matplotlib-users Mailing List for matplotlib

 No challenge here, just a lack of knowledge.
 My application will be writing a progress log to a text file as it chews on
the data and spits out the bones. Among the lines of text that document how
input data are used to produce the output will be plots of the
under-generation solution fuzzy set (a simple 2D plot). Also, I want the text
to be in LaTeX (and the plots to be in a compatible format; e.g., .eps or
.pdf) so the report can be printed with pdflatex.
 I just looked at the PyX web site and it appears that there is similarity
in abilities -- for my needs, at least -- between matplotlib and pyx. What
are the relative advantages of each?
 Your advice, suggestions, thoughts, and other contributions are solicited.
TIA,
Rich
-- 
Richard B. Shepard, Ph.D. | Author of "Quantifying Environmental
Applied Ecosystem Services, Inc. (TM) | Impact Assessments Using Fuzzy Logic"
<http://www.appl-ecosys.com> Voice: 503-667-4517 Fax: 503-667-8863

On Jan 16, 2006, at 2:14 PM, Eric Firing wrote:
> On my machine, with latest svn numpy and cvs mpl, I don't get an 
> import error. My numerix/fft/__init__.py looks like this:
>
>
> from matplotlib.numerix import which
>
> if which[0] == "numarray":
> from numarray.fft import *
> elif which[0] == "numeric":
> from FFT import *
> elif which[0] == "numpy":
> from numpy.dft import *
> else:
> raise RuntimeError("invalid numerix selector")
>
>
> This is quite different from what you describe, so I think your 
> mpl, and maybe numpy, are not quite up-to-date. Numpy and its mpl 
> support are still evolving rapidly in tandem.
Hmm ... I just did a CVS update this morning. I will try again.
C.
--
Christopher J. Fonnesbeck
Population Ecologist, Marine Mammal Section
Fish & Wildlife Research Institute (FWC)
St. Petersburg, FL
Adjunct Assistant Professor
Warnell School of Forest Resources
University of Georgia
Athens, GA
T: 727.235.5570
E: chris at trichech.us

Chris,
On my machine, with latest svn numpy and cvs mpl, I don't get an import 
error. My numerix/fft/__init__.py looks like this:
from matplotlib.numerix import which
if which[0] == "numarray":
 from numarray.fft import *
elif which[0] == "numeric":
 from FFT import *
elif which[0] == "numpy":
 from numpy.dft import *
else:
 raise RuntimeError("invalid numerix selector")
This is quite different from what you describe, so I think your mpl, and 
maybe numpy, are not quite up-to-date. Numpy and its mpl support are 
still evolving rapidly in tandem.
Eric
Christopher Fonnesbeck wrote:
> Using matplotlib from cvs with numpy still gives an fft import error:
> 
> In [1]: import pylab
> ------------------------------------------------------------------------ 
> ---
> exceptions.ImportError Traceback (most 
> recent call last)
> 
> /Users/chris/<ipython console>
> 
> /Library/Frameworks/Python.framework/Versions/2.4/lib/python2.4/site- 
> packages/matplotlib-0.86.1-py2.4-macosx-10.4-ppc.egg/pylab.py
> ----> 1 from matplotlib.pylab import *
> global matplotlib.pylab = undefined
> 
> /Library/Frameworks/Python.framework/Versions/2.4/lib/python2.4/site- 
> packages/matplotlib-0.86.1-py2.4-macosx-10.4-ppc.egg/matplotlib/pylab.py
> 194 import cm
> 195 import _pylab_helpers
> --> 196 import mlab #so I can override hist, psd, etc...
> mlab = undefined
> 197
> 198 from axes import Axes, PolarAxes
> 
> /Library/Frameworks/Python.framework/Versions/2.4/lib/python2.4/site- 
> packages/matplotlib-0.86.1-py2.4-macosx-10.4-ppc.egg/matplotlib/mlab.py
> 72
> 73 from numerix.mlab import hanning, cov, diff, svd, rand, std
> ---> 74 from numerix.fft import fft, inverse_fft
> numerix.fft = undefined
> fft = None
> inverse_fft = undefined
> 75
> 76 from cbook import iterable
> 
> ImportError: cannot import name inverse_fft
> 
> 
> It turns out that the __init__.py file is not importing inverse_fft 
> (which is now ifft in numpy):
> 
> from matplotlib.numerix import which
> 
> if which[0] == "numarray":
> from numarray.fft import *
> elif which[0] == "numeric":
> from FFT import *
> elif which[0] == "numpy":
> from numpy import fft
> else:
> raise RuntimeError("invalid numerix selector")
> 
> You need to add:
> 
> from numpy import ifft as inverse_fft
> 
> C.
> 
> -- 
> Christopher J. Fonnesbeck
> 
> Population Ecologist, Marine Mammal Section
> Fish & Wildlife Research Institute (FWC)
> St. Petersburg, FL
> 
> Adjunct Assistant Professor
> Warnell School of Forest Resources
> University of Georgia
> Athens, GA
> 
> T: 727.235.5570
> E: chris at trichech.us
> 
> 

