NGC 5921: red-shifted HI emission 6.5.2: Difference between revisions

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Where:
Where:
     vis='filename.ms'.      # sets the name of the input measurement set
     vis='filename.ms'.      # sets the name of the input measurement set

Revision as of 18:09, 23 November 2022

This version is being edited. See NGC 5921: red-shifted HI emission for the current version of this cookbook!

Disclaimer: Due to continuous CASA software updates, GUI images may look different on more recent versions than those shown here.

Last checked on CASA Version 5.7.2.

Overview

The technique used to calibrate and image continuum datasets generally applies to spectral line observations, except that an additional calibration step is required. Bandpass calibration flattens the spectral response of the observations, ensuring that spectral channel images are properly calibrated in amplitude and phase.

The following tutorial derives from an annotated script provided in the CASA Cookbook. The script is largely reproduced and additionally annotated with figures and illustrations. It is assumed that this tutorial will be used interactively, and so interactive pauses in the original script have been removed.

DATA: The data are included with the CASA installation.

Setting up the CASA environment

Start up CASA in the directory you want to use.

# in bash
mkdir NGC5921
cd NGC5921
casa


We'll use a python os command to get the appropriate CASA path for your installation in order to import the data. The use of os.environ.get is explained in the Appendix. This is not part of the data reduction, just an initial step to find where the example dataset has been stored when CASA was installed – you will not normally need to do this if you are working on your own data.

# In CASA
%cpaste

# Press Enter or Return, then copy/paste the following:
import os
pathname=os.environ.get('CASAPATH').split()[0]
fitsdata=pathname+'/data/demo/NGC5921.fits'
--

Scripts are of course modified and repeated to the satisfaction of observer. To help clean up the bookkeeping and further avoid issues of write privileges, remove any prior versions of the measurement set and calibration tables.

This should be done with the rmtables task, either interactively or using rmtables('table_name'), in preference to the operating system rm -rf command, as rmtables also clears data in the CASA cache.


Import the data

The next step is to import the multisource UVFITS data to a CASA measurement set via the importuvfits task. This task is used to read in data UVFITS data from the legacy VLA or other telescope; for reading in EVLA data in ASDM format the task importasdm would be used.

Note that you can set each parameter for any particular task one-by-one ('interactive CASA', or you can supply the task and input parameters with a single command ('pseudo-interactive CASA').

# Interactive CASA
default importuvfits
inp
fitsfile = fitsdata
vis='ngc5921.demo.ms'
inp
saveinputs('importuvfits', 'ngc5921.demo.importuvfits.saved')
go 
# Pseudo-interactive CASA
importuvfits(fitsfile=fitsdata,vis="ngc5921.demo.ms")
Where:
    default importuvfits     # loads importuvfits with the default parameters
    inp                      # lists the inputs available for this task
    fitsfile='filename.fits' # sets the filename of the fits file to use
    vis='filename.ms'        # sets the name of the output measurement set created (.ms)
    go                       # executes the task with the given inputs

A few things to note:

  • The first inp reveals three parameters with defaults fitsfile=' '; vis=' '; antnamescheme='old'. We only set two of these, leaving antnamescheme='old' set to the default.
  • fitsfile=fitsdata sets the value of fitsfile to the fitsdata string variable defined earlier. If you were using your own dataset, you could enter it directly as a string (e.g., fitsfile='mydata.fits') or define it as a variable before setting fitsfile (e.g. fitsdata='mydata.fits', then fitsfile=fitsdata). You should avoid using 'fitsfile' as a variable name, as this will be overwritten by 'default importuvfits' or 'tget importuvfits'.
  • The second inp shows that the string variable fitsdata, defined earlier, has been expanded. A valid entry shows in blue, while an invalid entry shows in red. Default entries (as for antnamescheme) show in black.

Inspecting the data

The next step is to inspect to measurement set using the listobs task. This provides almost all relevant observational parameters – to the extent that the exist in the dataset – such as correlator setup (frequencies, bandwidths, channel number and widths, polarization products), sources, scans, scan intents, and antenna locations. Setting verbose=True (the default, so not included in the commands below) will display all of the contents of the raw data and setting listfile='listobs.txt' will create a text file you can refer to later (if this is not set, the output will instead display in the CASA Logger). Some of the parameters (such as scan intents) are not available for legacy VLA data such as this, so are left blank in the output.

# Interactive CASA
default listobs
inp
vis='ngc5921.demo.ms'
listfile='listobs.txt'
inp
go
listobs(vis='ngc5921.demo.ms', listfile='listobs.txt')

You will get a summary, not well formatted for human readability, in the CASA terminal. It is best to ignore this and look at the output text file, which has more information and is better formatted. This looks like:

================================================================================
           MeasurementSet Name:  <path to directory>/ngc5921.demo.ms      MS Version 2
================================================================================
   Observer: TEST     Project:   
Observation: VLA
Data records: 22653       Total elapsed time = 5310 seconds
   Observed from   13-Apr-1995/09:18:45.0   to   13-Apr-1995/10:47:15.0 (TAI)

