View source for EVLA Spectral Line Calibration IRC+10216

[[Category:EVLA]][[Category:Calibration]][[Category:Spectral Line]]


<pre style="background-color: #FFFF00;">
This tutorial is under construction. There are several things still to be added 

For the time being (until release candidate is built) you want to run this on casapy-test

</pre>

== Overview ==
This tutorial describes the data reduction for two spectral lines observed toward the AGB star IRC+10216. This carbon star, which is a few times more massive than our sun, is nearing the end of its life and is thought to be in the process of forming a planetary nebula. 

In this EVLA OSRO1 mode observation one subband was observed in each of two basebands, the subbands were centered on the HC3N and SiS lines near 36 GHz. The raw data were loaded into CASA with [[importevla]], where zero and shadowed data were flagged. Then the data were "[[split]]", so we could average from the native 1 second integrations to 10 seconds, select only antennas with Ka-band receivers, and select only spectral windows (called spw in CASA) with Ka-band data. This produces a significantly smaller dataset for processing.

The post-split averaged data can be downloaded from http://casa.nrao.edu/Data/EVLA/IRC10216/day2_TDEM0003_10s_norx.tar

== The Observing Log, Antenna Position Corrections, and other Calibration "Priors"==

For all EVLA observations, the operators keep an observing log. You can look at
the observing logs at the observing log [[http://www.vla.nrao.edu/cgi-bin/oplogs.cgi website]]. Pertinent information from this observation are repeated below. 
<pre style="background-color: #E0FFFF;">
INFORMATION FROM OBSERVING LOG:
Date of the observation: 26-April-2010
There are no Ka-band receivers on ea11, ea13, ea14, ea16, ea17, ea18, ea26  
Antennas ea10, ea06 are out of the array
Antenna ea12 is newly back
The pointing is often bad on ea15
Antennas ea10, ea12, ea22 do not have good baseline positions
</pre>

As mentioned in the log, antennas ea10, ea12, and ea22 do not have good baseline positions.
Antenna ea10 was not in the array, but for the other two antennas we need to check for
any improved baseline positions that were derived after the observations were taken.

In CASA, we need to insert these corrections by hand using '''[[gencal]]'''. The resulting table will need to be supplied as a "prior" calibration to all subsequent calibration steps. The corrections can be ascertained from the [http://www.vla.nrao.edu/astro/archive/baselines/ EVLA/VLA Baseline Corrections page]. Be sure to carefully read to the bottom of that 
webpage to see how to calculate the additive corrections. The current case is simple as there is only a single correction for each antenna. In the future we will implement an automated lookup of the corrections. 

<source lang="python">
# In CASA
gencal(vis='day2_TDEM0003_10s_norx',caltable='antpos.cal',
       caltype='antpos',
       antenna='ea12,ea22',
       parameter=[-0.0072,0.0045,-0.0017, -0.0220,0.0040,-0.0190])
</source>

'''Please note: '''if you are reducing VLA data taken before March 1, 2010, you need to set caltype='antposvla'.



There are two other types of "priors" that we will need to apply at each calibration stage described below:

(1) Opacity correction -- in the near future the opacity will be calculated from the weather
data and an atmospheric model, or alternatively from a tipping scan, or a combination of
both. For now we use a cannonical value for the zenith opacity based on the weather on that day, which at this
frequency (36 GHz) is about 0.03 on the best days. We will use a zenith opacity of <math>tau_z</math>=0.04. The zenith opacity is then corrected for 
the elevation of the data automatically using <math> e^{[-cosec(el)tau_z]}</math>.

(2) Gaincurve -- the gaincurve describes how each antenna behaves as a function of elevation, for each receiver band.

==Initial Inspection and Flagging==

<source lang="python">
# In CASA
listobs(vis='day2_TDEM0003_10s_norx')
</source>

Below we have cut and pasted the most relevant output from the logger.

