'/')[-1][:-4] + 'spec.wavsolpars.pkl'
print "\t\tUnpickling wavelength solution from", pkl_wsol, " ..."
wsol_dict = pickle.load(open(pkl_wsol, 'r'))
# Apply new wavelength solution including barycentric correction
equis = np.arange(data.shape[0])
for order in range(nord1):
#order = 16
#print order
m = order + ro0
chebs = GLOBALutils.Calculate_chebs(equis, m, npix=data.shape[0],\
order0=ro0, ntotal=nord1, Inverse=Inverse_m,nx=ncoef_x,nm=ncoef_m)
WavSol = lbary_ltopo * (
1.0 / m) * GLOBALutils.Joint_Polynomial_Cheby(
wsol_dict['p1'], chebs, ncoef_x, ncoef_m)
spec[0, order, :] = GLOBALutils.ToVacuum(WavSol)
spec[1, order, :] = sci_S['chip1'][order, 1, :]
#spec[1,order,:300] = 0.
spec[2, order, :] = sci_S['chip1'][order, 2, :]
spec[3, order, :] = spec[1, order, :] / sflat['chip1'][order][::-1]
spec[4,
order, :] = spec[2, order, :] * sflat['chip1'][order][::-1]**2
ccoef = GLOBALutils.get_cont_single(spec[0, order],
spec[3, order],
spec[4, order],
ll=1.5,
lu=5,
nc=3)
ratio = np.polyval(ccoef, spec[0, order])
L = np.where(spec[1, order, :] != 0)
spec[5, order, :][L] = spec[3, order, :][L] / ratio[L]
# Apply new wavelength solution including barycentric correction
equis = np.arange(data.shape[1])
del_vels = []
for order in range(n_useful):
m = order + 37
chebs = GLOBALutils.Calculate_chebs(equis,
m,
npix=data.shape[1],
order0=37,
ntotal=n_useful,
Inverse=Inverse_m,
nx=ncoef_x,
nm=ncoef_m)
WavSol = GLOBALutils.ToVacuum(
((1. + 1.0e-6 * psh) / float(m)) *
GLOBALutils.Joint_Polynomial_Cheby(pref, chebs, ncoef_x,
ncoef_m) * lbary_ltopo)
spec[0, order, :] = WavSol
spec[1, order, :] = sci_S[order, 1, :]
if len(np.where(np.isnan(spec[1, order, :]))[0]) > 0:
spec[1, order, :] = sci_Ss[order, :]
spec[2, order, :] = 1. / (spec[1, order, :] / gain +
(ronoise / gain)**2)
blaze = flat_S_n[order] #scipy.signal.medfilt(flat_S[order],21)
spec[3, order, :] = spec[1, order, :] / blaze
spec[4, order, :] = spec[2, order, :] * blaze**2
#cont_coef = continuum.NORM_single(spec[0,order,:],scipy.signal.medfilt(spec[3,order,:],7),orden=3)
cont_coef = GLOBALutils.get_cont_single(spec[0, order],
spec[3, order],
spec[4, order],
ll=1.5,
print('\t\tWavelength calibration:')
print("\t\t\tInstrumental drift:",(1e-6*p_shift)*299792458.0)
# Apply new wavelength solution including barycentric correction
equis = np.arange( data.shape[1] )
if len(mjds_thar) > 1:
p_shift = scipy.interpolate.splev(mjd,tck_shift)
else:
p_shift = 0.
order = ro0
ind = 0
while order < ro0 + n_useful:
oss = order - difo
m = order
chebs = GLOBALutils.Calculate_chebs(equis, m, npix=data.shape[1], order0=ro0, ntotal=n_useful, Inverse=Inverse_m,nx=ncoef_x,nm=ncoef_m)
WavSol = GLOBALutils.ToVacuum( lbary_ltopo * (1.0 + 1.0e-6*p_shift) * (1.0/float(m)) * \
GLOBALutils.Joint_Polynomial_Cheby(p_ref,chebs,ncoef_x,ncoef_m) )
spec[0,ind,:] = WavSol
spec[1,ind,:] = sci_S[oss,1]
spec[2,ind,:] = sci_S[oss,2]
fn = S_flat[oss,1,:]
L = np.where( fn == 0 )[0]
spec[3,ind,:] = spec[1,ind,:] / S_flat[oss,1,:]
spec[4,ind,:] = spec[2,ind] * ( S_flat_n[oss,1,:] ** 2 )
spec[3,ind,L] = 0.
