{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Kepler Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## The Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "SIMBAD info: http://simbad.u-strasbg.fr/simbad/sim-id?Ident=KIC7198959\n",
    "\n",
    "Lightcurve data from: https://archive.stsci.edu/kepler/publiclightcurves.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# !curl -O http://archive.stsci.edu/pub/kepler/lightcurves/0071/007198959/kplr007198959-2009259160929_llc.fits"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Filename: kplr007198959-2009259160929_llc.fits\n",
      "No.    Name         Type      Cards   Dimensions   Format\n",
      "  0  PRIMARY     PrimaryHDU      58   ()      \n",
      "  1  LIGHTCURVE  BinTableHDU    155   4354R x 20C   [D, E, J, E, E, E, E, E, E, J, D, E, D, E, D, E, D, E, E, E]   \n",
      "  2  APERTURE    ImageHDU        48   (12, 41)   int32   \n"
     ]
    }
   ],
   "source": [
    "from astropy.io import fits\n",
    "hdulist = fits.open('kplr007198959-2009259160929_llc.fits')\n",
    "hdulist.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "XTENSION= 'BINTABLE'           / marks the beginning of a new HDU               \n",
       "BITPIX  =                    8 / array data type                                \n",
       "NAXIS   =                    2 / number of array dimensions                     \n",
       "NAXIS1  =                  100 / length of first array dimension                \n",
       "NAXIS2  =                 4354 / length of second array dimension               \n",
       "PCOUNT  =                    0 / group parameter count (not used)               \n",
       "GCOUNT  =                    1 / group count (not used)                         \n",
       "TFIELDS =                   20 / number of table fields                         \n",
       "TTYPE1  = 'TIME    '           / column title: data time stamps                 \n",
       "TFORM1  = 'D       '           / column format: 64-bit floating point           \n",
       "TUNIT1  = 'BJD - 2454833'      / column units: barycenter corrected JD          \n",
       "TDISP1  = 'D14.7   '           / column display format                          \n",
       "TTYPE2  = 'TIMECORR'           / column title: barycenter - timeslice correction\n",
       "TFORM2  = 'E       '           / column format: 32-bit floating point           \n",
       "TUNIT2  = 'd       '           / column units: day                              \n",
       "TDISP2  = 'E13.6   '           / column display format                          \n",
       "TTYPE3  = 'CADENCENO'          / column title: unique cadence number            \n",
       "TFORM3  = 'J       '           / column format: signed 32-bit integer           \n",
       "TDISP3  = 'I10     '           / column display format                          \n",
       "TTYPE4  = 'SAP_FLUX'           / column title: aperture photometry flux         \n",
       "TFORM4  = 'E       '           / column format: 32-bit floating point           \n",
       "TUNIT4  = 'e-/s    '           / column units: electrons per second             \n",
       "TDISP4  = 'E14.7   '           / column display format                          \n",
       "TTYPE5  = 'SAP_FLUX_ERR'       / column title: aperture phot. flux error        \n",
       "TFORM5  = 'E       '           / column format: 32-bit floating point           \n",
       "TUNIT5  = 'e-/s    '           / column units: electrons per second (1-sigma)   \n",
       "TDISP5  = 'E14.7   '           / column display format                          \n",
       "TTYPE6  = 'SAP_BKG '           / column title: aperture phot. background flux   \n",
       "TFORM6  = 'E       '           / column format: 32-bit floating point           \n",
       "TUNIT6  = 'e-/s    '           / column units: electrons per second             \n",
       "TDISP6  = 'E14.7   '           / column display format                          \n",
