/libc.so.6 (0xf7d97000)
>     /lib/ld-linux.so.2 (0x56555000)
> The lack of links to the full lapack module doesn't appear to break anything
> that I do - I'm just plotting simple lines and I don't use any of the numpy
> routines in my code.
> This is what happens on the newer systems:
> nat@linux2.6> ldd lapack_lite.so
>     linux-gate.so.1 => (0xffffe000)
>     liblapack.so.3 => not found
>     libblas.so.3 => not found
>     libg2c.so.0 => /usr/lib/libg2c.so.0 (0xf7fb6000)
>     libm.so.6 => /lib/libm.so.6 (0xf7f8f000)
>     libgcc_s.so.1 => /lib/libgcc_s.so.1 (0xf7f82000)
>     libc.so.6 => /lib/libc.so.6 (0xf7e45000)
>     /lib/ld-linux.so.2 (0x56555000)
> This results in an import error on systems that *don't* have lapack3
> installed. We would prefer to avoid having to tell our users to install
> more software in order to use what I've written. Is there any way to force
> numpy to *not* link to anything besides what it saw in the first example? I
> would prefer to avoid hacking into the numpy distutils scripts if possible.
> Sorry this isn't directly matplotlib-related, but I thought I'd see if
> someone here had encountered this problem before I subscribed to another
> list.
> thanks,
> Nat
> ------------------------------------------------------------------------------
> Register Now & Save for Velocity, the Web Performance & Operations
> Conference from O'Reilly Media. Velocity features a full day of
> expert-led, hands-on workshops and two days of sessions from industry
> leaders in dedicated Performance & Operations tracks. Use code vel09scf
> and Save an extra 15% before 5/3. http://p.sf.net/sfu/velocityconf
> _______________________________________________
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> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
>
-- 
Information System Engineer, Ph.D.
Website: http://matthieu-brucher.developpez.com/
Blogs: http://matt.eifelle.com and http://blog.developpez.com/?blog=92
LinkedIn: http://www.linkedin.com/in/matthieubrucher

I need to distribute matplotlib as part of a large and somewhat
heterogeneous package of Python-based software. On Macs, lapack is
installed by default, and I can rely on the linking working regardless of
which OS version it was compiled on (we use 10.4.11, but it runs fine on
10.5). On Linux, it's variable - the kernel 2.6-based OSes we use appear to
have it, but not the older 2.4-based systems. For the older systems this is
not a problem - it results in this:
nat@linux2.4> ldd lapack_lite.so
 linux-gate.so.1 => (0xffffe000)
 libc.so.6 => /lib/libc.so.6 (0xf7d97000)
 /lib/ld-linux.so.2 (0x56555000)
The lack of links to the full lapack module doesn't appear to break anything
that I do - I'm just plotting simple lines and I don't use any of the numpy
routines in my code.
This is what happens on the newer systems:
nat@linux2.6> ldd lapack_lite.so
 linux-gate.so.1 => (0xffffe000)
 liblapack.so.3 => not found
 libblas.so.3 => not found
 libg2c.so.0 => /usr/lib/libg2c.so.0 (0xf7fb6000)
 libm.so.6 => /lib/libm.so.6 (0xf7f8f000)
 libgcc_s.so.1 => /lib/libgcc_s.so.1 (0xf7f82000)
 libc.so.6 => /lib/libc.so.6 (0xf7e45000)
 /lib/ld-linux.so.2 (0x56555000)
This results in an import error on systems that *don't* have lapack3
installed. We would prefer to avoid having to tell our users to install
more software in order to use what I've written. Is there any way to force
numpy to *not* link to anything besides what it saw in the first example? I
would prefer to avoid hacking into the numpy distutils scripts if possible.
Sorry this isn't directly matplotlib-related, but I thought I'd see if
someone here had encountered this problem before I subscribed to another
list.
thanks,
Nat

