def process_options(args):
opt = adict()
filename = os.path.abspath(__file__).rsplit('/', 1)[0] + '/default.cfg'
opt = parse_config(filename)
if os.path.lexists('./plot.cfg'):
opt = parse_config('./plot.cfg', opt)
opt.atom = readatom(molecules=True)
if opt.Rfwhm is not None:
if isinstance(opt.Rfwhm, basestring):
if opt.Rfwhm == 'convolve_with_COS_FOS':
if convolve_with_COS_FOS is None:
raise ValueError('convolve_with_COS_FOS() not available')
print('Using tailored FWHM for COS/FOS data')
opt.Rfwhm = 'convolve_with_COS_FOS'
elif opt.Rfwhm.endswith('fits'):
print('Reading Resolution FWHM from', opt.Rfwhm)
res = readtabfits(opt.Rfwhm)
opt.Rfwhm = res.res / 2.354
else:
print('Reading Resolution FWHM from', opt.Rfwhm)
fh = open(opt.Rfwhm)
opt.Rfwhm = 1 / 2.354 * np.array([float(r) for r in fh])
fh.close()
else:
opt.Rfwhm = float(opt.Rfwhm)
if opt.features is not None:
print('Reading feature list from', opt.features)
opt.features = readtabfits(opt.features)
if opt.f26 is not None:
name = opt.f26
print('Reading ions and fitting regions from', name)
opt.f26 = readf26(name)
opt.f26.filename = name
if opt.transitions is not None:
print('Reading transitions from', opt.transitions)
fh = open(opt.transitions)
trans = list(fh)
fh.close()
temp = []
for tr in trans:
tr = tr.strip()
if tr and not tr.startswith('#'):
junk = tr.split()
tr = junk[0] + ' ' + junk[1]
t = findtrans(tr, atomdat=opt.atom)
temp.append(dict(name=t[0], wa=t[1][0], tr=t[1]))
opt.linelist = temp
else:
opt.linelist = readtxt(get_data_path() + 'linelists/qsoabs_lines',
names='wa,name,select')
if opt.f26 is None and opt.taulines is not None:
print('Reading ions from', opt.taulines)
fh = open(opt.taulines)
lines = []
for row in fh:
if row.lstrip().startswith('#'):
continue
items = row.split()
lines.append([items[0]] + list(map(float, items[1:])))
fh.close()
opt.lines = lines
if opt.show_regions is None:
opt.show_regions = True
if hasattr(opt, 'aodname'):
opt.aod = Table.read(opt.aodname)
return opt
def read_gal():
print 'Reading galaxy info'
M = readtabfits('/home/ntejos/Q0107/catalogs/master20100921.fits')
deimos = (M.Z_DEIMOS > 1e-3) & (M.ZCONF_DEIMOS > 2)
gmos = (M.Z_GMOS > 1e-3) & (M.ZCONF_GMOS == 'a')
vimos = (M.Z_VIMOS > 1e-3) & (M.ZCONF_VIMOS > 2)
cfht = (M.Z_CFHT > 1e-3)
isgal = deimos | gmos | vimos | cfht
print 'N gmos', gmos.sum()
print 'N vimos', vimos.sum()
print 'N deimos', deimos.sum()
print 'N CFHT',cfht.sum()
print 'total', isgal.sum()
# correct the VIMOS redshifts to match DEIMOS (add 150 km/s)
# new correction from gas-galaxy correlation callibration by eye using 1>W>0.5 A. (add 250 km/s)
zv = M.Z_VIMOS[vimos]
M.Z_VIMOS[vimos] = zv + (250/Ckms)*(1 + zv)
# same for GMOS (add 50 km/s)
# new correction from gas-galaxy correlation callibration by eye using 1>W>0.5 A. (add 100 km/s)
zg = M.Z_GMOS[gmos]
M.Z_GMOS[gmos] = zg + (100/Ckms)*(1 + zg)
# same for DEIMOS (add 0 km/s)
# new correction from gas-galaxy correlation callibration by eye using 1>W>0.5 A. (add 50 km/s)
zg = M.Z_DEIMOS[deimos]
M.Z_DEIMOS[deimos] = zg + (50/Ckms)*(1 + zg)
# Now consolidate z list, choose z such that deimos > gmos > vimos >
# cfht
zg = []
isd = np.zeros(len(M), bool)
isv = np.zeros(len(M), bool)
isg = np.zeros(len(M), bool)
isc = np.zeros(len(M), bool)
for i in range(len(M)):
z = -1
if deimos[i]:
z = M.Z_DEIMOS[i]
isd[i] = 1
elif gmos[i]:
z = M.Z_GMOS[i]
isg[i] = 1
elif vimos[i]:
z = M.Z_VIMOS[i]
isv[i] = 1
elif cfht[i]:
z = M.Z_CFHT[i]
isc[i] = 1
zg.append(z)
zg = np.array(zg)[isgal]
isd = isd[isgal]
isv = isv[isgal]
isg = isg[isgal]
isc = isc[isgal]
ra = M[isgal].ALPHA_J2000
dec = M[isgal].DELTA_J2000
# index into the master catalogue
ind = M[isgal].NUMBER - 1
mag = M[isgal].MAG_AUTO
template = M[isgal].VIMOS_TEMPLATE
rec = np.rec.fromarrays([ra,dec,zg,isd,isv,isg,isc,mag,template],
names='ra,dec,z,dei,vim,gmos,cfht,mag,template')
return rec
