def build_observation_list(observations, start_wlen, end_wlen, delta_wlen):
''' This function takes a list of observations and redshifts them and
resamples them to be on the same grid. '''
wlen_range = np.arange(start_wlen, end_wlen, delta_wlen)
qsos = list()
for info, qso in observations.items():
rest_frame = redshift(z_in=qso.z, z_out=0, data_in=qso.data,
rules=[dict(name='wavelength', exponent=1),
dict(name='flux', exponent=-1),
dict(name='dflux', exponent=-1)])
resampled = resample(rest_frame, x_in='wavelength',
x_out=wlen_range, y=('flux', 'dflux'))
qsos.append(resampled)
return qsos
def main():
parser = argparse.ArgumentParser(
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
description='Build the chi2 grid.')
parser.add_argument('-v',
'--verbose',
action='store_true',
help='toggle on verbose output')
parser.add_argument('--zmin',
type=float,
default=0.5,
metavar='',
help='minimum redshift')
parser.add_argument('--zmax',
type=float,
default=1.0,
metavar='',
help='maximum redshift')
parser.add_argument('--zbin',
type=float,
default=0.25,
metavar='',
help='redshift bin size')
args = parser.parse_args()
# Set the debugging level
if args.verbose:
lvl = logging.DEBUG
else:
lvl = logging.INFO
logging.basicConfig(format='%(message)s', level=lvl, stream=sys.stdout)
log = logging.getLogger('__name__')
topdir = os.getenv('SEQUELS_DIR')
outdir = os.path.join(topdir, 'stacks')
# Build the redshift bin (centers). Only works if ZBIN is an integer
# multiple of [ZMIN,ZMAX].
zbins = np.concatenate(
([zmin], np.arange(zmin, zmax, zbin) + zbin / 2, [zmax]))
# Loop on all the plates
plates = ['7280']
for pl in plates:
platefile = glob(
os.path.join(topdir, pl, 'spPlate-' + pl + '-?????.fits'))[0]
zbestfile = glob(
os.path.join(topdir, pl, 'spZbest-' + pl + '-?????.fits'))[0]
zall = fits.getdata(zbestfile, 1)
plug = fits.getdata(platefile, 5)
fluxall, hdr = fits.getdata(platefile, 0, header=True)
wave = 10**(hdr['CRVAL1'] + np.arange(hdr['NAXIS1']) * hdr['CD1_1'])
ivarall = fits.getdata(platefile, 1)
# Pick out the "good" LRGs
iz_wise = (plug['EBOSS_TARGET0'] & 2) > 0
ri_wise = (plug['EBOSS_TARGET0'] & 4) > 0
zcut = (zall['Z'] > args.zmin) * (zall['Z'] < args.zmax) * (
zall['RCHI2DIFF_NOQSO'] > 0.005)
lrg = np.where(np.logical_and(np.logical_or(iz_wise, ri_wise),
zcut))[0]
if len(lrg) > 0:
flux = fluxall[lrg, :]
ivar = ivarall[lrg, :]
zlrg = zall[lrg]
# Assign each object to the right redshift bin.
idx = np.digitize(x, bins)
#print(nbin, bins, xmin, xmax)
for ib in range(len([0, 1])):
zflux = flux[lrg[ib], :]
zivar = ivar[lrg[ib], :]
rules = [
dict(name='wave', exponent=+1, array_in=wave),
dict(name='flux', exponent=-1, array_in=zflux),
dict(name='ivar', exponent=+2, array_in=zivar)
]
out = redshift(zbest['z'][lrg[ib]], 0.2, rules=rules)
print(out.shape)
def main():
parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter,
description='Build the chi2 grid.')
