Colour the background in seaborn kdeplot (python)

Question

I am using seaborn kernel density estimation to plot probability density contours like so:

import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import make_axes_locatable

x = np.random.normal(0, 3, 100)
y = np.random.normal(0, 1, 100)

fig, ax = plt.subplots()

ax.scatter(x,y, marker='.')

ax.set_aspect('equal')
ax.set(xlim=(-13,13))
ax.set(ylim=(-8,8))


divider = make_axes_locatable(ax)
cax = divider.append_axes("right", size="5%", pad=0.05)

sns.kdeplot(x,y, fill=True, shade_lowest=True, alpha=0.7, linewidths=3, \
            cmap='coolwarm', ax=ax, cbar=True, cbar_ax = cax)

colour = ax.collections[1].get_facecolor()

The result is:

I am producing many of these so to compare them I would like to have the plot limits fixed. As you can see, my issue is that when I change the limits of the plot, seaborn does not fill the background.

The variable colour in the last line of my code contains what I would like to fill the background with. I need help figuring out how to do so. I tried

ax.set_facecolor(colour.reshape(4))

which of course needs work to get to what I want:

This questions is essentially the same as this 6-year old question, which proposed to instead just remove the filling below the last contour. I am convinced there must be a way to get the desired behaviour though. I would really appreciate any help!

As a bonus: the linewidths argument of sns.kdeplot() does nothing. How can I change the linewidth of the contour lines?

Answer 1

As suggested in the comment by @mwaskom, you can use cut parameter .

This can be partially avoided with the cut parameter, which specifies how far the curve should extend beyond the extreme datapoints. But this influences only where the curve is drawn; the density estimate will still smooth over the range where no data can exist, causing it to be artifically low at the extremes of the distribution:

I used trial and error to get the correct value for cut which is 12 . Refer below code for more details.

import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import make_axes_locatable

x = np.random.normal(0, 3, 100)
y = np.random.normal(0, 1, 100)

fig, ax = plt.subplots()

ax.scatter(x,y, marker='.')

ax.set_aspect('equal')
ax.set(xlim=(-13,13))
ax.set(ylim=(-8,8))


divider = make_axes_locatable(ax)
cax = divider.append_axes("right", size="5%", pad=0.05)

sns.kdeplot(x,y, fill=True, thresh=0, alpha=0.7, cmap='coolwarm', ax=ax, cbar=True, cbar_ax = cax, cut=12) # `shade_lowest` is now deprecated in favor of `thresh`
colour = ax.collections[1].get_facecolor()

Output Image: