def __init__(self, t, mjd=None, date=None):
if t is None:
if date is not None:
mjd = datetomjd(date)
if mjd is not None:
t = mjd * 24. * 3600.
super(TAITime, self).__init__(t)
def __init__(self, t, mjd=None, date=None):
if t is None:
if date is not None:
mjd = datetomjd(date)
if mjd is not None:
t = mjd * 24. * 3600.
super(TAITime, self).__init__(t)
def timed_out(self, dt):
now = datenow()
dt = (now - self.lastNewFile).total_seconds()
print('No new images seen for', dt, 'seconds.')
markmjds = []
if dt > self.longtime:
edate = (self.lastNewFile +
datetime.timedelta(0, self.longtime))
markmjds.append((datetomjd(edate),'r'))
self.plot_recent(markmjds=markmjds)
class TAITime(ScalarParam, ArithmeticParams):
'''
This is TAI as used in the SDSS 'frame' headers; eg
TAI = 4507681767.55 / 1st row -
Number of seconds since Nov 17 1858
And http://mirror.sdss3.org/datamodel/glossary.html#tai
says:
MJD = TAI/(24*3600)
'''
equinox = 53084.28 # mjd of the spring equinox in 2004
daysperyear = 365.25 # Julian years, by definition
mjd2k = datetomjd(J2000)
def __init__(self, t, mjd=None, date=None):
if t is None:
if date is not None:
mjd = datetomjd(date)
if mjd is not None:
t = mjd * 24. * 3600.
super(TAITime, self).__init__(t)
def toMjd(self):
return self.getValue() / (24. * 3600.)
def getSunTheta(self):
mjd = self.toMjd()
th = 2. * np.pi * (mjd - TAITime.equinox) / TAITime.daysperyear
th = np.fmod(th, 2. * np.pi)
return th
def toYears(self):
''' years since Nov 17, 1858 ?'''
return float(self.getValue() / (24. * 3600. * TAITime.daysperyear))
def toYear(self):
''' to proper year '''
return self.toYears() - TAITime(None,
mjd=TAITime.mjd2k).toYears() + 2000.0
def plot_measurements(mm, plotfn, nom, mjds=[], mjdrange=None, allobs=None,
markmjds=[], show_plot=True):
import pylab as plt
T = db_to_fits(mm)
T.band = np.core.defchararray.replace(T.band, 'zd', 'z')
print(len(T), 'exposures')
T.mjd_end = T.mjd_obs + T.exptime / 86400.
#Tall = T
Tnonobject = T[T.obstype != 'object']
print(len(Tnonobject), 'exposures are not OBJECTs')
T = T[T.obstype == 'object']
print(len(T), 'OBJECT exposures')
if len(T) == 0:
return
ccmap = dict(g='g', r='r', z='m')
#bands = 'grz'
bands = np.unique(T.band)
#print('Unique bands:', bands)
TT = []
for band in bands:
G = T[T.band == band]
TT.append(G)
plt.clf()
plt.subplots_adjust(hspace=0.1, top=0.98, right=0.95, left=0.1,
bottom=0.07)
def limitstyle(band):
return dict(mec='k', mfc=ccmap[band], ms=8, mew=1)
# Check for bad things that can happen
bads = []
# bad_pixcnt
I = np.flatnonzero(T.bad_pixcnt)
for i in I:
bads.append((i, 'pixcnt'))
# low nmatched
I = np.flatnonzero((T.nmatched >= 0) * (T.nmatched < 10))
for i in I:
bads.append((i, 'nmatched'))
if allobs is not None:
# Duplicate md5sum
for i in range(len(T)):
if T.md5sum[i] == '':
continue
a = allobs.filter(md5sum=T.md5sum[i]).exclude(
filename=T.filename[i], extension=T.extension[i])
if a.count():
# Only report this one as bad if one of the repeats was earlier
for ai in a:
if ai.mjd_obs < T.mjd_obs[i]:
bads.append((i, 'md5sum'))
break
# Group together bad things for the same image.
bd = {}
for i,reason in bads:
if i in bd:
bd[i] = bd[i] + ', ' + reason
else:
bd[i] = reason
bads = bd.items()
ilatest = np.argmax(T.mjd_obs)
latest = T[ilatest]
SP = 5
mx = 2.