   ObservationID = 0         ArrayID = 0
  Date        Timerange (TAI)          Scan  FldId FieldName             nRows     SpwIds   Average Interval(s)    ScanIntent
  13-Apr-1995/09:18:45.0 - 09:24:45.0     1      0 1331+30500002_0           4509  [0]  [30] 
              09:27:15.0 - 09:29:45.0     2      1 1445+09900002_0           1890  [0]  [30] 
              09:32:45.0 - 09:48:15.0     3      2 N5921_2                   6048  [0]  [30] 
              09:50:15.0 - 09:51:15.0     4      1 1445+09900002_0            756  [0]  [30] 
              10:21:45.0 - 10:23:15.0     5      1 1445+09900002_0           1134  [0]  [30] 
              10:25:45.0 - 10:43:15.0     6      2 N5921_2                   6804  [0]  [30] 
              10:45:15.0 - 10:47:15.0     7      1 1445+09900002_0           1512  [0]  [30] 
           (nRows = Total number of rows per scan) 
Fields: 3
  ID   Code Name                RA               Decl           Epoch   SrcId      nRows
  0         1331+30500002_0     13:31:08.287300 +30.30.32.95900 J2000   0           4509
  1         1445+09900002_0     14:45:16.465600 +09.58.36.07300 J2000   1           5292
  2         N5921_2             15:22:00.000000 +05.04.00.00000 J2000   2          12852
Spectral Windows:  (1 unique spectral windows and 1 unique polarization setups)
  SpwID  Name   #Chans   Frame   Ch0(MHz)  ChanWid(kHz)  TotBW(kHz) CtrFreq(MHz)  Corrs  
  0      none      63   LSRK    1412.665        24.414      1550.2   1413.4219   RR  LL
Sources: 3
  ID   Name                SpwId RestFreq(MHz)  SysVel(km/s) 
  0    1331+30500002_0     0     1420.405752    0            
  1    1445+09900002_0     0     1420.405752    0            
  2    N5921_2             0     1420.405752    0            
Antennas: 27:
  ID   Name  Station   Diam.    Long.         Lat.                Offset from array center (m)                ITRF Geocentric coordinates (m)        
                                                                     East         North     Elevation               x               y               z
  0    1     VLA:N7    25.0 m   -107.37.07.2  +33.54.12.9        -30.2623      345.7477       -0.8872 -1601155.613187 -5041783.882304  3555162.343090
  1    2     VLA:W1    25.0 m   -107.37.05.9  +33.54.00.5          3.5004      -39.7725        0.9883 -1601188.991307 -5042000.530918  3554843.409670
  2    3     VLA:W2    25.0 m   -107.37.07.4  +33.54.00.9        -37.1358      -25.0262        1.0383 -1601225.244615 -5041980.431775  3554855.677111
  3    4     VLA:E1    25.0 m   -107.37.05.7  +33.53.59.2          6.9833      -79.6414        1.1565 -1601192.444530 -5042022.911771  3554810.411780
  4    5     VLA:E3    25.0 m   -107.37.02.8  +33.54.00.5         81.5188      -37.9632        1.0246 -1601114.335629 -5042023.211477  3554844.931655
  5    6     VLA:E9    25.0 m   -107.36.45.1  +33.53.53.6        536.8977     -250.3175        0.1183 -1600715.915813 -5042273.186780  3554668.167811
  6    7     VLA:E6    25.0 m   -107.36.55.6  +33.53.57.7        267.7566     -124.8145        1.2815 -1600951.554888 -5042125.947753  3554772.987072
  7    8     VLA:W8    25.0 m   -107.37.21.6  +33.53.53.0       -401.2640     -270.6305        2.2293 -1601614.059494 -5042001.699973  3554652.484758
  8    9     VLA:N5    25.0 m   -107.37.06.7  +33.54.08.0        -16.9948      194.1215       -0.1368 -1601168.756077 -5041869.099542  3555036.914367
  9    10    VLA:W3    25.0 m   -107.37.08.9  +33.54.00.1        -74.4964      -50.1921        1.1608 -1601265.132224 -5041982.597979  3554834.857504
  10   11    VLA:N4    25.0 m   -107.37.06.5  +33.54.06.1        -11.7487      134.3686        0.1774 -1601173.922897 -5041902.701204  3554987.495105
  11   12    VLA:W5    25.0 m   -107.37.13.0  +33.53.57.8       -179.2554     -120.8635        1.4872 -1601376.990711 -5041988.712764  3554776.381187
  12   13    VLA:N3    25.0 m   -107.37.06.3  +33.54.04.8         -8.2438       94.5297        0.3947 -1601177.362708 -5041925.112425  3554954.550128
  13   14    VLA:N1    25.0 m   -107.37.06.0  +33.54.01.8         -0.0030        0.0445        0.8773 -1601185.580779 -5041978.216463  3554876.396287
  14   15    VLA:N2    25.0 m   -107.37.06.2  +33.54.03.5         -4.7904       54.7090        0.5774 -1601180.839839 -5041947.470902  3554921.600805
  15   16    VLA:E7    25.0 m   -107.36.52.4  +33.53.56.5        348.8969     -162.6653        1.0336 -1600880.544215 -5042170.427468  3554741.431900
  16   17    VLA:E8    25.0 m   -107.36.48.9  +33.53.55.1        438.6654     -204.5038        0.5027 -1600801.910482 -5042219.412805  3554706.408864
  17   18    VLA:W4    25.0 m   -107.37.10.8  +33.53.59.1       -122.0163      -82.2819        1.2624 -1601315.866196 -5041985.352573  3554808.279150
  18   19    VLA:E5    25.0 m   -107.36.58.4  +33.53.58.8        195.8349      -91.2758        1.2155 -1601014.427180 -5042086.300814  3554800.787928
  19   20    VLA:W9    25.0 m   -107.37.25.1  +33.53.51.0       -491.1000     -331.2429        2.5539 -1601709.998072 -5042006.975455  3554602.355417
  20   21    VLA:W6    25.0 m   -107.37.15.6  +33.53.56.4       -244.9704     -165.2178        1.6861 -1601447.161927 -5041992.554228  3554739.677219
  21   22    VLA:E4    25.0 m   -107.37.00.8  +33.53.59.7        133.6478      -62.2829        1.0919 -1601068.773396 -5042051.970054  3554824.783566
  23   24    VLA:E2    25.0 m   -107.37.04.4  +33.54.01.1         40.6649      -18.9151        0.9550 -1601150.040469 -5042000.665669  3554860.702914
  24   25    VLA:N6    25.0 m   -107.37.06.9  +33.54.10.3        -23.2197      265.3902       -0.4819 -1601162.569974 -5041829.054708  3555095.873969
  25   26    VLA:N9    25.0 m   -107.37.07.8  +33.54.19.0        -46.5533      532.1581       -1.8550 -1601139.422904 -5041679.082136  3555316.518142
  26   27    VLA:N8    25.0 m   -107.37.07.5  +33.54.15.8        -38.0437      434.7201       -1.3387 -1601147.894127 -5041733.868915  3555235.935926
  27   28    VLA:W7    25.0 m   -107.37.18.4  +33.53.54.8       -319.1171     -215.2368        1.9407 -1601526.340031 -5041996.897001  3554698.302182

Key information from listobs

The output of listobs is dense with information, but some facts to note are (working down the file):

  • The observations were taken on 13 April 1995 between 09:18:45 and 10:47:15
  • There are three fields listed under "Fields": 1331+305*, 1445+099* and N5921_2.
    • As this is legacy VLA data, no scan intents are given. However, we can identify 1331+305 (field=0_ as 3C286, the flux and bandpass calibrator, 1445+099 (field=1) as the phase calibrator, and N5921_2 (field=2) as the science target.
  • A single spectral window (IF) is listed under "Spectral Windows", with SpwID = 0.
    • This is divided into 63 channels of 24.414 kHz width, centered on 1413.4219 MHz.
    • The correlations are RR and LL (cross-pols are absent).
  • The three sources listed under "Sources" correspond to the three fields under "Fields", but different information is given linking them to the spectral window(s).
    • All sources are associated with SpwID = 0 (if there were multiple spectral windows, there would be a line for each spectral window, repeating sources observed in multiple windows)
    • The rest frequency is set to the HI frequency and the systemic velocity to 0 km/s.

