def specidentify(images,linelist, outfile, guesstype, guessfile, function, \
order, rstep, interact, clobber,logfile,verbose,status):
with logging(logfile,debug) as log:
#set up the variables
infiles = []
outfiles = []
status = 0
# Check the input images
infiles = saltsafeio.argunpack ('Input',images)
# create list of output files
outfiles = saltsafeio.argunpack ('Input',outfile)
#if outfiles is a single image, turn it into a list
#of the same length as infiles
if len(outfiles)!=len(infiles):
if len(outfiles)==1:
outfiles=outfiles*len(infiles)
elif len(outfiles)==0:
outfiles=[None]*len(infiles)
else:
msg='Please enter an appropriate number of outfiles'
raise SALTSpecError(msg)
# open the line lists
slines, sfluxes = readlinelist(linelist)
# Identify the lines in each file
for img, oimg in zip(infiles, outfiles):
identify(img, oimg, slines, sfluxes, guesstype, guessfile, function,
order, rstep, interact, clobber, verbose)
def specidentify(images, linelist, outfile, guesstype, guessfile, function,
order, rstep, interact, clobber, logfile, verbose, status):
with logging(logfile, debug) as log:
# set up the variables
infiles = []
outfiles = []
# Check the input images
infiles = saltsafeio.argunpack('Input', images)
print(infiles)
# create list of output files
outfiles = saltsafeio.argunpack('Input', outfile)
# if outfiles is a single image, turn it into a list
# of the same length as infiles
if len(outfiles) != len(infiles):
if len(outfiles) == 1:
outfiles = outfiles * len(infiles)
elif len(outfiles) == 0:
outfiles = [None] * len(infiles)
else:
msg = 'Please enter an appropriate number of outfiles'
raise SALTSpecError(msg)
# open the line lists
slines, sfluxes = st.readlinelist(linelist)
# Identify the lines in each file
for img, oimg in zip(infiles, outfiles):
log.message('Proccessing image %s' % img)
identify(img, oimg, slines, sfluxes, guesstype, guessfile,
function, order, rstep, interact, clobber, log, verbose)
def specextract(images,
outfile,
method='normal',
section=None,
thresh=3.0,
minsize=3.0,
outformat='ascii',
ext=1,
convert=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.argunpack('outfile', outfile)
if method is 'weighted':
msg = 'This mode is not supported yet'
raise SALTSpecError(msg)
section = saltio.checkfornone(section)
if section is not None:
sections = saltio.getSection(section, iraf_format=False)
section = []
for i in range(0, len(sections), 2):
section.append((sections[i], sections[i + 1]))
# Identify the lines in each file
for img, ofile in zip(infiles, outfiles):
log.message('\nExtracting spectrum in image %s to %s' %
(img, ofile),
with_header=False,
with_stdout=verbose)
# open the images
hdu = saltio.openfits(img)
ap_list = extract(hdu,
ext=ext,
method=method,
section=section,
minsize=minsize,
thresh=thresh,
convert=convert)
# write the spectra out
if ap_list:
write_extract(ofile.strip(),
ap_list,
outformat=outformat,
clobber=clobber)
log.message('', with_header=False, with_stdout=verbose)
def specextract(
images,
outfile,
method="normal",
section=None,
thresh=3.0,
minsize=3.0,
outformat="ascii",
ext=1,
convert=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.argunpack("outfile", outfile)
if method is "weighted":
msg = "This mode is not supported yet"
raise SALTSpecError(msg)
section = saltio.checkfornone(section)
if section is not None:
sections = saltio.getSection(section, iraf_format=False)
section = []
for i in range(0, len(sections), 2):
section.append((sections[i], sections[i + 1]))
# Identify the lines in each file
for img, ofile in zip(infiles, outfiles):
log.message(
"\nExtracting spectrum in image %s to %s" % (img, ofile), with_header=False, with_stdout=verbose
)
# open the images
hdu = saltio.openfits(img)
ap_list = extract(
hdu, ext=ext, method=method, section=section, minsize=minsize, thresh=thresh, convert=convert
)
# write the spectra out
if ap_list:
write_extract(ofile.strip(), ap_list, outformat=outformat, clobber=clobber)
log.message("", 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 specselfid(images, outimages, outpref, refimage=None, ystart='middlerow',
rstep=3, clobber=False, logfile='salt.log', verbose=True):
with logging(logfile, debug) as log:
# set up the variables
infiles = []
outfiles = []
