CCD data reduction

Creation of lists

 filter="L"
 ls bias*[0-9].fit > bias.list
 ls dark600s-00*fit > dark600s.list
 ls dark*5sec*fit > dark5s.list
 ls flat*${filter}.fit > flat${filter}.list
 sed s/^/b/g flat${filter}.list > bflat${filter}.list
 sed s/^/bd/g flat${filter}.list > bdflat${filter}.list
 ls ngc*${filter}.fit > ${filter}.list 
 sed s/^/b/g ${filter}.list > b${filter}.list
 sed s/^/bd/g ${filter}.list > bd${filter}.list
 sed s/^/bdf/g ${filter}.list > bdf${filter}.list
 sed s/^/objbdf/g ${filter}.list | sed s/fit/pl/g > objbdf${filter}.list

Basic data reduction

1. Below is a bash script that creates lists of all images: biases, flats, darks and targets.
2. Special case of dark frames of 600sec that Milankovic generates is used
3. Last lines create ascii files with median values in flat frames that will be used
4. for their normalization

1. !/bin/bash

rm *list for frame in $(ls *fit); do filterType=$(gethead filter $frame) imageType=$(gethead imagetyp $frame) outFileName=$(echo $imageType | tr '[:upper:]' '[:lower:]') # test if DARK if [ ${imageType} = "DARK" ]; then exptime=$(gethead exptime $frame | cut -d. -f1) ls $frame >> ${outFileName}${exptime}"s".list echo "b"$frame >> "b"${outFileName}${exptime}"s".list else ls $frame >> ${outFileName}${filterType}.list fi # test if LIGHT and create additional lists if [ ${imageType} = "LIGHT" ]; then exptime=$(gethead exptime $frame | cut -d. -f1) echo $exptime >> exptime${filterType}.list echo "b"$frame >> "b"${outFileName}${filterType}.list echo "bd"$frame >> "bd"${outFileName}${filterType}.list echo "bdf"$frame >> "bdf"${outFileName}${filterType}.list else if [ ${imageType} = "FLAT" ]; then

               echo "b"$frame >> "b"${outFileName}${filterType}.list
               echo "bd"$frame >> "bd"${outFileName}${filterType}.list

echo "nbd"$frame >> "nbd"${outFileName}${filterType}.list fi fi done

1. Create dark current corresponding to each light frame using exposure time

for exptime in $(ls exptime*.list); do filter=$(echo $exptime | sed -e s/exptime//g -e s/\.list//g); awk -v filter=${filter} '{print "dc"NR"_"filter".fits"}' exptime${filter}.list > dc${filter}.list done

if [ -e reduce.cl ]; then rm reduce.cl; fi echo "imdelete master_bias,dc_600s,dc_5s,dc_1s" >> reduce.cl echo "imcombine @bias.list master_bias comb=med" >> reduce.cl echo "imarith @dark600s.list - master_bias @bdark600s.list" >> reduce.cl echo "imarith @dark5s.list - master_bias @bdark5s.list" >> reduce.cl echo "imcombine @bdark5s.list dc_5s comb=med" >> reduce.cl echo "imcombine @bdark600s.list dc_600s comb=med" >> reduce.cl echo "imarith dc_600s / 600 dc_1s" >> reduce.cl

for flats in $(ls flat*list); do filterType=$(echo $flats | sed s/flat//g | cut -d. -f1) #echo $filterType echo "imarith @flat${filterType}.list - master_bias @bflat${filterType}.list" >> reduce.cl echo "imarith @bflat${filterType}.list - dc_5s @bdflat${filterType}.list" >> reduce.cl echo "imstat @bdflat${filterType}.list fields=\"image,midpt\" format- > norm${filterType}.txt" >> reduce.cl done

BPM & object mask creation

 # cat bpmask.cl
 imstat dc_300s field="image,mean,stddev" for- > hot.txt
 imstat master_flat_FILTER fields="image,mean" for- > cold.txt
 cl < bpmask.cl
 # awk -v filter="L" '{print "imexpr \"((a > b) ? 1 : 0)\" hot"filter".pl a="$1" b="($2+3.*$3)*0.75}' hot.txt > hot.cl
 # awk -v filter="L" '{print "imexpr \"((a < b) ? 1 : 0)\" cold"filter".pl a="$1" b="$2*0.9}' cold.txt > cold.cl
 cl < hot.cl
 cl < cold.cl
 # cat bpm.cl
 imexpr "max(a,b)" bpmFILTER.pl a=hotFILTER.pl b=coldFILTER.pl
 hedit @bdfFILTER.list BPM bpmFILTER.pl add+ ver- 
 # sed 's/FILTER/'${filter}'/g'  bpm.cl > dobpm.cl
 cl < dobpm.cl
 
