def identify(arc_fn, arc_lamp, mods_channel, data_path='.', params={}):
"""
Run iraf identify to find and label lines in arc lamp for
wavelength solution. This one needs to be done by hand :(
Parameters
----------
arc_fn : str
The arc lamp fits file name
arc_lamp : str
The arc lamp
mods_channel : str
MODS red or blue channel
data_path : str
Directory that contains the data.
params : dict
Iraf identify parameters
"""
_check_working_dir(data_path)
line_list = os.path.join(
calipath, 'line_lists/{}_{}.wav'.format(arc_lamp, mods_channel))
logger.info('running iraf identify')
iraf.identify.unlearn()
iraf.identify.units = 'angstrom'
iraf.identify.nsum = params.pop('nsum', 30)
iraf.identify.function = params.pop('function', 'chebyshev')
iraf.identify.order = params.pop('order', 4)
iraf.identify.cradius = params.pop('cradius', 5)
iraf.identify.database = params.pop('database', 'database')
iraf.identify(images=arc_fn, coordlist=line_list)
def identify():
iraf.twodspec()
iraf.longslit()
iraf.identify(images='Lamp.fits',
section='middle column',
database='database',
coordlist=cdherb_file,
nsum=10,
match=-3.0,
maxfeatures=50,
zwidth=100.0,
ftype='emission',
fwidth=20.0,
cradius=7.0,
threshold=0.0,
minsep=2.0,
function='chebyshev',
order=6,
sample='*',
niterate=0,
low_reject=3.0,
high_reject=3.0,
grow=0.0,
autowrite='no')
iraf.flpr()
def rssidentify(self, arc):
if not os.path.exists('database'): os.system('mkdir database')
rt.loadparam(self.rssconfig, ['iraf.identify', 'iraf.reidentify', 'iraf.fitcoords'])
coordfile = self.linelist_dir+arc.linelist
while not os.path.exists(coordfile):
print("***** rssidentify error *** The coordinate "+str(coordfile)+" IS NOT in our directory *****")
coordfile = raw_input('Enter a correct path for coordinate files: ')
arc.coordfile = coordfile
copy2(coordfile, './')
# check if the setup has been already identified before
if os.path.isfile(self.rssdatadir+"/database/id"+arc.idname) and \
os.path.isfile(self.rssdatadir+"/"+arc.idfits):
copy2(self.rssdatadir+"/database/id"+arc.idname, 'database/')
copy2(self.rssdatadir+"/"+arc.idfits,'./')
else:
copy2(arc.name, arc.idfits)
rt.rsswave(arc.idfits)
iraf.identify(arc.idname, coordlist=coordfile, mode='h')
iraf.reidentify(arc.idname, arc.idname, coordlist=coordfile, mode='h')
iraf.fitcoord(arc.idname, mode='h')
copy2(arc.idfits, self.rssdatadir+'/'+arc.idfits)
copy2('database/id'+arc.idname, self.rssdatadir+'/database/id'+arc.idname)
copy2('database/fc'+arc.idname, self.rssdatadir+'/database/fc'+arc.idname)
print("***** Reducing of ARCs *****")
if not os.path.isfile("database/id"+arc.noext) or not os.path.isfile("database/fc"+arc.noext):
iraf.reidentify(arc.idname, arc.noext, coordlist=coordfile, mode='h')
iraf.reidentify(arc.noext, arc.noext, coordlist=coordfile, mode='h')
iraf.fitcoord(arc.noext, mode='h')
def wal(lstfile):
iraf.noao()
iraf.twodspec()
iraf.longslit()
iraf.identify(images = 'Lamp'
, section = 'middle column', database = 'database'
, coordlist = 'linelists$idhenear.dat', units = '', nsum = 10
, match = -3.0, maxfeatures = 50, zwidth = 100.0
, ftype = 'emission', fwidth = 20.0, cradius = 5.0
, threshold = 0.0, minsep = 2.0, function = 'chebyshev'
, order = 6, sample = '*', niterate = 0
, low_reject = 3.0, high_reject = 3.0, grow = 0.0
, autowrite = False, graphics = 'stdgraph', cursor = ''
, crval = '', cdelt = '')
iraf.reidentify(reference = 'Lamp'
, images = 'Lamp', interactive = 'no', section = 'column'
, newaps = True, override = True, refit = True, trace = False
, step = 10, nsum = 10, shift = 0.0, search = 0.0, nlost = 5
, cradius = 7.0, threshold = 0.0, addfeatures = False
, coordlist = 'linelists$idhenear.dat', match = -3.0, maxfeatures = 50
, minsep = 2.0, database = 'database', logfiles = 'logfile'
, plotfile = '', verbose = False, graphics = 'stdgraph', cursor = ''
, answer = 'yes', crval = '', cdelt = '', mode = 'al')
iraf.fitcoords(images = 'Lamp'
, fitname = 'Lamp', interactive = True, combine = False, database = 'database'
, deletions = 'deletions.db', function = 'chebyshev', xorder = 6
, yorder = 6, logfiles = 'STDOUT,logfile', plotfile = 'plotfile'
, graphics = 'stdgraph', cursor = '', mode = 'al')
iraf.longslit(dispaxis = 2)
iraf.transform(input = '%ftbo%ftbo%@' + lstfile
, output = '%wftbo%wftbo%@' + lstfile, minput = '', moutput = ''
, fitnames = 'LampLamp', database = 'database', interptype = 'spline3'