Log files

EVLA and VLA logs from October 2013 can be accessed via the operator logs] tool. For earlier observations, such as these, the older VLA operator logs page gives logs by month from January 1989. This is a single, large text file for each month and it is necessary to search through to find the relevant observation. For this observation, we find:

************************************************************************
Program:       TEST/VANMOORSEL
Observer:      G. van Moorsel
Date:          Thursday, Apr 13 1995
User Number:   1102
Source File:   528MTST             Subarray:  #1
Observe Mode:  Line                Operator:  T. Perreault

** Weather Information **
Time             Dew Point Temp.   Wind           Bar. Pressure Remarks:
95Apr13 08:49:59 -13.3°C   1.1°C   W @ 1 m/s      794.6mbars    The sky is clear.
95Apr13 10:30:39 -10.9°C   3.3°C   NNW @ 1 m/s    794.1mbars    The sky is clear.

** Visibility Tape Information **
Tape #                 File #                  Time of Final Record:
N6078                   1                      

** Monitor Tape Information **
Tape #                 File #                  Time of Final Record:
N6080                   3                      

Antenna(s) Used:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 24 25 26 27 28 

** Operator Comments **

Start Time         End Time            Form #      Ant #         Downtime
95Apr13 08:46:40                                                 (in Minutes)
Start of observe file. The band(s) used is(are) L   band(s).

Start Time         End Time            Form #      Ant #         Downtime
95Apr13 08:50:00                                                 
On source 1331+305 with all available antennas. 

Start Time         End Time            Form #      Ant #         Downtime
95Apr13 09:50:02                                                 
The test e-mail message from the computer Zia was received. Observe
mail should work fine.
End of program TEST/VANMOORSEL.  Total Downtime = 0.0 minutes (0.0% of total time).


AsciiFileOut Version: 1.00 -- Version Date: March 31, 1995
******************************************

From this we can see that there are no obvious problems – antenna faults or the like – affecting these observations.

Antenna positions

The antenna positions are given in the output from listobs, but a graphical display can be easier to understand and aid in selecting a good reference antenna. This can be plotted using the plotants task.

# Interactive CASA
default plotants
inp
vis='ngc5921.demo.ms'
inp
go
# Psuedo-interactive CASA
plotants(vis='ngc5921.demo.ms')
Where:
    vis='filename.ms'.       # sets the name of the input measurement set
Optional parameters:
    logpos=True              # plots the distance from the center of the array logarithmically
    figfile='antlayout.png'  # saves the plot to the specified file

Flagging

Flag the autocorrelations

We don't need the autocorrelation data, and we can use flagdata to get rid of them. You shouldn't have to specify the measurement set, because the variable vis is already set, but it never hurts to be cautious.

flagdata(vis="ngc5921.demo.ms", autocorr=True)

CASA issues a warning when running this command, but this can be disregarded.

Interactive Flagging

Plotms settings for flagging spectral line data. Click to enlarge.

plotms is a good tool for flagging spectral line data. Check out the tutorial that describes editing VLA continuum data. Spectral line data of course require some consideration of channels and channel averaging.

plotms()


The figure at right highlights the settings needed for effective editing of a spectral line data set. The key settings are as follows.

  • Specify the measurement set in File; the Browse button allows you to hunt down the measurement set.
  • It's better to edit one source at a time. In the illustrated example, the flux / bandpass calibrator 1331+305* is displayed.
  • Average the channels. First, specify the central channels to remove band edge effects. Channels 6~56 in the first spectral window (IF) are appropriate (see #Inspect the Bandpass Response Curve, below). In plotms() specify: spw=0:6~56. In the Channel Averaging box, enter 51 channels to average over all channels in the given range.
  • Ideally you want the channels to have the same (u, v) coverage (projected baseline spacings as viewed from the source); otherwise, the beam (point spread function) will be different for each channel. Therefore, if you flag data from a given channel it's usually a good idea to flag those data from all channels. Under the Flagging tab, specify Extend flags to Channel.


With these settings, interactive flagging proceeds as for continuum data. When you're satisfied with the edits, File → Quit to return to the CASA prompt.

Calibration

Calibration of spectral line data broadly follows the approach for continuum data, except that the amplitude and phase corrections are a function of frequency and so must be corrected by bandpass calibration. The basic calibration steps follow.

  • Set the flux scale of the primary calibrator, here, 1331+305 = 3C 286.
  • Determine bandpass corrections based on the primary calibrator. In the script that follows, the bandpass calibration will be stored in ngc5921.demo.bcal.
  • Inspect the bandpass correction to determine viable channels for averaging and imaging. We want to toss out end channels where the response is poor.
  • Determine the gain calibrations on the bandpass-corrected and channel-averaged data. In this step, we effectively turn the spectral line data into a single-channel continuum data set and calibrate accordingly. The calibration is first stored in ngc5921.demo.gcal. In the second part of this step we correct the fluxscale of the .gcal table, and store the final calibration solutions with correct fluxes in ngc5921.demo.fluxscale (this is the table that needs to be applied later to the data, not the .gcal version).
  • Inspect the gain calibration solutions to look for any aberrant solutions that hint at bad calibrator data.
  • Apply the calibration solutions to the source (N5921_2). This action literally adds a new column of data to the measurement set. This new column contains the data with the gain calibration and bandpass calibration applied, but it does not overwrite the raw data in case the calibration needs revision.