spec[4,ind,L] = 0.
ind+=1
order+=1
ccoefs = GLOBALutils.get_cont(spec[0,:,:],spec[3,:,:])
order = ro0
ind = 0
equis = np.arange(np.shape(thar_wav_Ss)[2])
order = orwa
orre = 0
while orre < nup:
m = order + oro0
chebs = GLOBALutils.Calculate_chebs(equis,
m,
order0=oro0,
ntotal=nup,
npix=len(thar_order),
Inverse=Inverse_m,
nx=ncoef_x,
nm=ncoef_m)
thar_wav_Ss[0, orre, :] = GLOBALutils.ToVacuum(
(1.0 / m) * GLOBALutils.Joint_Polynomial_Cheby(
p1, chebs, ncoef_x, ncoef_m))[::-1]
thar_wav_Ss[1, orre, :] = thar_Ss[orre][::-1]
orre += 1
order += 1
if (os.access(thar_fits_simple_wav, os.F_OK)):
os.remove(thar_fits_simple_wav)
hdu = pyfits.PrimaryHDU(thar_wav_Ss)
hdu.writeto(thar_fits_simple_wav)
#if rms_ms/np.sqrt(NL)<50:
nThAr_ref.append(thar)
nthtimes.append(thtime)
pdict = {
for i in range(spec.shape[1]):
if spec[0,i,0]<6500:
first_o = i
break
last_o = spec.shape[1]
for i in range(spec.shape[1]):
if spec[0,i,0]<4300:
last_o = i
break
spec1 = spec[:,first_o:last_o+1,:]
# Read in mask
ml, mh, weight = np.loadtxt(mask,unpack=True)
ml_v = GLOBALutils.ToVacuum( ml )
mh_v = GLOBALutils.ToVacuum( mh )
# make mask larger accounting for factor ~3 lower res in DUPONT w/r to HARPS
av_m = 0.5*( ml_v + mh_v )
ml_v -= 1.5*(av_m - ml_v)
mh_v += 1.5*(mh_v - av_m)
mask_hw_kms = (GLOBALutils.Constants.c/1e3) * 0.5*(mh_v - ml_v) / av_m
disp = GLOBALutils.get_disp(obname, reffile=reffile)
if disp == 0:
known_sigma = False
if vsini != -999 and vsini != 0.:
disp = vsini
else:
pdict1 = pickle.load(open(wavsol_pkl1,'r'))
global1 = pdict1['p1']
or01 = pdict1['or0']
orwa1 = pdict1['orwa']
oro0 = pdict1['oro0']
final = np.zeros( [3, n_last-orwa1, np.shape(obj_S)[1]] )
equis = np.arange( np.shape(obj_S)[1] )
order = orwa1
orre = or01
final2 = np.zeros( [nn, np.shape(obj_S)[1]] )
while order < n_last:
m = order + oro0
chebs = GLOBALutils.Calculate_chebs(equis, m, order0=oro0, ntotal=ntotal, npix=obj_S.shape[1], Inverse=Inverse_m, nx=ncoef_x,nm=ncoef_m )
WavSol = lbary_ltopo*(1.0/m) * GLOBALutils.Joint_Polynomial_Cheby(global1,chebs,ncoef_x,ncoef_m)
final[0,orre,:] = GLOBALutils.ToVacuum(WavSol[::-1])
final[1,orre,:] = obj_S[orre,:][::-1]
order += 1
orre += 1
final[2,:,:] = dupontutils.get_blaze(final[0,:,:],final[1,:,:])
blaze = np.zeros((2,final.shape[1],final.shape[2]))
blaze[0] = final[0]
blaze[1] = dupontutils.get_blaze(final[0,:,:],final[1,:,:])
if (os.access(dirout+'blaze_f.fits',os.F_OK)):
os.remove( dirout+'blaze_f.fits' )
hdu = pyfits.PrimaryHDU( blaze )
hdu.writeto(dirout+'blaze_f.fits' )
else: