def kepdeltapix(infile,
nexp,
columns,
rows,
fluxes,
prfdir,
interpolation,
tolerance,
fittype,
imscale,
colmap,
verbose,
logfile,
status,
cmdLine=False):
# input arguments
status = 0
seterr(all="ignore")
# log the call
hashline = '----------------------------------------------------------------------------'
kepmsg.log(logfile, hashline, verbose)
call = 'KEPDELTAPIX -- '
call += 'infile=' + infile + ' '
call += 'nexp=' + str(nexp) + ' '
call += 'columns=' + columns + ' '
call += 'rows=' + rows + ' '
call += 'fluxes=' + fluxes + ' '
call += 'prfdir=' + prfdir + ' '
call += 'interpolation=' + interpolation + ' '
call += 'tolerance=' + str(tolerance) + ' '
call += 'fittype=' + str(fittype) + ' '
call += 'imscale=' + imscale + ' '
call += 'colmap=' + colmap + ' '
chatter = 'n'
if (verbose): chatter = 'y'
call += 'verbose=' + chatter + ' '
call += 'logfile=' + logfile
kepmsg.log(logfile, call + '\n', verbose)
# test log file
logfile = kepmsg.test(logfile)
# start time
kepmsg.clock('KEPDELTAPIX started at', logfile, verbose)
# reference color map
if colmap == 'browse':
status = cmap_plot(cmdLine)
# open TPF FITS file
if status == 0:
try:
kepid, channel, skygroup, module, output, quarter, season, \
ra, dec, column, row, kepmag, xdim, ydim, barytime, status = \
kepio.readTPF(infile,'TIME',logfile,verbose)
except:
message = 'ERROR -- KEPDELTAPIX: is %s a Target Pixel File? ' % infile
status = kepmsg.err(logfile, message, 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)
# print target data
if status == 0 and verbose:
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 ''
# determine suitable PRF calibration file
if status == 0:
if int(module) < 10:
prefix = 'kplr0'
else:
prefix = 'kplr'
prfglob = prfdir + '/' + prefix + str(module) + '.' + str(
output) + '*' + '_prf.fits'
try:
prffile = glob.glob(prfglob)[0]
except:
message = 'ERROR -- KEPDELTAPIX: No PRF file found in ' + prfdir
status = kepmsg.err(logfile, message, verbose)
# read PRF images
if status == 0:
prfn = [0, 0, 0, 0, 0]
crpix1p = numpy.zeros((5), dtype='float32')
crpix2p = numpy.zeros((5), dtype='float32')
crval1p = numpy.zeros((5), dtype='float32')
crval2p = numpy.zeros((5), dtype='float32')
cdelt1p = numpy.zeros((5), dtype='float32')
cdelt2p = numpy.zeros((5), dtype='float32')
for i in range(5):
prfn[i], crpix1p[i], crpix2p[i], crval1p[i], crval2p[i], cdelt1p[i], cdelt2p[i], status \
= kepio.readPRFimage(prffile,i+1,logfile,verbose)
# choose rows in the TPF table at random
if status == 0:
i = 0
rownum = []
while i < nexp:
work = int(random.random() * len(barytime))
if numpy.isfinite(barytime[work]) and numpy.isfinite(
fluxpixels[work, ydim * xdim / 2]):
rownum.append(work)
i += 1
# construct input pixel image
if status == 0:
fscat = numpy.empty((len(fluxes), nexp), dtype='float32')
xscat = numpy.empty((len(columns), nexp), dtype='float32')
yscat = numpy.empty((len(rows), nexp), dtype='float32')
for irow in range(nexp):
flux = fluxpixels[rownum[irow], :]
# image scale and intensity limits of pixel data
if status == 0:
flux_pl, zminfl, zmaxfl = kepplot.intScale1D(flux, imscale)
n = 0
imgflux_pl = empty((ydim, xdim))
for i in range(ydim):
for j in range(xdim):
imgflux_pl[i, j] = flux_pl[n]
n += 1
# fit PRF model to pixel data
if status == 0:
start = time.time()
f, y, x, prfMod, prfFit, prfRes = kepfit.fitMultiPRF(
flux, ydim, xdim, column, row, prfn, crval1p, crval2p,
cdelt1p, cdelt2p, interpolation, tolerance, fluxes,
columns, rows, fittype, verbose, logfile)
if verbose:
print '\nConvergence time = %.1fs' % (time.time() - start)
# best fit parameters
if status == 0:
for i in range(len(f)):
fscat[i, irow] = f[i]
xscat[i, irow] = x[i]
yscat[i, irow] = y[i]
# replace starting guess with previous fit parameters
if status == 0:
fluxes = copy(f)
columns = copy(x)
rows = copy(y)
# mean and rms results
if status == 0:
fmean = []
fsig = []
xmean = []
xsig = []
ymean = []
ysig = []
for i in range(len(f)):
fmean.append(numpy.mean(fscat[i, :]))
xmean.append(numpy.mean(xscat[i, :]))
ymean.append(numpy.mean(yscat[i, :]))
fsig.append(numpy.std(fscat[i, :]))
xsig.append(numpy.std(xscat[i, :]))
ysig.append(numpy.std(yscat[i, :]))
txt = 'Flux = %10.2f e-/s ' % fmean[-1]
txt += 'X = %7.4f +/- %6.4f pix ' % (xmean[-1], xsig[i])
txt += 'Y = %7.4f +/- %6.4f pix' % (ymean[-1], ysig[i])
kepmsg.log(logfile, txt, True)
# output results for kepprfphot
if status == 0:
txt1 = 'columns=0.0'
txt2 = ' rows=0.0'
for i in range(1, len(f)):
txt1 += ',%.4f' % (xmean[i] - xmean[0])
txt2 += ',%.4f' % (ymean[i] - ymean[0])
kepmsg.log(logfile, '\nkepprfphot input fields:', True)
kepmsg.log(logfile, txt1, True)
kepmsg.log(logfile, txt2, True)
# image scale and intensity limits for PRF model image
if status == 0:
imgprf_pl, zminpr, zmaxpr = kepplot.intScale2D(prfMod, imscale)
# image scale and intensity limits for PRF fit image
if status == 0:
imgfit_pl, zminfi, zmaxfi = kepplot.intScale2D(prfFit, imscale)
# image scale and intensity limits for data - fit residual
if status == 0:
imgres_pl, zminre, zmaxre = kepplot.intScale2D(prfRes, imscale)
# plot style
if status == 0:
try:
params = {
'backend': 'png',
'axes.linewidth': 2.5,
'axes.labelsize': 24,
'axes.font': 'sans-serif',
'axes.fontweight': 'bold',
'text.fontsize': 12,
'legend.fontsize': 12,
'xtick.labelsize': 10,
'ytick.labelsize': 10
}
pylab.rcParams.update(params)
except:
pass
pylab.figure(figsize=[10, 10])
pylab.clf()
plotimage(imgflux_pl, zminfl, zmaxfl, 1, row, column, xdim, ydim, 0.06,
0.52, 'flux', colmap)
plotimage(imgfit_pl, zminfl, zmaxfl, 3, row, column, xdim, ydim, 0.06,
0.06, 'fit', colmap)
plotimage(imgres_pl, zminfl, zmaxfl, 4, row, column, xdim, ydim, 0.52,
0.06, 'residual', colmap)
plotimage(imgprf_pl, zminpr, zmaxpr * 0.9, 2, row, column, xdim, ydim,
0.52, 0.52, 'model', colmap)
for i in range(len(f)):
pylab.plot(xscat[i, :], yscat[i, :], 'o', color='k')
