def kaitproc(inlist, clobber=globclob, verbose=globver):
infiles = iraffiles(inlist)
# Big loop
for image in infiles:
# Fix bad header keywords
root,ext = image.split('.')
fimg = pyfits.open(image)
fimg.verify('fix')
image2 = '%s.fits' % root
print fimg[0].header
fimg.writeto(image2)
#iraf.imcopy(image, image2)
# Update the WCS keywords
update_head(image2, ['CD1_1', 'CD2_2', 'CD1_2', 'CD2_1', 'PIXSCALE'],
[CD11, CD22, CD12, CD21, PIXSCALE])
update_head(image2, ['WCSDIM','LTM1_1','LTM2_2','WAT0_001','WAT1_001',
'WAT2_001'], [2,1.0,1.0,'system=image',
'wtype=tan axtype=ra','wtype=tan axtype=dec'])
delete_head(image2, ['CROTA1','CROTA2','CDELT1','CDELT2','CSOURCE'])
# Update RA and Dec to J2000.0
[ra0, dec0, epoch] = get_head(image2, ['RA','DEC','EPOCH'])
point = ephem.readdb('Point,f|M|F7,%s,%s,0.0,%f' % (ra0,dec0,epoch))
point.compute(epoch='2000.0')
coo=astrocoords(str(point.a_ra),str(point.a_dec))
update_head(image2, ['RA','DEC','EPOCH','CRVAL1','CRVAL2'],
[coo.sxg()[0],coo.sxg()[1],2000.0,coo.radeg(),coo.dcdeg()])
# Need Date to determine gain and readnoise (camera switch in May 2007)
dateobs=get_head(image2,"DATE-OBS")
tobs=DateTime(int(dateobs[6:]),int(dateobs[3:5]),int(dateobs[:2]))
if tobs-TFL > 0:
gain=FL_GAIN
readn=FL_READN
else:
gain=AP_GAIN
readn=AP_READN
update_head(image2,['GAIN','READN'],[gain,readn])
# Clean cosmic rays
#tmpimg=iraf.mktemp("iqcr")+".fits"
#check_exist("%s_%s.fits" % (root,CRSFX),"w",clobber)
#iraf.lacos_im(image2,tmpimg,"%s_%s.fits" % (root,CRSFX),
#gain=gain,readn=readn,skyval=0.0,sigclip=4.5,
#sigfrac=0.5,objlim=2.0,niter=1)
#iraf.imdel(image2,verify=no,go_ahead=yes)
#iraf.imcopy(tmpimg,image2,verbose=no)
#iraf.imdel(tmpimg,verify=no,go_ahead=yes)
# Detect Objects
iraf.iqobjs(image2,SIGMA,SATVAL,skyval="0.0",masksfx=MASKSFX,
wtimage="",fwhm=FWHM,pix=PIXSCALE,aperture=2*FWHM/PIXSCALE,
gain=gain,minlim=no,clobber=yes,verbose=no)
# Fit WCS
iraf.iqwcs(image2,objkey='OBJECT',rakey='RA',deckey='DEC',
pixscl=PIXSCALE,pixtol=0.05,starfile='!STARFILE',nstar=40,
catalog='web',ubhost="localhost",diffuse=yes,
clobber=yes,verbose=verbose)
# Calculate zero-point
if get_head(image2,'IQWCS'):
object=get_head(image2,'OBJECT')
iraf.iqzeropt(image2,REFMAG,starfile="!STARFILE",
catalog=object.replace(" ","_")+".cat",pixtol=3.0,
useflags=yes,maxnum=50,method="mean",rejout=1,
fencelim=0.50,sigma=1.5,maxfrac=0.25,zptkey=ZPTKEY,
zpukey=ZPUKEY,clobber=yes,verbose=verbose)
print 'Exiting Successfully'
return
def defringe(self,qombos):
if type(qombos) is StringType:
qombo=qombos
qombos=[qombo]
# Loop over input list of qombos
for qombo in qombos:
# Corresponding files
offiles2=self.science_images(qombo,pfx=self.flatpfx)
if len(offiles2)==0:
continue
oflist2=','.join(offiles2)
# Check for existence of fringe image
offrg=self.fringepre+qombo+'.fits'
if not os.path.exists(offrg):
self.mkfringe(qombo)
# Defringe images
iraf.iqdefringe(oflist2,offrg,outpfx=self.defrgpfx,
skykey="SKYBKG",minlim=no,
clobber=self.clobber,verbose=no)
# List of defringed images
offiles3=pfx_list(offiles2,self.defrgpfx)
oflist3=','.join(offiles3)
# Clipping of defringed images
clipreg=self.clipreg
if len(clipreg)>0:
re1=re.search('(\d+):(\d+),(\d+):(\d+)',clipreg)
if re1:
szx=int(re1.group(2))-int(re1.group(1))+1
szy=int(re1.group(4))-int(re1.group(3))+1
for image in offiles3:
# Check that it's not already clipped
naxis1,naxis2=get_head(image,['NAXIS1','NAXIS2'])
if naxis1<=szx and naxis2<=szy:
continue
# Clip the defringed images
iraf.imcopy(image+clipreg,image,verbose=no)
# Clip the corresponding BPM
oldbpm=get_head(image,'BPM')
newbpm=oldbpm.replace('.pl',self.clpsfx+'.pl')
if os.path.exists(oldbpm) and \
not os.path.exists(newbpm):
iraf.imcopy(oldbpm+clipreg,newbpm,verbose=yes)
