def get_scan_start_stop(scn):
"""
Given an scan, get the start and stop times (returned as a two-
element tuple).
"""
# UNIX timestamp for the start
tStart = utcjd_to_unix(scn.mjd + MJD_OFFSET)
tStart += scn.mpm / 1000.0
# UNIX timestamp for the stop
tStop = tStart + scn.dur / 1000.0
# Conversion to a timezone-aware datetime instance
tStart = _UTC.localize( datetime.utcfromtimestamp(tStart) )
tStop = _UTC.localize( datetime.utcfromtimestamp(tStop ) )
# Return
return tStart, tStop
def main(args):
# Filenames in an easier format - input
inputIDF = args.filename
if args.date is not None:
y, m, d = args.date.split('/', 2)
args.date = date(int(y,10), int(m,10), int(d,10))
if args.time is not None:
h, m, s = args.time.split(':', 2)
us = int((float(s) - int(float(s)))*1e6)
s = int(float(s))
if us >= 1000000:
us -= 1000000
s += 1
args.time = time(int(h,10), int(m,10), s, us)
# Parse the input file and get the dates of the scans
station = stations.lwa1
project = idf.parse_idf(inputIDF)
# Load the station and objects to find the Sun and Jupiter
observer = station.get_observer()
Sun = ephem.Sun()
Jupiter = ephem.Jupiter()
nObs = len(project.runs[0].scans)
tStart = [None,]*nObs
for i in range(nObs):
tStart[i] = utcjd_to_unix(project.runs[0].scans[i].mjd + MJD_OFFSET)
tStart[i] += project.runs[0].scans[i].mpm / 1000.0
tStart[i] = datetime.utcfromtimestamp(tStart[i])
tStart[i] = _UTC.localize(tStart[i])
# Get the LST at the start
observer.date = (min(tStart)).strftime('%Y/%m/%d %H:%M:%S')
lst = observer.sidereal_time()
# Report on the file
print("Filename: %s" % inputIDF)
print(" Project ID: %s" % project.id)
print(" Run ID: %i" % project.runs[0].id)
print(" Scans appear to start at %s" % (min(tStart)).strftime(formatString))
print(" -> LST at %s for this date/time is %s" % (station.name, lst))
# Filenames in an easier format - output
if not args.query:
if args.outname is not None:
outputIDF = args.outname
else:
outputIDF = None
# Query only mode starts here...
if args.query:
lastDur = project.runs[0].scans[nObs-1].dur
lastDur = timedelta(seconds=int(lastDur/1000), microseconds=(lastDur*1000) % 1000000)
runDur = max(tStart) - min(tStart) + lastDur
print(" ")
print(" Total Run Duration: %s" % runDur)
print(" -> First scan starts at %s" % min(tStart).strftime(formatString))
print(" -> Last scan ends at %s" % (max(tStart) + lastDur).strftime(formatString))
print(" Correlator Setup:")
print(" -> %i channels" % project.runs[0].corr_channels)
print(" -> %.3f s integration time" % project.runs[0].corr_inttime)
print(" -> %s output polarization basis" % project.runs[0].corr_basis)
print(" ")
print(" Number of scans: %i" % nObs)
print(" Scan Detail:")
for i in range(nObs):
currDur = project.runs[0].scans[i].dur
currDur = timedelta(seconds=int(currDur/1000), microseconds=(currDur*1000) % 1000000)
print(" Scan #%i" % (i+1,))
## Basic setup
print(" Target: %s" % project.runs[0].scans[i].target)
print(" Intent: %s" % project.runs[0].scans[i].intent)
print(" Start:")
print(" MJD: %i" % project.runs[0].scans[i].mjd)
print(" MPM: %i" % project.runs[0].scans[i].mpm)
print(" -> %s" % get_scan_start_stop(project.runs[0].scans[i])[0].strftime(formatString))
print(" Duration: %s" % currDur)
## DP setup
print(" Tuning 1: %.3f MHz" % (project.runs[0].scans[i].frequency1/1e6,))
print(" Tuning 2: %.3f MHz" % (project.runs[0].scans[i].frequency2/1e6,))
print(" Filter code: %i" % project.runs[0].scans[i].filter)
## Comments/notes
print(" Observer Comments: %s" % project.runs[0].scans[i].comments)
# Valid?
print(" ")
try:
if project.validate():
print(" Valid? Yes")
else:
print(" Valid? No")
except:
print(" Valid? No")
# And then exits
sys.exit()
#
# Query the time and compute the time shifts
#
if (not args.no_update):
# Get the new start date/time in UTC and report on the difference
if args.lst:
if args.date is None:
print(" ")
print("Enter the new UTC start date:")
tNewStart = input('YYYY/MM/DD-> ')
try:
fields = tNewStart.split('/', 2)
fields = [int(f) for f in fields]
tNewStart = date(fields[0], fields[1], fields[2])
tNewStart = datetime.combine(tNewStart, min(tStart).time())
except Exception as e:
print("Error: %s" % str(e))
sys.exit(1)
else:
tNewStart = datetime.combine(args.date, min(tStart).time())
tNewStart = _UTC.localize(tNewStart)
# Figure out a new start time on the correct day
diff = ((tNewStart - min(tStart)).days) * siderealRegression
## Try to make sure that the timedelta object is less than 1 day
while diff.days > 0:
diff -= siderealDay
while diff.days < -1:
diff += siderealDay
## Come up with the new start time
siderealShift = tNewStart - diff
## Another check to make sure we are are the right day
if siderealShift.date() < tNewStart.date():
siderealShift += siderealDay
if siderealShift.date() > tNewStart.date():
siderealShift -= siderealDay
## And yet another one to deal with the corner case that scan starts at ~UT 00:00
if min(tStart) == siderealShift:
newSiderealShift1 = siderealShift + siderealDay
newSiderealShift2 = siderealShift - siderealDay
if newSiderealShift1.date() == tNewStart.date():
siderealShift = newSiderealShift1
elif newSiderealShift2.date() == tNewStart.date():
siderealShift = newSiderealShift2
tNewStart = siderealShift
else:
if args.date is None or args.time is None:
print(" ")
print("Enter the new UTC start date/time:")
tNewStart = input('YYYY/MM/DD HH:MM:SS.SSS -> ')
try:
tNewStart = datetime.strptime(tNewStart, '%Y/%m/%d %H:%M:%S.%f')
except ValueError:
try:
tNewStart = datetime.strptime(tNewStart, '%Y/%m/%d %H:%M:%S')
except Exception as e:
print("Error: %s" % str(e))
sys.exit(1)
else:
tNewStart = datetime.combine(args.date, args.time)
tNewStart = _UTC.localize(tNewStart)
# Get the new shift needed to translate the old times to the new times
tShift = tNewStart - min(tStart)
# Get the LST at the new start
observer.date = (tNewStart).strftime('%Y/%m/%d %H:%M:%S')
lst = observer.sidereal_time()
print(" ")
print("Shifting scans to start at %s" % tNewStart.strftime(formatString))
print("-> Difference of %i days, %.3f seconds" % (tShift.days, (tShift.seconds + tShift.microseconds/1000000.0),))
print("-> LST at %s for this date/time is %s" % (station.name, lst))
if tShift.days == 0 and tShift.seconds == 0 and tShift.microseconds == 0:
print(" ")
print("The current shift is zero. Do you want to continue anyways?")
yesNo = input("-> [y/N] ")
if yesNo not in ('y', 'Y'):
sys.exit()
else:
tShift = timedelta(seconds=0)
# Shift the start times and recompute the MJD and MPM values
for i in range(nObs):
tStart[i] += tShift
#
# Query and set the new run ID
#
print(" ")
if args.rid is None:
print("Enter the new run ID or return to keep current:")
sid = input('-> ')
if len(sid) > 0:
sid = int(sid)
else:
sid = project.runs[0].id
else:
sid = args.rid
print("Shifting run ID from %i to %i" % (project.runs[0].id, sid))
project.runs[0].id = sid
#
# Go! (apply the changes to the scans)
#
print(" ")
newPOOC = []
for i in range(nObs):
print("Working on Scan #%i" % (i+1,))
newPOOC.append("")
#
# Start MJD,MPM Shifting
#
if (not args.no_update) and tShift != timedelta(seconds=0):
if len(newPOOC[-1]) != 0:
newPOOC[-1] += ';;'
newPOOC[-1] += 'Original MJD:%i,MPM:%i' % (project.runs[0].scans[i].mjd, project.runs[0].scans[i].mpm)
start = tStart[i].strftime("%Z %Y %m %d %H:%M:%S.%f")
start = start[:-3]
utc = Time(tStart[i], format=Time.FORMAT_PY_DATE)
mjd = int(utc.utc_mjd)
utcMidnight = datetime(tStart[i].year, tStart[i].month, tStart[i].day, 0, 0, 0, tzinfo=_UTC)
diff = tStart[i] - utcMidnight
mpm = int(round((diff.seconds + diff.microseconds/1000000.0)*1000.0))
print(" Time shifting")
print(" MJD: %8i -> %8i" % (project.runs[0].scans[i].mjd, mjd))
print(" MPM: %8i -> %8i" % (project.runs[0].scans[i].mpm, mpm))
project.runs[0].scans[i].mjd = mjd
project.runs[0].scans[i].mpm = mpm
project.runs[0].scans[i].start = start
#
# Project office comments
#
# Update the project office comments with this change
newPOSC = "Shifted IDF with shiftIDF.py (v%s);;Time Shift? %s" % (__version__, 'Yes' if (not args.no_update) else 'No')
if project.project_office.runs[0] is None:
project.project_office.runs[0] = newPOSC
else:
project.project_office.runs[0] += ';;%s' % newPOSC
for i in range(nObs):
try:
project.project_office.scans[0][i] += ';;%s' % newPOOC[i]
except Exception as e:
print(e)
project.project_office.scans[0][i] = '%s' % newPOOC[i]
#
# Save
#
if outputIDF is None:
pID = project.id
rID = project.runs[0].id
foStart = min(tStart)
outputIDF = '%s_%s_%s_%04i.idf' % (pID, foStart.strftime('%y%m%d'), foStart.strftime('%H%M'), rID)
print(" ")
print("Saving to: %s" % outputIDF)
fh = open(outputIDF, 'w')
if not project.validate():
# Make sure we are about to be valid
project.validate(verbose=True)
raise RuntimeError("Cannot validate IDF file")
fh.write( project.render() )
fh.close()
def main(args):
# Parse the command line
## Baseline list
if args.baseline is not None:
## Fill the baseline list with the conjugates, if needed
newBaselines = []
for pair in args.baseline:
newBaselines.append((pair[1], pair[0]))
args.baseline.extend(newBaselines)
## Polarization
plot_pols = []
if args.xx:
plot_pols.append('XX')
if args.xy:
plot_pols.append('XY')
if args.yx:
plot_pols.append('YX')
if args.yy:
plot_pols.append('YY')
filename = args.filename
figs = {}
first = True
for filename in args.filename:
print("Working on '%s'" % os.path.basename(filename))
# Open the FITS IDI file and access the UV_DATA extension
hdulist = astrofits.open(filename, mode='readonly')
andata = hdulist['ANTENNA']
fqdata = hdulist['FREQUENCY']
fgdata = None
for hdu in hdulist[1:]:
if hdu.header['EXTNAME'] == 'FLAG':
fgdata = hdu
uvdata = hdulist['UV_DATA']
# Pull out various bits of information we need to flag the file
## Antenna look-up table
antLookup = {}
for an, ai in zip(andata.data['ANNAME'], andata.data['ANTENNA_NO']):
antLookup[an] = ai
## Frequency and polarization setup
nBand, nFreq, nStk = uvdata.header['NO_BAND'], uvdata.header[
'NO_CHAN'], uvdata.header['NO_STKD']
stk0 = uvdata.header['STK_1']
## Baseline list
bls = uvdata.data['BASELINE']
## Time of each integration
obsdates = uvdata.data['DATE']
obstimes = uvdata.data['TIME']
inttimes = uvdata.data['INTTIM']
## Source list
srcs = uvdata.data['SOURCE']
## Band information
fqoffsets = fqdata.data['BANDFREQ'].ravel()
## Frequency channels
freq = (numpy.arange(nFreq) -
(uvdata.header['CRPIX3'] - 1)) * uvdata.header['CDELT3']
freq += uvdata.header['CRVAL3']
## UVW coordinates
try:
u, v, w = uvdata.data['UU'], uvdata.data['VV'], uvdata.data['WW']
except KeyError:
u, v, w = uvdata.data['UU---SIN'], uvdata.data[
'VV---SIN'], uvdata.data['WW---SIN']
uvw = numpy.array([u, v, w]).T
## The actual visibility data
flux = uvdata.data['FLUX'].astype(numpy.float32)
# Convert the visibilities to something that we can easily work with
nComp = flux.shape[1] // nBand // nFreq // nStk
if nComp == 2:
## Case 1) - Just real and imaginary data
flux = flux.view(numpy.complex64)
else:
## Case 2) - Real, imaginary data + weights (drop the weights)
flux = flux[:, 0::nComp] + 1j * flux[:, 1::nComp]
flux.shape = (flux.shape[0], nBand, nFreq, nStk)
# Find unique baselines, times, and sources to work with
ubls = numpy.unique(bls)
utimes = numpy.unique(obstimes)
usrc = numpy.unique(srcs)
# Convert times to real times
times = utcjd_to_unix(obsdates + obstimes)
times = numpy.unique(times)
