from KDEpy import FFTKDE
from scipy.stats import norm

# Generate a distribution and some data
dist = norm(loc=0, scale=1)
data = dist.rvs(2**8) # Generate 2**8 points

# Compute density estimates using 'silverman'
x, y = FFTKDE(kernel='gaussian', bw='silverman').fit(data).evaluate()
plt.plot(x, y, label='KDE /w silverman')

plt.plot(x, dist.pdf(x), label='True pdf')
plt.grid(True, ls='--', zorder=-15); plt.legend();