EVLA 6cmWideband Tutorial SN2010FZ: Difference between revisions

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== Overview ==
#REDIRECT [[EVLA 6cmWideband Tutorial SN2010FZ-CASA4.4]]
This article describes the calibration and imaging of a single-pointing 6cm EVLA wideband continuum dataset on the galaxy NGC2967 (UGC5180) which was the location of the supernova candidate SN2010FZ.  No supernova was detected in this observation, but the galactic continuum emission from this face-on spiral is adequately imaged. The data were taken in RSRO mode, with 1024 MHz of bandwidth in each of two widely spaced basebands (comprised each of 8 128 MHz spectral windows), spanning 4.5 to 7.5 GHz.  We will use wideband imaging techniques in this tutorial.
 
This is a more advanced tutorial, and if you are a relative novice (and <em>particularly</em> for EVLA continuum calibration and imaging), it is <em>strongly</em> recommended that you start with the [[EVLA Continuum Tutorial 3C391]] before tackling this dataset.  We will not include basic information on CASA processing in this tutorial.
 
== CASA Versions ==
 
This tutorial was written for the CASA Version 3.2.1 (release r15198 26 May 2011).
 
== Obtaining the Data ==
 
The scheduling block (SB) processed appears in the EVLA archive under program AS1015 as
<tt>AS1015_sb1658169_1.55388.89474846065</tt>
and was run on 2010-07-11 from 21:28 to 22:28 UT (size 37.74GB).
 
For the purposes of this tutorial, we have provided the raw SDM data (as would be extracted from the archive) as well as measurement sets created by filling the data (with the {{importevla}} task) and upon time-averaging to 10s (after application of the online flags). 
 
To start your tutorial, depending on which dataset you start with, proceed to:
* <em>To start with the raw SDM data:</em> Start with the section below titled "[[#Importing your EVLA data from SDM]]". This is where you would start if you were reducing data from the archive.
* <em>To start with the raw filled MS:</em> Start with the section below titled "[[#Application of Online Flags and Averaging your MS]]".
* <em>To start with the flagged and averaged MS:</em> Start with the section below titled "[[#Examining and Flagging your Averaged MS]]".
 
== Importing your EVLA data from SDM ==
 
For the purposes of this tutorial, we assume that the SDM is resident on disk, in this case at the location:
<pre>/lustre/smyers/AS1015/AS1015_sb1658169_1.55388.89474846065</pre> 
Use the actual location of your data when you carry out the commands.
 
The {{listsdm}} task will print out a summary of the scans, fields, spectral windows, and antennas present in your SDM.
 
<source lang="python">
# In CASA
listsdm('/lustre/smyers/AS1015/AS1015_sb1658169_1.55388.89474846065')
</source>
 
