def tabappend(hdu1, hdu2, logfile, verbose):
status = 0
nrows1 = hdu1.data.shape[0]
nrows2 = hdu2.data.shape[0]
nrows = nrows1 + nrows2
out = pyfits.new_table(hdu1.columns, nrows=nrows)
for name in hdu1.columns.names:
try:
out.data.field(name)[nrows1:] = hdu2.data.field(name)
except:
message = 'WARNING -- KEPIO.TABAPPEND: could not append column '
message += str(name)
status = kepmsg.warn(logfile, message, verbose)
return out, status
def tabappend(hdu1,hdu2,logfile,verbose):
status = 0
nrows1 = hdu1.data.shape[0]
nrows2 = hdu2.data.shape[0]
nrows = nrows1 + nrows2
out = pyfits.new_table(hdu1.columns,nrows=nrows)
for name in hdu1.columns.names:
try:
out.data.field(name)[nrows1:] = hdu2.data.field(name)
except:
message = 'WARNING -- KEPIO.TABAPPEND: could not append column '
message += str(name)
status = kepmsg.warn(logfile,message,verbose)
return out, status
def kepimages(infile,outfix,imtype,ranges,clobber,verbose,logfile,status):
# startup parameters
status = 0
# log the call
hashline = '----------------------------------------------------------------------------'
kepmsg.log(logfile,hashline,verbose)
call = 'KEPIMAGES -- '
call += 'infile='+infile+' '
call += 'outfix='+outfix+' '
call += 'imtype='+imtype+' '
call += 'ranges='+str(ranges)+' '
overwrite = 'n'
if (clobber): overwrite = 'y'
call += 'clobber='+overwrite+ ' '
chatter = 'n'
if (verbose): chatter = 'y'
call += 'verbose='+chatter+' '
call += 'logfile='+logfile
kepmsg.log(logfile,call+'\n',verbose)
# start time
kepmsg.clock('KEPIMAGES started at',logfile,verbose)
# test log file
logfile = kepmsg.test(logfile)
# open input file
status = 0
print ' '
instr = pyfits.open(infile,mode='readonly',memmap=True)
cards0 = instr[0].header.cards
cards1 = instr[1].header.cards
cards2 = instr[2].header.cards
# fudge non-compliant FITS keywords with no values
if status == 0:
instr = kepkey.emptykeys(instr,file,logfile,verbose)
# ingest time series data
if status == 0:
time = instr[1].data.field('TIME')[:] + 2454833.0
timecorr = instr[1].data.field('TIMECORR')[:]
cadenceno = instr[1].data.field('CADENCENO')[:]
raw_cnts = instr[1].data.field('RAW_CNTS')[:]
flux = instr[1].data.field('FLUX')[:]
flux_err = instr[1].data.field('FLUX_ERR')[:]
flux_bkg = instr[1].data.field('FLUX_BKG')[:]
flux_bkg_err = instr[1].data.field('FLUX_BKG_ERR')[:]
cosmic_rays = instr[1].data.field('COSMIC_RAYS')[:]
quality = instr[1].data.field('QUALITY')[:]
pos_corr1 = instr[1].data.field('POS_CORR1')[:]
pos_corr2 = instr[1].data.field('POS_CORR2')[:]
# choose output image
if status == 0:
if imtype.lower() == 'raw_cnts':
outim = raw_cnts
elif imtype.lower() == 'flux_err':
outim = flux_err
elif imtype.lower() == 'flux_bkg':
outim = flux_bkg
elif imtype.lower() == 'flux_bkg_err':
outim = flux_bkg_err
elif imtype.lower() == 'cosmic_rays':
outim = cosmic_rays
else:
outim = flux
# identify images to be exported
if status == 0:
tim = array([]); dat = array([]); err = array([])
tstart, tstop, status = kepio.timeranges(ranges,logfile,verbose)
if status == 0:
cadencelis, status = kepstat.filterOnRange(time,tstart,tstop)
# provide name for each output file and clobber if file exists
if status == 0:
for cadence in cadencelis:
outfile = outfix + '_BJD%.4f' % time[cadence] + '.fits'
if clobber and status == 0: status = kepio.clobber(outfile,logfile,verbose)
if kepio.fileexists(outfile) and status == 0:
message = 'ERROR -- KEPIMAGES: ' + outfile + ' exists. Use --clobber'
status = kepmsg.err(logfile,message,True)
# construct output primary extension
if status == 0:
ncad = 0
for cadence in cadencelis:
outfile = outfix + '_BJD%.4f' % time[cadence] + '.fits'
hdu0 = pyfits.PrimaryHDU()
for i in range(len(cards0)):
try:
if cards0[i].key not in hdu0.header.keys():
hdu0.header.update(cards0[i].key, cards0[i].value, cards0[i].comment)
else:
hdu0.header.cards[cards0[i].key].comment = cards0[i].comment
except:
pass
status = kepkey.history(call,hdu0,outfile,logfile,verbose)
outstr = HDUList(hdu0)
# construct output image extension
hdu1 = ImageHDU(flux[cadence])
for i in range(len(cards2)):
try:
if cards2[i].key not in hdu1.header.keys():
hdu1.header.update(cards2[i].key, cards2[i].value, cards2[i].comment)
except:
pass
for i in range(len(cards1)):
if (cards1[i].key not in hdu1.header.keys() and
cards1[i].key[:4] not in ['TTYP','TFOR','TUNI','TDIS','TDIM','WCAX','1CTY',
'2CTY','1CRP','2CRP','1CRV','2CRV','1CUN','2CUN',
'1CDE','2CDE','1CTY','2CTY','1CDL','2CDL','11PC',
'12PC','21PC','22PC','WCSN','TFIE']):
hdu1.header.update(cards1[i].key, cards1[i].value, cards1[i].comment)
try:
int_time = cards1['INT_TIME'].value
except:
kepmsg.warn(logfile,'WARNING -- KEPIMAGES: cannot find INT_TIME keyword')
try:
frametim = cards1['FRAMETIM'].value
except:
kepmsg.warn(logfile,'WARNING -- KEPIMAGES: cannot find FRAMETIM keyword')
try:
num_frm = cards1['NUM_FRM'].value
except:
kepmsg.warn(logfile,'WARNING -- KEPIMAGES: cannot find NUM_FRM keyword')
hdu1.header.update('EXTNAME','IMAGE','name of extension')
try:
hdu1.header.update('TELAPSE',frametim * num_frm,'[s] elapsed time for exposure')
except:
hdu1.header.update('TELAPSE',-999,'[s] elapsed time for exposure')
try:
hdu1.header.update('LIVETIME',int_time * num_frm,'[s] TELASPE multiplied by DEADC')
except:
hdu1.header.update('LIVETIME',-999,'[s] TELASPE multiplied by DEADC')
try:
hdu1.header.update('EXPOSURE',int_time * num_frm,'[s] time on source')
except:
hdu1.header.update('EXPOSURE',-999,'[s] time on source')
try:
hdu1.header.update('MIDTIME',time[cadence],'[BJD] mid-time of exposure')
except:
hdu1.header.update('MIDTIME',-999,'[BJD] mid-time of exposure')
try:
hdu1.header.update('TIMECORR',timecorr[cadence],'[d] barycenter - timeslice correction')
except:
hdu1.header.update('TIMECORR',-999,'[d] barycenter - timeslice correction')
try:
hdu1.header.update('CADENCEN',cadenceno[cadence],'unique cadence number')
except:
hdu1.header.update('CADENCEN',-999,'unique cadence number')
try:
hdu1.header.update('QUALITY',quality[cadence],'pixel quality flag')
except:
hdu1.header.update('QUALITY',-999,'pixel quality flag')
try:
if True in numpy.isfinite(cosmic_rays[cadence]):
hdu1.header.update('COSM_RAY',True,'cosmic ray detected?')
else:
hdu1.header.update('COSM_RAY',False,'cosmic ray detected?')
except:
hdu1.header.update('COSM_RAY',-999,'cosmic ray detected?')
try:
pc1 = str(pos_corr1[cadence])
pc2 = str(pos_corr2[cadence])
hdu1.header.update('POSCORR1',pc1,'[pix] column position correction')
hdu1.header.update('POSCORR2',pc2,'[pix] row position correction')
except:
hdu1.header.update('POSCORR1',-999,'[pix] column position correction')
hdu1.header.update('POSCORR2',-999,'[pix] row position correction')
outstr.append(hdu1)
# write output file
if status == 0:
outstr.writeto(outfile,checksum=True)
ncad += 1
txt = '\r%3d%% ' % (float(ncad) / float(len(cadencelis)) * 100.0)
txt += '%s ' % outfile
sys.stdout.write(txt)
sys.stdout.flush()
# close input structure
if status == 0:
status = kepio.closefits(instr,logfile,verbose)
print '\n'
# end time
kepmsg.clock('KEPIMAGES finished at',logfile,verbose)
def MASTRADec(ra,dec,darcsec,srctab):
# coordinate limits
darcsec /= 3600.0
ra1 = ra - darcsec / cos(dec * pi / 180)
ra2 = ra + darcsec / cos(dec * pi / 180)
dec1 = dec - darcsec
dec2 = dec + darcsec
# build mast query
url = 'http://archive.stsci.edu/kepler/kepler_fov/search.php?'
url += 'action=Search'
url += '&masterRA=' + str(ra1) + '..' + str(ra2)
url += '&masterDec=' + str(dec1) + '..' + str(dec2)
url += '&max_records=10000'
url += '&verb=3'
url += '&outputformat=CSV'
# retrieve results from MAST
if srctab:
try:
lines = urllib.request.urlopen(url)
except:
message = 'WARNING -- KEPFIELD: Cannot retrieve data from MAST'
status = kepmsg.warn(logfile,message)
lines = ''
else:
lines = ''
# collate nearby sources
kepid = []
kepmag = []
ra = []
dec = []
for line in lines:
line = line.strip()
# Python 3 hack
try:
'Kepler' in line
except:
line = line.decode('ascii')
if (len(line) > 0 and
'Kepler' not in line and
'integer' not in line and
'no rows found' not in line):
out = line.split(',')
r,d = sex2dec(out[0],out[1])
try:
if out[-22] != 'Possible_artifact': kepid.append(int(out[2]))
except:
if out[-22] != 'Possible_artifact': kepid.append(0)
try:
if out[-22] != 'Possible_artifact': kepmag.append(float(out[42]))
except:
if out[-22] != 'Possible_artifact': kepmag.append(0.0)
if out[-22] != 'Possible_artifact': ra.append(r)
if out[-22] != 'Possible_artifact': dec.append(d)
kepid = array(kepid)
kepmag = array(kepmag)
ra = array(ra)
dec = array(dec)
return kepid,ra,dec,kepmag
def keppixseries(infile,outfile,plotfile,plottype,filter,function,cutoff,clobber,verbose,logfile,status, cmdLine=False):
# input arguments
status = 0
seterr(all="ignore")
# log the call
hashline = '----------------------------------------------------------------------------'
kepmsg.log(logfile,hashline,verbose)
call = 'KEPPIXSERIES -- '
call += 'infile='+infile+' '
call += 'outfile='+outfile+' '
call += 'plotfile='+plotfile+' '
call += 'plottype='+plottype+' '
filt = 'n'
if (filter): filt = 'y'
call += 'filter='+filt+ ' '
call += 'function='+function+' '
call += 'cutoff='+str(cutoff)+' '
overwrite = 'n'
if (clobber): overwrite = 'y'
call += 'clobber='+overwrite+ ' '
chatter = 'n'
if (verbose): chatter = 'y'
call += 'verbose='+chatter+' '
call += 'logfile='+logfile
kepmsg.log(logfile,call+'\n',verbose)
# start time
kepmsg.clock('KEPPIXSERIES started at',logfile,verbose)
# test log file
logfile = kepmsg.test(logfile)
# clobber output file
if clobber: status = kepio.clobber(outfile,logfile,verbose)
if kepio.fileexists(outfile):
message = 'ERROR -- KEPPIXSERIES: ' + outfile + ' exists. Use --clobber'
status = kepmsg.err(logfile,message,verbose)
# open TPF FITS file
if status == 0:
kepid, channel, skygroup, module, output, quarter, season, \
ra, dec, column, row, kepmag, xdim, ydim, barytime, status = \
kepio.readTPF(infile,'TIME',logfile,verbose)
if status == 0:
kepid, channel, skygroup, module, output, quarter, season, \
ra, dec, column, row, kepmag, xdim, ydim, tcorr, status = \
kepio.readTPF(infile,'TIMECORR',logfile,verbose)
if status == 0:
kepid, channel, skygroup, module, output, quarter, season, \
ra, dec, column, row, kepmag, xdim, ydim, cadno, status = \
kepio.readTPF(infile,'CADENCENO',logfile,verbose)
if status == 0:
kepid, channel, skygroup, module, output, quarter, season, \
ra, dec, column, row, kepmag, xdim, ydim, fluxpixels, status = \
kepio.readTPF(infile,'FLUX',logfile,verbose)
if status == 0:
kepid, channel, skygroup, module, output, quarter, season, \
ra, dec, column, row, kepmag, xdim, ydim, errpixels, status = \
kepio.readTPF(infile,'FLUX_ERR',logfile,verbose)
if status == 0:
kepid, channel, skygroup, module, output, quarter, season, \
ra, dec, column, row, kepmag, xdim, ydim, qual, status = \
kepio.readTPF(infile,'QUALITY',logfile,verbose)
# read mask defintion data from TPF file
if status == 0:
maskimg, pixcoord1, pixcoord2, status = kepio.readMaskDefinition(infile,logfile,verbose)
# print target data
if status == 0:
print ''
print ' KepID: %s' % kepid
print ' RA (J2000): %s' % ra
print 'Dec (J2000): %s' % dec
print ' KepMag: %s' % kepmag
print ' SkyGroup: %2s' % skygroup
print ' Season: %2s' % str(season)
print ' Channel: %2s' % channel
print ' Module: %2s' % module
print ' Output: %1s' % output
print ''
# how many quality = 0 rows?
if status == 0:
npts = 0
nrows = len(fluxpixels)
for i in range(nrows):
if qual[i] == 0 and \
numpy.isfinite(barytime[i]) and \
numpy.isfinite(fluxpixels[i,ydim*xdim/2]):
npts += 1
time = empty((npts))
timecorr = empty((npts))
cadenceno = empty((npts))
quality = empty((npts))
pixseries = empty((ydim,xdim,npts))
errseries = empty((ydim,xdim,npts))
# construct output light curves
if status == 0:
np = 0
for i in range(ydim):
for j in range(xdim):
npts = 0
for k in range(nrows):
if qual[k] == 0 and \
numpy.isfinite(barytime[k]) and \
numpy.isfinite(fluxpixels[k,ydim*xdim/2]):
time[npts] = barytime[k]
timecorr[npts] = tcorr[k]
cadenceno[npts] = cadno[k]
quality[npts] = qual[k]
pixseries[i,j,npts] = fluxpixels[k,np]
errseries[i,j,npts] = errpixels[k,np]
npts += 1
np += 1
# define data sampling
if status == 0 and filter:
tpf, status = kepio.openfits(infile,'readonly',logfile,verbose)
if status == 0 and filter:
cadence, status = kepkey.cadence(tpf[1],infile,logfile,verbose)
tr = 1.0 / (cadence / 86400)
timescale = 1.0 / (cutoff / tr)
# define convolution function
if status == 0 and filter:
if function == 'boxcar':
filtfunc = numpy.ones(numpy.ceil(timescale))
elif function == 'gauss':
timescale /= 2
dx = numpy.ceil(timescale * 10 + 1)
filtfunc = kepfunc.gauss()
filtfunc = filtfunc([1.0,dx/2-1.0,timescale],linspace(0,dx-1,dx))
elif function == 'sinc':
dx = numpy.ceil(timescale * 12 + 1)
fx = linspace(0,dx-1,dx)
fx = fx - dx / 2 + 0.5
fx /= timescale
filtfunc = numpy.sinc(fx)
filtfunc /= numpy.sum(filtfunc)
# pad time series at both ends with noise model
if status == 0 and filter:
for i in range(ydim):
for j in range(xdim):
ave, sigma = kepstat.stdev(pixseries[i,j,:len(filtfunc)])
padded = numpy.append(kepstat.randarray(numpy.ones(len(filtfunc)) * ave, \
numpy.ones(len(filtfunc)) * sigma), pixseries[i,j,:])
ave, sigma = kepstat.stdev(pixseries[i,j,-len(filtfunc):])
padded = numpy.append(padded, kepstat.randarray(numpy.ones(len(filtfunc)) * ave, \
numpy.ones(len(filtfunc)) * sigma))
# convolve data
if status == 0:
convolved = convolve(padded,filtfunc,'same')
# remove padding from the output array
if status == 0:
outdata = convolved[len(filtfunc):-len(filtfunc)]
# subtract low frequencies
if status == 0:
outmedian = median(outdata)
pixseries[i,j,:] = pixseries[i,j,:] - outdata + outmedian
# construct output file
if status == 0 and ydim*xdim < 1000:
instruct, status = kepio.openfits(infile,'readonly',logfile,verbose)
status = kepkey.history(call,instruct[0],outfile,logfile,verbose)
hdulist = HDUList(instruct[0])
cols = []
cols.append(Column(name='TIME',format='D',unit='BJD - 2454833',disp='D12.7',array=time))
cols.append(Column(name='TIMECORR',format='E',unit='d',disp='E13.6',array=timecorr))
cols.append(Column(name='CADENCENO',format='J',disp='I10',array=cadenceno))
cols.append(Column(name='QUALITY',format='J',array=quality))
for i in range(ydim):
for j in range(xdim):
colname = 'COL%d_ROW%d' % (i+column,j+row)
cols.append(Column(name=colname,format='E',disp='E13.6',array=pixseries[i,j,:]))
hdu1 = new_table(ColDefs(cols))
try:
hdu1.header.update('INHERIT',True,'inherit the primary header')
except:
status = 0
try:
hdu1.header.update('EXTNAME','PIXELSERIES','name of extension')
except:
status = 0
try:
hdu1.header.update('EXTVER',instruct[1].header['EXTVER'],'extension version number (not format version)')
except:
status = 0
try:
hdu1.header.update('TELESCOP',instruct[1].header['TELESCOP'],'telescope')
except:
status = 0
try:
hdu1.header.update('INSTRUME',instruct[1].header['INSTRUME'],'detector type')
except:
status = 0
try:
hdu1.header.update('OBJECT',instruct[1].header['OBJECT'],'string version of KEPLERID')
except:
status = 0
try:
hdu1.header.update('KEPLERID',instruct[1].header['KEPLERID'],'unique Kepler target identifier')
except:
status = 0
try:
hdu1.header.update('RADESYS',instruct[1].header['RADESYS'],'reference frame of celestial coordinates')
except:
status = 0
try:
hdu1.header.update('RA_OBJ',instruct[1].header['RA_OBJ'],'[deg] right ascension from KIC')
except:
status = 0
try:
hdu1.header.update('DEC_OBJ',instruct[1].header['DEC_OBJ'],'[deg] declination from KIC')
except:
status = 0
try:
hdu1.header.update('EQUINOX',instruct[1].header['EQUINOX'],'equinox of celestial coordinate system')
except:
status = 0
try:
hdu1.header.update('TIMEREF',instruct[1].header['TIMEREF'],'barycentric correction applied to times')
except:
status = 0
try:
hdu1.header.update('TASSIGN',instruct[1].header['TASSIGN'],'where time is assigned')
except:
status = 0
try:
hdu1.header.update('TIMESYS',instruct[1].header['TIMESYS'],'time system is barycentric JD')
except:
status = 0
try:
hdu1.header.update('BJDREFI',instruct[1].header['BJDREFI'],'integer part of BJD reference date')
except:
status = 0
try:
hdu1.header.update('BJDREFF',instruct[1].header['BJDREFF'],'fraction of the day in BJD reference date')
except:
status = 0
try:
hdu1.header.update('TIMEUNIT',instruct[1].header['TIMEUNIT'],'time unit for TIME, TSTART and TSTOP')
except:
status = 0
try:
hdu1.header.update('TSTART',instruct[1].header['TSTART'],'observation start time in BJD-BJDREF')
except:
status = 0
try:
hdu1.header.update('TSTOP',instruct[1].header['TSTOP'],'observation stop time in BJD-BJDREF')
except:
status = 0
try:
hdu1.header.update('LC_START',instruct[1].header['LC_START'],'mid point of first cadence in MJD')
except:
status = 0
try:
hdu1.header.update('LC_END',instruct[1].header['LC_END'],'mid point of last cadence in MJD')
except:
status = 0
try:
hdu1.header.update('TELAPSE',instruct[1].header['TELAPSE'],'[d] TSTOP - TSTART')
except:
status = 0
try:
hdu1.header.update('LIVETIME',instruct[1].header['LIVETIME'],'[d] TELAPSE multiplied by DEADC')
except:
status = 0
try:
hdu1.header.update('EXPOSURE',instruct[1].header['EXPOSURE'],'[d] time on source')
except:
status = 0
try:
hdu1.header.update('DEADC',instruct[1].header['DEADC'],'deadtime correction')
except:
status = 0
try:
hdu1.header.update('TIMEPIXR',instruct[1].header['TIMEPIXR'],'bin time beginning=0 middle=0.5 end=1')
except:
status = 0
try:
hdu1.header.update('TIERRELA',instruct[1].header['TIERRELA'],'[d] relative time error')
except:
status = 0
try:
hdu1.header.update('TIERABSO',instruct[1].header['TIERABSO'],'[d] absolute time error')
except:
status = 0
try:
hdu1.header.update('INT_TIME',instruct[1].header['INT_TIME'],'[s] photon accumulation time per frame')
except:
status = 0
try:
hdu1.header.update('READTIME',instruct[1].header['READTIME'],'[s] readout time per frame')
except:
status = 0
try:
hdu1.header.update('FRAMETIM',instruct[1].header['FRAMETIM'],'[s] frame time (INT_TIME + READTIME)')
except:
status = 0
try:
hdu1.header.update('NUM_FRM',instruct[1].header['NUM_FRM'],'number of frames per time stamp')
except:
status = 0
try:
hdu1.header.update('TIMEDEL',instruct[1].header['TIMEDEL'],'[d] time resolution of data')
except:
status = 0
try:
hdu1.header.update('DATE-OBS',instruct[1].header['DATE-OBS'],'TSTART as UTC calendar date')
except:
status = 0
try:
hdu1.header.update('DATE-END',instruct[1].header['DATE-END'],'TSTOP as UTC calendar date')
except:
status = 0
try:
hdu1.header.update('BACKAPP',instruct[1].header['BACKAPP'],'background is subtracted')
except:
status = 0
try:
hdu1.header.update('DEADAPP',instruct[1].header['DEADAPP'],'deadtime applied')
except:
status = 0
try:
hdu1.header.update('VIGNAPP',instruct[1].header['VIGNAPP'],'vignetting or collimator correction applied')
except:
status = 0
try:
hdu1.header.update('GAIN',instruct[1].header['GAIN'],'[electrons/count] channel gain')
except:
status = 0
try:
hdu1.header.update('READNOIS',instruct[1].header['READNOIS'],'[electrons] read noise')
except:
status = 0
try:
hdu1.header.update('NREADOUT',instruct[1].header['NREADOUT'],'number of read per cadence')
except:
status = 0
try:
hdu1.header.update('TIMSLICE',instruct[1].header['TIMSLICE'],'time-slice readout sequence section')
except:
status = 0
try:
hdu1.header.update('MEANBLCK',instruct[1].header['MEANBLCK'],'[count] FSW mean black level')
except:
status = 0
hdulist.append(hdu1)
hdulist.writeto(outfile)
status = kepkey.new('EXTNAME','APERTURE','name of extension',instruct[2],outfile,logfile,verbose)
pyfits.append(outfile,instruct[2].data,instruct[2].header)
status = kepio.closefits(instruct,logfile,verbose)
else:
message = 'WARNING -- KEPPIXSERIES: output FITS file requires > 999 columns. Non-compliant with FITS convention.'
