def getSkyMeanSDinAnnulus(ann,delta=5):
iraf.noao()
iraf.digiphot()
iraf.apphot()
iraf.photpars.setParam('apertures','1')
iraf.phot.setParam('interactive','no')
iraf.phot.setParam('image',fitsDir+fitsFile)
iraf.phot.setParam('coords',fitsDir+fitsFile+".coo")
outmag=".maglim"
try:
os.remove(fitsDir+fitsFile+outmag)
except:
print "File does not exist BEFORE running phot, so no need to delete."
iraf.phot.setParam('output',fitsDir+fitsFile+outmag)
iraf.phot.setParam('interac','no')
iraf.fitskypars.setParam('annulus',str(ann))
iraf.fitskypars.setParam('dannulus',str(delta))
## NO SIGMA CLIPPING! JUST TO BE SAFE: (6/2013)
iraf.fitskypars.setParam('sloclip',"0")
iraf.fitskypars.setParam('shiclip',"0")
iraf.phot(fitsDir+fitsFile,Stdin=cr)
aa, nn, xx, ss = ao.readPhotMagFile(fitsDir,fitsFile,outmag)
try:
os.remove(fitsDir+fitsFile+outmag)
except:
print "File not found to delete AFTER running phot; that's odd."
return xx
def fitcoord_edge_each(fname, overwrite=False):
nteractive = 'yes'
database = 'database'
function = 'chebyshev'
xorder = 2
yorder = 7
logfiles = 'STDOUT,fitcoord_edge.log'
interactive = 'yes'
cursor = ''
# cursor = filibdir+'fitcoord_edge.cur'
idfile = database + '/id' + fname
if not os.path.isfile(idfile):
print('\t Edge identification files do not exist. ' + idfile)
return
fcfile = database + '/fc' + fname
if os.path.isfile(fcfile) and not overwrite:
print('\t Edge fitcoord files already exist. ' + fcfile)
print('\t This procedure is skipped.')
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
iraf.fitcoord(fname, fitname='', interactive=interactive, \
combine='no', database=database, deletions='',\
function = function,xorder=xorder, yorder=yorder,\
logfiles=logfiles, graphics='stdgraph', cursor=cursor)
return
def StandardTask(self, InputFile, OutputFile, FitsFolder, airmass_value, exptime_value):
iraf.noao(_doprint=0)
iraf.onedspec(_doprint=0)
#From the fits file determine which is the star being treated
StarName = self.StarnameFromFileName(InputFile)
#Get the corresponding Calibration file
CalibrationFile, Bandwidth, Bandsep = self.getCalibrationFile(StarName)
#Incase no output name is given, we generate one with the provided "preffix" (The defaul format is a_std_wolf.dat)
if OutputFile == None:
OutputFile = 'a_std_' + StarName
#Prepare dictionary with the configuration for the tasks
Standard_conf_Comb = self.StandardAttributes(InputFile, OutputFile, CalibrationFile, FitsFolder, airmass_value, exptime_value, Bandwidth, Bandsep)
#Display the equivalent command in IRAF
Command = self.printIrafCommand('standard', Standard_conf_Comb)
print '--- Using the command'
print Command
#Run the task
iraf.onedspec.standard(**Standard_conf_Comb)
return OutputFile
def align_combine(fitsdir, myfilter, examine=True):
from pyraf import iraf
iraf.noao(_doprint=0)
iraf.digiphot(_doprint=0)
iraf.apphot(_doprint=0)
os.chdir(fitsdir)
listfiles = glob.glob(myfilter)
listfiles.sort()
if (examine):
print "Opening ",listfiles[0]," to examine."
iraf.imexamine(input=listfiles[0], \
logfile="coords.dat", \
keeplog="yes")
with open("align.list",'w') as f:
for i in listfiles:
f.write(i+"\n")
print "Aligning with reference:",listfiles[0]
iraf.imalign( input = "@align.list", referenc= listfiles[0], coords = "coords.dat", output = "*****@*****.**")
listfiles = glob.glob("a_"+myfilter)
listfiles.sort()
with open("comb.list",'w') as f:
for i in listfiles:
f.write(i+"\n")
print "Combining"
iraf.imcombine(input = "@comb.list",\
output = "out.fits",\
combine= "median")
def combinebias(lstfn):
"""
call iraf command zerocombine, combine bias fits.
lstfn : lst file name
type : string
output file : Zero.fits
"""
iraf.noao()
iraf.imred()
iraf.ccdred()
iraf.zerocombine(input='o//@' + lstfn,
output='Zero',
combine='average',
reject='minmax',
ccdtype='',
process=False,
delete=False,
clobber=False,
scale='none',
statsec='',
nlow=0,
nhigh=1,
nkeep=1,
mclip=True,
lsigma=3.0,
hsigma=3.0,
rdnoise='rdnoise',
gain='gain',
snoise=0.0,
pclip=-0.5,
blank=0.0)
def standard(namelst):
iraf.noao()
iraf.twodspec()
iraf.longslit(dispaxis=2, nsum=1, observatory=func.obs.name,
extinction=extpath, caldir=stdpath)
if os.path.isfile('Std'):
print('remove file Std')
os.remove('Std')
for std_fitsname in namelst:
stdname, stdmag, stdmagband = func.standard_star_info(std_fitsname)
print(colored('the standard star is ' + stdname, 'green'))
wid, sep = get_band_width_sep(std_fitsname)
airmas = pyfits.getval(std_fitsname, 'airmass')
exposure = pyfits.getval(std_fitsname, 'exptime')
iraf.standard(input=std_fitsname, output='Std', samestar=True,
beam_switch=False, apertures='', bandwidth=wid,
bandsep=sep, # 30.0 20.0
fnuzero=3.6800000000000E-20, extinction=extpath,
caldir=stdpath, observatory=func.obs.name, interact=True,
graphics='stdgraph', cursor='', star_name=stdname,
airmass=airmas, exptime=exposure, mag=stdmag,
magband=stdmagband, teff='', answer='yes')
if os.path.isfile('Sens.fits'):
print('remove file Sens.fits')
os.remove('Sens.fits')
iraf.sensfunc(standards='Std', sensitivity='Sens',
extinction=extpath, function='spline3', order=9)
iraf.splot('Sens')
def apall_config(
config_file,
config_default='/Users/ando/andry/research/Make_software/saltrss/apall_conf.yml'
):
config = yaml.safe_load(open(config_default))
custom_config = {}
if os.path.exists(config_file):
custom_config = yaml.safe_load(open(config_file))
config = config_merge(custom_config, config)
sections = [
'iraf.apall',
]
iraf.noao(_doprint=0)
iraf.twodspec(_doprint=0)
iraf.onedspec(_doprint=0)
iraf.apextract(_doprint=0)
iraf.apextract.unlearn()
iraf.apall.unlearn()
iraf.apsum.unlearn()
iraf.apextract.setParam('dispaxis', 1)
for section_name in sections:
params = config[section_name].items()
for param_id in params:
eval(section_name).setParam(param_id[0], param_id[1])
return config
def _get_photometry(self):
""" Get the photometry for the target.
