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def massTorres(teff, erteff, logg, erlogg, feh, erfeh, 
                ntrials=10000, corrected=True):
    randomteff = teff + erteff * np.random.randn(ntrials)
    randomlogg = logg + erlogg * np.random.randn(ntrials)
    randomfeh = feh + erfeh * np.random.randn(ntrials)

    # Parameters for the Torres calibration
    a1 = 1.5689
    a2 = 1.3787
    a3 = 0.4243

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gs -o - -sDEVICE=inkcov input.pdf | grep -v "^ 0.00000  0.00000  0.00000" | grep "^ " | wc -l

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# MIT Licensed
# Copyright (c) 2009-2010 Peter Shinners <pete@shinners.org> 
#
# Permission is hereby granted, free of charge, to any person
# obtaining a copy of this software and associated documentation
# files (the "Software"), to deal in the Software without
# restriction, including without limitation the rights to use,
# copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the
# Software is furnished to do so, subject to the following

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import numpy as np
from scipy.stats import binned_statistic
from astropy.convolution import convolve, Box1DKernel

def f8(time, flux):
    """
    Calculate the F8 statistic, as in Bastien et al.
    Both `time` and `flux` should be numpy arrays.
    The 8-hour flicker (F8) is determined by performing a 16-point (8 hour) 
    boxcar smoothing of the light curve, subtracting it from the original light curve

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from IPython import get_ipython

timer = lambda code: get_ipython().run_line_magic('timeit', '-o ' + code)

out = timer('pass')
out = timer('a = 0')

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#include <iostream>
#include <mkl.h>
#include <math.h>
#include <pybind11/pybind11.h>
#include <pybind11/numpy.h>

namespace py = pybind11;
using namespace pybind11::literals;
using namespace std;

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def develop():
    import reimport, os
    mod = reimport.modified()
    try:
        mod.remove('__main__')
    except ValueError:
        pass
    reimport.reimport(*mod)
    print 'Done re-importing'

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#!/usr/bin/python
# -*- coding: utf-8 -*-

"""
Print the acknowledgements sentence with all the project references!
See acknowledgements.py -h or run acknowledgements.py ? for help or simply use as 
acknowledgements.py Author1 Author2
"""

name = 'acknowledgements'

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from astropy.constants import G
import astropy.units as u

# we assume m_planet << m_star

def get_planet_mass(P, K, e, star_mass=1.0):
    """ 
    P in days, K in m/s, star_mass in solar masses 
    output is planet mass in Jupiter masses
    """

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import numpy as np
from scipy.optimize import bisect
from scipy.special import binom as binom_coeff
from scipy.integrate import quad
from functools import partial

def binom_function(N, n, p):
	c = binom_coeff(N, n)
	return c * p**n * (1.-p)**(N-n)