# Check the input images
infiles = saltio.argunpack('Input', images)
# create list of output files
outfiles = saltio.listparse(
'Outimages',
outimages,
outpref,
infiles,
'')
# set up defaults
if saltio.checkfornone(refimage) is not None:
rhdu = saltio.openfits(refimage)
else:
refimage = None
# read in rectify each image
for img, oimg, in zip(infiles, outfiles):
hdu = saltio.openfits(img)
log.message(
'Performing self-identification and rectification on %s' %
img)
for i in range(1, len(hdu)):
if hdu[i].name == 'SCI':
if refimage is None:
sdata = hdu[i].data
else:
sdata = rhdu[i].data
hdu[i].data = selfid(
hdu[i].data,
sdata,
ystart=ystart,
rstep=rstep)
if saltkey.found('VAREXT', hdu[i]):
varext = saltkey.get('VAREXT', hdu[i])
hdu[varext].data = selfid(
hdu[varext].data,
sdata,
ystart=ystart,
rstep=rstep)
if saltkey.found('BPMEXT', hdu[i]):
bpmext = saltkey.get('BPMEXT', hdu[i])
hdu[bpmext].data = selfid(
hdu[bpmext].data,
sdata,
ystart=ystart,
rstep=rstep)
# write out the oimg
saltio.writefits(hdu, oimg, clobber=clobber)
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 saltobslog(images,
outfile,
clobber=False,
logfile='salt.log',
verbose=True):
"""Create the observation log from the input files"""
#start the logging
with logging(logfile, debug) as log:
# Check the input images
infiles = saltio.argunpack('Input', images)
#create the header dictionary
headerDict = obslog(infiles, log)
#clobber the output if it exists
if (clobber and os.path.isfile(outfile)):
saltio.delete(outfile)
#create the fits file
struct = createobslogfits(headerDict)
# close table file
saltio.writefits(struct, outfile)
#indicate the log was created
log.message('\nSALTLOG -- created observation log ' + outfile)
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 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 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 specsky(images,outimages,outpref, method='normal', section=None,
function='polynomial', order=2,
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,'')
if method not in ['normal', 'fit']:
msg='%s mode is not supported yet' % method
raise SALTSpecError(msg)
if section is None:
section=saltio.getSection(section)
msg='This mode is not supported yet'
raise SALTSpecError(msg)
else:
section=saltio.getSection(section)
# Identify the lines in each file
for img, ofile in zip(infiles, outfiles):
log.message('Subtracting sky spectrum in image %s into %s' % (img, ofile))
#open the images
hdu=saltio.openfits(img)
#sky subtract the array
hdu=skysubtract(hdu, method=method, section=section, funct=function, order=order)
#write out the image
if clobber and os.path.isfile(ofile): saltio.delete(ofile)
hdu.writeto(ofile)
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 bvitftp(propcode, obsdate, sdbhost,sdbname,sdbuser, password,
server,username,sender, bcc, emailfile,
notify=False, clobber=True,logfile='salt.log',verbose=True):
# set up
proposers = []
propids = []
pids = []
with logging(logfile,debug) as log:
# are the arguments defined
if propcode.strip().upper()=='ALL':
pids=getbvitproposalcodes(str(obsdate))
else:
pids = saltio.argunpack('propcode',propcode)
if len(pids)==0:
#throw a warning adn exit if not data needs to be filterd
log.warning('No data to distribute\n', with_stdout=verbose)
return
#log into the database
sdb=saltmysql.connectdb(sdbhost,sdbname,sdbuser,password)
# check PI directories exist
ftpdir='/salt/ftparea/'
for datapath in pids:
pid=os.path.basename(datapath)
movebvitdata(pid, datapath, ftpdir, obsdate, sdb, clobber)
if notify:
notifybvituser(sdb, pid, obsdate, server,username,password,sender, bcc, emailfile)
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 saltobslog(images,outfile,clobber=False,logfile='salt.log',verbose=True):
"""Create the observation log from the input files"""
#start the logging
with logging(logfile,debug) as log:
# Check the input images
infiles = saltio.argunpack ('Input',images)
#create the header dictionary
headerDict=obslog(infiles, log)
#clobber the output if it exists
if (clobber and os.path.isfile(outfile)):
saltio.delete(outfile)
#create the fits file
struct=createobslogfits(headerDict)
# close table file
saltio.writefits(struct, outfile)
#indicate the log was created
log.message('\nSALTLOG -- created observation log ' + outfile)
