hdu = GLOBALutils.update_header(hdu, 'HIERARCH OBS ALTITUDE',
h[ih].header['SITEALT'])
hdu = GLOBALutils.update_header(hdu, 'HIERARCH TARG AIRMASS',
h[ih].header['AIRMASS'])
psh = scipy.interpolate.splev(mjd, tck_sh)
# 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
models_path = base + "data/COELHO_MODELS/R_40000b/"
ref_RES = 60000.
# get ThAr closest in time
im = np.argmin(np.absolute(np.array(ThAr_ref_dates) - mjd))
pkl_wsol = dirout + ThAr_ref[im].split(
'/')[-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,
ref_RES = -999
# get ThAr closest in time
im = np.argmin(np.absolute(np.array(ThAr_ref_dates) - mjd))
pkl_wsol = dirout + ThAr_ref[im].split('/')[-1][:-4] + 'spec_' + str(
int(chip)) + '.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[1])
for order in range(nord):
#order = 16
#print order
m = order + ro0
chebs = GLOBALutils.Calculate_chebs(equis, m, npix=data.shape[1],\
order0=ro0, ntotal=nord, 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[order, 1, :]
#spec[1,order,-100:] = 0.
spec[2, order, :] = sci_S[order, 2, :]
spec[3, order, :] = spec[1, order, :] / sflat[order]
spec[4, order, :] = spec[2, order, :] * sflat[order]**2
I = np.where(spec[1, order] != 0)[0]
cont_coef, x, y = hiresutils.get_cont(spec[0, order, I],
scipy.signal.medfilt(
spec[3, order, I], 11),
n=3)
#show()
p0 = np.zeros(npar_wsol)
p0[0] = (32 + 93) * Global_ZP
p1, G_pix, G_ord, G_wav, II, rms_ms, G_res = \
GLOBALutils.Fit_Global_Wav_Solution(All_Pixel_Centers, All_Wavelengths, All_Orders,\
np.ones(All_Intensities.shape), p0, Cheby=use_cheby,\
maxrms=50, Inv=Inverse_m,minlines=minlines_glob,order0=93, \
ntotal=n_useful,npix=len(thar_order),nx=ncoef_x,nm=ncoef_m)
equis = np.arange(thar_S.shape[2])
for order in range(n_useful):
m = order + 93
chebs = GLOBALutils.Calculate_chebs(equis,
m,
npix=thar_S.shape[2],
order0=93,
ntotal=n_useful,
Inverse=Inverse_m,
nx=ncoef_x,
nm=ncoef_m)
WavSol = (1.0 / m) * GLOBALutils.Joint_Polynomial_Cheby(
p1, chebs, ncoef_x, ncoef_m)
thar_data[0, order, :] = WavSol
if (os.access(thar_out, os.F_OK)):
os.remove(thar_out)
hdu = pyfits.PrimaryHDU(thar_data)
hdu = GLOBALutils.update_header(hdu, 'SLITNAME', hd['SLITNAME'])
hdu.writeto(thar_out)
#for orde in np.unique(G_ord):
#for odd in np.unique(G_ord):
# Io = np.where(G_ord == odd)[0]
# plot(G_wav[Io], G_res[Io],'.')
#show()
#print gfd
thar_wav_Ss = np.zeros((2, nup, dthar.shape[1]))
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)
orders_offset = pdict['orders_offset']
orderi = 0
if orders_offset < 0:
orderi = - orders_offset
orderf = nord - 1
if orderf + orders_offset >= n_useful:
orderf = n_useful - orders_offset - 1
final = np.zeros( [11, orderf - orderi + 1, np.shape(obj_S)[2]] )
equis = np.arange( obj_S.shape[2] )
for order in range(orderi,orderf+1):
m = order + oro0
chebs = GLOBALutils.Calculate_chebs(equis, m, order0=oro0, ntotal=n_useful, npix=obj_S.shape[2], 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,order,:] = WavSol
final[1,order,:] = obj_S[order,1,:]
final[2,order,:] = obj_S[order,2,:]
final[3,order,:] = final[1,order,:]/flat[order,1]
final[4,order,:] = final[2,order,:]*(flat[order,1]**2)
ccoef = GLOBALutils.get_cont_single(final[0,order],final[3,order],final[4,order],ll=1.5,lu=5,nc=3)
L = np.where( final[1,order] != 0 )
ratio = np.polyval(ccoef,final[0,order])
final[5,order,:] = final[3,order,:]/ratio
Inan = np.where( np.isnan(final[1,order,:]) == True )[0]
final[5,order,Inan] = 1.
p0[0] = (25 + 49) * Global_ZP
p1, G_pix, G_ord, G_wav, II, rms_ms, G_res = \
GLOBALutils.Fit_Global_Wav_Solution(All_Pixel_Centers, All_Wavelengths, All_Orders,\
np.ones(All_Intensities.shape), p0, Cheby=True,\
maxrms=MRMS, Inv=Inverse_m,minlines=400,order0=49, \
ntotal=nord_ob,npix=len(thar_order),nx=ncoef_x,nm=ncoef_m)
thar_out = np.zeros((2, nord_ob, lines_thar_ob.shape[1]))
equis = np.arange(lines_thar_ob.shape[1])
order = 0
while order < nord_ob:
m = order + 49
chebs = GLOBALutils.Calculate_chebs(equis,
m,
Inverse=Inverse_m,
order0=49,
ntotal=nord_ob,
npix=len(thar_order),
nx=ncoef_x,
nm=ncoef_m)
WavSol = (1.0 / m) * GLOBALutils.Joint_Polynomial_Cheby(
p1, chebs, ncoef_x, ncoef_m)
thar_out[0, order, :] = WavSol
thar_out[1, order, :] = lines_thar_ob[order]
order += 1
if os.access(thar_spec_ob, os.F_OK):
os.system('rm ' + thar_spec_ob)
hdu = pyfits.PrimaryHDU(thar_out)
hdu.writeto(thar_spec_ob)
for order in range(nord_co):