Setting the Flux Scale

setjy generates a source model for the primary calibrator, 1331+305 = 3C286. From CASA 5.3+ the default standard is Perley-Butler 2017, and includes resolved structure of the calibrators. This is 1.4GHz D-config and 1331+305 is sufficiently unresolved that, in principle, we don't need a model image; however, here we proceed with applying the detailed model, as a good practice.

setjy also looks up the radio SED for common flux calibrators and automatically assigns the total flux density.

# 1331+305 = 3C286 is our primary calibrator. Use the wildcard on the end of the source name
setjy(vis='ngc5921.demo.ms', field='1331+305*', model='3C286_L.im')


A summary of the operation is sent to the logger window. Here's a listing of the output.

2018-09-12 20:43:38 INFO setjy	##########################################
2018-09-12 20:43:38 INFO setjy	##### Begin Task: setjy              #####
2018-09-12 20:43:38 INFO setjy	setjy(vis="ngc5921.demo.ms",field="1331+305*",spw="",selectdata=False,timerange="",
2018-09-12 20:43:38 INFO setjy	        scan="",intent="",observation="",scalebychan=True,standard="Perley-Butler 2017",
2018-09-12 20:43:38 INFO setjy	        model="3C286_L.im",modimage="",listmodels=False,fluxdensity=-1,spix=0.0,
2018-09-12 20:43:38 INFO setjy	        reffreq="1GHz",polindex=[],polangle=[],rotmeas=0.0,fluxdict={},
2018-09-12 20:43:38 INFO setjy	        useephemdir=False,interpolation="nearest",usescratch=False,ismms=False)
2018-09-12 20:43:38 INFO setjy	{'field': '1331+305*'}
2018-09-12 20:43:38 INFO Imager	Opening MeasurementSet [...]
2018-09-12 20:43:38 INFO setjy	Using /home/casa/data/distro/nrao/VLA/CalModels/3C286_L.im for modimage.
2018-09-12 20:43:38 INFO setjy	CASA Version 5.3.0-143  
2018-09-12 20:43:38 INFO setjy	   
2018-09-12 20:43:39 INFO imager	Using channel dependent flux densities
2018-09-12 20:43:39 INFO imager	Selected 4509 out of 22653 rows.
2018-09-12 20:43:39 INFO imager	1331+30500002_0 (fld ind 0) spw 0  [I=15.016, Q=0, U=0, V=0] Jy @ 1.4127e+09Hz, (Perley-Butler 2017)
2018-09-12 20:43:40 INFO imager	Using model image /home/casa/data/distro/nrao/VLA/CalModels/3C286_L.im
2018-09-12 20:43:40 INFO imager	Scaling spw(s) [0]'s model image by channel to  I = 15.0159, 15.0118, 15.0077 Jy @(1.41265e+09, 1.41343e+09, 1.41419e+09)Hz (LSRK) for visibility prediction (a few representative values are shown).
2018-09-12 20:43:40 INFO imager	The model image's reference pixel is 0.00904522 arcsec from 1331+30500002_0's phase center.
2018-09-12 20:43:40 INFO imager	Will clear any existing model with matching field=1331+30500002_0 and spw=*
2018-09-12 20:43:40 INFO  	Clearing model records in MS header for selected fields.
2018-09-12 20:43:40 INFO  	 1331+30500002_0 (id = 0) deleted.
2018-09-12 20:43:40 INFO imager	Selected 4509 out of 22653 rows.
2018-09-12 20:43:40 INFO setjy	##### End Task: setjy                #####
2018-09-12 20:43:40 INFO setjy	##########################################


Bandpass Calibration

The flux calibrator 1331+305 = 3C 286 now has a model assigned to it. Since the bandwidth of our observations is only 1.55 MHz, the model doesn't change over this narrow range of frequencies, so we can use it to determine amplitude and phase (gain) corrections for each channel independently. The result is the bandpass calibration.

As for any antenna-based calibration scheme, we have to pick an antenna to act as the reference point for the calibration. Any antenna will do, but it's better to pick one near the center of the array. For the remainder of the calibration, we will use refant = '15'.

# We can first do the bandpass on the single 5min scan on 1331+305. At 1.4GHz phase stablility should be sufficient to do this without
# a first (rough) gain calibration. This will give us the relative antenna gain as a function of frequency.
bandpass(vis='ngc5921.demo.ms', caltable='ngc5921.demo.bcal', field='0', selectdata=False, bandtype='B', solint='inf', combine='scan', refant='15')
  • field='0' : Use the flux calibrator 1331+305 = 3C286 (FIELD_ID 0) as bandpass calibrator.
  • bandtype='B' : Choose bandpass solution type. Pick standard time-binned B (rather than BPOLY).
  • solint='inf' and combine='scan' : Set solution interval arbitrarily long (get single bandpass).
  • refant = '15' : Reference antenna Name 15 (15=VLA:N2) (Id 14)


Inspect the Bandpass Response Curve

Bandpass response curves generated by plotms. The solutions for different antennas are indicated by differently colored plotting symbols. Plots for individual antennas can be generated by setting iteraxis = 'antenna' for plotms.

In the gain calibration to follow, we will effectively convert the spectral line data into a continuum data set. Before proceeding, we need to inspect the bandpass calibration to make sure that it contains no bad values and also to inspect which channels to average to produce the continuum data. Plotms is the standard tool for plotting calibration solutions. The following commands produce the figure at right.

# Set up 2x1 panels - upper panel amp vs. channel
plotms(vis='ngc5921.demo.bcal', field='0', gridrows=2, gridcols=1, plotindex=0, rowindex=0, xaxis='channel', yaxis='amp', showgui=True, clearplots=False, coloraxis='antenna1')
# Set up 2x1 panels - lower panel phase vs. channel
plotms(vis='ngc5921.demo.bcal', field='0', gridrows=2, gridcols=1, plotindex=1, rowindex=1, xaxis='channel', yaxis='phase', showgui=True, clearplots=False, coloraxis='antenna1')

By inspection, the amplitude response curve is flat over channels 6~56; that channel range will be used to generate the continuum data for gain calibration. If you want to further inspect the plots interactively and iterate over antenna, set iteraxis = 'antenna'

Notice that plotms is run twice: once to display gain amplitudes as a function of channel (frequency), and again to plot gain phases as a function of channel.