In the logger you should see:
<pre>
================================================================================
  SDM File: /lustre/smyers/AS1015/AS1015_sb1658169_1.55388.89474846065
================================================================================
  Observer: Dr. Alicia M. Soderberg
  Facility: EVLA, D-configuration
      Observed from 2010/07/11/21:28:28.41 to 2010/07/11/22:28:17.73 (UTC)
      Total integration time = 3589.32 seconds (1.00 hours)
Scan listing:
  Timerange (UTC)          Scan FldID  FieldName      SpwIDs        Intent(s)
  21:28:28.41 - 21:29:27.40    1    0  J0925+0019      [0, 1]  CALIBRATE_PHASE
  21:29:27.40 - 21:30:57.16    2    0  J0925+0019      [0, 1]  CALIBRATE_PHASE
  21:30:57.16 - 21:32:26.91    3    0  J0925+0019      [0, 1]  CALIBRATE_PHASE
  21:32:26.91 - 21:33:56.67    4    0  J0925+0019      [0, 1]  CALIBRATE_PHASE
  21:33:56.67 - 21:34:56.50    5    0  J0925+0019      [0, 1]  CALIBRATE_PHASE
  21:34:56.50 - 21:35:56.34    6    0  J0925+0019      [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]  CALIBRATE_PHASE
  21:35:56.34 - 21:37:26.09    7    0  J0925+0019      [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]  CALIBRATE_PHASE
  21:37:26.09 - 21:38:25.93    8    0  J0925+0019      [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]  CALIBRATE_PHASE
  21:38:25.93 - 21:39:55.68    9    1  SN2010FZ        [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]  OBSERVE_TARGET
  21:39:55.68 - 21:41:25.44  10    1  SN2010FZ        [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]  OBSERVE_TARGET
  21:41:25.44 - 21:42:55.19  11    1  SN2010FZ        [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]  OBSERVE_TARGET
  21:42:55.19 - 21:44:24.94  12    1  SN2010FZ        [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]  OBSERVE_TARGET
  21:44:24.94 - 21:45:54.70  13    1  SN2010FZ        [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]  OBSERVE_TARGET
  21:45:54.70 - 21:47:24.45  14    1  SN2010FZ        [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]  OBSERVE_TARGET
  21:47:24.45 - 21:47:54.37  15    1  SN2010FZ        [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]  OBSERVE_TARGET
  21:47:54.37 - 21:49:24.12  16    0  J0925+0019      [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]  CALIBRATE_PHASE
  21:49:24.12 - 21:50:53.88  17    1  SN2010FZ        [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]  OBSERVE_TARGET
  21:50:53.88 - 21:52:23.63  18    1  SN2010FZ        [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]  OBSERVE_TARGET
  21:52:23.63 - 21:53:53.39  19    1  SN2010FZ        [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]  OBSERVE_TARGET
  21:53:53.39 - 21:55:23.14  20    1  SN2010FZ        [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]  OBSERVE_TARGET
  21:55:23.14 - 21:56:52.89  21    1  SN2010FZ        [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]  OBSERVE_TARGET
  21:56:52.89 - 21:58:22.65  22    1  SN2010FZ        [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]  OBSERVE_TARGET
  21:58:22.65 - 21:58:52.57  23    1  SN2010FZ        [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]  OBSERVE_TARGET
  21:58:52.57 - 22:00:22.32  24    0  J0925+0019      [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]  CALIBRATE_PHASE
  22:00:22.32 - 22:01:52.07  25    1  SN2010FZ        [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]  OBSERVE_TARGET
  22:01:52.07 - 22:03:21.83  26    1  SN2010FZ        [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]  OBSERVE_TARGET
  22:03:21.83 - 22:04:51.58  27    1  SN2010FZ        [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]  OBSERVE_TARGET
  22:04:51.58 - 22:06:21.34  28    1  SN2010FZ        [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]  OBSERVE_TARGET
  22:06:21.34 - 22:07:51.09  29    1  SN2010FZ        [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]  OBSERVE_TARGET
  22:07:51.09 - 22:09:20.85  30    1  SN2010FZ        [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]  OBSERVE_TARGET
  22:09:20.85 - 22:09:50.76  31    1  SN2010FZ        [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]  OBSERVE_TARGET
  22:09:50.76 - 22:11:20.52  32    0  J0925+0019      [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]  CALIBRATE_PHASE
  22:11:20.52 - 22:12:50.27  33    1  SN2010FZ        [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]  OBSERVE_TARGET
  22:12:50.27 - 22:14:20.02  34    1  SN2010FZ        [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]  OBSERVE_TARGET
  22:14:20.02 - 22:15:49.78  35    1  SN2010FZ        [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]  OBSERVE_TARGET
  22:15:49.78 - 22:17:19.53  36    1  SN2010FZ        [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]  OBSERVE_TARGET
  22:17:19.53 - 22:18:49.29  37    1  SN2010FZ        [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]  OBSERVE_TARGET
  22:18:49.29 - 22:20:19.04  38    1  SN2010FZ        [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]  OBSERVE_TARGET
  22:20:19.04 - 22:20:48.96  39    1  SN2010FZ        [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]  OBSERVE_TARGET
  22:20:48.96 - 22:22:18.71  40    0  J0925+0019      [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]  CALIBRATE_PHASE
  22:22:18.71 - 22:23:48.47  41    2  3C286          [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]  CALIBRATE_BANDPASS CALIBRATE_AMPLI
  22:23:48.47 - 22:25:18.22  42    2  3C286          [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]  CALIBRATE_BANDPASS CALIBRATE_AMPLI
  22:25:18.22 - 22:26:47.98  43    2  3C286          [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]  CALIBRATE_BANDPASS CALIBRATE_AMPLI
  22:26:47.98 - 22:28:17.73  44    2  3C286          [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]  CALIBRATE_BANDPASS CALIBRATE_AMPLI
Spectral window information:
  SpwID  #Chans  Ch0(MHz)  ChWidth(kHz) TotBW(MHz)  Baseband
  0      64      7686.0    2000.0      128.0      BB_4   
  1      64      7836.0    2000.0      128.0      BB_8   
  2      64      4488.0    2000.0      128.0      BB_4   
  3      64      4616.0    2000.0      128.0      BB_4   
  4      64      4744.0    2000.0      128.0      BB_4   
  5      64      4872.0    2000.0      128.0      BB_4   
  6      64      5000.0    2000.0      128.0      BB_4   
  7      64      5128.0    2000.0      128.0      BB_4   
  8      64      5256.0    2000.0      128.0      BB_4   
  9      64      5384.0    2000.0      128.0      BB_4   
  10    64      6488.0    2000.0      128.0      BB_8   
  11    64      6616.0    2000.0      128.0      BB_8   
  12    64      6744.0    2000.0      128.0      BB_8   
  13    64      6872.0    2000.0      128.0      BB_8   
  14    64      7000.0    2000.0      128.0      BB_8   
  15    64      7128.0    2000.0      128.0      BB_8   
  16    64      7256.0    2000.0      128.0      BB_8   
  17    64      7384.0    2000.0      128.0      BB_8   
Field information:
  FldID  Code  Name            RA            Dec            SrcID
  0      D      J0925+0019      09:25:07.82  +000.19.13.933  0   
  1      NONE  SN2010FZ        09:42:04.77  +000.19.51.000  1   
  2      K      3C286            13:31:08.29  +030.30.32.959  2   
Antennas (27):
  ID    Name  Station  Diam.(m)  Lat.          Long.
  0    ea01  W09      25.0      +000.00.00.0  +000.00.00.0
  1    ea02  E02      25.0      +033.53.51.0  -107.37.25.2
  2    ea03  E09      25.0      +033.54.01.1  -107.37.04.4
  3    ea04  W01      25.0      +033.53.53.6  -107.36.45.1
  4    ea05  W08      25.0      +033.54.00.5  -107.37.05.9
  5    ea06  N06      25.0      +033.53.53.0  -107.37.21.6
  6    ea08  N01      25.0      +033.54.10.3  -107.37.06.9
  7    ea09  E06      25.0      +033.54.01.8  -107.37.06.0
  8    ea10  N03      25.0      +033.53.57.7  -107.36.55.6
  9    ea11  E04      25.0      +033.54.04.8  -107.37.06.3
  10    ea12  E08      25.0      +033.53.59.7  -107.37.00.8
  11    ea13  N07      25.0      +033.53.55.1  -107.36.48.9
  12    ea14  E05      25.0      +033.54.12.9  -107.37.07.2
  13    ea15  W06      25.0      +033.53.58.8  -107.36.58.4
  14    ea16  W02      25.0      +033.53.56.4  -107.37.15.6
  15    ea17  W07      25.0      +033.54.00.9  -107.37.07.5
  16    ea18  N09      25.0      +033.53.54.8  -107.37.18.4
  17    ea19  W04      25.0      +033.54.19.0  -107.37.07.8
  18    ea20  N05      25.0      +033.53.59.1  -107.37.10.8
  19    ea21  E01      25.0      +033.54.08.0  -107.37.06.7
  20    ea22  N04      25.0      +033.53.59.2  -107.37.05.7
  21    ea23  E07      25.0      +033.54.06.1  -107.37.06.5
  22    ea24  W05      25.0      +033.53.56.5  -107.36.52.4
  23    ea25  N02      25.0      +033.53.57.8  -107.37.13.0
  24    ea26  W03      25.0      +033.54.03.5  -107.37.06.2
  25    ea27  E03      25.0      +033.54.00.1  -107.37.08.9
  26    ea28  N08      25.0      +033.54.00.5  -107.37.02.8
</pre>
The C-band data of interest is contained in scans 6-44 and spans spectral windows 2 to 17.
 
We use the {{importevla}} task to convert the SDM dataset from the archive to a CASA Measurement Set (MS).
 
<source lang="python">
# In CASA
importevla(asdm='/lustre/smyers/AS1015/AS1015_sb1658169_1.55388.89474846065', \
          vis='SN2010FZ_filled.ms',online=True,flagzero=True, \
          shadow=True,applyflags=False,tbuff=1.5,flagbackup=False)
</source>
 
Here we had the task create (but not apply) the online flagging commands, plus flags for zero-clipping and shadowing.  The timeranges for the online flags were extended by 1.5sec (the integration time was 1sec) to account for some timing mismatches present in the EVLA data at this time.  These online flags indicated times where the antennas were not on source (e.g. slewing) or had other detectable faults. The created flagging commands will be stored in the <tt>FLAG_CMD</tt> MS table and can be applied later.  Note that if you set <tt>applyflags=True</tt> here then after filling the task will go ahead and apply the flags for you.
 
For the purposes of this exercise, in order to save time and disk space, we have turned off the automatic creation of flag column backups by setting <tt>flagbackup=False</tt>.  If we make a mistake and need to recover flags then we will have to rerun all previous commands.  We recommend that for real data processing that you leave the default value <tt>flagbackup=True</tt> in this and subsequent tasks.
 