, flux = True)
def make_lambda_solution(arc_list,fcnamedict):
irf_prm.set_identify_calibration(iraf.identify)
irf_prm.set_reidentify_calibration(iraf.reidentify)
irf_prm.set_fitcoords_calibration(iraf.fitcoords)
for arc in arc_list:
iraf.identify(images=arc)
iraf.reidentify(reference=arc,images=arc)
iraf.fitcoords(images=arc[:-5],fitname=fcnamedict[arc])
return
def ident():
lexlist = glob.glob('LAMP*EX.fits')
linelist = 'Lines_HgCdHeNeAr600.dat'
width = 10.0
radius = 15.0
idref = lexlist[0].rsplit('.fits',1)[0]
iraf.identify(idref,coordlist=linelist,fwidth=width,cradius=radius)
lexlist = lexlist[1:]
for img in lexlist:
iraf.reidentify(idref,img,cradius=radius)
return idref
def reference_arc(image, output, reference,
coordlist='home$linelists/licklinelist.dat'):
'''Construct reference wavelength solution from arc lamps'''
iraf.apall(image, output=output, references=reference, interactive=no,
find=no, recenter=no, resize=no, edit=no, trace=no, fittrace=no,
extract=yes, extras=yes, review=no, background='none')
iraf.identify(output, coordlist=coordlist)
return
def wavelength_calibration(targetdir):
"""
Does wavelength calibration.
Writes every fit to database so make sure it's using the correct one.
This needs to be run in object directory for database
"""
print 'Target directory is ' + targetdir
print 'Doing wavelength calibration...'
if os.getcwd() != targetdir:
print 'Warning: current working directory must be target directory!'
return None
iraf.noao(_doprint=0)
iraf.onedspec(_doprint=0)
iraf.unlearn('identify')
iraf.identify.setParam('images','aimcomb.fits')
iraf.identify.setParam('coordli','/home/lc585/Dropbox/IoA/WHT_Proposal_2015a/argon+xenon.dat')
iraf.identify.setParam('niterat',1)
iraf.identify.setParam('function','spline3')
iraf.identify.setParam('order',3)
iraf.identify.setParam('zwidth',200.0) # Zoom graph width in user units
iraf.identify.setParam('database','database')
iraf.identify()
# Update fits header
print '\n' '\n' '\n'
print 'Updating fits header...'
iraf.hedit.setParam('images','imcomb.ms.fits')
iraf.hedit.setParam('fields','REFSPEC1')
iraf.hedit.setParam('value','aimcomb.fits') # should be wavelength calibrated?
iraf.hedit.setParam('add','yes')
iraf.hedit.setParam('verify','yes')
iraf.hedit.setParam('show','yes')
iraf.hedit()
return None
def standard_trace(standard_list,supplement_list,outname='star'):
irf_prm.set_identify_standard(iraf.identify)
irf_prm.set_reidentify_standard(iraf.reidentify)
irf_prm.set_fitcoords_standard(iraf.fitcoords)
all_standards = ''
for standrd in standard_list:
iraf.identify(images=standrd)
iraf.reidentify(reference=standrd,images=standrd)
all_standards += standrd[:-5]+','
for supplement in supplement_list:
iraf.identify(images=supplement)
iraf.reidentify(reference=supplement,images=supplement)
all_standards += supplement[:-5]+','
iraf.fitcoords(images=all_standards,fitname=outname)
return
def identify_gap(infile, overwrite=False):
print('\n#############################')
print('Identifying the spectrum gaps.')
database = 'database'
idfile = database + '/id' + os.path.splitext(infile)[0]
if os.path.exists(idfile):
if overwrite:
try:
os.remove(idfile)
except:
pass
else:
print('\t ID file already exists: '+idfile)
print('\t This precedure is skipped.')
return
# Checking version consistency
if not fi.check_version_f(infile):
return
# Not to display items in IRAF packages
sys.stdout = open('/dev/null', 'w')
iraf.noao()
iraf.twodspec()
iraf.longslit()
sys.stdout = sys.__stdout__ # Back to the stadard output
binfct1 = fits.getval(infile, 'BIN-FCT1')
coordlist = fi.filibdir+'pseudoslitgap_binx'+str(binfct1)+'.dat'
iraf.identify(infile, section='middle line', database=database, \
coordlist=coordlist, units='', nsum=20,\
match=-15., ftype='absorption', fwidth=16./binfct1, \
cradius=5.,\
threshold=0., function='chebyshev', order=2, sample='*', \
niter=0, autowrite='no')
iraf.reidentify(infile, infile, interac='no', nsum=50, \
section='middle line', newaps='no', override='no',\
refit='yes', trace='yes', step=100, shift=0,\
nlost=20, cradius=5., threshold=0., addfeatures='no',\
coordlist=coordlist, match=-3., \
database=database, logfile='identify_gap.log', plotfile='', \
verbose='yes', cursor='')
return
def get_wl_identy(filename, coordlistname):
iraf.onedspec()
print 'run get_wl_identy identify...'