Gain Calibration

From inspection of the bandpass response curve, we can average channels 6~56 to produce continuum data for the calibrators. For VLA data, this averaging is specified through the spw (spectral window) parameter, which takes the form IF:Channel-range, as follows.

spw = '0:6~56'

That is, there is only one spectral window (IF), spw = 0, and we want to average channels 6~56 within that spectral window.

Gain calibrations are otherwise determined as for continuum data.

  • gaincal() is run only on the calibrators, 1331+305 (flux calibrator) and 1445+099 (phase calibrator).
  • The default model for gain calibrations is a 1 Jy point-source. The flux scale is overridden by setjy, which has been performed for the flux calibrator. We need to transfer that flux scale to the phase calibrator using fluxscale().
  • Note that fluxscale() determines the flux density of the phase calibrator and accordingly adjusts its model and calibration solutions. A report of the results are sent to the logger window.
  • Unless you use parameter incremental=True while executing fluxscale() (the default is False), the resulting .fluxscale table will replace the .gcal table at this point. This particularly important in the applycal() stage.
# Armed with the bandpass, we now solve for the time-dependent antenna gains using our previously determined bandpass.
# Note this will automatically be applied to all sources not just the one used to determine the bandpass

gaincal(vis='ngc5921.demo.ms', caltable='ngc5921.demo.gcal', gaintable=['ngc5921.demo.bcal'], interp=['nearest'], field='0,1', spw='0:6~56', gaintype='G', solint='inf', calmode='ap', refant='15')


# Now we will transfer the flux scale to the phase calibrator. 
# We will be using 1331+305 (the source we did setjy on) as our flux standard reference.
# Note its extended name as in the FIELD table summary above (it has a VLA seq number appended)

fluxscale(vis='ngc5921.demo.ms', fluxtable='ngc5921.demo.fluxscale', caltable='ngc5921.demo.gcal', reference='1331*', transfer='1445*')


The output from fluxscale follows. A relatively large uncertainty for the phase calibrator is a sign that something went wrong, perhaps bad solutions in gaincal. Here, the phase calibrator scaled to 2.486 ± 0.001 Jy, which looks reasonable.

2018-09-12 22:38:05 INFO fluxscale	##########################################
2018-09-12 22:38:05 INFO fluxscale	##### Begin Task: fluxscale          #####
2018-09-12 22:38:05 INFO fluxscale	fluxscale(vis="ngc5921.demo.ms",caltable="ngc5921.demo.gcal",fluxtable="ngc5921.demo.fluxscale",reference="1331*",transfer="1445*",
2018-09-12 22:38:05 INFO fluxscale	        listfile="",append=False,refspwmap=[-1],gainthreshold=-1.0,antenna="",
2018-09-12 22:38:05 INFO fluxscale	        timerange="",scan="",incremental=False,fitorder=1,display=False)
2018-09-12 22:38:05 INFO fluxscale	****Using NEW VI2-driven calibrater tool****
2018-09-12 22:38:05 INFO fluxscale	Opening MS: ngc5921.demo.ms for calibration.
2018-09-12 22:38:05 INFO fluxscale	Initializing nominal selection to the whole MS.
2018-09-12 22:38:05 INFO fluxscale	Beginning fluxscale--(MSSelection version)-------
2018-09-12 22:38:05 INFO fluxscale	 Found reference field(s): 1331+30500002_0
2018-09-12 22:38:05 INFO fluxscale	 Found transfer field(s):  1445+09900002_0
2018-09-12 22:38:05 INFO fluxscale	 Flux density for 1445+09900002_0 in SpW=0 (freq=1.41342e+09 Hz) is: 2.52609 +/- 0.00218206 (SNR = 1157.67, N = 54)
2018-09-12 22:38:05 INFO fluxscale	Storing result in ngc5921.demo.fluxscale
2018-09-12 22:38:05 INFO fluxscale	Writing solutions to table: ngc5921.demo.fluxscale
2018-09-12 22:38:06 INFO fluxscale	CASA Version 5.3.0-143  
2018-09-12 22:38:06 INFO fluxscale	   
2018-09-12 22:38:07 INFO fluxscale	##### End Task: fluxscale            #####
2018-09-12 22:38:07 INFO fluxscale	##########################################


Inspect the Calibration Solutions

Gain calibration solutions from gaincal and fluxscale.

Now inspect the results of gaincal. The setup is identical to that used to plot the bandpass response curve. The only change is that we are plotting the gaintable ngc5921.demo.gcal, and we're looking at solutions for both of the calibrator sources. The results are shown at right.

# Set up 2x1 panels - upper panel amp vs. time
plotms(vis='ngc5921.demo.fluxscale', field='0,1', gridrows=2, gridcols=1, plotindex=0, rowindex=0, yaxis='amp', showgui=True, clearplots=False, coloraxis='antenna1')
# Set up 2x1 panels - lower panel phase vs. time
plotms(vis='ngc5921.demo.fluxscale', field='0,1', gridrows=2, gridcols=1, plotindex=1, rowindex=1, yaxis='phase', showgui=True, clearplots=False, coloraxis='antenna1')

The amp and phase coherence looks good. If you want to do this interactively and iterate over antenna, set iteraxis = 'antenna'.


Apply the Solutions

Next, apply the calibration solutions to the calibrators themselves, and finally transfer the calibration solutions by interpolation (or nearest-neighbor sampling) to the source. The relevant task is applycal, which fills out a new column (CORRECTED_DATA) of calibrated data in the measurement set without wiping out the raw data column. The application is identical to that used for continuum data, except that the bandpass table is also included in the calibration. To apply multiple calibrations at once, provide the gaintable parameter with a list of calibration tables, as follows.

gaintable = ['ngc5921.demo.fluxscale', 'ngc5921.demo.bcal']

We want to correct the calibrators using themselves and transfer from 1445+099 to itself and the target N5921. Start with the fluxscale/gain and bandpass tables. We will pick the 1445+099 out of the gain table for transfer and use all of the bandpass table. Also, note that the table .fluxscale has the .gcal solutions with the correct flux scale applied, and so there is no need to invoke the .gcal again in the applycal() command below.

applycal(vis='ngc5921.demo.ms', field='1,2', gaintable=['ngc5921.demo.fluxscale','ngc5921.demo.bcal'], gainfield=['1','*'], 
         interp=['linear','nearest'], spwmap=[], selectdata=False)

Now for completeness apply 1331+305 to itself.

applycal(vis='ngc5921.demo.ms', field='0', gaintable=['ngc5921.demo.fluxscale','ngc5921.demo.bcal'], gainfield=['0','*'], 
         interp=['linear','nearest'], spwmap=[], selectdata=False)


Plot the Spectrum

plotms settings to produce the integrated spectrum from the calibrated visibilities data.

