t_div = target / r_avg
t_err = np.sqrt(target)
# find the target uncertainty
t_div_err = t_div * np.sqrt((t_err / target)**2 + (r_avg_err / r_avg)**2)
from astropy.stats import LombScargle
radius = 0.01
upper_range = 0.054105527 + radius
lower_range = 0.054105527 - radius
frequency = np.linspace(lower_range, upper_range, 1000)
power = LombScargle(hr, t_div, t_div_err).power(frequency)
print "Power at peak frequency: ", np.max(power)
print "Peak frequency: ", frequency[power.argmax()]
# PLOT LOMB-SCARGLE
fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(12.8, 7.6))
ax1.plot(frequency, power, 'k')
ax1.set_title("Lomb-Scargle Periodogram of HD 345439")
ax1.set_xlabel("Frequency (Cycles per hour)")
ax1.set_ylabel("Power")
ax1.set_xlim([np.min(frequency), np.max(frequency)])
ax1.annotate("Power at peak frequency: %.4f" % np.max(power),
xy=(0.01, 0.85),
xycoords='axes fraction')
ax1.annotate("Peak Frequency: %.11f" % frequency[power.argmax()],
xy=(0.01, 0.90),
xycoords='axes fraction')
def kepperiodogram(infile, outfile=None, datacol='PDCSAP_FLUX', pmin=0.1, pmax=10., nfreq=2000,
plot=False, noninteractive=False, overwrite=False, verbose=False,
logfile='kepperiodogram.log'):
"""
kepperiodogram -- Calculate and store a Lomb Scargle Periodogram based on a
Kepler time series. The result is stored in a new FITS file that is a
direct copy of the input file but with an additional table extension
containing the periodogram.
Parameters
----------
infile : str
The name of a MAST standard format FITS file containing a Kepler light
curve within the first data extension.
outfile : str
The name of the output FITS file with a new extension containing the
Fourier spectrum.
datacol : str
The name of the FITS table column in extension 1 of infile upon which
the Fourier transform will be calculated.
pmin : float [day]
The minimum of the period range over which the Fourier transform will
be calculated.
pmax : float [day]
The maximum of the period range over which the Fourier transform will
be calculated.
nfreq : int
The number of uniform frequency steps between :math:`1/pmax` and
:math:`1/pmin` that the Fourier transform will be calculated.
plot : bool
Plot the output Fourier spectrum?
non-interactive : bool
If True, prevents the matplotlib window to pop up.
overwrite : bool
Overwrite the output file?
verbose : bool
Print informative messages and warnings to the shell and logfile?
logfile : str
Name of the logfile containing error and warning messages.
Examples
--------
.. code-block:: bash
$ kepperiodogram kplr002436324-2009259160929_llc.fits --pmin 0.5
--pmax 100 --nfreq 1000 --plot --verbose
.. image:: ../_static/images/api/kepperiodogram.png
:align: center
"""
if outfile is None:
outfile = infile.split('.')[0] + "-{}.fits".format(__all__[0])
## log the call
hashline = '--------------------------------------------------------------'
kepmsg.log(logfile, hashline, verbose)
call = ('kepperiodogram -- '
+ ' infile={}'.format(infile)
+ ' outfile={}'.format(outfile)
+ ' datacol={}'.format(datacol)
+ ' pmin={}'.format(pmin)
+ ' pmax={}'.format(pmax)
+ ' nfreq={}'.format(nfreq)
+ ' plot={}'.format(plot)
+ ' noninteractive={}'.format(noninteractive)
+ ' overwrite={}'.format(overwrite)
+ ' verbose={}'.format(verbose)
+ ' logfile={}'.format(logfile))
kepmsg.log(logfile, call+'\n', verbose)
## start time
kepmsg.clock('Start time is', logfile, verbose)
## overwrite output file
if overwrite:
kepio.overwrite(outfile, logfile, verbose)
if kepio.fileexists(outfile):
errmsg = 'ERROR -- kepperiodogram: {} exists. Use --overwrite'.format(outfile)
kepmsg.err(logfile, errmsg, verbose)
## open input file
instr = pyfits.open(infile)
tstart, tstop, bjdref, cadence = kepio.timekeys(instr, infile, logfile,
verbose)
## fudge non-compliant FITS keywords with no values
instr = kepkey.emptykeys(instr, infile, logfile, verbose)
## read table columns
try:
barytime = instr[1].data.field('barytime') + bjdref
except:
barytime = kepio.readfitscol(infile, instr[1].data, 'time', logfile,
verbose) + bjdref
signal = kepio.readfitscol(infile, instr[1].data, datacol, logfile, verbose)
## remove infinite data from time series
incols = [barytime, signal]
outcols = kepstat.removeinfinlc(signal, incols)
barytime = outcols[0]
signal = outcols[1] - np.median(outcols[1])
## period to frequency conversion
fmin = 1.0 / pmax
fmax = 1.0 / pmin
deltaf = (fmax - fmin) / nfreq
## loop through frequency steps; determine FT power
fr = np.linspace(fmin,fmax,nfreq)
power = LombScargle(barytime, signal, deltaf).power(fr)
#find highest power period
period = 1. / fr[power.argmax()]
## write output file
col1 = pyfits.Column(name='FREQUENCY', format='E', unit='1/day',
array=fr)
col2 = pyfits.Column(name='POWER', format='E', array=power)
cols = pyfits.ColDefs([col1, col2])
instr.append(pyfits.BinTableHDU.from_columns(cols))
instr[-1].header['EXTNAME'] = ('POWER SPECTRUM', 'extension name')
instr[-1].header['PERIOD'] = (period, 'most significant trial period [d]')
kepmsg.log(logfile, "kepperiodogram - best period found: {}".format(period), verbose)
kepmsg.log(logfile, "Writing output file {}...".format(outfile), verbose)
instr.writeto(outfile)
## history keyword in output file
kepkey.history(call, instr[0], outfile, logfile, verbose)
## close input file
instr.close()
## data limits
nrm = int(math.log10(power.max()))
power = power / 10 ** nrm
ylab = 'Power (x10$^{}$)'.format(nrm)
xmin = fr.min()
xmax = fr.max()
ymin = power.min()
ymax = power.max()
xr = xmax - xmin
yr = ymax - ymin
fr = np.insert(fr, [0], fr[0])
fr = np.append(fr, fr[-1])
power = np.insert(power, [0], 0.0)
power = np.append(power, 0.0)
if plot:
plt.figure()
plt.clf()
plt.axes([0.06, 0.113, 0.93, 0.86])
plt.plot(fr, power, color='#0000ff', linestyle='-', linewidth=1.0)
plt.fill(fr, power, color='#ffff00', linewidth=0.0, alpha=0.2)
plt.xlim(xmin - xr * 0.01, xmax + xr * 0.01)
if ymin - yr * 0.01 <= 0.0:
plt.ylim(1.0e-10, ymax + yr * 0.01)
else:
plt.ylim(ymin - yr * 0.01, ymax + yr *0.01)
plt.xlabel(r'Frequency (d$^{-1}$)', {'color' : 'k'})
plt.ylabel(ylab, {'color' : 'k'})
plt.grid()
# render plot
if not noninteractive:
plt.show()
## end time
kepmsg.clock('kepperiodogram completed at', logfile, verbose)