How to get a smoothed contour line in matplotlib given non-smooth underlying data

Question

I have boolean data on a 2D grid and want to use matplotlib to plot a countour between the areas where the data is True and False.

However, the separation between these areas is not smooth within the actual data. How can I compute a smoothed countour given this data?

Here is a minimal example:

import numpy as np
import matplotlib.pyplot as plt

# generate some non-smooth example data
MESHSIZE = 10
REFINEMENT = 4*MESHSIZE
x = np.linspace(-MESHSIZE, MESHSIZE, REFINEMENT)
xv, yv = np.meshgrid(x, x)
xvf = xv.reshape(-1)
yvf = yv.reshape(-1)


def choppy_circle(x, y):
    inner = x.astype(int)**2+y.astype(int)**2 < 10.0
    return inner


# consider this the *actual* data given to me as-is
my_x = xvf
my_y = yvf
my_z = choppy_circle(xvf, yvf)

# need to visualize the contour that separates areas where
# my_z is True/False
plt.tricontour(my_x, my_y, my_z, levels=np.array([1.0-1e-3]))
plt.scatter(xv, yv, s=0.1)
plt.show()

This produces the following plot, which is faithful to the data, but not what I'm looking for:

How can I use the data given in my_x, my_y and my_z to construct a smoothed contour around the domain where my_z is True?

Something like this:

Answer 1

Extracting the contour data like proposed in this answer and interpolating with splines as proposed by @user2640045 allows doing it for arbitrary contours:

# my_x, my_y, my_z as above...

# get contour data
cs = plt.tricontour(my_x, my_y, my_z, levels=np.array([1.0-1e-3]))
print(type(cs))

# process each contour
for contour in cs.collections[0].get_paths():
    vert = contour.vertices
    vert_x = vert[:, 0]
    vert_y = vert[:, 1]

    # plot contour
    plt.plot(vert_x, vert_y)

    # interpolate contour points
    s = 20
    tck, u = interpolate.splprep([vert_x, vert_y], per=1, s=s)
    x_interp, y_interp = interpolate.splev(np.linspace(0, 1, 10**3), tck)

    # plot interpolated contour
    plt.plot(x_interp, y_interp)

# plot grid
plt.scatter(xv, yv, s=0.1)

# display plot
plt.show()

The important bit is the loop header

for contour in cs.collections[0].get_paths():

where the x-y data of each contour line is obtained.