VLA CASA Bandpass Slope-CASA4.5.2
This CASA Guide is for CASA version 4.5.2
Overview
For the standard VLA flux calibrators, CASA includes a spatial and spectral model that is being applied for the and bandpass calibration. This model takes out the source characteristics and calibration solution then represent the instrument and atmospheric corrections. The VLA standards, however, have a relatively steep spectral index and are relatively weak at high frequencies. Although this is usually not a problem for absolute flux calibration, a good bandpass determination requires a very strong source, particularly for narrow channel widths. So for the high frequency, narrow channel case it is thus advisable to observe a different, but very strong source to correct for the bandpass. Such sources typically are variable and show a spectral slope that needs to be corrected for when the bandwidth is large. This tutorial describes how to model such a slope and correct the bandpass solution for it.
Data is taken in wide, 3-bit mode for the protostar G192.16-3.84 in Ka-band with spectral windows centered 29 and 36.5 GHz Each baseband has over 4 GHz of bandwidth comprised of 32 128-MHz spectral windows.
This is a more advanced tutorial, so if you are a relative novice, it is strongly recommended that you start with the EVLA Continuum Tutorial 3C391 (at least read it through), or even Getting Started in CASA before proceeding with this tutorial.
Obtaining the Data
As this tutorial concerns bandpass solutions only, we removed all other sources from the MS and only keep the bandpass calibrator scans. We also applied flagging and all pre-calibration steps including antenna position offsets, requantizer gains, opacity corrections, and gain-elevation curves. The original data (TVER0004.sb14459364.eb14492359.56295.26287841435) can be obtained through the [NRAO archive] and has a raw size of 57.04 GB.
The trimmed measurement set can be downloaded directly from http://casa.nrao.edu/Data/EVLA/G192/G192-BP.ms.tar.gz (dataset size: 2.1 GB)
Your first step will be to unzip and untar the file in a terminal (before you start CASA):
tar -xzvf G192-BP.ms.tar.gz
Starting CASA
As usual, to start CASA, type:
casa
This will run a script to initialize CASA, setting paths appropriately. It will also start writing to a file called ipython-<unique-stamp>.log, which will contain a record of all the text you enter at the CASA prompt, as well as casapy-<unique-stamp>.log, which will contain all the messages that are printed to the CASA logger window. It is recommended that you keep your log files in tact - you may need them to remind you of the last step you completed in your data reduction! (It is also a good idea to include your log files when submitting a help desk ticket).
