[Matplotlib-devel] Use of contourf changed?

[Ian Thomas]

This is indeed a bug.  Both the legacy code and the new code produce
incorrect output, but differently incorrect.

I have opened an issue on github for this:
https://github.com/matplotlib/matplotlib/issues/5477

Viktoria,
Thanks for reporting this.  It is a bug that has been around for a long
time and needs to be dealt with.  If you don't want to read through all of
the github issue, which may get a bit technical, the key thing from your
point of view is that even though the v1.4 code gave you what you wanted to
see, it wasn't actually the correct output given what your code asked for.
When we fix the underlying bug, if you keep using the same code you will
get the correct output which will be no good to you!  Instead of using

    levels = [L1, L2, L3, Lmin]
    plt.contourf(hist2D, levels=levels, colors=['b', 'b', 'b'])

you should instead use something like

    levels = [L1, L2, L3, Lmin]
    for level in levels:
        plt.contourf(hist2D, levels=[level, np.inf], colors='b']

This will give you the results that you want now, as well as when we fix
the bug.

Ian


On 12 November 2015 at 17:34, Viktoria Schubert via Matplotlib-devel <
matplotlib-devel at python.org> wrote:

> Hello,
>
> Yeah, this helps indeed with "corner_mask='legacy' the result is
> identical, even though I get a warning:
> /usr/lib/python3.5/site-packages/matplotlib/cbook.py:136:
> MatplotlibDeprecationWarning: The corner_mask='legacy' attribute was
> deprecated in version 1.5. Use corner_mask=False or True instead.
>   warnings.warn(message, mplDeprecation, stacklevel=1)
>
> I tried creating a minimal example which recreates the problem with
> simpler data. The result does not exactly represent 100% of the
> problem, but it is screwed anyway. Again, with the option
> corner_mask='legacy' option, it looks just fine.
> You can find my example here:
> https://paste.kde.org/poyn7upbi
>
> Thank you very much!
> Viktoria
>
>
>
> 2015-11-12 17:09 GMT+01:00 Benjamin Root <ben.v.root at gmail.com>:
> > Interesting, but it is hard to tell what is going on without any code or
> > data. In particular, matplotlib's contourf polygons has always been
> > "unstacked". In other words, the polygons representing a contour level
> does
> > not overlap with any other polygon of another contour level, so I am not
> > exactly sure how you are getting the behavior you are seeing in either
> > image.
> >
> > Now, the default algorithm for contouring did change in v1.5. You can
> access
> > the old algorithm by passing `corner_mask='legacy'` as a keyword
> argument to
> > contourf() in v1.5. Could you try that and see if at least you get
> identical
> > results for v1.5 and v1.4?  Note, that keyword argument is not available
> in
> > v1.4. This should help us narrow down the source of your issue, but I
> > wouldn't treat it as a solution because the old algorithm is slated for
> > removal at some point, and it still doesn't explain the difference you
> are
> > seeing with the new contouring algorithm.
> >
> > Ben
> >
> >
> > On Thu, Nov 12, 2015 at 8:11 AM, Viktoria Schubert via Matplotlib-devel
> > <matplotlib-devel at python.org> wrote:
> >>
> >> Hello together,
> >>
> >> Since the 1.5 version of matplotlib together with python 3.5, I get
> >> strange results from using the contourf function. What I'm actually
> >> doing is plotting a lot of points in a 2D-space. The density equals the
> >> likelihood of the data, so what I want is to plot the 1Sigma, 2Sigma and
> >> 3Sigma areas of the data.
> >> For this purpose, I was using the following line of code:
> >> cs = plt.contourf(hist2D, extent=extent, levels=[L1,L2,L3,Lmin],
> >> linestyles=['-','-','-','-'], colors=['blue','blue','blue'], alpha=0.25)
> >>
> >> The problem now is, that with matplotlib 1.4, the resulting image shows
> >> the most dense area in white instead of darker blue, which was the
> >> previous behavior. I did not change my code, I can get the old result
> >> simply by moving back to 1.4.
> >> I link to the two pictures I created, so maybe one of you can explain
> >> me, what changed with the version so that the plot is getting messed up.
> >> V1.4:
> >> http://i.imgur.com/HH7jKBE.png
> >> V1.5:
> >> http://i.imgur.com/0LZ9Tso.png
> >>
> >> Thank you very much,
> >> Viktoria
> >> _______________________________________________
> >> Matplotlib-devel mailing list
> >> Matplotlib-devel at python.org
> >> https://mail.python.org/mailman/listinfo/matplotlib-devel
> >
> >
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