matplotlib-users Mailing List for matplotlib (Page 12)

On 09/13/2010 04:46 PM, jules hummon wrote:
> Virgil
>
> The scheme illustrated below actually does work.
>
>> Message: 5
>> Date: 2010年9月13日 12:55:43 -1000
>> From: Eric Firing<ef...@ha...>
>> Subject: Re: [Matplotlib-users] matplotlib on Ubuntu 10.04 (64-bit)
>> To: mat...@li...
>> Message-ID:<4C8...@ha...>
>> Content-Type: text/plain; charset="iso-8859-1"
>>
>> On 09/13/2010 12:08 PM, Virgil Stokes wrote:
>>>> On 2010年09月13日 21:55, Benjamin Root wrote:
>>>>>> On Mon, Sep 13, 2010 at 2:38 PM, Virgil Stokes<vs...@it...
>>>>>> <mailto:vs...@it...>> wrote:
>>>>>>
>
>
>> If you would like up-to-date versions of both numpy and matplotlib, then
>> you can either find and install the *dev packages individually, or do
>> something like this:
>>
>> sudo apt-get build-dep python-matplotlib
>> sudo apt-get remove python
> ^^^^^^^
>
> No, that is probably supposed to be
>
> 	sudo apt-get remove numpy
Horrible mistake on my part. Put your version and mine together, and it 
works:
sudo apt-get remove python-numpy
>
>>
>> Now untar your numpy, go in, build and install:
>>
>> setup.py build
>> sudo setup.py install
>>
>> And last, do the same for matplotlib, preferably with a checkout from
>> svn. Some bugs have been fixed since the last release.
>>
>> Before all of this, you might do well to uninstall whatever versions or
>> parts of numpy and matplotlib had been installed via your previous efforts.
>>
> >[snip]
> >
> > Eric
>
> You can tell whether you have any leftover pieces of numpy or matplotlib
> from the *.deb files by looking in /usr/lib/python2.6/dist-packages
> for "numpy" or "matplotlib".
>
> Eric, the script was scrubbed. Does it land somewhere else?
It was in the message as distributed, and as received by at least one 
mail archive:
http://www.mail-archive.com/mat...@li.../msg18475.html
Eric
>
> Jules
>
> (Jules Hummon/Univ. Hawaii/physical oceanography)
>

Hi Ben,
Thanks for your reply it sure helps.
My awkward work around until now was to put before the colorbar:
matplotlib.rc('axes',edgecolor='w')
and the return it to
matplotlib.rc('axes',edgecolor='k').
Does some one knows how to increase the distance between the color bar and
the X-axis ?
Now I noticed that the color bar hides the xlabel ....
Thanks again,
Oz
> I agree, Colorbar isn't the most elegant of objects and is probably due for
> some improvements. I am sure there is probably a better way to do what you
> have done, but I am not familiar with it. Anyway, to get rid of the box
> around the colorbar, the colorbar object has a member attribute called
> "outline" which you can set_visible(False).
>
> a = plt.colorbar()
> a.outline.set_visible(False)
>
> Should do the trick for that part.
>
> I hope this helps!
> Ben Root
>
>
-- 
Oz Nahum
Graduate Student
Zentrum für Angewandte Geologie
Universität Tübingen
---
Imagine there's no countries
it isn't hard to do
Nothing to kill or die for
And no religion too
Imagine all the people
Living life in peace

Virgil
The scheme illustrated below actually does work.
> Message: 5
> Date: 2010年9月13日 12:55:43 -1000
> From: Eric Firing <ef...@ha...>
> Subject: Re: [Matplotlib-users] matplotlib on Ubuntu 10.04 (64-bit)
> To: mat...@li...
> Message-ID: <4C8...@ha...>
> Content-Type: text/plain; charset="iso-8859-1"
>
> On 09/13/2010 12:08 PM, Virgil Stokes wrote:
>> > On 2010年09月13日 21:55, Benjamin Root wrote:
>>> >> On Mon, Sep 13, 2010 at 2:38 PM, Virgil Stokes <vs...@it...
>>> >> <mailto:vs...@it...>> wrote:
>>> >>
> If you would like up-to-date versions of both numpy and matplotlib, then
> you can either find and install the *dev packages individually, or do
> something like this:
>
> sudo apt-get build-dep python-matplotlib
> sudo apt-get remove python
 ^^^^^^^
No, that is probably supposed to be
	sudo apt-get remove numpy
>
> Now untar your numpy, go in, build and install:
>
> setup.py build
> sudo setup.py install
>
> And last, do the same for matplotlib, preferably with a checkout from
> svn. Some bugs have been fixed since the last release.
>
> Before all of this, you might do well to uninstall whatever versions or
> parts of numpy and matplotlib had been installed via your previous efforts.
>
 >[snip]
 >
 > Eric
You can tell whether you have any leftover pieces of numpy or matplotlib
from the *.deb files by looking in /usr/lib/python2.6/dist-packages
for "numpy" or "matplotlib".
Eric, the script was scrubbed. Does it land somewhere else?
Jules
(Jules Hummon/Univ. Hawaii/physical oceanography)

