def main(outfn='ccds-annotated.fits', ccds=None, **kwargs):
survey = LegacySurveyData(ccds=ccds)
if ccds is None:
ccds = survey.get_ccds()
# Set to True if we successfully read the calibration products and computed
# annotated values
init_annotations(ccds)
annotate(ccds, **kwargs)
print('Writing to', outfn)
ccds.writeto(outfn)
print('Wrote', outfn)
def queue():
if False:
survey = LegacySurveyData()
ccds = survey.get_ccds()
bricks = survey.get_bricks()
print(len(bricks), 'bricks')
print(len(ccds), 'CCDs')
bricks.cut((bricks.dec >= -30) * (bricks.dec <= 30))
print(len(bricks), 'in Dec [-30, +30]')
I = survey.photometric_ccds(ccds)
ccds.cut(I)
print(len(ccds), 'pass photometric cut')
I, J, d = match_radec(bricks.ra,
bricks.dec,
ccds.ra,
ccds.dec,
0.5,
nearest=True)
print(len(I), 'bricks with CCDs nearby')
bricks.cut(I)
bricknames = bricks.brickname
else:
# DR7: use Martin's list of bricks w/ CCD coverage
f = open('nccds.dat')
bricknames = []
for line in f.readlines():
words = line.strip().split(' ')
brick = words[0]
nccd = int(words[1])
if nccd > 0:
bricknames.append(brick)
# qdo
bb = bricknames
while len(bb):
print(' '.join(bb[:100]))
bb = bb[100:]
return
mp = multiproc(16)
N = len(bricks)
args = [(brick, i, N, plots, {}) for i, brick in enumerate(bricks)]
mp.map(run_one_brick, args)
def main():
ps = PlotSequence('cov')
survey = LegacySurveyData()
ra, dec = 242.0, 10.2
fn = 'coverage-ccds.fits'
if not os.path.exists(fn):
ccds = survey.get_ccds()
ccds.cut(ccds.filter == 'r')
ccds.cut(ccds.propid == '2014B-0404')
ccds.cut(np.hypot(ccds.ra_bore - ra, ccds.dec_bore - dec) < 2.5)
print(np.unique(ccds.expnum), 'unique exposures')
print('propids', np.unique(ccds.propid))
ccds.writeto(fn)
else:
ccds = fits_table(fn)
plt.clf()
for e in np.unique(ccds.expnum):
I = np.flatnonzero(ccds.expnum == e)
plt.plot(ccds.ra[I], ccds.dec[I], '.')
ps.savefig()
degw = 3.0
pixscale = 10.
W = degw * 3600 / 10.
H = W
hi = 6
cmap = cmap_discretize('jet', hi + 1)
wcs = Tan(ra, dec, W / 2. + 0.5, H / 2. + 0.5, -pixscale / 3600., 0., 0.,
pixscale / 3600., float(W), float(H))
r0, d0 = wcs.pixelxy2radec(1, 1)
r1, d1 = wcs.pixelxy2radec(W, H)
extent = [min(r0, r1), max(r0, r1), min(d0, d1), max(d0, d1)]
for expnums in [
[348666],
[348666, 348710, 348686],
[348659, 348667, 348658, 348666, 348665, 348669, 348668],
None,
[
348683, 348687, 347333, 348686, 348685, 348692, 348694, 348659,
348667, 348658, 348666, 348665, 348669, 348668, 348707, 348709,
348708, 348710, 348711, 348716, 348717
],
]:
nexp = np.zeros((H, W), np.uint8)
for ccd in ccds:
if expnums is not None and not ccd.expnum in expnums:
continue
ccdwcs = survey.get_approx_wcs(ccd)
r, d = ccdwcs.pixelxy2radec(1, 1)
ok, x0, y0 = wcs.radec2pixelxy(r, d)
r, d = ccdwcs.pixelxy2radec(ccd.width, ccd.height)
ok, x1, y1 = wcs.radec2pixelxy(r, d)
xlo = np.clip(int(np.round(min(x0, x1))) - 1, 0, W - 1)
xhi = np.clip(int(np.round(max(x0, x1))) - 1, 0, W - 1)
ylo = np.clip(int(np.round(min(y0, y1))) - 1, 0, H - 1)
yhi = np.clip(int(np.round(max(y0, y1))) - 1, 0, H - 1)
nexp[ylo:yhi + 1, xlo:xhi + 1] += 1
plt.clf()
plt.imshow(nexp,
interpolation='nearest',
origin='lower',
vmin=-0.5,
vmax=hi + 0.5,
cmap=cmap,
extent=extent)
plt.colorbar(ticks=np.arange(hi + 1))
ps.savefig()
O = fits_table('obstatus/decam-tiles_obstatus.fits')
O.cut(np.hypot(O.ra - ra, O.dec - dec) < 2.5)
for p in [1, 2, 3]:
print('Pass', p, 'exposures:', O.r_expnum[O.get('pass') == p])
O.cut(O.get('pass') == 2)
print(len(O), 'pass 2 nearby')
d = np.hypot(O.ra - ra, O.dec - dec)
print('Dists:', d)
I = np.flatnonzero(d < 0.5)
assert (len(I) == 1)
ocenter = O[I[0]]
print('Center expnum', ocenter.r_expnum)
I = np.flatnonzero(d >= 0.5)
O.cut(I)
#center = ccds[ccds.expnum == ocenter.r_expnum]
#p2 = ccds[ccds.
ok, xc, yc = wcs.radec2pixelxy(ocenter.ra, ocenter.dec)
xx, yy = np.meshgrid(np.arange(W) + 1, np.arange(H) + 1)
c_d2 = (xc - xx)**2 + (yc - yy)**2
best = np.ones((H, W), bool)
for o in O:
ok, x, y = wcs.radec2pixelxy(o.ra, o.dec)
d2 = (x - xx)**2 + (y - yy)**2
best[d2 < c_d2] = False
del d2
del c_d2, xx, yy
# plt.clf()
# plt.imshow(best, interpolation='nearest', origin='lower', cmap='gray',
# vmin=0, vmax=1)
# ps.savefig()
plt.clf()
plt.imshow(nexp * best,
interpolation='nearest',
origin='lower',
vmin=-0.5,
vmax=hi + 0.5,
cmap=cmap,
extent=extent)
plt.colorbar(ticks=np.arange(hi + 1))
ps.savefig()
plt.clf()
n, b, p = plt.hist(np.clip(nexp[best], 0, hi),
range=(-0.5, hi + 0.5),
bins=hi + 1)
plt.xlim(-0.5, hi + 0.5)
ps.savefig()
print('b', b)
print('n', n)
print('fracs', np.array(n) / np.sum(n))
print('pcts',
', '.join(['%.1f' % f for f in 100. * np.array(n) / np.sum(n)]))
def main():
"""Main program.
"""
import argparse
parser = argparse.ArgumentParser(
description=
"This script is used to produce lists of CCDs or bricks, for production purposes (building qdo queue, eg)."
)
parser.add_argument('--calibs',
action='store_true',
help='Output CCDs that need to be calibrated.')
parser.add_argument('--nper',
type=int,
default=None,
help='Batch N calibs per line')
parser.add_argument(
'--byexp',
action='store_true',
default=False,
help='Run one whole exposure per job (not one CCD per job)')
parser.add_argument('--forced',
action='store_true',
help='Output forced-photometry commands')
parser.add_argument('--lsb',
action='store_true',
help='Output Low-Surface-Brightness commands')
parser.add_argument('--stage', help='Stage image files to given directory')
parser.add_argument('--touching',
action='store_true',
help='Cut to only CCDs touching selected bricks')
parser.add_argument('--near',
action='store_true',
help='Quick cut to only CCDs near selected bricks')
parser.add_argument('--check-coadd',
action='store_true',
help='Check which coadds actually need to run.')
parser.add_argument('--out',
help='Output filename for calibs, default %(default)s',
default='jobs')
parser.add_argument('--command',
action='store_true',
help='Write out full command-line to run calib')
parser.add_argument('--opt', help='With --command, extra options to add')
parser.add_argument('--maxra', type=float, help='Maximum RA to run')
parser.add_argument('--minra', type=float, help='Minimum RA to run')
parser.add_argument('--maxdec', type=float, help='Maximum Dec to run')
parser.add_argument('--mindec', type=float, help='Minimum Dec to run')
parser.add_argument('--region', help='Region to select')
parser.add_argument('--bricks', help='Set bricks.fits file to load')
parser.add_argument('--ccds', help='Set ccds.fits file to load')
parser.add_argument('--ignore_cuts',
action='store_true',
default=False,
help='no photometric cuts')
parser.add_argument('--save_to_fits',
action='store_true',
default=False,
help='save cut brick,ccd to fits table')
parser.add_argument(
'--name',
action='store',
default='dr3',
help='save with this suffix, e.g. refers to ccds table')
parser.add_argument('--delete-sky',
action='store_true',
help='Delete any existing sky calibration files')
parser.add_argument('--write-ccds', help='Write CCDs list as FITS table?')
parser.add_argument('--nccds',
action='store_true',
default=False,
help='Prints number of CCDs per brick')
parser.add_argument('--bands',
default='g,r,z',
help='Set bands to keep: comma-separated list.')
opt = parser.parse_args()
want_ccds = (opt.calibs or opt.forced or opt.lsb)
want_bricks = not want_ccds
survey = LegacySurveyData()
if opt.bricks is not None:
B = fits_table(opt.bricks)
log('Read', len(B), 'from', opt.bricks)
else:
B = survey.get_bricks()
log('Bricks Dec range:', B.dec.min(), B.dec.max())
if opt.ccds is not None:
T = fits_table(opt.ccds)
log('Read', len(T), 'from', opt.ccds)
else:
T = survey.get_ccds()
log(len(T), 'CCDs')
T.index = np.arange(len(T))
if opt.ignore_cuts == False:
log('Applying CCD cuts...')
if 'ccd_cuts' in T.columns():
T.cut(T.ccd_cuts == 0)
log(len(T), 'CCDs survive cuts')
bands = opt.bands.split(',')
log('Filters:', np.unique(T.filter))
T.cut(np.flatnonzero(np.array([f in bands for f in T.filter])))
log('Cut to', len(T), 'CCDs in filters', bands)
log('CCDs Dec range:', T.dec.min(), T.dec.max())
# I,J,d,counts = match_radec(B.ra, B.dec, T.ra, T.dec, 0.2, nearest=True, count=True)
# plt.clf()
# plt.hist(counts, counts.max()+1)
# plt.savefig('bricks.png')
# B.cut(I[counts >= 9])
# plt.clf()
# plt.plot(B.ra, B.dec, 'b.')
# #plt.scatter(B.ra[I], B.dec[I], c=counts)
# plt.savefig('bricks2.png')
# DES Stripe82
#rlo,rhi = 350.,360.
# rlo,rhi = 300., 10.
# dlo,dhi = -6., 4.
# TINY bit
#rlo,rhi = 350.,351.1
#dlo,dhi = 0., 1.1
# EDR+
# 860 bricks
# ~10,000 CCDs
#rlo,rhi = 239,246
#dlo,dhi = 5, 13
# DR1
#rlo,rhi = 0, 360
# part 1
#dlo,dhi = 25, 40
# part 2
#dlo,dhi = 20,25
# part 3
#dlo,dhi = 15,20
# part 4
#dlo,dhi = 10,15
# part 5
#dlo,dhi = 5,10
# the rest
#dlo,dhi = -11, 5
#dlo,dhi = 15,25.5
dlo, dhi = -25, 40
rlo, rhi = 0, 360
# Arjun says 3x3 coverage area is roughly
# RA=240-252 DEC=6-12 (but not completely rectangular)
# COSMOS
#rlo,rhi = 148.9, 151.2
#dlo,dhi = 0.9, 3.5
# A nice well-behaved region (EDR2/3)
# rlo,rhi = 243.6, 244.6
# dlo,dhi = 8.1, 8.6
# 56 bricks, ~725 CCDs
#B.cut((B.ra > 240) * (B.ra < 242) * (B.dec > 5) * (B.dec < 7))
# 240 bricks, ~3000 CCDs
#B.cut((B.ra > 240) * (B.ra < 244) * (B.dec > 5) * (B.dec < 9))
# 535 bricks, ~7000 CCDs
#B.cut((B.ra > 240) * (B.ra < 245) * (B.dec > 5) * (B.dec < 12))
if opt.region in ['test1', 'test2', 'test3', 'test4']:
nm = dict(
test1='2446p115', # weird stuff around bright star
test2='1183p292', # faint sources around bright galaxy
test3='3503p005', # DES
test4='1163p277', # Pollux
)[opt.region]
B.cut(np.flatnonzero(np.array([s == nm for s in B.brickname])))
log('Cut to', len(B), 'bricks')
log(B.ra, B.dec)
dlo, dhi = -90, 90
rlo, rhi = 0, 360
elif opt.region == 'edr':
# EDR:
# 535 bricks, ~7000 CCDs
rlo, rhi = 240, 245
dlo, dhi = 5, 12
elif opt.region == 'dr8-decam':
rlo, rhi = 0, 360
dlo, dhi = -70, 40
log('DR8-DECam region')
elif opt.region == 'edrplus':
rlo, rhi = 235, 248
dlo, dhi = 5, 15
elif opt.region == 'edr-south':
rlo, rhi = 240, 245
dlo, dhi = 5, 10
elif opt.region == 'cosmos1':
# 16 bricks in the core of the COSMOS field.
rlo, rhi = 149.75, 150.75
dlo, dhi = 1.6, 2.6
elif opt.region == 'pristine':
# Stream?
rlo, rhi = 240, 250
dlo, dhi = 10, 15
elif opt.region == 'des':
dlo, dhi = -6., 4.
rlo, rhi = 317., 7.
T.cut(np.flatnonzero(np.array(['CPDES82' in fn for fn in T.cpimage])))
log('Cut to', len(T), 'CCDs with "CPDES82" in filename')
elif opt.region == 'subdes':
rlo, rhi = 320., 360.
dlo, dhi = -1.25, 1.25
elif opt.region == 'northwest':
rlo, rhi = 240, 360
dlo, dhi = 20, 40
elif opt.region == 'north':
rlo, rhi = 120, 240
dlo, dhi = 20, 40
elif opt.region == 'northeast':
rlo, rhi = 0, 120
dlo, dhi = 20, 40
elif opt.region == 'southwest':
rlo, rhi = 240, 360
dlo, dhi = -20, 0
elif opt.region == 'south':
rlo, rhi = 120, 240
dlo, dhi = -20, 0
elif opt.region == 'southeast':
rlo, rhi = 0, 120
dlo, dhi = -20, 0
elif opt.region == 'southsoutheast':
rlo, rhi = 0, 120
dlo, dhi = -20, -10
elif opt.region == 'midwest':
rlo, rhi = 240, 360
dlo, dhi = 0, 20
elif opt.region == 'middle':
rlo, rhi = 120, 240
dlo, dhi = 0, 20
elif opt.region == 'mideast':
rlo, rhi = 0, 120
dlo, dhi = 0, 20
elif opt.region == 'grz':
# Bricks with grz coverage.
# Be sure to use --bricks survey-bricks-in-dr1.fits
# which has_[grz] columns.
B.cut((B.has_g == 1) * (B.has_r == 1) * (B.has_z == 1))
log('Cut to', len(B), 'bricks with grz coverage')
elif opt.region == 'nogrz':
# Bricks without grz coverage.
# Be sure to use --bricks survey-bricks-in-dr1.fits
# which has_[grz] columns.
B.cut(np.logical_not((B.has_g == 1) * (B.has_r == 1) * (B.has_z == 1)))
log('Cut to', len(B), 'bricks withOUT grz coverage')
elif opt.region == 'deep2':
rlo, rhi = 250, 260
dlo, dhi = 30, 35
elif opt.region == 'deep2f2':
rlo, rhi = 251.4, 254.4
dlo, dhi = 34.6, 35.3
elif opt.region == 'deep2f3':
rlo, rhi = 351.25, 353.75
dlo, dhi = 0, 0.5
elif opt.region == 'deep3':
rlo, rhi = 214, 216
dlo, dhi = 52.25, 53.25
elif opt.region == 'virgo':
rlo, rhi = 185, 190
dlo, dhi = 10, 15
elif opt.region == 'virgo2':
rlo, rhi = 182, 192
dlo, dhi = 8, 18
elif opt.region == 'coma':
# van Dokkum et al Coma cluster ultra-diffuse galaxies: 3x3 field centered on Coma cluster
rc, dc = 195., 28.
dd = 1.5
cosdec = np.cos(np.deg2rad(dc))
rlo, rhi = rc - dd / cosdec, rc + dd / cosdec
dlo, dhi = dc - dd, dc + dd
elif opt.region == 'lsb':
rlo, rhi = 147.2, 147.8
dlo, dhi = -0.4, 0.4
elif opt.region == 'eboss-sgc':
# generous boundaries to make sure get all relevant images
# RA -45 to +45
# Dec -5 to +7
rlo, rhi = 310., 50.
dlo, dhi = -6., 6.
elif opt.region == 'eboss-ngc':
# generous boundaries to make sure get all relevant images
# NGC ELGs
# RA 115 to 175
# Dec 15 to 30
# rlo,rhi = 122., 177.
# dlo,dhi = 12., 32.
rlo, rhi = 126., 168.
dlo, dhi = 18., 33.
elif opt.region == 'mzls':
dlo, dhi = -10., 90. # -10: pull in Stripe 82 data too
elif opt.region == 'dr4-bootes':
# https://desi.lbl.gov/trac/wiki/DecamLegacy/DR4sched
#dlo,dhi = 34., 35.