def saltcombine(images,outimage, method='average', reject=None, mask=True, \
weight=True, blank=0, scale=None, statsec=None, lthresh=3, \
hthresh=3, clobber=False, logfile='salt.log',verbose=True):
with logging(logfile,debug) as log:
# Check the input images
infiles = saltio.argunpack ('Input',images)
#set reject as None
reject=saltio.checkfornone(reject)
if reject is not None: reject=reject.lower()
#set scale
scale=saltio.checkfornone(scale)
if scale is not None: scale=scale.lower()
#set statsec
statsec=saltio.checkfornone(statsec)
statsec=saltio.getSection(statsec, iraf_format=True)
#Fast combine the images
outstruct=imcombine(infiles, method=method, reject=reject, mask=mask, \
weight=weight, blank=blank, scale=scale, \
statsec=statsec, lthresh=lthresh, hthresh=hthresh)
# housekeeping keywords
fname, hist=history(level=1, wrap=False)
saltkey.housekeeping(outstruct[0],'SCOMBINE', 'File Combined by SALTCOMBINE', hist)
# write FITS file
saltio.writefits(outstruct, outimage)
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 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 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 saltcombine(images,outimage, method='average', reject=None, mask=True, \
weight=True, blank=0, scale=None, statsec=None, lthresh=3, \
hthresh=3, clobber=False, logfile='salt.log',verbose=True):
with logging(logfile, debug) as log:
# Check the input images
infiles = saltio.argunpack('Input', images)
#set reject as None
reject = saltio.checkfornone(reject)
if reject is not None: reject = reject.lower()
#set scale
scale = saltio.checkfornone(scale)
if scale is not None: scale = scale.lower()
#set statsec
statsec = saltio.checkfornone(statsec)
statsec = saltio.getSection(statsec, iraf_format=True)
#Fast combine the images
outstruct=imcombine(infiles, method=method, reject=reject, mask=mask, \
weight=weight, blank=blank, scale=scale, \
statsec=statsec, lthresh=lthresh, hthresh=hthresh)
# housekeeping keywords
fname, hist = history(level=1, wrap=False)
saltkey.housekeeping(outstruct[0], 'SCOMBINE',
'File Combined by SALTCOMBINE', hist)
# write FITS file
saltio.writefits(outstruct, outimage)
def specselfid(images,
outimages,
outpref,
refimage=None,
ystart='middlerow',
rstep=3,
clobber=False,
logfile='salt.log',
verbose=True):
with logging(logfile, debug) as log:
# set up the variables
infiles = []
outfiles = []
# Check the input images
infiles = saltio.argunpack('Input', images)
# create list of output files
outfiles = saltio.listparse('Outimages', outimages, outpref, infiles,
'')
# set up defaults
if saltio.checkfornone(refimage) is not None:
rhdu = saltio.openfits(refimage)
else:
refimage = None
# read in rectify each image
for img, oimg, in zip(infiles, outfiles):
hdu = saltio.openfits(img)
log.message(
'Performing self-identification and rectification on %s' % img)
for i in range(1, len(hdu)):
if hdu[i].name == 'SCI':
if refimage is None:
sdata = hdu[i].data
else:
sdata = rhdu[i].data
hdu[i].data = selfid(hdu[i].data,
sdata,
ystart=ystart,
rstep=rstep)
if saltkey.found('VAREXT', hdu[i]):
varext = saltkey.get('VAREXT', hdu[i])
hdu[varext].data = selfid(hdu[varext].data,
sdata,
ystart=ystart,
rstep=rstep)
if saltkey.found('BPMEXT', hdu[i]):
bpmext = saltkey.get('BPMEXT', hdu[i])
hdu[bpmext].data = selfid(hdu[bpmext].data,
sdata,
ystart=ystart,
rstep=rstep)
# write out the oimg
saltio.writefits(hdu, oimg, 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 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 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 specwavemap(
images,
outimages,
outpref,
solfile=None,
caltype="line",
function="polynomial",
order=3,
blank=0,
nearest=False,
clobber=True,
logfile="salt.log",
verbose=True,
):
with logging(logfile, debug) as log:
# set up the variables
infiles = []
outfiles = []
# Check the input images
infiles = saltsafeio.argunpack("Input", images)
# create list of output files
outfiles = saltsafeio.listparse("Outimages", outimages, outpref, infiles, "")
# read in the wavelength solutions and enter them into
# there own format
if caltype == "line":
soldict = sr.entersolution(solfile)
else:
soldict = None
# read in rectify each image
for img, oimg in zip(infiles, outfiles):
