coolworlds / weirddetector Goto Github PK

Pkg.add("Interpolations")
Pkg.add("DataFrames")
Pkg.add("FITSIO")

push!(LOAD_PATH, "/directory/containing/this/code")
using WeirdDetector

#here's how you can get a Kepler light curve detrended like we did in the paper
getFITS(8462852, fitsdir="./") #download FITS files for Boyajian's star to the current directory
df = loadFITS(8462852, fitsdir="./") #load all quarters into single data frame, perform ourlier rejection and detrending
data = pointsify(df) #convert to data type taken by periodogram()

#Here's how to prep arbitary data
t = ...      # array of epochs
F = ...      # array of flux values
sigmaF = ... # array of 1-sigma uncertainties
data = Point.(t, F, sigmaF) #this constructs an array of Points with Julia's broadcast syntax

periods = optimal_periods(pmin=0.25, pmax=50) #construct array of periods used in paper.  Any array of Float32's will do.
output = periodogram(data, periods, parallel=true) #construct a DataFrame containing the chi-squared and kurtosis values for each period
                                                   #if you want to parallelize, start Julia with "julia -n <number of cores>"

#do some postprocessing 
output[:delt_chi2] = flatten(output[:chi2], periods) #calculate \Delta \chi^2 (see equation N)

null_output = scrambled_periodogram(data, periods)
null_output[:delt_chi2] = flatten(null_output[:chi2], periods)
sigma = movingstd((null_output[:kurtosis] .- 3) .* (null_output[:delt_chi2])

output[:zeta] = (output[:kurtosis] .- 3) .* output[:delt_chi2] ./ sigma

#plot the periodogram
using PyPlot
plot(periods, output[:zeta])