def read_desi_spectra(fin):
h = fitsio.FITS(fin)
nbins = int((llmax - llmin) / dll)
tids = h[1]["TARGETID"][:]
nspec = len(tids)
fl = np.zeros((nspec, nbins))
iv = np.zeros((nspec, nbins))
if nspec == 0: return None
for band in ["B", "R", "Z"]:
wave = h["{}_WAVELENGTH".format(band)].read()
w = (np.log10(wave) > llmin) & (np.log10(wave) < llmax)
wave = wave[w]
bins = np.floor((np.log10(wave) - llmin) / dll).astype(int)
fl_aux = h["{}_FLUX".format(band)].read()[:, w]
iv_aux = h["{}_IVAR".format(band)].read()[:, w]
for i in range(nspec):
c = np.bincount(bins, weights=fl_aux[i] * iv_aux[i])
fl[i, :len(c)] += c
c = np.bincount(bins, weights=iv_aux[i])
iv[i, :len(c)] += c
w = iv > 0
fl[w] /= iv[w]
fl = np.hstack((fl, iv))
## select QSO targets:
wqso = h[1]['DESI_TARGET'][:] & desi_mask.mask('QSO')
wqso = wqso > 0
print("INFO: founds {} qso targets".format(wqso.sum()))
fl = fl[wqso, :]
tids = tids[wqso]
return tids, fl
def read_desi_spectra(fin, ignore_quasar_mask=False):
try:
from desitarget import desi_mask
quasar_mask = desi_mask.mask('QSO')
except:
print("WARN: can't load desi_mask, ignoring mask!")
quasar_mask = 1
h = fitsio.FITS(fin)
nbins = int((llmax - llmin) / dll)
wqso = h[1]['DESI_TARGET'][:] & quasar_mask
if ignore_quasar_mask:
wqso |= 1
wqso = wqso > 0
print("INFO: found {} quasar targets".format(wqso.sum()))
tids = h[1]["TARGETID"][:][wqso]
utids = np.unique(tids)
nspec = len(utids)
fl = np.zeros((nspec, nbins))
iv = np.zeros((nspec, nbins))
if nspec == 0: return None
for band in ["B", "R", "Z"]:
wave = h["{}_WAVELENGTH".format(band)].read()
w = (np.log10(wave) > llmin) & (np.log10(wave) < llmax)
wave = wave[w]
bins = np.floor((np.log10(wave) - llmin) / dll).astype(int)
fl_aux = h["{}_FLUX".format(band)].read()[:, w]
iv_aux = h["{}_IVAR".format(band)].read()[:, w]
fl_aux = fl_aux[wqso]
iv_aux = iv_aux[wqso]
ivfl_aux = fl_aux * iv_aux
for i, t in enumerate(tids):
j = np.argwhere(utids == t)[0]
c = np.bincount(bins, weights=ivfl_aux[i])
fl[j, :len(c)] += c
c = np.bincount(bins, weights=iv_aux[i])
iv[j, :len(c)] += c
w = iv > 0
fl[w] /= iv[w]
fl = np.hstack((fl, iv))
print("INFO: founds {} good spectra".format(wqso.sum()))
return utids, fl
def test_numobs(self):
t = self.targets
#- No target bits set is an error
with self.assertRaises(ValueError):
calc_numobs(t)
#- ELGs and QSOs get one observation
t['DESI_TARGET'] = desi_mask.ELG
self.assertTrue(np.all(calc_numobs(t) == 1))
t['DESI_TARGET'] = desi_mask.QSO
self.assertTrue(np.all(calc_numobs(t) == 4))
#- LRG numobs depends upon zflux (DECAM_FLUX index 4)
t['DESI_TARGET'] = desi_mask.LRG
nobs = calc_numobs(t)
self.assertTrue(np.all(nobs == [1, 1, 2, 3, 3]))
#- test astropy Table
t = Table(t)
nobs = calc_numobs(t)
