matplotlib-users Mailing List for matplotlib

Hello all,

I believe I have found a bug in matplotlib's `dviread.py' file.

I am running Ubuntu 10.10 x86_64 and Sage 4.6.1, which includes
matplotlib 1.0.0.  Also I have TeX Live 2010 installed (full install
from the web installer).

It is important to note that the issue to be described *does not occur*
when TeX Live 2009 from the Ubuntu repositories is installed instead of
TeX Live 2010.

The issue also occurs with matplotlib 1.0.1.

When trying to save a matplotlib figure as a PDF with `text.usetex =
True' in `matplotlibrc', at some point the `PsfontsMap' function in
`dviread.py' attempts to parse TeX Live 2010's `pdftex.map' file and fails.

Other people are having the same problem.  See the following two links
for more information:

http://groups.google.com/group/sage-support/browse_thread/thread/dd4a97c3e06e831f
(see second post)
http://article.gmane.org/gmane.comp.python.matplotlib.general/26110

Here is a minimal test case to demonstrate:


----------------------------------------------------------------------
| Sage Version 4.6.1, Release Date: 2011-01-11                       |
| Type notebook() for the GUI, and license() for information.        |
----------------------------------------------------------------------
sage: from matplotlib.dviread import *
sage: PsfontsMap(find_tex_file('pdftex.map'))
---------------------------------------------------------------------------
AssertionError                            Traceback (most recent call last)

/home/michael/<ipython console> in <module>()

/opt/local/sage/local/lib/python2.6/site-packages/matplotlib/dviread.pyc
in __init__(self, filename)
    666         file = open(filename, 'rt')
    667         try:
--> 668             self._parse(file)
    669         finally:
    670             file.close()

/opt/local/sage/local/lib/python2.6/site-packages/matplotlib/dviread.pyc
in _parse(self, file)
    699                 while pos < len(line) and line[pos] == ' ':
    700                     pos += 1
--> 701             self._register(words)
    702
    703     def _register(self, words):

/opt/local/sage/local/lib/python2.6/site-packages/matplotlib/dviread.pyc
in _register(self, words)
    725                     encoding = word[1:]
    726                 elif word.endswith('.enc'):
--> 727                     assert encoding is None
    728                     encoding = word
    729                 else:

AssertionError:
sage:


Here is some debug information (the last two lines may be relevant):


