def sumFibers(self, inIm, **kwargs):
print "\nSUMMING FIBERS FROM " + inIm
# delete previous summed spectra
# TODO: add attribute to class to turn imdelete verifications on/off
iraf.imdelete("a" + inIm)
# sum the fibers and view the final spectrum
iraf.gfapsum(inIm, **kwargs)
iraf.splot("a" + inIm + "[SCI,1]")
return
def reduce_stdstar(rawdir,
rundir,
caldir,
starobj,
stdstar,
flat,
arc,
twilight,
twilight_flat,
starimg,
bias,
overscan,
vardq,
lacos,
observatory,
apply_lacos,
lacos_xorder,
lacos_yorder,
lacos_objlim,
lacos_sigclip,
bpm,
instrument,
slits,
fl_gscrrej,
wltrim_frac=0.03,
sens_order=6,
sens_function='spline3',
apsum_radius=1):
"""
Reduction pipeline for standard star.
Parameters
----------
rawdir: string
Directory containing raw images.
rundi: string
Directory where processed files are saved.
caldir: string
Directory containing standard star calibration files.
starobj: string
Object keyword for the star image.
stdstar: string
Star name in calibration file.
flat: list
Names of the files containing flat field images.
arc: list
Arc images.
twilight: list
Twilight flat images.
starimg: string
Name of the file containing the image to be reduced.
bias: list
Bias images.
"""
iraf.set(stdimage='imtgmos')
iraf.task(lacos_spec=lacos)
iraf.gemini()
iraf.unlearn('gemini')
iraf.gmos()
iraf.unlearn('gmos')
iraf.gemtools()
iraf.unlearn('gemtools')
iraf.gmos.logfile = 'logfile.log'
iraf.gemtools.gloginit.logfile = 'logfile.log'
iraf.gfextract.verbose = 'no'
# set directories
iraf.set(caldir=rawdir) #
iraf.set(rawdir=rawdir) # raw files
iraf.set(procdir=rundir) # processed files
# os.path.isfile('arquivo')
iraf.cd('procdir')
flat = flat.strip('.fits')
twilight = twilight.strip('.fits')
twilight_flat = twilight_flat.strip('.fits')
arc = arc.strip('.fits')
starimg = starimg.strip('.fits')
mdffile = 'mdf' + flat + '.fits'
iraf.gfreduce.bias = 'rawdir$' + bias
iraf.gfreduce.fl_fulldq = 'yes'
iraf.gfreduce.fl_fixgaps = 'yes'
iraf.gireduce.bpm = 'rawdir$' + bpm
cal_reduction(rawdir=rawdir,
rundir=rundir,
flat=flat,
arc=arc,
twilight=twilight,
bias=bias,
bpm=bpm,
overscan=overscan,
vardq=vardq,
instrument=instrument,
slits=slits,
twilight_flat=twilight_flat)
#
# Actually reduce star
#
imageName = 'rg' + starimg + '.fits'
if os.path.isfile(imageName):
skipwarn(imageName)
else:
imageName = 'g' + starimg + '.fits'
if os.path.isfile(imageName):
iraf.printlog(
'GIREDS: WARNING: Removing file {:s}'.format(imageName),
'logfile.log', 'yes')
iraf.delete(imageName)
iraf.gfreduce(starimg,
slits='header',
rawpath='rawdir$',
fl_inter='no',
fl_addmdf='yes',
key_mdf='MDF',
mdffile=mdffile,
weights='no',
fl_over=overscan,
fl_trim='yes',
fl_bias='yes',
trace='no',
recenter='no',
fl_flux='no',
fl_gscrrej='no',
fl_extract='no',
fl_gsappwave='no',
fl_wavtran='no',
fl_novl='yes',
fl_skysub='no',
fl_vardq=vardq,
mdfdir='procdir$')
prefix = 'rg'
#
# Gemfix
#
imageName = 'p' + prefix + starimg + '.fits'
if os.path.isfile(imageName):
skipwarn(imageName)
else:
iraf.gemfix(prefix + starimg,
out='p' + prefix + starimg,
method='fit1d',
bitmask=1,
axis=1)
prefix = 'p' + prefix
#
# LA Cosmic
#
if apply_lacos:
imageName = 'l' + prefix + starimg + '.fits'
if os.path.isfile(imageName):
skipwarn(imageName)
else:
if apply_lacos:
iraf.gemcrspec(prefix + starimg,
out='l' + prefix + starimg,
sigfrac=0.32,
niter=4,
fl_vardq=vardq,
xorder=lacos_xorder,
yorder=lacos_yorder,
objlim=lacos_objlim,
sigclip=lacos_sigclip)
prefix = 'l' + prefix
#
# Extraction and Gemini's comsmic ray rejection
#
if fl_gscrrej:
imageName = 'x' + prefix + starimg + '.fits'
if os.path.isfile(imageName):
skipwarn(imageName)
fl_gscrrej = False
else:
imageName = 'ex' + prefix + starimg + '.fits'
if os.path.isfile(imageName):
skipwarn(imageName)
else:
iraf.gfreduce(prefix + starimg,
slits='header',
rawpath='./',
fl_inter='no',
fl_addmdf='no',
key_mdf='MDF',
mdffile=mdffile,
fl_over='no',
fl_trim='no',
fl_bias='no',
trace='no',
recenter='no',
fl_flux='no',
fl_gscrrej=fl_gscrrej,
fl_extract='yes',
fl_gsappwave='yes',
fl_wavtran='no',
fl_novl='no',
fl_skysub='no',
reference='eprg' + flat,
weights='no',
wavtraname='eprg' + arc,
response='eprg' + flat + '_response.fits',
fl_vardq=vardq)
prefix = 'ex' + prefix
else:
imageName = 'e' + prefix + starimg + '.fits'
if os.path.isfile(imageName):
skipwarn(imageName)
else:
iraf.gfreduce(prefix + starimg,
slits='header',
rawpath='./',
fl_inter='no',
fl_addmdf='no',
key_mdf='MDF',
mdffile=mdffile,
fl_over='no',
fl_trim='no',
fl_bias='no',
trace='no',
recenter='no',
fl_flux='no',
fl_gscrrej=fl_gscrrej,
fl_extract='yes',
fl_gsappwave='yes',
fl_wavtran='no',
fl_novl='no',
fl_skysub='no',
reference='eprg' + flat,
weights='no',
wavtraname='eprg' + arc,
response='eprg' + flat + '_response.fits',
fl_vardq=vardq)
prefix = 'e' + prefix
#
# Wavelength transform
#
wl1, wl2 = wl_lims(prefix + starimg + '.fits', wltrim_frac)
imageName = 't' + prefix + starimg + '.fits'
if os.path.isfile(imageName):
skipwarn(imageName)
else:
iraf.gfreduce(prefix + starimg,
slits='header',
rawpath='./',
fl_inter='no',
fl_addmdf='no',
key_mdf='MDF',
mdffile=mdffile,
fl_over='no',
fl_trim='no',
fl_bias='no',
trace='no',
recenter='no',
fl_flux='no',
fl_gscrrej='no',
fl_extract='no',
fl_gsappwave='no',
fl_wavtran='yes',
fl_novl='no',
fl_skysub='no',
reference='eprg' + flat,
weights='no',
wavtraname='eprg' + arc,
response='eprg' + flat + '_response.fits',
fl_vardq=vardq,
w1=wl1,
w2=wl2)
prefix = 't' + prefix
#
# Sky subtraction
#
imageName = 's' + prefix + starimg + '.fits'
if os.path.isfile(imageName):
skipwarn(imageName)
else:
iraf.gfreduce(prefix + starimg,
slits='header',
rawpath='./',
fl_inter='no',
fl_addmdf='no',
key_mdf='MDF',
mdffile=mdffile,
fl_over='no',
fl_trim='no',
fl_bias='no',
trace='no',
recenter='no',
fl_flux='no',
fl_gscrrej='no',
fl_extract='no',
fl_gsappwave='no',
fl_wavtran='no',
fl_novl='no',
fl_skysub='yes',
reference='eprg' + flat,
weights='no',
wavtraname='eprg' + arc,
response='eprg' + flat + '_response.fits',
fl_vardq=vardq,
w1=wl1,
w2=wl2)
prefix = 's' + prefix
#
# Apsumming the stellar spectra
#
xinst = pf.getdata(prefix + starimg + '.fits', ext=1)['XINST']
if instrument == 'GMOS-N':
x0 = np.average(xinst[xinst < 10])
elif instrument == 'GMOS-S':
x0 = np.average(xinst[xinst > 10])