Once CASA has started, a logger window will appear. Note that you can rescale this window or change the font size as desired (the latter is under "View").
Examining the Measurement Set (MS)
We use listobs to summarize our MS:
# In CASA: listobs on the initial data set
listobs('G192-BP.ms', listfile='G192_listobs.txt')
This will write the output to a file called G192_listobs.txt, which we can print to the terminal using the cat command:
# In CASA
cat G192_listobs.txt
================================================================================ MeasurementSet Name: /lustre/aoc/sciops/jott/casa/topicalguide/bandpass/G192-BP.ms MS Version 2 ================================================================================ Observer: Dr. Debra Shepherd Project: uid://evla/pdb/7303457 Observation: EVLA Data records: 1064490 Total elapsed time = 444 seconds Observed from 03-Jan-2013/07:40:27.0 to 03-Jan-2013/07:47:51.0 (UTC) ObservationID = 0 ArrayID = 0 Date Timerange (UTC) Scan FldId FieldName nRows SpwIds Average Interval(s) ScanIntent 03-Jan-2013/07:40:27.0 - 07:47:51.0 64 0 3c84-J0319+413 1064490 [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63] [6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6] [CALIBRATE_BANDPASS#UNSPECIFIED,OBSERVE_TARGET#UNSPECIFIED] (nRows = Total number of rows per scan) Fields: 1 ID Code Name RA Decl Epoch SrcId nRows 0 F 3c84-J0319+413 03:19:48.160102 +41.30.42.10305 J2000 0 1064490 Spectral Windows: (64 unique spectral windows and 1 unique polarization setups) SpwID Name #Chans Frame Ch0(MHz) ChanWid(kHz) TotBW(kHz) CtrFreq(MHz) BBC Num Corrs 0 EVLA_KA#A1C1#2 128 TOPO 34476.000 1000.000 128000.0 34539.5000 10 RR LL 1 EVLA_KA#A1C1#3 128 TOPO 34604.000 1000.000 128000.0 34667.5000 10 RR LL 2 EVLA_KA#A1C1#4 128 TOPO 34732.000 1000.000 128000.0 34795.5000 10 RR LL 3 EVLA_KA#A1C1#5 128 TOPO 34860.000 1000.000 128000.0 34923.5000 10 RR LL 4 EVLA_KA#A1C1#6 128 TOPO 34988.000 1000.000 128000.0 35051.5000 10 RR LL 5 EVLA_KA#A1C1#7 128 TOPO 35116.000 1000.000 128000.0 35179.5000 10 RR LL 6 EVLA_KA#A1C1#8 128 TOPO 35244.000 1000.000 128000.0 35307.5000 10 RR LL 7 EVLA_KA#A1C1#9 128 TOPO 35372.000 1000.000 128000.0 35435.5000 10 RR LL 8 EVLA_KA#A1C1#10 128 TOPO 35500.000 1000.000 128000.0 35563.5000 10 RR LL 9 EVLA_KA#A1C1#11 128 TOPO 35628.000 1000.000 128000.0 35691.5000 10 RR LL 10 EVLA_KA#A1C1#12 128 TOPO 35756.000 1000.000 128000.0 35819.5000 10 RR LL 11 EVLA_KA#A1C1#13 128 TOPO 35884.000 1000.000 128000.0 35947.5000 10 RR LL 12 EVLA_KA#A1C1#14 128 TOPO 36012.000 1000.000 128000.0 36075.5000 10 RR LL 13 EVLA_KA#A1C1#15 128 TOPO 36140.000 1000.000 128000.0 36203.5000 10 RR LL 14 EVLA_KA#A1C1#16 128 TOPO 36268.000 1000.000 128000.0 36331.5000 