def calibphot(inlist, fwhm,
rdnoise='2.6', gain='2.5',
interact=yes, config='',
objkey="OBJECT", airkey="AIRMASS",
filtkey='FILTER', skykey='SKYBKG', phosfx="pho",
possfx="pos",
clobber=globclob, verbose=globver):
""" perform aperture photometry on a standard field to fit the
transformation equations. these transformation equations will
then be applied to comparison stars' aperture photometries
outputted by psfphot.py, in order to find the true magnitudes of
the comparison stars. this will then provide and apply the
corrections to the magnitude of a single target star (SN?). """
# Defaults / constants
alpha=list('abcdefghijklmnopqrstuvwxyz')
psfmult=5 #standard factor (multiplied by fwhm to get psfradius)
imgprop={}
imglist={}
allobjs={}
allfilt={}
# Necessary package
iraf.imutil()
# Parse gain/readnoise inputs
gainkey=None
re1=re.search('^!(.+)',gain)
re2=re.search('^[\d\.]+',gain)
if re1:
gainkey=re1.group(1)
elif re2:
try:
gainval=float(gain)
except:
print "Error converting gain"
return
else:
print "Error finding gain"
return
rdnskey=None
re1=re.search('^!(.+)',rdnoise)
re2=re.search('^[\d\.]+',rdnoise)
if re1:
rdnskey=re1.group(1)
elif re2:
try:
readval=float(rdnoise)
except:
print "Error converting readnoise"
return
else:
print "Error finding readnoise"
return
# Parse inputs
infiles=iraffiles(inlist)
#first make sure to add back in background of sky
iraf.iqsubsky(inlist, sub=no, skykey=skykey)
# Process each file in turn
for image in infiles:
# Check that the image is there
check_exist(image,"r")
# Grab all the useful keywords
[sky,objname,filter,airmass] = \
get_head(image,[skykey,objkey,filtkey,airkey])
# Get gain & readnoise, if necessary
if gainkey:
gainval=get_head(image,gainkey)
if rdnskey:
readval=get_head(image,rdnskey)
# Calculate theoretical sigma of sky
if len(str(sky))>0:
sigma= (((sky * gainval) + readval**2)**.5) / gainval
else:
print "Failed to retrieve sky value from image header"
return
# check standard field name
if len(objname)==0:
print "Failed to retrieve object name from image header"
return
# Generate posfile and phofile names
posfile=objname+'.'+possfx
phofile=objname+'.'+phosfx
# check filter name
if len(filter)==0:
print "Failed to retrieve filter name from image header"
return
# Check airmass value
if len(airmass)>0:
try:
airval=float(airmass)
except:
print "Failed to convert airmass value to float"
return
else:
print "Failed to retrieve airmass value from image header"
return
# Save keyword values for this image
imgprop[image]=[gainval,readval,sky,objname,filter,airmass]
# Add dictionary entries for the current image
listkey=objname+'-'+filter
if imglist.has_key(listkey):
imglist[listkey].append(image)
else:
imglist[listkey]=[image]
# Keep track of all filters/object fields
allobjs[objname]=1
allfilt[filter]=1
#add in extra range of aperture radii, leave in background?
fwhmpsf=float(fwhm)
ap1 = fwhmpsf
ap15 = 1.5 * fwhmpsf
ap2 = 2 * fwhmpsf
ap25 = 2.5 * fwhmpsf
ap3 = 3 * fwhmpsf
innersky = 3.5 * fwhmpsf
#do photometry on all stars in field
check_exist(image+".mag.std.1", "w", clobber=yes)
iraf.phot(image, output = image+".mag.std.1", coords=posfile,
sigma=sigma, datamin = sky - 3.5*sigma, apertures = ap25,
dannulus="10", annulus=innersky, verify="no")
##############################
#make imsets file
imsetsfile="stdfield.dat"
imsetstuff = open(imsetsfile,"w")
for objname in allobjs.keys():
maxnum=0
for key in imglist.keys():
if re.search(objname,key):
maxnum=max(maxnum,len(imglist[key]))
for i in range(maxnum):
imset=objname+alpha[i]+" :"
for key in imglist.keys():
if re.search(objname,key):
if i<len(imglist[key]):
imset+=" "+imglist[key][i]
imsetstuff.write(imset+"\n")
imsetstuff.close()
#make observations file (specify aperture number?)
obsfile = "standobs"
check_exist(obsfile, "w", clobber=yes)
iraf.mknobsfile(photfiles = "*.mag.std.1",
idfilters = " ".join(allfilt.keys()),
imsets = imsetsfile, observations = obsfile,
tolerance="500")
#rename stars in catalog file so they agree, print good stars to new file
catpholines = getlines(phofile)
s=1
newcatpholines = [catpholines[0]]
lastline = catpholines[-1]
lastlinedata = lastline.split()
digits = len(lastlinedata[0])+1
for line in catpholines:
if re.search("vary?", line):
continue
ess=str(s)
idlength=len(objname)+len(ess)+1
numspace= digits - idlength + 1
newline = " "*numspace+objname+"-"+ess+line[digits:]
s=s+1
if not re.search("99.999",newline):
newcatpholines.append(newline)
newcatdata = "\n".join(newcatpholines)
newphofile = phofile+".2"
newphostuff = open(phofile+".2", "w")
newphostuff.write(newcatdata)
newphostuff.close()
#rename stars in standobs to be field-# instead of fielda-#, fieldb-#, etc
#what is field?
obsdatalines=getlines(obsfile)
for i in range(len(obsdatalines)):
line=obsdatalines[i]
for objname in allobjs.keys():
if re.search(objname,line):
index=line.index(objname)
lline=list(line)
lline[index:index+len(objname)+1]=list(" "+objname)
line="".join(lline)
obsdatalines[i]=line
break
newobsdata = "\n".join(obsdatalines)
fixobsfile = "fix"+obsfile
fixobsstuff = open(fixobsfile, "w")
fixobsstuff.write(newobsdata)
fixobsstuff.close()
#if no config file exists, make one
#first, make a file that has stetson catalog formats in it
if not config:
newconfig="fcat.dat"
check_exist(newconfig, "w", clobber=yes)
catformat=open(newconfig, "w")
catinfo = ["#Declare the catalog variables", " ", "catalog", " ",
" B\t2", "Berror\t3", "V\t6", "Verror\t7",
"R\t10", "Rerror\t11", "I\t14", "Ierror\t15"]
catdata = "\n".join(catinfo)
catformat.write(catdata)
catformat.close()
config="cat.cfg"
transfile="ftrans.dat"
check_exist(transfile, "w", clobber=yes)
transstuff=open(transfile, "w")
transinfo = ["transformation", " ", "fit v1 = 0, v2 = 0.17, v3= 0", "fit b1 = 0, b2 = 0.35, b3= 0", "fit r1 = 0, r2 = 0.08, r3= 0", " ", "const v4 = 0", "const b4 = 0", "const r4 = 0", " ", "Vfit : V = mV + v1 + v2*XV + v3*(mB-mV) + v4*(mB-mV)*XV", "Bfit : B = mB + b1 + b2*XB + b3*(mB-mV) + b4*(mB-mV)*XB", "Rfit : R = mR + r1 + r2*XR + r3*(mV-mR) + r4*(mV-mR)*XR"]
transdata = "\n".join(transinfo)+"\n"
transstuff.write(transdata)
transstuff.close()
check_exist(config, "w", clobber=yes)
iraf.mkconfig(config, catalog = newconfig,
observations = "f"+obsfile+".dat",
transform=transfile, check=no, edit=no)
#fit parameters of transformation equations (specify aperture in ansfile?)
ansfile = objname+".ans.1"
check_exist(ansfile, "w", clobber=yes)
iraf.fitparams(observations = fixobsfile, catalogs = newphofile,
config=config, parameters = ansfile, interactive = interact)
#apply to standard stars to check to make sure fits are okay?
calibfile = objname+".calib.1"
check_exist(calibfile, "w", clobber=yes)
iraf.evalfit(observations = fixobsfile, config = config,
parameters = ansfile, calib = calibfile)
def psfphot(inlist,
ra,
dec,
reffilt,
interact,
fwhm,
readnoise,
gain,
threshold,
refimage=None,
starfile=None,
maxnpsf=5,
clobber=globclob,
verbose=globver,
skykey='SKYBKG',
filtkey='FILTER',
pixtol=3.0):
""" perform PSF-based photometry on a single target star (SN?) at RA, Dec and
also on a set of comparison stars, using daophot. simultaneously
perform aperture photometry on all the comparison stars (after
subtracting off contributions from neighbors) to enable absolute
photometry by comparison to aperture photometry of standard stars
observed in other fields """
# Defaults / constants
psfmult = 5.0 #standard factor (multiplied by fwhm to get psfradius)
psfmultsmall = 3.0 #similar to psfmult, adjusted for nstar and substar
# Necessary package
iraf.imutil()
# Parse inputs
infiles = iraffiles(inlist)
# Which file is reffilt? call it refimage
if refimage == None:
for image in infiles:
if check_head(image, filtkey):
try:
imgfilt = get_head(image, filtkey)
if imgfilt == reffilt:
refimage = image
break
except:
pass
if not refimage:
print "BAD USER! No image corresponds to the filter: %s" % reffilt
return
else:
refroot = 's' + refimage.split('.')[0]
#first make sure to add back in background of sky
iraf.iqsubsky(inlist, sub=no, skykey=skykey)
#put reference image first on list
infiles.remove(refimage)
infiles.insert(0, refimage)
#setup for keywords
if gain == "!GAIN":
try:
gainval = float(get_head(image, gain))
except:
print "Bad header keyword for gain."
else:
gainval = float(gain)
if readnoise == "!READNOISE":
try:
readval = float(get_head(image, readnoise))
except:
print "Bad header keyword for readnoise."
else:
readval = float(readnoise)
# Process each file in turn
for image in infiles:
# Check that the image is there
check_exist(image, "r")
# Grab image root name
root = image.split('.')[0]
# Map image to reference image
if not (image == refimage):
[nx, ny] = get_head(image, ['NAXIS1', 'NAXIS2'])
stars = Starlist(get_head(image, 'STARFILE'))
refstars = Starlist(get_head(refimage, 'STARFILE'))
refstars.pix2wcs(refimage)
refstars.wcs2pix(image)
match, refmatch = stars.match(refstars, useflags=yes, tol=10.0)
nstars = len(match)
if not (nstars > 2):
print 'Could not find star matches between reference and %s' % image
infiles.remove(image)
continue
refmatch.pix2wcs(image)
refmatch.wcs2pix(refimage)
matchfile = open('%s.match' % root, 'w')
for i in range(len(match)):
matchfile.write('%10.3f%10.3f%10.3f%10.3f\n' %
(refmatch[i].xval, refmatch[i].yval,
match[i].xval, match[i].yval))
matchfile.close()
check_exist('%s.geodb' % root, 'w', clobber=clobber)
iraf.geomap('%s.match' % root,
'%s.geodb' % root,
1.0,
nx,
1.0,
ny,
verbose=no,
interactive=no)
check_exist('s%s.fits' % root, 'w', clobber=clobber)
iraf.geotran(image,
's%s' % root,
'%s.geodb' % root,
'%s.match' % root,
geometry="geometric",
boundary="constant",
verbose=no)
else:
iraf.imcopy(image, 's%s' % root)
root = 's%s' % root
#get sky level and calculate sigma
#if check_head(image, skykey):
# try:
# sky=float(get_head(image, skykey))
# except:
# print "No sky levels in header."
#sigma= (((sky * gainval) + readval**2)**.5) / gainval
iraf.iterstat(image)
# Saturation level
if not check_head(image, "SATURATE"):
saturate = 60000.0
else:
saturate = get_head(image, "SATURATE")
# Update datapars and daopars
iraf.datapars.fwhmpsf = fwhm
iraf.datapars.sigma = iraf.iterstat.sigma
iraf.datapars.datamin = iraf.iterstat.median - 10 * iraf.iterstat.sigma
iraf.datapars.datamax = 0.90 * saturate
iraf.datapars.readnoise = readval
iraf.datapars.epadu = gainval
iraf.datapars.filter = filtkey
iraf.daopars.psfrad = psfmult * fwhm
iraf.daopars.fitrad = fwhm
iraf.daopars.function = "gauss,moffat15,moffat25,lorentz,penny1"
#find stars in image unless a starlist is given
if image == refimage and starfile == None:
iraf.daophot.daofind(root,
'refimage.coo.1',
threshold=threshold,
verify=no,
verbose=verbose)
elif image == refimage:
shutil.copy(starfile, 'refimage.coo.1')
#initial photometry
iraf.daophot.phot(root,
'refimage.coo.1',
'default',
aperture=fwhm,
verify=no,
verbose=verbose)
#select stars for psf the first time
refstarsfile = "refimage.pst.1"
if image == refimage:
iraf.pstselect(root,
'default',
refstarsfile,
maxnpsf,
interactive=yes,
verify=no,
verbose=verbose)
#fit the psf
iraf.psf(root,
'default',
refstarsfile,
'default',
'default',
'default',
interactive=interact,
verify=no,
verbose=verbose)
#identify neighboring/interfering stars to selected stars
groupingfile = root + ".psg.1"
iraf.nstar(root,
groupingfile,
'default',
'default',
'default',
psfrad=psfmultsmall * fwhm,
verify=no,
verbose=verbose)
#subtract out neighboring stars from image
iraf.substar(root,
'default',
refstarsfile,
'default',
'default',
psfrad=psfmultsmall * fwhm,
verify=no,
verbose=verbose)
#repeat psf to get better psf model
#IRAF's interactive version usually crashes
subtractedimage = root + ".sub.1"
iraf.psf(subtractedimage,
root + ".nst.1",
refstarsfile,
'%s.psf.2' % root,
'%s.pst.2' % root,
'%s.psg.2' % root,
interactive=interact,
verify=no,
verbose=verbose)
#Need to make sure SN was detected by daofind
stars = Starlist('%s.mag.1' % root)
SN = Star(name='SN', radeg=ra, dcdeg=dec, fwhm=2.0, fwhmw=2.0)
SNlis = Starlist(stars=[SN])
SNlis.wcs2pix(image)
if (len(stars.match(SNlis)[0]) == 0):
#No match - need to add to daofind file
print "No match!"
coofile = open('refimage.coo.1', 'a+')
coofile.write('%10.3f%10.3f%9.3f%8.3f%13.3f%12.3f%8i\n' %
(SNlis[0].xval, SNlis[0].yval, 99.999, 0.500, 0.000,
0.000, 999))
coofile.close()
#repeat aperture photometry to get good comparisons to standard fields
iraf.daophot.phot(root,
'refimage.coo.1',
'default',
aperture=psfmult * fwhm,
verify=no,
verbose=verbose)
# allstar run
iraf.allstar(root,
'default',
'default',
'default',
'default',
'default',
verify=no,
verbose=verbose)
def calibphot(inlist,
fwhm,
rdnoise='2.6',
gain='2.5',
interact=yes,
config='',
objkey="OBJECT",
airkey="AIRMASS",
filtkey='FILTER',
skykey='SKYBKG',
phosfx="pho",
possfx="pos",
clobber=globclob,
verbose=globver):
""" perform aperture photometry on a standard field to fit the
transformation equations. these transformation equations will
then be applied to comparison stars' aperture photometries
outputted by psfphot.py, in order to find the true magnitudes of
the comparison stars. this will then provide and apply the
corrections to the magnitude of a single target star (SN?). """
# Defaults / constants
alpha = list('abcdefghijklmnopqrstuvwxyz')
psfmult = 5 #standard factor (multiplied by fwhm to get psfradius)
imgprop = {}
imglist = {}
allobjs = {}
allfilt = {}
# Necessary package
iraf.imutil()
# Parse gain/readnoise inputs
gainkey = None
re1 = re.search('^!(.+)', gain)
re2 = re.search('^[\d\.]+', gain)
if re1:
gainkey = re1.group(1)
elif re2:
try:
gainval = float(gain)
except:
print "Error converting gain"
return
else:
print "Error finding gain"
return
rdnskey = None
re1 = re.search('^!(.+)', rdnoise)
re2 = re.search('^[\d\.]+', rdnoise)
if re1:
rdnskey = re1.group(1)
elif re2:
try:
readval = float(rdnoise)
except:
print "Error converting readnoise"
return
else:
print "Error finding readnoise"
return
# Parse inputs
infiles = iraffiles(inlist)
#first make sure to add back in background of sky
iraf.iqsubsky(inlist, sub=no, skykey=skykey)
# Process each file in turn
for image in infiles:
# Check that the image is there
check_exist(image, "r")
# Grab all the useful keywords
[sky,objname,filter,airmass] = \
get_head(image,[skykey,objkey,filtkey,airkey])
# Get gain & readnoise, if necessary
if gainkey:
gainval = get_head(image, gainkey)
if rdnskey:
readval = get_head(image, rdnskey)
# Calculate theoretical sigma of sky
if len(str(sky)) > 0:
sigma = (((sky * gainval) + readval**2)**.5) / gainval
else:
print "Failed to retrieve sky value from image header"
return
# check standard field name
if len(objname) == 0:
print "Failed to retrieve object name from image header"
return
# Generate posfile and phofile names
posfile = objname + '.' + possfx
phofile = objname + '.' + phosfx
# check filter name
if len(filter) == 0:
print "Failed to retrieve filter name from image header"
return
# Check airmass value
if len(airmass) > 0:
try:
airval = float(airmass)
except:
print "Failed to convert airmass value to float"
return
else:
print "Failed to retrieve airmass value from image header"
return
# Save keyword values for this image
imgprop[image] = [gainval, readval, sky, objname, filter, airmass]
# Add dictionary entries for the current image
listkey = objname + '-' + filter
if imglist.has_key(listkey):
imglist[listkey].append(image)
else:
imglist[listkey] = [image]
# Keep track of all filters/object fields
allobjs[objname] = 1
allfilt[filter] = 1
#add in extra range of aperture radii, leave in background?
fwhmpsf = float(fwhm)
ap1 = fwhmpsf
ap15 = 1.5 * fwhmpsf
ap2 = 2 * fwhmpsf
ap25 = 2.5 * fwhmpsf
ap3 = 3 * fwhmpsf
innersky = 3.5 * fwhmpsf
#do photometry on all stars in field
check_exist(image + ".mag.std.1", "w", clobber=yes)
iraf.phot(image,
output=image + ".mag.std.1",
coords=posfile,
sigma=sigma,
datamin=sky - 3.5 * sigma,
apertures=ap25,
dannulus="10",
annulus=innersky,
verify="no")
##############################
#make imsets file
imsetsfile = "stdfield.dat"
imsetstuff = open(imsetsfile, "w")
for objname in allobjs.keys():
maxnum = 0
for key in imglist.keys():
if re.search(objname, key):
maxnum = max(maxnum, len(imglist[key]))
for i in range(maxnum):
imset = objname + alpha[i] + " :"
for key in imglist.keys():
if re.search(objname, key):
if i < len(imglist[key]):
imset += " " + imglist[key][i]
imsetstuff.write(imset + "\n")
imsetstuff.close()
#make observations file (specify aperture number?)
obsfile = "standobs"
check_exist(obsfile, "w", clobber=yes)
iraf.mknobsfile(photfiles="*.mag.std.1",
idfilters=" ".join(allfilt.keys()),
imsets=imsetsfile,
observations=obsfile,
tolerance="500")
#rename stars in catalog file so they agree, print good stars to new file
catpholines = getlines(phofile)
s = 1
newcatpholines = [catpholines[0]]
lastline = catpholines[-1]
lastlinedata = lastline.split()
digits = len(lastlinedata[0]) + 1
for line in catpholines:
if re.search("vary?", line):
continue
ess = str(s)
idlength = len(objname) + len(ess) + 1
numspace = digits - idlength + 1
newline = " " * numspace + objname + "-" + ess + line[digits:]
s = s + 1
if not re.search("99.999", newline):
newcatpholines.append(newline)
newcatdata = "\n".join(newcatpholines)
newphofile = phofile + ".2"
newphostuff = open(phofile + ".2", "w")
newphostuff.write(newcatdata)
newphostuff.close()
#rename stars in standobs to be field-# instead of fielda-#, fieldb-#, etc
#what is field?