if caltype == "line":
msg = "Creating wave map image %s from image %s using files %s" % (oimg, img, solfile)
else:
msg = "Creating wave map image %s from image %s using RSS Model" % (oimg, img)
log.message(msg)
hdu = saltsafeio.openfits(img)
hdu = wavemap(
hdu,
soldict,
caltype=caltype,
function=function,
order=order,
blank=blank,
nearest=nearest,
clobber=clobber,
log=log,
verbose=verbose,
)
saltsafeio.writefits(hdu, oimg, clobber=clobber)
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 specwavemap(images,
outimages,
outpref,
solfile=None,
caltype='line',
function='polynomial',
order=3,
blank=0,
nearest=False,
clobber=True,
logfile='salt.log',
verbose=True):
with logging(logfile, debug) as log:
# set up the variables
infiles = []
outfiles = []
# Check the input images
infiles = saltsafeio.argunpack('Input', images)
# create list of output files
outfiles = saltsafeio.listparse('Outimages', outimages, outpref,
infiles, '')
# read in the wavelength solutions and enter them into
# there own format
if caltype == 'line':
soldict = sr.entersolution(solfile)
else:
soldict = None
# read in rectify each image
for img, oimg, in zip(infiles, outfiles):
if caltype == 'line':
msg = 'Creating wave map image %s from image %s using files %s' % (
oimg, img, solfile)
else:
msg = 'Creating wave map image %s from image %s using RSS Model' % (
oimg, img)
log.message(msg)
hdu = saltsafeio.openfits(img)
hdu = wavemap(hdu,
soldict,
caltype=caltype,
function=function,
order=order,
blank=blank,
nearest=nearest,
clobber=clobber,
log=log,
verbose=verbose)
saltsafeio.writefits(hdu, oimg, clobber=clobber)
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 specsky(images,
outimages,
outpref,
method='normal',
section=None,
function='polynomial',
order=2,
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, '')
if method not in ['normal', 'fit']:
msg = '%s mode is not supported yet' % method
raise SALTSpecError(msg)
if section is None:
section = saltio.getSection(section)
msg = 'This mode is not supported yet'
raise SALTSpecError(msg)
else:
section = saltio.getSection(section)
# Identify the lines in each file
for img, ofile in zip(infiles, outfiles):
log.message('Subtracting sky spectrum in image %s into %s' %
(img, ofile))
# open the images
hdu = saltio.openfits(img)
# sky subtract the array
hdu = skysubtract(hdu,
method=method,
section=section,
funct=function,
order=order)
# write out the image
if clobber and os.path.isfile(ofile):
saltio.delete(ofile)
hdu.writeto(ofile)
def saltsdbloadfits(images, sdbhost, sdbname, sdbuser, password, logfile, verbose):
"""Upload data about images (which is either a fits file, or specificied by @list)
to the science data base, sdb
"""
with logging(logfile,debug) as log:
#open up the infiles
infiles = saltio.argunpack('Input',images)
sdb=saltmysql.connectdb(sdbhost,sdbname,sdbuser,password)
for infile in infiles:
sdbloadfits(infile, sdb, log, verbose)
def saltfpcalring(images,outfile, waves, method=None, thresh=5, minsize=10, niter=3, conv=0.05,
axc=None, ayc=None,
clobber=False,logfile='salt.log',verbose=True):
"""Fits rings in Fabry-Perot ring images"""
with logging(logfile,debug) as log:
# Check the input images
infiles = saltio.argunpack ('Input',images)
# if the outfile exists and not clobber, fail
saltio.overwrite(outfile,clobber)
#open the output file
fout = saltio.openascii(outfile, 'w')
#make sure that the list of waves is convertable to a numpy array
#convert to floats in case the wave is given as a string
if isinstance(waves, str):
waves=[float(x) for x in waves.split(',')]
try:
waves=np.array(waves)
except:
raise SaltError('%s is not convertable to a numpy array' % waves)
#check the value of method
method=saltio.checkfornone(method)
#setup the output file
fout.write('#Comment\n')
fout.write('# radius err xc yc z ut wave dn file\n')
# open each image and detect the ring
for img,w in zip(infiles, waves):
#open the image
hdu=saltio.openfits(img)
#measure the ring in each file
xc, yc, radius, err, z, ut=make_calring(hdu, method=method, thresh=thresh, niter=niter, conv=conv, minsize=minsize, axc=axc, ayc=ayc)
#output the results
outstr=' %7.2f %6.2f %7.2f %7.2f %6.2f %7.4f %8.3f 0 %s\n' % (radius, err, xc, yc, z, ut, w, img)
fout.write(outstr)