plt.subplot(SP,1,1)
for band,Tb in zip(bands, TT):
plt.plot(Tb.mjd_obs, Tb.seeing, 'o', color=ccmap[band])
I = np.flatnonzero(Tb.seeing > mx)
if len(I):
plt.plot(Tb.mjd_obs[I], [mx]*len(I), '^', **limitstyle(band))
yl,yh = plt.ylim()
plt.axhline(1.3, color='k', alpha=0.5)
plt.axhline(1.2, color='k', alpha=0.1)
plt.axhline(1.0, color='k', alpha=0.1)
plt.axhline(0.8, color='k', alpha=0.1)
plt.text(latest.mjd_obs, yl+0.01*(yh-yl),
'%.2f' % latest.seeing, ha='center')
y = yl + 0.01*(yh-yl)
plt.plot(np.vstack((T.mjd_obs, T.mjd_end)),
np.vstack((y, y)), '-', lw=3, alpha=0.5, color=ccmap[band],
solid_joinstyle='bevel')
plt.ylim(yl,min(yh,mx))
plt.ylabel('Seeing (arcsec)')
ax = plt.axis()
for i,reason in bads:
plt.axvline(T.mjd_obs[i], color='r', lw=3, alpha=0.3)
plt.text(T.mjd_obs[i], ax[3], reason,
rotation=90, va='top')
plt.axis(ax)
plt.subplot(SP,1,2)
mx = 20
for band,Tb in zip(bands, TT):
sky0 = nom.sky(band)
plt.plot(Tb.mjd_obs, Tb.sky, 'o', color=ccmap[band])
plt.axhline(sky0, color=ccmap[band], alpha=0.5)
I = np.flatnonzero(Tb.sky > mx)
if len(I):
plt.plot(Tb.mjd_obs[I], [mx]*len(I), '^', **limitstyle(band))
yl,yh = plt.ylim()
yh = min(yh,mx)
plt.text(latest.mjd_obs, yl+0.01*(yh-yl),
'%.2f' % latest.sky, ha='center')
for t in T:
if t.passnumber > 0:
plt.text(t.mjd_obs, min(mx, t.sky) - 0.03*(yh-yl),
#yl+0.1*(yh-yl),
'%i' % t.passnumber, ha='center', va='top')
plt.ylim(yl,yh)
plt.ylabel('Sky (mag)')
plt.subplot(SP,1,3)
mx = 1.2
mn = 0.5
for band,Tb in zip(bands, TT):
plt.plot(Tb.mjd_obs, Tb.transparency, 'o', color=ccmap[band])
I = np.flatnonzero(Tb.transparency > mx)
if len(I):
plt.plot(Tb.mjd_obs[I], [mx]*len(I), '^', **limitstyle(band))
I = np.flatnonzero(Tb.transparency < mn)
if len(I):
plt.plot(Tb.mjd_obs[I], [mn]*len(I), 'v', **limitstyle(band))
plt.axhline(1.0, color='k', alpha=0.5)
plt.axhline(0.9, color='k', ls='--', alpha=0.5)
plt.ylabel('Transparency')
yl,yh = plt.ylim()
yl,yh = min(0.89, max(mn, yl)), min(mx, max(yh, 1.01))
plt.text(latest.mjd_obs, yl+0.01*(yh-yl),
'%.2f' % latest.transparency, ha='center')
plt.ylim(yl, yh)
plt.subplot(SP,1,4)
mx = 300
for band,Tb in zip(bands, TT):
fid = nom.fiducial_exptime(band)
basetime = fid.exptime
lo,hi = fid.exptime_min, fid.exptime_max
exptime = basetime * Tb.expfactor
clipped = np.clip(exptime, lo, hi)
if band == 'z':
t_sat = nom.saturation_time(band, Tb.sky)
clipped = np.minimum(clipped, t_sat)
Tb.clipped_exptime = clipped
Tb.depth_factor = Tb.exptime / clipped
I = np.flatnonzero(exptime > clipped)
if len(I):
plt.plot(Tb.mjd_obs[I], exptime[I], 'v', **limitstyle(band))
I = np.flatnonzero(exptime > mx)
if len(I):
plt.plot(Tb.mjd_obs[I], [mx]*len(I), '^', **limitstyle(band))
I = np.flatnonzero(exptime < clipped)
if len(I):
plt.plot(Tb.mjd_obs[I], exptime[I], '^', **limitstyle(band))
plt.plot(Tb.mjd_obs, clipped, 'o', color=ccmap[band])
plt.plot(Tb.mjd_obs, Tb.exptime, 'o', mec='k', mfc='none')
yl,yh = plt.ylim()
for band,Tb in zip(bands, TT):
dt = dict(g=-0.5,r=+0.5,z=0)[band]
fid = nom.fiducial_exptime(band)
basetime = fid.exptime
lo,hi = fid.exptime_min, fid.exptime_max