<pre style="background-color: #fffacd;">
Fields: 4
  ID   Code Name         RA            Decl           Epoch   SrcId nVis   
  2    D    J0954+1743   09:54:56.8236 +17.43.31.2224 J2000   2     65326  
  3    NONE IRC+10216    09:47:57.3820 +13.16.40.6600 J2000   3     208242 
  5    F    J1229+0203   12:29:06.6997 +02.03.08.5982 J2000   5     10836  
  7    E    J1331+3030   13:31:08.2880 +30.30.32.9589 J2000   7     5814   
   (nVis = Total number of time/baseline visibilities per field) 
Spectral Windows:  (2 unique spectral windows and 1 unique polarization setups)
  SpwID  #Chans Frame Ch1(MHz)    ChanWid(kHz)TotBW(kHz)  Ref(MHz)    Corrs           
  0          64 TOPO  36387.2295  125         8000        36387.2295  RR  RL  LR  LL  
  1          64 TOPO  36304.542   125         8000        36304.542   RR  RL  LR  LL  
Sources: 10
  ID   Name         SpwId RestFreq(MHz)  SysVel(km/s) 
  0    J1008+0730   0     0.03639232     -0.026       
  0    J1008+0730   1     0.03639232     -0.026       
  2    J0954+1743   0     0.03639232     -0.026       
  2    J0954+1743   1     0.03639232     -0.026       
  3    IRC+10216    0     0.03639232     -0.026       
  3    IRC+10216    1     0.03639232     -0.026       
  5    J1229+0203   0     0.03639232     -0.026       
  5    J1229+0203   1     0.03639232     -0.026       
  7    J1331+3030   0     0.03639232     -0.026       
  7    J1331+3030   1     0.03639232     -0.026       
Antennas: 19:
  ID   Name  Station   Diam.    Long.         Lat.         
  0    ea01  W09       25.0 m   -107.37.25.2  +33.53.51.0  
  1    ea02  E02       25.0 m   -107.37.04.4  +33.54.01.1  
  2    ea03  E09       25.0 m   -107.36.45.1  +33.53.53.6  
  3    ea04  W01       25.0 m   -107.37.05.9  +33.54.00.5  
  4    ea05  W08       25.0 m   -107.37.21.6  +33.53.53.0  
  5    ea07  N06       25.0 m   -107.37.06.9  +33.54.10.3  
  6    ea08  N01       25.0 m   -107.37.06.0  +33.54.01.8  
  7    ea09  E06       25.0 m   -107.36.55.6  +33.53.57.7  
  8    ea12  E08       25.0 m   -107.36.48.9  +33.53.55.1  
  9    ea15  W06       25.0 m   -107.37.15.6  +33.53.56.4  
  10   ea19  W04       25.0 m   -107.37.10.8  +33.53.59.1  
  11   ea20  N05       25.0 m   -107.37.06.7  +33.54.08.0  
  12   ea21  E01       25.0 m   -107.37.05.7  +33.53.59.2  
  13   ea22  N04       25.0 m   -107.37.06.5  +33.54.06.1  
  14   ea23  E07       25.0 m   -107.36.52.4  +33.53.56.5  
  15   ea24  W05       25.0 m   -107.37.13.0  +33.53.57.8  
  16   ea25  N02       25.0 m   -107.37.06.2  +33.54.03.5  
  17   ea27  E03       25.0 m   -107.37.02.8  +33.54.00.5  
  18   ea28  N08       25.0 m   -107.37.07.5  +33.54.15.8  
</pre>

<pre style="background-color: #E0FFFF;">
Summary of Observing Strategy
Gain Calibrator: J0954+1743 field id=2
Bandpass Calibrator: J1229+0203   field id=5
Flux Calibrator: J1331+3030 (3C286) field id=7
Target: IRC+10216  field id=3
Ka-band spws = 0,1
</pre> 

[[Image:Ant_locations.png|thumb|Antenna locations from running plotants ]]
Look at a graphical plot of the antenna locations and save hardcopy
in case you want it later. This will be useful for picking a reference antenna --
typically a good choice is an antenna close to the center of the array. Unless it 
shows problems after inspection of the data, we provisionally chose ea02.

[[Image:elevationvstime.png|thumb|Elevation as a function of time (after selecting colorize by field).]]
<source lang="python">
# In CASA
plotants(vis='day2_TDEM0003_10s_norx',figfile='ant_locations.png')
</source>

Next, let's look at the elevation as a function of time for all sources. It's not the case for these data, but if the elevation is very low (usually at start or end of track) you may want to flag. Also, how near in elevation your flux calibrator is to your target will impact your ultimate absolute flux calibration accuracy. Unfortunately, the target and flux calibrator are not particularly well-matched for this observation, as y ou can show by plotting the elevation for each source:

 

<source lang="python">
# In CASA
plotms(vis='day2_TDEM0003_10s_norx',
       xaxis='time',yaxis='elevation',correlation='RR,LL',
       avgchannel='64',spw='0:4~60')
</source>

Thus we are strongly dependent on the opacity and gaincurve corrections to get the flux scale right for these data. (This is something to keep in mind when planning observations!)

[[Image:plotallfields.png|thumb|Result of plotms after selecting colorize by field]]
[[Image:Zoom1_mark.png|thumb|Zooming in and marking region (hatched box)]]

Next,let's look at all the source amplitudes as a function of time.
<source lang="python">
# In CASA
plotms(vis='day2_TDEM0003_10s_norx',
       xaxis='time',yaxis='amp',correlation='RR,LL',
       avgchannel='64',spw='0:4~60')
</source>

Select the "Display" tab and colorize by field, and click Plot button. 


Now zoom in on the region very near zero amplitude for sources J0954+1743 and IRC+10216. To zoom, select the 
Zoom tool in lower left corner of  the [[plotms]] GUI, then you can left click to draw a box. 
Look for the low values (you may want to zoom a few times to really see the suspect points clearly). Now use the Mark Region and Locate buttons (located along the bottom of the GUI) to see which antenna is causing problems. Since all the "located" baselines include ea12, this is the responsible antenna.

