matplotlib-users Mailing List for matplotlib (Page 3)

Continuing from a previous thread re the new matshow(), adding a 
colorbar() causes the matrix to shrink relative to the colorbar. 
Furthermore this colorbar overlaps with the figure title.

For those like me who need a colorbar as a legend and/or who do not want 
the matrix visualisation in a new figure with aspect ratio constrained, 
all that needs to be done is to replace line 1424 in pylab.py for 
matshow() as follows

     # OLD LINE: fig = figure(fignum, figsize=figaspect(A))
     fig = gcf()

You're probably best off to create a new function matshowB() in case you 
ever need the default functionality.

Cheers,
Suresh

On 3/28/07, Giorgio F. Gilestro <gil...@gm...> wrote:
> Hi,
> I have to question that will help some colleagues/friends of mine to switch
> to python from matlab.
>
> 1 - is there an automatic translator of code from matlab to
> python/numpy/matplotlib? I believe it would be very easy to implement due
> the similar syntax between the two. I could do something similar myself but
> first I better make sure it doesn't exist yet.

None that I know of, and it probably wouldn't be easy.  For one thing,
matlab uses parentheses for function calls and indexing, and it is
probably not always obvious which is which for a translator.  One
could write something that got it mostly right and flagged
ambiguities, but I think you should expect that a human would have to
clean it up afterwards unless you attempt something ambitious and not
easy.  Prove me wrong!

> 2 - Is there a python/numpy/mpl equivalent of EEGlab? see:
> http://www.sccn.ucsd.edu/eeglab/

There is pbrain, which is not and does not attempt to be an equivalent
of EEGLab, but it is an EEG viewer/analysis package in python, which
uses matplotlib (and VTK).  It is specialized for spectral analysis,
but could be extended to do other things.

  http://neuroimaging.scipy.org/pbrain/

I first wrote an EEG analysis package in matlab, and after becoming
frustrated with the lack of good support for complex data structures,
networking, and programming paradigms, I jettisoned it for python and
wrote pbrain.  I wrote matplotlib in support of the pbrain
application, so some of the work has already been done :-)

JDH

Hi,
I have to question that will help some colleagues/friends of mine to switch
to python from matlab.

1 - is there an automatic translator of code from matlab to
python/numpy/matplotlib? I believe it would be very easy to implement due
the similar syntax between the two. I could do something similar myself but
first I better make sure it doesn't exist yet.

2 - Is there a python/numpy/mpl equivalent of EEGlab? see:
http://www.sccn.ucsd.edu/eeglab/

thanks
Giorgio

On 3/28/07, Ken McIvor <mc...@ii...> wrote:

> You'd almost certainly be happier doing things the other way around.
> Most GUI toolkits are extremely fussy about what thread the GUI event
> loop runs in.  For example, wxPython requires App.MainLoop() be
> called from the thread that first imported the wxPython module.  That
> being said, it's possible to run the GUI thread in the background --
> the iPython wizards might be able to help you figure it out.

No, the limitation you describe is there just as much.  What we do in
ipython is push the *user code* execution into the secondary thread,
to make sure we keep the GUI toolkits happy for the very reasons you
outline.

Cheers,

f

On Mar 27, 2007, at 12:35 PM, Antonino Ingargiola wrote:
>
> I'm searching to display in realtime some data read serial port. The
> data is a 2D matrix and is read element wise from the serial, one
> pixel each one (or more) seconds.

You shouldn't have any problems making this happen, although it  
requires a lot more legwork than creating normal interactive plots.

> I'm running the script from "ipython -pylab" using the command "run
> scriptname". After "loading" the script I interactively launch the
> function that start the data acquisition and I would like to see the
> acquired data so far.

I've never tried to do something like this using pylab before, so I  
probably can't be of much help there.  However, I can point you  
toward an example of how to do it from within wxPython using a timer.

> In the loop that perform the data acquisition I'm currently calling  
> this function to plot data:
>
> def plot_data_in_itinere(data, **kwargs):
>    global first_plot
>    d = data.ravel()[find(data.ravel() > 0)]
>    m = d.mean()
>    vr = round(5*d.std() / m, 3)
>    #clf()
>    title('Scanning Data')
>    xlabel('Mean Value: '+str(int(round(m)))+' -- Relative  
> Variation: '+str(vr))
>    b,t = ylim()
>    ylim(t,b)
>    imshow(data.astype(float),
>            interpolation='nearest',
>            vmin=0,
>            origin='lower', **kwargs)
>    if first_plot:
>        colorbar()
>        first_plot = False
>
> However the call to the function is "blocking". So the acquisition
> time is longer (not only I have to wait the data but I have to wait
> the plot too).

You should probably do the acquisition asynchronously by running it  
in a separate thread.  That thread would read in the data one point  
at a time, perform any pre-processing, and post the results to a  
place that's shared between it and the main plotting thread.  The  
main thread would periodically check and see if the shared data has  
changed and redraw the plot if needed.  I'm not sure how hard this is  
to do in a reasonable way in pylab, but I've used this approach  
before in wxPython GUIs.

> Furthermore, this function plot the new data above the
> old one, so the plot becomes slower and slower while the acquisition
> goes on. If I uncommented the cla() line, I get a plot that is blank
> most of the time and that shows the data only for a fraction of second
> while the new plot is performed.
`
You might want to consider create a mock data source that generates a  
stream of values from some pre-collected data or Python's "random"  
module.  That would let you work on debugging the plotting end of  
things first.  It would also make it easier for you to share your  
code with the list.

> Is there a way to update (or substitute) the current showed matrix
> data, deleting the old plots (in the axis). I have to confess that
> I've have not understand well how the pylab interactive mode works.

pylab.imshow() returns a matplotlib.image.AxesImage object.  It looks  
like you can update the data array using its set_data() method.  The  
class documentation is available on the matplotlib website:

	http://matplotlib.sourceforge.net/matplotlib.image.html#AxesImage

> Ideally the plot should be performed in background, while the script
> goes on and wait the next data arrival.