self.assertTrue(np.all(nobs == [1, 1, 2, 3, 3]))
#- LRG numobs also works with ZFLUX instead of DECAM*
t['ZFLUX'] = t['DECAM_FLUX'][:, 4] / t['DECAM_MW_TRANSMISSION'][:, 4]
t.remove_column('DECAM_FLUX')
t.remove_column('DECAM_MW_TRANSMISSION')
nobs = calc_numobs(t)
self.assertTrue(np.all(nobs == [1, 1, 2, 3, 3]))
#- this is true even if other targeting bits are set
t['DESI_TARGET'] |= desi_mask.mask('ELG|BGS_ANY')
nobs = calc_numobs(t)
self.assertTrue(np.all(nobs == [1, 1, 2, 3, 3]))
#- But if no *FLUX available, default to LRGs with 2 obs
t.remove_column('ZFLUX')
nobs = calc_numobs(t)
self.assertTrue(np.all(nobs == 2))
def test_numobs(self):
t = self.targets
#- default DESI_TARGET=0 should be no observations
self.assertTrue(np.all(calc_numobs(t) == 0))
#- ELGs and QSOs get one observation
t['DESI_TARGET'] = desi_mask.ELG
self.assertTrue(np.all(calc_numobs(t) == 1))
t['DESI_TARGET'] = desi_mask.QSO
self.assertTrue(np.all(calc_numobs(t) == 4))
#- LRG numobs depends upon zflux (DECAM_FLUX index 4)
t['DESI_TARGET'] = desi_mask.LRG
nobs = calc_numobs(t)
self.assertTrue(np.all(nobs == [1, 1, 2, 3, 3]))
#- test astropy Table
t = Table(t)
nobs = calc_numobs(t)
self.assertTrue(np.all(nobs == [1, 1, 2, 3, 3]))
#- LRG numobs also works with ZFLUX instead of DECAM*
t['ZFLUX'] = t['DECAM_FLUX'][:,4] / t['DECAM_MW_TRANSMISSION'][:,4]
t.remove_column('DECAM_FLUX')
t.remove_column('DECAM_MW_TRANSMISSION')
nobs = calc_numobs(t)
self.assertTrue(np.all(nobs == [1, 1, 2, 3, 3]))
#- this is true even if other targeting bits are set
t['DESI_TARGET'] |= desi_mask.mask('ELG|BGS_ANY')
nobs = calc_numobs(t)
self.assertTrue(np.all(nobs == [1, 1, 2, 3, 3]))
#- But if no *FLUX available, default to LRGs with 2 obs
t.remove_column('ZFLUX')
nobs = calc_numobs(t)
self.assertTrue(np.all(nobs == 2))
INVARR = []
INVARZ = []
WAVB = []
WAVR = []
WAVZ = []
ID = []
print("Opening Files")
for f in Folder_all:
folder_list = os.listdir(Platedir + slash + f)
for l in folder_list:
filefolder_list = os.listdir(Platedir + slash + f + slash + l)
for n in filefolder_list:
if 'spectra' in n:
c = Platedir + slash + f + slash + l + slash + n
plate_ = fits.open(c, memmap=True)
wqso = plate_[1].data['DESI_TARGET'][:] & desi_mask.mask('QSO')
wqso = wqso > 0
Bin_info_ = plate_[1].data[wqso]
Flux_B = plate_[3].data[wqso]
Flux_R = plate_[8].data[wqso]
Flux_Z = plate_[13].data[wqso]
AND_B = plate_[5].data[wqso]
AND_R = plate_[10].data[wqso]
AND_Z = plate_[15].data[wqso]
INV_B = plate_[4].data[wqso]
INV_R = plate_[9].data[wqso]
INV_Z = plate_[14].data[wqso]
WAV_B = plate_[2].data
WAV_R = plate_[7].data
WAV_Z = plate_[12].data
FluxB.append(Flux_B)
def qa_qso(targets, truth, qadir='.'):
"""Detailed QA plots for QSOs."""