On Mon, Sep 13, 2010 at 5:55 PM, Eric Firing <ef...@ha...> wrote:
> On 09/13/2010 12:08 PM, Virgil Stokes wrote:
>
>> On 2010年09月13日 21:55, Benjamin Root wrote:
>>
>>> On Mon, Sep 13, 2010 at 2:38 PM, Virgil Stokes <vs...@it...
>>> <mailto:vs...@it...>> wrote:
>>>
>>> I have tried to produce a very simple plot with my recent
>>> installation of matplotlib (1.0.0 64-bit) and numpy (1.5.0 64-bit)
>>> using the following code (taken from the matplotlib tutorial
>>> material).
>>>
>>> *import matplotlib
>>> import numpy
>>> import matplotlib.pyplot as plt
>>>
>>> print matplotlib.__version__
>>> print numpy.__version__
>>>
>>> plt.plot([1,2,3,4])
>>> plt.ylabel('some numbers')
>>> plt.show()*
>>>
>>> If I execute this in Windows 7 (64-bit) it works correctly. If I
>>> execute this in Windows Vista (32-bit) it works correctly.
>>> If I execute this in Ubuntu 10.04 64-bit the versions are printed
>>> out correctly and thus I believe that the packages are being
>>> imported; but, /no plot is produced!/
>>>
>>> Why not?
>>>
>>>
>>> Virgil,
>>>
>>> Did you build matplotlib from source?
>>>
>> I did try this and believe that it succeeded (saw no errors displayed
>> during the build).
>>
>>> If so, then chances are that one or more backends were not built
>>> properly.
>>>
>> But, I do not understand what you mean here...
>>
>>> This typically happens if you do not have all the build dependencies.
>>>
>> And what can I do to correct this?
>>
>>>
>>> Note, the build will not necessarily fail if some dependencies are
>>> missing because the core portions of matplotlib still build successfully.
>>>
>> Sorry Ben, bu I do not understand what you mean here.
>> Would you please explain how I can use some combination of the following
>> (with Python 2.6 on Ubuntu 10.04 both 64-bit) to get a working
>> matplotlib and numpy.
>>
>> * *python-numpy_1.4.1-4_amd64.deb*
>> * *python-numpy_1.5.0-1ppa1_amd64.deb*
>> * *numpy-1.5.0.tar.gz*
>>
>> and,
>>
>> * *matplotlib_0.99.3-1ubuntu1.debian.tar.gz*
>> * *matplotlib_0.99.3.orig.tar.gz*
>> * *matplotlib-1.0.0.tar.gz*
>>
>> This has become such a frustrating task that I would settle for vers.
>> 0.99.3 of matplotlib and/or vers. 1.4.1-4 of numpy. I thought I
>> understood Python and Ubuntu 10.04 enough to accomplish this task; but,
>> obviously this was not the case. And I have looked at the FAQs and help
>> given at matplotlib's homepage.
>>
>
> If you would like up-to-date versions of both numpy and matplotlib, then
> you can either find and install the *dev packages individually, or do
> something like this:
>
> sudo apt-get build-dep python-matplotlib
> sudo apt-get remove python
>
> Now untar your numpy, go in, build and install:
>
> setup.py build
> sudo setup.py install
>
> And last, do the same for matplotlib, preferably with a checkout from svn.
> Some bugs have been fixed since the last release.
>
> Before all of this, you might do well to uninstall whatever versions or
> parts of numpy and matplotlib had been installed via your previous efforts.
>
> The point of the first apt-get is to install things like freetype and the
> gui toolkits. The only problem is that this also installs an old version of
> numpy, hence the second apt-get command.
>
> The good news is that once you get over the hump of having the dependencies
> installed, subsequent updates and compilations of numpy and matplotlib are
> easy. It is usually advisable to delete the build directory, since setup.py
> is not very smart with respect to knowing what needs to be recompiled.
> Sometimes it is also necessary to clean out the old version from its
> installation location. See attached script for an example of mpl
> uninstallation.
>
> Eric
>
>
Eric,
I keep on forgetting about that useful build-dep command. Maybe it might be
a good idea to include some of this information in the documentation as a
tip of some sort? I should also see if yum for RedHat-based systems also
have something similar. Finding all the dependencies can be a little
tedious at times and I often over-do it.
Ben Root

On Tue, Sep 14, 2010 at 12:09 AM, Kenshi hibino
<hi...@ku...> wrote:
> I thought that "axis([0,pi,0,1])" make the writing domain semi-circle,
> but complete circle was written as domain.
>
> Does anyone know how I should write?
>
With "polar" projection, it is not possible to make semi-circle domain.
You need to make a custom projection
(http://matplotlib.sourceforge.net/devel/add_new_projection.html). But
it would not be easy for a normal user.
Another option is to use mpl_toolkits.axisartist (distributed with mpl
1.0). However, learning curve of the axisartist is also steep. You may
play around with the last figure in the example below.
http://matplotlib.sourceforge.net/examples/axes_grid/demo_floating_axes.html
Regards,
-JJ

On 09/13/2010 12:08 PM, Virgil Stokes wrote:
> On 2010年09月13日 21:55, Benjamin Root wrote:
>> On Mon, Sep 13, 2010 at 2:38 PM, Virgil Stokes <vs...@it...
>> <mailto:vs...@it...>> wrote:
>>
>> I have tried to produce a very simple plot with my recent
>> installation of matplotlib (1.0.0 64-bit) and numpy (1.5.0 64-bit)
>> using the following code (taken from the matplotlib tutorial
>> material).
>>
>> *import matplotlib
>> import numpy
>> import matplotlib.pyplot as plt
>>
>> print matplotlib.__version__
>> print numpy.__version__
>>
>> plt.plot([1,2,3,4])
>> plt.ylabel('some numbers')
>> plt.show()*
>>
>> If I execute this in Windows 7 (64-bit) it works correctly. If I
>> execute this in Windows Vista (32-bit) it works correctly.
>> If I execute this in Ubuntu 10.04 64-bit the versions are printed
>> out correctly and thus I believe that the packages are being
>> imported; but, /no plot is produced!/
>>
>> Why not?
>>
>>
>> Virgil,
>>
>> Did you build matplotlib from source?
> I did try this and believe that it succeeded (saw no errors displayed
> during the build).
>> If so, then chances are that one or more backends were not built
>> properly.
> But, I do not understand what you mean here...
>> This typically happens if you do not have all the build dependencies.
> And what can I do to correct this?
>>
>> Note, the build will not necessarily fail if some dependencies are
>> missing because the core portions of matplotlib still build successfully.
> Sorry Ben, bu I do not understand what you mean here.
> Would you please explain how I can use some combination of the following
> (with Python 2.6 on Ubuntu 10.04 both 64-bit) to get a working
> matplotlib and numpy.
>
> * *python-numpy_1.4.1-4_amd64.deb*
> * *python-numpy_1.5.0-1ppa1_amd64.deb*
> * *numpy-1.5.0.tar.gz*
>
> and,
>
> * *matplotlib_0.99.3-1ubuntu1.debian.tar.gz*
> * *matplotlib_0.99.3.orig.tar.gz*
> * *matplotlib-1.0.0.tar.gz*
>
> This has become such a frustrating task that I would settle for vers.
> 0.99.3 of matplotlib and/or vers. 1.4.1-4 of numpy. I thought I
> understood Python and Ubuntu 10.04 enough to accomplish this task; but,
> obviously this was not the case. And I have looked at the FAQs and help
> given at matplotlib's homepage.
If you would like up-to-date versions of both numpy and matplotlib, then 
you can either find and install the *dev packages individually, or do 
something like this:
sudo apt-get build-dep python-matplotlib
sudo apt-get remove python
Now untar your numpy, go in, build and install:
setup.py build
sudo setup.py install
And last, do the same for matplotlib, preferably with a checkout from 
svn. Some bugs have been fixed since the last release.
Before all of this, you might do well to uninstall whatever versions or 
parts of numpy and matplotlib had been installed via your previous efforts.
The point of the first apt-get is to install things like freetype and 
the gui toolkits. The only problem is that this also installs an old 
version of numpy, hence the second apt-get command.
The good news is that once you get over the hump of having the 
dependencies installed, subsequent updates and compilations of numpy and 
matplotlib are easy. It is usually advisable to delete the build 
directory, since setup.py is not very smart with respect to knowing what 
needs to be recompiled. Sometimes it is also necessary to clean out the 
old version from its installation location. See attached script for an 
example of mpl uninstallation.
Eric

On 09/11/2010 11:12 AM, freeeeeekk wrote:
>
> Im trying to do a very simple x vs y plot. Where the x values range between
> 3247 and 3256 and y between 0 and 1. This data is stored in data.dat. I plot
> it using the code below, the resulting plot is shown in the first of the two
> plots below. Everything goes well except for the x axis, for some reason
> tickmarks from 0 up to 9 appear. At the far end of the axis my xmin is
> printed: 3.247e3.
> I started looking for the cause and it turns out that as long as my range in
> x is lower than 10, this happens. If I change the xlimits to xlim(3246,3256)
> I get the plot at the bottom of this page, everything is fine. But if I
> change this to for instance xlim(3246.01,3256) or xlim(3245, 3254.99) I get
> the same behaviour as in the first graph.
>
> Does any one have any experience with this/ know the reason for this
> happening? Thanks!
>
> from numpy import *
> from pylab import *
>
> datafile = mlab.load('./data.dat')
> xx=datafile[:,0]
> yy=datafile[:,1]
>
> plot(xx,yy,'black')
> xlim(3247,3256)
> ylim(0,1.2)
with older mpl, try this:
gca().xaxis.set_major_formatter(ScalarFormatter(useOffset=False))
with 1.0 or later try the following instead:
ticklabel_format(useOffset=False)
Eric
>
> show()
>
>
> http://old.nabble.com/file/p29687404/wrong.png
> http://old.nabble.com/file/p29687404/right.png

