lgbouma / qatspy

python wrapper for QATS algorithm by Carter & Agol (2012)

This is a wrapper for the Quasiperiodic Automated Transit Search (QATS) algorithm.

If you use the code, please cite Carter & Agol (2012) and Kel'manov and Jeon (2004).

Pim Schellart showed me how to implement the wrapper in pybind11.

Contents

• demo_qatspy.py: run a demo on Kepler 36 data.

• README.txt: Joshua Carter's readme to his C++ implementation of the algorithm, available at Eric Agol's website.

• qats.h: detailed function descriptions.

• carter_agol_2012_fig7_reproduce.py reproduce the top panel of Figure 7 of Carter & Agol (2012).

• carter_agol_2012_river_reproduce.py reproduce a river plot from the bottom panels of Figure 7, Carter & Agol (2012).

Install

after cloning the repo,

python setup.py install --user

for instance in your favorite venv, which will let you access the library anywhere.

Then you should be able to run demo_qatspy.py. The shell output should be:

S_best: 127.4420, M_best: 55
[  110   904  1699  2494  3290  4085  4880  5676  6470  7265  8059  8853
  9647 10441 11235 12029 12823 13617 14411 15205 15999 16793 17587 18381
 19175 19969 20763 21557 22351 23146 23941 24736 25532 26327 27122 27917
 28713 29507 30302 31096 31890 32684 33478 34272 35066 35860 36654 37448
 38242 39036 39830 40624 41418 42212 43006]

Warnings

Following the notes from Sec 3.3 of Carter & Agol (2012), this algorithm assumes uniformly spaced data. Missing points should be filled in with zeros.

License

The license for the Python files and qatspy.cpp is the MIT License. qats.cpp and qats.h are written by J. Carter and provided by E. Agol; it appears to be re-distributable, but please make sure to cite Carter & Agol (2012) and Kel'manov and Jeon (2004) if you use this implementation.