# Build a mask
mask = numpy.zeros(flux.shape, dtype=numpy.bool)
if fgdata is not None and not args.drop:
reltimes = obsdates - obsdates[0] + obstimes
maxtimes = reltimes + inttimes / 2.0 / 86400.0
mintimes = reltimes - inttimes / 2.0 / 86400.0
bls_ant1 = bls // 256
bls_ant2 = bls % 256
for row in fgdata.data:
ant1, ant2 = row['ANTS']
## Only deal with flags that we need for the plots
process_flag = False
if args.include_auto or ant1 != ant2 or ant1 == 0 or ant2 == 0:
if ant1 == 0 and ant2 == 0:
process_flag = True
elif args.baseline is not None:
if ant2 == 0 and ant1 in [
a0 for a0, a1 in args.baseline
]:
process_flag = True
elif (ant1, ant2) in args.baseline:
process_flag = True
elif args.ref_ant is not None:
if ant1 == args.ref_ant or ant2 == args.ref_ant:
process_flag = True
else:
process_flag = True
if not process_flag:
continue
tStart, tStop = row['TIMERANG']
band = row['BANDS']
try:
len(band)
except TypeError:
band = [
band,
]
cStart, cStop = row['CHANS']
if cStop == 0:
cStop = -1
pol = row['PFLAGS'].astype(numpy.bool)
if ant1 == 0 and ant2 == 0:
btmask = numpy.where(
((maxtimes >= tStart) & (mintimes <= tStop)))[0]
elif ant1 == 0 or ant2 == 0:
ant1 = max([ant1, ant2])
btmask = numpy.where( ( (bls_ant1 == ant1) | (bls_ant2 == ant1) ) \
& ( (maxtimes >= tStart) & (mintimes <= tStop) ) )[0]
else:
btmask = numpy.where( ( (bls_ant1 == ant1) & (bls_ant2 == ant2) ) \
& ( (maxtimes >= tStart) & (mintimes <= tStop) ) )[0]
for b, v in enumerate(band):
if not v:
continue
mask[btmask, b, cStart - 1:cStop, :] |= pol
plot_bls = []
cross = []
for i in xrange(len(ubls)):
bl = ubls[i]
ant1, ant2 = (bl >> 8) & 0xFF, bl & 0xFF
if args.include_auto or ant1 != ant2:
if args.baseline is not None:
if (ant1, ant2) in args.baseline:
plot_bls.append(bl)
cross.append(i)
elif args.ref_ant is not None:
if ant1 == args.ref_ant or ant2 == args.ref_ant:
plot_bls.append(bl)
cross.append(i)
else:
plot_bls.append(bl)
cross.append(i)
nBL = len(cross)
# Decimation, if needed
if args.decimate > 1:
if nFreq % args.decimate != 0:
raise RuntimeError(
"Invalid freqeunce decimation factor: %i %% %i = %i" %
(nFreq, args.decimate, nFreq % args.decimate))
nFreq //= args.decimate
freq.shape = (freq.size // args.decimate, args.decimate)
freq = freq.mean(axis=1)
flux.shape = (flux.shape[0], flux.shape[1],
flux.shape[2] // args.decimate, args.decimate,
flux.shape[3])
flux = flux.mean(axis=3)
mask.shape = (mask.shape[0], mask.shape[1],
mask.shape[2] // args.decimate, args.decimate,
mask.shape[3])
mask = mask.mean(axis=3)
good = numpy.arange(freq.size // 8,
freq.size * 7 // 8) # Inner 75% of the band
if first:
ref_time = obsdates[0] + obstimes[0]
# NOTE: Assumes that the Stokes parameters increment by -1
namMapper = {}
for i in xrange(nStk):
stk = stk0 - i
namMapper[i] = NUMERIC_STOKES[stk]
polMapper = {'XX': 0, 'YY': 1, 'XY': 2, 'YX': 3}
for b in xrange(len(plot_bls)):
bl = plot_bls[b]
valid = numpy.where(bls == bl)[0]
i, j = (bl >> 8) & 0xFF, bl & 0xFF
dTimes = obsdates[valid] + obstimes[valid]
dTimes -= ref_time
dTimes *= 86400.0
for p in plot_pols:
blName = (i, j)
blName = '%s-%s - %s' % (
'EA%02i' % blName[0] if blName[0] < 51 else 'LWA%i' %
(blName[0] - 50),
'EA%02i' % blName[1] if blName[1] < 51 else 'LWA%i' %
(blName[1] - 50), namMapper[polMapper[p]])
if first or blName not in figs:
fig = plt.figure()
fig.suptitle('%s' % blName)
fig.subplots_adjust(hspace=0.001)
axA = fig.add_subplot(1, 2, 1)
axP = fig.add_subplot(1, 2, 2)
figs[blName] = (fig, axA, axP)
fig, axA, axP = figs[blName]
for band, offset in enumerate(fqoffsets):
frq = freq + offset
vis = numpy.ma.array(flux[valid, band, :, polMapper[p]],
mask=mask[valid, band, :,
polMapper[p]])
amp = numpy.ma.abs(vis)
vmin, vmax = percentile(amp, 1), percentile(amp, 99)
axA.imshow(amp,
extent=(frq[0] / 1e6, frq[-1] / 1e6, dTimes[0],
dTimes[-1]),
origin='lower',
interpolation='nearest',
vmin=vmin,
vmax=vmax)
axP.imshow(numpy.ma.angle(vis),
extent=(frq[0] / 1e6, frq[-1] / 1e6, dTimes[0],
dTimes[-1]),
origin='lower',
vmin=-numpy.pi,
vmax=numpy.pi,
interpolation='nearest')
first = False
for blName in figs:
fig, axA, axP = figs[blName]
fig.suptitle("%s UTC\n%s" % (datetime.utcfromtimestamp(
times[0]).strftime("%Y/%m/%d %H:%M"), blName))
axA.axis('auto')
axA.set_title('Amp.')
axA.set_xlabel('Frequency [MHz]')
axA.set_ylabel('Amp. - Elapsed Time [s]')
axP.axis('auto')
axP.set_title('Phase')
axP.set_xlabel('Frequency [MHz]')
if args.save_images:
fig.savefig('fringes-%s.png' % (blName.replace(' ', ''), ))
if not args.save_images:
plt.show()
def main(args):
# Parse the command line
filenames = args.filename
for filename in filenames:
t0 = time.time()
print("Working on '%s'" % os.path.basename(filename))
# Open the FITS IDI file and access the UV_DATA extension
hdulist = astrofits.open(filename, mode='readonly')
andata = hdulist['ANTENNA']
fqdata = hdulist['FREQUENCY']
fgdata = None
for hdu in hdulist[1:]:
if hdu.header['EXTNAME'] == 'FLAG':
fgdata = hdu
uvdata = hdulist['UV_DATA']
# Verify we can flag this data
if uvdata.header['STK_1'] > 0:
raise RuntimeError("Cannot flag data with STK_1 = %i" %
uvdata.header['STK_1'])
if uvdata.header['NO_STKD'] < 4:
raise RuntimeError("Cannot flag data with NO_STKD = %i" %
uvdata.header['NO_STKD'])
# NOTE: Assumes that the Stokes parameters increment by -1
polMapper = {}
for i in xrange(uvdata.header['NO_STKD']):
stk = uvdata.header['STK_1'] - i
polMapper[i] = NUMERIC_STOKES[stk]
# Pull out various bits of information we need to flag the file
## Antenna look-up table
antLookup = {}
for an, ai in zip(andata.data['ANNAME'], andata.data['ANTENNA_NO']):
antLookup[an] = ai
## Frequency and polarization setup
nBand, nFreq, nStk = uvdata.header['NO_BAND'], uvdata.header[
'NO_CHAN'], uvdata.header['NO_STKD']
## Baseline list
bls = uvdata.data['BASELINE']
## Time of each integration
obsdates = uvdata.data['DATE']
obstimes = uvdata.data['TIME']
inttimes = uvdata.data['INTTIM']
## Source list
srcs = uvdata.data['SOURCE']
## Band information
fqoffsets = fqdata.data['BANDFREQ'].ravel()
## Frequency channels
freq = (numpy.arange(nFreq) -
(uvdata.header['CRPIX3'] - 1)) * uvdata.header['CDELT3']
freq += uvdata.header['CRVAL3']
## UVW coordinates
try:
u, v, w = uvdata.data['UU'], uvdata.data['VV'], uvdata.data['WW']
except KeyError:
u, v, w = uvdata.data['UU---SIN'], uvdata.data[
'VV---SIN'], uvdata.data['WW---SIN']
uvw = numpy.array([u, v, w]).T
## The actual visibility data
flux = uvdata.data['FLUX'].astype(numpy.float32)
# Convert the visibilities to something that we can easily work with
nComp = flux.shape[1] // nBand // nFreq // nStk
if nComp == 2:
## Case 1) - Just real and imaginary data
flux = flux.view(numpy.complex64)
else:
## Case 2) - Real, imaginary data + weights (drop the weights)
flux = flux[:, 0::nComp] + 1j * flux[:, 1::nComp]
flux.shape = (flux.shape[0], nBand, nFreq, nStk)
# Find unique baselines, times, and sources to work with
ubls = numpy.unique(bls)
utimes = numpy.unique(obstimes)
usrc = numpy.unique(srcs)
# Find unique scans to work on, making sure that there are no large gaps
blocks = []
for src in usrc:
valid = numpy.where(src == srcs)[0]
blocks.append([valid[0], valid[0]])
for v in valid[1:]:
if v == blocks[-1][1] + 1 \
and (obsdates[v] - obsdates[blocks[-1][1]] + obstimes[v] - obstimes[blocks[-1][1]])*86400 < 10*inttimes[v]:
blocks[-1][1] = v
else:
blocks.append([v, v])
blocks.sort()
# Build up the mask
mask = numpy.zeros(flux.shape, dtype=numpy.bool)
for i, block in enumerate(blocks):
tS = time.time()
print(' Working on scan %i of %i' % (i + 1, len(blocks)))
match = range(block[0], block[1] + 1)
bbls = numpy.unique(bls[match])
times = obstimes[match] * 86400.0
scanStart = datetime.utcfromtimestamp(
utcjd_to_unix(obsdates[match[0]] + obstimes[match[0]]))
scanStop = datetime.utcfromtimestamp(
utcjd_to_unix(obsdates[match[-1]] + obstimes[match[-1]]))
print(' Scan spans %s to %s UTC' %
(scanStart.strftime('%Y/%m/%d %H:%M:%S'),
scanStop.strftime('%Y/%m/%d %H:%M:%S')))
for b, offset in enumerate(fqoffsets):
print(' IF #%i' % (b + 1, ))
crd = uvw[match, :]
visXX = flux[match, b, :, 0]
visYY = flux[match, b, :, 1]
nBL = len(bbls)
if b == 0:
times = times[0::nBL]
crd.shape = (crd.shape[0] // nBL, nBL, 1, 3)
visXX.shape = (visXX.shape[0] // nBL, nBL, visXX.shape[1])
visYY.shape = (visYY.shape[0] // nBL, nBL, visYY.shape[1])
print(
' Scan/IF contains %i times, %i baselines, %i channels'
% visXX.shape)
if visXX.shape[0] < 5:
print(' Too few integrations, skipping')
continue
antennas = []
for j in xrange(nBL):
ant1, ant2 = (bbls[j] >> 8) & 0xFF, bbls[j] & 0xFF
if ant1 not in antennas:
antennas.append(ant1)
if ant2 not in antennas:
antennas.append(ant2)
print(' Flagging baselines')
maskXX = mask_bandpass(antennas,
times,
freq + offset,
visXX,
freq_range=args.freq_range)
maskYY = mask_bandpass(antennas,
times,
freq + offset,
visYY,
freq_range=args.freq_range)
visXX = numpy.ma.array(visXX, mask=maskXX)
visYY = numpy.ma.array(visYY, mask=maskYY)
if args.scf_passes > 0:
print(' Flagging spurious correlations')
for p in xrange(args.scf_passes):
print(' Pass #%i' % (p + 1, ))
visXX.mask = mask_spurious(antennas, times, crd,
freq + offset, visXX)
visYY.mask = mask_spurious(antennas, times, crd,
freq + offset, visYY)
print(' Cleaning masks')
visXX.mask = cleanup_mask(visXX.mask)
visYY.mask = cleanup_mask(visYY.mask)
print(' Saving polarization masks')
submask = visXX.mask
submask.shape = (len(match), flux.shape[2])
mask[match, b, :, 0] = submask
submask = visYY.mask
submask.shape = (len(match), flux.shape[2])
mask[match, b, :, 1] = submask
print(' Statistics for this scan/IF')
print(' -> %s - %.1f%% flagged' % (
polMapper[0],
100.0 * mask[match, b, :, 0].sum() /
mask[match, b, :, 0].size,
))
print(' -> %s - %.1f%% flagged' % (
polMapper[1],
100.0 * mask[match, b, :, 1].sum() /
mask[match, b, :, 0].size,
))
print(' -> Elapsed - %.3f s' % (time.time() - tS, ))
# Convert the masks into a format suitable for writing to a FLAG table
print(" Building FLAG table")
ants, times, bands, chans, pols, reas, sevs = [], [], [], [], [], [], []
if not args.drop:
## Old flags
if fgdata is not None:
for row in fgdata.data:
ants.append(row['ANTS'])
times.append(row['TIMERANG'])
try:
len(row['BANDS'])
bands.append(row['BANDS'])
except TypeError:
bands.append([
row['BANDS'],
])
chans.append(row['CHANS'])
pols.append(row['PFLAGS'])
reas.append(row['REASON'])
sevs.append(row['SEVERITY'])
## New Flags
nBL = len(ubls)
for i in xrange(nBL):
blset = numpy.where(bls == ubls[i])[0]
ant1, ant2 = (ubls[i] >> 8) & 0xFF, ubls[i] & 0xFF
if i % 100 == 0 or i + 1 == nBL:
print(" Baseline %i of %i" % (i + 1, nBL))
if len(blset) == 0:
continue
for b, offset in enumerate(fqoffsets):
maskXX = mask[blset, b, :, 0]
maskYY = mask[blset, b, :, 1]
flagsXX, _ = create_flag_groups(obstimes[blset], freq + offset,
maskXX)
flagsYY, _ = create_flag_groups(obstimes[blset], freq + offset,
maskYY)
for flag in flagsXX:
ants.append((ant1, ant2))
times.append(
(obsdates[blset[flag[0]]] + obstimes[blset[flag[0]]] -
obsdates[0], obsdates[blset[flag[1]]] +
obstimes[blset[flag[1]]] - obsdates[0]))
bands.append([1 if j == b else 0 for j in xrange(nBand)])
chans.append((flag[2] + 1, flag[3] + 1))
pols.append((1, 0, 1, 1))
reas.append('FLAGIDI.PY')
sevs.append(-1)
for flag in flagsYY:
ants.append((ant1, ant2))
times.append(
(obsdates[blset[flag[0]]] + obstimes[blset[flag[0]]] -
obsdates[0], obsdates[blset[flag[1]]] +
obstimes[blset[flag[1]]] - obsdates[0]))
bands.append([1 if j == b else 0 for j in xrange(nBand)])
chans.append((flag[2] + 1, flag[3] + 1))
pols.append((0, 1, 1, 1))
reas.append('FLAGIDI.PY')
sevs.append(-1)
## Figure out our revision
try:
repo = git.Repo(os.path.dirname(os.path.abspath(__file__)))
try:
branch = repo.active_branch.name
hexsha = repo.active_branch.commit.hexsha
except TypeError:
branch = '<detached>'
hexsha = repo.head.commit.hexsha
shortsha = hexsha[-7:]
dirty = ' (dirty)' if repo.is_dirty() else ''
except git.exc.GitError:
branch = 'unknown'
hexsha = 'unknown'
shortsha = 'unknown'
dirty = ''
## Build the FLAG table
print(' FITS HDU')
### Columns
nFlags = len(ants)
c1 = astrofits.Column(name='SOURCE_ID',
format='1J',
array=numpy.zeros((nFlags, ), dtype=numpy.int32))
c2 = astrofits.Column(name='ARRAY',
format='1J',
array=numpy.zeros((nFlags, ), dtype=numpy.int32))
c3 = astrofits.Column(name='ANTS',
format='2J',
array=numpy.array(ants, dtype=numpy.int32))
c4 = astrofits.Column(name='FREQID',
format='1J',
array=numpy.zeros((nFlags, ), dtype=numpy.int32))
c5 = astrofits.Column(name='TIMERANG',
format='2E',
array=numpy.array(times, dtype=numpy.float32))
c6 = astrofits.Column(name='BANDS',
format='%iJ' % nBand,
array=numpy.array(bands,
dtype=numpy.int32).squeeze())
c7 = astrofits.Column(name='CHANS',
format='2J',
array=numpy.array(chans, dtype=numpy.int32))
c8 = astrofits.Column(name='PFLAGS',
format='4J',
array=numpy.array(pols, dtype=numpy.int32))
c9 = astrofits.Column(name='REASON',
format='A40',
array=numpy.array(reas))
c10 = astrofits.Column(name='SEVERITY',
format='1J',
array=numpy.array(sevs, dtype=numpy.int32))
colDefs = astrofits.ColDefs([c1, c2, c3, c4, c5, c6, c7, c8, c9, c10])
### The table itself
flags = astrofits.BinTableHDU.from_columns(colDefs)
### The header
flags.header['EXTNAME'] = ('FLAG', 'FITS-IDI table name')
flags.header['EXTVER'] = (1 if fgdata is None else
fgdata.header['EXTVER'] + 1,
'table instance number')
flags.header['TABREV'] = (2, 'table format revision number')
for key in ('NO_STKD', 'STK_1', 'NO_BAND', 'NO_CHAN', 'REF_FREQ',
'CHAN_BW', 'REF_PIXL', 'OBSCODE', 'ARRNAM', 'RDATE'):
try:
flags.header[key] = (uvdata.header[key],
uvdata.header.comments[key])
except KeyError:
pass
flags.header['HISTORY'] = 'Flagged with %s, revision %s.%s%s' % (
os.path.basename(__file__), branch, shortsha, dirty)
# Clean up the old FLAG tables, if any, and then insert the new table where it needs to be
if args.drop:
## Reset the EXTVER on the new FLAG table
flags.header['EXTVER'] = (1, 'table instance number')
## Find old tables
toRemove = []
for hdu in hdulist:
try:
if hdu.header['EXTNAME'] == 'FLAG':
toRemove.append(hdu)
except KeyError:
pass
## Remove old tables
for hdu in toRemove:
ver = hdu.header['EXTVER']
del hdulist[hdulist.index(hdu)]
print(" WARNING: removing old FLAG table - version %i" % ver)
## Insert the new table right before UV_DATA
hdulist.insert(-1, flags)
# Save
print(" Saving to disk")
## What to call it
outname = os.path.basename(filename)
outname, outext = os.path.splitext(outname)
outname = '%s_flagged%s' % (outname, outext)
## Does it already exist or not
if os.path.exists(outname):
if not args.force:
yn = raw_input("WARNING: '%s' exists, overwrite? [Y/n] " %
outname)
else:
yn = 'y'
if yn not in ('n', 'N'):
os.unlink(outname)
else:
raise RuntimeError("Output file '%s' already exists" % outname)
## Open and create a new primary HDU
hdulist2 = astrofits.open(outname, mode='append')
primary = astrofits.PrimaryHDU()
processed = []
for key in hdulist[0].header:
if key in ('COMMENT', 'HISTORY'):
if key not in processed:
parts = str(hdulist[0].header[key]).split('\n')
for part in parts:
primary.header[key] = part
processed.append(key)
else:
primary.header[key] = (hdulist[0].header[key],
hdulist[0].header.comments[key])
hdulist2.append(primary)
hdulist2.flush()
## Copy the extensions over to the new file
for hdu in hdulist[1:]:
hdulist2.append(hdu)
hdulist2.flush()
hdulist2.close()
hdulist.close()
print(" -> Flagged FITS IDI file is '%s'" % outname)
print(" Finished in %.3f s" % (time.time() - t0, ))
def main(args):
# Filenames in an easier format - input
inputSDF = args.filename
if args.date is not None:
y, m, d = args.date.split('/', 2)
args.date = date(int(y,10), int(m,10), int(d,10))
if args.time is not None:
h, m, s = args.time.split(':', 2)
us = int((float(s) - int(float(s)))*1e6)
s = int(float(s))
if us >= 1000000:
us -= 1000000
s += 1
args.time = time(int(h,10), int(m,10), s, us)
# Parse the input file and get the dates of the observations
try:
## LWA-1
station = stations.lwa1
project = sdf.parse_sdf(inputSDF)
adp = False
except Exception as e:
## LWA-SV
### Try again
station = stations.lwasv
project = sdfADP.parse_sdf(inputSDF)
adp = True
# Load the station and objects to find the Sun and Jupiter
observer = station.get_observer()
Sun = ephem.Sun()
Jupiter = ephem.Jupiter()
nObs = len(project.sessions[0].observations)
tStart = [None,]*nObs
for i in range(nObs):
tStart[i] = utcjd_to_unix(project.sessions[0].observations[i].mjd + MJD_OFFSET)
tStart[i] += project.sessions[0].observations[i].mpm / 1000.0
tStart[i] = datetime.utcfromtimestamp(tStart[i])
tStart[i] = _UTC.localize(tStart[i])
# Get the LST at the start
observer.date = (min(tStart)).strftime('%Y/%m/%d %H:%M:%S')
lst = observer.sidereal_time()
# Report on the file
print("Filename: %s" % inputSDF)
print(" Project ID: %s" % project.id)
print(" Session ID: %i" % project.sessions[0].id)
print(" Observations appear to start at %s" % (min(tStart)).strftime(formatString))
print(" -> LST at %s for this date/time is %s" % (station.name, lst))
# Filenames in an easier format - output
if not args.query:
if args.outname is not None:
outputSDF = args.outname
else:
outputSDF = None
# Query only mode starts here...
if args.query:
lastDur = project.sessions[0].observations[nObs-1].dur
lastDur = timedelta(seconds=int(lastDur/1000), microseconds=(lastDur*1000) % 1000000)
sessionDur = max(tStart) - min(tStart) + lastDur
print(" ")
print(" Total Session Duration: %s" % sessionDur)
print(" -> First observation starts at %s" % min(tStart).strftime(formatString))
print(" -> Last observation ends at %s" % (max(tStart) + lastDur).strftime(formatString))
if project.sessions[0].observations[0].mode not in ('TBW', 'TBN'):
drspec = 'No'
if project.sessions[0].spcSetup[0] != 0 and project.sessions[0].spcSetup[1] != 0:
drspec = 'Yes'
drxBeam = project.sessions[0].drx_beam
if drxBeam < 1:
drxBeam = "MCS decides"
else:
drxBeam = "%i" % drxBeam
print(" DRX Beam: %s" % drxBeam)
print(" DR Spectrometer used? %s" % drspec)
if drspec == 'Yes':
mt = project.sessions[0].spcMetatag
if mt is None:
mt = '{Stokes=XXYY}'
junk, mt = mt.split('=', 1)
mt = mt.replace('}', '')
if mt in ('XX', 'YY', 'XY', 'YX', 'XXYY', 'XXXYYXYY'):
products = len(mt)//2
mt = [mt[2*i:2*i+2] for i in range(products)]
else:
products = len(mt)
mt = [mt[1*i:1*i+1] for i in range(products)]
print(" -> %i channels, %i windows/integration" % tuple(project.sessions[0].spcSetup))
print(" -> %i data products (%s)" % (products, ','.join(mt)))
else:
print(" Transient Buffer: %s\n" % ('Wide band' if project.sessions[0].observations[0].mode == 'TBW' else 'Narrow band',))
print(" ")
print(" Number of observations: %i" % nObs)
print(" Observation Detail:")
for i in range(nObs):
currDur = project.sessions[0].observations[i].dur
currDur = timedelta(seconds=int(currDur/1000), microseconds=(currDur*1000) % 1000000)
print(" Observation #%i" % (i+1,))
## Basic setup
print(" Target: %s" % project.sessions[0].observations[i].target)
print(" Mode: %s" % project.sessions[0].observations[i].mode)
print(" Start:")
print(" MJD: %i" % project.sessions[0].observations[i].mjd)
print(" MPM: %i" % project.sessions[0].observations[i].mpm)
print(" -> %s" % getObsStartStop(project.sessions[0].observations[i])[0].strftime(formatString))
print(" Duration: %s" % currDur)
## DP setup
if project.sessions[0].observations[i].mode not in ('TBW',):
print(" Tuning 1: %.3f MHz" % (project.sessions[0].observations[i].frequency1/1e6,))
if project.sessions[0].observations[i].mode not in ('TBW', 'TBN'):
print(" Tuning 2: %.3f MHz" % (project.sessions[0].observations[i].frequency2/1e6,))
if project.sessions[0].observations[i].mode not in ('TBW',):
print(" Filter code: %i" % project.sessions[0].observations[i].filter)
## Comments/notes
print(" Observer Comments: %s" % project.sessions[0].observations[i].comments)
# Valid?
print(" ")
try:
if project.validate():
print(" Valid? Yes")
else:
print(" Valid? No")
except:
print(" Valid? No")
# And then exits
sys.exit()
#
# Query the time and compute the time shifts
#
if (not args.no_update):
# Get the new start date/time in UTC and report on the difference
if args.lst:
if args.date is None:
print(" ")
print("Enter the new UTC start date:")
tNewStart = input('YYYY/MM/DD-> ')
try:
fields = tNewStart.split('/', 2)
fields = [int(f) for f in fields]
tNewStart = date(fields[0], fields[1], fields[2])
tNewStart = datetime.combine(tNewStart, min(tStart).time())
except Exception as e:
print("Error: %s" % str(e))
sys.exit(1)
else:
tNewStart = datetime.combine(args.date, min(tStart).time())
tNewStart = _UTC.localize(tNewStart)
# Figure out a new start time on the correct day
diff = ((tNewStart - min(tStart)).days) * siderealRegression
## Try to make sure that the timedelta object is less than 1 day
while diff.days > 0:
diff -= siderealDay
while diff.days < -1:
diff += siderealDay
## Come up with the new start time
siderealShift = tNewStart - diff
## Another check to make sure we are are the right day
if siderealShift.date() < tNewStart.date():
siderealShift += siderealDay
if siderealShift.date() > tNewStart.date():
siderealShift -= siderealDay
## And yet another one to deal with the corner case that observation starts at ~UT 00:00
if min(tStart) == siderealShift:
newSiderealShift1 = siderealShift + siderealDay
newSiderealShift2 = siderealShift - siderealDay
if newSiderealShift1.date() == tNewStart.date():
siderealShift = newSiderealShift1
elif newSiderealShift2.date() == tNewStart.date():
siderealShift = newSiderealShift2
tNewStart = siderealShift
else:
if args.date is None or args.time is None:
print(" ")
print("Enter the new UTC start date/time:")
tNewStart = input('YYYY/MM/DD HH:MM:SS.SSS -> ')
try:
tNewStart = datetime.strptime(tNewStart, '%Y/%m/%d %H:%M:%S.%f')
except ValueError:
try:
tNewStart = datetime.strptime(tNewStart, '%Y/%m/%d %H:%M:%S')
except Exception as e:
print("Error: %s" % str(e))
sys.exit(1)
else:
tNewStart = datetime.combine(args.date, args.time)
tNewStart = _UTC.localize(tNewStart)
# Get the new shift needed to translate the old times to the new times
tShift = tNewStart - min(tStart)
# Get the LST at the new start
observer.date = (tNewStart).strftime('%Y/%m/%d %H:%M:%S')
lst = observer.sidereal_time()
print(" ")
print("Shifting observations to start at %s" % tNewStart.strftime(formatString))
print("-> Difference of %i days, %.3f seconds" % (tShift.days, (tShift.seconds + tShift.microseconds/1000000.0),))
print("-> LST at %s for this date/time is %s" % (station.name, lst))
if tShift.days == 0 and tShift.seconds == 0 and tShift.microseconds == 0:
print(" ")
print("The current shift is zero. Do you want to continue anyways?")
