M100 Band3 SingleDish 4.2.2: Difference between revisions

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The data have already been converted to CASA Measurement Set (MS) format using the CASA task importasdm.
The data have already been converted to CASA Measurement Set (MS) format using the CASA task importasdm.
== Summary of the observing ==
There were six observations made. The table below indicates the uid reference of each and the start and end times.
uid___A002_X60b415_X39a     Observed from   14-Apr-2013/05:34:15.7   to   14-Apr-2013/05:58:23.8 (UTC)
uid___A002_X60b415_X6f7     Observed from   14-Apr-2013/06:23:03.0   to   14-Apr-2013/06:47:11.0 (UTC)
uid___A002_X6218fb_X264     Observed from   28-Apr-2013/04:12:06.1   to   28-Apr-2013/04:36:07.5 (UTC)
uid___A002_X6218fb_X425     Observed from   28-Apr-2013/04:38:56.8   to   28-Apr-2013/05:03:00.3 (UTC)
uid___A002_X6321c5_X3a7     Observed from   12-May-2013/02:22:16.9   to   12-May-2013/02:43:59.8 (UTC)
uid___A002_X6321c5_X5ca     Observed from   12-May-2013/02:47:16.8   to   12-May-2013/03:09:00.9 (UTC)


==Initial Inspection, Sky subtraction, Tsys application==
==Initial Inspection, Sky subtraction, Tsys application==

Revision as of 10:08, 8 July 2013

M100 Single Dish Data Reduction


Overview

This portion of the M100 Single Dish Data Reduction CASA Guide will cover the reduction of the Total Power (TP) array data into units of Kelvins on the antenna temperature (Ta*) scale and imaging. Converting this image to the Jansky scale (Jy/beam) to be combined with interferometric data is covered in the M100 Band3 Combine 4.1 section.

This guide is designed for CASA 4.1.0.

If you haven't downloaded the data, you can XXXXXXX and XXXXXX:

Once the download has finished, upack the file:

# In a terminal outside CASA
tar -xvzf XXXsingledish_datasetXXX_TBD.tgz

cd XXrelevant_directoryXXX

# Start CASA
casapy

Confirm your version of CASA

This guide has been written for CASA release 4.1.0. Please confirm your version before proceeding.

# In CASA
version = casadef.casa_version
print "You are using " + version
if (version < '4.1.0'):
    print "YOUR VERSION OF CASA IS TOO OLD FOR THIS GUIDE."
    print "PLEASE UPDATE IT BEFORE PROCEEDING."
else:
    print "Your version of CASA is appropriate for this guide."

The data have already been converted to CASA Measurement Set (MS) format using the CASA task importasdm.

Summary of the observing

There were six observations made. The table below indicates the uid reference of each and the start and end times.

uid___A002_X60b415_X39a     Observed from   14-Apr-2013/05:34:15.7   to   14-Apr-2013/05:58:23.8 (UTC) uid___A002_X60b415_X6f7     Observed from   14-Apr-2013/06:23:03.0   to   14-Apr-2013/06:47:11.0 (UTC) uid___A002_X6218fb_X264     Observed from   28-Apr-2013/04:12:06.1   to   28-Apr-2013/04:36:07.5 (UTC) uid___A002_X6218fb_X425     Observed from   28-Apr-2013/04:38:56.8   to   28-Apr-2013/05:03:00.3 (UTC) uid___A002_X6321c5_X3a7     Observed from   12-May-2013/02:22:16.9   to   12-May-2013/02:43:59.8 (UTC) uid___A002_X6321c5_X5ca     Observed from   12-May-2013/02:47:16.8   to   12-May-2013/03:09:00.9 (UTC)

Initial Inspection, Sky subtraction, Tsys application

We will eventually concatenate the six datasets used here into one large dataset. However, we will keep them separate for now, as some of the steps to follow require individual datasets to be calibrated separately (namely, the sky/Tsys calibration and baseline subtraction). We therefore start by defining an array "basename" that includes the names of the six files in chronological order. This will simplify the following steps by allowing us to loop through the files using a simple for-loop in python. Remember that if you log out of CASA, you will have to re-issue this command. We will remind you of this in the relevant sections by repeating the command at the start.

# In CASA
basename=['uid___A002_X60b415_X39a','uid___A002_X60b415_X6f7','uid___A002_X6218fb_X264', 'uid___A002_X6218fb_X425','uid___A002_X6321c5_X3a7','uid___A002_X6321c5_X5ca']

The usual first step is then to get some basic information about the data. We do this using the task listobs, which will output a detailed summary of each dataset supplied.

# In CASA
for name in basename:
        listobs(vis=name+'.ms')

Note that after cutting and pasting a for-loop you often have to press return several times to execute. The output will be sent to the CASA logger. You will have to scroll up to see the individual output for each of the six datasets. Here is an example of the most relevant output for the fifth file in the list.