You'd almost certainly be happier doing things the other way around.   
Most GUI toolkits are extremely fussy about what thread the GUI event  
loop runs in.  For example, wxPython requires App.MainLoop() be  
called from the thread that first imported the wxPython module.  That  
being said, it's possible to run the GUI thread in the background --  
the iPython wizards might be able to help you figure it out.

> I've tried to do this with a simple gtk app that embeds a  
> matplotlib plot. Hoever, I don't know how to send the application  
> in background. I've tried to do something like this:
>
<snip>
>
> the PlotScanApp implement the gui (full files attached). Running the
> script the image should be updated with random data each 1 sec. but
> only the first image is showed. I suppose this is not the way to put a
> gui drawing app in background...

Well, using pylab from within a GUI application is a bit dodgy to  
begin with.  I can see a few potential problems.  The first is that  
you're calling plotting commands from within the main thread,  
although the GUI is running in a background thread.  You might try  
doing the plotting from within the GUI thread by having a timer fire  
once a second to redraw the plot.  The second problem is that you're  
not calling pylab.draw(), which forces the current figure to redraw  
itself.  Whether or not pylab is running in interactive mode might be  
a factor here.  There's some documentation about interactive mode and  
the ion()/ioff() commands here:

	http://matplotlib.sourceforge.net/interactive.html

Ken

Hello to all,
I've thread that apperead some time ago on this list about matlab and 
teaching.
I've discovered python recently  and translated part of the routine I 
use in python (www.chemometrics.it).
Some of my collegue asked me if I could show them how to use python. For 
matlab user I guess the first problem is to setup everything, but I just 
fixed it preparing a directory with all the package I need and a 
matplotlibrc file for interactive mode + a shortcut for idle -n use.
The second problem is that people now  wants some bells and whistles of 
matlab that I have to admit sometime can be very helpful for saving 
time. The bells and whistles are about the workspace.
It's difficult to cut and paste from gnumeric/excel (I generally use txt 
file but it's no so immediate) and also there is no "visual" workspace. 
I cannot succeed also in saving workspace (I know there is a function so 
iosave.mat but I didn't manage easily hot to use it)
For overpass this problems I've tried to use QME-DEV which is in early 
stage of development (alpha) but promise well.
What people like of python/matplot/scipy
-its free ;)
-they like a lot the plotting style and capabilities (they find the png 
and svg file very clear and accurate)
-they like IDLE as editor (ehy it's has the same color of matlab ;) ! )

So my question is . Do you have a similar experience ?
How do you help people in moving the first step ?
do you use (and also does it exist) a more friendly environment than 
IDLE except from QME-DEV.

I know that this question may look silly, but in my opinion also how 
much is user friendly a software is very important for getting new users.
Cheers to all
Giorgio

On 3/28/07, Nadia Dencheva <den...@st...> wrote:
> Numarray does not work with Python 2.5 on 64 bit Linux.
> If this is a 64 bit Linux machine try using numpy instead.

If this doesn't help, here are the generic "segfault" instructions::

# How to diagnose where a segfault is occurring

First thing to try is simply rm -rf the site-packages/matplotlib and
build subdirs and get a clean install.  Installing a new version over
a pretty old version has been known to cause trouble, segfault, etc.

Try importing these packages individually

  import matplotlib._image
  import matplotlib._transforms

  #one of these three depending on which numerix package you are using
  import matplotlib.backends._na_backend_agg # for numarray
  import matplotlib.backends._nc_backend_agg # for Numeric
  import matplotlib.backends._ns_backend_agg # for numpy

  import matplotlib.backends._tkagg
  import matplotlib._agg


If the last two work and the others don't, it is likely you need to
upgrade your gcc, because on some platforms (OS X for sure) old
versions of gcc cannot compile new versions of pycxx, which matplotlib
uses for building some but not all of it's extensions.  Report back
which if any work or segfault or raise tracebacks,

If that shed additional light, again flush the build and install dirs,
and try setting VERBOSE=True in setup.py before doing a clean install.
The VERBOSE setting will generate lots of extra output and may help
indicate where the segfault is occurring

On 3/28/07, jens haemmerling <jha...@gm...> wrote:

> I have problems to plot surfaces like f(x,y)=x*y...
> for example "plot_surface([1,2,3], [4,5,6], [7,8,9])" doesn't work either...
>
> I imported the following:
>
> from numpy import *
> import pylab as p
> import matplotlib.axes3d as p3
>
> does anybody have an advice?
You can do surface plots with axe3d, but mpl isn't really suited for
3d plotting since 3d plotting is nascent and not supported.  We
include it in hopes that someone else will ike it and improve it but
that hasn't happened yet.

Personally, unless you are doing interactive stuff like rotating your
figure, surface plots don't help much, and mpl 3d is really too slow
for interactive 3d.  I use imshow or pcolor with colormapping, which
will give you just about all the information you can get out of a
non-interactive 3d plot.

JDH

On 3/28/07, Mark Bakker <ma...@gm...> wrote:
> Hello List -
>
> A while back, the default font changed in the matplotlibrc file.
> Does anybody recall what the old default font was?
> I kinda liked it better than the current font, but I don't recall what it
> was.

The default font listing was
#font.serif          : Bitstream Vera Serif, New Century Schoolbook,
Century Schoolbook L, Utopia, ITC Bookman, Bookman, Nimbus Roman No9
L, Times New Roman, Times, Palatino, Charter, serif
#font.sans-serif     : Bitstream Vera Sans, Lucida Grande, Verdana,
Geneva, Lucid, Arial, Helvetica, Avant Garde, sans-serif
#font.cursive        : Apple Chancery, Textile, Zapf Chancery, Sand, cursive
#font.fantasy        : Comic Sans MS, Chicago, Charcoal, Impact,
Western, fantasy
#font.monospace      : Bitstream Vera Sans Mono, Andale Mono, Nimbus
Mono L, Courier New, Courier, Fixed, Terminal, monospace

in the rc file.  In the last release, we decided to go with a
"commented out" rc file and rely on internal defaults unless user
explicitly uncommented something.  This makes it easier for us to
change the default ors rc settings and not generate as many warnings
to naive users.  But when we went to the internal default, for some
reason this listing was not preserved internally.  I just readded it
and committed it.