yesNo = input("-> [y/N] ")
if yesNo not in ('y', 'Y'):
sys.exit()
else:
tShift = timedelta(seconds=0)
# Shift the start times and recompute the MJD and MPM values
for i in range(nObs):
tStart[i] += tShift
#
# Query and set the new session ID
#
print(" ")
if args.sid is None:
print("Enter the new session ID or return to keep current:")
sid = input('-> ')
if len(sid) > 0:
sid = int(sid)
else:
sid = project.sessions[0].id
else:
sid = args.sid
print("Shifting session ID from %i to %i" % (project.sessions[0].id, sid))
project.sessions[0].id = sid
#
# Go! (apply the changes to the observations)
#
print(" ")
newPOOC = []
for i in range(nObs):
print("Working on Observation #%i" % (i+1,))
newPOOC.append("")
#
# Start MJD,MPM Shifting
#
if (not args.no_update) and tShift != timedelta(seconds=0):
if len(newPOOC[-1]) != 0:
newPOOC[-1] += ';;'
newPOOC[-1] += 'Original MJD:%i,MPM:%i' % (project.sessions[0].observations[i].mjd, project.sessions[0].observations[i].mpm)
start = tStart[i].strftime("%Z %Y %m %d %H:%M:%S.%f")
start = start[:-3]
utc = Time(tStart[i], format=Time.FORMAT_PY_DATE)
mjd = int(utc.utc_mjd)
utcMidnight = datetime(tStart[i].year, tStart[i].month, tStart[i].day, 0, 0, 0, tzinfo=_UTC)
diff = tStart[i] - utcMidnight
mpm = int(round((diff.seconds + diff.microseconds/1000000.0)*1000.0))
print(" Time shifting")
print(" MJD: %8i -> %8i" % (project.sessions[0].observations[i].mjd, mjd))
print(" MPM: %8i -> %8i" % (project.sessions[0].observations[i].mpm, mpm))
project.sessions[0].observations[i].mjd = mjd
project.sessions[0].observations[i].mpm = mpm
project.sessions[0].observations[i].start = start
#
# Project office comments
#
# Update the project office comments with this change
newPOSC = "Shifted SDF with shiftSDF.py (v%s);;Time Shift? %s" % (__version__, 'Yes' if (not args.no_update) else 'No')
if project.project_office.sessions[0] is None:
project.project_office.sessions[0] = newPOSC
else:
project.project_office.sessions[0] += ';;%s' % newPOSC
for i in range(nObs):
try:
project.project_office.observations[0][i] += ';;%s' % newPOOC[i]
except Exception as e:
print(e)
project.project_office.observations[0][i] = '%s' % newPOOC[i]
#
# Save
#
if outputSDF is None:
pID = project.id
sID = project.sessions[0].id
beam = project.sessions[0].drx_beam
foStart = min(tStart)
if project.sessions[0].observations[0].mode not in ('TBW', 'TBN'):
if beam == -1:
print(" ")
print("Enter the DRX beam to use:")
newBeam = input('[1 through 4]-> ')
try:
newBeam = int(newBeam)
except Exception as e:
print("Error: %s" % str(e))
sys.exit(1)
if adp:
if newBeam not in (1,):
print("Error: beam '%i' is out of range" % newBeam)
sys.exit(1)
else:
if newBeam not in (1, 2, 3, 4):
print("Error: beam '%i' is out of range" % newBeam)
sys.exit(1)
print("Shifting DRX beam from %i to %i" % (beam, newBeam))
beam = newBeam
project.sessions[0].drx_beam = beam
outputSDF = '%s_%s_%s_%04i_B%i.sdf' % (pID, foStart.strftime('%y%m%d'), foStart.strftime('%H%M'), sID, beam)
else:
outputSDF = '%s_%s_%s_%04i_%s.sdf' % (pID, foStart.strftime('%y%m%d'), foStart.strftime('%H%M'), sID, project.sessions[0].observations[0].mode)
print(" ")
print("Saving to: %s" % outputSDF)
fh = open(outputSDF, 'w')
if not project.validate():
# Make sure we are about to be valid
project.validate(verbose=True)
raise RuntimeError("Cannot validate SDF file")
fh.write( project.render() )
fh.close()
def main(args):
# Parse the command line
## Baseline list
if args.baseline is not None:
## Fill the baseline list with the conjugates, if needed
newBaselines = []
for pair in args.baseline:
newBaselines.append( (pair[1],pair[0]) )
args.baseline.extend(newBaselines)
## Search limits
args.delay_window = [float(v) for v in args.delay_window.split(',', 1)]
args.rate_window = [float(v) for v in args.rate_window.split(',', 1)]
figs = {}
first = True
for filename in args.filename:
print("Working on '%s'" % os.path.basename(filename))
# Open the FITS IDI file and access the UV_DATA extension
hdulist = astrofits.open(filename, mode='readonly')
andata = hdulist['ANTENNA']
fqdata = hdulist['FREQUENCY']
fgdata = None
for hdu in hdulist[1:]:
if hdu.header['EXTNAME'] == 'FLAG':
fgdata = hdu
uvdata = hdulist['UV_DATA']
# Pull out various bits of information we need to flag the file
## Antenna look-up table
antLookup = {}
for an, ai in zip(andata.data['ANNAME'], andata.data['ANTENNA_NO']):
antLookup[an] = ai
## Frequency and polarization setup
nBand, nFreq, nStk = uvdata.header['NO_BAND'], uvdata.header['NO_CHAN'], uvdata.header['NO_STKD']
stk0 = uvdata.header['STK_1']
## Baseline list
bls = uvdata.data['BASELINE']
## Time of each integration
obsdates = uvdata.data['DATE']
obstimes = uvdata.data['TIME']
inttimes = uvdata.data['INTTIM']
## Source list
srcs = uvdata.data['SOURCE']
## Band information
fqoffsets = fqdata.data['BANDFREQ'].ravel()
## Frequency channels
freq = (numpy.arange(nFreq)-(uvdata.header['CRPIX3']-1))*uvdata.header['CDELT3']
freq += uvdata.header['CRVAL3']
## UVW coordinates
try:
u, v, w = uvdata.data['UU'], uvdata.data['VV'], uvdata.data['WW']
except KeyError:
u, v, w = uvdata.data['UU---SIN'], uvdata.data['VV---SIN'], uvdata.data['WW---SIN']
uvw = numpy.array([u, v, w]).T
## The actual visibility data
flux = uvdata.data['FLUX'].astype(numpy.float32)
# Convert the visibilities to something that we can easily work with
nComp = flux.shape[1] // nBand // nFreq // nStk
if nComp == 2:
## Case 1) - Just real and imaginary data
flux = flux.view(numpy.complex64)
else:
## Case 2) - Real, imaginary data + weights (drop the weights)
flux = flux[:,0::nComp] + 1j*flux[:,1::nComp]
flux.shape = (flux.shape[0], nBand, nFreq, nStk)
# Find unique baselines, times, and sources to work with
ubls = numpy.unique(bls)
utimes = numpy.unique(obstimes)
usrc = numpy.unique(srcs)
# Convert times to real times
times = utcjd_to_unix(obsdates + obstimes)
times = numpy.unique(times)
# Build a mask
mask = numpy.zeros(flux.shape, dtype=numpy.bool)
if fgdata is not None and not args.drop:
reltimes = obsdates - obsdates[0] + obstimes
maxtimes = reltimes + inttimes / 2.0 / 86400.0
mintimes = reltimes - inttimes / 2.0 / 86400.0
bls_ant1 = bls//256
bls_ant2 = bls%256
for row in fgdata.data:
ant1, ant2 = row['ANTS']
## Only deal with flags that we need for the plots
process_flag = False
if ant1 != ant2 or ant1 == 0 or ant2 == 0:
if ant1 == 0 and ant2 == 0:
process_flag = True
elif args.baseline is not None:
if ant2 == 0 and ant1 in [a0 for a0,a1 in args.baseline]:
process_flag = True
elif (ant1,ant2) in args.baseline:
process_flag = True
elif args.ref_ant is not None:
if ant1 == args.ref_ant or ant2 == args.ref_ant:
process_flag = True
else:
process_flag = True
if not process_flag:
continue
tStart, tStop = row['TIMERANG']
band = row['BANDS']
try:
len(band)
except TypeError:
band = [band,]
cStart, cStop = row['CHANS']
if cStop == 0:
cStop = -1
pol = row['PFLAGS'].astype(numpy.bool)
if ant1 == 0 and ant2 == 0:
btmask = numpy.where( ( (maxtimes >= tStart) & (mintimes <= tStop) ) )[0]
elif ant1 == 0 or ant2 == 0:
ant1 = max([ant1, ant2])
btmask = numpy.where( ( (bls_ant1 == ant1) | (bls_ant2 == ant1) ) \
& ( (maxtimes >= tStart) & (mintimes <= tStop) ) )[0]
else:
btmask = numpy.where( ( (bls_ant1 == ant1) & (bls_ant2 == ant2) ) \
& ( (maxtimes >= tStart) & (mintimes <= tStop) ) )[0]
for b,v in enumerate(band):
if not v:
continue
mask[btmask,b,cStart-1:cStop,:] |= pol
# Make sure the reference antenna is in there
if first:
if args.ref_ant is None:
bl = bls[0]
i,j = (bl>>8)&0xFF, bl&0xFF
args.ref_ant = i
else:
found = False
for bl in bls:
i,j = (bl>>8)&0xFF, bl&0xFF
if i == args.ref_ant:
found = True
break
if not found:
raise RuntimeError("Cannot file reference antenna %i in the data" % args.ref_ant)
plot_bls = []
cross = []
for i in xrange(len(ubls)):
bl = ubls[i]
ant1, ant2 = (bl>>8)&0xFF, bl&0xFF
if ant1 != ant2:
if args.baseline is not None:
if (ant1,ant2) in args.baseline:
plot_bls.append( bl )
cross.append( i )
elif args.ref_ant is not None:
if ant1 == args.ref_ant or ant2 == args.ref_ant:
plot_bls.append( bl )
cross.append( i )
else:
plot_bls.append( bl )
cross.append( i )
nBL = len(cross)
# Decimation, if needed
if args.decimate > 1:
if nFreq % args.decimate != 0:
raise RuntimeError("Invalid freqeunce decimation factor: %i %% %i = %i" % (nFreq, args.decimate, nFreq%args.decimate))
nFreq //= args.decimate
freq.shape = (freq.size//args.decimate, args.decimate)
freq = freq.mean(axis=1)
flux.shape = (flux.shape[0], flux.shape[1], flux.shape[2]//args.decimate, args.decimate, flux.shape[3])
flux = flux.mean(axis=3)
mask.shape = (mask.shape[0], mask.shape[1], mask.shape[2]//args.decimate, args.decimate, mask.shape[3])
mask = mask.mean(axis=3)
good = numpy.arange(freq.size//8, freq.size*7//8) # Inner 75% of the band
iSize = int(round(args.interval/robust.mean(inttimes)))
print(" -> Chunk size is %i intervals (%.3f seconds)" % (iSize, iSize*robust.mean(inttimes)))
iCount = times.size//iSize
print(" -> Working with %i chunks of data" % iCount)
print("Number of frequency channels: %i (~%.1f Hz/channel)" % (len(freq), freq[1]-freq[0]))
dTimes = times - times[0]
if first:
ref_time = (int(times[0]) / 60) * 60
dMax = 1.0/(freq[1]-freq[0])/4
dMax = int(dMax*1e6)*1e-6
if -dMax*1e6 > args.delay_window[0]:
args.delay_window[0] = -dMax*1e6
if dMax*1e6 < args.delay_window[1]:
args.delay_window[1] = dMax*1e6
rMax = 1.0/robust.mean(inttimes)/4
rMax = int(rMax*1e2)*1e-2
if -rMax*1e3 > args.rate_window[0]:
args.rate_window[0] = -rMax*1e3
if rMax*1e3 < args.rate_window[1]:
args.rate_window[1] = rMax*1e3
dres = 1.0
nDelays = int((args.delay_window[1]-args.delay_window[0])/dres)
while nDelays < 50:
dres /= 10
nDelays = int((args.delay_window[1]-args.delay_window[0])/dres)
while nDelays > 5000:
dres *= 10
nDelays = int((args.delay_window[1]-args.delay_window[0])/dres)
nDelays += (nDelays + 1) % 2
rres = 10.0
nRates = int((args.rate_window[1]-args.rate_window[0])/rres)
while nRates < 50:
rres /= 10
nRates = int((args.rate_window[1]-args.rate_window[0])/rres)
while nRates > 5000:
rres *= 10
nRates = int((args.rate_window[1]-args.rate_window[0])/rres)
nRates += (nRates + 1) % 2
print("Searching delays %.1f to %.1f us in steps of %.2f us" % (args.delay_window[0], args.delay_window[1], dres))
print(" rates %.1f to %.1f mHz in steps of %.2f mHz" % (args.rate_window[0], args.rate_window[1], rres))
print(" ")
delay = numpy.linspace(args.delay_window[0]*1e-6, args.delay_window[1]*1e-6, nDelays) # s
drate = numpy.linspace(args.rate_window[0]*1e-3, args.rate_window[1]*1e-3, nRates ) # Hz