parser.add_argument('-v', '--verbose', action='store_true',
help='toggle on verbose output')
parser.add_argument('--zmin', type=float, default=0.5, metavar='',
help='minimum redshift')
parser.add_argument('--zmax', type=float, default=1.0, metavar='',
help='maximum redshift')
parser.add_argument('--zbin', type=float, default=0.25, metavar='',
help='redshift bin size')
args = parser.parse_args()
# Set the debugging level
if args.verbose:
lvl = logging.DEBUG
else:
lvl = logging.INFO
logging.basicConfig(format='%(message)s',level=lvl,stream=sys.stdout)
log = logging.getLogger('__name__')
topdir = os.getenv('SEQUELS_DIR')
outdir = os.path.join(topdir,'stacks')
# Build the redshift bin (centers). Only works if ZBIN is an integer
# multiple of [ZMIN,ZMAX].
zbins = np.concatenate(([zmin],np.arange(zmin,zmax,zbin)+zbin/2,[zmax]))
# Loop on all the plates
plates = ['7280']
for pl in plates:
platefile = glob(os.path.join(topdir,pl,'spPlate-'+pl+'-?????.fits'))[0]
zbestfile = glob(os.path.join(topdir,pl,'spZbest-'+pl+'-?????.fits'))[0]
zall = fits.getdata(zbestfile,1)
plug = fits.getdata(platefile,5)
fluxall, hdr = fits.getdata(platefile,0,header=True)
wave = 10**(hdr['CRVAL1'] + np.arange(hdr['NAXIS1'])*hdr['CD1_1'])
ivarall = fits.getdata(platefile,1)
# Pick out the "good" LRGs
iz_wise = (plug['EBOSS_TARGET0'] & 2)>0
ri_wise = (plug['EBOSS_TARGET0'] & 4)>0
zcut = (zall['Z']>args.zmin)*(zall['Z']<args.zmax)*(zall['RCHI2DIFF_NOQSO']>0.005)
lrg = np.where(np.logical_and(np.logical_or(iz_wise,ri_wise),zcut))[0]
if len(lrg)>0:
flux = fluxall[lrg,:]
ivar = ivarall[lrg,:]
zlrg = zall[lrg]
# Assign each object to the right redshift bin.
idx = np.digitize(x,bins)
#print(nbin, bins, xmin, xmax)
for ib in range(len([0,1])):
zflux = flux[lrg[ib],:]
zivar = ivar[lrg[ib],:]
rules = [dict(name='wave', exponent=+1, array_in=wave),
dict(name='flux', exponent=-1, array_in=zflux),
dict(name='ivar', exponent=+2, array_in=zivar)]
out = redshift(zbest['z'][lrg[ib]],0.2,rules=rules)
print(out.shape)
# STACKING QUSARS
DR12Q = bossdata.meta.Database(finder, mirror, quasar_catalog=True, lite=False)
qso_table = DR12Q.select_all(where="PLATE=6641 and ZWARNING=0", what="PLATE,MJD,FIBER,Z_VI")
print "Found {0} QSO targets for plate 6641.".format(len(qso_table))
fiducial_grid = np.arange(1000.0, 3000.0)
rest_frame, resampled, spec_qso = None, None, None
for row in qso_table:
filename = finder.get_spec_path(plate=row["PLATE"], mjd=row["MJD"], fiber=row["FIBER"], lite=True)
spectrum = bossdata.spec.SpecFile(mirror.get(filename))
data = spectrum.get_valid_data(use_ivar=True, fiducial_grid=True)
rest_frame = speclite.redshift(
z_in=row["Z_VI"],
z_out=0,
data_in=data,
data_out=rest_frame,
rules=[dict(name="wavelength", exponent=+1), dict(name="flux", exponent=-1), dict(name="ivar", exponent=+2)],
)
resampled = speclite.resample(
rest_frame, x_in="wavelength", x_out=fiducial_grid, y=("flux", "ivar"), data_out=resampled
)
spec_qso = speclite.accumulate(spec_qso, resampled, data_out=spec_qso, join="wavelength", add="flux", weight="ivar")
plot_stack(spec_qso, truncate_percentile=99.5)
filename = finder.get_plate_spec_path(plate=6641, mjd=56383)
plate = bossdata.plate.PlateFile(mirror.get(filename))
plate_data = plate.get_valid_data(qso_table["FIBER"], use_ivar=True, fiducial_grid=True)
zorder = np.argsort(qso_table["Z_VI"])