Before this, there was a different ordering but I would have to dig
through the svn archive to find it.  I decided to make bitstream the
default since we ship it.  If you are referring to the "pre bitstream"
default, I suggest you start poking through older revisions of the
matplotlibrc.template file in svn.

JDH

Numarray does not work with Python 2.5 on 64 bit Linux.
If this is a 64 bit Linux machine try using numpy instead.

Nadia Dencheva


Matt Beal wrote:
> Having upgraded to 2.5, I get a segfault when running a very simple plot 
> script (test.py) at the show() function.  Prior to show() I can save to 
> file and the result looks good.  The GUI is crashing on show().
>  
> Any suggestions to fix welcome (I'm guessing many of you know the 
> solution to this problem).
>  
> "Annoying" debug information below:
>  
> Thanks!
> -Matt
>  
> hostname:~/.matplotlib>cat test.py
> from pylab import *
> plot([1,2,3])
> show()
> 
> hostname:~/.matplotlib>python test.py --verbose-debug-annoying -dTkAgg
> matplotlib data path ..../python2.5/site-packages/matplotlib/mpl-data
> $HOME=/home/username
> loaded rc file /home/username/.matplotlib/matplotlibrc
> matplotlib version 0.90.0
> verbose.level debug-annoying
> interactive is False
> platform is linux2
> loaded modules: ['_bisect', '_sha512', 'pylab', 'datetime', 
> 'matplotlib.tempfile ', 'distutils.sysconfig', 'encodings.encodings', 'str
> uct', 'tempfile', 'pytz.os', 'zipimport', 'string', 
> 'matplotlib.__future__', 'pytz.tzinfo', ' pytz.datetime', 'distutils.re 
> <http://distutils.re>', 'bisect'
> , 'signal', 'random', 'matplotlib.pytz', 'locale', 'encodings', 
> 'dateutil', ' matplotlib.warnings', 'pytz.pytz', 'matplotlib.sys', 're
> ', 'math', 'fcntl', 'UserDict', 'distutils.os', 'matplotlib', 'codecs', 
> 'md5', '_locale', ' matplotlib.os', 'thread', 'itertools', 'di
> stutils.sys', 'os', '__future__', '_sre', '__builtin__', 'matplotlib.re 
> <http://matplotlib.re>', 'operator', ' distutils.string', 
> 'matplotlib.datetime', 'pos
> ixpath', 'errno', 'binascii', 'sre_constants', '_sha256', 
> 'matplotlib.md5', 'types', 'pytz.sys', '_codecs', 'pytz', 'copy', '_struct'
> , '_types', 'matplotlib.dateutil', 'hashlib', 'distutils', 'posix', 
> 'encodings.aliases', 'exceptions', 'sre_parse', 'pytz.bisect', 'd
> istutils.distutils ', 'copy_reg', 'sre_compile', '_hashlib', '_random', 
> 'site', '__main__', 'shutil', 'strop', 'encodings.codecs', 'ge
> ttext', 'pytz.sets ', 'stat', 'warnings', 'encodings.types', 
> 'encodings.ascii', 'sys', 'os.path', 'pytz.gettext', 'matplotlib.distutil
> s', 'distutils.errors', 'linecache', ' matplotlib.shutil', 'sets']
> numerix numarray 1.5.2
> font search path ['..../python2.5/site-packages/matplotlib/mpl-data']
> trying fontname ..../python2.5/site-packages/matplotlib/mpl-data/cmtt10.ttf
> trying fontname 
> ..../python2.5/site-packages/matplotlib/mpl-data/VeraMoIt.ttf
> trying fontname ..../python2.5/site-packages/matplotlib/mpl-data/cmex10.ttf
> trying fontname ..../python2.5/site-packages/matplotlib/mpl-data/VeraBI.ttf
> trying fontname ..../python2.5/site-packages/matplotlib/mpl-data/VeraBd.ttf
> trying fontname ..../python2.5/site-packages/matplotlib/mpl-data/cmmi10.ttf
> trying fontname 
> ..../python2.5/site-packages/matplotlib/mpl-data/VeraSeBd.ttf
> trying fontname ..../python2.5/site-packages/matplotlib/mpl-data/cmr10.ttf
> trying fontname 
> ..../python2.5/site-packages/matplotlib/mpl-data/VeraMono.ttf
> trying fontname ..../python2.5/site-packages/matplotlib/mpl-data/cmsy10.ttf
> trying fontname ..../python2.5/site-packages/matplotlib/mpl-data/Vera.ttf
> CONFIGDIR=/home/username/.matplotlib
> loaded ttfcache file /home/username/.matplotlib/ttffont.cache
> backend TkAgg version 8.5
> FigureCanvasAgg.draw
> RendererAgg.__init__
> RendererAgg.__init__ width=650.0,                         height=490.0
> RendererAgg.__init__ _RendererAgg done
> RendererAgg.__init__ done
> RendererAgg._get_agg_font
>         findfont found sans-serif, normal, normal 400, normal, 12.0
> findfont returning ..../python2.5/site-packages/matplotlib/mpl-data/Vera.ttf
> RendererAgg._get_agg_font
> RendererAgg.draw_text
> RendererAgg._get_agg_font
> RendererAgg.points_to_pixels
> RendererAgg.points_to_pixels
> RendererAgg._get_agg_font
> RendererAgg._get_agg_font
> RendererAgg.draw_text
> RendererAgg._get_agg_font
> RendererAgg.points_to_pixels
> RendererAgg.points_to_pixels
> RendererAgg._get_agg_font
> RendererAgg._get_agg_font
> RendererAgg.draw_text
> RendererAgg._get_agg_font
> RendererAgg.points_to_pixels
> RendererAgg.points_to_pixels
> RendererAgg._get_agg_font
> RendererAgg._get_agg_font
> RendererAgg.draw_text
> RendererAgg._get_agg_font
> RendererAgg._get_agg_font
> RendererAgg._get_agg_font
> RendererAgg.draw_text
> RendererAgg._get_agg_font
> RendererAgg._get_agg_font
> RendererAgg._get_agg_font
> RendererAgg.draw_text
> RendererAgg._get_agg_font
> RendererAgg.points_to_pixels
> RendererAgg.points_to_pixels
> RendererAgg._get_agg_font
> RendererAgg._get_agg_font
> RendererAgg.draw_text
> RendererAgg._get_agg_font
> RendererAgg.points_to_pixels
> RendererAgg.points_to_pixels
> RendererAgg._get_agg_font
> RendererAgg._get_agg_font
> RendererAgg.draw_text
> RendererAgg._get_agg_font
> RendererAgg.points_to_pixels
> RendererAgg.points_to_pixels
> RendererAgg._get_agg_font
> RendererAgg._get_agg_font
> RendererAgg.draw_text
> RendererAgg._get_agg_font
> RendererAgg._get_agg_font
> RendererAgg._get_agg_font
> RendererAgg.draw_text
> RendererAgg._get_agg_font
> Segmentation fault (core dumped)
> 
> hostname:~/.matplotlib>
>  
> 
> 
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Hello List -

