A forward model using SVR to estimate stellar parameters from spectra.
Project description
SLAM
Stellar LAbel Machine (SLAM) is a forward model to estimate stellar labels (e.g., Teff, logg and chemical abundances). It is based on Support Vector Regression (SVR) which is a non-parametric regression method.
For details of SLAM, see Zhang et al. (2019).
Author
Bo Zhang (bozhang@nao.cas.cn)
Home page
Install
- for the latest stable version:
pip install astroslam
- for the latest github version:
pip install git+git://github.com/hypergravity/astroslam
Requirements
- numpy
- scipy
- matplotlib
- astropy
- scikit-learn
- joblib
- pandas
- emcee
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
astroslam-1.2019.918.0.tar.gz
(100.8 kB
view hashes)
Built Distribution
Close
Hashes for astroslam-1.2019.918.0-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 21976cf6140f0e79679d81d728a4c66a186feb3e695b43fd52828e4b1bef85f9 |
|
MD5 | ae097468222fdc014d00723cc6eaa3d8 |
|
BLAKE2b-256 | f90cabd6c0cc3f4a65a138f8356a9d11eaad0b66c6fc373609755065b7c1551d |