 # Object masks creation
 nproto
 objmask @bdfFILTER.list @objbdfFILTER.list masks="!BPM" hsig=2 lsig=2

Astrometry

# cat astrometry.sh
gethead OBJCTRA @bdfFILTER.list > name_ra.txt 
gethead OBJCTDEC @bdfFILTER.list | awk '{print $2,$3,$4}' > dec.txt
paste -d" " name_ra.txt dec.txt | awk '{print $1,($2+$3/60+$4/3600)*15,$5+$6/60+$7/3600}' > astrometryFILTER.txt
# sed s/FILTER/${filter}/g astrometry.sh  > astrometry${filter}.sh

sh astrometry${filter}.sh

 # This could be used:
 # cat komanda.sh
 solve-field img --ra imagera --dec imagedec --radius 0.2 --scale-units arcsecperpix --scale-low 0.38 --scale-high 0.40 --crpix-center --wcs img.wcs 
 ### The next command creates new files instead of just wcs binaries that can later be added to the header. It's a stand-alone command. And should be ignored.
 ### solve-field img --ra imagera --dec imagedec --radius 0.2 --scale-units arcsecperpix --scale-low 0.38 --scale-high 0.40 --crpix-center -p -N wcsimg.fit  \ 
 ###  -O -I noneI.fits -M none.fits -R none.fits -B none.fits -P none -k none -U none -y -S none --axy noneaxy 
 #while read line; do img=$(echo $line | awk '{print $1}'); imagera=$(echo $line | awk '{print $2}'); imagedec=$(echo $line | awk '{print $3}'); sed -e 's/img/'$img'/g' \ 
-e 's/imagera/'${imagera}'/g' -e 's/imagedec/'${imagedec}'/g' komanda.sh; done < astrometry${filter}.txt > doAstrometry.sh 
# Or this:
 awk '{print "solve-field "$1" --ra "$2" --dec "$3" --radius 0.2 --scale-units arcsecperpix --scale-low 0.38 --scale-high 0.40 --crpix-center -p -N wcs"$1" \ 
 -O -I noneI.fits -M none.fits -R none.fits -B none.fits -P none -k none -U none -y -S none --axy noneaxy --wcs bla.wcs"}' astrometry${filter}.txt > doAstrometry.sh

# /bin/bash doAstrometry.sh
 #ls *wcs > wcs${filter}.list
 # echo "wcscopy @bdf${filter}.list @wcs${filter}.list ver-" > dowcs.cl
cl < dowcs.cl

Supersky flat

# Creation of super sky flat, normalization to each individual image median background and final stacking
# cat stat.cl
real mini
real sky
imstat("img",fields="min",lower=INDEF,upper=INDEF,for-) | scanf("%g", mini)
imcalc(input="img,msk",output="skyimage",equals="if(im2==0.) then im1 else "//mini-0.001,ver-)
imstat("skyimage",fields="midpt",lower=mini-0.001,upper=INDEF,for-) | scanf("%g", sky)
print("img"," ",sky)
imarith("img","/",sky,"norm")
imdelete("skyimage",yes)
# while read line; do img=$(echo $line | awk '{print $1}'); msk="obj"${img%.*}.pl; rsky="norm"${img}; cat stat.cl | sed -e 's/img/'${img}'/g' \
-e 's/msk/'${msk}'/g'  -e 's/norm/'${rsky}'/g'; done < bdf${filter}.list >  bla.cl
cl < bla.cl > med_values.txt
# ls normbdf*fit > norm.list
imcomb @norm.list norm.fits comb=med masktype="!OBJMASK" maskval=0
# awk '{print "imarith norm.fits * "$2," n"$1}' med_values.txt > donorm.cl
cl < donorm.cl
# awk '{print "imarith",$1,"-","n"$1,"s"$1}' med_values.txt > do.cl
cl < do.cl
   
imcomb s@bdfFILTER.list final.fits comb=med offset="wcs"

Surface brightness limit

1. Calibrate the image taking non-saturated stars and not too faint stars: intercept and slope (TOPCAT with SDSS DR12 from Vizier)
2. Calculate statistics inside at least 20 (empty, i.e. without objects) boxes of the size of 10" (for example if 1pix=0.396" than 10"~25 pix so boxes = 25 pix × 25 pix)
3. Take the mean value of the standard deviation inside boxes and it's standard deviation
4. Calculate SBmin and SBmax as: 
   SBmax =-2.5*log10(<σ>-stdev(<σ>))*slope+intercept 
   SBmin =-2.5*log10(<σ>+stdev(<σ>))*slope+intercept 
where <σ> is the average standard deviation inside boxes and stdev(<σ>) its standard deviation.
5. Finally, 1 sigma surface brightness limit (SBlim) is given as:
   SBlim = (SBmin+SBmax)/2 +/- (SBmax-SBmin)/2