log.message(outstr.strip(), with_stdout=verbose, with_header=False)
fout.close()
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 specrectify(images, outimages, outpref, solfile=None, caltype='line',
function='polynomial', order=3, inttype='linear', w1=None,
w2=None, dw=None, nw=None, blank=0, conserve=False, nearest=False,
clobber=True, logfile='salt.log', verbose=True):
with logging(logfile, debug) as log:
# set up the variables
infiles = []
outfiles = []
# Check the input images
infiles = saltsafeio.argunpack('Input', images)
# create list of output files
outfiles = saltsafeio.listparse(
'Outimages',
outimages,
outpref,
infiles,
'')
# read in the wavelength solutions and enter them into
# there own format
if caltype == 'line':
soldict = entersolution(solfile)
else:
soldict = None
# read in rectify each image
for img, oimg, in zip(infiles, outfiles):
if caltype == 'line':
msg = 'Creating rectified image %s from image %s using files %s' % (
oimg, img, solfile)
else:
msg = 'Creating rectified image %s from image %s using RSS Model' % (
oimg, img)
log.message(msg)
hdu = saltsafeio.openfits(img)
hdu = rectify(hdu, soldict, caltype=caltype, function=function,
order=order, inttype=inttype, w1=w1, w2=w2, dw=dw, nw=nw,
pixscale=0.0, blank=blank, conserve=conserve, nearest=nearest,
clobber=clobber, log=log, verbose=verbose)
# write out the oimg
saltsafeio.writefits(hdu, oimg, clobber=clobber)
def saltemail(propcode, obsdate,readme,server='mail.saao.ac.za',username='', password='',
bcc='',sdbhost='sdb.saao',sdbname='sdb',sdbuser='******',
logfile='salt.log',verbose=True):
"""For a given date, look into the database for observations made on that
date. If propcode='all' send an email to all of the PIs that had data taken on that date.
If propcode gives a specific proposal, only send emails to that PI.
"""
# set up
sender = '*****@*****.**'
bcclist = bcc.split(',')
date_obss = []
propids = []
pis = []
pids = []
email = []
with logging(logfile,debug) as log:
#set up the proposal list
pids = saltio.argunpack('propcode',propcode)
#check to see if the argument is defined
saltio.argdefined('obsdate',obsdate)
# check readme file exists
saltio.fileexists(readme)
#connect to the email server
try:
smtp = smtplib.SMTP()
smtp.connect(server)
smtp.ehlo()
smtp.starttls()
smtp.ehlo()
except Exception, e:
message = 'Cannot connect to %s because %s' % (server, e)
log.error(message)
try:
smtp.login(username,password)
except Exception, e:
message = 'Cannot login to %s as %s because %s' % (server, username, e)
log.error(message)
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 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 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 slotback(images,
outfits,
extension,
imgtype='image',
subbacktype='median',
sigback=3,
mbin=7,
sorder=3,
niter=5,
ampperccd=2,
ignorexp=6,
clobber=False,
logfile='salt.log',
verbose=True):
with logging(logfile, debug) as log:
# set up the variables
order = sorder
plotfreq = 0.01
ftime = plotfreq
# is the input file specified?
infiles = saltio.argunpack('Input', images)
# is the output file specified?
saltio.filedefined('Output', outfits)
#open the first file and check its charactistics
struct = saltio.openfits(infiles[0])
# how many extensions?
nextend = saltkey.get('NEXTEND', struct[0])
if nextend < extension:
msg = 'Insufficient number of extensions in %s' % (infile)
raise SaltIOError(msg)
# how many amplifiers?
amplifiers = saltkey.get('NCCDS', struct[0])
amplifiers = int(ampperccd * float(amplifiers))
if ampperccd > 0:
nframes = nextend / amplifiers
nstep = amplifiers
else:
nframes = nextend
nstep = 1
ntotal = nframes * len(infiles)
# image size
naxis1 = saltkey.get('NAXIS1', struct[extension])
naxis2 = saltkey.get('NAXIS2', struct[extension])
# CCD binning
ccdsum = saltkey.get('CCDSUM', struct[0])
binx = int(ccdsum.split(' ')[0])
biny = int(ccdsum.split(' ')[1])
# If a total file is to written out, create it and update it
hdu = 1
# delete the file if clobber is on and the file exists
if os.path.isfile(outfits):
if clobber:
saltio.delete(outfits)
else:
raise SaltIOError(
'Output fits file ' + writenewfits +
'already exists. Use Clobber=yes to overwrite file')
# create the output file
try:
hdu = pyfits.PrimaryHDU()
hdu.header = struct[0].header
