fastlens:

Public package of FFT based evaluation of extended source magnification, fastlens, which is named after fast microlensing. Please cite Sugiyama 2022.

FFT based method of extended soruce magnification is implemented in fastlens/mag_fft.py. FFT based method of time averaged magnification is implemented in fastlens/timeave.py.

Please cite my paper if you use my code for your project.

FFT based method uses public FFTLog code by Xiao Fang, available at FFTLog-and-beyond, and developed in Fang et al (2019); arXiv:1911.11947.

fastlens is open source and distributed with MIT license.

Installation

This package is installable with both of pip and conda. Just install by running below on your shell

pip install fastlens

for pip user, or

conda install -c XXX fastlens

for conda user.

If you prefer to download the repo and install the package from source, run

python setup.py install

Contents: notebooks and a script

All the ipython notebooks are saved in ipynb direcotry. Tutorials are available in

• howtouse.ipynb shows how to use module in magnification.
• howtouse-previous-methods.ipynb shows how to use modeles for methods developed in the previous studies. Validation and comparison to previous methods are performed in
• timeave.ipynb validate the accuracy of implementation of time averaging effect with FFT.
• comparison.ipynb makes a plot of comparison of residuals by various evaluation methods of extended source magnification.
• timeit_methods.ipynb measures computational time of various methods.
• paperfig.ipynb can reproduce figures shown in the paper.
• testdata.py is a module to generate reference magnification using scipy.integrate.quad, which will be used for validation of the FFT based method.