#rlo,rhi = 209.5, 210.5
dlo, dhi = 33., 36.
rlo, rhi = 216.5, 219.5
elif opt.region == 'des-sn-x3':
#rlo,rhi = 36., 37.
#dlo,dhi = -5., -4.
rlo, rhi = 36., 36.5
dlo, dhi = -4.5, -4.
elif opt.region == 'ngc2632':
# open cluster
rlo, rhi = 129.0, 131.0
dlo, dhi = 19.0, 20.5
elif opt.region == 'dr8sky':
rlo, rhi = 35.0, 37.0
dlo, dhi = -3.0, -1.0
# ADM DR8 test regions, see, e.g.:
# https://desi.lbl.gov/trac/wiki/DecamLegacy/DR8#Testregions
elif opt.region == 'dr8-test-s82':
rlo, rhi = 0, 45
dlo, dhi = -1.25, 1.25
elif opt.region == 'dr8-test-hsc-sgc':
rlo, rhi = 30, 40
dlo, dhi = -6.5, -1.25
elif opt.region == 'dr8-test-hsc-ngc':
rlo, rhi = 177.5, 182.5
dlo, dhi = -1, 1
elif opt.region == 'dr8-test-edr':
rlo, rhi = 240, 245
dlo, dhi = 5, 12
elif opt.region == 'dr8-test-hsc-north':
rlo, rhi = 240, 250
dlo, dhi = 42, 45
elif opt.region == 'dr8-test-deep2-egs':
rlo, rhi = 213, 216.5
dlo, dhi = 52, 54
elif opt.region == 'dr8-test-overlap':
rlo, rhi = 132, 140.5
dlo, dhi = 31.5, 35
if opt.mindec is not None:
dlo = opt.mindec
if opt.maxdec is not None:
dhi = opt.maxdec
if opt.minra is not None:
rlo = opt.minra
if opt.maxra is not None:
rhi = opt.maxra
if rlo < rhi:
B.cut((B.ra >= rlo) * (B.ra <= rhi) * (B.dec >= dlo) * (B.dec <= dhi))
else: # RA wrap
B.cut(
np.logical_or(B.ra >= rlo, B.ra <= rhi) * (B.dec >= dlo) *
(B.dec <= dhi))
log(len(B), 'bricks in range; cut Dec range', B.dec.min(), B.dec.max())
#for name in B.get('brickname'):
# print(name)
#B.writeto('bricks-cut.fits')
bricksize = 0.25
# A bit more than 0.25-degree brick radius + Bok image radius ~ 0.57
search_radius = 1.05 * np.sqrt(2.) * (bricksize +
(0.455 * 4096 / 3600.)) / 2.
log(len(T), 'CCDs')
log(len(B), 'Bricks')
I, J, d = match_radec(B.ra,
B.dec,
T.ra,
T.dec,
search_radius,
nearest=True)
B.cut(I)
log('Cut to', len(B), 'bricks near CCDs')
log('Bricks Dec range:', B.dec.min(), B.dec.max())
# plt.clf()
# plt.plot(B.ra, B.dec, 'b.')
# plt.title('DR3 bricks')
# plt.axis([360, 0, np.min(B.dec)-1, np.max(B.dec)+1])
# plt.savefig('bricks.png')
if opt.touching:
I, J, d = match_radec(T.ra,
T.dec,
B.ra,
B.dec,
search_radius,
nearest=True)
# list the ones that will be cut
# drop = np.ones(len(T))
# drop[I] = False
# for i in np.flatnonzero(drop):
# from astrometry.util.starutil_numpy import degrees_between
# dists = degrees_between(B.ra, B.dec, T.ra[i], T.dec[i])
# mindist = min(dists)
# print('Dropping:', T.ra[i], T.dec[i], 'min dist', mindist, 'search_radius', search_radius)
T.cut(I)
log('Cut to', len(T), 'CCDs near bricks')
# sort by RA increasing
B.cut(np.argsort(B.ra))
if opt.save_to_fits:
assert (opt.touching)
# Write cut tables to file
for tab, typ in zip([B, T], ['bricks', 'ccds']):
fn = '%s-%s-cut.fits' % (typ, opt.region)
if os.path.exists(fn):
os.remove(fn)
tab.writeto(fn)
log('Wrote %s' % fn)
# Write text files listing ccd and filename names
# nm1,nm2= 'ccds-%s.txt'% opt.region,'filenames-%s.txt' % opt.region
# if os.path.exists(nm1):
# os.remove(nm1)
# if os.path.exists(nm2):
# os.remove(nm2)
# f1,f2=open(nm1,'w'),open(nm2,'w')
# fns= list(set(T.get('image_filename')))
# for fn in fns:
# f2.write('%s\n' % fn.strip())
# for ti in T:
# f1.write('%s\n' % ti.get('image_filename').strip())
# f1.close()
# f2.close()
# log('Wrote *-names.txt')
if opt.touching:
if want_bricks:
# Shortcut the list of bricks that are definitely touching CCDs --
# a brick-ccd pair within this radius must be touching.
closest_radius = 0.95 * (bricksize + 0.262 * 2048 / 3600.) / 2.
J1, nil, nil = match_radec(B.ra,
B.dec,
T.ra,
T.dec,
closest_radius,
nearest=True)
log(len(J1), 'of', len(B), 'bricks definitely touch CCDs')
tocheck = np.ones(len(B), bool)
tocheck[J1] = False
J2 = []
for j in np.flatnonzero(tocheck):
b = B[j]
wcs = wcs_for_brick(b)
I = ccds_touching_wcs(wcs, T)
log(len(I), 'CCDs for brick', b.brickname)
if len(I) == 0:
continue
J2.append(j)
J = np.hstack((J1, J2))
J = np.sort(J).astype(int)
B.cut(J)
log('Cut to', len(B), 'bricks touching CCDs')
else:
J = []
allI = set()
for j, b in enumerate(B):
wcs = wcs_for_brick(b)
I = ccds_touching_wcs(wcs, T)
log(len(I), 'CCDs for brick', b.brickname)
if len(I) == 0:
continue
allI.update(I)
J.append(j)
allI = list(allI)
allI.sort()
B.cut(np.array(J))
log('Cut to', len(B), 'bricks touching CCDs')
elif opt.near:
# Find CCDs near bricks
allI, nil, nil = match_radec(T.ra,
T.dec,
B.ra,
B.dec,
search_radius,
nearest=True)
# Find bricks near CCDs
J, nil, nil = match_radec(B.ra,
B.dec,
T.ra,
T.dec,
search_radius,
nearest=True)
B.cut(J)
log('Cut to', len(B), 'bricks near CCDs')
else:
allI = np.arange(len(T))
if opt.byexp:
nil, eI = np.unique(T.expnum[allI], return_index=True)
allI = allI[eI]
print('Cut to', len(allI), 'expnums')
if opt.nccds:
from queue import Queue
from threading import Thread
log('Checking number of CCDs per brick')
def worker():
while True:
i = q.get()
if i is None:
break
b = B[i]
wcs = wcs_for_brick(b)
I = ccds_touching_wcs(wcs, T)
log(b.brickname, len(I))
q.task_done()
q = Queue()
num_threads = 24
threads = []
for i in range(num_threads):
t = Thread(target=worker)
t.start()
threads.append(t)
for i in range(len(B)):
q.put(i)
q.join()
for i in range(num_threads):
q.put(None)
for t in threads:
t.join()
if opt.write_ccds:
T[allI].writeto(opt.write_ccds)
log('Wrote', opt.write_ccds)
if want_bricks:
# Print the list of bricks and exit.
for b in B:
print(b.brickname)
if opt.save_to_fits:
B.writeto('bricks-%s-touching.fits' % opt.region)
if not want_ccds:
sys.exit(0)
## Be careful here -- T has been cut; we want to write out T.index.
## 'allI' contains indices into T.
if opt.stage is not None:
cmd_pat = 'rsync -LRarv %s %s'
fns = set()
for iccd in allI:
im = survey.get_image_object(T[iccd])
fns.update([
im.imgfn, im.wtfn, im.dqfn, im.psffn, im.merged_psffn,
im.merged_splineskyfn, im.splineskyfn
])
for i, fn in enumerate(fns):
print('File', i + 1, 'of', len(fns), ':', fn)
if not os.path.exists(fn):
print('No such file:', fn)
continue
base = survey.get_survey_dir()
if base.endswith('/'):
base = base[:-1]
rel = os.path.relpath(fn, base)
dest = os.path.join(opt.stage, rel)
print('Dest:', dest)
if os.path.exists(dest):
print('Exists:', dest)
continue
cmd = cmd_pat % ('%s/./%s' % (base, rel), opt.stage)
print(cmd)
rtn = os.system(cmd)
assert (rtn == 0)
sys.exit(0)
if opt.forced:
log('Writing forced-photometry commands to', opt.out)
f = open(opt.out, 'w')
log('Total of', len(allI), 'CCDs')
for j, i in enumerate(allI):
expstr = '%08i' % T.expnum[i]
imgfn = os.path.join(survey.survey_dir, 'images',
T.image_filename[i].strip())
if (not os.path.exists(imgfn) and imgfn.endswith('.fz')
and os.path.exists(imgfn[:-3])):
imgfn = imgfn[:-3]
outfn = os.path.join(
expstr[:5], expstr, 'forced-%s-%s-%s.fits' %
(T.camera[i].strip(), expstr, T.ccdname[i]))
f.write(
'python legacypipe/forced_photom.py --apphot --derivs --catalog-dir /project/projectdirs/cosmo/data/legacysurvey/dr7/ %i %s forced/%s\n'
% (T.expnum[i], T.ccdname[i], outfn))
f.close()
log('Wrote', opt.out)
fn = 'forced-ccds.fits'
T[allI].writeto(fn)
print('Wrote', fn)
sys.exit(0)
if opt.lsb:
log('Writing LSB commands to', opt.out)
f = open(opt.out, 'w')
log('Total of', len(allI), 'CCDs')
for j, i in enumerate(allI):
exp = T.expnum[i]
ext = T.ccdname[i].strip()
outfn = 'lsb/lsb-%s-%s.fits' % (exp, ext)
f.write(
'python legacyanalysis/lsb.py --expnum %i --extname %s --out %s -F -n > lsb/lsb-%s-%s.log 2>&1\n'
% (exp, ext, outfn, exp, ext))
f.close()
log('Wrote', opt.out)
sys.exit(0)
log('Writing calibs to', opt.out)
f = open(opt.out, 'w')
log('Total of', len(allI), 'CCDs')
batch = []
def write_batch(f, batch, cmd):
if cmd is None:
cmd = ''
f.write(cmd + ' '.join(batch) + '\n')
cmd = None
if opt.command:
cmd = 'python legacypipe/run-calib.py '
if opt.opt is not None:
cmd += opt.opt + ' '
for j, i in enumerate(allI):
if opt.delete_sky:
log(j + 1, 'of', len(allI))
im = survey.get_image_object(T[i])
if opt.delete_sky and os.path.exists(im.skyfn):
log(' deleting:', im.skyfn)
os.unlink(im.skyfn)
if opt.command:
if opt.byexp:
s = '--expnum %i' % (T.expnum[i])
else:
s = '%i-%s' % (T.expnum[i], T.ccdname[i])
prefix = 'python legacypipe/run-calib.py '
if opt.opt is not None:
prefix = prefix + opt.opt
#('python legacypipe/run-calib.py --expnum %i --ccdname %s' %
# (T.expnum[i], T.ccdname[i]))
else:
s = '%i' % T.index[i]
prefix = ''
if j < 10:
print('Index', T.index[i], 'expnum', T.expnum[i], 'ccdname',
T.ccdname[i], 'filename', T.image_filename[i])
if not opt.nper:
f.write(prefix + s + '\n')
else:
batch.append(s)
if len(batch) >= opt.nper:
write_batch(f, batch, cmd)
batch = []
if len(batch):
write_batch(f, batch, cmd)
f.close()
log('Wrote', opt.out)
return 0
def main():
parser = argparse.ArgumentParser()
parser.add_argument('--build-sample', action='store_true', help='Build the sample.')
parser.add_argument('--jpg-cutouts', action='store_true', help='Get jpg cutouts from the viewer.')
parser.add_argument('--ccd-cutouts', action='store_true', help='Get CCD cutouts of each galaxy.')
parser.add_argument('--runbrick', action='store_true', help='Run the pipeline.')
parser.add_argument('--build-webpage', action='store_true', help='(Re)build the web content.')
args = parser.parse_args()
# Top-level directory
key = 'LEGACY_SURVEY_LARGE_GALAXIES'
if key not in os.environ:
print('Required ${} environment variable not set'.format(key))
return 0
largedir = os.getenv(key)
samplefile = os.path.join(largedir, 'large-galaxies-sample.fits')
# --------------------------------------------------
# Build the sample of large galaxies based on the available imaging.
if args.build_sample:
# Read the parent catalog.
cat = read_rc3()
# Create a simple WCS object for each object and find all the CCDs
# touching that WCS footprint.
survey = LegacySurveyData(version='dr2') # hack!