$HOME=/home/michael
CONFIGDIR=/home/michael/.sage//matplotlib-1.0.0
matplotlib data path
/opt/local/sage/local/lib/python2.6/site-packages/matplotlib/mpl-data
loaded rc file
/opt/local/sage/local/lib/python2.6/site-packages/matplotlib/mpl-data/matplotlibrc
matplotlib version 1.0.0
verbose.level debug
interactive is False
units is False
platform is linux2
loaded modules: ['numpy.lib._iotools', 'xml.sax.urlparse', 'distutils',
'numpy.lib.npyio', 'matplotlib.errno', 'matplotlib.matplotlib',
'_bisect', 'subprocess', 'gc', 'matplotlib.tempfile',
'distutils.sysconfig', 'ctypes._endian', 'encodings.encodings',
'matplotlib.colors', 'numpy.core.numerictypes', 'numpy.testing.sys',
'numpy.core.info', 'xml', 'numpy.fft.types', 'numpy.ma.cPickle',
'struct', 'numpy.matrixlib.defmatrix', 'numpy.random.info', 'tempfile',
'numpy.compat.types', 'base64', 'numpy.linalg', 'matplotlib.threading',
'numpy.core.machar', 'numpy.testing.types', 'numpy.testing',
'collections', 'numpy.polynomial.sys', 'numpy.core.umath',
'distutils.types', 'numpy.testing.operator', 'numpy.lib.numpy',
'numpy.core.scalarmath', 'numpy.ma.sys', 'zipimport', 'string',
'matplotlib.subprocess', 'numpy.testing.os', 'matplotlib.locale',
'numpy.lib.arraysetops', 'numpy.testing.unittest', 'numpy.lib.math',
'encodings.utf_8', 'matplotlib.__future__', 'ssl', 'numpy.testing.re',
'itertools', 'numpy.version', 'numpy.lib.re', 'distutils.re',
'numpy.matrixlib.sys', 'ctypes.os', 'numpy.core.os',
'numpy.lib.type_check', 'numpy.compat.sys', 'numpy.lib.__builtin__',
'signal', 'numpy.lib.types', 'numpy.lib._datasource', 'random',
'numpy.ma.extras', 'numpy.fft.fftpack_lite', 'matplotlib.cbook',
'ctypes.ctypes', 'xml.sax.xmlreader', 'numpy.polynomial.string',
'distutils.version', 'cStringIO', 'numpy.polynomial', 'numpy.numpy',
'matplotlib.StringIO', 'locale', 'numpy.add_newdocs',
'numpy.core.getlimits', 'xml.sax.saxutils', 'numpy.lib.sys',
'encodings', 'numpy.ma.itertools', 'array', 'StringIO', 'abc',
'numpy.matrixlib', 'numpy.ctypes', 'numpy.testing.decorators',
'matplotlib.warnings', 'rfc822', 'matplotlib.string', 'urllib',
'matplotlib.sys', 're', 'numpy.lib._compiled_base', 'threading', 'new',
'numpy.random.mtrand', 'urllib2', 'matplotlib.cPickle', 'math',
'numpy.fft.helper', 'fcntl', 'numpy.ma.warnings', 'matplotlib.numpy',
'UserDict', 'numpy.lib.function_base', 'distutils.os', 'matplotlib',
'numpy.fft.numpy', 'xml.sax.codecs', 'exceptions', 'numpy.lib.info',
'ctypes', 'numpy.lib.warnings', 'ctypes.struct', 'codecs',
'numpy.core._sort', 'numpy.os', '_functools', '_locale',
'numpy.__builtin__', 'matplotlib.sre_constants', 'matplotlib.os',
'thread', 'numpy.lib.ufunclike', 'numpy.core.memmap', 'traceback',
'numpy.testing.warnings', 'weakref', 'numpy.core._internal',
'numpy.compat._inspect', 'numpy.linalg.lapack_lite', 'numpy.ma',
'distutils.sys', 'os', 'marshal', 'numpy.lib.itertools', '__future__',
'matplotlib.copy', 'xml.sax.types', 'matplotlib.traceback', '_sre',
'unittest', 'numpy.core.sys', 'numpy.random', 'numpy.linalg.numpy',
'__builtin__', 'numpy.lib.twodim_base', 'numpy.ma.core',
'matplotlib.re', 'numpy.core.cPickle', 'operator',
'numpy.polynomial.polytemplate', 'numpy.core.arrayprint',
'distutils.string', 'numpy.lib.arrayterator', 'select',
'ctypes._ctypes', 'ctypes.sys', 'matplotlib.datetime', 'posixpath',
'numpy.lib.financial', 'numpy.core.multiarray', 'errno', '_socket',
'binascii', 'sre_constants', 'datetime', 'numpy.core.shape_base',
'functools', 'xml.sax.handler', 'os.path', 'numpy.core.function_base',
'numpy.compat.py3k', 'numpy.lib.stride_tricks', 'numpy.core.numpy',
'numpy', '_warnings', 'numpy.polynomial.chebyshev', 'matplotlib.types',
'xml.sax.os', 'cPickle', 'encodings.__builtin__',
'numpy.polynomial.warnings', 'matplotlib.xml', 'matplotlib.new',
'_codecs', 'numpy.lib.operator', 'numpy.polynomial.polynomial',
'numpy.__config__', '_collections', 'matplotlib.pyparsing', 'httplib',
'numpy.ma.numpy', 'copy', 'numpy.core.re', '_struct',
'numpy.core.fromnumeric', 'hashlib', 'numpy.ctypeslib', 'keyword',
'numpy.lib.scimath', 'numpy.fft', 'numpy.lib', 'bisect',
'numpy.random.numpy', 'matplotlib.urllib2', 'matplotlib.random',
'numpy.polynomial.__future__', 'posix', 'encodings.aliases',
'matplotlib.fontconfig_pattern', 'fnmatch', 'sre_parse', 'pickle',
'numpy.core.ctypes', 'mimetools', 'distutils.distutils', 'copy_reg',
'sre_compile', 'xml.sax', 'numpy.fft.fftpack', '_random', '_ctypes',
'numpy.lib.__future__', 'site', 'numpy.lib.polynomial', 'numpy.compat',
'numpy._import_tools', '__main__', 'numpy.fft.info',
'numpy.core.records', 'shutil', 'numpy.lib.cPickle', 'numpy.sys',
'matplotlib.weakref', 'xml.sax.urllib', 'numpy.core._dotblas',
'numpy.testing.traceback', 'strop', 'numpy.testing.numpytest',
'numpy.polynomial.numpy', 'numpy.core.numeric', 'numpy.linalg.info',
'encodings.codecs', '_abcoll', 'numpy.core', 'matplotlib.rcsetup',
'matplotlib.time', 'xml.sax._exceptions', 'genericpath', 'stat', '_ssl',
'numpy.lib.index_tricks', 'numpy.testing.utils', 'warnings',
'numpy.lib.utils', 'numpy.core.defchararray',
'numpy.polynomial.polyutils', 'numpy.lib.shape_base',
'numpy.core.types', 'textwrap', 'sys', '_hashlib',
'numpy.core.warnings', 'socket', 'numpy.core.__builtin__',
'xml.sax.sys', 'numpy.lib.format', 'numpy.lib.os',
'numpy.testing.nosetester', 'types', 'numpy.lib.shutil',
'matplotlib.distutils', '_weakref', 'distutils.errors',
'numpy.matrixlib.numpy', 'urlparse', 'linecache', 'matplotlib.shutil',
'numpy.lib.cStringIO', 'time', 'numpy.linalg.linalg', 'numpy.testing.numpy']
find_tex_file(pdftex.map): ['kpsewhich', 'pdftex.map']
find_tex_file result:
/usr/local/texlive/2010/texmf-var/fonts/map/pdftex/updmap/pdftex.map