       "TTYPE7  = 'SAP_BKG_ERR'        / column title: ap. phot. background flux error  \n",
       "TFORM7  = 'E       '           / column format: 32-bit floating point           \n",
       "TUNIT7  = 'e-/s    '           / column units: electrons per second (1-sigma)   \n",
       "TDISP7  = 'E14.7   '           / column display format                          \n",
       "TTYPE8  = 'PDCSAP_FLUX'        / column title: aperture phot. PDC flux          \n",
       "TFORM8  = 'E       '           / column format: 32-bit floating point           \n",
       "TUNIT8  = 'e-/s    '           / column units: electrons per second             \n",
       "TDISP8  = 'E14.7   '           / column display format                          \n",
       "TTYPE9  = 'PDCSAP_FLUX_ERR'    / column title: ap. phot. PDC flux error         \n",
       "TFORM9  = 'E       '           / column format: 32-bit floating point           \n",
       "TUNIT9  = 'e-/s    '           / column units: electrons per second (1-sigma)   \n",
       "TDISP9  = 'E14.7   '           / column display format                          \n",
       "TTYPE10 = 'SAP_QUALITY'        / column title: aperture photometry quality flag \n",
       "TFORM10 = 'J       '           / column format: signed 32-bit integer           \n",
       "TDISP10 = 'B16.16  '           / column display format                          \n",
       "TTYPE11 = 'PSF_CENTR1'         / column title: PSF-fitted column centroid       \n",
       "TFORM11 = 'D       '           / column format: 64-bit floating point           \n",
       "TUNIT11 = 'pixel   '           / column units: pixel                            \n",
       "TDISP11 = 'F10.5   '           / column display format                          \n",
       "TTYPE12 = 'PSF_CENTR1_ERR'     / column title: PSF-fitted column error          \n",
       "TFORM12 = 'E       '           / column format: 32-bit floating point           \n",
       "TUNIT12 = 'pixel   '           / column units: pixel (1-sigma)                  \n",
       "TDISP12 = 'E14.7   '           / column display format                          \n",
       "TTYPE13 = 'PSF_CENTR2'         / column title: PSF-fitted row centroid          \n",
       "TFORM13 = 'D       '           / column format: 64-bit floating point           \n",
       "TUNIT13 = 'pixel   '           / column units: pixel                            \n",
       "TDISP13 = 'F10.5   '           / column display format                          \n",
       "TTYPE14 = 'PSF_CENTR2_ERR'     / column title: PSF-fitted row error             \n",
       "TFORM14 = 'E       '           / column format: 32-bit floating point           \n",
       "TUNIT14 = 'pixel   '           / column units: pixel (1-sigma)                  \n",
       "TDISP14 = 'E14.7   '           / column display format                          \n",
       "TTYPE15 = 'MOM_CENTR1'         / column title: moment-derived column centroid   \n",
       "TFORM15 = 'D       '           / column format: 64-bit floating point           \n",
       "TUNIT15 = 'pixel   '           / column units: pixel                            \n",
       "TDISP15 = 'F10.5   '           / column display format                          \n",
       "TTYPE16 = 'MOM_CENTR1_ERR'     / column title: moment-derived column error      \n",
       "TFORM16 = 'E       '           / column format: 32-bit floating point           \n",
       "TUNIT16 = 'pixel   '           / column units: pixel (1-sigma)                  \n",
       "TDISP16 = 'E14.7   '           / column display format                          \n",
       "TTYPE17 = 'MOM_CENTR2'         / column title: moment-derived row centroid      \n",
       "TFORM17 = 'D       '           / column format: 64-bit floating point           \n",
       "TUNIT17 = 'pixel   '           / column units: pixel                            \n",