hdu.header['NCCDS'] = 1
hdu.header['NSCIEXT'] = ntotal - ignorexp
hdu.header['NEXTEND'] = ntotal - ignorexp
hduList = pyfits.HDUList(hdu)
hduList.verify()
hduList.writeto(outfits)
except:
raise SaltIOError('Could not create new fits file named ' +
writenewfits)
# read it back in for updating
hduList = saltio.openfits(outfits, mode='update')
# set up the completeness tracker
if verbose:
j = 0
x2 = float(j) / float(ntotal)
ctext = 'Percentage Complete: %3.2f' % x2
sys.stdout.write(ctext)
sys.stdout.flush()
for infile in infiles:
struct = saltio.openfits(infile)
# Skip through the frames and process each frame individually
for i in range(nframes):
if not (infile == infiles[0] and i < ignorexp):
hdu = extension + i * nstep
try:
header = struct[hdu].header
array = struct[hdu].data
array = array * 1.0
except Exception, e:
msg = 'Unable to open extension %i in image %s because %s' % (
hdu, infile, e)
raise SaltIOError(msg)
# start the analysis of each frame
# gain and readout noise
try:
gain = float(header['GAIN'])
except:
gain = 1
log.warning('Gain not specified in image header')
try:
rdnoise = float(header['RDNOISE'])
except:
rdnoise = 0
log.warning('RDNOISE not specified in image header')
# background subtraction
if not subbacktype == 'none':
try:
narray = subbackground(array, sigback, mbin, order,
niter, subbacktype)
except:
log.warning('Image ' + infile + ' extention ' +
str(i) + ' is blank, skipping')
continue
# create output array
try:
if imgtype == 'background':
oarray = narray - array
else:
oarray = narray
except:
oarray = array
# print progress
if verbose:
x2 = float(j) / float(ntotal)
if x2 > ftime:
ctext = '\b\b\b\b\b %3.2f' % x2
sys.stdout.write(ctext)
sys.stdout.flush()
ftime += plotfreq
# update the header values with the image name and extension number
try:
hdue = pyfits.ImageHDU(oarray)
hdue.header = header
hdue.header.update('ONAME', infile,
'Original image name')
hdue.header.update('OEXT', hdu,
'Original extension number')
except Exception, e:
msg='SALTPHOT--WARNING: Could not update image in newfits file for %s ext %i because %s' \
% (infile, hdu, e)
raise SaltIOError(msg)
hduList.append(hdue)
j += 1
# close FITS file
saltio.closefits(struct)
def saltclean(images,
outpath,
obslogfile=None,
gaindb=None,
xtalkfile=None,
geomfile=None,
subover=True,
trim=True,
masbias=None,
subbias=False,
median=False,
function='polynomial',
order=5,
rej_lo=3,
rej_hi=3,
niter=5,
interp='linear',
clobber=False,
logfile='salt.log',
verbose=True):
"""SALTCLEAN will provide basic CCD reductions for a set of data. It will
sort the data, and first process the biases, flats, and then the science
frames. It will record basic quality control information about each of
the steps.
"""
plotover = False
#start logging
with logging(logfile, debug) as log:
# Check the input images
infiles = saltio.argunpack('Input', images)
# create list of output files
outpath = saltio.abspath(outpath)
#does the gain database file exist
if gaindb:
dblist = saltio.readgaindb(gaindb)
else:
dblist = []
# does crosstalk coefficient data exist
if xtalkfile:
xtalkfile = xtalkfile.strip()
xdict = saltio.readxtalkcoeff(xtalkfile)
else:
xdict = None
#does the mosaic file exist--raise error if no
saltio.fileexists(geomfile)
# Delete the obslog file if it already exists
if os.path.isfile(obslogfile) and clobber: saltio.delete(obslogfile)
#read in the obsveration log or create it
if os.path.isfile(obslogfile):
msg = 'The observing log already exists. Please either delete it or run saltclean with clobber=yes'
raise SaltError(msg)
else:
headerDict = obslog(infiles, log)
obsstruct = createobslogfits(headerDict)
saltio.writefits(obsstruct, obslogfile)
#create the list of bias frames and process them
filename = obsstruct.data.field('FILENAME')
detmode = obsstruct.data.field('DETMODE')
ccdtype = obsstruct.data.field('CCDTYPE')
#set the bias list of objects
biaslist = filename[ccdtype == 'ZERO']
masterbias_dict = {}
for img in infiles:
if os.path.basename(img) in biaslist:
#open the image
struct = fits.open(img)
bimg = outpath + 'bxgp' + os.path.basename(img)
#print the message
if log:
message = 'Processing Zero frame %s' % img
log.message(message, with_stdout=verbose)
#process the image
struct = clean(struct,
createvar=False,