# Update the image headers
update_head(image,'BPM',newbpm)
else:
print "Failed to parse clipping region... not clipping"
####################
# Attempt WCS refinement
for image in offiles3:
# Skip images with good WCS
if check_head(image,'IQWCS'):
if int(get_head(image,'IQWCS')):
continue
# Object-detection
iraf.iqobjs(image,self.sigma,self.satval,skyval="!SKYBKG",
masksfx=self.masksfx,wtimage="",minlim=no,
clobber=yes,verbose=no)
# WCS refinement
iraf.iqwcs(image,objkey=self.objkey,rakey='RA',
deckey='DEC',pixscl=self.pix,pixtol=0.05,
starfile='!STARFILE',catalog='ir',
diffuse=yes,clobber=yes,verbose=self.verbose)
# Figure out which have good WCS
wcsdict=keysplit(offiles3,'IQWCS')
# Interpolate WCS onto files without good WCS so far
if wcsdict.has_key(""):
wcsbadfiles=wcsdict[""]
if len(wcsbadfiles)==len(offiles3):
print "No images with good WCS in this set"
else:
wcsgoodfiles=wcsdict[1]
wcsinterp(wcsbadfiles,wcsgoodfiles)
# Done with Step #5
update_head(offiles3,'IQWRCSTP',5,
"Stage of IQWIRC processing")
def flatten(self,qombos,flat=None,flatscale=no):
if type(qombos) is StringType:
qombo=qombos
qombos=[qombo]
# Loop over input list of qombos
for qombo in qombos:
# Check for presence of calibration files
obj,filt=qombo_split(qombo)
if not self.check_calib(filt):
self.calib()
# Corresponding files
offiles=self.science_images(qombo)
if len(offiles)==0:
continue
# Make a text ".lis" file to record this
putlines(qombo+'.lis',offiles,clobber=yes)
# Create the renormalized flatfield
inflat=self.flatpre+filt+'.fits'
outflat=self.flatpre+qombo+'.fits'
check_exist(outflat,"w",clobber=self.clobber)
# Rescale flatfield if requested
if flatscale:
wirc_flatscale(offiles,inflat,outflat,clipfrac=0.02,
clobber=yes)
else:
iraf.imcopy(inflat,outflat,verbose=no)
check_exist(outflat,"r")
# Further preprocessing
for image in offiles:
# Flatfielding
update_head(image,self.filtset,filt)
iraf.iqflatten(image,outflat,outpfx=self.flatpfx,
normflat=yes,statsec=self.statsec,
subsky=yes,vignflat=no,
clobber=yes,verbose=no)
# Set bad pixels to zero
image2=self.flatpfx+image
iraf.iqmask(image2,mask='!BPM',method='constant',value=0.0,
clobber=yes,verbose=no)
# Reject cosmic rays / bad pixels
#iraf.lacos_im(image2, "tempcr.fits", "tempcrmask.fits",
#gain=5.5, readn=12.0, statsec="*,*",
#skyval=get_head(image2,"SKYBKG"), sigclip=6.0,
#sigfrac=0.5, objlim=1.0, niter=1, verbose=no)
#shutil.move("tempcr.fits", image2)
#os.remove("tempcrmask.fits")
# Write Useful Keywords
update_head(image2,'PROCESSD',1,
"Image has been processed by iqwirc")
update_head(image2,'PROCVER',version,
"Version number of iqwirc used")
update_head(image2,'ZEROPT','INDEF',
"Zero-point relative to 2MASS or INDEF")
update_head(image2,'PROCPROB','None',
"Problems encountered in iqwirc processing")
# List of flatfielded images
offiles2=pfx_list(offiles,self.flatpfx)
oflist2=','.join(offiles2)
# Object-detection
iraf.iqobjs(oflist2,self.sigma,self.satval,
skyval="!SKYBKG",masksfx=self.masksfx,
wtimage="",minlim=no,
clobber=yes,verbose=no)
# Attempt WCS refinement
iraf.iqwcs(oflist2,objkey=self.objkey,rakey='RA',
deckey='DEC',pixscl=self.pix,pixtol=0.05,
starfile='!STARFILE',catalog='ir',
nstar=60,nstarmax=60,
diffuse=yes,clobber=yes,verbose=self.verbose)
# Done with Step #3
update_head(offiles2,'IQWRCSTP',3,
"Stage of IQWIRC processing")
def flatten(self,qombos,flat=None,flatscale=no):
if type(qombos) is StringType:
qombo=qombos
qombos=[qombo]
# Loop over input list of qombos
for qombo in qombos:
# Check for presence of calibration files
obj,filt=qombo_split(qombo)
if not self.check_calib(filt):
self.calib()
# Corresponding files
offiles=self.science_images(qombo)
if len(offiles)==0:
continue
# Make a text ".lis" file to record this
putlines(qombo+'.lis',offiles,clobber=yes)
