matplotlib-users Mailing List for matplotlib

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 Firing<ef...@ha...>  
> 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

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', 'numpy.lib.machar',
'numpy.linalg.linalg', 'numpy.testing.utils']

d:\>


Can somebody help me??

On Sat, Aug 29, 2009 at 1:12 PM, Eric Firing<ef...@ha...> 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.

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.

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.

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.

JDH

Chris Michalski wrote:

> 
> Offered for those who might have the same need – a Python pchip() 
> equivalent ==> pypchip().  Since I'm not sure how attachments work (or 
> if they work at all...), I copied the code I used below, followed by a 
> PNG showing "success":

Chris,

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.

It would also be helpful if you include the actual URLs of the Wikipedia 
articles that you used.  (Or did I miss them?)

Thanks for providing this code, example, and references.

Eric

Is this the only way to plot a sin from x=0 to x=2pi, but shade where x>0.25pi and x<0.75pi?

x0 = np.linspace(0.0, 0.25*np.pi, 100)
x1 = np.linspace(0.25*np.pi, 0.75*np.pi, 100)
x2 = np.linspace(0.75*np.pi,2*np.pi, 100)

y0 = np.sin(x0)
y1 = np.sin(x1)
y2 = np.sin(x2)

fig = figure()
ax1 = fig.add_subplot(111)

ax1.plot(x0,y0)
ax1.fill_between(x1,0,y1)
ax1.plot(x2,y2)
show() 

thanks

Marc Desmarais





      

here's an example

a call to pyplot.axis() after I call pcolor straightens it out though. thx
gokhan, and sorry to all for not picking that up in the docs myself.

and finally, `demolishor' is a great and hilarious song by a band called the
acacia strain, in case there are parties interested in music that might make
your officemates think you're satanic. i am delighted this thread generated
such an enthusiastic response in this regard.

ta ta

On Fri, Aug 28, 2009 at 3:32 PM, John Hunter <jd...@gm...> wrote:

> On Fri, Aug 28, 2009 at 1:59 PM, DEMOLISHOR! the
> Demolishor<des...@gm...> wrote:
> > This is the result from a call to pyplot.pcolor() -- why do the axes
> > automatically expand beyond the range of the data? And how can I set them
> > back? I am not seeing an obvious keyword argument in the pcolor docs to
> do
> > this...
> >
>
> could you post a complete example that replicates the problem?
>
> JDH
>

Here you go.