print 'the input file is ' + filename
print 'implot %s' % filename
iraf.implot(image = filename)
print 'run identify...'
iraf.identify(images = filename
, section = 'middle line', database = 'database'
, coordlist = coordlistname, units = '', nsum = 10
, match = -3.0, maxfeatures = 50, zwidth = 100.0
, ftype = 'emission', fwidth = 18.0, cradius = 5.0
, threshold = 0.0, minsep = 2.0, function = 'spline3'
, order = 1, sample = '*', niterate = 0
, low_reject = 3.0, high_reject = 3.0, grow = 0.0
, autowrite = False, graphics = 'stdgraph', cursor = ''
, crval = '', cdelt = '')
def identify_each(inname, database='database', \
coordlist=fi.filibdir+'thar.300.dat', \
section_x=50, \
overwrite=False):
# Not to display items in IRAF packages
sys.stdout = open('/dev/null', 'w')
iraf.noao()
iraf.twodspec()
iraf.longslit()
sys.stdout = sys.__stdout__ # Back to the stadard output
idfile = database + '/id' + inname
if os.path.isfile(idfile) and overwrite == False:
print('ID file already exists. '+idfile)
else:
if os.path.isfile(idfile) and overwrite == True:
print('Removing ' + idfile)
try:
os.remove(idfile)
except:
pass
# Creating the "section" parameter
section = 'y '+str(section_x)
iraf.identify(inname, section=section,
database=database, coordlist=coordlist, units='',
nsum=nsum, match=match, ftype='emission', fwidth=fwidth,
cradius=cradius, threshold=threshold,
function='chebyshev', order=order, sample='*',
niter=niter, autowrite=autowrite, cursor='')
iraf.reidentify(inname, inname,
interac='no', section=section, newaps=newaps,
override=override, refit=refit, trace=trace,
step=step, shift=0, nlost=nlost, cradius=cradius,
threshold=threshold, addfeatures=addfeatures,
coordlist=coordlist, match=match, database=database,
logfile=logfile, plotfile='', verbose=verbose,
cursor='')
return
def reference_arc(image,
output,
reference,
coordlist='home$linelists/licklinelist.dat'):
'''Construct reference wavelength solution from arc lamps'''
iraf.apall(image,
output=output,
references=reference,
interactive=no,
find=no,
recenter=no,
resize=no,
edit=no,
trace=no,
fittrace=no,
extract=yes,
extras=yes,
review=no,
background='none')
iraf.identify(output, coordlist=coordlist)
return
def identify(imlist_name):
"""
identify arc image for wavelength calibration.
image section "column" is good.
fitting function : "chebyshev", "legendre", "spline1", or "spline3"
"""
import glob
import os, sys
from pyraf import iraf
iraf.noao()
iraf.imred()
iraf.kpnoslit()
imlist = glob.glob(imlist_name)
imlist.sort()
for i in range(len(imlist)):
inim = imlist[i]
print('Identification ongoing...')
iraf.identify(images=inim,
section='middle column',
function='chebyshev',
order=15,
niterate=20,
low_reject=3,
high_reject=3)
def identify_edge(infile, overwrite=False):
print('\n#############################')
print('Identifying the edges.')
binfct1 = fits.getval(infile, 'BIN-FCT1')
coordlist = fi.filibdir + 'edge' + str(binfct1) + '.dat'
section = 'middle line'
verbose = 'yes'
nsum = 50
match = -10.
fwidth = 6. / binfct1
cradius = 20. / binfct1
threshold = 0.
function = 'chebyshev'
order = 2
niter = 0
autowrite = 'yes'
newaps = 'yes'
override = 'yes'
refit = 'no'
trace = 'yes'
step = 50
shift = 0
nlost = 0
minsep = 60. / binfct1
addfeatures = 'no'
database = 'database'
logfile = 'identify_edge.log'
# Not to display items in IRAF packages
sys.stdout = open('/dev/null', 'w')
iraf.noao()
iraf.twodspec()
iraf.longslit()
sys.stdout = sys.__stdout__ # Back to the stadard output
# entering the channel image directory.
# os.chdir() does not change the directory for pyraf only in this function.
print('\t Entering the channel image directory, \"' + fi.chimagedir +
'\".')
iraf.cd(fi.chimagedir)
basename = fits.getval('../' + infile, 'FRAMEID')
idfile = database + '/id' + basename + '.ch01edge'
if os.path.isfile(idfile) and not overwrite:
print('\t Edge identification files already exist, ' + idfile \
+ '. Skipping.')