# Plot creep of target position over time, relative to the central source
# barytime0 = float(int(barytime[0] / 100) * 100.0)
# barytime -= barytime0
# xlab = 'BJD $-$ %d' % barytime0
# xmin = numpy.nanmin(barytime)
# xmax = numpy.nanmax(barytime)
# y1min = numpy.nanmin(data)
# y1max = numpy.nanmax(data)
# xr = xmax - xmin
# yr = ymax - ymin
# barytime = insert(barytime,[0],[barytime[0]])
# barytime = append(barytime,[barytime[-1]])
# data = insert(data,[0],[0.0])
# data = append(data,0.0)
#
# pylab.figure(2,figsize=[10,10])
# pylab.clf()
# ax = pylab.subplot(211)
# pylab.subplots_adjust(0.1,0.5,0.88,0.42)
# 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, fontsize=ticksize)
# for i in range(1,len(f)):
# pylab.plot(rownum,xscat[i,:]-xscat[0,:],'o')
# pylab.ylabel('$\Delta$Columns', {'color' : 'k'})
# ax = pylab.subplot(211)
# pylab.subplots_adjust(0.1,0.1,0.88,0.42)
# 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, fontsize=ticksize)
# for i in range(1,len(f)):
# pylab.plot(rownum,yscat[i,:]-yscat[0,:],'o')
# pylab.xlim(xmin-xr*0.01,xmax+xr*0.01)
# if ymin-yr*0.01 <= 0.0 or fullrange:
# pylab.ylim(1.0e-10,ymax+yr*0.01)
# else:
# pylab.ylim(ymin-yr*0.01,ymax+yr*0.01)
# pylab.ylabel('$\Delta$Rows', {'color' : 'k'})
# pylab.xlabel(xlab, {'color' : 'k'})
# render plot
if status == 0:
if cmdLine:
pylab.show(block=True)
else:
pylab.ion()
pylab.plot([])
pylab.ioff()
# stop time
kepmsg.clock('\nKEPDELTAPIX ended at', logfile, verbose)
return
def kepmask(infile,mfile,pfile,tabrow,imin,imax,iscale,cmap,verbose,logfile,status,cLine=False):
global pimg, zscale, zmin, zmax, xmin, xmax, ymin, ymax, quarter
global pxdim, pydim, kepmag, skygroup, season, channel
global module, output, row, column, maskfile, plotfile
global pkepid, pkepmag, pra, pdec, colmap, cmdLine
# input arguments
status = 0
numpy.seterr(all="ignore")
zmin = imin; zmax = imax; zscale = iscale; colmap = cmap
maskfile = mfile; plotfile = pfile
cmdLine = cLine
# log the call
hashline = '----------------------------------------------------------------------------'
kepmsg.log(logfile,hashline,verbose)
call = 'KEPMASK -- '
call += 'infile='+infile+' '
call += 'maskfile='+mfile+' '
call += 'plotfile='+pfile+' '
call += 'tabrow='+str(tabrow)+' '
call += 'imin='+str(imin)+' '
call += 'imax='+str(imax)+' '
call += 'iscale='+str(iscale)+' '
call += 'cmap='+str(cmap)+' '
chatter = 'n'
if (verbose): chatter = 'y'
call += 'verbose='+chatter+' '
call += 'logfile='+logfile
kepmsg.log(logfile,call+'\n',verbose)
# start time
kepmsg.clock('KEPMASK started at',logfile,verbose)
# reference color map
if cmap == 'browse':
status = cmap_plot()
# open TPF FITS file and check tabrow exists
if status == 0:
tpf, status = kepio.openfits(infile,'readonly',logfile,verbose)
if status == 0:
try:
naxis2 = tpf['TARGETTABLES'].header['NAXIS2']
except:
txt = 'ERROR -- KEPMASK: No NAXIS2 keyword in ' + infile + '[TARGETTABLES]'
status = kepmsg.err(logfile,txt,True)
if status == 0 and tabrow > naxis2:
txt = 'ERROR -- KEPMASK: tabrow is too large. There are ' + str(naxis2) + ' rows in the table.'
status = kepmsg.err(logfile,txt,True)
if status == 0:
status = kepio.closefits(tpf,logfile,verbose)
# read TPF data pixel image
if status == 0:
kepid, channel, skygroup, module, output, quarter, season, \
ra, dec, column, row, kepmag, xdim, ydim, pixels, status = \
kepio.readTPF(infile,'FLUX',logfile,verbose)
img = pixels[tabrow]
pkepid = copy(kepid)
pra = copy(ra)
pdec = copy(dec)
pkepmag = copy(kepmag)
pxdim = copy(xdim)
pydim = copy(ydim)
pimg = copy(img)
# 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('')
# subimage of channel for plot
if status == 0:
ymin = copy(row)
ymax = ymin + ydim
xmin = copy(column)
xmax = xmin + xdim
# intensity scale
if status == 0:
pimg, imin, imax = kepplot.intScale1D(pimg,zscale)
if zmin and zmax and 'log' in zscale:
zmin = log10(zmin)
zmax = log10(zmax)
elif zmin and zmax and 'sq' in zscale:
zmin = sqrt(zmin)
zmax = sqrt(zmax)
elif zmin and zmax and 'li' in zscale:
zmin *= 1.0
zmax *= 1.0
else:
zmin = copy(imin)
zmax = copy(imax)
# nstat = 2; pixels = []
# work = array(sort(img),dtype=float32)
# for i in range(len(work)):
# if 'nan' not in str(work[i]):
# pixels.append(work[i])
# pixels = array(pixels,dtype=float32)
# if int(float(len(pixels)) / 10 + 0.5) > nstat:
# nstat = int(float(len(pixels)) / 10 + 0.5)
# if not zmin:
# zmin = median(pixels[:nstat])
# if not zmax:
# zmax = median(pixels[-nstat:])
# if 'log' in zscale:
# pimg = log10(pimg)
# if 'sq' in zscale:
# pimg = sqrt(pimg)
# plot limits
ymin = float(ymin) - 0.5
ymax = float(ymax) - 0.5
xmin = float(xmin) - 0.5
xmax = float(xmax) - 0.5
# plot style
try:
params = {'backend': 'png',
'axes.linewidth': 2.5,
'axes.labelsize': 24,
'axes.font': 'sans-serif',
'axes.fontweight' : 'bold',
'text.fontsize': 12,
'legend.fontsize': 12,
'xtick.labelsize': 14,
'ytick.labelsize': 14}
pylab.rcParams.update(params)
except:
pass
if status == 0:
pylab.figure(figsize=[10,7])
plotimage(cmdLine)
return
def kepmask(infile,
mfile,
pfile,
tabrow,
imin,
imax,
iscale,
cmap,
verbose,
logfile,
status,
cLine=False):
global pimg, zscale, zmin, zmax, xmin, xmax, ymin, ymax, quarter
global pxdim, pydim, kepmag, skygroup, season, channel
global module, output, row, column, maskfile, plotfile
global pkepid, pkepmag, pra, pdec, colmap, cmdLine
# input arguments
status = 0
numpy.seterr(all="ignore")
zmin = imin
zmax = imax
zscale = iscale
colmap = cmap
maskfile = mfile
plotfile = pfile
cmdLine = cLine
# log the call
hashline = '----------------------------------------------------------------------------'
kepmsg.log(logfile, hashline, verbose)
call = 'KEPMASK -- '
call += 'infile=' + infile + ' '
call += 'maskfile=' + mfile + ' '
call += 'plotfile=' + pfile + ' '
call += 'tabrow=' + str(tabrow) + ' '
call += 'imin=' + str(imin) + ' '
call += 'imax=' + str(imax) + ' '
call += 'iscale=' + str(iscale) + ' '
call += 'cmap=' + str(cmap) + ' '
chatter = 'n'
if (verbose): chatter = 'y'
call += 'verbose=' + chatter + ' '
call += 'logfile=' + logfile
kepmsg.log(logfile, call + '\n', verbose)
# start time
kepmsg.clock('KEPMASK started at', logfile, verbose)
# reference color map
if cmap == 'browse':
status = cmap_plot()
# open TPF FITS file and check tabrow exists
if status == 0:
tpf, status = kepio.openfits(infile, 'readonly', logfile, verbose)
if status == 0:
try:
naxis2 = tpf['TARGETTABLES'].header['NAXIS2']
except:
txt = 'ERROR -- KEPMASK: No NAXIS2 keyword in ' + infile + '[TARGETTABLES]'
status = kepmsg.err(logfile, txt, True)
if status == 0 and tabrow > naxis2:
txt = 'ERROR -- KEPMASK: tabrow is too large. There are ' + str(
naxis2) + ' rows in the table.'
