def salt2iraf(images,
outimages,
outpref,
ext=1,
clobber=True,
logfile='salt.log',
verbose=True):
with logging(logfile, debug) as log:
# Check the input images
infiles = saltio.argunpack('Input', images)
# create list of output files
outfiles = saltio.listparse('Outfile', outimages, outpref, infiles, '')
#verify that the input and output lists are the same length
saltio.comparelists(infiles, outfiles, 'Input', 'output')
for img, oimg in zip(infiles, outfiles):
message = "SALT2IRAF--Converting %s to %s" % (img, oimg)
log.message(message, with_header=False)
try:
convertsalt(img, oimg, ext=ext, clobber=clobber)
except SaltError, e:
log.message('%s' % e)
def hrsstack(images,
outimages,
outpref,
clobber=True,
logfile='salt.log',
verbose=True):
"""Convert MEF HRS data into a single image. If variance frames and BPMs, then
convert them to the same format as well. Returns an MEF image but that is
combined into a single frame
"""
with logging(logfile, debug) as log:
# Check the input images
infiles = saltio.argunpack('Input', images)
# create list of output files
outfiles = saltio.listparse('Outfile', outimages, outpref, infiles, '')
#verify that the input and output lists are the same length
saltio.comparelists(infiles, outfiles, 'Input', 'output')
#open the file and write out as a fits files in the output directory
for img, oimg in zip(infiles, outfiles):
hdu = saltio.openfits(img)
hdu = stack(hdu)
log.message('Stacking HRS %s to %s' % (img, oimg),
with_header=False)
saltio.writefits(hdu, oimg, clobber=clobber)
return
def saltillum(images, outimages, outpref, mbox=11, clobber=False, logfile="salt.log", verbose=True):
with logging(logfile, debug) as log:
# Check the input images
infiles = saltio.argunpack("Input", images)
# create list of output files
outfiles = saltio.listparse("Outfile", outimages, outpref, infiles, "")
# verify that the input and output lists are the same length
saltio.comparelists(infiles, outfiles, "Input", "output")
# open each raw image file
for infile, outfile in zip(infiles, outfiles):
struct = saltio.openfits(infile)
struct = illum_cor(struct, mbox)
# add any header keywords like history
fname, hist = history(level=1, wrap=False)
saltkey.housekeeping(struct[0], "SILLUM", "File Illumination corrected", hist)
# write it out and close it
saltio.writefits(struct, outfile, clobber=clobber)
saltio.closefits(struct)
# output the information
log.message("Illumination corrected image %s " % (infile), with_header=False, with_stdout=verbose)
def saltprepare(images,outimages,outpref,createvar=False, badpixelimage=None, clobber=True,logfile='salt.log',verbose=True):
with logging(logfile,debug) as log:
# Check the input images
infiles = saltio.argunpack ('Input',images)
# create list of output files
outfiles=saltio.listparse('Outfile', outimages, outpref,infiles,'')
#verify that the input and output lists are the same length
saltio.comparelists(infiles,outfiles,'Input','output')
# open the badpixel image
if saltio.checkfornone(badpixelimage) is None:
badpixelstruct=None
else:
try:
badpixelstruct = saltio.openfits(badpixelimage)
except saltio.SaltIOError,e:
msg='badpixel image must be specificied\n %s' % e
raise SaltError(msg)
# open each raw image file
for img, oimg, in zip(infiles, outfiles):
#open the fits file
struct=saltio.openfits(img)
#if createvar, throw a warning if it is using slotmode
if saltkey.fastmode(saltkey.get('DETMODE', struct[0])) and createvar:
msg='Creating variance frames for slotmode data in %s' % img
log.warning(msg)
# identify instrument
instrume,keyprep,keygain,keybias,keyxtalk,keyslot = saltkey.instrumid(struct)
# has file been prepared already?
try:
key = struct[0].header[keyprep]
message = 'ERROR -- SALTPREPARE: File ' + infile
message += ' has already been prepared'
raise SaltError(message)
except:
pass
# prepare file
struct=prepare(struct,createvar=createvar, badpixelstruct=badpixelstruct)
# housekeeping keywords
fname, hist=history(level=1, wrap=False, exclude=['images', 'outimages', 'outpref'])
saltkey.housekeeping(struct[0],keyprep, 'File prepared for IRAF', hist)
# write FITS file
saltio.writefits(struct,oimg, clobber=clobber)
saltio.closefits(struct)
message = 'SALTPREPARE -- %s => %s' % (img, oimg)
log.message(message, with_header=False)
def hrsstack(images, outimages, outpref, clobber=True, logfile='salt.log',verbose=True):
"""Convert MEF HRS data into a single image. If variance frames and BPMs, then
convert them to the same format as well. Returns an MEF image but that is
combined into a single frame
"""
with logging(logfile,debug) as log:
# Check the input images
infiles = saltio.argunpack ('Input',images)
# create list of output files
outfiles=saltio.listparse('Outfile', outimages, outpref,infiles,'')
#verify that the input and output lists are the same length
saltio.comparelists(infiles,outfiles,'Input','output')
#open the file and write out as a fits files in the output directory
for img,oimg in zip(infiles, outfiles):
hdu=saltio.openfits(img)
hdu=stack(hdu)
log.message('Stacking HRS %s to %s' % (img, oimg), with_header=False)
saltio.writefits(hdu, oimg, clobber=clobber)
return
def saltsurface(images,outimages,outpref, mask=True, order=3, minlevel=0,
clobber=False, logfile='salt.log',verbose=True):
with logging(logfile,debug) as log:
# Check the input images
infiles = saltio.argunpack ('Input',images)
# create list of output files
outfiles=saltio.listparse('Outfile', outimages, outpref,infiles,'')
#verify that the input and output lists are the same length
saltio.comparelists(infiles,outfiles,'Input','output')
# open each raw image file
for infile, outfile in zip(infiles,outfiles):
struct = saltio.openfits(infile)
struct = surface_fit(struct, order=order, mask=mask, minlevel=minlevel)
#add any header keywords like history
fname, hist=history(level=1, wrap=False)
saltkey.housekeeping(struct[0],'SURFIT', 'File fit by a surface', hist)
#write it out and close it
saltio.writefits(struct,outfile,clobber=clobber)
saltio.closefits(struct)
#output the information
log.message('Surface fitted image %s ' % (infile), with_header=False, with_stdout=verbose)
def saltillum(images,outimages,outpref, mbox=11, clobber=False, \
logfile='salt.log',verbose=True):
with logging(logfile, debug) as log:
# Check the input images
infiles = saltio.argunpack('Input', images)
# create list of output files
outfiles = saltio.listparse('Outfile', outimages, outpref, infiles, '')
#verify that the input and output lists are the same length
saltio.comparelists(infiles, outfiles, 'Input', 'output')
# open each raw image file
for infile, outfile in zip(infiles, outfiles):
struct = saltio.openfits(infile)
struct = illum_cor(struct, mbox)
#add any header keywords like history
fname, hist = history(level=1, wrap=False)
saltkey.housekeeping(struct[0], 'SILLUM',
'File Illumination corrected', hist)
#write it out and close it
saltio.writefits(struct, outfile, clobber=clobber)
saltio.closefits(struct)
#output the information
log.message('Illumination corrected image %s ' % (infile),
with_header=False,
with_stdout=verbose)
def saltprepare(images,outimages,outpref,createvar=False, badpixelimage=None, clobber=True,logfile='salt.log',verbose=True):
with logging(logfile,debug) as log:
# Check the input images
infiles = saltio.argunpack ('Input',images)
# create list of output files
outfiles=saltio.listparse('Outfile', outimages, outpref,infiles,'')
#verify that the input and output lists are the same length
saltio.comparelists(infiles,outfiles,'Input','output')
# open the badpixel image
if saltio.checkfornone(badpixelimage) is None:
badpixelstruct=None
else:
try:
badpixelstruct = saltio.openfits(badpixelimage)
except saltio.SaltIOError,e:
msg='badpixel image must be specificied\n %s' % e
raise SaltError(msg)
# open each raw image file
for img, oimg, in zip(infiles, outfiles):
#open the fits file
struct=saltio.openfits(img)
#if createvar, throw a warning if it is using slotmode
if saltkey.fastmode(saltkey.get('DETMODE', struct[0])) and createvar:
msg='Creating variance frames for slotmode data in %s' % img
log.warning(msg)
# identify instrument
instrume,keyprep,keygain,keybias,keyxtalk,keyslot = saltkey.instrumid(struct)
# has file been prepared already?
try:
key = struct[0].header[keyprep]
message = 'ERROR -- SALTPREPARE: File ' + infile
message += ' has already been prepared'
raise SaltError(message)
except:
pass
# prepare file
struct=prepare(struct,createvar=createvar, badpixelstruct=badpixelstruct)
# housekeeping keywords
fname, hist=history(level=1, wrap=False, exclude=['images', 'outimages', 'outpref'])
saltkey.housekeeping(struct[0],keyprep, 'File prepared for IRAF', hist)
# write FITS file
saltio.writefits(struct,oimg, clobber=clobber)
saltio.closefits(struct)
message = 'SALTPREPARE -- %s => %s' % (img, oimg)
log.message(message, with_header=False)
def saltgain(images,
outimages,
outpref,
gaindb=None,
usedb=False,
mult=True,
clobber=True,
logfile='salt.log',
verbose=True):
#start logging
with logging(logfile, debug) as log:
# Check the input images
infiles = saltio.argunpack('Input', images)
# create list of output files
outfiles = saltio.listparse('Outfile', outimages, outpref, infiles, '')
#verify that the input and output lists are the same length
saltio.comparelists(infiles, outfiles, 'Input', 'output')
# read in the database file if usedb is true
if usedb:
gaindb = gaindb.strip()
dblist = saltio.readgaindb(gaindb)
else:
dblist = []
for img, oimg in zip(infiles, outfiles):
#open the fits file
struct = saltio.openfits(img)
# identify instrument
instrume, keyprep, keygain, keybias, keyxtalk, keyslot = saltkey.instrumid(
struct)
