def shift_time(told, target):
''' This is for calculating a time shift for a given schedule, to
bring it to the current date. When editing a .scd file with
calibrators, enter the first time as a Time() object told,
and enter the current date/time as a Time() object target.
Returns a new Time() object with the date/time that the schedule
should be adjusted to. There is a potential for the time to
be off by four minutes (one day's sidereal lag).
'''
from astropy.time import TimeDelta
dt = TimeDelta((util.lobe(eovsa_lst(target) - eovsa_lst(told)) * 0.158720),
format='jd')
print dt
return target - dt
def rd_calpnt(filename):
''' Read and return contents of output of CALPNT or CALPNT2M observation
Note that the "x" offsets are dRA and dAZ. To apply these in subsequent
routines, dRA is converted to dHA by inverting the sign, while dAZ is
converted to dXEL (angle on the sky) by multiplying by cos(EL).
'''
import dbutil
f = open(filename, 'r')
lines = f.readlines()
f.close()
ants = lines[0].split('Ant ')[1:]
antlist = []
try:
for ant in ants:
antlist.append(int(ant[:2]))
except:
print 'Unrecognized format (header line) for', filename
return None
nants = len(ants)
lines = lines[1:]
nlines = len(lines)
dra = np.zeros((nants, nlines), np.float)
ddec = np.zeros((nants, nlines), np.float)
ha = []
dec = []
source = []
timstr = []
for i, line in enumerate(lines):
if len(line) < 9:
dra = dra[:, :i]
ddec = ddec[:, :i]
break
vals = line[9:].split()
if len(vals) != nants * 2 + 4:
print 'Error reading line', i + 2, 'of', filename
dra = dra[:, :i]
ddec = ddec[:, :i]
break
else:
try:
source.append(line[:8])
timstr.append(vals[0] + ' ' + vals[1])
ha.append(vals[2])
dec.append(vals[3])
dra[:, i] = np.array(vals[4::2]).astype(float)
ddec[:, i] = np.array(vals[5::2]).astype(float)
except:
print 'Error parsing line', i + 2, 'of', filename
# Convert HA, Dec from degrees to radians, and then convert HA to RA
ha = np.array(ha).astype(float) * np.pi / 180.
dec = np.array(dec).astype(float) * np.pi / 180.
times = Time(timstr)
ra = np.zeros_like(ha)
for i in range(len(ha)):
ra[i] = eovsa_lst(times[i]) - ha[i]
# Read pointing parameters from SQL database at time of first observation
params_old = np.zeros((9, 15), int)
cursor = dbutil.get_cursor()
timestamp = times[0].lv
# Read stateframe data at time of first observation
D15data = dbutil.get_dbrecs(cursor,
dimension=15,
timestamp=timestamp,
nrecs=1)
for p in range(9):
params_old[p], = D15data['Ante_Cont_PointingCoefficient' + str(p + 1)]
params_old = params_old[:, np.array(antlist) -
1] # Pare down to only antennas in antlist
return {
'filename': filename,
'source': source,
'time': times,
'params_old': params_old,
'ra': ra,
'dec': dec,
'ha': ha,
'antlist': antlist,
'dra': dra,
'ddec': ddec
}
def idb_readXdata(filename, filter=False):
'''This routine reads the data from a single IDBfile. Optional
Keywords: filter boolean--if True, returns only non-zero
frequencies if False (default), returns all frequencies. This
differs from Dale's version in that it includes all
correlations, drops the tp_only option, and the outputs that
are not in the UDB files.
