https://github.com/lsst-dm/legacy-multiprofit
Multi-object/band source modelling/galaxy fitting code
https://github.com/lsst-dm/legacy-multiprofit
Last synced: 18 days ago
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Multi-object/band source modelling/galaxy fitting code
- Host: GitHub
- URL: https://github.com/lsst-dm/legacy-multiprofit
- Owner: lsst-dm
- License: gpl-3.0
- Created: 2018-10-10T15:18:06.000Z (over 6 years ago)
- Default Branch: main
- Last Pushed: 2024-11-06T22:37:49.000Z (7 months ago)
- Last Synced: 2024-11-06T23:27:49.719Z (7 months ago)
- Language: Python
- Size: 32.5 MB
- Stars: 10
- Watchers: 9
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.rst
- License: LICENSE
Awesome Lists containing this project
README
This is the original repository for multiprofit and is now superseded by
`multiprofit `_ in the lsst organization.
MultiProFit
###########
.. todo image:: https://travis-ci.org/ICRAR/multiprofit.svg?branch=master
.. todo :target: https://travis-ci.org/lsst-dm/multiprofit
.. todo image:: https://img.shields.io/pypi/v/multiprofit.svg
.. todo :target: https://pypi.python.org/pypi/multiprofit
.. todo image:: https://img.shields.io/pypi/pyversions/multiprofit.svg
.. todo :target: https://pypi.python.org/pypi/multiprofit
*multiprofit* is a Python astronomical source modelling code, inspired by `ProFit `_, but made for LSST Data Management. MultiProFit means Multiple Profile Fitting. The
multi- aspect can be multi-object, multi-component, multi-band, multi-instrument, and someday multi-epoch.
*multiprofit* can fit any kind of imaging data while modelling sources as Gaussian mixtures - including
approximations to Sersic profiles - using a Gaussian pixel-convolved point spread function. It can also use
`GalSim `_ or `libprofit `_
via `pyprofit `_ to generate true Sersic and/or other supported
models convolved with arbitrary PSFs images or models.
*multiprofit* has support for multi-object fitting and experimental support for multi-band fitting, albeit
currently limited to pixel-matched images of identical dimensions. Unlike ProFit, Bayesian MCMC is not
available (yet).
*multiprofit* requires Python 3, along with `pybind11 `_ for C++ bindings,
and `gauss2d `_ for evaluating Gaussian mixtures. It can be installed
using setup.py like so:
python3 setup.py install --user
.. todo *multiprofit* is available in `PyPI `_
.. and thus can be easily installed via::
.. pip install multiprofit