else:
if os.path.isfile(idfile) and overwrite:
print('\t Removing ' + idfile)
try:
os.remove(idfile)
except:
pass
print('\t Identifying: ' + basename + '.ch01edge.fits')
iraf.identify(basename + '.ch01edge',
section=section,
database=database,
coordlist=coordlist,
units='',
nsum=nsum,
match=match,
maxfeat=2,
ftype='emission',
fwidth=fwidth,
cradius=cradius,
threshold=threshold,
function=function,
order=order,
sample='*',
niter=niter,
autowrite=autowrite)
print('\t Reidentifying: ' + basename + '.ch01edge.fits')
iraf.reidentify(basename + '.ch01edge',
basename + '.ch01edge',
interac='no',
section=section,
newaps=newaps,
override=override,
refit=refit,
trace=trace,
step=step,
nsum=nsum,
shift=shift,
nlost=nlost,
cradius=cradius,
threshold=threshold,
addfeatures=addfeatures,
coordlist=coordlist,
match=match,
maxfeat=2,
minsep=minsep,
database=database,
logfile=logfile,
plotfile='',
verbose=verbose,
cursor='')
for i in range(2, 25):
print('\t Reidentifying: ' + basename + '.ch%02dedge.fits' % i)
idfile = database + '/id' + basename + '.ch%02dedge' % i
if os.path.isfile(idfile) and not overwrite:
print('\t Edge identification files already exist, ' + idfile +
'. Skipping.')
else:
if os.path.isfile(idfile) and overwrite:
print('\t Removing ' + idfile)
try:
os.remove(idfile)
except:
pass
# treatment for VPH650
if i == 12:
disperser = fits.getval(basename + '.ch12edge.fits',
'DISPERSR')
if disperser == 'SCFCGRHD65':
nlost = 1
if i == 13:
disperser = fits.getval(basename + '.ch12edge.fits',
'DISPERSR')
if disperser == 'SCFCGRHD65':
nlost = 0
iraf.reidentify(basename+'.ch%02dedge'%(i-1), \
basename+'.ch%02dedge'%i, \
interac='no', section=section, newaps=newaps, \
override=override, refit=refit, trace=trace, \
step=0.0, nsum=nsum, shift=shift, nlost=nlost, \
cradius=cradius, threshold=threshold, \
addfeatures=addfeatures, coordlist=coordlist, \
match=match, maxfeat=2, minsep=minsep, \
database=database, logfile=logfile, \
plotfile='', verbose=verbose, cursor='')
#Check the result
iraf.identify(basename+'.ch%02dedge'%i, section=section, \
database=database, coordlist=coordlist, units='', \
nsum=nsum, match=match, maxfeat=2,ftype='emission', \
fwidth=fwidth, cradius=cradius, threshold=threshold, \
function=function, order=order, sample='*', \
niter=niter, autowrite=autowrite)
iraf.reidentify(basename+'.ch%02dedge'%i, \
basename+'.ch%02dedge'%i, \
interac='no', section=section, newaps=newaps, \
override=override, refit=refit, trace=trace, \
step=step, nsum=nsum, shift=shift, nlost=nlost, \
cradius=cradius, threshold=threshold, \
addfeatures=addfeatures, coordlist=coordlist, \
match=match, maxfeat=2, minsep=minsep, \
database=database, logfile=logfile, \
plotfile='', verbose=verbose, cursor='')
print('\t Go back to the original directory.')
iraf.cd('..')
disperser = fits.getval(fi.chimagedir + basename + '.ch12edge.fits',
'DISPERSR')
if disperser == 'SCFCGRHD65':
correct_ch12_edge(basename, overwrite=overwrite)
return
print("Starting the identify task")
iraf.identify(images="FeAr_250_3500_4_Grism_7_2015_06_17_yf170019bap.fits",
section="middle line",
database="database",
coordlist="/home/aries/Music/Atsoa2018/fear_new.dat",
units="",
nsum="10",
match=10.,
maxfeatures=50,
zwidth=100.,
ftype="emission",
fwidth=4.,
cradius=5.,
threshold=0.,
minsep=2.,
function="spline3",
order=1,
sample="*",
niterate=0,
low_reject=3.,
high_reject=3.,
grow=0.,
autowrite="no",
graphics="stdgraph",
cursor="",
crval="",
cdelt="",
aidpars="")
print('header editing')
# Run the spectral extraction program.
iraf.apextract.setParam("dispaxis", "1")
iraf.apall(input=filename,
find="No",
recenter="No",
resize="No",
interactive="Yes")
# Make sure that the dispersion axis is in the header.
iraf.hedit(images=[filename], fields=["DISPAXIS"], value=["1"], add="Yes")
iraf.identify(filename[:-5],
coordli=home + "/Downloads/HgNe(1).dat",
section="line 105 125",
crval=crval,
cdelt=dispersion,
fwidth=5)
# Tell the extracted spectrum what the wavelength solutions are.
iraf.hedit(images=[extracted_filename],
fields=["REFSPEC1"], \
value=[filename], add="Yes")
iraf.refspec(input=extracted_filename,
referen=filename[:-5],
sort='',
group='',
confirm='no')
iraf.dispcor(input=extracted_filename, output=calibrated_filename)