A while back, the default font changed in the matplotlibrc file.
Does anybody recall what the old default font was?
I kinda liked it better than the current font, but I don't recall what it
was.

Thanks,

Mark

hello 

I have problems to plot surfaces like f(x,y)=x*y...
for example "plot_surface([1,2,3], [4,5,6], [7,8,9])" doesn't work either...

I imported the following:

from numpy import *
import pylab as p
import matplotlib.axes3d as p3

does anybody have an advice?

-- 
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Thanks, Eric,

Yes, that works for the stripped down version, but not for what I am trying
to do.  The examples I have given have the range of one of the plots nicely
fitting inside that of the other (ie, plot 1 range 15 to 26, plot 2 range 17
to 23), but sometimes with what I am doing I have, for example,  plot 1
range 15 to 23 and plot 2 range 17 to 25.  In this case, passing the levels
from plot 1 to plot 2 means that levels 24 and 25 of plot 2 are stripped
away; this, at least, is what I think is happening because I have white
areas of my plot that weren't there before.  It seems to me that it would be
quite useful to have the option to override the colorbar range, setting it
to be the same as defined by clim, or some other values.

As a solution for now, I think I will just use one colorbar for the two
plots.  Thanks for your help with this, and the tip about being explicit in
my programs!

-Evan




On 3/27/07, Eric Firing <ef...@ha...> wrote:
>
> Evan,
>
> OK, I see what the problem is: you need to tell the second contour
> command to use the same contour levels as the first one is using.
> Something like this:
>
> figure(1)
> CS1 = contourf(x)
> clim(cmin, cmax)
> colorbar()
> figure(2)
> CS2 = contourf(y, levels=CS1.levels)
> clim(cmin, cmax)
> colorbar()
>
> Does this give the desired result?
>
> The big difference between pcolor and contourf in this context is that
> pcolor is automatically generating a colormap with 256 colors, and may
> use any or all of those colors, so the colorbar is effectively
> continuous.  Contourf works with a small discrete set of colors taken
> from such a colormap, so colorbar shows the same discrete set.  The
> boundaries are either generated automatically in contourf, or set via
> the levels kwarg.  Colorbar gets the boundaries from the output of the
> contourf call, which pylab saves and passes along to colorbar even if
> you don't do so explicitly yourself.  But pylab has no way of knowing
> that you want the contour levels in the second figure to match the
> first, so you have to be explicit.
>
> Usually at this point someone chimes in to point out the virtues of
> being explicit in your program even when you don't have to...
>
> Eric
>
>
>
> Evan Mason wrote:
> > Hi Eric, the following lines below will show this.  Interestingly, the
> > correct (or, at least, what I want) behaviour results from using pcolor,
> > but not with contourf.
> >
> >
> > a = arange(12, 27, .5)
> > b = arange(17, 23, .5)
> > x, y = meshgrid(a, b)
> >
> > # get max and min for clim
> > cmin = min(x.min(), y.min()) # cmin = 12
> > cmax = max(x.max(), y.max()) # cmax = 26.5
> >
> > figure(1)
> > contourf(x)
> > #pcolor(x)
> > clim([cmin, cmax])
> > colorbar()
> > figure(2)
> > contourf(y)
> > #pcolor(y)
> > clim([cmin, cmax])
> > colorbar()
> >
> >
> > -Evan
> >
> >
> >
> >
> > On 3/27/07, *Eric Firing* < ef...@ha...
> > <mailto:ef...@ha...>> wrote:
> >
> >     Evan,
> >
> >     That is getting clearer, but it still seems to me that no override
> >     should be needed in this case; it should "just work", so if it
> doesn't,
> >     either there is a bug in mpl or a bug in the code.  It would be most
> >     helpful if you would write a stripped-down simplest-possible script
> >     that
> >     illustrates the problem.  Then I can either show how to fix the
> script,
> >     or I can use the script to help me track down the mpl bug, if that
> is
> >     the problem.
> >
> >     Eric
> >
> >     Evan Mason wrote:
> >      > Hi Eric
> >      >
> >      > I am using matplotlib-0.90.0.
> >      >
> >      > I am making 2 contourf subplots of temperature values which have
> >     similar
> >      > but not equal ranges.  In subplot1 the range is 15-25; in
> >     subplot2 it is
> >      > 16 to 24.  I use clim, giving it the max and min values obtained
> >     from a
> >      > comparison of subplot1 and 2; i.e., I use clim([15, 25]) on both
> >      > subplots.  The two subplots display exactly as I want them to.
> >      >
> >      > Next, I want 2 colorbars to go with the two subplots.  I want the
> >     range
> >      > of each colorbar to be the same, set as the clim values (15 and
> 25).
> >      > This happens for subplot1, but not for subplot2, which shows the
> >     range
> >      > 16-24, following its input data range and not the clim values.
> >      >
> >      > So what I want to know is if it is possible to overide the
> colorbar
> >      > limits, setting them to 15-25?
> >      >
> >      > I hope that's clearer now, thanks, Evan
> >      >
> >      >
> >      >
> >      > On 3/27/07, * Eric Firing* < ef...@ha...
> >     <mailto:ef...@ha...>
> >      > <mailto:ef...@ha... <mailto:ef...@ha...>>> wrote:
> >      >
> >      >     Evan,
> >      >
> >      >     It is still not quite clear to me what you want versus what
> >     you are
> >      >     getting.  With recent versions of mpl, the colorbar
> >     automatically uses
> >      >     the same color boundaries as contourf, if that is what the
> >     colorbar is
> >      >     tracking.  What version of mpl are you using?
> >      >
> >      >     (With the most recent mpl I see that there is a strange bug
> >     such that
> >      >     setting clim clobbers the axis tick labeling for the
> >     colorbar--yet
> >      >     another thing that needs to be figured out and fixed.)
> >      >
> >      >
> >
> >
>
>

