Open lukelbd opened 4 years ago
It's a very nice feature! I can hardly wait!
I made some custom KDE graphs for a publication recently:
These type of graphs are called 'raincloudplots': https://wellcomeopenresearch.org/articles/4-63 (which has a python implementation but is based on seaborn and therefore has the same problems) The code for the KDE part of the graph is here: https://github.com/Jhsmit/PyHDX-paper/blob/master/biorxiv_v2/functions/rainbows.py
Feel free to use the code in proplot
if you find it useful (although some parts are from joyplot). I'm using scipy's kde function which mostly works fine but especially for the 2D case it can be slow if you have a lot of datapoints.
I might want to try to find time to make a PR myself, I'm a big fan of proplot. I've started using it for my last publication and the subplot layout and sizing options in proplot really made my life a lot easier :) (paper / code)
I'll try to provide some feedback to proplot if that helps you. PS. perhaps you could consider connecting your repository to zenodo such that the project can be cited.
Thanks for the code! This is a good base for adding KDE functionality -- I probably won't have time to work on this until later this year but happy to accept PRs if you feel inclined/want it sooner. Proplot's source code recently underwent some major improvements so it should be much easier to contribute.
We probably want to add the following:
axes/plot.py
that controls KDE estimation for various plotting functions. Users should be able to pass keyword arguments to the KDE algorithm from the plotting functions.violinplot
option to plot a left- or right-half violin (like in your example), maybe with the argument side='left'
and side='right'
(or side='top'
or side='bottom'
for horizontal violins), with side='both'
being the default.violinplot
to use your method for KDE estimation rather than matplotlib's method. It would probably simply call fill_between
or fill_betweenx
and then you can add outlines to the violins like you would any other patch. It would still be able to add error bars/boxes using the shared PlotAxes._apply_bar
method.raincloudplot
method (with the shorthand raincloud
, consistent with other plotting commands) as a thin wrapper that calls boxplot
, violinplot
, and scatter
. It would call boxplot
and violinplot
with reduced default widths
arguments and default side='left'
or side='top'
for the violins.violinplot
have no colormap gradations by default, but let users add them by passing cmap='name'
to violinplot
or raincloudplot
(it should also accept vmin
and vmax
arguments, but set the default vmin
and vmax
to the minimum and maximum of all the distributions). To implement colormap gradations, violinplot
will set the facecolor of the patch to 'none'
(i.e., completely transparent) so that an imshow
can be drawn underneath the patch border and "clipped" by the border coordinates, as you've done in your code.kdeplot
and kdeplot2d
commands (with shorthands kde
and kde2d
, consistent with other functions) that show KDE estimations using lines and contours (respectively). They should be thin wrappers around plot
and contour
/contourf
, similar to how hist
and hist2d
are thin wrappers around bar
and pcolor
.kde=True
to hist
and hist2d
and this will draw the kde
and kde2d
lines on top of the histograms, analogous to the current ability of passing linewidth=N
to contourf
and proplot adds an additional contour
plot on top of the filled contours. KDE-algorithm or KDE-styling keywords could be passed to hist
and hist2d
with kde_kw={key: value, ...}
, analogous to various other arguments ending in _kw
.And glad you find proplot useful :) it's already published on Zenodo but that probably wasn't clear -- there was just a Zenodo badge to the github home page. I've now added a link to the readthedocs homepage.
I'd like to add KDE (kernel density estimation) functionality for the 1D and 2D histogram plotting functions,
hist
,hist2d
, and maybehexbin
. Users can then optionally add marginal distribution panels withpanel_axes
.Currently, the only matplotlib plotting function supporting KDE estimation is
violinplot
, but the result is often gross -- the "violins" do not smoothly taper to zero-width tails like in seaborn. Instead they abruptly cut off at the distribution minimum/maximum. So, we shouldn't try to use the existing KDE engine -- we should implement a new KDE estimation engine, similar to seaborn, and use it to powerhist
,hist2d
, andviolinplot
. This may involve writing a newviolinplot
from scratch.