# has file been prepared already?
if saltkey.found(keygain, struct[0]):
message = 'SALTGAIN: %s has already been gain-corrected' % img
raise SaltError(message)
# gain correct the data
struct = gain(struct,
mult=mult,
usedb=usedb,
dblist=dblist,
log=log,
verbose=verbose)
# housekeeping keywords
fname, hist = history(level=1,
wrap=False,
exclude=['images', 'outimages', 'outpref'])
saltkey.housekeeping(struct[0], keygain,
'Images have been gain corrected', hist)
# write FITS file
saltio.writefits(struct, oimg, clobber=clobber)
saltio.closefits(struct)
def hrsprepare(images, outimages, outpref, clobber=True, logfile='salt.log',verbose=True):
"""Convert .fit files to .fits files and place HRS data into
standard SALT FITS format
"""
with logging(logfile,debug) as log:
# Check the input images
infiles = saltio.argunpack ('Input',images)
# create list of output files
outfiles=saltio.listparse('Outfile', outimages, outpref,infiles,'')
#verify that the input and output lists are the same length
saltio.comparelists(infiles,outfiles,'Input','output')
#open the file and write out as a fits files in the output directory
for img,oimg in zip(infiles, outfiles):
hdu=saltio.openfits(img)
hdu=prepare(hdu)
log.message('Preparing HRS %s to %s' % (img, oimg), with_header=False)
saltio.writefits(hdu, oimg, clobber=clobber)
return
def saltfpskyring(
images,
outimages,
outpref,
axc,
ayc,
arad,
rxc,
ryc,
pmin,
pmax,
swindow=5,
clobber=False,
logfile="salt.log",
verbose=True,
):
"""Sky subtracts Fabry-Perot images"""
# start log now that all parameter are set up
with logging(logfile, debug) as log:
# Check the input images
infiles = saltio.argunpack("Input", images)
# create list of output files
outfiles = saltio.listparse("Outfile", outimages, outpref, infiles, "")
# verify that the input and output lists are the same length
saltio.comparelists(infiles, outfiles, "Input", "output")
for img, oimg in zip(infiles, outfiles):
# open up the file
hdu = saltio.openfits(img)
# determine the azimuthally averaged profile
rpro, radial_profile = median_radial_profile(
hdu[0].data, xc=axc, yc=ayc, rmax=arad, nbins=100, pmin=pmin, pmax=pmax
)
if swindow > 1:
radial_profile = np.convolve(radial_profile, np.ones(swindow), mode="same") / swindow
# calculate the indices from the image
y, x = np.indices(hdu[0].data.shape)
radius = np.hypot(x - axc, y - ayc)
# subtract off the sky data
mdata = hdu[0].data - np.interp(radius, rpro, radial_profile)
hdu[0].data = mdata
# write FITS file
saltio.writefits(hdu, oimg, clobber=clobber)
saltio.closefits(hdu)
message = "SALTFPSKYRING -- Subtracted sky from %s" % (img)
log.message(message, with_header=False)
def saltxtalk(images,outimages,outpref,xtalkfile=None, usedb=False,
clobber=True, logfile='salt.log',verbose=True):
#start logging
with logging(logfile,debug) as log:
# Check the input images
infiles = saltio.argunpack ('Input',images)
# create list of output files
outfiles=saltio.listparse('Outfile', outimages, outpref,infiles,'')
# are input and output lists the same length?
saltio.comparelists(infiles,outfiles,'Input','output')
# does crosstalk coefficient data exist
if usedb:
xtalkfile = xtalkfile.strip()
xdict = saltio.readxtalkcoeff(xtalkfile)
else:
xdict=None
for img, oimg in zip(infiles, outfiles):
#open the fits file
struct=saltio.openfits(img)
#find the best xcoeff for the image if using the db
if usedb:
obsdate=saltkey.get('DATE-OBS', struct[0])
obsdate=int('%s%s%s' % (obsdate[0:4],obsdate[5:7], obsdate[8:]))
xkey=np.array(xdict.keys())
date=xkey[abs(xkey-obsdate).argmin()]
xcoeff=xdict[date]
else:
xcoeff=[]
# identify instrument
instrume,keyprep,keygain,keybias,keyxtalk,keyslot = saltkey.instrumid(struct)
# has file been prepared already?
if saltkey.found(keyxtalk, struct[0]):
message='%s has already been xtalk corrected' % img
raise SaltError(message)
#apply the cross-talk correction
struct = xtalk(struct, xcoeff, log=log, verbose=verbose)
# housekeeping keywords
fname, hist=history(level=1, wrap=False, exclude=['images', 'outimages', 'outpref'])
saltkey.housekeeping(struct[0], 'SXTALK', 'Images have been xtalk corrected', hist)
# write FITS file
saltio.writefits(struct,oimg, clobber=clobber)
saltio.closefits(struct)
def saltcrclean(images,outimages,outpref,crtype='fast',thresh=5,mbox=3, \
bthresh=3, flux_ratio=0.2, bbox=11, gain=1, rdnoise=5, fthresh=5,\
bfactor=2, gbox=3, maxiter=5, multithread=False, update=True,
clobber=True, logfile='salt.log', verbose=True):
with logging(logfile,debug) as log:
# Check the input images
infiles = saltio.argunpack ('Input',images)
# create list of output files
outfiles=saltio.listparse('Outfile', outimages, outpref,infiles,'')
#verify that the input and output lists are the same length
saltio.comparelists(infiles,outfiles,'Input','output')
#check to see if multithreading is available
if mp:
pass
else:
multithread=False
log.warning('multiprocessing module is not available. Setting multiththread=False')
# Begin processes each file
for infile,outfile in zip(infiles,outfiles):
#open the infile
struct=saltio.openfits(infile)
#clean the cosmic rays
if multithread and len(struct)>1:
struct=multicrclean(struct, crtype, thresh, mbox, bbox, bthresh, flux_ratio, \
gain, rdnoise, bfactor, fthresh, gbox, maxiter, log, verbose=verbose)
else:
struct=crclean(struct, crtype, thresh, mbox, bbox, bthresh, flux_ratio, \
gain, rdnoise, bfactor, fthresh, gbox, maxiter, update, log, verbose=verbose)
#log the call
#log.message('Cleaned %i cosmic rays from %s using %s method' % (totcr, infile, crtype), with_header=False)
log.message('', with_header=False, with_stdout=verbose)
#add house keeping keywords
saltkey.put('SAL-TLM',time.asctime(time.localtime()), struct[0])
#add the history keyword
fname, hist=history(level=1, wrap=False)
saltkey.history(struct[0],hist)
#write out the file
saltio.writefits(struct, outfile, clobber=clobber)
#close the image
saltio.closefits(struct)
def saltcrclean(images,outimages,outpref,crtype='fast',thresh=5,mbox=3, \
bthresh=3, flux_ratio=0.2, bbox=11, gain=1, rdnoise=5, fthresh=5,\
bfactor=2, gbox=3, maxiter=5, multithread=False, update=True,
clobber=True, logfile='salt.log', verbose=True):
with logging(logfile, debug) as log:
# Check the input images
infiles = saltio.argunpack('Input', images)
# create list of output files
outfiles = saltio.listparse('Outfile', outimages, outpref, infiles, '')
#verify that the input and output lists are the same length
saltio.comparelists(infiles, outfiles, 'Input', 'output')
#check to see if multithreading is available
if mp:
pass
else:
multithread = False
log.warning(
'multiprocessing module is not available. Setting multiththread=False'
)
# Begin processes each file
for infile, outfile in zip(infiles, outfiles):
#open the infile
struct = saltio.openfits(infile)
#clean the cosmic rays
if multithread and len(struct) > 1:
struct=multicrclean(struct, crtype, thresh, mbox, bbox, bthresh, flux_ratio, \
gain, rdnoise, bfactor, fthresh, gbox, maxiter, log, verbose=verbose)
else:
struct=crclean(struct, crtype, thresh, mbox, bbox, bthresh, flux_ratio, \
gain, rdnoise, bfactor, fthresh, gbox, maxiter, update, log, verbose=verbose)
#log the call
#log.message('Cleaned %i cosmic rays from %s using %s method' % (totcr, infile, crtype), with_header=False)
log.message('', with_header=False, with_stdout=verbose)
#add house keeping keywords
saltkey.put('SAL-TLM', time.asctime(time.localtime()), struct[0])
#add the history keyword
fname, hist = history(level=1, wrap=False)
saltkey.history(struct[0], hist)
#write out the file
saltio.writefits(struct, outfile, clobber=clobber)
#close the image
saltio.closefits(struct)
def saltslot(images,
outimages,
outpref,
gaindb='',
xtalkfile='',
usedb=False,
clobber=False,
logfile='salt.log',
verbose=True):
#start logging
with logging(logfile, debug) as log:
# Check the input images
infiles = saltio.argunpack('Input', images)
# create list of output files
outfiles = saltio.listparse('Outfile', outimages, outpref, infiles, '')
# are input and output lists the same length?
saltio.comparelists(infiles, outfiles, 'Input', 'output')
# does crosstalk coefficient data exist
if usedb:
dblist = saltio.readgaindb(gaindb)
xtalkfile = xtalkfile.strip()
xdict = saltio.readxtalkcoeff(xtalkfile)
else:
dblist = []
xdict = None
for img, oimg in zip(infiles, outfiles):
#open the fits file
struct = saltio.openfits(img)
# identify instrument
instrume, keyprep, keygain, keybias, keyxtalk, keyslot = saltkey.instrumid(
struct)
# has file been prepared already?
if saltkey.found(keygain, struct[0]):
message = '%s has already been reduced' % img
raise SaltError(message)
# housekeeping keywords
fname, hist = history(level=1,
wrap=False,
exclude=['images', 'outimages', 'outpref'])
saltkey.housekeeping(struct[0], keyslot,
'Images have been slotmode reduced', hist)
# write FITS file
saltio.writefits(struct, oimg, clobber=clobber)
saltio.closefits(struct)
def saltarith(operand1, op, operand2, result, outpref, divzero=0, clobber=False, \
logfile='salt.log',verbose=True):
with logging(logfile, debug) as log:
# Check the input images
infiles = saltio.argunpack('Input', operand1)
# create list of output files
outfiles = saltio.listparse('Outfile', result, outpref, infiles, '')
#verify that the input and output lists are the same length
saltio.comparelists(infiles, outfiles, 'Input', 'output')
#let's keep track of whether operand2 is an image or not
is_image = False
#load in operand2, or, if it's not an image, assume it's a number
try:
operand2struct = float(operand2)
except ValueError:
operand2struct = saltio.openfits(operand2)
is_image = True
#open the input image files
for infile, outfile in zip(infiles, outfiles):
struct = saltio.openfits(infile)
#do some math!
outstruct = arith(struct, op, operand2struct, is_image, divzero)
try:
pass
except Exception, e:
msg = 'Unable to do math %s because %s' % (infile, e)
raise SaltError(msg)
#update header stuff
fname, hist = history(level=1, wrap=False)
saltkey.housekeeping(struct[0], 'SARITH',
'Some arithmatic was performed', hist)
#write it. close it.
