[Matplotlib-users] After update to 0.99.0 - mpl doesn't work

[Sebastian Pająk]

Hi
When I try to import anything from mpl, Python's interpreter exits
without any error.
This happens after the 0.99.0 upgrade. This is example session:

d:\python
Python 2.6.2 (r262:71605, Apr 14 2009, 22:40:02) [MSC v.1500 32 bit
(Intel)] on win32
Type help, copyright, credits or license for more information.
 import matplotlib.pyplot as plt

matplotlib data path D:\msys\opt\python\lib\site-packages\matplotlib\mpl-data
loaded rc file D:\msys\etc\.matplotlib\matplotlibrc
matplotlib version 0.99.0
verbose.level debug-annoying
interactive is False
units is False
platform is win32
loaded modules: ['numpy.lib._iotools', 'xml.sax.urlparse',
'distutils', 'functools', 'matplotlib.matplotlib', 'subprocess', 'gc',
'matplotlib.tempfile', 'distutils.sysconfig', 'ctypes._endian',
'encodings.encodings', 'matplotlib.colors', 'msvcrt',
'numpy.testing.sys', 'numpy.core.info', 'xml', 'numpy.fft.types',
'numpy.ma.operator', 'numpy.ma.cPickle', 'matplotlib.copy',
'numpy.random.info', 'tempfile', 'base64', 'numpy.linalg',
'matplotlib.threading', 'numpy.testing.operator', 'imp',
'numpy.testing', 'collections', 'numpy.core.umath', '_struct',
'distutils.types', 'numpy.lib.numpy', 'numpy.core.scalarmath',
'zipimport', 'string', 'matplotlib.subprocess', 'numpy.testing.os',
'matplotlib.locale', 'numpy.lib.arraysetops',
'numpy.testing.unittest', 'numpy.lib.math', 'textwrap',
'matplotlib.__future__', 'ssl', 'numpy.testing.re', 'itertools',
'numpy.version', 'numpy.lib.re', 'distutils.re',
'ctypes.os', 'numpy.core.os', 'numpy.lib.type_check',
'numpy.lib.__builtin__', 'signal', 'numpy.lib.types',
'numpy.lib._datasource', 'random', 'threading', 'token',
'numpy.fft.fftpack_lite', 'matplotlib.cbook', 'ctypes.ctypes',
'xml.sax.xmlreader', 'numpy.__builtin__', 'dis', 'distutils.version',
'cStringIO', 'numpy.ma.core', 'encodings.cp852',
'matplotlib.StringIO', 'numpy.ma.extras', 'locale',
'numpy.add_newdocs', 'numpy.lib.getlimits', 'xml.sax.saxutils',
'matplotlib.numpy', 'numpy.lib.sys',
'encodings', 'numpy.ma.itertools', 'StringIO', 'numpy.lib.io', 'abc',
'numpy.ctypes', 'numpy.testing.decorators', 'matplotlib.warnings',
'matplotlib.string', '_subprocess', 'urllib', 'matplotlib.sys', 're',
'numpy.lib._compiled_base', 'ntpath', 'numpy.random.mtrand', 'math',
'numpy.fft.helper', 'numpy.ma.warnings', 'inspect',
'numpy.ma.inspect', 'UserDict', 'numpy.lib.function_base',
'distutils.os', 'matplotlib', 'numpy.fft.numpy', 'xml.sax.codecs',
'exceptions', 'numpy.lib.info', 'numpy.core.numerictypes', 'ctypes',
'numpy.lib.warnings', 'ctypes.struct', 'codecs', 'numpy.core._sort',
'numpy.os', 'struct', '_functools', '_locale',
'matplotlib.sre_constants', 'matplotlib.os', 'thread',
'numpy.lib.ufunclike', 'numpy.core.memmap', 'traceback', 'weakref',
'numpy.core._internal', 'numpy.fft.fftpack', 'opcode',
'numpy.linalg.lapack_lite', 'distutils.sys', 'os',
'numpy.lib.itertools', '__future__', '_collections', 'xml.sax.types',
'matplotlib.traceback', '_sre', 'unittest', 'numpy.core.sys',
'numpy.random', 'numpy.linalg.numpy', '__builtin__',
'numpy.lib.twodim_base', 'matplotlib.re', 'numpy.core.cPickle',
'operator', 'numpy.core.arrayprint', 'distutils.string',
'numpy.lib.arrayterator',
'numpy.numpy', 'ctypes.sys', 'matplotlib.errno',
'numpy.lib.financial', 'numpy.core.multiarray', 'errno', '_socket',
'binascii', 'sre_constants', 'datetime', 'numpy.ma',
'xml.sax.handler', 'os.path',
'tokenize', 'numpy.lib.stride_tricks', 'numpy.core.numpy', 'numpy',
'_warnings', 'matplotlib.types', 'numpy.core.defmatrix', 'xml.sax.os',
'cPickle', 'encodings.__builtin__', 'matplotlib.xml', '_codecs',
'numpy.lib.operator', 'numpy.__config__', 'matplotlib.pyparsing',
'nturl2path', 'numpy.ma.numpy', 'copy', 'numpy.core.re', 'socket',
'numpy.core.fromnumeric', 'numpy.ctypeslib', 'keyword',
'numpy.lib.scimath', 'numpy.fft', 'numpy.lib', 'numpy.random.numpy',
'encodings.aliases', 'matplotlib.distutils', 'fnmatch', 'sre_parse',
'numpy.core.ctypes', 'distutils.distutils', 'copy_reg', 'sre_compile',
'xml.sax', '_random', 'numpy.lib.__future__', 'site',
'numpy.lib.polynomial', 'encodings.cp1250',
'numpy._import_tools', '__main__', 'numpy.fft.info',
'numpy.core.records', 'shutil', 'numpy.lib.cPickle', 'numpy.sys',
'matplotlib.weakref', 'xml.sax.urllib', 'numpy.testing.traceback',
'strop', 'numpy.testing.numpytest', 'numpy.core.numeric',
'numpy.linalg.info', 'encodings.codecs', 'ctypes._ctypes', '_abcoll',
'numpy.core', 'matplotlib.rcsetup', 'matplotlib.time', 'nt',
'xml.sax._exceptions', 'genericpath', 'stat', '_ssl',
'numpy.lib.index_tricks', 'warnings', 'numpy.lib.utils',
'numpy.core.defchararray', '_ctypes', 'numpy.lib.shape_base',
'numpy.core.types', 'sys', 'numpy.core.warnings',
'numpy.core.__builtin__', 'xml.sax.sys', 'numpy.lib.format',
'numpy.lib.os', 'numpy.testing.nosetester', 'types',
'numpy.lib.shutil', 'matplotlib.datetime',
'matplotlib.fontconfig_pattern', '_weakref',
'distutils.errors', 'urlparse', 'linecache', 'matplotlib.shutil',
'numpy.lib.cStringIO', 'time', 