Please let me know if there's anything more I may do to help fix
whatever is going awry here.

-Michael

On Sat, Feb 5, 2011 at 10:54 PM, Paul Leopardi
<pau...@ii...>wrote:

> Hi all,
> I'm having trouble using multiple figures with mplot3d. Once each new
> figure
> is plotted, the plots from new figure is also displayed in all of the old
> figures. For example, once the plot for figure 2 has finished, the plot fo
> figure 1 is replaced by a copy of the plot for figure 2, and so on...
> I have included an abbreviated version of my script code. My original code
> uses Cython and my GluCat library, but I am fairly sure the cause of the
> problem lies either with mplot3d or with my Python script code.
>
> I am using openSUSE 11.2 with
> python-base-2.6.2-6.7.1.x86_64
> python-matplotlib-1.0.1-20.1.x86_64
> python-matplotlib-tk-1.0.1-20.1.x86_64
> python-matplotlib-wx-1.0.1-20.1.x86_64
>
> Best, Paul
>
> Script excerpt:
>
> ...
> from mpl_toolkits.mplot3d import Axes3D
> import matplotlib.pyplot as plt
> ...
> # Plot C curves.
> for i in xrange(0,C):
>  ...
>  # Use a new figure for each curve.
>  fig=plt.figure(figsize=(15,12))
>  ax = fig.gca(projection='3d')
>  plt.show()
>  ...
>  # Split the curve into M segments, each with an appropriate colour.
>  for j in range(0,M):
>  # Find N points forming a curve segment ...
>  # Determine the colour of the curve segment...
>  # Plot the curve segment using the chosen colour.
>  alow=(abot-1 if j>0 else abot)
>  ax.plot(x[0,alow:atop],x[1,alow:atop],x[2,alow:atop],c=rgb.tolist())
>  plt.draw()
>  plt.show()
>
>
Paul,

I am not exactly sure what your sample script is trying to do.  Could you
please attach a short self-contained working script that demonstrates your
problem?

Ben Root

> Your data are embedded in a Line2d object which is itself a child of an
> Axes, itself child of the figure. Try:
> Fig = F.matplotlib()
> ax = Fig.get_axes()[0] # to get the first (and maybe only) subplot
> line = ax.get_axes()[0]
> xdata = line.get_xdata()
> ydata = line.get_ydata()

There is something wrong ...

sage: var('x,y') 

(x, y)
sage: F=implicit_plot(x**2+y**2==1,(x,-5,5),(y,-5,5))
sage: Fig = F.matplotlib()
sage: ax = Fig.get_axes()[0] <-- I checked  : it is the only element :)
sage: line = ax.get_axes()[0]
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call 
last) 
 

TypeError: 'AxesSubplot' object does not support indexing 
 

sage:line=ax.get_axes() 

sage:type(line) 

<class 'matplotlib.axes.AxesSubplot'>

However, using some "grep get_ydata" from that point, I suceed to track 
my information.
It was in the segments argument of matplotlib.collections.LineCollection

Now I'm tracking back the information ... It is in
mcontour.QuadContourSet(self, *args, **kwargs).allsegs
in the method matplotlib.axes.Axes.contour()

I'm almost done.

Thanks for help !

Have a nice afternoon
Laurent

PS :
I'll post the final answer here :
http://ask.sagemath.org/question/359/get_minmax_data-on-implicit_plot

PPS :
Argh !! Someone already did !