You now have a MS called <tt>SN2010FZ_filled.ms</tt> in your working area.  This should be 37GB like the SDM.
 
== Application of Online Flags and Averaging your MS ==
 
If you are starting from the filled MS, you can find this at the AOC at:
<pre>/lustre/smyers/AS1015/SN2010FZ_filled.ms</pre>
Again, use the actual location of this file for your system.
 
NOTE: the following step will not work in Version 3.2.1 (you will get a blank plot) but should in later versions).
You can examine the commands stored in the <tt>FLAG_CMD</tt> table using {{flagcmd}}.
<source lang="python">
# In CASA
flagcmd(vis='SN2010FZ_filled.ms',flagmode='table',optype='plot')
</source>
This will bring up a <tt>matplotlib</tt> plotter.  You can have it plot to a PNG file instead:
<source lang="python">
# In CASA
flagcmd(vis='SN2010FZ_filled.ms',flagmode='table',optype='plot',outfile='plotSN2010FZ_flagcmd.png')
</source>
 
To apply the flags also use {{flagcmd}}:
<source lang="python">
# In CASA
flagcmd(vis='SN2010FZ_filled.ms',flagmode='table',optype='apply',flagbackup=False)
</source>
This can take a while for our 37GB dataset.  It took 20min on my workstation.
 
With the known bad data flagged, we can now split out the data we want and also average down in time to make a smaller MS.
For D-configuration (max baselines 1km) we can safely average to 3s or even 10s to reduce dataset size:
<source lang="python">
# In CASA
split(vis='SN2010FZ_filled.ms',outputvis='SN2010FZ_filled10s.ms',datacolumn='data',timebin='10s')
</source>
This can also take a while for our 37GB dataset.  It took 20min on my workstation.
 
You now have a MS called <tt>SN2010FZ_filled10s.ms</tt> in your working area.  This should be 3.2GB in size.
 
== Examining and Flagging your Averaged MS ==
 
If you are starting from the pre-flagged averaged split MS, you can find this at the AOC at:
<pre>/lustre/smyers/AS1015/SN2010FZ_filled10s.ms</pre>
 
We use {{listobs}} to summarize our new MS:
<source lang="python">
# In CASA
listobs('SN2010FZ_filled10s.ms')
</source>
Scan 6 is a dummy scan so we will use scans 7 to 44 when we process our data.
 
[[Image:plotSN2010FZ_plotants.png|200px|thumb|right|plotants plotter]]
To plot up the antenna positions in the array:
<source lang="python">
# In CASA
plotants('SN2010FZ_filled10s.ms')
</source>
NOTE: if after this point or any other you get table locks, use {{clearstat}} to clear them:
<source lang="python">
# In CASA
clearstat
</source>
 
Now we examine the MS looking for bad data to flag. We will use {{plotms}} to bring up an interactive GUI that will display 2-D Y vs.X style line plots. NOTE: We do not recommend using the editing/flagging features of plotms.  It is very easy to mess up your data that way.  Also, we will be restricting the scope of plotting so most box/flag operations would not get rid of all the bad data.  We will instead use plotms to identify bad data and then use flagcmd to flag it.  This will also allow full scripting of the flagging.
 
WARNING: The Flag button on the plotms GUI is close to other buttons you will be using, in particular the one that gets rid of boxes you have drawn.  Be careful and don't hit the Flag button by mistake!
 
The useful spw are 2~17. To get an idea of the data layout, plot a single baseline/channel versus time:
<source lang="python">
# In CASA
plotms(vis='SN2010FZ_filled10s.ms',field='',spw='2~17:31~31', \
      antenna='ea01&ea02',correlation='RR,LL',xaxis='time',yaxis='amp')
</source>
 
[[Image:plotSN2010FZ_plotms_ants.png|200px|thumb|right|plotms ant2 vs ea01]]
Look for bad antennas by picking the last field and plotting baselines versus antenna <tt>ea01</tt>:
<source lang="python">
# In CASA
plotms(vis='SN2010FZ_filled10s.ms',field='2',spw='2~17:31~31', \
      antenna='ea01',correlation='RR,LL',xaxis='antenna2',yaxis='amp')
</source>
You should be able to see that antenna 11 (= ea13) is bad (very low amplitude, it has no C-band receiver!) and that some of the spectral windows on 15 and 23 (ea17,ea25) are also on the low side.  Boxing and using Locate will show that spw 10~17 are suspect for these antennas.
 
[[Image:plotSN2010FZ_plotms_ea02.png|200px|thumb|right|plotms ea02 vs frequency]]
Now look at the bandpass for ea02 - it is in the inner core and a prospective reference antenna. Exclude ea13 using negation in the selection:
<source lang="python">
# In CASA
plotms(vis='SN2010FZ_filled10s.ms',field='2',spw='2~17', \
      antenna='ea02;!ea13',correlation='RR,LL',xaxis='frequency',yaxis='amp')
</source>
There is clearly less data for spw 11, and use of Locate shows spw 11 data only for ea02,ea03,04,08,09,11,12. We will later delete this incomplete spw.  Note also the very strong RFI spike at 6614MHz (spw 10 ch 63) with clear ringing contaminating both spw 10 and 11. There is also a tremendous roll-off in spw 10.  We will drop these spectral window when we process the data.
 
We can also step through the baselines to our antenna using iteraxis - use the ">" button to step through:
<source lang="python">
# In CASA
plotms(vis='SN2010FZ_filled10s.ms',field='2',spw='2~17',antenna='ea02;!ea13',correlation='RR,LL',xaxis='frequency',yaxis='amp',iteraxis='baseline')
</source>
This will make it easier to isolate the bad antennas. Now plot the phases, iterating through baselines to ea02:
<source lang="python">
# In CASA
plotms(vis='SN2010FZ_filled10s.ms',field='2',spw='2~17',antenna='ea02;!ea13',correlation='RR,LL',xaxis='frequency',yaxis='phase',iteraxis='baseline')
</source>
You see the slopes due to residual delays. Mostly a turn or less over a 128MHz subband, but there are some outliers.
Step through to ea20.  You see that there is a very large delay in RR (via locate) for
the first baseband (spw 0~7).  We will delete this (will also delete LL so there are no orphan polarization products).
Note ea17 and ea25 baselines drop close to zero in the middle of upper baseband (e.g. plot 'ea17&ea25') so we will delete these.
 
To carry out flagging, we again use {{flagcmd}} in the mode where it takes a list of command strings:
<source lang="python">
# In CASA
flaglist = ['antenna="ea13"',
            'antenna="ea17" spw="10~17"',
            'antenna="ea25" spw="10~17"',
            'antenna="ea20" spw="2~9"']
flagcmd(vis='SN2010FZ_filled10s.ms',flagmode='cmd',command=flaglist,optype='apply',flagbackup=False)
</source>
These commands will be carried out as well as being added to the FLAG_CMD table (marked as applied).
 