# Find RFI and trim it out. This is done by computing average visibility
# amplitudes (a "spectrum") and running a median filter in frequency to extract
# the bandpass. After the spectrum has been bandpassed, 3sigma features are
# trimmed. Additionally, area where the bandpass fall below 10% of its mean
# value are also masked.
spec = numpy.median(numpy.abs(flux[:,0,:,0]), axis=0)
spec += numpy.median(numpy.abs(flux[:,0,:,1]), axis=0)
smth = spec*0.0
winSize = int(250e3/(freq[1]-freq[0]))
winSize += ((winSize+1)%2)
for i in xrange(smth.size):
mn = max([0, i-winSize//2])
mx = min([i+winSize, smth.size])
smth[i] = numpy.median(spec[mn:mx])
smth /= robust.mean(smth)
bp = spec / smth
good = numpy.where( (smth > 0.1) & (numpy.abs(bp-robust.mean(bp)) < 3*robust.std(bp)) )[0]
nBad = nFreq - len(good)
print("Masking %i of %i channels (%.1f%%)" % (nBad, nFreq, 100.0*nBad/nFreq))
freq2 = freq*1.0
freq2.shape += (1,)
dirName = os.path.basename( filename )
for b in xrange(len(plot_bls)):
bl = plot_bls[b]
valid = numpy.where( bls == bl )[0]
i,j = (bl>>8)&0xFF, bl&0xFF
dTimes = obsdates[valid] + obstimes[valid]
dTimes = numpy.array([utcjd_to_unix(v) for v in dTimes])
## Skip over baselines that are not in the baseline list (if provided)
if args.baseline is not None:
if (i,j) not in args.baseline:
continue
## Skip over baselines that don't include the reference antenna
elif i != args.ref_ant and j != args.ref_ant:
continue
## Check and see if we need to conjugate the visibility, i.e., switch from
## baseline (*,ref) to baseline (ref,*)
doConj = False
if j == args.ref_ant:
doConj = True
## Figure out which polarizations to process
if args.cross_hands:
polToUse = ('XX', 'XY', 'YY')
visToUse = (0, 2, 1)
else:
polToUse = ('XX', 'YY')
visToUse = (0, 1)
blName = (i, j)
if doConj:
blName = (j, i)
blName = '%s-%s' % ('EA%02i' % blName[0] if blName[0] < 51 else 'LWA%i' % (blName[0]-50),
'EA%02i' % blName[1] if blName[1] < 51 else 'LWA%i' % (blName[1]-50))
if first or blName not in figs:
fig = plt.figure()
fig.suptitle('%s' % blName)
fig.subplots_adjust(hspace=0.001)
axR = fig.add_subplot(2, 1, 1)
axD = fig.add_subplot(2, 1, 2, sharex=axR)
figs[blName] = (fig, axR, axD)
fig, axR, axD = figs[blName]
markers = {'XX':'s', 'YY':'o', 'XY':'v', 'YX':'^'}
for pol,vis in zip(polToUse, visToUse):
for i in xrange(iCount):
subStart, subStop = dTimes[iSize*i], dTimes[iSize*(i+1)-1]
if (subStop - subStart) > 1.1*args.interval:
continue
subTime = dTimes[iSize*i:iSize*(i+1)].mean()
dTimes2 = dTimes[iSize*i:iSize*(i+1)]*1.0
dTimes2 -= dTimes2[0]
dTimes2.shape += (1,)
subData = flux[valid,...][iSize*i:iSize*(i+1),0,good,vis]*1.0
subPhase = flux[valid,...][iSize*i:iSize*(i+1),0,good,vis]*1.0
if doConj:
subData = subData.conj()
subPhase = subPhase.conj()
subData = numpy.dot(subData, numpy.exp(-2j*numpy.pi*freq2[good,:]*delay))
subData /= freq2[good,:].size
amp = numpy.dot(subData.T, numpy.exp(-2j*numpy.pi*dTimes2*drate))
amp = numpy.abs(amp / dTimes2.size)
subPhase = numpy.angle(subPhase.mean()) * 180/numpy.pi
subPhase %= 360
if subPhase > 180:
subPhase -= 360
best = numpy.where( amp == amp.max() )
if amp.max() > 0:
bsnr = (amp[best]-amp.mean())[0]/amp.std()
bdly = delay[best[0][0]]*1e6
brat = drate[best[1][0]]*1e3
c = axR.scatter(subTime-ref_time, brat, c=bsnr, marker=markers[pol],
cmap='gist_yarg', vmin=3, vmax=40)
c = axD.scatter(subTime-ref_time, bdly, c=bsnr, marker=markers[pol],
cmap='gist_yarg', vmin=3, vmax=40)
first = False
for blName in figs:
fig, axR, axD = figs[blName]
# Colorbar
cb = fig.colorbar(c, ax=axR, orientation='horizontal')
cb.set_label('SNR')
# Legend and reference marks
handles = []
for pol in polToUse:
handles.append(Line2D([0,], [0,], linestyle='', marker=markers[pol], color='k', label=pol))
axR.legend(handles=handles, loc=0)
oldLim = axR.get_xlim()
for ax in (axR, axD):
ax.hlines(0, oldLim[0], oldLim[1], linestyle=':', alpha=0.5)
axR.set_xlim(oldLim)
# Set the labels
axR.set_ylabel('Rate [mHz]')
axD.set_ylabel('Delay [$\\mu$s]')
for ax in (axR, axD):
ax.set_xlabel('Elapsed Time [s since %s]' % datetime.utcfromtimestamp(ref_time).strftime('%Y%b%d %H:%M'))
# Set the y ranges
axR.set_ylim((-max([100, max([abs(v) for v in axR.get_ylim()])]), max([100, max([abs(v) for v in axR.get_ylim()])])))
axD.set_ylim((-max([0.5, max([abs(v) for v in axD.get_ylim()])]), max([0.5, max([abs(v) for v in axD.get_ylim()])])))
# No-go regions for the delays
xlim, ylim = axD.get_xlim(), axD.get_ylim()
axD.add_patch(Box(xy=(xlim[0],ylim[0]), width=xlim[1]-xlim[0], height=-0.5001-ylim[0],
fill=True, color='red', alpha=0.2))
axD.add_patch(Box(xy=(xlim[0],0.5001), width=xlim[1]-xlim[0], height=ylim[1]-0.5001,
fill=True, color='red', alpha=0.2))
axD.set_xlim(xlim)
axD.set_ylim(ylim)
fig.tight_layout()
plt.draw()
if args.save_images:
fig.savefig('sniffer-%s.png' % blName)
if not args.save_images:
plt.show()
def vla_to_unix(timetag):
"""
Convert a VLA timetag in MJD nanoseconds to a UNIX timestamp.
"""
return utcjd_to_unix(vla_to_utcmjd(timetag) + MJD_OFFSET)
def main(args):
reference = args.ref_source
filenames = args.filename
#
# Gather the station meta-data from its various sources
#
dataDict = numpy.load(filenames[0])
ssmifContents = dataDict['ssmifContents']
if ssmifContents.shape == ():
site = lwa1
else:
fh, tempSSMIF = tempfile.mkstemp(suffix='.txt', prefix='ssmif-')
fh = open(tempSSMIF, 'w')
for line in ssmifContents:
fh.write('%s\n' % line)
fh.close()
site = parse_ssmif(tempSSMIF)
os.unlink(tempSSMIF)
print(site.name)
observer = site.get_observer()
antennas = site.antennas
nAnts = len(antennas)
#
# Find the reference source
#
srcs = [ephem.Sun(),]
for line in _srcs:
srcs.append( ephem.readdb(line) )
refSrc = None
for i in xrange(len(srcs)):
if srcs[i].name == reference:
refSrc = srcs[i]
if refSrc is None:
print("Cannot find reference source '%s' in source list, aborting." % reference)
sys.exit(1)
#
# Parse the input files
#
data = []
time = []
freq = []
oldRef = None
oldMD5 = None
maxTime = -1
for filename in filenames:
dataDict = numpy.load(filename)
ref_ant = dataDict['ref'].item()
refX = dataDict['refX'].item()
refY = dataDict['refY'].item()
tInt = dataDict['tInt'].item()
times = dataDict['times']
phase = dataDict['simpleVis']
central_freq = dataDict['central_freq'].item()
ssmifContents = dataDict['ssmifContents']
beginDate = datetime.utcfromtimestamp(times[0])
observer.date = beginDate.strftime("%Y/%m/%d %H:%M:%S")
# Make sure we aren't mixing reference antennas
if oldRef is None:
oldRef = ref_ant
if ref_ant != oldRef:
raise RuntimeError("Dataset has different reference antennas than previous (%i != %i)" % (ref_ant, oldRef))
# Make sure we aren't mixing SSMIFs
ssmifMD5 = md5sum(ssmifContents)
if oldMD5 is None:
oldMD5 = ssmifMD5
if ssmifMD5 != oldMD5:
raise RuntimeError("Dataset has different SSMIF than previous (%s != %s)" % (ssmifMD5, oldMD5))
print("Central Frequency: %.3f Hz" % central_freq)
print("Start date/time: %s" % beginDate.strftime("%Y/%m/%d %H:%M:%S"))
print("Integration Time: %.3f s" % tInt)
print("Number of time samples: %i (%.3f s)" % (phase.shape[0], phase.shape[0]*tInt))
allRates = {}
for src in srcs:
src.compute(observer)
if src.alt > 0:
fRate = getFringeRate(antennas[0], antennas[refX], observer, src, central_freq)
allRates[src.name] = fRate
# Calculate the fringe rates of all sources - for display purposes only
print("Starting Fringe Rates:")
for name in allRates.keys():
fRate = allRates[name]
print(" %-4s: %+6.3f mHz" % (name, fRate*1e3))
freq.append( central_freq )
time.append( numpy.array([unix_to_utcjd(t) for t in times]) )
data.append( phase )
## Save the length of the `time` entry so that we can trim them
## all down to the same size later
if time[-1].size > maxTime:
maxTime = time[-1].size
# Pad with NaNs to the same length
for i in xrange(len(filenames)):
nTimes = time[i].size
if nTimes < maxTime:
## Pad 'time'
newTime = numpy.zeros(maxTime, dtype=time[i].dtype)
newTime += numpy.nan
newTime[0:nTimes] = time[i][:]
time[i] = newTime
## Pad 'data'
newData = numpy.zeros((maxTime, data[i].shape[1]), dtype=data[i].dtype)
newData += numpy.nan
newData[0:nTimes,:] = data[i][:,:]
data[i] = newData
# Convert to 2-D and 3-D numpy arrays
freq = numpy.array(freq)
time = numpy.array(time)
data = numpy.array(data)
#
# Sort the data by frequency
#
order = numpy.argsort(freq)
freq = numpy.take(freq, order)
time = numpy.take(time, order, axis=0)
data = numpy.take(data, order, axis=0)
#
# Find the fringe stopping averaging times
#
ls = {}
for fStart in xrange(20, 90, 5):
fStop = fStart + 5
l = numpy.where( (freq >= fStart*1e6) & (freq < fStop*1e6) )[0]
if len(l) > 0:
ls[fStart] = l
ms = {}
for fStart in ls.keys():
m = 1e6
for l in ls[fStart]:
good = numpy.where( numpy.isfinite(time[l,:]) == 1 )[0]
if len(good) < m:
m = len(good)
ms[fStart] = m
print("Minimum fringe stopping times:")
for fStart in sorted(ls.keys()):
fStop = fStart + 5
m = ms[fStart]
print(" >=%i Mhz and <%i MHz: %.3f s" % (fStart, fStop, m*tInt,))
#
# Report on progress and data coverage
#
nFreq = len(freq)
print("Reference stand #%i (X: %i, Y: %i)" % (ref_ant, refX, refY))
print("-> X: %s" % str(antennas[refX]))
print("-> Y: %s" % str(antennas[refY]))
print("Using a set of %i frequencies" % nFreq)
print("->", freq/1e6)
#
# Compute source positions/fringe stop and remove the source
#
print("Fringe stopping on '%s':" % refSrc.name)
pbar = ProgressBar(max=freq.size*520)
for i in xrange(freq.size):
fq = freq[i]
for j in xrange(data.shape[2]):
# Compute the times in seconds relative to the beginning
times = time[i,:] - time[i,0]
times *= 24.0
times *= 3600.0
# Compute the fringe rates across all time
fRate = [None,]*data.shape[1]
for k in xrange(data.shape[1]):
jd = time[i,k]
try:
currDate = datetime.utcfromtimestamp(utcjd_to_unix(jd))
except ValueError:
pass
observer.date = currDate.strftime("%Y/%m/%d %H:%M:%S")
refSrc.compute(observer)
if j % 2 == 0:
fRate[k] = getFringeRate(antennas[j], antennas[refX], observer, refSrc, fq)
else:
fRate[k] = getFringeRate(antennas[j], antennas[refY], observer, refSrc, fq)
# Create the basis rate and the residual rates
baseRate = fRate[0]
residRate = numpy.array(fRate) - baseRate
# Fringe stop to more the source of interest to the DC component
data[i,:,j] *= numpy.exp(-2j*numpy.pi* baseRate*(times - times[0]))
data[i,:,j] *= numpy.exp(-2j*numpy.pi*residRate*(times - times[0]))
# Calculate the geometric delay term across all time
gDelay = [None,]*data.shape[1]
for k in xrange(data.shape[1]):
jd = time[i,k]
try:
currDate = datetime.utcfromtimestamp(utcjd_to_unix(jd))
except ValueError:
pass
observer.date = currDate.strftime("%Y/%m/%d %H:%M:%S")
refSrc.compute(observer)
az = refSrc.az
el = refSrc.alt
if j % 2 == 0:
gDelay[k] = getGeoDelay(antennas[j], antennas[refX], az, el, Degrees=False)
else:
gDelay[k] = getGeoDelay(antennas[j], antennas[refY], az, el, Degrees=False)
# Create the basis delay and the residual delays
baseDelay = gDelay[0]
residDelay = numpy.array(gDelay) - baseDelay
# Remove the array geometry
data[i,:,j] *= numpy.exp(-2j*numpy.pi*fq* baseDelay)
data[i,:,j] *= numpy.exp(-2j*numpy.pi*fq*residDelay)
pbar.inc()
sys.stdout.write("%s\r" % pbar.show())
sys.stdout.flush()
sys.stdout.write('\n')
# Average down to remove other sources/the correlated sky
print("Input (pre-averaging) data shapes:")
print(" time:", time.shape)
print(" data:", data.shape)
time = time[:,0]
data2 = numpy.zeros((data.shape[0], data.shape[2]), dtype=data.dtype)
for j in xrange(data2.shape[1]):
for fStart in ls.keys():
l = ls[fStart]
m = ms[fStart]
data2[l,j] = data[l,:m,j].mean(axis=1)
data = data2
print("Output (post-averaging) data shapes:")
print(" time:", time.shape)
print(" data:", data.shape)
#
# Save
#
outname = args.output
outname, ext = os.path.splitext(outname)
outname = "%s-ref%03i%s" % (outname, ref_ant, ext)
numpy.savez(outname, ref_ant=ref_ant, refX=refX, refY=refY, freq=freq, time=time, data=data, ssmifContents=ssmifContents)
def main(args):
# Get the site and observer
site = stations.lwa1
observer = site.get_observer()