badpixelstruct=None,
mult=True,
dblist=dblist,
xdict=xdict,
subover=subover,
trim=trim,
subbias=False,
bstruct=None,
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], 'SPREPARE',
'Images have been prepared', hist)
saltkey.new('SGAIN', time.asctime(time.localtime()),
'Images have been gain corrected', struct[0])
saltkey.new('SXTALK', time.asctime(time.localtime()),
'Images have been xtalk corrected', struct[0])
saltkey.new('SBIAS', time.asctime(time.localtime()),
'Images have been de-biased', struct[0])
# write FITS file
saltio.writefits(struct, bimg, clobber=clobber)
saltio.closefits(struct)
#add files to the master bias list
masterbias_dict = compareimages(struct,
bimg,
masterbias_dict,
keylist=biasheader_list)
#create the master bias frame
for i in masterbias_dict.keys():
bkeys = masterbias_dict[i][0]
blist = masterbias_dict[i][1:]
mbiasname = outpath + createmasterbiasname(blist, bkeys)
bfiles = ','.join(blist)
saltcombine(bfiles, mbiasname, method='median', reject='sigclip', mask=False,
weight=False, blank=0, scale=None, statsec=None, lthresh=3, \
hthresh=3, clobber=False, logfile=logfile,verbose=verbose)
#create the list of flatfields and process them
flatlist = filename[ccdtype == 'FLAT']
masterflat_dict = {}
for img in infiles:
if os.path.basename(img) in flatlist:
#open the image
struct = fits.open(img)
fimg = outpath + 'bxgp' + os.path.basename(img)
#print the message
if log:
message = 'Processing Flat frame %s' % img
log.message(message, with_stdout=verbose)
#process the image
struct = clean(struct,
createvar=False,
badpixelstruct=None,
mult=True,
dblist=dblist,
xdict=xdict,
subover=subover,
trim=trim,
subbias=False,
bstruct=None,
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], 'SPREPARE',
'Images have been prepared', hist)
saltkey.new('SGAIN', time.asctime(time.localtime()),
'Images have been gain corrected', struct[0])
saltkey.new('SXTALK', time.asctime(time.localtime()),
'Images have been xtalk corrected', struct[0])
saltkey.new('SBIAS', time.asctime(time.localtime()),
'Images have been de-biased', struct[0])
# write FITS file
saltio.writefits(struct, fimg, clobber=clobber)
saltio.closefits(struct)
#add files to the master bias list
masterflat_dict = compareimages(struct,
fimg,
masterflat_dict,
keylist=flatheader_list)
#create the master flat frame
for i in masterflat_dict.keys():
fkeys = masterflat_dict[i][0]
flist = masterflat_dict[i][1:]
mflatname = outpath + createmasterflatname(flist, fkeys)
ffiles = ','.join(flist)
saltcombine(ffiles, mflatname, method='median', reject='sigclip', mask=False,
weight=False, blank=0, scale=None, statsec=None, lthresh=3, \
hthresh=3, clobber=False, logfile=logfile,verbose=verbose)
#process the science data
for img in infiles:
nimg = os.path.basename(img)
#print nimg, nimg in flatlist, nimg in biaslist
if not (nimg in biaslist):
#open the image
struct = fits.open(img)
simg = outpath + 'bxgp' + os.path.basename(img)
#print the message
if log:
message = 'Processing science frame %s' % img
log.message(message, with_stdout=verbose)
#process the image
struct = clean(struct,
createvar=False,
badpixelstruct=None,
mult=True,
dblist=dblist,
xdict=xdict,
subover=subover,
trim=trim,
subbias=False,
bstruct=None,
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], 'SPREPARE',
'Images have been prepared', hist)
saltkey.new('SGAIN', time.asctime(time.localtime()),
'Images have been gain corrected', struct[0])
saltkey.new('SXTALK', time.asctime(time.localtime()),
'Images have been xtalk corrected', struct[0])
saltkey.new('SBIAS', time.asctime(time.localtime()),
'Images have been de-biased', struct[0])
# write FITS file
saltio.writefits(struct, simg, clobber=clobber)
saltio.closefits(struct)
#mosaic the files--currently not in the proper format--will update when it is
if not saltkey.fastmode(saltkey.get('DETMODE', struct[0])):
mimg = outpath + 'mbxgp' + os.path.basename(img)
saltmosaic(images=simg,
outimages=mimg,
outpref='',
geomfile=geomfile,
interp=interp,
cleanup=True,
clobber=clobber,
logfile=logfile,
verbose=verbose)
#remove the intermediate steps
saltio.delete(simg)
def specarcstraighten(images, outfile, function='poly', order=3, rstep=1,
rstart='middlerow', nrows=1,
y1=None, y2=None, sigma=5, sections=3, niter=5,
