orbitutils 0.1.4

Easily make Monte Carlo simulations of binary or triple orbits.

This package allows for easy and very quick Monte Carlo simulation of populations of orbits, giving instantly distributions of projected separations, relative RVs between components, etc. Includes calculations for eccentric orbits. Handy for simulating imaging or RV observations. This code is one of the modules that makes up the Morton (2012) validation procedure.

Makes occasional use of the astropy Quantity object to keep track of some quantities, and the astropy SkyCoord object to keep track of coordinates. Also uses pandas to save/restore populations.

See below for a quick intro, and the notebook demo for more.

Installation

$ pip install [--user] orbitutils

Or clone the repository and install:

$ git clone https://github.com/timothydmorton/orbitutils.git
$ cd orbitutils
$ python setup.py install [--user]

Basic usage

Simulate a population for given primary and secondary mass(es), and orbital periods. Eccentricity is zero by default, but can be set.

from orbitutils import OrbitPopulation
pop = OrbitPopulation(1,1,1000,n=1e4) #Primary mass, secondary mass, orbital period (d)

You can also create a distribution of secondary masses, and/or a distribution of periods:

import numpy as np
from orbitutils import OrbitPopulation
N=1e4
M2s = np.linspace(0.1,1,N)
Ps = np.logspace(1,3,N) #periods evenly log-spaced from 10 to 1000 days
pop = OrbitPopulation(1,M2s,Ps)

OrbitPopulation objects can be saved using the save_hdf method:

pop.save_hdf('mypop.h5')

and then read back in/restored as follows:

from orbitutils import OrbitPopulation_FromH5
pop_again = OrbitPopulation_FromH5('mypop.h5')

Attribution

If you use this software for your research, please let me know. Eventually there will be a more current publication to cite; until then, please cite my 2012 planet validation method paper which used this code:

@ARTICLE{2012ApJ...761....6M,
   author = {{Morton}, T.~D.},
    title = "{An Efficient Automated Validation Procedure for Exoplanet Transit Candidates}",
  journal = {\apj},
archivePrefix = "arXiv",
   eprint = {1206.1568},
 primaryClass = "astro-ph.EP",
 keywords = {planetary systems, stars: statistics },
     year = 2012,
    month = dec,
   volume = 761,
      eid = {6},
    pages = {6},
      doi = {10.1088/0004-637X/761/1/6},
   adsurl = {http://adsabs.harvard.edu/abs/2012ApJ...761....6M},
  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}