<pre style="background-color: #98FB98;">
IMPORTANT NOTES ON PLOTMS:

* When using the locate button it is important to have only selected a modest number 
of points with the mark region tool (see example of marked region in the thumnail), 
otherwise the response will be very slow and possibly hang the tool 
(all of the information will be output to your terminal window, not the logger). 

* Throughout the tutorial, when you are done marking/locate use the Clear Regions 
tool to get rid of the marked box before plotting other things. 

* After flagdata command flagging, you have to force a complete reload of the cache 
to look at the same plot again with the new flags applied. To do this change anything 
in the plotms GUI (the colorize parameter, antenna, spw, anything) and hit the 
plot button.

* If the plotms tool does get hung during a plot try clicking the cancel button on the 
load progress GUI, and/or if you see a "table locked" message try typing 
clearstat on the CASA command line.

* Occasionally plotms will get into a strange state that you cannot clear from inside. 
We are working on these issues, but for now, when all else fails, exit from casapy and 
restart.  

</pre> 

Now click the unmark region button, and then go back to the zoom button to zoom in further to note exactly what the time range is: 03:41:00~04:10:00.

Check the other sideband by changing spw to 1:4~60. You will have to
rezoom. If you have trouble, click on the Mark icon and then back to
zoom.  In spw=1, ea07 is bad from the beginning until after next
pointing run: 03:21:40~04:10:00.  To see this, compare the amplitudes when antenna is set to 'ea07' and when it is set to one of the other antennas, such as 'ea08'.

If you set antenna to 'ea12' and zoom in on this intial timerange, you can also see that ea12 is bad during the same time range as for spw 0.  You can also see this by entering '!ea07' for antenna, which removes ea07 from the plot (in CASA selection, ! deselects). 

We can set up a flagging command to get both bad antennas for the
appropriate time and spw:

<source lang="python">
# In CASA
flagdata(vis='day2_TDEM0003_10s_norx',
         field=['2,3','2,3'],
         spw=['','1'],
         antenna=['ea12','ea07'],
         timerange=['03:41:00~04:10:00','03:21:40~04:10:00'])
</source>

Note that because  the chosen timerange is limited to fields 2 and 3,the field parameter is not really
needed; however, flagdata will run fastest if you put as many constraints as possible.

Now remove the !ea07 from antenna and replot both spw, zooming in to
be sure that all obviously low points are gone. Also zoom in and
check 3C286 (J1229+0203 is already obvious because it is so bright!). 

[[Image:IRC10216_uvdist1.png|thumb|Amplitude vs. uv-distance for IRC+10216, both spw (after colorize by spw)]]

Lets look more closely at IRC+10216:

<source lang="python">
# In CASA
plotms(vis='day2_TDEM0003_10s_norx',field='3',
       xaxis='time',yaxis='amp',correlation='RR,LL',
       avgchannel='64',spw='0~1:4~60')
</source>

Go to the "display" tab and choose colorize by spw. You can see a
that there are some noisy high points. But now try

<source lang="python">
# In CASA
plotms(vis='day2_TDEM0003_10s_norx',field='3',
       xaxis='uvdist',yaxis='amp',correlation='RR,LL',
       avgchannel='64',spw='0~1:4~60')
</source>

Most of the high points on IRC+10216 are due to large scale emission on short baselines, but there is still some noisy stuff -- for a target like this with extended emission its best to wait until later to decide what to do about it. We will not be able to get adequate calibration for antennas that are truly bad (even if they don't stand out here) so these will be obvious later.

==Set the Flux Calibrator==

Next, we tell CASA to look up the appropriate fluxes for 3C286:

<source lang="python">
# In CASA
setjy(vis='day2_TDEM0003_10s_norx',field='7',spw='0~1',
      modimage='/usr/lib64/casapy/data/nrao/VLA/CalModels/3C286_K.im')
</source>

<pre style="background-color: #fffacd;">
The logger output for each spw is:
setjy	  J1331+3030  spwid=  0  [I=1.692, Q=0, U=0, V=0] Jy, (Perley-Taylor 99)
setjy	  J1331+3030  spwid=  1  [I=1.695, Q=0, U=0, V=0] Jy, (Perley-Taylor 99)
</pre>

The modimage location is appropriate for running CASA at the AOC. If you are running elsewhere (laptop or Mac), in a terminal type

<source lang='bash'>
# in a terminal, outside of CASA:
locate 3C286_K.im 
</source>

to find where the models live (the models are always shipped with CASA).

==Bandpass==

Before determining the bandpass solution, we need to inspect phase and amplitude
variations with time and frequency on the bandpass calibrator to
decide how best to proceed. We limit the number of antennas to make
the plot easier to see. We chose ea02 as it seems like a good
candidate for the reference antenna.

<source lang="python">
# In CASA
plotms(vis='day2_TDEM0003_10s_norx',field='5',
       xaxis='channel',yaxis='phase',correlation='RR',
       avgtime='1e8',spw='0:4~60',antenna='ea02&ea23')
</source>
[[Image:Nobandpass_phase.png|thumb|Phase as a function of channel for ea02 (after colorize by Antenna2, and Custom and upping "Style" to 3.)]]
The phase variation is modest ~10 degrees.  Now expand to all antennas with ea02 and 
select colorize by Antenna2, then hit the "Plot" button.

