matplotlib-devel Mailing List for matplotlib

For what it is worth, if D were made the default colormap, I would be very
happy.
On 1 July 2015 at 22:35, Thomas Caswell <tca...@gm...> wrote:
> We would like to tag 1.5 around scipy and it would be nice to get the new
> color maps out, even if they are not yet the default.
>
> On Wed, Jul 1, 2015, 11:13 PM Nathaniel Smith <nj...@po...> wrote:
>
>> On Jul 1, 2015 6:31 PM, "Eric Firing" <ef...@ha...> wrote:
>> >
>> > On 2015年07月01日 1:56 PM, Nathaniel Smith wrote:
>> > > On Tue, Jun 16, 2015 at 7:14 PM, Nathaniel Smith <nj...@po...>
>> wrote:
>> > >
>> > > [...snip discussion of how option D was the favorite of 80% of people
>> > > in the survey...]
>> > >
>> > >> So the next question is where we go from here.
>> >
>> > One thing we need to do is get some of these maps into _cm.py via PR.
>>
>> We've been a bit distracted getting the software and talk together ahead
>> of scipy, but PR (with names) will follow within the next week or so. The
>> decision part is pretty orthogonal though I think? It's not like matplotlib
>> 2.0 is going to branch between now and scipy :-).
>>
>> > I would prefer not to have them go in as huge tables if they can be made
>> > more compact, either by being function-generated or by using the
>> > LinearSegmentedColormap mechanism with a moderate number of breakpoints.
>> >
>> > Suggestions?
>>
>> Depends on how you define "moderate", but my guess is that linear
>> segmented is the best approach -- the exact colormaps have a pretty terse
>> representation as bezier control points, but using this at runtime would
>> require pulling in the full colorspace apparatus as a dependency. Which I
>> guess has points in its favor for other reasons, but nonetheless.
>>
>> These kinds of details can be worked out in the PR review process,
>> though. The blocking issue is that we need a decision :-).
>>
>> -n
>>
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Hi Tom,
tried to understand the internals of matplotlib during the weekend. 
Sorry, cound not figure out how matloblib works and where to catch the 
exceptions.
It would be appreciated if someone of the dev group could add the 
special cases handling.
Elmar
On 04.07.2015 15:23, Thomas Caswell wrote:
> Yes, that seems reasonable. @elmar you seem to have a pretty good grasp
> of the code and the use case, would you mind taking a crack at adding
> those special cases?
>
> Tom
>
> On Sat, Jul 4, 2015 at 8:58 AM elmar werling <el...@ne...
> <mailto:el...@ne...>> wrote:
>
> having a look at seaborns ViolinPlotter class
> (https://github.com/mwaskom/seaborn/blob/master/seaborn/categorical.py),
> they explicit handle the special case of "no data" and "single unique
> datapoint" at line 580 ff.
>
> Could something similar be added to matplotlibs violinplot?
>
> On 04.07.2015 12:28, elmar werling wrote:
> > from an end user point of view, matplotlibs violinplot should just do
> > the same as seaborns violinplot.
> >
> >
> > #####################################################################
> > import numpy as np
> > import matplotlib.pyplot as plt
> > import seaborn as sns
> >
> > N = 100
> > y1 = np.random.randn(N) + 3.0
> > y2 = np.random.randn(N) * 5.0 + 50
> > y3 = np.ones(N) * 100 # causing plt.violinplot problem
> > y4 = np.arange(0) # causing plt.violinplot problem
> >
> > #plt.violinplot([y1, y2, y3, y4])
> >
> > sns.violinplot(data=[y1, y2, y3, y4])
> >
> >
> > On 03.07.2015 17:52, Thomas Caswell wrote:
> >> The KDE computation code is a copy of the KDE code from scipy
> >> (https://github.com/scipy/scipy/blob/master/scipy/stats/kde.py), I
> >> suggest raising this issue on their mailing list/github.
> >>
> >> I strongly suspect that violin plot should be doing data
> sanitation on
> >> the way in or catching exceptions like this, but I am not familiar
> >> enough with the math to be sure what it should do instead.
> >>
> >> Tom
> >>
> >> On Fri, Jul 3, 2015 at 11:41 AM elmar werling
> >> <el...@ne...
> <mailto:el...@ne...>
> >> <mailto:el...@ne...
> <mailto:el...@ne...>>> wrote:
> >>
> >>
> >> Hi all,
> >>
> >> violinplot is crashing with singular matrix data. See example.
> >>
> >> Is this behaviour for a singular matrix intended or just a bug?
> >>
> >> Cheers
> >> Elmar
> >>
> >>
> >>
> >> #####################################################
> >> import numpy as np
> >> import matplotlib.pyplot as plt
> >>
> >> # data mimicing the
> >> # original cumsum data (may sum up to 100)
> >> N = 100
> >> y1 = np.random.randn(N) + 3.0
> >> y2 = np.random.randn(N) * 5.0 + 50
> >> y3 = np.ones(N) * 100 # data set causing violinplot problem
> >>
> >> plt.violinplot([y1, y2, y3])
> >>
> >> plt.boxplot([y1, y2, y3]) # ok
> >> plt.ylim(0,110)
> >>
> >> #####################################################
> >>
> >> OS: Debian
> >> Anaconda 2.3.0 (64-bit)
> >> Python 2.7.10
> >> numpy 2.3.0
> >> matplotlib 1.4.3
> >>
> >>
> >>
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There is a long thread on IPython-dev discussing how to make matplotlib 
"just work" in a notebook without requiring "%matplotlib inline" or any 
other such magic at the top. As a side topic in the thread, there are 
comments as to how useful "%pylab" still is for real work.
http://article.gmane.org/gmane.comp.python.ipython.devel/15434
Eric