'''
# Open uv file for reading
uv = aipy.miriad.UV(filename)
nf_orig = len(uv['sfreq'])
good_idx = np.arange(nf_orig)
if filter:
good_idx = []
# Read a bunch of records to get number of good frequencies,
# i.e. those with at least some non-zero data. Read 20
# records for baseline 1-2, XX pol
uv.select('antennae',0,2,include=True)
uv.select('polarization',-5,-5,include=True)
for i in range(20):
preamble, data = uv.read()
idx, = data.nonzero()
if len(idx) > len(good_idx):
good_idx = copy.copy(idx)
uv.select('clear',0,0)
uv.rewind()
#endif
#set up outputs
nf = len(good_idx)
print 'NF: ', nf
freq = uv['sfreq'][good_idx]
npol = uv['npol']
polarr = np.array([-5, -6, -7, -8])
nants = uv['nants']
nbl = nants*(nants-1)/2
nblc = nbl+nants
# all-correlations, add a mask for the output vis array
outx0 = np.zeros((nf, nblc, npol, 600),dtype=np.complex64)
omask = np.zeros((nf, nblc, npol, 600),dtype=np.int32)
outx = ma.masked_array(outx0, mask = omask)
i0array = np.zeros((nblc, 600), dtype = np.int32)
j0array = np.zeros((nblc, 600), dtype = np.int32)
outpx = np.zeros((nf*nants, 600), dtype=np.float)
outpy = np.zeros((nf*nants, 600), dtype=np.float)
uvwarray = np.zeros((3, nblc, 600), dtype=np.float)
delayarray = np.zeros((nants, 600), dtype=np.float)
#lists for time arrays
utarray = []
timearray = []
lstarray = []
l = -1
tprev = 0
tsav = 0
# Use antennalist if available
if 'antlist' in uv.vartable:
ants = strip_non_printable(uv['antlist'])
antlist = map(int, ants.split())
else:
antlist = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16]
#endelse
#keep autocorrelations in the array
bl2ord = p.bl_list()
for ij in range(len(antlist)):
bl2ord[ij, ij] = nbl+ij
#endfor
for preamble, data in uv.all():
uvw, t, (i0,j0) = preamble
i = antlist.index(i0+1)
j = antlist.index(j0+1)
if i > j:
# Reverse order of indices
j = antlist.index(i0+1)
i = antlist.index(j0+1)
#endif
# Assumes uv['pol'] is one of -5, -6, -7, -8
k = -5 - uv['pol']
if filter:
if len(data.nonzero()[0]) == nf:
if t != tprev:
# New time
l += 1
if l == 600:
break
#endif
tprev = t
timearray.append(t)
utarray.append(uv['ut'])
try:
lstarray.append(uv['lst'])
except:
pass
#endexcept
xdata0 = uv['xsampler'].reshape(nf_orig,nants,3)
xdata = xdata0[good_idx, :, 0]
outpx[:,l] = xdata.reshape(nf*nants)
ydata0 = uv['ysampler'].reshape(nf_orig,nants,3)
ydata = ydata0[good_idx, :, 0]
outpy[:,l] = ydata.reshape(nf*nants)
delayarray[:,l] = uv['delay']
#endif
outx[:, bl2ord[i,j],k,l] = data[data.nonzero()]
if k == 3:
uvwarray[:, bl2ord[i,j],l] = uvw
i0array[bl2ord[i,j],l] = i0
j0array[bl2ord[i,j],l] = j0
#endif
#endif, for len(data.nonzero()) == nf
else:
if t != tprev:
# New time
l += 1
if l == 600:
break
tprev = t
timearray.append(t)
utarray.append(uv['ut'])
try:
lstarray.append(uv['lst'])
except:
pass
#endexcept
xdata = uv['xsampler'].reshape(nf,nants,3)
outpx[:,l] = xdata[:, :, 0].reshape(nf*nants)
ydata = uv['ysampler'].reshape(nf,nants,3)
outpy[:,l] = ydata[:, :, 0].reshape(nf*nants)
delayarray[:,l] = uv['delay']
#endif
outx[:,bl2ord[i,j],k,l] = data
if k == 3:
uvwarray[:,bl2ord[i,j],l] = uvw
i0array[bl2ord[i,j],l] = i0
j0array[bl2ord[i,j],l] = j0
#endif
#endelse (not filter)
#endfor
# Truncate in case of early end of data
nt = len(timearray)
outpx = outpx[:,:nt]
outpy = outpy[:,:nt]
outx = outx[:,:,:,:nt]