       "TDISP17 = 'F10.5   '           / column display format                          \n",
       "TTYPE18 = 'MOM_CENTR2_ERR'     / column title: moment-derived row error         \n",
       "TFORM18 = 'E       '           / column format: 32-bit floating point           \n",
       "TUNIT18 = 'pixel   '           / column units: pixel (1-sigma)                  \n",
       "TDISP18 = 'E14.7   '           / column display format                          \n",
       "TTYPE19 = 'POS_CORR1'          / column title: column position correction       \n",
       "TFORM19 = 'E       '           / column format: 32-bit floating point           \n",
       "TUNIT19 = 'pixels  '           / column units: pixel                            \n",
       "TDISP19 = 'E14.7   '           / column display format                          \n",
       "TTYPE20 = 'POS_CORR2'          / column title: row position correction          \n",
       "TFORM20 = 'E       '           / column format: 32-bit floating point           \n",
       "TUNIT20 = 'pixels  '           / column units: pixel                            \n",
       "TDISP20 = 'E14.7   '           / column display format                          \n",
       "INHERIT =                    T / inherit the primary header                     \n",
       "EXTNAME = 'LIGHTCURVE'         / name of extension                              \n",
       "EXTVER  =                    1 / extension version number (not format version)  \n",
       "TELESCOP= 'Kepler  '           / telescope                                      \n",
       "INSTRUME= 'Kepler Photometer'  / detector type                                  \n",
       "OBJECT  = 'KIC 7198959'        / string version of target id                    \n",
       "KEPLERID=              7198959 / unique Kepler target identifier                \n",
       "RADESYS = 'ICRS    '           / reference frame of celestial coordinates       \n",
       "RA_OBJ  =           291.366301 / [deg] right ascension                          \n",
       "DEC_OBJ =            42.784367 / [deg] declination                              \n",
       "EQUINOX =               2000.0 / equinox of celestial coordinate system         \n",
       "EXPOSURE=          81.90687481 / [d] time on source                             \n",
       "TIMEREF = 'SOLARSYSTEM'        / barycentric correction applied to times        \n",
       "TASSIGN = 'SPACECRAFT'         / where time is assigned                         \n",
       "TIMESYS = 'TDB     '           / time system is barycentric JD                  \n",
       "BJDREFI =              2454833 / integer part of BJD reference date             \n",
       "BJDREFF =           0.00000000 / fraction of the day in BJD reference date      \n",
       "TIMEUNIT= 'd       '           / time unit for TIME, TSTART and TSTOP           \n",
       "TELAPSE =          88.96781229 / [d] TSTOP - TSTART                             \n",
       "LIVETIME=          81.90687481 / [d] TELAPSE multiplied by DEADC                \n",
       "TSTART  =         169.51002764 / observation start time in BJD-BJDREF           \n",
       "TSTOP   =         258.47783993 / observation stop time in BJD-BJDREF            \n",
       "LC_START=       55002.01747542 / mid point of first cadence in MJD              \n",
       "LC_END  =       55090.96492052 / mid point of last cadence in MJD               \n",
       "DEADC   =           0.92063492 / deadtime correction                            \n",
       "TIMEPIXR=                  0.5 / bin time beginning=0 middle=0.5 end=1          \n",
       "TIERRELA=             5.78E-07 / [d] relative time error                        \n",
       "TIERABSO=                      / [d] absolute time error                        \n",
       "INT_TIME=       6.019802903270 / [s] photon accumulation time per frame         \n",
       "READTIME=       0.518948526144 / [s] readout time per frame                     \n",