The solution incase anyone has a similar issue...
data = np.random.randint(0,50,100*100).reshape(100, 100) 
m = Basemap(llcrnrlon=1.5, llcrnrlat=10.5, urcrnrlon=3.5, urcrnrlat=13.5,
 resolution='c', projection='cyl') 
fig = plt.figure(figsize=(8, 6)) 
ax = fig.add_axes([0.1, 0.1, 0.6, 0.7])
m.ax = ax 
ticks = [0, 10, 20, 30, 40, 50]
colours = cm.Greys_r(np.linspace(0.3, 1.0, 6))
colourmap = colors.ListedColormap(colours)
norm = colors.BoundaryNorm(ticks, colourmap.N)
im = m.imshow(data, cmap=colourmap, norm=norm, interpolation='nearest')
pos = ax.get_position()
l, b, w, h = pos.bounds
cax = plt.axes([l+w+0.045, b, 0.05, h]) 
cbar = mpl.colorbar.ColorbarBase(cax, cmap=colourmap, norm=norm,
ticks=ticks)
plt.show()
-- 
View this message in context: http://old.nabble.com/Exclude-colour-from-a-colourbar-tp29699746p29703615.html
Sent from the matplotlib - users mailing list archive at Nabble.com.

Many thanks, that helper.
After some more problems with scipy, I got a working EXE.
PyQt4 is still in the library, though. Eating almost 15Mb... Now all I
have to do is to find out how to remove it..
cheers
Carlos
On Mon, Sep 13, 2010 at 18:47, Goyo <goy...@gm...> wrote:
> 2010年9月13日 Carlos Grohmann <car...@gm...>:
>> Hello all,
>>
>> I'm trying to build an executable distribution of an app I'm working
>> using py2exe.
>>
>> After a lot of googling, I found what it seems to be a good
>> combination of parameters, but when I try to run the .exe, it fails.
>>
>> The .log file shows me that the module backend_qt4agg wasn't found:
>>
>>> ImportError: No module named backend_qt4agg
>>
>> Also, using py2exe -x shows me that PyQt4 is being imported by
>> matplotlib.pyplot.
>>
>> The thing is, this is a WxPython application.
>>
>> Why is pyplot importing pyqt?? How do I stop it?
>
> Maybe it's specified in the matplotlib.rc.
> Make sure your intended backend is in use *before* you import pyplot:
>
> import matplotlib as mpl
> mpl.use('WXAgg')
> import pyplot as plt
>
-- 
Prof. Carlos Henrique Grohmann - Geologist D.Sc.
Institute of Geosciences - Univ. of São Paulo, Brazil
http://www.igc.usp.br/pessoais/guano
http://lattes.cnpq.br/5846052449613692
Linux User #89721
________________
Can’t stop the signal.

 On 2010年09月13日 21:55, Benjamin Root wrote:
> On Mon, Sep 13, 2010 at 2:38 PM, Virgil Stokes <vs...@it... 
> <mailto:vs...@it...>> wrote:
>
> I have tried to produce a very simple plot with my recent
> installation of matplotlib (1.0.0 64-bit) and numpy (1.5.0 64-bit)
> using the following code (taken from the matplotlib tutorial
> material).
>
> *import matplotlib
> import numpy
> import matplotlib.pyplot as plt
>
> print matplotlib.__version__
> print numpy.__version__
>
> plt.plot([1,2,3,4])
> plt.ylabel('some numbers')
> plt.show()*
>
> If I execute this in Windows 7 (64-bit) it works correctly. If I
> execute this in Windows Vista (32-bit) it works correctly.
> If I execute this in Ubuntu 10.04 64-bit the versions are printed
> out correctly and thus I believe that the packages are being
> imported; but, /no plot is produced!/
>
> Why not?
>
>
> Virgil,
>
> Did you build matplotlib from source?
I did try this and believe that it succeeded (saw no errors displayed 
during the build).
> If so, then chances are that one or more backends were not built 
> properly.
But, I do not understand what you mean here...
> This typically happens if you do not have all the build dependencies.
And what can I do to correct this?
>
> Note, the build will not necessarily fail if some dependencies are 
> missing because the core portions of matplotlib still build successfully.
Sorry Ben, bu I do not understand what you mean here.
Would you please explain how I can use some combination of the following 
(with Python 2.6 on Ubuntu 10.04 both 64-bit) to get a working 
matplotlib and numpy.
* *python-numpy_1.4.1-4_amd64.deb*
* *python-numpy_1.5.0-1ppa1_amd64.deb*
* *numpy-1.5.0.tar.gz*
and,
* *matplotlib_0.99.3-1ubuntu1.debian.tar.gz*
* *matplotlib_0.99.3.orig.tar.gz*
* *matplotlib-1.0.0.tar.gz*
This has become such a frustrating task that I would settle for vers. 
0.99.3 of matplotlib and/or vers. 1.4.1-4 of numpy. I thought I 
understood Python and Ubuntu 10.04 enough to accomplish this task; but, 
obviously this was not the case. And I have looked at the FAQs and help 
given at matplotlib's homepage.
--V

On 9/11/2010 3:10 PM, Oz Nahum wrote:
> my question, how to remove the axes around the colorbar, or at least changed the to be non-visible, still stands...
Did you resolve this?
Alan Isaac