10 RR LL 15 EVLA_KA#A1C1#17 128 TOPO 36396.000 1000.000 128000.0 36459.5000 10 RR LL 16 EVLA_KA#A2C2#18 128 TOPO 36476.000 1000.000 128000.0 36539.5000 11 RR LL 17 EVLA_KA#A2C2#19 128 TOPO 36604.000 1000.000 128000.0 36667.5000 11 RR LL 18 EVLA_KA#A2C2#20 128 TOPO 36732.000 1000.000 128000.0 36795.5000 11 RR LL 19 EVLA_KA#A2C2#21 128 TOPO 36860.000 1000.000 128000.0 36923.5000 11 RR LL 20 EVLA_KA#A2C2#22 128 TOPO 36988.000 1000.000 128000.0 37051.5000 11 RR LL 21 EVLA_KA#A2C2#23 128 TOPO 37116.000 1000.000 128000.0 37179.5000 11 RR LL 22 EVLA_KA#A2C2#24 128 TOPO 37244.000 1000.000 128000.0 37307.5000 11 RR LL 23 EVLA_KA#A2C2#25 128 TOPO 37372.000 1000.000 128000.0 37435.5000 11 RR LL 24 EVLA_KA#A2C2#26 128 TOPO 37500.000 1000.000 128000.0 37563.5000 11 RR LL 25 EVLA_KA#A2C2#27 128 TOPO 37628.000 1000.000 128000.0 37691.5000 11 RR LL 26 EVLA_KA#A2C2#28 128 TOPO 37756.000 1000.000 128000.0 37819.5000 11 RR LL 27 EVLA_KA#A2C2#29 128 TOPO 37884.000 1000.000 128000.0 37947.5000 11 RR LL 28 EVLA_KA#A2C2#30 128 TOPO 38012.000 1000.000 128000.0 38075.5000 11 RR LL 29 EVLA_KA#A2C2#31 128 TOPO 38140.000 1000.000 128000.0 38203.5000 11 RR LL 30 EVLA_KA#A2C2#32 128 TOPO 38268.000 1000.000 128000.0 38331.5000 11 RR LL 31 EVLA_KA#A2C2#33 128 TOPO 38396.000 1000.000 128000.0 38459.5000 11 RR LL 32 EVLA_KA#B1D1#34 128 TOPO 26976.000 1000.000 128000.0 27039.5000 13 RR LL 33 EVLA_KA#B1D1#35 128 TOPO 27104.000 1000.000 128000.0 27167.5000 13 RR LL 34 EVLA_KA#B1D1#36 128 TOPO 27232.000 1000.000 128000.0 27295.5000 13 RR LL 35 EVLA_KA#B1D1#37 128 TOPO 27360.000 1000.000 128000.0 27423.5000 13 RR LL 36 EVLA_KA#B1D1#38 128 TOPO 27488.000 1000.000 128000.0 27551.5000 13 RR LL 37 EVLA_KA#B1D1#39 128 TOPO 27616.000 1000.000 128000.0 27679.5000 13 RR LL 38 EVLA_KA#B1D1#40 128 TOPO 27744.000 1000.000 128000.0 27807.5000 13 RR LL 39 EVLA_KA#B1D1#41 128 TOPO 27872.000 1000.000 128000.0 27935.5000 13 RR LL 40 EVLA_KA#B1D1#42 128 TOPO 28000.000 1000.000 128000.0 28063.5000 13 RR LL 41 EVLA_KA#B1D1#43 128 TOPO 28128.000 1000.000 128000.0 28191.5000 13 RR LL 42 EVLA_KA#B1D1#44 128 TOPO 28256.000 1000.000 128000.0 28319.5000 13 RR LL 43 EVLA_KA#B1D1#45 128 TOPO 28384.000 1000.000 128000.0 28447.5000 13 RR LL 44 EVLA_KA#B1D1#46 128 TOPO 28512.000 1000.000 128000.0 28575.5000 13 RR LL 45 EVLA_KA#B1D1#47 128 TOPO 28640.000 1000.000 128000.0 28703.5000 13 RR LL 46 EVLA_KA#B1D1#48 128 TOPO 28768.000 1000.000 128000.0 28831.5000 13 RR LL 47 EVLA_KA#B1D1#49 128 TOPO 28896.000 1000.000 128000.0 28959.5000 13 RR LL 48 EVLA_KA#B2D2#50 128 TOPO 28976.000 1000.000 128000.0 29039.5000 14 RR LL 49 EVLA_KA#B2D2#51 128 TOPO 29104.000 1000.000 128000.0 29167.5000 14 RR LL 50 EVLA_KA#B2D2#52 128 TOPO 29232.000 1000.000 128000.0 29295.5000 14 RR LL 51 EVLA_KA#B2D2#53 128 TOPO 29360.000 1000.000 128000.0 29423.5000 14 RR LL 52 EVLA_KA#B2D2#54 128 TOPO 29488.000 1000.000 128000.0 29551.5000 14 RR LL 53 EVLA_KA#B2D2#55 128 TOPO 29616.000 1000.000 128000.0 29679.5000 14 RR LL 54 EVLA_KA#B2D2#56 128 TOPO 29744.000 1000.000 128000.0 29807.5000 14 RR LL 55 EVLA_KA#B2D2#57 128 TOPO 29872.000 1000.000 128000.0 29935.5000 14 RR LL 56 EVLA_KA#B2D2#58 128 TOPO 30000.000 1000.000 128000.0 30063.5000 14 RR LL 57 EVLA_KA#B2D2#59 128 TOPO 30128.000 1000.000 128000.0 30191.5000 14 RR LL 58 EVLA_KA#B2D2#60 128 TOPO 30256.000 1000.000 128000.0 30319.5000 14 RR LL 59 EVLA_KA#B2D2#61 128 TOPO 30384.000 1000.000 128000.0 30447.5000 14 RR LL 60 EVLA_KA#B2D2#62 128 TOPO 30512.000 1000.000 128000.0 30575.5000 14 RR LL 61 EVLA_KA#B2D2#63 128 TOPO 30640.000 1000.000 128000.0 30703.5000 14 RR LL 62 EVLA_KA#B2D2#64 128 TOPO 30768.000 1000.000 128000.0 30831.5000 14 RR LL 63 EVLA_KA#B2D2#65 128 TOPO 30896.000 1000.000 128000.0 30959.5000 14 RR LL Sources: 64 ID Name SpwId RestFreq(MHz) SysVel(km/s) 0 3c84-J0319+413 0 - - 0 3c84-J0319+413 1 - - 0 3c84-J0319+413 2 - - 0 3c84-J0319+413 3 - - 0 3c84-J0319+413 4 - - 0 3c84-J0319+413 5 - - 0 3c84-J0319+413 6 - - 0 3c84-J0319+413 7 - - 0 3c84-J0319+413 8 - - 0 3c84-J0319+413 9 - - 0 3c84-J0319+413 10 - - 0 3c84-J0319+413 11 - - 0 3c84-J0319+413 12 - - 0 3c84-J0319+413 13 - - 0 3c84-J0319+413 14 - - 0 3c84-J0319+413 15 - - 0 3c84-J0319+413 16 - - 0 3c84-J0319+413 17 - - 0 3c84-J0319+413 18 - - 0 3c84-J0319+413 19 - - 0 3c84-J0319+413 20 - - 0 3c84-J0319+413 21 - - 0 3c84-J0319+413 22 - - 0 3c84-J0319+413 23 - - 0 3c84-J0319+413 24 - - 0 3c84-J0319+413 25 - - 0 3c84-J0319+413 26 - - 0 3c84-J0319+413 27 - - 0 3c84-J0319+413 28 - - 0 3c84-J0319+413 29 - - 0 3c84-J0319+413 30 - - 0 3c84-J0319+413 31 - - 0 3c84-J0319+413 32 - - 0 3c84-J0319+413 33 - - 0 3c84-J0319+413 34 - - 0 3c84-J0319+413 35 - - 0 3c84-J0319+413 36 - - 0 3c84-J0319+413 37 - - 0 3c84-J0319+413 38 - - 0 3c84-J0319+413 39 - - 0 3c84-J0319+413 40 - - 0 3c84-J0319+413 41 - - 0 3c84-J0319+413 42 - - 0 3c84-J0319+413 43 - - 0 3c84-J0319+413 44 - - 0 3c84-J0319+413 45 - - 0 3c84-J0319+413 46 - - 0 3c84-J0319+413 47 - - 0 3c84-J0319+413 48 - - 0 3c84-J0319+413 49 - - 0 3c84-J0319+413 50 - - 0 3c84-J0319+413 51 - - 0 3c84-J0319+413 52 - - 0 3c84-J0319+413 53 - - 0 3c84-J0319+413 54 - - 0 3c84-J0319+413 55 - - 0 3c84-J0319+413 56 - - 0 3c84-J0319+413 57 - - 0 3c84-J0319+413 58 - - 0 3c84-J0319+413 59 - - 0 3c84-J0319+413 60 - - 0 3c84-J0319+413 61 - - 0 3c84-J0319+413 62 - - 0 3c84-J0319+413 63 - - Antennas: 22: ID Name Station Diam. Long. Lat. Offset from array center (m) ITRF Geocentric coordinates (m) East North Elevation x y z 1 ea02 N56 25.0 m -107.37.47.9 +34.00.38.4 -1105.2071 