# Plot the extracted spectrum?
print('\n' + 'Extracting arc file')
iraf.apall(input=arcfile,
output='arc.ms',
apertur=1,
interac='yes',
find='yes',
nfind=1,
recente='yes',
resize='yes',
background='none')
## identify lines
print('\n' + 'Identify arc lines')
iraf.identify(images='arc.ms',
coordlist='Xe.txt',
function='spline3',
order=3,
maxfeatures=10)
if extract_spectra != 'n':
### apall on spectrum
for n in final:
### Remove previous extractions
if os.path.exists(n + '.ms.fits') == True:
print('Removing', n + '.ms.fits')
os.remove(n + '.ms.fits')
if os.path.exists(n + '.w.fits') == True:
print('Removing', n + '.w.fits')
os.remove(n + '.w.fits')
def wal(lstfile, lampname):
iraf.noao()
iraf.twodspec()
iraf.longslit()
# iraf.identify(images = 'Lamp.fits', section = 'middle column',
# database = 'database', coordlist = 'linelists$idhenear.dat',
# nsum = 10, match = -3.0, maxfeatures = 50, zwidth = 100.0,
# ftype = 'emission', fwidth = 20.0, cradius = 7.0, threshold = 0.0,
# minsep = 2.0, function = 'chebyshev', order = 6, sample = '*',
# niterate = 0, low_reject = 3.0, high_reject = 3.0, grow = 0.0,
# autowrite = 'no')
# iraf.reidentify(reference = 'Lamp', images = 'Lamp', interactive = 'no',
# section = 'column', newaps = 'yes', override = 'yes', refit = 'yes',
# trace = 'no', step = 10, nsum = 10, shift = 0.0, search = 0.0,
# nlost = 5, cradius = 7.0, threshold = 0.0, addfeatures = 'no',
# coordlist = 'linelists$idhenear.dat', match = -3.0,
# maxfeatures = 50, minsep = 2.0, database = 'database')
iraf.identify(images=lampname,
section='middle column',
database='database',
coordlist='linelists$idhenear.dat',
units='',
nsum=10,
match=-3.0,
maxfeatures=50,
zwidth=100.0,
ftype='emission',
fwidth=20.0,
cradius=7.0,
threshold=0.0,
minsep=2.0,
function='chebyshev',
order=6,
sample='*',
niterate=0,
low_reject=3.0,
high_reject=3.0,
grow=0.0,
autowrite=False,
graphics='stdgraph',
cursor='',
crval='',
cdelt='')
iraf.reidentify(reference=lampname,
images=lampname,
interactive='no',
section='column',
newaps=True,
override=True,
refit=True,
trace=False,
step=10,
nsum=10,
shift=0.0,
search=0.0,
nlost=5,
cradius=7.0,
threshold=0.0,
addfeatures=False,
coordlist='linelists$idhenear.dat',
match=-3.0,
maxfeatures=50,
minsep=2.0,
database='database',
logfiles='logfile',
plotfile='',
verbose=False,
graphics='stdgraph',
cursor='',
answer='yes',
crval='',
cdelt='',
mode='al')
iraf.fitcoords(images=lampname,
fitname=lampname,
interactive=True,
combine=False,
database='database',
deletions='deletions.db',
function='chebyshev',
xorder=6,
yorder=6,
logfiles='STDOUT,logfile',
plotfile='plotfile',
graphics='stdgraph',
cursor='',
mode='al')
iraf.longslit(dispaxis=2)
iraf.transform(input='%ftbo%ftbo%@' + lstfile,
output='%wftbo%wftbo%@' + lstfile,
minput='',
moutput='',
fitnames=lampname + lampname,
database='database',
interptype='spline3',
flux=True)
if writefiles:
pyfits.writeto(redfn,
np.tile(arcspec, (4, 1, 1)).astype(np.float32),
archeader,
clobber=clobber)
if wavecal:
os.chdir(_proc)
iraf.chdir(_proc)
loc_redfn = os.path.split(redfn)[1]
if waveCalRef is None:
iraf.identify(loc_redfn,
database=_wldat,
ftype='emission',
fwidth=3,
order=2,
niterate=3,
cradius=3,
coordlist=lamp_list,
function='spline3')
waveCalRef = '' + loc_redfn
else:
iraf.reidentify(waveCalRef,
loc_redfn,
interactive='no',
override='yes',
refit='yes',
nlost=1,
cradius=10,
addfeatures='no',
coordlist=lamp_list
def extractSpectra():
"""
Extract 1D spectra using IRAF interactively
Interpolate across the two arcs either side to
get the most accurate wavelength solution
TODO: Finish docstring
