Flat, RO_fl, GA_fl = uvesutils.MedianCombine(flats, bias=MasterBias)
hdu = pyfits.PrimaryHDU(Flat)
if (os.access(dirout + 'Flat.fits', os.F_OK)):
os.remove(dirout + 'Flat.fits')
hdu.writeto(dirout + 'Flat.fits')
print "\t\t-> MasterFlat: done!"
hdu = pyfits.open(orderref[0])
d1 = hdu[1].data - MasterBias[:, :, 0]
d2 = hdu[2].data - MasterBias[:, :, 1]
d1 = d1.T
d2 = d2.T
print "\tTracing echelle orders..."
c_all1, nord1 = GLOBALutils.get_them(d1,
int(0.2 * ext_aperture),
trace_degree,
mode=1,
nsigmas=10)
print '\t\t' + str(nord1) + ' orders for chip1 found...'
c_all2, nord2 = GLOBALutils.get_them(d2,
int(0.2 * ext_aperture),
trace_degree,
mode=1,
nsigmas=10,
endat=2030)
print '\t\t' + str(nord2) + ' orders for chip2 found...'
trace_dict = {'c_all1':c_all1,'nord1':nord1,\
'c_all2':c_all2,'nord2':nord2,\
'GA_bias': GA_bias, 'RO_bias': RO_bias,\
'GA_fl': GA_fl, 'RO_fl': RO_fl}
hdu = pyfits.PrimaryHDU( MasterBias )
if (os.access(dirout+'MasterBias.fits',os.F_OK)):
os.remove(dirout+'MasterBias.fits')
hdu.writeto(dirout+'MasterBias.fits')
print("\t\t-> Masterbias: done!")
# median combine list of flats
Flat, RO_fl, GA_fl = cafeutils.MedianCombine(flats, zero=dirout+'MasterBias.fits')
hdu = pyfits.PrimaryHDU(Flat)
if (os.access(dirout+'Flat.fits',os.F_OK)):
os.remove(dirout+'Flat.fits')
hdu.writeto(dirout+'Flat.fits')
print("\t\t-> Masterflats: done!")
print("\tTracing echelle orders...")
c_all,nord = GLOBALutils.get_them(Flat, ext_aperture, trace_degree, maxords=-1, mode=1)
c_all, nord = GLOBALutils.good_orders(c_all,nord,Flat.shape[0],Flat.shape[1],ext_aperture)
if nord >= 90:
c_all = c_all[:90]
nord=90
print('\t\t'+ str(nord)+' orders found.')
# pickle traces
trace_dict = {'c_all':c_all,
'nord':nord,
'GA_bias': GA_bias, 'RO_bias' : RO_bias,
'GA_fl': GA_fl, 'RO_fl': RO_fl}
pickle.dump( trace_dict, open( dirout+"trace.pkl", 'w' ) )
else:
trace_dict = pickle.load( open( dirout+"trace.pkl", 'r' ) )
pre_process = 1
else:
print "\tPre-processing files found, going straight to extraction"
pre_process = 0
if pre_process == 1:
# Find orders & traces
print "\tTracing echelle orders..."
h = pyfits.open(dirin + stst)
if len(h) > 1:
h[0].data = h[1].data
d = h[0].data
d = mikeutils.OverscanTrim(d, bias_sec, ov_sec)
d = d.T
c_all, nord = GLOBALutils.get_them(d, ext_aperture, 4, mode=1)
c_all = c_all[1:-1]
nord = len(c_all)
print '\t\t', nord, 'orders found in red CCD'
hb = pyfits.open(dirin + 'b' + stst[1:])
if len(h) > 1:
hb[0].data = hb[1].data
db = hb[0].data
db = mikeutils.OverscanTrim(db, bias_sec, ov_sec)
db = db.T
c_all_b, nord_b = GLOBALutils.get_them(db, ext_aperture, 4, mode=1)
print '\t\t', nord_b, 'orders found in blue CCD'
# median combine list of ob flats
print "\tMedian combining flat frames"
os.remove(dirout + 'Flat.fits')
hdu.writeto(dirout + 'Flat.fits')
print "\t\t-> Masterflat: done!"
#Flat = pyfits.getdata(dirout+'Flat.fits')
#RO_flat, GA_flat = 1.,1.