dens = dict()
these = np.where(targets['DESI_TARGET'] & desi_mask.mask('QSO') != 0)[0]
dens['QSO_TARGETS'] = target_density(targets[these])
these = np.where((targets['DESI_TARGET'] & desi_mask.mask('QSO') != 0) *
(truth['TRUEZ'] < 2.1))[0]
dens['QSO_TRACER'] = target_density(targets[these])
these = np.where((targets['DESI_TARGET'] & desi_mask.mask('QSO') != 0) *
(truth['TRUEZ'] >= 2.1))[0]
dens['QSO_LYA'] = target_density(targets[these])
these = np.where(
(targets['DESI_TARGET'] & desi_mask.mask('QSO') != 0) *
(truth['CONTAM_TARGET'] & contam_mask.mask('QSO_IS_GALAXY')) != 0)[0]
dens['QSO_IS_GALAXY'] = target_density(targets[these])
these = np.where(
(targets['DESI_TARGET'] & desi_mask.mask('QSO') != 0) *
(truth['CONTAM_TARGET'] & contam_mask.mask('QSO_IS_STAR')) != 0)[0]
dens['QSO_IS_STAR'] = target_density(targets[these])
bins = 50
lim = (0, 280)
fig, ax = plt.subplots(1, 2, figsize=(12, 5))
ax[0].hist(dens['QSO_TARGETS'],
bins=bins,
range=lim,
label='All Targets',
color='k',
lw=1,
histtype='step')
ax[0].hist(dens['QSO_TRACER'],
bins=bins,
range=lim,
alpha=0.6,
ls='--',
lw=2,
label='Tracer QSOs') #, histtype='step')
ax[0].hist(dens['QSO_LYA'], bins=bins, range=lim, lw=2, label='Lya QSOs')
ax[0].set_ylabel('Number of Healpixels')
ax[0].set_xlabel('Targets / deg$^2$')
ax[0].set_title('True QSOs')
ax[0].legend(loc='upper right')
lim = (0, 100)
#ax[1].hist(dens['QSO_TARGETS'], bins=bins, range=lim, label='All Targets',
# color='k', lw=1, histtype='step')
ax[1].hist(dens['QSO_IS_STAR'],
bins=bins,
range=lim,
alpha=0.3,
label='QSO_IS_STAR')
ax[1].hist(dens['QSO_IS_GALAXY'],
bins=bins,
range=lim,
alpha=0.5,
label='QSO_IS_GALAXY')
ax[1].set_ylabel('Number of Healpixels')
ax[1].set_xlabel('Targets / deg$^2$')
ax[1].set_title('QSO Contaminants')
ax[1].legend(loc='upper right')
pngfile = os.path.join(qadir, '{}_detail_density.png'.format('qso'))
fig.savefig(pngfile)
return pngfile
def qa_targets_truth(output_dir, verbose=True):
"""Generate QA plots from the joined targets and truth catalogs.
time select_mock_targets --output_dir debug --qa
"""
import fitsio
from desiutil.log import get_logger, DEBUG
from desitarget import desi_mask, bgs_mask, mws_mask, contam_mask
if verbose:
log = get_logger(DEBUG)
else:
log = get_logger()
qadir = os.path.join(output_dir, 'qa')
if os.path.exists(qadir):
if os.listdir(qadir):
log.warning('Output directory {} is not empty.'.format(qadir))
else:
log.info('Creating directory {}'.format(qadir))
os.makedirs(qadir)
log.info('Writing to output QA directory {}'.format(qadir))
# Read the catalogs.
targfile = os.path.join(output_dir, 'targets.fits')
truthfile = os.path.join(output_dir, 'truth.fits')
skyfile = os.path.join(output_dir, 'sky.fits')
stddarkfile = os.path.join(output_dir, 'standards-dark.fits')
stdbrightfile = os.path.join(output_dir, 'standards-bright.fits')
cat = list()
for ff in (targfile, truthfile, skyfile, stddarkfile, stdbrightfile):
if os.path.exists(ff):
log.info('Reading {}'.format(ff))
cat.append(fitsio.read(ff, ext=1, upper=True))
else:
log.warning('File {} not found.'.format(ff))
cat.append(None)
targets, truth, sky, stddark, stdbright = [cc for cc in cat]
# Do some sanity checking of the catalogs.
nobj, nsky, ndark, nbright = [
len(cc) for cc in (targets, sky, stddark, stdbright)
]
if nobj != len(truth):
log.fatal(
'Mismatch in the number of objects in targets.fits (N={}) and truth.fits (N={})!'
.format(nobj, len(truth)))
raise ValueError
# Assign healpixels to estimate the area covered by the catalog.
nside = 256
npix = hp.nside2npix(nside)
areaperpix = hp.nside2pixarea(nside, degrees=True)
pix = radec2pix(nside, targets['RA'], targets['DEC'])
counts = np.bincount(pix, weights=None, minlength=npix)
area = np.sum(counts > 10) * areaperpix
log.info('Approximate area spanned by catalog = {:.2f} deg2'.format(area))
binarea = 1.0
htmlfile = os.path.join(qadir, 'index.html')
log.info('Building {}'.format(htmlfile))
html = open(htmlfile, 'w')
html.write('<html><body>\n')
html.write('<h1>QA directory: {}</h1>\n'.format(qadir))
html.write('<ul>\n')
html.write('<li>Approximate total area = {:.1f} deg2</li>\n'.format(area))
html.write('<li>Science targets = {}</li>\n'.format(nobj))
html.write('<li>Sky targets = {}</li>\n'.format(nsky))
html.write('<li>Dark standards = {}</li>\n'.format(ndark))
html.write('<li>Bright standards = {}</li>\n'.format(nbright))
html.write('</ul>\n')