kepmsg.warn(logfile,message)
# plot style
if status == 0:
try:
params = {'backend': 'png',
'axes.linewidth': 2.0,
'axes.labelsize': 32,
'axes.font': 'sans-serif',
'axes.fontweight' : 'bold',
'text.fontsize': 8,
'legend.fontsize': 8,
'xtick.labelsize': 12,
'ytick.labelsize': 12}
pylab.rcParams.update(params)
except:
pass
# plot pixel array
fmin = 1.0e33
fmax = -1.033
if status == 0:
pylab.figure(num=None,figsize=[12,12])
pylab.clf()
dx = 0.93 / xdim
dy = 0.94 / ydim
ax = pylab.axes([0.06,0.05,0.93,0.94])
pylab.gca().xaxis.set_major_formatter(pylab.ScalarFormatter(useOffset=False))
pylab.gca().yaxis.set_major_formatter(pylab.ScalarFormatter(useOffset=False))
pylab.gca().xaxis.set_major_locator(matplotlib.ticker.MaxNLocator(integer=True))
pylab.gca().yaxis.set_major_locator(matplotlib.ticker.MaxNLocator(integer=True))
labels = ax.get_yticklabels()
setp(labels, 'rotation', 90, fontsize=12)
pylab.xlim(numpy.min(pixcoord1) - 0.5,numpy.max(pixcoord1) + 0.5)
pylab.ylim(numpy.min(pixcoord2) - 0.5,numpy.max(pixcoord2) + 0.5)
pylab.xlabel('time', {'color' : 'k'})
pylab.ylabel('arbitrary flux', {'color' : 'k'})
for i in range(ydim):
for j in range(xdim):
tmin = amin(time)
tmax = amax(time)
try:
numpy.isfinite(amin(pixseries[i,j,:]))
numpy.isfinite(amin(pixseries[i,j,:]))
fmin = amin(pixseries[i,j,:])
fmax = amax(pixseries[i,j,:])
except:
ugh = 1
xmin = tmin - (tmax - tmin) / 40
xmax = tmax + (tmax - tmin) / 40
ymin = fmin - (fmax - fmin) / 20
ymax = fmax + (fmax - fmin) / 20
if kepstat.bitInBitmap(maskimg[i,j],2):
pylab.axes([0.06+float(j)*dx,0.05+i*dy,dx,dy],axisbg='lightslategray')
elif maskimg[i,j] == 0:
pylab.axes([0.06+float(j)*dx,0.05+i*dy,dx,dy],axisbg='black')
else:
pylab.axes([0.06+float(j)*dx,0.05+i*dy,dx,dy])
if j == int(xdim / 2) and i == 0:
pylab.setp(pylab.gca(),xticklabels=[],yticklabels=[])
elif j == 0 and i == int(ydim / 2):
pylab.setp(pylab.gca(),xticklabels=[],yticklabels=[])
else:
pylab.setp(pylab.gca(),xticklabels=[],yticklabels=[])
ptime = time * 1.0
ptime = numpy.insert(ptime,[0],ptime[0])
ptime = numpy.append(ptime,ptime[-1])
pflux = pixseries[i,j,:] * 1.0
pflux = numpy.insert(pflux,[0],-1000.0)
pflux = numpy.append(pflux,-1000.0)
pylab.plot(time,pixseries[i,j,:],color='#0000ff',linestyle='-',linewidth=0.5)
if not kepstat.bitInBitmap(maskimg[i,j],2):
pylab.fill(ptime,pflux,fc='lightslategray',linewidth=0.0,alpha=1.0)
pylab.fill(ptime,pflux,fc='#FFF380',linewidth=0.0,alpha=1.0)
if 'loc' in plottype:
pylab.xlim(xmin,xmax)
pylab.ylim(ymin,ymax)
if 'glob' in plottype:
pylab.xlim(xmin,xmax)
pylab.ylim(1.0e-10,numpy.nanmax(pixseries) * 1.05)
if 'full' in plottype:
pylab.xlim(xmin,xmax)
pylab.ylim(1.0e-10,ymax * 1.05)
# render plot
if cmdLine:
pylab.show()
else:
pylab.ion()
pylab.plot([])
pylab.ioff()
if plotfile.lower() != 'none':
pylab.savefig(plotfile)
# stop time
if status == 0:
kepmsg.clock('KEPPIXSERIES ended at',logfile,verbose)
return
def kepflatten(infile,outfile,datacol,errcol,nsig,stepsize,winsize,npoly,niter,ranges,
plot,clobber,verbose,logfile,status,cmdLine=False):
# startup parameters
status = 0
labelsize = 32
ticksize = 18
xsize = 16
ysize = 10
lcolor = '#0000ff'
lwidth = 1.0
fcolor = '#ffff00'
falpha = 0.2
# log the call
hashline = '----------------------------------------------------------------------------'
kepmsg.log(logfile,hashline,verbose)
call = 'KEPFLATTEN -- '
call += 'infile='+infile+' '
call += 'outfile='+outfile+' '
call += 'datacol='+str(datacol)+' '
call += 'errcol='+str(errcol)+' '
call += 'nsig='+str(nsig)+' '
call += 'stepsize='+str(stepsize)+' '
call += 'winsize='+str(winsize)+' '
call += 'npoly='+str(npoly)+' '
call += 'niter='+str(niter)+' '
call += 'ranges='+str(ranges)+' '
plotit = 'n'
if (plot): plotit = 'y'
call += 'plot='+plotit+ ' '
overwrite = 'n'
if (clobber): overwrite = 'y'
call += 'clobber='+overwrite+ ' '
chatter = 'n'
if (verbose): chatter = 'y'
call += 'verbose='+chatter+' '
call += 'logfile='+logfile
kepmsg.log(logfile,call+'\n',verbose)
# start time
kepmsg.clock('KEPFLATTEN started at',logfile,verbose)
# test log file
logfile = kepmsg.test(logfile)
# test winsize > stepsize
if winsize < stepsize:
message = 'ERROR -- KEPFLATTEN: winsize must be greater than stepsize'
status = kepmsg.err(logfile,message,verbose)
# clobber output file
if clobber: status = kepio.clobber(outfile,logfile,verbose)
if kepio.fileexists(outfile):
message = 'ERROR -- KEPFLATTEN: ' + outfile + ' exists. Use clobber=yes'
status = kepmsg.err(logfile,message,verbose)
# open input file
if status == 0:
instr, status = kepio.openfits(infile,'readonly',logfile,verbose)
if status == 0:
tstart, tstop, bjdref, cadence, status = kepio.timekeys(instr,infile,logfile,verbose,status)
if status == 0:
try:
work = instr[0].header['FILEVER']
cadenom = 1.0
except:
cadenom = cadence
# fudge non-compliant FITS keywords with no values
if status == 0:
instr = kepkey.emptykeys(instr,file,logfile,verbose)
# read table structure
if status == 0:
table, status = kepio.readfitstab(infile,instr[1],logfile,verbose)
# filter input data table
if status == 0:
try:
datac = table.field(datacol)
except:
message = 'ERROR -- KEPFLATTEN: cannot find or read data column ' + datacol
status = kepmsg.err(logfile,message,verbose)
if status == 0:
try:
err = table.field(errcol)
except:
message = 'WARNING -- KEPFLATTEN: cannot find or read error column ' + errcol
errcol = 'None'
if status == 0:
if errcol.lower() == 'none' or errcol == 'PSF_FLUX_ERR':
err = datac * cadence
err = numpy.sqrt(numpy.abs(err)) / cadence
work1 = numpy.array([table.field('time'), datac, err])
else:
work1 = numpy.array([table.field('time'), datac, err])
work1 = numpy.rot90(work1,3)
work1 = work1[~numpy.isnan(work1).any(1)]
# read table columns
if status == 0:
intime = work1[:,2] + bjdref
indata = work1[:,1]
inerr = work1[:,0]
if len(intime) == 0:
message = 'ERROR -- KEPFLATTEN: one of the input arrays is all NaN'
status = kepmsg.err(logfile,message,verbose)
# time ranges for region to be corrected
if status == 0:
t1, t2, status = kepio.timeranges(ranges,logfile,verbose)
cadencelis, status = kepstat.filterOnRange(intime,t1,t2)
# find limits of each time step
if status == 0:
tstep1 = []; tstep2 = []
work = intime[0]
while work <= intime[-1]:
tstep1.append(work)
tstep2.append(array([work+winsize,intime[-1]],dtype='float64').min())
work += stepsize
# find cadence limits of each time step
if status == 0:
cstep1 = []; cstep2 = []
for n in range(len(tstep1)):
for i in range(len(intime)-1):
if intime[i] <= tstep1[n] and intime[i+1] > tstep1[n]:
for j in range(i,len(intime)-1):
if intime[j] < tstep2[n] and intime[j+1] >= tstep2[n]:
cstep1.append(i)
cstep2.append(j+1)
# comment keyword in output file
if status == 0:
status = kepkey.history(call,instr[0],outfile,logfile,verbose)
# clean up x-axis unit
if status == 0:
intime0 = float(int(tstart / 100) * 100.0)
ptime = intime - intime0
xlab = 'BJD $-$ %d' % intime0
# clean up y-axis units
if status == 0:
pout = copy(indata)
nrm = len(str(int(pout.max())))-1
pout = pout / 10**nrm
ylab = '10$^%d$ e$^-$ s$^{-1}$' % nrm
# data limits
xmin = ptime.min()
xmax = ptime.max()
ymin = pout.min()
ymax = pout.max()
xr = xmax - xmin
yr = ymax - ymin
ptime = insert(ptime,[0],[ptime[0]])
ptime = append(ptime,[ptime[-1]])
pout = insert(pout,[0],[0.0])
pout = append(pout,0.0)
# plot light curve
if status == 0 and plot:
plotLatex = True
try:
params = {'backend': 'png',
'axes.linewidth': 2.5,
'axes.labelsize': labelsize,
'axes.font': 'sans-serif',
'axes.fontweight' : 'bold',
'text.fontsize': 12,
'legend.fontsize': 12,
'xtick.labelsize': ticksize,
'ytick.labelsize': ticksize}
rcParams.update(params)
except:
plotLatex = False
if status == 0 and plot:
pylab.figure(figsize=[xsize,ysize])
pylab.clf()
# plot data
ax = pylab.axes([0.06,0.54,0.93,0.43])
# force tick labels to be absolute rather than relative
pylab.gca().xaxis.set_major_formatter(pylab.ScalarFormatter(useOffset=False))
pylab.gca().yaxis.set_major_formatter(pylab.ScalarFormatter(useOffset=False))
# rotate y labels by 90 deg
labels = ax.get_yticklabels()
pylab.setp(labels, 'rotation', 90)
pylab.setp(pylab.gca(),xticklabels=[])
pylab.plot(ptime[1:-1],pout[1:-1],color=lcolor,linestyle='-',linewidth=lwidth)
pylab.fill(ptime,pout,color=fcolor,linewidth=0.0,alpha=falpha)
if not plotLatex:
ylab = '10**%d electrons/sec' % nrm
ylabel(ylab, {'color' : 'k'})
grid()
# loop over each time step, fit data, determine rms
if status == 0:
fitarray = numpy.zeros((len(indata),len(cstep1)),dtype='float32')
sigarray = numpy.zeros((len(indata),len(cstep1)),dtype='float32')
fitarray[:,:] = numpy.nan
sigarray[:,:] = numpy.nan
masterfit = indata * 0.0
mastersigma = numpy.zeros(len(masterfit))
functype = 'poly' + str(npoly)
for i in range(len(cstep1)):
timeSeries = intime[cstep1[i]:cstep2[i]+1]-intime[cstep1[i]]
dataSeries = indata[cstep1[i]:cstep2[i]+1]
fitTimeSeries = numpy.array([],dtype='float32')
fitDataSeries = numpy.array([],dtype='float32')
pinit = [dataSeries.mean()]
if npoly > 0:
for j in range(npoly):
pinit.append(0.0)
pinit = array(pinit,dtype='float32')
try:
if len(fitarray[cstep1[i]:cstep2[i]+1,i]) > len(pinit):
coeffs, errors, covar, iiter, sigma, chi2, dof, fit, plotx, ploty, status = \
kepfit.lsqclip(functype,pinit,timeSeries,dataSeries,None,nsig,nsig,niter,
logfile,verbose)
fitarray[cstep1[i]:cstep2[i]+1,i] = 0.0
sigarray[cstep1[i]:cstep2[i]+1,i] = sigma
for j in range(len(coeffs)):
fitarray[cstep1[i]:cstep2[i]+1,i] += coeffs[j] * timeSeries**j
except:
for j in range(cstep1[i],cstep2[i]+1):
fitarray[cstep1[i]:cstep2[i]+1,i] = 0.0
sigarray[cstep1[i]:cstep2[i]+1,i] = 1.0e-10
message = 'WARNING -- KEPFLATTEN: could not fit range '
message += str(intime[cstep1[i]]) + '-' + str(intime[cstep2[i]])
kepmsg.warn(None,message)
# find mean fit for each timestamp
if status == 0:
for i in range(len(indata)):
masterfit[i] = scipy.stats.nanmean(fitarray[i,:])
mastersigma[i] = scipy.stats.nanmean(sigarray[i,:])
masterfit[-1] = masterfit[-4] #fudge
masterfit[-2] = masterfit[-4] #fudge
masterfit[-3] = masterfit[-4] #fudge
pylab.plot(intime-intime0, masterfit / 10**nrm,'g',lw='3')
# reject outliers
if status == 0:
rejtime = []; rejdata = []; naxis2 = 0
for i in range(len(masterfit)):
if abs(indata[i] - masterfit[i]) > nsig * mastersigma[i] and i in cadencelis:
rejtime.append(intime[i])
rejdata.append(indata[i])
rejtime = array(rejtime,dtype='float64')
rejdata = array(rejdata,dtype='float32')
if plot:
pylab.plot(rejtime-intime0,rejdata / 10**nrm,'ro')
# new data for output file
if status == 0:
outdata = indata / masterfit
outerr = inerr / masterfit
# plot ranges
if status == 0 and plot:
pylab.xlim(xmin-xr*0.01,xmax+xr*0.01)
if ymin >= 0.0:
pylab.ylim(ymin-yr*0.01,ymax+yr*0.01)
else:
pylab.ylim(1.0e-10,ymax+yr*0.01)
# plot residual data
if status == 0 and plot:
ax = pylab.axes([0.06,0.09,0.93,0.43])
# force tick labels to be absolute rather than relative
if status == 0 and plot:
pylab.gca().xaxis.set_major_formatter(pylab.ScalarFormatter(useOffset=False))
pylab.gca().yaxis.set_major_formatter(pylab.ScalarFormatter(useOffset=False))
# rotate y labels by 90 deg
labels = ax.get_yticklabels()
setp(labels, 'rotation', 90)
# clean up y-axis units
if status == 0:
pout = copy(outdata)
ylab = 'Normalized Flux'
# data limits
if status == 0 and plot:
ymin = pout.min()
ymax = pout.max()
yr = ymax - ymin
pout = insert(pout,[0],[0.0])
pout = append(pout,0.0)
pylab.plot(ptime[1:-1],pout[1:-1],color=lcolor,linestyle='-',linewidth=lwidth)
pylab.fill(ptime,pout,color=fcolor,linewidth=0.0,alpha=falpha)
pylab.xlabel(xlab, {'color' : 'k'})
pylab.ylabel(ylab, {'color' : 'k'})
pylab.grid()
# plot ranges
if status == 0 and plot:
pylab.xlim(xmin-xr*0.01,xmax+xr*0.01)
if ymin >= 0.0:
pylab.ylim(ymin-yr*0.01,ymax+yr*0.01)
else:
pylab.ylim(1.0e-10,ymax+yr*0.01)
# render plot
if status == 0 and plot:
pylab.savefig(re.sub('.fits','.png',outfile))
if cmdLine:
pylab.show(block=True)
else:
pylab.ion()
pylab.plot([])
pylab.ioff()
# add NaNs back into data
if status == 0:
n = 0
work1 = array([],dtype='float32')
work2 = array([],dtype='float32')
instr, status = kepio.openfits(infile,'readonly',logfile,verbose)
table, status = kepio.readfitstab(infile,instr[1],logfile,verbose)
tn = table.field('time')
dn = table.field(datacol)
for i in range(len(table.field(0))):
if numpy.isfinite(tn[i]) and numpy.isfinite(dn[i]) and numpy.isfinite(err[i]):
try:
work1 = numpy.append(work1,outdata[n])
work2 = numpy.append(work2,outerr[n])
n += 1
except:
pass
else:
work1 = numpy.append(work1,numpy.nan)
work2 = numpy.append(work2,numpy.nan)
# history keyword in output file
if status == 0:
status = kepkey.history(call,instr[0],outfile,logfile,verbose)
# write output file
try:
col1 = pyfits.Column(name='DETSAP_FLUX',format='E13.7',array=work1)
col2 = pyfits.Column(name='DETSAP_FLUX_ERR',format='E13.7',array=work2)
cols = instr[1].data.columns + col1 + col2
instr[1] = pyfits.new_table(cols,header=instr[1].header)
instr.writeto(outfile)
except ValueError:
try:
instr[1].data.field('DETSAP_FLUX')[:] = work1
instr[1].data.field('DETSAP_FLUX_ERR')[:] = work2
instr.writeto(outfile)
except:
message = 'ERROR -- KEPFLATTEN: cannot add DETSAP_FLUX data to FITS file'
status = kepmsg.err(logfile,message,verbose)
# close input file
if status == 0:
status = kepio.closefits(instr,logfile,verbose)
## end time
if (status == 0):
message = 'KEPFLATTEN completed at'
else:
message = '\nKEPFLATTEN aborted at'
kepmsg.clock(message,logfile,verbose)
def getWCSs(file,struct,logfile,verbose):
status = 0
crpix1 = 0.0
crpix2 = 0.0
crval1 = 0.0
crval2 = 0.0
cdelt1 = 0.0
cdelt2 = 0.0
pc = [0.0,0.0,0.0,0.0]
try:
crpix1, status = get(file,struct,'CRPIX1',logfile,verbose)
except:
txt = 'WARNING -- KEPKEY.GETWCSS: Cannot read keyword CRPIX1 in file ' + file
kepmsg.warn(logfile,txt)
status = 1
try:
crpix2, status = get(file,struct,'CRPIX2',logfile,verbose)
except:
txt = 'WARNING -- KEPKEY.GETWCSS: Cannot read keyword CRPIX2 in file ' + file
kepmsg.warn(logfile,txt)
status = 1
try:
crval1, status = get(file,struct,'CRVAL1',logfile,verbose)
except:
txt = 'WARNING -- KEPKEY.GETWCSS: Cannot read keyword CRVAL1 in file ' + file
kepmsg.warn(logfile,txt)
status = 1
try:
crval2, status = get(file,struct,'CRVAL2',logfile,verbose)
except:
txt = 'WARNING -- KEPKEY.GETWCSS: Cannot read keyword CRVAL2 in file ' + file
kepmsg.warn(logfile,txt)
status = 1
try:
cdelt1, status = get(file,struct,'CDELT1',logfile,verbose)
except:
txt = 'WARNING -- KEPKEY.GETWCSS: Cannot read keyword CDELT1 in file ' + file
kepmsg.warn(logfile,txt)
status = 1
try:
cdelt2, status = get(file,struct,'CDELT2',logfile,verbose)
except:
txt = 'WARNING -- KEPKEY.GETWCSS: Cannot read keyword CDELT2 in file ' + file
kepmsg.warn(logfile,txt)
status = 1
try:
pc1_1, status = get(file,struct,'PC1_1',logfile,verbose)
except:
txt = 'WARNING -- KEPKEY.GETWCSS: Cannot read keyword PC1_1 in file ' + file
kepmsg.warn(logfile,txt)
status = 1
try:
pc1_2, status = get(file,struct,'PC1_2',logfile,verbose)
except:
txt = 'WARNING -- KEPKEY.GETWCSS: Cannot read keyword PC1_2 in file ' + file
kepmsg.warn(logfile,txt)
status = 1
try:
pc2_1, status = get(file,struct,'PC2_1',logfile,verbose)
except:
txt = 'WARNING -- KEPKEY.GETWCSS: Cannot read keyword PC2_1 in file ' + file
kepmsg.warn(logfile,txt)
status = 1
try:
pc2_2, status = get(file,struct,'PC2_2',logfile,verbose)
except:
txt = 'WARNING -- KEPKEY.GETWCSS: Cannot read keyword PC2_2 in file ' + file
kepmsg.warn(logfile,txt)
status = 1
try:
pc = numpy.array([[pc1_1,pc1_2],[pc2_1,pc2_2]])
pc = numpy.linalg.inv(pc)
except:
pass
return crpix1, crpix2, crval1, crval2, cdelt1, cdelt2, pc, status
def kepstitch(infiles,outfile,clobber,verbose,logfile,status):
# startup parameters
status = 0
lct = []; bjd = []
# log the call
hashline = '----------------------------------------------------------------------------'
kepmsg.log(logfile,hashline,verbose)
call = 'KEPSTITCH -- '
call += 'infiles='+infiles+' '
call += 'outfile='+outfile+' '
overwrite = 'n'
if (clobber): overwrite = 'y'
call += 'clobber='+overwrite+ ' '
chatter = 'n'
if (verbose): chatter = 'y'
call += 'verbose='+chatter+' '
call += 'logfile='+logfile
kepmsg.log(logfile,call+'\n',verbose)
# start time
kepmsg.clock('KEPSTITCH started at',logfile,verbose)
# test log file
logfile = kepmsg.test(logfile)
# parse input file list
infiles, status = kepio.parselist(infiles,logfile,verbose)
# clobber output file
if clobber: status = kepio.clobber(outfile,logfile,verbose)
if kepio.fileexists(outfile):
message = 'ERROR -- KEPSTITCH: ' + outfile + ' exists. Use clobber=yes'
kepmsg.err(logfile,message,verbose)
status = 1
# open output file
if status == 0:
outstr, status = kepio.openfits(infiles[0],'readonly',logfile,verbose)
nrows1 = outstr[1].data.shape[0]
# fudge non-compliant FITS keywords with no values
if status == 0:
outstr = kepkey.emptykeys(outstr,file,logfile,verbose)
head0 = outstr[0].header
head1 = outstr[1].header
# open input files
nfiles = 0
if status == 0:
for infile in infiles:
instr, status = kepio.openfits(infile,'readonly',logfile,verbose)
# append table data
if nfiles > 0:
nrows2 = instr[1].data.shape[0]
nrows = nrows1 + nrows2
outtab = pyfits.new_table(outstr[1].columns,nrows=nrows)
for name in outstr[1].columns.names:
try:
outtab.data.field(name)[nrows1:]=instr[1].data.field(name)
except:
message = 'ERROR -- KEPSTITCH: column ' + name + ' missing from some files.'