saltio.writefits(outstruct, outfile, clobber=clobber)
saltio.closefits(struct)
#output the information
log.message('imarith: %s %s %s %s' %
(infile, op, operand2, outfile),
with_header=False,
with_stdout=verbose)
#close the operand2 image
if is_image: saltio.closefits(operand2struct)
def slotreadtimefix(images,
outimages,
outpref,
clobber=False,
logfile='slot.log',
verbose=True):
with logging(logfile, debug) as log:
# Check the input images
infiles = saltio.argunpack('Input', images)
# create list of output files
outfiles = saltio.listparse('Outfile', outimages, outpref, infiles, '')
#verify that the input and output lists are the same length
saltio.comparelists(infiles, outfiles, 'Input', 'output')
for img, oimg in zip(infiles, outfiles):
#check to see if the out image already exists
if not clobber and os.path.isfile(oimg):
raise SaltIOError('%s alraedy exists' % oimg)
#open the file
struct = saltio.openfits(img)
#log the message
log.message('Updateing times in %s' % img,
with_header=False,
with_stdout=verbose)
#now for each science frame, corrent the readtime
#Assumes SALT format and that the first extension
#is empty
for i in range(1, len(struct)):
try:
struct[i] = readtimefix(struct[i])
except SaltIOError, e:
raise SaltError('%s %s' % (img, e))
#Add history keywords
# housekeeping keywords
fname, hist = history(level=1,
wrap=False,
exclude=['images', 'outimages', 'outpref'])
saltkey.housekeeping(struct[0], "SLOTREAD", 'READTIME added', hist)
#write to the output
saltio.writefits(struct, oimg, clobber)
return
def saltarith(operand1, op, operand2, result, outpref, divzero=0, clobber=False, \
logfile='salt.log',verbose=True):
with logging(logfile,debug) as log:
# Check the input images
infiles = saltio.argunpack ('Input',operand1)
# create list of output files
outfiles=saltio.listparse('Outfile', result, outpref, infiles,'')
#verify that the input and output lists are the same length
saltio.comparelists(infiles,outfiles,'Input','output')
#let's keep track of whether operand2 is an image or not
is_image = False
#load in operand2, or, if it's not an image, assume it's a number
try: operand2struct = float(operand2)
except ValueError:
operand2struct = saltio.openfits(operand2)
is_image = True
#open the input image files
for infile, outfile in zip(infiles,outfiles):
struct = saltio.openfits(infile)
#do some math!
outstruct = arith(struct, op, operand2struct, is_image, divzero)
try:
pass
except Exception as e:
msg='Unable to do math %s because %s' % (infile, e)
raise SaltError(msg)
#update header stuff
fname, hist = history(level=1, wrap=False)
saltkey.housekeeping(struct[0],'SARITH', 'Some arithmatic was performed',hist)
#write it. close it.
saltio.writefits(outstruct,outfile,clobber=clobber)
saltio.closefits(struct)
#output the information
log.message('imarith: %s %s %s %s' % (infile, op, operand2, outfile), with_header=False, with_stdout=verbose)
#close the operand2 image
if is_image: saltio.closefits(operand2struct)
def saltmosaic(images,outimages,outpref,geomfile,interp='linear',geotran=True, cleanup=True,clobber=False,logfile=None,verbose=True):
#Start the logging
with logging(logfile,debug) as log:
# Check the input images
infiles = saltio.argunpack ('Input',images)
# create list of output files
outfiles=saltio.listparse('Outfile', outimages, outpref,infiles,'')
#verify that the input and output lists are the same length
saltio.comparelists(infiles,outfiles,'Input','output')
# does CCD geometry definition file exist
geomfilefile = geomfile.strip()
saltio.fileexists(geomfile)
gap = 0
xshift = [0, 0]
yshift = [0, 0]
rotation = [0, 0]
gap, xshift, yshift, rotation=saltio.readccdgeom(geomfile)
# open each raw image file and apply the transformation to it
for img, oimg in zip(infiles, outfiles):
#open the structure
struct = saltio.openfits(img)
#create the mosaic
ostruct=make_mosaic(struct, gap, xshift, yshift, rotation, interp_type=interp, geotran=geotran, cleanup=cleanup, log=log, verbose=verbose)
#update the header information
# housekeeping keywords
fname, hist=history(level=1, wrap=False, exclude=['images', 'outimages', 'outpref'])
saltkey.housekeeping(ostruct[0], 'SMOSAIC', 'Images have been mosaicked ', hist)
#write the image out
saltio.writefits(ostruct,oimg, clobber=clobber)
#close the files
saltio.closefits(struct)
saltio.closefits(ostruct)
def saltgain(images,outimages, outpref, gaindb=None,usedb=False, mult=True,
clobber=True, logfile='salt.log',verbose=True):
#start logging
with logging(logfile,debug) as log:
# Check the input images
infiles = saltio.argunpack ('Input',images)
# create list of output files
outfiles=saltio.listparse('Outfile', outimages, outpref,infiles,'')
#verify that the input and output lists are the same length
saltio.comparelists(infiles,outfiles,'Input','output')
# read in the database file if usedb is true
if usedb:
gaindb = gaindb.strip()
dblist= saltio.readgaindb(gaindb)
else:
dblist=[]
for img, oimg in zip(infiles, outfiles):
#open the fits file
struct=saltio.openfits(img)
# identify instrument
instrume,keyprep,keygain,keybias,keyxtalk,keyslot = saltkey.instrumid(struct)
# has file been prepared already?
if saltkey.found(keygain, struct[0]):
message='SALTGAIN: %s has already been gain-corrected' % img
raise SaltError(message)
# gain correct the data
struct = gain(struct,mult=mult, usedb=usedb, dblist=dblist, log=log, verbose=verbose)
# housekeeping keywords
fname, hist=history(level=1, wrap=False, exclude=['images', 'outimages', 'outpref'])
saltkey.housekeeping(struct[0],keygain, 'Images have been gain corrected', hist)
# write FITS file
saltio.writefits(struct,oimg, clobber=clobber)
saltio.closefits(struct)
def saltslot(images,outimages,outpref,gaindb='',xtalkfile='',usedb=False, clobber=False,logfile='salt.log',verbose=True):
#start logging
with logging(logfile,debug) as log:
# Check the input images
infiles = saltio.argunpack ('Input',images)
# create list of output files
outfiles=saltio.listparse('Outfile', outimages, outpref,infiles,'')
# are input and output lists the same length?
saltio.comparelists(infiles,outfiles,'Input','output')
# does crosstalk coefficient data exist
if usedb:
dblist= saltio.readgaindb(gaindb)
xtalkfile = xtalkfile.strip()
xdict = saltio.readxtalkcoeff(xtalkfile)
else:
dblist=[]
xdict=None
for img, oimg in zip(infiles, outfiles):
#open the fits file
struct=saltio.openfits(img)
# identify instrument
instrume,keyprep,keygain,keybias,keyxtalk,keyslot = saltkey.instrumid(struct)
# has file been prepared already?
if saltkey.found(keygain, struct[0]):
message='%s has already been reduced' % img
raise SaltError(message)
# housekeeping keywords
fname, hist=history(level=1, wrap=False, exclude=['images', 'outimages', 'outpref'])
saltkey.housekeeping(struct[0],keyslot, 'Images have been slotmode reduced', hist)
# write FITS file
saltio.writefits(struct,oimg, clobber=clobber)
saltio.closefits(struct)
def saltfpmask(images, outimages, outpref, axc,ayc, arad, maskmethod='c', maskvalue=0, \
radi=None,rado=None,clobber=False, logfile='saltfp.log', verbose=True):
"""Aperture masks Fabry-Perot images"""
with logging(logfile, debug) as log:
# Check the input images
infiles = saltio.argunpack('Input', images)
# create list of output files
outfiles = saltio.listparse('Outfile', outimages, outpref, infiles, '')
#verify that the input and output lists are the same length
saltio.comparelists(infiles, outfiles, 'Input', 'output')
for img, oimg in zip(infiles, outfiles):
#open the image
hdu = saltio.openfits(img)
#test that the data are in the first
try:
data = hdu[0].data
except Exception, e:
message = 'SALTFPMASK--ERROR: Could not access data in Primary exention of %s because %s' % (
img, e)
log.message(message)
#determine the mask value if it is a region
if maskmethod == 'region':
maskvalue = calc_maskvalue(data, axc, ayc, radi, rado)
#mask the image
message = "SALTFPMASK--Masking image %s with a value of %s" % (
img, maskvalue)
log.message(message, with_header=False)
hdu[0].data = maskimage(data, axc, ayc, arad, maskvalue)
try:
pass
except Exception, e:
message = 'SALTFPMASK--ERROR: Could not create mask for %s because %s' % (
img, e)
log.message(message)
#write out the image
saltio.writefits(hdu, oimg, clobber=clobber)
def slotreadtimefix(images,outimages, outpref,
clobber=False, logfile='slot.log',verbose=True):
with logging(logfile,debug) as log:
# Check the input images
infiles = saltio.argunpack ('Input',images)
# create list of output files
outfiles=saltio.listparse('Outfile', outimages, outpref,infiles,'')
#verify that the input and output lists are the same length
saltio.comparelists(infiles,outfiles,'Input','output')
for img, oimg in zip(infiles, outfiles):
#check to see if the out image already exists
if not clobber and os.path.isfile(oimg):
raise SaltIOError('%s alraedy exists' % oimg)
#open the file
struct=saltio.openfits(img)
#log the message
log.message('Updateing times in %s' % img, with_header=False, with_stdout=verbose)
#now for each science frame, corrent the readtime
#Assumes SALT format and that the first extension
#is empty
for i in range(1,len(struct)):
try:
struct[i]=readtimefix(struct[i])
except SaltIOError,e :
raise SaltError('%s %s' % (img,e))
#Add history keywords
# housekeeping keywords
fname, hist=history(level=1, wrap=False, exclude=['images', 'outimages', 'outpref'])
saltkey.housekeeping(struct[0],"SLOTREAD", 'READTIME added', hist)
#write to the output
saltio.writefits(struct, oimg, clobber)
return
def saltsurface(images,
outimages,
outpref,
mask=True,
order=3,
minlevel=0,
clobber=False,
logfile='salt.log',
verbose=True):
with logging(logfile, debug) as log:
# Check the input images
infiles = saltio.argunpack('Input', images)
# create list of output files
outfiles = saltio.listparse('Outfile', outimages, outpref, infiles, '')
#verify that the input and output lists are the same length
saltio.comparelists(infiles, outfiles, 'Input', 'output')
# open each raw image file
for infile, outfile in zip(infiles, outfiles):
struct = saltio.openfits(infile)
struct = surface_fit(struct,
order=order,
mask=mask,
minlevel=minlevel)
#add any header keywords like history
fname, hist = history(level=1, wrap=False)
saltkey.housekeeping(struct[0], 'SURFIT', 'File fit by a surface',
hist)
#write it out and close it
saltio.writefits(struct, outfile, clobber=clobber)
saltio.closefits(struct)
#output the information
log.message('Surface fitted image %s ' % (infile),
with_header=False,
with_stdout=verbose)
def saltfpmask(images, outimages, outpref, axc,ayc, arad, maskmethod='c', maskvalue=0, \