Plot the data again now having flagged:
<source lang="python">
# In CASA
plotms(vis='SN2010FZ_filled10s.ms',field='2',spw='2~17',antenna='ea02',correlation='RR,LL',xaxis='frequency',yaxis='amp',scan='7~44')
</source>
Now our phase calibrator - it is weaker, and we now start to see the RFI:
<source lang="python">
# In CASA
plotms(vis='SN2010FZ_filled10s.ms',field='0',spw='2~17',antenna='ea02',correlation='RR,LL',xaxis='frequency',yaxis='amp',scan='7~44')
</source>
Use the Zoom feature, Mark rectangles and use Locate to identify the frequency/channel of RFI. In particular, we note in our analysis:
* 6614MHz (spw 10 ch 63) super strong
* 6772-6778MHz (spw 12 ch 14-17)
* 7260-7264MHz (spw 16 ch 2-4)
* 7314-7340MHz (spw 16 ch 29-42)
* 7402-7418MHz (spw 17 ch  9-17)
* 7458-7466MHz (spw 17 ch 37-41)
* 7488MHz (spw 17 ch 52)
 
If you plot all antennas and avoid the band edges you see spw 16,17 are pretty wiped out:
<source lang="python">
# In CASA
plotms(vis='SN2010FZ_filled10s.ms',field='0',spw='2~17:4~59',antenna='',correlation='RR,LL',xaxis='frequency',yaxis='amp',scan='7~44')
</source>
For now we will not flag these channels but note them to mask out when creating continuum calibration tables and images.
 
Finally, split off the good scans and spw, this will allow us to work on the data without having to start completely over if we mess something up badly as well as letting us do simpler selection:
<source lang="python">
# In CASA
split(vis='SN2010FZ_filled10s.ms',outputvis='SN2010FZ_flagged10s.ms',datacolumn='data', spw='2~9,12~17',scan='7~44')
</source>
 
You now have a MS called <tt>SN2010FZ_flagged10s.ms</tt> in your working area.  This should be 2.8GB in size.
 
== Calibration ==
 
Summarize the split flagged MS:
<source lang="python">
# In CASA
listobs('SN2010FZ_flagged10s.ms')
</source>
In the logger we see:
<pre>
================================================================================
          MeasurementSet Name:  /home/sandrock2/smyers/casa/tutorials/SN2010FZ/SN2010FZ_flagged10s.ms      MS Version 2
================================================================================
  Observer: Dr. Alicia M. Soderberg    Project: T.B.D. 
Observation: EVLA
Data records: 1374548      Total integration time = 3042 seconds
  Observed from  11-Jul-2010/21:36:01.0  to  11-Jul-2010/22:26:43.0 (UTC)
 