If the target is a standard star, aperture photometry will be performed. For the moment nothing is done with
the others, but in due time (TODO) photometry.py will be included here. """
basename = "standards"
fd, coords_file = tempfile.mkstemp(prefix=basename, suffix=".coords")
os.write(fd, "{0} {1} \n".format(self.RA, self.DEC))
os.close(fd)
if self.objtype == "standard":
iraf.noao(_doprint=0)
iraf.digiphot(_doprint=0)
iraf.apphot(_doprint=0)
seeing = self.header.hdr[self.header.seeingk]
photfile_name = self.header.im_name + ".mag.1"
utilities.if_exists_remove(photfile_name)
kwargs = dict(output=photfile_name, coords=coords_file,
wcsin='world', fwhm=seeing, gain=self.header.gaink, exposure=self.header.exptimek,
airmass=self.header.airmassk, annulus=6*seeing, dannulus=3*seeing,
apert=2*seeing, verbose="no", verify="no", interac="no")
iraf.phot(self.header.im_name, **kwargs)
[counts] = iraf.module.txdump(photfile_name, 'FLUX', 'yes', Stdout=subprocess.PIPE)
utilities.if_exists_remove(coords_file)
return float(counts)
def calibrate(namelst):
iraf.noao()
iraf.twodspec()
iraf.longslit(dispaxis=2,
nsum=1,
observatory='ca',
extinction=extpath,
caldir=stdpath)
for fitname in namelst:
outname = 'mark_' + fitname
if os.path.isfile(outname):
print('remove file ' + outname)
os.remove(outname)
iraf.calibrate(input=fitname,
output=outname,
extinct='yes',
flux='yes',
extinction=extpath,
ignoreaps='yes',
sensitivity='Sens',
fnu='no')
iraf.splot(images=outname)
iraf.flpr()
def thar_cal(object_b_fn_ec, object_b_fn_ec_w, colour):
# Import IRAF modules:
iraf.noao(_doprint=0)
iraf.onedspec(_doprint=0)
# Check input file and reference extraction exist before proceeding:
if os.path.isfile(object_b_fn_ec) == True:
# Perform dispersion correction:
iraf.dispcor(input=object_b_fn_ec, output=object_b_fn_ec_w)
print ' '
print '~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~'
print colour.capitalize() + ' object spectrum '
print '(' + str(object_b_fn_ec) + ')'
print 'successfully wavelength calibrated in file '
print str(object_b_fn_ec_w) + '.'
print '~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~'
print ' '
else:
print ' '
print '~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~'
print 'Input frame '
print str(object_b_fn_ec)
print 'does not exist. Exiting script. '
print '~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~'
print ' '
print ' '
sys.exit()
def identify_objects(fnlist,skysiglist,fwhmlist,suffix=".coo"):
"""Runs the IRAF routine 'daofind' to locate objects in a series of images,
creating coordinate files.
Inputs:
fnlist -> List of strings, each the path to a fits image.
skysiglist -> List of floats, each the sky background sigma for an image.
fwhmlist -> List of floats, each the FWHM of objects in an image.
suffix -> Suffix for the coordinate files. '.coo' by default.
Outputs:
coolist -> List of strings, each the path to the coordinate files created.
"""
print "Identifying objects in images..."
coolist = []
#Open IRAF packages
iraf.noao(_doprint=0)
iraf.digiphot(_doprint=0)
iraf.apphot(_doprint=0)
for i in range(len(fnlist)):
coolist.append(fnlist[i]+suffix)
iraf.daofind(image=fnlist[i],
output=fnlist[i]+suffix,
fwhmpsf=fwhmlist[i],
sigma=skysiglist[i],
threshold=4.0,
datamin='INDEF',
datamax='INDEF',
verify='N')
return coolist
def standard():
stdpath = os.path.split(os.path.realpath(__file__))[0] + os.sep + 'standarddir' + os.sep
print('standard dir is ' + stdpath)
extpath = os.path.split(os.path.realpath(__file__))[0] + os.sep + 'LJextinct.dat'
iraf.noao()
iraf.twodspec()
iraf.longslit(dispaxis = 2, nsum = 1, observatory = 'Lijiang',
extinction = extpath, caldir = stdpath)
for objname in stdgroup:
stdname, stdmag, stdmagband = get_std_name(objname)
print('the standard star is ' + stdname)
stdmag = float(stdmag)
outname1 = 'stdawftbo' + stdgroup[objname][0]
inname = ''
for tmpname in stdgroup[objname]:
inname = inname + 'awftbo' + tmpname + ','
inname = inname[0:-1]
iraf.standard(input = inname
, output = outname1, samestar = True, beam_switch = False
, apertures = '', bandwidth = 30.0, bandsep = 20.0
, fnuzero = 3.6800000000000E-20, extinction = extpath
, caldir = stdpath, observatory = ')_.observatory'
, interact = True, graphics = 'stdgraph', cursor = ''
, star_name = stdname, airmass = '', exptime = ''
, mag = stdmag, magband = stdmagband, teff = '', answer = 'yes')
for name in stdgroup:
inpar = 'stdawftbo' + stdgroup[name][0]
iraf.sensfunc(standards = inpar, sensitivity = 'sensawftbo' + stdgroup[name][0],
extinction = extpath, function = 'spline3', order = 9)
def run_fxcor(lstl, lstu, tpl, tpu, chip):
if chip == 'l':
templ = tpl
lst = lstl
else:
templ = tpu
lst = lstu
lista = '@' + lst
chip_par = 'rvout_' + chip
iraf.noao()
iraf.rv()
iraf.fxcor(lista,
templ,
output=chip_par,
verbose='txtonly',
interac='no',
observa='paranal')
rv = []
rvlist = open(chip_par + '.txt', "r")
for cols in (raw.strip().split() for raw in rvlist):
vobs_index = len(cols) - 3
if cols[0][0] != '#':
rv.append(float(cols[vobs_index]))
rvlist.close()
return rv
def get_seeing(file, scale, ref):
coords = file.replace('fits','dao')
log = file.replace('fits','psf')
out = file.replace('fits','seeing')
iraf.noao()
iraf.noao.obsutil()
iraf.set(stdgraph="uepsf")
data = iraf.psfmeasure(file, coords='markall', wcs='logical', display='no', frame=1, level=0.5, size='FWHM', radius=10.0, sbuffer=1.0, swidth=3.0, iterations=1, logfile=log, imagecur=coords, Stdout=1)
fwhm = data.pop().split().pop()
fwhm_pix = float(fwhm)
fwhm = fwhm_pix*scale
seeing = dimm_seeing(fwhm_pix, ref, scale)
print "Seeing: ", seeing
fp = open(out, 'w')
fp.write("%f %f\n" % (fwhm_pix, seeing))
fp.close()
os.system("echo \"image;text 85 500 # text={Spot FWHM = %5.2f pixels}\" | xpaset WFS regions" % fwhm_pix)
os.system("echo \'image;text 460 500 # text={Seeing = %4.2f\"}\' | xpaset WFS regions" % seeing)
os.system("echo \"set wfs_seeing %4.2f\" | nc hacksaw 7666" % seeing)
