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Microlsening analysis package.

Project description

Build Status DOI

pyLIMA

Authors : Etienne Bachelet (etibachelet@gmail.com), Rachel Street (rstreet@lcogt.net), Valerio Bozza (valboz@sa.infn.it), Yiannis Tsapras (ytsapras@ari.uni-heidelberg.de) and friends!

pyLIMA is the first open source software for modeling microlensing events. It should be flexible enough to handle your data and fit it. You can also practice by simulating events.

Documentation and Installation

Documentation

Required materials

You need pip and python, that's it!

Installation and use

>>> pip install pyLIMA

You should be able to load pyLIMA as general module :

import pyLIMA
print(pyLIMA.__version__)

Examples

Examples can be found in the pyLIMA directory after cloning this repository. More details can be found in the Documentation There is two version for each examples, one using Jupyter notebook or classic Python file.

Example_1 : HOW TO FIT MY DATA?

Example_2 : HOW TO USE YOUR PREFERED PARAMETERS?

Example_3 : HOW TO SIMULATE EVENST?

Example_4 : HOW TO USE YOUR OWN FITTING ROUTINES?

Example_5 : HOW TO FIT PARALLAX?

How to contribute?

Want to contribute? Bug detections? Comments? Please email us (etibachelet@gmail.com) or raise an issue (recommended).

Project details


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Source Distribution

pyLIMA-1.9.tar.gz (3.7 MB view hashes)

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