On Mon, May 4, 2009 at 2:22 AM, Erik Tollerud <eri...@gm...>wrote:
> I'm hoping to generate a line plot where the color of each pixel on
> the plot is given by linearly interpolating the colormap from each
> point specified in the line, instead of having the whole line be a
> solid color. I can "mock this up" by doing a scatter plot where the
> points are much closer together than the screen resolution, but that
> seems inelegant, and sometimes produces weird output. So is there a
> way to do effectively the same thing with a line plot or somehow
> specify this behavior in scatter?
IIRC, the backends that matplotlib uses (Gtk, Agg, etc.) only support a
single color per line, so breaking up the line into different
segments/points is really your only option. Instead of scatter, you can
break up your line into separate sections and have them colormapped for you,
using a LineCollection.
Ryan
-- 
Ryan May
Graduate Research Assistant
School of Meteorology
University of Oklahoma
Sent from Norman, Oklahoma, United States

I believe that it is just moved to another directory (lib/matplotlib/sphinxext).
http://www.nabble.com/Re%3A-Sphinx-custom-extension-mess%2C-and-patches-p22037746.html
Regards,
-JJ
On Mon, May 4, 2009 at 11:02 AM, Timmie <tim...@gm...> wrote:
> Hello,
> why is the matplotlib.sphinxext.mathmpl been taken off the SVN repository:
> https://matplotlib.svn.sourceforge.net/svnroot/
> matplotlib/trunk/matplotlib/doc/sphinxext/
>
> I have been using it to parse formulas in my documentation source.
>
> It is still used by the Sphinx configuration from mpl svn:
>
> extensions = ['matplotlib.sphinxext.mathmpl', 'math_symbol_table',
>       'sphinx.ext.autodoc', 'matplotlib.sphinxext.only_directives',
>       'matplotlib.sphinxext.plot_directive', 'inheritance_diagram',
>       'gen_gallery', 'gen_rst']
>
> Thanks in advance,
> Timmie
>
>
> ------------------------------------------------------------------------------
> Register Now & Save for Velocity, the Web Performance & Operations
> Conference from O'Reilly Media. Velocity features a full day of
> expert-led, hands-on workshops and two days of sessions from industry
> leaders in dedicated Performance & Operations tracks. Use code vel09scf
> and Save an extra 15% before 5/3. http://p.sf.net/sfu/velocityconf
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>

Hello,
why is the matplotlib.sphinxext.mathmpl been taken off the SVN repository:
https://matplotlib.svn.sourceforge.net/svnroot/
matplotlib/trunk/matplotlib/doc/sphinxext/
I have been using it to parse formulas in my documentation source.
It is still used by the Sphinx configuration from mpl svn:
extensions = ['matplotlib.sphinxext.mathmpl', 'math_symbol_table', 
 'sphinx.ext.autodoc', 'matplotlib.sphinxext.only_directives',
 'matplotlib.sphinxext.plot_directive', 'inheritance_diagram',
 'gen_gallery', 'gen_rst']
Thanks in advance,
Timmie

Hi,
I'm new with matplotlib.
I need to make a graph with the X axis represents time in hours and
minutes. My script don't works, I want to display all the values of time
that I have.
I use a list of string like this :
t=['0015', '0030', '0045', '0100', '0115', '0130', '0145', '0200',
'0215', '0230', '0245', '0300', '03
15', '0330', '0345', '0400', '0415', '0430', '0445', '0500', '0515',
'0530', '0545', '0600', '0615',
 '0630', '0645', '0700', '0715', '0730', '0745', '0800', '0815', '0830',
'0845', '0900', '0915', '09
30', '0945', '1000', '1015', '1030', '1045', '1100', '1115', '1130',
'1145', '1200', '1215', '1230',
 '1245', '1300', '1315', '1330', '1345', '1400', '1415']
ax.plot(t, y)
I tried to convert hours and minutes to the base 100 ( , it works but I
can not show on the x-axis the hours, minutes.
I tried to use plot_date, but I don't understand "x and/or y can be a
sequence of dates represented as float days since 0001年01月01日 UTC."
Could you help me, please ?
/olivier