Evan,

OK, I see what the problem is: you need to tell the second contour 
command to use the same contour levels as the first one is using. 
Something like this:

figure(1)
CS1 = contourf(x)
clim(cmin, cmax)
colorbar()
figure(2)
CS2 = contourf(y, levels=CS1.levels)
clim(cmin, cmax)
colorbar()

Does this give the desired result?

The big difference between pcolor and contourf in this context is that 
pcolor is automatically generating a colormap with 256 colors, and may 
use any or all of those colors, so the colorbar is effectively 
continuous.  Contourf works with a small discrete set of colors taken 
from such a colormap, so colorbar shows the same discrete set.  The 
boundaries are either generated automatically in contourf, or set via 
the levels kwarg.  Colorbar gets the boundaries from the output of the 
contourf call, which pylab saves and passes along to colorbar even if 
you don't do so explicitly yourself.  But pylab has no way of knowing 
that you want the contour levels in the second figure to match the 
first, so you have to be explicit.

Usually at this point someone chimes in to point out the virtues of 
being explicit in your program even when you don't have to...

Eric



Evan Mason wrote:
> Hi Eric, the following lines below will show this.  Interestingly, the 
> correct (or, at least, what I want) behaviour results from using pcolor, 
> but not with contourf.
> 
> 
> a = arange(12, 27, .5)
> b = arange(17, 23, .5)
> x, y = meshgrid(a, b)
> 
> # get max and min for clim
> cmin = min(x.min(), y.min()) # cmin = 12
> cmax = max(x.max(), y.max()) # cmax = 26.5
> 
> figure(1)
> contourf(x)
> #pcolor(x)
> clim([cmin, cmax])
> colorbar()
> figure(2)
> contourf(y)
> #pcolor(y)
> clim([cmin, cmax])
> colorbar()
> 
> 
> -Evan
> 
> 
> 
> 
> On 3/27/07, *Eric Firing* < ef...@ha... 
> <mailto:ef...@ha...>> wrote:
> 
>     Evan,
> 
>     That is getting clearer, but it still seems to me that no override
>     should be needed in this case; it should "just work", so if it doesn't,
>     either there is a bug in mpl or a bug in the code.  It would be most
>     helpful if you would write a stripped-down simplest-possible script
>     that
>     illustrates the problem.  Then I can either show how to fix the script,
>     or I can use the script to help me track down the mpl bug, if that is
>     the problem.
> 
>     Eric
> 
>     Evan Mason wrote:
>      > Hi Eric
>      >
>      > I am using matplotlib-0.90.0.
>      >
>      > I am making 2 contourf subplots of temperature values which have
>     similar
>      > but not equal ranges.  In subplot1 the range is 15-25; in
>     subplot2 it is
>      > 16 to 24.  I use clim, giving it the max and min values obtained
>     from a
>      > comparison of subplot1 and 2; i.e., I use clim([15, 25]) on both
>      > subplots.  The two subplots display exactly as I want them to.
>      >
>      > Next, I want 2 colorbars to go with the two subplots.  I want the
>     range
>      > of each colorbar to be the same, set as the clim values (15 and 25).
>      > This happens for subplot1, but not for subplot2, which shows the
>     range
>      > 16-24, following its input data range and not the clim values.
>      >
>      > So what I want to know is if it is possible to overide the colorbar
>      > limits, setting them to 15-25?
>      >
>      > I hope that's clearer now, thanks, Evan
>      >
>      >
>      >
>      > On 3/27/07, * Eric Firing* < ef...@ha...
>     <mailto:ef...@ha...>
>      > <mailto:ef...@ha... <mailto:ef...@ha...>>> wrote:
>      >
>      >     Evan,
>      >
>      >     It is still not quite clear to me what you want versus what
>     you are
>      >     getting.  With recent versions of mpl, the colorbar
>     automatically uses
>      >     the same color boundaries as contourf, if that is what the
>     colorbar is
>      >     tracking.  What version of mpl are you using?
>      >
>      >     (With the most recent mpl I see that there is a strange bug
>     such that
>      >     setting clim clobbers the axis tick labeling for the
>     colorbar--yet
>      >     another thing that needs to be figured out and fixed.)
>      >
>      >
> 
> 

Hi Eric, the following lines below will show this.  Interestingly, the
correct (or, at least, what I want) behaviour results from using pcolor, but
not with contourf.