Before we attempt to image the 21 cm cube of the source, we need to subtract off the underlying continuum, which means we need to plot the integrated spectrum of the source to determine the continuum channels.

We can do this in plotms.

plotms(vis='ngc5921.demo.ms', selectdata=True, field='N5921*', spw='0:6~56', averagedata=True, avgtime='3600', avgscan=True, 
       avgbaseline=True, xaxis='channel', yaxis='amp', ydatacolumn='corrected')

Note that we have entered all the relevent parameters via the task interface, as an alternative to entering each option into the GUI. If the symbols appear too small, the size may be increased via the Display tab: change the Unflagged Points Symbol to 'Custom' and increase the number of pixels for the plotting symbol. The resulting plot is illustrated in the figure at right. Briefly, we want to average both in time and over baselines to get the signal-to-noise necessary to reveal the 21 cm profile (see Averaging data in plotms for more details on averaging options). If you wish to enter the values directly into the GUI, you can follow the (Tab)Command convention of the flagging tutorial with the following settings :

  • (Data)field = N5921*
  • (Data)spw = 0:6~56
  • (Data)Averaging → Time = 3600 (average over some long time window)
  • (Data)Averaging → Scan = True (checkmark; average in time across scan boundaries)
  • (Data)Averaging → All Baselines = True (checkmark)
  • (Axes)X Axis = Channel
  • (Axes)Y Axis = Amp

Now remove 0:6~56 from the spw field to see all channels. From inspection of this plot, it looks like channels 4~6 and 50~59 contain line-free channels, suitable to use for continuum subtraction.

Continuum Subtraction

The next step is to split off the NGC 5921 data from the multisource measurement set and subtract the continuum. Splitting uses the split command, as follows.

split(vis='ngc5921.demo.ms', outputvis='ngc5921.demo.src.split.ms', field='N5921*', spw='', datacolumn='corrected')


This action generated a new measurement set called ngc5921.demo.src.split.ms and copied the calibrated source data (datacolumn = 'corrected') into it.

uvcontsub subtracts the continuum from the data in the visibility (u, v) plane. We will be using channels 4-6 and 50-59 for continuum.

uvcontsub(vis='ngc5921.demo.src.split.ms', field='N5921*', fitspw='0:4~6;50~59', spw='0', solint=0.0, fitorder=0, want_cont=True)


Notice that uvcontsub splits the data into two new measurement sets, 'ngc5921.demo.ms.cont', which contains an average of the continuum channels, and 'ngc5921.demo.ms.contsub', which contains the continuum-subtracted spectral line data.



Imaging

Plot of amplitude vs. projected baseline length (in units of the observing wavelength) produced by casaplotms. The maximum baseline is just below 5 kilo-lambda.

Now we can generate the primary science product, a tclean data cube (ra, dec, velocity) from the continuum-subtracted (u, v, channel) measurement set, ngc5921.demo.ms.contsub. Things to consider in using tclean:

  • To ensure channels aren't averaged prior to imaging, choose mode='channel'.
  • Specify the channels to image using start = 5, width = 1 (no averaging over channels), nchan = 46; only channels 5~51 will be imaged.
  • The maximum baseline is just under 5 kilolambda (see the figure at right), and so the expected synthetic beam is roughly 1.22 × 206265 / 5000 = 50 arcseconds (subject to the details of u, v weighting). Pixels should sample the beam better than 3 times, so 15 arcseconds is a good choice of pixel size (cell = ['15.0arcsec','15.0arcsec']).
  • We only want to tclean down to the noise, which is easily determined by trial-and-error imaging of a single channel (choosing nchan=1 and start appropriately). Here, tclean stops when the maximum residual on the channel is below threshold='8.0mJy'.


# Image the continuum subtracted measurement set
tclean(vis='ngc5921.demo.src.split.ms.contsub', imagename='ngc5921.demo.tclean', field='0', datacolumn='data', specmode='cube', nchan=46, start=5, width=1, spw='', deconvolver='hogbom', gridder='standard', niter=6000, gain=0.1, threshold='8.0mJy', imsize=[256,256], cell=['15.0arcsec','15.0arcsec'], weighting='briggs', robust=0.5,  mask = 'box[[108pix,108pix],[148pix,148pix]]', interactive=False, pblimit=-0.2)


Use imhead to look at the cube header:

imhead(imagename='ngc5921.demo.tclean.image', mode='summary')


The output, as follows, appears in the logger window.