# Desired target densities, including contaminants.
html.write('<hr>\n')
html.write('<hr>\n')
html.write('<h2>Raw target densities (including contaminants)</h2>\n')
targdens = {'ELG': 2400, 'LRG': 350, 'QSO': 260, 'SKY': 1400}
if nobj > 0:
html.write(
'<h3>Science targets - ELG, LRG, QSO, BGS_ANY, MWS_ANY</h3>\n')
for obj in ('ELG', 'LRG', 'QSO', 'BGS_ANY', 'MWS_ANY'):
these = np.where(
(targets['DESI_TARGET'] & desi_mask.mask(obj)) != 0)[0]
if len(these) > 0:
pngfile = qadensity(targets[these],
obj,
targdens,
qadir=qadir,
max_bin_area=binarea)
_img2html(html, pngfile, log)
html.write('<h3>Science targets - BGS_BRIGHT, BGS_FAINT</h3>\n')
for obj in ('BGS_BRIGHT', 'BGS_FAINT'):
these = np.where(
(targets['BGS_TARGET'] & bgs_mask.mask(obj)) != 0)[0]
if len(these) > 0:
pngfile = qadensity(targets[these],
obj,
targdens,
qadir=qadir,
max_bin_area=binarea)
_img2html(html, pngfile, log)
html.write(
'<h3>Science targets - MWS_MAIN, MWS_MAIN_VERY_FAINT, MWS_NEARBY, MWS_WD</h3>\n'
)
for obj in ('MWS_MAIN', 'MWS_MAIN_VERY_FAINT', 'MWS_NEARBY', 'MWS_WD'):
these = np.where(
(targets['MWS_TARGET'] & mws_mask.mask(obj)) != 0)[0]
if len(these) > 0:
pngfile = qadensity(targets[these],
obj,
targdens,
qadir=qadir,
max_bin_area=binarea)
_img2html(html, pngfile, log)
html.write('<hr>\n')
if nsky > 0:
html.write('<h3>Sky targets</h3>\n')
obj = 'SKY'
these = np.where((sky['DESI_TARGET'] & desi_mask.mask(obj)) != 0)[0]
if len(these) > 0:
pngfile = qadensity(sky[these],
obj,
targdens,
qadir=qadir,
max_bin_area=binarea)
_img2html(html, pngfile, log)
html.write('<hr>\n')
if ndark > 0 or nbright > 0:
html.write('<h3>Standard Stars</h3>\n')
for cat, nn, obj in zip((stddark, stdbright), (ndark, nbright),
('STD_FSTAR', 'STD_BRIGHT')):
if nn > 0:
these = np.where(
(cat['DESI_TARGET'] & desi_mask.mask(obj)) != 0)[0]
if len(these) > 0:
pngfile = qadensity(cat[these],
obj,
targdens,
qadir=qadir,
max_bin_area=binarea)
_img2html(html, pngfile, log)
html.write('<hr>\n')
html.write('<hr>\n')
# Desired target densities, including contaminants.
html.write('<h2>Detailed target densities</h2>\n')
html.write('<h3>QSOs</h3>\n')
pngfile = qa_qso(targets, truth, qadir=qadir)
_img2html(html, pngfile, log)
html.write('<hr>\n')
html.write('<h3>ELGs</h3>\n')
pngfile = qa_elg(targets, truth, qadir=qadir)
_img2html(html, pngfile, log)
html.write('<hr>\n')
html.write('</html></body>\n')
html.close()
def qa_elg(targets, truth, qadir='.'):
"""Detailed QA plots for ELGs."""