Le dimanche 06 février 2011 à 14:29 +0100, Laurent a écrit :
> If it can help, I have the following in a Sage terminal :
> 
> sage: var('x,y')
> sage: F=implicit_plot(x**2+y**2==2,(x,-5,5),(y,-5,5),plot_points=100)
> sage: F.matplotlib()
> <matplotlib.figure.Figure object at 0xbfb60ac>
> sage: F.matplotlib().get_children()
> [<matplotlib.patches.Rectangle object at 0xc144e4c>, 
> <matplotlib.axes.AxesSubplot object at 0xc14472c>]
> 
> I really do not understand where is the data ??? In the Rectangle ? In 
> the Axes ?

Your data are embedded in a Line2d object which is itself a child of an
Axes, itself child of the figure. Try:
Fig = F.matplotlib()
ax = Fig.get_axes()[0] # to get the first (and maybe only) subplot
line = ax.get_axes()[0]
xdata = line.get_xdata()
ydata = line.get_ydata()

-- 
Fabrice Silva

Dear Sebastian,

Your solution is simple, well described and it works with minimal effort
Thank you so much!
I hope the Matplotlib devellopers will take some action.

Tom

Op 6-2-2011 13:16, Sebastian Voigt schreef:
> Hello Tom,
>
> I encountered the same problem recently. The toolbar icons are a mix of
> png and svg images. The png images are displayed properly while the svg
> icons are not shown.  This is a problem with PyQt. I found a proposal on
> the web, where you should add the line
>
>       import PyQt4.QtXml
>
> somewhere to your code. This is because xml support is needed to read
> svg files. However, this did not work for me. Instead I now use a rather
> ugly workaround: I rename the original *.png icon files to *.svg for
> those icons that are expected to be svg files. Qt will then find an svg
> file but it's clever enough to load it as png.
> Save those modified files somewhere as resources. Add them to the
> data_files list in your setup script and they will overwrite the
> original files at every build so you don't have to care any more.
>
> You can find out which files have to be renamed by looking into
> PACKAGEPATH/matplotlib/backends/backend_qt4.py line 399 and below.
> Another approach would be to directly rename the files in
> NavigationToolbar2QT._init_toolbar() to *.png since matplotlib provides
> png and svg files for every icon.
>
> Greetings,
>       Sebastian
>
>
> Am 06.02.2011 11:20, schrieb Tom van der Hoeven:
>> Hello,
>>
>> I have a simple program
>> ---------------graf.py--------------
>>
>> import matplotlib.pyplot as plt
>> plt.plot([1,2,3,8,0,9,1,10,5])
>> plt.ylabel('some numbers')
>> plt.show()
>> --------------------------------------------------
>> If I look to a matplotlib figures on my screen using the exe made with
>> py2exe I mis all the buttons but one of the navigation bar.
>> If I work direct with the Python interpreted they are there.
>> I use the current version of Pythonxy
>>
>> ------------ setup.py --------------
>> from distutils.core import setup
>> import py2exe
>> import matplotlib
>>
>> name = 'graf.py'
>> INCLUDES = [ 'sip' , 'matplotlib.numerix.random_array'
>>                                  #        , 'PyQt4._qt'
>>                                           , 'matplotlib.backends'
>>                                           ,
>> 'matplotlib.backends.backend_qt4agg']
>> #['matplotlib.backends.backend_qt4agg']
>> EXCLUDES = []
>> [ '_gtkagg' , '_tkagg' , 'Tkconstants' , 'Tkinter' ,'tcl' ]
>> #['_tkagg' , '_ps' , '_fltkagg' , 'Tkinter' , 'Tkconstants' , '_cairo' ,
>> '_gtk' , 'gtkcairo' ,
>>               # 'pydoc' , 'sqlite3' , 'bsddb' , 'curses' , 'tcl' ,
>> '_wxagg' , '_gtagg' , '_cocoaagg' , '_wx' ]
>> DLL_EXCLUDES = ['MSVCP90.dll']
>> ICON_RESOURSES = []
>> OTHER_RESOURCES = []
>> DATA_FILES = matplotlib.get_py2exe_datafiles()
>>
>> setup(name             = name,
>>          version          = '1.0',
>>          options          = { "py2exe" : { 'compressed'   : 1,
>>                                            'optimize'     : 2,
>>                                            'bundle_files' : 2,
>>                                            'includes'     : INCLUDES,
>>                                            'excludes'     : EXCLUDES,
>>                                            'dll_excludes' : DLL_EXCLUDES }
>> } ,
>>          console          = [ { 'script'          : name,
>>                                 'icon_resources'  : ICON_RESOURSES,
>>                                 'other_resources' : OTHER_RESOURCES, } ] ,
>>          description      = 'Hele mooie',
>>          author           = 'Tom van der Hoeven',
>>          author_email     = 'To...@va...' ,
>>          maintainer       = 'Tom van der Hoeven',
>>          maintainer_email = 'To...@va...',
>>          license          = '',
>>          url              = 'http://projecthomepage.com',
>>          data_files       = DATA_FILES,
>>          )
>> -------------------------
>> can you help me
>>
>> Tom
>>
>> ------------------------------------------------------------------------------
>> The modern datacenter depends on network connectivity to access resources
>> and provide services. The best practices for maximizing a physical server's
>> connectivity to a physical network are well understood - see how these
>> rules translate into the virtual world?
>> http://p.sf.net/sfu/oracle-sfdevnlfb
>> _______________________________________________
>> Matplotlib-users mailing list
>> Mat...@li...
>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>
>
> ------------------------------------------------------------------------------
> The modern datacenter depends on network connectivity to access resources
> and provide services. The best practices for maximizing a physical server's
> connectivity to a physical network are well understood - see how these
> rules translate into the virtual world?
> http://p.sf.net/sfu/oracle-sfdevnlfb
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>