radi=None,rado=None,clobber=False, logfile='saltfp.log', verbose=True):
"""Aperture masks Fabry-Perot images"""
with logging(logfile, debug) as log:
# Check the input images
infiles = saltio.argunpack ('Input',images)
# create list of output files
outfiles=saltio.listparse('Outfile', outimages, outpref,infiles,'')
#verify that the input and output lists are the same length
saltio.comparelists(infiles,outfiles,'Input','output')
for img, oimg in zip(infiles, outfiles):
#open the image
hdu=saltio.openfits(img)
#test that the data are in the first
try:
data=hdu[0].data
except Exception, e:
message='SALTFPMASK--ERROR: Could not access data in Primary exention of %s because %s' % (img, e)
log.message(message)
#determine the mask value if it is a region
if maskmethod=='region':
maskvalue=calc_maskvalue(data, axc, ayc, radi, rado)
#mask the image
message="SALTFPMASK--Masking image %s with a value of %s" % (img, maskvalue)
log.message(message, with_header=False)
hdu[0].data= maskimage(data, axc, ayc, arad, maskvalue)
try:
pass
except Exception, e:
message='SALTFPMASK--ERROR: Could not create mask for %s because %s' % (img, e)
log.message(message)
#write out the image
saltio.writefits(hdu, oimg, clobber=clobber)
def saltfpzeropoint(images,outimages, outpref, calfile, fpa, fpb, fpc, fpd, fpe, fpf, clobber=False,logfile='salt.log',verbose=True):
"""Adds zeropoint information to each image"""
with logging(logfile,debug) as log:
# Check the input images
infiles = saltio.argunpack ('Input',images)
# create the output files
outfiles=saltio.listparse('Outfile', outimages, outpref,infiles,'')
#verify that the input and output lists are the same length
saltio.comparelists(infiles,outfiles,'Input','output')
#calculate the zeropoint coefficients
fpcoef=np.array([fpa,fpb,fpc,fpd,fpe,fpf])
zpcoef,tstart=calc_zpcoef(calfile, fpcoef)
# open each image and detect the ring
for img, oimg in zip(infiles, outfiles):
hdu=saltio.openfits(img)
#get the image time
t=(get_datetime(hdu)-tstart).seconds
#add the header values to the image
saltkey.new('FPA',fpa+zpcoef[1]+zpcoef[0]*t,'FPA Coef',hdu[0])
saltkey.new('FPB',fpb,'FPB Coef',hdu[0])
saltkey.new('FPC',fpc,'FPC Coef',hdu[0])
saltkey.new('FPD',fpd,'FPD Coef',hdu[0])
saltkey.new('FPE', 0,'FPE Coef',hdu[0])
saltkey.new('FPF',fpf,'FPF Coef',hdu[0])
#write the file out
saltio.writefits(hdu, oimg, clobber)
#log the action
msg='Updating the FP information in %s' % (img)
log.message(msg, with_stdout=verbose, with_header=False)
def specprepare(images,outimages,outpref,badpixelimage='', \
clobber=True,logfile='salt.log',verbose=True):
with logging(logfile,debug) as log:
# Check the input images
infiles = saltio.argunpack ('Input',images)
# create list of output files
outfiles=saltio.listparse('Outfile', outimages, outpref,infiles,'')
#verify that the input and output lists are the same length
saltio.comparelists(infiles,outfiles,'Input','output')
# open the badpixel image
if saltio.checkfornone(badpixelimage) is None:
badpixelstruct=None
else:
try:
badpixelstruct = saltio.openfits(badpixelimage)
except saltio.SaltIOError,e:
msg='badpixel image must be specificied\n %s' % e
raise SALTSpecError(msg)
# open each raw image file
for img, oimg, in zip(infiles, outfiles):
#open the fits file
struct=saltio.openfits(img)
# prepare file
struct=prepare(struct,badpixelstruct)
# write FITS file
saltio.writefits(struct,oimg, clobber=clobber)
saltio.closefits(struct)
message = 'SPECPREPARE -- %s => %s' % (img, oimg)
log.message(message)
def saltfpprep(images, outimages, outpref,
clobber=True, logfile='saltfp.log', verbose=True):
"""Prepares data for Fabry-Perot reductions"""
with logging(logfile, debug) as log:
# Check the input images
infiles = saltio.argunpack ('Input',images)
# create list of output files
outfiles=saltio.listparse('Outfile', outimages, outpref,infiles,'')
#verify that the input and output lists are the same length
saltio.comparelists(infiles,outfiles,'Input','output')
for img, oimg in zip(infiles, outfiles):
message="SALTFPPREP--Preparing image %s" % (img)
log.message(message, with_header=False)
try:
convertsalt(img, oimg, clobber=clobber)
except SaltError, e:
log.message('%s' %e)
def saltfpprep(images, outimages, outpref,
clobber=True, logfile='saltfp.log', verbose=True):
"""Prepares data for Fabry-Perot reductions"""
with logging(logfile, debug) as log:
# Check the input images
infiles = saltio.argunpack ('Input',images)
# create list of output files
outfiles=saltio.listparse('Outfile', outimages, outpref,infiles,'')
#verify that the input and output lists are the same length
saltio.comparelists(infiles,outfiles,'Input','output')
for img, oimg in zip(infiles, outfiles):
message="SALTFPPREP--Preparing image %s" % (img)
log.message(message, with_header=False)
try:
convertsalt(img, oimg, clobber=clobber)
except SaltError as e:
log.message('%s' %e)
def salt2iraf(images,outimages,outpref,ext=1, clobber=True,logfile='salt.log',
verbose=True):
with logging(logfile,debug) as log:
# Check the input images
infiles = saltio.argunpack ('Input',images)
# create list of output files
outfiles=saltio.listparse('Outfile', outimages, outpref,infiles,'')
#verify that the input and output lists are the same length
saltio.comparelists(infiles,outfiles,'Input','output')
for img, oimg in zip(infiles, outfiles):
message="SALT2IRAF--Converting %s to %s" % (img, oimg)
log.message(message, with_header=False)
try:
convertsalt(img, oimg, ext=ext, clobber=clobber)
except SaltError, e:
log.message('%s' % e)
def specprepare(images, outimages, outpref, badpixelimage='',
clobber=True, logfile='salt.log', verbose=True):
with logging(logfile, debug) as log:
# Check the input images
infiles = saltio.argunpack('Input', images)
# create list of output files
outfiles = saltio.listparse('Outfile', outimages, outpref, infiles, '')
# verify that the input and output lists are the same length
saltio.comparelists(infiles, outfiles, 'Input', 'output')
# open the badpixel image
if saltio.checkfornone(badpixelimage) is None:
badpixelstruct = None
else:
try:
badpixelstruct = saltio.openfits(badpixelimage)
except saltio.SaltIOError as e:
msg = 'badpixel image must be specificied\n %s' % e
raise SALTSpecError(msg)
# open each raw image file
for img, oimg, in zip(infiles, outfiles):
# open the fits file
struct = saltio.openfits(img)
# prepare file
struct = prepare(struct, badpixelstruct)
# write FITS file
saltio.writefits(struct, oimg, clobber=clobber)
saltio.closefits(struct)
message = 'SPECPREPARE -- %s => %s' % (img, oimg)
log.message(message)
def saltembed(images,outimages,outpref, clobber=True,logfile='salt.log',verbose=True):
with logging(logfile,debug) as log:
# Check the input images
infiles = saltio.argunpack ('Input',images)
# create list of output files
outfiles=saltio.listparse('Outfile', outimages, outpref,infiles,'')
#verify that the input and output lists are the same length
saltio.comparelists(infiles,outfiles,'Input','output')
# open each raw image file
for img, oimg, in zip(infiles, outfiles):
#open the fits file
struct=saltio.openfits(img)
#get the number of CCDs
nccd=saltkey.get('NCCDS', struct[0])
#set the number of amps per CCD--*TODO* Read from header
namps=2
#get the number of windows--try to read from header
try:
nwindows=saltkey.get('NWINDOWS', struct[0])
except:
nwindows=len(struct)/(nccd*namps)
outstruct=embedimage(struct, nccd, namps, nwindows)
saltio.writefits(outstruct, oimg, clobber=clobber)
message = 'SALTEMBED -- %s => %s' % (img, oimg)
log.message(message, with_header=False)
def saltembed(images,outimages,outpref, clobber=True,logfile='salt.log',verbose=True):
with logging(logfile,debug) as log:
# Check the input images
infiles = saltio.argunpack ('Input',images)
# create list of output files
outfiles=saltio.listparse('Outfile', outimages, outpref,infiles,'')
#verify that the input and output lists are the same length
saltio.comparelists(infiles,outfiles,'Input','output')
# open each raw image file
for img, oimg, in zip(infiles, outfiles):
#open the fits file
struct=saltio.openfits(img)
#get the number of CCDs
nccd=saltkey.get('NCCDS', struct[0])
#set the number of amps per CCD--*TODO* Read from header
namps=2
#get the number of windows--try to read from header
try:
nwindows=saltkey.get('NWINDOWS', struct[0])
except:
nwindows=len(struct)/(nccd*namps)
outstruct=embedimage(struct, nccd, namps, nwindows)
saltio.writefits(outstruct, oimg, clobber=clobber)
message = 'SALTEMBED -- %s => %s' % (img, oimg)
log.message(message, with_header=False)
def saltflat(images,outimages,outpref, flatimage,minflat=1, allext=False, clobber=False, \
logfile='salt.log',verbose=True):
with logging(logfile,debug) as log:
# Check the input images
infiles = saltio.argunpack ('Input',images)
# create list of output files
outfiles=saltio.listparse('Outfile', outimages, outpref,infiles,'')
#verify that the input and output lists are the same length
saltio.comparelists(infiles,outfiles,'Input','output')
# check flatfield image exists
flaimage= flatimage.strip()
saltio.fileexists(flatimage)
flatstruct= saltio.openfits(flatimage)
# Normalize the flat field image
# This requires to go through each science extension and divide it by
# mean of the image. Things that have to be checked:
# that data exist, that it is a science extension
#determine the global mean
fmean=0
fcount=0
#replace bad pixels
for i in range(len(flatstruct)):
if flatstruct[i].data is not None and (flatstruct[i].name=='SCI' or flatstruct[i].name=='PRIMARY'):
data = flatstruct[i].data
mask = (data > minflat)
if (numpy.nan==flatstruct[i].data).sum() or (numpy.inf==flatstruct[i].data).sum():
message = '\nWARNING -- SALTFLAT: %s contains invalid values' % flatimage
log.warning(message,with_stdout=verbose)
flatstruct[i].data[mask==0] = minflat
flatstruct[i].data[flatstruct[i].data==numpy.inf] = minflat
#determine the mean
mask = (data > minflat)
fmean += data[mask].sum()
fcount += data[mask].size
if fcount>0: fmean=fmean/fcount
for i in range(len(flatstruct)):
if flatstruct[i].name=='PRIMARY':
#is it a flat--if not throw a warning
try:
key_ccdtype=saltkey.get('CCDTYPE', flatstruct[i])
except:
key_ccdtype=None
if key_ccdtype!='FLAT':
message = '\nWARNING -- SALTFLAT: %s does not have CCDTYPE=FLAT' % flatimage
log.warning(message,with_stdout=verbose)
#if there are data, normalize it
if flatstruct[i].data is not None:
flatstruct[i].data=flatnormalize(flatstruct[i].data, minflat)
#Noramlize the science extensions
if flatstruct[i].name=='SCI':
if flatstruct[i].data is not None:
if allext is False: fmean=flatstruct[i].data.mean()