dens_all = 2400
dens_loz = dens_all * 0.05
dens_hiz = dens_all * 0.05
dens_star = dens_all * 0.1
dens_rightz = dens_all - dens_loz - dens_hiz - dens_star
dens = dict()
these = np.where(targets['DESI_TARGET'] & desi_mask.mask('ELG') != 0)[0]
dens['ELG_TARGETS'] = target_density(targets[these])
these = np.where((targets['DESI_TARGET'] & desi_mask.mask('ELG') != 0) *
(truth['TRUEZ'] >= 0.6) * (truth['TRUEZ'] <= 1.6))[0]
dens['ELG_IS_RIGHTZ'] = target_density(targets[these])
these = np.where((targets['DESI_TARGET'] & desi_mask.mask('QSO') != 0) *
(truth['TRUEZ'] < 0.6))[0]
dens['ELG_IS_LOZ'] = target_density(targets[these])
these = np.where((targets['DESI_TARGET'] & desi_mask.mask('QSO') != 0) *
(truth['TRUEZ'] > 1.6))[0]
dens['ELG_IS_HIZ'] = target_density(targets[these])
these = np.where(
(targets['DESI_TARGET'] & desi_mask.mask('ELG') != 0) *
(truth['CONTAM_TARGET'] & contam_mask.mask('ELG_IS_STAR')) != 0)[0]
dens['ELG_IS_STAR'] = target_density(targets[these])
bins = 50
lim = (0, 3000)
fig, ax = plt.subplots(1, 2, figsize=(12, 5))
#line = ax[0].axvline(x=dens_all, ls='-')
ax[0].hist(
dens['ELG_TARGETS'],
bins=bins,
range=lim, #color=line.get_color(),
color='k',
lw=1,
label='All Targets',
histtype='step')
#line = ax[0].axvline(x=dens_rightz, ls='--')
ax[0].hist(
dens['ELG_IS_RIGHTZ'],
bins=bins,
range=lim,
alpha=0.6, # color=line.get_color(),
ls='--',
lw=2,
label='ELG (0.6<z<1.6)') #, histtype='step')
ax[0].set_ylabel('Number of Healpixels')
ax[0].set_xlabel('Targets / deg$^2$')
ax[0].set_title('True ELGs')
ax[0].legend(loc='upper left')
lim = (0, 300)
#ax[1].hist(dens['ELG_TARGETS'], bins=bins, range=lim, label='All Targets',
# color='k', lw=1, histtype='step')
#line = ax[1].axvline(x=dens_star, ls='-')
ax[1].hist(
dens['ELG_IS_STAR'],
bins=bins,
range=lim, #color=line.get_color(),
alpha=0.5,
label='ELG_IS_STAR')
#line = ax[1].axvline(x=dens_loz, ls='-')
ax[1].hist(
dens['ELG_IS_LOZ'],
bins=bins,
range=lim, #color=line.get_color(),
alpha=0.5,
label='ELG_IS_LOZ (z<0.6)')
#line = ax[1].axvline(x=dens_hiz, ls='-')
ax[1].hist(
dens['ELG_IS_HIZ'],
bins=bins,
range=lim, #color=line.get_color(),
alpha=0.5,
label='ELG_IS_HIZ (z>1.6)')
ax[1].set_ylabel('Number of Healpixels')
ax[1].set_xlabel('Targets / deg$^2$')
ax[1].set_title('ELG Contaminants')
ax[1].legend(loc='upper right')
pngfile = os.path.join(qadir, '{}_detail_density.png'.format('elg'))
fig.savefig(pngfile)
return pngfile
def setUpClass(cls):
cls.ntiles = 4
tiles = desimodel.io.load_tiles()
cls.tileids = tiles['TILEID'][0:cls.ntiles]
cls.tilefiles = ['tile-{:05d}.fits'.format(i) for i in cls.tileids]
cls.tilefiles_multiobs = [
'multitile-{:05d}.fits'.format(i) for i in cls.tileids
]
cls.nspec = n = 1000
targets = Table()
targets['TARGETID'] = np.random.randint(0, 2**60, size=n)
targets['DESI_TARGET'] = 2**np.random.randint(0, 3, size=n)
targets['BGS_TARGET'] = np.zeros(n, dtype=int)
targets['MWS_TARGET'] = np.zeros(n, dtype=int)
isLRG = (targets['DESI_TARGET'] & desi_mask.LRG) != 0
isELG = (targets['DESI_TARGET'] & desi_mask.ELG) != 0
isQSO = (targets['DESI_TARGET'] & desi_mask.QSO) != 0
cls.targets = targets
#- Make a few of them BGS and MWS
