Fast, robust, deep isophotal solutions for galaxy images
Project description
AutoProf is a pipeline for basic and advanced non-parametric galaxy image analysis. Its design allows for fast startup and provides flexibility to explore new ideas and support advanced users. It was written by Connor Stone with contributions from Nikhil Arora, Stephane Courteau, and Jean-Charles Cuillandre.
Install
pip install autoprof
Documentation
See our documentation for a full description of AutoProf's capabilities
Citation
Please see the ADS Bibliographic Record of the AutoProf paper for proper citation.
Notice
This is the AutoProf isophotal code, it works great in its domain which is wherever one would use isophotal fitting. Thus it is suitable for mostly isolated, mostly resolved, objects. If you are limited by the PSF, crowding, or want to model multi-band/epoch data you may want to consider "AstroPhot" a full forward modelling code. Just follow this link to check it out!
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
File details
Details for the file autoprof-1.2.0-py2.py3-none-any.whl.
File metadata
- Download URL: autoprof-1.2.0-py2.py3-none-any.whl
- Upload date:
- Size: 138.5 kB
- Tags: Python 2, Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.8.10
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 208bf11cb44aaf4fd7f187d53cbf909abec5029986f30c335bd6ac1e252d9635 |
|
| MD5 | be6f63c83cc48958cef5b9586062f61b |
|
| BLAKE2b-256 | 1edd96f2800f2add009d3079bd236f74acba5bfe89e4d91c42ca4a6f9324d5a9 |
