Metadata-Version: 2.0
Name: mosfit
Version: 1.0.2
Summary: Modular software for fitting semi-analytical model predictions to observed astronomical transient data.
Home-page: https://github.com/guillochon/mosfit
Author: & 
Author-email: guillochon@gmail.com
License: MIT
Download-URL: https://github.com/guillochon/mosfit/tarball/1.0.2
Description-Content-Type: UNKNOWN
Keywords: astronomy,fitting,monte carlo,modeling
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Astronomy
Classifier: Topic :: Scientific/Engineering :: Physics
Requires-Dist: astrocats (>=0.3.28)
Requires-Dist: astropy (>=1.3)
Requires-Dist: Cython (>=0.24.1)
Requires-Dist: emcee (>=2.2.1)
Requires-Dist: extinction (>=0.2.2)
Requires-Dist: inflect (>=0.2.5)
Requires-Dist: matplotlib (>=1.5.3)
Requires-Dist: mpi4py (>=2.0.0)
Requires-Dist: nbstripout (>=0.2.9)
Requires-Dist: numexpr (>=2.6.1)
Requires-Dist: numpy (>=1.11.1)
Requires-Dist: palettable (>=2.1.1)
Requires-Dist: schwimmbad (>=0.2.1)
Requires-Dist: scipy (!=0.19.0,>=0.18)
Requires-Dist: seaborn (>=0.7.1)
Requires-Dist: six

<p align="center"><img src="logo.png" align="left" alt="MOSFiT" width="300"/></p>
<a href="https://travis-ci.org/guillochon/MOSFiT"><img src="https://img.shields.io/travis/guillochon/MOSFiT.svg?branch=master" alt="Build Status"></a>
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<a href="https://www.python.org"><img src="https://img.shields.io/badge/python-2.7%2C%203.4%2C%203.5%2C%203.6-blue.svg" alt="Python Version"></a>
<a href="https://badge.fury.io/py/mosfit"><img src="https://badge.fury.io/py/mosfit.svg" alt="PyPI version"></a>
<a href="http://mosfit.readthedocs.io/en/latest/?badge=latest"><img src="https://readthedocs.org/projects/mosfit/badge/?version=latest" alt="Documentation Status"></a>
<a href="http://ascl.net/1710.006"><img src="https://img.shields.io/badge/ascl-1710.006-blue.svg?colorB=262255" alt="ascl:1710.006" /></a>
<a href="https://slack.astrocats.space"><img src="https://slack.astrocats.space/badge.svg" alt="Currently logged-in users in MOSFiT Slack channel" /></a>

`MOSFiT` (**M**odular **O**pen-**S**ource **Fi**tter for **T**ransients) is a Python 2.7/3.x package for fitting, sharing, and estimating the parameters of transients via user-contributed transient models. Data for a transient can either be provided by the user in a wide range of formats (JSON, ASCII tables, CDS, LaTeX), or can be pulled automatically from one of the Open Catalogs (e.g. the [Open Supernova Catalog](https://sne.space), [Open TDE Catalog](https://tde.space), and [Open Nova Catalog](https://opennova.space)) by its name. With the use of an optional upload flag, fits performed by users can then be uploaded back to the Open Catalogs for the benefit of the transient community.<br clear="all">

## Installation

`MOSFiT` is available on `conda` and `pip`, and can be installed using:

```bash
conda install -c conda-forge mosfit
```

or:

```bash
pip install mosfit
```

For a development install of `MOSFiT`, the repository should be cloned from GitHub and then installed into your Python environment via the `setup.py` script:

```bash
git clone https://github.com/guillochon/MOSFiT.git
cd MOSFiT
python setup.py develop
```

## Using MOSFiT

For detailed instructions on using MOSFiT, please see our documentation on RTD: <http://mosfit.readthedocs.io/>


