searborn adaptation need for Matptotlib-2.2.0rc1 · Issue #10585 · matplotlib/matplotlib · GitHub

Bug report

Bug summary

My historic Seaborn example doesn't seem to work anymore with Matplotlib-2.2.0rc1. is it a volontary change ?

# Seaborn
# for more examples, see http://stanford.edu/~mwaskom/software/seaborn/examples/index.html
import seaborn as sns
sns.set()
df = sns.load_dataset("iris")
sns.pairplot(df, hue="species", size=1.5)

Actual outcome

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-9-78e2f3db95aa> in <module>()
      4 sns.set()
      5 df = sns.load_dataset("iris")
----> 6 sns.pairplot(df, hue="species", size=1.5)

C:\WinPython\bd35\buildQt5\winpython-32bit-3.5.x.2\python-3.5.4\lib\site-packages\seaborn\axisgrid.py in pairplot(data, hue, hue_order, palette, vars, x_vars, y_vars, kind, diag_kind, markers, size, aspect, dropna, plot_kws, diag_kws, grid_kws)
   2058     if grid.square_grid:
   2059         if diag_kind == "hist":
-> 2060             grid.map_diag(plt.hist, **diag_kws)
   2061         elif diag_kind == "kde":
   2062             diag_kws["legend"] = False

C:\WinPython\bd35\buildQt5\winpython-32bit-3.5.x.2\python-3.5.4\lib\site-packages\seaborn\axisgrid.py in map_diag(self, func, **kwargs)
   1333                     diag_ax = ax._make_twin_axes(sharex=ax,
   1334                                                  sharey=diag_axes[0],
-> 1335                                                  frameon=False)
   1336                 else:
   1337                     diag_ax = ax._make_twin_axes(sharex=ax, frameon=False)

C:\WinPython\bd35\buildQt5\winpython-32bit-3.5.x.2\python-3.5.4\lib\site-packages\matplotlib\axes\_subplots.py in _make_twin_axes(self, *kl, **kwargs)
    174         from matplotlib.projections import process_projection_requirements
    175         if 'sharex' in kwargs and 'sharey' in kwargs:
--> 176             raise ValueError("Twinned Axes may share only one axis.")
    177         kl = (self.get_subplotspec(),) + kl
    178         projection_class, kwargs, key = process_projection_requirements(

ValueError: Twinned Axes may share only one axis.

Matplotlib version

Operating system: windows10
Matplotlib version: 2.2.0rc1 of feb 18th cgohlke
Matplotlib backend (print(matplotlib.get_backend())):module://ipykernel.pylab.backend_inline
Python version: 3.5.4
Jupyter version (if applicable): Jupyterlab-0.31.8
Other libraries:

so it comes from this change:
#10033

how should we rewrite an old code like :

ax._make_twin_axes(sharex=ax,
 sharey=diag_axes[0],
 frameon=False)

is it ?:

ax._make_twin_axes(# don't ax me twice sharex=ax,
 sharey=diag_axes[0],
 frameon=False)

attn @efiring

I think was was intentional to account for interactions between twin, shared axes, and fixed aspect ratio.

ok, I patched seaborn for my need. seaborn maintainer ask if this internal breakage could be avoided:
mwaskom/seaborn#1378 (comment)

Can you distill to a non-seaborn example? I’m still not sure what seaborn is trying to do that breaks, but I haven’t read the source.

Similar examples would come from holoviews (replace 'bokeh' per 'matplotlib'):

http://holoviews.org/gallery/demos/bokeh/iris_splom_example.html#bokeh-gallery-iris-splom-example

more similar would be with hv.Histogram, yet more verbose than compact seaborn

from bokeh.sampledata.iris import flowers
from holoviews.operation import gridmatrix
ds = hv.Dataset(flowers)
grouped_by_species = ds.groupby('species', container_type=hv.NdOverlay)
grid = gridmatrix(grouped_by_species, diagonal_type=hv.Histogram)

I meant can you trigger the error using matplotlib only?

hum, it's not an internal error of Matplotlib-2.2.0rc1, if that is your question.

So I'm confused; is this a matplotlib problem (i.e. something that worked pre #10033)? If so, then it must be triggerable with just matplotlib calls.

seaborn was using an "internal API", functions starting per the undescore characters:

there has been a change there,
and seaborn is no longer actively maintained.