kepmsg.warn(logfile,message)
pass
outstr[1] = outtab
outstr[0].header = head0
outstr[1].header = head1
nrows1 = nrows
# start and stop times of data
fitsvers = 1.0
lc_start, status = kepkey.get(infile,instr[1],'LC_START',logfile,verbose)
lc_end, status = kepkey.get(infile,instr[1],'LC_END',logfile,verbose)
try:
startbjd = instr[1].header['STARTBJD']
except:
startbjd, status = kepkey.get(infile,instr[1],'TSTART',logfile,verbose)
fitsvers = 2.0
try:
endbjd = instr[1].header['ENDBJD']
except:
endbjd, status = kepkey.get(infile,instr[1],'TSTOP',logfile,verbose)
fitsvers = 2.0
lct.append(lc_start); lct.append(lc_end)
bjd.append(startbjd); bjd.append(endbjd)
# close input files
status = kepio.closefits(instr,logfile,verbose)
nfiles += 1
# maxmimum and minimum times in file sample
if status == 0:
lc_start = kepstat.min(lct)
lc_end = kepstat.max(lct)
startbjd = kepstat.min(bjd)
endbjd = kepstat.max(bjd)
status = kepkey.change('LC_START',lc_start,outstr[1],outfile,logfile,verbose)
status = kepkey.change('LC_END',lc_end,outstr[1],outfile,logfile,verbose)
if fitsvers == 1.0:
status = kepkey.change('STARTBJD',startbjd,outstr[1],outfile,logfile,verbose)
status = kepkey.change('ENDBJD',endbjd,outstr[1],outfile,logfile,verbose)
else:
status = kepkey.change('TSTART',startbjd,outstr[1],outfile,logfile,verbose)
status = kepkey.change('TSTOP',endbjd,outstr[1],outfile,logfile,verbose)
# comment keyword in output file
if status == 0:
status = kepkey.comment(call,outstr[0],outfile,logfile,verbose)
# close output file
if status == 0:
outstr.writeto(outfile)
status = kepio.closefits(outstr,logfile,verbose)
## end time
if (status == 0):
message = 'KEPSTITCH completed at'
else:
message = '\nKEPSTITCH aborted at'
kepmsg.clock(message,logfile,verbose)
def kepbls(infile,outfile,datacol,errcol,minper,maxper,mindur,maxdur,nsearch,
nbins,plot,clobber,verbose,logfile,status,cmdLine=False):
# startup parameters
numpy.seterr(all="ignore")
status = 0
labelsize = 32
ticksize = 18
xsize = 16
ysize = 8
lcolor = '#0000ff'
lwidth = 1.0
fcolor = '#ffff00'
falpha = 0.2
# log the call
hashline = '----------------------------------------------------------------------------'
kepmsg.log(logfile,hashline,verbose)
call = 'KEPBLS -- '
call += 'infile='+infile+' '
call += 'outfile='+outfile+' '
call += 'datacol='+str(datacol)+' '
call += 'errcol='+str(errcol)+' '
call += 'minper='+str(minper)+' '
call += 'maxper='+str(maxper)+' '
call += 'mindur='+str(mindur)+' '
call += 'maxdur='+str(maxdur)+' '
call += 'nsearch='+str(nsearch)+' '
call += 'nbins='+str(nbins)+' '
plotit = 'n'
if (plot): plotit = 'y'
call += 'plot='+plotit+ ' '
overwrite = 'n'
if (clobber): overwrite = 'y'
call += 'clobber='+overwrite+ ' '
chatter = 'n'
if (verbose): chatter = 'y'
call += 'verbose='+chatter+' '
call += 'logfile='+logfile
kepmsg.log(logfile,call+'\n',verbose)
# start time
kepmsg.clock('KEPBLS started at',logfile,verbose)
# is duration greater than one bin in the phased light curve?
if float(nbins) * maxdur / 24.0 / maxper <= 1.0:
message = 'WARNING -- KEPBLS: ' + str(maxdur) + ' hours transit duration < 1 phase bin when P = '
message += str(maxper) + ' days'
kepmsg.warn(logfile,message)
# test log file
logfile = kepmsg.test(logfile)
# clobber output file
if clobber: status = kepio.clobber(outfile,logfile,verbose)
if kepio.fileexists(outfile):
message = 'ERROR -- KEPBLS: ' + outfile + ' exists. Use clobber=yes'
status = kepmsg.err(logfile,message,verbose)
# open input file
if status == 0:
instr, status = kepio.openfits(infile,'readonly',logfile,verbose)
if status == 0:
tstart, tstop, bjdref, cadence, status = kepio.timekeys(instr,infile,logfile,verbose,status)
# fudge non-compliant FITS keywords with no values
if status == 0:
instr = kepkey.emptykeys(instr,file,logfile,verbose)
# read table structure
if status == 0:
table, status = kepio.readfitstab(infile,instr[1],logfile,verbose)
# filter input data table
if status == 0:
work1 = numpy.array([table.field('time'), table.field(datacol), table.field(errcol)])
work1 = numpy.rot90(work1,3)
work1 = work1[~numpy.isnan(work1).any(1)]
# read table columns
if status == 0:
intime = work1[:,2] + bjdref
indata = work1[:,1]
inerr = work1[:,0]
# test whether the period range is sensible
if status == 0:
tr = intime[-1] - intime[0]
if maxper > tr:
message = 'ERROR -- KEPBLS: maxper is larger than the time range of the input data'
status = kepmsg.err(logfile,message,verbose)
# prepare time series
if status == 0:
work1 = intime - intime[0]
work2 = indata - numpy.mean(indata)
# start period search
if status == 0:
srMax = numpy.array([],dtype='float32')
transitDuration = numpy.array([],dtype='float32')
transitPhase = numpy.array([],dtype='float32')
dPeriod = (maxper - minper) / nsearch
trialPeriods = numpy.arange(minper,maxper+dPeriod,dPeriod,dtype='float32')
complete = 0
print ' '
for trialPeriod in trialPeriods:
fracComplete = float(complete) / float(len(trialPeriods) - 1) * 100.0
txt = '\r'
txt += 'Trial period = '
txt += str(int(trialPeriod))
txt += ' days ['
txt += str(int(fracComplete))
txt += '% complete]'
txt += ' ' * 20
sys.stdout.write(txt)
sys.stdout.flush()
complete += 1
srMax = numpy.append(srMax,0.0)
transitDuration = numpy.append(transitDuration,numpy.nan)
transitPhase = numpy.append(transitPhase,numpy.nan)
trialFrequency = 1.0 / trialPeriod
# minimum and maximum transit durations in quantized phase units
duration1 = max(int(float(nbins) * mindur / 24.0 / trialPeriod),2)
duration2 = max(int(float(nbins) * maxdur / 24.0 / trialPeriod) + 1,duration1 + 1)
# 30 minutes in quantized phase units
halfHour = int(0.02083333 / trialPeriod * nbins + 1)
# compute folded time series with trial period
work4 = numpy.zeros((nbins),dtype='float32')
work5 = numpy.zeros((nbins),dtype='float32')
phase = numpy.array(((work1 * trialFrequency) - numpy.floor(work1 * trialFrequency)) * float(nbins),dtype='int')
ptuple = numpy.array([phase, work2, inerr])
ptuple = numpy.rot90(ptuple,3)
phsort = numpy.array(sorted(ptuple,key=lambda ph: ph[2]))
for i in range(nbins):
elements = numpy.nonzero(phsort[:,2] == float(i))[0]
work4[i] = numpy.mean(phsort[elements,1])
work5[i] = math.sqrt(numpy.sum(numpy.power(phsort[elements,0], 2)) / len(elements))
# extend the work arrays beyond nbins by wrapping
work4 = numpy.append(work4,work4[:duration2])
work5 = numpy.append(work5,work5[:duration2])
# calculate weights of folded light curve points
sigmaSum = numpy.nansum(numpy.power(work5,-2))
omega = numpy.power(work5,-2) / sigmaSum
# calculate weighted phased light curve
s = omega * work4
# iterate through trial period phase
for i1 in range(nbins):
# iterate through transit durations
for duration in range(duration1,duration2+1,int(halfHour)):
# calculate maximum signal residue
i2 = i1 + duration
sr1 = numpy.sum(numpy.power(s[i1:i2],2))
sr2 = numpy.sum(omega[i1:i2])
sr = math.sqrt(sr1 / (sr2 * (1.0 - sr2)))
if sr > srMax[-1]:
srMax[-1] = sr
transitDuration[-1] = float(duration)
transitPhase[-1] = float((i1 + i2) / 2)
# normalize maximum signal residue curve
bestSr = numpy.max(srMax)
bestTrial = numpy.nonzero(srMax == bestSr)[0][0]
srMax /= bestSr
transitDuration *= trialPeriods / 24.0
BJD0 = numpy.array(transitPhase * trialPeriods / nbins,dtype='float64') + intime[0] - 2454833.0
print '\n'
# clean up x-axis unit
if status == 0:
ptime = copy(trialPeriods)
xlab = 'Trial Period (days)'
# clean up y-axis units
if status == 0:
pout = copy(srMax)
ylab = 'Normalized Signal Residue'
# data limits
xmin = ptime.min()
xmax = ptime.max()
ymin = pout.min()
ymax = pout.max()
xr = xmax - xmin
yr = ymax - ymin
ptime = insert(ptime,[0],[ptime[0]])
ptime = append(ptime,[ptime[-1]])
pout = insert(pout,[0],[0.0])
pout = append(pout,0.0)
# plot light curve
if status == 0 and plot:
plotLatex = True
try:
params = {'backend': 'png',
'axes.linewidth': 2.5,
'axes.labelsize': labelsize,
'axes.font': 'sans-serif',
'axes.fontweight' : 'bold',
'text.fontsize': 12,
'legend.fontsize': 12,
'xtick.labelsize': ticksize,
'ytick.labelsize': ticksize}
rcParams.update(params)
except:
plotLatex = False
if status == 0 and plot:
pylab.figure(figsize=[xsize,ysize])
pylab.clf()
# plot data
ax = pylab.axes([0.06,0.10,0.93,0.87])
# force tick labels to be absolute rather than relative
pylab.gca().xaxis.set_major_formatter(pylab.ScalarFormatter(useOffset=False))
pylab.gca().yaxis.set_major_formatter(pylab.ScalarFormatter(useOffset=False))
# rotate y labels by 90 deg
labels = ax.get_yticklabels()
pylab.setp(labels, 'rotation', 90)
# plot curve
if status == 0 and plot:
pylab.plot(ptime[1:-1],pout[1:-1],color=lcolor,linestyle='-',linewidth=lwidth)
pylab.fill(ptime,pout,color=fcolor,linewidth=0.0,alpha=falpha)
pylab.xlabel(xlab, {'color' : 'k'})
pylab.ylabel(ylab, {'color' : 'k'})
pylab.grid()
# plot ranges
if status == 0 and plot:
pylab.xlim(xmin-xr*0.01,xmax+xr*0.01)
if ymin >= 0.0:
pylab.ylim(ymin-yr*0.01,ymax+yr*0.01)
else:
pylab.ylim(1.0e-10,ymax+yr*0.01)
# render plot
if status == 0 and plot:
if cmdLine:
pylab.show()
else:
pylab.ion()
pylab.plot([])
pylab.ioff()
# append new BLS data extension to the output file
if status == 0:
col1 = Column(name='PERIOD',format='E',unit='days',array=trialPeriods)
col2 = Column(name='BJD0',format='D',unit='BJD - 2454833',array=BJD0)
col3 = Column(name='DURATION',format='E',unit='hours',array=transitDuration)
col4 = Column(name='SIG_RES',format='E',array=srMax)
cols = ColDefs([col1,col2,col3,col4])
instr.append(new_table(cols))
instr[-1].header.cards['TTYPE1'].comment = 'column title: trial period'
instr[-1].header.cards['TTYPE2'].comment = 'column title: trial mid-transit zero-point'
instr[-1].header.cards['TTYPE3'].comment = 'column title: trial transit duration'
instr[-1].header.cards['TTYPE4'].comment = 'column title: normalized signal residue'
instr[-1].header.cards['TFORM1'].comment = 'column type: float32'
instr[-1].header.cards['TFORM2'].comment = 'column type: float64'
instr[-1].header.cards['TFORM3'].comment = 'column type: float32'
instr[-1].header.cards['TFORM4'].comment = 'column type: float32'
instr[-1].header.cards['TUNIT1'].comment = 'column units: days'
instr[-1].header.cards['TUNIT2'].comment = 'column units: BJD - 2454833'
instr[-1].header.cards['TUNIT3'].comment = 'column units: hours'
instr[-1].header.update('EXTNAME','BLS','extension name')
instr[-1].header.update('PERIOD',trialPeriods[bestTrial],'most significant trial period [d]')
instr[-1].header.update('BJD0',BJD0[bestTrial] + 2454833.0,'time of mid-transit [BJD]')
instr[-1].header.update('TRANSDUR',transitDuration[bestTrial],'transit duration [hours]')
instr[-1].header.update('SIGNRES',srMax[bestTrial] * bestSr,'maximum signal residue')
# history keyword in output file
if status == 0:
status = kepkey.history(call,instr[0],outfile,logfile,verbose)
instr.writeto(outfile)
# close input file
if status == 0:
status = kepio.closefits(instr,logfile,verbose)
# print best trial period results
if status == 0:
print ' Best trial period = %.5f days' % trialPeriods[bestTrial]
print ' Time of mid-transit = BJD %.5f' % (BJD0[bestTrial] + 2454833.0)
print ' Transit duration = %.5f hours' % transitDuration[bestTrial]
print ' Maximum signal residue = %.4g \n' % (srMax[bestTrial] * bestSr)
# end time
if (status == 0):
message = 'KEPBLS completed at'
else:
message = '\nKEPBLS aborted at'
kepmsg.clock(message,logfile,verbose)
def lsqclip(functype,pinit,x,y,yerr,rej_lo,rej_hi,niter,logfile,verbose):
# functype = unctional form
# pinit = initial guess for parameters
# x = list of x data
# y = list of y data
# yerr = list of 1-sigma y errors
# order = polynomial order
# rej_lo = lower rejection threshold (units=sigma)
# rej_hi = upper rejection threshold (units=sugma)
# niter = number of sigma-clipping iterations
npts = []
iiter = 0
iterstatus = 1
status = 0
# error catching
if (len(x) == 0):
status = kepmsg.exit('ERROR -- KEPFIT.LSQCLIP: x data array is empty')
if (len(y) == 0):
status = kepmsg.exit('ERROR -- KEPFIT.LSQCLIP: y data array is empty')
if (len(x) < len(pinit)):
kepmsg.warn(logfile,'WARNING -- KEPFIT.LSQCLIP: no degrees of freedom')
# sigma-clipping iterations
while (iiter < niter and len(x) > len(pinit) and iterstatus > 0):
iterstatus = 0
tmpx = []
tmpy = []
tmpyerr = []
npts.append(len(x))
coeffs,errors,covar,sigma,chi2,dof,fit,plotx,ploty,status = \
leastsquare(functype,pinit,x,y,yerr,logfile,verbose)
pinit = coeffs
# point-by-point sigma-clipping test
for ix in range(npts[iiter]):
if (y[ix] - fit[ix] < rej_hi * sigma and
fit[ix] - y[ix] < rej_lo * sigma):
tmpx.append(x[ix])
tmpy.append(y[ix])
if (yerr != None): tmpyerr.append(yerr[ix])
else:
iterstatus = 1
x = scipy.array(tmpx)
y = scipy.array(tmpy)
if (yerr != None): yerr = scipy.array(tmpyerr)
iiter += 1
# fudge scalar models
# for i in range(len(plotx)):
# coeffs = best fit coefficients
# covar = covariance matrix
# iiter = number of sigma clipping iteration before convergence
return coeffs, errors, covar, iiter, sigma, chi2, dof, fit, plotx, ploty, status
def kepfold(infile,
outfile,
period,
phasezero,
bindata,
binmethod,
threshold,
niter,
nbins,
rejqual,
plottype,
plotlab,
clobber,
verbose,
logfile,
status,
cmdLine=False):
# startup parameters
status = 0
labelsize = 32
ticksize = 18
xsize = 18
ysize = 10
lcolor = '#0000ff'
lwidth = 2.0
fcolor = '#ffff00'
falpha = 0.2
# log the call
hashline = '----------------------------------------------------------------------------'
kepmsg.log(logfile, hashline, verbose)
call = 'KEPFOLD -- '
call += 'infile=' + infile + ' '
call += 'outfile=' + outfile + ' '
call += 'period=' + str(period) + ' '
call += 'phasezero=' + str(phasezero) + ' '
binit = 'n'
if (bindata): binit = 'y'
call += 'bindata=' + binit + ' '
call += 'binmethod=' + binmethod + ' '
call += 'threshold=' + str(threshold) + ' '
call += 'niter=' + str(niter) + ' '
call += 'nbins=' + str(nbins) + ' '
qflag = 'n'
if (rejqual): qflag = 'y'
call += 'rejqual=' + qflag + ' '
call += 'plottype=' + plottype + ' '
call += 'plotlab=' + plotlab + ' '
overwrite = 'n'
if (clobber): overwrite = 'y'
call += 'clobber=' + overwrite + ' '
chatter = 'n'
if (verbose): chatter = 'y'
call += 'verbose=' + chatter + ' '
call += 'logfile=' + logfile
kepmsg.log(logfile, call + '\n', verbose)
# start time
kepmsg.clock('KEPFOLD started at', logfile, verbose)
# test log file
logfile = kepmsg.test(logfile)
# clobber output file
if clobber: status = kepio.clobber(outfile, logfile, verbose)
if kepio.fileexists(outfile):
message = 'ERROR -- KEPFOLD: ' + outfile + ' exists. Use --clobber'
status = kepmsg.err(logfile, message, verbose)
# open input file
if status == 0:
instr, status = kepio.openfits(infile, 'readonly', logfile, verbose)
if status == 0:
tstart, tstop, bjdref, cadence, status = kepio.timekeys(
instr, infile, logfile, verbose, status)
if status == 0:
try:
work = instr[0].header['FILEVER']
cadenom = 1.0
except:
cadenom = cadence
# fudge non-compliant FITS keywords with no values
if status == 0:
instr = kepkey.emptykeys(instr, file, logfile, verbose)
# input data
if status == 0:
table = instr[1].data
incards = instr[1].header.cards
try:
sap = instr[1].data.field('SAP_FLUX')
except:
try:
sap = instr[1].data.field('ap_raw_flux')
except:
sap = zeros(len(table.field(0)))
try:
saperr = instr[1].data.field('SAP_FLUX_ERR')
except:
try:
saperr = instr[1].data.field('ap_raw_err')
except:
saperr = zeros(len(table.field(0)))
try:
pdc = instr[1].data.field('PDCSAP_FLUX')
except:
try:
pdc = instr[1].data.field('ap_corr_flux')
except:
pdc = zeros(len(table.field(0)))
try:
pdcerr = instr[1].data.field('PDCSAP_FLUX_ERR')
except:
try:
pdcerr = instr[1].data.field('ap_corr_err')
except:
pdcerr = zeros(len(table.field(0)))
try:
cbv = instr[1].data.field('CBVSAP_FLUX')
except:
cbv = zeros(len(table.field(0)))
if 'cbv' in plottype:
txt = 'ERROR -- KEPFOLD: CBVSAP_FLUX column is not populated. Use kepcotrend'
status = kepmsg.err(logfile, txt, verbose)
try:
det = instr[1].data.field('DETSAP_FLUX')
except:
det = zeros(len(table.field(0)))
if 'det' in plottype:
txt = 'ERROR -- KEPFOLD: DETSAP_FLUX column is not populated. Use kepflatten'
status = kepmsg.err(logfile, txt, verbose)
try:
deterr = instr[1].data.field('DETSAP_FLUX_ERR')
except:
deterr = zeros(len(table.field(0)))
if 'det' in plottype:
txt = 'ERROR -- KEPFOLD: DETSAP_FLUX_ERR column is not populated. Use kepflatten'
status = kepmsg.err(logfile, txt, verbose)
try:
quality = instr[1].data.field('SAP_QUALITY')
except:
quality = zeros(len(table.field(0)))
if qualflag:
txt = 'WARNING -- KEPFOLD: Cannot find a QUALITY data column'
kepmsg.warn(logfile, txt)
if status == 0:
barytime, status = kepio.readtimecol(infile, table, logfile, verbose)
barytime1 = copy(barytime)
# filter out NaNs and quality > 0
work1 = []
work2 = []
work3 = []
work4 = []
work5 = []
work6 = []
work8 = []
work9 = []
if status == 0:
if 'sap' in plottype:
datacol = copy(sap)
errcol = copy(saperr)
if 'pdc' in plottype:
datacol = copy(pdc)
errcol = copy(pdcerr)
if 'cbv' in plottype:
datacol = copy(cbv)
errcol = copy(saperr)
if 'det' in plottype:
datacol = copy(det)
errcol = copy(deterr)
for i in range(len(barytime)):
if (numpy.isfinite(barytime[i]) and numpy.isfinite(datacol[i])
and datacol[i] != 0.0 and numpy.isfinite(errcol[i])
and errcol[i] > 0.0):
if rejqual and quality[i] == 0:
work1.append(barytime[i])
work2.append(sap[i])
work3.append(saperr[i])
work4.append(pdc[i])
work5.append(pdcerr[i])
work6.append(cbv[i])
work8.append(det[i])
work9.append(deterr[i])
elif not rejqual:
work1.append(barytime[i])
work2.append(sap[i])
work3.append(saperr[i])
work4.append(pdc[i])
work5.append(pdcerr[i])
work6.append(cbv[i])
work8.append(det[i])
work9.append(deterr[i])
barytime = array(work1, dtype='float64')
sap = array(work2, dtype='float32') / cadenom
saperr = array(work3, dtype='float32') / cadenom
pdc = array(work4, dtype='float32') / cadenom
pdcerr = array(work5, dtype='float32') / cadenom
cbv = array(work6, dtype='float32') / cadenom
det = array(work8, dtype='float32') / cadenom
deterr = array(work9, dtype='float32') / cadenom
# calculate phase
if status == 0:
if phasezero < bjdref:
phasezero += bjdref
date1 = (barytime1 + bjdref - phasezero)
phase1 = (date1 / period) - floor(date1 / period)
date2 = (barytime + bjdref - phasezero)
phase2 = (date2 / period) - floor(date2 / period)
phase2 = array(phase2, 'float32')
# sort phases
if status == 0:
ptuple = []
phase3 = []
sap3 = []
saperr3 = []
pdc3 = []
pdcerr3 = []
cbv3 = []
cbverr3 = []
det3 = []
deterr3 = []
for i in range(len(phase2)):
ptuple.append([
phase2[i], sap[i], saperr[i], pdc[i], pdcerr[i], cbv[i],
saperr[i], det[i], deterr[i]
])
phsort = sorted(ptuple, key=lambda ph: ph[0])
for i in range(len(phsort)):
phase3.append(phsort[i][0])
sap3.append(phsort[i][1])
saperr3.append(phsort[i][2])
pdc3.append(phsort[i][3])
pdcerr3.append(phsort[i][4])
cbv3.append(phsort[i][5])
cbverr3.append(phsort[i][6])
det3.append(phsort[i][7])
deterr3.append(phsort[i][8])
phase3 = array(phase3, 'float32')
sap3 = array(sap3, 'float32')
saperr3 = array(saperr3, 'float32')
pdc3 = array(pdc3, 'float32')
pdcerr3 = array(pdcerr3, 'float32')
cbv3 = array(cbv3, 'float32')
cbverr3 = array(cbverr3, 'float32')
det3 = array(det3, 'float32')
deterr3 = array(deterr3, 'float32')
# bin phases
if status == 0 and bindata:
work1 = array([sap3[0]], 'float32')
work2 = array([saperr3[0]], 'float32')
work3 = array([pdc3[0]], 'float32')
work4 = array([pdcerr3[0]], 'float32')
work5 = array([cbv3[0]], 'float32')
work6 = array([cbverr3[0]], 'float32')
work7 = array([det3[0]], 'float32')
work8 = array([deterr3[0]], 'float32')
phase4 = array([], 'float32')
sap4 = array([], 'float32')
saperr4 = array([], 'float32')
pdc4 = array([], 'float32')
pdcerr4 = array([], 'float32')
cbv4 = array([], 'float32')
cbverr4 = array([], 'float32')
det4 = array([], 'float32')
deterr4 = array([], 'float32')
dt = 1.0 / nbins
nb = 0.0
rng = numpy.append(phase3, phase3[0] + 1.0)
for i in range(len(rng)):
if rng[i] < nb * dt or rng[i] >= (nb + 1.0) * dt:
if len(work1) > 0:
phase4 = append(phase4, (nb + 0.5) * dt)
if (binmethod == 'mean'):
sap4 = append(sap4, kepstat.mean(work1))
saperr4 = append(saperr4, kepstat.mean_err(work2))
pdc4 = append(pdc4, kepstat.mean(work3))
pdcerr4 = append(pdcerr4, kepstat.mean_err(work4))
cbv4 = append(cbv4, kepstat.mean(work5))
cbverr4 = append(cbverr4, kepstat.mean_err(work6))
det4 = append(det4, kepstat.mean(work7))
deterr4 = append(deterr4, kepstat.mean_err(work8))
elif (binmethod == 'median'):
sap4 = append(sap4, kepstat.median(work1, logfile))
saperr4 = append(saperr4, kepstat.mean_err(work2))
pdc4 = append(pdc4, kepstat.median(work3, logfile))
pdcerr4 = append(pdcerr4, kepstat.mean_err(work4))
cbv4 = append(cbv4, kepstat.median(work5, logfile))
cbverr4 = append(cbverr4, kepstat.mean_err(work6))
det4 = append(det4, kepstat.median(work7, logfile))
deterr4 = append(deterr4, kepstat.mean_err(work8))
else:
coeffs, errors, covar, iiter, sigma, chi2, dof, fit, plotx, ploty, status = \
kepfit.lsqclip('poly0',[scipy.stats.nanmean(work1)],arange(0.0,float(len(work1)),1.0),work1,work2,
threshold,threshold,niter,logfile,False)
sap4 = append(sap4, coeffs[0])
saperr4 = append(saperr4, kepstat.mean_err(work2))
coeffs, errors, covar, iiter, sigma, chi2, dof, fit, plotx, ploty, status = \
kepfit.lsqclip('poly0',[scipy.stats.nanmean(work3)],arange(0.0,float(len(work3)),1.0),work3,work4,
threshold,threshold,niter,logfile,False)
pdc4 = append(pdc4, coeffs[0])
pdcerr4 = append(pdcerr4, kepstat.mean_err(work4))
coeffs, errors, covar, iiter, sigma, chi2, dof, fit, plotx, ploty, status = \
kepfit.lsqclip('poly0',[scipy.stats.nanmean(work5)],arange(0.0,float(len(work5)),1.0),work5,work6,
threshold,threshold,niter,logfile,False)
cbv4 = append(cbv4, coeffs[0])
cbverr4 = append(cbverr4, kepstat.mean_err(work6))
coeffs, errors, covar, iiter, sigma, chi2, dof, fit, plotx, ploty, status = \
kepfit.lsqclip('poly0',[scipy.stats.nanmean(work7)],arange(0.0,float(len(work7)),1.0),work7,work8,
threshold,threshold,niter,logfile,False)
det4 = append(det4, coeffs[0])
deterr4 = append(deterr4, kepstat.mean_err(work8))
work1 = array([], 'float32')
work2 = array([], 'float32')
work3 = array([], 'float32')
work4 = array([], 'float32')
work5 = array([], 'float32')
work6 = array([], 'float32')
work7 = array([], 'float32')
work8 = array([], 'float32')
nb += 1.0
else:
work1 = append(work1, sap3[i])
work2 = append(work2, saperr3[i])
work3 = append(work3, pdc3[i])
work4 = append(work4, pdcerr3[i])
work5 = append(work5, cbv3[i])
work6 = append(work6, cbverr3[i])
work7 = append(work7, det3[i])
work8 = append(work8, deterr3[i])
# update HDU1 for output file
if status == 0:
cols = (instr[1].columns +
ColDefs([Column(name='PHASE', format='E', array=phase1)]))
instr[1] = pyfits.new_table(cols)
instr[1].header.cards[
'TTYPE' +
str(len(instr[1].columns))].comment = 'column title: phase'
instr[1].header.cards[
'TFORM' +
str(len(instr[1].columns))].comment = 'data type: float32'
for i in range(len(incards)):
if incards[i].key not in list(instr[1].header.keys()):
instr[1].header.update(incards[i].key, incards[i].value,
incards[i].comment)
else:
instr[1].header.cards[
incards[i].key].comment = incards[i].comment
instr[1].header.update('PERIOD', period,
'period defining the phase [d]')
instr[1].header.update('BJD0', phasezero, 'time of phase zero [BJD]')
# write new phased data extension for output file
if status == 0 and bindata:
col1 = Column(name='PHASE', format='E', array=phase4)
col2 = Column(name='SAP_FLUX',
format='E',
unit='e/s',
array=sap4 / cadenom)
col3 = Column(name='SAP_FLUX_ERR',
format='E',
unit='e/s',
array=saperr4 / cadenom)
col4 = Column(name='PDC_FLUX',
format='E',
unit='e/s',