def process_options(args):
opt = adict()
filename = os.path.abspath(__file__).rsplit('/', 1)[0] + '/default.cfg'
opt = parse_config(filename)
if os.path.lexists('./plot.cfg'):
opt = parse_config('./plot.cfg', opt)
opt.atom = readatom(molecules=True)
if opt.Rfwhm is not None:
if isinstance(opt.Rfwhm, basestring):
if opt.Rfwhm == 'convolve_with_COS_FOS':
if convolve_with_COS_FOS is None:
raise ValueError('convolve_with_COS_FOS() not available')
print('Using tailored FWHM for COS/FOS data')
opt.Rfwhm = 'convolve_with_COS_FOS'
elif opt.Rfwhm.endswith('fits'):
print('Reading Resolution FWHM from', opt.Rfwhm)
res = readtabfits(opt.Rfwhm)
opt.Rfwhm = res.res / 2.354
else:
print('Reading Resolution FWHM from', opt.Rfwhm)
fh = open(opt.Rfwhm)
opt.Rfwhm = 1 / 2.354 * np.array([float(r) for r in fh])
fh.close()
else:
opt.Rfwhm = float(opt.Rfwhm)
if opt.features is not None:
print('Reading feature list from', opt.features)
opt.features = readtabfits(opt.features)
if opt.f26 is not None:
name = opt.f26
print('Reading ions and fitting regions from', name)
opt.f26 = readf26(name)
opt.f26.filename = name
if opt.transitions is not None:
print('Reading transitions from', opt.transitions)
fh = open(opt.transitions)
trans = list(fh)
fh.close()
temp = []
for tr in trans:
tr = tr.strip()
if tr and not tr.startswith('#'):
junk = tr.split()
tr = junk[0] + ' ' + junk[1]
t = findtrans(tr, atomdat=opt.atom)
temp.append(dict(name=t[0], wa=t[1][0], tr=t[1]))
opt.linelist = temp
else:
opt.linelist = readtxt(get_data_path() + 'linelists/qsoabs_lines',
names='wa,name,select')
if opt.f26 is None and opt.taulines is not None:
print('Reading ions from', opt.taulines)
fh = open(opt.taulines)
lines = []
for row in fh:
if row.lstrip().startswith('#'):
continue
items = row.split()
lines.append([items[0]] + list(map(float, items[1:])))
fh.close()
opt.lines = lines
if opt.show_regions is None:
opt.show_regions = True
if hasattr(opt, 'aodname'):
opt.aod = Table.read(opt.aodname)
return opt
def read_gal():
print 'Reading galaxy info'
M = readtabfits('/home/ntejos/Q0107/catalogs/master20100921.fits')
deimos = (M.Z_DEIMOS > 1e-3) & (M.ZCONF_DEIMOS > 2)
gmos = (M.Z_GMOS > 1e-3) & (M.ZCONF_GMOS == 'a')
vimos = (M.Z_VIMOS > 1e-3) & (M.ZCONF_VIMOS > 2)
cfht = (M.Z_CFHT > 1e-3)
isgal = deimos | gmos | vimos | cfht
print 'N gmos', gmos.sum()
print 'N vimos', vimos.sum()
print 'N deimos', deimos.sum()
print 'N CFHT', cfht.sum()
print 'total', isgal.sum()
# correct the VIMOS redshifts to match DEIMOS (add 150 km/s)
# new correction from gas-galaxy correlation callibration by eye using 1>W>0.5 A. (add 250 km/s)
zv = M.Z_VIMOS[vimos]
M.Z_VIMOS[vimos] = zv + (250 / Ckms) * (1 + zv)
# same for GMOS (add 50 km/s)
# new correction from gas-galaxy correlation callibration by eye using 1>W>0.5 A. (add 100 km/s)
zg = M.Z_GMOS[gmos]
M.Z_GMOS[gmos] = zg + (100 / Ckms) * (1 + zg)
# same for DEIMOS (add 0 km/s)
# new correction from gas-galaxy correlation callibration by eye using 1>W>0.5 A. (add 50 km/s)
zg = M.Z_DEIMOS[deimos]
M.Z_DEIMOS[deimos] = zg + (50 / Ckms) * (1 + zg)
# Now consolidate z list, choose z such that deimos > gmos > vimos >
# cfht
zg = []
isd = np.zeros(len(M), bool)
isv = np.zeros(len(M), bool)
isg = np.zeros(len(M), bool)
isc = np.zeros(len(M), bool)
for i in range(len(M)):
z = -1
if deimos[i]:
z = M.Z_DEIMOS[i]
isd[i] = 1
elif gmos[i]:
z = M.Z_GMOS[i]
isg[i] = 1
elif vimos[i]:
z = M.Z_VIMOS[i]
isv[i] = 1
elif cfht[i]:
z = M.Z_CFHT[i]
isc[i] = 1
zg.append(z)
zg = np.array(zg)[isgal]
isd = isd[isgal]
isv = isv[isgal]
isg = isg[isgal]
isc = isc[isgal]
ra = M[isgal].ALPHA_J2000
dec = M[isgal].DELTA_J2000
# index into the master catalogue
ind = M[isgal].NUMBER - 1
mag = M[isgal].MAG_AUTO
template = M[isgal].VIMOS_TEMPLATE
rec = np.rec.fromarrays([ra, dec, zg, isd, isv, isg, isc, mag, template],
names='ra,dec,z,dei,vim,gmos,cfht,mag,template')
return rec