uvwarray = uvwarray[:, :, :nt]
delayarray = delayarray[:, :nt]
if len(lstarray) != 0:
pass
else:
tarray = Time(timearray,format='jd')
for t in tarray:
lstarray.append(el.eovsa_lst(t))
#endfor
#endelse
#i0 and j0 should always be the same
i0array = i0array[:,0]
j0array = j0array[:,0]
#timearray, lstarray and utarray are lists
out = {'x':outx,'uvw':uvwarray,'time':np.array(timearray),'px':outpx,'py':outpy,'i0':i0array,'j0':j0array,'lst':np.array(lstarray),'pol':polarr,'delay':delayarray,'ut':np.array(utarray),'file0':filename}
return out
def readXdata(filename):
'''This routine reads the data from a single UDB file. '''
# Open uv file for reading
uv = aipy.miriad.UV(filename)
# Read all to get a time array
utcount = 0
ut = 0.0
for preamble, data in uv.all():
# Look for time change
if preamble[1] != ut:
ut = preamble[1]
utcount = utcount+1
#endif
#endfor
uv.rewind()
#set up outputs
src = uv['source']
sfreq = uv['sfreq']
nf = len(sfreq)
sdf = uv['sdf']
npol = uv['npol']
polarr = np.array([-5, -6, -7, -8])
nants = uv['nants']
nbl = nants*(nants-1)/2
nblc = nants+nbl
# all-correlations, add a mask for the output vis array
outx0 = np.zeros((nf, nblc, npol, utcount),dtype=np.complex64)
omask = np.zeros((nf, nblc, npol, utcount),dtype=np.int32)
outx = ma.masked_array(outx0, mask = omask)
i0array = np.zeros((nblc, utcount), dtype = np.int32)
j0array = np.zeros((nblc, utcount), dtype = np.int32)
outpx = np.zeros((nants*nf, utcount), dtype=np.float)
outpy = np.zeros((nants*nf, utcount), dtype=np.float)
uvwarray = np.zeros((3, nblc, utcount), dtype=np.float)
delayarray = np.zeros((nants, utcount), dtype=np.float)
utarray = []
timearray = []
lstarray = []
l = -1
tprev = 0
tsav = 0
# Use antennalist if available
if 'antlist' in uv.vartable:
ants = strip_non_printable(uv['antlist'])
antlist = map(int, ants.split())
else:
antlist = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16]
#endelse
#keep autocorrelations in the array
bl2ord = p.bl_list()
for ij in range(len(antlist)):
bl2ord[ij, ij] = nbl+ij
#endfor
xxx = 0
for preamble, data in uv.all():
uvw, t, (i0,j0) = preamble
i = antlist.index(i0+1)
j = antlist.index(j0+1)
if i > j: #this should not happen post-2016
# Reverse order of indices
j = antlist.index(i0+1)
i = antlist.index(j0+1)
# Assumes uv['pol'] is one of -5, -6, -7, -8
# Endif
k = -5 - uv['pol']
if t != tprev:
# New time
l += 1
if l == utcount:
break
#endif
tprev = t
try:
lstarray.append(uv['lst'])
except:
pass
timearray.append(t)
utarray.append(uv['ut'])
xdata = uv['xtsys']
ydata = uv['ytsys']
outpx[:, l] = xdata
outpy[:, l] = ydata
delayarray[:, l] = uv['delay']
#endif
outx[:,bl2ord[i,j],k,l] = data
#apply mask
outx[:,bl2ord[i,j],k,l].mask = data.mask
if k == 3:
uvwarray[:, bl2ord[i,j],l] = uvw
i0array[bl2ord[i,j],l] = i0
j0array[bl2ord[i,j],l] = j0
#endif
#endfor
if len(lstarray) != 0:
pass
else:
tarray = Time(timearray,format='jd')
for t in tarray:
lstarray.append(el.eovsa_lst(t))
#endfor
#endelse
#i0 and j0 should always be the same
i0array = i0array[:,0]
j0array = j0array[:,0]
#timearray, lstarray and utarray are lists
out = {'x':outx,'uvw':uvwarray,'time':np.array(timearray),'px':outpx,'py':outpy,'i0':i0array,'j0':j0array,'lst':np.array(lstarray),'pol':polarr,'delay':delayarray,'ut':np.array(utarray),'file0':filename}
return out