status = kepmsg.err(logfile, txt, True)
if status == 0:
status = kepio.closefits(tpf, logfile, verbose)
# read TPF data pixel image
if status == 0:
kepid, channel, skygroup, module, output, quarter, season, \
ra, dec, column, row, kepmag, xdim, ydim, pixels, status = \
kepio.readTPF(infile,'FLUX',logfile,verbose)
img = pixels[tabrow]
pkepid = copy(kepid)
pra = copy(ra)
pdec = copy(dec)
pkepmag = copy(kepmag)
pxdim = copy(xdim)
pydim = copy(ydim)
pimg = copy(img)
# 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 ''
# subimage of channel for plot
if status == 0:
ymin = copy(row)
ymax = ymin + ydim
xmin = copy(column)
xmax = xmin + xdim
# intensity scale
if status == 0:
pimg, imin, imax = kepplot.intScale1D(pimg, zscale)
if zmin and zmax and 'log' in zscale:
zmin = log10(zmin)
zmax = log10(zmax)
elif zmin and zmax and 'sq' in zscale:
zmin = sqrt(zmin)
zmax = sqrt(zmax)
elif zmin and zmax and 'li' in zscale:
zmin *= 1.0
zmax *= 1.0
else:
zmin = copy(imin)
zmax = copy(imax)
# nstat = 2; pixels = []
# work = array(sort(img),dtype=float32)
# for i in range(len(work)):
# if 'nan' not in str(work[i]):
# pixels.append(work[i])
# pixels = array(pixels,dtype=float32)
# if int(float(len(pixels)) / 10 + 0.5) > nstat:
# nstat = int(float(len(pixels)) / 10 + 0.5)
# if not zmin:
# zmin = median(pixels[:nstat])
# if not zmax:
# zmax = median(pixels[-nstat:])
# if 'log' in zscale:
# pimg = log10(pimg)
# if 'sq' in zscale:
# pimg = sqrt(pimg)
# plot limits
ymin = float(ymin) - 0.5
ymax = float(ymax) - 0.5
xmin = float(xmin) - 0.5
xmax = float(xmax) - 0.5
# plot style
try:
params = {
'backend': 'png',
'axes.linewidth': 2.5,
'axes.labelsize': 24,
'axes.font': 'sans-serif',
'axes.fontweight': 'bold',
'text.fontsize': 12,
'legend.fontsize': 12,
'xtick.labelsize': 14,
'ytick.labelsize': 14
}
pylab.rcParams.update(params)
except:
pass
if status == 0:
pylab.figure(figsize=[10, 7])
plotimage(cmdLine)
return
def kepfield(infile,plotfile,rownum,imscale,colmap,lcolor,srctab,verbose,logfile,status,cmdLine=False):
# input arguments
status = 0
seterr(all="ignore")
# log the call
hashline = '----------------------------------------------------------------------------'
kepmsg.log(logfile,hashline,verbose)
call = 'KEPFIELD -- '
call += 'infile='+infile+' '
call += 'plotfile='+plotfile+' '
call += 'rownum='+str(rownum)+' '
call += 'imscale='+imscale+' '
call += 'colmap='+colmap+' '
call += 'lcolor='+lcolor+' '
srct = 'n'
if (srctab): srct = 'y'
call += 'srctab='+srct+' '
chatter = 'n'
if (verbose): chatter = 'y'
call += 'verbose='+chatter+' '
call += 'logfile='+logfile
kepmsg.log(logfile,call+'\n',verbose)
# start time
kepmsg.clock('KEPFIELD started at',logfile,verbose)
# test log file
logfile = kepmsg.test(logfile)
# reference color map
if colmap == 'browse':
status = cmap_plot(cmdLine)
# open TPF FITS file
if status == 0:
try:
kepid, channel, skygroup, module, output, quarter, season, \
ra, dec, column, row, kepmag, xdim, ydim, barytime, status = \
kepio.readTPF(infile,'TIME',logfile,verbose)
except:
message = 'ERROR -- KEPFIELD: is %s a Target Pixel File? ' % infile
status = kepmsg.err(logfile,message,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)
# observed or simulated data?
if status == 0:
coa = False
instr = pyfits.open(infile,mode='readonly',memmap=True)
filever, status = kepkey.get(infile,instr[0],'FILEVER',logfile,verbose)
if filever == 'COA': coa = True
# print target data
if status == 0 and verbose:
print('')
print(' KepID: %s' % kepid)
print(' BJD: %.2f' % (barytime[rownum-1] + 2454833.0))
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('')
# is this a good row with finite timestamp and pixels?
if status == 0:
if not numpy.isfinite(barytime[rownum-1]) or not numpy.nansum(fluxpixels[rownum-1,:]):
message = 'ERROR -- KEPFIELD: Row ' + str(rownum) + ' is a bad quality timestamp'
status = kepmsg.err(logfile,message,verbose)
# construct input pixel image
if status == 0:
flux = fluxpixels[rownum-1,:]
# image scale and intensity limits of pixel data
if status == 0:
flux_pl, zminfl, zmaxfl = kepplot.intScale1D(flux,imscale)
n = 0
imgflux_pl = empty((ydim+2,xdim+2))
for i in range(ydim+2):
for j in range(xdim+2):
imgflux_pl[i,j] = numpy.nan
for i in range(ydim):
for j in range(xdim):
imgflux_pl[i+1,j+1] = flux_pl[n]
n += 1
# cone search around target coordinates using the MAST target search form
if status == 0:
dr = max([ydim+2,xdim+2]) * 4.0
kepid,ra,dec,kepmag = MASTRADec(float(ra),float(dec),dr,srctab)
# convert celestial coordinates to detector coordinates
if status == 0:
sx = numpy.array([])
sy = numpy.array([])
inf, status = kepio.openfits(infile,'readonly',logfile,verbose)
try:
crpix1, crpix2, crval1, crval2, cdelt1, cdelt2, pc, status = \
kepkey.getWCSs(infile,inf['APERTURE'],logfile,verbose)
crpix1p, crpix2p, crval1p, crval2p, cdelt1p, cdelt2p, status = \
kepkey.getWCSp(infile,inf['APERTURE'],logfile,verbose)
for i in range(len(kepid)):
dra = (ra[i] - crval1) * math.cos(math.radians(dec[i])) / cdelt1
ddec = (dec[i] - crval2) / cdelt2
if coa:
sx = numpy.append(sx,-(pc[0,0] * dra + pc[0,1] * ddec) + crpix1 + crval1p - 1.0)
else:
sx = numpy.append(sx,pc[0,0] * dra + pc[0,1] * ddec + crpix1 + crval1p - 1.0)
sy = numpy.append(sy,pc[1,0] * dra + pc[1,1] * ddec + crpix2 + crval2p - 1.0)
except:
message = 'ERROR -- KEPFIELD: Non-compliant WCS information within file %s' % infile
status = kepmsg.err(logfile,message,verbose)
# plot style
if status == 0:
try:
params = {'backend': 'png',
'axes.linewidth': 2.5,
'axes.labelsize': 48,
'axes.font': 'sans-serif',
'axes.fontweight' : 'bold',
'text.fontsize': 12,
'legend.fontsize': 12,
'xtick.labelsize': 20,
'ytick.labelsize': 20}
pylab.rcParams.update(params)
except:
pass
pylab.figure(figsize=[10,10])
pylab.clf()
# pixel limits of the subimage
if status == 0:
ymin = copy(float(row))
ymax = ymin + ydim
xmin = copy(float(column))
xmax = xmin + xdim
# plot limits for flux image
if status == 0:
ymin = float(ymin) - 1.5
ymax = float(ymax) + 0.5
xmin = float(xmin) - 1.5
xmax = float(xmax) + 0.5
# plot the image window
if status == 0:
ax = pylab.axes([0.1,0.11,0.88,0.88])
pylab.imshow(imgflux_pl,aspect='auto',interpolation='nearest',origin='lower',
vmin=zminfl,vmax=zmaxfl,extent=(xmin,xmax,ymin,ymax),cmap=colmap)
pylab.gca().set_autoscale_on(False)
labels = ax.get_yticklabels()
setp(labels, 'rotation', 90)
pylab.gca().xaxis.set_major_formatter(pylab.ScalarFormatter(useOffset=False))
pylab.gca().yaxis.set_major_formatter(pylab.ScalarFormatter(useOffset=False))
pylab.xlabel('Pixel Column Number', {'color' : 'k'})
pylab.ylabel('Pixel Row Number', {'color' : 'k'})
# plot mask borders
if status == 0:
kepplot.borders(maskimg,xdim,ydim,pixcoord1,pixcoord2,1,lcolor,'--',0.5)
# plot aperture borders
if status == 0:
kepplot.borders(maskimg,xdim,ydim,pixcoord1,pixcoord2,2,lcolor,'-',4.0)
# list sources
if status == 0:
print('Column Row RA J2000 Dec J2000 Kp Kepler ID')
print('----------------------------------------------------')
for i in range(len(sx)-1,-1,-1):
if sx[i] >= xmin and sx[i] < xmax and sy[i] >= ymin and sy[i] < ymax:
if kepid[i] != 0 and kepmag[i] != 0.0:
print('%6.1f %6.1f %9.5f %8.5f %5.2f KIC %d' % \
(float(sx[i]),float(sy[i]),float(ra[i]),float(dec[i]),float(kepmag[i]),int(kepid[i])))
elif kepid[i] != 0 and kepmag[i] == 0.0:
print('%6.1f %6.1f %9.5f %8.5f KIC %d' % \
(float(sx[i]),float(sy[i]),float(ra[i]),float(dec[i]),int(kepid[i])))
else:
print('%6.1f %6.1f %9.5f %8.5f' % (float(sx[i]),float(sy[i]),float(ra[i]),float(dec[i])))
# plot sources
if status == 0:
for i in range(len(sx)-1,-1,-1):
if kepid[i] != 0 and kepmag[i] != 0.0:
size = max(array([80.0,80.0 + (2.5**(18.0 - max(12.0,float(kepmag[i])))) * 250.0]))
pylab.scatter(sx[i],sy[i],s=size,facecolors='g',edgecolors='k',alpha=0.4)
else:
pylab.scatter(sx[i],sy[i],s=80,facecolors='r',edgecolors='k',alpha=0.4)
# render plot
if status == 0 and len(plotfile) > 0 and plotfile.lower() != 'none':
pylab.savefig(plotfile)
if status == 0:
if cmdLine:
pylab.show(block=True)
else:
pylab.ion()
pylab.plot([])
pylab.ioff()
# stop time
kepmsg.clock('\nKEPFIELD ended at',logfile,verbose)
return
def kepdiffim(infile,
outfile,
plotfile,
imscale,
colmap,
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 = 'KEPDIFFIM -- '
call += 'infile=' + infile + ' '
call += 'outfile=' + outfile + ' '
call += 'plotfile=' + plotfile + ' '
call += 'imscale=' + imscale + ' '
call += 'colmap=' + colmap + ' '
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('KEPDIFFIM 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 -- KEPDIFFIM: ' + outfile + ' exists. Use --clobber'
status = kepmsg.err(logfile, message, verbose)
# reference color map
if colmap == 'browse':
status = cmap_plot()
# 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 * 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, npts] = fluxpixels[k, np]
errseries[i, 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 * xdim):
ave, sigma = kepstat.stdev(pixseries[i, :len(filtfunc)])
padded = numpy.append(kepstat.randarray(numpy.ones(len(filtfunc)) * ave, \
numpy.ones(len(filtfunc)) * sigma), pixseries[i,:])
ave, sigma = kepstat.stdev(pixseries[i, -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, :] = pixseries[i, :] - outdata + outmedian
# sum pixels over cadence
if status == 0:
np = 0
nrows = len(fluxpixels)
pixsum = zeros((ydim * xdim))
errsum = zeros((ydim * xdim))
for i in range(npts):
if quality[i] == 0:
pixsum += pixseries[:, i]
errsum += errseries[:, i]**2
np += 1
pixsum /= np
errsum = sqrt(errsum) / np
# calculate standard deviation pixels
if status == 0:
pixvar = zeros((ydim * xdim))
for i in range(npts):
if quality[i] == 0:
pixvar += (pixsum - pixseries[:, i] / errseries[:, i])**2
pixvar = numpy.sqrt(pixvar)
# median pixel errors
if status == 0:
errmed = empty((ydim * xdim))
for i in range(ydim * xdim):
errmed[i] = numpy.median(errseries[:, i])
# calculate chi distribution pixels
if status == 0:
pixdev = zeros((ydim * xdim))
for i in range(npts):
if quality[i] == 0:
pixdev += ((pixsum - pixseries[:, i]) / pixsum)**2
pixdev = numpy.sqrt(pixdev)
# pixdev = numpy.sqrt(pixvar) / errsum #errmed
# image scale and intensity limits
if status == 0:
pixsum_pl, zminsum, zmaxsum = kepplot.intScale1D(pixsum, imscale)
pixvar_pl, zminvar, zmaxvar = kepplot.intScale1D(pixvar, imscale)
pixdev_pl, zmindev, zmaxdev = kepplot.intScale1D(pixdev, imscale)
# construct output summed image
if status == 0:
imgsum = empty((ydim, xdim))
imgvar = empty((ydim, xdim))
imgdev = empty((ydim, xdim))
imgsum_pl = empty((ydim, xdim))
imgvar_pl = empty((ydim, xdim))
imgdev_pl = empty((ydim, xdim))
n = 0
for i in range(ydim):
for j in range(xdim):
imgsum[i, j] = pixsum[n]
imgvar[i, j] = pixvar[n]
imgdev[i, j] = pixdev[n]
imgsum_pl[i, j] = pixsum_pl[n]
imgvar_pl[i, j] = pixvar_pl[n]
imgdev_pl[i, j] = pixdev_pl[n]
n += 1
# 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])
hdulist.writeto(outfile)
status = kepkey.new('EXTNAME', 'FLUX', 'name of extension',
instruct[2], outfile, logfile, verbose)
pyfits.append(outfile, imgsum, instruct[2].header)
status = kepkey.new('EXTNAME', 'CHI', 'name of extension', instruct[2],
outfile, logfile, verbose)
pyfits.append(outfile, imgvar, instruct[2].header)
status = kepkey.new('EXTNAME', 'STDDEV', 'name of extension',
instruct[2], outfile, logfile, verbose)
pyfits.append(outfile, imgdev, instruct[2].header)
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)
# pixel limits of the subimage
if status == 0:
ymin = row
ymax = ymin + ydim
xmin = column
xmax = xmin + xdim
# plot limits for summed image
ymin = float(ymin) - 0.5
ymax = float(ymax) - 0.5
xmin = float(xmin) - 0.5
xmax = float(xmax) - 0.5
# plot style
try:
params = {
'backend': 'png',
'axes.linewidth': 2.5,
'axes.labelsize': 24,
'axes.font': 'sans-serif',
'axes.fontweight': 'bold',
'text.fontsize': 12,
'legend.fontsize': 12,
'xtick.labelsize': 10,
'ytick.labelsize': 10
}
pylab.rcParams.update(params)
except:
'ERROR -- KEPDIFFIM: install latex for scientific plotting'
status = 1
if status == 0:
plotimage(imgsum_pl, imgvar_pl, imgdev_pl, zminsum, zminvar, zmindev,
zmaxsum, zmaxvar, zmaxdev, xmin, xmax, ymin, ymax, colmap,
plotfile, cmdLine)
# stop time
kepmsg.clock('KEPDIFFIM ended at: ', logfile, verbose)
return
def kepdiffim(infile,outfile,plotfile,imscale,colmap,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 = 'KEPDIFFIM -- '
call += 'infile='+infile+' '
call += 'outfile='+outfile+' '
call += 'plotfile='+plotfile+' '
call += 'imscale='+imscale+' '
call += 'colmap='+colmap+' '
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('KEPDIFFIM 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 -- KEPDIFFIM: ' + outfile + ' exists. Use --clobber'
status = kepmsg.err(logfile,message,verbose)
# reference color map
if colmap == 'browse':
status = cmap_plot()
# 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*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,npts] = fluxpixels[k,np]
errseries[i,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*xdim):
ave, sigma = kepstat.stdev(pixseries[i,:len(filtfunc)])
padded = numpy.append(kepstat.randarray(numpy.ones(len(filtfunc)) * ave, \
numpy.ones(len(filtfunc)) * sigma), pixseries[i,:])
ave, sigma = kepstat.stdev(pixseries[i,-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,:] = pixseries[i,:] - outdata + outmedian
# sum pixels over cadence
if status == 0:
np = 0
nrows = len(fluxpixels)
pixsum = zeros((ydim*xdim))
errsum = zeros((ydim*xdim))
for i in range(npts):
if quality[i] == 0:
pixsum += pixseries[:,i]
errsum += errseries[:,i]**2
np += 1
pixsum /= np
errsum = sqrt(errsum) / np
# calculate standard deviation pixels
if status == 0:
pixvar = zeros((ydim*xdim))
for i in range(npts):
if quality[i] == 0:
pixvar += (pixsum - pixseries[:,i] / errseries[:,i])**2
pixvar = numpy.sqrt(pixvar)
# median pixel errors
if status == 0:
errmed = empty((ydim*xdim))
for i in range(ydim*xdim):
errmed[i] = numpy.median(errseries[:,i])
# calculate chi distribution pixels
if status == 0:
pixdev = zeros((ydim*xdim))
for i in range(npts):
if quality[i] == 0:
pixdev += ((pixsum - pixseries[:,i]) / pixsum)**2
pixdev = numpy.sqrt(pixdev)
