Lightning fast, lightweight, and reliable kernel density estimation.
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.
pip install lightkde
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:
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.