ap_expression = '((XINST-{:.2f})**2 + '\
'(YINST-2.45)**2)**0.5 < {:.2f}'.format(x0, apsum_radius)
imageName = 'a' + prefix + starimg + '.fits'
if os.path.isfile(imageName):
skipwarn(imageName)
else:
iraf.gfapsum(prefix + starimg,
fl_inter='no',
lthreshold='INDEF',
hthreshold='INDEF',
reject='avsigclip',
expr=ap_expression)
#
# Building sensibility function
#
if os.path.isfile('std' + starimg)\
and os.path.isfile('sens' + starimg + '.fits'):
skipwarn('std{0:s} and sens{0:s}.fits'.format(starimg))
else:
imageName = 'std' + starimg
if os.path.isfile(imageName):
iraf.printlog(
'GIREDS: WARNING: Removing file {:s}'.format(imageName),
'logfile.log', 'yes')
iraf.delete(imageName)
imageName = 'sens' + starimg + '.fits'
if os.path.isfile(imageName):
iraf.printlog(
'GIREDS: WARNING: Removing file {:s}'.format(imageName),
'logfile.log', 'yes')
iraf.delete(imageName)
iraf.gsstandard('a' + prefix + starimg,
starname=stdstar,
observatory=observatory,
sfile='std' + starimg,
sfunction='sens' + starimg,
caldir=caldir,
order=sens_order,
function=sens_function)
#
# Apply flux calibration to star
#
imageName = 'c' + prefix + starimg + '.fits'
if os.path.isfile(imageName):
skipwarn(imageName)
else:
iraf.gscalibrate(prefix + starimg,
sfuncti='sens' + starimg,
extinct='onedstds$ctioextinct.dat',
observatory=observatory,
fluxsca=1,
fl_vardq=vardq)
#
# Create data cubes
#
imageName = 'dc' + prefix + starimg + '.fits'
if os.path.isfile(imageName):
skipwarn(imageName)
else:
data_cube = CubeBuilder('c' + prefix + starimg + '.fits')
data_cube.build_cube()
data_cube.fit_refraction_function()
data_cube.fix_atmospheric_refraction()
data_cube.write(imageName)
#
# Test calibration
#
iraf.cd(caldir)
caldata = np.loadtxt(stdstar + '.dat', unpack=True)
iraf.cd('procdir')
calflux = mag2flux(caldata[0], caldata[1])
imageName = 'ca' + prefix + starimg + '.fits'
if os.path.isfile(imageName):
skipwarn(imageName)
else:
iraf.gscalibrate('a' + prefix + starimg,
sfuncti='sens' + starimg,
extinct='onedstds$ctioextinct.dat',
observatory=observatory,
fluxsca=1)
sumflux = pf.getdata('ca' + prefix + starimg + '.fits', ext=2)
sumhead = pf.getheader('ca' + prefix + starimg + '.fits', ext=2)
sumwl = sumhead['crval1'] + np.arange(
sumhead['naxis1']) * sumhead['cdelt1']
plt.close('all')
plt.plot(sumwl, sumflux, 'b', lw=.5)
plt.plot(caldata[0], calflux, 'r', lw=1.5)
plt.xlim(sumwl[0] * .99, sumwl[-1] * 1.01)
plt.ylim(min(calflux) * .8, max(calflux) * 1.2)
plt.savefig('calib' + starimg + '.eps')
def reduce_stdstar(rawdir, rundir, caldir, starobj, stdstar, flat,
arc, twilight, starimg, bias, overscan, vardq):
"""
Reduction pipeline for standard star.
Parameters
----------
rawdir: string
Directory containing raw images.
rundi: string
Directory where processed files are saved.
caldir: string
Directory containing standard star calibration files.
starobj: string
Object keyword for the star image.
stdstar: string
Star name in calibration file.
flat: list
Names of the files containing flat field images.
arc: list
Arc images.
twilight: list
Twilight flat images.
starimg: string
Name of the file containing the image to be reduced.
bias: list
Bias images.