# Rescale flatfield if requested
inflat=self.flatpre+filt+'.fits'
outflat=self.flatpre+qombo+'.fits'
check_exist(outflat,"w",clobber=self.clobber)
if flatscale:
nirc_flatscale(offiles,inflat,outflat,clipfrac=0.02,
clobber=yes)
else:
iraf.imcopy(inflat,outflat,verbose=no)
check_exist(outflat,"r")
# Clip flatfield and update BPM
iraf.iqclip(outflat,lthresh=self.flatlow,
hthresh=self.flathigh,bookend=no,
replace=1.0,maskin='!BPM',maskval=1,
maskout=self.bpmsfx)
# Rename the updated BPM
newbpm1=get_head(outflat,'BPM')
newbpm2=newbpm1.replace(self.flatpre,'')
check_exist(newbpm2,'w',clobber=self.clobber)
iraf.imrename(newbpm1,newbpm2,verbose=no)
update_head(outflat,'BPM',newbpm2)
# Further preprocessing
for image in offiles:
# Keyword updates
update_head(image,[self.filtset,'BPM'],
[filt,newbpm2])
# Flatfielding
iraf.iqflatten(image,outflat,outpfx=self.flatpfx,
normflat=no,statsec=self.statsec,
subsky=yes,vignflat=no,clipflat=no,
clobber=yes,verbose=no)
# Set bad pixels to zero
image2=self.flatpfx+image
iraf.iqmask(image2,mask='!BPM',method='constant',value=0.0,
clobber=yes,verbose=no)
# Write Useful Keywords
update_head(image2,'PROCESSD',1,
"Image has been processed by iqnirc")
update_head(image2,'PROCVER',version,
"Version number of iqnirc used")
update_head(image2,'ZEROPT','INDEF',
"Zero-point relative to 2MASS or INDEF")
update_head(image2,'PROCPROB','None',
"Problems encountered in iqnirc processing")
# List of flatfielded images
offiles2=pfx_list(offiles,self.flatpfx)
oflist2=','.join(offiles2)
# Object-detection
iraf.iqobjs(oflist2,self.sigma,self.satval,
skyval="!SKYBKG",masksfx=self.masksfx,
wtimage="",minlim=no,
clobber=yes,verbose=no)
# Attempt WCS refinement
iraf.iqwcs(oflist2,objkey=self.objkey,rakey='RA',
deckey='DEC',pixscl=self.pix,pixtol=0.05,
starfile='!STARFILE',catalog='ir',
diffuse=yes,clobber=yes,verbose=self.verbose)
# Done with Step #3
update_head(offiles2,'IQWRCSTP',3,
"Stage of IQWIRC processing")
def iqp60(inpat,endhow="never",endwhen="",focmode="all",
logfile="",clobber=globclob,verbose=globver):
""" intelligent processing of P60 data files """
# Defaults
twait=30
reduced={}
filtkey="FILTER"
biaskey="IMGTYPE"
biasre="BIAS"
biasroot="Bias"
biaspfx="b"
flatkey="IMGTYPE"
flatre="DOMEFLAT"
flatpre="Flat-"
flatpfx="f"
bpm0root="BPM0"
bpmroot="BPM"
binkey="CCDSUM"
detseckey="DETSEC"
binroikey="BINROI"
binroidef="A"
nfocus=10
focuskey="IMGTYPE"
focusre="^FOCUS"
fseqkey="FOCUSSEQ"
skipkey="IMGTYPE"
skipre="SAOFOCUS"
statsec=""
reqkeys=['IMGTYPE','OBJECT','FILTER','BINROI',
'CCDSUM','DETSEC','ROISEC']
sigma=3.0
minraw=0.0
maxraw=65535.0
satval=50000.0
masksfx="mask"
rawpix=0.3787
zptkey="ZEROPT"
zpukey="ZEROPTU"
# For now:
#catmags={'B':'BMAG','V':'BMAG','g':'BMAG',
# 'R':'RMAG','r':'RMAG','I':'IMAG',
# 'i':'IMAG','ip':'IMAG','z':'IMAG',
# 'zp':'IMAG','zl':'IMAG','zs':'IMAG'}
## In the future, once Sloan mags are written to the ubcone output:
catmags={'B':'BMAG','V':'VMAG','g':'GPMAG',
'R':'RMAG','r':'RPMAG','I':'IMAG',
'i':'IMAG','ip':'IPMAG','z':'ZPMAG',
'zp':'ZPMAG','zl':'ZPMAG','zs':'ZPMAG',
'upr':'UPMAG','gpr':'GPMAG','rpr':'RPMAG',
'ipr':'IPMAG','zpr':'ZPMAG'}
exptmkey="EXPTIME"
exptmstd=60.0
minzpts={}
minskys={}
fwhm0=1.5
gain=2.3
readn=7.5
crsfx="crm"
statfile="Status_Science.txt"
# Parse end-condition "time"
if endhow=="time":
re1=re.search("^(\d+):(\d+)",endwhen)
if re1:
tnow=time.gmtime()
# Force UT calculation w/ ignoring of DST issues
reftime=time.mktime([tnow[0],tnow[1],tnow[2],
int(re1.group(1)),int(re1.group(2)),0,
tnow[6],tnow[7],0]) - time.timezone
if reftime<time.time():
reftime+=86400
if verbose:
print "Running until %s" % \
time.strftime("%d %b %H:%M",time.gmtime(reftime))
else:
print "Failed to parse %s as UT time" % endwhen
print "Running until stopped..."