# New function call to insert seeing value into MySQL database.
fits2mysql(file, mode, fwhm, seeing)
def run_scombine(listin, fn):
namefil = []
namelist = open(listin, "r")
for cols in (raw.strip().split() for raw in namelist):
namefil.append(cols[0])
namelist.close()
obs = []
count = -1
for i in range(len(namefil)):
if namefil[i - 1][0:2] != namefil[i][0:2]:
obs.append([])
count += 1
obs[count].append(namefil[i])
spec = []
for i in range(len(obs[0])):
spec.append([])
for j in range(len(obs)):
spec[i].append(obs[j][i])
iraf.noao()
iraf.onedspec()
for i in range(len(spec)):
temp = open('temp_list', 'w')
for j in range(len(spec[i])):
temp.write(spec[i][j] + '\n')
temp.close()
if (spec[i][0][-6] == 'L') or (spec[i][0][-6] == 'U'):
name_index = '0_' + spec[i][0][-6]
else:
name_index = spec[i][0][-6] + '_' + spec[i][0][-8]
if len(fibnum) != 0:
newname = ob_id[fibnum.index(name_index[0])] + '_' + name_index[-1]
name_index = newname
iraf.scombine('@temp_list', name_index, logfile='combine_log')
fn.append(name_index)
def coroverbiastrim(lstfile):
iraf.noao()
iraf.imred()
iraf.ccdred()
x1,x2,y1,y2 = get_trim_sec()
iraf.ccdproc(images = '@' + lstfile + '//[1]'
, output = '%bo%bo%@' + lstfile
, ccdtype = '', max_cache = 0, noproc = False
, fixpix = False, overscan = True, trim = False
, zerocor = True, darkcor = False, flatcor = False
, illumcor = False, fringecor = False, readcor = False
, scancor = False, readaxis = 'line', fixfile = ''
, biassec = '[5:45,%s:%s]'%(y1,y2), trimsec = '[%s:%s,%s:%s]'%(x1,x2,y1,y2)
, zero = 'Zero', dark = '', flat = '', illum = '', fringe = ''
, minreplace = 1.0, scantype = 'shortscan', nscan = 1
, interactive = False, function = 'chebyshev', order = 1
, sample = '*', naverage = 1, niterate = 1
, low_reject = 3.0, high_reject = 3.0, grow = 1.0)
iraf.ccdproc(images = '%bo%bo%@' + lstfile
, output = '%tbo%tbo%@' + lstfile
, ccdtype = '', max_cache = 0, noproc = False
, fixpix = False, overscan = False, trim = True
, zerocor = False, darkcor = False, flatcor = False
, illumcor = False, fringecor = False, readcor = False
, scancor = False, readaxis = 'line', fixfile = ''
, biassec = '[5:45,%s:%s]'%(y1,y2), trimsec = '[%s:%s,%s:%s]'%(x1,x2,y1,y2)
, zero = 'Zero', dark = '', flat = '', illum = '', fringe = ''
, minreplace = 1.0, scantype = 'shortscan', nscan = 1
, interactive = False, function = 'chebyshev', order = 1
, sample = '*', naverage = 1, niterate = 1
, low_reject = 3.0, high_reject = 3.0, grow = 1.0)
iraf.flpr()
def standard(imlist_name, obj, obs):
"""
standard -- Add standard stars to sensitivity file
standard input [records] output
standard wfcdbstd.ms.fits (no) "sao"
extinct = "/iraf/iraf/noao/lib/onedstds/iidscal/feige56.dat"
caldir = "/iraf/iraf/noao/lib/onedstds/iidscal/"
"""
import glob
import os, sys
from pyraf import iraf
iraf.noao()
iraf.onedspec()
imlist = glob.glob(imlist_name)
imlist.sort()
for i in range(len(imlist)):
inim = imlist[i]
iraf.standard(
input=inim,
output='s' + inim[:-5],
extinct='/iraf/iraf/noao/lib/onedstds/iidscal/feige56.dat',
observatory=obs,
caldir="/iraf/iraf/noao/lib/onedstds/iidscal/",
star_name=obj)
def align_combine(fitsdir, myfilter, examine=True):
from pyraf import iraf
iraf.noao(_doprint=0)
iraf.digiphot(_doprint=0)
iraf.apphot(_doprint=0)
os.chdir(fitsdir)
listfiles = glob.glob(myfilter)
listfiles.sort()
if (examine):
print "Opening ",listfiles[0]," to examine."
iraf.imexamine(input=listfiles[0], \
logfile="coords.dat", \
keeplog="yes")
with open("align.list",'w') as f:
for i in listfiles:
f.write(i+"\n")
print "Aligning with reference:",listfiles[0]
iraf.imalign( input = "@align.list", referenc= listfiles[0], coords = "coords.dat", output = "*****@*****.**")
listfiles = glob.glob("a_"+myfilter)
listfiles.sort()
with open("comb.list",'w') as f:
for i in listfiles:
f.write(i+"\n")
print "Combining"
iraf.imcombine(input = "@comb.list",\
output = "out.fits",\
combine= "median")
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 combine_flat(lstfile):
iraf.noao()
iraf.imred()
iraf.ccdred()
iraf.flatcombine(input='tbo//@' + lstfile,
output='Halogen',
combine='average',
reject='crreject',
ccdtype='',
process=False,
subsets=False,
delete=False,
clobber=False,
scale='mode',
statsec='',
nlow=1,
nhigh=1,
nkeep=1,
mclip=True,
lsigma=3.0,
hsigma=3.0,
rdnoise='rdnoise',
gain='gain',
snoise=0.0,
pclip=-0.5,
blank=1.0)
def makeObject(self, inObjectFile="mkobject.coo"):
"""IRAF routine: mkobjects. This places a star in the fits image that is the parent object of this class, at the given ra and dec. It takes as input a file of "ra dec magnitude" for a star type object.
1. Get info from the header files if you want noise
2. Get FWHM for size of the star for the given image
3. Generate the star
radius = FWHM / scale, from statistics, scale = 2*sqrt(2*ln(2))
"""
# 1.
self.loadHeader()
INFODICT = {
"RON": self.getHeader("RON"), \
"GAIN": self.getHeader("GAIN"), \
"EXPTIME": self.getHeader("EXPTIME"), \
"MAGZP": self._ZPDICT[self.getHeader("FILTER")], \
"POISSON": "no", \
"STAR": "gaussian", \
}
# 2.
scale = 2*scipy.sqrt(2*scipy.log(2))
self.getMyMedianFWHM()
INFODICT["RADIUS"] = self._MEDFWHM / scale
# 3.
outputname = self._Name.replace(".fits", "_mko.fits")
iraf.noao(_doprint=0)
iraf.artdata(_doprint=0)
iraf.mkobjects(input=self._Name, \
output=outputname, \
# When creating new images
#title="",\
#ncols=self.xdim, \
#nlines=self.ydim, \
#header=self.hdrfile, \
#background=0.0, \
# When creating objects
objects=inObjectFile, \
xoffset=0.0, \
yoffset=0.0, \
star=INFODICT["STAR"], \
radius=INFODICT["RADIUS"], # this is fwhm/scale (pixels), where scale = 2sqrt(2ln2)\
#beta=2.5, # for star=moffat profile\
ar=1.0, \
pa=0.0, \
distance=1.0, \
exptime=INFODICT["EXPTIME"], \
magzero=INFODICT["MAGZP"], \
# Noise parameters
gain=INFODICT["GAIN"], \
rdnoise=INFODICT["RON"], \
poisson=INFODICT["POISSON"], \
seed=1, \
comments=1)
return outputname
def wspectext_allap(filepath, apaxis=0):
""" this can be directly evaluated in terminal
Parameters
----------
filepath: string
filepath
apaxis: integer
0 or 1.
0 denotes dispersion along rows (this is the case for Xinglong216HRS)
1 denotes dispersion along columns
Examples
--------
wspectext_allap('./w20160120001s.fits')
"""
nrow, ncol = fits.open(filepath)[0].data.shape
print '@Cham: nrow = %d, ncol=%d' % (nrow, ncol)
iraf.noao()
iraf.noao.onedspec()
filename = filepath.split(os.path.sep)[-1]
# determine dirname & dirpath
dirname = filepath.split(os.path.sep)[-1].replace('.fits', '')
if os.path.dirname(filepath) == '':
dirpath = dirname
else:
dirpath = os.path.dirname(filepath) + os.path.sep + dirname
if os.path.exists(dirpath):
# if dirpath exists
print '@Cham: directory exists ... (%s)' % dirpath
else:
# if dirpath doesn't exist, mkdir
os.mkdir(dirpath)
print '@Cham: mkdir %s'%dirpath
# execute wspectest
if not apaxis == 1:
for apnum in xrange(1, nrow+1):
_input = '%s[1:%d, %d]' % (filename, ncol, apnum)
_output = dirpath + os.sep + filename.replace('.fits', '_%04d.dat' % apnum)
print '@Cham: wspectext running ... [%s]' % _output
iraf.onedspec.wspectext(input=_input, output=_output, header='no')
else:
for apnum in xrange(1, ncol+1):
_input = '%s[%d, 1:%d]' % (filename, apnum, nrow)
_output = dirpath + os.sep + filename.replace('.fits', '_%04d.dat' % apnum)
print '@Cham: wspectext running ... [%s]' % _output
iraf.onedspec.wspectext(input=_input, output=_output, header='no')
# print masseges
print '@Cham: ----------------------'
print '@Cham: mission complete!'