Re: [Matplotlib-users] Piecewise Cubic Hermite Interpolating Polynomial in python

[Chris Michalski]

Thanks for the inputs...  perhaps it will provide the impetus for  
future postings as well...

chris

On Aug 29, 2009, at 11:49 AM, John Hunter wrote:

 On Sat, Aug 29, 2009 at 1:12 PM, Eric Firingefir...@hawaii.edu  
 wrote:

 This looks interesting.  I successfully ran your program by using  
 copy
 and paste to get it into a file, but for the future I certainly
 recommend that you attach such a file directly--file attachments
 generally work very well these days, but bad things can happen to  
 code
 included as inline text.

I haven't contributed to matplotlib or numpy even though I've used  
them for some years now, so I wasn't sure about the etiquette of  
file attachments.

The other thing I recommend is do not use the pylab namespace for any

 of the numerics.  pylab is getting all the numerical functions from
 numpy, so if you

  import numpy as np

 and then refer to any numerical functions you need as np.somefunc.

Point well taken.  Since pylab exposes most of the numpy calls I use,  
I typically include pylab instead for nump.

 Finally, for the functions to be suitable for inclusion in a
 production package like numpy or matplotlib.mlab, you should not use
 any print statements in the function, but rather a combination of
 warnings.warn or exceptions or if it for matplotlib, use the
 verbose.report infrastructure.  That way users can configure how much
 verbosity they want, where the output should be directed, etc.

Point also well taken.  I figured out when there were problems, but  
even after 7 years of writing large Python package, I haven't found  
the best way to handle exceptions.  Usually I purposely cause a  
crash so I don't miss the fact that the code had ill formed data.

 After a cleanup, you may want to check with numpy or scipy to see of
 it could find a home there.  There was a discussion at scipy on the
 need to improve scipy.interpolate and this seems to go part of the way
 toward that objective.  So I would start there.

I'll send it along to the scipy people.  I figured since I figured out  
a relatively simple solution to a problem that is often encountered,  
it might find use even in its primitive form.  I'll add the URLs to  
the WIkipedia references as well.

 JDH


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[Matplotlib-users] setting axis label offset from end of spine

[jason-sage]

I'm trying to change the position of the axis label so that it is a 
certain number of points off the end of the spine representing the 
x-axis.  I'm trying to use the transform attribute and the offset_copy 
function to say put the label 5 points right of the end of the spine.  
So far, my code looks something like:

xlabel=subplot.xaxis.get_label()
xlabel.set_horizontalalignment('left')
xlabel.set_verticalalignment('baseline')
xtrans=offset_copy(subplot.transData, subplot.figure, x=5, y=0, 
units='points')
subplot.xaxis.set_label_coords(subplot.get_xlim()[1], 0,transform=xtrans)

However, this doesn't handle the case where the spine representing the 
x-axis is not the same as the line y=0.  Any ideas on how to construct 
the transform to say 5 points to the right of the right end of this 
given spine?

Thanks,

Jason

--
Jason Grout



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