endhow="never"
# Parse focmode setting
fonly=0
if focmode=="nofocus":
skipre="FOCUS"
elif focmode=="focus":
fonly=1
skipre="SCIENCE"
# Parse logfile setting
if len(logfile)>0:
check_exist(logfile,'w',yes)
try:
log=open(logfile,'w')
sys.stdout=log
except:
print "Failed to open logfile %s for writing" % logfile
# Setup ccdproc options
ccdproc=iraf.ccdred.ccdproc
ccdproc.overscan=yes
ccdproc.trim=yes
ccdproc.zerocor=no
ccdproc.interactive=no
ccdproc.function="chebyshev"
ccdproc.order=3
ccdproc.sample="*"
ccdproc.naverage=3
ccdproc.niterate=2
ccdproc.low_reject=3.0
ccdproc.high_reject=3.0
ccdproc.grow=0.0
# Demosaic all the files
allfiles=glob.glob(inpat)
alllist=','.join(allfiles)
iraf.iqmosaic(alllist,outpfx="",biassec="!BIASSEC",
trimsec="!TRIMSEC",joinkeys="CCDSIZE,DETSEC,ROISEC",
splitkeys="AMPSEC,CCDSEC,TRIM,OVERSCAN,CCDPROC",
clobber=yes,verbose=verbose)
iraf.add_wcs(alllist,instrument="p60new",binkey=binkey)
# Set ccdproc params for bias-subtraction only
ccdproc.overscan=no
ccdproc.trim=no
ccdproc.zerocor=yes
# Determine if we need to make calibration files
dobias=no
doflats=no
for image in allfiles:
# Criteria for bias image
biasval,flatval=get_head(image,[biaskey,flatkey])
if re.search(biasre,biasval,re.I):
dobias=yes
reduced[image]=yes
elif re.search(flatre,flatval,re.I):
doflats=yes
reduced[image]=yes
# Calibrations
if (dobias or doflats) and not fonly:
iraf.iqcals(alllist,dobias=dobias,biasproc=no,
biaskey=biaskey,biasre=biasre,biasroot=biasroot,
doflats=doflats,flatproc=yes,flatkey=flatkey,
flatre=flatre,filtkey=filtkey,flatpre=flatpre,
flatscale="mode",statsec="",normflat=yes,
dobpm=no,bpmroot=bpmroot,classkey=binroikey,
classdef=binroidef,mosaic=no,
clobber=clobber,verbose=verbose)
# Delete binroi-specific BPMs and flatfields
oldbpms=glob.glob(bpmroot+'-'+'*.pl')
for oldbpm in oldbpms:
iraf.imdel(oldbpm,verify=no,go_ahead=yes)
oldflats=glob.glob(flatpre+'*-*.fits')
for oldflat in oldflats:
iraf.imdel(oldflat,verify=no,go_ahead=yes)
# Clip all flatfields and update BPM as we go
bpm0name=bpm0root+'.pl'
bpmname=bpmroot+'.pl'
if os.path.exists(bpmname):
check_exist(bpm0name,'w',clobber=yes)
iraf.imrename(bpmname,bpm0name,verbose=no)
allflats=glob.glob(flatpre+'*.fits')
for flatimg in allflats:
iraf.iqclip(flatimg,lthresh=0.75,hthresh=1.25,bookend=no,
replace=1.0,maskin=bpm0name,maskout=bpmname,
maskval=1,clobber=yes,verbose=no)
iraf.imdel(bpm0name,verify=no,go_ahead=yes)
iraf.imrename(bpmname,bpm0name,verbose=no)
update_head(flatimg,"CLIPFLAT",1,"Has flatfield been clipped?")
update_head(flatimg,"CLIPREPL",1.0,
"Replacement value for clipped pixels")
iraf.imrename(bpm0name,bpmname,verbose=no)
##################################################
# Lists of focusfiles
allfocus=[]
focusfiles=[]
# Should additional calibrations be taken later on...
biasfiles=[]
flatfiles=[]
# Big Loop
done=no
while not done:
# Parse inputs
allfiles=glob.glob(inpat)
newfiles=[]
for image in allfiles:
if not reduced.has_key(image):
# Exclude Bias & Flats
if re.search(biasroot,image,re.I) or \
re.search(flatpre,image,re.I):
reduced[image]=yes
continue
# Exclude calibration files (for now)
biasval,flatval=get_head(image,[biaskey,flatkey])
if re.search(biasre,biasval,re.I):
biasfiles.append(image)
reduced[image]=yes
elif re.search(flatre,flatval,re.I):
flatfiles.append(image)
reduced[image]=yes
# Exclude "skippable" files
skipval=get_head(image,skipkey)
if re.search(skipre,skipval,re.I):
reduced[image]=yes
# Queue file for processing
else:
reduced[image]=no
newfiles.append(image)
elif not reduced[image]:
# Attempted reduction before, but failed?
newfiles.append(image)
if newfiles:
# Brief pause to avoid file conflicts (?)
time.sleep(3.0)
# Demosaic
newlist=','.join(newfiles)
ccdproc.overscan=yes
ccdproc.trim=yes
ccdproc.zerocor=no
iraf.iqmosaic(newlist,outpfx="",biassec="!BIASSEC",
trimsec="!TRIMSEC",joinkeys="DETSEC",
splitkeys="AMPSEC,CCDSEC,TRIM,OVERSCAN",
clobber=yes,verbose=verbose)
iraf.add_wcs(newlist,instrument="p60new",binkey=binkey)
# Reset ccdproc params for bias-subtraction only
ccdproc.overscan=no
ccdproc.biassec=""
ccdproc.trim=no
ccdproc.trimsec=""
ccdproc.zerocor=yes
ccdproc.flatcor=no
##############################
# Process new images
for image in newfiles:
# Required keyword check
if not check_head(image,reqkeys):
print "Image %s is missing required keywords" % image
continue
# Attempt processing only once per image
reduced[image]=yes
if verbose:
print "Reducing new image %s" % image
# Track useful status information
scistat={}
# Prepare for processing
pix=rawpix
binroi=binroidef
biasname=biasroot+'.fits'
bpmname=bpmroot+'.pl'
filt=get_head(image,filtkey)
flatname=flatpre+filt+".fits"
# Calibration files for BINROI setting
if check_head(image,binroikey):
binroi=get_head(image,binroikey)
if binroi != binroidef:
# Get the right calibration files
fullbias=biasname
biasname=biasroot+'-'+binroi+'.fits'
fullbpm =bpmroot+'.pl'
bpmname =bpmroot+'-'+binroi+'.pl'
fullflat=flatname
flatname=flatpre+filt+'-'+binroi+".fits"
# Details of this binning/roi combo
[binval,detsec]=get_head(image,[binkey,detseckey])
binning=p60parsebin(binval)
roi=p60parseroi(detsec)
# Pixel scale (no anisotropic binning, sorry)
pix=binning[0]*rawpix
# Check for existance of bias; make it if we have to
if not os.path.exists(biasname):
print ("Failed to find bias for %s=%s; "+ \
"constructing one from full-frame bias") % \
(binroikey,binroi)
p60roiflat(fullbias,biasname,binning,roi)
# Produce the flatfield if necessary
if not os.path.exists(flatname):
p60roiflat(fullflat,flatname,binning,roi)
# Produce the bad-pixel mask if necessary
if not os.path.exists(bpmname):
# Get BPM into FITS format
bpm1=iraf.mktemp("iqbpm")+".fits"
iraf.imcopy(fullbpm,bpm1,verbose=no)
# Adjust BPM for binning/ROI
bpm2=iraf.mktemp("iqbpm")+".fits"
p60roibpm(bpm1,bpm2,binning,roi)
# Convert BPM to PL format
iraf.imcopy(bpm2,bpmname,verbose=no)
# Delete temporary files
iraf.imdel(bpm1,verify=no,go_ahead=yes)
iraf.imdel(bpm2,verify=no,go_ahead=yes)
# Bias subtraction
check_exist(biasname,"r")
ccdproc.zero=biasname
image1=biaspfx+image
check_exist(image1,'w',clobber)
iraf.ccdproc(image,output=image1,Stdout=1)
# Flatfielding
check_exist(flatname,"r")
iraf.iqflatten(image1,flatname,outpfx=flatpfx,
normflat=no,clipflat=no,
statsec=statsec,subsky=yes,
vignflat=no,clobber=yes,verbose=no)
imagef=flatpfx+image1
# Clip (bookend) flattened & sky-subtracted image
skybkg=float(get_head(image1,'SKYBKG'))
iraf.iqclip(image1,lthresh=minraw-skybkg,hthresh=maxraw-skybkg,
bookend=yes,maskin="",maskout="",clobber=yes,
verbose=no)
# Rename the file, if everything is well-behaved
reim=re.search('^%s%s(.+[^r])r?\.fits' % (flatpfx,biaspfx),
imagef,re.I)
if reim:
image2=reim.group(1)+'p.fits'
check_exist(image2,"w",yes)
iraf.imrename(imagef,image2,verbose=verbose)
else:
image2=imagef
# Set bad pixels to zero
update_head(image2,'BPM',bpmname,"Bad Pixel Mask")
iraf.iqmask(image2,mask='!BPM',method='constant',value='0.0',
clobber=yes,verbose=no)
# Defringing happens later, in bunches
# Cosmic Ray Rejection
tmpimg=iraf.mktemp("iqcr")+".fits"
check_exist("%s_%s.fits" % (image2[:15],crsfx),"w",clobber)
iraf.lacos_im(image2,tmpimg,"%s_%s.fits" % (image2[:15],crsfx),
gain=gain,readn=readn,skyval=skybkg,sigclip=4.5,
sigfrac=0.5,objlim=1.0,niter=1)
iraf.imdel(image2,verify=no,go_ahead=yes)
iraf.imcopy(tmpimg,image2,verbose=no)
iraf.imdel(tmpimg,verify=no,go_ahead=yes)
# Object-detection
if scistat.has_key("SEEING_%s" % file):
try:
fwhm=float(scistat["SEEING_%s" % file])
except:
fwhm=fwhm0
else:
fwhm=fwhm0
iraf.iqobjs(image2,sigma,satval,skyval="!SKYBKG",masksfx=masksfx,
wtimage="",fwhm=fwhm,pix=rawpix,aperture=2*fwhm/rawpix,
gain=gain,minlim=no,clobber=yes,verbose=no)
# Track some status information
nstars=get_head(image2,'NSTARS')
scistat['NSTARS']=nstars
if minskys.has_key(filt):
minsky=minskys[filt]
