def superaverage(*args):
"""
Average the scans in the designated tables
The arguments may be a comma-separated supertable sequence or a list
of supertables
"""
supertables = get_supertables(args)
if supertables:
mylogger.debug("Calling asap.average_time for %s", str(supertables))
new_scantable = average_time(supertables)
mylogger.debug("New scantable is %s", str(new_scantable))
if new_scantable:
supertab = attach_hdu(supertables, new_scantable)
mylogger.debug("New supertable is %s", str(supertab))
return supertab
return None
#s.summary() #summary info # summary
# fileout,'Orion-S-reduced.fits'
s.set_fluxunit('K') # make 'K' default unit
#scal = sd.calps(s, [20,21,22,23]) # Calibrate CH3OH scans # for i=21,24,2 do begin getps,i,ifnum=2,plnum=0,units='Ta*',
scal = sd.calps(s, [21,22,23,24]) # Calibrate CH3OH scans # for i=21,24,2 do begin getps,i,ifnum=2,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=2,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(2) # select CH3OH 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 (1/Tsys**2) average
sd.plotter.plot(spave) # plot
# what is going on with autoscaling?
# do some smoothing
spave.smooth('boxcar', 10) # boxcar 10 # boxcar,10
#spave.auto_poly_baseline(order=5) # baseline fit order=5 # nfit,5
# you can also set the baseline region or
basemask = spave.create_mask([350,2700],[3500,7500]) # nregion,[500,3500,5000,7500]
spave.poly_baseline(basemask, order=5) # nfit,5
sd.plotter.plot(spave) # plot # baseline
spave.set_unit('GHz') # freq
sd.plotter.plot(spave)
#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
sd.plotter.plot(spave) # plot # baseline
spave.set_unit('GHz') # freq
sd.plotter.plot(spave)
sd.plotter.set_histogram(hist=True) # draw spectrum using histogram # histogram
sd.plotter.axhline(color='r', linewidth=2) # zline # zline
sd.plotter.save('irc_hc3n_reduced.eps') # save postscript spectrum # write_ps,'irc_hc3n.ps'
spave.set_unit('channel') # chan
#scal = sd.calps(s, [20,21,22,23]) # Calibrate CH3OH scans # for i=21,24,2 do begin getps,i,ifnum=2,plnum=0,units='Ta*',
scal = sd.calps(
s, [21, 22, 23, 24]
) # Calibrate CH3OH scans # for i=21,24,2 do begin getps,i,ifnum=2,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=2,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(2) # select CH3OH 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 (1/Tsys**2) average
sd.plotter.plot(spave) # plot
# what is going on with autoscaling?
# do some smoothing
spave.smooth('boxcar', 10) # boxcar 10 # boxcar,10
#spave.auto_poly_baseline(order=5) # baseline fit order=5 # nfit,5
# you can also set the baseline region or
basemask = spave.create_mask([350, 2700],
[3500, 7500]) # nregion,[500,3500,5000,7500]
spave.poly_baseline(basemask, order=5) # nfit,5
sd.plotter.plot(spave) # plot # baseline
# scal = sd.calps(s, [20,21,22,23]) # Calibrate HC3N scans # for i=21,24,2 do begin getps,i,ifnum=0,plnum=0,units='Ta*',
scal = sd.calps(
s, [21, 22, 23, 24]
) # Calibrate HC3N scans # for i=21,24,2 do begin getps,i,ifnum=0,plnum=0,units='Ta*',
#
del s # remove s from memory
antennaname = scal.get_antennaname()
# recalculate az/el (NOT needed for GBT data)
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(0) # select HC3N 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 (1/Tsys**2) average
sd.plotter.plot(spave) # plot
# what is going on with autoscaling?
# do some smoothing
spave.smooth("boxcar", 5) # boxcar 5 # boxcar,5
spave.auto_poly_baseline(
edge=[50], order=2, threshold=5, chan_avg_limit=4
) # baseline fit order=2 # chan & nregion,[500,3000,5000,7500] & nfit,2
sd.plotter.plot(spave) # plot # baseline
spave.set_unit("GHz") # freq
sd.plotter.plot(spave)
sd.plotter.set_histogram(hist=True) # draw spectrum using histogram # histogram