array=pdc4 / cadenom)
col5 = Column(name='PDC_FLUX_ERR',
format='E',
unit='e/s',
array=pdcerr4 / cadenom)
col6 = Column(name='CBV_FLUX',
format='E',
unit='e/s',
array=cbv4 / cadenom)
col7 = Column(name='DET_FLUX', format='E', array=det4 / cadenom)
col8 = Column(name='DET_FLUX_ERR', format='E', array=deterr4 / cadenom)
cols = ColDefs([col1, col2, col3, col4, col5, col6, col7, col8])
instr.append(new_table(cols))
instr[-1].header.cards['TTYPE1'].comment = 'column title: phase'
instr[-1].header.cards[
'TTYPE2'].comment = 'column title: simple aperture photometry'
instr[-1].header.cards[
'TTYPE3'].comment = 'column title: SAP 1-sigma error'
instr[-1].header.cards[
'TTYPE4'].comment = 'column title: pipeline conditioned photometry'
instr[-1].header.cards[
'TTYPE5'].comment = 'column title: PDC 1-sigma error'
instr[-1].header.cards[
'TTYPE6'].comment = 'column title: cotrended basis vector photometry'
instr[-1].header.cards[
'TTYPE7'].comment = 'column title: Detrended aperture photometry'
instr[-1].header.cards[
'TTYPE8'].comment = 'column title: DET 1-sigma error'
instr[-1].header.cards['TFORM1'].comment = 'column type: float32'
instr[-1].header.cards['TFORM2'].comment = 'column type: float32'
instr[-1].header.cards['TFORM3'].comment = 'column type: float32'
instr[-1].header.cards['TFORM4'].comment = 'column type: float32'
instr[-1].header.cards['TFORM5'].comment = 'column type: float32'
instr[-1].header.cards['TFORM6'].comment = 'column type: float32'
instr[-1].header.cards['TFORM7'].comment = 'column type: float32'
instr[-1].header.cards['TFORM8'].comment = 'column type: float32'
instr[-1].header.cards[
'TUNIT2'].comment = 'column units: electrons per second'
instr[-1].header.cards[
'TUNIT3'].comment = 'column units: electrons per second'
instr[-1].header.cards[
'TUNIT4'].comment = 'column units: electrons per second'
instr[-1].header.cards[
'TUNIT5'].comment = 'column units: electrons per second'
instr[-1].header.cards[
'TUNIT6'].comment = 'column units: electrons per second'
instr[-1].header.update('EXTNAME', 'FOLDED', 'extension name')
instr[-1].header.update('PERIOD', period,
'period defining the phase [d]')
instr[-1].header.update('BJD0', phasezero, 'time of phase zero [BJD]')
instr[-1].header.update('BINMETHD', binmethod, 'phase binning method')
if binmethod == 'sigclip':
instr[-1].header.update('THRSHOLD', threshold,
'sigma-clipping threshold [sigma]')
instr[-1].header.update('NITER', niter,
'max number of sigma-clipping iterations')
# history keyword in output file
if status == 0:
status = kepkey.history(call, instr[0], outfile, logfile, verbose)
instr.writeto(outfile)
# clean up x-axis unit
if status == 0:
ptime1 = array([], 'float32')
ptime2 = array([], 'float32')
pout1 = array([], 'float32')
pout2 = array([], 'float32')
if bindata:
work = sap4
if plottype == 'pdc':
work = pdc4
if plottype == 'cbv':
work = cbv4
if plottype == 'det':
work = det4
for i in range(len(phase4)):
if (phase4[i] > 0.5):
ptime2 = append(ptime2, phase4[i] - 1.0)
pout2 = append(pout2, work[i])
ptime2 = append(ptime2, phase4)
pout2 = append(pout2, work)
for i in range(len(phase4)):
if (phase4[i] <= 0.5):
ptime2 = append(ptime2, phase4[i] + 1.0)
pout2 = append(pout2, work[i])
work = sap3
if plottype == 'pdc':
work = pdc3
if plottype == 'cbv':
work = cbv3
if plottype == 'det':
work = det3
for i in range(len(phase3)):
if (phase3[i] > 0.5):
ptime1 = append(ptime1, phase3[i] - 1.0)
pout1 = append(pout1, work[i])
ptime1 = append(ptime1, phase3)
pout1 = append(pout1, work)
for i in range(len(phase3)):
if (phase3[i] <= 0.5):
ptime1 = append(ptime1, phase3[i] + 1.0)
pout1 = append(pout1, work[i])
xlab = 'Orbital Phase ($\phi$)'
# clean up y-axis units
if status == 0:
nrm = len(str(int(pout1[isfinite(pout1)].max()))) - 1
pout1 = pout1 / 10**nrm
pout2 = pout2 / 10**nrm
if nrm == 0:
ylab = plotlab
else:
ylab = '10$^%d$ %s' % (nrm, plotlab)
# data limits
xmin = ptime1.min()
xmax = ptime1.max()
ymin = pout1[isfinite(pout1)].min()
ymax = pout1[isfinite(pout1)].max()
xr = xmax - xmin
yr = ymax - ymin
ptime1 = insert(ptime1, [0], [ptime1[0]])
ptime1 = append(ptime1, [ptime1[-1]])
pout1 = insert(pout1, [0], [0.0])
pout1 = append(pout1, 0.0)
if bindata:
ptime2 = insert(ptime2, [0], ptime2[0] - 1.0 / nbins)
ptime2 = insert(ptime2, [0], ptime2[0])
ptime2 = append(
ptime2, [ptime2[-1] + 1.0 / nbins, ptime2[-1] + 1.0 / nbins])
pout2 = insert(pout2, [0], [pout2[-1]])
pout2 = insert(pout2, [0], [0.0])
pout2 = append(pout2, [pout2[2], 0.0])
# plot new light curve
if status == 0 and plottype != 'none':
try:
params = {
'backend': 'png',
'axes.linewidth': 2.5,
'axes.labelsize': labelsize,
'axes.font': 'sans-serif',
'axes.fontweight': 'bold',
'text.fontsize': 18,
'legend.fontsize': 18,
'xtick.labelsize': ticksize,
'ytick.labelsize': ticksize
}
pylab.rcParams.update(params)
except:
print('ERROR -- KEPFOLD: install latex for scientific plotting')
status = 1
if status == 0 and plottype != 'none':
pylab.figure(figsize=[17, 7])
pylab.clf()
ax = pylab.axes([0.06, 0.11, 0.93, 0.86])
pylab.gca().xaxis.set_major_formatter(
pylab.ScalarFormatter(useOffset=False))
pylab.gca().yaxis.set_major_formatter(
pylab.ScalarFormatter(useOffset=False))
labels = ax.get_yticklabels()
setp(labels, 'rotation', 90)
if bindata:
pylab.fill(ptime2,
pout2,
color=fcolor,
linewidth=0.0,
alpha=falpha)
else:
if 'det' in plottype:
pylab.fill(ptime1,
pout1,
color=fcolor,
linewidth=0.0,
alpha=falpha)
pylab.plot(ptime1,
pout1,
color=lcolor,
linestyle='',
linewidth=lwidth,
marker='.')
if bindata:
pylab.plot(ptime2[1:-1],
pout2[1:-1],
color='r',
linestyle='-',
linewidth=lwidth,
marker='')
xlabel(xlab, {'color': 'k'})
ylabel(ylab, {'color': 'k'})
xlim(-0.49999, 1.49999)
if ymin >= 0.0:
ylim(ymin - yr * 0.01, ymax + yr * 0.01)
# ylim(0.96001,1.03999)
else:
ylim(1.0e-10, ymax + yr * 0.01)
grid()
if cmdLine:
pylab.show()
else:
pylab.ion()
pylab.plot([])
pylab.ioff()
# close input file
if status == 0:
status = kepio.closefits(instr, logfile, verbose)
# stop time
kepmsg.clock('KEPFOLD ended at: ', logfile, verbose)
def kephalophot(infile,
outfile,
plotfile,
plottype,
filter,
function,
cutoff,
clobber,
verbose,
logfile,
status,
cmdLine=False):
# input arguments
status = 0
seterr(all="ignore")
# log the call
hashline = '----------------------------------------------------------------------------'
kepmsg.log(logfile, hashline, verbose)
call = 'KEPHALOPHOT -- '
call += 'infile=' + infile + ' '
call += 'outfile=' + outfile + ' '
call += 'plotfile=' + plotfile + ' '
call += 'plottype=' + plottype + ' '
filt = 'n'
if (filter): filt = 'y'
call += 'filter=' + filt + ' '
call += 'function=' + function + ' '
call += 'cutoff=' + str(cutoff) + ' '
overwrite = 'n'
if (clobber): overwrite = 'y'
call += 'clobber=' + overwrite + ' '
chatter = 'n'
if (verbose): chatter = 'y'
call += 'verbose=' + chatter + ' '
call += 'logfile=' + logfile
kepmsg.log(logfile, call + '\n', verbose)
# start time
kepmsg.clock('KEPHALOPHOT started at', logfile, verbose)
# test log file
logfile = kepmsg.test(logfile)
# clobber output file
if clobber: status = kepio.clobber(outfile, logfile, verbose)
if kepio.fileexists(outfile):
message = 'ERROR -- KEPHALOPHOT: ' + outfile + ' exists. Use --clobber'
status = kepmsg.err(logfile, message, verbose)
# open TPF FITS file
if status == 0:
kepid, channel, skygroup, module, output, quarter, season, \
ra, dec, column, row, kepmag, xdim, ydim, barytime, status = \
kepio.readTPF(infile,'TIME',logfile,verbose)
if status == 0:
kepid, channel, skygroup, module, output, quarter, season, \
ra, dec, column, row, kepmag, xdim, ydim, tcorr, status = \
kepio.readTPF(infile,'TIMECORR',logfile,verbose)
if status == 0:
kepid, channel, skygroup, module, output, quarter, season, \
ra, dec, column, row, kepmag, xdim, ydim, cadno, status = \
kepio.readTPF(infile,'CADENCENO',logfile,verbose)
if status == 0:
kepid, channel, skygroup, module, output, quarter, season, \
ra, dec, column, row, kepmag, xdim, ydim, fluxpixels, status = \
kepio.readTPF(infile,'FLUX',logfile,verbose)
if status == 0:
kepid, channel, skygroup, module, output, quarter, season, \
ra, dec, column, row, kepmag, xdim, ydim, errpixels, status = \
kepio.readTPF(infile,'FLUX_ERR',logfile,verbose)
if status == 0:
kepid, channel, skygroup, module, output, quarter, season, \
ra, dec, column, row, kepmag, xdim, ydim, qual, status = \
kepio.readTPF(infile,'QUALITY',logfile,verbose)
# read mask defintion data from TPF file
if status == 0:
maskimg, pixcoord1, pixcoord2, status = kepio.readMaskDefinition(
infile, logfile, verbose)
# print target data
if status == 0:
print('')
print(' KepID: %s' % kepid)
print(' RA (J2000): %s' % ra)
print('Dec (J2000): %s' % dec)
print(' KepMag: %s' % kepmag)
print(' SkyGroup: %2s' % skygroup)
print(' Season: %2s' % str(season))
print(' Channel: %2s' % channel)
print(' Module: %2s' % module)
print(' Output: %1s' % output)
print('')
# how many quality = 0 rows? how many pixels?
if status == 0:
np = ydim * xdim
nrows = len(fluxpixels)
npts = 0
for i in range(nrows):
if qual[i] < 1e4 and \
numpy.isfinite(barytime[i]) and \
numpy.isfinite(fluxpixels[i,ydim*xdim/2]):
npts += 1
time = empty((npts))
timecorr = empty((npts))
cadenceno = empty((npts))
quality = empty((npts))
pixseries = zeros((npts, np))
errseries = zeros((npts, np))
# pixseries = empty((ydim,xdim,npts))
# errseries = empty((ydim,xdim,npts))
# construct output light curves
if status == 0:
for i in range(np):
npts = 0
for j in range(nrows):
if qual[j] < 1e4 and \
numpy.isfinite(barytime[j]) and \
numpy.isfinite(fluxpixels[j,i]):
time[npts] = barytime[j]
timecorr[npts] = tcorr[j]
cadenceno[npts] = cadno[j]
quality[npts] = qual[j]
pixseries[npts, i] = fluxpixels[j, i]
errseries[npts, i] = errpixels[j, i]
npts += 1
# define data sampling
if status == 0 and filter:
tpf, status = kepio.openfits(infile, 'readonly', logfile, verbose)
if status == 0 and filter:
cadence, status = kepkey.cadence(tpf[1], infile, logfile, verbose)
tr = 1.0 / (cadence / 86400)
timescale = 1.0 / (cutoff / tr)
# define convolution function
if status == 0 and filter:
if function == 'boxcar':
filtfunc = numpy.ones(numpy.ceil(timescale))
elif function == 'gauss':
timescale /= 2
dx = numpy.ceil(timescale * 10 + 1)
filtfunc = kepfunc.gauss()
filtfunc = filtfunc([1.0, dx / 2 - 1.0, timescale],
linspace(0, dx - 1, dx))
elif function == 'sinc':
dx = numpy.ceil(timescale * 12 + 1)
fx = linspace(0, dx - 1, dx)
fx = fx - dx / 2 + 0.5
fx /= timescale
filtfunc = numpy.sinc(fx)
filtfunc /= numpy.sum(filtfunc)
# pad time series at both ends with noise model
if status == 0 and filter:
for i in range(ydim):
for j in range(xdim):
ave, sigma = kepstat.stdev(pixseries[i, j, :len(filtfunc)])
padded = numpy.append(kepstat.randarray(numpy.ones(len(filtfunc)) * ave, \
numpy.ones(len(filtfunc)) * sigma), pixseries[i,j,:])
ave, sigma = kepstat.stdev(pixseries[i, j, -len(filtfunc):])
padded = numpy.append(padded, kepstat.randarray(numpy.ones(len(filtfunc)) * ave, \
numpy.ones(len(filtfunc)) * sigma))
# convolve data
if status == 0:
convolved = convolve(padded, filtfunc, 'same')
# remove padding from the output array
if status == 0:
outdata = convolved[len(filtfunc):-len(filtfunc)]
# subtract low frequencies
if status == 0:
outmedian = median(outdata)
pixseries[i,
j, :] = pixseries[i, j, :] - outdata + outmedian
# construct weighted time series
if status == 0:
wgt = numpy.ones((np, 3))
twgt = numpy.ones((np, 3))
wgt /= sum(wgt, axis=0)
satlvl = 0.8 * numpy.max(numpy.max(pixseries, axis=1))
brk1 = 9.7257203
brk2 = 45.
ind1 = where(time - time[0] < brk1)
ind2 = where((time - time[0] >= brk1) & (time - time[0] < brk2))
ind3 = where(time - time[0] >= brk2)
z = numpy.array([0.0, 0.0, 0.0])
for i in range(np):
if max(pixseries[ind1, i].flatten()) > satlvl or max(
pixseries[ind1, i].flatten()) <= 100:
wgt[i, 0] = 0
z[0] += 1
if max(pixseries[ind2, i].flatten()) > satlvl or max(
pixseries[ind2, i].flatten()) <= 100:
wgt[i, 1] = 0
z[1] += 1
if max(pixseries[ind3, i].flatten()) > satlvl or max(
pixseries[ind3, i].flatten()) <= 100:
wgt[i, 2] = 0
z[2] += 1
print(z)
print(np - z)
sf1 = numpy.dot(pixseries[ind1, :], wgt[:, 0]).flatten()
sf2 = numpy.dot(pixseries[ind2, :], wgt[:, 1]).flatten()
sf3 = numpy.dot(pixseries[ind3, :], wgt[:, 2]).flatten()
sf1 /= numpy.median(sf1)
sf2 /= numpy.median(sf2)
sf3 /= numpy.median(sf3)
originalflux = numpy.concatenate([sf1, sf2, sf3])
# a=numpy.array([0.0,0.0,0.0])
# t=0
# ca = numpy.array([0.0,0.0,0.0])
# ct = 0
# sig1 = numpy.std(sf1)
# sig2 = numpy.std(sf2)
# sig3 = numpy.std(sf3)
# while 1:
# j = int(numpy.floor(numpy.random.random()*np))
# if sum(wgt[j,:]) == 0: continue
# if ct == 1000:
# print(ca)
# if ca[0] < 333 and ca[1] < 333 and ca[2] < 333: break
# ca = numpy.array([0.0,0.0,0.0])
# ct = 0
# t += 1
# ct += 1
# wgt /= sum(wgt,axis=0)
# twgt=copy(wgt)
# twgt[j,:]*=numpy.random.normal(1.0,0.05,3)
# twgt /= sum(twgt,axis=0)
# tsf1 = numpy.dot(pixseries[ind1,:],twgt[:,0]).flatten()
# tsf2 = numpy.dot(pixseries[ind2,:],twgt[:,1]).flatten()
# tsf3 = numpy.dot(pixseries[ind3,:],twgt[:,2]).flatten()
# tsf1 /= numpy.median(tsf1)
# tsf2 /= numpy.median(tsf2)
# tsf3 /= numpy.median(tsf3)
# tsig1 = numpy.std(tsf1)
# tsig2 = numpy.std(tsf2)
# tsig3 = numpy.std(tsf3)
# if tsig1 < sig1:
# wgt[:,0] = twgt[:,0]
# sig1 = tsig1
# a[0] += 1
# ca[0] += 1
# if tsig2 < sig2:
# wgt[:,1] = twgt[:,1]
# sig2 = tsig2
# a[1] += 1
# ca[1] += 1
# if tsig3 < sig3:
# wgt[:,2] = twgt[:,2]
# sig3 = tsig3
# a[2] += 1
# ca[2] += 1
# print(100*a/t)
# sf1 = numpy.dot(pixseries[ind1,:],wgt[:,0]).flatten()
# sf2 = numpy.dot(pixseries[ind2,:],wgt[:,1]).flatten()
# sf3 = numpy.dot(pixseries[ind3,:],wgt[:,2]).flatten()
# sf1 /= numpy.median(sf1)
# sf2 /= numpy.median(sf2)
# sf3 /= numpy.median(sf3)
#
# a=numpy.array([0.0,0.0,0.0])
# t=0
# ca = numpy.array([0.0,0.0,0.0])
# ct = 0
# sig1 = sum(numpy.fabs(sf1[1:]-sf1[:-1]))
# sig2 = sum(numpy.fabs(sf2[1:]-sf2[:-1]))
# sig3 = sum(numpy.fabs(sf3[1:]-sf3[:-1]))
# while 1:
# j = int(numpy.floor(numpy.random.random()*np))
# if sum(wgt[j,:]) == 0: continue
# if ct == 1000:
# print(ca)
# if ca[0] < 167 and ca[1] < 167 and ca[2] < 167: break#
# ca = numpy.array([0.0,0.0,0.0])
# ct = 0
# t += 1
# ct += 1
# wgt /= sum(wgt,axis=0)
# twgt=copy(wgt)
# twgt[j,:]*=numpy.random.normal(1.0,0.05,3)
# twgt /= sum(twgt,axis=0)
# tsf1 = numpy.dot(pixseries[ind1,:],twgt[:,0]).flatten()
# tsf2 = numpy.dot(pixseries[ind2,:],twgt[:,1]).flatten()
# tsf3 = numpy.dot(pixseries[ind3,:],twgt[:,2]).flatten()
# tsf1 /= numpy.median(tsf1)
# tsf2 /= numpy.median(tsf2)
# tsf3 /= numpy.median(tsf3)
# tsig1 = sum(numpy.fabs(tsf1[1:]-tsf1[:-1]))
# tsig2 = sum(numpy.fabs(tsf2[1:]-tsf2[:-1]))
# tsig3 = sum(numpy.fabs(tsf3[1:]-tsf3[:-1]))
# if tsig1 < sig1:
# wgt[:,0] = twgt[:,0]
# sig1 = tsig1
# a[0] += 1
# ca[0] += 1
# if tsig2 < sig2:
# wgt[:,1] = twgt[:,1]
# sig2 = tsig2
# a[1] += 1
# ca[1] += 1
# if tsig3 < sig3:
# wgt[:,2] = twgt[:,2]
# sig3 = tsig3
# a[2] += 1
# ca[2] += 1
# print(100*a/t)
# sf1 = numpy.dot(pixseries[ind1,:],wgt[:,0]).flatten()
# sf2 = numpy.dot(pixseries[ind2,:],wgt[:,1]).flatten()
# sf3 = numpy.dot(pixseries[ind3,:],wgt[:,2]).flatten()
# sf1 /= numpy.median(sf1)
# sf2 /= numpy.median(sf2)
# sf3 /= numpy.median(sf3)
a = numpy.array([0.0, 0.0, 0.0])
t = 0
ca = numpy.array([0.0, 0.0, 0.0])
ct = 0
sig1 = sum(numpy.fabs(sf1[2:] - 2 * sf1[1:-1] + sf1[:-2]))
sig2 = sum(numpy.fabs(sf2[2:] - 2 * sf2[1:-1] + sf2[:-2]))
sig3 = sum(numpy.fabs(sf3[2:] - 2 * sf3[1:-1] + sf3[:-2]))
while 1:
j = int(numpy.floor(numpy.random.random() * np))
if sum(wgt[j, :]) == 0: continue
if ct == 1000:
print(ca)
if ca[0] < 20 and ca[1] < 20 and ca[2] < 20: break
if t > 1000000: break
ca = numpy.array([0.0, 0.0, 0.0])
ct = 0
t += 1
ct += 1
wgt /= sum(wgt, axis=0)
twgt = copy(wgt)
twgt[j, :] *= numpy.random.normal(1.0, 0.05, 3)
twgt /= sum(twgt, axis=0)
tsf1 = numpy.dot(pixseries[ind1, :], twgt[:, 0]).flatten()
tsf2 = numpy.dot(pixseries[ind2, :], twgt[:, 1]).flatten()
tsf3 = numpy.dot(pixseries[ind3, :], twgt[:, 2]).flatten()
tsf1 /= numpy.median(tsf1)
tsf2 /= numpy.median(tsf2)
tsf3 /= numpy.median(tsf3)
tsig1 = sum(numpy.fabs(tsf1[2:] - 2 * tsf1[1:-1] + tsf1[:-2]))
tsig2 = sum(numpy.fabs(tsf2[2:] - 2 * tsf2[1:-1] + tsf2[:-2]))
tsig3 = sum(numpy.fabs(tsf3[2:] - 2 * tsf3[1:-1] + tsf3[:-2]))
if tsig1 < sig1:
wgt[:, 0] = twgt[:, 0]
sig1 = tsig1
a[0] += 1
ca[0] += 1
if tsig2 < sig2:
wgt[:, 1] = twgt[:, 1]
sig2 = tsig2
a[1] += 1
ca[1] += 1
if tsig3 < sig3:
wgt[:, 2] = twgt[:, 2]
sig3 = tsig3
a[2] += 1
ca[2] += 1
print(100 * a / t)
sf1 = numpy.dot(pixseries[ind1, :], wgt[:, 0]).flatten()
sf2 = numpy.dot(pixseries[ind2, :], wgt[:, 1]).flatten()
sf3 = numpy.dot(pixseries[ind3, :], wgt[:, 2]).flatten()
sf1 /= numpy.median(sf1)
sf2 /= numpy.median(sf2)
sf3 /= numpy.median(sf3)
finalflux = numpy.concatenate([sf1, sf2, sf3])
# construct output file
if status == 0:
instruct, status = kepio.openfits(infile, 'readonly', logfile, verbose)
status = kepkey.history(call, instruct[0], outfile, logfile, verbose)
hdulist = HDUList(instruct[0])
cols = []
cols.append(
Column(name='TIME',
format='D',
unit='BJD - 2454833',
disp='D12.7',
array=time))
cols.append(
Column(name='TIMECORR',
format='E',
unit='d',
disp='E13.6',
array=timecorr))
cols.append(
Column(name='CADENCENO', format='J', disp='I10', array=cadenceno))
cols.append(Column(name='QUALITY', format='J', array=quality))
cols.append(
Column(name='ORGFLUX',
format='E',
disp='E13.6',
array=originalflux))
cols.append(
Column(name='FLUX', format='E', disp='E13.6', array=finalflux))
# for i in range(ydim):
# for j in range(xdim):
# colname = 'COL%d_ROW%d' % (i+column,j+row)
# cols.append(Column(name=colname,format='E',disp='E13.6',array=pixseries[i,j,:]))
hdu1 = new_table(ColDefs(cols))
try:
hdu1.header.update('INHERIT', True, 'inherit the primary header')
except:
status = 0
try:
hdu1.header.update('EXTNAME', 'PIXELSERIES', 'name of extension')
except:
status = 0
try:
hdu1.header.update(
'EXTVER', instruct[1].header['EXTVER'],
'extension version number (not format version)')
except:
status = 0
try:
hdu1.header.update('TELESCOP', instruct[1].header['TELESCOP'],
'telescope')
except:
status = 0
try:
hdu1.header.update('INSTRUME', instruct[1].header['INSTRUME'],
'detector type')
except:
status = 0
try:
hdu1.header.update('OBJECT', instruct[1].header['OBJECT'],
'string version of KEPLERID')
except:
status = 0
try:
hdu1.header.update('KEPLERID', instruct[1].header['KEPLERID'],
'unique Kepler target identifier')
except:
status = 0
try:
hdu1.header.update('RADESYS', instruct[1].header['RADESYS'],
'reference frame of celestial coordinates')
except:
status = 0
try:
hdu1.header.update('RA_OBJ', instruct[1].header['RA_OBJ'],
'[deg] right ascension from KIC')
except:
status = 0
try:
hdu1.header.update('DEC_OBJ', instruct[1].header['DEC_OBJ'],
'[deg] declination from KIC')
except:
status = 0
try:
hdu1.header.update('EQUINOX', instruct[1].header['EQUINOX'],
'equinox of celestial coordinate system')
except:
status = 0
try:
hdu1.header.update('TIMEREF', instruct[1].header['TIMEREF'],
'barycentric correction applied to times')
except:
status = 0
try:
hdu1.header.update('TASSIGN', instruct[1].header['TASSIGN'],
'where time is assigned')
except:
status = 0
try:
hdu1.header.update('TIMESYS', instruct[1].header['TIMESYS'],
'time system is barycentric JD')
except:
status = 0
try:
hdu1.header.update('BJDREFI', instruct[1].header['BJDREFI'],
'integer part of BJD reference date')
except:
status = 0
try:
hdu1.header.update('BJDREFF', instruct[1].header['BJDREFF'],
'fraction of the day in BJD reference date')
except:
status = 0
try:
hdu1.header.update('TIMEUNIT', instruct[1].header['TIMEUNIT'],
'time unit for TIME, TSTART and TSTOP')
except:
status = 0
try:
hdu1.header.update('TSTART', instruct[1].header['TSTART'],
'observation start time in BJD-BJDREF')
except:
status = 0
try:
hdu1.header.update('TSTOP', instruct[1].header['TSTOP'],
'observation stop time in BJD-BJDREF')
except:
status = 0
try:
hdu1.header.update('LC_START', instruct[1].header['LC_START'],
'mid point of first cadence in MJD')
except:
status = 0
try:
hdu1.header.update('LC_END', instruct[1].header['LC_END'],
'mid point of last cadence in MJD')
except:
status = 0
try:
hdu1.header.update('TELAPSE', instruct[1].header['TELAPSE'],
'[d] TSTOP - TSTART')
except:
status = 0
try:
hdu1.header.update('LIVETIME', instruct[1].header['LIVETIME'],
'[d] TELAPSE multiplied by DEADC')
except:
status = 0
try:
hdu1.header.update('EXPOSURE', instruct[1].header['EXPOSURE'],
'[d] time on source')
except:
status = 0
try:
hdu1.header.update('DEADC', instruct[1].header['DEADC'],
'deadtime correction')
except:
status = 0
try:
hdu1.header.update('TIMEPIXR', instruct[1].header['TIMEPIXR'],
'bin time beginning=0 middle=0.5 end=1')
except:
status = 0
try:
hdu1.header.update('TIERRELA', instruct[1].header['TIERRELA'],
'[d] relative time error')
except:
status = 0
try:
hdu1.header.update('TIERABSO', instruct[1].header['TIERABSO'],
'[d] absolute time error')
except:
status = 0
try:
hdu1.header.update('INT_TIME', instruct[1].header['INT_TIME'],
'[s] photon accumulation time per frame')
except:
status = 0
try:
hdu1.header.update('READTIME', instruct[1].header['READTIME'],
'[s] readout time per frame')
except:
status = 0
try:
hdu1.header.update('FRAMETIM', instruct[1].header['FRAMETIM'],
'[s] frame time (INT_TIME + READTIME)')
except:
status = 0
try:
hdu1.header.update('NUM_FRM', instruct[1].header['NUM_FRM'],
'number of frames per time stamp')
except:
status = 0
try:
hdu1.header.update('TIMEDEL', instruct[1].header['TIMEDEL'],
'[d] time resolution of data')
except:
status = 0
try:
hdu1.header.update('DATE-OBS', instruct[1].header['DATE-OBS'],
'TSTART as UTC calendar date')
except:
status = 0
try:
hdu1.header.update('DATE-END', instruct[1].header['DATE-END'],
'TSTOP as UTC calendar date')
except:
status = 0
try:
hdu1.header.update('BACKAPP', instruct[1].header['BACKAPP'],
'background is subtracted')
except:
status = 0
try:
hdu1.header.update('DEADAPP', instruct[1].header['DEADAPP'],
'deadtime applied')
except:
status = 0
try:
hdu1.header.update('VIGNAPP', instruct[1].header['VIGNAPP'],
'vignetting or collimator correction applied')
except:
status = 0
try:
hdu1.header.update('GAIN', instruct[1].header['GAIN'],
'[electrons/count] channel gain')
except:
status = 0
try:
hdu1.header.update('READNOIS', instruct[1].header['READNOIS'],
'[electrons] read noise')
except:
status = 0
try:
hdu1.header.update('NREADOUT', instruct[1].header['NREADOUT'],
'number of read per cadence')
except:
status = 0
try:
hdu1.header.update('TIMSLICE', instruct[1].header['TIMSLICE'],
'time-slice readout sequence section')
except:
status = 0
try:
hdu1.header.update('MEANBLCK', instruct[1].header['MEANBLCK'],
'[count] FSW mean black level')
except:
status = 0
hdulist.append(hdu1)
hdulist.writeto(outfile)
status = kepkey.new('EXTNAME', 'APERTURE', 'name of extension',
instruct[2], outfile, logfile, verbose)
pyfits.append(outfile, instruct[2].data, instruct[2].header)
wgt1 = numpy.reshape(wgt[:, 0], (ydim, xdim))
wgt2 = numpy.reshape(wgt[:, 1], (ydim, xdim))
wgt3 = numpy.reshape(wgt[:, 2], (ydim, xdim))
hdu3 = ImageHDU(data=wgt1, header=instruct[2].header, name='WEIGHTS1')
hdu4 = ImageHDU(data=wgt2, header=instruct[2].header, name='WEIGHTS2')
hdu5 = ImageHDU(data=wgt3, header=instruct[2].header, name='WEIGHTS3')
pyfits.append(outfile, hdu3.data, hdu3.header)
pyfits.append(outfile, hdu4.data, hdu4.header)
pyfits.append(outfile, hdu5.data, hdu5.header)
status = kepio.closefits(instruct, logfile, verbose)
else:
message = 'WARNING -- KEPHALOPHOT: output FITS file requires > 999 columns. Non-compliant with FITS convention.'