startext=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.argunpack('Output', outfile)
# Identify the lines in each file
for img, ofile in zip(infiles, outfiles):
# open the image
hdu = saltio.openfits(img)
# get the basic information about the spectrograph
dateobs = saltkey.get('DATE-OBS', hdu[0])
try:
utctime = saltkey.get('UTC-OBS', hdu[0])
except SaltError:
utctime = saltkey.get('TIME-OBS', hdu[0])
instrume = saltkey.get('INSTRUME', hdu[0]).strip()
grating = saltkey.get('GRATING', hdu[0]).strip()
grang = saltkey.get('GR-ANGLE', hdu[0])
grasteps = saltkey.get('GRTILT', hdu[0])
arang = saltkey.get('AR-ANGLE', hdu[0])
arsteps = saltkey.get('CAMANG', hdu[0])
rssfilter = saltkey.get('FILTER', hdu[0])
specmode = saltkey.get('OBSMODE', hdu[0])
masktype = saltkey.get('MASKTYP', hdu[0]).strip().upper()
slitname = saltkey.get('MASKID', hdu[0])
xbin, ybin = saltkey.ccdbin(hdu[0], img)
for i in range(startext, len(hdu)):
if hdu[i].name == 'SCI':
log.message('Proccessing extension %i in %s' % (i, img))
# things that will change for each slit
if masktype == 'LONGSLIT':
slit = st.getslitsize(slitname)
objid = None
#elif masktype == 'MOS':
#slit = 1.5
# slit=saltkey.get('SLIT', hdu[i])
# set up the x and y positions
#miny = hdu[i].header['MINY']
#maxy = hdu[i].header['MAXY']
#ras = hdu[i].header['SLIT_RA']
#des = hdu[i].header['SLIT_DEC']
#objid = hdu[i].header['SLITNAME']
# Check the perfomance of masks at different PA
#rac = hdu[0].header['MASK_RA']
#dec = hdu[0].header['MASK_DEC']
#pac = hdu[0].header['PA']
else:
msg = '%s is not a currently supported masktype' % masktype
raise SALTSpecError(msg)
if instrume not in ['PFIS', 'RSS']:
msg = '%s is not a currently supported instrument' % instrume
raise SALTSpecError(msg)
# set up the data for the source
try:
data = hdu[i].data
except Exception as e:
message = 'Unable to read in data array in %s because %s' % (
img, e)
raise SALTSpecError(message)
# set up the center row
if rstart == 'middlerow':
ystart = int(0.5 * len(data))
else:
ystart = rstart
# set up the xarr array based on the image
xarr = np.arange(len(data[ystart]), dtype='int64')
# calculate the transformation
ImageSolution = arcstraight(data, xarr, ystart, function=function, order=order,
rstep=rstep, y1=y1, y2=y2, sigma=sigma, sections=sections,
niter=niter, log=log, verbose=verbose)
if outfile and len(ImageSolution):
writeIS(ImageSolution, outfile, dateobs=dateobs, utctime=utctime, instrume=instrume,
grating=grating, grang=grang, grasteps=grasteps, arsteps=arsteps,
arang=arang, rfilter=rssfilter, slit=slit, xbin=xbin,
ybin=ybin, objid=objid,
filename=img, log=log, verbose=verbose)
def specslitnormalize(images,
outimages,
outpref,
response=None,
response_output=None,
order=2,
conv=1e-2,
niter=20,
startext=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, '')
# read in the response function
response = saltio.checkfornone(response)
if response:
log.message('Loading response from %s' % response)
response = readresponse(response)
# Identify the lines in each file
for img, ofile in zip(infiles, outfiles):
# open the image
hdu = saltio.openfits(img)
for i in range(startext, len(hdu)):
if hdu[i].name == 'SCI':
log.message('Normalizing extension %i in %s' % (i, img))
# things that will change for each slit
# set up the data for the source
try:
data = hdu[i].data
except Exception as e:
message = \
'Unable to read in data array in %s because %s' % \
(img, e)
raise SALTSpecError(message)
if response is None:
response = create_response(data,
spatial_axis=1,
order=order,
conv=conv,
niter=niter)
if response_output:
write_response(response, clobber=clobber)
else:
# add a check that the response is the same shape as
# the data
if len(response) != data.shape[0]:
raise SALTSpecError(
'Length of response function does not equal size of image array'
)
# correct the data
data = data / response
# correct the variance frame
if saltkey.found('VAREXT', hdu[i]):
vhdu = saltkey.get('VAREXT', hdu[i])
hdu[vhdu].data = hdu[vhdu].data / response
saltio.writefits(hdu, ofile, clobber=clobber)
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 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 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 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()