12254.3069 -34.2426 -1600128.383400 -5035104.146500 3565024.672100 2 ea03 N16 25.0 m -107.37.10.9 +33.54.48.0 -155.8511 1426.6436 -9.3827 -1601061.956000 -5041175.880700 3556058.037600 3 ea05 W08 25.0 m -107.37.21.6 +33.53.53.0 -432.1184 -272.1472 -1.5070 -1601614.092200 -5042001.650900 3554652.508900 4 ea06 N32 25.0 m -107.37.22.0 +33.56.33.6 -441.7237 4689.9748 -16.9332 -1600781.042100 -5039347.435200 3558761.533000 5 ea07 E40 25.0 m -107.32.35.4 +33.52.16.9 6908.8279 -3240.7316 39.0057 -1595124.924100 -5045829.461500 3552210.685200 6 ea09 E24 25.0 m -107.35.13.4 +33.53.18.1 2858.1754 -1349.1257 13.7290 -1598663.097500 -5043581.389700 3553767.027800 8 ea11 W56 25.0 m -107.44.26.7 +33.49.54.6 -11333.2153 -7637.6824 15.3542 -1613255.404300 -5042613.085000 3548545.901400 9 ea12 E08 25.0 m -107.36.48.9 +33.53.55.1 407.8285 -206.0065 -3.2272 -1600801.926000 -5042219.366500 3554706.448200 11 ea14 W16 25.0 m -107.37.57.4 +33.53.33.0 -1348.7083 -890.6269 1.3068 -1602592.853600 -5042055.005300 3554140.703900 12 ea15 W72 25.0 m -107.48.24.0 +33.47.41.2 -17419.4730 -11760.2869 14.9578 -1619757.314900 -5042937.673700 3545120.385300 13 ea16 N08 25.0 m -107.37.07.5 +33.54.15.8 -68.9252 433.1901 -5.0683 -1601147.956700 -5041733.824100 3555235.952500 14 ea17 E48 25.0 m -107.30.56.1 +33.51.38.4 9456.5938 -4431.6366 37.9317 -1592894.088800 -5047229.121000 3551221.221100 15 ea18 E72 25.0 m -107.24.42.3 +33.49.18.0 19041.8754 -8769.2059 4.7234 -1584460.867200 -5052385.599300 3547599.997600 17 ea20 N72 25.0 m -107.38.10.5 +34.04.12.2 -1685.6775 18861.8403 -43.4734 -1599557.932000 -5031396.371000 3570494.760600 18 ea21 E64 25.0 m -107.27.00.1 +33.50.06.7 15507.6045 -7263.7280 67.1961 -1587600.190400 -5050575.873800 3548885.396600 19 ea22 N24 25.0 m -107.37.16.1 +33.55.37.7 -290.3745 2961.8582 -12.2374 -1600930.087700 -5040316.398500 3557330.387000 20 ea23 N64 25.0 m -107.37.58.7 +34.02.20.5 -1382.3750 15410.1463 -40.6373 -1599855.675100 -5033332.371000 3567636.622500 21 ea24 W40 25.0 m -107.41.13.5 +33.51.43.1 -6377.9740 -4286.7919 8.2191 -1607962.456900 -5042338.214500 3551324.943600 22 ea25 W48 25.0 m -107.42.44.3 +33.50.52.1 -8707.9407 -5861.7854 15.5265 -1610451.925400 -5042471.123100 3550021.056800 23 ea26 W32 25.0 m -107.39.54.8 +33.52.27.2 -4359.4561 -2923.1223 11.7579 -1605808.647100 -5042230.071500 3552459.203400 24 ea27 E16 25.0 m -107.36.09.8 +33.53.40.0 1410.0316 -673.4696 -0.7909 -1599926.110000 -5042772.967300 3554319.791200 25 ea28 N40 25.0 m -107.37.29.5 +33.57.44.4 -633.6167 6878.5984 -20.7748 -1600592.764000 -5038121.352000 3560574.847300
We have trimmed to MS to contain only one scan on the bandpass calibrator 3C84, but retained all 64 spectral windows, each 128MHz wide and containing 128 1MHz channels.