kepmsg.warn(logfile, message)
# plot style
if status == 0:
try:
params = {
'backend': 'png',
'axes.linewidth': 2.0,
'axes.labelsize': 32,
'axes.font': 'sans-serif',
'axes.fontweight': 'bold',
'text.fontsize': 8,
'legend.fontsize': 8,
'xtick.labelsize': 12,
'ytick.labelsize': 12
}
pylab.rcParams.update(params)
except:
pass
# plot pixel array
fmin = 1.0e33
fmax = -1.033
if status == 0:
pylab.figure(num=None, figsize=[12, 12])
pylab.clf()
dx = 0.93 #/ xdim
dy = 0.94 #/ ydim
ax = pylab.axes([0.06, 0.05, 0.93, 0.94])
pylab.gca().xaxis.set_major_formatter(
pylab.ScalarFormatter(useOffset=False))
pylab.gca().yaxis.set_major_formatter(
pylab.ScalarFormatter(useOffset=False))
pylab.gca().xaxis.set_major_locator(
matplotlib.ticker.MaxNLocator(integer=True))
pylab.gca().yaxis.set_major_locator(
matplotlib.ticker.MaxNLocator(integer=True))
labels = ax.get_yticklabels()
setp(labels, 'rotation', 90, fontsize=12)
pylab.xlim(numpy.min(pixcoord1) - 0.5, numpy.max(pixcoord1) + 0.5)
pylab.ylim(numpy.min(pixcoord2) - 0.5, numpy.max(pixcoord2) + 0.5)
pylab.xlabel('time', {'color': 'k'})
pylab.ylabel('arbitrary flux', {'color': 'k'})
tmin = amin(time)
tmax = amax(time)
try:
numpy.isfinite(amin(finalflux))
numpy.isfinite(amin(finalflux))
fmin = amin(finalflux)
fmax = amax(finalflux)
except:
ugh = 1
xmin = tmin - (tmax - tmin) / 40
xmax = tmax + (tmax - tmin) / 40
ymin = fmin - (fmax - fmin) / 20
ymax = fmax + (fmax - fmin) / 20
pylab.axes([0.06, 0.05, dx, dy])
pylab.setp(pylab.gca(), xticklabels=[], yticklabels=[])
ptime = time * 1.0
ptime = numpy.insert(ptime, [0], ptime[0])
ptime = numpy.append(ptime, ptime[-1])
pflux = finalflux * 1.0
pflux = numpy.insert(pflux, [0], -1000.0)
pflux = numpy.append(pflux, -1000.0)
pylab.plot(time,
finalflux,
color='#0000ff',
linestyle='-',
linewidth=0.5)
pylab.fill(ptime, pflux, fc='#FFF380', linewidth=0.0, alpha=1.0)
if 'loc' in plottype:
pylab.xlim(xmin, xmax)
pylab.ylim(ymin, ymax)
if 'glob' in plottype:
pylab.xlim(xmin, xmax)
pylab.ylim(1.0e-10, numpy.nanmax(pixseries) * 1.05)
if 'full' in plottype:
pylab.xlim(xmin, xmax)
pylab.ylim(1.0e-10, ymax * 1.05)
# render plot
if cmdLine:
pylab.show()
else:
pylab.ion()
pylab.plot([])
pylab.ioff()
if plotfile.lower() != 'none':
pylab.savefig(plotfile)
# stop time
if status == 0:
kepmsg.clock('KEPHALOPHOT ended at', logfile, verbose)
return
def kepoutlier(infile,outfile,datacol,nsig,stepsize,npoly,niter,
operation,ranges,plot,plotfit,clobber,verbose,logfile,status, cmdLine=False):
# startup parameters
status = 0
labelsize = 24
ticksize = 16
xsize = 16
ysize = 6
lcolor = '#0000ff'
lwidth = 1.0
fcolor = '#ffff00'
falpha = 0.2
# log the call
hashline = '----------------------------------------------------------------------------'
kepmsg.log(logfile,hashline,verbose)
call = 'KEPOUTLIER -- '
call += 'infile='+infile+' '
call += 'outfile='+outfile+' '
call += 'datacol='+str(datacol)+' '
call += 'nsig='+str(nsig)+' '
call += 'stepsize='+str(stepsize)+' '
call += 'npoly='+str(npoly)+' '
call += 'niter='+str(niter)+' '
call += 'operation='+str(operation)+' '
call += 'ranges='+str(ranges)+' '
plotit = 'n'
if (plot): plotit = 'y'
call += 'plot='+plotit+ ' '
plotf = 'n'
if (plotfit): plotf = 'y'
call += 'plotfit='+plotf+ ' '
overwrite = 'n'
if (clobber): overwrite = 'y'
call += 'clobber='+overwrite+ ' '
chatter = 'n'
if (verbose): chatter = 'y'
call += 'verbose='+chatter+' '
call += 'logfile='+logfile
kepmsg.log(logfile,call+'\n',verbose)
# start time
kepmsg.clock('KEPOUTLIER started at',logfile,verbose)
# test log file
logfile = kepmsg.test(logfile)
# clobber output file
if clobber: status = kepio.clobber(outfile,logfile,verbose)
if kepio.fileexists(outfile):
message = 'ERROR -- KEPOUTLIER: ' + outfile + ' exists. Use clobber=yes'
status = kepmsg.err(logfile,message,verbose)
# open input file
if status == 0:
instr, status = kepio.openfits(infile,'readonly',logfile,verbose)
if status == 0:
tstart, tstop, bjdref, cadence, status = kepio.timekeys(instr,infile,logfile,verbose,status)
if status == 0:
try:
work = instr[0].header['FILEVER']
cadenom = 1.0
except:
cadenom = cadence
# fudge non-compliant FITS keywords with no values
if status == 0:
instr = kepkey.emptykeys(instr,file,logfile,verbose)
# read table structure
if status == 0:
table, status = kepio.readfitstab(infile,instr[1],logfile,verbose)
# filter input data table
if status == 0:
try:
nanclean = instr[1].header['NANCLEAN']
except:
naxis2 = 0
try:
for i in range(len(table.field(0))):
if numpy.isfinite(table.field('barytime')[i]) and \
numpy.isfinite(table.field(datacol)[i]):
table[naxis2] = table[i]
naxis2 += 1
instr[1].data = table[:naxis2]
except:
for i in range(len(table.field(0))):
if numpy.isfinite(table.field('time')[i]) and \
numpy.isfinite(table.field(datacol)[i]):
table[naxis2] = table[i]
naxis2 += 1
instr[1].data = table[:naxis2]
comment = 'NaN cadences removed from data'
status = kepkey.new('NANCLEAN',True,comment,instr[1],outfile,logfile,verbose)
# read table columns
if status == 0:
try:
intime = instr[1].data.field('barytime') + 2.4e6
except:
intime, status = kepio.readfitscol(infile,instr[1].data,'time',logfile,verbose)
indata, status = kepio.readfitscol(infile,instr[1].data,datacol,logfile,verbose)
if status == 0:
intime = intime + bjdref
indata = indata / cadenom
# time ranges for region to be corrected
if status == 0:
t1, t2, status = kepio.timeranges(ranges,logfile,verbose)
cadencelis, status = kepstat.filterOnRange(intime,t1,t2)
# find limits of each time step
if status == 0:
tstep1 = []; tstep2 = []
work = intime[0]
while work < intime[-1]:
tstep1.append(work)
tstep2.append(array([work+stepsize,intime[-1]],dtype='float64').min())
work += stepsize
# find cadence limits of each time step
if status == 0:
cstep1 = []; cstep2 = []
work1 = 0; work2 = 0
for i in range(len(intime)):
if intime[i] >= intime[work1] and intime[i] < intime[work1] + stepsize:
work2 = i
else:
cstep1.append(work1)
cstep2.append(work2)
work1 = i; work2 = i
cstep1.append(work1)
cstep2.append(work2)
outdata = indata * 1.0
# comment keyword in output file
if status == 0:
status = kepkey.history(call,instr[0],outfile,logfile,verbose)
# clean up x-axis unit
if status == 0:
intime0 = float(int(tstart / 100) * 100.0)
ptime = intime - intime0
xlab = 'BJD $-$ %d' % intime0
# clean up y-axis units
if status == 0:
pout = indata * 1.0
nrm = len(str(int(pout.max())))-1
pout = pout / 10**nrm
ylab = '10$^%d$ e$^-$ s$^{-1}$' % nrm
# data limits
xmin = ptime.min()
xmax = ptime.max()
ymin = pout.min()
ymax = pout.max()
xr = xmax - xmin
yr = ymax - ymin
ptime = insert(ptime,[0],[ptime[0]])
ptime = append(ptime,[ptime[-1]])
pout = insert(pout,[0],[0.0])
pout = append(pout,0.0)
# plot light curve
if status == 0 and plot:
plotLatex = True
try:
params = {'backend': 'png',
'axes.linewidth': 2.5,
'axes.labelsize': labelsize,
'axes.font': 'sans-serif',
'axes.fontweight' : 'bold',
'text.fontsize': 12,
'legend.fontsize': 12,
'xtick.labelsize': ticksize,
'ytick.labelsize': ticksize}
rcParams.update(params)
except:
plotLatex = False
if status == 0 and plot:
pylab.figure(figsize=[xsize,ysize])
pylab.clf()
# plot data
ax = pylab.axes([0.06,0.1,0.93,0.87])
# force tick labels to be absolute rather than relative
pylab.gca().xaxis.set_major_formatter(pylab.ScalarFormatter(useOffset=False))
pylab.gca().yaxis.set_major_formatter(pylab.ScalarFormatter(useOffset=False))
# rotate y labels by 90 deg
labels = ax.get_yticklabels()
setp(labels, 'rotation', 90, fontsize=12)
pylab.plot(ptime,pout,color=lcolor,linestyle='-',linewidth=lwidth)
fill(ptime,pout,color=fcolor,linewidth=0.0,alpha=falpha)
xlabel(xlab, {'color' : 'k'})
if not plotLatex:
ylab = '10**%d electrons/sec' % nrm
ylabel(ylab, {'color' : 'k'})
grid()
# loop over each time step, fit data, determine rms
if status == 0:
masterfit = indata * 0.0
mastersigma = zeros(len(masterfit))
functype = 'poly' + str(npoly)
for i in range(len(cstep1)):
pinit = [indata[cstep1[i]:cstep2[i]+1].mean()]
if npoly > 0:
for j in range(npoly):
pinit.append(0.0)
pinit = array(pinit,dtype='float32')
try:
coeffs, errors, covar, iiter, sigma, chi2, dof, fit, plotx, ploty, status = \
kepfit.lsqclip(functype,pinit,intime[cstep1[i]:cstep2[i]+1]-intime[cstep1[i]],
indata[cstep1[i]:cstep2[i]+1],None,nsig,nsig,niter,logfile,
verbose)
for j in range(len(coeffs)):
masterfit[cstep1[i]:cstep2[i]+1] += coeffs[j] * \
(intime[cstep1[i]:cstep2[i]+1] - intime[cstep1[i]])**j
for j in range(cstep1[i],cstep2[i]+1):
mastersigma[j] = sigma
if plotfit:
pylab.plot(plotx+intime[cstep1[i]]-intime0,ploty / 10**nrm,
'g',lw='3')
except:
for j in range(cstep1[i],cstep2[i]+1):
masterfit[j] = indata[j]
mastersigma[j] = 1.0e10
message = 'WARNING -- KEPOUTLIER: could not fit range '
message += str(intime[cstep1[i]]) + '-' + str(intime[cstep2[i]])
kepmsg.warn(None,message)
# reject outliers
if status == 0:
rejtime = []; rejdata = []; naxis2 = 0
for i in range(len(masterfit)):
if abs(indata[i] - masterfit[i]) > nsig * mastersigma[i] and i in cadencelis:
rejtime.append(intime[i])
rejdata.append(indata[i])
if operation == 'replace':
[rnd] = kepstat.randarray([masterfit[i]],[mastersigma[i]])
table[naxis2] = table[i]
table.field(datacol)[naxis2] = rnd
naxis2 += 1
else:
table[naxis2] = table[i]
naxis2 += 1
instr[1].data = table[:naxis2]
rejtime = array(rejtime,dtype='float64')
rejdata = array(rejdata,dtype='float32')
pylab.plot(rejtime-intime0,rejdata / 10**nrm,'ro')
# plot ranges
xlim(xmin-xr*0.01,xmax+xr*0.01)
if ymin >= 0.0:
ylim(ymin-yr*0.01,ymax+yr*0.01)
else:
ylim(1.0e-10,ymax+yr*0.01)
# render plot
if cmdLine:
pylab.show()
else:
pylab.ion()
pylab.plot([])
pylab.ioff()
# write output file
if status == 0:
instr.writeto(outfile)
# close input file
if status == 0:
status = kepio.closefits(instr,logfile,verbose)
# end time
if (status == 0):
message = 'KEPOUTLIER completed at'
else:
message = '\nKEPOUTLIER aborted at'
kepmsg.clock(message,logfile,verbose)
def lsqclip(functype, pinit, x, y, yerr, rej_lo, rej_hi, niter, logfile,
verbose):
# functype = unctional form
# pinit = initial guess for parameters
# x = list of x data
# y = list of y data
# yerr = list of 1-sigma y errors
# order = polynomial order
# rej_lo = lower rejection threshold (units=sigma)
# rej_hi = upper rejection threshold (units=sugma)
# niter = number of sigma-clipping iterations
npts = []
iiter = 0
iterstatus = 1
status = 0
# error catching
if (len(x) == 0):
status = kepmsg.exit('ERROR -- KEPFIT.LSQCLIP: x data array is empty')
if (len(y) == 0):
status = kepmsg.exit('ERROR -- KEPFIT.LSQCLIP: y data array is empty')
if (len(x) < len(pinit)):
kepmsg.warn(logfile,
'WARNING -- KEPFIT.LSQCLIP: no degrees of freedom')
# sigma-clipping iterations
while (iiter < niter and len(x) > len(pinit) and iterstatus > 0):
iterstatus = 0
tmpx = []
tmpy = []
tmpyerr = []
npts.append(len(x))
coeffs,errors,covar,sigma,chi2,dof,fit,plotx,ploty,status = \
leastsquare(functype,pinit,x,y,yerr,logfile,verbose)
pinit = coeffs
# point-by-point sigma-clipping test
for ix in range(npts[iiter]):
if (y[ix] - fit[ix] < rej_hi * sigma
and fit[ix] - y[ix] < rej_lo * sigma):
tmpx.append(x[ix])
tmpy.append(y[ix])
if (yerr != None): tmpyerr.append(yerr[ix])
else:
iterstatus = 1
x = scipy.array(tmpx)
y = scipy.array(tmpy)
if (yerr != None): yerr = scipy.array(tmpyerr)
iiter += 1
# fudge scalar models
# for i in range(len(plotx)):
# coeffs = best fit coefficients
# covar = covariance matrix
# iiter = number of sigma clipping iteration before convergence
return coeffs, errors, covar, iiter, sigma, chi2, dof, fit, plotx, ploty, status
def MASTRADec(ra, dec, darcsec, srctab):
# coordinate limits
darcsec /= 3600.0
ra1 = ra - darcsec / cos(dec * pi / 180)
ra2 = ra + darcsec / cos(dec * pi / 180)
dec1 = dec - darcsec
dec2 = dec + darcsec
# build mast query
url = 'http://archive.stsci.edu/kepler/kepler_fov/search.php?'