       "FRAMETIM=       6.538751429414 / [s] frame time (INT_TIME + READTIME)           \n",
       "NUM_FRM =                  270 / number of frames per time stamp                \n",
       "TIMEDEL =     0.02043359821692 / [d] time resolution of data                    \n",
       "DATE-OBS= '2009-06-20T00:10:27.146Z' / TSTART as UTC calendar date              \n",
       "DATE-END= '2009-09-16T23:24:11.862Z' / TSTOP as UTC calendar date               \n",
       "BACKAPP =                    T / background is subtracted                       \n",
       "DEADAPP =                    T / deadtime applied                               \n",
       "VIGNAPP =                    T / vignetting or collimator correction applied    \n",
       "GAIN    =                111.9 / [electrons/count] channel gain                 \n",
       "READNOIS=            80.176350 / [electrons] read noise                         \n",
       "NREADOUT=                  270 / number of read per cadence                     \n",
       "TIMSLICE=                    2 / time-slice readout sequence section            \n",
       "MEANBLCK=                  728 / [count] FSW mean black level                   \n",
       "LCFXDOFF=               419400 / long cadence fixed offset                      \n",
       "SCFXDOFF=               219400 / short cadence fixed offset                     \n",
       "CDPP3_0 =     4018.13134765625 / [ppm] RMS CDPP on 3.0-hr time scales           \n",
       "CDPP6_0 =    3200.025146484375 / [ppm] RMS CDPP on 6.0-hr time scales           \n",
       "CDPP12_0=     2240.04345703125 / [ppm] RMS CDPP on 12.0-hr time scales          \n",
       "CROWDSAP=               0.9991 / Ratio of target flux to total flux in op. ap.  \n",
       "FLFRCSAP=               0.9981 / Frac. of target flux w/in the op. aperture     \n",
       "NSPSDDET=                    0 / Number of SPSDs detected                       \n",
       "NSPSDCOR=                    0 / Number of SPSDs corrected                      \n",
       "PDCVAR  =      8497.4873046875 / Target variability                             \n",
       "PDCMETHD= 'regularMap'         / PDC algorithm used for target                  \n",
       "NUMBAND =                    1 / Number of scale bands                          \n",
       "FITTYPE1= 'prior   '           / Fit type used for band 1                       \n",
       "PR_GOOD1=   0.9999999403953552 / Prior goodness for band 1                      \n",
       "PR_WGHT1=           7.222428E7 / Prior weight for band 1                        \n",
       "PDC_TOT =   0.9671307802200317 / PDC total goodness metric for target           \n",
       "PDC_TOTP=    47.21249771118164 / PDC_TOT percentile compared to mod/out         \n",
       "PDC_COR =   0.9740492701530457 / PDC correlation goodness metric for target     \n",
       "PDC_CORP=    16.63991355895996 / PDC_COR percentile compared to mod/out         \n",
       "PDC_VAR =   0.9556516408920288 / PDC variability goodness metric for target     \n",
       "PDC_VARP=   25.864707946777344 / PDC_VAR percentile compared to mod/out         \n",
       "PDC_NOI =   0.9995011687278748 / PDC noise goodness metric for target           \n",
       "PDC_NOIP=     99.8350601196289 / PDC_NOI percentile compared to mod/out         \n",
       "PDC_EPT =                  1.0 / PDC earth point goodness metric for target     \n",
       "PDC_EPTP=    76.93851470947266 / PDC_EPT percentile compared to mod/out         \n",
       "CHECKSUM= '5dE25ZB05bB05ZB0'   / HDU checksum updated 2015-09-07T00:10:06Z      "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hdulist[1].header"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<Table length=4354>\n",
