matplotlib-users Mailing List for matplotlib

I'm not aware of the problem (but I'm not a regular wxmpl user).

 From 0.91 to 0.98, a major refactoring was done to make it easier to 
add new kinds of projections.  So PolarAxes is no longer a special case, 
it is just one of many possible non-Cartesian projections.  
Unfortunately to do this, the API had to change in a number of places.  
These are documented in the API_CHANGES file in the "TRANSFORMS 
REFACTORING" section.

wxmpl needs to be updated based on those instructions in order to be 
compatible with mpl 0.98.  Hopefully that process won't be too 
difficult, but it's hard to say without trying.  basemap, a fairly large 
mpl toolkit, was able to handle the transition fairly smoothly.

Let me know if I can be of further assistance.

Cheers,
Mike

massimo sandal wrote:
> Hi,
>
> Sorry if bothering you. Here we use a software (that I've written) 
> that is based on wxmpl and matplotlib, among other things. A collegue 
> of mine noticed a problem when installing it on Windows, with the 
> following error:
>
>   File "hooke.py", line 21, in <module>
>     import wxmpl
>   File "C:\Python25\lib\site-packages\wxmpl.py", line 26, in <module>
>     from matplotlib.axes import PolarAxes, _process_plot_var_args
> ImportError: cannot import name PolarAxes
>
> He was using matplotlib 0.98.3 .Downgrading to 0.91 solved the issue.
> I remember the same happened when, some month ago, I tried to install 
> the same software on OS X using what were basically SVN versions of 
> mpl, labeled "0.98pre" (see http://macinscience.org/?page_id=6 )
>
> I guess you are probably aware of the problem: are you already working 
> on it :) ? Is there any workaround?
>
> I'd like to help you patching it, if within my skills, but I'd need 
> some direction on how the mpl API have been updated.
>
> m.
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>   

That looks perfect, how did you do it?

Thanks


kippertoffee wrote:
> 
> here's an example of pcolormesh on a random 10x10 array
> 
>  http://www.nabble.com/file/p18874393/spam2.png 
> 
> 
> stuartornum wrote:
>> 
>> Hi Pete,
>> 
>> Thanks for the quick response.
>> 
>> Will imshow() actually plot the graph?
>> 
>> Do I not need to do something like:
>> 
>> contourf(X, Y, Z, levels)
>> 
>> Thanks
>> 
> 
> 

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Hi,

Sorry if bothering you. Here we use a software (that I've written) that 
is based on wxmpl and matplotlib, among other things. A collegue of mine 
noticed a problem when installing it on Windows, with the following error:

   File "hooke.py", line 21, in <module>
     import wxmpl
   File "C:\Python25\lib\site-packages\wxmpl.py", line 26, in <module>
     from matplotlib.axes import PolarAxes, _process_plot_var_args
ImportError: cannot import name PolarAxes

He was using matplotlib 0.98.3 .Downgrading to 0.91 solved the issue.
I remember the same happened when, some month ago, I tried to install 
the same software on OS X using what were basically SVN versions of mpl, 
labeled "0.98pre" (see http://macinscience.org/?page_id=6 )

I guess you are probably aware of the problem: are you already working 
on it :) ? Is there any workaround?

I'd like to help you patching it, if within my skills, but I'd need some 
direction on how the mpl API have been updated.

m.
-- 
Massimo Sandal , Ph.D.
University of Bologna
Department of Biochemistry "G.Moruzzi"

snail mail:
Via Irnerio 48, 40126 Bologna, Italy

email:
mas...@un...

web:
http://www.biocfarm.unibo.it/samori/people/sandal.html

tel: +39-051-2094388
fax: +39-051-2094387

here's an example of pcolormesh on a random 10x10 array

http://www.nabble.com/file/p18874393/spam2.png 


stuartornum wrote:
> 
> Hi Pete,
> 
> Thanks for the quick response.
> 
> Will imshow() actually plot the graph?
> 
> Do I not need to do something like:
> 
> contourf(X, Y, Z, levels)
> 
> Thanks
> 

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What is the difference between setting clip_on and clip_box?  For an annotation, there does not appear to be any difference. But if I give the annotation a bbox, then only clip_box works to clip the box at the axes boundary.  The example below demonstrates:

from matplotlib.pyplot import figure, show

fig = figure()
ax = fig.add_subplot(111)

ax.annotate('This is a long annotation',
            xy=(1, 1),
            clip_on=True,
            bbox=dict(facecolor = 'white',
                      clip_on=True))
                      #clip_box = ax.bbox))

ax.set_xlim(-5, 2.8)
ax.set_ylim(-5, 5)
show()


PS. I am using MPL 0.98.3.

Hi Pete,

Thanks for the quick response.

Will imshow() actually plot the graph?

Do I not need to do something like:

contourf(X, Y, Z, levels)

Thanks
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> On Wed, Aug 6, 2008 at 5:02 PM, Richard Lawrence <rw...@ps...> wrote:

>> My setup is:
>> Mac Pro PPC G5, OS X 10.5.4
>> Python 2.5.1 (Apple build)
>> Numpy 1.2.0.dev5615 -- ran svn update and rebuilt this morning

>> REQUIRED DEPENDENCIES
>> ~                        * numpy 1.1 or later is required; you have
>> ~                        * 1.0.5.dev4673

Apple distributed a version of numpy with the system python, and set up 
sys.path so that their stuff would be found before site-packages, so you 
may be getting Apple's version of numpy rather than the one you built 
and installed. (I'm not running 10.5, so I can't supply details)

There are ways to work around this -- a little googling should help you 
figure it out, but I recommend that you avoid the whole problem (and 
others) by installing python.org's build of 2.5.2, and go from there -- 
the binaries on the numpy site are built for that version.

-Chris



-- 
Christopher Barker, Ph.D.
Oceanographer

Emergency Response Division
NOAA/NOS/OR&R            (206) 526-6959   voice
7600 Sand Point Way NE   (206) 526-6329   fax
Seattle, WA  98115       (206) 526-6317   main reception

Chr...@no...

Someone more knowlegeable than me may corrct me here, but the code for
getting your data into a grid could be greatly simplified to:

X = array([0,1,2,3,4,5,6,7,8,9,])
Y = array([0,1,2,3,4,5,6,7,8,9,])
Z = ListValues.reshape(10,10)

than you could use something like imshow() to show the data without any
interpolation.

Pete.

2008/8/7 stuartornum <st...@mu...>

>
> Hi,
>
> I have been using matplotlib for about 2 weeks now. I thought it would be
> good to try plotting heatmaps to show some data.
>
> The idea:
>
> I have 100 values all ranging from 0.00 to 1.00, I would like to create a
> graph with a 10 by 10 grid. Therefore each value has 1 section of the grid.
>
> So, for example if the value was 0.10, the colour would be blue, or if
> 0.95,
> the colour red.
>
> Now the problem is I do not know how to access each individual grid
> position, I guess I would have some form of counter system to count 0 -> 9
> on the X axis and 0 -> 9 on the Y also.
>
> Here is my pseudo code:
>
> ##########################################
>
> Count1 = 0   ## For the X axis
> Count2 = 0   ## For the Y axis
> Max = 0       ## To count 0 - 99
>
> ListValues = [0.11, 0.09, 0.34, 0.44, 0.29,.... all the way to 100 values]
>
> while Max < 100:
>
>        if Count1 == 10:
>                Count2 = Count2 + 1     ## Increase the Y axis by one
>                Count1 = 0                  ## If X axis counter = 10, reset
> it to 0
>        else:
>                GridPosition = []
>                GridPosition.append(Count1)
>                GridPosition.append(Count2)
>                GridValue = ListValues[Max]
>
>                # Now armed with the GridPosition and GridValue, im stuck on
> how to plot the square...
>
> ##########################################
>
> So as you can see from above, I have the data ready to fill the relevant
> grid position, just unsure on how to actually do it!
>
> Just to clarify, this is a heatmap, so the GridValue should correspond to a
> colour and fill that particular square with the colour from the colorbar
> i.e.
>
> levels = arange(0.0, 1.0, 0.025)
>
> Thank you in advance for any help.
> --
> View this message in context:
> http://www.nabble.com/Contour-Contourf-Plot-Heatmap---Grid---Multiple-Items-tp18872991p18872991.html
> Sent from the matplotlib - users mailing list archive at Nabble.com.
>
>
> -------------------------------------------------------------------------
> This SF.Net email is sponsored by the Moblin Your Move Developer's
> challenge
> Build the coolest Linux based applications with Moblin SDK & win great
> prizes
> Grand prize is a trip for two to an Open Source event anywhere in the world
> http://moblin-contest.org/redirect.php?banner_id=100&url=/
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>

