VLA CASA Bandpass Slope-CASA4.5.2: Difference between revisions
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MeasurementSet Name: /lustre/aoc/sciops/jott/casa/topicalguide/bandpass/G192_6s-BP.ms MS Version 2 | |||
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Revision as of 21:03, 13 April 2016
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. 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_6s-BP.ms.tar.gz (dataset size: 2.9 GB)
Your first step will be to unzip and untar the file in a terminal (before you start CASA):
tar -xzvf G192_6s.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_6s-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_6s-BP.ms MS Version 2
================================================================================
Observer: Dr. Debra Shepherd Project: uid://evla/pdb/7303457
Observation: EVLA
Data records: 1537600 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 1537600 [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 1537600
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: 26:
ID Name Station Diam. Long. Lat. Offset from array center (m) ITRF Geocentric coordinates (m)
East North Elevation x y z
0 ea01 N48 25.0 m -107.37.38.1 +33.59.06.2 -855.2759 9405.9595 -25.9351 -1600374.885000 -5036704.201000 3562667.881900
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
7 ea10 E32 25.0 m -107.34.01.5 +33.52.50.3 4701.6588 -2209.7063 25.2191 -1597053.120700 -5044604.691600 3553059.009300
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
10 ea13 W24 25.0 m -107.38.49.0 +33.53.04.0 -2673.3434 -1784.5870 10.4960 -1604008.742800 -5042135.827600 3553403.728800
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
16 ea19 W64 25.0 m -107.46.20.1 +33.48.50.9 -14240.7600 -9606.2738 17.1055 -1616361.584300 -5042770.519200 3546911.442800
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
##### End Task: listobs #####
##########################################
This task displays a lot of information about the MS. We can see that the observation was performed with the EVLA over an integration time of 4557 seconds (1.3 hours). The number of data records (10,061,248) is approximately equal to the number of baselines (N_antenna * [N_antenna - 1] / 2) X the number of integrations (observing time / time-average binning) X the number of spectral windows. For this observation, this is roughly 325 baselines (26X25/2) X 760 integrations (4557s total/6s avg) X 64 spectral windows = 15,808,000. Note that this is high by ~50%; this is because the "total time" reported is simply (start time) - (end time) of the MS, which includes periods of slewing, flagged data, and scans that were excluded from the final MS. Extra exercise: examine the MS using browsetable to see what a data record looks like (equivalent to a row, as displayed by this task).
The most useful parts of the listobs output are the scan, field, and spectral window listings. From the spectral window information, we can see that there are a total of 64 (0 through 63) spectral windows in this dataset, each with 128 channels, and that they are all at Ka-band (which spans 26.5 - 40.0 GHz).
The field listing shows four sources:
- 3C147 (Field ID 0), the flux calibration source;
- J0603+174 (1), used for calibrating the complex gains;
- G192.16-3.84 (2), the science target; and
- 3c84 (3), used for calibrating the spectral bandpass.
Note the rapid switching between G192 and J0603: this will help us accurately calculate and transfer the gain phase solutions for these high-frequency data. Note that the original MS also included reference pointing calibration scans at X-band, but since the pointing solutions were already applied during observing, we did not retain these scans (in the interest of limiting dataset size).
Calibrating delays and initial bandpass solutions
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_flagged_6s.ms', caltable='calG192.G0', \
field='3', spw='*:60~68', \
gaintable=['calG192.antpos','calG192.gaincurve', \
'calG192.requantizer','calG192.opacity'], \
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=['calG192.antpos', 'calG192.gaincurve', 'calG192.requantizer', 'calG192.opacity'] : Pre-apply the antenna position corrections, gaincurve, opacity, and requantizer calibration tables.
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])
Step through the antenna-based solutions. 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_flagged_6s.ms', caltable='calG192.K0', \
gaintable=['calG192.antpos', 'calG192.gaincurve', 'calG192.requantizer', \
'calG192.opacity', 'calG192.G0'], \
field='3', spw='*:5~122', gaintype='K', \
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.antpos', 'calG192.gaincurve', 'calG192.requantizer', \
'calG192.opacity', 'calG192.G0', 'calG192.K0'], \
field='3', 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.
This is the first amplitude-scaling calibration that we do, so it is important to have used the calG192.gaincurve caltable (or set gaincurve=True) as well as the calG192.opacity caltable (or set opacity appropriately).
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
Unfortunately, our flux density calibrator was not bright enough at Ka-band to use as the bandpass calibration source. 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='0,3', \
gaintable=['calG192.antpos', 'calG192.gaincurve', 'calG192.requantizer', \
'calG192.opacity', '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.
