lightkde

A lightning fast, lightweight, and reliable kernel density estimation.

• Easy to use, e.g. density_vec, x_vec = kde_1d(sample_vec=sample).
• Works with 1d and 2d samples.
• Works with weighted samples as well.
• Based on the MATLAB implementations of Botev: kde, kde2d.

Install

pip install lightkde

Usage

import numpy as np
from lightkde import kde_1d

sample = np.random.randn(1000)

density_vec, x_vec = kde_1d(sample_vec=sample)

For further examples see the documentation.

Other kde packages

Other python packages for kernel density estimation:

• scipy.stats.gaussian_kde
• KDEpy