Hi,

I have been using matplotlib for about 2 weeks now. I thought it would be
good to try plotting heatmaps to show some data.

The idea:

I have 100 values all ranging from 0.00 to 1.00, I would like to create a
graph with a 10 by 10 grid. Therefore each value has 1 section of the grid.

So, for example if the value was 0.10, the colour would be blue, or if 0.95,
the colour red.

Now the problem is I do not know how to access each individual grid
position, I guess I would have some form of counter system to count 0 -> 9
on the X axis and 0 -> 9 on the Y also.

Here is my pseudo code:

##########################################

Count1 = 0   ## For the X axis
Count2 = 0   ## For the Y axis
Max = 0       ## To count 0 - 99

ListValues = [0.11, 0.09, 0.34, 0.44, 0.29,.... all the way to 100 values]

while Max < 100:

	if Count1 == 10:                   
		Count2 = Count2 + 1     ## Increase the Y axis by one
		Count1 = 0                  ## If X axis counter = 10, reset it to 0
	else:
		GridPosition = []
                GridPosition.append(Count1)
                GridPosition.append(Count2)
                GridValue = ListValues[Max]
		
                # Now armed with the GridPosition and GridValue, im stuck on
how to plot the square...

##########################################

So as you can see from above, I have the data ready to fill the relevant
grid position, just unsure on how to actually do it!

Just to clarify, this is a heatmap, so the GridValue should correspond to a
colour and fill that particular square with the colour from the colorbar
i.e.

levels = arange(0.0, 1.0, 0.025)

Thank you in advance for any help.
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-----BEGIN PGP SIGNED MESSAGE-----
Hash: SHA1

John,

Thanks for your help.

|
| Most likely there is another version of numpy on your system that easy
| install is picking up (multiple versions of python perhaps?).  You
| might try to find them with
|
|   > find / -name numpy -type d
|
Indeed, this did turn up another installation, and I am now searching
for a third, even older one.  I wish I understood the layout of /Library
better...or that there was only a single site-packages directory for
each version of Python :)  Once I weed them all out, I will give the egg
another shot.  I would still like to be able to build it from source,
though, so I can stay up to date.

| Did you edit setupext.py to remove the basedir settings ans Charlie
| recommended?  Also, let's make sure that the files in your ld path are
| there and of the right type?  What does
|
|   > file /usr/local/src/mpl-build/libpng-1.2.29/libpng*
|
| return?
I did in fact edit setupext.py, and the 'darwin' key of basedir is set
to an empty list.  The file command does report universal binaries for
libpng*; the relevant output lines are:

libpng-1.2.29/libpng.a:                Mach-O universal binary with 2
architectures
libpng-1.2.29/libpng.a (for architecture i386):	current ar archive
random library
libpng-1.2.29/libpng.a (for architecture ppc):	current ar archive random
library

(There are similar messages for the various .o and .lo files.)

| One other option is to try following the build instructions I posted
| at http://ipython.scipy.org/moin/Py4Science/InstallationOSX

Actually, the reason I went with the "whole hog" method of compiling
libpng and freetype from source was that I was running into a similar
architecture error when I tried compiling against the freetype and
libpng in /usr/X11R6.  Perhaps there is some deeper include path issue
that I can't see?

- --
Richard Lawrence
Research Coordinator
Computational Memory Lab
rw...@ps...
215-746-0407
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Hello everybody,

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 pacolormesh
(which can map the grid to any kind of shape), we "only" have to deal
with rectangular grids
with irregularly spaced x- and y- graduations.

