Tutorials MulensModel:
- Basic usage tutorial,
- Fitting tutorial,
- Microlensing parallax fitting tutorial,
- Explanation of microlensing parameters,
- Explanation of methods used for calculating magnification,
- Instructions on getting satellite positions - useful only if you have satellite data.
Examples on how to use the code:
- Example 01 - plot simple point-source/point-lens (PSPL) model and model with planetary lens,
- Example 02 - fit PSPL model to the data using scipy.optimize.minimize(),
- Example 03 - define PSPL model using physical properties and plot the resulting magnification curve,
- Example 04 - calculate the Einstein ring size for a grid of lens masses and distances,
- Example 05 - plot multiple datasets for a single model, plot the residuals, and do this both in magnitude and magnification spaces,
- Example 06 - fit parallax model using EMCEE,
- Example 07 - fit parallax model using MultiNest,
- Example 08 - shows how to fit simulated WFIRST light curve with planetary model,
- Example 09 - fit point lens model using chi^2 gradient,
- Example 10 - fit model and extract posterior fluxes, use config file to pass all parameters,
- Example 11 - simulate and fit binary source event,
- Example 12 - fit parallax model to ground and satellite data, plot models and trajectories at the end,
- Example 13 - fit planetary event using caustic entrance and exit epochs as parameters (uses config file),
- Example 14 - plot caustic using standard method and uniform sampling,
- Example 15 - fitting binary lens model with many options - use config file for ob05390 or mb07192; settings are read by this file,
- Example 16 - high-level fitting example where all settings are read from a human-readable YAML file, there is a separate description of that example in this README file,
- Three files producing plots presented in paper describing MulensModel: plots_1.py, plots_2.py, and plots_3.py.
MulensModel documentation includes description of input and output of every function.
If you have used MulensModel and wrote a code that you think might be useful for others, then please send it to code authors or submit a pull request.