Difference between revisions of "EVLA high frequency spectral line tutorial - IRC+10216 - calibration"

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(Data Inspection)
Line 12: Line 12:
 
</source>
 
</source>
  
=Data Inspection=
+
= Inspection and Flagging =
 +
 
 +
== List observational parameters ==
  
 
{{listobs}} provides almost all relevant observational parameters such as correlator setup (frequencies, bandwidths, channel number and widths, polarization products), sources, scans, scan intents, and antenna locations.  The following command writes the listobs output to a file on disk.  You can review the output at any time using '''less''' from the casapy or UNIX command line.
 
{{listobs}} provides almost all relevant observational parameters such as correlator setup (frequencies, bandwidths, channel number and widths, polarization products), sources, scans, scan intents, and antenna locations.  The following command writes the listobs output to a file on disk.  You can review the output at any time using '''less''' from the casapy or UNIX command line.
Line 72: Line 74:
  
 
Note that the Rest Frequency and Systemic Velocity are wrong in the listobs log by a factor 10^6 and 1000, respectively, given the quoted units (MHz) and (km/s). This was due to a temporary error in the EVLA Observing Tool that has subsequently been fixed. Because the sky frequencies are correct, and we set the rest frequency explicitly later in the deconvolution stage, this does not present a problem for the data reductions.
 
Note that the Rest Frequency and Systemic Velocity are wrong in the listobs log by a factor 10^6 and 1000, respectively, given the quoted units (MHz) and (km/s). This was due to a temporary error in the EVLA Observing Tool that has subsequently been fixed. Because the sky frequencies are correct, and we set the rest frequency explicitly later in the deconvolution stage, this does not present a problem for the data reductions.
 +
 +
We summarize the observing strategy in this table.
 +
 +
{| border="1" align="center" cellpadding="10" cellspacing="0"
 +
! Gain calibrator
 +
| J0954+1743
 +
| field id = 2
 +
|-
 +
! Bandpass calibrator
 +
| J1229+0203
 +
| field id = 5
 +
|-
 +
! Flux calibrator
 +
| J1331+3030 (3C286)
 +
| field id = 7
 +
|-
 +
! Science target
 +
| IRC+10216
 +
| field id = 3
 +
|}
 +
 +
== Plot antenna positions ==
 +
 +
We can use task {{plotants}} to generate a plot of the antenna positions.  This is useful for choosing a reference antenna.
 +
 +
<source lang="Python">
 +
# In CASA
 +
plotants(vis=vis,figfile=vis+'.plotants.png')
 +
</source>
 +
 +
We will use <tt>ea02</tt> as the reference antenna.
 +
 +
== Flagging ==
 +
 +
Next, let's look at the elevation as a function of time for all sources. We will use {{plotms}} to plot the data.  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 you can show by plotting the elevation for each source (each sources has a different colors).  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!)
 +
 +
<source lang="Python">
 +
# In CASA
 +
plotms(vis=vis, xaxis='time',yaxis='elevation',correlation='RR,LL',
 +
      avgchannel='64',spw='0:4~60', coloraxis='field')
 +
</source>
 +
 +
Next, let's look at all the source amplitudes as a function of time.
 +
 +
<source lang="Python">
 +
# In CASA
 +
plotms(vis=vis, xaxis='time',yaxis='amp',correlation='RR,LL',
 +
      avgchannel='64',spw='0:4~60', coloraxis='field')
 +
</source>
 +
 +
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. The output is be shown in the logger. Since all the "located" baselines include ea12, this is the responsible antenna.
 +
 +
Now click the clear 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=vis, field=['2,3','2,3'], spw=['','1'], antenna=['ea12','ea07'],
 +
        timerange=['03:41:00~04:10:00','03:21:40~04:10:00'])
 +
</source>
 +
 +
{{flagdata}} works by spanning up a matrix. The first entries in each list must be taken as one flagging command, as well as the second entries etc. Lists within lists are fine. In the above example, the first flagging command is issued for fields 2 and 3 for all spws and within the 03:41:00~04:10:00 timerange. A second command is again for the fields 2 and 3 but for spw 1 only and for the second timerange in the list '03:21:40~04:10:00'.
 +
 +
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!).
 +
 +
Lets look more closely at IRC+10216:
 +
 +
<source lang="Python">
 +
# In CASA
 +
plotms(vis=vis,field='3', xaxis='time',yaxis='amp',correlation='RR,LL',
 +
      avgchannel='64',spw='0~1:4~60', coloraxis='spw')
 +
</source>
 +
 +
You can see a that there are some noisy high points. But now try
 +
 +
<source lang="Python">
 +
# In CASA
 +
plotms(vis=vis, field='3', xaxis='uvdist', yaxis='amp', correlation='RR,LL',
 +
      avgchannel='64', spw='0~1:4~60', coloraxis='spw')
 +
</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 it's 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.

