Kernel density estimation via diffusion in 1d and 2d.
Project description
Kernel density estimation via diffusion in 1d and 2d.
Provides the fast, adaptive kernel density estimator based on linear diffusion processes for one-dimensional and two-dimensional input data as outlined in the 2010 paper by Botev et al. The reference implementation for 1d and 2d, in Matlab, was provided by the paper's first author, Zdravko Botev. This is a re-implementation in Python, with added test coverage.
For more information, refer to the full documentation at Read-the-Docs.
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distributions
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file KDE_diffusion-1.0.0-py3-none-any.whl.
File metadata
- Download URL: KDE_diffusion-1.0.0-py3-none-any.whl
- Upload date:
- Size: 7.6 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: python-requests/2.23.0
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
019cf685226db3cd551841f2e213bda736e6c85fbb489996e4e928d63221d7fd
|
|
| MD5 |
33460cfb0538774b0fef9161607c20b0
|
|
| BLAKE2b-256 |
e175f173b73754470a634e4125b25cb170d003f6c4a01249a728c961670b6c40
|