scistat["SKYBKG_%s" % filt]=skybkg/minsky
# Is it a focus frame?
focusval=get_head(image2,focuskey)
# Focus frame actions
if re.search(focusre,focusval,re.I):
focusfiles.append(image2)
# Find its place in the sequence
focusseq=get_head(image2,fseqkey)
ref=re.search("(\d+)of(\d+)",focusseq,re.I)
if ref:
ifocus=int(ref.group(1))
nfocus=int(ref.group(2))
# Non-focus frame actions
else:
# Make a new keyword for mosaic objects
objkey='OBJECT'
if check_head(image2,'MSCSIZE'):
mscsize=get_head(image2,'MSCSIZE')
mscdims=mscsize.split(',')
if int(mscdims[0])>1 or int(mscdims[1])>1:
object=get_head(image2,'OBJECT')
mscposn=get_head(image2,'MSCPOSN')
objmsc=object+'-'+mscposn
update_head(image2,'OBJMSC',objmsc,
'Object Name/Mosaic Position')
objkey='OBJMSC'
# Refine WCS (also calculates seeing in arcsec)
iraf.iqwcs(image2,objkey=objkey,rakey='RA',
deckey='DEC',pixtol=0.05,starfile='!STARFILE',
nstar=40,catalog='web',ubhost="localhost",
diffuse=yes,clobber=yes,verbose=verbose,
nstarmax=40)
# Retry if unsuccessful
if not check_head(image2,'IQWCS'):
iraf.iqwcs(image2,objkey=objkey,rakey='RA',
deckey='DEC',pixtol=0.05,starfile="!STARFILE",
nstar=40,catalog='web',ubhost="localhost",
diffuse=yes,clobber=yes,verbose=verbose,
nstarmax=1000)
# Calculate further quantities if WCS was successful
extinct='INDEF'
if check_head(image2,'IQWCS'):
scistat['WCSGOOD'] = 1
scistat["SEEING_%s" % filt]=get_head(image2,'SEEING')
[rapt,dcpt,lenx,leny]=get_head(image2,
['RA','DEC','NAXIS1','NAXIS2'])
[[ractr,dcctr]]=impix2wcs(image2,0.5*(1+float(lenx)),
0.5*(1+float(leny)))
coopt=astrocoords(rapt,dcpt)
cooctr=astrocoords(ractr,dcctr)
[offra,offdc]=radecdiff(coopt.radeg(),coopt.dcdeg(),
cooctr.radeg(),cooctr.dcdeg())
update_head(image2,'PTOFFSET',"%.2f %.2f" % \
(offra,offdc),
"Offset from nominal pointing (arcsec)")
scistat['PTOFFSET']="%.2f,%.2f" % (offra,offdc)
# Get zero-point against SDSS/NOMAD/USNO-B
if catmags.has_key(filt):
if check_head(image2,'OBJMSC'):
object=get_head(image2,'OBJMSC')
else:
object=get_head(image2,'OBJECT')
zpcat=""
# See if attempt already made for SDSS
if not (os.path.exists("%s.sdss" % object)):
getsdss(image2, "%s.sdss" % object)
# If successful, set to SDSS
sdssfile=open("%s.sdss" % object)
if (len(sdssfile.readlines())>2):
catalog="%s.sdss" % object
zpcat="SDSS"
# If SDSS unsuccessful, update USNO-B
if not zpcat:
update_usnob("%s.cat" % object,
outfile="%s.reg" % object)
catalog="%s.reg" % object
zpcat="USNO-B"
# Update image header
update_head(image2,"ZPCAT",zpcat)
# Run the zeropoint calculation
iraf.iqzeropt(image2,catmags[filt],
starfile="!STARFILE",catalog=catalog,
pixtol=3.0,useflags=yes,maxnum=50,
method="mean",rejout=1,fencelim=0.50,
sigma=1.5,maxfrac=0.25,
zptkey=zptkey,zpukey=zpukey,
clobber=yes,verbose=verbose)
# Use that to get an extinction estimate
zeropt,zeroptu,exptime=get_head(image2,[zptkey,
zpukey,exptmkey])
zeropt=float(zeropt)
zeroptu=float(zeroptu)
exptime=float(exptime)
scistat["ZEROPT_%s" % filt] = \
zeropt - 2.5*math.log10(exptime/exptmstd)
if minzpts.has_key(filt):
extinct = zeropt - \
2.5*math.log10(exptime/exptmstd) - \
minzpts[filt]
scistat["EXTINCT_%s" % filt]=extinct
# Fix the SEEING keyword if WCS fit was not successful
else:
scistat['WCSGOOD'] = 0
try:
seepix=float(get_head(image2,'SEEPIX'))
seeing= "%.3f" % (pix*seepix)
except:
seeing='INDEF'
update_head(image2,'SEEING',seeing,
"Estimated seeing in arcsec or INDEF")
# Write Archive Keywords
update_head(image2,'PROCESSD',1,
"Image has been processed by iqp60")
update_head(image2,'PROCVER',version,
"Version number of iqp60 used")
update_head(image2,'EXTINCT',extinct,
"Estimated mags extinction or INDEF")
update_head(image2,'PROCPROB','None',
"Problems encountered in iqp60 processing")
# Update status file
p60status(statfile,image2,scistat)
# Clean up
check_exist(image1,"w",yes)
##############################
# If a set of focus images have been processed, find best focus
if len(focusfiles)>=nfocus:
print "%d focus images have been processed" % len(focusfiles)
# Pick a starfile
focusfiles.sort()
medfile=focusfiles[len(focusfiles)/2]
starfile=get_head(medfile,'STARFILE')