Revision as of 14:32, 5 January 2012

This guide is under development.

Getting the data

The data for this tutorial can be obtained by anonymous FTP from ftp://ftp.aoc.nrao.edu/staff/gvanmoor/community_day/. Download all 4 files TAR in this directory.

For example,

# In UNIX
wget 'ftp://ftp.aoc.nrao.edu/staff/gvanmoor/community_day/*'

Inspection and Flagging

List observational parameters

listobs provides almost all relevant observational parameters such as correlator setup (frequencies, bandwidths, channel number and widths, polarization products), sources, scans, scan intents, and antenna locations. The following command writes the listobs output to a file on disk. You can review the output at any time using less from the casapy or UNIX command line.

# In CASA
vis='day2_TDEM0003_20s_full'
listobs(vis=vis, verbose=True, listfile=vis+'.listobs.txt')

Here is a subset of the listobs output.

Fields: 4
  ID   Code Name                RA              Decl          Epoch   SrcId nVis
  2    D    J0954+1743          09:54:56.82363 +17.43.31.2224 J2000   2     32726
  3    NONE IRC+10216           09:47:57.38200 +13.16.40.6600 J2000   3     99540
  5    F    J1229+0203          12:29:06.69973 +02.03.08.5982 J2000   5     5436
  7    E    J1331+3030          13:31:08.28798 +30.30.32.9589 J2000   7     2736
   (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)  Corrs
  0          64 TOPO  36387.2295  125           8000        RR  RL  LR  LL
  1          64 TOPO  36304.542   125           8000        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

Note that the Rest Frequency and Systemic Velocity are wrong in the listobs log by a factor 10^6 and 1000, respectively, given the quoted units (MHz) and (km/s). This was due to a temporary error in the EVLA Observing Tool that has subsequently been fixed. Because the sky frequencies are correct, and we set the rest frequency explicitly later in the deconvolution stage, this does not present a problem for the data reductions.

We summarize the observing strategy in this table.

Gain calibrator J0954+1743 field id = 2
Bandpass calibrator J1229+0203 field id = 5
Flux calibrator J1331+3030 (3C286) field id = 7
Science target IRC+10216 field id = 3

Plot antenna positions

We can use task plotants to generate a plot of the antenna positions. This is useful for choosing a reference antenna.

# In CASA
plotants(vis=vis,figfile=vis+'.plotants.png')

We will use ea02 as the reference antenna.

Flagging

Next, let's look at the elevation as a function of time for all sources. We will use plotms to plot the data. 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 you can show by plotting the elevation for each source (each sources has a different colors). 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!)

# In CASA
plotms(vis=vis, xaxis='time',yaxis='elevation',correlation='RR,LL',
       avgchannel='64',spw='0:4~60', coloraxis='field')

Next, let's look at all the source amplitudes as a function of time.

# In CASA
plotms(vis=vis, xaxis='time',yaxis='amp',correlation='RR,LL',
       avgchannel='64',spw='0:4~60', coloraxis='field')

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. The output is be shown in the logger. Since all the "located" baselines include ea12, this is the responsible antenna.

Now click the clear 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:

# In CASA
flagdata(vis=vis, field=['2,3','2,3'], spw=['','1'], antenna=['ea12','ea07'],
         timerange=['03:41:00~04:10:00','03:21:40~04:10:00'])

flagdata works by spanning up a matrix. The first entries in each list must be taken as one flagging command, as well as the second entries etc. Lists within lists are fine. In the above example, the first flagging command is issued for fields 2 and 3 for all spws and within the 03:41:00~04:10:00 timerange. A second command is again for the fields 2 and 3 but for spw 1 only and for the second timerange in the list '03:21:40~04:10:00'.

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!).

Lets look more closely at IRC+10216:

# In CASA
plotms(vis=vis,field='3', xaxis='time',yaxis='amp',correlation='RR,LL',
       avgchannel='64',spw='0~1:4~60', coloraxis='spw')

You can see a that there are some noisy high points. But now try

# In CASA
plotms(vis=vis, field='3', xaxis='uvdist', yaxis='amp', correlation='RR,LL',
       avgchannel='64', spw='0~1:4~60', coloraxis='spw')

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 it's 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.