Calibrating delays and initial bandpass solutions
As a first step, we use an antenna that is near the center of the array and has a minimum of flags. The array can be mapped with plotants:
# In CASA: phase only calibration
plotants(vis='G192-BP.ms')
although the plot is a bit crowded, a zoom in shows that ea05 sits close to the center and appears to be a good choice.
First, we do a phase-only calibration solution on a narrow range of channels near the center of each spectral window on the bandpass calibrator 3C84 to flatten them with respect to time before solving for the bandpass. The range 60~68 should work. Pick a reference antenna near the center of the array -- ea05 is a reasonable choice (see above):
# In CASA: phase only calibration
gaincal(vis='G192-BP.ms', caltable='calG192.G0', \
field='0', spw='*:60~68', \
gaintype='G', refant='ea05', calmode='p', \
solint='int', minsnr=3)
- refant='ea05' : Use ea05 as the reference antenna
- solint='int' : Do a per-integration solve (every 6 seconds, since we've time-averaged the data).
- minsnr=3 : Apply a minimum signal-to-noise cutoff. Solutions with less than this value will be flagged.
- gaintable is not set here as we have already applied pre-calibrations.
Plot the phase solutions (using full phase range, -180 to 180, instead of autorange):
# In CASA
plotcal(caltable='calG192.G0', xaxis='time', yaxis='phase', \
iteration='antenna', plotrange=[-1,-1,-180,180])
The first panel is blanked as ea01 is completely flagged. Step through the antenna-based solutions, here they look good (and fairly flat over the scans).
NOTE: When you are done plotting and want to use the calibration table in another task (e.g., for subsequent calibration or viewing with plotms), use the Quit button on the GUI to dismiss the plotter and free-up the lock on the calibration table. You should see a message in your terminal window saying "Resetting plotcal" which means you are good to go!
If you want to make single-page, multipanel plots (like those shown to the right), particularly for a hardcopy (where it only shows the first page), you can do:
# In CASA
plotcal(caltable='calG192.G0', xaxis='time', yaxis='phase', \
antenna='0~10,12~15', subplot=531, iteration='antenna', \
plotrange=[-1,-1,-180,180], fontsize=8.0, \
markersize=3.0, figfile='plotG192_plotcal_G0p1.png')
plotcal(caltable='calG192.G0', xaxis='time', yaxis='phase', \
antenna='16~26', subplot=531, iteration='antenna', \
plotrange=[-1,-1,-180,180], fontsize=8.0, \
markersize=3.0, figfile='plotG192_plotcal_G0p2.png')
We can now solve for the residual delays that we saw in plotms when we plotted phase vs. frequency. This uses the gaintype='K' option in gaincal. Note that this currently does not do a "global fringe-fitting" solution for delays, but instead does a baseline-based delay solution for all baselines to the reference antenna, treating these as antenna-based delays. In most cases with high-enough S/N to get baseline-based delay solutions, this will suffice. We avoid the edge channels of each spectral window by selecting channels 5~122:
# In CASA: residual delays
gaincal(vis='G192-BP.ms', caltable='calG192.K0', \
field='0', spw='*:5~122', gaintype='K', \
gaintable=['calG192.G0'],
refant='ea05', solint='inf', minsnr=3)
Note that we have also pre-applied our initial phase table, calG192.G0. We can plot the delays, in nanoseconds, as a function of antenna index (you will get one for each spw and polarization):
# In CASA
plotcal(caltable='calG192.K0', xaxis='antenna', yaxis='delay')
The delays range from around -5 to 4 nanoseconds.