flatstruct[i].data=flatnormalize(flatstruct[i].data, minflat, fmean)
#Apply to the variance frames
if saltkey.found('VAREXT', flatstruct[i]):
varext=saltkey.get('VAREXT',flatstruct[i])
flatstruct[varext].data=flatstruct[varext].data/fmean**2
# open each raw image file
for infile, outfile in zip(infiles,outfiles):
struct = saltio.openfits(infile)
# flat field correct the image
outstruct = flat(struct, flatstruct)
try:
pass
except Exception,e:
msg='Unable to flatten %s because %s' % (infile, e)
raise SaltError(msg)
#add any header keywords like history
fname, hist=history(level=1, wrap=False)
saltkey.housekeeping(struct[0],'SFLAT', 'File flatfield corrected', hist)
#write it out and close it
saltio.writefits(outstruct,outfile,clobber=clobber)
saltio.closefits(struct)
#output the information
log.message('Flatfields image %s using %s' % (infile, flatimage), with_header=False, with_stdout=verbose)
#clost the flatfield image
saltio.closefits(flatstruct)
def saltmosaic(images,
outimages,
outpref,
geomfile,
interp='linear',
geotran=True,
fill=False,
cleanup=True,
clobber=False,
logfile=None,
verbose=True):
# Start the logging
with logging(logfile, debug) as log:
# Check the input images
infiles = saltio.argunpack('Input', images)
# create list of output files
outfiles = saltio.listparse('Outfile', outimages, outpref, infiles, '')
# verify that the input and output lists are the same length
saltio.comparelists(infiles, outfiles, 'Input', 'output')
# does CCD geometry definition file exist
geomfilefile = geomfile.strip()
saltio.fileexists(geomfile)
gap = 0
xshift = [0, 0]
yshift = [0, 0]
rotation = [0, 0]
gap, xshift, yshift, rotation = saltio.readccdgeom(geomfile)
# open each raw image file and apply the transformation to it
for img, oimg in zip(infiles, outfiles):
# open the structure
struct = saltio.openfits(img)
# create the mosaic
ostruct = make_mosaic(struct,
gap,
xshift,
yshift,
rotation,
interp_type=interp,
geotran=geotran,
fill=fill,
cleanup=cleanup,
log=log,
verbose=verbose)
# update the header information
# housekeeping keywords
fname, hist = history(level=1,
wrap=False,
exclude=['images', 'outimages', 'outpref'])
saltkey.housekeeping(ostruct[0], 'SMOSAIC',
'Images have been mosaicked', hist)
# write the image out
ostruct.writeto(oimg, clobber=clobber, output_verify='ignore')
# close the files
struct.close()
ostruct.close()
def specslit(image, outimage, outpref, exttype='auto', slitfile='', outputslitfile='',
regprefix='', sections=3, width=25, sigma=2.2, thres=6, order=3, padding=5, yoffset=0,
inter=False, clobber=True, logfile='salt.log', verbose=True):
with logging(logfile, debug) as log:
# check all the input and make sure that all the input needed is provided
# by the user
# read the image or image list and check if each in the list exist
infiles = saltio.argunpack('Input', image)
# unpack the outfiles
outfiles = saltio.listparse(
'Outimages',
outimage,
outpref,
infiles,
'')
# from the extraction type, check whether the input file is specified.
# if the slitfile parameter is specified then use the slit files for
# the extraction. if the extraction type is auto then use image for the
# detection and the slit extraction
if exttype == 'rsmt' or exttype == 'fits' or exttype == 'ascii' or exttype == 'ds9':
slitfiles = saltio.argunpack('Slitfile', slitfile)
if len(slitfiles) == 1:
slitfiles = slitfiles * len(infiles)
saltio.comparelists(infiles, slitfiles, 'image', 'slitfile')
elif exttype == 'auto':
slitfiles = infiles
log.message(
'Extraction type is AUTO. Slit detection will be done from image')
# read in if an optional ascii file is requested
if len(outputslitfile) > 0:
outslitfiles = saltio.argunpack('Outslitfiles', outputslitfile)
saltio.comparelists(
infiles,
outslitfiles,
'image',
'outputslitfile')
else:
outslitfiles = [''] * len(infiles)
# check if the width and sigma parameters were specified.
# default is 25 and 2.2
if width < 10.:
msg = 'The width parameter needs be a value larger than 10'
raise SALTSpecError(msg)
if sigma < 0.0:
msg = 'Sigma must be greater than zero'
raise SaltSpecError(msg)
# check the treshold parameter. this needs to be specified by the user
if thres <= 0.0:
msg = 'Threshold must be greater than zero'
raise SaltSpecError(msg)
# check to make sure that the sections are greater than the order
if sections <= order:
msg = 'Number of sections must be greater than the order for the spline fit'
raise SaltSpecError(msg)
# run through each of the images and extract the slits
for img, oimg, sfile, oslit in zip(
infiles, outfiles, slitfiles, outslitfiles):
log.message('Proccessing image %s' % img)
# open the image
struct = saltio.openfits(img)
ylen, xlen = struct[1].data.shape
xbin, ybin = saltkey.ccdbin(struct[0], img)
# setup the VARIANCE and BPM frames
if saltkey.found('VAREXT', struct[1]):
varext = saltkey.get('VAREXT', struct[1])
varlist = []
else:
varext = None
# setup the BPM frames
if saltkey.found('BPMEXT', struct[1]):
bpmext = saltkey.get('BPMEXT', struct[1])
bpmlist = []
else:
bpmext = None
# open the slit definition file or identify the slits in the image
slitmask = None
ycheck = False
if exttype == 'rsmt':
log.message('Using slits from %s' % sfile)
if yoffset is None:
yoffset = 0
ycheck = True
slitmask = mt.read_slitmask_from_xml(sfile)
xpos = -0.3066
ypos = 0.0117
cx = int(xlen / 2.0)
cy = int(ylen / 2.0) + ypos / 0.015 / ybin + yoffset
order, slit_positions = mt.convert_slits_from_mask(
slitmask, order=1, xbin=xbin, ybin=ybin, pix_scale=0.1267, cx=cx, cy=cy)
sections = 1
elif exttype == 'fits':
log.message('Using slits from %s' % sfile)
order, slit_positions = read_slits_from_fits(sfile)
elif exttype == 'ascii':
log.message('Using slits from %s' % sfile)
order, slit_positions = mt.read_slits_from_ascii(sfile)
elif exttype == 'ds9':
log.message('Using slits from %s' % sfile)
order, slit_positions, slitmask = mt.read_slits_from_ds9(
sfile, order=order)
slitmask = None
sections = 1
elif exttype == 'auto':
log.message('Identifying slits in %s' % img)
# identify the slits in the image
order, slit_positions = identify_slits(
struct[1].data, order, sections, width, sigma, thres)
# write out the slit identifications if ofile has been supplied
if oslit:
log.message('Writing slit positions to %s' % oslit)
mt.write_outputslitfile(slit_positions, oslit, order)
if ycheck:
slit_positions, dy = check_ypos(slit_positions, struct[1].data)
log.message('Using an offset of {}'.format(dy))
# extract the slits
spline_x = mt.divide_image(struct[1].data, sections)
spline_x = 0.5 * (np.array(spline_x[:-1]) + np.array(spline_x[1:]))
extracted_spectra, spline_positions = mt.extract_slits(slit_positions,
spline_x, struct[1].data, order=order, padding=padding)
if varext:
extracted_var, var_positions = mt.extract_slits(slit_positions,
spline_x, struct[varext].data, order=order, padding=padding)
if bpmext:
extracted_bpm, bpm_positions = mt.extract_slits(slit_positions,
spline_x, struct[bpmext].data, order=order, padding=padding)
# write out the data to the new array
# create the new file
hdulist = fits.HDUList([struct[0]])
# log the extracted spectra if needed
log.message('', with_stdout=verbose)
# setup output ds9 file
if regprefix:
regout = open(
regprefix +
os.path.basename(img).strip('.fits') +
'.reg',
'w')
regout.write('# Region file format: DS9 version 4.1\n')
regout.write('# Filename: %s\n' % img)
regout.write(
'global color=green dashlist=8 3 width=1 font="helvetica 10 normal roman" select=1 highlite=1 dash=0 fixed=0 edit=1 move=1 delete=1 include=1 source=1\nphysical\n')
# add each
imglist = []
nslits = len(spline_positions)
for i in range(nslits):
y1 = spline_positions[i][0].min()
y2 = spline_positions[i][1].max()
msg = 'Extracted Spectra %i between %i to %i' % (i + 1, y1, y2)
# log.message(msg, with_header=False, with_stdout=verbose)
sdu = fits.ImageHDU(
extracted_spectra[i],
header=struct[1].header)
if varext:
vdu = fits.ImageHDU(
extracted_var[i],
header=struct[varext].header)
sdu.header['VAREXT'] = i + nslits + 1
varlist.append(vdu)
if bpmext:
bdu = fits.ImageHDU(
extracted_bpm[i],
header=struct[bpmext].header)
sdu.header['BPMEXT']= i + 2 * nslits + 1
bpmlist.append(bdu)
imglist.append(sdu)
# add in some additional keywords
imglist[i].header['MINY'] = (y1,
'Lower Y value in original image')
imglist[i].header['MAXY'] = (y2,
'Upper Y value in original image')
if regprefix:
xsize = struct[1].data.shape[1]
xsize = int(0.5 * xsize)
rtext = ''
if slitmask:
# rtext='%s, %8.7f, %8.7f, %3.2f' % (slitmask.slitlets.data[i]['name'], slitmask.slitlets.data[i]['targ_ra'], slitmask.slitlets.data[i]['targ_dec'], slitmask.slitlets.data[i]['slit_width'])
pass
regout.write('box(%i,%i, %i, %i) #text={%s}\n' % (
xsize, 0.5 * (y1 + y2), 2 * xsize, y2 - y1, rtext))
# add slit information
if slitmask:
imglist[i].header['SLITNAME'] = (slitmask.slitlets.data[i]['name'],
'Slit Name')
imglist[i].header['SLIT_RA'] = (slitmask.slitlets.data[i]['targ_ra'],
'Slit RA')
imglist[i].header['SLIT_DEC'] = (slitmask.slitlets.data[i]['targ_dec'],
'Slit DEC')
imglist[i].header['SLIT'] = (slitmask.slitlets.data[i]['slit_width'],
'Slit Width')
# add to the hdulist
hdulist += imglist
if varext:
hdulist += varlist
if bpmext:
hdulist += bpmlist
# write the slit positions to the header
# create the binary table HDU that contains the split positions
tbhdu = mt.slits_HDUtable(slit_positions, order)
bintable_hdr = tbhdu.header
# add the extname parameter to the extension
tbhdu.header['EXTNAME'] = 'BINTABLE'
# add the extname parameter to the extension
hdulist[0].header['SLITEXT'] = len(hdulist)
hdulist.append(tbhdu)
# add addition header information about the mask
if slitmask:
hdulist[0].header['MASKNAME'] = (slitmask.mask_name, 'SlitMask Name')
hdulist[0].header['MASK_RA'] = (slitmask.center_ra,
'SlitMask RA')
hdulist[0].header['MASK_DEC'] = ( slitmask.center_dec,
'SlitMask DEC')
hdulist[0].header['MASK_PA'] = ( slitmask.position_angle,
'SlitMask Position Angle')
# write out the image
saltio.writefits(hdulist, oimg, clobber)
def specslit(image,
outimage,
outpref,
exttype='auto',
slitfile='',
outputslitfile='',
regprefix='',
sections=3,
width=25,
sigma=2.2,
thres=6,
order=3,
padding=5,
yoffset=0,
inter=False,
clobber=True,
logfile='salt.log',
verbose=True):
with logging(logfile, debug) as log:
# check all the input and make sure that all the input needed is provided
# by the user
# read the image or image list and check if each in the list exist
infiles = saltio.argunpack('Input', image)
# unpack the outfiles
outfiles = saltio.listparse('Outimages', outimage, outpref, infiles,
'')