a = arange(12, 27, .5)
b = arange(17, 23, .5)
x, y = meshgrid(a, b)

# get max and min for clim
cmin = min(x.min(), y.min()) # cmin = 12
cmax = max(x.max(), y.max()) # cmax = 26.5

figure(1)
contourf(x)
#pcolor(x)
clim([cmin, cmax])
colorbar()
figure(2)
contourf(y)
#pcolor(y)
clim([cmin, cmax])
colorbar()


-Evan




On 3/27/07, Eric Firing <ef...@ha...> wrote:
>
> Evan,
>
> That is getting clearer, but it still seems to me that no override
> should be needed in this case; it should "just work", so if it doesn't,
> either there is a bug in mpl or a bug in the code.  It would be most
> helpful if you would write a stripped-down simplest-possible script that
> illustrates the problem.  Then I can either show how to fix the script,
> or I can use the script to help me track down the mpl bug, if that is
> the problem.
>
> Eric
>
> Evan Mason wrote:
> > Hi Eric
> >
> > I am using matplotlib-0.90.0.
> >
> > I am making 2 contourf subplots of temperature values which have similar
> > but not equal ranges.  In subplot1 the range is 15-25; in subplot2 it is
> > 16 to 24.  I use clim, giving it the max and min values obtained from a
> > comparison of subplot1 and 2; i.e., I use clim([15, 25]) on both
> > subplots.  The two subplots display exactly as I want them to.
> >
> > Next, I want 2 colorbars to go with the two subplots.  I want the range
> > of each colorbar to be the same, set as the clim values (15 and 25).
> > This happens for subplot1, but not for subplot2, which shows the range
> > 16-24, following its input data range and not the clim values.
> >
> > So what I want to know is if it is possible to overide the colorbar
> > limits, setting them to 15-25?
> >
> > I hope that's clearer now, thanks, Evan
> >
> >
> >
> > On 3/27/07, * Eric Firing* <ef...@ha...
> > <mailto:ef...@ha...>> wrote:
> >
> >     Evan,
> >
> >     It is still not quite clear to me what you want versus what you are
> >     getting.  With recent versions of mpl, the colorbar automatically
> uses
> >     the same color boundaries as contourf, if that is what the colorbar
> is
> >     tracking.  What version of mpl are you using?
> >
> >     (With the most recent mpl I see that there is a strange bug such
> that
> >     setting clim clobbers the axis tick labeling for the colorbar--yet
> >     another thing that needs to be figured out and fixed.)
> >
> >
>
>

Evan,

That is getting clearer, but it still seems to me that no override 
should be needed in this case; it should "just work", so if it doesn't, 
either there is a bug in mpl or a bug in the code.  It would be most 
helpful if you would write a stripped-down simplest-possible script that 
illustrates the problem.  Then I can either show how to fix the script, 
or I can use the script to help me track down the mpl bug, if that is 
the problem.

Eric

Evan Mason wrote:
> Hi Eric
> 
> I am using matplotlib-0.90.0.
> 
> I am making 2 contourf subplots of temperature values which have similar 
> but not equal ranges.  In subplot1 the range is 15-25; in subplot2 it is 
> 16 to 24.  I use clim, giving it the max and min values obtained from a 
> comparison of subplot1 and 2; i.e., I use clim([15, 25]) on both 
> subplots.  The two subplots display exactly as I want them to.
> 
> Next, I want 2 colorbars to go with the two subplots.  I want the range 
> of each colorbar to be the same, set as the clim values (15 and 25).  
> This happens for subplot1, but not for subplot2, which shows the range 
> 16-24, following its input data range and not the clim values.
> 
> So what I want to know is if it is possible to overide the colorbar 
> limits, setting them to 15-25?
> 
> I hope that's clearer now, thanks, Evan
> 
> 
> 
> On 3/27/07, * Eric Firing* <ef...@ha... 
> <mailto:ef...@ha...>> wrote:
> 
>     Evan,
> 
>     It is still not quite clear to me what you want versus what you are
>     getting.  With recent versions of mpl, the colorbar automatically uses
>     the same color boundaries as contourf, if that is what the colorbar is
>     tracking.  What version of mpl are you using?
> 
>     (With the most recent mpl I see that there is a strange bug such that
>     setting clim clobbers the axis tick labeling for the colorbar--yet
>     another thing that needs to be figured out and fixed.)
> 
> 

Hi Eric

I am using matplotlib-0.90.0.

I am making 2 contourf subplots of temperature values which have similar but
not equal ranges.  In subplot1 the range is 15-25; in subplot2 it is 16 to
24.  I use clim, giving it the max and min values obtained from a comparison
of subplot1 and 2; i.e., I use clim([15, 25]) on both subplots.  The two
subplots display exactly as I want them to.

Next, I want 2 colorbars to go with the two subplots.  I want the range of
each colorbar to be the same, set as the clim values (15 and 25).  This
happens for subplot1, but not for subplot2, which shows the range 16-24,
following its input data range and not the clim values.

So what I want to know is if it is possible to overide the colorbar limits,
setting them to 15-25?

I hope that's clearer now, thanks, Evan



On 3/27/07, Eric Firing <ef...@ha...> wrote:
>
> Evan,
>
> It is still not quite clear to me what you want versus what you are
> getting.  With recent versions of mpl, the colorbar automatically uses
> the same color boundaries as contourf, if that is what the colorbar is
> tracking.  What version of mpl are you using?
>
> (With the most recent mpl I see that there is a strange bug such that
> setting clim clobbers the axis tick labeling for the colorbar--yet
> another thing that needs to be figured out and fixed.)
>

Matt Beal wrote:
> Having upgraded to 2.5, I get a segfault when running a very simple plot 
> script (test.py) at the show() function.  Prior to show() I can save to 
> file and the result looks good.  The GUI is crashing on show().
>  
> Any suggestions to fix welcome (I'm guessing many of you know the 
> solution to this problem).