       "<table id=\"table4501720424\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>TIME</th><th>TIMECORR</th><th>CADENCENO</th><th>SAP_FLUX</th><th>SAP_FLUX_ERR</th><th>SAP_BKG</th><th>SAP_BKG_ERR</th><th>PDCSAP_FLUX</th><th>PDCSAP_FLUX_ERR</th><th>SAP_QUALITY</th><th>PSF_CENTR1</th><th>PSF_CENTR1_ERR</th><th>PSF_CENTR2</th><th>PSF_CENTR2_ERR</th><th>MOM_CENTR1</th><th>MOM_CENTR1_ERR</th><th>MOM_CENTR2</th><th>MOM_CENTR2_ERR</th><th>POS_CORR1</th><th>POS_CORR2</th></tr></thead>\n",
       "<thead><tr><th>float64</th><th>float32</th><th>int32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>int32</th><th>float64</th><th>float32</th><th>float64</th><th>float32</th><th>float64</th><th>float32</th><th>float64</th><th>float32</th><th>float32</th><th>float32</th></tr></thead>\n",
       "<tr><td>169.520244707</td><td>0.00276929</td><td>2965</td><td>1.04089e+07</td><td>80.6514</td><td>17445.8</td><td>6.81535</td><td>nan</td><td>nan</td><td>256</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>658.98490534</td><td>5.95852e-06</td><td>48.3103679836</td><td>6.3673e-05</td><td>-0.00062082</td><td>-0.0417439</td></tr>\n",
       "<tr><td>169.540678885</td><td>0.00276986</td><td>2966</td><td>1.02251e+07</td><td>79.9479</td><td>17458.6</td><td>6.81904</td><td>nan</td><td>nan</td><td>256</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>658.984756055</td><td>6.02055e-06</td><td>48.3645953434</td><td>6.32755e-05</td><td>-0.000859906</td><td>-0.0414842</td></tr>\n",
       "<tr><td>169.561113062</td><td>0.00277044</td><td>2967</td><td>1.00993e+07</td><td>79.4513</td><td>17447.1</td><td>6.81976</td><td>nan</td><td>nan</td><td>256</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>658.984589033</td><td>6.06324e-06</td><td>48.3997750666</td><td>6.29868e-05</td><td>-0.00104417</td><td>-0.0411753</td></tr>\n",
       "<tr><td>169.581547239</td><td>0.00277102</td><td>2968</td><td>1.01336e+07</td><td>79.5974</td><td>17440.8</td><td>6.83005</td><td>nan</td><td>nan</td><td>8576</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>658.984422904</td><td>6.04838e-06</td><td>48.390495693</td><td>6.31236e-05</td><td>-0.00107995</td><td>-0.0406672</td></tr>\n",
       "<tr><td>169.601981415</td><td>0.0027716</td><td>2969</td><td>1.02778e+07</td><td>80.1858</td><td>17444.1</td><td>6.82776</td><td>nan</td><td>nan</td><td>393600</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>658.984122755</td><td>5.99424e-06</td><td>48.3358836774</td><td>6.35298e-05</td><td>-0.00127112</td><td>-0.0405857</td></tr>\n",
       "<tr><td>169.622415492</td><td>0.00277217</td><td>2970</td><td>1.02574e+07</td><td>80.072</td><td>17459.8</td><td>6.82085</td><td>nan</td><td>nan</td><td>256</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>658.984584229</td><td>5.99411e-06</td><td>48.3514164486</td><td>6.3458e-05</td><td>-0.00144995</td><td>-0.0403933</td></tr>\n",
       "<tr><td>169.642849768</td><td>0.00277275</td><td>2971</td><td>9.98968e+06</td><td>79.0959</td><td>17483.7</td><td>6.82168</td><td>nan</td><td>nan</td><td>384</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>658.984344926</td><td>6.09163e-06</td><td>48.4532447707</td><td>6.3e-05</td><td>-0.00170547</td><td>-0.0402648</td></tr>\n",
       "<tr><td>169.663283944</td><td>0.00277332</td><td>2972</td><td>9.77098e+06</td><td>78.2334</td><td>17483.0</td><td>6.82184</td><td>nan</td><td>nan</td><td>384</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>658.98438983</td><td>6.17017e-06</td><td>48.4774463806</td><td>6.24124e-05</td><td>-0.00160952</td><td>-0.0400706</td></tr>\n",
       "<tr><td>169.68371802</td><td>0.0027739</td><td>2973</td><td>1.00747e+07</td><td>79.3498</td><td>17492.0</td><td>6.82596</td><td>nan</td><td>nan</td><td>8576</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>658.984164904</td><td>6.05106e-06</td><td>48.4005135707</td><td>6.30872e-05</td><td>-0.00186426</td><td>-0.0400735</td></tr>\n",
       "<tr><td>169.704152195</td><td>0.00277448</td><td>2974</td><td>1.16034e+07</td><td>85.2008</td><td>17466.9</td><td>6.84612</td><td>nan</td><td>nan</td><td>384</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>658.98393699</td><td>5.57952e-06</td><td>48.1491895595</td><td>6.69151e-05</td><td>-0.00199162</td><td>-0.0393474</td></tr>\n",