On Sat, Sep 11, 2010 at 2:10 PM, Oz Nahum <na...@gm...> wrote:
> Hi Everyone again,
>
> So, with the weekend comes some time to think and I found an answer to
> another question of mine.
>
> I know now how to remove xticks in colorbar, and I also know how to
> customize the widths of the lines in the color bar.
>
> import matplotlib
> import numpy as np
> import matplotlib.cm as cm
> import matplotlib.mlab as mlab
> import matplotlib.pyplot as plt
> from pylab import *
>
> matplotlib.rcParams['xtick.direction'] = 'out'
> matplotlib.rcParams['ytick.direction'] = 'out'
>
> delta = 0.025
> x = np.arange(-3.0, 3.0, delta)
> y = np.arange(-2.0, 2.0, delta)
> X, Y = np.meshgrid(x, y)
> Z1 = mlab.bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0)
> Z2 = mlab.bivariate_normal(X, Y, 1.5, 0.5, 1, 1)
> # difference of Gaussians
> Z = 10.0 * (Z2 - Z1)
>
>
>
> # Create a simple contour plot with labels using default colors. The
> # inline argument to clabel will control whether the labels are draw
> # over the line segments of the contour, removing the lines beneath
> # the label
> plt.figure()
> CS = plt.contour(X, Y, Z)
> plt.clabel(CS, inline=1, fontsize=10,inlinespacing=50)
> a=plt.colorbar()
>
> ticks = a.ax.get_xticklines()
> lines = a.ax.get_ygridlines()
> children=a.ax.get_children()
>
> children=a.ax.get_children()
>
> children[4].set_linewidths([12,12,12,12,12,12])
>
> for tick in ticks:
> setp(tick, [])
>
>
> plt.title('Customize colorbar')
>
>
> I hope someone finds that useful. And someone is still following my
> monologue, my question, how to remove the axes around the colorbar, or at
> least changed the to be non-visible, still stands...
>
> Thanks,
>
> Oz
>
>
Oz,
I agree, Colorbar isn't the most elegant of objects and is probably due for
some improvements. I am sure there is probably a better way to do what you
have done, but I am not familiar with it. Anyway, to get rid of the box
around the colorbar, the colorbar object has a member attribute called
"outline" which you can set_visible(False).
a = plt.colorbar()
a.outline.set_visible(False)
Should do the trick for that part.
I hope this helps!
Ben Root

On Sat, Sep 11, 2010 at 6:57 PM, freeeeeekk <fre...@gm...> wrote:
>
> Im trying to do a very simple x vs y plot. Where the x values range between
> 3247 and 3256 and y between 0 and 1. This data is stored in data.dat. I
> plot
> it using the code below, the resulting plot is shown in the first of the
> two
> plots below. Everything goes well except for the x axis, for some reason
> tickmarks from 0 up to 9 appear. At the far end of the axis my xmin is
> printed: 3.247e3.
> I started looking for the cause and it turns out that as long as my range
> in
> x is lower than 10, this happens. If I change the xlimits to
> xlim(3246,3256)
> I get the plot at the bottom of this page, everything is fine. But if I
> change this to for instance xlim(3246.01,3256) or xlim(3245, 3254.99) I get
> the same behaviour as in the first graph.
>
> Does any one have any experience with this/ know the reason for this
> happening? Thanks!
>
> from numpy import *
> from pylab import *
>
> datafile = mlab.load('./data.dat')
> xx=datafile[:,0]
> yy=datafile[:,1]
>
> plot(xx,yy,'black')
> xlim(3247,3256)
> ylim(0,1.2)
>
> show()
>
>
> http://old.nabble.com/file/p29687404/wrong.png
> http://old.nabble.com/file/p29687404/right.png
>
What is happening isn't a bug, it is a feature, although it probably could
be done a little bit better.
When the range of values to display for ticks is fairly small compared to
the size of the values, then matplotlib displays only the part that changes
as a value relative to some constant offset. In your case, the constant
offset is the +3.247e3 on the right hand side of the axis. This can also
happen for the y-axis as well.
This is similar to the idea of how matplotlib would display very large
numbers like range(1e7, 10e7, 1e7) as "1 2 3 4 5 6 7 8 9" with a
1e7 at the end of the axis.
I hope this makes sense.
Ben Root