# pixdev = numpy.sqrt(pixvar) / errsum #errmed
# image scale and intensity limits
if status == 0:
pixsum_pl, zminsum, zmaxsum = kepplot.intScale1D(pixsum,imscale)
pixvar_pl, zminvar, zmaxvar = kepplot.intScale1D(pixvar,imscale)
pixdev_pl, zmindev, zmaxdev = kepplot.intScale1D(pixdev,imscale)
# construct output summed image
if status == 0:
imgsum = empty((ydim,xdim))
imgvar = empty((ydim,xdim))
imgdev = empty((ydim,xdim))
imgsum_pl = empty((ydim,xdim))
imgvar_pl = empty((ydim,xdim))
imgdev_pl = empty((ydim,xdim))
n = 0
for i in range(ydim):
for j in range(xdim):
imgsum[i,j] = pixsum[n]
imgvar[i,j] = pixvar[n]
imgdev[i,j] = pixdev[n]
imgsum_pl[i,j] = pixsum_pl[n]
imgvar_pl[i,j] = pixvar_pl[n]
imgdev_pl[i,j] = pixdev_pl[n]
n += 1
# 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])
hdulist.writeto(outfile)
status = kepkey.new('EXTNAME','FLUX','name of extension',instruct[2],outfile,logfile,verbose)
pyfits.append(outfile,imgsum,instruct[2].header)
status = kepkey.new('EXTNAME','CHI','name of extension',instruct[2],outfile,logfile,verbose)
pyfits.append(outfile,imgvar,instruct[2].header)
status = kepkey.new('EXTNAME','STDDEV','name of extension',instruct[2],outfile,logfile,verbose)
pyfits.append(outfile,imgdev,instruct[2].header)
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)
# pixel limits of the subimage
if status == 0:
ymin = row
ymax = ymin + ydim
xmin = column
xmax = xmin + xdim
# plot limits for summed image
ymin = float(ymin) - 0.5
ymax = float(ymax) - 0.5
xmin = float(xmin) - 0.5
xmax = float(xmax) - 0.5
# plot style
try:
params = {'backend': 'png',
'axes.linewidth': 2.5,
'axes.labelsize': 24,
'axes.font': 'sans-serif',
'axes.fontweight' : 'bold',
'text.fontsize': 12,
'legend.fontsize': 12,
'xtick.labelsize': 10,
'ytick.labelsize': 10}
pylab.rcParams.update(params)
except:
'ERROR -- KEPDIFFIM: install latex for scientific plotting'
status = 1
if status == 0:
plotimage(imgsum_pl,imgvar_pl,imgdev_pl,zminsum,zminvar,zmindev,
zmaxsum,zmaxvar,zmaxdev,xmin,xmax,ymin,ymax,colmap,plotfile,cmdLine)
# stop time
kepmsg.clock('KEPDIFFIM ended at: ',logfile,verbose)
return
def kepfield(infile,plotfile,rownum,imscale='linear',colmap='YlOrBr',lcolor='gray',verbose=0,
logfile='kepfield.log',status=0,kic=0,cmdLine=False):
# input arguments
seterr(all="ignore")
# log the call
hashline = '----------------------------------------------------------------------------'
kepmsg.log(logfile,hashline,verbose)
call = 'KEPFIELD -- '
call += 'infile='+infile+' '
call += 'plotfile='+plotfile+' '
call += 'rownum='+str(rownum)+' '
call += 'imscale='+imscale+' '
call += 'colmap='+colmap+' '
call += 'lcolor='+lcolor+' '
chatter = 'n'
if (verbose): chatter = 'y'
call += 'verbose='+chatter+' '
call += 'logfile='+logfile
kepmsg.log(logfile,call+'\n',verbose)
# start time
kepmsg.clock('KEPFIELD started at',logfile,verbose)
# test log file
logfile = kepmsg.test(logfile)
# reference color map
if colmap == 'browse':
status = cmap_plot(cmdLine)
# open TPF FITS file
if status == 0:
try:
kepid, channel, skygroup, module, output, quarter, season, \
ra, dec, column, row, kepmag, xdim, ydim, barytime, status = \
kepio.readTPF(infile,'TIME',logfile,verbose)
except:
message = 'ERROR -- KEPFIELD: is %s a Target Pixel File? ' % infile
status = kepmsg.err(logfile,message,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)
# observed or simulated data?
if status == 0:
coa = False
instr = pyfits.open(infile,mode='readonly',memmap=True)
filever, status = kepkey.get(infile,instr[0],'FILEVER',logfile,verbose)
if filever == 'COA': coa = True
# print target data
if status == 0 and verbose:
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 ''
# is this a good row with finite timestamp and pixels?
if status == 0:
if not numpy.isfinite(barytime[rownum-1]) or not numpy.nansum(fluxpixels[rownum-1,:]):
message = 'ERROR -- KEPFIELD: Row ' + str(rownum) + ' is a bad quality timestamp'
status = kepmsg.err(logfile,message,verbose)
# construct input pixel image
if status == 0:
flux = fluxpixels[rownum-1,:]
# image scale and intensity limits of pixel data
if status == 0:
flux_pl, zminfl, zmaxfl = kepplot.intScale1D(flux,imscale)
n = 0
imgflux_pl = empty((ydim+2,xdim+2))
for i in range(ydim+2):
for j in range(xdim+2):
imgflux_pl[i,j] = numpy.nan
for i in range(ydim):
for j in range(xdim):
imgflux_pl[i+1,j+1] = flux_pl[n]
n += 1
# cone search around target coordinates using the MAST target search form
if status == 0:
dr = max([ydim+2,xdim+2]) * 4.0
kepid,ra,dec,kepmag = MASTRADec(float(ra),float(dec),dr)
# convert celestial coordinates to detector coordinates
if status == 0:
sx = numpy.array([])
sy = numpy.array([])
inf, status = kepio.openfits(infile,'readonly',logfile,verbose)
crpix1, crpix2, crval1, crval2, cdelt1, cdelt2, pc, status = \
kepkey.getWCSs(infile,inf['APERTURE'],logfile,verbose)
crpix1p, crpix2p, crval1p, crval2p, cdelt1p, cdelt2p, status = \
kepkey.getWCSp(infile,inf['APERTURE'],logfile,verbose)
for i in range(len(kepid)):
dra = (ra[i] - crval1) * math.sin(math.radians(dec[i])) / cdelt1
ddec = (dec[i] - crval2) / cdelt2
if coa:
sx = numpy.append(sx,-(pc[0,0] * dra + pc[0,1] * ddec) + crpix1 + crval1p - 1.0)
else:
sx = numpy.append(sx,pc[0,0] * dra + pc[0,1] * ddec + crpix1 + crval1p - 1.0)
sy = numpy.append(sy,pc[1,0] * dra + pc[1,1] * ddec + crpix2 + crval2p - 1.0)
# plot style
if status == 0:
try:
params = {'backend': 'png',
'axes.linewidth': 2.0,
'axes.labelsize': 24,
'axes.font': 'sans-serif',
'axes.fontweight' : 'bold',
'text.fontsize': 12,
'legend.fontsize': 12,
'xtick.labelsize': 18,
'ytick.labelsize': 18}
pylab.rcParams.update(params)
except:
pass
pylab.figure(figsize=[10,10])
pylab.clf()
# pixel limits of the subimage
if status == 0:
ymin = copy(float(row))
ymax = ymin + ydim
xmin = copy(float(column))
xmax = xmin + xdim
# plot limits for flux image
if status == 0:
ymin = float(ymin) - 1.5
ymax = float(ymax) + 0.5
xmin = float(xmin) - 1.5
xmax = float(xmax) + 0.5
# plot the image window
if status == 0:
ax = pylab.axes([0.1,0.11,0.88,0.88])
pylab.imshow(imgflux_pl,aspect='auto',interpolation='nearest',origin='lower',
vmin=zminfl,vmax=zmaxfl,extent=(xmin,xmax,ymin,ymax),cmap=colmap)
pylab.gca().set_autoscale_on(False)
labels = ax.get_yticklabels()
setp(labels, 'rotation', 90)
pylab.gca().xaxis.set_major_formatter(pylab.ScalarFormatter(useOffset=False))
pylab.gca().yaxis.set_major_formatter(pylab.ScalarFormatter(useOffset=False))
pylab.xlabel('Pixel Column Number', {'color' : 'k'})
pylab.ylabel('Pixel Row Number', {'color' : 'k'})
# plot mask borders
if status == 0:
kepplot.borders(maskimg,xdim,ydim,pixcoord1,pixcoord2,1,lcolor,'-',1)
# plot aperture borders
if status == 0:
kepplot.borders(maskimg,xdim,ydim,pixcoord1,pixcoord2,2,lcolor,'-',4.0)
# list sources
if status == 0 and verbose:
print 'Column Row RA J2000 Dec J2000 Kp Kepler ID'
print '----------------------------------------------------'
for i in range(len(sx)-1,-1,-1):
if sx[i] >= xmin and sx[i] < xmax and sy[i] >= ymin and sy[i] < ymax:
if kepid[i] != 0 and kepmag[i] != 0.0:
print '%6.1f %6.1f %9.5f %8.5f %5.2f KIC %d' % \