Add method of using super arc for inital
identify
"""
# load IRAF from the location of the login.cl file
here = os.getcwd()
os.chdir(loginCl_location)
from pyraf import iraf
os.chdir(here)
time.sleep(2)
# make a list of the science images to be analysed
templist = g.glob('i_s*')
# import IRAF packages for spectroscopy
iraf.imred(_doprint=0)
iraf.kpnoslit(_doprint=0)
# apall parameters
iraf.apall.setParam('format', 'multispec')
iraf.apall.setParam('interac', 'yes')
iraf.apall.setParam('find', 'yes')
iraf.apall.setParam('recen', 'yes')
iraf.apall.setParam('resize', 'yes')
iraf.apall.setParam('trace', 'yes')
iraf.apall.setParam('fittrac', 'yes')
iraf.apall.setParam('extract', 'yes')
iraf.apall.setParam('extras', 'yes')
iraf.apall.setParam('review', 'yes')
iraf.apall.setParam('line', 'INDEF')
iraf.apall.setParam('nsum', '12')
iraf.apall.setParam('lower', '-6')
iraf.apall.setParam('upper', '6')
iraf.apall.setParam('b_funct', 'chebyshev')
iraf.apall.setParam('b_order', '1')
iraf.apall.setParam('b_sampl', '-25:-15,15:25')
iraf.apall.setParam('b_naver', '-100')
iraf.apall.setParam('b_niter', '0')
iraf.apall.setParam('b_low_r', '3')
iraf.apall.setParam('b_high', '3')
iraf.apall.setParam('b_grow', '0')
iraf.apall.setParam('width', '10')
iraf.apall.setParam('radius', '10')
iraf.apall.setParam('threshold', '0')
iraf.apall.setParam('nfind', '1')
iraf.apall.setParam('t_nsum', '10')
iraf.apall.setParam('t_step', '10')
iraf.apall.setParam('t_nlost', '3')
iraf.apall.setParam('t_niter', '7')
iraf.apall.setParam('t_funct', 'spline3')
iraf.apall.setParam('t_order', '3')
iraf.apall.setParam('backgro', 'fit')
iraf.apall.setParam('skybox', '1')
iraf.apall.setParam('weights', 'variance')
iraf.apall.setParam('pfit', 'fit1d')
iraf.apall.setParam('clean', 'yes')
iraf.apall.setParam('saturat', SATURATION)
iraf.apall.setParam('readnoi', RDNOISE)
iraf.apall.setParam('gain', GAIN)
iraf.apall.setParam('lsigma', '4.0')
iraf.apall.setParam('usigma', '4.0')
iraf.apall.setParam('nsubaps', '1')
iraf.apall.saveParList(filename="apall.pars")
# make reference arc for reidentify
if '.' in args.refarc:
args.refarc = args.refarc.split('.')[0]
refarc = "a_s_{}_t.fits".format(args.refarc)
refarc_out = "a_s_{}_t.ms.fits".format(args.refarc)
# loop over all the the spectra
for i in range(0, len(templist)):
hdulist = fits.open(templist[i])
prihdr = hdulist[0].header
target_id = prihdr['CAT-NAME']
spectrum_id = int(templist[i].split('_')[2].split('r')[1])
if args.ds9:
os.system('xpaset fuckingds9 fits < {}'.format(templist[i]))
# extract the object spectrum
print("[{}/{}] Extracting spectrum of {} from image {}".format(i+1, len(templist), target_id, templist[i]))
print("[{}/{}] Check aperture and background. Change if required".format(i+1, len(templist)))
print("[{}/{}] AP: m = mark aperture, d = delete aperture".format(i+1, len(templist)))
print("[{}/{}] SKY: s = mark sky, t = delete sky, f = refit".format(i+1, len(templist)))
print("[{}/{}] q = continue".format(i+1, len(templist)))
iraf.apall(input=templist[i])
print("Spectrum extracted!")
# find the arcs either side of the object
arclist = []
arc1 = "a_s_r{0:d}_t.fits".format(spectrum_id-1)
arc2 = "a_s_r{0:d}_t.fits".format(spectrum_id+1)
arc1_out = "a_s_r{0:d}_t.ms.fits".format(spectrum_id-1)
arc2_out = "a_s_r{0:d}_t.ms.fits".format(spectrum_id+1)
# predict the arc names
print("\nPredicting arcs names...")
print("Arc1: {}".format(arc1))
print("Arc2: {}".format(arc2))
# setup a reference filename for the arc conditions in database
reffile = templist[i].split('.fits')[0]
# extract the arcs
print("\nExtracting arcs under the same conditions...")