# from the extraction type, check whether the input file is specified.
# if the slitfile parameter is specified then use the slit files for
# the extraction. if the extraction type is auto then use image for the
# detection and the slit extraction
if exttype == 'rsmt' or exttype == 'fits' or exttype == 'ascii' or exttype == 'ds9':
slitfiles = saltio.argunpack('Slitfile', slitfile)
if len(slitfiles) == 1:
slitfiles = slitfiles * len(infiles)
saltio.comparelists(infiles, slitfiles, 'image', 'slitfile')
elif exttype == 'auto':
slitfiles = infiles
log.message(
'Extraction type is AUTO. Slit detection will be done from image'
)
# read in if an optional ascii file is requested
if len(outputslitfile) > 0:
outslitfiles = saltio.argunpack('Outslitfiles', outputslitfile)
saltio.comparelists(infiles, outslitfiles, 'image',
'outputslitfile')
else:
outslitfiles = [''] * len(infiles)
# check if the width and sigma parameters were specified.
# default is 25 and 2.2
if width < 10.:
msg = 'The width parameter needs be a value larger than 10'
raise SALTSpecError(msg)
if sigma < 0.0:
msg = 'Sigma must be greater than zero'
raise SaltSpecError(msg)
# check the treshold parameter. this needs to be specified by the user
if thres <= 0.0:
msg = 'Threshold must be greater than zero'
raise SaltSpecError(msg)
# check to make sure that the sections are greater than the order
if sections <= order:
msg = 'Number of sections must be greater than the order for the spline fit'
raise SaltSpecError(msg)
# run through each of the images and extract the slits
for img, oimg, sfile, oslit in zip(infiles, outfiles, slitfiles,
outslitfiles):
log.message('Proccessing image %s' % img)
# open the image
struct = saltio.openfits(img)
ylen, xlen = struct[1].data.shape
xbin, ybin = saltkey.ccdbin(struct[0], img)
# setup the VARIANCE and BPM frames
if saltkey.found('VAREXT', struct[1]):
varext = saltkey.get('VAREXT', struct[1])
varlist = []
else:
varext = None
# setup the BPM frames
if saltkey.found('BPMEXT', struct[1]):
bpmext = saltkey.get('BPMEXT', struct[1])
bpmlist = []
else:
bpmext = None
# open the slit definition file or identify the slits in the image
slitmask = None
ycheck = False
if exttype == 'rsmt':
log.message('Using slits from %s' % sfile)
if yoffset is None:
yoffset = 0
ycheck = True
slitmask = mt.read_slitmask_from_xml(sfile)
xpos = -0.3066
ypos = 0.0117
cx = int(xlen / 2.0)
cy = int(ylen / 2.0) + ypos / 0.015 / ybin + yoffset
order, slit_positions = mt.convert_slits_from_mask(
slitmask,
order=1,
xbin=xbin,
ybin=ybin,
pix_scale=0.1267,
cx=cx,
cy=cy)
sections = 1
elif exttype == 'fits':
log.message('Using slits from %s' % sfile)
order, slit_positions = read_slits_from_fits(sfile)
elif exttype == 'ascii':
log.message('Using slits from %s' % sfile)
order, slit_positions = mt.read_slits_from_ascii(sfile)
elif exttype == 'ds9':
log.message('Using slits from %s' % sfile)
order, slit_positions, slitmask = mt.read_slits_from_ds9(
sfile, order=order)
slitmask = None
sections = 1
elif exttype == 'auto':
log.message('Identifying slits in %s' % img)
# identify the slits in the image
order, slit_positions = identify_slits(struct[1].data, order,
sections, width, sigma,
thres)
# write out the slit identifications if ofile has been supplied
if oslit:
log.message('Writing slit positions to %s' % oslit)
mt.write_outputslitfile(slit_positions, oslit, order)
if ycheck:
slit_positions, dy = check_ypos(slit_positions, struct[1].data)
log.message('Using an offset of {}'.format(dy))
# extract the slits
spline_x = mt.divide_image(struct[1].data, sections)
spline_x = 0.5 * (np.array(spline_x[:-1]) + np.array(spline_x[1:]))
extracted_spectra, spline_positions = mt.extract_slits(
slit_positions,
spline_x,
struct[1].data,
order=order,
padding=padding)
if varext:
extracted_var, var_positions = mt.extract_slits(
slit_positions,
spline_x,
struct[varext].data,
order=order,
padding=padding)
if bpmext:
extracted_bpm, bpm_positions = mt.extract_slits(
slit_positions,
spline_x,
struct[bpmext].data,
order=order,
padding=padding)
# write out the data to the new array
# create the new file
hdulist = fits.HDUList([struct[0]])
# log the extracted spectra if needed
log.message('', with_stdout=verbose)
# setup output ds9 file
if regprefix:
regout = open(
regprefix + os.path.basename(img).strip('.fits') + '.reg',
'w')
regout.write('# Region file format: DS9 version 4.1\n')
regout.write('# Filename: %s\n' % img)
regout.write(
'global color=green dashlist=8 3 width=1 font="helvetica 10 normal roman" select=1 highlite=1 dash=0 fixed=0 edit=1 move=1 delete=1 include=1 source=1\nphysical\n'
)
# add each
imglist = []
nslits = len(spline_positions)
for i in range(nslits):
y1 = spline_positions[i][0].min()
y2 = spline_positions[i][1].max()
msg = 'Extracted Spectra %i between %i to %i' % (i + 1, y1, y2)
# log.message(msg, with_header=False, with_stdout=verbose)
sdu = fits.ImageHDU(extracted_spectra[i],
header=struct[1].header)
if varext:
vdu = fits.ImageHDU(extracted_var[i],
header=struct[varext].header)
sdu.header['VAREXT'] = i + nslits + 1
varlist.append(vdu)
if bpmext:
bdu = fits.ImageHDU(extracted_bpm[i],
header=struct[bpmext].header)
sdu.header['BPMEXT'] = i + 2 * nslits + 1
bpmlist.append(bdu)
imglist.append(sdu)
# add in some additional keywords
imglist[i].header['MINY'] = (y1,
'Lower Y value in original image')
imglist[i].header['MAXY'] = (y2,
'Upper Y value in original image')
if regprefix:
xsize = struct[1].data.shape[1]
xsize = int(0.5 * xsize)
rtext = ''
if slitmask:
# rtext='%s, %8.7f, %8.7f, %3.2f' % (slitmask.slitlets.data[i]['name'], slitmask.slitlets.data[i]['targ_ra'], slitmask.slitlets.data[i]['targ_dec'], slitmask.slitlets.data[i]['slit_width'])
pass
regout.write('box(%i,%i, %i, %i) #text={%s}\n' %
(xsize, 0.5 *
(y1 + y2), 2 * xsize, y2 - y1, rtext))
# add slit information
if slitmask:
imglist[i].header['SLITNAME'] = (
slitmask.slitlets.data[i]['name'], 'Slit Name')
imglist[i].header['SLIT_RA'] = (
slitmask.slitlets.data[i]['targ_ra'], 'Slit RA')
imglist[i].header['SLIT_DEC'] = (
slitmask.slitlets.data[i]['targ_dec'], 'Slit DEC')
imglist[i].header['SLIT'] = (
slitmask.slitlets.data[i]['slit_width'], 'Slit Width')
# add to the hdulist
hdulist += imglist
if varext:
hdulist += varlist
if bpmext:
hdulist += bpmlist
# write the slit positions to the header
# create the binary table HDU that contains the split positions
tbhdu = mt.slits_HDUtable(slit_positions, order)
bintable_hdr = tbhdu.header
# add the extname parameter to the extension
tbhdu.header['EXTNAME'] = 'BINTABLE'
# add the extname parameter to the extension
hdulist[0].header['SLITEXT'] = len(hdulist)
hdulist.append(tbhdu)
# add addition header information about the mask
if slitmask:
hdulist[0].header['MASKNAME'] = (slitmask.mask_name,
'SlitMask Name')
hdulist[0].header['MASK_RA'] = (slitmask.center_ra,
'SlitMask RA')
hdulist[0].header['MASK_DEC'] = (slitmask.center_dec,
'SlitMask DEC')
hdulist[0].header['MASK_PA'] = (slitmask.position_angle,
'SlitMask Position Angle')
# write out the image
saltio.writefits(hdulist, oimg, clobber)
def salteditkey(images,outimages,outpref, keyfile, recfile=None,clobber=False,logfile='salt.log',verbose=True):
with logging(logfile,debug) as log:
# Check the input images
infiles = saltio.argunpack ('Input',images)
# create list of output files
outfiles=saltio.listparse('Outfile', outimages, outpref,infiles,'')
#verify that the input and output lists are the same length
saltio.comparelists(infiles,outfiles,'Input','output')
#is key file defined
saltio.argdefined('keyfile',keyfile)
keyfile = keyfile.strip()
saltio.fileexists(keyfile)
# if the data are the same, set up to use update instead of write
openmode='copyonwrite'
if (infiles!=outfiles): openmode='copyonwrite'
# determine the date of the observations
obsdate=saltstring.makeobsdatestr(infiles, 1,9)
if len(obsdate)!=8:
message = 'Either FITS files from multiple dates exist, '
message += 'or raw FITS files exist with non-standard names.'