"""
iraf.set(stdimage='imtgmos')
iraf.gemini()
iraf.gemtools()
iraf.gmos()
#iraf.unlearn('gemini')
#iraf.unlearn('gmos')
iraf.task(lacos_spec='/storage/work/gemini_pairs/lacos_spec.cl')
tstart = time.time()
#set directories
iraf.set(caldir=rawdir) #
iraf.set(rawdir=rawdir) # raw files
iraf.set(procdir=rundir) # processed files
iraf.gmos.logfile='logfile.log'
iraf.cd('procdir')
# building lists
def range_string(l):
return (len(l)*'{:4s},').format(*[i[-9:-5] for i in l])
iraf.gemlist(range=range_string(flat), root=flat[0][:-9],
Stdout='flat.list')
iraf.gemlist(range=range_string(arc), root=arc[0][:-9],
Stdout='arc.list')
#iraf.gemlist(range=range_string(star), root=star[0][:-4],
# Stdout='star.list')
iraf.gemlist(range=range_string(twilight),
root=twilight[0][:-9], Stdout='twilight.list')
iraf.gfreduce.bias = 'caldir$'+bias[0]
#######################################################################
#######################################################################
### Star reduction #
#######################################################################
#######################################################################
#
# Flat reduction
#
iraf.gfreduce(
'@flat.list', slits='header', rawpath='rawdir$', fl_inter='no',
fl_addmdf='yes', key_mdf='MDF', mdffile='default', weights='no',
fl_over=overscan, fl_trim='yes', fl_bias='yes', trace='yes', t_order=4,
fl_flux='no', fl_gscrrej='no', fl_extract='yes', fl_gsappwave='no',
fl_wavtran='no', fl_novl='no', fl_skysub='no', reference='',
recenter='yes', fl_vardq=vardq)
iraf.gfreduce('@twilight.list', slits='header', rawpath='rawdir$',
fl_inter='no', fl_addmdf='yes', key_mdf='MDF',
mdffile='default', weights='no',
fl_over=overscan, fl_trim='yes', fl_bias='yes', trace='yes',
recenter='no',
fl_flux='no', fl_gscrrej='no', fl_extract='yes', fl_gsappwave='no',
fl_wavtran='no', fl_novl='no', fl_skysub='no',
reference='erg'+flat[0], fl_vardq=vardq)
#
# Response function
#
for i, j in enumerate(flat):
j = j[:-5]
iraf.imdelete(j+'_response')
iraf.gfresponse('erg'+j+'.fits', out='erg'+j+'_response',
skyimage='erg'+twilight[i], order=95, fl_inter='no',
func='spline3',
sample='*', verbose='yes')
# Arc reduction
#
iraf.gfreduce(
'@arc.list', slits='header', rawpath='rawdir$', fl_inter='no',
fl_addmdf='yes', key_mdf='MDF', mdffile='default', weights='no',
fl_over=overscan, fl_trim='yes', fl_bias='yes', trace='no',
recenter='no',
fl_flux='no', fl_gscrrej='no', fl_extract='yes', fl_gsappwave='no',
fl_wavtran='no', fl_novl='no', fl_skysub='no', reference='erg'+flat[0],
fl_vardq=vardq)
# Finding wavelength solution
# Note: the automatic identification is very good
#
for i in arc:
iraf.gswavelength('erg'+i, function='chebyshev', nsum=15, order=4,
fl_inter='no', nlost=5, ntarget=20, aiddebug='s', threshold=5,
section='middle line')
#
# Apply wavelength solution to the lamp 2D spectra
#
iraf.gftransform('erg'+i, wavtran='erg'+i, outpref='t', fl_vardq=vardq)
##
## Actually reduce star
##
iraf.gfreduce(
starimg, slits='header', rawpath='rawdir$', fl_inter='no',
fl_addmdf='yes', key_mdf='MDF', mdffile='default', weights='no',
fl_over=overscan, fl_trim='yes', fl_bias='yes', trace='no',
recenter='no',
fl_flux='no', fl_gscrrej='no', fl_extract='no', fl_gsappwave='no',
fl_wavtran='no', fl_novl='yes', fl_skysub='no', fl_vardq=vardq)
iraf.gemcrspec('rg{:s}'.format(starimg), out='lrg'+starimg, sigfrac=0.32,
