def process_image(fn, ext, nom, sfd, opt, obs, tiles):
db = opt.db
print('Reading', fn)
if sfd is None:
sfd = gSFD
# Read primary FITS header
phdr = fitsio.read_header(fn)
obstype = phdr.get('OBSTYPE','').strip()
print('obstype:', obstype)
exptime = phdr.get('EXPTIME', 0)
expnum = phdr.get('EXPNUM', 0)
filt = phdr.get('FILTER', None)
if filt is not None:
filt = filt.strip()
filt = filt.split()[0]
if filt is None:
filt = ''
airmass = phdr.get('AIRMASS', 0.)
ra = hmsstring2ra (phdr.get('RA', '0'))
dec = dmsstring2dec(phdr.get('DEC', '0'))
# Write QA plots to files named by the exposure number
print('Exposure number:', expnum)
skip = False
if obstype in ['zero', 'focus', 'dome flat', '']:
print('Skipping obstype =', obstype)
skip = True
if exptime == 0:
print('Exposure time EXPTIME in header =', exptime)
skip = True
if expnum == '':
print('No expnum in header')
skip = True
if filt == 'solid':
print('Solid (block) filter.')
skip = True
if skip and not db:
return None
if db:
import obsdb
if ext is None:
ext = get_default_extension(fn)
m,created = obsdb.MeasuredCCD.objects.get_or_create(
filename=fn, extension=ext)
m.obstype = obstype
m.camera = camera_name(phdr)
m.expnum = expnum
m.exptime = exptime
m.mjd_obs = phdr.get('MJD-OBS', 0.)
m.airmass = airmass
m.rabore = ra
m.decbore = dec
m.band = filt
m.bad_pixcnt = ('PIXCNT1' in phdr)
m.readtime = phdr.get('READTIME', 0.)
if opt.focus and obstype == 'focus' and m.camera == 'mosaic3':
from mosaic_focus import Mosaic3FocusMeas
show_plot = opt.show
if show_plot:
import pylab as plt
plt.figure(2, figsize=(8,10))
if ext is None:
ext = get_default_extension(fn)
meas = Mosaic3FocusMeas(fn, ext, nom)
focusfn = 'focus.png'
meas.run(ps=None, plotfn=focusfn)
print('Wrote', focusfn)
if show_plot:
plt.draw()
plt.show(block=False)
plt.pause(0.001)
plt.figure(1)
if skip:
m.save()
return None
if opt.doplots:
from astrometry.util.plotutils import PlotSequence
ps = PlotSequence('qa-%i' % expnum)
ps.printfn = False
else:
ps = None
# Measure the new image
kwa = {}
if ext is not None:
kwa.update(ext=ext)
if opt.n_fwhm is not None:
kwa.update(n_fwhm=opt.n_fwhm)
M = measure_raw(fn, ps=ps, **kwa)
if opt.doplots:
from glob import glob
# Gather all the QAplots into a single pdf and clean them up.
qafile = 'qa-%i.pdf' % expnum
pnglist = sorted(glob('qa-%i-??.png' % expnum))
cmd = 'convert {} {}'.format(' '.join(pnglist), qafile)
print('Writing out {}'.format(qafile))
#print(cmd)
os.system(cmd)
if not opt.keep_plots:
[os.remove(png) for png in pnglist]
# (example results for testig)
#M = {'seeing': 1.4890481099577366, 'airmass': 1.34,
#'skybright': 18.383479116033314, 'transparency': 0.94488537276869045,
#'band': 'z', 'zp': 26.442847814941093}
#print('Measurements:', M)
trans = M.get('transparency', 0)
band = M['band']
# Look up E(B-V) in SFD map
ebv = sfd.ebv(ra, dec)[0]
print('E(B-V): %.3f' % ebv)
if trans > 0:
fid = nom.fiducial_exptime(band)
expfactor = exposure_factor(fid, nom,
airmass, ebv, M['seeing'], M['skybright'],
trans)
print('Exposure factor: %6.3f' % expfactor)
t_exptime = expfactor * fid.exptime
print('Target exposure time: %6.1f' % t_exptime)
t_exptime = np.clip(t_exptime, fid.exptime_min, fid.exptime_max)
print('Clipped exposure time: %6.1f' % t_exptime)
if band == 'z':
t_sat = nom.saturation_time(band, M['skybright'])
if t_exptime > t_sat:
t_exptime = t_sat
print('Reduced exposure time to avoid z-band saturation: %.1f' % t_exptime)
print
print('Actual exposure time taken: %6.1f' % exptime)
print('Depth (exposure time) factor: %6.3f' % (exptime / t_exptime))
# If you were going to re-plan, you would run with these args:
plandict = dict(seeing=M['seeing'], transparency=trans)
# Assume the sky is as much brighter than canonical in each band... unlikely
dsky = M['skybright'] - nom.sky(M['band'])
for b in 'grz':
plandict['sb'+b] = nom.sky(b) + dsky
# Note that nightlystrategy.py takes UTC dates.
start = datenow()
# Start the strategy 5 minutes from now.
start += datetime.timedelta(0, 5*60)
d = start.date()
plandict['startdate'] = '%04i-%02i-%02i' % (d.year, d.month, d.day)
t = start.time()
plandict['starttime'] = t.strftime('%H:%M:%S')
# Make an hour-long plan
end = start + datetime.timedelta(0, 3600)
d = end.date()
plandict['enddate'] = '%04i-%02i-%02i' % (d.year, d.month, d.day)
t = end.time()
plandict['endtime'] = t.strftime('%H:%M:%S')
# Set "--date" to be the UTC date at previous sunset.
# (nightlystrategy will ask for the next setting of the sun below
# -18-degrees from that date to define the sn_18). We could
# probably also get away with subtracting, like, 12 hours from
# now()...
sun = ephem.Sun()
obs.date = datenow()
# not the proper horizon, but this doesn't matter -- just need it to
# be before -18-degree twilight.
obs.horizon = 0.
sunset = obs.previous_setting(sun)
# pyephem's Date.tuple() splits a date into y,m,d,h,m,s
d = sunset.tuple()
#print('Date at sunset, UTC:', d)
year,month,day = d[:3]
plandict['date'] = '%04i-%02i-%02i' % (year, month, day)
# Decide the pass.
goodseeing = plandict['seeing'] < 1.3
photometric = plandict['transparency'] > 0.9
if goodseeing and photometric:
passnum = 1
elif goodseeing or photometric:
passnum = 2
else:
passnum = 3
plandict['pass'] = passnum
## ??
plandict['portion'] = 1.0
print('Replan command:')
print()
print('python2.7 nightlystrategy.py --seeg %(seeing).3f --seer %(seeing).3f --seez %(seeing).3f --sbg %(sbg).3f --sbr %(sbr).3f --sbz %(sbz).3f --transparency %(transparency).3f --start-date %(startdate)s --start-time %(starttime)s --end-date %(enddate)s --end-time %(endtime)s --date %(date)s --portion %(portion)f --pass %(pass)i' % plandict)
print()
else:
plandict = None
expfactor = 0.
rtn = (M, plandict, expnum)
if not db:
return rtn
m.racenter = M['ra_ccd']
m.deccenter = M['dec_ccd']
m.ebv = ebv
zp = M.get('zp', 0.)
if zp is None:
zp = 0.
m.zeropoint = zp
m.transparency = trans
m.seeing = M.get('seeing', 0.)
m.sky = M['skybright']
m.expfactor = expfactor
m.dx = M.get('dx', 0)
m.dy = M.get('dy', 0)
m.nmatched = M.get('nmatched',0)
img = fitsio.read(fn, ext=1)
cheaphash = np.sum(img)
# cheaphash becomes an int64.
m.md5sum = cheaphash
set_tile_fields(m, phdr, tiles)
m.save()
return rtn
