pyLIMA (python Lightcurve Identification and Microlensing Analysis) fits microlensing lightcurves and derives the physical quantities of lens systems. The package provides microlensing modeling, and the magnification estimation for high cadence lightcurves has been optimized. pyLIMA is designed to make microlensing modeling and event simulation widely available to the community.

VBBinaryLensing forward models gravitational microlensing events using the advanced contour integration method; it supports single and binary lenses. The lens map is inverted on a collection of points on the source boundary to obtain a corresponding collection of points on the boundaries of the images from which the area of the images can be recovered by use of Green’s theorem. The code takes advantage of a number of techniques to make contour integration much more efficient, including using a parabolic correction to increase the accuracy of the summation, introducing an error estimate on each arc of the boundary to enable defining an optimal sampling, and allowing the inclusion of limb darkening. The code is written as a C++ library and wrapped as a Python package, and can be called from either C++ or Python.

This package is no longer maintained.

RTModel models and interprets microlensing events. It uses photometric time series collected from ground and/or space telescopes to propose one or more of the following possible models:

- single-lens-single-source microlensing;
- single-lens-binary-source microlensing, with or without xallarap; and/or
- binary-lens-single-source microlensing, including planetary microlensing, parallax and orbital motion.

All models include the finite-size of the source(s). The modeling strategy is based on a grid search in the parameter space for single-lens models, whereas a template library for binary-lens models is used including all possible geometries of the source trajectory with respect to the caustics. In addition to this global search, planets are searched where maximal deviations from a Paczynski model occurs. The RTModel package also including subpackages for creating an immediate visualization of models and the possibility to review each individual fitting process as an animated GIF.