  ObservationID = 0        ArrayID = 0
  Date        Timerange (UTC)          Scan  FldId FieldName nVis  Int(s)  SpwIds      ScanIntent
  11-Jul-2010/21:36:01.0 - 21:38:20.5    7      0 J0925+0019  73710  9.93    [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]CALIBRATE_PHASE#UNSPECIFIED
              21:38:44.0 - 21:39:51.0    9      1 SN2010FZ    39312  9.11    [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]OBSERVE_TARGET#UNSPECIFIED
              21:40:01.0 - 21:41:20.5    10      1 SN2010FZ    44226  9.89    [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]OBSERVE_TARGET#UNSPECIFIED
              21:41:30.0 - 21:42:50.0    11      1 SN2010FZ    44226  10      [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]OBSERVE_TARGET#UNSPECIFIED
              21:43:00.0 - 21:44:20.0    12      1 SN2010FZ    44226  10      [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]OBSERVE_TARGET#UNSPECIFIED
              21:44:30.0 - 21:45:50.0    13      1 SN2010FZ    44226  10      [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]OBSERVE_TARGET#UNSPECIFIED
              21:46:00.0 - 21:47:19.5    14      1 SN2010FZ    44226  9.89    [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]OBSERVE_TARGET#UNSPECIFIED
              21:47:29.0 - 21:47:48.5    15      1 SN2010FZ    14742  9.67    [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]OBSERVE_TARGET#UNSPECIFIED
              21:48:12.0 - 21:49:18.5    16      0 J0925+0019  39312  8.92    [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]CALIBRATE_PHASE#UNSPECIFIED
              21:49:42.0 - 21:50:49.0    17      1 SN2010FZ    39312  9.11    [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]OBSERVE_TARGET#UNSPECIFIED
              21:50:59.0 - 21:52:19.0    18      1 SN2010FZ    44226  10      [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]OBSERVE_TARGET#UNSPECIFIED
              21:52:29.0 - 21:53:48.5    19      1 SN2010FZ    44226  9.89    [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]OBSERVE_TARGET#UNSPECIFIED
              21:53:58.0 - 21:55:18.0    20      1 SN2010FZ    44226  10      [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]OBSERVE_TARGET#UNSPECIFIED
              21:55:28.0 - 21:56:48.0    21      1 SN2010FZ    44226  10      [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]OBSERVE_TARGET#UNSPECIFIED
              21:56:58.0 - 21:58:18.0    22      1 SN2010FZ    44226  10      [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]OBSERVE_TARGET#UNSPECIFIED
              21:58:28.0 - 21:58:47.0    23      1 SN2010FZ    14742  9.33    [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]OBSERVE_TARGET#UNSPECIFIED
              21:59:11.0 - 22:00:17.0    24      0 J0925+0019  39312  8.93    [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]CALIBRATE_PHASE#UNSPECIFIED
              22:00:40.0 - 22:01:47.0    25      1 SN2010FZ    39312  9.12    [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]OBSERVE_TARGET#UNSPECIFIED
              22:01:57.0 - 22:03:17.0    26      1 SN2010FZ    44226  10      [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]OBSERVE_TARGET#UNSPECIFIED
              22:03:27.0 - 22:04:47.0    27      1 SN2010FZ    44226  10      [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]OBSERVE_TARGET#UNSPECIFIED
              22:04:57.0 - 22:06:16.5    28      1 SN2010FZ    44226  9.89    [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]OBSERVE_TARGET#UNSPECIFIED
              22:06:26.0 - 22:07:46.0    29      1 SN2010FZ    44226  10      [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]OBSERVE_TARGET#UNSPECIFIED
              22:07:56.0 - 22:09:16.0    30      1 SN2010FZ    44226  10      [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]OBSERVE_TARGET#UNSPECIFIED
              22:09:26.0 - 22:09:45.0    31      1 SN2010FZ    14742  9.33    [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]OBSERVE_TARGET#UNSPECIFIED
              22:10:08.5 - 22:11:15.0    32      0 J0925+0019  39312  8.94    [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]CALIBRATE_PHASE#UNSPECIFIED
              22:11:38.5 - 22:12:45.5    33      1 SN2010FZ    39312  9.11    [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]OBSERVE_TARGET#UNSPECIFIED
              22:12:55.0 - 22:14:15.0    34      1 SN2010FZ    44226  10      [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]OBSERVE_TARGET#UNSPECIFIED
              22:14:25.0 - 22:15:45.0    35      1 SN2010FZ    44226  10      [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]OBSERVE_TARGET#UNSPECIFIED
              22:15:55.0 - 22:17:15.0    36      1 SN2010FZ    44226  10      [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]OBSERVE_TARGET#UNSPECIFIED
              22:17:25.0 - 22:18:44.5    37      1 SN2010FZ    44226  9.89    [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]OBSERVE_TARGET#UNSPECIFIED
              22:18:54.0 - 22:20:14.0    38      1 SN2010FZ    44226  10      [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]OBSERVE_TARGET#UNSPECIFIED
              22:20:24.0 - 22:20:43.5    39      1 SN2010FZ    14742  9.6      [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]OBSERVE_TARGET#UNSPECIFIED
              22:21:06.5 - 22:22:13.5    40      0 J0925+0019  38584  8.96    [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]CALIBRATE_PHASE#UNSPECIFIED
              22:25:13.0 - 22:25:13.0    42      2 3C286        770    2.65    [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]CALIBRATE_BANDPASS#UNSPECIFIED,CALIBRATE_AMPLI#UNSPECIFIED
              22:25:23.0 - 22:26:43.0    43      2 3C286        42812  9.62    [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]CALIBRATE_BANDPASS#UNSPECIFIED,CALIBRATE_AMPLI#UNSPECIFIED
          (nVis = Total number of time/baseline visibilities per scan)
Fields: 3
  ID  Code Name        RA            Decl          Epoch  SrcId nVis 
  0    D    J0925+0019  09:25:07.8150 +00.19.13.9334 J2000  0    230230
  1    NONE SN2010FZ    09:42:04.7700 +00.19.51.0000 J2000  1    1100736
  2    K    3C286        13:31:08.2880 +30.30.32.9589 J2000  2    43582 
  (nVis = Total number of time/baseline visibilities per field)
Spectral Windows:  (14 unique spectral windows and 1 unique polarization setups)
  SpwID  #Chans Frame Ch1(MHz)    ChanWid(kHz)TotBW(kHz)  Ref(MHz)    Corrs         
  0          64 TOPO  4488        2000        128000      4488        RR  RL  LR  LL 
  1          64 TOPO  4616        2000        128000      4616        RR  RL  LR  LL 
  2          64 TOPO  4744        2000        128000      4744        RR  RL  LR  LL 
  3          64 TOPO  4872        2000        128000      4872        RR  RL  LR  LL 
  4          64 TOPO  5000        2000        128000      5000        RR  RL  LR  LL 
  5          64 TOPO  5128        2000        128000      5128        RR  RL  LR  LL 
  6          64 TOPO  5256        2000        128000      5256        RR  RL  LR  LL 
  7          64 TOPO  5384        2000        128000      5384        RR  RL  LR  LL 
  8          64 TOPO  6744        2000        128000      6744        RR  RL  LR  LL 
  9          64 TOPO  6872        2000        128000      6872        RR  RL  LR  LL 
  10        64 TOPO  7000        2000        128000      7000        RR  RL  LR  LL 
  11        64 TOPO  7128        2000        128000      7128        RR  RL  LR  LL 
  12        64 TOPO  7256        2000        128000      7256        RR  RL  LR  LL 
  13        64 TOPO  7384        2000        128000      7384        RR  RL  LR  LL 
Sources: 42
  ID  Name        SpwId RestFreq(MHz)  SysVel(km/s)
  0    J0925+0019  0    -              -           
  0    J0925+0019  1    -              -           
  0    J0925+0019  2    -              -           
  0    J0925+0019  3    -              -           
  0    J0925+0019  4    -              -           
  0    J0925+0019  5    -              -           
  0    J0925+0019  6    -              -           
  0    J0925+0019  7    -              -           
  0    J0925+0019  8    -              -           
  0    J0925+0019  9    -              -           
  0    J0925+0019  10    -              -           
  0    J0925+0019  11    -              -           
  0    J0925+0019  12    -              -           
  0    J0925+0019  13    -              -           
  1    SN2010FZ    0    -              -           
  1    SN2010FZ    1    -              -           
  1    SN2010FZ    2    -              -           
  1    SN2010FZ    3    -              -           
  1    SN2010FZ    4    -              -           
  1    SN2010FZ    5    -              -           
  1    SN2010FZ    6    -              -           
  1    SN2010FZ    7    -              -           
  1    SN2010FZ    8    -              -           
  1    SN2010FZ    9    -              -           
  1    SN2010FZ    10    -              -           
  1    SN2010FZ    11    -              -           
  1    SN2010FZ    12    -              -           
  1    SN2010FZ    13    -              -           
  2    3C286        0    -              -           
  2    3C286        1    -              -           
  2    3C286        2    -              -           
  2    3C286        3    -              -           
  2    3C286        4    -              -           
  2    3C286        5    -              -           
  2    3C286        6    -              -           
  2    3C286        7    -              -           
  2    3C286        8    -              -           
  2    3C286        9    -              -           
  2    3C286        10    -              -           
  2    3C286        11    -              -           
  2    3C286        12    -              -           
  2    3C286        13    -              -           
Antennas: 27:
  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    ea06  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    ea10  N03      25.0 m  -107.37.06.3  +33.54.04.8 
  9    ea11  E04      25.0 m  -107.37.00.8  +33.53.59.7 
  10  ea12  E08      25.0 m  -107.36.48.9  +33.53.55.1 
  11  ea13  N07      25.0 m  -107.37.07.2  +33.54.12.9 
  12  ea14  E05      25.0 m  -107.36.58.4  +33.53.58.8 
  13  ea15  W06      25.0 m  -107.37.15.6  +33.53.56.4 
  14  ea16  W02      25.0 m  -107.37.07.5  +33.54.00.9 
  15  ea17  W07      25.0 m  -107.37.18.4  +33.53.54.8 
  16  ea18  N09      25.0 m  -107.37.07.8  +33.54.19.0 
  17  ea19  W04      25.0 m  -107.37.10.8  +33.53.59.1 
  18  ea20  N05      25.0 m  -107.37.06.7  +33.54.08.0 
  19  ea21  E01      25.0 m  -107.37.05.7  +33.53.59.2 
  20  ea22  N04      25.0 m  -107.37.06.5  +33.54.06.1 
  21  ea23  E07      25.0 m  -107.36.52.4  +33.53.56.5 
  22  ea24  W05      25.0 m  -107.37.13.0  +33.53.57.8 
  23  ea25  N02      25.0 m  -107.37.06.2  +33.54.03.5 
  24  ea26  W03      25.0 m  -107.37.08.9  +33.54.00.1 
  25  ea27  E03      25.0 m  -107.37.02.8  +33.54.00.5 
  26  ea28  N08      25.0 m  -107.37.07.5  +33.54.15.8 
</pre>
Note that the spws are re-numbered to 0-13.
 