       "<tr><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td></tr>\n",
       "<tr><td>258.283726632</td><td>0.00270851</td><td>7309</td><td>1.31303e+07</td><td>90.7647</td><td>17822.3</td><td>6.88246</td><td>1.31696e+07</td><td>90.8242</td><td>0</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>658.976566253</td><td>5.28842e-06</td><td>48.556622252</td><td>6.65606e-05</td><td>-0.00338648</td><td>0.0333565</td></tr>\n",
       "<tr><td>258.304159514</td><td>0.00270789</td><td>7310</td><td>1.29471e+07</td><td>90.1064</td><td>17815.1</td><td>6.87775</td><td>1.29858e+07</td><td>90.159</td><td>0</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>658.976785138</td><td>5.28611e-06</td><td>48.5489829917</td><td>6.71985e-05</td><td>-0.00362269</td><td>0.0343312</td></tr>\n",
       "<tr><td>258.324592595</td><td>0.00270728</td><td>7311</td><td>1.27119e+07</td><td>89.2577</td><td>17829.2</td><td>6.86093</td><td>1.27434e+07</td><td>89.3091</td><td>0</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>658.97690318</td><td>5.31089e-06</td><td>48.4355448483</td><td>6.73667e-05</td><td>-0.00367731</td><td>0.0329374</td></tr>\n",
       "<tr><td>258.345025577</td><td>0.00270666</td><td>7312</td><td>1.24702e+07</td><td>88.3857</td><td>17808.9</td><td>6.86379</td><td>1.25071e+07</td><td>88.4538</td><td>0</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>658.976988051</td><td>5.34708e-06</td><td>48.2808913315</td><td>6.72824e-05</td><td>-0.00375214</td><td>0.0333151</td></tr>\n",
       "<tr><td>258.365458458</td><td>0.00270604</td><td>7313</td><td>1.22394e+07</td><td>87.5396</td><td>17795.8</td><td>6.86721</td><td>1.22863e+07</td><td>87.6056</td><td>8192</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>658.976720505</td><td>5.3801e-06</td><td>48.1381236156</td><td>6.72635e-05</td><td>-0.00439123</td><td>0.0352742</td></tr>\n",
       "<tr><td>258.385891439</td><td>0.00270542</td><td>7314</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>32800</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td></tr>\n",
       "<tr><td>258.406324519</td><td>0.0027048</td><td>7315</td><td>1.16802e+07</td><td>85.472</td><td>17810.2</td><td>6.84704</td><td>1.17144e+07</td><td>85.5362</td><td>0</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>658.978009467</td><td>5.4965e-06</td><td>48.0239072802</td><td>6.65793e-05</td><td>-0.00313238</td><td>0.0327484</td></tr>\n",
       "<tr><td>258.4267574</td><td>0.00270418</td><td>7316</td><td>1.13527e+07</td><td>84.2527</td><td>17809.3</td><td>6.85194</td><td>1.1391e+07</td><td>84.311</td><td>0</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>658.977539358</td><td>5.58907e-06</td><td>48.1019007076</td><td>6.57001e-05</td><td>-0.00367803</td><td>0.033705</td></tr>\n",
       "<tr><td>258.44719038</td><td>0.00270356</td><td>7317</td><td>1.10874e+07</td><td>83.2584</td><td>17793.6</td><td>6.84324</td><td>1.11284e+07</td><td>83.3245</td><td>0</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>658.977533777</td><td>5.6692e-06</td><td>48.1753740325</td><td>6.50243e-05</td><td>-0.00364378</td><td>0.0347512</td></tr>\n",
       "<tr><td>258.46762346</td><td>0.00270294</td><td>7318</td><td>1.09189e+07</td><td>82.6193</td><td>17790.1</td><td>6.85121</td><td>1.09536e+07</td><td>82.6836</td><td>0</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>658.977162406</td><td>5.72111e-06</td><td>48.2262843684</td><td>6.45673e-05</td><td>-0.0039766</td><td>0.0342977</td></tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<Table length=4354>\n",
       "     TIME      TIMECORR  CADENCENO ... MOM_CENTR2_ERR  POS_CORR1   POS_CORR2 \n",
       "   float64     float32     int32   ...    float32       float32     float32  \n",
       "------------- ---------- --------- ... -------------- ------------ ----------\n",
       "169.520244707 0.00276929      2965 ...     6.3673e-05  -0.00062082 -0.0417439\n",
       "169.540678885 0.00276986      2966 ...    6.32755e-05 -0.000859906 -0.0414842\n",
       "169.561113062 0.00277044      2967 ...    6.29868e-05  -0.00104417 -0.0411753\n",
       "169.581547239 0.00277102      2968 ...    6.31236e-05  -0.00107995 -0.0406672\n",
       "169.601981415  0.0027716      2969 ...    6.35298e-05  -0.00127112 -0.0405857\n",
       "169.622415492 0.00277217      2970 ...     6.3458e-05  -0.00144995 -0.0403933\n",
       "169.642849768 0.00277275      2971 ...        6.3e-05  -0.00170547 -0.0402648\n",
       "169.663283944 0.00277332      2972 ...    6.24124e-05  -0.00160952 -0.0400706\n",
       " 169.68371802  0.0027739      2973 ...    6.30872e-05  -0.00186426 -0.0400735\n",
       "169.704152195 0.00277448      2974 ...    6.69151e-05  -0.00199162 -0.0393474\n",
       "          ...        ...       ... ...            ...          ...        ...\n",
       "258.283726632 0.00270851      7309 ...    6.65606e-05  -0.00338648  0.0333565\n",
       "258.304159514 0.00270789      7310 ...    6.71985e-05  -0.00362269  0.0343312\n",
       "258.324592595 0.00270728      7311 ...    6.73667e-05  -0.00367731  0.0329374\n",
       "258.345025577 0.00270666      7312 ...    6.72824e-05  -0.00375214  0.0333151\n",
       "258.365458458 0.00270604      7313 ...    6.72635e-05  -0.00439123  0.0352742\n",
       "258.385891439 0.00270542      7314 ...            nan          nan        nan\n",
       "258.406324519  0.0027048      7315 ...    6.65793e-05  -0.00313238  0.0327484\n",
       "  258.4267574 0.00270418      7316 ...    6.57001e-05  -0.00367803   0.033705\n",
       " 258.44719038 0.00270356      7317 ...    6.50243e-05  -0.00364378  0.0347512\n",
       " 258.46762346 0.00270294      7318 ...    6.45673e-05   -0.0039766  0.0342977"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from astropy.table import Table\n",
    "data = Table(hdulist[1].data)\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4354, 3)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = data.to_pandas()[['TIME', 'SAP_FLUX', 'SAP_FLUX_ERR']]\n",
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4083, 3)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df.dropna()\n",
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from astropy.stats import LombScargle\n",
    "\n",
    "plt.style.use('seaborn-whitegrid')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data and Window"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from astropy.stats import LombScargle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/jakevdp/anaconda/envs/python3.5/lib/python3.5/site-packages/astropy/stats/lombscargle/implementations/fast_impl.py:123: RuntimeWarning: invalid value encountered in true_divide\n",
      "  power = (YC * YC / CC + YS * YS / SS)\n"
     ]
    }
   ],
   "source": [
    "ls = LombScargle(df['TIME'], 1, center_data=False, fit_mean=False)\n",
    "freqW, powerW = ls.autopower(minimum_frequency=0,\n",
    "                             maximum_frequency=200)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Find the maximum near 2 hours\n",
    "f, p = ls.autopower(minimum_frequency=1.95*24,\n",
    "                    maximum_frequency=2.05*24,\n",
    "                    samples_per_peak=100)\n",
    "f_ny = f[np.argmax(p)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "t_sorted = np.sort(df['TIME'])\n",
    "p_ny = 24 * 60 * 60 / f_ny\n",
    "delta_t = (t_sorted[1:] - t_sorted[:-1]) * 24 * 60 * 60"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "ls = LombScargle(df['TIME'], df['SAP_FLUX'], df['SAP_FLUX_ERR'])\n",
    "freq, power = ls.autopower(minimum_frequency=0,\n",
    "                           maximum_frequency=200)\n",
    "\n",