obsdatalines = getlines(obsfile)
for i in range(len(obsdatalines)):
line = obsdatalines[i]
for objname in allobjs.keys():
if re.search(objname, line):
index = line.index(objname)
lline = list(line)
lline[index:index + len(objname) + 1] = list(" " + objname)
line = "".join(lline)
obsdatalines[i] = line
break
newobsdata = "\n".join(obsdatalines)
fixobsfile = "fix" + obsfile
fixobsstuff = open(fixobsfile, "w")
fixobsstuff.write(newobsdata)
fixobsstuff.close()
#if no config file exists, make one
#first, make a file that has stetson catalog formats in it
if not config:
newconfig = "fcat.dat"
check_exist(newconfig, "w", clobber=yes)
catformat = open(newconfig, "w")
catinfo = [
"#Declare the catalog variables", " ", "catalog", " ", " B\t2",
"Berror\t3", "V\t6", "Verror\t7", "R\t10", "Rerror\t11", "I\t14",
"Ierror\t15"
]
catdata = "\n".join(catinfo)
catformat.write(catdata)
catformat.close()
config = "cat.cfg"
transfile = "ftrans.dat"
check_exist(transfile, "w", clobber=yes)
transstuff = open(transfile, "w")
transinfo = [
"transformation", " ", "fit v1 = 0, v2 = 0.17, v3= 0",
"fit b1 = 0, b2 = 0.35, b3= 0", "fit r1 = 0, r2 = 0.08, r3= 0",
" ", "const v4 = 0", "const b4 = 0", "const r4 = 0", " ",
"Vfit : V = mV + v1 + v2*XV + v3*(mB-mV) + v4*(mB-mV)*XV",
"Bfit : B = mB + b1 + b2*XB + b3*(mB-mV) + b4*(mB-mV)*XB",
"Rfit : R = mR + r1 + r2*XR + r3*(mV-mR) + r4*(mV-mR)*XR"
]
transdata = "\n".join(transinfo) + "\n"
transstuff.write(transdata)
transstuff.close()
check_exist(config, "w", clobber=yes)
iraf.mkconfig(config,
catalog=newconfig,
observations="f" + obsfile + ".dat",
transform=transfile,
check=no,
edit=no)
#fit parameters of transformation equations (specify aperture in ansfile?)
ansfile = objname + ".ans.1"
check_exist(ansfile, "w", clobber=yes)
iraf.fitparams(observations=fixobsfile,
catalogs=newphofile,
config=config,
parameters=ansfile,
interactive=interact)
#apply to standard stars to check to make sure fits are okay?
calibfile = objname + ".calib.1"
check_exist(calibfile, "w", clobber=yes)
iraf.evalfit(observations=fixobsfile,
config=config,
parameters=ansfile,
calib=calibfile)
def psfphot(inlist, ra, dec, reffilt, interact, fwhm, readnoise, gain,
threshold,refimage=None,starfile=None,maxnpsf=5,
clobber=globclob,verbose=globver,skykey='SKYBKG',
filtkey='FILTER',pixtol=3.0):
""" perform PSF-based photometry on a single target star (SN?) at RA, Dec and
also on a set of comparison stars, using daophot. simultaneously
perform aperture photometry on all the comparison stars (after
subtracting off contributions from neighbors) to enable absolute
photometry by comparison to aperture photometry of standard stars
observed in other fields """
# Defaults / constants
psfmult=5.0 #standard factor (multiplied by fwhm to get psfradius)
psfmultsmall=3.0 #similar to psfmult, adjusted for nstar and substar
# Necessary package
iraf.imutil()
# Parse inputs
infiles=iraffiles(inlist)
# Which file is reffilt? call it refimage
if refimage==None:
for image in infiles:
if check_head(image, filtkey):
try:
imgfilt = get_head(image, filtkey)
if imgfilt == reffilt:
refimage = image
break
except:
pass
if not refimage:
print "BAD USER! No image corresponds to the filter: %s" % reffilt
return
else:
refroot='s'+refimage.split('.')[0]
#first make sure to add back in background of sky
iraf.iqsubsky(inlist, sub=no, skykey=skykey)
#put reference image first on list
infiles.remove(refimage)
infiles.insert(0,refimage)
#setup for keywords
if gain == "!GAIN":
try: gainval = float(get_head(image, gain))
except:
print "Bad header keyword for gain."
else:
gainval = float(gain)
if readnoise == "!READNOISE":
try: readval = float(get_head(image, readnoise))
except:
print "Bad header keyword for readnoise."