Prepare the MS for calibration by adding scratch columns. This will take a few minutes.
<source lang="python">
# In CASA
clearcal('SN2010FZ_flagged10s.ms')
</source>
 
Before calibrating, we put a model for flux calibration source 3C286 into the MS (in the MODEL_DATA column we just created).
Have it set the flux on a per-channel basis.
NOTE: This uses the AOC Unix location for casapy models (yours may be different):
<source lang="python">
# In CASA
setjy(vis='SN2010FZ_flagged10s.ms',field='2',spw='',scalebychan=True, \
      modimage='/usr/lib64/casapy/data/nrao/VLA/CalModels/3C286_C.im')
</source>
It reports to logger that its about 7.7Jy at lower end to 5.7Jy at upper frequency limit.
 
First, we do a phase-only calibration solution on a narrow range of channels in each spw on the bandpass/flux calibrator 3c286 to flatten them before solving for the bandpass. Note where we saw RFI in the higher spw and avoid those channels. The range 23~28 should work. Pick a refant near center - ea02 is a reasonable bet:
<source lang="python">
# In CASA
gaincal(vis='SN2010FZ_flagged10s.ms',caltable='calSN2010FZ.G0',field='2',spw='0~13:23~28', \
        gaintype='G',refant='ea02',calmode='p',solint='int',minsnr=3)
</source>
 
Plot the phase solutions (using full phase range instead of autorange)
<source lang="python">
# In CASA
plotcal(caltable='calSN2010FZ.G0',xaxis='time',yaxis='phase',iteration='antenna', \
        plotrange=[-1,-1,-180,180])
</source>
Step through the antenna-based solutions.  They look good (and fairly flat over the scans).
 
We can now solve for the residual antenna-based delays that we saw in phase vs. frequency:
<source lang="python">
# In CASA
gaincal(vis='SN2010FZ_flagged10s.ms',caltable='calSN2010FZ.K0',gaintable='calSN2010FZ.G0', \
        field='2',spw='0~13:4~59',gaintype='K', \
        refant='ea02',combine='scan',solint='inf',minsnr=3)
</source>
We pre-apply our initial phase table, and produce a new K-type caltable for input to bandpass calibration.
The delays found are sent to the terminal.  They are up to a few nanoseconds.
 
Now solve for the bandpass using the previous tables:
<source lang="python">
# In CASA
bandpass(vis='SN2010FZ_flagged10s.ms',caltable='calSN2010FZ.B0', \
        gaintable=['calSN2010FZ.G0','calSN2010FZ.K0'], \
        field='2',refant='ea02',solnorm=True, \
        bandtype='B', combine='scan', solint='inf')
</source>
Now plot this, in amplitude then phase:
<source lang="python">
# In CASA
plotcal(caltable='calSN2010FZ.B0',xaxis='freq',yaxis='amp',iteration='antenna')
 
plotcal(caltable='calSN2010FZ.B0',xaxis='freq',yaxis='phase',iteration='antenna', \
        plotrange=[-1,-1,-180,180])
</source>
In the bandpass phase you no longer see the residual antenna delays but there are some band edge effects.
Note that some antennas have a little strange bandpasses at upper end of lower baseband in spw 5,6,7.
 
Now calibrate phases for real with wider bandwidth. First the flux calibrator again, with a per-integration solution time:
<source lang="python">
# In CASA
gaincal(vis='SN2010FZ_flagged10s.ms',caltable='calSN2010FZ.G1', \
        gaintable=['calSN2010FZ.K0','calSN2010FZ.B0'], \
        field='2',refant='ea02',solnorm=F, spw='0~13:4~59', \
        solint='int',gaintype='G',calmode='p')
</source>
Next our phase calibrator, appending these solutions to previous table.
Exclude RFI channels here, and obtain one solution per scan:
<source lang="python">
# In CASA
gaincal(vis='SN2010FZ_flagged10s.ms',caltable='calSN2010FZ.G1',
        gaintable=['calSN2010FZ.K0','calSN2010FZ.B0'], \
        field='0',refant='ea02',solnorm=F, \
        spw='0:10~59,1~7:4~59,8:4~13;18~59,9~11:4~59,12:4~13;18~29;31~33;46~51;53~59,13:4~8;15~36;42~59', \
        solint='inf',gaintype='G',calmode='p',append=True)
</source>
The phases look reasonably connected:
<source lang="python">
# In CASA
plotcal(caltable='calSN2010FZ.G1',xaxis='time',yaxis='phase',iteration='antenna', \
        plotrange=[-1,-1,-180,180])
</source>
 
Now solve for amplitudes on a per scan interval. Do these separately using gainfield so phases don't get
transferred across fields. Uses linear interpolation of the previously determined phases by default.
Pre-apply the gaincurve also:
<source lang="python">
# In CASA
gaincal(vis='SN2010FZ_flagged10s.ms', caltable='calSN2010FZ.G2', \
        gaintable=['calSN2010FZ.K0','calSN2010FZ.B0','calSN2010FZ.G1'], \
        gainfield=['2','2','2'], field='2',refant='ea02',solnorm=F,
        spw='0:10~59,1~7:4~59,8:4~13;18~59,9~11:4~59,12:4~13;18~29;31~33;46~51;53~59,13:4~8;15~36;42~59', \
        solint='inf',gaintype='G',calmode='a',gaincurve=True)
 
gaincal(vis='SN2010FZ_flagged10s.ms', caltable='calSN2010FZ.G2', \
        gaintable=['calSN2010FZ.K0','calSN2010FZ.B0','calSN2010FZ.G1'],\
        gainfield=['2','2','0'], field='0',refant='ea02',solnorm=F, \
        spw='0:10~59,1~7:4~59,8:4~13;18~59,9~11:4~59,12:4~13;18~29;31~33;46~51;53~59,13:4~8;15~36;42~59', \
        solint='inf',gaintype='G',calmode='a',gaincurve=True,append=True)
</source>
 
Since the flux on the gain calibrator is not scaled to its correct flux (but to 1.0Jy)
use fluxscale to transfer the amplitude gains from 3c286:
<source lang="python">
# In CASA
fluxscale(vis='SN2010FZ_flagged10s.ms',caltable='calSN2010FZ.G2',fluxtable='calSN2010FZ.F2', \
          reference='2',transfer='0')
</source>
As it so happens, the derived flux for J0925+0019 is about 1 Jy and flat spectrum (you can plot up the raw amplitudes for fields 0,2 and convince yourself this is indeed true and not a bug). Plot these:
<source lang="python">
# In CASA
plotcal(caltable='calSN2010FZ.F2',xaxis='time',yaxis='amp',iteration='antenna')
</source>
The phase calibrator has consistent gains across the short run, though there is a slight offset to 3c286 (which is not nearby in any event).
 