I hope someone does, because I don't.  But until someone comes up with 
the answer, here are possibly relevant questions:  Did you build mpl 
from source?  If so, did you delete the build directory before 
rebuilding with 2.5?  My guess is that there is a version mismatch 
somewhere, and this is the sort of thing that can occur if a major 
change is made and a complete rebuild is not done.  setup.py is not 
smart enough to always know what really needs to be rebuilt, I think.

Eric

>  
> "Annoying" debug information below:
>  
> Thanks!
> -Matt
>  
> hostname:~/.matplotlib>cat test.py
> from pylab import *
> plot([1,2,3])
> show()
> 
> hostname:~/.matplotlib>python test.py --verbose-debug-annoying -dTkAgg
> matplotlib data path ..../python2.5/site-packages/matplotlib/mpl-data
> $HOME=/home/username
> loaded rc file /home/username/.matplotlib/matplotlibrc
> matplotlib version 0.90.0
> verbose.level debug-annoying
> interactive is False
> platform is linux2
> loaded modules: ['_bisect', '_sha512', 'pylab', 'datetime', 
> 'matplotlib.tempfile ', 'distutils.sysconfig', 'encodings.encodings', 'str
> uct', 'tempfile', 'pytz.os', 'zipimport', 'string', 
> 'matplotlib.__future__', 'pytz.tzinfo', ' pytz.datetime', 'distutils.re 
> <http://distutils.re>', 'bisect'
> , 'signal', 'random', 'matplotlib.pytz', 'locale', 'encodings', 
> 'dateutil', ' matplotlib.warnings', 'pytz.pytz', 'matplotlib.sys', 're
> ', 'math', 'fcntl', 'UserDict', 'distutils.os', 'matplotlib', 'codecs', 
> 'md5', '_locale', ' matplotlib.os', 'thread', 'itertools', 'di
> stutils.sys', 'os', '__future__', '_sre', '__builtin__', 'matplotlib.re 
> <http://matplotlib.re>', 'operator', ' distutils.string', 
> 'matplotlib.datetime', 'pos
> ixpath', 'errno', 'binascii', 'sre_constants', '_sha256', 
> 'matplotlib.md5', 'types', 'pytz.sys', '_codecs', 'pytz', 'copy', '_struct'
> , '_types', 'matplotlib.dateutil', 'hashlib', 'distutils', 'posix', 
> 'encodings.aliases', 'exceptions', 'sre_parse', 'pytz.bisect', 'd
> istutils.distutils ', 'copy_reg', 'sre_compile', '_hashlib', '_random', 
> 'site', '__main__', 'shutil', 'strop', 'encodings.codecs', 'ge
> ttext', 'pytz.sets ', 'stat', 'warnings', 'encodings.types', 
> 'encodings.ascii', 'sys', 'os.path', 'pytz.gettext', 'matplotlib.distutil
> s', 'distutils.errors', 'linecache', ' matplotlib.shutil', 'sets']
> numerix numarray 1.5.2
> font search path ['..../python2.5/site-packages/matplotlib/mpl-data']
> trying fontname ..../python2.5/site-packages/matplotlib/mpl-data/cmtt10.ttf
> trying fontname 
> ..../python2.5/site-packages/matplotlib/mpl-data/VeraMoIt.ttf
> trying fontname ..../python2.5/site-packages/matplotlib/mpl-data/cmex10.ttf
> trying fontname ..../python2.5/site-packages/matplotlib/mpl-data/VeraBI.ttf
> trying fontname ..../python2.5/site-packages/matplotlib/mpl-data/VeraBd.ttf
> trying fontname ..../python2.5/site-packages/matplotlib/mpl-data/cmmi10.ttf
> trying fontname 
> ..../python2.5/site-packages/matplotlib/mpl-data/VeraSeBd.ttf
> trying fontname ..../python2.5/site-packages/matplotlib/mpl-data/cmr10.ttf
> trying fontname 
> ..../python2.5/site-packages/matplotlib/mpl-data/VeraMono.ttf
> trying fontname ..../python2.5/site-packages/matplotlib/mpl-data/cmsy10.ttf
> trying fontname ..../python2.5/site-packages/matplotlib/mpl-data/Vera.ttf
> CONFIGDIR=/home/username/.matplotlib
> loaded ttfcache file /home/username/.matplotlib/ttffont.cache
> backend TkAgg version 8.5
> FigureCanvasAgg.draw
> RendererAgg.__init__
> RendererAgg.__init__ width=650.0,                         height=490.0
> RendererAgg.__init__ _RendererAgg done
> RendererAgg.__init__ done
> RendererAgg._get_agg_font
>         findfont found sans-serif, normal, normal 400, normal, 12.0
> findfont returning ..../python2.5/site-packages/matplotlib/mpl-data/Vera.ttf
> RendererAgg._get_agg_font
> RendererAgg.draw_text
> RendererAgg._get_agg_font
> RendererAgg.points_to_pixels
> RendererAgg.points_to_pixels
> RendererAgg._get_agg_font
> RendererAgg._get_agg_font
> RendererAgg.draw_text
> RendererAgg._get_agg_font
> RendererAgg.points_to_pixels
> RendererAgg.points_to_pixels
> RendererAgg._get_agg_font
> RendererAgg._get_agg_font
> RendererAgg.draw_text
> RendererAgg._get_agg_font
> RendererAgg.points_to_pixels
> RendererAgg.points_to_pixels
> RendererAgg._get_agg_font
> RendererAgg._get_agg_font
> RendererAgg.draw_text
> RendererAgg._get_agg_font
> RendererAgg._get_agg_font
> RendererAgg._get_agg_font
> RendererAgg.draw_text
> RendererAgg._get_agg_font
> RendererAgg._get_agg_font
> RendererAgg._get_agg_font
> RendererAgg.draw_text
> RendererAgg._get_agg_font
> RendererAgg.points_to_pixels
> RendererAgg.points_to_pixels
> RendererAgg._get_agg_font
> RendererAgg._get_agg_font
> RendererAgg.draw_text
> RendererAgg._get_agg_font
> RendererAgg.points_to_pixels
> RendererAgg.points_to_pixels
> RendererAgg._get_agg_font
> RendererAgg._get_agg_font
> RendererAgg.draw_text
> RendererAgg._get_agg_font
> RendererAgg.points_to_pixels
> RendererAgg.points_to_pixels
> RendererAgg._get_agg_font
> RendererAgg._get_agg_font
> RendererAgg.draw_text
> RendererAgg._get_agg_font
> RendererAgg._get_agg_font
> RendererAgg._get_agg_font
> RendererAgg.draw_text
> RendererAgg._get_agg_font
> Segmentation fault (core dumped)
> 
> hostname:~/.matplotlib>
>  
> 
> 
> ------------------------------------------------------------------------
> 
> -------------------------------------------------------------------------
> Take Surveys. Earn Cash. Influence the Future of IT
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C M wrote:
> Hi, I'm new to mpl and want to learn date plotting.  Would like to start 
> with the demo, but date_demo1 won't run for me. (My specs:  winXP, 
> Python 2.5, matplotlib 0.9.0, numpy 1.0, and yes was connected to the 
> internet when I ran it).  I just copied into IDLE and saved it and got 
> this error:
> 
> Traceback (most recent call last):
>   File "C:/Documents and Settings/user/Desktop/datedemo.py", line 22, in 
> <module>
>     quotes = quotes_historical_yahoo('INTC', date1, date2)
>   File "C:\Python25\lib\site-packages\matplotlib\finance.py", line 153, 
> in quotes_historical_yahoo
>     try: ret = parse_yahoo_historical(fh, asobject, adjusted)
>   File "C:\Python25\lib\site-packages\matplotlib\finance.py", line 53, 
> in parse_yahoo_historical
>     dt = datetime.date(*time.strptime(datestr, '%d-%b-%y')[:3])
>   File "C:\Python25\lib\_strptime.py", line 310, in strptime
>     (data_string, format))
> ValueError: time data did not match format:  data=2003-12-01  fmt=%d-%b-%y
> 
> Any idea what I'm doing wrong?  