print '@Cham: ----------------------'
def combine_lamp(lstfile):
iraf.noao()
iraf.imred()
iraf.ccdred()
iraf.imcombine(input='%ftbo%ftbo%@' + lstfile,
output=lstfile.replace('.lst', ''),
combine='sum',
reject='none')
def combinelamp(lst):
iraf.noao()
iraf.imred()
iraf.ccdred()
iraf.imcombine(input='%ftbo%ftbo%@' + lst,
output='Lamp',
combine='sum',
reject='none')
def initialize_iraf():
iraf.noao(_doprint=0)
iraf.imred(_doprint=0)
iraf.ccdred(_doprint=0)
iraf.specred(_doprint=0)
iraf.twodspec(_doprint=0)
iraf.longslit(_doprint=0)
return
def normalize(fn):
iraf.noao()
iraf.onedspec()
for i in range(len(fn)):
if fn[i][-1] == 'L':
nord = '10'
else:
nord = '7'
iraf.continuum(fn[i], fn[i], order=nord, ask='no', logfile='norm_log')
def combinelamp(lst):
iraf.noao()
iraf.imred()
iraf.ccdred()
iraf.imcombine(input='%ftb%ftb%@' + lst,
output='Lamp',
combine='sum',
reject='none')
print('<<<<<combine the lamp & generate the Lamp.fits>>>>>')
iraf.flpr()
def normalize(setup, filelist):
iraf.noao()
iraf.onedspec()
for i in (filelist):
name = setup + '/' + i
iraf.continuum(name,
name,
order=1,
ask='no',
logfile=setup + '/norm_log')
def psfmeasure(image,
coords,
radius,
output='STDOUT',
size='FWHM',
pxscale=None):
iraf.noao(_doprint=0)
iraf.obsutil(_doprint=0)
if size == 'all':
sname = ['FWHM', 'GFWHM', 'MFWHM']
tbls = []
for s in sname:
stbl = psfmeasure(image, coords, radius, output, s, pxscale)
tbls.append(stbl)
tbl = join(tbls[0], tbls[1])
tbl = join(tbl, tbls[2])
return tbl
results = iraf.obsutil.psfmeasure(image,
coords='mark1',
size=size,
imagecur=coords,
display='no',
radius=radius,
logfile='',
Stdout=1,
StdoutG="dev$null",
scale=1)
#print results
results = results[2:4]
results[0] = results[0].strip()
results = {k: v for k, v in zip(results[0].split(), results[1].split())}
for k in results.keys():
try:
results[k] = np.float(results[k])
except ValueError:
continue
tbl = Table([results])
tbl = tbl[[k for k in P_COLMAP.keys() if k in tbl.colnames]]
for k, v in P_COLMAP.iteritems():
if k in tbl.colnames:
tbl.rename_column(k, v)
fwhmcol = tbl.colnames[-1]
tbl[fwhmcol] /= 2.0 # make hwhm
if pxscale:
tbl.add_column(
Column(tbl[fwhmcol] * u.pix * pxscale,
name='%s_s' % fwhmcol,
unit=u.arcsec,
format='%.3f'))
tbl[fwhmcol].unit = u.pix
return tbl
def psf(args):
""" Calculate the PSF of an image.
"""
# Load iraf packages: phot, pstselect, psf will be needed
iraf.noao(_doprint=0)
iraf.digiphot(_doprint=0)
iraf.module.daophot(_doprint=0)
# Read the seeing and sigma of the sky from the header
seeing, sigma = utils.get_from_header(args.input, args.FWHM_key, args.sigma)
# Do photometry on the image
#print "photometry: \n"
photfile_name = args.input + ".mag.1"
utils.if_exists_remove(photfile_name)
iraf.module.phot(args.input, output=photfile_name, coords=args.stars,
wcsin=args.coords, fwhm=seeing,
sigma=sigma, datamax=args.maxval, datamin=args.minval,
ccdread=args.ron_key, gain=args.gain_key, exposure=args.expt_key,
airmass=args.airm_key, annulus=6*seeing, dannulus=3*seeing,
apert=2*seeing, verbose="no", verify="no", interac="no")
# Select stars on the image
#print "pstselect: \n"
pstfile_name = args.input + ".pst.1"
utils.if_exists_remove(pstfile_name)
iraf.module.pstselect(args.input, photfile=photfile_name, pstfile=pstfile_name,
maxnpsf=20, fwhm=seeing, sigma=sigma,
datamax=args.maxval, ccdread=args.ron_key, gain=args.gain_key,
exposure=args.expt_key, function="auto", nclean=1,
psfrad=2*seeing, fitrad=seeing, maxnstar=20, verbose="no",
verify="no")
# Build psf of the stars
#print "psf: \n"
psffile_table = args.input + ".psf.1.fits" # iraf keeps adding the .fits :(
psgfile_name = args.input + ".psg.1"
pstfile_name2 = args.input + ".pst.2"
utils.if_exists_remove(psffile_table,psgfile_name, pstfile_name2)
iraf.module.psf( args.input, photfile=photfile_name, pstfile=pstfile_name,
groupfile=psgfile_name, opstfile=pstfile_name2,
psfimage=psffile_table,fwhm=seeing, sigma=sigma, datamax=args.maxval,
datamin=args.minval, ccdread=args.ron_key, gain=args.gain_key,
exposure=args.expt_key, function="moffat25", nclean=1,
psfrad=12, fitrad=seeing, maxnstar=20, interactive="no",
varorder=-1, verbose="no",verify="no")
# Use seepsf to build the image of the psf
psffile_name = args.input + ".psf.fits"
utils.if_exists_remove(psffile_name)
iraf.module.seepsf(psffile_table, psffile_name)
return psffile_name
def combine_flat(lstfile):
if os.path.isfile('Halogen.fits'):
print 'remove Halogen.fits'
os.remove('Halogen.fits')
if os.path.isfile('Resp.fits'):
print 'remove Resp.fits'
os.remove('Resp.fits')
iraf.noao()
iraf.imred()
iraf.ccdred()
iraf.flatcombine(input='tbo//@' + lstfile,
output='Halogen',
combine='average',
reject='crreject',
ccdtype='',
process=False,
subsets=False,
delete=False,
clobber=False,
scale='mode',
statsec='',
nlow=1,
nhigh=1,
nkeep=1,
mclip=True,
lsigma=3.0,
hsigma=3.0,
rdnoise='rdnoise',
gain='gain',
snoise=0.0,
pclip=-0.5,
blank=1.0)
iraf.twodspec()
iraf.longslit(dispaxis=2,
nsum=1,
observatory='Lijiang',
extinction=func.config_path + os.sep + 'LJextinct.dat',
caldir=func.std_path + os.sep,
interp='poly5')
iraf.response(calibration='Halogen',
normalization='Halogen',
response='Resp',
interactive=True,
threshold='INDEF',
sample='*',
naverage=1,
function='spline3',
order=25,
low_reject=10.0,
high_reject=10.0,
niterate=1,
grow=0.0,
graphics='stdgraph',
cursor='')
def darkcom(input_dark):
import glob
import os, sys
import numpy as np
from pyraf import iraf
from astropy.io import fits
from astropy.io import ascii
curdir = os.getcwd()
curdate = curdir.split('/')[-1]
#dark = ", ".join(input_dark)
iraf.noao()
iraf.imred()
iraf.ccdred()
iraf.ccdred.setinst(instrume='camera', directo='/iraf/iraf/noao/imred/ccdred/ccddb/', query='q', review='no')
#iraf.chdir('./dark')
#dark = glob.glob('cal*dk*.fit')
#dark = ascii.read('dark.list', guess=True, data_start=0)
'''
allexptime = []
for i in range(len(dark)) :
hdr = fits.getheader(dark[i])
allexptime.append(hdr['exptime'])
expset = set(allexptime)
exptime = list(sorted(expset))
i=0
for i in range(len(exptime)) :
print('Find images with exptime of '+str(exptime[i]))
imlist = []
for j in range(len(dark)) :
hdr = fits.getheader(dark[j])
if hdr['exptime'] == exptime[i] :
imlist.append(dark[j])
else :
pass
print(imlist)
input_name = 'dark'+str(int(exptime[i]))+'.list'
output_name = curdate+'_dark'+str(int(exptime[i]))+'.fits'
#input_name = output_name[:-5]+'.list'
f=open(input_name,'w+')
for k in range(len(imlist)) :
f.write(imlist[k]+'\n')
f.close()
'''
#output_name = curdate+'_dark'+str(int(exptime[i]))+'.fits'
output_name = curdate+'_'+input_dark[:-5]+'.fits'
print('Darkcombine is running...')
iraf.imstat(images='z@'+input_dark)
iraf.darkcombine(input='z@'+input_dark, output=output_name, combine='median', reject='minmax', process='no', scale='none', ccdtype='' )
#os.system('/usr/bin/cp '+output_name+' ../')
os.system('/usr/bin/cp '+output_name+' /data1/KHAO/MDFTS/red/masterdark/')
#os.system('/usr/bin/rm d*.list')
#iraf.chdir('../')
iraf.dir('.')