2019-09-03 22:25:25 INFO imhead	##### Begin Task: imhead             #####
2019-09-03 22:25:25 INFO imhead	imhead(imagename="ngc5921.demo.tclean.image",mode="summary",hdkey="",hdvalue="",verbose=False)
2019-09-03 22:25:25 INFO ImageMetaData	   
2019-09-03 22:25:25 INFO ImageMetaData	Image name       : ngc5921.demo.tclean.image
2019-09-03 22:25:25 INFO ImageMetaData	Object name      : N5921_2
2019-09-03 22:25:25 INFO ImageMetaData	Image type       : PagedImage
2019-09-03 22:25:25 INFO ImageMetaData	Image quantity   : Intensity
2019-09-03 22:25:25 INFO ImageMetaData	Pixel mask(s)    : None
2019-09-03 22:25:25 INFO ImageMetaData	Region(s)        : None
2019-09-03 22:25:25 INFO ImageMetaData	Image units      : Jy/beam
2019-09-03 22:25:25 INFO ImageMetaData	Restoring Beams 
2019-09-03 22:25:25 INFO ImageMetaData	Pol   Type Chan        Freq     Vel
2019-09-03 22:25:25 INFO ImageMetaData	  I    Max    7 1.41296e+09 1571.92   51.6639 arcsec x   47.3594 arcsec pa=  8.3205 deg
2019-09-03 22:25:25 INFO ImageMetaData	  I    Min   43 1.41384e+09 1386.42   51.5897 arcsec x   47.3127 arcsec pa=  8.3869 deg
2019-09-03 22:25:25 INFO ImageMetaData	  I Median   13 1.41310e+09 1541.00   51.6611 arcsec x   47.3318 arcsec pa=  8.1425 deg
2019-09-03 22:25:25 INFO ImageMetaData	   
2019-09-03 22:25:25 INFO ImageMetaData	Direction reference : J2000
2019-09-03 22:25:25 INFO ImageMetaData	Spectral  reference : LSRK
2019-09-03 22:25:25 INFO ImageMetaData	Velocity  type      : RADIO
2019-09-03 22:25:25 INFO ImageMetaData	Rest frequency      : 1.42041e+09 Hz
2019-09-03 22:25:25 INFO ImageMetaData	Pointing center     :  15:22:00.000000  +05.04.00.000000
2019-09-03 22:25:25 INFO ImageMetaData	Telescope           : VLA
2019-09-03 22:25:25 INFO ImageMetaData	Observer            : TEST
2019-09-03 22:25:25 INFO ImageMetaData	Date observation    : 1995/04/13/09:33:00
2019-09-03 22:25:25 INFO ImageMetaData	Telescope position: [-1.60119e+06m, -5.04198e+06m, 3.55488e+06m] (ITRF)
2019-09-03 22:25:25 INFO ImageMetaData	   
2019-09-03 22:25:25 INFO ImageMetaData	Axis Coord Type      Name             Proj Shape Tile   Coord value at pixel    Coord incr Units
2019-09-03 22:25:25 INFO ImageMetaData	------------------------------------------------------------------------------------------------ 
2019-09-03 22:25:25 INFO ImageMetaData	0    0     Direction Right Ascension   SIN   256   64  15:22:00.000   128.00 -1.500000e+01 arcsec
2019-09-03 22:25:25 INFO ImageMetaData	1    0     Direction Declination       SIN   256   64 +05.04.00.000   128.00  1.500000e+01 arcsec
2019-09-03 22:25:25 INFO ImageMetaData	2    1     Stokes    Stokes                    1    1             I
2019-09-03 22:25:25 INFO ImageMetaData	3    2     Spectral  Frequency                46    8   1.41279e+09     0.00 2.4414062e+04 Hz
2019-09-03 22:25:25 INFO ImageMetaData	                     Velocity                               1607.99     0.00 -5.152860e+00 km/s
2019-09-03 22:25:25 INFO imhead	##### End Task: imhead               #####
2019-09-03 22:25:25 INFO imhead	##########################################



Additional Science Products

If things went well, you should now have a spectral line cube (ngc5921.demo.tclean.image) as a primary science product. The demo script illustrates further how to generate cube statistics (using imstat), an integrated spectrum, and moment maps.

Cube Statistics

imstat is the tool for displaying statistics of images and cubes. The following example displays the statistics for an empty region of the whole cube.


cubestat=imstat(imagename='ngc5921.demo.tclean.image', box='10,10,100,100')


2019-09-03 22:40:15 INFO imstat	##########################################
2019-09-03 22:40:15 INFO imstat	##### Begin Task: imstat             #####
2019-09-03 22:40:15 INFO imstat	imstat(imagename="ngc5921.demo.tclean.image",axes=-1,region="",box="10,10,100,100",chans="",
2019-09-03 22:40:15 INFO imstat	        stokes="",listit=True,verbose=True,mask="",stretch=False,
2019-09-03 22:40:15 INFO imstat	        logfile="",append=True,algorithm="classic",fence=-1,center="mean",
2019-09-03 22:40:15 INFO imstat	        lside=True,zscore=-1,maxiter=-1,clmethod="auto",niter=3)
2019-09-03 22:40:15 INFO imstat	Using specified box(es) 10,10,100,100
2019-09-03 22:40:15 INFO imstat	Determining stats for image ngc5921.demo.tclean.image
2019-09-03 22:40:15 INFO imstat	Selected bounding box : 
2019-09-03 22:40:15 INFO imstat	    [10, 10, 0, 0] to [100, 100, 0, 45]  (15:23:58.379, +04.34.29.305, I, 1.41279e+09Hz to 15:22:28.105, +04.56.59.962, I, 1.41389e+09Hz)
2019-09-03 22:40:15 INFO imstat	Statistics calculated using Classic algorithm
2019-09-03 22:40:15 INFO imstat	Regions --- 
2019-09-03 22:40:15 INFO imstat	         -- bottom-left corner (pixel) [blc]:  [10, 10, 0, 0]
2019-09-03 22:40:15 INFO imstat	         -- top-right corner (pixel) [trc]:    [100, 100, 0, 45]
2019-09-03 22:40:15 INFO imstat	         -- bottom-left corner (world) [blcf]: 15:23:58.379, +04.34.29.305, I, 1.41279e+09Hz
2019-09-03 22:40:15 INFO imstat	         -- top-right corner (world) [trcf]:   15:22:28.105, +04.56.59.962, I, 1.41389e+09Hz
2019-09-03 22:40:15 INFO imstat	Values --- 
2019-09-03 22:40:15 INFO imstat	         -- flux [flux]:                            1.99425 Jy.km/s
2019-09-03 22:40:15 INFO imstat	         -- number of points [npts]:                380926
2019-09-03 22:40:15 INFO imstat	         -- maximum value [max]:                    0.00953276 Jy/beam
2019-09-03 22:40:15 INFO imstat	         -- minimum value [min]:                    -0.0100478 Jy/beam
2019-09-03 22:40:15 INFO imstat	         -- position of max value (pixel) [maxpos]: [85, 63, 0, 8]
2019-09-03 22:40:15 INFO imstat	         -- position of min value (pixel) [minpos]: [30, 18, 0, 7]
2019-09-03 22:40:15 INFO imstat	         -- position of max value (world) [maxposf]: 15:22:43.151, +04.47.44.907, I, 1.41298e+09Hz
2019-09-03 22:40:15 INFO imstat	         -- position of min value (world) [minposf]: 15:23:38.319, +04.36.29.518, I, 1.41296e+09Hz
2019-09-03 22:40:15 INFO imstat	         -- Sum of pixel values [sum]:               4.76561 Jy/beam
2019-09-03 22:40:15 INFO imstat	         -- Sum of squared pixel values [sumsq]:     1.38125 Jy/beam.Jy/beam
2019-09-03 22:40:15 INFO imstat	Statistics --- 
2019-09-03 22:40:15 INFO imstat	        -- Mean of the pixel values [mean]:         1.25106e-05 Jy/beam
2019-09-03 22:40:15 INFO imstat	        -- Variance of the pixel values :           3.62589e-06 Jy/beam
2019-09-03 22:40:15 INFO imstat	        -- Standard deviation of the Mean [sigma]:  0.00190418 Jy/beam
2019-09-03 22:40:15 INFO imstat	        -- Root mean square [rms]:                  0.00190421 Jy/beam
2019-09-03 22:40:15 INFO imstat	        -- Median of the pixel values [median]:     6.37541e-06 Jy/beam
2019-09-03 22:40:15 INFO imstat	        -- Median of the deviations [medabsdevmed]: 0.00127676 Jy/beam
2019-09-03 22:40:15 INFO imstat	        -- IQR [quartile]:                          0.00255348 Jy/beam
2019-09-03 22:40:15 INFO imstat	        -- First quartile [q1]:                     -0.00126604 Jy/beam
2019-09-03 22:40:15 INFO imstat	        -- Third quartile [q3]:                     0.00128744 Jy/beam
2019-09-03 22:40:15 INFO imstat	Sum column unit = Jy/beam
2019-09-03 22:40:15 INFO imstat	Mean column unit = Jy/beam
2019-09-03 22:40:15 INFO imstat	Std_dev column unit = Jy/beam
2019-09-03 22:40:15 INFO imstat	Minimum column unit = Jy/beam
2019-09-03 22:40:15 INFO imstat	Maximum column unit = Jy/beam
2019-09-03 22:40:15 INFO imstat	Npts          Sum           Mean          Rms           Std_dev       Minimum       Maximum     
2019-09-03 22:40:15 INFO imstat	 3.809260e+05  4.765615e+00  1.251060e-05  1.904215e-03  1.904176e-03 -1.004781e-02  9.532760e-03
2019-09-03 22:40:15 INFO imstat	##### End Task: imstat               #####
2019-09-03 22:40:15 INFO imstat	##########################################