Hi John,
On Sun, May 3, 2009 at 00:21, John Hunter <jd...@gm...> wrote:
> On Sat, May 2, 2009 at 9:42 AM, Sandro Tosi <mo...@de...> wrote:
>>
>> Hi all!
>> I'd like to embed a mpl graph into a GTK application (and for that
>> embedding_in_gtk*.py examples are fine) but I would also like to
>> dynamically update the graph with time.
>
>
>>
>> Consider like if I want to plot some dynamic system information, like
>> cpu usage, memory occupation, or so. Than I want to gather those info
>> at 1 sec interval, and dynamically update the graph adding the new
>> values.
>>
>> How can I do it? I'm stuck with the "update data as they come" part
>> (please note I need for GTK embedded mpl code).
>
> The idioms in the examples/animations dir should be directly portable
> to an embedded gtk app, eg simple_anim_gtk.py,
> dynamic_image_gtkagg.py, etc.  You will need to either use an idle
> handle, a timeout handler, or a special event in the gtk event
> handling framework to trigger an update to the data and draw. You can
> extend the gobject signals to handle custom events (eg data arrives)
> if you want to go this route, but since you are trying to illustrate
> mpl more than gtk (I assume) you may want to go the easy route and use
you assume right :)
> the timeout or idle handler and just check and see if new data has
> arrived and then update as necessary.
yeah, I solved with "gobject.idle_add"
>> PS: if there's someone that knows how to gather cpu percentage usage
>> on a linux sys, please tell me :) It seems not that easy to find it
>> out from google ;)
>
> http://tinyurl.com/d7lkga
>
> Sorry :-) Couldn't resist
ehhe :) but you're right, I've expressed the question wrongly: I was
searching some python module / binding :)
> (less obnoxious answer
> http://www.cyberciti.biz/tips/how-do-i-find-out-linux-cpu-utilization.html)
At the end I used subprocess module to call sar
Cheers,
-- 
Sandro Tosi (aka morph, morpheus, matrixhasu)
My website: http://matrixhasu.altervista.org/
Me at Debian: http://wiki.debian.org/SandroTosi

Hi,
Could you send your setup.
I'm not expert but I can check it.
/olivier 
-----Original Message-----
From: sordnay [mailto:so...@gm...] 
Sent: jeudi 30 avril 2009 18:23
To: mat...@li...
Subject: [Matplotlib-users] mathtext and py2exe
hello,
I have written a program which uses matplotlib to plot some figures, it
uses mathtext to add some special chars (basically just the square on
acceleration units), and the program works just fine, but using py2exe
to build a windows executable, it fails somewhere drawing that square
symbol. 
The error the program yields is something like "unable to convert string
to unicode". 
Has anyone experienced this kind of problem with mathtext and py2exe or
has any clue what is needed to be included at the py2exe setup.py to fix
it?
I know this is not the best place for an answer, but I couldn't find
where to get help on py2exe site :-/ so if anyone could help...
Thanks a lot.
--
View this message in context:
http://www.nabble.com/mathtext-and-py2exe-tp23319691p23319691.html
Sent from the matplotlib - users mailing list archive at Nabble.com.
------------------------------------------------------------------------
------
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Hi Erik,
On Mon, May 4, 2009 at 09:22, Erik Tollerud <eri...@gm...> wrote:
> I'm hoping to generate a line plot where the color of each pixel on
> the plot is given by linearly interpolating the colormap from each
> point specified in the line, instead of having the whole line be a
> solid color. I can "mock this up" by doing a scatter plot where the
> points are much closer together than the screen resolution, but that
> seems inelegant, and sometimes produces weird output. So is there a
> way to do effectively the same thing with a line plot or somehow
> specify this behavior in scatter?
maybe this[1] could be of help?
[1] http://www.scipy.org/Cookbook/Matplotlib/MulticoloredLine
Cheers,
-- 
Sandro Tosi (aka morph, morpheus, matrixhasu)
My website: http://matrixhasu.altervista.org/
Me at Debian: http://wiki.debian.org/SandroTosi

I'm hoping to generate a line plot where the color of each pixel on
the plot is given by linearly interpolating the colormap from each
point specified in the line, instead of having the whole line be a
solid color. I can "mock this up" by doing a scatter plot where the
points are much closer together than the screen resolution, but that
seems inelegant, and sometimes produces weird output. So is there a
way to do effectively the same thing with a line plot or somehow
specify this behavior in scatter?