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 w
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 wrote:
> having a look at seaborns ViolinPlotter class
> (https://github.com/mwask
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 12:2
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.ran
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
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