    "fmax = freq[np.argmax(power)] / 24"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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27YuOHTvyLsMGNjIzMwW3Uxhu3rwJADAzMxNcRl9fHxUqVOCyaOS9efOGG8ZnaGgIkUjE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\nmpk8eTJjYmLCmJiYFOj2c4MygXKHfjXXHGUCaY7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syf7pcXbd//DDD9iwYYMyj9nZ2c3i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xVV4dnBCCGEEKI8ydnchEIhsrKyIBQKuRndCgoK8OnTJ6Snp3OzuknO7FZYWAixWIyCggJk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\nQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1103db550>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(2, 2, figsize=(12, 5))\n",
    "\n",
    "fig.suptitle('Kepler object ID 007198959', size=14)\n",
    "fig.subplots_adjust(hspace=0.35, wspace=0.15, left=0.07, right=0.97)\n",
    "\n",
    "# upper left\n",
    "ax[0, 0].plot(df['TIME'], df['SAP_FLUX'] / 1E6, 'ok', markersize=2, rasterized=True)\n",
    "ax[0, 0].set(ylabel='SAP flux ($10^6 e^-/s$)',\n",
    "             title='Observed light curve',\n",
    "             xlim=(168, 260))\n",
    "\n",
    "# bottom left\n",
    "left, bottom, width, height = ax[1, 0].get_position().bounds\n",
    "ax[1, 0].set_position([left, bottom + 0.15, width, height-0.15])\n",
    "inset = fig.add_axes([left, bottom, width, 0.1])\n",
    "\n",
    "ax[1, 0].plot(t_sorted[:-1], delta_t / 60, 'ok', markersize=2, rasterized=True)\n",
    "ax[1, 0].axhline(p_ny / 60, color='gray', linestyle='--')\n",
    "ax[1, 0].set(xlim=ax[0, 0].get_xlim(),\n",
    "             ylim=(10, 10000),\n",
    "             yscale='log',\n",
    "             ylabel='$\\Delta t$ (min)',\n",
    "             title='Time between observations')\n",
    "ax[1, 0].xaxis.set_major_formatter(plt.NullFormatter())\n",
    "\n",
    "inset.plot(t_sorted[:-1], 1000 * (delta_t - p_ny), 'ok', markersize=2, rasterized=True)\n",
    "inset.axhline(0, color='gray', linestyle='--')\n",
    "inset.set(xlim=ax[0, 0].get_xlim(),\n",
    "          ylim=(-100, 100),\n",
    "          xlabel='Observation time (days)',\n",
    "          ylabel='$\\Delta t - p_{W}$ (ms)')\n",
    "inset.yaxis.set_major_locator(plt.MaxNLocator(3));\n",
    "\n",
    "# Upper right\n",
    "ax[0, 1].plot(freqW / 24, powerW, '-k', rasterized=True);\n",
    "ax[0, 1].set(xlim=(0, 6.5),\n",
    "             ylim=(-0.1, 1.1),\n",
    "             ylabel='Lomb-Scargle power',\n",
    "             title='Window Power Spectrum');\n",
    "ax[0, 1].annotate('', (0, 0.6), (f_ny / 24, 0.6),\n",
    "                  arrowprops=dict(arrowstyle='<->', color='gray'));\n",
    "ax[0, 1].text(f_ny / 48, 0.6, r'$({0:.1f}\\ {{\\rm minutes}})^{{-1}}$'.format(24 * 60 / f_ny),\n",
    "              size=12, ha='center', va='bottom');\n",
    "\n",
    "# Lower right\n",
    "ax[1, 1].plot(freq / 24, power, '-k', rasterized=True)\n",
    "ax[1, 1].fill_between([0.5 * f_ny / 24, 1.5 * f_ny / 24], -0.05, 1,\n",
    "                      color='gray', alpha=0.3)\n",
    "ax[1, 1].text(2.25, 0.95, r\"(Aliased Region)\", size=14, color='gray', ha='right', va='top')\n",
    "ax[1, 1].text(fmax, 0.85, r\"$f_{{max}}=({0:.2f}\\ {{\\rm hours}})^{{-1}}$\".format(1 / fmax),\n",
    "              size=12)\n",
    "ax[1, 1].set(xlim=(0, 2.3),\n",
    "             ylim=(-0.05, 1.0),\n",
    "             xlabel='frequency (hours$^{-1}$)',\n",
    "             ylabel='Lomb-Scargle power',\n",
    "             title='Light Curve Power Spectrum');\n",
    "\n",
    "fig.savefig('fig16_kepler_data.pdf')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Size of required grid"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "f_ny = 48.9393547811\n",
      "T = 88.947378753\n",
      "n_grid = 21765.1366282\n"
     ]
    }
   ],
   "source": [
    "n_o = 5\n",
    "T = df['TIME'].max() - df['TIME'].min()\n",
    "delta_f = 1. / n_o / T\n",
    "\n",
    "print(\"f_ny =\", f_ny)\n",
    "print(\"T =\", T)\n",
    "print(\"n_grid =\", f_ny / delta_f)"
   ]
  }
 ],
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