So far I have tried this...
colourmap = cm.get_cmap("Greys_r")
colourmap = colourmap._segmentdata
# exclude 0, 0, 0...i.e. black from dictionary
bvals = colourmap['blue'][1:]
gvals = colourmap['green'][1:]
rvals = colourmap['red'][1:]
colourmap = { "blue":bvals, "green":gvals, "red":rvals }
colourmap = cm.set_cmap(colourmap)
But it doesn't seem to like the set_cmap command
colourmap = cm.set_cmap(colourmap)
AttributeError: 'module' object has no attribute 'set_cmap'
So I guess that isn't the way, nor I suspect is that all that elegant.
Martin
mdekauwe wrote:
> 
> Hi,
> 
> I am setting a colourbar where I explictly set the tick intervals. However
> I would like to exclude the colour black from this colourbar. The reason
> for this is I would like to overplot some contour lines in black, so would
> like to make them stand out.
> 
> An example...where I would like to exclude black as the bottom colour of
> the colourbar, i.e. use the next level of gray.
> 
> import numpy as np
> from mpl_toolkits.basemap import Basemap
> import matplotlib.pyplot as plt
> import matplotlib.colors as colors
> import matplotlib as mpl
> 
> data = np.random.randint(0,50,100*100).reshape(100, 100) 
> m = Basemap(llcrnrlon=1.5, llcrnrlat=10.5, urcrnrlon=3.5, urcrnrlat=13.5,
> resolution='c', projection='cyl') 
> fig = plt.figure(figsize=(8, 6)) 
> ax = fig.add_axes([0.1, 0.1, 0.6, 0.7])
> m.ax = ax 
> 
> colourmap = plt.cm.Greys_r
> ticks = [0, 10, 20, 30, 40, 50]
> norm = colors.BoundaryNorm(ticks, colourmap.N)
> im = m.imshow(data, colourmap, norm=norm, interpolation='nearest')
> pos = ax.get_position()
> l, b, w, h = pos.bounds
> cax = plt.axes([l+w+0.045, b, 0.05, h]) 
> cbar = mpl.colorbar.ColorbarBase(cax, cmap=colourmap, norm=norm,
> ticks=ticks)
> plt.show()
> 
> Many thanks,
> 
> Martin
> 
-- 
View this message in context: http://old.nabble.com/Exclude-colour-from-a-colourbar-tp29699746p29702394.html
Sent from the matplotlib - users mailing list archive at Nabble.com.

On Mon, Sep 13, 2010 at 2:38 PM, Virgil Stokes <vs...@it...> wrote:
> I have tried to produce a very simple plot with my recent installation of
> matplotlib (1.0.0 64-bit) and numpy (1.5.0 64-bit) using the following code
> (taken from the matplotlib tutorial material).
>
> *import matplotlib
> import numpy
> import matplotlib.pyplot as plt
>
> print matplotlib.__version__
> print numpy.__version__
>
> plt.plot([1,2,3,4])
> plt.ylabel('some numbers')
> plt.show()*
>
> If I execute this in Windows 7 (64-bit) it works correctly. If I execute
> this in Windows Vista (32-bit) it works correctly.
> If I execute this in Ubuntu 10.04 64-bit the versions are printed out
> correctly and thus I believe that the packages are being imported; but, *no
> plot is produced!*
>
> Why not?
>
>
Virgil,
Did you build matplotlib from source? If so, then chances are that one or
more backends were not built properly. This typically happens if you do not
have all the build dependencies.
Note, the build will not necessarily fail if some dependencies are missing
because the core portions of matplotlib still build successfully.
Ben Root

 On 9/13/10 1:38 PM, Virgil Stokes wrote:
> I have tried to produce a very simple plot with my recent installation 
> of matplotlib (1.0.0 64-bit) and numpy (1.5.0 64-bit) using the 
> following code (taken from the matplotlib tutorial material).
>
> *import matplotlib
> import numpy
> import matplotlib.pyplot as plt
>
> print matplotlib.__version__
> print numpy.__version__
>
> plt.plot([1,2,3,4])
> plt.ylabel('some numbers')
> plt.show()*
>
> If I execute this in Windows 7 (64-bit) it works correctly. If I 
> execute this in Windows Vista (32-bit) it works correctly.
> If I execute this in Ubuntu 10.04 64-bit the versions are printed out 
> correctly and thus I believe that the packages are being imported; 
> but, /no plot is produced!/
>
> Why not?
>
Virgil:
Probably your default backend on Ubuntu is a non-gui backend (like Agg).
See http://matplotlib.sourceforge.net/faq/installing_faq.html#backends 
for the definition of a "backend" and how to change the default.
-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

 I have tried to produce a very simple plot with my recent installation 
of matplotlib (1.0.0 64-bit) and numpy (1.5.0 64-bit) using the 
following code (taken from the matplotlib tutorial material).
*import matplotlib
import numpy
import matplotlib.pyplot as plt
print matplotlib.__version__
print numpy.__version__
plt.plot([1,2,3,4])
plt.ylabel('some numbers')
plt.show()*
If I execute this in Windows 7 (64-bit) it works correctly. If I execute 
this in Windows Vista (32-bit) it works correctly.
If I execute this in Ubuntu 10.04 64-bit the versions are printed out 
correctly and thus I believe that the packages are being imported; but, 
/no plot is produced!/
Why not?

Hello all,
I'm trying to build an executable distribution of an app I'm working
using py2exe.
After a lot of googling, I found what it seems to be a good
combination of parameters, but when I try to run the .exe, it fails.
The .log file shows me that the module backend_qt4agg wasn't found:
> ImportError: No module named backend_qt4agg
Also, using py2exe -x shows me that PyQt4 is being imported by
matplotlib.pyplot.
The thing is, this is a WxPython application.
Why is pyplot importing pyqt?? How do I stop it?
thanks
-- 
Prof. Carlos Henrique Grohmann - Geologist D.Sc.
Institute of Geosciences - Univ. of São Paulo, Brazil
http://www.igc.usp.br/pessoais/guano
http://lattes.cnpq.br/5846052449613692
Linux User #89721
________________
Can’t stop the signal.