You are not doing anything wrong.  I noticed the bug recently also.  I 
don't know when or why it started.  It is not python 2.5-specific; I see 
it while running 2.4 and svn mpl.

Thanks for reporting it.

Eric


> 
> Thanks,
> Che

Evan,

It is still not quite clear to me what you want versus what you are 
getting.  With recent versions of mpl, the colorbar automatically uses 
the same color boundaries as contourf, if that is what the colorbar is 
tracking.  What version of mpl are you using?

(With the most recent mpl I see that there is a strange bug such that 
setting clim clobbers the axis tick labeling for the colorbar--yet 
another thing that needs to be figured out and fixed.)

Eric

Evan Mason wrote:
> Sorry, I realise that my example in my original post doesn't quite make 
> sense.  My data range is 17 to 23.  I set clim to be clim([15, 25]).  I 
> then want the colorbar limits to be the same as clim, 15 to 25.  The 
> questions remains the same, which is how to set the range for colorbar.
> 
> Thanks, Evan

On Tuesday 27 March 2007 16:27:35 C M wrote:

> ValueError: time data did not match format:  data=2003-12-01  fmt=%d-%b-%y
>
> Any idea what I'm doing wrong?

Well, if data='2003-12-01', the format should be "%y-%m-%d" or "%y-%d-%m" 
depending on the local convention. Here, 2003 is interpreted as a day, which 
of course doesn't work.

Sorry, I realise that my example in my original post doesn't quite make
sense.  My data range is 17 to 23.  I set clim to be clim([15, 25]).  I then
want the colorbar limits to be the same as clim, 15 to 25.  The questions
remains the same, which is how to set the range for colorbar.

Thanks, Evan

Tyler Hayes wrote:
> Ideally I'd like to just make the one call:
> 
> from pylab import *
> 
> Which would load SciPy (& NumPy) automatically

I recommend simply making your own file with all of the imports you need.
Implicitly relying on scipy being the chosen 'numerix' will make your code
difficult to understand.

-- 
Robert Kern

"I have come to believe that the whole world is an enigma, a harmless enigma
 that is made terrible by our own mad attempt to interpret it as though it had
 an underlying truth."
  -- Umberto Eco

Hi
I want to set the limits of my colorbar to something different from that of
my plot.  For example I have a contourf plot where I set the colour limits
to be, say:

clim([15,  25])

But I want the limits of the colorbar to be 10 and 30.  I suspect this is
something to do with mappable and vmin and vmax, but I don't see anything
specific about how to do this, either on this forum or on mpl/sourceforge.

Thanks for any help, Evan

Hi, I'm new to mpl and want to learn date plotting.  Would like to start
with the demo, but date_demo1 won't run for me. (My specs:  winXP, Python
2.5, matplotlib 0.9.0, numpy 1.0, and yes was connected to the internet when
I ran it).  I just copied into IDLE and saved it and got this error:

Traceback (most recent call last):
  File "C:/Documents and Settings/user/Desktop/datedemo.py", line 22, in
<module>
    quotes = quotes_historical_yahoo('INTC', date1, date2)
  File "C:\Python25\lib\site-packages\matplotlib\finance.py", line 153, in
quotes_historical_yahoo
    try: ret = parse_yahoo_historical(fh, asobject, adjusted)
  File "C:\Python25\lib\site-packages\matplotlib\finance.py", line 53, in
parse_yahoo_historical
    dt = datetime.date(*time.strptime(datestr, '%d-%b-%y')[:3])
  File "C:\Python25\lib\_strptime.py", line 310, in strptime
    (data_string, format))
ValueError: time data did not match format:  data=2003-12-01  fmt=%d-%b-%y

Any idea what I'm doing wrong?

Thanks,
Che