allccds = survey.get_ccds()
keep = np.concatenate((survey.apply_blacklist(allccds),
survey.photometric_ccds(allccds)))
allccds.cut(keep)
ccdlist = []
outcat = []
for gal in cat:
galwcs = _simplewcs(gal)
ccds1 = allccds[ccds_touching_wcs(galwcs, allccds)]
ccds1 = ccds1[_uniqccds(ccds1)]
if len(ccds1) > 0 and 'g' in ccds1.filter and 'r' in ccds1.filter and 'z' in ccds1.filter:
print('Found {} CCDs for {}, D(25)={:.4f}'.format(
len(ccds1), gal['GALAXY'], gal['RADIUS']))
ccdsfile = os.path.join(largedir, 'ccds', '{}-ccds.fits'.format(gal['GALAXY'].strip().lower()))
print(' Writing {}'.format(ccdsfile))
if os.path.isfile(ccdsfile):
os.remove(ccdsfile)
ccds1.writeto(ccdsfile)
ccdlist.append(ccds1)
if len(outcat) == 0:
outcat = gal
else:
outcat = vstack((outcat, gal))
#if gal['GALAXY'] == 'MCG5-19-36':
# pdb.set_trace()
# Write out the final catalog.
samplefile = os.path.join(largedir, 'large-galaxies-sample.fits')
if os.path.isfile(samplefile):
os.remove(samplefile)
print('Writing {}'.format(samplefile))
outcat.write(samplefile)
print(outcat)
# Do we need to transfer any of the data to nyx?
_getfiles(merge_tables(ccdlist))
# --------------------------------------------------
# Get data, model, and residual cutouts from the legacysurvey viewer. Also
# get thumbnails that are lower resolution.
if args.jpg_cutouts:
thumbsize = 100
sample = fits.getdata(samplefile, 1)
for gal in sample:
size = np.ceil(10*gal['RADIUS']/PIXSCALE)
thumbpixscale = PIXSCALE*size/thumbsize
#imageurl = 'http://legacysurvey.org/viewer/jpeg-cutout-decals-dr2?ra={:.6f}&dec={:.6f}'.format(gal['RA'], gal['DEC'])+\
# '&pixscale={:.3f}&size={:g}'.format(PIXSCALE, size)
#imagejpg = os.path.join(largedir, 'cutouts', gal['GALAXY'].strip().lower()+'-image.jpg')
#if os.path.isfile(imagejpg):
# os.remove(imagejpg)
#os.system('wget --continue -O {:s} "{:s}"' .format(imagejpg, imageurl))
thumburl = 'http://legacysurvey.org/viewer/jpeg-cutout-decals-dr2?ra={:.6f}&dec={:.6f}'.format(gal['RA'], gal['DEC'])+\
'&pixscale={:.3f}&size={:g}'.format(thumbpixscale, thumbsize)
thumbjpg = os.path.join(largedir, 'cutouts', gal['GALAXY'].strip().lower()+'-image-thumb.jpg')
if os.path.isfile(thumbjpg):
os.remove(thumbjpg)
os.system('wget --continue -O {:s} "{:s}"' .format(thumbjpg, thumburl))
# --------------------------------------------------
# (Re)build the webpage.
if args.build_webpage:
# index.html
html = open(os.path.join(largedir, 'index.html'), 'w')
html.write('<html><body>\n')
html.write('<h1>Sample of Large Galaxies</h1>\n')
html.write('<table border="2" width="30%">\n')
html.write('<tbody>\n')
sample = fits.getdata(samplefile, 1)
for gal in sample:
# Add coordinates and sizes here.
galaxy = gal['GALAXY'].strip().lower()
html.write('<tr>\n')
html.write('<td><a href="html/{}.html">{}</a></td>\n'.format(galaxy, galaxy.upper()))
html.write('<td><a href="http://legacysurvey.org/viewer/?ra={:.6f}&dec={:.6f}" target="_blank"><img src=cutouts/{}-image-thumb.jpg alt={} /></a></td>\n'.format(gal['RA'], gal['DEC'], galaxy, galaxy.upper()))
# html.write('<td><a href="html/{}.html"><img src=cutouts/{}-image-thumb.jpg alt={} /></a></td>\n'.format(galaxy, galaxy, galaxy.upper()))
html.write('</tr>\n')
html.write('</tbody>\n')
html.write('</table>\n')
html.write('</body></html>\n')
html.close()
sys.exit(1)
# individual galaxy pages
for gal in sample[:3]:
galaxy = gal['GALAXY'].strip().lower()
html = open(os.path.join(largedir, 'html/{}.html'.format(galaxy)), 'w')
html.write('<html><body>\n')
html.write('<a href=../cutouts/{}.jpg><img src=../cutouts/{}-image.jpg alt={} /></a>\n'.format(galaxy, galaxy, galaxy, galaxy.upper()))
html.write('</body></html>\n')
html.close()
# --------------------------------------------------
# Get cutouts of all the CCDs for each galaxy.
if args.ccd_cutouts:
sample = fits.getdata(samplefile, 1)
for gal in sample[1:2]:
galaxy = gal['GALAXY'].strip().lower()
ccdsfile = os.path.join(largedir, 'ccds', '{}-ccds.fits'.format(galaxy))
ccds = fits.getdata(ccdsfile)
pdb.set_trace()
# --------------------------------------------------
# Run the pipeline.
if args.runbrick:
sample = fits.getdata(samplefile, 1)
for gal in sample[1:2]:
galaxy = gal['GALAXY'].strip().lower()
diam = 10*np.ceil(gal['RADIUS']/PIXSCALE).astype('int16') # [pixels]
# Note: zoom is relative to the center of an imaginary brick with
# dimensions (0, 3600, 0, 3600).
survey = LegacySurveyData(version='dr2', output_dir=largedir)
run_brick(None, survey, radec=(gal['RA'], gal['DEC']), blobxy=zip([diam/2], [diam/2]),
threads=1, zoom=(1800-diam/2, 1800+diam/2, 1800-diam/2, 1800+diam/2),
wise=False, forceAll=True, writePickles=False, do_calibs=False,
write_metrics=False, pixPsf=True, splinesky=True,
early_coadds=True, stages=['writecat'], ceres=False)
pdb.set_trace()
def main():
ps = PlotSequence('cov')
survey = LegacySurveyData()
ra,dec = 242.0, 10.2
fn = 'coverage-ccds.fits'
if not os.path.exists(fn):
ccds = survey.get_ccds()
ccds.cut(ccds.filter == 'r')
ccds.cut(ccds.propid == '2014B-0404')
ccds.cut(np.hypot(ccds.ra_bore - ra, ccds.dec_bore - dec) < 2.5)
print(np.unique(ccds.expnum), 'unique exposures')
print('propids', np.unique(ccds.propid))
ccds.writeto(fn)
else:
ccds = fits_table(fn)
plt.clf()
for e in np.unique(ccds.expnum):
I = np.flatnonzero(ccds.expnum == e)
plt.plot(ccds.ra[I], ccds.dec[I], '.')
ps.savefig()
degw = 3.0
pixscale = 10.
W = degw * 3600 / 10.
H = W
hi = 6
cmap = cmap_discretize('jet', hi+1)
wcs = Tan(ra, dec, W/2.+0.5, H/2.+0.5,
-pixscale/3600., 0., 0., pixscale/3600., float(W), float(H))
r0,d0 = wcs.pixelxy2radec(1,1)
r1,d1 = wcs.pixelxy2radec(W,H)
extent = [min(r0,r1),max(r0,r1), min(d0,d1),max(d0,d1)]
for expnums in [ [348666], [348666,348710, 348686],
[348659, 348667, 348658, 348666, 348665, 348669, 348668],
None,
[348683, 348687, 347333, 348686, 348685, 348692, 348694,
348659, 348667, 348658, 348666, 348665, 348669, 348668,
348707, 348709, 348708, 348710, 348711, 348716, 348717],
]:
nexp = np.zeros((H,W), np.uint8)
for ccd in ccds:
if expnums is not None and not ccd.expnum in expnums:
continue
ccdwcs = survey.get_approx_wcs(ccd)
r,d = ccdwcs.pixelxy2radec(1, 1)
ok,x0,y0 = wcs.radec2pixelxy(r, d)
r,d = ccdwcs.pixelxy2radec(ccd.width, ccd.height)
ok,x1,y1 = wcs.radec2pixelxy(r, d)
xlo = np.clip(int(np.round(min(x0,x1))) - 1, 0, W-1)
xhi = np.clip(int(np.round(max(x0,x1))) - 1, 0, W-1)
ylo = np.clip(int(np.round(min(y0,y1))) - 1, 0, H-1)
yhi = np.clip(int(np.round(max(y0,y1))) - 1, 0, H-1)
nexp[ylo:yhi+1, xlo:xhi+1] += 1
plt.clf()
plt.imshow(nexp, interpolation='nearest', origin='lower',
vmin=-0.5, vmax=hi+0.5, cmap=cmap, extent=extent)
plt.colorbar(ticks=np.arange(hi+1))
ps.savefig()
O = fits_table('obstatus/decam-tiles_obstatus.fits')
O.cut(np.hypot(O.ra - ra, O.dec - dec) < 2.5)
for p in [1,2,3]:
print('Pass', p, 'exposures:', O.r_expnum[O.get('pass') == p])
O.cut(O.get('pass') == 2)
print(len(O), 'pass 2 nearby')
d = np.hypot(O.ra - ra, O.dec - dec)
print('Dists:', d)
I = np.flatnonzero(d < 0.5)
assert(len(I) == 1)
ocenter = O[I[0]]
print('Center expnum', ocenter.r_expnum)
I = np.flatnonzero(d >= 0.5)
O.cut(I)
#center = ccds[ccds.expnum == ocenter.r_expnum]
#p2 = ccds[ccds.
ok,xc,yc = wcs.radec2pixelxy(ocenter.ra, ocenter.dec)
xx,yy = np.meshgrid(np.arange(W)+1, np.arange(H)+1)
c_d2 = (xc - xx)**2 + (yc - yy)**2
best = np.ones((H,W), bool)
for o in O:
ok,x,y = wcs.radec2pixelxy(o.ra, o.dec)
d2 = (x - xx)**2 + (y - yy)**2
best[d2 < c_d2] = False
del d2
del c_d2,xx,yy
# plt.clf()
# plt.imshow(best, interpolation='nearest', origin='lower', cmap='gray',
# vmin=0, vmax=1)
# ps.savefig()
plt.clf()
plt.imshow(nexp * best, interpolation='nearest', origin='lower',
vmin=-0.5, vmax=hi+0.5, cmap=cmap, extent=extent)
plt.colorbar(ticks=np.arange(hi+1))
ps.savefig()
plt.clf()
n,b,p = plt.hist(np.clip(nexp[best], 0, hi), range=(-0.5,hi+0.5), bins=hi+1)
plt.xlim(-0.5, hi+0.5)
ps.savefig()
print('b', b)
print('n', n)
print('fracs', np.array(n) / np.sum(n))
print('pcts', ', '.join(['%.1f' % f for f in 100. * np.array(n)/np.sum(n)]))
def main():
"""Main program.
"""
import argparse
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument(
'--force',
action='store_true',
help='Run calib processes even if files already exist?')
parser.add_argument('--ccds', help='Set ccds.fits file to load')
parser.add_argument(
'--expnum',
type=str,
help='Cut to a single or set of exposures; comma-separated list')
parser.add_argument('--extname',
'--ccdname',
help='Cut to a single extension/CCD name')
parser.add_argument('--no-psf',
dest='psfex',
action='store_false',
help='Do not compute PsfEx calibs')
parser.add_argument('--no-sky',
dest='sky',
action='store_false',
help='Do not compute sky models')
parser.add_argument('--run-se',
action='store_true',
help='Run SourceExtractor')
parser.add_argument('--splinesky',
action='store_true',
help='Spline sky, not constant')
parser.add_argument('--threads',
type=int,
help='Run multi-threaded',
default=None)
parser.add_argument('--continue',
dest='cont',
default=False,
action='store_true',
help='Continue even if one file fails?')
parser.add_argument('args', nargs=argparse.REMAINDER)
opt = parser.parse_args()
survey = LegacySurveyData()
if opt.ccds is not None:
T = fits_table(opt.ccds)
T = survey.cleanup_ccds_table(T)
print('Read', len(T), 'from', opt.ccds)
else:
T = survey.get_ccds()
#print len(T), 'CCDs'
if len(opt.args) == 0:
if opt.expnum is not None:
expnums = set([int(e) for e in opt.expnum.split(',')])
T.cut(np.array([e in expnums for e in T.expnum]))
print('Cut to', len(T), 'with expnum in', expnums)
if opt.extname is not None:
T.cut(np.array([(t.strip() == opt.extname) for t in T.ccdname]))
print('Cut to', len(T), 'with extname =', opt.extname)
opt.args = range(len(T))
args = []
for a in opt.args:
# Check for "expnum-ccdname" format.
if '-' in str(a):
words = a.split('-')
assert (len(words) == 2)
expnum = int(words[0])
ccdname = words[1]
I = np.flatnonzero((T.expnum == expnum) * (T.ccdname == ccdname))
if len(I) != 1:
print('Found', len(I), 'CCDs for expnum', expnum, 'CCDname',
ccdname, ':', I)
print('WARNING: skipping this expnum,ccdname')
continue
assert (len(I) == 1)
t = T[I[0]]
else:
i = int(a)
print('Index', i)
t = T[i]
#print('CCDnmatch', t.ccdnmatch)
#if t.ccdnmatch < 20 and not opt.force:
# print('Skipping ccdnmatch = %i' % t.ccdnmatch)
# continue
im = survey.get_image_object(t)
print('Running', im.name)
kwargs = dict(psfex=opt.psfex, sky=opt.sky)
if opt.force:
kwargs.update(force=True)
if opt.run_se:
kwargs.update(se=True)
if opt.splinesky:
kwargs.update(splinesky=True)
if opt.cont:
kwargs.update(noraise=True)
if opt.threads:
args.append((im, kwargs))
else:
run_calibs((im, kwargs))
if opt.threads:
from astrometry.util.multiproc import multiproc
mp = multiproc(opt.threads)
mp.map(run_calibs, args)
return 0
def main(outfn='ccds-annotated.fits', ccds=None):
survey = LegacySurveyData(ccds=ccds)
if ccds is None:
ccds = survey.get_ccds()
# File from the "observing" svn repo:
# https://desi.lbl.gov/svn/decam/code/observing/trunk
tiles = fits_table('decam-tiles_obstatus.fits')
I = survey.photometric_ccds(ccds)
ccds.photometric = np.zeros(len(ccds), bool)
ccds.photometric[I] = True
I = survey.apply_blacklist(ccds)
ccds.blacklist_ok = np.zeros(len(ccds), bool)
ccds.blacklist_ok[I] = True
ccds.good_region = np.empty((len(ccds), 4), np.int16)
ccds.good_region[:,:] = -1
ccds.ra0 = np.zeros(len(ccds), np.float64)
ccds.dec0 = np.zeros(len(ccds), np.float64)
ccds.ra1 = np.zeros(len(ccds), np.float64)
ccds.dec1 = np.zeros(len(ccds), np.float64)
ccds.ra2 = np.zeros(len(ccds), np.float64)
ccds.dec2 = np.zeros(len(ccds), np.float64)
ccds.ra3 = np.zeros(len(ccds), np.float64)
ccds.dec3 = np.zeros(len(ccds), np.float64)
ccds.dra = np.zeros(len(ccds), np.float32)
ccds.ddec = np.zeros(len(ccds), np.float32)
ccds.ra_center = np.zeros(len(ccds), np.float64)
ccds.dec_center = np.zeros(len(ccds), np.float64)
ccds.sig1 = np.zeros(len(ccds), np.float32)
ccds.meansky = np.zeros(len(ccds), np.float32)
ccds.stdsky = np.zeros(len(ccds), np.float32)
ccds.maxsky = np.zeros(len(ccds), np.float32)
ccds.minsky = np.zeros(len(ccds), np.float32)
ccds.pixscale_mean = np.zeros(len(ccds), np.float32)
ccds.pixscale_std = np.zeros(len(ccds), np.float32)
ccds.pixscale_max = np.zeros(len(ccds), np.float32)
ccds.pixscale_min = np.zeros(len(ccds), np.float32)
ccds.psfnorm_mean = np.zeros(len(ccds), np.float32)
ccds.psfnorm_std = np.zeros(len(ccds), np.float32)
ccds.galnorm_mean = np.zeros(len(ccds), np.float32)
ccds.galnorm_std = np.zeros(len(ccds), np.float32)
gaussgalnorm = np.zeros(len(ccds), np.float32)
# 2nd moments
ccds.psf_mx2 = np.zeros(len(ccds), np.float32)
ccds.psf_my2 = np.zeros(len(ccds), np.float32)
ccds.psf_mxy = np.zeros(len(ccds), np.float32)
#
ccds.psf_a = np.zeros(len(ccds), np.float32)
ccds.psf_b = np.zeros(len(ccds), np.float32)
ccds.psf_theta = np.zeros(len(ccds), np.float32)
ccds.psf_ell = np.zeros(len(ccds), np.float32)
ccds.humidity = np.zeros(len(ccds), np.float32)
ccds.outtemp = np.zeros(len(ccds), np.float32)
ccds.tileid = np.zeros(len(ccds), np.int32)
ccds.tilepass = np.zeros(len(ccds), np.uint8)
ccds.tileebv = np.zeros(len(ccds), np.float32)
plvers = []
for iccd,ccd in enumerate(ccds):
im = survey.get_image_object(ccd)
print('Reading CCD %i of %i:' % (iccd+1, len(ccds)), im)
X = im.get_good_image_subregion()
for i,x in enumerate(X):
if x is not None:
ccds.good_region[iccd,i] = x
W,H = ccd.width, ccd.height
psf = None
wcs = None
sky = None
try:
tim = im.get_tractor_image(pixPsf=True, splinesky=True, subsky=False,
pixels=False, dq=False, invvar=False)
except:
import traceback
traceback.print_exc()
plvers.append('')
continue
if tim is None:
plvers.append('')
continue
psf = tim.psf
wcs = tim.wcs.wcs
sky = tim.sky
hdr = tim.primhdr
# print('Got PSF', psf)
# print('Got sky', type(sky))
# print('Got WCS', wcs)
ccds.humidity[iccd] = hdr.get('HUMIDITY')
ccds.outtemp[iccd] = hdr.get('OUTTEMP')
ccds.sig1[iccd] = tim.sig1
plvers.append(tim.plver)
# parse 'DECaLS_15150_r' to get tile number
obj = ccd.object.strip()
words = obj.split('_')
tile = None
if len(words) == 3 and words[0] == 'DECaLS':
try:
tileid = int(words[1])
tile = tiles[tileid - 1]
if tile.tileid != tileid:
I = np.flatnonzero(tile.tileid == tileid)
tile = tiles[I[0]]
except:
pass
if tile is not None:
ccds.tileid [iccd] = tile.tileid
ccds.tilepass[iccd] = tile.get('pass')
ccds.tileebv [iccd] = tile.ebv_med
# Instantiate PSF on a grid
S = 32
xx = np.linspace(1+S, W-S, 5)
yy = np.linspace(1+S, H-S, 5)
xx,yy = np.meshgrid(xx, yy)
psfnorms = []
galnorms = []
for x,y in zip(xx.ravel(), yy.ravel()):
p = im.psf_norm(tim, x=x, y=y)
g = im.galaxy_norm(tim, x=x, y=y)
psfnorms.append(p)
galnorms.append(g)
ccds.psfnorm_mean[iccd] = np.mean(psfnorms)
ccds.psfnorm_std [iccd] = np.std (psfnorms)
ccds.galnorm_mean[iccd] = np.mean(galnorms)
ccds.galnorm_std [iccd] = np.std (galnorms)
# PSF in center of field
cx,cy = (W+1)/2., (H+1)/2.
p = psf.getPointSourcePatch(cx, cy).patch
ph,pw = p.shape
px,py = np.meshgrid(np.arange(pw), np.arange(ph))
psum = np.sum(p)
# print('psum', psum)
p /= psum
# centroids
cenx = np.sum(p * px)
ceny = np.sum(p * py)
# print('cenx,ceny', cenx,ceny)
# second moments
x2 = np.sum(p * (px - cenx)**2)
y2 = np.sum(p * (py - ceny)**2)
xy = np.sum(p * (px - cenx)*(py - ceny))
# semi-major/minor axes and position angle
theta = np.rad2deg(np.arctan2(2 * xy, x2 - y2) / 2.)
theta = np.abs(theta) * np.sign(xy)
s = np.sqrt(((x2 - y2)/2.)**2 + xy**2)
a = np.sqrt((x2 + y2) / 2. + s)
b = np.sqrt((x2 + y2) / 2. - s)
ell = 1. - b/a
# print('PSF second moments', x2, y2, xy)
# print('PSF position angle', theta)
# print('PSF semi-axes', a, b)
# print('PSF ellipticity', ell)
ccds.psf_mx2[iccd] = x2
ccds.psf_my2[iccd] = y2
ccds.psf_mxy[iccd] = xy
ccds.psf_a[iccd] = a
ccds.psf_b[iccd] = b
ccds.psf_theta[iccd] = theta
ccds.psf_ell [iccd] = ell
print('Computing Gaussian approximate PSF quantities...')
# Galaxy norm using Gaussian approximation of PSF.
realpsf = tim.psf
tim.psf = im.read_psf_model(0, 0, gaussPsf=True,
psf_sigma=tim.psf_sigma)
gaussgalnorm[iccd] = im.galaxy_norm(tim, x=cx, y=cy)
tim.psf = realpsf
# Sky -- evaluate on a grid (every ~10th pixel)
skygrid = sky.evaluateGrid(np.linspace(0, ccd.width-1, int(1+ccd.width/10)),
np.linspace(0, ccd.height-1, int(1+ccd.height/10)))
ccds.meansky[iccd] = np.mean(skygrid)
ccds.stdsky[iccd] = np.std(skygrid)
ccds.maxsky[iccd] = skygrid.max()
ccds.minsky[iccd] = skygrid.min()
# WCS
ccds.ra0[iccd],ccds.dec0[iccd] = wcs.pixelxy2radec(1, 1)
ccds.ra1[iccd],ccds.dec1[iccd] = wcs.pixelxy2radec(1, H)
ccds.ra2[iccd],ccds.dec2[iccd] = wcs.pixelxy2radec(W, H)
ccds.ra3[iccd],ccds.dec3[iccd] = wcs.pixelxy2radec(W, 1)
midx, midy = (W+1)/2., (H+1)/2.
rc,dc = wcs.pixelxy2radec(midx, midy)
ra,dec = wcs.pixelxy2radec([1,W,midx,midx], [midy,midy,1,H])
ccds.dra [iccd] = max(degrees_between(ra, dc+np.zeros_like(ra),
rc, dc))
ccds.ddec[iccd] = max(degrees_between(rc+np.zeros_like(dec), dec,
rc, dc))
ccds.ra_center [iccd] = rc
ccds.dec_center[iccd] = dc
# Compute scale change across the chip
# how many pixels to step
step = 10
xx = np.linspace(1+step, W-step, 5)
yy = np.linspace(1+step, H-step, 5)
xx,yy = np.meshgrid(xx, yy)
pixscale = []
for x,y in zip(xx.ravel(), yy.ravel()):
sx = [x-step, x-step, x+step, x+step, x-step]
sy = [y-step, y+step, y+step, y-step, y-step]
sr,sd = wcs.pixelxy2radec(sx, sy)
rc,dc = wcs.pixelxy2radec(x, y)
# project around a tiny little TAN WCS at (x,y), with 1" pixels
locwcs = Tan(rc, dc, 0., 0., 1./3600, 0., 0., 1./3600, 1., 1.)
ok,lx,ly = locwcs.radec2pixelxy(sr, sd)
#print('local x,y:', lx, ly)
A = polygon_area((lx, ly))
pixscale.append(np.sqrt(A / (2*step)**2))
# print('Pixel scales:', pixscale)
ccds.pixscale_mean[iccd] = np.mean(pixscale)
ccds.pixscale_min[iccd] = min(pixscale)
ccds.pixscale_max[iccd] = max(pixscale)
ccds.pixscale_std[iccd] = np.std(pixscale)
ccds.plver = np.array(plvers)
sfd = tractor.sfd.SFDMap()
allbands = 'ugrizY'
filts = ['%s %s' % ('DES', f) for f in allbands]
wisebands = ['WISE W1', 'WISE W2', 'WISE W3', 'WISE W4']
ebv,ext = sfd.extinction(filts + wisebands, ccds.ra_center,
ccds.dec_center, get_ebv=True)
ext = ext.astype(np.float32)
ccds.ebv = ebv.astype(np.float32)
ccds.decam_extinction = ext[:,:len(allbands)]
ccds.wise_extinction = ext[:,len(allbands):]
# Depth
detsig1 = ccds.sig1 / ccds.psfnorm_mean
depth = 5. * detsig1
# that's flux in nanomaggies -- convert to mag
ccds.psfdepth = -2.5 * (np.log10(depth) - 9)
detsig1 = ccds.sig1 / ccds.galnorm_mean
depth = 5. * detsig1
# that's flux in nanomaggies -- convert to mag
ccds.galdepth = -2.5 * (np.log10(depth) - 9)
# Depth using Gaussian FWHM.
psf_sigma = ccds.fwhm / 2.35
gnorm = 1./(2. * np.sqrt(np.pi) * psf_sigma)
detsig1 = ccds.sig1 / gnorm
depth = 5. * detsig1
# that's flux in nanomaggies -- convert to mag
ccds.gausspsfdepth = -2.5 * (np.log10(depth) - 9)
# Gaussian galaxy depth
detsig1 = ccds.sig1 / gaussgalnorm
depth = 5. * detsig1
# that's flux in nanomaggies -- convert to mag
ccds.gaussgaldepth = -2.5 * (np.log10(depth) - 9)
ccds.writeto(outfn)
from __future__ import print_function
from legacypipe.survey import LegacySurveyData
import numpy as np
from glob import glob
import os
if __name__ == '__main__':
survey = LegacySurveyData()
ccds = survey.get_ccds()
print('Read', len(ccds), 'CCDs')
expnums = np.unique(ccds.expnum)
print(len(expnums), 'unique exposure numbers')
####
sky = False
###
#expnums = expnums[expnums < 140000]
#pat = os.path.join(survey.survey_dir, 'calib', 'decam',
# 'psfex-merged', '0013*', '*.fits')
pat = os.path.join(survey.survey_dir, 'calib', 'decam', 'psfex-merged',
'*', '*.fits')
if sky:
pat.replace('psfex', 'splinesky')
print('file pattern:', pat)
got_expnums = set()
merged_fns = glob(pat)
merged_fns.sort()
def main():
survey = LegacySurveyData()
ccds = survey.get_ccds()
print(len(ccds), 'CCDs')
expnums = np.unique(ccds.expnum)
print(len(expnums), 'unique exposures')
for expnum in expnums:
expnumstr = '%08i' % expnum
skyoutfn = os.path.join('splinesky', expnumstr[:5], 'decam-%s.fits' % expnumstr)
psfoutfn = os.path.join('psfex', expnumstr[:5], 'decam-%s.fits' % expnumstr)
if os.path.exists(skyoutfn) and os.path.exists(psfoutfn):
print('Exposure', expnum, 'is done already')
continue
C = ccds[ccds.expnum == expnum]
print(len(C), 'CCDs in expnum', expnum)
psfex = []
psfhdrvals = []
splinesky = []
skyhdrvals = []
for ccd in C:
im = survey.get_image_object(ccd)
fn = im.splineskyfn
if os.path.exists(fn):
T = fits_table(fn)
splinesky.append(T)
# print(fn)
# T.about()
hdr = fitsio.read_header(fn)
skyhdrvals.append([hdr[k] for k in [
'SKY', 'LEGPIPEV', 'PLVER']] + [expnum, ccd.ccdname])
else:
print('File not found:', fn)
fn = im.psffn
if os.path.exists(fn):
T = fits_table(fn)
hdr = fitsio.read_header(fn, ext=1)
keys = ['LOADED', 'ACCEPTED', 'CHI2', 'POLNAXIS',
'POLNGRP', 'PSF_FWHM', 'PSF_SAMP', 'PSFNAXIS',
'PSFAXIS1', 'PSFAXIS2', 'PSFAXIS3',]
if hdr['POLNAXIS'] == 0:
# No polynomials. Fake it.
T.polgrp1 = np.array([0])
T.polgrp2 = np.array([0])
T.polname1 = np.array(['fake'])
T.polname2 = np.array(['fake'])
T.polzero1 = np.array([0])
T.polzero2 = np.array([0])
T.polscal1 = np.array([1])
T.polscal2 = np.array([1])
T.poldeg1 = np.array([0])
T.poldeg2 = np.array([0])
else:
keys.extend([
'POLGRP1', 'POLNAME1', 'POLZERO1', 'POLSCAL1',
'POLGRP2', 'POLNAME2', 'POLZERO2', 'POLSCAL2',
'POLDEG1'])
for k in keys:
T.set(k.lower(), np.array([hdr[k]]))
psfex.append(T)
#print(fn)
#T.about()
hdr = fitsio.read_header(fn)
psfhdrvals.append([hdr.get(k,'') for k in [
'LEGPIPEV', 'PLVER']] + [expnum, ccd.ccdname])
else:
print('File not found:', fn)
if len(psfex):
padded = pad_arrays([p.psf_mask[0] for p in psfex])
cols = psfex[0].columns()
cols.remove('psf_mask')
T = merge_tables(psfex, columns=cols)
T.psf_mask = np.concatenate([[p] for p in padded])
T.legpipev = np.array([h[0] for h in psfhdrvals])
T.plver = np.array([h[1] for h in psfhdrvals])
T.expnum = np.array([h[2] for h in psfhdrvals])
T.ccdname = np.array([h[3] for h in psfhdrvals])
fn = psfoutfn
trymakedirs(fn, dir=True)
T.writeto(fn)
print('Wrote', fn)
if len(splinesky):
T = fits_table()
T.gridw = np.array([t.gridvals[0].shape[1] for t in splinesky])
T.gridh = np.array([t.gridvals[0].shape[0] for t in splinesky])
padded = pad_arrays([t.gridvals[0] for t in splinesky])
T.gridvals = np.concatenate([[p] for p in padded])
padded = pad_arrays([t.xgrid[0] for t in splinesky])
T.xgrid = np.concatenate([[p] for p in padded])
padded = pad_arrays([t.xgrid[0] for t in splinesky])
T.ygrid = np.concatenate([[p] for p in padded])
cols = splinesky[0].columns()
print('Columns:', cols)
for c in ['gridvals', 'xgrid', 'ygrid']:
cols.remove(c)
T.add_columns_from(merge_tables(splinesky, columns=cols))
T.skyclass = np.array([h[0] for h in skyhdrvals])
T.legpipev = np.array([h[1] for h in skyhdrvals])
T.plver = np.array([h[2] for h in skyhdrvals])
T.expnum = np.array([h[3] for h in skyhdrvals])
T.ccdname = np.array([h[4] for h in skyhdrvals])
fn = skyoutfn
trymakedirs(fn, dir=True)
T.writeto(fn)
print('Wrote', fn)
def main():
"""Main program.