(float(sx[i]),float(sy[i]),float(ra[i]),float(dec[i]),float(kepmag[i]),int(kepid[i]))
elif kepid[i] != 0 and kepmag[i] == 0.0:
print '%6.1f %6.1f %9.5f %8.5f KIC %d' % \
(float(sx[i]),float(sy[i]),float(ra[i]),float(dec[i]),int(kepid[i]))
else:
print '%6.1f %6.1f %9.5f %8.5f' % (float(sx[i]),float(sy[i]),float(ra[i]),float(dec[i]))
# plot sources
if status == 0:
for i in range(len(sx)-1,-1,-1):
if kepid[i] != 0 and kepmag[i] != 0.0:
size = max(array([80.0,80.0 + (2.5**(18.0 - max(12.0,float(kepmag[i])))) * 250.0]))
pylab.scatter(sx[i],sy[i],s=size,facecolors='g',edgecolors='k',alpha=0.4)
else:
pylab.scatter(sx[i],sy[i],s=80,facecolors='r',edgecolors='k',alpha=0.4)
# render plot
if status == 0 and len(plotfile) > 0 and plotfile.lower() != 'none':
pylab.savefig(plotfile)
if status == 0:
if cmdLine:
pylab.show(block=True)
else:
pylab.ion()
pylab.plot([])
pylab.ioff()
pylab.clf()
# stop time
kepmsg.clock('\nKEPFIELD ended at',logfile,verbose)
# pdb.set_trace()
if kic > 0:
ind = np.where(kepid == kic)
colret = sx[ind]
rowret = sy[ind]
raret = ra[ind]
decret = dec[ind]
kepmagret = kepmag[ind]
kepidret = kepid[ind]
else:
inds = np.where(kepmag != 0.0)
colret = sx[inds]
rowret = sy[inds]
raret = ra[inds]
decret = dec[inds]
kepmagret = kepmag[inds]
kepidret = kepid[inds]
return colret,rowret,raret,decret,kepmagret,kepidret
def kepdeltapix(infile,nexp,columns,rows,fluxes,prfdir,interpolation,tolerance,fittype,imscale,
colmap,verbose,logfile,status,cmdLine=False):
# input arguments
status = 0
seterr(all="ignore")
# log the call
hashline = '----------------------------------------------------------------------------'
kepmsg.log(logfile,hashline,verbose)
call = 'KEPDELTAPIX -- '
call += 'infile='+infile+' '
call += 'nexp='+str(nexp)+' '
call += 'columns='+columns+' '
call += 'rows='+rows+' '
call += 'fluxes='+fluxes+' '
call += 'prfdir='+prfdir+' '
call += 'interpolation='+interpolation+' '
call += 'tolerance='+str(tolerance)+' '
call += 'fittype='+str(fittype)+' '
call += 'imscale='+imscale+' '
call += 'colmap='+colmap+' '
chatter = 'n'
if (verbose): chatter = 'y'
call += 'verbose='+chatter+' '
call += 'logfile='+logfile
kepmsg.log(logfile,call+'\n',verbose)
# test log file
logfile = kepmsg.test(logfile)
# start time
kepmsg.clock('KEPDELTAPIX started at',logfile,verbose)
# reference color map
if colmap == 'browse':
status = cmap_plot(cmdLine)
# open TPF FITS file
if status == 0:
try:
kepid, channel, skygroup, module, output, quarter, season, \
ra, dec, column, row, kepmag, xdim, ydim, barytime, status = \
kepio.readTPF(infile,'TIME',logfile,verbose)
except:
message = 'ERROR -- KEPDELTAPIX: is %s a Target Pixel File? ' % infile
status = kepmsg.err(logfile,message,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)
# print target data
if status == 0 and verbose:
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 ''
# determine suitable PRF calibration file
if status == 0:
if int(module) < 10:
prefix = 'kplr0'
else:
prefix = 'kplr'
prfglob = prfdir + '/' + prefix + str(module) + '.' + str(output) + '*' + '_prf.fits'
try:
prffile = glob.glob(prfglob)[0]
except:
message = 'ERROR -- KEPDELTAPIX: No PRF file found in ' + prfdir
status = kepmsg.err(logfile,message,verbose)
# read PRF images
if status == 0:
prfn = [0,0,0,0,0]
crpix1p = numpy.zeros((5),dtype='float32')
crpix2p = numpy.zeros((5),dtype='float32')
crval1p = numpy.zeros((5),dtype='float32')
crval2p = numpy.zeros((5),dtype='float32')
cdelt1p = numpy.zeros((5),dtype='float32')
cdelt2p = numpy.zeros((5),dtype='float32')
for i in range(5):
prfn[i], crpix1p[i], crpix2p[i], crval1p[i], crval2p[i], cdelt1p[i], cdelt2p[i], status \
= kepio.readPRFimage(prffile,i+1,logfile,verbose)
# choose rows in the TPF table at random
if status == 0:
i = 0
rownum = []
while i < nexp:
work = int(random.random() * len(barytime))
if numpy.isfinite(barytime[work]) and numpy.isfinite(fluxpixels[work,ydim*xdim/2]):
rownum.append(work)
i += 1
# construct input pixel image
if status == 0:
fscat = numpy.empty((len(fluxes),nexp),dtype='float32')
xscat = numpy.empty((len(columns),nexp),dtype='float32')
yscat = numpy.empty((len(rows),nexp),dtype='float32')
for irow in range(nexp):
flux = fluxpixels[rownum[irow],:]
# image scale and intensity limits of pixel data
if status == 0:
flux_pl, zminfl, zmaxfl = kepplot.intScale1D(flux,imscale)
n = 0
imgflux_pl = empty((ydim,xdim))
for i in range(ydim):
for j in range(xdim):
imgflux_pl[i,j] = flux_pl[n]
n += 1
# fit PRF model to pixel data
if status == 0:
start = time.time()
f,y,x,prfMod,prfFit,prfRes = kepfit.fitMultiPRF(flux,ydim,xdim,column,row,prfn,crval1p,
crval2p,cdelt1p,cdelt2p,interpolation,tolerance,fluxes,columns,rows,fittype,
verbose,logfile)
if verbose:
print '\nConvergence time = %.1fs' % (time.time() - start)
# best fit parameters
if status == 0:
for i in range(len(f)):
fscat[i,irow] = f[i]
xscat[i,irow] = x[i]
yscat[i,irow] = y[i]
# replace starting guess with previous fit parameters
if status == 0:
fluxes = copy(f)
columns = copy(x)
rows = copy(y)
# mean and rms results
if status == 0:
fmean = []; fsig = []
xmean = []; xsig = []
ymean = []; ysig = []
for i in range(len(f)):
fmean.append(numpy.mean(fscat[i,:]))
xmean.append(numpy.mean(xscat[i,:]))
ymean.append(numpy.mean(yscat[i,:]))
fsig.append(numpy.std(fscat[i,:]))
xsig.append(numpy.std(xscat[i,:]))
ysig.append(numpy.std(yscat[i,:]))
txt = 'Flux = %10.2f e-/s ' % fmean[-1]
txt += 'X = %7.4f +/- %6.4f pix ' % (xmean[-1], xsig[i])
txt += 'Y = %7.4f +/- %6.4f pix' % (ymean[-1], ysig[i])
kepmsg.log(logfile,txt,True)
# output results for kepprfphot
if status == 0:
txt1 = 'columns=0.0'
txt2 = ' rows=0.0'
for i in range(1,len(f)):
txt1 += ',%.4f' % (xmean[i] - xmean[0])
txt2 += ',%.4f' % (ymean[i] - ymean[0])
kepmsg.log(logfile,'\nkepprfphot input fields:',True)
kepmsg.log(logfile,txt1,True)
kepmsg.log(logfile,txt2,True)
# image scale and intensity limits for PRF model image
if status == 0:
imgprf_pl, zminpr, zmaxpr = kepplot.intScale2D(prfMod,imscale)
# image scale and intensity limits for PRF fit image
if status == 0:
imgfit_pl, zminfi, zmaxfi = kepplot.intScale2D(prfFit,imscale)
# image scale and intensity limits for data - fit residual
if status == 0:
imgres_pl, zminre, zmaxre = kepplot.intScale2D(prfRes,imscale)
# plot style
if status == 0:
try:
params = {'backend': 'png',
'axes.linewidth': 2.5,
'axes.labelsize': 24,
'axes.font': 'sans-serif',
'axes.fontweight' : 'bold',
'text.fontsize': 12,
'legend.fontsize': 12,
'xtick.labelsize': 10,
'ytick.labelsize': 10}
pylab.rcParams.update(params)
except:
pass
pylab.figure(figsize=[10,10])
pylab.clf()
plotimage(imgflux_pl,zminfl,zmaxfl,1,row,column,xdim,ydim,0.06,0.52,'flux',colmap)
plotimage(imgfit_pl,zminfl,zmaxfl,3,row,column,xdim,ydim,0.06,0.06,'fit',colmap)
plotimage(imgres_pl,zminfl,zmaxfl,4,row,column,xdim,ydim,0.52,0.06,'residual',colmap)
plotimage(imgprf_pl,zminpr,zmaxpr*0.9,2,row,column,xdim,ydim,0.52,0.52,'model',colmap)
for i in range(len(f)):
pylab.plot(xscat[i,:],yscat[i,:],'o',color='k')