print('Output master '+output_name+' is created.')
def findStars(frame,fwhm,sigma,thresh,extra="",overwrite=True,interactive=True):
if overwrite:
if os.path.isfile(frame+".fullcoo"):
os.system("rm "+frame+".fullcoo")
iraf.noao()
iraf.digiphot()
iraf.daophot()
iraf.datapars.setParam("fwhmpsf",fwhm)
iraf.datapars.setParam("sigma",sigma)
iraf.findpars.setParam("thresh",thresh)
foo = iraf.daofind(image=frame+extra,output=frame+".fullcoo",Stdin=cr,Stdout=1)
def combinebias(filename):
iraf.noao()
iraf.imred()
iraf.ccdred()
iraf.zerocombine(input = 'o//@' + filename
, output = 'Zero', combine = 'average', reject = 'minmax'
, ccdtype = '', process = False, delete = False
, clobber = False, scale = 'none', statsec = ''
, nlow = 0, nhigh = 1, nkeep = 1, mclip = True
, lsigma = 3.0, hsigma = 3.0, rdnoise = 'rdnoise'
, gain = 'gain', snoise = 0.0, pclip = -0.5, blank = 0.0)
def standard_sens(infile, caldir=')_.caldir', noext=False, overwrite=False):
print('\n#############################')
print('Deriving sensitivity funciton')
# Not to display items in IRAF packages
sys.stdout = open('/dev/null', 'w')
iraf.noao()
iraf.onedspec()
sys.stdout = sys.__stdout__ # Back to the stadard output
basename = fits.getval(infile, 'FRAMEID')
std = basename + '.std'
if noext:
extinction = ''
else:
extinction = fi.filibdir + 'mkoextinct.dat'
if os.path.isfile(std) and not overwrite:
print('\t The output file of IRAF STANDARD '+\
'task already exits. '+std)
print('\t STANDARD is skipped.')
else:
if overwrite:
print('Removing ' + std)
try:
os.remove(std)
except:
pass
iraf.standard(infile, std, extinction=extinction,\
caldir=caldir, beam_sw='no', aperture='')
print('Output file of IRAF STANDARD task: ' + std)
sens = basename + '.sens.fits'
if os.path.isfile(sens) and not overwrite:
print('\t The output file of IRAF SENSFUNC task already exits. ' +
sens)
print('\t SENSFUNC is skipped.')
else:
if overwrite:
print('Removing ' + sens)
try:
os.remove(sens)
except:
pass
iraf.sensfunc(std, sens, aperture='', ignoreaps='yes',\
extinction=extinction,\
logfile='sensfunc.log')
print('Output file of IRAF SENSFUNC task: ' + sens)
return sens, True
def get_masked_image(img):
# Running IRAF
iraf.noao(_doprint=0)
mask = make_mask_cross(img)
masked = img.replace(".fits", "_masked.fits")
if (os.path.isfile(masked)):
os.remove(masked)
iraf.imarith(img, "*", mask, masked)
return masked
def get_masked_image(img):
# Running IRAF
iraf.noao(_doprint=0)
mask = make_mask_cross(img)
masked = img.replace(".fits", "_masked.fits")
if (os.path.isfile(masked)):
os.remove(masked)
iraf.imarith(img, "*", mask, masked)
return masked
def standard(namelst):
iraf.noao()
iraf.twodspec()
iraf.longslit(dispaxis=2,
nsum=1,
observatory='ca',
extinction=extpath,
caldir=stdpath)
std_fitsname = namelst[0]
stdname, stdmag, stdmagband = standard_star_info(std_fitsname)
wid, sep = get_band_width_sep(stdname)
print('<<<<<the standard star is ', stdname, '>>>>>')
print std_fitsname
if os.path.isfile('Std'):
print('remove file Std')
os.remove('Std')
iraf.standard(
input=std_fitsname,
output='Std',
samestar=True,
beam_switch=False,
apertures='',
bandwidth=wid,
bandsep=sep, # 30.0 20.0
fnuzero=3.6800000000000E-20,
extinction=extpath,
caldir=stdpath,
observatory='ca',
interact=True,
graphics='stdgraph',
cursor='',
star_name=stdname,
airmass='',
exptime='',
mag=stdmag,
magband=stdmagband,
teff='',
answer='yes')
if os.path.isfile('Sens.fits'):
print('remove file Sens.fits')
os.remove('Sens.fits')
iraf.sensfunc(standards='Std',
sensitivity='Sens',
extinction=extpath,
function='spline3',
order=15)
iraf.splot('Sens')
iraf.flpr()
def extractComps(assignments, dorefspec=1):
'''This task takes a dictionary 'assignments' which has keywords equal
to the objects spectrum and value equal to the comparison spectrum
which should be used for the object spectrum. You could use
closest_time_pos() to figure this out, for example. The apertures
of each comp are then extracted using apall and the object's spectrum
as a reference. Finally, the object's headers are updated using
the REFSPEC1 keyword (unless dorefspec=0).'''
iraf.noao()
iraf.imred()
iraf.echelle()
# First things first, we save the old paramter list.
iraf.apall.saveParList(filename='temp.apall.par')
# iraf.apall.unlearn()
iraf.apall.format = 'echelle'
# now, get the associated list of references and comps:
stuff = assignments
for ref in stuff.keys():
print 'extracting %s using %s as reference' % (stuff[ref], ref)
comp = stuff[ref]
if iraf.imaccess(re.sub('\.fits', '.ec.fits', comp)):
print 'Extracted comparison exists, skipping...'
else:
iraf.apall(input=comp,
references=re.sub('\.ec', '', ref),
interactive=0,
find=0,
recenter=0,
resize=0,
edit=0,
trace=0,
fittrace=0,
extract=1,
extras=0,
review=0)
# Now, since we've used them to extract the spectra, we can assign
# them using refspec:
# print "now assigning reference spectrum"
if dorefspec:
iraf.hedit(images=ref,
fields='REFSPEC1',
value=re.sub('\.fits', '.ec', comp),
add=1,
addonly=1,
verify=0,
show=1)
iraf.apall.setParList(ParList='temp.apall.par')
def flatcom(input_flat='zFLAT*.fit'):
import glob
import os, sys
import itertools
import numpy as np
from pyraf import iraf
from astropy.io import fits
from astropy.io import ascii
iraf.noao()
iraf.imred()
iraf.ccdred()
iraf.ccdred.setinst(instrume='camera', directo='/iraf/iraf/noao/imred/ccdred/ccddb/', query='q', review='no')
# Filter classification
calflat = glob.glob(input_flat)
allfilter = []
i=0
for i in range(len(calflat)) :
hdr = fits.getheader(calflat[i])
allfilter.append(hdr['filter'])
filterset = set(allfilter)
infilter = list(sorted(filterset))
i=0
for i in range(len(infilter)) :
print('Find images with filter of '+str(infilter[i]))
imlist = []
for j in range(len(calflat)) :
hdr = fits.getheader(calflat[j])
if hdr['filter'] == infilter[i] :
imlist.append(calflat[j])
else :
pass
print(imlist)
imlist.sort()
input_name = str(infilter[i])+'flat.list'
k=0
f=open(input_name,'w+')
for k in range(len(imlist)) :
f.write(imlist[k]+'\n')
f.close()
output_name = input_name[:-5]+'.fits'
#iraf.flatcombine(input='@'+input_name, output=output_name, combine='average', reject='crreject', process='no', scale='mode', ccdtype='', lsigma='3.', hsigma='3.' )
iraf.flatcombine(input='@'+input_name, output=output_name, combine='median', reject='minmax', process='no', scale='mode', ccdtype='')
print(output_name+' is created. Normalizing...')
data, newhdr = fits.getdata(output_name, header=True)
x = np.mean(data)
nimage = data/x
newflat_name = curdate+'_n'+str(infilter[i])+'flat.fits'
fits.writeto(newflat_name, nimage, header=newhdr, overwrite=True)
#os.system('/usr/bin/cp '+newflat_name+' ../')
os.system('/usr/bin/cp '+newflat_name+' /data1/KHAO/MDFTS/red/masterflat_'+infilter[i]+'/')
print('Normalised master flats are created.')