log.warning(message)
# FITS file columns to record keyword changes
fitcol = []
keycol = []
oldcol = []
newcol = []
# Set up the rules to change the files
keyedits=readkeyfile(keyfile, log=log, verbose=verbose)
#now step through the images
for img, oimg in zip(infiles, outfiles):
#determine the appropriate keyword edits for the image
klist=[]
for frange in keyedits:
if checkfitsfile(img, frange, keyedits[frange]):
klist.append(keyedits[frange][3])
if klist:
#open up the new files
struct = saltio.openfits(img,mode=openmode)
struct.verify('fix')
for kdict in klist:
for keyword in kdict:
#record the changes
value=kdict[keyword]
fitcol.append(img)
keycol.append(keyword)
newcol.append(value)
try:
oldcol.append(struct[0].header[keyword].lstrip())
except:
oldcol.append('None')
#update the keyword
if saltkey.found(keyword, struct[0]):
try:
saltkey.put(keyword,value,struct[0])
message='\tUpdating %s in %s to %s' % (keyword, os.path.basename(img), value)
log.message(message, with_header=False, with_stdout=verbose)
except Exception, e:
message = 'Could not update %s in %s because %s' % (keyword, img, str(e))
raise SaltError(message)
else:
try:
saltkey.new(keyword.strip(),value,'Added Comment',struct[0])
message='\tAdding %s in %s to %s' % (keyword, os.path.basename(img), value)
log.message(message, with_header=False, with_stdout=verbose)
except Exception,e :
message = 'Could not update %s in %s because %s' % (keyword, img, str(e))
raise SaltError(message)
#updat the history keywords
#fname, hist=history(level=1, wrap=False, exclude=['images', 'outimages', 'outpref'])
#saltkey.housekeeping(struct[0],'SAL-EDT', 'Keywords updated by SALTEDITKEY', hist)
#write the file out
if openmode=='update':
saltio.updatefits(struct)
message = 'Updated file ' + os.path.basename(oimg)
else:
saltio.writefits(struct, oimg, clobber)
message = 'Created file ' + os.path.basename(oimg)
log.message(message, with_header=False, with_stdout=True)
struct.close()
def slotmerge(images,outimages,outpref,geomfile,clobber,logfile,verbose):
with logging(logfile,debug) as log:
# are the arguments defined
saltsafeio.argdefined('images',images)
saltsafeio.argdefined('geomfile',geomfile)
saltsafeio.argdefined('logfile',logfile)
# if the input file is a list, does it exist?
if images[0] == '@':
saltsafeio.listexists('Input',images)
# parse list of input files
infiles=saltsafeio.listparse('Raw image',images,'','','')
# check input files exist
saltsafeio.filesexist(infiles,'','r')
# load output name list: @list, * and comma separated
outimages = outimages.strip()
outpref = outpref.strip()
if len(outpref) == 0 and len(outimages) == 0:
raise SaltIOError('Output file(s) not specified')
# test output @filelist exists
if len(outimages) > 0 and outimages[0] == '@':
saltsafeio.listexists('Output',outimages)
# parse list of output files
outfiles=saltsafeio.listparse('Output image',outimages,outpref,infiles,'')
# are input and output lists the same length?
saltsafeio.comparelists(infiles,outfiles,'Input','output')
# do the output files already exist?
if not clobber:
saltsafeio.filesexist(outfiles,'','w')
# does CCD geometry definition file exist
geomfilefile = geomfile.strip()
saltsafeio.fileexists(geomfile)
# read geometry definition file
gap = 0
xshift = [0, 0]
yshift = [0, 0]
rotation = [0, 0]
gap, xshift, yshift, rotation=saltsafeio.readccdgeom(geomfile)
for ro in rotation:
if ro!=0:
log.warning('SLOTMERGE currently ignores CCD rotation')
# Begin processes each file
for infile, outfile in zip(infiles, outfiles):
# determine the name for the output file
outpath = outfile.rstrip(os.path.basename(outfile))
if (len(outpath) == 0):
outpath = '.'
# open each raw image
struct=saltsafeio.openfits(infile)
# identify instrument
instrume,keyprep,keygain,keybias,keyxtalk,keyslot=saltsafekey.instrumid(struct,infile)
# how many amplifiers?
nccds=saltsafekey.get('NCCDS',struct[0],infile)
amplifiers = nccds * 2
#if (nccds != 2):
# raise SaltError('Can not currently handle more than two CCDs')
# CCD geometry coefficients
if instrume == 'RSS' or instrume == 'PFIS':
xsh = [xshift[0], 0., xshift[1]]
ysh = [yshift[0], 0., yshift[1]]
rot = [rotation[0], 0., rotation[1]]
refid = 1
if instrume == 'SALTICAM':
xsh = [xshift[0], 0.]
ysh = [yshift[0], 0.]
rot = [rotation[0], 0]
refid = 1
# how many extensions?
nextend=saltsafekey.get('NEXTEND',struct[0],infile)
# how many exposures
exposures = nextend/amplifiers
# CCD on-chip binning
xbin, ybin=saltsafekey.ccdbin(struct[0],infile)
gp = int(gap / xbin)
# create output hdu structure
outstruct = [None] * int(exposures+1)
outstruct[0]=struct[0]
# iterate over exposures, stitch them to produce file of CCD images
for i in range(exposures):
# Determine the total size of the image
xsize=0
ysize=0
for j in range(amplifiers):
hdu=i*amplifiers+j+1
try:
xsize += len(struct[hdu].data[0])
if ysize < len(struct[hdu].data):
ysize=len(struct[hdu].data)
except:
msg='Unable to access extension %i ' % hdu
raise SaltIOError(msg)
xsize += gp* (nccds-1)
maxxsh, minxsh = determineshifts(xsh)
maxysh, minysh = determineshifts(ysh)
xsize += (maxxsh-minxsh)
ysize += (maxysh-minysh)
# Determine the x and y origins for each frame
xdist=0
ydist=0
shid=0
x0=np.zeros(amplifiers)
y0=np.zeros(amplifiers)
for j in range(amplifiers):
x0[j]=xdist+xsh[shid]-minxsh
y0[j]=ysh[shid]-minysh
hdu=i*amplifiers+j+1
darr=struct[hdu].data
xdist += len(darr[0])
if j%2==1:
xdist += gp
shid += 1
# make the out image
outarr=np.zeros((ysize, xsize), np.float64)
# Embed each frame into the output array
for j in range(amplifiers):
hdu=i*amplifiers+j+1
darr=struct[hdu].data
outarr=salttran.embed(darr, x0[j], y0[j], outarr)
# Add the outimage to the output structure
hdu=i*amplifiers+1
outhdu=i+1
outstruct[outhdu] = pyfits.ImageHDU(outarr)
outstruct[outhdu].header=struct[hdu].header
# Fix the headers in each extension
datasec='[1:%4i,1:%4i]' % (xsize, ysize)
saltsafekey.put('DATASEC',datasec, outstruct[outhdu], outfile)
saltsafekey.rem('DETSIZE',outstruct[outhdu],outfile)
saltsafekey.rem('DETSEC',outstruct[outhdu],outfile)
saltsafekey.rem('CCDSEC',outstruct[outhdu],outfile)
saltsafekey.rem('AMPSEC',outstruct[outhdu],outfile)
# add housekeeping key words
outstruct[outhdu]=addhousekeeping(outstruct[outhdu], outhdu, outfile)
# close input FITS file
saltsafeio.closefits(struct)
# housekeeping keywords
keymosaic='SLOTMERG'
fname, hist=history(level=1, wrap=False)
saltsafekey.housekeeping(struct[0],keymosaic,'Amplifiers have been mosaiced', hist)
#saltsafekey.history(outstruct[0],hist)
# this is added for later use by
saltsafekey.put('NCCDS', 0.5, outstruct[0])
saltsafekey.put('NSCIEXT', exposures, outstruct[0])
saltsafekey.put('NEXTEND', exposures, outstruct[0])
# write FITS file of mosaiced image
outstruct=pyfits.HDUList(outstruct)
saltsafeio.writefits(outstruct, outfile, clobber=clobber)
def slotmerge(images, outimages, outpref, geomfile, clobber, logfile, verbose):
with logging(logfile, debug) as log:
# are the arguments defined
saltsafeio.argdefined('images', images)
saltsafeio.argdefined('geomfile', geomfile)
saltsafeio.argdefined('logfile', logfile)
# if the input file is a list, does it exist?
if images[0] == '@':
saltsafeio.listexists('Input', images)
# parse list of input files
infiles = saltsafeio.listparse('Raw image', images, '', '', '')
# check input files exist
saltsafeio.filesexist(infiles, '', 'r')
# load output name list: @list, * and comma separated
outimages = outimages.strip()
outpref = outpref.strip()
if len(outpref) == 0 and len(outimages) == 0:
raise SaltIOError('Output file(s) not specified')
# test output @filelist exists
if len(outimages) > 0 and outimages[0] == '@':
saltsafeio.listexists('Output', outimages)
# parse list of output files
outfiles = saltsafeio.listparse('Output image', outimages, outpref,
infiles, '')
# are input and output lists the same length?
saltsafeio.comparelists(infiles, outfiles, 'Input', 'output')
# do the output files already exist?
if not clobber:
saltsafeio.filesexist(outfiles, '', 'w')
# does CCD geometry definition file exist
geomfilefile = geomfile.strip()
saltsafeio.fileexists(geomfile)
# read geometry definition file
gap = 0
xshift = [0, 0]
yshift = [0, 0]
rotation = [0, 0]
gap, xshift, yshift, rotation = saltsafeio.readccdgeom(geomfile)
for ro in rotation:
if ro != 0:
log.warning('SLOTMERGE currently ignores CCD rotation')
# Begin processes each file
for infile, outfile in zip(infiles, outfiles):
# determine the name for the output file
outpath = outfile.rstrip(os.path.basename(outfile))
if (len(outpath) == 0):
outpath = '.'