plt.axhline(basetime+dt, color=ccmap[band], alpha=0.2)
plt.axhline(lo+dt, color=ccmap[band], ls='--', alpha=0.5)
plt.axhline(hi+dt, color=ccmap[band], ls='--', alpha=0.5)
if band == 'z':
plt.plot(Tb.mjd_obs, t_sat, color=ccmap[band], ls='--', alpha=0.5)
plt.ylim(yl,min(mx, yh))
plt.ylabel('Target exposure time (s)')
plt.subplot(SP,1,5)
mn,mx = 0.6, 1.4
for band,Tb in zip(bands, TT):
plt.plot(Tb.mjd_obs, Tb.depth_factor, 'o', color=ccmap[band])
# lower and upper limits
I = np.flatnonzero(Tb.depth_factor < mn)
if len(I):
plt.plot(Tb.mjd_obs[I], [mn]*len(I), 'v', **limitstyle(band))
I = np.flatnonzero(Tb.depth_factor > mx)
if len(I):
plt.plot(Tb.mjd_obs[I], [mx]*len(I), '^', **limitstyle(band))
plt.axhline(1.0, color='k', alpha=0.5)
plt.axhline(0.9, color='k', ls='--', alpha=0.5)
plt.axhline(1.1, color='k', ls='--', alpha=0.5)
F = Tnonobject[Tnonobject.obstype == 'focus']
print(len(F), 'focus frames')
if len(F):
plt.plot(F.mjd_obs, 0.9 + np.zeros(len(F)), 'ko')
for f in F:
plt.text(f.mjd_obs, 0.88, 'F', ha='center', va='top')
if len(T) > 50:
ii = [np.argmin(T.expnum + (T.expnum == 0)*1000000),
np.argmax(T.expnum)]
else:
ii = range(len(T))
for i in ii:
if T.expnum[i] == 0:
continue
plt.text(T.mjd_obs[i], mx, '%i ' % T.expnum[i],
rotation=90, va='top', ha='center')
if len(T) <= 50:
# Mark focus frames too
for i in range(len(F)):
plt.text(F.mjd_obs[i], mx, '%i ' % F.expnum[i],
rotation=90, va='top', ha='center')
plt.ylim(mn,mx)
plt.ylabel('Depth factor')
plt.xlabel('MJD')
if mjdrange is not None:
for sp in range(SP):
plt.subplot(SP,1,sp+1)
plt.xlim(mjdrange)
plt.subplot(SP,1,SP)
xl,xh = plt.xlim()
if xh - xl < 2./24.:
# range of less than 2 hours: label every ten minutes
tx = []
tt = []
dl = mjdtodate(xl)
d = datetime.datetime(dl.year, dl.month, dl.day, dl.hour)
while True:
mjd = datetomjd(d)
if mjd > xh:
break
if mjd > xl:
tx.append(mjd)
tt.append(d.strftime('%H:%M'))
d += datetime.timedelta(0, 600)
plt.xticks(tx, tt)
plt.xlabel(dl.strftime('Time UTC starting %Y-%m-%d'))
elif xh - xl < 1:
# range of less than a day: label the hours
tx = []
tt = []
dl = mjdtodate(xl)
d = datetime.datetime(dl.year, dl.month, dl.day, dl.hour)
while True:
mjd = datetomjd(d)
if mjd > xh:
break
if mjd > xl:
tx.append(mjd)
tt.append(d.strftime('%H:%M'))
d += datetime.timedelta(0, 3600)
plt.xticks(tx, tt)
plt.xlabel(dl.strftime('Time UTC starting %Y-%m-%d'))
else:
tx,tt = plt.xticks()
# Set consistent tick marks but no labels on top plots
tt = ['']*len(tx)
for sp in range(1, SP):
plt.subplot(SP,1,sp)
plt.xticks(tx,tt)
plt.xlim(xl,xh)
plt.xlim(xl,xh)
if len(markmjds):
for sp in range(1, SP+1):
plt.subplot(SP,1,sp)
ax = plt.axis()
for mjd,c in markmjds:
plt.axvline(mjd, color=c, alpha=0.5, lw=2)
plt.axis(ax)
if show_plot:
plt.draw()
plt.show(block=False)
plt.pause(0.001)
plt.savefig(plotfn)
print('Saved', plotfn)
if show_plot:
plt.draw()
plt.show(block=False)
plt.pause(0.001)
def ephem_date_to_mjd(edate):
from astrometry.util.starutil_numpy import datetomjd
return datetomjd(edate.datetime())
def mjdnow():
from astrometry.util.starutil_numpy import datetomjd
return datetomjd(datenow()) + mjdnow_offset