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From: Rich Shepard <rshepard@ap...>  20060116 22:33:48

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 undergeneration 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.applecosys.com>; Voice: 5036674517 Fax: 5036678863 
From: Christopher Fonnesbeck <chris@tr...>  20060116 19:49:48

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 uptodate. 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 
From: Eric Firing <efiring@ha...>  20060116 19:14:57

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 uptodate. 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/matplotlib0.86.1py2.4macosx10.4ppc.egg/pylab.py > > 1 from matplotlib.pylab import * > global matplotlib.pylab = undefined > > /Library/Frameworks/Python.framework/Versions/2.4/lib/python2.4/site > packages/matplotlib0.86.1py2.4macosx10.4ppc.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/matplotlib0.86.1py2.4macosx10.4ppc.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 > > 
From: Eric Firing <efiring@ha...>  20060116 18:50:21

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 
From: Christopher Fonnesbeck <chris@tr...>  20060116 16:37:33

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/matplotlib0.86.1py2.4macosx10.4ppc.egg/pylab.py > 1 from matplotlib.pylab import * global matplotlib.pylab = undefined /Library/Frameworks/Python.framework/Versions/2.4/lib/python2.4/site packages/matplotlib0.86.1py2.4macosx10.4ppc.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/matplotlib0.86.1py2.4macosx10.4ppc.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 
From: Steve Schmerler <elcorto@gm...>  20060116 16:15:08

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 xaxis, the ylabel on the "bottom" of the yaxis). What's up? cheers, steve  "People like Blood Sausage too. People are Morons!"  Phil Connors, Groundhog Day 
From: Eric Firing <efiring@ha...>  20060116 02:08:47

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. 
From: Eric Firing <efiring@ha...>  20060116 00:43:12

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, prenormalization data value 4 (xaxis) 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 > 