url += 'action=Search'
url += '&masterRA=' + str(ra1) + '..' + str(ra2)
url += '&masterDec=' + str(dec1) + '..' + str(dec2)
url += '&max_records=10000'
url += '&verb=3'
url += '&outputformat=CSV'
# retrieve results from MAST
if srctab:
try:
lines = urllib.request.urlopen(url)
except:
message = 'WARNING -- KEPFIELD: Cannot retrieve data from MAST'
status = kepmsg.warn(logfile, message)
lines = ''
else:
lines = ''
# collate nearby sources
kepid = []
kepmag = []
ra = []
dec = []
for line in lines:
line = line.strip()
# Python 3 hack
try:
'Kepler' in line
except:
line = line.decode('ascii')
if (len(line) > 0 and 'Kepler' not in line and 'integer' not in line
and 'no rows found' not in line):
out = line.split(',')
r, d = sex2dec(out[0], out[1])
try:
if out[-22] != 'Possible_artifact': kepid.append(int(out[2]))
except:
if out[-22] != 'Possible_artifact': kepid.append(0)
try:
if out[-22] != 'Possible_artifact':
kepmag.append(float(out[42]))
except:
if out[-22] != 'Possible_artifact': kepmag.append(0.0)
if out[-22] != 'Possible_artifact': ra.append(r)
if out[-22] != 'Possible_artifact': dec.append(d)
kepid = array(kepid)
kepmag = array(kepmag)
ra = array(ra)
dec = array(dec)
return kepid, ra, dec, kepmag
def getWCSp(file, struct, logfile, verbose):
status = 0
crpix1p = 0.0
crpix2p = 0.0
crval1p = 0.0
crval2p = 0.0
cdelt1p = 0.0
cdelt2p = 0.0
try:
crpix1p, status = get(file, struct, 'CRPIX1P', logfile, verbose)
except:
txt = 'WARNING -- KEPKEY.GETWCSP: Cannot read keyword CRPIX1P in file ' + file
kepmsg.warn(logfile, txt)
status = 1
try:
crpix2p, status = get(file, struct, 'CRPIX2P', logfile, verbose)
except:
txt = 'WARNING -- KEPKEY.GETWCSP: Cannot read keyword CRPIX2P in file ' + file
kepmsg.warn(logfile, txt)
status = 1
try:
crval1p, status = get(file, struct, 'CRVAL1P', logfile, verbose)
except:
txt = 'WARNING -- KEPKEY.GETWCSP: Cannot read keyword CRVAL1P in file ' + file
kepmsg.warn(logfile, txt)
status = 1
try:
crval2p, status = get(file, struct, 'CRVAL2P', logfile, verbose)
except:
txt = 'WARNING -- KEPKEY.GETWCSP: Cannot read keyword CRVAL2P in file ' + file
kepmsg.warn(logfile, txt)
status = 1
try:
cdelt1p, status = get(file, struct, 'CDELT1P', logfile, verbose)
except:
txt = 'WARNING -- KEPKEY.GETWCSP: Cannot read keyword CDELT1P in file ' + file
kepmsg.warn(logfile, txt)
status = 1
try:
cdelt2p, status = get(file, struct, 'CDELT2P', logfile, verbose)
except:
txt = 'WARNING -- KEPKEY.GETWCSP: Cannot read keyword CDELT2P in file ' + file
kepmsg.warn(logfile, txt)
status = 1
return crpix1p, crpix2p, crval1p, crval2p, cdelt1p, cdelt2p, status
def getWCSs(file, struct, logfile, verbose):
status = 0
crpix1 = 0.0
crpix2 = 0.0
crval1 = 0.0
crval2 = 0.0
cdelt1 = 0.0
cdelt2 = 0.0
pc = [0.0, 0.0, 0.0, 0.0]
try:
crpix1, status = get(file, struct, 'CRPIX1', logfile, verbose)
except:
txt = 'WARNING -- KEPKEY.GETWCSS: Cannot read keyword CRPIX1 in file ' + file
kepmsg.warn(logfile, txt)
status = 1
try:
crpix2, status = get(file, struct, 'CRPIX2', logfile, verbose)
except:
txt = 'WARNING -- KEPKEY.GETWCSS: Cannot read keyword CRPIX2 in file ' + file
kepmsg.warn(logfile, txt)
status = 1
try:
crval1, status = get(file, struct, 'CRVAL1', logfile, verbose)
except:
txt = 'WARNING -- KEPKEY.GETWCSS: Cannot read keyword CRVAL1 in file ' + file
kepmsg.warn(logfile, txt)
status = 1
try:
crval2, status = get(file, struct, 'CRVAL2', logfile, verbose)
except:
txt = 'WARNING -- KEPKEY.GETWCSS: Cannot read keyword CRVAL2 in file ' + file
kepmsg.warn(logfile, txt)
status = 1
try:
cdelt1, status = get(file, struct, 'CDELT1', logfile, verbose)
except:
txt = 'WARNING -- KEPKEY.GETWCSS: Cannot read keyword CDELT1 in file ' + file
kepmsg.warn(logfile, txt)
status = 1
try:
cdelt2, status = get(file, struct, 'CDELT2', logfile, verbose)
except:
txt = 'WARNING -- KEPKEY.GETWCSS: Cannot read keyword CDELT2 in file ' + file
kepmsg.warn(logfile, txt)
status = 1
try:
pc1_1, status = get(file, struct, 'PC1_1', logfile, verbose)
except:
txt = 'WARNING -- KEPKEY.GETWCSS: Cannot read keyword PC1_1 in file ' + file
kepmsg.warn(logfile, txt)
status = 1
try:
pc1_2, status = get(file, struct, 'PC1_2', logfile, verbose)
except:
txt = 'WARNING -- KEPKEY.GETWCSS: Cannot read keyword PC1_2 in file ' + file
kepmsg.warn(logfile, txt)
status = 1
try:
pc2_1, status = get(file, struct, 'PC2_1', logfile, verbose)
except:
txt = 'WARNING -- KEPKEY.GETWCSS: Cannot read keyword PC2_1 in file ' + file
kepmsg.warn(logfile, txt)
status = 1
try:
pc2_2, status = get(file, struct, 'PC2_2', logfile, verbose)
except:
txt = 'WARNING -- KEPKEY.GETWCSS: Cannot read keyword PC2_2 in file ' + file
kepmsg.warn(logfile, txt)
status = 1
try:
pc = numpy.array([[pc1_1, pc1_2], [pc2_1, pc2_2]])
pc = numpy.linalg.inv(pc)
except:
pass
return crpix1, crpix2, crval1, crval2, cdelt1, cdelt2, pc, status
def kepbls(infile,
outfile,
datacol,
errcol,
minper,
maxper,
mindur,
maxdur,
nsearch,
nbins,
plot,
clobber,
verbose,
logfile,
status,
cmdLine=False):
# startup parameters
numpy.seterr(all="ignore")
status = 0
labelsize = 32
ticksize = 18
xsize = 16
ysize = 8
lcolor = '#0000ff'
lwidth = 1.0
fcolor = '#ffff00'
falpha = 0.2
# log the call
hashline = '----------------------------------------------------------------------------'
kepmsg.log(logfile, hashline, verbose)
call = 'KEPBLS -- '
call += 'infile=' + infile + ' '
call += 'outfile=' + outfile + ' '
call += 'datacol=' + str(datacol) + ' '
call += 'errcol=' + str(errcol) + ' '
call += 'minper=' + str(minper) + ' '
call += 'maxper=' + str(maxper) + ' '
call += 'mindur=' + str(mindur) + ' '
call += 'maxdur=' + str(maxdur) + ' '
call += 'nsearch=' + str(nsearch) + ' '
call += 'nbins=' + str(nbins) + ' '
plotit = 'n'
if (plot): plotit = 'y'
call += 'plot=' + plotit + ' '
overwrite = 'n'
if (clobber): overwrite = 'y'
call += 'clobber=' + overwrite + ' '
chatter = 'n'
if (verbose): chatter = 'y'
call += 'verbose=' + chatter + ' '
call += 'logfile=' + logfile
kepmsg.log(logfile, call + '\n', verbose)
# start time
kepmsg.clock('KEPBLS started at', logfile, verbose)
# is duration greater than one bin in the phased light curve?
if float(nbins) * maxdur / 24.0 / maxper <= 1.0:
message = 'WARNING -- KEPBLS: ' + str(
maxdur) + ' hours transit duration < 1 phase bin when P = '
message += str(maxper) + ' days'
kepmsg.warn(logfile, message)
# test log file
logfile = kepmsg.test(logfile)
# clobber output file
if clobber: status = kepio.clobber(outfile, logfile, verbose)
if kepio.fileexists(outfile):
message = 'ERROR -- KEPBLS: ' + outfile + ' exists. Use clobber=yes'
status = kepmsg.err(logfile, message, verbose)
# open input file
if status == 0:
instr, status = kepio.openfits(infile, 'readonly', logfile, verbose)
if status == 0:
tstart, tstop, bjdref, cadence, status = kepio.timekeys(
instr, infile, logfile, verbose, status)
# fudge non-compliant FITS keywords with no values
if status == 0:
instr = kepkey.emptykeys(instr, file, logfile, verbose)
# read table structure
if status == 0:
table, status = kepio.readfitstab(infile, instr[1], logfile, verbose)
# filter input data table
if status == 0:
work1 = numpy.array(
[table.field('time'),
table.field(datacol),
table.field(errcol)])
work1 = numpy.rot90(work1, 3)
work1 = work1[~numpy.isnan(work1).any(1)]
# read table columns
if status == 0:
intime = work1[:, 2] + bjdref
indata = work1[:, 1]
inerr = work1[:, 0]
# test whether the period range is sensible
if status == 0:
tr = intime[-1] - intime[0]
if maxper > tr:
message = 'ERROR -- KEPBLS: maxper is larger than the time range of the input data'
status = kepmsg.err(logfile, message, verbose)
# prepare time series
if status == 0:
work1 = intime - intime[0]
work2 = indata - numpy.mean(indata)
# start period search
if status == 0:
srMax = numpy.array([], dtype='float32')
transitDuration = numpy.array([], dtype='float32')
transitPhase = numpy.array([], dtype='float32')
dPeriod = (maxper - minper) / nsearch
trialPeriods = numpy.arange(minper,
maxper + dPeriod,
dPeriod,
dtype='float32')
complete = 0
print ' '
for trialPeriod in trialPeriods:
fracComplete = float(complete) / float(len(trialPeriods) -
1) * 100.0
txt = '\r'
txt += 'Trial period = '
txt += str(int(trialPeriod))
txt += ' days ['
txt += str(int(fracComplete))
txt += '% complete]'
txt += ' ' * 20
sys.stdout.write(txt)
sys.stdout.flush()
complete += 1
srMax = numpy.append(srMax, 0.0)
transitDuration = numpy.append(transitDuration, numpy.nan)
transitPhase = numpy.append(transitPhase, numpy.nan)
trialFrequency = 1.0 / trialPeriod
# minimum and maximum transit durations in quantized phase units
duration1 = max(int(float(nbins) * mindur / 24.0 / trialPeriod), 2)
duration2 = max(
int(float(nbins) * maxdur / 24.0 / trialPeriod) + 1,
duration1 + 1)
# 30 minutes in quantized phase units
halfHour = int(0.02083333 / trialPeriod * nbins + 1)
# compute folded time series with trial period
work4 = numpy.zeros((nbins), dtype='float32')
work5 = numpy.zeros((nbins), dtype='float32')
phase = numpy.array(
((work1 * trialFrequency) -
numpy.floor(work1 * trialFrequency)) * float(nbins),
dtype='int')
ptuple = numpy.array([phase, work2, inerr])
ptuple = numpy.rot90(ptuple, 3)
phsort = numpy.array(sorted(ptuple, key=lambda ph: ph[2]))
for i in range(nbins):
elements = numpy.nonzero(phsort[:, 2] == float(i))[0]
work4[i] = numpy.mean(phsort[elements, 1])
work5[i] = math.sqrt(
numpy.sum(numpy.power(phsort[elements, 0], 2)) /
len(elements))
# extend the work arrays beyond nbins by wrapping
work4 = numpy.append(work4, work4[:duration2])
work5 = numpy.append(work5, work5[:duration2])
# calculate weights of folded light curve points
sigmaSum = numpy.nansum(numpy.power(work5, -2))
omega = numpy.power(work5, -2) / sigmaSum
# calculate weighted phased light curve
s = omega * work4
# iterate through trial period phase
for i1 in range(nbins):
# iterate through transit durations
for duration in range(duration1, duration2 + 1, int(halfHour)):
# calculate maximum signal residue
i2 = i1 + duration
sr1 = numpy.sum(numpy.power(s[i1:i2], 2))
sr2 = numpy.sum(omega[i1:i2])
sr = math.sqrt(sr1 / (sr2 * (1.0 - sr2)))
if sr > srMax[-1]:
srMax[-1] = sr
transitDuration[-1] = float(duration)
transitPhase[-1] = float((i1 + i2) / 2)
# normalize maximum signal residue curve
bestSr = numpy.max(srMax)
bestTrial = numpy.nonzero(srMax == bestSr)[0][0]
srMax /= bestSr
transitDuration *= trialPeriods / 24.0
BJD0 = numpy.array(transitPhase * trialPeriods / nbins,
dtype='float64') + intime[0] - 2454833.0
print '\n'
# clean up x-axis unit
if status == 0:
ptime = copy(trialPeriods)
xlab = 'Trial Period (days)'
# clean up y-axis units
if status == 0:
pout = copy(srMax)
ylab = 'Normalized Signal Residue'
# data limits
xmin = ptime.min()
xmax = ptime.max()
ymin = pout.min()
ymax = pout.max()
xr = xmax - xmin
yr = ymax - ymin
ptime = insert(ptime, [0], [ptime[0]])
ptime = append(ptime, [ptime[-1]])
pout = insert(pout, [0], [0.0])
pout = append(pout, 0.0)
# plot light curve
if status == 0 and plot:
plotLatex = True
try:
params = {
'backend': 'png',
'axes.linewidth': 2.5,
'axes.labelsize': labelsize,
'axes.font': 'sans-serif',
'axes.fontweight': 'bold',
'text.fontsize': 12,
'legend.fontsize': 12,
'xtick.labelsize': ticksize,
'ytick.labelsize': ticksize
}
rcParams.update(params)
except:
plotLatex = False
if status == 0 and plot:
pylab.figure(figsize=[xsize, ysize])
pylab.clf()
# plot data
ax = pylab.axes([0.06, 0.10, 0.93, 0.87])
# force tick labels to be absolute rather than relative
pylab.gca().xaxis.set_major_formatter(
pylab.ScalarFormatter(useOffset=False))
pylab.gca().yaxis.set_major_formatter(
pylab.ScalarFormatter(useOffset=False))
# rotate y labels by 90 deg
labels = ax.get_yticklabels()
pylab.setp(labels, 'rotation', 90)
# plot curve
if status == 0 and plot:
pylab.plot(ptime[1:-1],
pout[1:-1],
color=lcolor,
linestyle='-',
linewidth=lwidth)
pylab.fill(ptime, pout, color=fcolor, linewidth=0.0, alpha=falpha)
pylab.xlabel(xlab, {'color': 'k'})
pylab.ylabel(ylab, {'color': 'k'})
pylab.grid()
# plot ranges
if status == 0 and plot:
pylab.xlim(xmin - xr * 0.01, xmax + xr * 0.01)
if ymin >= 0.0:
pylab.ylim(ymin - yr * 0.01, ymax + yr * 0.01)
else:
pylab.ylim(1.0e-10, ymax + yr * 0.01)
# render plot
if status == 0 and plot:
if cmdLine:
pylab.show()
else:
pylab.ion()
pylab.plot([])
pylab.ioff()
# append new BLS data extension to the output file
if status == 0:
col1 = Column(name='PERIOD',
format='E',
unit='days',
array=trialPeriods)
col2 = Column(name='BJD0',
format='D',
unit='BJD - 2454833',
array=BJD0)
col3 = Column(name='DURATION',
format='E',
unit='hours',
array=transitDuration)
col4 = Column(name='SIG_RES', format='E', array=srMax)
cols = ColDefs([col1, col2, col3, col4])
instr.append(new_table(cols))
instr[-1].header.cards['TTYPE1'].comment = 'column title: trial period'
instr[-1].header.cards[
'TTYPE2'].comment = 'column title: trial mid-transit zero-point'
instr[-1].header.cards[
'TTYPE3'].comment = 'column title: trial transit duration'
instr[-1].header.cards[
'TTYPE4'].comment = 'column title: normalized signal residue'
instr[-1].header.cards['TFORM1'].comment = 'column type: float32'
instr[-1].header.cards['TFORM2'].comment = 'column type: float64'
instr[-1].header.cards['TFORM3'].comment = 'column type: float32'
instr[-1].header.cards['TFORM4'].comment = 'column type: float32'
instr[-1].header.cards['TUNIT1'].comment = 'column units: days'
instr[-1].header.cards[
'TUNIT2'].comment = 'column units: BJD - 2454833'
instr[-1].header.cards['TUNIT3'].comment = 'column units: hours'
instr[-1].header.update('EXTNAME', 'BLS', 'extension name')
instr[-1].header.update('PERIOD', trialPeriods[bestTrial],
'most significant trial period [d]')
instr[-1].header.update('BJD0', BJD0[bestTrial] + 2454833.0,
'time of mid-transit [BJD]')
instr[-1].header.update('TRANSDUR', transitDuration[bestTrial],
'transit duration [hours]')
instr[-1].header.update('SIGNRES', srMax[bestTrial] * bestSr,
'maximum signal residue')
# history keyword in output file
if status == 0:
status = kepkey.history(call, instr[0], outfile, logfile, verbose)
instr.writeto(outfile)
# close input file
if status == 0:
status = kepio.closefits(instr, logfile, verbose)
# print best trial period results
if status == 0:
print ' Best trial period = %.5f days' % trialPeriods[bestTrial]
print ' Time of mid-transit = BJD %.5f' % (BJD0[bestTrial] +
2454833.0)
print ' Transit duration = %.5f hours' % transitDuration[
bestTrial]
print ' Maximum signal residue = %.4g \n' % (srMax[bestTrial] * bestSr)
# end time
if (status == 0):
message = 'KEPBLS completed at'
else:
message = '\nKEPBLS aborted at'
kepmsg.clock(message, logfile, verbose)
def kepoutlier(infile,outfile,datacol,nsig,stepsize,npoly,niter,
operation,ranges,plot,plotfit,clobber,verbose,logfile,status, cmdLine=False):
# startup parameters
status = 0
labelsize = 24
ticksize = 16
xsize = 16
ysize = 6
lcolor = '#0000ff'
lwidth = 1.0
fcolor = '#ffff00'
falpha = 0.2
# log the call
hashline = '----------------------------------------------------------------------------'
kepmsg.log(logfile,hashline,verbose)
call = 'KEPOUTLIER -- '
call += 'infile='+infile+' '
call += 'outfile='+outfile+' '
call += 'datacol='+str(datacol)+' '
call += 'nsig='+str(nsig)+' '
call += 'stepsize='+str(stepsize)+' '
call += 'npoly='+str(npoly)+' '
call += 'niter='+str(niter)+' '
call += 'operation='+str(operation)+' '
call += 'ranges='+str(ranges)+' '
plotit = 'n'
if (plot): plotit = 'y'
call += 'plot='+plotit+ ' '
plotf = 'n'
if (plotfit): plotf = 'y'
call += 'plotfit='+plotf+ ' '
overwrite = 'n'
if (clobber): overwrite = 'y'
call += 'clobber='+overwrite+ ' '
chatter = 'n'
if (verbose): chatter = 'y'
call += 'verbose='+chatter+' '
call += 'logfile='+logfile
kepmsg.log(logfile,call+'\n',verbose)
# start time
kepmsg.clock('KEPOUTLIER started at',logfile,verbose)
# test log file
logfile = kepmsg.test(logfile)
# clobber output file
if clobber: status = kepio.clobber(outfile,logfile,verbose)
if kepio.fileexists(outfile):
message = 'ERROR -- KEPOUTLIER: ' + outfile + ' exists. Use clobber=yes'
status = kepmsg.err(logfile,message,verbose)
# open input file
if status == 0:
instr, status = kepio.openfits(infile,'readonly',logfile,verbose)
if status == 0:
tstart, tstop, bjdref, cadence, status = kepio.timekeys(instr,infile,logfile,verbose,status)
if status == 0:
try:
work = instr[0].header['FILEVER']
cadenom = 1.0
except:
cadenom = cadence
# fudge non-compliant FITS keywords with no values
if status == 0:
instr = kepkey.emptykeys(instr,file,logfile,verbose)
# read table structure
if status == 0:
table, status = kepio.readfitstab(infile,instr[1],logfile,verbose)
# filter input data table
if status == 0:
try:
nanclean = instr[1].header['NANCLEAN']
except:
naxis2 = 0
try:
for i in range(len(table.field(0))):
if numpy.isfinite(table.field('barytime')[i]) and \
numpy.isfinite(table.field(datacol)[i]):
table[naxis2] = table[i]
naxis2 += 1
instr[1].data = table[:naxis2]
except:
for i in range(len(table.field(0))):
if numpy.isfinite(table.field('time')[i]) and \
numpy.isfinite(table.field(datacol)[i]):
table[naxis2] = table[i]
naxis2 += 1
instr[1].data = table[:naxis2]
comment = 'NaN cadences removed from data'
status = kepkey.new('NANCLEAN',True,comment,instr[1],outfile,logfile,verbose)
# read table columns
if status == 0:
try:
intime = instr[1].data.field('barytime') + 2.4e6
except:
intime, status = kepio.readfitscol(infile,instr[1].data,'time',logfile,verbose)
indata, status = kepio.readfitscol(infile,instr[1].data,datacol,logfile,verbose)
if status == 0:
intime = intime + bjdref
indata = indata / cadenom
# time ranges for region to be corrected
if status == 0:
t1, t2, status = kepio.timeranges(ranges,logfile,verbose)
cadencelis, status = kepstat.filterOnRange(intime,t1,t2)
# find limits of each time step
if status == 0:
tstep1 = []; tstep2 = []
work = intime[0]
while work < intime[-1]:
tstep1.append(work)
tstep2.append(array([work+stepsize,intime[-1]],dtype='float64').min())
work += stepsize
# find cadence limits of each time step
if status == 0:
cstep1 = []; cstep2 = []
work1 = 0; work2 = 0
for i in range(len(intime)):
if intime[i] >= intime[work1] and intime[i] < intime[work1] + stepsize:
work2 = i
else:
cstep1.append(work1)
cstep2.append(work2)
work1 = i; work2 = i
cstep1.append(work1)
cstep2.append(work2)
outdata = indata * 1.0
# comment keyword in output file
if status == 0:
status = kepkey.history(call,instr[0],outfile,logfile,verbose)
# clean up x-axis unit
if status == 0:
intime0 = float(int(tstart / 100) * 100.0)
ptime = intime - intime0
xlab = 'BJD $-$ %d' % intime0
# clean up y-axis units
if status == 0:
pout = indata * 1.0
nrm = len(str(int(pout.max())))-1
pout = pout / 10**nrm
ylab = '10$^%d$ e$^-$ s$^{-1}$' % nrm
# data limits
xmin = ptime.min()
xmax = ptime.max()
ymin = pout.min()
ymax = pout.max()
xr = xmax - xmin
yr = ymax - ymin
ptime = insert(ptime,[0],[ptime[0]])
ptime = append(ptime,[ptime[-1]])
pout = insert(pout,[0],[0.0])
pout = append(pout,0.0)
# plot light curve
if status == 0 and plot:
plotLatex = True
try:
params = {'backend': 'png',
'axes.linewidth': 2.5,
'axes.labelsize': labelsize,
'axes.font': 'sans-serif',
'axes.fontweight' : 'bold',
'text.fontsize': 12,
'legend.fontsize': 12,
'xtick.labelsize': ticksize,
'ytick.labelsize': ticksize}
rcParams.update(params)
except:
plotLatex = False
if status == 0 and plot:
pylab.figure(figsize=[xsize,ysize])
pylab.clf()
# plot data
ax = pylab.axes([0.06,0.1,0.93,0.87])
# force tick labels to be absolute rather than relative
pylab.gca().xaxis.set_major_formatter(pylab.ScalarFormatter(useOffset=False))
pylab.gca().yaxis.set_major_formatter(pylab.ScalarFormatter(useOffset=False))
# rotate y labels by 90 deg
labels = ax.get_yticklabels()
setp(labels, 'rotation', 90, fontsize=12)
pylab.plot(ptime,pout,color=lcolor,linestyle='-',linewidth=lwidth)
fill(ptime,pout,color=fcolor,linewidth=0.0,alpha=falpha)
xlabel(xlab, {'color' : 'k'})
if not plotLatex:
ylab = '10**%d electrons/sec' % nrm
ylabel(ylab, {'color' : 'k'})
grid()
# loop over each time step, fit data, determine rms
if status == 0:
masterfit = indata * 0.0
mastersigma = zeros(len(masterfit))
functype = 'poly' + str(npoly)
for i in range(len(cstep1)):
pinit = [indata[cstep1[i]:cstep2[i]+1].mean()]
if npoly > 0:
for j in range(npoly):
pinit.append(0.0)
pinit = array(pinit,dtype='float32')
try:
coeffs, errors, covar, iiter, sigma, chi2, dof, fit, plotx, ploty, status = \
kepfit.lsqclip(functype,pinit,intime[cstep1[i]:cstep2[i]+1]-intime[cstep1[i]],
indata[cstep1[i]:cstep2[i]+1],None,nsig,nsig,niter,logfile,
verbose)
for j in range(len(coeffs)):
masterfit[cstep1[i]:cstep2[i]+1] += coeffs[j] * \
(intime[cstep1[i]:cstep2[i]+1] - intime[cstep1[i]])**j
for j in range(cstep1[i],cstep2[i]+1):
mastersigma[j] = sigma
if plotfit:
pylab.plot(plotx+intime[cstep1[i]]-intime0,ploty / 10**nrm,
'g',lw='3')
except:
for j in range(cstep1[i],cstep2[i]+1):
masterfit[j] = indata[j]
mastersigma[j] = 1.0e10
message = 'WARNING -- KEPOUTLIER: could not fit range '
message += str(intime[cstep1[i]]) + '-' + str(intime[cstep2[i]])
kepmsg.warn(None,message)
# reject outliers
if status == 0:
rejtime = []; rejdata = []; naxis2 = 0
for i in range(len(masterfit)):
if abs(indata[i] - masterfit[i]) > nsig * mastersigma[i] and i in cadencelis:
rejtime.append(intime[i])
rejdata.append(indata[i])
if operation == 'replace':
[rnd] = kepstat.randarray([masterfit[i]],[mastersigma[i]])
table[naxis2] = table[i]
table.field(datacol)[naxis2] = rnd
naxis2 += 1
else:
table[naxis2] = table[i]
naxis2 += 1
instr[1].data = table[:naxis2]
rejtime = array(rejtime,dtype='float64')
rejdata = array(rejdata,dtype='float32')
pylab.plot(rejtime-intime0,rejdata / 10**nrm,'ro')
# plot ranges
xlim(xmin-xr*0.01,xmax+xr*0.01)
if ymin >= 0.0:
ylim(ymin-yr*0.01,ymax+yr*0.01)
else:
ylim(1.0e-10,ymax+yr*0.01)
# render plot
if cmdLine:
pylab.show()
else:
pylab.ion()
pylab.plot([])
pylab.ioff()
# write output file
if status == 0:
instr.writeto(outfile)
# close input file
if status == 0:
status = kepio.closefits(instr,logfile,verbose)
## end time
if (status == 0):
message = 'KEPOUTLIER completed at'
else:
message = '\nKEPOUTLIER aborted at'
kepmsg.clock(message,logfile,verbose)
def kepimages(infile,outfix,imtype,ranges,clobber,verbose,logfile,status):
# startup parameters
status = 0
# log the call
hashline = '----------------------------------------------------------------------------'
kepmsg.log(logfile,hashline,verbose)
call = 'KEPIMAGES -- '
call += 'infile='+infile+' '
call += 'outfix='+outfix+' '
call += 'imtype='+imtype+' '
call += 'ranges='+str(ranges)+' '
overwrite = 'n'
if (clobber): overwrite = 'y'
call += 'clobber='+overwrite+ ' '
chatter = 'n'
if (verbose): chatter = 'y'
call += 'verbose='+chatter+' '
call += 'logfile='+logfile
kepmsg.log(logfile,call+'\n',verbose)
# start time
kepmsg.clock('KEPIMAGES started at',logfile,verbose)
# test log file
logfile = kepmsg.test(logfile)
# open input file
status = 0
print(' ')
instr = pyfits.open(infile,mode='readonly',memmap=True)
cards0 = instr[0].header.cards
cards1 = instr[1].header.cards
cards2 = instr[2].header.cards
# fudge non-compliant FITS keywords with no values
if status == 0:
instr = kepkey.emptykeys(instr,file,logfile,verbose)
# ingest time series data
if status == 0:
time = instr[1].data.field('TIME')[:] + 2454833.0
timecorr = instr[1].data.field('TIMECORR')[:]
cadenceno = instr[1].data.field('CADENCENO')[:]
raw_cnts = instr[1].data.field('RAW_CNTS')[:]
flux = instr[1].data.field('FLUX')[:]
flux_err = instr[1].data.field('FLUX_ERR')[:]
flux_bkg = instr[1].data.field('FLUX_BKG')[:]
flux_bkg_err = instr[1].data.field('FLUX_BKG_ERR')[:]
cosmic_rays = instr[1].data.field('COSMIC_RAYS')[:]
quality = instr[1].data.field('QUALITY')[:]
pos_corr1 = instr[1].data.field('POS_CORR1')[:]
pos_corr2 = instr[1].data.field('POS_CORR2')[:]
# choose output image
if status == 0:
if imtype.lower() == 'raw_cnts':
outim = raw_cnts
elif imtype.lower() == 'flux_err':
outim = flux_err
elif imtype.lower() == 'flux_bkg':
outim = flux_bkg
elif imtype.lower() == 'flux_bkg_err':
outim = flux_bkg_err
elif imtype.lower() == 'cosmic_rays':
outim = cosmic_rays
else:
outim = flux
# identify images to be exported
if status == 0:
tim = array([]); dat = array([]); err = array([])
tstart, tstop, status = kepio.timeranges(ranges,logfile,verbose)
if status == 0:
cadencelis, status = kepstat.filterOnRange(time,tstart,tstop)
# provide name for each output file and clobber if file exists
if status == 0:
for cadence in cadencelis:
outfile = outfix + '_BJD%.4f' % time[cadence] + '.fits'
if clobber and status == 0: status = kepio.clobber(outfile,logfile,verbose)
if kepio.fileexists(outfile) and status == 0:
message = 'ERROR -- KEPIMAGES: ' + outfile + ' exists. Use --clobber'
status = kepmsg.err(logfile,message,True)
# construct output primary extension
if status == 0:
ncad = 0
for cadence in cadencelis:
outfile = outfix + '_BJD%.4f' % time[cadence] + '.fits'
hdu0 = pyfits.PrimaryHDU()
for i in range(len(cards0)):
try:
if cards0[i].key not in list(hdu0.header.keys()):
hdu0.header.update(cards0[i].key, cards0[i].value, cards0[i].comment)
else:
hdu0.header.cards[cards0[i].key].comment = cards0[i].comment
except:
pass
status = kepkey.history(call,hdu0,outfile,logfile,verbose)
outstr = HDUList(hdu0)
# construct output image extension
hdu1 = ImageHDU(flux[cadence])
for i in range(len(cards2)):
try:
if cards2[i].key not in list(hdu1.header.keys()):
hdu1.header.update(cards2[i].key, cards2[i].value, cards2[i].comment)
except:
pass
for i in range(len(cards1)):
if (cards1[i].key not in list(hdu1.header.keys()) and
cards1[i].key[:4] not in ['TTYP','TFOR','TUNI','TDIS','TDIM','WCAX','1CTY',
'2CTY','1CRP','2CRP','1CRV','2CRV','1CUN','2CUN',
'1CDE','2CDE','1CTY','2CTY','1CDL','2CDL','11PC',
'12PC','21PC','22PC','WCSN','TFIE']):
hdu1.header.update(cards1[i].key, cards1[i].value, cards1[i].comment)
try:
int_time = cards1['INT_TIME'].value
except:
kepmsg.warn(logfile,'WARNING -- KEPIMAGES: cannot find INT_TIME keyword')
try:
frametim = cards1['FRAMETIM'].value
except:
kepmsg.warn(logfile,'WARNING -- KEPIMAGES: cannot find FRAMETIM keyword')
try:
num_frm = cards1['NUM_FRM'].value
except:
kepmsg.warn(logfile,'WARNING -- KEPIMAGES: cannot find NUM_FRM keyword')
hdu1.header.update('EXTNAME','IMAGE','name of extension')
try:
hdu1.header.update('TELAPSE',frametim * num_frm,'[s] elapsed time for exposure')
except:
hdu1.header.update('TELAPSE',-999,'[s] elapsed time for exposure')
try:
hdu1.header.update('LIVETIME',int_time * num_frm,'[s] TELASPE multiplied by DEADC')
except:
hdu1.header.update('LIVETIME',-999,'[s] TELASPE multiplied by DEADC')
try:
hdu1.header.update('EXPOSURE',int_time * num_frm,'[s] time on source')
except:
hdu1.header.update('EXPOSURE',-999,'[s] time on source')
try:
hdu1.header.update('MIDTIME',time[cadence],'[BJD] mid-time of exposure')
except:
hdu1.header.update('MIDTIME',-999,'[BJD] mid-time of exposure')
try:
hdu1.header.update('TIMECORR',timecorr[cadence],'[d] barycenter - timeslice correction')
except:
hdu1.header.update('TIMECORR',-999,'[d] barycenter - timeslice correction')
try:
hdu1.header.update('CADENCEN',cadenceno[cadence],'unique cadence number')
except:
hdu1.header.update('CADENCEN',-999,'unique cadence number')
try:
hdu1.header.update('QUALITY',quality[cadence],'pixel quality flag')
except:
hdu1.header.update('QUALITY',-999,'pixel quality flag')
try:
if True in numpy.isfinite(cosmic_rays[cadence]):
hdu1.header.update('COSM_RAY',True,'cosmic ray detected?')