The change in _make_twin_axes was deliberate. Under what circumstances does it make sense to share both axes with twin axes? The point of twin axes is to share one axis and have the other one differ.

ok. I agree it was probably a functional bug of seaborn.

@efiring

The change in _make_twin_axes was deliberate. Under what circumstances does it make sense to share both axes with twin axes? The point of twin axes is to share one axis and have the other one differ.

seaborn shouldn't have been using a private method here, but if the issue is just redundancy, is there any reason matplotlib needs to raise on getting sharex and sharey when one of the shared axes is self?

Speaking as a matplotlib dev with no attachment to the APIs in question, I'm sensitive to the idea that we not break one of the more prominent downstream libraries. So I'm ok with getting in a change to avoid this breakage before we cut 2.2.

I'm also pretty damned irritated that we have to work around this prominent library using an internal API; especially since it seems that this downstream library has made no effort whatsoever in getting a public version of this API. (Please correct me if I'm wrong on this.) So I'm also tempted to say that unless a seaborn dev is willing to put some skin in the game and propose a PR to get a public API that serves their purpose, we don't do a thing. THIS is literally the reason that as a developer of another project, YOU DON'T USE SOMEONE ELSE'S INTERNAL APIS.

OK, fair enough - tracing through all the twin code is difficult. I did reopen and remilestone so this will at least get discussion before 2.2 drops.

I'm still not clear why you want twin axes versus just clearing the diagonal axes and resetting the share properties. But no doubt I'm not following exactly what PairGrid etc are doing.
Again, the changes implimented in Improve handling of shared axes with specified aspect ratio #10033 fix a lot of other critical bugs. So, if you can figure out how to fix seaborn w/o breaking Improve handling of shared axes with specified aspect ratio #10033, I think that PR would be great.

EDIT: Ooops, crossing comments....

Thanks @dopplershift for the constructive contributions.

My proposal is literally to change

if 'sharex' in kwargs and 'sharey' in kwargs:
    raise ValueError("Twinned Axes may share only one axis.")

to

if 'sharex' in kwargs and 'sharey' in kwargs:
    if kwargs["sharex"] is not self and kwargs["sharey"] is not self:
        raise ValueError("Twinned Axes may share only one axis.")

We can also have a conversation about a public API for twinned, shared axes (which I've proposed above), but that shouldn't be a blocker for 2.2. And, as noted, fixing this error check would be a precondition for making that possible.

make seaborn great again on Matplotlib-2.2

@mwaskom is it not possible write (or just copy the old code in _make_twin_axes) a method to do what you want to do instead of relying on our private one, and then putting out a patch release of seaborn with that fix?

No.

Why not?

That doesn't solve the problem of all the existing installs being broken.

Note that @lkjell took a crack at adding share/unshare in #9923. I think that is what would be useful for the seaborn use case...

Closed #10622

make seaborn great again on Matplotlib-2.2

searborn adaptation need for Matptotlib-2.2.0rc1 · Issue #10585 · matplotlib/matplotlib · GitHub

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searborn adaptation need for Matptotlib-2.2.0rc1 #10585

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searborn adaptation need for Matptotlib-2.2.0rc1 · Issue #10585 · matplotlib/matplotlib · GitHub

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searborn adaptation need for Matptotlib-2.2.0rc1 #10585

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stonebig commented on Feb 24, 2018

tacaswell commented on Feb 24, 2018

stonebig commented on Feb 24, 2018

jklymak commented on Feb 24, 2018

stonebig commented on Feb 24, 2018

stonebig commented on Feb 24, 2018

jklymak commented on Feb 24, 2018

stonebig commented on Feb 24, 2018

jklymak commented on Feb 24, 2018

stonebig commented on Feb 25, 2018

efiring commented on Feb 25, 2018

stonebig commented on Feb 25, 2018

mwaskom commented on Feb 27, 2018

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dopplershift commented on Feb 27, 2018

jklymak commented on Feb 27, 2018

mwaskom commented on Feb 27, 2018

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mwaskom commented on Feb 27, 2018

dstansby commented on Feb 27, 2018

mwaskom commented on Feb 27, 2018

dstansby commented on Feb 27, 2018

dopplershift commented on Feb 28, 2018

jklymak commented on Feb 28, 2018

jklymak commented on Feb 28, 2018

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