Travis et al.,
Jeff Whitaker pointed out to me that masked array support in matplotlib 
contouring does not work with numpy. The problem is that the shape 
function does not work with masked arrays. One easy solution is to 
return to the older Numeric version of shape via the attached patch 
against svn (edited to remove irrelevant chunks).
Thanks.
Eric

Using matplotlib from cvs with numpy still gives an fft import error:
In [1]: import pylab
------------------------------------------------------------------------ 
---
exceptions.ImportError Traceback (most 
recent call last)
/Users/chris/<ipython console>
/Library/Frameworks/Python.framework/Versions/2.4/lib/python2.4/site- 
packages/matplotlib-0.86.1-py2.4-macosx-10.4-ppc.egg/pylab.py
----> 1 from matplotlib.pylab import *
 global matplotlib.pylab = undefined
/Library/Frameworks/Python.framework/Versions/2.4/lib/python2.4/site- 
packages/matplotlib-0.86.1-py2.4-macosx-10.4-ppc.egg/matplotlib/pylab.py
 194 import cm
 195 import _pylab_helpers
--> 196 import mlab #so I can override hist, psd, etc...
 mlab = undefined
 197
 198 from axes import Axes, PolarAxes
/Library/Frameworks/Python.framework/Versions/2.4/lib/python2.4/site- 
packages/matplotlib-0.86.1-py2.4-macosx-10.4-ppc.egg/matplotlib/mlab.py
 72
 73 from numerix.mlab import hanning, cov, diff, svd, rand, std
---> 74 from numerix.fft import fft, inverse_fft
 numerix.fft = undefined
 fft = None
 inverse_fft = undefined
 75
 76 from cbook import iterable
ImportError: cannot import name inverse_fft
It turns out that the __init__.py file is not importing inverse_fft 
(which is now ifft in numpy):
from matplotlib.numerix import which
if which[0] == "numarray":
 from numarray.fft import *
elif which[0] == "numeric":
 from FFT import *
elif which[0] == "numpy":
 from numpy import fft
else:
 raise RuntimeError("invalid numerix selector")
You need to add:
 from numpy import ifft as inverse_fft
C.
--
Christopher J. Fonnesbeck
Population Ecologist, Marine Mammal Section
Fish & Wildlife Research Institute (FWC)
St. Petersburg, FL
Adjunct Assistant Professor
Warnell School of Forest Resources
University of Georgia
Athens, GA
T: 727.235.5570
E: chris at trichech.us

Hi
With MPL 0.86 and 0.86.1 I found that the axes labels aren't centered 
(i.e. the xlabel is on the left side of the x-axis, the ylabel on the 
"bottom" of the y-axis). What's up?
cheers,
steve
-- 
"People like Blood Sausage too. People are Morons!" -- Phil Connors, 
Groundhog Day

Mike,
Thanks for checking the output after the change. I have committed the 
change to CVS. There may be some lag before it shows up on your mirror.
The revisions are:
Checking in lib/matplotlib/contour.py;
/cvsroot/matplotlib/matplotlib/lib/matplotlib/contour.py,v <-- contour.py
new revision: 1.20; previous revision: 1.19
done
Checking in lib/matplotlib/figure.py;
/cvsroot/matplotlib/matplotlib/lib/matplotlib/figure.py,v <-- figure.py
new revision: 1.44; previous revision: 1.43
Eric
>> I've stumbled onto a bug in colorbar() when displaying an image with a 
>> nonlinear normalization (using a recent CVS version of mpl). If one 
>> subclasses matplotlib.colors.normalize and uses a nonlinear function 
>> in the __call__() method, then colorbar() will mismatch colors and 
>> data values in the colorbar.

Michael,
You are right, I left the norm kwarg out of the contour function, and 
colorbar uses contourf. I think I have it fixed now, and I can commit 
to CVS shortly, but I should do a little more checking first. I will 
send you a png file offline, and you can tell me if it is giving the 
result you expect.
Eric
Michael Fitzgerald wrote:
> Hello all,
> 
> I've stumbled onto a bug in colorbar() when displaying an image with a 
> nonlinear normalization (using a recent CVS version of mpl). If one 
> subclasses matplotlib.colors.normalize and uses a nonlinear function in the 
> __call__() method, then colorbar() will mismatch colors and data values in 
> the colorbar.
> 
> Some code illustrating a test case is attached. Here, I use the sqrt() 
> function to normalize some data in the domain (0, 10) to the range (0, 1) 
> [f(x)=sqrt(x/10)]. I display an image which consists of a linear ramp, each 
> value given by the abcissa. The normalization function y=f(x) is overplotted 
> for reference. imshow() applies the normalization before looking up the 
> colormap value, as expected (colors are bunched to the left). However, note 
> the values in the colorbar annotation do not correspond to the data values! 
> For example, pre-normalization data value 4 (x-axis) is correctly colored as 
> yellow, however the color bar erroneously lists that value as cyan (which is 
> the color where y=4/10=.4).
> 
> The error is that colorbar() assumes linearity over the normalization domain. 
> Ultimately, I think I'd like a choice as to whether to stretch colors in the 
> colorbar with a linear sampling of the data domain, or keep the color 
> sequence linear and invert the normalization step to determine the tick 
> values. Has anyone encountered and/or coded a solution for this?
> 
> Thanks,
> Mike
>