Now we solve for the antenna bandpasses using the previous tables:
# In CASA: antenna bandpasses
bandpass(vis='G192_flagged_6s.ms', caltable='calG192.B0', \
gaintable=['calG192.G0', 'calG192.K0'], \
field='0', refant='ea05', solnorm=False, \
bandtype='B', solint='inf')
WARNING: You must set solnorm=False here or later on you will find some offsets among spws due to the way the amplitude scaling adjusts weights internally during solving.
You will see in the terminal some reports of solutions failing due to "Insufficient unflagged antennas" -- note that these are for the channels we flagged earlier.
Plot the resulting bandpasses in amplitude and phase:
# In CASA
plotcal(caltable='calG192.B0', xaxis='freq', yaxis='amp', \
spw='0~31', iteration='antenna')
#
plotcal(caltable='calG192.B0', xaxis='freq', yaxis='amp', \
spw='32~63', iteration='antenna')
#
plotcal(caltable='calG192.B0', xaxis='freq', yaxis='phase', \
iteration='antenna', spw='0~31', \
plotrange=[-1,-1,-180,180])
#
plotcal(caltable='calG192.B0', xaxis='freq', yaxis='phase', \
iteration='antenna', spw='32~63', \
plotrange=[-1,-1,-180,180])
In the bandpass phases you no longer see the residual antenna delays (just residual spw phase offsets from the delay solution registration), but there are some band edge effects apparent.
Bootstrapping the bandpass calibrator spectrum
Since there is no a priori spectral information for our chosen bandpass calibrator, 3C84, we need to bootstrap to find its spectral index, then recalibrate with this information in order to avoid folding the intrinsic spectral shape of 3C84 into our calibration.
First, we use the initial round of bandpass calibration to create gain solutions for the flux and bandpass calibrators:
# In CASA: flux and bandpass calibrators gain
gaincal(vis='G192_flagged_6s.ms', caltable='calG192.G1', field='0', \
gaintable=['calG192.K0', 'calG192.B0'], \
gaintype='G', refant='ea05', calmode='ap', solint='30s', minsnr=3)
Now let's have a look at the phase and amplitude solutions, iterating over antenna. We will look at the flux calibrator (3C147) and bandpass calibrator (3C84) individually since they're widely separated in time:
# In CASA
plotcal(caltable='calG192.G1', xaxis='time', yaxis='amp', \
field='0', iteration='antenna')
#
plotcal(caltable='calG192.G1', xaxis='time', yaxis='amp', \
field='3', iteration='antenna')
#
plotcal(caltable='calG192.G1', xaxis='time', yaxis='phase', \
iteration='antenna', plotrange=[-1,-1,-180,180], \
field='0')
#
plotcal(caltable='calG192.G1', xaxis='time', yaxis='phase', \
iteration='antenna', plotrange=[-1,-1,-180,180], \
field='3')
The solutions all look reasonable and relatively constant with time.
Now that we have gain solutions for the flux and bandpass calibrators, we can use fluxscale to scale the gain amplitudes of the bandpass calibrator:
# In CASA: bandpass calibrator gain amplitudes scaling
flux1 = fluxscale(vis='G192_flagged_6s.ms', caltable='calG192.G1', \
fluxtable='calG192.F1', reference='0', \
transfer='3', listfile='3C84.fluxinfo', fitorder=1)
- flux1 = fluxscale(...): by providing a variable flux1, we allow fluxscale to use this for the output Python dictionary it returns with lots of information about the flux scaling. You can inspect the output dictionary flux1 by typing "print flux1" at the CASA command line.
- fluxtable='calG192.F1': this is the output scaled gain table. Since we are only using this to find the spectral index of 3C84, we won't be using this table.
- listfile='3C84.fluxinfo': an output file that contains the derived flux values and fit information.
- fitorder=1: only find a spectral index, ignoring curvature in the spectrum.