# Filenames in an easier format
inputTGZ = args.filename
# Parse the input file and get the dates of the observations. Be default
# this is for LWA1 but we switch over to LWA-SV if an error occurs.
try:
# LWA1
project = metabundle.get_sdf(inputTGZ)
obsImpl = metabundle.get_observation_spec(inputTGZ)
fileInfo = metabundle.get_session_metadata(inputTGZ)
aspConfigB = metabundle.get_asp_configuration_summary(
inputTGZ, which='Beginning')
aspConfigE = metabundle.get_asp_configuration_summary(inputTGZ,
which='End')
except:
# LWA-SV
## Site changes
site = stations.lwasv
observer = site.get_observer()
## Try again
project = metabundleADP.get_sdf(inputTGZ)
obsImpl = metabundleADP.get_observation_spec(inputTGZ)
fileInfo = metabundleADP.get_session_metadata(inputTGZ)
aspConfigB = metabundleADP.get_asp_configuration_summary(
inputTGZ, which='Beginning')
aspConfigE = metabundleADP.get_asp_configuration_summary(inputTGZ,
which='End')
nObs = len(project.sessions[0].observations)
tStart = [
None,
] * nObs
for i in range(nObs):
tStart[i] = utcjd_to_unix(project.sessions[0].observations[i].mjd +
MJD_OFFSET)
tStart[i] += project.sessions[0].observations[i].mpm / 1000.0
tStart[i] = datetime.utcfromtimestamp(tStart[i])
tStart[i] = _UTC.localize(tStart[i])
# Get the LST at the start
observer.date = (min(tStart)).strftime('%Y/%m/%d %H:%M:%S')
lst = observer.sidereal_time()
# Report on the file
print("Filename: %s" % inputTGZ)
print(" Project ID: %s" % project.id)
print(" Session ID: %i" % project.sessions[0].id)
print(" Observations appear to start at %s" %
(min(tStart)).strftime(_FORMAT_STRING))
print(" -> LST at %s for this date/time is %s" % (site.name, lst))
lastDur = project.sessions[0].observations[nObs - 1].dur
lastDur = timedelta(seconds=int(lastDur / 1000),
microseconds=(lastDur * 1000) % 1000000)
sessionDur = max(tStart) - min(tStart) + lastDur
print(" ")
print(" Total Session Duration: %s" % sessionDur)
print(" -> First observation starts at %s" %
min(tStart).strftime(_FORMAT_STRING))
print(" -> Last observation ends at %s" %
(max(tStart) + lastDur).strftime(_FORMAT_STRING))
if project.sessions[0].observations[0].mode not in ('TBW', 'TBN'):
drspec = 'No'
if project.sessions[0].spcSetup[0] != 0 and project.sessions[
0].spcSetup[1] != 0:
drspec = 'Yes'
drxBeam = project.sessions[0].drx_beam
if drxBeam < 1:
drxBeam = "MCS decides"
else:
drxBeam = "%i" % drxBeam
print(" DRX Beam: %s" % drxBeam)
print(" DR Spectrometer used? %s" % drspec)
if drspec == 'Yes':
print(" -> %i channels, %i windows/integration" %
tuple(project.sessions[0].spcSetup))
else:
tbnCount = 0
tbwCount = 0
for obs in project.sessions[0].observations:
if obs.mode == 'TBW':
tbwCount += 1
else:
tbnCount += 1
if tbwCount > 0 and tbnCount == 0:
print(" Transient Buffer Mode: TBW")
elif tbwCount == 0 and tbnCount > 0:
print(" Transient Buffer Mode: TBN")
else:
print(" Transient Buffer Mode: both TBW and TBN")
print(" ")
print("File Information:")
for obsID in fileInfo.keys():
print(" Obs. #%i: %s" % (obsID, fileInfo[obsID]['tag']))
print(" ")
print("ASP Configuration:")
print(' Beginning')
for k, v in aspConfigB.items():
print(' %s: %i' % (k, v))
print(' End')
for k, v in aspConfigE.items():
print(' %s: %i' % (k, v))
print(" ")
print(" Number of observations: %i" % nObs)
print(" Observation Detail:")
for i in range(nObs):
currDur = project.sessions[0].observations[i].dur
currDur = timedelta(seconds=int(currDur / 1000),
microseconds=(currDur * 1000) % 1000000)
print(" Observation #%i" % (i + 1, ))
currObs = None
for j in range(len(obsImpl)):
if obsImpl[j]['obsID'] == i + 1:
currObs = obsImpl[j]
break
## Basic setup
print(" Target: %s" % project.sessions[0].observations[i].target)
print(" Mode: %s" % project.sessions[0].observations[i].mode)
print(" Start:")
print(" MJD: %i" % project.sessions[0].observations[i].mjd)
print(" MPM: %i" % project.sessions[0].observations[i].mpm)
print(" -> %s" % get_observation_start_stop(
project.sessions[0].observations[i])[0].strftime(_FORMAT_STRING))
print(" Duration: %s" % currDur)
## DP setup
if project.sessions[0].observations[i].mode not in ('TBW', ):
print(" Tuning 1: %.3f MHz" %
(project.sessions[0].observations[i].frequency1 / 1e6, ))
if project.sessions[0].observations[i].mode not in ('TBW', 'TBN'):
print(" Tuning 2: %.3f MHz" %
(project.sessions[0].observations[i].frequency2 / 1e6, ))
if project.sessions[0].observations[i].mode not in ('TBW', ):
print(" Filter code: %i" %
project.sessions[0].observations[i].filter)
if currObs is not None:
if project.sessions[0].observations[i].mode not in ('TBW', ):
if project.sessions[0].observations[i].mode == 'TBN':
print(" Gain setting: %i" % currObs['tbnGain'])
else:
print(" Gain setting: %i" % currObs['drxGain'])
else:
print(
" WARNING: observation specification not found for this observation"
)
## Comments/notes
print(" Observer Comments: %s" %
project.sessions[0].observations[i].comments)
def main(args):
# Parse the command line
filenames = args.filename
for filename in filenames:
t0 = time.time()
print("Working on '%s'" % os.path.basename(filename))
# Open the FITS IDI file and access the UV_DATA extension
hdulist = astrofits.open(filename, mode='readonly')
andata = hdulist['ANTENNA']
fqdata = hdulist['FREQUENCY']
srdata = hdulist['SOURCE']
fgdata = None
for hdu in hdulist[1:]:
if hdu.header['EXTNAME'] == 'FLAG':
fgdata = hdu
uvdata = hdulist['UV_DATA']
# Verify we can flag this data
if uvdata.header['STK_1'] > 0:
raise RuntimeError("Cannot flag data with STK_1 = %i" %
uvdata.header['STK_1'])
if uvdata.header['NO_STKD'] < 4:
raise RuntimeError("Cannot flag data with NO_STKD = %i" %
uvdata.header['NO_STKD'])
# NOTE: Assumes that the Stokes parameters increment by -1
polMapper = {}
for i in xrange(uvdata.header['NO_STKD']):
stk = uvdata.header['STK_1'] - i
polMapper[i] = NUMERIC_STOKES[stk]
# Pull out various bits of information we need to flag the file
## Antenna look-up table
antLookup = {}
for an, ai in zip(andata.data['ANNAME'], andata.data['ANTENNA_NO']):
antLookup[an] = ai
## Frequency and polarization setup
nBand, nFreq, nStk = uvdata.header['NO_BAND'], uvdata.header[
'NO_CHAN'], uvdata.header['NO_STKD']
## Baseline list
bls = uvdata.data['BASELINE']
## Time of each integration
obsdates = uvdata.data['DATE']
obstimes = uvdata.data['TIME']
inttimes = uvdata.data['INTTIM']
## Source list
srcs = uvdata.data['SOURCE']
## Band information
fqoffsets = fqdata.data['BANDFREQ'].ravel()
## Frequency channels
freq = (numpy.arange(nFreq) -
(uvdata.header['CRPIX3'] - 1)) * uvdata.header['CDELT3']
freq += uvdata.header['CRVAL3']
## The actual visibility data
flux = uvdata.data['FLUX'].astype(numpy.float32)
# Convert the visibilities to something that we can easily work with
nComp = flux.shape[1] // nBand // nFreq // nStk
if nComp == 2:
## Case 1) - Just real and imaginary data
flux = flux.view(numpy.complex64)
else:
## Case 2) - Real, imaginary data + weights (drop the weights)
flux = flux[:, 0::nComp] + 1j * flux[:, 1::nComp]
flux.shape = (flux.shape[0], nBand, nFreq, nStk)
# Find unique baselines and scans to work on
ubls = numpy.unique(bls)
blocks = get_source_blocks(hdulist)
# Create a mask of the old flags, if needed
old_flag_mask = get_flags_as_mask(hdulist, version=0 - args.drop)
# Dedisperse
mask = numpy.zeros(flux.shape, dtype=numpy.bool)
for i, block in enumerate(blocks):
tS = time.time()
print(' Working on scan %i of %i' % (i + 1, len(blocks)))
match = range(block[0], block[1] + 1)
bbls = numpy.unique(bls[match])
times = obstimes[match] * 86400.0
ints = inttimes[match]
scanStart = datetime.utcfromtimestamp(
utcjd_to_unix(obsdates[match[0]] + obstimes[match[0]]))
scanStop = datetime.utcfromtimestamp(
utcjd_to_unix(obsdates[match[-1]] + obstimes[match[-1]]))
print(' Scan spans %s to %s UTC' %
(scanStart.strftime('%Y/%m/%d %H:%M:%S'),
scanStop.strftime('%Y/%m/%d %H:%M:%S')))
freq_comb = []
for b, offset in enumerate(fqoffsets):
freq_comb.append(freq + offset)
freq_comb = numpy.concatenate(freq_comb)
nBL = len(bbls)
vis = flux[match, :, :, :]
ofm = old_flag_mask[match, :, :, :]
## If this is the last block, check and see if there is anything that
## we can pull out next file in the sequence so that we don't have a
## dedispersion gap
to_trim = -1
if i == len(blocks) - 1:
src_name = srdata.data['SOURCE'][srcs[match[0]] - 1]
nextmask, nextflux = get_trailing_scan(
filename, src_name, max(delay(freq_comb, args.DM)))
if nextmask is not None and nextflux is not None:
to_trim = ofm.shape[0]
vis = numpy.concatenate([vis, nextflux])
ofm = numpy.concatenate([ofm, nextmask])
print(
' Appended %i times from the next file in the sequence'
% (nextflux.shape[0] // nBL))
vis.shape = (vis.shape[0] // nBL, nBL, vis.shape[1] * vis.shape[2],
vis.shape[3])
ofm.shape = (ofm.shape[0] // nBL, nBL, ofm.shape[1] * ofm.shape[2],
ofm.shape[3])
print(
' Scan contains %i times, %i baselines, %i bands/channels, %i polarizations'
% vis.shape)
if vis.shape[0] < 5:
print(' Too few integrations, skipping')
vis[:, :, :, :] = numpy.nan
ofm[:, :, :, :] = True
else:
for j in xrange(nBL):
for k in xrange(nStk):
vis[:, j, :, k] = incoherent(freq_comb,
vis[:, j, :, k],
ints[0],
args.DM,
boundary='fill',
fill_value=numpy.nan)
ofm[:, j, :, k] = incoherent(freq_comb,
ofm[:, j, :, k],
ints[0],
args.DM,
boundary='fill',
fill_value=True)
vis.shape = (vis.shape[0] * vis.shape[1], len(fqoffsets),
vis.shape[2] // len(fqoffsets), vis.shape[3])
ofm.shape = (ofm.shape[0] * ofm.shape[1], len(fqoffsets),
ofm.shape[2] // len(fqoffsets), ofm.shape[3])
if to_trim != -1:
print(' Removing the appended times')
vis = vis[:to_trim, ...]
ofm = ofm[:to_trim, ...]