iibright = np.random.choice(np.arange(n), size=6, replace=False)
isBGS = iibright[0:3]
isMWS = iibright[3:6]
targets['DESI_TARGET'][isBGS] = desi_mask.BGS_ANY
targets['BGS_TARGET'][isBGS] = bgs_mask.BGS_BRIGHT
targets['DESI_TARGET'][isMWS] = desi_mask.MWS_ANY
targets['MWS_TARGET'][isMWS] = mws_mask.MWS_MAIN
#- Add some fake photometry; no attempt to get colors right
flux = np.zeros((n, 6)) #- ugrizY; DESI has grz
flux[isLRG, 1] = np.random.uniform(0, 1.0, np.count_nonzero(isLRG))
flux[isLRG, 2] = np.random.uniform(0, 5.0, np.count_nonzero(isLRG))
flux[isLRG, 4] = np.random.uniform(0, 5.0, np.count_nonzero(isLRG))
flux[isELG, 1] = np.random.uniform(0, 4.0, np.count_nonzero(isELG))
flux[isELG, 2] = np.random.uniform(0, 4.0, np.count_nonzero(isELG))
flux[isELG, 4] = np.random.uniform(0, 10.0, np.count_nonzero(isELG))
flux[isQSO, 1] = np.random.uniform(0, 4.0, np.count_nonzero(isQSO))
flux[isQSO, 2] = np.random.uniform(0, 4.0, np.count_nonzero(isQSO))
flux[isQSO, 4] = np.random.uniform(0, 6.0, np.count_nonzero(isQSO))
flux[isBGS, 1] = np.random.uniform(10, 600, np.count_nonzero(isBGS))
flux[isBGS, 2] = np.random.uniform(15, 1000, np.count_nonzero(isBGS))
flux[isBGS, 4] = np.random.uniform(10, 1400, np.count_nonzero(isBGS))
flux[isMWS, 1] = np.random.uniform(10, 150, np.count_nonzero(isMWS))
flux[isMWS, 2] = np.random.uniform(15, 350, np.count_nonzero(isMWS))
flux[isMWS, 4] = np.random.uniform(10, 1500, np.count_nonzero(isMWS))
targets['DECAM_FLUX'] = flux
truth = Table()
truth['TARGETID'] = targets['TARGETID']
truth['TRUEZ'] = np.random.uniform(0, 1.5, size=n)
truth['TRUESPECTYPE'] = np.zeros(n, dtype=(str, 10))
truth['GMAG'] = np.random.uniform(18.0, 24.0, size=n)
ii = (targets['DESI_TARGET'] & desi_mask.mask('LRG|ELG|BGS_ANY')) != 0
truth['TRUESPECTYPE'][ii] = 'GALAXY'
ii = (targets['DESI_TARGET'] == desi_mask.QSO)
truth['TRUESPECTYPE'][ii] = 'QSO'
starmask = desi_mask.mask('MWS_ANY|STD_FSTAR|STD_WD|STD_BRIGHT')
ii = (targets['DESI_TARGET'] & starmask) != 0
truth['TRUESPECTYPE'][ii] = 'STAR'
#- Add some fake [OII] fluxes for the ELGs; include some that will fail
isELG = (targets['DESI_TARGET'] & desi_mask.ELG) != 0
nELG = np.count_nonzero(isELG)
truth['OIIFLUX'] = np.zeros(n, dtype=float)
truth['OIIFLUX'][isELG] = np.random.normal(2e-17, 2e-17,
size=nELG).clip(0)
cls.truth = truth
fiberassign = truth['TARGETID', ]
fiberassign['RA'] = np.random.uniform(0, 5, size=n)
fiberassign['DEC'] = np.random.uniform(0, 5, size=n)
fiberassign.meta['EXTNAME'] = 'FIBER_ASSIGNMENTS'
nx = cls.nspec // cls.ntiles
cls.targets_in_tile = dict()
for i, filename in enumerate(cls.tilefiles):
subset = fiberassign[i * nx:(i + 1) * nx]
subset.write(filename)
cls.targets_in_tile[cls.tileids[i]] = subset['TARGETID']
hdulist = fits.open(filename, mode='update')
hdr = hdulist[1].header
hdr.set('TILEID', cls.tileids[i])
hdulist.close()
#- Also create a test of tile files that have multiple observations
nx = cls.nspec // cls.ntiles
for i, filename in enumerate(cls.tilefiles_multiobs):
subset = fiberassign[0:(i + 1) * nx]
subset.write(filename)
hdulist = fits.open(filename, mode='update')
hdr = hdulist[1].header
hdr.set('TILEID', cls.tileids[i])
hdulist.close()