else:
hdu1.header.update('COSM_RAY',False,'cosmic ray detected?')
except:
hdu1.header.update('COSM_RAY',-999,'cosmic ray detected?')
try:
pc1 = str(pos_corr1[cadence])
pc2 = str(pos_corr2[cadence])
hdu1.header.update('POSCORR1',pc1,'[pix] column position correction')
hdu1.header.update('POSCORR2',pc2,'[pix] row position correction')
except:
hdu1.header.update('POSCORR1',-999,'[pix] column position correction')
hdu1.header.update('POSCORR2',-999,'[pix] row position correction')
outstr.append(hdu1)
# write output file
if status == 0:
outstr.writeto(outfile,checksum=True)
ncad += 1
txt = '\r%3d%% ' % (float(ncad) / float(len(cadencelis)) * 100.0)
txt += '%s ' % outfile
sys.stdout.write(txt)
sys.stdout.flush()
# close input structure
if status == 0:
status = kepio.closefits(instr,logfile,verbose)
print('\n')
# end time
kepmsg.clock('KEPIMAGES finished at',logfile,verbose)
def getWCSp(file,struct,logfile,verbose):
status = 0
crpix1p = 0.0
crpix2p = 0.0
crval1p = 0.0
crval2p = 0.0
cdelt1p = 0.0
cdelt2p = 0.0
try:
crpix1p, status = get(file,struct,'CRPIX1P',logfile,verbose)
except:
txt = 'WARNING -- KEPKEY.GETWCSP: Cannot read keyword CRPIX1P in file ' + file
kepmsg.warn(logfile,txt)
status = 1
try:
crpix2p, status = get(file,struct,'CRPIX2P',logfile,verbose)
except:
txt = 'WARNING -- KEPKEY.GETWCSP: Cannot read keyword CRPIX2P in file ' + file
kepmsg.warn(logfile,txt)
status = 1
try:
crval1p, status = get(file,struct,'CRVAL1P',logfile,verbose)
except:
txt = 'WARNING -- KEPKEY.GETWCSP: Cannot read keyword CRVAL1P in file ' + file
kepmsg.warn(logfile,txt)
status = 1
try:
crval2p, status = get(file,struct,'CRVAL2P',logfile,verbose)
except:
txt = 'WARNING -- KEPKEY.GETWCSP: Cannot read keyword CRVAL2P in file ' + file
kepmsg.warn(logfile,txt)
status = 1
try:
cdelt1p, status = get(file,struct,'CDELT1P',logfile,verbose)
except:
txt = 'WARNING -- KEPKEY.GETWCSP: Cannot read keyword CDELT1P in file ' + file
kepmsg.warn(logfile,txt)
status = 1
try:
cdelt2p, status = get(file,struct,'CDELT2P',logfile,verbose)
except:
txt = 'WARNING -- KEPKEY.GETWCSP: Cannot read keyword CDELT2P in file ' + file
kepmsg.warn(logfile,txt)
status = 1
return crpix1p, crpix2p, crval1p, crval2p, cdelt1p, cdelt2p, status
def keppixseries(infile,
outfile,
plotfile,
plottype,
filter,
function,
cutoff,
clobber,
verbose,
logfile,
status,
cmdLine=False):
# input arguments
status = 0
seterr(all="ignore")
# log the call
hashline = '----------------------------------------------------------------------------'
kepmsg.log(logfile, hashline, verbose)
call = 'KEPPIXSERIES -- '
call += 'infile=' + infile + ' '
call += 'outfile=' + outfile + ' '
call += 'plotfile=' + plotfile + ' '
call += 'plottype=' + plottype + ' '
filt = 'n'
if (filter): filt = 'y'
call += 'filter=' + filt + ' '
call += 'function=' + function + ' '
call += 'cutoff=' + str(cutoff) + ' '
overwrite = 'n'
if (clobber): overwrite = 'y'
call += 'clobber=' + overwrite + ' '
chatter = 'n'
if (verbose): chatter = 'y'
call += 'verbose=' + chatter + ' '
call += 'logfile=' + logfile
kepmsg.log(logfile, call + '\n', verbose)
# start time
kepmsg.clock('KEPPIXSERIES started at', logfile, verbose)
# test log file
logfile = kepmsg.test(logfile)
# clobber output file
if clobber: status = kepio.clobber(outfile, logfile, verbose)
if kepio.fileexists(outfile):
message = 'ERROR -- KEPPIXSERIES: ' + outfile + ' exists. Use --clobber'
status = kepmsg.err(logfile, message, verbose)
# open TPF FITS file
if status == 0:
kepid, channel, skygroup, module, output, quarter, season, \
ra, dec, column, row, kepmag, xdim, ydim, barytime, status = \
kepio.readTPF(infile,'TIME',logfile,verbose)
if status == 0:
kepid, channel, skygroup, module, output, quarter, season, \
ra, dec, column, row, kepmag, xdim, ydim, tcorr, status = \
kepio.readTPF(infile,'TIMECORR',logfile,verbose)
if status == 0:
kepid, channel, skygroup, module, output, quarter, season, \
ra, dec, column, row, kepmag, xdim, ydim, cadno, status = \
kepio.readTPF(infile,'CADENCENO',logfile,verbose)
if status == 0:
kepid, channel, skygroup, module, output, quarter, season, \
ra, dec, column, row, kepmag, xdim, ydim, fluxpixels, status = \
kepio.readTPF(infile,'FLUX',logfile,verbose)
if status == 0:
kepid, channel, skygroup, module, output, quarter, season, \
ra, dec, column, row, kepmag, xdim, ydim, errpixels, status = \
kepio.readTPF(infile,'FLUX_ERR',logfile,verbose)
if status == 0:
kepid, channel, skygroup, module, output, quarter, season, \
ra, dec, column, row, kepmag, xdim, ydim, qual, status = \
kepio.readTPF(infile,'QUALITY',logfile,verbose)
# read mask defintion data from TPF file
if status == 0:
maskimg, pixcoord1, pixcoord2, status = kepio.readMaskDefinition(
infile, logfile, verbose)
# print target data
if status == 0:
print ''
print ' KepID: %s' % kepid
print ' RA (J2000): %s' % ra
print 'Dec (J2000): %s' % dec
print ' KepMag: %s' % kepmag
print ' SkyGroup: %2s' % skygroup
print ' Season: %2s' % str(season)
print ' Channel: %2s' % channel
print ' Module: %2s' % module
print ' Output: %1s' % output
print ''
# how many quality = 0 rows?
if status == 0:
npts = 0
nrows = len(fluxpixels)
for i in range(nrows):
if qual[i] == 0 and \
numpy.isfinite(barytime[i]) and \
numpy.isfinite(fluxpixels[i,ydim*xdim/2]):
npts += 1
time = empty((npts))
timecorr = empty((npts))
cadenceno = empty((npts))
quality = empty((npts))
pixseries = empty((ydim, xdim, npts))
errseries = empty((ydim, xdim, npts))
# construct output light curves
if status == 0:
np = 0
for i in range(ydim):
for j in range(xdim):
npts = 0
for k in range(nrows):
if qual[k] == 0 and \
numpy.isfinite(barytime[k]) and \
numpy.isfinite(fluxpixels[k,ydim*xdim/2]):
time[npts] = barytime[k]
timecorr[npts] = tcorr[k]
cadenceno[npts] = cadno[k]
quality[npts] = qual[k]
pixseries[i, j, npts] = fluxpixels[k, np]
errseries[i, j, npts] = errpixels[k, np]
npts += 1
np += 1
# define data sampling
if status == 0 and filter:
tpf, status = kepio.openfits(infile, 'readonly', logfile, verbose)
if status == 0 and filter:
cadence, status = kepkey.cadence(tpf[1], infile, logfile, verbose)
tr = 1.0 / (cadence / 86400)
timescale = 1.0 / (cutoff / tr)
# define convolution function
if status == 0 and filter:
if function == 'boxcar':
filtfunc = numpy.ones(numpy.ceil(timescale))
elif function == 'gauss':
timescale /= 2
dx = numpy.ceil(timescale * 10 + 1)
filtfunc = kepfunc.gauss()
filtfunc = filtfunc([1.0, dx / 2 - 1.0, timescale],
linspace(0, dx - 1, dx))
elif function == 'sinc':
dx = numpy.ceil(timescale * 12 + 1)
fx = linspace(0, dx - 1, dx)
fx = fx - dx / 2 + 0.5
fx /= timescale
filtfunc = numpy.sinc(fx)
filtfunc /= numpy.sum(filtfunc)
# pad time series at both ends with noise model
if status == 0 and filter:
for i in range(ydim):
for j in range(xdim):
ave, sigma = kepstat.stdev(pixseries[i, j, :len(filtfunc)])
padded = numpy.append(kepstat.randarray(numpy.ones(len(filtfunc)) * ave, \
numpy.ones(len(filtfunc)) * sigma), pixseries[i,j,:])
ave, sigma = kepstat.stdev(pixseries[i, j, -len(filtfunc):])
padded = numpy.append(padded, kepstat.randarray(numpy.ones(len(filtfunc)) * ave, \
numpy.ones(len(filtfunc)) * sigma))
# convolve data
if status == 0:
convolved = convolve(padded, filtfunc, 'same')
# remove padding from the output array
if status == 0:
outdata = convolved[len(filtfunc):-len(filtfunc)]
# subtract low frequencies
if status == 0:
outmedian = median(outdata)
pixseries[i,
j, :] = pixseries[i, j, :] - outdata + outmedian
# construct output file
if status == 0 and ydim * xdim < 1000:
instruct, status = kepio.openfits(infile, 'readonly', logfile, verbose)
status = kepkey.history(call, instruct[0], outfile, logfile, verbose)
hdulist = HDUList(instruct[0])
cols = []
cols.append(
Column(name='TIME',
format='D',
unit='BJD - 2454833',
disp='D12.7',
array=time))
cols.append(
Column(name='TIMECORR',
format='E',
unit='d',
disp='E13.6',
array=timecorr))
cols.append(
Column(name='CADENCENO', format='J', disp='I10', array=cadenceno))
cols.append(Column(name='QUALITY', format='J', array=quality))
for i in range(ydim):
for j in range(xdim):
colname = 'COL%d_ROW%d' % (i + column, j + row)
cols.append(
Column(name=colname,
format='E',
disp='E13.6',
array=pixseries[i, j, :]))
hdu1 = new_table(ColDefs(cols))
try:
hdu1.header.update('INHERIT', True, 'inherit the primary header')
except:
status = 0
try:
hdu1.header.update('EXTNAME', 'PIXELSERIES', 'name of extension')
except:
status = 0
try:
hdu1.header.update(
'EXTVER', instruct[1].header['EXTVER'],
'extension version number (not format version)')
except:
status = 0
try:
hdu1.header.update('TELESCOP', instruct[1].header['TELESCOP'],
'telescope')
except:
status = 0
try:
hdu1.header.update('INSTRUME', instruct[1].header['INSTRUME'],
'detector type')
except:
status = 0
try:
hdu1.header.update('OBJECT', instruct[1].header['OBJECT'],
'string version of KEPLERID')
except:
status = 0
try:
hdu1.header.update('KEPLERID', instruct[1].header['KEPLERID'],
'unique Kepler target identifier')
except:
status = 0
try:
hdu1.header.update('RADESYS', instruct[1].header['RADESYS'],
'reference frame of celestial coordinates')
except:
status = 0
try:
hdu1.header.update('RA_OBJ', instruct[1].header['RA_OBJ'],
'[deg] right ascension from KIC')
except:
status = 0
try:
hdu1.header.update('DEC_OBJ', instruct[1].header['DEC_OBJ'],
'[deg] declination from KIC')
except:
status = 0
try:
hdu1.header.update('EQUINOX', instruct[1].header['EQUINOX'],
'equinox of celestial coordinate system')
except:
status = 0
try:
hdu1.header.update('TIMEREF', instruct[1].header['TIMEREF'],
'barycentric correction applied to times')
except:
status = 0
try:
hdu1.header.update('TASSIGN', instruct[1].header['TASSIGN'],
'where time is assigned')
except:
status = 0
try:
hdu1.header.update('TIMESYS', instruct[1].header['TIMESYS'],
'time system is barycentric JD')
except:
status = 0
try:
hdu1.header.update('BJDREFI', instruct[1].header['BJDREFI'],
'integer part of BJD reference date')
except:
status = 0
try:
hdu1.header.update('BJDREFF', instruct[1].header['BJDREFF'],
'fraction of the day in BJD reference date')
except:
status = 0
try:
hdu1.header.update('TIMEUNIT', instruct[1].header['TIMEUNIT'],
'time unit for TIME, TSTART and TSTOP')
except:
status = 0
try:
hdu1.header.update('TSTART', instruct[1].header['TSTART'],
'observation start time in BJD-BJDREF')
except:
status = 0
try:
hdu1.header.update('TSTOP', instruct[1].header['TSTOP'],
'observation stop time in BJD-BJDREF')
except:
status = 0
try:
hdu1.header.update('LC_START', instruct[1].header['LC_START'],
'mid point of first cadence in MJD')
except:
status = 0
try:
hdu1.header.update('LC_END', instruct[1].header['LC_END'],
'mid point of last cadence in MJD')
except:
status = 0
try:
hdu1.header.update('TELAPSE', instruct[1].header['TELAPSE'],
'[d] TSTOP - TSTART')
except:
status = 0
try:
hdu1.header.update('LIVETIME', instruct[1].header['LIVETIME'],
'[d] TELAPSE multiplied by DEADC')
except:
status = 0
try:
hdu1.header.update('EXPOSURE', instruct[1].header['EXPOSURE'],
'[d] time on source')
except:
status = 0
try:
hdu1.header.update('DEADC', instruct[1].header['DEADC'],
'deadtime correction')
except:
status = 0
try:
hdu1.header.update('TIMEPIXR', instruct[1].header['TIMEPIXR'],
'bin time beginning=0 middle=0.5 end=1')
except:
status = 0
try:
hdu1.header.update('TIERRELA', instruct[1].header['TIERRELA'],
'[d] relative time error')
except:
status = 0
try:
hdu1.header.update('TIERABSO', instruct[1].header['TIERABSO'],
'[d] absolute time error')
except:
status = 0
try:
hdu1.header.update('INT_TIME', instruct[1].header['INT_TIME'],
'[s] photon accumulation time per frame')
except:
status = 0
try:
hdu1.header.update('READTIME', instruct[1].header['READTIME'],
'[s] readout time per frame')
except:
status = 0
try:
hdu1.header.update('FRAMETIM', instruct[1].header['FRAMETIM'],
'[s] frame time (INT_TIME + READTIME)')
except:
status = 0
try:
hdu1.header.update('NUM_FRM', instruct[1].header['NUM_FRM'],
'number of frames per time stamp')
except:
status = 0
try:
hdu1.header.update('TIMEDEL', instruct[1].header['TIMEDEL'],
'[d] time resolution of data')
except:
status = 0
try:
hdu1.header.update('DATE-OBS', instruct[1].header['DATE-OBS'],
'TSTART as UTC calendar date')
except:
status = 0
try:
hdu1.header.update('DATE-END', instruct[1].header['DATE-END'],
'TSTOP as UTC calendar date')
except:
status = 0
try:
hdu1.header.update('BACKAPP', instruct[1].header['BACKAPP'],
'background is subtracted')
except:
status = 0
try:
hdu1.header.update('DEADAPP', instruct[1].header['DEADAPP'],
'deadtime applied')
except:
status = 0
try:
hdu1.header.update('VIGNAPP', instruct[1].header['VIGNAPP'],
'vignetting or collimator correction applied')
except:
status = 0
try:
hdu1.header.update('GAIN', instruct[1].header['GAIN'],
'[electrons/count] channel gain')
except:
status = 0
try:
hdu1.header.update('READNOIS', instruct[1].header['READNOIS'],
'[electrons] read noise')
except:
status = 0
try:
hdu1.header.update('NREADOUT', instruct[1].header['NREADOUT'],
'number of read per cadence')
except:
status = 0
try:
hdu1.header.update('TIMSLICE', instruct[1].header['TIMSLICE'],
'time-slice readout sequence section')
except:
status = 0
try:
hdu1.header.update('MEANBLCK', instruct[1].header['MEANBLCK'],
'[count] FSW mean black level')
except:
status = 0
hdulist.append(hdu1)
hdulist.writeto(outfile)
status = kepkey.new('EXTNAME', 'APERTURE', 'name of extension',
instruct[2], outfile, logfile, verbose)
pyfits.append(outfile, instruct[2].data, instruct[2].header)
status = kepio.closefits(instruct, logfile, verbose)
else:
message = 'WARNING -- KEPPIXSERIES: output FITS file requires > 999 columns. Non-compliant with FITS convention.'