Is there a drawing function in Matplotlib which would be able to work
with such a rectangular non-uniform grid?
And if not, what about an extension of imshow which would work as this:
 
im = imshow(Z,x_gridpos=x, y_gridpos=y)  #specify explicitely the
position of the grid's node, 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.

In the following code the displayed image is initially displayed with axes
going from 0 to 103, ie there is no white space between the image and the
axes. 

After the first ginput mouse click the axes limits change to -20 to 120 with
white space between the image and the axes. This is a little disconcerting
if the user is trying to accurately pick points on an image. 

if I use ax1.axis('off') the white space disappears but the image changes
size. How do I fix the image size so ginput dosen't rescale it. 


import pylab

x1 = pylab.rand(103, 103)
fig1 = pylab.figure(1)
ax1 = fig1.add_subplot(111)
ax1.imshow(x1)
x = fig1.ginput(2)

fig1.show()
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On Wed, Aug 6, 2008 at 5:02 PM, Richard Lawrence <rw...@ps...> wrote:
> -----BEGIN PGP SIGNED MESSAGE-----
> Hash: SHA1
>
> Hello everyone,
>
> I've had a heck of a time trying to install matplotlib.  I've tried
> installing both from svn and from the pre-built 0.98.3 egg with no
> success.  Any tips would be appreciated.
>
> My setup is:
> Mac Pro PPC G5, OS X 10.5.4
> Python 2.5.1 (Apple build)
> Numpy 1.2.0.dev5615 -- ran svn update and rebuilt this morning
> Scipy 0.7.0.dev4603 -- ran svn update and rebuilt this morning
>
> 1. Error with the SourceForge 0.98.3 egg for OS X:
> $ easy_install matplotlib-0.98.3-py2.5-macosx-10.3.egg
> [snip]
> REQUIRED DEPENDENCIES
> ~                        * numpy 1.1 or later is required; you have
> ~                        * 1.0.5.dev4673
> error: Setup script exited with 1
>
> As far as I know, numpy 1.0.5.dev4673 was never installed on this
> machine.  Running python and checking numpy.__version__ gives the
> version string listed above (1.2.etc.).  I can't find any other versions
> on the system, and I don't know where the egg would be finding this
> phantom version.

Most likely there is another version of numpy on your system that easy
install is picking up (multiple versions of python perhaps?).  You
might try to find them with

  > find / -name numpy -type d

> - -lfreetype -lz -lz -lstdc++ -lm -o
> build/lib.macosx-10.3-fat-2.5/matplotlib/ft2font.so
> - -Wl,-framework,CoreServices,-framework,ApplicationServices
> ld: in /Developer/SDKs/MacOSX10.4u.sdk/usr/local/lib/libPng.dylib, file
> is not of required architecture for architecture i386
> collect2: ld returned 1 exit status
> lipo: can't open input file:
> /var/folders/7h/7hHE3mwXHGCNGWujjUd1L++++U2/-Tmp-//ccS3ZBhp.out (No such
> file or directory)
> error: command 'g++' failed with exit status 1
>
> ~From this, it would seem that the build is attempting to use an external
> libpng, despite the fact that I built it from source without a problem,
> it's located in /usr/local/src/mpl-build/libpng-1.2.29, and:
>
> $ echo $CFLAGS
> - -arch ppc -arch i386 -I/usr/local/src/mpl-build/libpng-1.2.29
> - -I/usr/local/src/mpl-build/freetype-2.3.7/include
> $ echo $LDFLAGS
> - -arch ppc -arch i386 -L/usr/local/src/mpl-build/libpng-1.2.29
> - -L/usr/local/src/mpl-build/freetype-2.3.7
>
> What am I missing?

Did you edit setupext.py to remove the basedir settings ans Charlie
recommended?  Also, let's make sure that the files in your ld path are
there and of the right type?  What does

  > file /usr/local/src/mpl-build/libpng-1.2.29/libpng*

return?

> Any help would be greatly appreciated...I've played with this all day
> and made little progress.

One other option is to try following the build instructions I posted
at http://ipython.scipy.org/moin/Py4Science/InstallationOSX