"""
import argparse
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument('--force', action='store_true',
help='Run calib processes even if files already exist?')
parser.add_argument('--ccds', help='Set ccds.fits file to load')
parser.add_argument('--expnum', type=int, help='Cut to a single exposure')
parser.add_argument('--extname', '--ccdname', help='Cut to a single extension/CCD name')
parser.add_argument('--no-psf', dest='psfex', action='store_false',
help='Do not compute PsfEx calibs')
parser.add_argument('--no-sky', dest='sky', action='store_false',
help='Do not compute sky models')
parser.add_argument('--run-se', action='store_true', help='Run SourceExtractor')
parser.add_argument('--splinesky', action='store_true', help='Spline sky, not constant')
parser.add_argument('--threads', type=int, help='Run multi-threaded', default=None)
parser.add_argument('args',nargs=argparse.REMAINDER)
opt = parser.parse_args()
survey = LegacySurveyData()
if opt.ccds is not None:
T = fits_table(opt.ccds)
print('Read', len(T), 'from', opt.ccds)
else:
T = survey.get_ccds()
#print len(T), 'CCDs'
if len(opt.args) == 0:
if opt.expnum is not None:
T.cut(T.expnum == opt.expnum)
print('Cut to', len(T), 'with expnum =', opt.expnum)
if opt.extname is not None:
T.cut(np.array([(t.strip() == opt.extname) for t in T.ccdname]))
print('Cut to', len(T), 'with extname =', opt.extname)
opt.args = range(len(T))
args = []
for a in opt.args:
# Check for "expnum-ccdname" format.
if '-' in str(a):
words = a.split('-')
assert(len(words) == 2)
expnum = int(words[0])
ccdname = words[1]
I = np.flatnonzero((T.expnum == expnum) * (T.ccdname == ccdname))
if len(I) != 1:
print('Found', len(I), 'CCDs for expnum', expnum, 'CCDname', ccdname, ':', I)
assert(len(I) == 1)
t = T[I[0]]
else:
i = int(a)
print('Index', i)
t = T[i]
print('CCDnmatch', t.ccdnmatch)
if t.ccdnmatch < 20 and not opt.force:
print('Skipping ccdnmatch = %i' % t.ccdnmatch)
continue
im = survey.get_image_object(t)
print('Running', im.calname)
kwargs = dict(psfex=opt.psfex, sky=opt.sky)
if opt.force:
kwargs.update(force=True)
if opt.run_se:
kwargs.update(se=True)
if opt.splinesky:
kwargs.update(splinesky=True)
if opt.threads:
args.append((im, kwargs))
else:
run_calibs((im, kwargs))
if opt.threads:
from astrometry.util.multiproc import multiproc
mp = multiproc(opt.threads)
mp.map(run_calibs, args)
return 0
def make_pickle_file(pfn, derivs=False, agn=False):
survey = LegacySurveyData()
ccds = survey.get_ccds()
brickname = '0364m042'
bricks = survey.get_bricks()
brick = bricks[bricks.brickname == brickname][0]
print('Brick', brick)
catfn = survey.find_file('tractor', brick=brickname)
print('Reading catalog from', catfn)
cat = fits_table(catfn)
print(len(cat), 'catalog entries')
cat.cut(cat.brick_primary)
print(len(cat), 'brick primary')
'''
BRICKNAM BRICKID BRICKQ BRICKROW BRICKCOL RA DEC
0364m042 306043 3 343 145 36.4255910987483 -4.25000000000000
RA1 RA2 DEC1 DEC2
36.3004172461752 36.5507649513213 -4.37500000000000 -4.12500000000000
'''
rlo, rhi = brick.ra1, brick.ra2
dlo, dhi = brick.dec1, brick.dec2
#rlo,rhi = 36.4, 36.5
#dlo,dhi = -4.4, -4.3
ra, dec = (rlo + rhi) / 2., (dlo + dhi) / 2.
## optional
cat.cut(
(cat.ra > rlo) * (cat.ra < rhi) * (cat.dec > dlo) * (cat.dec < dhi))
print('Cut to', len(cat), 'catalog objects in RA,Dec box')
lightcurves = dict([((brickname, oid), []) for oid in cat.objid])
# close enough to equator to ignore cos(dec)
dra = 4096 / 2. * 0.262 / 3600.
ddec = 2048 / 2. * 0.262 / 3600.
ccds.cut((np.abs(ccds.ra - ra) <
(rhi - rlo) / 2. + dra) * (np.abs(ccds.dec - dec) <
(dhi - dlo) / 2. + ddec))
print('Cut to', len(ccds), 'CCDs overlapping brick')
### HACK
#ccds = ccds[:50]
for i, (expnum, ccdname) in enumerate(zip(ccds.expnum, ccds.ccdname)):
ee = '%08i' % expnum
flavor = 'vanilla'
cols = [
'brickname', 'objid', 'camera', 'expnum', 'ccdname', 'mjd',
'filter', 'flux', 'flux_ivar'
]
if derivs:
flavor = 'derivs'
cols.extend(
['flux_dra', 'flux_ddec', 'flux_dra_ivar', 'flux_ddec_ivar'])
if agn:
flavor = 'agn'
cols.extend(['flux_agn', 'flux_agn_ivar'])
fn = 'forced/%s/%s/%s/forced-decam-%s-%s.fits' % (flavor, ee[:5], ee,
ee, ccdname)
if not os.path.exists(fn):
print('WARNING: missing:', fn)
continue
T = fits_table(fn)
print(i + 1, 'of', len(ccds), ':', len(T), 'in', fn)
T.cut(T.brickname == brickname)
print(len(T), 'in brick', brickname)
found = 0
for t in T: #oid,expnum,ccdname,mjd,filter,flux,fluxiv in zip(T.objid, T.expnum, T.ccdname, T.mjd, T.filter, T.flux, T.flux_ivar):
lc = lightcurves.get((t.brickname, t.objid), None)
if lc is None:
continue
found += 1
#lc.append((expnum, ccdname, mjd, filter, flux, fluxiv))
lc.append([t.get(c) for c in cols])
print('Matched', found, 'sources to light curves')
#pickle_to_file(lightcurves, pfn)
ll = {}
for k, v in lightcurves.items():
if len(v) == 0:
continue
T = fits_table()
# T.expnum = np.array([vv[0] for vv in v])
# T.ccdname= np.array([vv[1] for vv in v])
# T.mjd = np.array([vv[2] for vv in v])
# T.filter = np.array([vv[3] for vv in v])
# T.flux = np.array([vv[4] for vv in v])
# T.fluxiv = np.array([vv[5] for vv in v])
for i, c in enumerate(cols):
T.set(c, np.array([vv[i] for vv in v]))
ll[k] = T
pickle_to_file(ll, pfn)
def main():
survey = LegacySurveyData()
ccds = survey.get_ccds()
print(len(ccds), 'CCDs')
expnums = np.unique(ccds.expnum)
print(len(expnums), 'unique exposures')
for expnum in expnums:
expnumstr = '%08i' % expnum
skyoutfn = os.path.join('splinesky', expnumstr[:5], 'decam-%s.fits' % expnumstr)
psfoutfn = os.path.join('psfex', expnumstr[:5], 'decam-%s.fits' % expnumstr)
if os.path.exists(skyoutfn) and os.path.exists(psfoutfn):
print('Exposure', expnum, 'is done already')
continue
C = ccds[ccds.expnum == expnum]
print(len(C), 'CCDs in expnum', expnum)
psfex = []
psfhdrvals = []
splinesky = []
skyhdrvals = []
for ccd in C:
im = survey.get_image_object(ccd)
fn = im.splineskyfn
if os.path.exists(fn):
print('Reading', fn)
T = None
try:
T = fits_table(fn)
except KeyboardInterrupt:
raise
except:
print('Failed to read file', fn, ':', sys.exc_info()[1])
if T is not None:
splinesky.append(T)
# print(fn)
# T.about()
hdr = fitsio.read_header(fn)
skyhdrvals.append([hdr[k] for k in [
'SKY', 'LEGPIPEV', 'PLVER']] + [expnum, ccd.ccdname])
else:
print('File not found:', fn)
fn = im.psffn
if os.path.exists(fn):
T = fits_table(fn)
hdr = fitsio.read_header(fn, ext=1)
keys = ['LOADED', 'ACCEPTED', 'CHI2', 'POLNAXIS',
'POLNGRP', 'PSF_FWHM', 'PSF_SAMP', 'PSFNAXIS',
'PSFAXIS1', 'PSFAXIS2', 'PSFAXIS3',]
if hdr['POLNAXIS'] == 0:
# No polynomials. Fake it.
T.polgrp1 = np.array([0])
T.polgrp2 = np.array([0])
T.polname1 = np.array(['fake'])
T.polname2 = np.array(['fake'])
T.polzero1 = np.array([0])
T.polzero2 = np.array([0])
T.polscal1 = np.array([1])
T.polscal2 = np.array([1])
T.poldeg1 = np.array([0])
else:
keys.extend([
'POLGRP1', 'POLNAME1', 'POLZERO1', 'POLSCAL1',
'POLGRP2', 'POLNAME2', 'POLZERO2', 'POLSCAL2',
'POLDEG1'])
for k in keys:
try:
v = hdr[k]
except:
print('Did not find key', k, 'in', fn)
sys.exit(-1)
T.set(k.lower(), np.array([hdr[k]]))
psfex.append(T)
#print(fn)
#T.about()
hdr = fitsio.read_header(fn)
psfhdrvals.append([hdr.get(k,'') for k in [
'LEGPIPEV', 'PLVER']] + [expnum, ccd.ccdname])
else:
print('File not found:', fn)
if len(psfex):
padded = pad_arrays([p.psf_mask[0] for p in psfex])
cols = psfex[0].columns()
cols.remove('psf_mask')
T = merge_tables(psfex, columns=cols)
T.psf_mask = np.concatenate([[p] for p in padded])
T.legpipev = np.array([h[0] for h in psfhdrvals])
T.plver = np.array([h[1] for h in psfhdrvals])
T.expnum = np.array([h[2] for h in psfhdrvals])
T.ccdname = np.array([h[3] for h in psfhdrvals])
fn = psfoutfn
trymakedirs(fn, dir=True)
T.writeto(fn)
print('Wrote', fn)
if len(splinesky):
T = fits_table()
T.gridw = np.array([t.gridvals[0].shape[1] for t in splinesky])
T.gridh = np.array([t.gridvals[0].shape[0] for t in splinesky])
padded = pad_arrays([t.gridvals[0] for t in splinesky])
T.gridvals = np.concatenate([[p] for p in padded])
padded = pad_arrays([t.xgrid[0] for t in splinesky])
T.xgrid = np.concatenate([[p] for p in padded])
padded = pad_arrays([t.xgrid[0] for t in splinesky])
T.ygrid = np.concatenate([[p] for p in padded])
cols = splinesky[0].columns()
print('Columns:', cols)
for c in ['gridvals', 'xgrid', 'ygrid']:
cols.remove(c)
T.add_columns_from(merge_tables(splinesky, columns=cols))
T.skyclass = np.array([h[0] for h in skyhdrvals])
T.legpipev = np.array([h[1] for h in skyhdrvals])
T.plver = np.array([h[2] for h in skyhdrvals])
T.expnum = np.array([h[3] for h in skyhdrvals])
T.ccdname = np.array([h[4] for h in skyhdrvals])
fn = skyoutfn
trymakedirs(fn, dir=True)
T.writeto(fn)
print('Wrote', fn)
def main():
parser = argparse.ArgumentParser()
parser.add_argument('--build-sample',
action='store_true',
help='Build the sample.')
parser.add_argument('--jpg-cutouts',
action='store_true',
help='Get jpg cutouts from the viewer.')
parser.add_argument('--ccd-cutouts',
action='store_true',
help='Get CCD cutouts of each galaxy.')
parser.add_argument('--runbrick',
action='store_true',
help='Run the pipeline.')
parser.add_argument('--build-webpage',
action='store_true',
help='(Re)build the web content.')
args = parser.parse_args()
# Top-level directory
key = 'LEGACY_SURVEY_LARGE_GALAXIES'
if key not in os.environ:
print('Required ${} environment variable not set'.format(key))
return 0
largedir = os.getenv(key)
samplefile = os.path.join(largedir, 'large-galaxies-sample.fits')
# --------------------------------------------------
# Build the sample of large galaxies based on the available imaging.
if args.build_sample:
# Read the parent catalog.
cat = read_rc3()
# Create a simple WCS object for each object and find all the CCDs
# touching that WCS footprint.
survey = LegacySurveyData(version='dr2') # hack!
allccds = survey.get_ccds()
keep = np.concatenate((survey.apply_blacklist(allccds),
survey.photometric_ccds(allccds)))
allccds.cut(keep)
ccdlist = []
outcat = []
for gal in cat:
galwcs = _simplewcs(gal)
ccds1 = allccds[ccds_touching_wcs(galwcs, allccds)]
ccds1 = ccds1[_uniqccds(ccds1)]
if len(
ccds1
) > 0 and 'g' in ccds1.filter and 'r' in ccds1.filter and 'z' in ccds1.filter:
print('Found {} CCDs for {}, D(25)={:.4f}'.format(
len(ccds1), gal['GALAXY'], gal['RADIUS']))
ccdsfile = os.path.join(
largedir, 'ccds',
'{}-ccds.fits'.format(gal['GALAXY'].strip().lower()))
print(' Writing {}'.format(ccdsfile))
if os.path.isfile(ccdsfile):
os.remove(ccdsfile)
ccds1.writeto(ccdsfile)
ccdlist.append(ccds1)
if len(outcat) == 0:
outcat = gal
else:
outcat = vstack((outcat, gal))
#if gal['GALAXY'] == 'MCG5-19-36':
# pdb.set_trace()
# Write out the final catalog.
samplefile = os.path.join(largedir, 'large-galaxies-sample.fits')
if os.path.isfile(samplefile):
os.remove(samplefile)
print('Writing {}'.format(samplefile))
outcat.write(samplefile)
print(outcat)