== Applying the Calibration and Final Editing ==
 
Next we actually apply all our accumulated calibration tables. First to the flux calibrator:
<source lang="python">
# In CASA
applycal(vis='SN2010FZ_flagged10s.ms',field='2', \
        gaintable=['calSN2010FZ.K0','calSN2010FZ.B0','calSN2010FZ.G1','calSN2010FZ.F2'], \
        gainfield=['','','2','2'],interp=['nearest','nearest','linear','nearest'], \
        parang=False,calwt=F,gaincurve=T)
</source>
We can examine the corrected data using our RFI mask from above and avoiding band edges
<source lang="python">
# In CASA
plotms(vis='SN2010FZ_flagged10s.ms',field='2', \
      spw='0:10~59,1~7:4~59,8:4~13;18~59,9~11:4~59,12:4~13;18~29;31~33;46~51;53~59,13:4~8;15~36;42~59', \
      correlation='RR,LL',xaxis='frequency',yaxis='amp',ydatacolumn='corrected')
</source>
We now see problems in spw 5 and 6 for baseline ea17&ea25, which gives a really strange response:
<source lang="python">
# In CASA
plotms(vis='SN2010FZ_flagged10s.ms',field='2', \
      spw='0:10~59,1~7:4~59,8:4~13;18~59,9~11:4~59,12:4~13;18~29;31~33;46~51;53~59,13:4~8;15~36;42~59', \
      antenna='ea17&ea25', \
      correlation='RR,LL',xaxis='frequency',yaxis='amp',ydatacolumn='corrected')
</source>
You can exclude this through antenna negation:
<source lang="python">
# In CASA
plotms(vis='SN2010FZ_flagged10s.ms',field='2', \
      spw='0:10~59,1~7:4~59,8:4~13;18~59,9~11:4~59,12:4~13;18~29;31~33;46~51;53~59,13:4~8;15~36;42~59', \
      antenna='!ea17&ea25', \
      correlation='RR,LL',xaxis='frequency',yaxis='amp',ydatacolumn='corrected')
</source>
Then use Locate for the other bad points, which seem to indicate spw 5,6,7 for ea14,ea16,ea17,ea25.
Exclude these and replot:
<source lang="python">
# In CASA
plotms(vis='SN2010FZ_flagged10s.ms',field='2', \
      spw='0:10~59,1~7:4~59,8:4~13;18~59,9~11:4~59,12:4~13;18~29;31~33;46~51;53~59,13:4~8;15~36;42~59', \
      antenna='!ea14;!ea16;!ea17;!ea25', \
      correlation='RR,LL',xaxis='frequency',yaxis='amp',ydatacolumn='corrected')
</source>
This now looks clean except for the RFI in the upper subbands.
 
Do flagging based on these:
<source lang="python">
# In CASA
flaglist = ['antenna="ea14,ea16,ea17,ea25" spw="5~7"']
flagcmd(vis='SN2010FZ_flagged10s.ms',flagmode='cmd',command=flaglist,optype='apply',flagbackup=False)
</source>
 
Now replot the corrected data (you may have to force reload if you plotted same thing right before this):
<source lang="python">
# In CASA
plotms(vis='SN2010FZ_flagged10s.ms',field='2', \
      spw='0:10~59,1~7:4~59,8:4~13;18~59,9~11:4~59,12:4~13;18~29;31~33;46~51;53~59,13:4~8;15~36;42~59', \
      correlation='RR,LL',xaxis='frequency',yaxis='amp',ydatacolumn='corrected')
</source>
Looks good. If we were more diligent we would go back and recalibrate, but this looks good enough for now.
 
Now lets apply the calibration to the phase calibrator and then plot the corrected data:
<source lang="python">
# In CASA
applycal(vis='SN2010FZ_flagged10s.ms',field='0', \
        gaintable=['calSN2010FZ.K0','calSN2010FZ.B0','calSN2010FZ.G1','calSN2010FZ.F2'], \
        gainfield=['','','0','0'], interp=['nearest','nearest','nearest','nearest'], \
        parang=False,calwt=F,gaincurve=T)
 
plotms(vis='SN2010FZ_flagged10s.ms',field='0', \
      spw='0:10~59,1~7:4~59,8:4~13;18~59,9~11:4~59,12:4~13;18~29;31~33;46~51;53~59,13:4~8;15~36;42~59', \
      correlation='RR,LL',xaxis='frequency',yaxis='amp',ydatacolumn='corrected')
</source>
You can see the roll-off pumping up noise at the baseband edges (about 8-16 channels worth). Also, we can see some RFI we missed:
* <6804MHz spw  8 below ch 30 lots of bad stuff (alot from ea18,ea22 but others too)
*  7168MHz spw 11 ch 20
*  pretty much all of spw 12,13
The ch 20 ones are all harmonics of the notorious 128MHz tone.
 
We will not flag these, but exclude them in imaging, so a good channel selection string for imaging might be:
<pre>
spw = '0:16~59,1~6:4~59,7:4~54,8:30~59,9~10:4~59,11:4~19;21~59'
</pre>
 
Finally we apply calibration from field 0 to the target field 1. This takes a few minutes:
<source lang="python">
# In CASA
applycal(vis='SN2010FZ_flagged10s.ms',field='1', \
        gaintable=['calSN2010FZ.K0','calSN2010FZ.B0','calSN2010FZ.G1','calSN2010FZ.F2'], \
        gainfield=['','','0','0'], interp=['nearest','nearest','linear','linear'], \
        parang=False,calwt=F,gaincurve=T)
</source>
You can look at the target source field='1' but there are lots of data so you will need to do alot of averaging.
For example:
<source lang="python">
# In CASA
plotms(vis='SN2010FZ_flagged10s.ms',field='1',avgtime='300s', \
      spw='0:16~59,1~6:4~59,7:4~54,8:30~59,9~10:4~59,11:4~19;21~59', \
      correlation='RR,LL',xaxis='frequency',yaxis='amp',ydatacolumn='corrected')
</source>
Alas, the upper baseband still has lots of low level RFI.
 