Hello all !

I'm sorry if my question is not clear, but I do not know ho to produce a 
simple example.

I'm plotting the graph of an implicit given function (say x^2+y^2=3) 
using Sage.

What I know it that
1. when I ask sage to plot   implicit_plot( f==3,(x,-5,5),(y,-5,5) ),
     Sage computes f-3 on an array of points in the square (-5,-5)x(5,5).
2. Sage creates an object matplotlib.figure.Figure that contains 
somewhere the information about the array of computed points and ask 
matplotlib to plot it

What I understood is that somewhere in matplotlib, the values are parsed 
and a path is created. That path is the set of points on which f-3=0


My aim : catch the set of points that satisfy f-3=0. That has to be 
stored --or at last computed-- somewhere in matplotlib.figure.Figure

I read the source, but I'm really lost.

The final purpose is to know the bounding box of the points that are 
*actually* plotted without taking into account the axes, labels and 
other decorations.

Does someone know how to do that ?

Since the object I have on hand is created by Sage[1] in a quite complex 
way, I'm sorry to not being able to furnish an example.


Thanks
Laurent


If it can help, I have the following in a Sage terminal :

sage: var('x,y')
sage: F=implicit_plot(x**2+y**2==2,(x,-5,5),(y,-5,5),plot_points=100)
sage: F.matplotlib()
<matplotlib.figure.Figure object at 0xbfb60ac>
sage: F.matplotlib().get_children()
[<matplotlib.patches.Rectangle object at 0xc144e4c>, 
<matplotlib.axes.AxesSubplot object at 0xc14472c>]

I really do not understand where is the data ??? In the Rectangle ? In 
the Axes ?

On the Sage's side, the discussion is here :
http://ask.sagemath.org/question/359/get_minmax_data-on-implicit_plot


[1] www.sagemath.org

Hello Tom,

I encountered the same problem recently. The toolbar icons are a mix of 
png and svg images. The png images are displayed properly while the svg 
icons are not shown.  This is a problem with PyQt. I found a proposal on 
the web, where you should add the line

     import PyQt4.QtXml

somewhere to your code. This is because xml support is needed to read 
svg files. However, this did not work for me. Instead I now use a rather 
ugly workaround: I rename the original *.png icon files to *.svg for 
those icons that are expected to be svg files. Qt will then find an svg 
file but it's clever enough to load it as png.
Save those modified files somewhere as resources. Add them to the 
data_files list in your setup script and they will overwrite the 
original files at every build so you don't have to care any more.

You can find out which files have to be renamed by looking into  
PACKAGEPATH/matplotlib/backends/backend_qt4.py line 399 and below. 
Another approach would be to directly rename the files in 
NavigationToolbar2QT._init_toolbar() to *.png since matplotlib provides 
png and svg files for every icon.