flux[match, :, :, :] = vis
print(' Saving polarization masks')
submask = numpy.where(numpy.isfinite(vis), False, True)
submask.shape = (len(match), flux.shape[1], flux.shape[2],
flux.shape[3])
mask[match, :, :, :] = submask
print(' Statistics for this scan')
print(' -> %s - %.1f%% flagged' % (
polMapper[0],
100.0 * mask[match, :, :, 0].sum() / mask[match, :, :, 0].size,
))
print(' -> %s - %.1f%% flagged' % (
polMapper[1],
100.0 * mask[match, :, :, 1].sum() / mask[match, :, :, 0].size,
))
print(' -> Elapsed - %.3f s' % (time.time() - tS, ))
# Add in the original flag mask
mask[match, :, :, :] |= ofm
# Convert the masks into a format suitable for writing to a FLAG table
print(" Building FLAG table")
ants, times, bands, chans, pols, reas, sevs = [], [], [], [], [], [], []
## New Flags
nBL = len(ubls)
for i in xrange(nBL):
blset = numpy.where(bls == ubls[i])[0]
ant1, ant2 = (ubls[i] >> 8) & 0xFF, ubls[i] & 0xFF
if i % 100 == 0 or i + 1 == nBL:
print(" Baseline %i of %i" % (i + 1, nBL))
if len(blset) == 0:
continue
for b, offset in enumerate(fqoffsets):
maskXX = mask[blset, b, :, 0]
maskYY = mask[blset, b, :, 1]
flagsXX, _ = create_flag_groups(obstimes[blset], freq + offset,
maskXX)
flagsYY, _ = create_flag_groups(obstimes[blset], freq + offset,
maskYY)
for flag in flagsXX:
ants.append((ant1, ant2))
times.append(
(obsdates[blset[flag[0]]] + obstimes[blset[flag[0]]] -
obsdates[0], obsdates[blset[flag[1]]] +
obstimes[blset[flag[1]]] - obsdates[0]))
bands.append([1 if j == b else 0 for j in xrange(nBand)])
chans.append((flag[2] + 1, flag[3] + 1))
pols.append((1, 0, 1, 1))
reas.append('DEDISPERSEIDI.PY')
sevs.append(-1)
for flag in flagsYY:
ants.append((ant1, ant2))
times.append(
(obsdates[blset[flag[0]]] + obstimes[blset[flag[0]]] -
obsdates[0], obsdates[blset[flag[1]]] +
obstimes[blset[flag[1]]] - obsdates[0]))
bands.append([1 if j == b else 0 for j in xrange(nBand)])
chans.append((flag[2] + 1, flag[3] + 1))
pols.append((0, 1, 1, 1))
reas.append('DEDISPERSEIDI.PY')
sevs.append(-1)
## Figure out our revision
try:
repo = git.Repo(os.path.dirname(os.path.abspath(__file__)))
try:
branch = repo.active_branch.name
hexsha = repo.active_branch.commit.hexsha
except TypeError:
branch = '<detached>'
hexsha = repo.head.commit.hexsha
shortsha = hexsha[-7:]
dirty = ' (dirty)' if repo.is_dirty() else ''
except git.exc.GitError:
branch = 'unknown'
hexsha = 'unknown'
shortsha = 'unknown'
dirty = ''
## Build the FLAG table
print(' FITS HDU')
### Columns
nFlags = len(ants)
c1 = astrofits.Column(name='SOURCE_ID',
format='1J',
array=numpy.zeros((nFlags, ), dtype=numpy.int32))
c2 = astrofits.Column(name='ARRAY',
format='1J',
array=numpy.zeros((nFlags, ), dtype=numpy.int32))
c3 = astrofits.Column(name='ANTS',
format='2J',
array=numpy.array(ants, dtype=numpy.int32))
c4 = astrofits.Column(name='FREQID',
format='1J',
array=numpy.zeros((nFlags, ), dtype=numpy.int32))
c5 = astrofits.Column(name='TIMERANG',
format='2E',
array=numpy.array(times, dtype=numpy.float32))
c6 = astrofits.Column(name='BANDS',
format='%iJ' % nBand,
array=numpy.array(bands,
dtype=numpy.int32).squeeze())
c7 = astrofits.Column(name='CHANS',
format='2J',
array=numpy.array(chans, dtype=numpy.int32))
c8 = astrofits.Column(name='PFLAGS',
format='4J',
array=numpy.array(pols, dtype=numpy.int32))
c9 = astrofits.Column(name='REASON',
format='A40',
array=numpy.array(reas))
c10 = astrofits.Column(name='SEVERITY',
format='1J',
array=numpy.array(sevs, dtype=numpy.int32))
colDefs = astrofits.ColDefs([c1, c2, c3, c4, c5, c6, c7, c8, c9, c10])
### The table itself
flags = astrofits.BinTableHDU.from_columns(colDefs)
### The header
flags.header['EXTNAME'] = ('FLAG', 'FITS-IDI table name')
flags.header['EXTVER'] = (1 if fgdata is None else
fgdata.header['EXTVER'] + 1,
'table instance number')
flags.header['TABREV'] = (2, 'table format revision number')
for key in ('NO_STKD', 'STK_1', 'NO_BAND', 'NO_CHAN', 'REF_FREQ',
'CHAN_BW', 'REF_PIXL', 'OBSCODE', 'ARRNAM', 'RDATE'):
try:
flags.header[key] = (uvdata.header[key],
uvdata.header.comments[key])
except KeyError:
pass
flags.header['HISTORY'] = 'Flagged with %s, revision %s.%s%s' % (
os.path.basename(__file__), branch, shortsha, dirty)
flags.header['HISTORY'] = 'Dedispersed at %.6f pc / cm^3' % args.DM
# Clean up the old FLAG tables, if any, and then insert the new table where it needs to be
if args.drop:
## Reset the EXTVER on the new FLAG table
flags.header['EXTVER'] = (1, 'table instance number')
## Find old tables
toRemove = []
for hdu in hdulist:
try:
if hdu.header['EXTNAME'] == 'FLAG':
toRemove.append(hdu)
except KeyError:
pass
## Remove old tables
for hdu in toRemove:
ver = hdu.header['EXTVER']
del hdulist[hdulist.index(hdu)]
print(" WARNING: removing old FLAG table - version %i" % ver)
## Insert the new table right before UV_DATA
hdulist.insert(-1, flags)
# Save
print(" Saving to disk")
## What to call it
outname = os.path.basename(filename)
outname, outext = os.path.splitext(outname)
outname = '%s_DM%.4f%s' % (outname, args.DM, outext)
## Does it already exist or not
if os.path.exists(outname):
if not args.force:
yn = raw_input("WARNING: '%s' exists, overwrite? [Y/n] " %
outname)
else:
yn = 'y'
if yn not in ('n', 'N'):
os.unlink(outname)
else:
raise RuntimeError("Output file '%s' already exists" % outname)
## Open and create a new primary HDU
hdulist2 = astrofits.open(outname, mode='append')
primary = astrofits.PrimaryHDU()
processed = []
for key in hdulist[0].header:
if key in ('COMMENT', 'HISTORY'):
if key not in processed:
parts = str(hdulist[0].header[key]).split('\n')
for part in parts:
primary.header[key] = part
processed.append(key)
else:
primary.header[key] = (hdulist[0].header[key],
hdulist[0].header.comments[key])
primary.header['HISTORY'] = 'Dedispersed with %s, revision %s.%s%s' % (
os.path.basename(__file__), branch, shortsha, dirty)
primary.header['HISTORY'] = 'Dedispersed at %.6f pc / cm^3' % args.DM
hdulist2.append(primary)
hdulist2.flush()
## Copy the extensions over to the new file
for hdu in hdulist[1:]:
if hdu.header['EXTNAME'] == 'UV_DATA':
### Updated the UV_DATA table with the dedispersed data
flux = numpy.where(numpy.isfinite(flux), flux, 0.0)
flux = flux.view(numpy.float32) # pylint: disable=no-member
flux = flux.astype(hdu.data['FLUX'].dtype)
flux.shape = hdu.data['FLUX'].shape
hdu.data['FLUX'][...] = flux
hdulist2.append(hdu)
hdulist2.flush()
hdulist2.close()
hdulist.close()
print(" -> Dedispersed FITS IDI file is '%s'" % outname)
print(" Finished in %.3f s" % (time.time() - t0, ))
def main(args):
# Parse the command line
## Baseline list
if args.baseline is not None:
## Fill the baseline list with the conjugates, if needed
newBaselines = []
for pair in args.baseline:
newBaselines.append((pair[1], pair[0]))
args.baseline.extend(newBaselines)
## Polarization
args.polToPlot = 'XX'
if args.xy:
args.polToPlot = 'XY'
elif args.yx:
args.polToPlot = 'YX'
elif args.yy:
args.polToPlot = 'YY'
filename = args.filename
print("Working on '%s'" % os.path.basename(filename))
# Open the FITS IDI file and access the UV_DATA extension
hdulist = astrofits.open(filename, mode='readonly')
andata = hdulist['ANTENNA']
fqdata = hdulist['FREQUENCY']
fgdata = None
for hdu in hdulist[1:]:
if hdu.header['EXTNAME'] == 'FLAG':
fgdata = hdu
uvdata = hdulist['UV_DATA']
# Pull out various bits of information we need to flag the file
## Antenna look-up table
antLookup = {}
for an, ai in zip(andata.data['ANNAME'], andata.data['ANTENNA_NO']):
antLookup[an] = ai
## Frequency and polarization setup
nBand, nFreq, nStk = uvdata.header['NO_BAND'], uvdata.header[
'NO_CHAN'], uvdata.header['NO_STKD']
stk0 = uvdata.header['STK_1']
## Baseline list
bls = uvdata.data['BASELINE']
## Time of each integration
obsdates = uvdata.data['DATE']
obstimes = uvdata.data['TIME']
inttimes = uvdata.data['INTTIM']
## Source list
srcs = uvdata.data['SOURCE']
## Band information
fqoffsets = fqdata.data['BANDFREQ'].ravel()
## Frequency channels
freq = (numpy.arange(nFreq) -
(uvdata.header['CRPIX3'] - 1)) * uvdata.header['CDELT3']
freq += uvdata.header['CRVAL3']
## UVW coordinates
try:
u, v, w = uvdata.data['UU'], uvdata.data['VV'], uvdata.data['WW']
except KeyError:
u, v, w = uvdata.data['UU---SIN'], uvdata.data[
'VV---SIN'], uvdata.data['WW---SIN']
uvw = numpy.array([u, v, w]).T
## The actual visibility data
flux = uvdata.data['FLUX'].astype(numpy.float32)
# Convert the visibilities to something that we can easily work with
nComp = flux.shape[1] // nBand // nFreq // nStk
if nComp == 2:
## Case 1) - Just real and imaginary data
flux = flux.view(numpy.complex64)
else:
## Case 2) - Real, imaginary data + weights (drop the weights)
flux = flux[:, 0::nComp] + 1j * flux[:, 1::nComp]
flux.shape = (flux.shape[0], nBand, nFreq, nStk)
# Find unique baselines, times, and sources to work with
ubls = numpy.unique(bls)
utimes = numpy.unique(obstimes)
usrc = numpy.unique(srcs)
# Convert times to real times
times = utcjd_to_unix(obsdates + obstimes)
times = numpy.unique(times)
# Build a mask
mask = numpy.zeros(flux.shape, dtype=numpy.bool)
if fgdata is not None and not args.drop:
reltimes = obsdates - obsdates[0] + obstimes
maxtimes = reltimes + inttimes / 2.0 / 86400.0
mintimes = reltimes - inttimes / 2.0 / 86400.0
bls_ant1 = bls // 256
bls_ant2 = bls % 256
for row in fgdata.data:
ant1, ant2 = row['ANTS']
## Only deal with flags that we need for the plots
process_flag = False
if args.include_auto or ant1 != ant2 or ant1 == 0 or ant2 == 0:
if ant1 == 0 and ant2 == 0:
process_flag = True
elif args.baseline is not None:
if ant2 == 0 and ant1 in [a0 for a0, a1 in args.baseline]:
process_flag = True
elif (ant1, ant2) in args.baseline:
process_flag = True
elif args.ref_ant is not None:
if ant1 == args.ref_ant or ant2 == args.ref_ant:
process_flag = True
else:
process_flag = True
if not process_flag:
continue
tStart, tStop = row['TIMERANG']
band = row['BANDS']
try:
len(band)
except TypeError:
band = [
band,
]
cStart, cStop = row['CHANS']
if cStop == 0:
cStop = -1
pol = row['PFLAGS'].astype(numpy.bool)
if ant1 == 0 and ant2 == 0:
btmask = numpy.where(
((maxtimes >= tStart) & (mintimes <= tStop)))[0]
elif ant1 == 0 or ant2 == 0:
ant1 = max([ant1, ant2])
btmask = numpy.where( ( (bls_ant1 == ant1) | (bls_ant2 == ant1) ) \
& ( (maxtimes >= tStart) & (mintimes <= tStop) ) )[0]
else:
btmask = numpy.where( ( (bls_ant1 == ant1) & (bls_ant2 == ant2) ) \
& ( (maxtimes >= tStart) & (mintimes <= tStop) ) )[0]
for b, v in enumerate(band):
if not v:
continue
mask[btmask, b, cStart - 1:cStop, :] |= pol
plot_bls = []
cross = []
for i in xrange(len(ubls)):
bl = ubls[i]
ant1, ant2 = (bl >> 8) & 0xFF, bl & 0xFF
if args.include_auto or ant1 != ant2:
if args.baseline is not None:
if (ant1, ant2) in args.baseline:
plot_bls.append(bl)
cross.append(i)
elif args.ref_ant is not None:
if ant1 == args.ref_ant or ant2 == args.ref_ant:
plot_bls.append(bl)
cross.append(i)
else:
plot_bls.append(bl)
cross.append(i)
nBL = len(cross)
# Decimation, if needed
if args.decimate > 1:
if nFreq % args.decimate != 0:
raise RuntimeError(
"Invalid freqeunce decimation factor: %i %% %i = %i" %
(nFreq, args.decimate, nFreq % args.decimate))
nFreq //= args.decimate
freq.shape = (freq.size // args.decimate, args.decimate)
freq = freq.mean(axis=1)
flux.shape = (flux.shape[0], flux.shape[1],
flux.shape[2] // args.decimate, args.decimate,
flux.shape[3])
flux = flux.mean(axis=3)
mask.shape = (mask.shape[0], mask.shape[1],
mask.shape[2] // args.decimate, args.decimate,
mask.shape[3])
mask = mask.mean(axis=3)
good = numpy.arange(freq.size // 8,
freq.size * 7 // 8) # Inner 75% of the band
# NOTE: Assumes that the Stokes parameters increment by -1
namMapper = {}
for i in xrange(nStk):
stk = stk0 - i
namMapper[i] = NUMERIC_STOKES[stk]
polMapper = {'XX': 0, 'YY': 1, 'XY': 2, 'YX': 3}
fig1 = plt.figure()
fig2 = plt.figure()
fig3 = plt.figure()
fig4 = plt.figure()
fig5 = plt.figure()
k = 0
nRow = int(numpy.sqrt(len(plot_bls)))
nCol = int(numpy.ceil(len(plot_bls) * 1.0 / nRow))
for b in xrange(len(plot_bls)):
bl = plot_bls[b]
valid = numpy.where(bls == bl)[0]
i, j = (bl >> 8) & 0xFF, bl & 0xFF
dTimes = obsdates[valid] + obstimes[valid]
dTimes -= dTimes[0]
dTimes *= 86400.0
ax1, ax2, ax3, ax4, ax5 = None, None, None, None, None
for band, offset in enumerate(fqoffsets):
frq = freq + offset
vis = numpy.ma.array(flux[valid, band, :,
polMapper[args.polToPlot]],
mask=mask[valid, band, :,
polMapper[args.polToPlot]])
ax1 = fig1.add_subplot(nRow,
nCol * nBand,
nBand * k + 1 + band,
sharey=ax1)
ax1.imshow(numpy.ma.angle(vis),
extent=(frq[0] / 1e6, frq[-1] / 1e6, dTimes[0],
dTimes[-1]),
origin='lower',
vmin=-numpy.pi,
vmax=numpy.pi,
interpolation='nearest')
ax1.axis('auto')
ax1.set_xlabel('Frequency [MHz]')
if band == 0:
ax1.set_ylabel('Elapsed Time [s]')
ax1.set_title("%i,%i - %s" %
(i, j, namMapper[polMapper[args.polToPlot]]))
ax1.set_xlim((frq[0] / 1e6, frq[-1] / 1e6))
ax1.set_ylim((dTimes[0], dTimes[-1]))
ax2 = fig2.add_subplot(nRow,
nCol * nBand,
nBand * k + 1 + band,
sharey=ax2)
amp = numpy.ma.abs(vis)
vmin, vmax = percentile(amp, 1), percentile(amp, 99)
ax2.imshow(amp,
extent=(frq[0] / 1e6, frq[-1] / 1e6, dTimes[0],
dTimes[-1]),
origin='lower',
interpolation='nearest',
vmin=vmin,
vmax=vmax)
ax2.axis('auto')
ax2.set_xlabel('Frequency [MHz]')
if band == 0:
ax2.set_ylabel('Elapsed Time [s]')
ax2.set_title("%i,%i - %s" %
(i, j, namMapper[polMapper[args.polToPlot]]))
ax2.set_xlim((frq[0] / 1e6, frq[-1] / 1e6))
ax2.set_ylim((dTimes[0], dTimes[-1]))
ax3 = fig3.add_subplot(nRow,
nCol * nBand,
nBand * k + 1 + band,
sharey=ax3)
ax3.plot(frq / 1e6, numpy.ma.abs(vis.mean(axis=0)))
ax3.set_xlabel('Frequency [MHz]')
if band == 0:
ax3.set_ylabel('Mean Vis. Amp. [lin.]')