<source lang="python">
# In CASA
plotms(vis='day2_TDEM0003_10s_norx',field='5',
       xaxis='channel',yaxis='phase',correlation='RR',
       avgtime='1e8',spw='0:4~60',antenna='ea02')
</source>
[[Image:Nobandpass_phasetime.png|thumb|Phase as a function of time for all baselines with antenna ea02 (after colorize by Antenna2, and Custom and upping "Style" to 3.)]]
Go to the "display" tab and chose colorize by antenna2. From this
you can see that the phase variation across the bandpass is
modest. Next check LL, and spw=1, both correlations. Also check
other antennas if you like.

Now look at the phase as a function of time.

<source lang="python">
# In CASA
plotms(vis='day2_TDEM0003_10s_norx',field='5',
       xaxis='time',yaxis='phase',correlation='RR',
       avgchannel='64',spw='0:4~60',antenna='ea02&ea23')
</source>


Expand to all antennas with ea02

<source lang="python">
# In CASA
plotms(vis='day2_TDEM0003_10s_norx',field='5',
       xaxis='time',yaxis='phase',correlation='RR',
       avgchannel='64',spw='0:4~60',antenna='ea02')
</source>

You can see that the phase variations are smooth, but do vary
significantly over the 5 minutes of observation -- in most cases by
a few 10s of degrees. Zoom in to see this better if you want.

The conclusion from this investigation is that you need to correct
the phase variations with time before solving for the bandpass to
prevent decorrelation of the vector averaged bandpass
solution. Since the phase variation as a function of channel is
modest, you can average over several channels to increase the signal
to noise of the phase vs. time solution. If the phase variation as a
function of channel is larger you may need to use only a few
channels to prevent introducing delay-based closure errors as can happen from averaging over
non-bandpass corrected channels with large phase variations.


Since the bandpass calibrator is quite strong we do the phase-only
solution on the integration time of 10 seconds (solint='int').

[[Image:Prebp_phasecal2.png|thumb|Phase only calibration before bandpass. The 4 lines are both polarizations in both spw, unfortunately two of them get the same color green at the moment.]]
<source lang="python">
# In CASA
gaincal(vis='day2_TDEM0003_10s_norx',caltable='bpphase.gcal',
        field='5',spw='0~1:20~40',
        refant='ea02',calmode='p',solint='int',minsnr=2.0,
        gaintable=['antpos.cal'],spwmap=[[]],
        opacity=0.04,gaincurve=T)
</source>

Plot the solutions

<source lang="python">
# In CASA
plotcal(caltable='bpphase.gcal',xaxis='time',yaxis='phase',
        iteration='antenna',subplot=331,plotrange=[0,0,-180,180])
</source>

After the first set of plots appear, push the "Next" button on the 
GUI to see the next set of antennas.

Next we can apply this phase solution on the fly while determining
the bandpass solutions on the timescale of the bandpass calibrator scan (solint='inf'). 

[[Image:Bandpass_amp.png|thumb|Amplitude Bandpass solutions]]
[[Image:Bandpass_phase1.png|thumb|Phase Bandpass solutions]]

<source lang="python">
# In CASA
bandpass(vis='day2_TDEM0003_10s_norx',caltable='bandpass.bcal',field='5',
        refant='ea02',solint='inf',solnorm=T,
        gaintable=['antpos.cal','bpphase.gcal'],spwmap=[[]],
        opacity=0.04,gaincurve=T)
</source>

'''A few words about solint and combine:'''

The use of  solint='inf' in [[bandpass]] will derive one bandpass
solution for the whole J1229+0203 scan. Note that if there had been two observations of the bandpass calibrator (for example), this command would have combined the data from both scans to form one bandpass solution, because the default of the combine parameter '''for [[bandpass]]''' is combine='scan'. To solve for one bandpass for each bandpass calibrator scan you would also need to include combine='''' '''' in the bandpass call. In all calibration tasks, regardless of solint, scan boundaries are only crossed when combine='scan'. Likewise, field (spw) boundaries are only crossed if combine='field' (combine='spw'), the latter two are not generally good ideas for bandpass solutions.  

Plot the solutions, amplitude and phase:

<source lang="python">
# In CASA
plotcal(caltable='bandpass.bcal',xaxis='chan',yaxis='amp',
        iteration='antenna',subplot=331)
</source>

<source lang="python">
# In CASA
plotcal(caltable='bandpass.bcal',xaxis='chan',yaxis='phase',
        iteration='antenna',subplot=331)
</source>

Note that phases on ea12 look noiser than on other antennas. This
jitter could indicate bad pointing; note that ea12 had just come back in
the array.

This step isn't necessary from a calibration perspective, but if you
want to go ahead and check the bandpass calibration on the bandpass
calibrator you can run applycal here. In future we hope to plot
corrected data on-the-fly without this applycal step. Later applycals
will overwrite this one, so no need to worry.