On Mon, Sep 13, 2010 at 9:23 AM, Jeff Whitaker <js...@fa...> wrote:
> Martin:
>
> You need a meshgrid
>
> x,y = np.meshgrid(x,y)
>
> just *before* (not after)
>
> px,py = m(x,y)
>
> so that x and y have the same shape as data2.
Yeah, my bad. That's what I get for responding *before* coffee this morning.
Ryan
-- 
Ryan May
Graduate Research Assistant
School of Meteorology
University of Oklahoma

Hi,
I am setting a colourbar where I explictly set the tick intervals. However I
would like to exclude the colour black from this colourbar. The reason for
this is I would like to overplot some contour lines in black, so would like
to make them stand out.
An example...where I would like to exclude black as the bottom colour of the
colourbar, i.e. use the next level of gray.
import numpy as np
from mpl_toolkits.basemap import Basemap
import matplotlib.pyplot as plt
import matplotlib.colors as colors
import matplotlib as mpl
data = np.random.randint(0,50,100*100).reshape(100, 100) 
m = Basemap(llcrnrlon=1.5, llcrnrlat=10.5, urcrnrlon=3.5, urcrnrlat=13.5,
 resolution='c', projection='cyl') 
fig = plt.figure(figsize=(8, 6)) 
ax = fig.add_axes([0.1, 0.1, 0.6, 0.7])
m.ax = ax 
colourmap = plt.cm.Greys_r
ticks = [0, 10, 20, 30, 40, 50]
norm = colors.BoundaryNorm(ticks, colourmap.N)
im = m.imshow(data, colourmap, norm=norm, interpolation='nearest')
pos = ax.get_position()
l, b, w, h = pos.bounds
cax = plt.axes([l+w+0.045, b, 0.05, h]) 
cbar = mpl.colorbar.ColorbarBase(cax, cmap=colourmap, norm=norm,
ticks=ticks)
plt.show()
Many thanks,
Martin
-- 
View this message in context: http://old.nabble.com/Exclude-colour-from-a-colourbar-tp29699746p29699746.html
Sent from the matplotlib - users mailing list archive at Nabble.com.

Hi!
I want to use polar plot and write contour in semi-circle domain.But I can't
do so.
Here is a part of my code. 
	
-----------------------------
from pylab import *
from scipy import *
fig=figure(figsize=(10,10))
ax=fig.add_axes([0.1,0.1,0.8,0.8],polar=True)
axis([0, pi, 0, 1])
show()
----------------------------
I thought that "axis([0,pi,0,1])" make the writing domain semi-circle,
but complete circle was written as domain.
Does anyone know how I should write?
Many thanks, 
Kenshi
-- 
View this message in context: http://old.nabble.com/contour-plot-in-semi-circle-domain-tp29699332p29699332.html
Sent from the matplotlib - users mailing list archive at Nabble.com.

On Mon, Sep 13, 2010 at 9:02 AM, mdekauwe <mde...@gm...> wrote:
>
> Hi,
>
> Well I tried...
>
> numrows = 17
> numcols = 16
> ulat, llat, ulon, llon = 15.61, 15.15, -1.32, -1.74
> m = Basemap(projection='geos', lon_0=0.0, llcrnrlon=llon,
> llcrnrlat=llat, urcrnrlon=ulon, urcrnrlat=ulat,
> resolution='c')
>
> data2 = np.random.sample((17,16))
> print 'DATA2 shape:', data2.shape
> x = np.linspace(-1.74, -1.32, 16)
> y = np.linspace(15.15, 15.61, 17)
> print 'x shape:', x.shape
> print 'y shape:', y.shape
> px, py = m(x, y)
>
>
> which gives...
>
> DATA2 shape: (17, 16)
> x shape: (16,)
> y shape: (17,)
>
> So that looks OK. Turns out the error now comes at the line px, py = m(x,
> y). So perhaps I am doing the basemap step incorrectly?
>
> Traceback (most recent call last):
> File "./recontour_plot.py", line 83, in <module>
> px, py = m(x, y)
> File
> "/users/eow/mgdk/sun4u//lib/python/mpl_toolkits/basemap/__init__.py",
> line 823, in __call__
> return self.projtran(x,y,inverse=inverse)
> File "/users/eow/mgdk/sun4u//lib/python/mpl_toolkits/basemap/proj.py",
> line 241, in __call__
> outx,outy = self._proj4(x, y, inverse=inverse)
> File "/users/eow/mgdk/sun4u//lib/python/mpl_toolkits/basemap/pyproj.py",
> line 193, in __call__
> _Proj._fwd(self, inx, iny, radians=radians, errcheck=errcheck)
> File "_proj.pyx", line 56, in _proj.Proj._fwd (src/_proj.c:725)
> RuntimeError: Buffer lengths not the same
>
>
Martin,
It would be more useful to see what are the shapes of px, py, X, and Y.
Ben Root