# Find orders & traces
print "\tTracing echelle orders..."
h = pyfits.open(dirin + stst)[0]
hth = pyfits.getheader(dirin + stst)
d = h.data
d = pfsutils.OverscanTrim(d, bias_section, over_section)
d -= MasterBias
c_all, nord = GLOBALutils.get_them(d,
ext_aperture - 1,
trace_degree,
mode=1,
nsigmas=5)
trace_dict = {
'c_all': c_all,
'nord': nord,
'GA_bias': GA_bias,
'RO_bias': RO_bias,
'GA_flat': GA_flat,
'RO_flat': RO_flat
}
pickle.dump(trace_dict, open(dirout + 'trace.pkl', 'w'))
else:
print '\t\tLoading Masterbias, Masterflat and traces'
print "\t\tGenerating Master calibration frames..."
Flat, RO_fl, GA_fl = hiresutils.MedianCombine(flats, chip=chip)
hdu = pyfits.PrimaryHDU(Flat)
if (os.access(dirout + 'Flat_' + str(int(chip)) + '.fits', os.F_OK)):
os.remove(dirout + 'Flat_' + str(int(chip)) + '.fits')
hdu.writeto(dirout + 'Flat_' + str(int(chip)) + '.fits')
print "\t\t-> Masterflat: done!"
hdu = pyfits.open(dirin + stst)
d = hdu[chip].data
d = hiresutils.OverscanTrim(d, hdu[chip].header['DATASEC'])
d = d.T
print "\tTracing echelle orders..."
c_all, nord = GLOBALutils.get_them(d,
ext_aperture + 5,
trace_degree,
mode=1,
nsigmas=10,
nc2=1)
print '\t\t' + str(nord) + ' orders found...'
# pickle traces
trace_dict = {'c_all': c_all, 'nord': nord, 'GA_fl': GA_fl, 'RO_fl': RO_fl}
pickle.dump(trace_dict,
open(dirout + 'trace_' + str(int(chip)) + '.pkl', 'w'))
else:
trace_dict = pickle.load(open(dirout + 'trace_' + str(int(chip)) + '.pkl'))
c_all = trace_dict['c_all']
nord = trace_dict['nord']
# recover GA*, RO*
GA_fl = trace_dict['GA_fl']
if (pre_process == 1):
# median combine list of flats
print "\t\tGenerating Master calibration frames..."
Flat, RO_fl, GA_fl = hiresutils.MedianCombine(flats, chip=chip)
hdu = pyfits.PrimaryHDU(Flat)
if (os.access(dirout + 'Flat_' + str(int(chip)) + '.fits', os.F_OK)):
os.remove(dirout + 'Flat_' + str(int(chip)) + '.fits')
hdu.writeto(dirout + 'Flat_' + str(int(chip)) + '.fits')
print "\t\t-> Masterflat: done!"
hdu = pyfits.open(dirin + stst)
d = hdu[chip].data
d = hiresutils.OverscanTrim(d, hdu[chip].header['DATASEC'])
d = d.T
print "\tTracing echelle orders..."
c_all, nord = GLOBALutils.get_them(d, ext_aperture, trace_degree, mode=1)
print '\t\t' + str(nord) + ' orders found...'
# pickle traces
trace_dict = {'c_all': c_all, 'nord': nord, 'GA_fl': GA_fl, 'RO_fl': RO_fl}
pickle.dump(trace_dict,
open(dirout + 'trace_' + str(int(chip)) + '.pkl', 'w'))
else:
trace_dict = pickle.load(open(dirout + 'trace_' + str(int(chip)) + '.pkl'))
c_all = trace_dict['c_all']
nord = trace_dict['nord']
# recover GA*, RO*
GA_fl = trace_dict['GA_fl']
RO_fl = trace_dict['RO_fl']
# recover flats & master bias
dirout +
'MasterBias.fits',
dark_bo=have_darks,
dlist=MasDarl)
hdu = pyfits.PrimaryHDU(Flat)
if (os.access(dirout + 'MasterFlat.fits', os.F_OK)):
os.remove(dirout + 'MasterFlat.fits')
hdu.writeto(dirout + 'MasterFlat.fits')
print "\t\t-> Masterflats: done!"
print "\tTracing echelle orders..."
h = pyfits.open(dirout + 'MasterFlat.fits')[0]
d = h.data
d = d.T
c_all, nord = GLOBALutils.get_them(d,
ext_aperture + 1,
trace_degree,
maxords=45)
print '\t\t' + str(nord) + ' orders found ...'
