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, Jean-Charles Cuillandre, and now more (see the GitHub contributors).
Install
pip install autoprof
Please use python version 3.9 or greater.
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!
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Metadata
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Release files for autoprof 1.3.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| autoprof-1.3.4.tar.gz | 42.5 MB | With provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| autoprof-1.3.4-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 42.7 MB
Release files / autoprof-1.3.4.tar.gz
| Download URL | autoprof-1.3.4.tar.gz |
|---|---|
| Size | 42.5 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Transparency logRelease files / autoprof-1.3.4-py3-none-any.whl
| Download URL | autoprof-1.3.4-py3-none-any.whl |
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| Size | 151.4 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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twine/6.0.1 CPython/3.12.8
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Transparency logSecurity for autoprof 1.3.4
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Attestation for autoprof-1.3.4.tar.gz
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Signed by GitHub Actions, verified by PyPI on Dec 16, 2025.
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