else:
readval = float(readnoise)
# Process each file in turn
for image in infiles:
# Check that the image is there
check_exist(image,"r")
# Grab image root name
root=image.split('.')[0]
# Map image to reference image
if not (image==refimage):
[nx,ny]=get_head(image,['NAXIS1','NAXIS2'])
stars=Starlist(get_head(image,'STARFILE'))
refstars=Starlist(get_head(refimage,'STARFILE'))
refstars.pix2wcs(refimage)
refstars.wcs2pix(image)
match,refmatch=stars.match(refstars,useflags=yes,tol=10.0)
nstars=len(match)
if not (nstars>2):
print 'Could not find star matches between reference and %s' % image
infiles.remove(image)
continue
refmatch.pix2wcs(image)
refmatch.wcs2pix(refimage)
matchfile=open('%s.match' % root, 'w')
for i in range(len(match)):
matchfile.write('%10.3f%10.3f%10.3f%10.3f\n' %
(refmatch[i].xval,refmatch[i].yval,
match[i].xval,match[i].yval))
matchfile.close()
check_exist('%s.geodb' % root, 'w', clobber=clobber)
iraf.geomap('%s.match' % root,'%s.geodb' % root,1.0,nx,1.0,ny,
verbose=no,interactive=no)
check_exist('s%s.fits' % root, 'w', clobber=clobber)
iraf.geotran(image,'s%s' % root,'%s.geodb' % root,
'%s.match' % root,geometry="geometric",
boundary="constant",verbose=no)
else:
iraf.imcopy(image,'s%s' % root)
root='s%s' % root
#get sky level and calculate sigma
#if check_head(image, skykey):
# try:
# sky=float(get_head(image, skykey))
# except:
# print "No sky levels in header."
#sigma= (((sky * gainval) + readval**2)**.5) / gainval
iraf.iterstat(image)
# Saturation level
if not check_head(image, "SATURATE"):
saturate = 60000.0
else:
saturate = get_head(image, "SATURATE")
# Update datapars and daopars
iraf.datapars.fwhmpsf=fwhm
iraf.datapars.sigma=iraf.iterstat.sigma
iraf.datapars.datamin=iraf.iterstat.median-10*iraf.iterstat.sigma
iraf.datapars.datamax=0.90*saturate
iraf.datapars.readnoise=readval
iraf.datapars.epadu=gainval
iraf.datapars.filter=filtkey
iraf.daopars.psfrad=psfmult*fwhm
iraf.daopars.fitrad=fwhm
iraf.daopars.function="gauss,moffat15,moffat25,lorentz,penny1"
#find stars in image unless a starlist is given
if image==refimage and starfile==None:
iraf.daophot.daofind(root,'refimage.coo.1',threshold=threshold,verify=no,
verbose=verbose)
elif image==refimage:
shutil.copy(starfile,'refimage.coo.1')
#initial photometry
iraf.daophot.phot(root,'refimage.coo.1','default',aperture=fwhm,verify=no,
verbose=verbose)
#select stars for psf the first time
refstarsfile = "refimage.pst.1"
if image == refimage:
iraf.pstselect(root,'default',refstarsfile,maxnpsf,
interactive=yes,verify=no,verbose=verbose)
#fit the psf
iraf.psf(root,'default',refstarsfile,'default','default','default',
interactive=interact,verify=no,verbose=verbose)
#identify neighboring/interfering stars to selected stars
groupingfile = root+".psg.1"
iraf.nstar(root,groupingfile,'default','default','default',
psfrad= psfmultsmall * fwhm,verify=no,verbose=verbose)
#subtract out neighboring stars from image
iraf.substar(root,'default',refstarsfile,'default','default',
psfrad=psfmultsmall*fwhm,verify=no,verbose=verbose)
#repeat psf to get better psf model
#IRAF's interactive version usually crashes
subtractedimage = root+".sub.1"
iraf.psf(subtractedimage,root+".nst.1",refstarsfile,'%s.psf.2' % root,
'%s.pst.2' % root,'%s.psg.2' % root,interactive=interact,
verify=no,verbose=verbose)
#Need to make sure SN was detected by daofind
stars=Starlist('%s.mag.1' % root)
SN=Star(name='SN',radeg=ra,dcdeg=dec,fwhm=2.0,fwhmw=2.0)
SNlis=Starlist(stars=[SN])
SNlis.wcs2pix(image)
if (len(stars.match(SNlis)[0])==0):
#No match - need to add to daofind file
print "No match!"
coofile=open('refimage.coo.1', 'a+')
coofile.write('%10.3f%10.3f%9.3f%8.3f%13.3f%12.3f%8i\n' % (SNlis[0].xval, SNlis[0].yval,99.999,0.500,0.000,0.000,999))
coofile.close()
#repeat aperture photometry to get good comparisons to standard fields
iraf.daophot.phot(root,'refimage.coo.1','default',aperture=psfmult*fwhm,
verify=no,verbose=verbose)
# allstar run
iraf.allstar(root,'default','default','default','default','default',
verify=no,verbose=verbose)