Greetings,
     Sebastian


Am 06.02.2011 11:20, schrieb Tom van der Hoeven:
> Hello,
>
> I have a simple program
> ---------------graf.py--------------
>
> import matplotlib.pyplot as plt
> plt.plot([1,2,3,8,0,9,1,10,5])
> plt.ylabel('some numbers')
> plt.show()
> --------------------------------------------------
> If I look to a matplotlib figures on my screen using the exe made with
> py2exe I mis all the buttons but one of the navigation bar.
> If I work direct with the Python interpreted they are there.
> I use the current version of Pythonxy
>
> ------------ setup.py --------------
> from distutils.core import setup
> import py2exe
> import matplotlib
>
> name = 'graf.py'
> INCLUDES = [ 'sip' , 'matplotlib.numerix.random_array'
>                                 #        , 'PyQt4._qt'
>                                          , 'matplotlib.backends'
>                                          ,
> 'matplotlib.backends.backend_qt4agg']
> #['matplotlib.backends.backend_qt4agg']
> EXCLUDES = []
> [ '_gtkagg' , '_tkagg' , 'Tkconstants' , 'Tkinter' ,'tcl' ]
> #['_tkagg' , '_ps' , '_fltkagg' , 'Tkinter' , 'Tkconstants' , '_cairo' ,
> '_gtk' , 'gtkcairo' ,
>              # 'pydoc' , 'sqlite3' , 'bsddb' , 'curses' , 'tcl' ,
> '_wxagg' , '_gtagg' , '_cocoaagg' , '_wx' ]
> DLL_EXCLUDES = ['MSVCP90.dll']
> ICON_RESOURSES = []
> OTHER_RESOURCES = []
> DATA_FILES = matplotlib.get_py2exe_datafiles()
>
> setup(name             = name,
>         version          = '1.0',
>         options          = { "py2exe" : { 'compressed'   : 1,
>                                           'optimize'     : 2,
>                                           'bundle_files' : 2,
>                                           'includes'     : INCLUDES,
>                                           'excludes'     : EXCLUDES,
>                                           'dll_excludes' : DLL_EXCLUDES }
> } ,
>         console          = [ { 'script'          : name,
>                                'icon_resources'  : ICON_RESOURSES,
>                                'other_resources' : OTHER_RESOURCES, } ] ,
>         description      = 'Hele mooie',
>         author           = 'Tom van der Hoeven',
>         author_email     = 'To...@va...' ,
>         maintainer       = 'Tom van der Hoeven',
>         maintainer_email = 'To...@va...',
>         license          = '',
>         url              = 'http://projecthomepage.com',
>         data_files       = DATA_FILES,
>         )
> -------------------------
> can you help me
>
> Tom
>
> ------------------------------------------------------------------------------
> The modern datacenter depends on network connectivity to access resources
> and provide services. The best practices for maximizing a physical server's
> connectivity to a physical network are well understood - see how these
> rules translate into the virtual world?
> http://p.sf.net/sfu/oracle-sfdevnlfb
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>

For an interactive use, you may use callbacks to update the visibility
of ticks automatically.
Regards,

-JJ


import matplotlib.transforms as mtransforms

def update_yticks(ax):

    axis = ax.yaxis
    interval = axis.get_view_interval()

    # get visible ticks
    myticks = [t for t in axis.iter_ticks() \
               if mtransforms.interval_contains(interval, t[1])]

    # make all ticks visible again
    for mytick in myticks: mytick[0].label1.set_visible(True)

    # make first tick invisible
    myticks[0][0].label1.set_visible(False)

    # make last tick invisible
    myticks[-1][0].label1.set_visible(False)


import matplotlib.pyplot as plt

ax = plt.subplot(111)
update_yticks(ax)
cid = ax.callbacks.connect('ylim_changed', update_yticks)