# Do we need to transfer any of the data to nyx?
_getfiles(merge_tables(ccdlist))
# --------------------------------------------------
# Get data, model, and residual cutouts from the legacysurvey viewer. Also
# get thumbnails that are lower resolution.
if args.jpg_cutouts:
thumbsize = 100
sample = fits.getdata(samplefile, 1)
for gal in sample:
size = np.ceil(10 * gal['RADIUS'] / PIXSCALE)
thumbpixscale = PIXSCALE * size / thumbsize
#imageurl = 'http://legacysurvey.org/viewer/jpeg-cutout-decals-dr2?ra={:.6f}&dec={:.6f}'.format(gal['RA'], gal['DEC'])+\
# '&pixscale={:.3f}&size={:g}'.format(PIXSCALE, size)
#imagejpg = os.path.join(largedir, 'cutouts', gal['GALAXY'].strip().lower()+'-image.jpg')
#if os.path.isfile(imagejpg):
# os.remove(imagejpg)
#os.system('wget --continue -O {:s} "{:s}"' .format(imagejpg, imageurl))
thumburl = 'http://legacysurvey.org/viewer/jpeg-cutout-decals-dr2?ra={:.6f}&dec={:.6f}'.format(gal['RA'], gal['DEC'])+\
'&pixscale={:.3f}&size={:g}'.format(thumbpixscale, thumbsize)
thumbjpg = os.path.join(
largedir, 'cutouts',
gal['GALAXY'].strip().lower() + '-image-thumb.jpg')
if os.path.isfile(thumbjpg):
os.remove(thumbjpg)
os.system('wget --continue -O {:s} "{:s}"'.format(
thumbjpg, thumburl))
# --------------------------------------------------
# (Re)build the webpage.
if args.build_webpage:
# index.html
html = open(os.path.join(largedir, 'index.html'), 'w')
html.write('<html><body>\n')
html.write('<h1>Sample of Large Galaxies</h1>\n')
html.write('<table border="2" width="30%">\n')
html.write('<tbody>\n')
sample = fits.getdata(samplefile, 1)
for gal in sample:
# Add coordinates and sizes here.
galaxy = gal['GALAXY'].strip().lower()
html.write('<tr>\n')
html.write('<td><a href="html/{}.html">{}</a></td>\n'.format(
galaxy, galaxy.upper()))
html.write(
'<td><a href="http://legacysurvey.org/viewer/?ra={:.6f}&dec={:.6f}" target="_blank"><img src=cutouts/{}-image-thumb.jpg alt={} /></a></td>\n'
.format(gal['RA'], gal['DEC'], galaxy, galaxy.upper()))
# html.write('<td><a href="html/{}.html"><img src=cutouts/{}-image-thumb.jpg alt={} /></a></td>\n'.format(galaxy, galaxy, galaxy.upper()))
html.write('</tr>\n')
html.write('</tbody>\n')
html.write('</table>\n')
html.write('</body></html>\n')
html.close()
sys.exit(1)
# individual galaxy pages
for gal in sample[:3]:
galaxy = gal['GALAXY'].strip().lower()
html = open(os.path.join(largedir, 'html/{}.html'.format(galaxy)),
'w')
html.write('<html><body>\n')
html.write(
'<a href=../cutouts/{}.jpg><img src=../cutouts/{}-image.jpg alt={} /></a>\n'
.format(galaxy, galaxy, galaxy, galaxy.upper()))
html.write('</body></html>\n')
html.close()
# --------------------------------------------------
# Get cutouts of all the CCDs for each galaxy.
if args.ccd_cutouts:
sample = fits.getdata(samplefile, 1)
for gal in sample[1:2]:
galaxy = gal['GALAXY'].strip().lower()
ccdsfile = os.path.join(largedir, 'ccds',
'{}-ccds.fits'.format(galaxy))
ccds = fits.getdata(ccdsfile)
pdb.set_trace()
# --------------------------------------------------
# Run the pipeline.
if args.runbrick:
sample = fits.getdata(samplefile, 1)
for gal in sample[1:2]:
galaxy = gal['GALAXY'].strip().lower()
diam = 10 * np.ceil(gal['RADIUS'] / PIXSCALE).astype(
'int16') # [pixels]
# Note: zoom is relative to the center of an imaginary brick with
# dimensions (0, 3600, 0, 3600).
survey = LegacySurveyData(version='dr2', output_dir=largedir)
run_brick(None,
survey,
radec=(gal['RA'], gal['DEC']),
blobxy=zip([diam / 2], [diam / 2]),
threads=1,
zoom=(1800 - diam / 2, 1800 + diam / 2, 1800 - diam / 2,
1800 + diam / 2),
wise=False,
forceAll=True,
writePickles=False,
do_calibs=False,
write_metrics=False,
pixPsf=True,
splinesky=True,
early_coadds=True,
stages=['writecat'],
ceres=False)
pdb.set_trace()
def main():
"""Main program.
"""
import argparse
parser = argparse.ArgumentParser(description="This script is used to produce lists of CCDs or bricks, for production purposes (building qdo queue, eg).")
parser.add_argument('--calibs', action='store_true',
help='Output CCDs that need to be calibrated.')
parser.add_argument('--nper', type=int, default=None,
help='Batch N calibs per line')
parser.add_argument('--forced', action='store_true',
help='Output forced-photometry commands')
parser.add_argument('--lsb', action='store_true',
help='Output Low-Surface-Brightness commands')
parser.add_argument('--touching', action='store_true',
help='Cut to only CCDs touching selected bricks')
parser.add_argument('--near', action='store_true',
help='Quick cut to only CCDs near selected bricks')
parser.add_argument('--check', action='store_true',
help='Check which calibrations actually need to run.')
parser.add_argument('--check-coadd', action='store_true',
help='Check which caoadds actually need to run.')
parser.add_argument('--out', help='Output filename for calibs, default %(default)s',
default='jobs')
parser.add_argument('--command', action='store_true',
help='Write out full command-line to run calib')
parser.add_argument('--opt', help='With --command, extra options to add')
parser.add_argument('--maxdec', type=float, help='Maximum Dec to run')
parser.add_argument('--mindec', type=float, help='Minimum Dec to run')
parser.add_argument('--region', help='Region to select')
parser.add_argument('--bricks', help='Set bricks.fits file to load')
parser.add_argument('--ccds', help='Set ccds.fits file to load')
parser.add_argument('--ignore_cuts', action='store_true',default=False,help='no photometric or blacklist cuts')
parser.add_argument('--save_to_fits', action='store_true',default=False,help='save cut brick,ccd to fits table')
parser.add_argument('--name', action='store',default='dr3',help='save with this suffix, e.g. refers to ccds table')
parser.add_argument('--delete-sky', action='store_true',
help='Delete any existing sky calibration files')
parser.add_argument('--delete-pvastrom', action='store_true',
help='Delete any existing PV WCS calibration files')
parser.add_argument('--write-ccds', help='Write CCDs list as FITS table?')
parser.add_argument('--brickq', type=int, default=None,
help='Queue only bricks with the given "brickq" value [0 to 3]')
parser.add_argument('--brickq-deps', action='store_true', default=False,
help='Queue bricks directly using qdo API, setting brickq dependencies')
parser.add_argument('--queue', default='bricks',
help='With --brickq-deps, the QDO queue name to use')
opt = parser.parse_args()
survey = LegacySurveyData()
if opt.bricks is not None:
B = fits_table(opt.bricks)
log('Read', len(B), 'from', opt.bricks)
else:
B = survey.get_bricks()
if opt.ccds is not None:
T = fits_table(opt.ccds)
log('Read', len(T), 'from', opt.ccds)
else:
T = survey.get_ccds()
log(len(T), 'CCDs')
T.index = np.arange(len(T))
if opt.ignore_cuts == False:
I = survey.photometric_ccds(T)
print(len(I), 'CCDs are photometric')
T.cut(I)
I = survey.apply_blacklist(T)
print(len(I), 'CCDs are not blacklisted')
T.cut(I)
print(len(T), 'CCDs remain')
# I,J,d,counts = match_radec(B.ra, B.dec, T.ra, T.dec, 0.2, nearest=True, count=True)
# plt.clf()
# plt.hist(counts, counts.max()+1)
# plt.savefig('bricks.png')
# B.cut(I[counts >= 9])
# plt.clf()
# plt.plot(B.ra, B.dec, 'b.')
# #plt.scatter(B.ra[I], B.dec[I], c=counts)
# plt.savefig('bricks2.png')
# DES Stripe82
#rlo,rhi = 350.,360.
# rlo,rhi = 300., 10.
# dlo,dhi = -6., 4.
# TINY bit
#rlo,rhi = 350.,351.1
#dlo,dhi = 0., 1.1
# EDR+
# 860 bricks
# ~10,000 CCDs
#rlo,rhi = 239,246
#dlo,dhi = 5, 13
# DR1
#rlo,rhi = 0, 360
# part 1
#dlo,dhi = 25, 40
# part 2
#dlo,dhi = 20,25
# part 3
#dlo,dhi = 15,20
# part 4
#dlo,dhi = 10,15
# part 5
#dlo,dhi = 5,10
# the rest
#dlo,dhi = -11, 5
#dlo,dhi = 15,25.5
dlo,dhi = -25, 40
rlo,rhi = 0, 360
# Arjun says 3x3 coverage area is roughly
# RA=240-252 DEC=6-12 (but not completely rectangular)
# COSMOS
#rlo,rhi = 148.9, 151.2
#dlo,dhi = 0.9, 3.5
# A nice well-behaved region (EDR2/3)
# rlo,rhi = 243.6, 244.6
# dlo,dhi = 8.1, 8.6
# 56 bricks, ~725 CCDs
#B.cut((B.ra > 240) * (B.ra < 242) * (B.dec > 5) * (B.dec < 7))
# 240 bricks, ~3000 CCDs
#B.cut((B.ra > 240) * (B.ra < 244) * (B.dec > 5) * (B.dec < 9))
# 535 bricks, ~7000 CCDs
#B.cut((B.ra > 240) * (B.ra < 245) * (B.dec > 5) * (B.dec < 12))
if opt.region in ['test1', 'test2', 'test3', 'test4']:
nm = dict(test1='2446p115', # weird stuff around bright star
test2='1183p292', # faint sources around bright galaxy
test3='3503p005', # DES
test4='1163p277', # Pollux
)[opt.region]
B.cut(np.flatnonzero(np.array([s == nm for s in B.brickname])))
log('Cut to', len(B), 'bricks')
log(B.ra, B.dec)
dlo,dhi = -90,90
rlo,rhi = 0, 360
elif opt.region == 'edr':
# EDR:
# 535 bricks, ~7000 CCDs
rlo,rhi = 240,245
dlo,dhi = 5, 12
elif opt.region == 'edrplus':
rlo,rhi = 235,248
dlo,dhi = 5, 15
elif opt.region == 'edr-south':
rlo,rhi = 240,245
dlo,dhi = 5, 10
elif opt.region == 'cosmos1':
# 16 bricks in the core of the COSMOS field.
rlo,rhi = 149.75, 150.75
dlo,dhi = 1.6, 2.6
elif opt.region == 'pristine':
# Stream?
rlo,rhi = 240,250
dlo,dhi = 10,15
elif opt.region == 'des':
dlo, dhi = -6., 4.
rlo, rhi = 317., 7.
T.cut(np.flatnonzero(np.array(['CPDES82' in fn for fn in T.cpimage])))
log('Cut to', len(T), 'CCDs with "CPDES82" in filename')
elif opt.region == 'subdes':
rlo,rhi = 320., 360.
dlo,dhi = -1.25, 1.25
elif opt.region == 'northwest':
rlo,rhi = 240,360
dlo,dhi = 20,40
elif opt.region == 'north':
rlo,rhi = 120,240
dlo,dhi = 20,40
elif opt.region == 'northeast':
rlo,rhi = 0,120
dlo,dhi = 20,40
elif opt.region == 'southwest':
rlo,rhi = 240,360
dlo,dhi = -20,0
elif opt.region == 'south':
rlo,rhi = 120,240
dlo,dhi = -20,0
elif opt.region == 'southeast':
rlo,rhi = 0,120
dlo,dhi = -20,0
elif opt.region == 'southsoutheast':
rlo,rhi = 0,120
dlo,dhi = -20,-10
elif opt.region == 'midwest':
rlo,rhi = 240,360
dlo,dhi = 0,20
elif opt.region == 'middle':
rlo,rhi = 120,240
dlo,dhi = 0,20
elif opt.region == 'mideast':
rlo,rhi = 0,120
dlo,dhi = 0,20
elif opt.region == 'grz':
# Bricks with grz coverage.
# Be sure to use --bricks survey-bricks-in-dr1.fits
# which has_[grz] columns.
B.cut((B.has_g == 1) * (B.has_r == 1) * (B.has_z == 1))
log('Cut to', len(B), 'bricks with grz coverage')
elif opt.region == 'nogrz':
# Bricks without grz coverage.
# Be sure to use --bricks survey-bricks-in-dr1.fits
# which has_[grz] columns.
B.cut(np.logical_not((B.has_g == 1) * (B.has_r == 1) * (B.has_z == 1)))
log('Cut to', len(B), 'bricks withOUT grz coverage')
elif opt.region == 'deep2':
rlo,rhi = 250,260
dlo,dhi = 30,35
elif opt.region == 'deep2f3':
rlo,rhi = 351.25, 353.75
dlo,dhi = 0, 0.5
elif opt.region == 'virgo':
rlo,rhi = 185,190
dlo,dhi = 10, 15
elif opt.region == 'virgo2':
rlo,rhi = 182,192
dlo,dhi = 8, 18
elif opt.region == 'lsb':
rlo,rhi = 147.2, 147.8
dlo,dhi = -0.4, 0.4
elif opt.region == 'eboss-elg':
# RA -45 to +45
# Dec -5 to +7
rlo,rhi = 315., 45.
dlo,dhi = -5., 7.
elif opt.region == 'eboss-ngc':
# NGC ELGs
# RA 115 to 175
# Dec 15 to 30
rlo,rhi = 115., 175.
dlo,dhi = 15., 30.
elif opt.region == 'mzls':
dlo,dhi = 30., 90.
elif opt.region == 'dr4-bootes':
# https://desi.lbl.gov/trac/wiki/DecamLegacy/DR4sched
#dlo,dhi = 34., 35.
#rlo,rhi = 209.5, 210.5
dlo,dhi = 33., 36.
rlo,rhi = 216.5, 219.5
if opt.mindec is not None:
dlo = opt.mindec
if opt.maxdec is not None:
dhi = opt.maxdec
if rlo < rhi:
B.cut((B.ra >= rlo) * (B.ra <= rhi) *
(B.dec >= dlo) * (B.dec <= dhi))
else: # RA wrap
B.cut(np.logical_or(B.ra >= rlo, B.ra <= rhi) *
(B.dec >= dlo) * (B.dec <= dhi))
log(len(B), 'bricks in range')
for name in B.get('brickname'):
print(name)
B.writeto('bricks-cut.fits')
I,J,d = match_radec(B.ra, B.dec, T.ra, T.dec, survey.bricksize)
keep = np.zeros(len(B), bool)
for i in I:
keep[i] = True
B.cut(keep)
log('Cut to', len(B), 'bricks near CCDs')
plt.clf()
plt.plot(B.ra, B.dec, 'b.')
plt.title('DR3 bricks')
plt.axis([360, 0, np.min(B.dec)-1, np.max(B.dec)+1])
plt.savefig('bricks.png')
if opt.brickq is not None:
B.cut(B.brickq == opt.brickq)
log('Cut to', len(B), 'with brickq =', opt.brickq)
if opt.touching:
keep = np.zeros(len(T), bool)
for j in J:
keep[j] = True
T.cut(keep)
log('Cut to', len(T), 'CCDs near bricks')
# Aside -- how many near DR1=1 CCDs?
if False:
T2 = D.get_ccds()
log(len(T2), 'CCDs')
T2.cut(T2.dr1 == 1)
log(len(T2), 'CCDs marked DR1=1')
log(len(B), 'bricks in range')
I,J,d = match_radec(B.ra, B.dec, T2.ra, T2.dec, survey.bricksize)
keep = np.zeros(len(B), bool)
for i in I:
keep[i] = True
B2 = B[keep]
log('Total of', len(B2), 'bricks near CCDs with DR1=1')
for band in 'grz':
Tb = T2[T2.filter == band]
log(len(Tb), 'in filter', band)
I,J,d = match_radec(B2.ra, B2.dec, Tb.ra, Tb.dec, survey.bricksize)
good = np.zeros(len(B2), np.uint8)
for i in I:
good[i] = 1
B2.set('has_' + band, good)
B2.writeto('survey-bricks-in-dr1.fits')
sys.exit(0)
# sort by dec decreasing
#B.cut(np.argsort(-B.dec))
# RA increasing
B.cut(np.argsort(B.ra))
for b in B:
if opt.check:
fn = 'dr1n/tractor/%s/tractor-%s.fits' % (b.brickname[:3], b.brickname)
if os.path.exists(fn):
print('Exists:', fn, file=sys.stderr)
continue
if opt.check_coadd:
fn = 'dr1b/coadd/%s/%s/decals-%s-image.jpg' % (b.brickname[:3], b.brickname, b.brickname)
if os.path.exists(fn):
print('Exists:', fn, file=sys.stderr)
continue
print(b.brickname)
if opt.save_to_fits:
assert(opt.touching)
# Write cut tables to file
for tab,typ in zip([B,T],['bricks','ccds']):
fn='%s-%s-cut.fits' % (typ,opt.name)
if os.path.exists(fn):
os.remove(fn)
tab.writeto(fn)
print('Wrote %s' % fn)
# Write text files listing ccd and filename names
nm1,nm2= 'ccds-%s.txt'% opt.name,'filenames-%s.txt' % opt.name
if os.path.exists(nm1):
os.remove(nm1)
if os.path.exists(nm2):
os.remove(nm2)
f1,f2=open(nm1,'w'),open(nm2,'w')
fns= list(set(T.get('image_filename')))
for fn in fns:
f2.write('%s\n' % fn.strip())
for ti in T:
f1.write('%s\n' % ti.get('image_filename').strip())
f1.close()
f2.close()
print('Wrote *-names.txt')
if opt.brickq_deps:
import qdo
from legacypipe.survey import on_bricks_dependencies
#... find Queue...