[[Image:Applybandpass_phase.png|thumb|Phase as a function of channel, plotting the corrected data (after colorize by Antenna2, and Custom and upping "Style" to 3.)]]

<source lang="python">
applycal(vis='day2_TDEM0003_10s_norx',field='5',
        gaintable=['antpos.cal','bandpass.bcal'],
        spwmap=[[]],gainfield=['','5'],
        opacity=0.04,gaincurve=T)
</source>

<source lang="python">
plotms(vis='day2_TDEM0003_10s_norx',field='5',
       xaxis='channel',yaxis='phase',ydatacolumn='corrected',
       correlation='RR',
       avgtime='1e8',spw='0:4~60',antenna='ea02')
</source>

<source lang="python">
plotms(vis='day2_TDEM0003_10s_norx',field='5',
       xaxis='channel',yaxis='amp',ydatacolumn='corrected',
       correlation='RR',
       avgtime='1e8',spw='0:4~60',antenna='ea02')
</source>

Note that the phase and amplitude as a function of channel are very flat now.

==Gain Calibration==

Now that we have a bandpass solution to apply we can solve for the antenna-based phase and amplitude gain calibration. Since the phase changes on a much shorter timescale than the amplitude, we will solve for them separately. In particular, if the phase changes significantly over a scan time, the amplitude would be decorrelated, if the un-corrected phase were averaged over this timescale. Note that we re-solve for the gain solutions of the bandpass calibrator, so we can derive new solutions that are corrected for the bandpass shape. Since the bandpass calibrator will not be used again, this is not strictly necessary, but is useful to check its calibrated flux density for example.

<source lang="python">
# In CASA
gaincal(vis='day2_TDEM0003_10s_norx',caltable='intphase.gcal',
        field='2,5,7',spw='0~1:4~60',
        refant='ea02',calmode='p',solint='int',minsnr=2.0,
        gaintable=['antpos.cal','bandpass.bcal'],spwmap=[[]],
        opacity=0.04,gaincurve=T)
</source>
[[Image:allcal_phaseint2.png|thumb|Plot of phase solutions on an integration time.]]

Here solint='int' coupled with calmode='p' will derive a single phase solution for each 10 second integration. Note that the bandpass table is applied on-the-fly before solving for the phase solutions, however the bandpass is NOT applied to the data permanently until applycal is run later on.

Now look at the phase solution, and note the obvious scatter within a scan time.

<source lang="python">
# In CASA
plotcal(caltable='intphase.gcal',xaxis='time',yaxis='phase',
        iteration='antenna',subplot=331,plotrange=[0,0,-180,180])
</source>

Although solint='int' (i.e. the integration time of 10 seconds) is the best choice to apply before for solving for the amplitude solutions, it is not a good idea to use this to apply to the target. This is because the phase-scatter within a scan can dominate the interpolation between calibrator scans. Instead, we also solve for the phase on the scan time, solint='inf' (but combine='''' '''', since we want one solution per scan) for application to the target later on. '''Unlike the bandpass task,''' for gaincal, the default of the combine parameter is combine='''' ''''.
[[Image:allcal_phaseinf2.png|thumb|Plot of phase solutions on a scan time.]]
<source lang="python">
# In CASA
gaincal(vis='day2_TDEM0003_10s_norx',caltable='scanphase.gcal',
        field='2,5,7',spw='0~1:4~60',
        refant='ea02',calmode='p',solint='inf',minsnr=2.0,
        gaintable=['antpos.cal','bandpass.bcal'],spwmap=[[]],
        opacity=0.04,gaincurve=T)
</source>

<source lang="python">
# In CASA
plotcal(caltable='scanphase.gcal',xaxis='time',yaxis='phase',
        iteration='antenna',subplot=331,plotrange=[0,0,-180,180])
</source>

Alternatively, one can also run [[smoothcal]] to smooth the solutions derived on the integration time.

Next we apply the bandpass and solint='int' phase-only calibration solutions on-the-fly to derive amplitude solutions. 
Here the use of solint='inf', but combine='''' '''' will result in one solution per scan interval.

<source lang="python">
# In CASA
gaincal(vis='day2_TDEM0003_10s_norx',caltable='amp.gcal',
        field='2,5,7',spw='0~1:4~60',
        refant='ea02',calmode='ap',solint='inf',minsnr=2.0,
        gaintable=['antpos.cal','bandpass.bcal','intphase.gcal'],spwmap=[[],[]],
        opacity=0.04,gaincurve=T)
</source>
[[Image:allcal_ampphase.png|thumb|Plot of residual phase solutions on a scan time]]

Now let's look at the resulting phase solutions.  Since we have taken out the phase as best we can by applying the solint='int' phase-only solution, this plot will give a good idea of the residual phase error. If you see scatter of more than a few degrees here, you should consider going back and looking for more data to flag, particularly bad timeranges etc.

