MulensModel is package for modeling microlensing (or μ-lensing) events.

Detailed documentation: https://rpoleski.github.io/MulensModel/

Latest release: 1.17.2 and we're working on further developing the code.

MulensModel can generate a microlensing light curve for a given set of microlensing parameters, fit that light curve to some data, and return a chi2 value. That chi2 can then be input into an arbitrary likelihood function to find the best-fit parameters.

If you want to learn more about microlensing, please visit Microlensing Source website.

Currently, MulensModel supports:

• Lens Systems: point lens or binary lens.
• Source Stars: single source or binary source.
• Effects: finite source (1-parameter), parallax (satellite & annual), binary lens orbital motion, different parametrizations of microlensing models.

Need more? Open an issue or send us an e-mail.

Are you using MulensModel for scientific research? Please give us credit by citing the paper published in "Astronomy and Computing" and ASCL reference. For arXiv see link.

We have more than a dozen of examples - starting from very simple ones (like plotting a model) to very advanced (like fitting a binary lens model with finite source effect). Please see:

• a list of examples and tutorials,
• description of all microlensing parameters used in MulensModel,
• methods used to calculate magnification in MulensModel, and
• high-level fitting example.

The full documentation of API is at https://rpoleski.github.io/MulensModel/.

Download the source code and run:

python setup.py install

MulensModel requires some standard packages plus astropy package. To make sure that you have everything that's needed, just run:

pip install -r requirements.txt

Alternatively, you can run makefiles: go to source/VBBL/ and run make, then go to source/AdaptiveContouring/ and do the same. Then and add the path MulensModel/source to your PYTHONPATH. If you have any problems, please contact the authors and we will try to help.

file revised Oct 2020