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run_ACF.py
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run_ACF.py
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# This is the wrapper that calls KeplerACF.py
import numpy as np
import glob
from Kepler_ACF import corr_run
import pyfits
def load_data(lc_file):
hdulist = pyfits.open(lc_file)
tbdata = hdulist[1].data
x = tbdata["TIME"]
y = tbdata["PDCSAP_FLUX"]
yerr = tbdata["PDCSAP_FLUX_ERR"]
q = tbdata["SAP_QUALITY"]
n = np.isfinite(x)*np.isfinite(y)*np.isfinite(yerr)*(q==0)
y[n] = y[n]/np.median(y[n]) - 1.
yerr[n] = yerr[n]/np.median(y[n])
return x[n], y[n], yerr[n]
# check consistency of period measurements
def check(DIR):
nq = 18
p = np.empty(nq); p_err = np.empty(nq)
for i in range(nq):
data = np.genfromtxt("%s/%sresult.txt"%(DIR, i))
p[i] = data[0]
p_err[i] = data[1]
print "mean = ", np.mean(p)
print "median = ", np.median(p)
print np.genfromtxt("%s/allresult.txt"%DIR)
for i in range(len(p)):
print p[i], p_err[i]
def quarter_acf(lc_files, quarters, savedir):
# record kid and quarter and run ACF
for i, lc_file in enumerate(lc_files):
q = quarters.index(str(lc_file[48:61]))
kid = lc_file[38:47]
time, flux, flux_err = load_data(lc_file)
corr_run(time, flux, flux_err, kid, q, savedir)
def year_acf(globfile, id_list, savedir):
# loop over stars
for i, kid in enumerate(id_list):
# load each quarter
lc_files = np.array(glob.glob('%s/kplr*%s*_llc.fits'%(globfile(int(kid)))))
for yr in range(4):
# initialise the time and flux arrays
time, flux, flux_err = load_data(lc_files[yr-4])
# loop over quarters
for i in range(yr-4+1, yr):
time = np.concatenate((time, load_data(lc_files[i])[0]))
flux = np.concatenate((flux, load_data(lc_files[i])[1]))
flux_err = np.concatenate((flux_err, load_data(lc_files[i])[2]))
# run ACF, once per star
corr_run(time, flux, flux_err, kid, 'yr%s'%(yr+1), savedir)
def all_acf(globfile, id_list, savedir):
# loop over stars
for i, kid in enumerate(id_list):
# load each quarter
lc_files = np.array(glob.glob('%s/kplr*%s*_llc.fits'%(globfile, int(kid))))
# initialise the time and flux arrays
time, flux, flux_err = load_data(lc_files[0])
# loop over quarters
for i in range(1, len(lc_files)):
time = np.concatenate((time, load_data(lc_files[i])[0]))
flux = np.concatenate((flux, load_data(lc_files[i])[1]))
flux_err = np.concatenate((flux_err, load_data(lc_files[i])[2]))
# run ACF, once per star
corr_run(time, flux, flux_err, kid, 'all', savedir)
if __name__ == "__main__":
# define directory where results will be saved
savedir = "/Users/angusr/angusr/ACF2" # directory in which results are saved
# index fits files
lc_files = np.array(glob.glob('/Users/angusr/angusr/data2/all_Qs/kplr*_llc.fits'))
# quarter list
quarters = ["2009131105131", "2009166043257", "2009259160929", "2009350155506", \
"2010078095331", "2010174085026", "2010265121752", "2010355172524", \
"2011073133259", "2011177032512", "2011271113734", "2012004120508", \
"2012088054726", "2012179063303", "2012277125453", "2013011073258", \
"2013098041711"]
# quarter_acf(lc_files, quarters, savedir)
# load list of targets
id_list = np.genfromtxt("/Users/angusr/Python/Gyro/data/astero_targets.txt").T
globfile = '/Users/angusr/angusr/data2/all_Qs/'
# year_acf(globfile, id_list, savedir)
all_acf(globfile, id_list, savedir)