iraf.imstat(images='*n?flat.fits')
def thar_ref(object_b_fn_ec, wave_ref, colour):
# Import IRAF modules:
iraf.noao(_doprint=0)
iraf.onedspec(_doprint=0)
# iraf.echelle(_doprint=0)
parList = "wavelength_calibration_refspectra.par"
if os.path.isfile(object_b_fn_ec) == True:
if os.path.isfile(wave_ref) == True:
if os.path.isfile(parList) == True:
# Assign reference spectra to input object spectra using IRAF task refspectra:
iraf.refspectra.setParList(ParList="wavelength_calibration_refspectra.par")
iraf.refspectra(input=object_b_fn_ec, references=wave_ref)
print ' '
print '~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~'
print colour.capitalize() + ' object spectrum '
print '(' + str(object_b_fn_ec) + ') '
print 'assigned to ' + str(colour) + ' reference spectrum '
print '(' + str(wave_ref) + ') successfully. '
print '~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~'
print ' '
else:
print ' '
print '~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~'
print 'Wavelength reference IRAF .par file '
print str(parList)
print 'does not exist. Exiting script. '
print '~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~'
print ' '
print ' '
sys.exit()
else:
print ' '
print '~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~'
print 'ThAr reference frame '
print str(wave_ref)
print 'does not exist. Exiting script. '
print '~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~'
print ' '
print ' '
sys.exit()
else:
print ' '
print '~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~'
print 'Input frame '
print str(object_b_fn_ec)
print 'does not exist. Exiting script. '
print '~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~'
print ' '
print ' '
sys.exit()
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 main():
iraf.noao()
iraf.imred()
iraf.ccdred()
print '=' * 20, 'Overscan', '=' * 20
correct_overscan('spec.lst')
print '=' * 20, 'combine bias', '=' * 20
combine_bias('bias.lst')
print '=' * 20, 'correct bias', '=' * 20
correct_bias('spec_no_bias.lst', 'bias_spec.fits')
name = os.popen('ls object*.lst').readlines()
name = [i.split()[0] for i in name]
for i in name:
ntrim_flat(i)
def fitcoord_dispersion(basenames, overwrite=False):
print('\n#############################')
print('Getting the dispersion map.')
# entering the channel image directory.
print('\t Entering the channel image directory, \"'+fi.chimagedir+'\".')
os.chdir(fi.chimagedir)
database='database'
function='chebyshev'
xorder=3
yorder=5
logfiles='STDOUT,fitcoord_dispersion.log'
# for multi-comparison images
combine = 'yes'
# 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
for i in range(1,25):
fcfile = basenames[0] + '.ch%02d'%i
if os.path.isfile(database + '/fc' + fcfile) and overwrite == False:
print('\t FC file already exits: ' + fcfile)
else:
if os.path.isfile(database + '/fc' + fcfile) and overwrite == True:
print('Removing ' + fcfile)
try:
os.remove(database + '/fc' + fcfile)
except:
pass
infiles = ''
for basename in basenames:
infiles = infiles + basename + '.ch%02d,'%i
iraf.fitcoord(infiles[:len(infiles)-1], fitname=fcfile, interactive='yes', \
combine=combine, database=database, deletions='',\
function = function,xorder=xorder, yorder=yorder,\
logfiles=logfiles, graphics='stdgraph', cursor='')
print('Going back to the original directory.')
os.chdir('..')
return
def marksn2(img,fitstab,frame=1,fitstab2='',verbose=False):
from pyraf import iraf
from numpy import array #,log10
import lsc
iraf.noao(_doprint=0)
iraf.digiphot(_doprint=0)
iraf.daophot(_doprint=0)
iraf.images(_doprint=0)
iraf.imcoords(_doprint=0)
iraf.proto(_doprint=0)
iraf.set(stdimage='imt1024')
hdr=lsc.util.readhdr(fitstab)
_filter=lsc.util.readkey3(hdr,'filter')
column=lsc.lscabsphotdef.makecatalogue([fitstab])[_filter][fitstab]
rasex=array(column['ra0'],float)
decsex=array(column['dec0'],float)
if fitstab2:
hdr=lsc.util.readhdr(fitstab2)
_filter=lsc.util.readkey3(hdr,'filter')
_exptime=lsc.util.readkey3(hdr,'exptime')
column=lsc.lscabsphotdef.makecatalogue([fitstab2])[_filter][fitstab2]
rasex2=array(column['ra0'],float)
decsex2=array(column['dec0'],float)
iraf.set(stdimage='imt1024')
iraf.display(img + '[0]',frame,fill=True,Stdout=1)
vector=[]
for i in range(0,len(rasex)):
vector.append(str(rasex[i])+' '+str(decsex[i]))
xy = iraf.wcsctran('STDIN',output="STDOUT",Stdin=vector,Stdout=1,image=img+'[0]',inwcs='world',units='degrees degrees',outwcs='logical',\
formats='%10.1f %10.1f',verbose='yes')[3:]
iraf.tvmark(frame,'STDIN',Stdin=list(xy),mark="circle",number='yes',label='no',radii=10,nxoffse=5,nyoffse=5,color=207,txsize=2)
if verbose:
# print 2.5*log10(_exptime)
for i in range(0,len(column['ra0'])):
print xy[i],column['ra0'][i],column['dec0'][i],column['magp3'][i],column['magp4'][i],column['smagf'][i],column['magp2'][i]
if fitstab2:
vector2=[]
for i in range(0,len(rasex2)):
vector2.append(str(rasex2[i])+' '+str(decsex2[i]))
xy1 = iraf.wcsctran('STDIN',output="STDOUT",Stdin=vector2,Stdout=1,image=img+'[0]',inwcs='world',units='degrees degrees',outwcs='logical',\
formats='%10.1f %10.1f',verbose='yes')[3:]
iraf.tvmark(frame,'STDIN',Stdin=list(xy1),mark="cross",number='yes',label='no',radii=10,nxoffse=5,nyoffse=5,color=205,txsize=2)
def gcDAR():
iraf.noao()
obs = iraf.noao.observatory
# Set up Keck observatory info
obs(command="set", obsid="keck")
keck = ephem.Observer()
keck.long = math.radians(-obs.longitude)
keck.lat = math.radians(obs.latitude)
keck.elev = obs.altitude
keck.pressure = 800.0
keck.temp = 278.0
# Date of Observations: 06maylgs1
keck.date = '2006/05/03 %d:%d:%f' % (obs.timezone+3, 28, 46.33)
# Set up the galactic center target
sgra = ephem.FixedBody()
sgra._ra = ephem.hours("17:45:40")
sgra._dec = ephem.degrees("-29:00:10")
sgra._epoch = 2000
sgra.compute()
pos2 = ephem.FixedBody()
pos2._ra = ephem.hours("17:45:40")
pos2._dec = ephem.degrees("-29:00:00")
pos2._epoch = 2000
pos2.compute()
print 'Date of Obs: ', keck.date
sgra.compute(keck)
pos2.compute(keck)
print 'Azimuth of Objects: %s vs. %s' % (sgra.az, pos2.az)
for ii in range(15):
keck.lat = math.radians(obs.latitude - (ii*2))
sgra.compute(keck)
pos2.compute(keck)
angAbs = ephem.separation((sgra.ra, sgra.dec), (pos2.ra, pos2.dec))
angAbs *= 206265.0
angRel = ephem.separation((sgra.az, sgra.alt), (pos2.az, pos2.alt))
angRel *= 206265.0
angDiff = angAbs - angRel
print 'Sgr A*: %s vs. %s deltaR = %5d (muas)' % \
(sgra.alt, pos2.alt, angDiff*1e6)
def gcDAR():
iraf.noao()
obs = iraf.noao.observatory
# Set up Keck observatory info
obs(command="set", obsid="keck")
keck = ephem.Observer()
keck.long = math.radians(-obs.longitude)
keck.lat = math.radians(obs.latitude)
keck.elev = obs.altitude
keck.pressure = 800.0
keck.temp = 278.0
# Date of Observations: 06maylgs1
keck.date = '2006/05/03 %d:%d:%f' % (obs.timezone + 3, 28, 46.33)
# Set up the galactic center target
sgra = ephem.FixedBody()
sgra._ra = ephem.hours("17:45:40")
sgra._dec = ephem.degrees("-29:00:10")
sgra._epoch = 2000
sgra.compute()
pos2 = ephem.FixedBody()
pos2._ra = ephem.hours("17:45:40")
pos2._dec = ephem.degrees("-29:00:00")
pos2._epoch = 2000
pos2.compute()