kepmsg.warn(logfile, message)
# plot style
if status == 0:
try:
params = {
'backend': 'png',
'axes.linewidth': 2.0,
'axes.labelsize': 32,
'axes.font': 'sans-serif',
'axes.fontweight': 'bold',
'text.fontsize': 8,
'legend.fontsize': 8,
'xtick.labelsize': 12,
'ytick.labelsize': 12
}
pylab.rcParams.update(params)
except:
pass
# plot pixel array
fmin = 1.0e33
fmax = -1.033
if status == 0:
pylab.figure(num=None, figsize=[12, 12])
pylab.clf()
dx = 0.93 / xdim
dy = 0.94 / ydim
ax = pylab.axes([0.06, 0.05, 0.93, 0.94])
pylab.gca().xaxis.set_major_formatter(
pylab.ScalarFormatter(useOffset=False))
pylab.gca().yaxis.set_major_formatter(
pylab.ScalarFormatter(useOffset=False))
pylab.gca().xaxis.set_major_locator(
matplotlib.ticker.MaxNLocator(integer=True))
pylab.gca().yaxis.set_major_locator(
matplotlib.ticker.MaxNLocator(integer=True))
labels = ax.get_yticklabels()
setp(labels, 'rotation', 90, fontsize=12)
pylab.xlim(numpy.min(pixcoord1) - 0.5, numpy.max(pixcoord1) + 0.5)
pylab.ylim(numpy.min(pixcoord2) - 0.5, numpy.max(pixcoord2) + 0.5)
pylab.xlabel('time', {'color': 'k'})
pylab.ylabel('arbitrary flux', {'color': 'k'})
for i in range(ydim):
for j in range(xdim):
tmin = amin(time)
tmax = amax(time)
try:
numpy.isfinite(amin(pixseries[i, j, :]))
numpy.isfinite(amin(pixseries[i, j, :]))
fmin = amin(pixseries[i, j, :])
fmax = amax(pixseries[i, j, :])
except:
ugh = 1
xmin = tmin - (tmax - tmin) / 40
xmax = tmax + (tmax - tmin) / 40
ymin = fmin - (fmax - fmin) / 20
ymax = fmax + (fmax - fmin) / 20
if kepstat.bitInBitmap(maskimg[i, j], 2):
pylab.axes([0.06 + float(j) * dx, 0.05 + i * dy, dx, dy],
axisbg='lightslategray')
elif maskimg[i, j] == 0:
pylab.axes([0.06 + float(j) * dx, 0.05 + i * dy, dx, dy],
axisbg='black')
else:
pylab.axes([0.06 + float(j) * dx, 0.05 + i * dy, dx, dy])
if j == int(xdim / 2) and i == 0:
pylab.setp(pylab.gca(), xticklabels=[], yticklabels=[])
elif j == 0 and i == int(ydim / 2):
pylab.setp(pylab.gca(), xticklabels=[], yticklabels=[])
else:
pylab.setp(pylab.gca(), xticklabels=[], yticklabels=[])
ptime = time * 1.0
ptime = numpy.insert(ptime, [0], ptime[0])
ptime = numpy.append(ptime, ptime[-1])
pflux = pixseries[i, j, :] * 1.0
pflux = numpy.insert(pflux, [0], -1000.0)
pflux = numpy.append(pflux, -1000.0)
pylab.plot(time,
pixseries[i, j, :],
color='#0000ff',
linestyle='-',
linewidth=0.5)
if not kepstat.bitInBitmap(maskimg[i, j], 2):
pylab.fill(ptime,
pflux,
fc='lightslategray',
linewidth=0.0,
alpha=1.0)
pylab.fill(ptime,
pflux,
fc='#FFF380',
linewidth=0.0,
alpha=1.0)
if 'loc' in plottype:
pylab.xlim(xmin, xmax)
pylab.ylim(ymin, ymax)
if 'glob' in plottype:
pylab.xlim(xmin, xmax)
pylab.ylim(1.0e-10, numpy.nanmax(pixseries) * 1.05)
if 'full' in plottype:
pylab.xlim(xmin, xmax)
pylab.ylim(1.0e-10, ymax * 1.05)
# render plot
if cmdLine:
pylab.show()
else:
pylab.ion()
pylab.plot([])
pylab.ioff()
if plotfile.lower() != 'none':
pylab.savefig(plotfile)
# stop time
if status == 0:
kepmsg.clock('KEPPIXSERIES ended at', logfile, verbose)
return
def kepfold(infile,outfile,period,phasezero,bindata,binmethod,threshold,niter,nbins,
rejqual,plottype,plotlab,clobber,verbose,logfile,status,cmdLine=False):
# startup parameters
status = 0
labelsize = 32; ticksize = 18; xsize = 18; ysize = 10
lcolor = '#0000ff'; lwidth = 2.0; fcolor = '#ffff00'; falpha = 0.2
# log the call
hashline = '----------------------------------------------------------------------------'
kepmsg.log(logfile,hashline,verbose)
call = 'KEPFOLD -- '
call += 'infile='+infile+' '
call += 'outfile='+outfile+' '
call += 'period='+str(period)+' '
call += 'phasezero='+str(phasezero)+' '
binit = 'n'
if (bindata): binit = 'y'
call += 'bindata='+binit+' '
call += 'binmethod='+binmethod+' '
call += 'threshold='+str(threshold)+' '
call += 'niter='+str(niter)+' '
call += 'nbins='+str(nbins)+' '
qflag = 'n'
if (rejqual): qflag = 'y'
call += 'rejqual='+qflag+ ' '
call += 'plottype='+plottype+ ' '
call += 'plotlab='+plotlab+ ' '
overwrite = 'n'
if (clobber): overwrite = 'y'
call += 'clobber='+overwrite+ ' '
chatter = 'n'
if (verbose): chatter = 'y'
call += 'verbose='+chatter+' '
call += 'logfile='+logfile
kepmsg.log(logfile,call+'\n',verbose)
# start time
kepmsg.clock('KEPFOLD started at',logfile,verbose)
# test log file
logfile = kepmsg.test(logfile)
# clobber output file
if clobber: status = kepio.clobber(outfile,logfile,verbose)
if kepio.fileexists(outfile):
message = 'ERROR -- KEPFOLD: ' + outfile + ' exists. Use --clobber'
status = kepmsg.err(logfile,message,verbose)
# open input file
if status == 0:
instr, status = kepio.openfits(infile,'readonly',logfile,verbose)
if status == 0:
tstart, tstop, bjdref, cadence, status = kepio.timekeys(instr,infile,logfile,verbose,status)
if status == 0:
try:
work = instr[0].header['FILEVER']
cadenom = 1.0
except:
cadenom = cadence
# fudge non-compliant FITS keywords with no values
if status == 0:
instr = kepkey.emptykeys(instr,file,logfile,verbose)
# input data
if status == 0:
table = instr[1].data
incards = instr[1].header.cards
try:
sap = instr[1].data.field('SAP_FLUX')
except:
try:
sap = instr[1].data.field('ap_raw_flux')
except:
sap = zeros(len(table.field(0)))
try:
saperr = instr[1].data.field('SAP_FLUX_ERR')
except:
try:
saperr = instr[1].data.field('ap_raw_err')
except:
saperr = zeros(len(table.field(0)))
try:
pdc = instr[1].data.field('PDCSAP_FLUX')
except:
try:
pdc = instr[1].data.field('ap_corr_flux')
except:
pdc = zeros(len(table.field(0)))
try:
pdcerr = instr[1].data.field('PDCSAP_FLUX_ERR')
except:
try:
pdcerr = instr[1].data.field('ap_corr_err')
except:
pdcerr = zeros(len(table.field(0)))
try:
cbv = instr[1].data.field('CBVSAP_FLUX')
except:
cbv = zeros(len(table.field(0)))
if 'cbv' in plottype:
txt = 'ERROR -- KEPFOLD: CBVSAP_FLUX column is not populated. Use kepcotrend'
status = kepmsg.err(logfile,txt,verbose)
try:
det = instr[1].data.field('DETSAP_FLUX')
except:
det = zeros(len(table.field(0)))
if 'det' in plottype:
txt = 'ERROR -- KEPFOLD: DETSAP_FLUX column is not populated. Use kepflatten'
status = kepmsg.err(logfile,txt,verbose)
try:
deterr = instr[1].data.field('DETSAP_FLUX_ERR')
except:
deterr = zeros(len(table.field(0)))
if 'det' in plottype:
txt = 'ERROR -- KEPFOLD: DETSAP_FLUX_ERR column is not populated. Use kepflatten'
status = kepmsg.err(logfile,txt,verbose)
try:
quality = instr[1].data.field('SAP_QUALITY')
except:
quality = zeros(len(table.field(0)))
if qualflag:
txt = 'WARNING -- KEPFOLD: Cannot find a QUALITY data column'
kepmsg.warn(logfile,txt)
if status == 0:
barytime, status = kepio.readtimecol(infile,table,logfile,verbose)
barytime1 = copy(barytime)
# filter out NaNs and quality > 0
work1 = []; work2 = []; work3 = []; work4 = []; work5 = []; work6 = []; work8 = []; work9 = []
if status == 0:
if 'sap' in plottype:
datacol = copy(sap)
errcol = copy(saperr)
if 'pdc' in plottype:
datacol = copy(pdc)
errcol = copy(pdcerr)
if 'cbv' in plottype:
datacol = copy(cbv)
errcol = copy(saperr)
if 'det' in plottype:
datacol = copy(det)
errcol = copy(deterr)
for i in range(len(barytime)):
if (numpy.isfinite(barytime[i]) and
numpy.isfinite(datacol[i]) and datacol[i] != 0.0 and
numpy.isfinite(errcol[i]) and errcol[i] > 0.0):
if rejqual and quality[i] == 0:
work1.append(barytime[i])
work2.append(sap[i])
work3.append(saperr[i])
work4.append(pdc[i])
work5.append(pdcerr[i])
work6.append(cbv[i])
work8.append(det[i])
work9.append(deterr[i])
elif not rejqual:
work1.append(barytime[i])
work2.append(sap[i])
work3.append(saperr[i])
work4.append(pdc[i])
work5.append(pdcerr[i])
work6.append(cbv[i])
work8.append(det[i])
work9.append(deterr[i])
barytime = array(work1,dtype='float64')
sap = array(work2,dtype='float32') / cadenom
saperr = array(work3,dtype='float32') / cadenom
pdc = array(work4,dtype='float32') / cadenom
pdcerr = array(work5,dtype='float32') / cadenom
cbv = array(work6,dtype='float32') / cadenom
det = array(work8,dtype='float32') / cadenom
deterr = array(work9,dtype='float32') / cadenom
# calculate phase
if status == 0:
if phasezero < bjdref:
phasezero += bjdref
date1 = (barytime1 + bjdref - phasezero)
phase1 = (date1 / period) - floor(date1/period)
date2 = (barytime + bjdref - phasezero)
phase2 = (date2 / period) - floor(date2/period)
phase2 = array(phase2,'float32')
# sort phases
if status == 0:
ptuple = []
phase3 = [];
sap3 = []; saperr3 = []
pdc3 = []; pdcerr3 = []
cbv3 = []; cbverr3 = []
det3 = []; deterr3 = []
for i in range(len(phase2)):
ptuple.append([phase2[i], sap[i], saperr[i], pdc[i], pdcerr[i], cbv[i], saperr[i], det[i], deterr[i]])
phsort = sorted(ptuple,key=lambda ph: ph[0])
for i in range(len(phsort)):
phase3.append(phsort[i][0])
sap3.append(phsort[i][1])
saperr3.append(phsort[i][2])
pdc3.append(phsort[i][3])
pdcerr3.append(phsort[i][4])
cbv3.append(phsort[i][5])
cbverr3.append(phsort[i][6])
det3.append(phsort[i][7])
deterr3.append(phsort[i][8])
phase3 = array(phase3,'float32')
sap3 = array(sap3,'float32')
saperr3 = array(saperr3,'float32')
pdc3 = array(pdc3,'float32')
pdcerr3 = array(pdcerr3,'float32')
cbv3 = array(cbv3,'float32')
cbverr3 = array(cbverr3,'float32')
det3 = array(det3,'float32')
deterr3 = array(deterr3,'float32')
# bin phases
if status == 0 and bindata:
work1 = array([sap3[0]],'float32')
work2 = array([saperr3[0]],'float32')
work3 = array([pdc3[0]],'float32')
work4 = array([pdcerr3[0]],'float32')
work5 = array([cbv3[0]],'float32')
work6 = array([cbverr3[0]],'float32')
work7 = array([det3[0]],'float32')
work8 = array([deterr3[0]],'float32')
phase4 = array([],'float32')
sap4 = array([],'float32')
saperr4 = array([],'float32')
pdc4 = array([],'float32')
pdcerr4 = array([],'float32')
cbv4 = array([],'float32')
cbverr4 = array([],'float32')
det4 = array([],'float32')
deterr4 = array([],'float32')
dt = 1.0 / nbins
nb = 0.0
rng = numpy.append(phase3,phase3[0]+1.0)
for i in range(len(rng)):
if rng[i] < nb * dt or rng[i] >= (nb + 1.0) * dt:
if len(work1) > 0:
phase4 = append(phase4,(nb + 0.5) * dt)
if (binmethod == 'mean'):
sap4 = append(sap4,kepstat.mean(work1))
saperr4 = append(saperr4,kepstat.mean_err(work2))
pdc4 = append(pdc4,kepstat.mean(work3))
pdcerr4 = append(pdcerr4,kepstat.mean_err(work4))
cbv4 = append(cbv4,kepstat.mean(work5))
cbverr4 = append(cbverr4,kepstat.mean_err(work6))
det4 = append(det4,kepstat.mean(work7))
deterr4 = append(deterr4,kepstat.mean_err(work8))
elif (binmethod == 'median'):
sap4 = append(sap4,kepstat.median(work1,logfile))
saperr4 = append(saperr4,kepstat.mean_err(work2))
pdc4 = append(pdc4,kepstat.median(work3,logfile))
pdcerr4 = append(pdcerr4,kepstat.mean_err(work4))
cbv4 = append(cbv4,kepstat.median(work5,logfile))
cbverr4 = append(cbverr4,kepstat.mean_err(work6))
det4 = append(det4,kepstat.median(work7,logfile))
deterr4 = append(deterr4,kepstat.mean_err(work8))
else:
coeffs, errors, covar, iiter, sigma, chi2, dof, fit, plotx, ploty, status = \
kepfit.lsqclip('poly0',[scipy.stats.nanmean(work1)],arange(0.0,float(len(work1)),1.0),work1,work2,
threshold,threshold,niter,logfile,False)
sap4 = append(sap4,coeffs[0])
saperr4 = append(saperr4,kepstat.mean_err(work2))
coeffs, errors, covar, iiter, sigma, chi2, dof, fit, plotx, ploty, status = \
kepfit.lsqclip('poly0',[scipy.stats.nanmean(work3)],arange(0.0,float(len(work3)),1.0),work3,work4,
threshold,threshold,niter,logfile,False)
pdc4 = append(pdc4,coeffs[0])
pdcerr4 = append(pdcerr4,kepstat.mean_err(work4))
coeffs, errors, covar, iiter, sigma, chi2, dof, fit, plotx, ploty, status = \
kepfit.lsqclip('poly0',[scipy.stats.nanmean(work5)],arange(0.0,float(len(work5)),1.0),work5,work6,
threshold,threshold,niter,logfile,False)
cbv4 = append(cbv4,coeffs[0])
cbverr4 = append(cbverr4,kepstat.mean_err(work6))
coeffs, errors, covar, iiter, sigma, chi2, dof, fit, plotx, ploty, status = \
kepfit.lsqclip('poly0',[scipy.stats.nanmean(work7)],arange(0.0,float(len(work7)),1.0),work7,work8,
threshold,threshold,niter,logfile,False)
det4 = append(det4,coeffs[0])
deterr4 = append(deterr4,kepstat.mean_err(work8))
work1 = array([],'float32')
work2 = array([],'float32')
work3 = array([],'float32')
work4 = array([],'float32')
work5 = array([],'float32')
work6 = array([],'float32')
work7 = array([],'float32')
work8 = array([],'float32')
nb += 1.0
else:
work1 = append(work1,sap3[i])
work2 = append(work2,saperr3[i])
work3 = append(work3,pdc3[i])
work4 = append(work4,pdcerr3[i])
work5 = append(work5,cbv3[i])
work6 = append(work6,cbverr3[i])
work7 = append(work7,det3[i])
work8 = append(work8,deterr3[i])
# update HDU1 for output file
if status == 0:
cols = (instr[1].columns + ColDefs([Column(name='PHASE',format='E',array=phase1)]))
instr[1] = pyfits.new_table(cols)
instr[1].header.cards['TTYPE'+str(len(instr[1].columns))].comment = 'column title: phase'
instr[1].header.cards['TFORM'+str(len(instr[1].columns))].comment = 'data type: float32'
for i in range(len(incards)):
if incards[i].key not in instr[1].header.keys():
instr[1].header.update(incards[i].key, incards[i].value, incards[i].comment)
else:
instr[1].header.cards[incards[i].key].comment = incards[i].comment
instr[1].header.update('PERIOD',period,'period defining the phase [d]')
instr[1].header.update('BJD0',phasezero,'time of phase zero [BJD]')
# write new phased data extension for output file
if status == 0 and bindata:
col1 = Column(name='PHASE',format='E',array=phase4)
col2 = Column(name='SAP_FLUX',format='E',unit='e/s',array=sap4/cadenom)
col3 = Column(name='SAP_FLUX_ERR',format='E',unit='e/s',array=saperr4/cadenom)
col4 = Column(name='PDC_FLUX',format='E',unit='e/s',array=pdc4/cadenom)
col5 = Column(name='PDC_FLUX_ERR',format='E',unit='e/s',array=pdcerr4/cadenom)
col6 = Column(name='CBV_FLUX',format='E',unit='e/s',array=cbv4/cadenom)
col7 = Column(name='DET_FLUX',format='E',array=det4/cadenom)
col8 = Column(name='DET_FLUX_ERR',format='E',array=deterr4/cadenom)
cols = ColDefs([col1,col2,col3,col4,col5,col6,col7,col8])
instr.append(new_table(cols))
instr[-1].header.cards['TTYPE1'].comment = 'column title: phase'
instr[-1].header.cards['TTYPE2'].comment = 'column title: simple aperture photometry'
instr[-1].header.cards['TTYPE3'].comment = 'column title: SAP 1-sigma error'
instr[-1].header.cards['TTYPE4'].comment = 'column title: pipeline conditioned photometry'
instr[-1].header.cards['TTYPE5'].comment = 'column title: PDC 1-sigma error'
instr[-1].header.cards['TTYPE6'].comment = 'column title: cotrended basis vector photometry'
instr[-1].header.cards['TTYPE7'].comment = 'column title: Detrended aperture photometry'
instr[-1].header.cards['TTYPE8'].comment = 'column title: DET 1-sigma error'
instr[-1].header.cards['TFORM1'].comment = 'column type: float32'
instr[-1].header.cards['TFORM2'].comment = 'column type: float32'
instr[-1].header.cards['TFORM3'].comment = 'column type: float32'
instr[-1].header.cards['TFORM4'].comment = 'column type: float32'
instr[-1].header.cards['TFORM5'].comment = 'column type: float32'
instr[-1].header.cards['TFORM6'].comment = 'column type: float32'
instr[-1].header.cards['TFORM7'].comment = 'column type: float32'
instr[-1].header.cards['TFORM8'].comment = 'column type: float32'
instr[-1].header.cards['TUNIT2'].comment = 'column units: electrons per second'
instr[-1].header.cards['TUNIT3'].comment = 'column units: electrons per second'
instr[-1].header.cards['TUNIT4'].comment = 'column units: electrons per second'
instr[-1].header.cards['TUNIT5'].comment = 'column units: electrons per second'
instr[-1].header.cards['TUNIT6'].comment = 'column units: electrons per second'
instr[-1].header.update('EXTNAME','FOLDED','extension name')
instr[-1].header.update('PERIOD',period,'period defining the phase [d]')
instr[-1].header.update('BJD0',phasezero,'time of phase zero [BJD]')
instr[-1].header.update('BINMETHD',binmethod,'phase binning method')
if binmethod =='sigclip':
instr[-1].header.update('THRSHOLD',threshold,'sigma-clipping threshold [sigma]')
instr[-1].header.update('NITER',niter,'max number of sigma-clipping iterations')
# history keyword in output file
if status == 0:
status = kepkey.history(call,instr[0],outfile,logfile,verbose)
instr.writeto(outfile)
# clean up x-axis unit
if status == 0:
ptime1 = array([],'float32')
ptime2 = array([],'float32')
pout1 = array([],'float32')
pout2 = array([],'float32')
if bindata:
work = sap4
if plottype == 'pdc':
work = pdc4
if plottype == 'cbv':
work = cbv4
if plottype == 'det':
work = det4
for i in range(len(phase4)):
if (phase4[i] > 0.5):
ptime2 = append(ptime2,phase4[i] - 1.0)
pout2 = append(pout2,work[i])
ptime2 = append(ptime2,phase4)
pout2 = append(pout2,work)
for i in range(len(phase4)):
if (phase4[i] <= 0.5):
ptime2 = append(ptime2,phase4[i] + 1.0)
pout2 = append(pout2,work[i])
work = sap3
if plottype == 'pdc':
work = pdc3
if plottype == 'cbv':
work = cbv3
if plottype == 'det':
work = det3
for i in range(len(phase3)):
if (phase3[i] > 0.5):
ptime1 = append(ptime1,phase3[i] - 1.0)
pout1 = append(pout1,work[i])
ptime1 = append(ptime1,phase3)
pout1 = append(pout1,work)
for i in range(len(phase3)):
if (phase3[i] <= 0.5):
ptime1 = append(ptime1,phase3[i] + 1.0)
pout1 = append(pout1,work[i])
xlab = 'Orbital Phase ($\phi$)'
# clean up y-axis units
if status == 0:
nrm = len(str(int(pout1[isfinite(pout1)].max())))-1
pout1 = pout1 / 10**nrm
pout2 = pout2 / 10**nrm
if nrm == 0:
ylab = plotlab
else:
ylab = '10$^%d$ %s' % (nrm, plotlab)
# data limits
xmin = ptime1.min()
xmax = ptime1.max()
ymin = pout1[isfinite(pout1)].min()
ymax = pout1[isfinite(pout1)].max()
xr = xmax - xmin
yr = ymax - ymin
ptime1 = insert(ptime1,[0],[ptime1[0]])
ptime1 = append(ptime1,[ptime1[-1]])
pout1 = insert(pout1,[0],[0.0])
pout1 = append(pout1,0.0)
if bindata:
ptime2 = insert(ptime2,[0],ptime2[0] - 1.0 / nbins)
ptime2 = insert(ptime2,[0],ptime2[0])
ptime2 = append(ptime2,[ptime2[-1] + 1.0 / nbins, ptime2[-1] + 1.0 / nbins])
pout2 = insert(pout2,[0],[pout2[-1]])
pout2 = insert(pout2,[0],[0.0])
pout2 = append(pout2,[pout2[2],0.0])
# plot new light curve
if status == 0 and plottype != 'none':
try:
params = {'backend': 'png',
'axes.linewidth': 2.5,
'axes.labelsize': labelsize,
'axes.font': 'sans-serif',
'axes.fontweight' : 'bold',
'text.fontsize': 18,
'legend.fontsize': 18,
'xtick.labelsize': ticksize,
'ytick.labelsize': ticksize}
pylab.rcParams.update(params)
except:
print 'ERROR -- KEPFOLD: install latex for scientific plotting'
status = 1
if status == 0 and plottype != 'none':
pylab.figure(figsize=[17,7])
pylab.clf()
ax = pylab.axes([0.06,0.11,0.93,0.86])
pylab.gca().xaxis.set_major_formatter(pylab.ScalarFormatter(useOffset=False))
pylab.gca().yaxis.set_major_formatter(pylab.ScalarFormatter(useOffset=False))
labels = ax.get_yticklabels()
setp(labels, 'rotation', 90)
if bindata:
pylab.fill(ptime2,pout2,color=fcolor,linewidth=0.0,alpha=falpha)
else:
if 'det' in plottype:
pylab.fill(ptime1,pout1,color=fcolor,linewidth=0.0,alpha=falpha)
pylab.plot(ptime1,pout1,color=lcolor,linestyle='',linewidth=lwidth,marker='.')
if bindata:
pylab.plot(ptime2[1:-1],pout2[1:-1],color='r',linestyle='-',linewidth=lwidth,marker='')
xlabel(xlab, {'color' : 'k'})
ylabel(ylab, {'color' : 'k'})
xlim(-0.49999,1.49999)
if ymin >= 0.0:
ylim(ymin-yr*0.01,ymax+yr*0.01)
# ylim(0.96001,1.03999)
else:
ylim(1.0e-10,ymax+yr*0.01)
grid()
if cmdLine:
pylab.show()
else:
pylab.ion()
pylab.plot([])
pylab.ioff()
# close input file
if status == 0:
status = kepio.closefits(instr,logfile,verbose)
# stop time
kepmsg.clock('KEPFOLD ended at: ',logfile,verbose)
def MASTRADec(ra, dec, darcsec, srctab, logfile):
# coordinate limits
darcsec /= 3600.0
ra1 = ra - darcsec / np.cos(dec * np.pi / 180)
ra2 = ra + darcsec / np.cos(dec * np.pi / 180)
dec1 = dec - darcsec
dec2 = dec + darcsec
# build mast query
url = "http://archive.stsci.edu/kepler/kepler_fov/search.php?"
url += "action=Search"
url += "&masterRA=" + str(ra1) + ".." + str(ra2)
url += "&masterDec=" + str(dec1) + ".." + str(dec2)
url += "&max_records=10000"
url += "&verb=3"
url += "&outputformat=CSV"
# retrieve results from MAST
if srctab:
try:
lines = urllib.request.urlopen(url)
except:
message = "WARNING -- KEPFIELD: Cannot retrieve data from MAST"
status = kepmsg.warn(logfile, message)
lines = ""
else:
lines = ""
# collate nearby sources
kepid = []
kepmag = []
ra = []
dec = []
for line in lines:
line = line.strip().decode("ascii")
if len(line) > 0 and "Kepler" not in line and "integer" not in line and "no rows found" not in line:
out = line.split(",")
r, d = sex2dec(out[0], out[1])
try:
if out[-22] != "Possible_artifact":
kepid.append(int(out[2]))
except:
if out[-22] != "Possible_artifact":
kepid.append(0)
try:
if out[-22] != "Possible_artifact":
kepmag.append(float(out[42]))
except:
if out[-22] != "Possible_artifact":
kepmag.append(0.0)
if out[-22] != "Possible_artifact":
ra.append(r)
if out[-22] != "Possible_artifact":
dec.append(d)
kepid = np.array(kepid)
kepmag = np.array(kepmag)
ra = np.array(ra)
dec = np.array(dec)
return kepid, ra, dec, kepmag