Hi Jeff,
many thanks that was exactly the problem!
Martin
Jeff Whitaker wrote:
> 
> On 9/13/10 8:02 AM, mdekauwe wrote:
>> Hi,
>>
>> Well I tried...
>>
>> numrows = 17
>> numcols = 16
>> ulat, llat, ulon, llon = 15.61, 15.15, -1.32, -1.74
>> m = Basemap(projection='geos', lon_0=0.0, llcrnrlon=llon,
>> llcrnrlat=llat, urcrnrlon=ulon, urcrnrlat=ulat,
>> resolution='c')
>>
>> data2 = np.random.sample((17,16))
>> print 'DATA2 shape:', data2.shape
>> x = np.linspace(-1.74, -1.32, 16)
>> y = np.linspace(15.15, 15.61, 17)
>> print 'x shape:', x.shape
>> print 'y shape:', y.shape
>> px, py = m(x, y)
>>
>>
>> which gives...
>>
>> DATA2 shape: (17, 16)
>> x shape: (16,)
>> y shape: (17,)
>>
>> So that looks OK. Turns out the error now comes at the line px, py = m(x,
>> y). So perhaps I am doing the basemap step incorrectly?
>>
>> Traceback (most recent call last):
>> File "./recontour_plot.py", line 83, in<module>
>> px, py = m(x, y)
>> File
>> "/users/eow/mgdk/sun4u//lib/python/mpl_toolkits/basemap/__init__.py",
>> line 823, in __call__
>> return self.projtran(x,y,inverse=inverse)
>> File "/users/eow/mgdk/sun4u//lib/python/mpl_toolkits/basemap/proj.py",
>> line 241, in __call__
>> outx,outy = self._proj4(x, y, inverse=inverse)
>> File
>> "/users/eow/mgdk/sun4u//lib/python/mpl_toolkits/basemap/pyproj.py",
>> line 193, in __call__
>> _Proj._fwd(self, inx, iny, radians=radians, errcheck=errcheck)
>> File "_proj.pyx", line 56, in _proj.Proj._fwd (src/_proj.c:725)
>> RuntimeError: Buffer lengths not the same
>>
>>
> Martin:
> 
> You need a meshgrid
> 
> x,y = np.meshgrid(x,y)
> 
> just *before* (not after)
> 
> px,py = m(x,y)
> 
> so that x and y have the same shape as data2.
> 
> -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
> 
> 
> ------------------------------------------------------------------------------
> Start uncovering the many advantages of virtual appliances
> and start using them to simplify application deployment and
> accelerate your shift to cloud computing
> http://p.sf.net/sfu/novell-sfdev2dev
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
> 
> 
-- 
View this message in context: http://old.nabble.com/basemap-and-contouring-tp29697864p29699166.html
Sent from the matplotlib - users mailing list archive at Nabble.com.

 On 9/13/10 8:02 AM, mdekauwe wrote:
> Hi,
>
> Well I tried...
>
> numrows = 17
> numcols = 16
> ulat, llat, ulon, llon = 15.61, 15.15, -1.32, -1.74
> m = Basemap(projection='geos', lon_0=0.0, llcrnrlon=llon,
> llcrnrlat=llat, urcrnrlon=ulon, urcrnrlat=ulat,
> resolution='c')
>
> data2 = np.random.sample((17,16))
> print 'DATA2 shape:', data2.shape
> x = np.linspace(-1.74, -1.32, 16)
> y = np.linspace(15.15, 15.61, 17)
> print 'x shape:', x.shape
> print 'y shape:', y.shape
> px, py = m(x, y)
>
>
> which gives...
>
> DATA2 shape: (17, 16)
> x shape: (16,)
> y shape: (17,)
>
> So that looks OK. Turns out the error now comes at the line px, py = m(x,
> y). So perhaps I am doing the basemap step incorrectly?
>
> Traceback (most recent call last):
> File "./recontour_plot.py", line 83, in<module>
> px, py = m(x, y)
> File "/users/eow/mgdk/sun4u//lib/python/mpl_toolkits/basemap/__init__.py",
> line 823, in __call__
> return self.projtran(x,y,inverse=inverse)
> File "/users/eow/mgdk/sun4u//lib/python/mpl_toolkits/basemap/proj.py",
> line 241, in __call__
> outx,outy = self._proj4(x, y, inverse=inverse)
> File "/users/eow/mgdk/sun4u//lib/python/mpl_toolkits/basemap/pyproj.py",
> line 193, in __call__
> _Proj._fwd(self, inx, iny, radians=radians, errcheck=errcheck)
> File "_proj.pyx", line 56, in _proj.Proj._fwd (src/_proj.c:725)
> RuntimeError: Buffer lengths not the same
>
>
Martin:
You need a meshgrid
x,y = np.meshgrid(x,y)
just *before* (not after)
px,py = m(x,y)
so that x and y have the same shape as data2.
-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

Thanks Alan. working nicely now.
Ted
On 13 September 2010 13:27, Alan G Isaac <ala...@gm...> wrote:
> On 9/13/2010 6:46 AM, Ted Kord wrote:
> > How do I increase the distance/padding between the tick labels (numbers)
> and the axis/axes?
>
>
> http://matplotlib.sourceforge.net/users/customizing.html#customizing-matplotlib
> (see the pad options)
>
> hth,
> Alan Isaac
>
>
>
> ------------------------------------------------------------------------------
> Start uncovering the many advantages of virtual appliances
> and start using them to simplify application deployment and
> accelerate your shift to cloud computing
> http://p.sf.net/sfu/novell-sfdev2dev
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>