# Update seeing values in all images based on good
# stars in the starfile.
ffiles=','.join(focusfiles)
iraf.iqseeing(ffiles,stars=starfile,
seekey="SEEING",method="acorr",useflags=yes,
skipstars=0,usestars=10,boxsize=64,
strictbox=no,imgsec="[940:1980,64:1980]",
update=yes,clobber=yes,verbose=no)
# Grab focus positions and seeing values
focx=[]
focy=[]
for image in focusfiles:
[fpos,seep]=list2float(get_head(image,['FOCUSPOS','SEEING']))
fpos=float(fpos)
seep=float(seep)
focx.append(fpos)
pix=rawpix
if check_head(image,binkey):
binval=get_head(image,binkey)
binels=binval.split()
binning=[int(binels[0]),int(binels[1])]
# Let's hope we don't ever do asymmetric binning
pix=binning[0]*rawpix
focy.append(pix*seep)
update_head(image,'SEEING',pix*seep,
"Estimated seeing in arcsec")
# Choose best-seeing as minimum of these
bestsee=min(focy)
bestfoc=focx[focy.index(bestsee)]
# This was too much verbosity for Brad
if verbose and 0:
print "Focus settings: "+liststr(focx,"%.2f")
print "Seeing values: "+liststr(focy,"%.1f")
print
print "Best focus: %.2f" % bestfoc
# Expunge the focusfiles list
allfocus.append(focusfiles)
focusfiles=[]
##############################
# Test end conditions
if endhow=="never":
done=no
elif endhow=="once":
done=yes
elif endhow=="time":
if time.time()>reftime:
done=yes
# Wait a little while
if not done:
time.sleep(twait)
def defringe(self, qombos):
if type(qombos) is StringType:
qombo = qombos
qombos = [qombo]
# Loop over input list of qombos
for qombo in qombos:
# Corresponding files
offiles2 = self.science_images(qombo, pfx=self.flatpfx)
if len(offiles2) == 0:
continue
oflist2 = ','.join(offiles2)
# Check for existence of fringe image
offrg = self.fringepre + qombo + '.fits'
if not os.path.exists(offrg):
self.mkfringe(qombo)
# Defringe images
iraf.iqdefringe(oflist2,
offrg,
outpfx=self.defrgpfx,
skykey="SKYBKG",
minlim=no,
clobber=self.clobber,
verbose=no)
# List of defringed images
offiles3 = pfx_list(offiles2, self.defrgpfx)
oflist3 = ','.join(offiles3)
# Clipping of defringed images
clipreg = self.clipreg
if len(clipreg) > 0:
re1 = re.search('(\d+):(\d+),(\d+):(\d+)', clipreg)
if re1:
szx = int(re1.group(2)) - int(re1.group(1)) + 1
szy = int(re1.group(4)) - int(re1.group(3)) + 1
for image in offiles3:
# Check that it's not already clipped
naxis1, naxis2 = get_head(image, ['NAXIS1', 'NAXIS2'])
if naxis1 <= szx and naxis2 <= szy:
continue
# Clip the defringed images
iraf.imcopy(image + clipreg, image, verbose=no)
# Clip the corresponding BPM
oldbpm = get_head(image, 'BPM')
newbpm = oldbpm.replace('.pl', self.clpsfx + '.pl')
if os.path.exists(oldbpm) and \
not os.path.exists(newbpm):
iraf.imcopy(oldbpm + clipreg, newbpm, verbose=yes)
# Update the image headers
update_head(image, 'BPM', newbpm)
else:
print "Failed to parse clipping region... not clipping"
####################
# Attempt WCS refinement
for image in offiles3:
# Skip images with good WCS
if check_head(image, 'IQWCS'):
if int(get_head(image, 'IQWCS')):
continue
# Object-detection
iraf.iqobjs(image,
self.sigma,
self.satval,
skyval="!SKYBKG",
masksfx=self.masksfx,
wtimage="",
minlim=no,
clobber=yes,
verbose=no)
# WCS refinement
iraf.iqwcs(image,
objkey=self.objkey,
rakey='RA',
deckey='DEC',
pixscl=self.pix,
pixtol=0.05,
starfile='!STARFILE',
catalog='ir',
diffuse=yes,
clobber=yes,
verbose=self.verbose)
# Figure out which have good WCS
wcsdict = keysplit(offiles3, 'IQWCS')
# Interpolate WCS onto files without good WCS so far
if wcsdict.has_key(""):
wcsbadfiles = wcsdict[""]
if len(wcsbadfiles) == len(offiles3):
print "No images with good WCS in this set"
else:
wcsgoodfiles = wcsdict[1]
wcsinterp(wcsbadfiles, wcsgoodfiles)
# Done with Step #5
update_head(offiles3, 'IQWRCSTP', 5, "Stage of IQWIRC processing")
def flatten(self, qombos, flat=None, flatscale=no):
if type(qombos) is StringType:
qombo = qombos
qombos = [qombo]
# Loop over input list of qombos
for qombo in qombos:
# Check for presence of calibration files
obj, filt = qombo_split(qombo)
if not self.check_calib(filt):
self.calib()
# Corresponding files
offiles = self.science_images(qombo)
if len(offiles) == 0:
continue
# Make a text ".lis" file to record this
putlines(qombo + '.lis', offiles, clobber=yes)
# Rescale flatfield if requested
inflat = self.flatpre + filt + '.fits'
outflat = self.flatpre + qombo + '.fits'
check_exist(outflat, "w", clobber=self.clobber)
if flatscale:
nirc_flatscale(offiles,
inflat,
outflat,
clipfrac=0.02,
clobber=yes)
else:
iraf.imcopy(inflat, outflat, verbose=no)
check_exist(outflat, "r")
# Clip flatfield and update BPM
iraf.iqclip(outflat,
lthresh=self.flatlow,
hthresh=self.flathigh,
bookend=no,
replace=1.0,
maskin='!BPM',
maskval=1,
maskout=self.bpmsfx)
# Rename the updated BPM
newbpm1 = get_head(outflat, 'BPM')
newbpm2 = newbpm1.replace(self.flatpre, '')
check_exist(newbpm2, 'w', clobber=self.clobber)
iraf.imrename(newbpm1, newbpm2, verbose=no)
update_head(outflat, 'BPM', newbpm2)
# Further preprocessing
for image in offiles:
# Keyword updates
update_head(image, [self.filtset, 'BPM'], [filt, newbpm2])
# Flatfielding
iraf.iqflatten(image,
outflat,
outpfx=self.flatpfx,
normflat=no,
statsec=self.statsec,
subsky=yes,
vignflat=no,
clipflat=no,
clobber=yes,
verbose=no)
# Set bad pixels to zero
image2 = self.flatpfx + image
iraf.iqmask(image2,
mask='!BPM',
method='constant',
value=0.0,
clobber=yes,
verbose=no)
# Write Useful Keywords
update_head(image2, 'PROCESSD', 1,
"Image has been processed by iqnirc")
update_head(image2, 'PROCVER', version,
"Version number of iqnirc used")
update_head(image2, 'ZEROPT', 'INDEF',
"Zero-point relative to 2MASS or INDEF")
update_head(image2, 'PROCPROB', 'None',
"Problems encountered in iqnirc processing")
# List of flatfielded images
offiles2 = pfx_list(offiles, self.flatpfx)
oflist2 = ','.join(offiles2)
# Object-detection
iraf.iqobjs(oflist2,
self.sigma,
self.satval,
skyval="!SKYBKG",
masksfx=self.masksfx,
wtimage="",
minlim=no,
clobber=yes,
verbose=no)
# Attempt WCS refinement
iraf.iqwcs(oflist2,
objkey=self.objkey,
rakey='RA',
deckey='DEC',
pixscl=self.pix,
pixtol=0.05,
starfile='!STARFILE',
catalog='ir',
diffuse=yes,
clobber=yes,
verbose=self.verbose)
# Done with Step #3
update_head(offiles2, 'IQWRCSTP', 3, "Stage of IQWIRC processing")
def kaitproc(inlist, clobber=globclob, verbose=globver):
infiles = iraffiles(inlist)
# Big loop
for image in infiles:
# Fix bad header keywords
root, ext = image.split('.')
fimg = pyfits.open(image)
fimg.verify('fix')
image2 = '%s.fits' % root
print fimg[0].header
fimg.writeto(image2)
#iraf.imcopy(image, image2)
# Update the WCS keywords
update_head(image2, ['CD1_1', 'CD2_2', 'CD1_2', 'CD2_1', 'PIXSCALE'],
[CD11, CD22, CD12, CD21, PIXSCALE])
update_head(
image2,
['WCSDIM', 'LTM1_1', 'LTM2_2', 'WAT0_001', 'WAT1_001', 'WAT2_001'],
[
2, 1.0, 1.0, 'system=image', 'wtype=tan axtype=ra',
'wtype=tan axtype=dec'
])
delete_head(image2,
['CROTA1', 'CROTA2', 'CDELT1', 'CDELT2', 'CSOURCE'])
# Update RA and Dec to J2000.0
[ra0, dec0, epoch] = get_head(image2, ['RA', 'DEC', 'EPOCH'])
point = ephem.readdb('Point,f|M|F7,%s,%s,0.0,%f' % (ra0, dec0, epoch))
point.compute(epoch='2000.0')
coo = astrocoords(str(point.a_ra), str(point.a_dec))
update_head(
image2, ['RA', 'DEC', 'EPOCH', 'CRVAL1', 'CRVAL2'],
[coo.sxg()[0],
coo.sxg()[1], 2000.0,
coo.radeg(),
coo.dcdeg()])
# Need Date to determine gain and readnoise (camera switch in May 2007)
dateobs = get_head(image2, "DATE-OBS")
tobs = DateTime(int(dateobs[6:]), int(dateobs[3:5]), int(dateobs[:2]))
if tobs - TFL > 0:
gain = FL_GAIN
readn = FL_READN
else:
gain = AP_GAIN
readn = AP_READN
update_head(image2, ['GAIN', 'READN'], [gain, readn])
# Clean cosmic rays
#tmpimg=iraf.mktemp("iqcr")+".fits"
#check_exist("%s_%s.fits" % (root,CRSFX),"w",clobber)
#iraf.lacos_im(image2,tmpimg,"%s_%s.fits" % (root,CRSFX),
#gain=gain,readn=readn,skyval=0.0,sigclip=4.5,
#sigfrac=0.5,objlim=2.0,niter=1)
#iraf.imdel(image2,verify=no,go_ahead=yes)
#iraf.imcopy(tmpimg,image2,verbose=no)
#iraf.imdel(tmpimg,verify=no,go_ahead=yes)
# Detect Objects
iraf.iqobjs(image2,
SIGMA,
SATVAL,
skyval="0.0",
masksfx=MASKSFX,
wtimage="",
fwhm=FWHM,
pix=PIXSCALE,
aperture=2 * FWHM / PIXSCALE,
gain=gain,
minlim=no,
clobber=yes,
verbose=no)
# Fit WCS
iraf.iqwcs(image2,
objkey='OBJECT',
rakey='RA',
deckey='DEC',
pixscl=PIXSCALE,
pixtol=0.05,
starfile='!STARFILE',
nstar=40,
catalog='web',
ubhost="localhost",
diffuse=yes,
clobber=yes,
verbose=verbose)
# Calculate zero-point
if get_head(image2, 'IQWCS'):
object = get_head(image2, 'OBJECT')
iraf.iqzeropt(image2,
REFMAG,
starfile="!STARFILE",
catalog=object.replace(" ", "_") + ".cat",
pixtol=3.0,
useflags=yes,
maxnum=50,
method="mean",
rejout=1,
fencelim=0.50,
sigma=1.5,
maxfrac=0.25,
zptkey=ZPTKEY,
zpukey=ZPUKEY,
clobber=yes,
verbose=verbose)
print 'Exiting Successfully'
return