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# https://stackoverflow.com/questions/35042255/how-to-plot-multiple-seaborn-jointplot-in-subplot | |
import matplotlib.pyplot as plt | |
import matplotlib.gridspec as gridspec | |
import seaborn as sns | |
import numpy as np | |
class SeabornFig2Grid(): | |
def __init__(self, seaborngrid, fig, subplot_spec): | |
self.fig = fig | |
self.sg = seaborngrid | |
self.subplot = subplot_spec | |
if (isinstance(self.sg, sns.axisgrid.FacetGrid) or isinstance(self.sg, sns.axisgrid.PairGrid)): | |
self._movegrid() | |
elif isinstance(self.sg, sns.axisgrid.JointGrid): | |
self._movejointgrid() | |
self._finalize() | |
def _movegrid(self): | |
""" Move PairGrid or Facetgrid """ | |
self._resize() | |
n = self.sg.axes.shape[0] | |
m = self.sg.axes.shape[1] | |
self.subgrid = gridspec.GridSpecFromSubplotSpec( | |
n, m, subplot_spec=self.subplot) | |
for i in range(n): | |
for j in range(m): | |
self._moveaxes(self.sg.axes[i, j], self.subgrid[i, j]) | |
def _movejointgrid(self): | |
""" Move Jointgrid """ | |
h = self.sg.ax_joint.get_position().height | |
h2 = self.sg.ax_marg_x.get_position().height | |
r = int(np.round(h / h2)) | |
self._resize() | |
self.subgrid = (gridspec.GridSpecFromSubplotSpec(r + 1, r + 1, | |
subplot_spec=self.subplot)) | |
self._moveaxes(self.sg.ax_joint, self.subgrid[1:, :-1]) | |
self._moveaxes(self.sg.ax_marg_x, self.subgrid[0, :-1]) | |
self._moveaxes(self.sg.ax_marg_y, self.subgrid[1:, -1]) | |
def _moveaxes(self, ax, gs): | |
# https://stackoverflow.com/a/46906599/4124317 | |
ax.remove() | |
ax.figure = self.fig | |
self.fig.axes.append(ax) | |
self.fig.add_axes(ax) | |
ax._subplotspec = gs | |
ax.set_position(gs.get_position(self.fig)) | |
ax.set_subplotspec(gs) | |
def _finalize(self): | |
plt.close(self.sg.fig) | |
self.fig.canvas.mpl_connect("resize_event", self._resize) | |
self.fig.canvas.draw() | |
def _resize(self, evt=None): | |
self.sg.fig.set_size_inches(self.fig.get_size_inches()) |
WindyCatHub
commented
Nov 27, 2020
via email
@WindyCatHub
It's hard for me to provide feedback without seeing your code. Perhaps the original SO post could help: https://stackoverflow.com/q/35042255/3197404
My gist is quite old. Perhaps the new plotly library has exactly what you need: https://plotly.com/python/2d-histogram-contour/
Hi, thank you for sharing this solution! I am wondering how can we save the figure as a pdf file if using your function. When I tried to do fig.savefig('xxx.pdf'), I will lose the marginal distribution plots in the file. I think it is due to the fact that we removed some axes, making it very tricky. Would appreciate it if you can help to figure it out.
Hi, thank you for sharing this solution! I am wondering how can we save the figure as a pdf file if using your function. When I tried to do fig.savefig('xxx.pdf'), I will lose the marginal distribution plots in the file. I think it is due to the fact that we removed some axes, making it very tricky. Would appreciate it if you can help to figure it out.
@YuHuang3019 a lot has changed in seaborne and I haven't used the pdf export myself.
As an alternative solution you could try Altair which is my current default plotting library:
https://iliatimofeev.github.io/altair-viz.github.io/gallery/scatter_marginal_hist.html
You can export Altair plots in different formats for downstream processing.
Hi, thank you for sharing this solution! I am wondering how can we save the figure as a pdf file if using your function. When I tried to do fig.savefig('xxx.pdf'), I will lose the marginal distribution plots in the file. I think it is due to the fact that we removed some axes, making it very tricky. Would appreciate it if you can help to figure it out.
@YuHuang3019 a lot has changed in seaborne and I haven't used the pdf export myself.
As an alternative solution you could try Altair which is my current default plotting library: https://iliatimofeev.github.io/altair-viz.github.io/gallery/scatter_marginal_hist.html
You can export Altair plots in different formats for downstream processing.
@dkapitan Hi Daniel, thank you so much for sharing this package with me. I just realized that I did plot out the marginal distributions but somehow the color and linewidth for the distributions are too light/small to show. I checked the pdf files on the browser before and I could not see the distribution plots. I later downloaded the file, zoomed in the pdf, and then I was able to figure this out. Sincerely thank you again for your quick response!