F8.py

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
    and measuring the root-mean-square (RMS) of the result. 
    """
    # bin the LC to 30 minutes to simulate Kepler cadence
    width = 30*60 # 30 min in seconds
    bins = np.arange(0, time[-1]+width, width)
    # binned time and flux
    btime = binned_statistic(time, time, bins=bins)[0]
    bflux = binned_statistic(time, flux, bins=bins)[0]
    # boxcar smooth using 16 pts (8 hours)
    convflux = convolve(bflux, Box1DKernel(16))
    # subtract smoothed lc
    newflux = bflux - convflux
    # F8 is the RMS
    return np.sqrt(np.sum(newflux**2)/newflux.size)