The Integrated Spectrum

Example of the viewer rectangle selection tool on one channel of the NGC 5921 21 cm data cube. The spectral profile window is shown at right.


We saw earlier how to generate an integrated spectrum from the (u, v) measurement set. Here's how to produce the integrated spectrum from the spectral line cube. First, load the cube into viewer.

viewer(infile='ngc5921.demo.tclean.image')


To generate the integrated spectrum, perform the following tasks.

  • Use the player controls VcrNext.png to inspect the cube one channel at a time.
  • From the viewer Tools menu, select Spectral Profile. A new graphics window should appear.
  • By default, the rectangle selection tool DrawingSelector.png is assigned to the right mouse button, and you can just right-click and drag a box over the region where you want to (spatially) integrate the spectrum. See the figure at upper right.
  • Alternatively, you can assign one of the other selection tools by right-clicking on the appropriate button.
  • The spectrum now appears in the graphics window; see the figure at right.

You can save the integrated spectrum to a text file by clicking the Save to text.png button on the graphics window. There are also buttons to print the figure or save the figure to disk.


Cube Moments

The moment 0 (integrated intensity) 21 cm image of NGC 5921, produced using immoments

Cube moments are maps of weighted sums along the velocity axis. In CASA, they are generated by the task immoments. The zeroth moment (moments = 0) is a sum of intensities along the velocity axis (the integrated intensity map); the first moment (moment = 1) is the sum of velocities weighted by intensity (the velocity field); the second moment (moment = 2) is a map of the velocity dispersion; see the immoments for additional options.

The following example produces maps of the zeroth and first moments, or the integrated intensity and velocity field. The respective measurement sets are the moment zero image ngc5921.demo.moments.integrated and moment one imagengc5921.demo.moments.weighted_coord.

We will do the zeroth and first moments and mask out noisy pixels using hard global limits. We will also collapse along the spectral (channel) axis and include all planes.

immoments(imagename='ngc5921.demo.tclean.image', moments=[0,1], excludepix=[-100, 0.009], axis='spectral', chans='', outfile='ngc5921.demo.moments')
  • moments = [0,1] : Do zeroth and first moments
  • excludepix = [-100,0.009] : Mask out noisy pixels using hard global limits
  • axis = 'spectral' : Collapse along the spectral (channel) axis
  • chans = :Include all planes


To examine the moment images, use viewer; the resulting moment zero image is displayed at right. Note that you may have to play with the color map (Data Display Options button in viewer) in order to replicate the image in this tutorial.

viewer(infile='ngc5921.demo.moments.integrated')

Export the Data

To export the (u, v) data and image cube as FITS files, use exportuvfits and exportfits, respectively.

Here's how to export the continuum-subtracted (u, v) data.

exportuvfits(vis='ngc5921.demo.src.split.ms.contsub', fitsfile='ngc5921.demo.contsub.uvfits', datacolumn='corrected', multisource=True)


And now, the FITS cube.

exportfits(imagename='ngc5921.demo.tclean.image', fitsimage='ngc5921.demo.tclean.fits')


The moment maps (or any CASA images) can be similarly exported using exportfits.


Appendix: Python Notes

os.system

os.system allows you to run shell commands from within python / CASA. For example:

import os
os.system('ls -sF')

will give an OS-level listing of the current directory's contents.

os.environ.get

It's worth having a look at the output of the os.environ.get command to understand the python syntax (alternative: os.getenv). You can think of os.environ as a list of operating system environment variables, and get is a method that extracts information about the requested environment variable, here, CASAPATH. Get returns a string of whitespace separated information, and .split() turns that string into a list. The array index [0] extracts the first element of that list, which contains the path.

To illustrate, here is some example python I/O in CASA.

CASA <12>: print os.environ.get('CASAPATH')
/usr/lib64/casapy/30.0.9709test-001 linux local el5bld64b

CASA <13>: print os.environ.get('CASAPATH').split()
['/usr/lib64/casapy/30.0.9709test-001', 'linux', 'local', 'el5bld64b']

CASA <14>: print os.environ.get('CASAPATH').split()[0]
/usr/lib64/casapy/30.0.9709test-001

Pre-upgrade VLA Tutorials

Last checked on CASA Version 5.7.2.