On Sun, Feb 6, 2011 at 5:17 PM, Paul Ivanov <piv...@gm...> wrote:
> Francesco Montesano, on 2011-02-04 17:01,  wrote:
>> Dear all again,
>>
>> I've tried to play with it again, but I couldn't find a
>> solution for the problem.  For clarity I report an example of
>> what each of the subplots looks like:
>
> Hi Francesco,
>
> thanks for the clarification, here are two ways to get the look
> you want. I added some comments to help you understand what was
> going on before. (The resulting figure is attached, just in case).
>
> import numpy as np
> import matplotlib.pyplot as plt
> mean=np.array([-0.9206394, -0.90127456, -0.91983625, -0.97765539, -1.02991184,
>    -1.02267017, -0.97730167, -0.93715172, -0.94324653, -0.92884379])
> stddev= np.array([0.16351397,0.15075966,0.13413909,0.15404823,0.13559582, 0.13109754,0.12128598,0.11589682,0.11921571,0.10866761])
>
> ax = plt.figure().add_axes([0.1,0.1,0.8,0.8])
> ax.errorbar(np.arange(10,20)/100., mean, yerr=stddev)
>
> ax.set_xlim([0.095, 0.195])
>
> lab = ax.get_ymajorticklabels()
> plt.draw() # ticks only get text assigned during a call to draw
> print lab
> for i in lab:
>    print i # note that \u2212 is a unicode minus sign
>
> # this work for the first draw - relies on l.get_text() returning
> # nothing for labels which aren't used/drawn - which isn't the
> # case in general after panning and zooming interactively
> shown_lab = [l for l in lab if l.get_text()]
> shown_lab[0].set_visible(False)
> shown_lab[-1].set_visible(False)
>
> ## alternative solution without extra draw(). more robust, can be
> ## used even after initial draw.
> #ymin,ymax = ax.get_ylim()
> #tl = ax.yaxis.get_majorticklocs()
> #lab[(tl<ymin).sum()].set_visible(False)
> #lab[-(tl>ymax).sum()-1].set_visible(False)
>
> ## hybrid of the two.
> #ymin,ymax = ax.get_ylim()
> #tl = ax.yaxis.get_majorticklocs()
> #shown_lab = [l for l,t  in zip(lab,tl) if t>ymin and t<ymax)
> #shown_lab[0].set_visible(False)
> #shown_lab[-1].set_visible(False)
>
> plt.show()
>
>
> best,
> --
> Paul Ivanov
> 314 address only used for lists,  off-list direct email at:
> http://pirsquared.org | GPG/PGP key id: 0x0F3E28F7
>
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> ihoAn1uni4kEu4Kq+B0IdCu26Kw1aA9Q
> =B6ZO
> -----END PGP SIGNATURE-----
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Hello,

I have a simple program
---------------graf.py--------------

import matplotlib.pyplot as plt
plt.plot([1,2,3,8,0,9,1,10,5])
plt.ylabel('some numbers')
plt.show()
--------------------------------------------------
If I look to a matplotlib figures on my screen using the exe made with 
py2exe I mis all the buttons but one of the navigation bar.
If I work direct with the Python interpreted they are there.
I use the current version of Pythonxy

------------ setup.py --------------
from distutils.core import setup
import py2exe
import matplotlib

name = 'graf.py'
INCLUDES = [ 'sip' , 'matplotlib.numerix.random_array'
                               #        , 'PyQt4._qt'
                                        , 'matplotlib.backends'
                                        , 
'matplotlib.backends.backend_qt4agg']
#['matplotlib.backends.backend_qt4agg']
EXCLUDES = []
[ '_gtkagg' , '_tkagg' , 'Tkconstants' , 'Tkinter' ,'tcl' ]
#['_tkagg' , '_ps' , '_fltkagg' , 'Tkinter' , 'Tkconstants' , '_cairo' , 
'_gtk' , 'gtkcairo' ,
            # 'pydoc' , 'sqlite3' , 'bsddb' , 'curses' , 'tcl' , 
'_wxagg' , '_gtagg' , '_cocoaagg' , '_wx' ]
DLL_EXCLUDES = ['MSVCP90.dll']
ICON_RESOURSES = []
OTHER_RESOURCES = []
DATA_FILES = matplotlib.get_py2exe_datafiles()

setup(name             = name,
       version          = '1.0',
       options          = { "py2exe" : { 'compressed'   : 1,
                                         'optimize'     : 2,
                                         'bundle_files' : 2,
                                         'includes'     : INCLUDES,
                                         'excludes'     : EXCLUDES,
                                         'dll_excludes' : DLL_EXCLUDES } 
} ,
       console          = [ { 'script'          : name,
                              'icon_resources'  : ICON_RESOURSES,
                              'other_resources' : OTHER_RESOURCES, } ] ,
       description      = 'Hele mooie',
       author           = 'Tom van der Hoeven',
       author_email     = 'To...@va...' ,
       maintainer       = 'Tom van der Hoeven',
       maintainer_email = 'To...@va...',
       license          = '',
       url              = 'http://projecthomepage.com',
       data_files       = DATA_FILES,
       )
-------------------------
can you help me

Tom

Francesco Montesano, on 2011-02-04 17:01,  wrote:
> Dear all again,
> 
> I've tried to play with it again, but I couldn't find a
> solution for the problem.  For clarity I report an example of
> what each of the subplots looks like:

Hi Francesco,

thanks for the clarification, here are two ways to get the look
you want. I added some comments to help you understand what was
going on before. (The resulting figure is attached, just in case).

