Computational Ridge Identification with SCMS for Python
Project description
CRISPy
Computational Ridge Identification with SCMS for Python
This code is a python implementation of the generalized Subspace Constrained Mean Shift (SCMS) algorithm, translated and modified from the R-code developed by Yen-Chi Chen (University of Washington).
Please cite the following papers when using the code:
- Ozertem, Umut, and Deniz Erdogmus. "Locally Defined Principal Curves and Surfaces." The Journal of Machine Learning Research 12 (2011): 1249-1286.
- Chen, Yen-Chi, Christopher Genovese, Christopher R. Genovese, and Larry Wasserman. "Generalized Mode and Ridge Estimation." (2014): arXiv :1406.1803
- Chen, Yen-Chi, Shirley Ho, Peter E. Freeman, Christopher R. Genovese, and Larry Wasserman. "Cosmic Web Reconstruction through Density Ridges: Method and Algorithm." MNRAS 454 1140 (2015) arXiv: 1501.05303
- Chen, Michael Chun-Yuan, et al. "Velocity-Coherent Filaments in NGC 1333: Evidence for Accretion Flow?" ApJ (2019, submitted)
Project details
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 Distribution
astro-crispy-0.1.0.tar.gz
(4.4 kB
view hashes)
Built Distribution
Close
Hashes for astro_crispy-0.1.0-py2-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 2b805cb912d3e7b118aebc07c291386a458840d86a5fcb6a9c3e7fe1989d509d |
|
MD5 | cbdfd7e56675819c4acaa6676aac80f8 |
|
BLAKE2b-256 | 11504c6be64266307e659de032cc5f454eb6a1a972ee454174606593d83fe7ae |