Ejemplo n.º 1
0
					#Notes:
					#scan numbers (zero-based) as compared to GBTIDL

					#changes made to get to IRC+10216_rawACSmod
					#  -- merge spectral windows with tolerance


s = sd.scantable('IRC+10216_rawACSmod', False)#load the data without averaging		# filein,'IRC.raw.fits'
#Cannot find any matching Tcal at/near the data timestamp. Set Tcal=0.0

#s.summary()				#summary info					# summary
											# fileout,'IRC+10216.reduced.fits'
s.set_fluxunit('K')         		# make 'K' default unit

#scal = sd.calnod(s, [236,237,238,239,248,249,250,251])	# Calibrate HC3N scans		# for i=237,240,2 do begin getps,i,ifnum=0,plnum=0,units='Ta*',
scal = sd.calnod(s, [237,238,239,240,249,250,251,252])	# Calibrate HC3N scans		# for i=237,240,2 do begin getps,i,ifnum=0,plnum=0,units='Ta*',
del s                                   # remove s from memory
# recalculate az/el (NOT needed for GBT data)
antennaname = scal.get_antennaname()
if ( antennaname != 'GBT'): scal.recalc_azel()      # recalculate az/el to 		# tau=0.09 & accum & getps, i, ifnum=0,plnum=1,units='Ta*',
scal.opacity(0.09)			# do opacity correction				# tau=0.09 & accum & end & ave
sel = sd.selector()			# Prepare a selection				# copy,0,9
sel.set_ifs(17)				# select HC3N IF				# for i=250,252,2 do begin getps,i,ifnum=0,plnum=0,units='Ta*',
scal.set_selection(sel)			# get this IF					# tau=0.09 & accum & getps, i, ifnum=0,plnum=1,units='Ta*',
stave = sd.average_time(scal, weight='tintsys')	# average in time			# tau=0.09 & accum & end & ave
spave = stave.average_pol(weight='tsys')	# average polarizations;Tsys-weighted average   # accum
sd.plotter.plot(spave)			# plot						# copy,9,0
											# accum
					# do some smoothing
spave.smooth('boxcar', 5)		# boxcar 5					# boxcar,5
spave.auto_poly_baseline(order=2, threshold=5, chan_avg_limit=4)	# baseline fit order=2	# nfit,2
Ejemplo n.º 2
0
					#Notes:
					#scan numbers (zero-based) as compared to GBTIDL

					#changes made to get to IRC+10216_rawACSmod
					#  -- merge spectral windows with tolerance


s = sd.scantable('IRC+10216_rawACSmod', False)#load the data without averaging		# filein,'IRC.raw.fits'
#Cannot find any matching Tcal at/near the data timestamp. Set Tcal=0.0

#s.summary()				#summary info					# summary
											# fileout,'IRC+10216.reduced.fits'
s.set_fluxunit('K')         		# make 'K' default unit

#scal = sd.calnod(s, [229,230])		# Calibrate CS scans	                        # for i=230,231,2 do begin getps,i,ifnum=3,plnum=0,units='Ta*',
scal = sd.calnod(s, [230, 231])		# Calibrate CS scans	                        # for i=230,231,2 do begin getps,i,ifnum=3,plnum=0,units='Ta*',
del s                                   # remove s from memory
# recalculate az/el (NOT needed for GBT data)
antennaname = scal.get_antennaname()
if ( antennaname != 'GBT'): scal.recalc_azel() 	  # recalculate az/el to 		# tau=0.09 & accum & getps, i, ifnum=3,plnum=1,units='Ta*',
scal.opacity(0.09)			# do opacity correction				# tau=0.09 & accum & end & ave
sel = sd.selector()			# Prepare a selection				# 
sel.set_ifs(3)				# select CS IF					#
scal.set_selection(sel)			# get this IF					#
stave = sd.average_time(scal, weight='tintsys')	# average in time			# 
spave = stave.average_pol(weight='tsys')	# average polarizations;Tsys-weighted average   #
sd.plotter.plot(spave)			# plot						# 
											# 
					# do some smoothing				# 
spave.smooth('boxcar', 5)		# boxcar 5					# boxcar,5
spave.auto_poly_baseline(order=1, threshold=5, chan_avg_limit=4)	# baseline fit order=2	# nregion,[200,1500,2600,3500]
Ejemplo n.º 3
0
#changes made to get to IRC+10216_rawACSmod
#  -- merge spectral windows with tolerance

s = sd.scantable(
    'IRC+10216_rawACSmod',
    False)  #load the data without averaging		# filein,'IRC.raw.fits'
#Cannot find any matching Tcal at/near the data timestamp. Set Tcal=0.0

#s.summary()				#summary info					# summary
# fileout,'IRC+10216.reduced.fits'
s.set_fluxunit('K')  # make 'K' default unit

#scal = sd.calnod(s, [229,230])		# Calibrate CS scans	                        # for i=230,231,2 do begin getps,i,ifnum=3,plnum=0,units='Ta*',
scal = sd.calnod(
    s, [230, 231]
)  # Calibrate CS scans	                        # for i=230,231,2 do begin getps,i,ifnum=3,plnum=0,units='Ta*',
del s  # remove s from memory
# recalculate az/el (NOT needed for GBT data)
antennaname = scal.get_antennaname()
if (antennaname != 'GBT'):
    scal.recalc_azel(
    )  # recalculate az/el to 		# tau=0.09 & accum & getps, i, ifnum=3,plnum=1,units='Ta*',
scal.opacity(0.09)  # do opacity correction				# tau=0.09 & accum & end & ave
sel = sd.selector()  # Prepare a selection				#
sel.set_ifs(3)  # select CS IF					#
scal.set_selection(sel)  # get this IF					#
stave = sd.average_time(scal, weight='tintsys')  # average in time			#
spave = stave.average_pol(
    weight='tsys')  # average polarizations;Tsys-weighted average   #
sd.plotter.plot(spave)  # plot						#
Ejemplo n.º 4
0
					#Notes:
					#scan numbers (zero-based) as compared to GBTIDL

					#changes made to get to IRC+10216_rawACSmod
					#  -- merge spectral windows with tolerance


s = sd.scantable('IRC+10216_rawACSmod', False)#load the data without averaging		# filein,'IRC.raw.fits'
#Cannot find any matching Tcal at/near the data timestamp. Set Tcal=0.0

#s.summary()				#summary info					# summary
											# fileout,'IRC+10216.reduced.fits'
s.set_fluxunit('K')         		# make 'K' default unit

#scal = sd.calnod(s, [240,241,242,243,244,245,246,247])	# Calibrate SiO scans		# for i=241,248,2 do begin getps,i,ifnum=0,plnum=0,units='Ta*',
scal = sd.calnod(s, [241,242,243,244,245,246,247,248])	# Calibrate SiO scans		# for i=241,248,2 do begin getps,i,ifnum=0,plnum=0,units='Ta*',
del s                                   # remove s from memory
# recalculate az/el (NOT needed for GBT data)
antennaname = scal.get_antennaname()
if ( antennaname != 'GBT'): scal.recalc_azel()      # recalculate az/el to 		# tau=0.09 & accum & getps, i, ifnum=0,plnum=1,units='Ta*',
scal.opacity(0.09)			# do opacity correction				# tau=0.09 & accum & end & ave
sel = sd.selector()			# Prepare a selection				# 
sel.set_ifs(30)				# select SiO IF					#
scal.set_selection(sel)			# get this IF					#
stave = sd.average_time(scal, weight='tintsys')	# average in time			# 
spave = stave.average_pol(weight='tsys')	# average polarizations;Tsys-weighted average   #
sd.plotter.plot(spave)			# plot						# 
											# 
					# do some smoothing
spave.smooth('boxcar', 5)		# boxcar 5					# boxcar,5
spave.auto_poly_baseline(order=1, threshold=5, chan_avg_limit=4)	# baseline fit order=2	# nregion,[200,1500,2600,3500]