<source lang="python">
# In CASA       
plotcal(caltable='amp.gcal',xaxis='time',yaxis='phase',
        iteration='antenna',subplot=331)
</source>

Indeed, both antenna ea12 (all times) and ea23 (first 1/3 of observation) show particularly large residual phase noise.
[[Image:allcal_amp.png|thumb|Plot of amplitude solutions on a scan time]]
<source lang="python">
# In CASA
plotcal(caltable='amp.gcal',xaxis='time',yaxis='amp',
        iteration='antenna',subplot=331)
</source>

Note that the amplitude solutions for ea12 are very low; this is another indication that this antenna is dubious.

Next we use the flux calibrator (whose flux density was set in [[setjy]] above) to derive the flux of the other calibrators. Note that the flux table REPLACES the amp.gcal in terms of future application of the calibration to the data, i.e. the flux table contains both the amp.gcal and flux scaling. Unlike the gain calibration steps, this is not an incremental table. 

<source lang="python">
# In CASA
fluxscale(vis='day2_TDEM0003_10s_norx',caltable='amp.gcal',
          fluxtable='flux.cal',reference='7')
</source>

[[Image:allcal_flux.png|thumb|Plot of flux corrected amplitude solutions.]]
It is a good idea to note down for your records the derived flux densities:

<pre style="background-color: #fffacd;">
Flux density for J0954+1743 in SpW=0 is: 0.235345 +/- 0.000879422 
    (SNR = 267.613, nAnt= 16)
Flux density for J0954+1743 in SpW=1 is: 0.241996 +/- 0.000930228 
    (SNR = 260.147, nAnt= 16)
Flux density for J1229+0203 in SpW=0 is: 25.2479 +/- 0 
    (SNR = inf, nAnt= 16)
Flux density for J1229+0203 in SpW=1 is: 24.9907 +/- 0 
    (SNR = inf, nAnt= 16)
</pre>

Obviously, the signal-to-noise for J1229+0203 can't be infinity! This is just an indication that their is only one scan for this source, and we derived a scan based amplitude solution, so there is no variation to calculate. 

Next, check that the flux.cal table looks as expected.

<source lang="python">
# In CASA
plotcal(caltable='flux.cal',xaxis='time',yaxis='amp',
        iteration='antenna',subplot=331)
</source>

==Applycal and Inspect==

Now we apply the calibration to each source, according to which tables are appropriate, and which source should be used to do that particular calibration. For the calibrators, all bandpass solutions come from the bandpass calibrator (id=5), and the phase and amplitude calibration comes from their own solutions. 

<source lang="python">
# In CASA
applycal(vis='day2_TDEM0003_10s_norx',field='2',
        gaintable=['antpos.cal','bandpass.bcal','intphase.gcal','flux.cal'],
        spwmap=[[]],gainfield=['','5','2','2'],
        opacity=0.04,gaincurve=T)
</source>

<source lang="python">
# In CASA
applycal(vis='day2_TDEM0003_10s_norx',field='5',
        gaintable=['antpos.cal','bandpass.bcal','intphase.gcal','flux.cal'],
        spwmap=[[]],gainfield=['','5','5','5'],
        opacity=0.04,gaincurve=T)
</source>

<source lang="python">
# In CASA
applycal(vis='day2_TDEM0003_10s_norx',field='7',
        gaintable=['antpos.cal','bandpass.bcal','intphase.gcal','flux.cal'],
        spwmap=[[]],gainfield=['','5','7','7'],
        opacity=0.04,gaincurve=T)
</source>

For the target we apply the bandpass from id=5, and the calibration from the gain calibrator (id=2):

<source lang="python">
# In CASA
applycal(vis='day2_TDEM0003_10s_norx',field='3',
        gaintable=['antpos.cal','bandpass.bcal','scanphase.gcal','flux.cal'],
        spwmap=[[]],gainfield=['','5','2','2'],
        opacity=0.04,gaincurve=T)
</source>

Now inspect the corrected data:
[[Image:applycal_inspect.png|thumb|Plot of calibrated amplitudes over time.]]
<source lang="python">
# In CASA
plotms(vis='day2_TDEM0003_10s_norx',field='5',ydatacolumn='corrected',
       xaxis='time',yaxis='amp',correlation='RR,LL',
       avgchannel='64',spw='0:4~60',antenna='')
</source>

This plot shows some data deviating from the average amplitudes. Use methods described above to 
mark a region for a small number of deviant data points, and click "Locate". You will find that ea12 is responsible.

<source lang="python">
# In CASA
plotms(vis='day2_TDEM0003_10s_norx',field='2',ydatacolumn='corrected',
       xaxis='time',yaxis='amp',correlation='RR,LL',
       avgchannel='64',spw='0:4~60',antenna='')
</source>

Here we see some problems, with high points. Mark some regions
and locate in [[plotms]] to find out which antennas and in which spws. Pay special
attention to antennas that have been called out already as showing some dubious behavior.