niter=4, fl_vardq=vardq)
iraf.gfreduce(
'lrg'+starimg, slits='header', rawpath='./', fl_inter='no',
fl_addmdf='no', key_mdf='MDF', mdffile='default',
fl_over='no', fl_trim='no', fl_bias='no', trace='no',
recenter='no',
fl_flux='no', fl_gscrrej='no', fl_extract='yes',
fl_gsappwave='yes',
fl_wavtran='yes', fl_novl='no', fl_skysub='yes',
reference='erg'+flat[0][:-5], weights='no',
wavtraname='erg'+arc[0][:-5],
response='erg'+flat[0][:-5]+'_response.fits',
fl_vardq=vardq)
#
# Apsumming the stellar spectra
#
iraf.gfapsum(
'stexlrg'+starimg, fl_inter='no', lthreshold=400.,
reject='avsigclip')
#
# Building sensibility function
#
iraf.gsstandard(
('astexlrg{:s}').format(starimg), starname=stdstar,
observatory='Gemini-South', sfile='std', sfunction='sens',
caldir=caldir)
#
# Apply flux calibration to galaxy
#
#
##iraf.imdelete('*****@*****.**')
#
##iraf.gscalibrate('*****@*****.**',sfunction='sens.fits',fl_ext='yes',extinct='onedstds$ctioextinct.dat',observatory='Gemini-South',fluxsca=1)
#
##
## Create data cubes
##
#
#
##for i in objs:
## iraf.imdelete('d0.1cstexlrg'+i+'.fits')
## iraf.gfcube('cstexlrg'+i+'.fits',outpref='d0.1',ssample=0.1,fl_atmd='yes',fl_flux='yes')
#
##
## Combine cubes
##
#
#
##iraf.imdelete('am2306-721r4_wcsoffsets.fits')
##iraf.imcombine('d0.1cstexlrgS20141113S00??.fits[1]',output='am2306-721r4_wcsoffsets.fits',combine='average',reject='sigclip',masktype='badvalue',lsigma=2,hsigma=2,offset='wcs',outlimits='2 67 2 48 100 1795')
#
tend = time.time()
print('Elapsed time in reduction: {:.2f}'.format(tend - tstart))
iraf.chdir(current_dir)
iraf.unlearn('gfapsum')
iraf.unlearn('gsstandard')
# ---------- Sensitivity function (after reducing standard star) ---------- #
std = np.loadtxt(ic.lst_std, dtype=str)
if (std.size > 1):
raise ValueError("Please check if there is only one image for the standard star.")
std0 = std.item(0)
# Sum the fibers
iraf.imdelete('astxeqxbrg@'+ic.lst_std)
iraf.gfapsum('stxeqxbrg'+std0, combine='sum', fl_inter='no')
iraf.splot('astxeqxbrg'+std0+'[sci,1]')
# Plot the sum spectra
spec_sum, hd = fits.getdata('astxeqxbrg'+std0+'.fits', ext=1, header=True)
w = hd['CRVAL1'] + np.arange(len(spec_sum))*hd['CD1_1']
fig, ax = plt.subplots(1, 1, figsize=(7,5))
plt.subplots_adjust(left=0.16, right=0.96, bottom=0.13, top=0.91)
plt.suptitle("Sum of spectra", x=0.55, ha='center', y=0.97, va='top',
fontsize=16.0, fontweight='bold')
ax.set_xlabel(r"Wavelength [${\rm \AA}$]", fontsize=12.0)
ax.set_ylabel("Counts", fontsize=12.0)
# ax.set_yscale('log')
ax.tick_params(axis='both', labelsize=12.0)
wavtraname='erg'+arc[m][0], response='erg'+flat[m][0]+'_response.fits',
fl_vardq='yes')
# (( TEMP ))
#for m, i in enumerate(star):
# # (B) Fiz fl_vardq-, pois mudei acima tambem --------
# iraf.imdelete('texlrg'+i+'.fits')
# iraf.gftransform('exlrg'+i, wavtran='erg'+arc[m][0], outpref='t', fl_vardq='yes')
#
# Apsumming the stellar spectra
#
for m, i in enumerate(star):
iraf.imdelete('astexlrg'+i)
iraf.gfapsum(
'stexlrg'+i, fl_inter='no', lthreshold=400.,
reject='avsigclip')
#-------------------------------------------------------------------------------------
#
# Building sensibility function
#
for m in range(len(star)):
iraf.delete('std'+str(m))
iraf.delete('sens'+str(m)+'.fits')
for m in range(len(star)):
iraf.gsstandard(
'astexlrg'+star[m], starname=stdstar[m],
