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 dispcor(imlist_name, database='database'):
"""
dispcor -- Dispersion correct and resample spectra
dispcor input output [records]
database -- path in which idXXX file. ex) /data1/SN2019ein/work/SAO_Spectrum/red/20190509/arc/database/
dispcor fcdbstd.ms.fits wfcdbstd.ms.fits
"""
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]
iraf.dispcor(input=inim,
output='w' + inim,
database='database',
linearize='no')
iraf.splot(images='w' + inim)
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)
import os
folderroot = '/Users/lucaizzo/Documents/NOT/test/'
os.chdir(folderroot)
import numpy as np
from astropy.io import fits
from matplotlib import pyplot as plt
import shutil
import sys
from pyraf import iraf
iraf.noao(_doprint=0)
iraf.imred(_doprint=0)
iraf.ccdred(_doprint=0)
iraf.twodspec(_doprint=0)
iraf.longslit(_doprint=0)
iraf.kpnoslit(_doprint=0)
iraf.astutil(_doprint=0)
iraf.onedspec(_doprint=0)
iraf.twodspec.longslit.dispaxis = 2
#read object keywords
for file in os.listdir(os.getcwd()):
if file.endswith('.fits'):
testfile = file
hduo = fits.open(testfile)
#name targets (science & standard)
target = hduo[0].header['OBJECT']
#target2 = 'SP0644p375'
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")
def flux_cal_new(objname, stdobjnames):
print 'run flux_cal...'
iraf.imred()
iraf.kpnoslit()
stdname, stdmag, stdmagband = get_std_name(stdobjnames[0])
print 'the standard star is ' + stdname
stdmag = float(stdmag)
stdairmass, stdexptime = get_fits_airmass_exptime(stdobjnames[0])
scripath = sys.argv[0]
tempindex = scripath.rfind(os.sep)
scripath = scripath[:tempindex]
extpath = scripath + os.sep + 'LJextinct.dat'
calpath = scripath + os.sep + 'standarddir' + os.sep
outname1 = 'std' + stdobjnames[0]
stdobjname = ''
for tempstdname in stdobjnames:
stdobjname = stdobjname + tempstdname + ','
stdobjname = stdobjname[:-1]
if os.path.isfile(outname1):
print 'file %s is already exist' % outname1
else:
print 'run standard...'
print 'make file %s ...' % outname1
iraf.standard(input = stdobjname
, output = outname1, samestar = True, beam_switch = False
, apertures = '', bandwidth = 30.0, bandsep = 20.0
, fnuzero = 3.6800000000000E-20, extinction = extpath
, caldir = calpath, observatory = ')_.observatory'
, interact = True, graphics = 'stdgraph', cursor = ''
, star_name = stdname, airmass = stdairmass, exptime = stdexptime
, mag = stdmag, magband = stdmagband, teff = '', answer = 'yes')
outname2 = 'sens' + stdobjname
if os.path.isfile(outname2):
print 'file %s is already exist' % outname2
else:
print 'run sensfunc...'
print 'make file %s ...' % outname2
iraf.sensfunc(standards = outname1
, sensitivity = outname2, apertures = '', ignoreaps = True
, logfile = 'logfile', extinction = ')_.extinction'
, newextinction = extpath, observatory = 'bao', function = 'spline3'
, order = 6, interactive = True, graphs = 'sr'
, marks = 'plus cross box', colors = '2 1 3 4', cursor =''
, device = 'stdgraph', answer = 'yes')
outname3 = 'c' + objname
if os.path.isfile(outname3):
print 'file %s is already exist' % outname3
else:
print 'run calibrate...'
print 'make file %s ...' % outname3
iraf.calibrate(input = objname
, output = outname3, extinct = True, flux = True
, extinction = extpath, observatory = 'bao', ignoreaps = True
, sensitivity = outname2, fnu = False)
final_outname = 'mark_' + objname
if os.path.isfile(final_outname):
print 'file %s is already exist'
else:
print 'run scopy'
print 'make file %s ...' % final_outname
iraf.scopy(input = outname3
, output = final_outname, w1 = 'INDEF', w2 = 'INDEF'
, apertures = '', bands = 1, beams = '', apmodulus = 0
, format = 'multispec', renumber = False, offset = 0
, clobber = False, merge = False, rebin = True, verbose = False)
print 'splot %s' % final_outname
iraf.splot(images = final_outname)
return final_outname
import sys import os import string from numpy import * import functions import spectype_functions import spectype_numerical_functions import matplotlib import matplotlib.pyplot as plt import pyfits from pyraf import iraf from scipy import interpolate iraf.kpnoslit() iraf.noao() iraf.rv() ################### ### Description ### ################### ### Take input spectrum ### Find chisq in logg - teff space for every reddenining ### Add over reddening ### Find min chisq ### usage: python spectype_main.py file_path file_name ### Takes input params from config_file #################
##############################
### Apply flux calibration ###
##############################
### Check new_data_test to see if we need to create new sensfunc
new_data_test = open("new_data_test").read()
new_data_test = string.split(new_data_test,"\n")[0]
if new_data_test == "True":
### Setup kpnoslit
iraf.kpnoslit(
extinction = program_dir + "flux_data/extinsso.tab",\
caldir = program_dir + "flux_data/",\
observatory = "SSO",\
interp = "poly5",\
dispaxis = 2,\
nsum = "1",\
database = "database",\
verbose = 1,\
logfile = "logfile")
### Run iraf.standard
os.system("rm std")
for i in range(len(SpecPhot_list)):
flux_name = "smoothdiv_"+SpecPhot_list[i] + ".fits"
hdulist = pyfits.open(flux_name)
name = hdulist[0].header['OBJECT']
air_mass = hdulist[0].header['AIRMASS']
exposure_time = hdulist[0].header['EXPTIME']
iraf.standard(