ax3.set_title("%i,%i - %s" %
(i, j, namMapper[polMapper[args.polToPlot]]))
ax3.set_xlim((frq[0] / 1e6, frq[-1] / 1e6))
ax4 = fig4.add_subplot(nRow,
nCol * nBand,
nBand * k + 1 + band,
sharey=ax4)
ax4.plot(numpy.ma.angle(vis[:, good].mean(axis=1)) * 180 /
numpy.pi,
dTimes,
linestyle='',
marker='+')
ax4.set_xlim((-180, 180))
ax4.set_xlabel('Mean Vis. Phase [deg]')
if band == 0:
ax4.set_ylabel('Elapsed Time [s]')
ax4.set_title("%i,%i - %s" %
(i, j, namMapper[polMapper[args.polToPlot]]))
ax4.set_ylim((dTimes[0], dTimes[-1]))
ax5 = fig5.add_subplot(nRow,
nCol * nBand,
nBand * k + 1 + band,
sharey=ax5)
ax5.plot(numpy.ma.abs(vis[:, good].mean(axis=1)) * 180 / numpy.pi,
dTimes,
linestyle='',
marker='+')
ax5.set_xlabel('Mean Vis. Amp. [lin.]')
if band == 0:
ax5.set_ylabel('Elapsed Time [s]')
ax5.set_title("%i,%i - %s" %
(i, j, namMapper[polMapper[args.polToPlot]]))
ax5.set_ylim((dTimes[0], dTimes[-1]))
if band > 0:
for ax in (ax1, ax2, ax3, ax4, ax5):
plt.setp(ax.get_yticklabels(), visible=False)
if band < nBand - 1:
for ax in (ax1, ax2, ax3, ax4, ax5):
xticks = ax.xaxis.get_major_ticks()
xticks[-1].label1.set_visible(False)
k += 1
for f in (fig1, fig2, fig3, fig4, fig5):
f.suptitle(
"%s to %s UTC" %
(datetime.utcfromtimestamp(times[0]).strftime("%Y/%m/%d %H:%M"),
datetime.utcfromtimestamp(times[-1]).strftime("%Y/%m/%d %H:%M")))
if nBand > 1:
f.subplots_adjust(wspace=0.0)
plt.show()
def main(args):
# Parse the command line
## Baseline list
if args.baseline is not None:
## Fill the baseline list with the conjugates, if needed
newBaselines = []
for pair in args.baseline:
newBaselines.append( (pair[1],pair[0]) )
args.baseline.extend(newBaselines)
## Search limits
args.delay_window = [float(v) for v in args.delay_window.split(',', 1)]
args.rate_window = [float(v) for v in args.rate_window.split(',', 1)]
print("Working on '%s'" % os.path.basename(args.filename))
# Open the FITS IDI file and access the UV_DATA extension
hdulist = astrofits.open(args.filename, mode='readonly')
andata = hdulist['ANTENNA']
fqdata = hdulist['FREQUENCY']
uvdata = hdulist['UV_DATA']
# Verify we can flag this data
if uvdata.header['STK_1'] > 0:
raise RuntimeError("Cannot flag data with STK_1 = %i" % uvdata.header['STK_1'])
if uvdata.header['NO_STKD'] < 4:
raise RuntimeError("Cannot flag data with NO_STKD = %i" % uvdata.header['NO_STKD'])
# Pull out various bits of information we need to flag the file
## Antenna look-up table
antLookup = {}
for an, ai in zip(andata.data['ANNAME'], andata.data['ANTENNA_NO']):
antLookup[an] = ai
## Frequency and polarization setup
nBand, nFreq, nStk = uvdata.header['NO_BAND'], uvdata.header['NO_CHAN'], uvdata.header['NO_STKD']
## Baseline list
bls = uvdata.data['BASELINE']
## Time of each integration
obsdates = uvdata.data['DATE']
obstimes = uvdata.data['TIME']
inttimes = uvdata.data['INTTIM']
## Source list
srcs = uvdata.data['SOURCE']
## Band information
fqoffsets = fqdata.data['BANDFREQ'].ravel()
## Frequency channels
freq = (numpy.arange(nFreq)-(uvdata.header['CRPIX3']-1))*uvdata.header['CDELT3']
freq += uvdata.header['CRVAL3']
## UVW coordinates
try:
u, v, w = uvdata.data['UU'], uvdata.data['VV'], uvdata.data['WW']
except KeyError:
u, v, w = uvdata.data['UU---SIN'], uvdata.data['VV---SIN'], uvdata.data['WW---SIN']
uvw = numpy.array([u, v, w]).T
## The actual visibility data
flux = uvdata.data['FLUX'].astype(numpy.float32)
# Convert the visibilities to something that we can easily work with
nComp = flux.shape[1] // nBand // nFreq // nStk
if nComp == 2:
## Case 1) - Just real and imaginary data
flux = flux.view(numpy.complex64)
else:
## Case 2) - Real, imaginary data + weights (drop the weights)
flux = flux[:,0::nComp] + 1j*flux[:,1::nComp]
flux.shape = (flux.shape[0], nBand, nFreq, nStk)
# Find unique baselines, times, and sources to work with
ubls = numpy.unique(bls)
utimes = numpy.unique(obstimes)
usrc = numpy.unique(srcs)
# Convert times to real times
times = utcjd_to_unix(obsdates + obstimes)
times = numpy.unique(times)
# Find unique scans to work on, making sure that there are no large gaps
blocks = []
for src in usrc:
valid = numpy.where( src == srcs )[0]
blocks.append( [valid[0],valid[0]] )
for v in valid[1:]:
if v == blocks[-1][1] + 1 \
and (obsdates[v] - obsdates[blocks[-1][1]] + obstimes[v] - obstimes[blocks[-1][1]])*86400 < 10*inttimes[v]:
blocks[-1][1] = v
else:
blocks.append( [v,v] )
blocks.sort()
# Make sure the reference antenna is in there
if args.ref_ant is None:
bl = ubls[0]
ant1, ant2 = (bl>>8)&0xFF, bl&0xFF
args.ref_ant = ant1
else:
found = False
for bl in ubls:
ant1, ant2 = (bl>>8)&0xFF, bl&0xFF
if ant1 == args.ref_ant:
found = True
break
if not found:
raise RuntimeError("Cannot file reference antenna %i in the data" % args.ref_ant)
search_bls = []
cross = []
for i in xrange(len(ubls)):
bl = ubls[i]
ant1, ant2 = (bl>>8)&0xFF, bl&0xFF
if ant1 != ant2:
search_bls.append( bl )
cross.append( i )
nBL = len(cross)
iTimes = numpy.zeros(times.size-1, dtype=times.dtype)
for i in xrange(1, len(times)):
iTimes[i-1] = times[i] - times[i-1]
print(" -> Interval: %.3f +/- %.3f seconds (%.3f to %.3f seconds)" % (iTimes.mean(), iTimes.std(), iTimes.min(), iTimes.max()))
print("Number of frequency channels: %i (~%.1f Hz/channel)" % (len(freq), freq[1]-freq[0]))
dTimes = times - times[0]
dMax = 1.0/(freq[1]-freq[0])/4
dMax = int(dMax*1e6)*1e-6
if -dMax*1e6 > args.delay_window[0]:
args.delay_window[0] = -dMax*1e6
if dMax*1e6 < args.delay_window[1]:
args.delay_window[1] = dMax*1e6
rMax = 1.0/iTimes.mean()/4
rMax = int(rMax*1e2)*1e-2
if -rMax*1e3 > args.rate_window[0]:
args.rate_window[0] = -rMax*1e3
if rMax*1e3 < args.rate_window[1]:
args.rate_window[1] = rMax*1e3
dres = 1.0
nDelays = int((args.delay_window[1]-args.delay_window[0])/dres)
while nDelays < 50:
dres /= 10
nDelays = int((args.delay_window[1]-args.delay_window[0])/dres)
while nDelays > 5000:
dres *= 10
nDelays = int((args.delay_window[1]-args.delay_window[0])/dres)
nDelays += (nDelays + 1) % 2
rres = 10.0
nRates = int((args.rate_window[1]-args.rate_window[0])/rres)
while nRates < 50:
rres /= 10
nRates = int((args.rate_window[1]-args.rate_window[0])/rres)
while nRates > 5000:
rres *= 10
nRates = int((args.rate_window[1]-args.rate_window[0])/rres)
nRates += (nRates + 1) % 2
print("Searching delays %.1f to %.1f us in steps of %.2f us" % (args.delay_window[0], args.delay_window[1], dres))
print(" rates %.1f to %.1f mHz in steps of %.2f mHz" % (args.rate_window[0], args.rate_window[1], rres))
print(" ")
delay = numpy.linspace(args.delay_window[0]*1e-6, args.delay_window[1]*1e-6, nDelays) # s
drate = numpy.linspace(args.rate_window[0]*1e-3, args.rate_window[1]*1e-3, nRates ) # Hz
# Find RFI and trim it out. This is done by computing average visibility
# amplitudes (a "spectrum") and running a median filter in frequency to extract
# the bandpass. After the spectrum has been bandpassed, 3sigma features are
# trimmed. Additionally, area where the bandpass fall below 10% of its mean
# value are also masked.
spec = numpy.median(numpy.abs(flux[:,0,:,0]), axis=0)
spec += numpy.median(numpy.abs(flux[:,0,:,1]), axis=0)
smth = spec*0.0
winSize = int(250e3/(freq[1]-freq[0]))
winSize += ((winSize+1)%2)
for i in xrange(smth.size):
mn = max([0, i-winSize//2])
mx = min([i+winSize//2+1, smth.size])
smth[i] = numpy.median(spec[mn:mx])
smth /= robust.mean(smth)
bp = spec / smth
good = numpy.where( (smth > 0.1) & (numpy.abs(bp-robust.mean(bp)) < 3*robust.std(bp)) )[0]
nBad = nFreq - len(good)
print("Masking %i of %i channels (%.1f%%)" % (nBad, nFreq, 100.0*nBad/nFreq))
if args.plot:
fig = plt.figure()
ax = fig.gca()
ax.plot(freq/1e6, numpy.log10(spec)*10)
ax.plot(freq[good]/1e6, numpy.log10(spec[good])*10)
ax.set_title('Mean Visibility Amplitude')
ax.set_xlabel('Frequency [MHz]')
ax.set_ylabel('PSD [arb. dB]')
plt.draw()
freq2 = freq*1.0
freq2.shape += (1,)
dTimes2 = dTimes*1.0
dTimes2.shape += (1,)
# NOTE: Assumed linear data
polMapper = {'XX':0, 'YY':1, 'XY':2, 'YX':3}
print("%3s %9s %2s %6s %9s %11s" % ('#', 'BL', 'Pl', 'S/N', 'Delay', 'Rate'))
for b in xrange(len(search_bls)):
bl = search_bls[b]
ant1, ant2 = (bl>>8)&0xFF, bl&0xFF
## Skip over baselines that are not in the baseline list (if provided)
if args.baseline is not None:
if (ant1, ant2) not in args.baseline:
continue
## Skip over baselines that don't include the reference antenna
elif ant1 != args.ref_ant and ant2 != args.ref_ant:
continue
## Check and see if we need to conjugate the visibility, i.e., switch from
## baseline (*,ref) to baseline (ref,*)
doConj = False
if ant2 == args.ref_ant:
doConj = True
## Figure out which polarizations to process
if ant1 not in (51, 52) and ant2 not in (51, 52):
### Standard VLA-VLA baseline
polToUse = ('XX', 'YY')
else:
### LWA-LWA or LWA-VLA baseline
if args.y_only:
polToUse = ('YX', 'YY')
else:
polToUse = ('XX', 'XY', 'YX', 'YY')
if args.plot:
fig = plt.figure()
axs = {}
axs['XX'] = fig.add_subplot(2, 2, 1)
axs['YY'] = fig.add_subplot(2, 2, 2)
axs['XY'] = fig.add_subplot(2, 2, 3)
axs['YX'] = fig.add_subplot(2, 2, 4)
valid = numpy.where( bls == bl )[0]
for pol in polToUse:
subData = flux[valid,0,:,polMapper[pol]]*1.0
subData = subData[:,good]
if doConj:
subData = subData.conj()
subData = numpy.dot(subData, numpy.exp(-2j*numpy.pi*freq2[good,:]*delay))
subData /= freq2[good,:].size
amp = numpy.dot(subData.T, numpy.exp(-2j*numpy.pi*dTimes2*drate))
amp = numpy.abs(amp / dTimes2.size)
blName = (ant1, ant2)
if doConj:
blName = (ant2, ant1)
blName = '%s-%s' % ('EA%02i' % blName[0] if blName[0] < 51 else 'LWA%i' % (blName[0]-50),
'EA%02i' % blName[1] if blName[1] < 51 else 'LWA%i' % (blName[1]-50))
best = numpy.where( amp == amp.max() )
if amp.max() > 0:
bsnr = (amp[best]-amp.mean())[0]/amp.std()
bdly = delay[best[0][0]]*1e6
brat = drate[best[1][0]]*1e3
print("%3i %9s %2s %6.2f %6.2f us %7.2f mHz" % (b, blName, pol, bsnr, bdly, brat))
else:
print("%3i %9s %2s %6s %9s %11s" % (b, blName, pol, '----', '----', '----'))
if args.plot:
axs[pol].imshow(amp, origin='lower', interpolation='nearest',
extent=(drate[0]*1e3, drate[-1]*1e3, delay[0]*1e6, delay[-1]*1e6),
cmap='gray_r')
axs[pol].plot(drate[best[1][0]]*1e3, delay[best[0][0]]*1e6, linestyle='', marker='x', color='r', ms=15, alpha=0.75)
if args.plot:
fig.suptitle(os.path.basename(args.filename))
for pol in axs.keys():
ax = axs[pol]
ax.axis('auto')
ax.set_title(pol)
ax.set_xlabel('Rate [mHz]')
ax.set_ylabel('Delay [$\\mu$s]')
fig.suptitle("%s" % blName)
plt.draw()
if args.plot:
plt.show()
def utc_dp(self):
return int(astro.utcjd_to_unix(self.utc_jd) * fS)
