Model fitting package for the chemical analysis of astronomical spectra
Project description
A Python library for the analysis of astronomical spectra. SpecSy includes a Bayesian sampler for the direct method parameter space, tools to fit photoionization model grids, and utilities for the analysis of stellar and gas continua.
Warning: This package is currently in an alpha release.
Installation
Install directly from PyPI with all the dependencies
(depending on the OS the "specsy[full]" must be quoted):
pip install specsy[full]
To upgrade to the latest version:
pip install --upgrade specsy
Citing
Previous work involving the results and development of SpecSy can be found in Fernández et al. (2019), Fernández et al. (2021), Fernández et al. (2023), and del Valle-Espinosa et al. (2025).
Development
SpecSy is currently in an alpha release. Please check the GitHub repository for the latest version or to report any issues.
Author: Vital Fernández — vgf@stsci.edu
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
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 specsy-0.10.0.tar.gz.
File metadata
- Download URL: specsy-0.10.0.tar.gz
- Upload date:
- Size: 14.7 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.13.14
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
1757f01f31669a14b397c5c245c4513c9b9d7c1d3303df2123f62c7616b5bf68
|
|
| MD5 |
e95a25e505e4798c1ba971c899ad1795
|
|
| BLAKE2b-256 |
4afe61c2e1a742ae87abcd71f54eef501f7147a1392399cd3a7983ca4ae4d776
|
File details
Details for the file specsy-0.10.0-py3-none-any.whl.
File metadata
- Download URL: specsy-0.10.0-py3-none-any.whl
- Upload date:
- Size: 14.7 MB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.13.14
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
c359e590ff784b2b37bf1643e7f9197fa23966704f36203e12b21ac42c4da779
|
|
| MD5 |
ce925e5e1aabe7be5337e0a4d99cfde4
|
|
| BLAKE2b-256 |
6994552462cf8e7bb5b79f69212ff9476d5ec044d7e4a1c60a18a6914a373afe
|