What you find is that ea07 which we flagged spw=1 above, is also bad for the same timerange in spw=0. This was not obvious in the raw data, because spw=0 was adjusted in the on-line system by a gain attenuator, while spw=1 wasn't. So a lack of power on this antenna can look like very low (and obvious) amplitudes in spw=1 but not for spw=0. Looking carefully you'll see that ea07 is actually pretty noisy throughout.
[[Image:ea12.png|thumb|Plot of antenna ea12 by itself]]
[[Image:ea23.png|thumb|Plot of antenna ea23 by itself]]

From the locate we also find that ea12 and ea23 show some high points; to see this, replot baselines using each of them alone:

<source lang="python">
plotms(vis='day2_TDEM0003_10s_norx',field='2',ydatacolumn='corrected',
       xaxis='time',yaxis='amp',correlation='RR,LL',
       avgchannel='64',spw='0:4~60',antenna='ea12')
</source>

<source lang="python">
plotms(vis='day2_TDEM0003_10s_norx',field='2',ydatacolumn='corrected',
       xaxis='time',yaxis='amp',correlation='RR,LL',
       avgchannel='64',spw='0:4~60',antenna='ea23')
</source>

ea12 needs to be flagged completely its just a bit noisy all around and ea23 is pretty noisy during the first scans between initial and second pointing. Recall that these are antennas we became suspicious of while inspecting the calibration solutions.

[[Image:target_uvdist.png|thumb|IRC+12216 as a function of uv-distance (after colorize by Antenna2).]]
Now lets see how the target looks. Because the target has resolved structure, its best to look at it as
a function of uvdistance. We'll go ahead and exclude the three antennas we already know have problems.

<source lang="python">
# In CASA
plotms(vis='day2_TDEM0003_10s_norx',field='3',ydatacolumn='corrected',
       xaxis='uvdist',yaxis='amp',correlation='RR,LL',
       avgchannel='64',spw='0:4~60',antenna='!ea07;!ea12;!ea23')
</source>

in "display" tab choose colorize by antenna2; then you can see that the spikes
are caused by a single antenna. Use, zoom, mark, and locate to see which one.
Also look at spw=1.

Turns out to be ea28; to confirm, replot with antenna=!ea28, and

<source lang="python">
# In CASA
plotms(vis='day2_TDEM0003_10s_norx',field='3',ydatacolumn='corrected',
       xaxis='uvdist',yaxis='amp',correlation='RR,LL',
       avgchannel='64',spw='0:4~60',antenna='!ea07;!ea12;!ea23;!ea28')
</source>

To see if it's restricted to a certain time

<source lang="python">
# In CASA
plotms(vis='day2_TDEM0003_10s_norx',field='3',ydatacolumn='corrected',
       xaxis='time',yaxis='amp',correlation='RR,LL',
       avgchannel='64',spw='0:4~60',antenna='ea28')
</source>


Baselines with ea28 clearly show issues until about two-thirds of the way through the observation. 
Plot another distant antenna to compare. We will go ahead and flag it all, since its hanging far out on the north
arm by itself.

The additional data we've identified as bad need to be flagged, and then all the calibration steps will need to be run
again.

<source lang="python">
# In CASA
flagdata(vis='day2_TDEM0003_10s_norx',
         field=['',''],
         spw=['',''],
         antenna=['ea07,ea12,ea28','ea07,ea23'],
         timerange=['','03:21:40~04:10:00'])
</source>

==Redo Calibration after more Flagging==

After flagging, you'll need to repeat the calibration steps above.  Here, we append  _redo to the table names to distinguish them from the first round, in case we want to compare with previous versions. 

<source lang="python">
# In CASA
gaincal(vis='day2_TDEM0003_10s_norx',caltable='bpphase_redo.gcal',
        field='5',spw='0~1:20~40',
        refant='ea02',calmode='p',solint='int',minsnr=2.0,
        opacity=0.04,gaincurve=T)
</source>

<source lang="python">
# In CASA
bandpass(vis='day2_TDEM0003_10s_norx',caltable='bandpass_redo.bcal',
        field='5',
        refant='ea02',solint='inf',solnorm=T,
        gaintable=['bpphase_redo.gcal'],spwmap=[[]],
        opacity=0.04,gaincurve=T)
</source>

<source lang="python">
# In CASA
gaincal(vis='day2_TDEM0003_10s_norx',caltable='intphase_redo.gcal',
        field='2,5,7',spw='0~1:4~60',
        refant='ea02',calmode='p',solint='int',minsnr=2.0,
        gaintable=['antpos.cal','bandpass_redo.bcal'],spwmap=[[]],
        opacity=0.04,gaincurve=T)
</source>

<source lang="python">
# In CASA
gaincal(vis='day2_TDEM0003_10s_norx',caltable='scanphase_redo.gcal',
        field='2,5,7',spw='0~1:4~60',
        refant='ea02',calmode='p',solint='inf',minsnr=2.0,
        gaintable=['antpos.cal','bandpass_redo.bcal'],spwmap=[[]],
        opacity=0.04,gaincurve=T)
</source>