# open each raw image
struct = saltsafeio.openfits(infile)
# identify instrument
instrume, keyprep, keygain, keybias, keyxtalk, keyslot = saltsafekey.instrumid(
struct, infile)
# how many amplifiers?
nccds = saltsafekey.get('NCCDS', struct[0], infile)
amplifiers = nccds * 2
#if (nccds != 2):
# raise SaltError('Can not currently handle more than two CCDs')
# CCD geometry coefficients
if instrume == 'RSS' or instrume == 'PFIS':
xsh = [xshift[0], 0., xshift[1]]
ysh = [yshift[0], 0., yshift[1]]
rot = [rotation[0], 0., rotation[1]]
refid = 1
if instrume == 'SALTICAM':
xsh = [xshift[0], 0.]
ysh = [yshift[0], 0.]
rot = [rotation[0], 0]
refid = 1
# how many extensions?
nextend = saltsafekey.get('NEXTEND', struct[0], infile)
# how many exposures
exposures = nextend / amplifiers
# CCD on-chip binning
xbin, ybin = saltsafekey.ccdbin(struct[0], infile)
gp = int(gap / xbin)
# create output hdu structure
outstruct = [None] * int(exposures + 1)
outstruct[0] = struct[0]
# iterate over exposures, stitch them to produce file of CCD images
for i in range(exposures):
# Determine the total size of the image
xsize = 0
ysize = 0
for j in range(amplifiers):
hdu = i * amplifiers + j + 1
try:
xsize += len(struct[hdu].data[0])
if ysize < len(struct[hdu].data):
ysize = len(struct[hdu].data)
except:
msg = 'Unable to access extension %i ' % hdu
raise SaltIOError(msg)
xsize += gp * (nccds - 1)
maxxsh, minxsh = determineshifts(xsh)
maxysh, minysh = determineshifts(ysh)
xsize += (maxxsh - minxsh)
ysize += (maxysh - minysh)
# Determine the x and y origins for each frame
xdist = 0
ydist = 0
shid = 0
x0 = np.zeros(amplifiers)
y0 = np.zeros(amplifiers)
for j in range(amplifiers):
x0[j] = xdist + xsh[shid] - minxsh
y0[j] = ysh[shid] - minysh
hdu = i * amplifiers + j + 1
darr = struct[hdu].data
xdist += len(darr[0])
if j % 2 == 1:
xdist += gp
shid += 1
# make the out image
outarr = np.zeros((ysize, xsize), np.float64)
# Embed each frame into the output array
for j in range(amplifiers):
hdu = i * amplifiers + j + 1
darr = struct[hdu].data
outarr = salttran.embed(darr, x0[j], y0[j], outarr)
# Add the outimage to the output structure
hdu = i * amplifiers + 1
outhdu = i + 1
outstruct[outhdu] = pyfits.ImageHDU(outarr)
outstruct[outhdu].header = struct[hdu].header
# Fix the headers in each extension
datasec = '[1:%4i,1:%4i]' % (xsize, ysize)
saltsafekey.put('DATASEC', datasec, outstruct[outhdu], outfile)
saltsafekey.rem('DETSIZE', outstruct[outhdu], outfile)
saltsafekey.rem('DETSEC', outstruct[outhdu], outfile)
saltsafekey.rem('CCDSEC', outstruct[outhdu], outfile)
saltsafekey.rem('AMPSEC', outstruct[outhdu], outfile)
# add housekeeping key words
outstruct[outhdu] = addhousekeeping(outstruct[outhdu], outhdu,
outfile)
# close input FITS file
saltsafeio.closefits(struct)
# housekeeping keywords
keymosaic = 'SLOTMERG'
fname, hist = history(level=1, wrap=False)
saltsafekey.housekeeping(struct[0], keymosaic,
'Amplifiers have been mosaiced', hist)
#saltsafekey.history(outstruct[0],hist)
# this is added for later use by
saltsafekey.put('NCCDS', 0.5, outstruct[0])
saltsafekey.put('NSCIEXT', exposures, outstruct[0])
saltsafekey.put('NEXTEND', exposures, outstruct[0])
# write FITS file of mosaiced image
outstruct = pyfits.HDUList(outstruct)
saltsafeio.writefits(outstruct, outfile, clobber=clobber)
def saltfpskyring(images,
outimages,
outpref,
axc,
ayc,
arad,
rxc,
ryc,
pmin,
pmax,
swindow=5,
clobber=False,
logfile='salt.log',
verbose=True):
"""Sky subtracts Fabry-Perot images"""
# start log now that all parameter are set up
with logging(logfile, debug) as log:
# Check the input images
infiles = saltio.argunpack('Input', images)
# create list of output files
outfiles = saltio.listparse('Outfile', outimages, outpref, infiles, '')
#verify that the input and output lists are the same length
saltio.comparelists(infiles, outfiles, 'Input', 'output')
for img, oimg in zip(infiles, outfiles):
#open up the file
hdu = saltio.openfits(img)
#determine the azimuthally averaged profile
rpro, radial_profile = median_radial_profile(hdu[0].data,
xc=axc,
yc=ayc,
rmax=arad,
nbins=100,
pmin=pmin,
pmax=pmax)
if swindow > 1:
radial_profile = np.convolve(
radial_profile, np.ones(swindow), mode='same') / swindow
# calculate the indices from the image
y, x = np.indices(hdu[0].data.shape)
radius = np.hypot(x - axc, y - ayc)
#subtract off the sky data
mdata = hdu[0].data - np.interp(radius, rpro, radial_profile)
hdu[0].data = mdata
# write FITS file
saltio.writefits(hdu, oimg, clobber=clobber)
saltio.closefits(hdu)
message = 'SALTFPSKYRING -- Subtracted sky from %s' % (img)
log.message(message, with_header=False)
def saltbias(images,
outimages,
outpref,
subover=True,
trim=True,
subbias=False,
masterbias='bias.fits',
median=False,
function='polynomial',
order=3,
rej_lo=3,
rej_hi=3,
niter=10,
plotover=False,
turbo=False,
clobber=False,
logfile='salt.log',
verbose=True):
status = 0
ifil = 0
ii = 0
mbiasdata = []
bstruct = ''
biasgn = ''
biassp = ''
biasbn = ''
biasin = ''
filetime = {}
biastime = {}
for i in range(1, 7):
filetime[i] = []
biastime[i] = []
with logging(logfile, debug) as log:
# Check the input images
infiles = saltio.argunpack('Input', images)
# create list of output files
outfiles = saltio.listparse('Outfile', outimages, outpref, infiles, '')
# are input and output lists the same length?
saltio.comparelists(infiles, outfiles, 'Input', 'output')
# Does master bias frame exist?
# gain, speed, binning and instrument of master bias frame
if subbias:
if os.path.isfile(masterbias):
bstruct = saltio.openfits(masterbias)
else:
message = 'Master bias frame %s does not exist' % masterbias
raise SaltError(message)
else:
bstruct = None
# open each raw image file
for img, oimg in zip(infiles, outfiles):
#open the file
struct = saltio.openfits(img)
#check to see if it has already been bias subtracted
instrume, keyprep, keygain, keybias, keyxtalk, keyslot = saltkey.instrumid(
struct)
# has file been biaseded already?
try:
key = struct[0].header[keybias]
message = 'File %s has already been de-biased ' % infile
raise SaltError(message)
except:
pass
#compare with the master bias to make sure they are the same
if subbias:
pass
#subtract the bias
struct = bias(struct,
subover=subover,
trim=trim,
subbias=subbias,
bstruct=bstruct,
median=median,
function=function,
order=order,
rej_lo=rej_lo,
rej_hi=rej_hi,
niter=niter,
plotover=plotover,
log=log,
verbose=verbose)
#write the file out
# housekeeping keywords
fname, hist = history(level=1,
wrap=False,
exclude=['images', 'outimages', 'outpref'])
saltkey.housekeeping(struct[0], keybias,
'Images have been de-biased', hist)
# write FITS file
saltio.writefits(struct, oimg, clobber=clobber)
saltio.closefits(struct)
def saltbias(images,outimages,outpref,subover=True,trim=True,subbias=False,
masterbias='bias.fits', median=False, function='polynomial',
order=3, rej_lo=3, rej_hi=3, niter=10, plotover=False,
turbo=False, clobber=False, logfile='salt.log', verbose=True):
status = 0
ifil = 0
ii = 0
mbiasdata = []
bstruct = ''
biasgn = ''
biassp = ''
biasbn = ''
biasin = ''
filetime = {}
biastime = {}
for i in range(1,7):
filetime[i] = []
biastime[i] = []
with logging(logfile,debug) as log:
# Check the input images
infiles = saltio.argunpack ('Input',images)
# create list of output files
outfiles=saltio.listparse('Outfile', outimages, outpref,infiles,'')
# are input and output lists the same length?
saltio.comparelists(infiles,outfiles,'Input','output')
# Does master bias frame exist?
# gain, speed, binning and instrument of master bias frame
if subbias:
if os.path.isfile(masterbias):
bstruct = saltio.openfits(masterbias)
else:
message = 'Master bias frame %s does not exist' % masterbias
raise SaltError(message)
else:
bstruct=None
# open each raw image file
for img, oimg in zip(infiles, outfiles):
#open the file
struct = saltio.openfits(img)
#check to see if it has already been bias subtracted
instrume,keyprep,keygain,keybias,keyxtalk,keyslot = saltkey.instrumid(struct)
# has file been biaseded already?
try:
key = struct[0].header[keybias]
message = 'File %s has already been de-biased ' % infile
raise SaltError(message)
except:
pass
#compare with the master bias to make sure they are the same
if subbias:
pass
#subtract the bias
struct=bias(struct,subover=subover, trim=trim, subbias=subbias,
bstruct=bstruct, median=median, function=function,
order=order, rej_lo=rej_lo, rej_hi=rej_hi, niter=niter,
plotover=plotover, log=log, verbose=verbose)
#write the file out
# housekeeping keywords
fname, hist=history(level=1, wrap=False, exclude=['images', 'outimages', 'outpref'])
saltkey.housekeeping(struct[0],keybias, 'Images have been de-biased', hist)
# write FITS file
saltio.writefits(struct,oimg, clobber=clobber)
saltio.closefits(struct)
def saltxtalk(images,
outimages,
outpref,
xtalkfile=None,
usedb=False,
clobber=True,
logfile='salt.log',
verbose=True):
#start logging
with logging(logfile, debug) as log:
# Check the input images
infiles = saltio.argunpack('Input', images)
# create list of output files
outfiles = saltio.listparse('Outfile', outimages, outpref, infiles, '')
# are input and output lists the same length?
saltio.comparelists(infiles, outfiles, 'Input', 'output')
# does crosstalk coefficient data exist
if usedb:
xtalkfile = xtalkfile.strip()
xdict = saltio.readxtalkcoeff(xtalkfile)
else:
xdict = None
for img, oimg in zip(infiles, outfiles):
#open the fits file
struct = saltio.openfits(img)
#find the best xcoeff for the image if using the db
if usedb:
obsdate = saltkey.get('DATE-OBS', struct[0])
obsdate = int('%s%s%s' %
(obsdate[0:4], obsdate[5:7], obsdate[8:]))
xkey = np.array(xdict.keys())
date = xkey[abs(xkey - obsdate).argmin()]
xcoeff = xdict[date]
else:
xcoeff = []
# identify instrument
instrume, keyprep, keygain, keybias, keyxtalk, keyslot = saltkey.instrumid(
struct)
# has file been prepared already?
if saltkey.found(keyxtalk, struct[0]):
message = '%s has already been xtalk corrected' % img
raise SaltError(message)
#apply the cross-talk correction
struct = xtalk(struct, xcoeff, log=log, verbose=verbose)
# housekeeping keywords
fname, hist = history(level=1,
wrap=False,
exclude=['images', 'outimages', 'outpref'])
saltkey.housekeeping(struct[0], 'SXTALK',
'Images have been xtalk corrected', hist)
# write FITS file
saltio.writefits(struct, oimg, clobber=clobber)
saltio.closefits(struct)