if os.path.exists(arc1):
iraf.apall(input=arc1,
reference=reffile,
recente="no",
trace="no",
backgro="no",
interac="no")
print("Arc1 {} extracted".format(arc1))
arclist.append(arc1_out)
else:
print("\n\nArc1 {} FILE NOT FOUND\n\n".format(arc1))
if os.path.exists(arc2):
iraf.apall(input=arc2,
reference=reffile,
recente="no",
trace="no",
backgro="no",
interac="no")
print("Arc2 {} extracted".format(arc2))
arclist.append(arc2_out)
else:
print("\n\nArc2 {} FILE NOT FOUND\n\n".format(arc2))
# get a list of the extracted arcs and objects
spectrum_out = "i_s_r{0:d}_t.ms.fits".format(spectrum_id)
if i == 0:
# extract the master reference arc
print("\nExtracting master arc {} under the same conditions...".format(refarc))
iraf.apall(input=refarc,
reference=reffile,
recente="no",
trace="no",
backgro="no",
interac="no")
print("Reference arc {} extracted".format(refarc))
# identify the lines in it
print("\nIdentify arc lines:")
print("Enter the following in the splot window")
print("\t:thres 500")
print("\t:order 1, max = 3")
print("\tfwidth 2")
print("Select 3-5 arc lines from line atlas")
print("Press 'm' to mark, then enter wavelength")
print("Then press 'l' to automatically ID the other lines")
print("Press 'f' to fit the dispersion correction")
print("Use 'd' to remove bad points, 'f' to refit")
print("'q' from fit, then 'q' from identify to continue\n")
iraf.identify(images=refarc_out, coordlist=lineList_location)
# use the refarc to ID all the subsequent arcs
for arc in arclist:
print("\nReidentifying arclines from {}".format(arc))
iraf.reidentify(reference=refarc_out, images=arc)
# add the refspec keywords to the image header for dispcor
# refspec_factor tells IRAF how to interpolate the arcs
refspec_factor = round((1./len(arclist)), 1)
for i in range(0, len(arclist)):
refspec = "{} {}".format(arclist[i].split(".fits")[0], refspec_factor)
print("REFSPEC{}: {}".format(i+1, refspec))
iraf.hedit(images=spectrum_out,
fields="REFSPEC{}".format(i+1),
value=refspec,
add="yes",
verify="no",
show="yes")
print("Headers updated!\n")
# apply the dispersion correction
print("Applying the dispersion correction")
iraf.dispcor(input=spectrum_out,
output=spectrum_out,
lineari="yes",
databas="database",
table="")
print("Correction applied!")
# normalize the spectrum using continuum
normspec_out = "{}n.ms.fits".format(spectrum_out.split('.ms')[0])
iraf.continuum(input=spectrum_out,
output=normspec_out,
logfile="logfile",
interac="yes",
functio="spline3",
order="5",
niterat="10",
markrej="yes")
print("\n\n")
overscan=False,
darkcor=False,
trim=True,
zerocor=True,
flatcor=True,
trimsec='[*,20:4600]',
zero='Zero',
flat='niFlat')
iraf.ccdlist('Zero, nFlat, niFlat, {0}, {1}'.format(science, cal))
iraf.imstat('Zero')
iraf.imstat('nFlat')
iraf.imstat(science)
iraf.imstat(cal)
ref = str(raw_input('Imagen de referencia (eg. hd161103_0001.fits):'))
iraf.imexamine(ref)
iraf.apall.unlearn()
iraf.apall(input=science, format='onedspec', readnoise='rdnoise', gain='gain')
iraf.apall(input=cal,
format='onedspec',
reference=ref,
readnoise='rdnoise',
gain='gain')
iraf.identify(images=cal[:-5] + '*.0001.fits', coordlist=linelist)
os.system("rm "+extracted_filename+" "+calibrated_filename)
# Run the spectral extraction program.
iraf.apextract.setParam("dispaxis", "1")
iraf.apall(input=filename, find="No", recenter="No", resize="No",interactive="Yes")
# Make sure that the dispersion axis is in the header.
iraf.hedit(images=[filename], fields=["DISPAXIS"], value=["1"], add="Yes")
iraf.identify(filename[:-5], coordli=home+"/Downloads/HgNe(1).dat",
section="line 105 125",
crval=crval,
cdelt=dispersion,
fwidth=5)
# Tell the extracted spectrum what the wavelength solutions are.
iraf.hedit(images=[extracted_filename],
fields=["REFSPEC1"], \
value=[filename], add="Yes")
iraf.refspec(input = extracted_filename,referen=filename[:-5],sort='',group='',confirm='no')
iraf.dispcor(input=extracted_filename,
output=calibrated_filename)