print 'Date of Obs: ', keck.date
sgra.compute(keck)
pos2.compute(keck)
print 'Azimuth of Objects: %s vs. %s' % (sgra.az, pos2.az)
for ii in range(15):
keck.lat = math.radians(obs.latitude - (ii * 2))
sgra.compute(keck)
pos2.compute(keck)
angAbs = ephem.separation((sgra.ra, sgra.dec), (pos2.ra, pos2.dec))
angAbs *= 206265.0
angRel = ephem.separation((sgra.az, sgra.alt), (pos2.az, pos2.alt))
angRel *= 206265.0
angDiff = angAbs - angRel
print 'Sgr A*: %s vs. %s deltaR = %5d (muas)' % \
(sgra.alt, pos2.alt, angDiff*1e6)
def apall(lstfile):
iraf.noao()
iraf.twodspec()
iraf.apextract(dispaxis = 2, database = 'database')
f = open(lstfile)
l = f.readlines()
f.close()
l = [tmp.split('\n')[0] for tmp in l]
path = os.getcwd()
for i in l:
infile = 'wftbo' + i
outfile = 'awftbo' + i
while True:
if os.path.isfile(outfile):
print('remove ' + outfile)
os.remove(outfile)
delfile = path + os.sep + 'database/ap' + infile[0:-5]
if os.path.isfile(delfile):
print('remove ' + delfile)
os.remove(delfile)
iraf.apall(input = infile
, output = outfile, apertures = 2, format = 'multispec'
, references = '', profiles = '', interactive = True
, find = True, recenter = True, resize = False
, edit = True, trace = True, fittrace = True
, extract = True, extras = True, review = True
, line = 'INDEF', nsum = 10, lower = -15.0
, upper = 15.0, apidtable = '', b_function = 'chebyshev'
, b_order = 2, b_sample = '-50:-26,26:50', b_naverage = -25
, b_niterate = 1, b_low_reject = 3.0, b_high_reject = 3.0
, b_grow = 0.0, width = 5.0, radius = 10.0
, threshold = 0.0, nfind = 2, minsep = 5.0
, maxsep = 100000.0, order = 'increasing', aprecenter = ''
, npeaks = 'INDEF', shift = True, llimit ='INDEF'
, ulimit = 'INDEF', ylevel = 0.1, peak = True
, bkg = True, r_grow = 0.0, avglimits = False
, t_nsum = 20, t_step = 10, t_nlost = 3, t_function = 'legendre'
, t_order = 7, t_sample = '*', t_naverage = 1
, t_niterate = 1, t_low_reject = 3.0, t_high_reject = 3.0
, t_grow = 0.0, background = 'fit', skybox = 1
, weights = 'variance', pfit = 'fit1d', clean = True
, saturation = 'INDEF', readnoise = 9.4, gain = 0.35
, lsigma = 4.0, usigma = 4.0, nsubaps = 1)
iraf.flpr()
sspecplot.sspecplot(outfile)
getval = raw_input('Are you need repeat apall,may be clean should be close(r/n)')
if getval != 'r':
break
def fwhm(directory,folders):
iraf.noao(_doprint=0)
iraf.obsutil(_doprint=0)
iraf.unlearn("psfmeasure")
rootdir = par.rootdir[0]
dir_contents = os.listdir(directory+'/data')
ds9s = [fn for fn in dir_contents if fn.startswith('ds9') and fn.endswith('.reg')]
ds9 = directory+'/data/'+ds9s[0]
print "\nMeasuring the fwhm of selected reference stars..."
iraf.noao.obsutil.psfmeasure.coords = "mark1"
iraf.noao.obsutil.psfmeasure.display = "no"
iraf.noao.obsutil.psfmeasure.size = "FWHM"
iraf.noao.obsutil.psfmeasure.scale = "1"
iraf.noao.obsutil.psfmeasure.radius = "11"
iraf.noao.obsutil.psfmeasure.swidth = "15"
iraf.noao.obsutil.psfmeasure.iterati = "1"
iraf.noao.obsutil.psfmeasure.imagecu = ds9
iraf.noao.obsutil.psfmeasure.graphcur = rootdir+"/src/q.reg"
iraf.noao.obsutil.psfmeasure.logfile = directory+"/data/fwhm.log"
if os.path.isfile(directory+"/data/fwhm.log"):
os.system("rm "+directory+"/data/fwhm.log")
imgs = [fn for fn in dir_contents if fn.startswith(par.image_name[0]) and fn.endswith(par.image_name[1])]
imgs = sorted(imgs)
for i in range(len(imgs)):
iraf.noao.obsutil.psfmeasure.imagecu = ds9
iraf.noao.obsutil.psfmeasure(directory+'/data/'+imgs[i])
N_stars = len(ds9)
fwhm = [[] for _ in range(len(imgs))]
values = [ line for line in open(directory+"/data/fwhm.log") if '.' in line and 'NOAO' not in line]
j = 0
for i in range(len(values)):
if values[i][2:9] == 'Average':
j += 1
if values[i][2:9] != 'Average':
fwhm[j].append(float(values[i][41:47]))
f = open(directory+'/data/fwhm.txt', 'w+')
for i in range(len(imgs)):
fwhm[i] = np.array(fwhm[i])
print >> f, np.median(fwhm[i]), imgs[i]
f.close()
def main():
config = {'combine': 'average', 'reject': 'minmax', 'nlow': 3, 'nhigh': 3}
path = '/btfidr/data/20130902/007/cam2'
kernel = 'biasEMOFF_A*'
list_of_files = glob.glob(os.path.join(path, kernel))
random.shuffle(list_of_files)
number_of_files = len(list_of_files)
iraf.noao(_doprint=0)
iraf.imred(_doprint=0)
iraf.ccdred(_doprint=0)
n, a, s = [], [], []
for l in range(2, number_of_files):
temp_list = 'list'
buffer = open(temp_list, mode='w')
for i in range(l):
buffer.write(list_of_files[i] + "\n")
buffer.close()
iraf.imcombine(input='@' + temp_list,
output='temp_output.fits',
**config)
data = pyfits.getdata('temp_output.fits')[700:899, 700:899]
n.append(l)
a.append(np.average(data))
s.append(np.std(data))
os.remove('temp_output.fits')
os.remove(temp_list)
output = 'output.dat'
buffer = open(output, mode='w')
for key in config.keys():
buffer.write('# {}: {}\n'.format(key, config[key]))
buffer.write('# N\tAVG\tSTD\n')
for i in range(len(n)):
buffer.write(u'{0:3d}\t{1:5.1f}\t{2:5.1f}\n'.format(n[i], a[i], s[i]))
buffer.close()
return 0
def findaperture(img, _interactive=False):
# print "LOGX:: Entering `findaperture` method/function in %(__file__)s" %
# globals()
import re
import string
import os
from pyraf import iraf
import ntt
iraf.noao(_doprint=0, Stdout=0)
iraf.imred(_doprint=0, Stdout=0)
iraf.specred(_doprint=0, Stdout=0)
toforget = ['specred.apfind']
for t in toforget:
iraf.unlearn(t)
iraf.specred.databas = 'database'
iraf.specred.dispaxi = 2
iraf.specred.apedit.thresho = 0
dv = ntt.dvex()
grism = ntt.util.readkey3(ntt.util.readhdr(img), 'grism')
if _interactive:
_interac = 'yes'
_edit = 'yes'
else:
_interac = 'no'
_edit = 'no'
if os.path.isfile('database/ap' + re.sub('.fits', '', img)):
ntt.util.delete('database/ap' + re.sub('.fits', '', img))
xx = iraf.specred.apfind(img,
interac=_interac,
find='yes',
recenter='yes',
edit=_edit,
resize='no',
aperture=1,
Stdout=1,
nfind=1,
line=dv['line'][grism],
nsum=50,
mode='h')
try:
for line in open('database/ap' + re.sub('.fits', '', img)):
if "center" in line:
center = float(string.split(line)[1])
except:
center = 9999
return center
def ImportPackages():
iraf.noao(_doprint=0)
iraf.rv(_doprint=0)
iraf.imred(_doprint=0)
iraf.kpnoslit(_doprint=0)
iraf.ccdred(_doprint=0)
iraf.astutil(_doprint=0)
iraf.keywpars.setParam('ra','CAT-RA')
iraf.keywpars.setParam('dec','CAT-DEC')
iraf.keywpars.setParam('ut','UT')
iraf.keywpars.setParam('utmiddl','UT-M_E')
iraf.keywpars.setParam('exptime','EXPTIME')
iraf.keywpars.setParam('epoch','CAT-EPOC')
iraf.keywpars.setParam('date_ob','DATE-OBS')
iraf.keywpars.setParam('hjd','HJD')
iraf.keywpars.setParam('mjd_obs','MJD-OBS')
iraf.keywpars.setParam('vobs','VOBS')
iraf.keywpars.setParam('vrel','VREL')
iraf.keywpars.setParam('vhelio','VHELIO')
iraf.keywpars.setParam('vlsr','VLSR')
iraf.keywpars.setParam('vsun','VSUN')
iraf.keywpars.setParam('mode','ql')
iraf.fxcor.setParam('continu','both')
iraf.fxcor.setParam('filter','none')
iraf.fxcor.setParam('rebin','smallest')
iraf.fxcor.setParam('pixcorr','no')
iraf.fxcor.setParam('apodize','0.2')
iraf.fxcor.setParam('function','gaussian')
iraf.fxcor.setParam('width','INDEF')
iraf.fxcor.setParam('height','0.')