q = qdo.connect(opt.queue, create_ok=True)
print('Connected to QDO queue', opt.queue, q)
brick_to_task = dict()
I = survey.photometric_ccds(T)
print(len(I), 'CCDs are photometric')
T.cut(I)
I = survey.apply_blacklist(T)
print(len(I), 'CCDs are not blacklisted')
T.cut(I)
print(len(T), 'CCDs remaining')
T.wra = T.ra + (T.ra > 180) * -360
wra = rlo - 360
plt.clf()
plt.plot(T.wra, T.dec, 'b.')
ax = [wra, rhi, dlo, dhi]
plt.axis(ax)
plt.title('CCDs')
plt.savefig('q-ccds.png')
B.wra = B.ra + (B.ra > 180) * -360
# this slight overestimate (for DECam images) is fine
radius = 0.3
Iccds = match_radec(B.ra, B.dec, T.ra, T.dec, radius,
indexlist=True)
ikeep = []
for ib,(b,Iccd) in enumerate(zip(B, Iccds)):
if Iccd is None or len(Iccd) == 0:
print('No matched CCDs to brick', b.brickname)
continue
wcs = wcs_for_brick(b)
cI = ccds_touching_wcs(wcs, T[np.array(Iccd)])
print(len(cI), 'CCDs touching brick', b.brickname)
if len(cI) == 0:
continue
ikeep.append(ib)
B.cut(np.array(ikeep))
print('Cut to', len(B), 'bricks touched by CCDs')
for brickq in range(4):
I = np.flatnonzero(B.brickq == brickq)
print(len(I), 'bricks with brickq =', brickq)
J = np.flatnonzero(B.brickq < brickq)
preB = B[J]
reqs = []
if brickq > 0:
for b in B[I]:
# find brick dependencies
brickdeps = on_bricks_dependencies(b, survey, bricks=preB)
# convert to task ids
taskdeps = [brick_to_task.get(b.brickname,None) for b in brickdeps]
# If we dropped a dependency brick from a previous brickq because
# of no overlapping CCDs, it won't appear in the brick_to_task map.
taskdeps = [t for t in taskdeps if t is not None]
reqs.append(taskdeps)
plt.clf()
plt.plot(B.wra, B.dec, '.', color='0.5')
plt.plot(B.wra[I], B.dec[I], 'b.')
plt.axis(ax)
plt.title('Bricks: brickq=%i' % brickq)
plt.savefig('q-bricks-%i.png' % brickq)
# submit to qdo queue
print('Queuing', len(B[I]), 'bricks')
if brickq == 0:
reqs = None
else:
assert(len(I) == len(reqs))
taskids = q.add_multiple(B.brickname[I], requires=reqs)
assert(len(taskids) == len(I))
print('Queued', len(taskids), 'bricks')
brick_to_task.update(dict(zip(B.brickname[I], taskids)))
if not (opt.calibs or opt.forced or opt.lsb):
sys.exit(0)
bands = 'grz'
log('Filters:', np.unique(T.filter))
T.cut(np.flatnonzero(np.array([f in bands for f in T.filter])))
log('Cut to', len(T), 'CCDs in filters', bands)
if opt.touching:
allI = set()
for b in B:
wcs = wcs_for_brick(b)
I = ccds_touching_wcs(wcs, T)
log(len(I), 'CCDs for brick', b.brickid, 'RA,Dec (%.2f, %.2f)' % (b.ra, b.dec))
if len(I) == 0:
continue
allI.update(I)
allI = list(allI)
allI.sort()
elif opt.near:
# Roughly brick radius + DECam image radius
radius = 0.35
allI,nil,nil = match_radec(T.ra, T.dec, B.ra, B.dec, radius, nearest=True)
else:
allI = np.arange(len(T))
if opt.write_ccds:
T[allI].writeto(opt.write_ccds)
log('Wrote', opt.write_ccds)
## Be careful here -- T has been cut; we want to write out T.index.
## 'allI' contains indices into T.
if opt.forced:
log('Writing forced-photometry commands to', opt.out)
f = open(opt.out,'w')
log('Total of', len(allI), 'CCDs')
for j,i in enumerate(allI):
expstr = '%08i' % T.expnum[i]
outfn = os.path.join('forced', expstr[:5], expstr,
'decam-%s-%s-forced.fits' %
(expstr, T.ccdname[i]))
imgfn = os.path.join(survey.survey_dir, 'images',
T.image_filename[i].strip())
if (not os.path.exists(imgfn) and
imgfn.endswith('.fz') and
os.path.exists(imgfn[:-3])):
imgfn = imgfn[:-3]
#f.write('python legacypipe/forced_photom_decam.py %s %i DR3 %s\n' %
# (imgfn, T.image_hdu[i], outfn))
f.write('python legacypipe/forced_photom_decam.py --apphot --constant-invvar %i %s DR3 %s\n' %
(T.expnum[i], T.ccdname[i], outfn))
f.close()
log('Wrote', opt.out)
sys.exit(0)
if opt.lsb:
log('Writing LSB commands to', opt.out)
f = open(opt.out,'w')
log('Total of', len(allI), 'CCDs')
for j,i in enumerate(allI):
exp = T.expnum[i]
ext = T.ccdname[i].strip()
outfn = 'lsb/lsb-%s-%s.fits' % (exp, ext)
f.write('python projects/desi/lsb.py --expnum %i --extname %s --out %s -F -n > lsb/lsb-%s-%s.log 2>&1\n' % (exp, ext, outfn, exp, ext))
f.close()
log('Wrote', opt.out)
sys.exit(0)
log('Writing calibs to', opt.out)
f = open(opt.out,'w')
log('Total of', len(allI), 'CCDs')
batch = []
def write_batch(f, batch, cmd):
if cmd is None:
cmd = ''
f.write(cmd + ' '.join(batch) + '\n')
cmd = None
if opt.command:
cmd = 'python legacypipe/run-calib.py '
if opt.opt is not None:
cmd += opt.opt + ' '
for j,i in enumerate(allI):
if opt.delete_sky or opt.delete_pvastrom:
log(j+1, 'of', len(allI))
im = survey.get_image_object(T[i])
if opt.delete_sky and os.path.exists(im.skyfn):
log(' deleting:', im.skyfn)
os.unlink(im.skyfn)
if opt.delete_pvastrom and os.path.exists(im.pvwcsfn):
log(' deleting:', im.pvwcsfn)
os.unlink(im.pvwcsfn)
if opt.check:
log(j+1, 'of', len(allI))
im = survey.get_image_object(T[i])
if not im.run_calibs(im, just_check=True):
log('Calibs for', im.expnum, im.ccdname, im.calname, 'already done')
continue
if opt.command:
s = '%i-%s' % (T.expnum[i], T.ccdname[i])
prefix = 'python legacypipe/run-calib.py ' + opt.opt
#('python legacypipe/run-calib.py --expnum %i --ccdname %s' %
# (T.expnum[i], T.ccdname[i]))
else:
s = '%i' % T.index[i]
prefix = ''
if j < 10:
print('Index', T.index[i], 'expnum', T.expnum[i], 'ccdname', T.ccdname[i],
'filename', T.image_filename[i])
if not opt.nper:
f.write(prefix + s + '\n')
else:
batch.append(s)
if len(batch) >= opt.nper:
write_batch(f, batch, cmd)
batch = []
if opt.check:
f.flush()
if len(batch):
write_batch(f, batch, cmd)
f.close()
log('Wrote', opt.out)
return 0
def main():
import argparse
parser = argparse.ArgumentParser()
parser.add_argument(
'--expnum',
type=str,
help='Run specified exposure numbers (can be comma-separated list')
parser.add_argument(
'--all-found',
action='store_true',
default=False,
help='Only write output if all required input files are found')
parser.add_argument('--ccds',
help='Set ccds.fits file to load, default is all')
parser.add_argument('--continue',
dest='con',
help='Continue even if one exposure is bad',
action='store_true',
default=False)
parser.add_argument('--outdir',
help='Output directory, default %(default)s',
default='calib')
opt = parser.parse_args()
survey = LegacySurveyData()
if opt.ccds:
ccds = fits_table(opt.ccds)
ccds = survey.cleanup_ccds_table(ccds)
survey.ccds = ccds
if opt.expnum is not None:
expnums = [(None, int(x, 10)) for x in opt.expnum.split(',')]
else:
ccds = survey.get_ccds()
expnums = set(zip(ccds.camera, ccds.expnum))
print(len(expnums), 'unique camera+expnums')
for i, (camera, expnum) in enumerate(expnums):
print()
print('Exposure', i + 1, 'of', len(expnums), ':', camera, 'expnum',
expnum)
if camera is None:
C = survey.find_ccds(expnum=expnum)
print(len(C), 'CCDs with expnum', expnum)
camera = C.camera[0]
print('Set camera to', camera)
C = survey.find_ccds(expnum=expnum, camera=camera)
print(len(C), 'CCDs with expnum', expnum, 'and camera', camera)
im0 = survey.get_image_object(C[0])
skyoutfn = im0.merged_skyfn
psfoutfn = im0.merged_psffn
print('Checking for', skyoutfn)
print('Checking for', psfoutfn)
if os.path.exists(skyoutfn) and os.path.exists(psfoutfn):
print('Exposure', expnum, 'is done already')
continue
if not os.path.exists(skyoutfn):
try:
merge_splinesky(survey, expnum, C, skyoutfn, opt)
except:
if not opt.con:
raise
import traceback
traceback.print_exc()
print('Exposure failed:', expnum, '. Continuing...')
if not os.path.exists(psfoutfn):
try:
merge_psfex(survey, expnum, C, psfoutfn, opt)
except:
if not opt.con:
raise
import traceback
traceback.print_exc()
print('Exposure failed:', expnum, '. Continuing...')
def main():
"""Main program.
"""
import argparse
parser = argparse.ArgumentParser(
description=
"This script is used to produce lists of CCDs or bricks, for production purposes (building qdo queue, eg)."
)
parser.add_argument('--calibs',
action='store_true',
help='Output CCDs that need to be calibrated.')
parser.add_argument('--nper',
type=int,
default=None,
help='Batch N calibs per line')
parser.add_argument('--forced',
action='store_true',
help='Output forced-photometry commands')
parser.add_argument('--lsb',
action='store_true',
help='Output Low-Surface-Brightness commands')
parser.add_argument('--touching',
action='store_true',
help='Cut to only CCDs touching selected bricks')
parser.add_argument('--near',
action='store_true',
help='Quick cut to only CCDs near selected bricks')
parser.add_argument('--check',
action='store_true',
help='Check which calibrations actually need to run.')
parser.add_argument('--check-coadd',
action='store_true',
help='Check which caoadds actually need to run.')
parser.add_argument('--out',
help='Output filename for calibs, default %(default)s',
default='jobs')
parser.add_argument('--command',
action='store_true',
help='Write out full command-line to run calib')
parser.add_argument('--opt', help='With --command, extra options to add')
parser.add_argument('--maxdec', type=float, help='Maximum Dec to run')
parser.add_argument('--mindec', type=float, help='Minimum Dec to run')
parser.add_argument('--region', help='Region to select')
parser.add_argument('--bricks', help='Set bricks.fits file to load')
parser.add_argument('--ccds', help='Set ccds.fits file to load')
parser.add_argument('--ignore_cuts',
action='store_true',
default=False,
help='no photometric or blacklist cuts')
parser.add_argument('--save_to_fits',
action='store_true',
default=False,
help='save cut brick,ccd to fits table')
parser.add_argument(
'--name',
action='store',
default='dr3',
help='save with this suffix, e.g. refers to ccds table')
parser.add_argument('--delete-sky',
action='store_true',
help='Delete any existing sky calibration files')
parser.add_argument('--delete-pvastrom',
action='store_true',
help='Delete any existing PV WCS calibration files')
parser.add_argument('--write-ccds', help='Write CCDs list as FITS table?')
parser.add_argument(
'--brickq',
type=int,
default=None,
help='Queue only bricks with the given "brickq" value [0 to 3]')
parser.add_argument(
'--brickq-deps',
action='store_true',
default=False,
help='Queue bricks directly using qdo API, setting brickq dependencies'
)
parser.add_argument('--queue',
default='bricks',
help='With --brickq-deps, the QDO queue name to use')
opt = parser.parse_args()
survey = LegacySurveyData()
if opt.bricks is not None:
B = fits_table(opt.bricks)
log('Read', len(B), 'from', opt.bricks)
else:
B = survey.get_bricks()
if opt.ccds is not None:
T = fits_table(opt.ccds)
log('Read', len(T), 'from', opt.ccds)
else:
T = survey.get_ccds()
log(len(T), 'CCDs')
T.index = np.arange(len(T))
if opt.ignore_cuts == False:
I = survey.photometric_ccds(T)
print(len(I), 'CCDs are photometric')
T.cut(I)
I = survey.apply_blacklist(T)
print(len(I), 'CCDs are not blacklisted')
T.cut(I)
print(len(T), 'CCDs remain')
# I,J,d,counts = match_radec(B.ra, B.dec, T.ra, T.dec, 0.2, nearest=True, count=True)
# plt.clf()
# plt.hist(counts, counts.max()+1)
# plt.savefig('bricks.png')
# B.cut(I[counts >= 9])
# plt.clf()
# plt.plot(B.ra, B.dec, 'b.')
# #plt.scatter(B.ra[I], B.dec[I], c=counts)
# plt.savefig('bricks2.png')
# DES Stripe82
#rlo,rhi = 350.,360.
# rlo,rhi = 300., 10.
# dlo,dhi = -6., 4.
# TINY bit
#rlo,rhi = 350.,351.1
#dlo,dhi = 0., 1.1
# EDR+
# 860 bricks
# ~10,000 CCDs
#rlo,rhi = 239,246
#dlo,dhi = 5, 13
# DR1
#rlo,rhi = 0, 360
# part 1
#dlo,dhi = 25, 40
# part 2
#dlo,dhi = 20,25
# part 3
#dlo,dhi = 15,20
# part 4
#dlo,dhi = 10,15
# part 5
#dlo,dhi = 5,10
# the rest
#dlo,dhi = -11, 5
#dlo,dhi = 15,25.5
dlo, dhi = -25, 40
rlo, rhi = 0, 360
# Arjun says 3x3 coverage area is roughly
# RA=240-252 DEC=6-12 (but not completely rectangular)
# COSMOS
#rlo,rhi = 148.9, 151.2
#dlo,dhi = 0.9, 3.5
# A nice well-behaved region (EDR2/3)
# rlo,rhi = 243.6, 244.6
# dlo,dhi = 8.1, 8.6
# 56 bricks, ~725 CCDs
#B.cut((B.ra > 240) * (B.ra < 242) * (B.dec > 5) * (B.dec < 7))
# 240 bricks, ~3000 CCDs
#B.cut((B.ra > 240) * (B.ra < 244) * (B.dec > 5) * (B.dec < 9))
# 535 bricks, ~7000 CCDs
#B.cut((B.ra > 240) * (B.ra < 245) * (B.dec > 5) * (B.dec < 12))
if opt.region in ['test1', 'test2', 'test3', 'test4']:
nm = dict(
test1='2446p115', # weird stuff around bright star
test2='1183p292', # faint sources around bright galaxy
test3='3503p005', # DES
test4='1163p277', # Pollux
)[opt.region]
B.cut(np.flatnonzero(np.array([s == nm for s in B.brickname])))
log('Cut to', len(B), 'bricks')
log(B.ra, B.dec)
dlo, dhi = -90, 90
rlo, rhi = 0, 360
elif opt.region == 'edr':
# EDR:
# 535 bricks, ~7000 CCDs
rlo, rhi = 240, 245
dlo, dhi = 5, 12
elif opt.region == 'edrplus':
rlo, rhi = 235, 248
dlo, dhi = 5, 15
elif opt.region == 'edr-south':
rlo, rhi = 240, 245
dlo, dhi = 5, 10
elif opt.region == 'cosmos1':
# 16 bricks in the core of the COSMOS field.
rlo, rhi = 149.75, 150.75
dlo, dhi = 1.6, 2.6
elif opt.region == 'pristine':
# Stream?
rlo, rhi = 240, 250
dlo, dhi = 10, 15
elif opt.region == 'des':
dlo, dhi = -6., 4.
rlo, rhi = 317., 7.