The last line in the file (and displayed in the logger) shows:
Fitted spectrum for 3c84-J0319+413 with fitorder=1: Flux density = 31.454 +/- 0.0310638 (freq=32.5128 GHz) spidx=-0.493668 +/- 0.00820698
Using the information in the returned flux dictionary, we can plot the derived spectrum:
# In CASA
freq = flux1['freq'] / 1e9
spw_list = range(0,64)
spw_str = []
for i in spw_list:
thisspw = str(i)
spw_str.append(thisspw)
bootstrapped_fluxes = []
for j in spw_str:
thisflux = flux1['3'][j]['fluxd'][0]
if thisflux ==None:
continue
else:
bootstrapped_fluxes.append(thisflux)
pl.clf()
pl.plot(freq, bootstrapped_fluxes, 'bo')
pl.xlabel('Frequency (GHz)')
pl.ylabel('Flux Density (Jy)')
pl.title('3C84')
pl.show()
Note the bump around 37 GHz -- what is this? We will not be able to account for it with the simple spectral index model, but still, ours is a good first approximation.
We can use the model from fluxscale to fill the MODEL column with 3C84's spectral information using setjy:
# In CASA: spectral information
setjy(vis='G192_flagged_6s.ms', field='3', scalebychan=True, \
standard = 'manual', fluxdensity=[29.8756, 0, 0, 0], spix=-0.598929, \
reffreq='32.4488GHz')
Checking with plotms that the data have been appropriately filled:
# In CASA
plotms(vis='G192_flagged_6s.ms', field='3', antenna='ea05&ea02', \
xaxis='freq', yaxis='amp', ydatacolumn='model')
Finally, we redo the previous calibration using this new model information. Although the commands are the same as what we issued earlier, keep in mind that the model values for the bandpass calibrator have changed, and therefore the results of these calibration calculations will differ:
# In CASA: phase only recalibration
gaincal(vis='G192_flagged_6s.ms', caltable='calG192.G0.b', \
field='3', spw='*:60~68', \
gaintable=['calG192.antpos', 'calG192.gaincurve', \
'calG192.requantizer', 'calG192.opacity'], \
gaintype='G', refant='ea05', calmode='p', \
solint='int', minsnr=3)
# In CASA: residual delays recalibration
gaincal(vis='G192_flagged_6s.ms', caltable='calG192.K0.b', \
gaintable=['calG192.antpos', 'calG192.gaincurve', 'calG192.requantizer', \
'calG192.opacity', 'calG192.G0.b'], \
field='3', spw='*:5~122', gaintype='K', \
refant='ea05', solint='inf', minsnr=3)
# In CASA: antenna bandpasses recalibration
bandpass(vis='G192_flagged_6s.ms', caltable='calG192.B0.b', \
gaintable=['calG192.antpos', 'calG192.gaincurve', 'calG192.requantizer', \
'calG192.opacity', 'calG192.G0.b', 'calG192.K0.b'], \
field='3', refant='ea05', solnorm=False, \
bandtype='B', solint='inf')
It's a good idea to inspect these solutions as well:
# In CASA
plotcal(caltable='calG192.B0.b', xaxis='freq', yaxis='amp', \
spw='0~31', iteration='antenna')
#
plotcal(caltable='calG192.B0.b', xaxis='freq', yaxis='amp', \
spw='32~63', iteration='antenna')
#
plotcal(caltable='calG192.B0.b', xaxis='freq', yaxis='phase', \
iteration='antenna', spw='0~31', \
plotrange=[-1,-1,-180,180])
#
plotcal(caltable='calG192.B0.b', xaxis='freq', yaxis='phase', \
iteration='antenna', spw='32~63', \
plotrange=[-1,-1,-180,180])
They look virtually unchanged from the previous solutions, with the exception that the amplitude scaling is corrected for the spectrum of 3C84. Now that we have the final version of our bandpass calibration, we can proceed to the full calibration of the dataset.