iraf.fxcor.setParam('peak','no')
iraf.fxcor.setParam('minwidt','3.')
iraf.fxcor.setParam('maxwidt','21.')
iraf.fxcor.setParam('weights','1.')
iraf.fxcor.setParam('backgro','0.')
iraf.fxcor.setParam('window','INDEF')
iraf.fxcor.setParam('wincent','INDEF')
iraf.fxcor.setParam('verbose','long')
iraf.fxcor.setParam('imupdat','no')
iraf.fxcor.setParam('graphic','stdgraph')
iraf.fxcor.setParam('interac','yes')
iraf.fxcor.setParam('autowri','yes')
iraf.fxcor.setParam('autodra','yes')
iraf.fxcor.setParam('ccftype','image')
iraf.fxcor.setParam('observa','lapalma')
iraf.fxcor.setParam('mode','ql')
return 0
def ReidentifyTask(self, ArcFile, Fits_Folder, ):
iraf.noao(_doprint=0)
iraf.twodspec(_doprint=0)
iraf.longslit(_doprint=0)
ReidentifyConf = self.ReidentifyAttributes(ArcFile, Fits_Folder)
#Display the equivalent command in IRAF
Command = self.printIrafCommand('reidentify', ReidentifyConf)
print '--- Using the command'
print Command
iraf.twodspec.longslit.reidentify(**ReidentifyConf)
return
def FitcoordsTask(self, ArcFile, Fits_Folder):
iraf.noao(_doprint=0)
iraf.twodspec(_doprint=0)
iraf.longslit(_doprint=0)
FitcoordsConf = self.FitcoordsAttributes(ArcFile, Fits_Folder)
#Display the equivalent command in IRAF
Command = self.printIrafCommand('fitcords', FitcoordsConf)
print '--- Using the command'
print Command
iraf.twodspec.longslit.fitcoords(**FitcoordsConf)
return
def set_instrument():
"""
Needed so that when we do flatcombine iraf doesn't try to do flat correction
etc. Might need to run before calling any other function. Not sure if specphot
is appropriate but seems to work.
"""
iraf.noao(_doprint=0)
iraf.imred(_doprint=0)
iraf.ccdred(_doprint=0)
iraf.setinstrument.setParam('instrument','specphot')
iraf.setinstrument()
return None
def inspect(self, event):
# Pull up the current TDSS spectrum in IRAF SPLOT
####
global TDSS_fiber_indices, TDSS_fiber_index
global plate, mjd
# load packages; splot is in the onedspec package, which is in noao.
# the special keyword _doprint=0 turns off displaying the tasks
# when loading a package.
iraf.noao(_doprint=0)
iraf.onedspec(_doprint=0)
# set/view IRAF task parameter.
#iraf.onedspec.splot.save_file = "splot_%s.log" % (root,)
# call IRAF task, and specify some parameters.
iraf.onedspec.splot('spPlate-'+str(plate)+'-'+str(mjd)+'.fits[0][*,'+str(TDSS_fiber_index+1)+']')
def atmofile(imgstd, imgout=''):
# print "LOGX:: Entering `atmofile` method/function in %(__file__)s" %
# globals()
from pyraf import iraf
import os
import ntt
iraf.noao(_doprint=0)
iraf.onedspec(_doprint=0)
iraf.set(direc=ntt.__path__[0] + '/')
_cursor = 'direc$standard/ident/cursor_sky_0'
if not imgout:
imgout = 'atmo_' + imgstd
os.system('rm -rf ' + imgout)
iraf.noao.onedspec.bplot(imgstd, cursor=_cursor,
spec2=imgstd, new_ima=imgout, overwri='yes')
return imgout
def createMagFile(inputDir, inputFile, useCoordFile, outputFile, fullyAutomatic=False, aperturesString='5,10,15,20', bestSkyAperture='100'):
cr=['\n']
iraf.cd(inputDir)
iraf.noao()
iraf.digiphot()
iraf.apphot()
iraf.phot.setParam('interactive','no')
iraf.centerpars.setParam('cbox','5')
iraf.photpars.setParam('apertures',aperturesString)
iraf.fitskypars.setParam('annulus',bestSkyAperture)
iraf.fitskypars.setParam('dannulus','10')
iraf.phot.setParam('image',inputFile)
iraf.phot.setParam('coords',useCoordFile)
iraf.phot.setParam('output',outputFile)
if fullyAutomatic: ## If you use this option, it will not prompt you for any of the aperture/sky settings
iraf.phot(mode='h',Stdin=cr)
else: # Otherwise, you can change them at will, and get to press enter a bunch
iraf.phot(mode='h')
def calibrate(lstfile):
stdpath = os.path.split(os.path.realpath(__file__))[0] + os.sep + 'standarddir' + os.sep
extpath = os.path.split(os.path.realpath(__file__))[0] + os.sep + 'LJextinct.dat'
iraf.noao()
iraf.twodspec()
iraf.longslit(dispaxis = 2, nsum = 1, observatory = 'Lijiang',
extinction = extpath, caldir = stdpath)
f = open(lstfile)
l = f.readlines()
f.close()
l = [tmp.split('\n')[0] for tmp in l]
for fitname in l:
stdobjname = select_std(fitname)
stdfitname = 'sensawftbo' + stdgroup[stdobjname][0]
iraf.calibrate(input = 'awftbo'+ fitname, output = 'mark_awftbo' + fitname,
extinct = 'yes', flux = 'yes', extinction = extpath,
ignoreaps = 'yes', sensitivity = stdfitname, fnu = 'no')
iraf.splot(images = 'mark_awftbo' + fitname)
def coroverscan(filename):
iraf.noao()
iraf.imred()
iraf.ccdred()
iraf.ccdproc(images = '@' + filename + '//[1]'
, output = '%o%o%@' + filename
, ccdtype = '', max_cache = 0, noproc = False
, fixpix = False, overscan = True, trim = False
, zerocor = False, darkcor = False, flatcor = False
, illumcor = False, fringecor = False, readcor = False
, scancor = False, readaxis = 'line', fixfile = ''
, biassec = '[5:45,1:4612]', trimsec = '', zero = ''
, dark = '', flat = '', illum = '', fringe = ''
, minreplace = 1.0, scantype = 'shortscan', nscan = 1
, interactive = False, function = 'chebyshev', order = 1
, sample = '*', naverage = 1, niterate = 1
, low_reject = 3.0, high_reject = 3.0, grow = 1.0)
iraf.flpr()