trace_dict = {'c_all': c_all, 'nord': nord, 'roF': roF, 'gaF': gaF}
pickle.dump(trace_dict, open(dirout + "trace.pkl", 'w'))
else:
h = pyfits.open(dirout + 'MasterBias.fits')
MasterBias = h[0].data
# load orders & tracers
trace_dict = pickle.load(open(dirout + "trace.pkl", 'r'))
#print trace_dict['c_all'].shape
c_all = trace_dict['c_all']
nord = trace_dict['nord']
roF = trace_dict['roF']
gaF = trace_dict['gaF']
Flat, RO_flat, GA_flat = vbtutils.MedianCombine(flats, zero_bo=True, dark_bo=False, flat_bo=False,zero=dirout+'MasterBias.fits')
hdu = pyfits.PrimaryHDU( Flat )
if (os.access(dirout+'MasterFlat.fits',os.F_OK)):
os.remove(dirout+'MasterFlat.fits')
hdu.writeto(dirout+'MasterFlat.fits')
print "\t\t-> Masterflat: done!"
# Find orders & traces
print "\tTracing echelle orders..."
h = pyfits.open(dirin+stst)[0]
hth = pyfits.getheader(dirin+stst)
d = h.data[0]
d = vbtutils.OverscanTrim(d,bsec)
d -= MasterBias
c_all, nord = GLOBALutils.get_them(d,20,trace_degree,mode=1,nsigmas=3,endat=4100)
print '\t\t'+str(nord)+' orders found...'
trace_dict = {'c_all':c_all, 'nord':nord, 'DARKS':MDARKS, 'dtimes':dark_times, 'RO_flat':RO_flat, 'GA_flat':GA_flat}
pickle.dump( trace_dict, open( dirout+"trace.pkl", 'w' ) )
else:
trace_dict = pickle.load( open( dirout+"trace.pkl", 'r' ) )
c_all = trace_dict['c_all']
nord = trace_dict['nord']
RO_flat = trace_dict['RO_flat']
GA_flat = trace_dict['GA_flat']
h = pyfits.open(dirout+'MasterBias.fits')
d = h.data
d = dupontutils.OverscanTrim(d,hth['BIASSEC'])
d -= MasterBias
d /= Flat
if bad_colummn:
d = dupontutils.b_col(d)
d = d[:1420,:]
if use_ref:
c_comp = pickle.load( open( ref_traces, 'r' ) )['c_all']
nord = pickle.load( open( ref_traces, 'r' ) )['nord']
lim = pickle.load( open( ref_traces, 'r' ) )['lims']
c_all,pshift = GLOBALutils.retrace( d, c_comp )
else:
c_all, nord = GLOBALutils.get_them(d,5,trace_degree,mode=1)
print '\t\t'+str(nord)+' orders found...'
else:
trace_dict = pickle.load( open( dirout+"trace.pkl", 'r' ) )
c_all = trace_dict['c_all']
nord = trace_dict['nord']
GAIN = trace_dict['GA_ob']
RON = trace_dict['RO_ob']
trace_dict = {'c_all':c_all, 'nord':nord, 'GA_ob': GAIN, 'RO_ob': RON, 'DARKS':MDARKS, 'dtimes':dark_times}
pickle.dump( trace_dict, open( dirout+"trace.pkl", 'w' ) )
else:
trace_dict = pickle.load( open( dirout+"trace.pkl", 'r' ) )
# Centers[i,:]=scipy.polyval(c_co[i],ejx)
#bac_co = GLOBALutils.get_scat(MasterFlat_co.T,Centers,span = 6)
#MasterFlat_co = MasterFlat_co - bac_co.T
#MasterFlat_ob = MasterFlat - MasterFlat_co
#plot(MasterFlat_ob[1000])
#show()
#plot(np.median(MasterFlat[:,2050:],axis=1))
#show()
#plot(MasterFlat[1000])
#plot(MasterFlat_co[1000])
#show()
c_all, nord_all = GLOBALutils.get_them(MasterFlat.T,
4.,
trace_degree,
maxords=-1,
nsigmas=1,
mode=1)
print nord_all
c_ob, c_co, nord_ob, nord_co = fideosutils.clean_orders(
c_all, MasterFlat.T)
print nord_ob, nord_co
c_co, nord_co = fideosutils.good_orders(c_co, nord_co, MasterFlat.shape[1],
MasterFlat.shape[0],
ext_aperture_co)
c_ob, nord_ob = fideosutils.good_orders(c_ob, nord_ob, MasterFlat.shape[1],
MasterFlat.shape[0],
ext_aperture_ob)
print nord_ob, nord_co
print nord_ob, 'object orders found'
print nord_co, 'comparison orders found'