On Fri, Oct 29, 2010 at 7:44 AM, Nikolaus Rath <nikol...@rath.org> wrote:
> Benjamin Root <ben.root-grryuj3d...@public.gmane.org> writes:
> > On Thu, Oct 28, 2010 at 3:31 PM, Nikolaus Rath <
> nikolaus-bth8mxji...@public.gmane.org> wrote:
> >
> >> Hello,
> >>
> >> I'm having a weird problem with a contour plot. Consider the following
> >> plots:
> >>
> >> import cPickle as pickle
> >> import matplotlib.pyplot as plt
> >> (Theta, Phi, Bnormal) = pickle.load(open('trouble.pickle', 'rb'))
> >> plt.figure(0)
> >> for i in [0, 300]:
> >> plt.plot(Theta, Bnormal[:, i], label='Bnormal at Phi=%.3g' % Phi[i])
> >>
> >> plt.ylabel('Theta')
> >> plt.legend()
> >> plt.savefig('figure0.png')
> >> plt.figure(1)
> >> plt.contourf(Phi, Theta, Bnormal)
> >> plt.xlabel('Phi')
> >> plt.ylabel('Theta')
> >> plt.colorbar()
> >> plt.savefig('figure1.png')
> >>
> >> The 'trouble.pickle' file is available on
> >> http://www.rath.org/trouble.pickle. At Phi=0 the contour plot agrees
> >> with the crossection (both show an n=7 oscillation), but at Phi=1.68 the
> >> contour plot shows a uniform value while the crossection shows a phase
> >> shifted version of oscillation at Phi=0.
> >>
> >> It seems to me that this is a blatant contradiction.
> >>
> >>
> >> I have also uploaded the two figures at http://www.rath.org/figure1.png
> >> and http://www.rath.org/figure0.png.
> >>
> >>
> >> Am I missing something, or is this a bug?
> >>
> >> $ python --version
> >> Python 2.6.5
> >> $ python -c 'import matplotlib; print matplotlib.__version__'
> >> 1.0.0
> >>
> >>
> >> Thanks,
> >>
> >> -Nikolaus
> >>
> >>
> > Nikolaus,
> >
> > What might be happening is that the Theta variable isn't monotonic. It
> > first goes from zero to pi, then from -pi to 0. This also explains the
> odd
> > lines that appear in the line plots at the top and bottom. Try reforming
> > your arrays so that the domain is monotonic (note that you will have to
> > adjust the Phi and the Bnormal arrays as well because they were arranged
> > assuming a certain domain from Theta.
>
> Indeed, this was the problem. Thank you very much!
>
>
> However, it seems to me that this is quite a serious bug. The contour
> documentation on
>
> http://matplotlib.sourceforge.net/api/axes_api.html#matplotlib.axes.Axes.contour
> does not mention this requirement, and obviously the contour method
> itself does not even bother to check if its arguments are monotonically
> increasing. Instead, it just *silently* produces garbage that in some
> cases even looks like plausible data(!).
>
> Am I missing something here? Otherwise I'll report this on the bug
> tracker. I think this should be documented and contour() should check
> its input and raise a ValueError if it's not monotonic.
>
>
>
> Best,
>
> -Nikolaus
>
>
Nikolaus,
You are right, the documentation is seriously lacking and woefully
out-of-date. It still claims that it can not handle internal regions
correctly with masked arrays (I am pretty sure that is fixed) and it says
nothing of any characteristics of X and Y. I also don't like how contourf()
things are in the doc string for contour() and things that are for contour()
are in contourf(). I wonder if we can do a much better job arranging this
documentation.
I don't know if there are any strict requirement on monotonicity for X and
Y, or if there are any cases where the plot is still valid even if that
property is violated. If it is a requirement, then I agree that there
should be a check.
Ben Root
P.S. - I find that in many cases, contourf() is the wrong function to use
for such plots, and find pcolor() (or one of its variants) to be better
suited. Don't know what is better for you in your case, but it might be
something to investigate.
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