import numpy as np
import matplotlib.pyplot as plt
mean=np.array([-0.9206394, -0.90127456, -0.91983625, -0.97765539, -1.02991184,
    -1.02267017, -0.97730167, -0.93715172, -0.94324653, -0.92884379])
stddev= np.array([0.16351397,0.15075966,0.13413909,0.15404823,0.13559582, 0.13109754,0.12128598,0.11589682,0.11921571,0.10866761])

ax = plt.figure().add_axes([0.1,0.1,0.8,0.8])
ax.errorbar(np.arange(10,20)/100., mean, yerr=stddev)

ax.set_xlim([0.095, 0.195])

lab = ax.get_ymajorticklabels()
plt.draw() # ticks only get text assigned during a call to draw
print lab
for i in lab: 
    print i # note that \u2212 is a unicode minus sign

# this work for the first draw - relies on l.get_text() returning
# nothing for labels which aren't used/drawn - which isn't the
# case in general after panning and zooming interactively
shown_lab = [l for l in lab if l.get_text()]
shown_lab[0].set_visible(False)
shown_lab[-1].set_visible(False)

## alternative solution without extra draw(). more robust, can be
## used even after initial draw.
#ymin,ymax = ax.get_ylim()
#tl = ax.yaxis.get_majorticklocs()
#lab[(tl<ymin).sum()].set_visible(False)
#lab[-(tl>ymax).sum()-1].set_visible(False)

## hybrid of the two.
#ymin,ymax = ax.get_ylim()
#tl = ax.yaxis.get_majorticklocs()
#shown_lab = [l for l,t  in zip(lab,tl) if t>ymin and t<ymax)
#shown_lab[0].set_visible(False)
#shown_lab[-1].set_visible(False)

plt.show()


best,
-- 
Paul Ivanov
314 address only used for lists,  off-list direct email at:
http://pirsquared.org | GPG/PGP key id: 0x0F3E28F7 

Hi all,
I'm having trouble using multiple figures with mplot3d. Once each new figure 
is plotted, the plots from new figure is also displayed in all of the old 
figures. For example, once the plot for figure 2 has finished, the plot fo 
figure 1 is replaced by a copy of the plot for figure 2, and so on...
I have included an abbreviated version of my script code. My original code 
uses Cython and my GluCat library, but I am fairly sure the cause of the 
problem lies either with mplot3d or with my Python script code.

I am using openSUSE 11.2 with
python-base-2.6.2-6.7.1.x86_64
python-matplotlib-1.0.1-20.1.x86_64
python-matplotlib-tk-1.0.1-20.1.x86_64
python-matplotlib-wx-1.0.1-20.1.x86_64

Best, Paul

Script excerpt:

...
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
...
# Plot C curves.
for i in xrange(0,C):
 ...
 # Use a new figure for each curve.
 fig=plt.figure(figsize=(15,12))
 ax = fig.gca(projection='3d')
 plt.show()
 ...
 # Split the curve into M segments, each with an appropriate colour.
 for j in range(0,M):
  # Find N points forming a curve segment ...
  # Determine the colour of the curve segment...
  # Plot the curve segment using the chosen colour.
  alow=(abot-1 if j>0 else abot)
  ax.plot(x[0,alow:atop],x[1,alow:atop],x[2,alow:atop],c=rgb.tolist())
  plt.draw()
 plt.show()

Hey all,
I try to create a .exe file using py2exe, but this error shows up when i try
to run the created file .exe:

Traceback (most recent call last):
  File "ModeloPitzer.py", line 2, in <module>
  File "zipextimporter.pyo", line 82, in load_module
  File "matplotlib\pyplot.pyo", line 95, in <module>
  File "matplotlib\backends\__init__.pyo", line 25, in pylab_setup
  File "zipextimporter.pyo", line 82, in load_module
  File "matplotlib\backends\backend_qt4agg.pyo", line 12, in <module>
  File "zipextimporter.pyo", line 82, in load_module
  File "matplotlib\backends\backend_qt4.pyo", line 16, in <module>
  File "zipextimporter.pyo", line 82, in load_module
  File "matplotlib\backends\qt4_editor\figureoptions.pyo", line 11, in
<module>
  File "zipextimporter.pyo", line 82, in load_module
  File "matplotlib\backends\qt4_editor\formlayout.pyo", line 51, in <module>
ImportError: Warning: formlayout requires PyQt4 >v4.3

My PyQt4 version is 4.5.4.

How can I solve that? Anyone?
-- 
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