def main():
global opt
opt, args = get_options()
# Get orbital ephemeris in requested time range
print 'Reading orbital ephemeris file', opt.ephemfile
ephem = Ska.Table.read_table(opt.ephemfile)
tstart = DateTime(opt.tstart).secs
tstop = DateTime(opt.tstop).secs
ephem = ephem[(ephem.Time >= tstart) & (ephem.Time <= tstop)][::opt.sample]
if len(ephem) == 0:
print 'Error: ephemeris file has no overlap with specified time interval'
sys.exit(0)
chandra_ecis = np.array([ephem.X, ephem.Y, ephem.Z]).copy().transpose()
ephem_times = ephem.Time.copy()
# Get spacecraft attitude in requested time range at the same sampling as ephemeris
dt = ephem.Time[1] - ephem.Time[0]
print(
'Fetching attitude telemetry between %s and %s at %d second intervals'
% (DateTime(ephem.Time[0]).date, DateTime(ephem.Time[-1]).date, dt))
cols, atts = fetch(
start=ephem.Time[0],
stop=ephem.Time[-1],
dt=dt,
time_format='secs',
colspecs=['aoattqt1', 'aoattqt2', 'aoattqt3', 'aoattqt4'])
atts = np.rec.fromrecords(atts, names=cols)
q1s = Ska.Numpy.interpolate(atts.aoattqt1, atts.date, ephem.Time)
q2s = Ska.Numpy.interpolate(atts.aoattqt2, atts.date, ephem.Time)
q3s = Ska.Numpy.interpolate(atts.aoattqt3, atts.date, ephem.Time)
q4s = Ska.Numpy.interpolate(atts.aoattqt4, atts.date, ephem.Time)
# Divy up calculations amongst the n-processors
i0s = range(0, len(q1s), len(q1s) // opt.nproc + 1)
i1s = i0s[1:] + [len(q1s)]
# Calculate illumination in a separate process over each sub-interval
for iproc, i0, i1 in zip(itertools.count(), i0s, i1s):
calc_vis_values(iproc, ephem_times[i0:i1], chandra_ecis[i0:i1],
q1s[i0:i1], q2s[i0:i1], q3s[i0:i1], q4s[i0:i1])
def main():
global opt
opt, args = get_options()
# Get orbital ephemeris in requested time range
print 'Reading orbital ephemeris file', opt.ephemfile
ephem = Ska.Table.read_table(opt.ephemfile)
tstart = DateTime(opt.tstart).secs
tstop = DateTime(opt.tstop).secs
ephem = ephem[(ephem.Time >= tstart)
& (ephem.Time <= tstop)][::opt.sample]
if len(ephem) == 0:
print 'Error: ephemeris file has no overlap with specified time interval'
sys.exit(0)
chandra_ecis = np.array([ephem.X, ephem.Y, ephem.Z]).copy().transpose()
ephem_times = ephem.Time.copy()
# Get spacecraft attitude in requested time range at the same sampling as ephemeris
dt = ephem.Time[1] - ephem.Time[0]
print ('Fetching attitude telemetry between %s and %s at %d second intervals'
% (DateTime(ephem.Time[0]).date, DateTime(ephem.Time[-1]).date, dt))
cols, atts = fetch(start=ephem.Time[0], stop=ephem.Time[-1], dt=dt, time_format='secs',
colspecs=['aoattqt1', 'aoattqt2', 'aoattqt3', 'aoattqt4'])
atts = np.rec.fromrecords(atts, names=cols)
q1s = Ska.Numpy.interpolate(atts.aoattqt1, atts.date, ephem.Time)
q2s = Ska.Numpy.interpolate(atts.aoattqt2, atts.date, ephem.Time)
q3s = Ska.Numpy.interpolate(atts.aoattqt3, atts.date, ephem.Time)
q4s = Ska.Numpy.interpolate(atts.aoattqt4, atts.date, ephem.Time)
# Divy up calculations amongst the n-processors
i0s = range(0, len(q1s), len(q1s) // opt.nproc + 1)
i1s = i0s[1:] + [len(q1s)]
# Calculate illumination in a separate process over each sub-interval
for iproc, i0, i1 in zip(itertools.count(), i0s, i1s):
calc_vis_values(iproc, ephem_times[i0:i1], chandra_ecis[i0:i1],
q1s[i0:i1], q2s[i0:i1], q3s[i0:i1], q4s[i0:i1])
def fetch_temps( starttime ):
(telem_hdr,telem_val) = fetch(start=DateTime(starttime).secs,
stop=( DateTime(starttime).secs+1),colspecs=['1pdeaat,1pin1at'])
telem = np.rec.fromrecords( telem_val, names=telem_hdr)
return telem