# Plot creep of target position over time, relative to the central source
# barytime0 = float(int(barytime[0] / 100) * 100.0)
# barytime -= barytime0
# xlab = 'BJD $-$ %d' % barytime0
# xmin = numpy.nanmin(barytime)
# xmax = numpy.nanmax(barytime)
# y1min = numpy.nanmin(data)
# y1max = numpy.nanmax(data)
# xr = xmax - xmin
# yr = ymax - ymin
# barytime = insert(barytime,[0],[barytime[0]])
# barytime = append(barytime,[barytime[-1]])
# data = insert(data,[0],[0.0])
# data = append(data,0.0)
#
# pylab.figure(2,figsize=[10,10])
# pylab.clf()
# ax = pylab.subplot(211)
# pylab.subplots_adjust(0.1,0.5,0.88,0.42)
# 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, fontsize=ticksize)
# for i in range(1,len(f)):
# pylab.plot(rownum,xscat[i,:]-xscat[0,:],'o')
# pylab.ylabel('$\Delta$Columns', {'color' : 'k'})
# ax = pylab.subplot(211)
# pylab.subplots_adjust(0.1,0.1,0.88,0.42)
# 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, fontsize=ticksize)
# for i in range(1,len(f)):
# pylab.plot(rownum,yscat[i,:]-yscat[0,:],'o')
# pylab.xlim(xmin-xr*0.01,xmax+xr*0.01)
# if ymin-yr*0.01 <= 0.0 or fullrange:
# pylab.ylim(1.0e-10,ymax+yr*0.01)
# else:
# pylab.ylim(ymin-yr*0.01,ymax+yr*0.01)
# pylab.ylabel('$\Delta$Rows', {'color' : 'k'})
# pylab.xlabel(xlab, {'color' : 'k'})
# render plot
if status == 0:
if cmdLine:
pylab.show(block=True)
else:
pylab.ion()
pylab.plot([])
pylab.ioff()
# stop time
kepmsg.clock('\nKEPDELTAPIX ended at',logfile,verbose)
return
def __init__(self,
infile,
rownum=0,
imscale='linear',
cmap='YlOrBr',
lcolor='k',
acolor='b',
query=True,
logfile='kepcrowd.log',
**kwargs):
self.colrow = []
self.fluxes = []
self._text = []
# hide warnings
np.seterr(all="ignore")
# test log file
logfile = kepmsg.test(logfile)
# info
hashline = '----------------------------------------------------------------------------'
kepmsg.log(logfile, hashline, False)
call = 'KEPFIELD -- '
call += 'infile=' + infile + ' '
call += 'rownum=' + str(rownum)
kepmsg.log(logfile, call + '\n', False)
try:
kepid, channel, skygroup, module, output, quarter, season, \
ra, dec, column, row, kepmag, xdim, ydim, barytime, status = \
kepio.readTPF(infile, 'TIME', logfile, False)
except:
message = 'ERROR -- KEPFIELD: is %s a Target Pixel File? ' % infile
kepmsg.err(logfile, message, False)
return "", "", "", None
kepid, channel, skygroup, module, output, quarter, season, \
ra, dec, column, row, kepmag, xdim, ydim, tcorr, status = \
kepio.readTPF(infile,'TIMECORR',logfile,False)
kepid, channel, skygroup, module, output, quarter, season, \
ra, dec, column, row, kepmag, xdim, ydim, cadno, status = \
kepio.readTPF(infile,'rownumNO',logfile,False)
kepid, channel, skygroup, module, output, quarter, season, \
ra, dec, column, row, kepmag, xdim, ydim, fluxpixels, status = \
kepio.readTPF(infile,'FLUX',logfile,False)
kepid, channel, skygroup, module, output, quarter, season, \
ra, dec, column, row, kepmag, xdim, ydim, errpixels, status = \
kepio.readTPF(infile,'FLUX_ERR',logfile,False)
kepid, channel, skygroup, module, output, quarter, season, \
ra, dec, column, row, kepmag, xdim, ydim, qual, status = \
kepio.readTPF(infile,'QUALITY',logfile,False)
# read mask defintion data from TPF file
maskimg, pixcoord1, pixcoord2, status = kepio.readMaskDefinition(
infile, logfile, False)
# observed or simulated data?
coa = False
instr = pyfits.open(infile, mode='readonly', memmap=True)
filever, status = kepkey.get(infile, instr[0], 'FILEVER', logfile,
False)
if filever == 'COA': coa = True
# is this a good row with finite timestamp and pixels?
if not np.isfinite(barytime[rownum - 1]) or not np.nansum(
fluxpixels[rownum - 1, :]):
message = 'ERROR -- KEPFIELD: Row ' + str(
rownum) + ' is a bad quality timestamp'
kepmsg.err(logfile, message, True)
return "", "", "", None
# construct input pixel image
flux = fluxpixels[rownum - 1, :]
# image scale and intensity limits of pixel data
flux_pl, zminfl, zmaxfl = kepplot.intScale1D(flux, imscale)
n = 0
imgflux_pl = np.empty((ydim + 2, xdim + 2))
for i in range(ydim + 2):
for j in range(xdim + 2):
imgflux_pl[i, j] = np.nan
for i in range(ydim):
for j in range(xdim):
imgflux_pl[i + 1, j + 1] = flux_pl[n]
n += 1
# cone search around target coordinates using the MAST target search form
dr = max([ydim + 2, xdim + 2]) * 4.0
kepid, ra, dec, kepmag = MASTRADec(float(ra), float(dec), dr, query,
logfile)
# convert celestial coordinates to detector coordinates
sx = np.array([])
sy = np.array([])
inf, status = kepio.openfits(infile, 'readonly', logfile, False)
try:
crpix1, crpix2, crval1, crval2, cdelt1, cdelt2, pc, status = \
kepkey.getWCSs(infile,inf['APERTURE'],logfile,False)
crpix1p, crpix2p, crval1p, crval2p, cdelt1p, cdelt2p, status = \
kepkey.getWCSp(infile,inf['APERTURE'],logfile,False)
for i in range(len(kepid)):
dra = (ra[i] - crval1) * np.cos(np.radians(dec[i])) / cdelt1
ddec = (dec[i] - crval2) / cdelt2
if coa:
sx = np.append(
sx, -(pc[0, 0] * dra + pc[0, 1] * ddec) + crpix1 +
crval1p - 1.0)
else:
sx = np.append(
sx, pc[0, 0] * dra + pc[0, 1] * ddec + crpix1 +
crval1p - 1.0)
sy = np.append(
sy,
pc[1, 0] * dra + pc[1, 1] * ddec + crpix2 + crval2p - 1.0)
except:
message = 'ERROR -- KEPFIELD: Non-compliant WCS information within file %s' % infile
kepmsg.err(logfile, message, True)
return "", "", "", None
# plot
self.fig = pl.figure(figsize=[10, 10])
pl.clf()
# pixel limits of the subimage
ymin = np.copy(float(row))
ymax = ymin + ydim
xmin = np.copy(float(column))
xmax = xmin + xdim
# plot limits for flux image
ymin = float(ymin) - 1.5
ymax = float(ymax) + 0.5
xmin = float(xmin) - 1.5
xmax = float(xmax) + 0.5
# plot the image window
ax = pl.axes([0.1, 0.11, 0.88, 0.82])
pl.title('Select sources for fitting (KOI first)', fontsize=24)
pl.imshow(imgflux_pl,
aspect='auto',
interpolation='nearest',
origin='lower',
vmin=zminfl,
vmax=zmaxfl,
extent=(xmin, xmax, ymin, ymax),
cmap=cmap)
pl.gca().set_autoscale_on(False)
labels = ax.get_yticklabels()
pl.setp(labels, 'rotation', 90)
pl.gca().xaxis.set_major_formatter(pl.ScalarFormatter(useOffset=False))
pl.gca().yaxis.set_major_formatter(pl.ScalarFormatter(useOffset=False))
pl.xlabel('Pixel Column Number', {'color': 'k'}, fontsize=24)
pl.ylabel('Pixel Row Number', {'color': 'k'}, fontsize=24)
# plot mask borders
kepplot.borders(maskimg, xdim, ydim, pixcoord1, pixcoord2, 1, lcolor,
'--', 0.5)
# plot aperture borders
kepplot.borders(maskimg, xdim, ydim, pixcoord1, pixcoord2, 2, lcolor,
'-', 4.0)
# list sources
with open(logfile, 'a') as lf:
print('Column Row RA J2000 Dec J2000 Kp Kepler ID',
file=lf)
print('----------------------------------------------------',
file=lf)
for i in range(len(sx) - 1, -1, -1):
if sx[i] >= xmin and sx[i] < xmax and sy[i] >= ymin and sy[
i] < ymax:
if kepid[i] != 0 and kepmag[i] != 0.0:
print('%6.1f %6.1f %9.5f %8.5f %5.2f KIC %d' % \
(float(sx[i]),float(sy[i]),float(ra[i]),float(dec[i]),float(kepmag[i]),int(kepid[i])), file = lf)
elif kepid[i] != 0 and kepmag[i] == 0.0:
print('%6.1f %6.1f %9.5f %8.5f KIC %d' % \
(float(sx[i]),float(sy[i]),float(ra[i]),float(dec[i]),int(kepid[i])), file = lf)
else:
print('%6.1f %6.1f %9.5f %8.5f' % (float(