Now split off the data for calibrators and target, to avoid later issues that can corrupt the MSes.
These will take a bit of time...field 1 took 18min on my workstation.
<source lang="python">
# In CASA
split(vis='SN2010FZ_flagged10s.ms',outputvis='SN2010FZ_split10s.ms',datacolumn='corrected',field='1')
 
split(vis='SN2010FZ_flagged10s.ms',outputvis='SN2010FZ_3c28610s.ms',datacolumn='corrected',field='2')
 
split(vis='SN2010FZ_flagged10s.ms',outputvis='SN2010FZ_J092510s.ms',datacolumn='corrected',field='0')
</source>
 
== Imaging ==
 
This is D-config data at C-band, look at the Obs Status Summary:
[http://evlaguides.nrao.edu/index.php?title=Observational_Status_Summary_-_Current]
Synthesized beam should be 12" at 6GHz with primary beam FOV 7.5arcmin (450").
Our data spans 4.5-7.5GHz : beam 9.6 at 7.5GHz and FOV 10' at 4.5GHz
A cellsize of 3" should work, with an imsize > 200 to cover 2xFWHM FOV
An imsize of 400+ will put the main beam inside the inner quarter safely
The Briggs robust (0.5) weighting is somewhere between uniform and natural
and will give reasonable resolution but still see some larger scale structure
 
Lets interactively clean one of the lower baseband spw (5):
NOTE: this first time will take a few minutes at start to create scratch columns
in the MS in case we want to do self-calibration later.
 
Start carefully by boxing the bright source and setting iterations to 10 at first
Gradually add more boxes and increase the number of iterations
Since this is not much more than a snapshot you see the six-fold sidelobe pattern
of the extended emission in the center of the map. This decreases as you clean
out this emission.
 
Stop cleaning when the residuals look like noise (and you cannot clearly see sources).
To stop click the red X button.
<source lang="python">
# In CASA
clean(vis='SN2010FZ_split10s.ms',spw='5:4~59',imagename='imgSN2010FZ10s_spw5_clean640', \
      mode='mfs',nterms=1,niter=10000,gain=0.1,threshold='0.0mJy', \
      psfmode='clark',imsize=[640,640],cell=['3.0arcsec'],stokes='I', \
      imagermode='csclean', cyclefactor=1.5, \
      weighting='briggs',robust=0.5,calready=True,interactive=True)
</source>
 
Note that there are some strange sidelobe patterns in lower left, possibly
from a source outside the image area.  We can make a bigger image starting from
our current model:
<source lang="python">
# In CASA
clean(vis='SN2010FZ_split10s.ms',spw='5:4~59',imagename='imgSN2010FZ10s_spw5_clean1280', \
      mode='mfs',nterms=1,niter=10000,gain=0.1,threshold='0.0mJy', \
      psfmode='clark',imsize=[1280,1280],cell=['3.0arcsec'],stokes='I', \
      imagermode='csclean', cyclefactor=1.5, modelimage='imgSN2010FZ10s_spw5_clean640.model', \
      weighting='briggs',robust=0.5,calready=True,interactive=True)
</source>
Sure enough, there is a bright source near the lower left. Box it, clean it a bit, and
stop.
<source lang="python">
# In CASA
viewer('imgSN2010FZ10s_spw5_clean1280.image')
</source>
Check the rms of the residuals:
<source lang="python">
# In CASA
mystat = imstat('imgSN2010FZ10s_spw5_clean1280.residual')
print 'Residual standard deviation = '+str(mystat['sigma'][0])
</source>
I got 31.8uJy for mine.
 
Now, image the entire lower baseband (spw 0-7).
Follow same iterative procedure as before, and get the best
residuals you can.  Because of the bandwidth and frequency
synthesis, the sidelobe pattern is different than before and
it is much easier to see fainter emission.
Be careful cleaning sources that lie near or on sidelobe splotches.
Clean the central emission region way down first to reduce the sidelobe
level before adding components in the sidelobe areas.
<source lang="python">
# In CASA
clean(vis='SN2010FZ_split10s.ms',spw='0:16~59,1~6:4~59,7:4~54', \
      imagename='imgSN2010FZ10s_spw0to7_clean1280', \
      mode='mfs',nterms=1,niter=10000,gain=0.1,threshold='0.0mJy', \
      psfmode='clark',imsize=[1280,1280],cell=['3.0arcsec'],stokes='I', \
      imagermode='csclean', cyclefactor=1.5, \
      weighting='briggs',robust=0.5,calready=True,interactive=True)
 
mystat = imstat('imgSN2010FZ10s_spw0to7_clean1280.residual')
print 'Residual standard deviation = '+str(mystat['sigma'][0])
</source>
I got 11.0uJy (and there is clearly structure left).
 
Lets try adding a spectral slope to the multi-frequency synthesis using nterms=2 on the lower baseband.
This will solve for images of the average and spectral slope simultaneously.
The dirty beam will have lower sidelobes so we turn up cyclefactor for csclean a bit:
<source lang="python">
# In CASA
clean(vis='SN2010FZ_split10s.ms',spw='0:16~59,1~6:4~59,7:4~54', \
      imagename='imgSN2010FZ10s_spw0to7_mfs2_clean1280', \
      mode='mfs',nterms=2,niter=10000,gain=0.1,threshold='0.0mJy', \
      psfmode='clark',imsize=[1280,1280],cell=['3.0arcsec'],stokes='I', \
      imagermode='csclean', cyclefactor=4.5, \
      weighting='briggs',robust=0.5,calready=True,interactive=True)
 
mystat = imstat('imgSN2010FZ10s_spw0to7_mfs2_clean1280.residual.tt0')
print 'Residual standard deviation = '+str(mystat['sigma'][0])
</source>
I got 10.5uJy (somewhat better looking than the nterms=1).
 
Finally, we try nterms=2 including the clean part of the upper baseband:
<source lang="python">
# In CASA
clean(vis='SN2010FZ_split10s.ms', \
      spw='0:16~59,1~6:4~59,7:4~54,8:30~59,9~10:4~59,11:4~19;21~59', \
      imagename='imgSN2010FZ10s_spw0to11_mfs2_clean1280', \
      mode='mfs',nterms=2,niter=10000,gain=0.1,threshold='0.0mJy', \
      psfmode='clark',imsize=[1280,1280],cell=['3.0arcsec'],stokes='I', \
      imagermode='csclean', cyclefactor=4.5, \
      weighting='briggs',robust=0.5,calready=True,interactive=True)
 
mystat = imstat('imgSN2010FZ10s_spw0to11_mfs2_clean1280.residual.tt0')
print 'Residual standard deviation = '+str(mystat['sigma'][0])
</source>
I got 8.2uJy.  If you try nterms=1 on this wide bandwidth you will get much poorer residuals.
 
Look at this in the viewer:
<source lang="python">
# In CASA
viewer('imgSN2010FZ10s_spw0to11_mfs2_clean1280.image.tt0')
</source>
Zoom in on the center:
[[Image:plotSN2010FZ viewerfinal.png|500px|thumb|center|final image]]
 
As a comparison, here is our image side by side with a i-band image from the Sloan Digital Sky Survey (SDSS) registered
to our image:
[[Image:plotSN2010FZ viewerfinalandSDSS.png|600px|thumb|center|final and sdss image]]
You can find this image and load it into your viewer, and blink against our 6cm image.

Latest revision as of 13:55, 12 November 2015