T.cut(np.flatnonzero(np.array(['CPDES82' in fn for fn in T.cpimage])))
log('Cut to', len(T), 'CCDs with "CPDES82" in filename')
elif opt.region == 'subdes':
rlo, rhi = 320., 360.
dlo, dhi = -1.25, 1.25
elif opt.region == 'northwest':
rlo, rhi = 240, 360
dlo, dhi = 20, 40
elif opt.region == 'north':
rlo, rhi = 120, 240
dlo, dhi = 20, 40
elif opt.region == 'northeast':
rlo, rhi = 0, 120
dlo, dhi = 20, 40
elif opt.region == 'southwest':
rlo, rhi = 240, 360
dlo, dhi = -20, 0
elif opt.region == 'south':
rlo, rhi = 120, 240
dlo, dhi = -20, 0
elif opt.region == 'southeast':
rlo, rhi = 0, 120
dlo, dhi = -20, 0
elif opt.region == 'southsoutheast':
rlo, rhi = 0, 120
dlo, dhi = -20, -10
elif opt.region == 'midwest':
rlo, rhi = 240, 360
dlo, dhi = 0, 20
elif opt.region == 'middle':
rlo, rhi = 120, 240
dlo, dhi = 0, 20
elif opt.region == 'mideast':
rlo, rhi = 0, 120
dlo, dhi = 0, 20
elif opt.region == 'grz':
# Bricks with grz coverage.
# Be sure to use --bricks survey-bricks-in-dr1.fits
# which has_[grz] columns.
B.cut((B.has_g == 1) * (B.has_r == 1) * (B.has_z == 1))
log('Cut to', len(B), 'bricks with grz coverage')
elif opt.region == 'nogrz':
# Bricks without grz coverage.
# Be sure to use --bricks survey-bricks-in-dr1.fits
# which has_[grz] columns.
B.cut(np.logical_not((B.has_g == 1) * (B.has_r == 1) * (B.has_z == 1)))
log('Cut to', len(B), 'bricks withOUT grz coverage')
elif opt.region == 'deep2':
rlo, rhi = 250, 260
dlo, dhi = 30, 35
elif opt.region == 'deep2f3':
rlo, rhi = 351.25, 353.75
dlo, dhi = 0, 0.5
elif opt.region == 'virgo':
rlo, rhi = 185, 190
dlo, dhi = 10, 15
elif opt.region == 'virgo2':
rlo, rhi = 182, 192
dlo, dhi = 8, 18
elif opt.region == 'lsb':
rlo, rhi = 147.2, 147.8
dlo, dhi = -0.4, 0.4
elif opt.region == 'eboss-sgc':
# generous boundaries to make sure get all relevant images
# RA -45 to +45
# Dec -5 to +7
rlo, rhi = 310., 50.
dlo, dhi = -6., 6.
elif opt.region == 'eboss-ngc':
# generous boundaries to make sure get all relevant images
# NGC ELGs
# RA 115 to 175
# Dec 15 to 30
rlo, rhi = 122., 177.
dlo, dhi = 12., 32.
elif opt.region == 'mzls':
dlo, dhi = 30., 90.
elif opt.region == 'dr4-bootes':
# https://desi.lbl.gov/trac/wiki/DecamLegacy/DR4sched
#dlo,dhi = 34., 35.
#rlo,rhi = 209.5, 210.5
dlo, dhi = 33., 36.
rlo, rhi = 216.5, 219.5
if opt.mindec is not None:
dlo = opt.mindec
if opt.maxdec is not None:
dhi = opt.maxdec
if rlo < rhi:
B.cut((B.ra >= rlo) * (B.ra <= rhi) * (B.dec >= dlo) * (B.dec <= dhi))
else: # RA wrap
B.cut(
np.logical_or(B.ra >= rlo, B.ra <= rhi) * (B.dec >= dlo) *
(B.dec <= dhi))
log(len(B), 'bricks in range')
#for name in B.get('brickname'):
#print(name)
B.writeto('bricks-cut.fits')
I, J, d = match_radec(B.ra, B.dec, T.ra, T.dec, survey.bricksize)
keep = np.zeros(len(B), bool)
for i in I:
keep[i] = True
B.cut(keep)
log('Cut to', len(B), 'bricks near CCDs')
plt.clf()
plt.plot(B.ra, B.dec, 'b.')
plt.title('DR3 bricks')
plt.axis([360, 0, np.min(B.dec) - 1, np.max(B.dec) + 1])
plt.savefig('bricks.png')
if opt.brickq is not None:
B.cut(B.brickq == opt.brickq)
log('Cut to', len(B), 'with brickq =', opt.brickq)
if opt.touching:
keep = np.zeros(len(T), bool)
for j in J:
keep[j] = True
T.cut(keep)
log('Cut to', len(T), 'CCDs near bricks')
# Aside -- how many near DR1=1 CCDs?
if False:
T2 = D.get_ccds()
log(len(T2), 'CCDs')
T2.cut(T2.dr1 == 1)
log(len(T2), 'CCDs marked DR1=1')
log(len(B), 'bricks in range')
I, J, d = match_radec(B.ra, B.dec, T2.ra, T2.dec, survey.bricksize)
keep = np.zeros(len(B), bool)
for i in I:
keep[i] = True
B2 = B[keep]
log('Total of', len(B2), 'bricks near CCDs with DR1=1')
for band in 'grz':
Tb = T2[T2.filter == band]
log(len(Tb), 'in filter', band)
I, J, d = match_radec(B2.ra, B2.dec, Tb.ra, Tb.dec,
survey.bricksize)
good = np.zeros(len(B2), np.uint8)
for i in I:
good[i] = 1
B2.set('has_' + band, good)
B2.writeto('survey-bricks-in-dr1.fits')
sys.exit(0)
# sort by dec decreasing
#B.cut(np.argsort(-B.dec))
# RA increasing
B.cut(np.argsort(B.ra))
for b in B:
if opt.check:
fn = 'dr1n/tractor/%s/tractor-%s.fits' % (b.brickname[:3],
b.brickname)
if os.path.exists(fn):
print('Exists:', fn, file=sys.stderr)
continue
if opt.check_coadd:
fn = 'dr1b/coadd/%s/%s/decals-%s-image.jpg' % (
b.brickname[:3], b.brickname, b.brickname)
if os.path.exists(fn):
print('Exists:', fn, file=sys.stderr)
continue
#print(b.brickname)
if opt.save_to_fits:
assert (opt.touching)
# Write cut tables to file
for tab, typ in zip([B, T], ['bricks', 'ccds']):
fn = '%s-%s-cut.fits' % (typ, opt.region)
if os.path.exists(fn):
os.remove(fn)
tab.writeto(fn)
print('Wrote %s' % fn)
# Write text files listing ccd and filename names
nm1, nm2 = 'ccds-%s.txt' % opt.region, 'filenames-%s.txt' % opt.region
if os.path.exists(nm1):
os.remove(nm1)
if os.path.exists(nm2):
os.remove(nm2)
f1, f2 = open(nm1, 'w'), open(nm2, 'w')
fns = list(set(T.get('image_filename')))
for fn in fns:
f2.write('%s\n' % fn.strip())
for ti in T:
f1.write('%s\n' % ti.get('image_filename').strip())
f1.close()
f2.close()
print('Wrote *-names.txt')
if opt.brickq_deps:
import qdo
from legacypipe.survey import on_bricks_dependencies
#... find Queue...
q = qdo.connect(opt.queue, create_ok=True)
print('Connected to QDO queue', opt.queue, q)
brick_to_task = dict()
I = survey.photometric_ccds(T)
print(len(I), 'CCDs are photometric')
T.cut(I)
I = survey.apply_blacklist(T)
print(len(I), 'CCDs are not blacklisted')
T.cut(I)
print(len(T), 'CCDs remaining')
T.wra = T.ra + (T.ra > 180) * -360
wra = rlo - 360
plt.clf()
plt.plot(T.wra, T.dec, 'b.')
ax = [wra, rhi, dlo, dhi]
plt.axis(ax)
plt.title('CCDs')
plt.savefig('q-ccds.png')
B.wra = B.ra + (B.ra > 180) * -360
# this slight overestimate (for DECam images) is fine
radius = 0.3
Iccds = match_radec(B.ra, B.dec, T.ra, T.dec, radius, indexlist=True)
ikeep = []
for ib, (b, Iccd) in enumerate(zip(B, Iccds)):
if Iccd is None or len(Iccd) == 0:
print('No matched CCDs to brick', b.brickname)
continue
wcs = wcs_for_brick(b)
cI = ccds_touching_wcs(wcs, T[np.array(Iccd)])
print(len(cI), 'CCDs touching brick', b.brickname)
if len(cI) == 0:
continue
ikeep.append(ib)
B.cut(np.array(ikeep))
print('Cut to', len(B), 'bricks touched by CCDs')
for brickq in range(4):
I = np.flatnonzero(B.brickq == brickq)
print(len(I), 'bricks with brickq =', brickq)
J = np.flatnonzero(B.brickq < brickq)
preB = B[J]
reqs = []
if brickq > 0:
for b in B[I]:
# find brick dependencies
brickdeps = on_bricks_dependencies(b, survey, bricks=preB)
# convert to task ids
taskdeps = [
brick_to_task.get(b.brickname, None) for b in brickdeps
]
# If we dropped a dependency brick from a previous brickq because
# of no overlapping CCDs, it won't appear in the brick_to_task map.
taskdeps = [t for t in taskdeps if t is not None]
reqs.append(taskdeps)
plt.clf()
plt.plot(B.wra, B.dec, '.', color='0.5')
plt.plot(B.wra[I], B.dec[I], 'b.')
plt.axis(ax)
plt.title('Bricks: brickq=%i' % brickq)
plt.savefig('q-bricks-%i.png' % brickq)
# submit to qdo queue
print('Queuing', len(B[I]), 'bricks')
if brickq == 0:
reqs = None
else:
assert (len(I) == len(reqs))
taskids = q.add_multiple(B.brickname[I], requires=reqs)
assert (len(taskids) == len(I))
print('Queued', len(taskids), 'bricks')
brick_to_task.update(dict(zip(B.brickname[I], taskids)))
if not (opt.calibs or opt.forced or opt.lsb):
sys.exit(0)
bands = 'grz'
log('Filters:', np.unique(T.filter))
T.cut(np.flatnonzero(np.array([f in bands for f in T.filter])))
log('Cut to', len(T), 'CCDs in filters', bands)
if opt.touching:
allI = set()
for b in B:
wcs = wcs_for_brick(b)
I = ccds_touching_wcs(wcs, T)
log(len(I), 'CCDs for brick', b.brickid,
'RA,Dec (%.2f, %.2f)' % (b.ra, b.dec))
if len(I) == 0:
continue
allI.update(I)
allI = list(allI)
allI.sort()
elif opt.near:
# Roughly brick radius + DECam image radius
radius = 0.35
allI, nil, nil = match_radec(T.ra,
T.dec,
B.ra,
B.dec,
radius,
nearest=True)
else:
allI = np.arange(len(T))
if opt.write_ccds:
T[allI].writeto(opt.write_ccds)
log('Wrote', opt.write_ccds)
## Be careful here -- T has been cut; we want to write out T.index.
## 'allI' contains indices into T.
if opt.forced:
log('Writing forced-photometry commands to', opt.out)
f = open(opt.out, 'w')
log('Total of', len(allI), 'CCDs')
for j, i in enumerate(allI):
expstr = '%08i' % T.expnum[i]
outfn = os.path.join(
'forced', expstr[:5], expstr,
'decam-%s-%s-forced.fits' % (expstr, T.ccdname[i]))
imgfn = os.path.join(survey.survey_dir, 'images',
T.image_filename[i].strip())
if (not os.path.exists(imgfn) and imgfn.endswith('.fz')
and os.path.exists(imgfn[:-3])):
imgfn = imgfn[:-3]
#f.write('python legacypipe/forced_photom_decam.py %s %i DR3 %s\n' %
# (imgfn, T.image_hdu[i], outfn))
f.write(
'python legacypipe/forced_photom_decam.py --apphot --constant-invvar %i %s DR3 %s\n'
% (T.expnum[i], T.ccdname[i], outfn))
f.close()
log('Wrote', opt.out)
sys.exit(0)
if opt.lsb:
log('Writing LSB commands to', opt.out)
f = open(opt.out, 'w')
log('Total of', len(allI), 'CCDs')
for j, i in enumerate(allI):
exp = T.expnum[i]
ext = T.ccdname[i].strip()
outfn = 'lsb/lsb-%s-%s.fits' % (exp, ext)
f.write(
'python projects/desi/lsb.py --expnum %i --extname %s --out %s -F -n > lsb/lsb-%s-%s.log 2>&1\n'
% (exp, ext, outfn, exp, ext))
f.close()
log('Wrote', opt.out)
sys.exit(0)
log('Writing calibs to', opt.out)
f = open(opt.out, 'w')
log('Total of', len(allI), 'CCDs')
batch = []
def write_batch(f, batch, cmd):
if cmd is None:
cmd = ''
f.write(cmd + ' '.join(batch) + '\n')
cmd = None
if opt.command:
cmd = 'python legacypipe/run-calib.py '
if opt.opt is not None:
cmd += opt.opt + ' '
for j, i in enumerate(allI):
if opt.delete_sky or opt.delete_pvastrom:
log(j + 1, 'of', len(allI))
im = survey.get_image_object(T[i])
if opt.delete_sky and os.path.exists(im.skyfn):
log(' deleting:', im.skyfn)
os.unlink(im.skyfn)
if opt.delete_pvastrom and os.path.exists(im.pvwcsfn):
log(' deleting:', im.pvwcsfn)
os.unlink(im.pvwcsfn)
if opt.check:
log(j + 1, 'of', len(allI))
im = survey.get_image_object(T[i])
if not im.run_calibs(im, just_check=True):
log('Calibs for', im.expnum, im.ccdname, im.calname,
'already done')
continue
if opt.command:
s = '%i-%s' % (T.expnum[i], T.ccdname[i])
prefix = 'python legacypipe/run-calib.py ' + opt.opt
#('python legacypipe/run-calib.py --expnum %i --ccdname %s' %
# (T.expnum[i], T.ccdname[i]))
else:
s = '%i' % T.index[i]
prefix = ''
if j < 10:
print('Index', T.index[i], 'expnum', T.expnum[i], 'ccdname',
T.ccdname[i], 'filename', T.image_filename[i])
if not opt.nper:
f.write(prefix + s + '\n')
else:
batch.append(s)
if len(batch) >= opt.nper:
write_batch(f, batch, cmd)
batch = []
if opt.check:
f.flush()
if len(batch):
write_batch(f, batch, cmd)
f.close()
log('Wrote', opt.out)
return 0