sx[i]), float(sy[i]), float(ra[i]), float(dec[i])),
file=lf)
# plot sources
for i in range(len(sx) - 1, -1, -1):
if kepid[i] != 0 and kepmag[i] != 0.0:
size = max(
np.array([
80.0, 80.0 +
(2.5**(18.0 - max(12.0, float(kepmag[i])))) * 250.0
]))
pl.scatter(sx[i],
sy[i],
s=size,
facecolors='g',
edgecolors='k',
alpha=0.4)
else:
pl.scatter(sx[i],
sy[i],
s=80,
facecolors='r',
edgecolors='k',
alpha=0.4)
# Sizes
for tick in ax.xaxis.get_major_ticks():
tick.label.set_fontsize(16)
for tick in ax.yaxis.get_major_ticks():
tick.label.set_fontsize(16)
# render plot and activate source selection
self.srcinfo = [kepid, sx, sy, kepmag]
pl.connect('button_release_event', self.on_mouse_release)
pl.show(block=True)
pl.close()
def __init__(
self,
infile,
rownum=0,
imscale="linear",
cmap="YlOrBr",
lcolor="k",
acolor="b",
query=True,
logfile="kepcrowd.log",
**kwargs
):
self.colrow = []
self.fluxes = []
self._text = []
# hide warnings
np.seterr(all="ignore")
# test log file
logfile = kepmsg.test(logfile)
# info
hashline = "----------------------------------------------------------------------------"
kepmsg.log(logfile, hashline, False)
call = "KEPFIELD -- "
call += "infile=" + infile + " "
call += "rownum=" + str(rownum)
kepmsg.log(logfile, call + "\n", False)
try:
kepid, channel, skygroup, module, output, quarter, season, ra, dec, column, row, kepmag, xdim, ydim, barytime, status = kepio.readTPF(
infile, "TIME", logfile, False
)
except:
message = "ERROR -- KEPFIELD: is %s a Target Pixel File? " % infile
kepmsg.err(logfile, message, False)
return "", "", "", None
kepid, channel, skygroup, module, output, quarter, season, ra, dec, column, row, kepmag, xdim, ydim, tcorr, status = kepio.readTPF(
infile, "TIMECORR", logfile, False
)
kepid, channel, skygroup, module, output, quarter, season, ra, dec, column, row, kepmag, xdim, ydim, cadno, status = kepio.readTPF(
infile, "rownumNO", logfile, False
)
kepid, channel, skygroup, module, output, quarter, season, ra, dec, column, row, kepmag, xdim, ydim, fluxpixels, status = kepio.readTPF(
infile, "FLUX", logfile, False
)
kepid, channel, skygroup, module, output, quarter, season, ra, dec, column, row, kepmag, xdim, ydim, errpixels, status = kepio.readTPF(
infile, "FLUX_ERR", logfile, False
)
kepid, channel, skygroup, module, output, quarter, season, ra, dec, column, row, kepmag, xdim, ydim, qual, status = kepio.readTPF(
infile, "QUALITY", logfile, False
)
# read mask defintion data from TPF file
maskimg, pixcoord1, pixcoord2, status = kepio.readMaskDefinition(infile, logfile, False)
# observed or simulated data?
coa = False
instr = pyfits.open(infile, mode="readonly", memmap=True)
filever, status = kepkey.get(infile, instr[0], "FILEVER", logfile, False)
if filever == "COA":
coa = True
# is this a good row with finite timestamp and pixels?
if not np.isfinite(barytime[rownum - 1]) or not np.nansum(fluxpixels[rownum - 1, :]):
message = "ERROR -- KEPFIELD: Row " + str(rownum) + " is a bad quality timestamp"
kepmsg.err(logfile, message, True)
return "", "", "", None
# construct input pixel image
flux = fluxpixels[rownum - 1, :]
# image scale and intensity limits of pixel data
flux_pl, zminfl, zmaxfl = kepplot.intScale1D(flux, imscale)
n = 0
imgflux_pl = np.empty((ydim + 2, xdim + 2))
for i in range(ydim + 2):
for j in range(xdim + 2):
imgflux_pl[i, j] = np.nan
for i in range(ydim):
for j in range(xdim):
imgflux_pl[i + 1, j + 1] = flux_pl[n]
n += 1
# cone search around target coordinates using the MAST target search form
dr = max([ydim + 2, xdim + 2]) * 4.0
kepid, ra, dec, kepmag = MASTRADec(float(ra), float(dec), dr, query, logfile)
# convert celestial coordinates to detector coordinates
sx = np.array([])
sy = np.array([])
inf, status = kepio.openfits(infile, "readonly", logfile, False)
try:
crpix1, crpix2, crval1, crval2, cdelt1, cdelt2, pc, status = kepkey.getWCSs(
infile, inf["APERTURE"], logfile, False
)
crpix1p, crpix2p, crval1p, crval2p, cdelt1p, cdelt2p, status = kepkey.getWCSp(
infile, inf["APERTURE"], logfile, False
)
for i in range(len(kepid)):
dra = (ra[i] - crval1) * np.cos(np.radians(dec[i])) / cdelt1
ddec = (dec[i] - crval2) / cdelt2
if coa:
sx = np.append(sx, -(pc[0, 0] * dra + pc[0, 1] * ddec) + crpix1 + crval1p - 1.0)
else:
sx = np.append(sx, pc[0, 0] * dra + pc[0, 1] * ddec + crpix1 + crval1p - 1.0)
sy = np.append(sy, pc[1, 0] * dra + pc[1, 1] * ddec + crpix2 + crval2p - 1.0)
except:
message = "ERROR -- KEPFIELD: Non-compliant WCS information within file %s" % infile
kepmsg.err(logfile, message, True)
return "", "", "", None
# plot
self.fig = pl.figure(figsize=[10, 10])
pl.clf()
# pixel limits of the subimage
ymin = np.copy(float(row))
ymax = ymin + ydim
xmin = np.copy(float(column))
xmax = xmin + xdim
# plot limits for flux image
ymin = float(ymin) - 1.5
ymax = float(ymax) + 0.5
xmin = float(xmin) - 1.5
xmax = float(xmax) + 0.5
# plot the image window
ax = pl.axes([0.1, 0.11, 0.88, 0.82])
pl.title("Select sources for fitting (KOI first)", fontsize=24)
pl.imshow(
imgflux_pl,
aspect="auto",
interpolation="nearest",
origin="lower",
vmin=zminfl,
vmax=zmaxfl,
extent=(xmin, xmax, ymin, ymax),
cmap=cmap,
)
pl.gca().set_autoscale_on(False)
labels = ax.get_yticklabels()
pl.setp(labels, "rotation", 90)
pl.gca().xaxis.set_major_formatter(pl.ScalarFormatter(useOffset=False))
pl.gca().yaxis.set_major_formatter(pl.ScalarFormatter(useOffset=False))
pl.xlabel("Pixel Column Number", {"color": "k"}, fontsize=24)
pl.ylabel("Pixel Row Number", {"color": "k"}, fontsize=24)
# plot mask borders
kepplot.borders(maskimg, xdim, ydim, pixcoord1, pixcoord2, 1, lcolor, "--", 0.5)
# plot aperture borders
kepplot.borders(maskimg, xdim, ydim, pixcoord1, pixcoord2, 2, lcolor, "-", 4.0)
# list sources
with open(logfile, "a") as lf:
print("Column Row RA J2000 Dec J2000 Kp Kepler ID", file=lf)
print("----------------------------------------------------", file=lf)
for i in range(len(sx) - 1, -1, -1):
if sx[i] >= xmin and sx[i] < xmax and sy[i] >= ymin and sy[i] < ymax:
if kepid[i] != 0 and kepmag[i] != 0.0:
print(
"%6.1f %6.1f %9.5f %8.5f %5.2f KIC %d"
% (
float(sx[i]),
float(sy[i]),
float(ra[i]),
float(dec[i]),
float(kepmag[i]),
int(kepid[i]),
),
file=lf,
)
elif kepid[i] != 0 and kepmag[i] == 0.0:
print(
"%6.1f %6.1f %9.5f %8.5f KIC %d"
% (float(sx[i]), float(sy[i]), float(ra[i]), float(dec[i]), int(kepid[i])),
file=lf,
)
else:
print(
"%6.1f %6.1f %9.5f %8.5f" % (float(sx[i]), float(sy[i]), float(ra[i]), float(dec[i])),
file=lf,
)
# plot sources
for i in range(len(sx) - 1, -1, -1):
if kepid[i] != 0 and kepmag[i] != 0.0:
size = max(np.array([80.0, 80.0 + (2.5 ** (18.0 - max(12.0, float(kepmag[i])))) * 250.0]))
pl.scatter(sx[i], sy[i], s=size, facecolors="g", edgecolors="k", alpha=0.4)
else:
pl.scatter(sx[i], sy[i], s=80, facecolors="r", edgecolors="k", alpha=0.4)
# Sizes
for tick in ax.xaxis.get_major_ticks():
tick.label.set_fontsize(16)
for tick in ax.yaxis.get_major_ticks():
tick.label.set_fontsize(16)
# render plot and activate source selection
self.srcinfo = [kepid, sx, sy, kepmag]
pl.connect("button_release_event", self.on_mouse_release)
pl.show(block=True)
pl.close()