# Plot the extracted spectrum?
iraf.splot(calibrated_filename)
arcspec = np.median(np.array(arcspecs), 0)
archeader = thesearcheaders[jj]
keys = 'BANDID1', 'BANDID2', 'BANDID3', 'BANDID4', 'APNUM1', 'WCSDIM' , 'CTYPE3' , 'CD3_3' , 'LTM1_1' , 'LTM2_2' , 'LTM3_3' , 'WAT0_001', 'WAT1_001', 'WAT2_001', 'WAT3_001', 3
keyvals = 'spectrum: background fit, weights variance, clean yes' , 'background: background fit' ,'sigma - background fit, weights variance, clean yes', 'wavelength', '1 1 540.99 550.99','1 1 538.02 548.02' ,'LINEAR ', 1., 1., 1., 1., 'system=equispec' , 'wtype=linear label=Pixel' , 'wtype=linear' , 'wtype=linear'
for kk, kv in zip(keys, keyvals):
archeader[kk] = kv
if writefiles:
pyfits.writeto(redfn, np.tile(arcspec, (4,1,1)).astype(np.float32), archeader, clobber=clobber)
if wavecal:
os.chdir(_proc)
iraf.chdir(_proc)
loc_redfn =os.path.split(redfn)[1]
if waveCalRef is None:
iraf.identify(loc_redfn, database=_wldat, ftype='emission', fwidth=3, order=2, niterate=3, cradius=3, coordlist=lamp_list, function='spline3')
waveCalRef = '' + loc_redfn
else:
iraf.reidentify(waveCalRef, loc_redfn, interactive='no', override='yes', refit='yes', nlost=1, cradius=10, addfeatures='no', coordlist=lamp_list) #, function='spline3', order=2, niterate=3)
disp_soln = ns.getdisp(_wldat + os.sep + 'id' + loc_redfn.replace('.fits',''), 'spline3')
if writefiles:
ns.wspectext(loc_redfn)
datasets.append([redfns[-nthissci:], redfn])
os.chdir(dir0)
iraf.chdir(dir0)
def reidentify_each(refname, inname, database='database', \
coordlist=fi.filibdir+'thar.300.dat', \
section_x=50, \
overwrite=False):
# Not to display items in IRAF packages
sys.stdout = open('/dev/null', 'w')
iraf.noao()
iraf.twodspec()
iraf.longslit()
sys.stdout = sys.__stdout__ # Back to the stadard output
idfile = database + '/id' + inname
if os.path.isfile(idfile) and overwrite == False:
print('ID file already exists. '+idfile)
else:
if os.path.isfile(idfile) and overwrite == True:
print('Removing ' + idfile)
try:
os.remove(idfile)
except:
pass
cdelt = fits.getval(inname+'.fits', 'CDELT2')
# Derivering shift with respect to the reference.
refdata = fits.getdata(refname+'.fits')
y_ref = np.mean(refdata[:,section_x-5:section_x+5], axis=1)
indata = fits.getdata(inname+'.fits')
y_in = np.mean(indata[:,section_x-5:section_x+5], axis=1)
shift = fi.cross_correlate(y_in, y_ref, sep=0.1, fit=False)
print('%s - %s; %.2f pix'%(refname, inname, shift))
# Creating the "section" parameter
section = 'y '+str(section_x)
print('\t reidentify '+inname)
iraf.reidentify(refname, inname, interac='no',
section=section, newaps=newaps, override=override,
refit=refit, trace=trace, step=0, shift=shift*cdelt,
nlost=nlost, cradius=cradius, threshold=threshold,
addfeatures=addfeatures, coordlist=coordlist, match=match,
database=database, logfile=logfile, plotfile='',
verbose=verbose, cursor='')
#Check the result
iraf.identify(inname, section=section,
database=database, coordlist=coordlist, units='',
nsum=nsum, match=match, ftype='emission', fwidth=fwidth,
cradius=cradius, threshold=threshold,
function='chebyshev', order=order, sample='*',
niter=niter, autowrite=autowrite, cursor='')
iraf.reidentify(inname, inname,
interac='no', section=section, newaps=newaps,
override=override, refit=refit, trace=trace,
step=step, shift=0, nlost=nlost, cradius=cradius,
threshold=threshold, addfeatures=addfeatures,
coordlist=coordlist, match=match, database=database,
logfile=logfile, plotfile='', verbose=verbose,
cursor='')
return
# Delete previous results.
os.system("rm "+extracted_filename+" "+calibrated_filename)
# Make sure that the dispersion axis is in the header.
iraf.hedit(images=[filename], fields=["DISPAXIS"], value=["1"], add="Yes")
# Run the spectral extraction program.
iraf.apextract.setParam("dispaxis", "1")
iraf.apall(input=filename, find="No", recenter="No", resize="No")
# Now identify the spectral lines in the arc lamps. Need to replace l1 l2
# with the range of rows that have the spectral lines.
iraf.identify(filename, section="line 265 285")
# Tell the extracted spectrum what the wavelength solutions are.
iraf.hedit(images=[extracted_filename], fields=["REFSPEC1"], \
value=[filename], add="Yes")
iraf.dispcor(input=extracted_filename, output=calibrated_filename)
# Plot the extracted spectrum?
iraf.splot(calibrated_filename)
# Delete previous results.
os.system("rm " + extracted_filename + " " + calibrated_filename)
# Make sure that the dispersion axis is in the header.
iraf.hedit(images=[filename], fields=["DISPAXIS"], value=["1"], add="Yes")
# Run the spectral extraction program.
iraf.apextract.setParam("dispaxis", "1")
iraf.apall(input=filename, find="No", recenter="No", resize="No")
# Now identify the spectral lines in the arc lamps. Need to replace l1 l2
# with the range of rows that have the spectral lines.
iraf.identify(filename, section="line 265 285")
# Tell the extracted spectrum what the wavelength solutions are.
iraf.hedit(images=[extracted_filename], fields=["REFSPEC1"], \
value=[filename], add="Yes")
iraf.dispcor(input=extracted_filename, output=calibrated_filename)
# Plot the extracted spectrum?
iraf.splot(calibrated_filename)