<source lang="python">
# In CASA
gaincal(vis='day2_TDEM0003_10s_norx',caltable='amp_redo.gcal',
        field='2,5,7',spw='0~1:4~60',
        refant='ea02',calmode='ap',solint='inf',minsnr=2.0,
        gaintable=['antpos.cal','bandpass_redo.bcal','intphase_redo.gcal'],
        spwmap=[[],[]],
        opacity=0.04,gaincurve=T)
</source>
 
<source lang="python">
# In CASA      
fluxscale(vis='day2_TDEM0003_10s_norx',caltable='amp_redo.gcal',
          fluxtable='flux_redo.cal',reference='7')
</source>

<pre style="background-color: #fffacd;">
Flux density for J0954+1743 in SpW=0 is: 0.235345 +/- 0.000879422 
    (SNR = 267.613, nAnt= 16)
Flux density for J0954+1743 in SpW=1 is: 0.241996 +/- 0.000930228 
    (SNR = 260.147, nAnt= 16)
Flux density for J1229+0203 in SpW=0 is: 25.2479 +/- 0 
    (SNR = inf, nAnt= 16)
Flux density for J1229+0203 in SpW=1 is: 24.9907 +/- 0 
    (SNR = inf, nAnt= 16)
</pre>

Feel free to pause here and remake the calibration solution plots from above, just be sure to put in the revised table names.

==Redo Applycal and Inspect==

Now, apply all the new calibrations, which will overwrite the old ones.  These commands are identical to those above, with the exception of the _redo part of each calibration filename.

<source lang="python">
# In CASA
applycal(vis='day2_TDEM0003_10s_norx',field='2',
        gaintable=['antpos.cal','bandpass_redo.bcal','intphase_redo.gcal','flux_redo.cal'],
        spwmap=[[]],gainfield=['','5','2','2'],
        opacity=0.04,gaincurve=T)
</source>

<source lang="python">
# In CASA
applycal(vis='day2_TDEM0003_10s_norx',field='5',
        gaintable=['antpos.cal','bandpass_redo.bcal','intphase_redo.gcal','flux_redo.cal'],
        spwmap=[[]],gainfield=['','5','5','5'],
        opacity=0.04,gaincurve=T)
</source>
[[Image:gaincal_corrflag.png|thumb|Gain calibrator after further flagging and recalibration]]
[[Image:target_corrflag.png|thumb|IRC+10216 after further flagging and recalibration (after selecting colorize by spw).]]
<source lang="python">
# In CASA
applycal(vis='day2_TDEM0003_10s_norx',field='7',
        gaintable=['antpos.cal','bandpass_redo.bcal','intphase_redo.gcal','flux_redo.cal'],
        spwmap=[[]],gainfield=['','5','7','7'],
        opacity=0.04,gaincurve=T)
</source>

<source lang="python">
# In CASA
applycal(vis='day2_TDEM0003_10s_norx',field='3',
        gaintable=['antpos.cal','bandpass_redo.bcal','scanphase_redo.gcal','flux_redo.cal'],
        spwmap=[[]],gainfield=['','5','2','2'],
        opacity=0.04,gaincurve=T)
</source>

Now you can inspect the calibrated data again. Except for random scatter things look pretty good.

<source lang="python">
# In CASA
plotms(vis='day2_TDEM0003_10s_norx',field='2',ydatacolumn='corrected',
       xaxis='time',yaxis='amp',correlation='RR,LL',
       avgchannel='64',spw='0:4~60',antenna='')
</source>

Lets check the target again, looking at both spws, and selecting "Display" colorize by spw. You can use the Mark and Locate buttons to assess that the remaining scatter seems random, i.e. no particular antenna or time range appears to be responsible.

<source lang="python">
# In CASA
plotms(vis='day2_TDEM0003_10s_norx',field='3',ydatacolumn='corrected',
       xaxis='uvdist',yaxis='amp',correlation='RR,LL',
       avgchannel='64',spw='0~1:4~60',antenna='')
</source>

==Split==

Now we split the data into individual files. This is not strictly necessary, as you can select the appropriate fields in later clean stages, but it is safer in case for example you get confused with later processing and want to fall back to this point (this is especially a good idea if you plan to do continuum subtraction or self calibration later on). It also makes smaller individual files in case you want to copy to another machine or colleague.

Here, we split off the data for the phase calibrator and the target:

<source lang="python">
# In CASA
split(vis='day2_TDEM0003_10s_norx',outputvis='J0954',
      field='2')
</source>

<source lang="python">
# In CASA
split(vis='day2_TDEM0003_10s_norx',outputvis='IRC10216',
      field='3')
</source>

To reinitialize the scratch columns for use by later tasks, we need to run clearcal for both new datasets

<source lang="python">
# In CASA
clearcal(vis='J0954')
</source>

<source lang="python">
# In CASA
clearcal(vis='IRC10216')
</source>

This concludes the calibration phase of the data reductions. The tutorial continues with continuum subtraction, imaging, and image analysis in 
[[EVLA Spectral Line Imaging Analysis IRC+10216]].

[[Main Page | &#8629; '''CASAguides''']]

--[[User:Cbrogan|Crystal Brogan]]