Observation: ALMA
Data records: 16588       Total integration time = 1302.91 seconds
   Observed from   12-May-2013/02:22:16.9   to   12-May-2013/02:43:59.8 (UTC)

   ObservationID = 0         ArrayID = 0
  Date        Timerange (UTC)          Scan  FldId FieldName           nRows   nUnflRows   SpwIds   Average Interval(s)    ScanIntent
  12-May-2013/02:22:16.3 - 02:22:42.8     1      0 M100                    900      0.00  [0, 1, 2, 3, 4, 5, 6, 7, 8]  [1.15, 0.48, 0.48, 0.48, 0.48, 0.48, 0.48, 0.48, 0.48] CALIBRATE_ATMOSPHE
RE#ON_SOURCE,CALIBRATE_WVR#ON_SOURCE
              02:23:24.3 - 02:25:11.4     2      0 M100                   1524      0.00  [0, 9, 10, 11, 12, 13, 14, 15, 16]  [1.15, 1.01, 1.01, 1.01, 1.01, 1.01, 1.01, 1.01, 1.01] OBSERVE_TAR
GET#OFF_SOURCE,CALIBRATE_WVR#OFF_SOURCE
              02:25:25.2 - 02:27:11.2     3      0 M100                   1522      0.00  [0, 9, 10, 11, 12, 13, 14, 15, 16]  [1.15, 1.01, 1.01, 1.01, 1.01, 1.01, 1.01, 1.01, 1.01] OBSERVE_TAR
GET#OFF_SOURCE,CALIBRATE_WVR#OFF_SOURCE
              02:27:25.1 - 02:29:11.0     4      0 M100                   1522      0.00  [0, 9, 10, 11, 12, 13, 14, 15, 16]  [1.15, 1.01, 1.01, 1.01, 1.01, 1.01, 1.01, 1.01, 1.01] OBSERVE_TAR
GET#OFF_SOURCE,CALIBRATE_WVR#OFF_SOURCE
              02:29:24.9 - 02:31:12.0     5      0 M100                   1524      0.00  [0, 9, 10, 11, 12, 13, 14, 15, 16]  [1.15, 1.01, 1.01, 1.01, 1.01, 1.01, 1.01, 1.01, 1.01] OBSERVE_TAR
GET#OFF_SOURCE,CALIBRATE_WVR#OFF_SOURCE
              02:31:25.8 - 02:33:11.8     6      0 M100                   1522      0.00  [0, 9, 10, 11, 12, 13, 14, 15, 16]  [1.15, 1.01, 1.01, 1.01, 1.01, 1.01, 1.01, 1.01, 1.01] OBSERVE_TAR
GET#OFF_SOURCE,CALIBRATE_WVR#OFF_SOURCE
              02:34:03.6 - 02:34:29.0     7      0 M100                    900      0.00  [0, 1, 2, 3, 4, 5, 6, 7, 8]  [1.15, 0.48, 0.48, 0.48, 0.48, 0.48, 0.48, 0.48, 0.48] CALIBRATE_ATMOSPHE
RE#ON_SOURCE,CALIBRATE_WVR#ON_SOURCE
              02:34:42.8 - 02:36:30.0     8      0 M100                   1524      0.00  [0, 9, 10, 11, 12, 13, 14, 15, 16]  [1.15, 1.01, 1.01, 1.01, 1.01, 1.01, 1.01, 1.01, 1.01] OBSERVE_TAR
GET#OFF_SOURCE,CALIBRATE_WVR#OFF_SOURCE
              02:36:43.8 - 02:38:29.8     9      0 M100                   1524      0.00  [0, 9, 10, 11, 12, 13, 14, 15, 16]  [1.15, 1.01, 1.01, 1.01, 1.01, 1.01, 1.01, 1.01, 1.01] OBSERVE_TAR
GET#OFF_SOURCE,CALIBRATE_WVR#OFF_SOURCE
              02:38:43.6 - 02:40:30.7    10      0 M100                   1524      0.00  [0, 9, 10, 11, 12, 13, 14, 15, 16]  [1.15, 1.01, 1.01, 1.01, 1.01, 1.01, 1.01, 1.01, 1.01] OBSERVE_TAR
GET#OFF_SOURCE,CALIBRATE_WVR#OFF_SOURCE
              02:40:44.5 - 02:42:30.5    11      0 M100                   1524      0.00  [0, 9, 10, 11, 12, 13, 14, 15, 16]  [1.15, 1.01, 1.01, 1.01, 1.01, 1.01, 1.01, 1.01, 1.01] OBSERVE_TAR
GET#OFF_SOURCE,CALIBRATE_WVR#OFF_SOURCE
              02:42:44.4 - 02:44:00.4    12      0 M100                   1078      0.00  [0, 9, 10, 11, 12, 13, 14, 15, 16]  [1.15, 1.01, 1.01, 1.01, 1.01, 1.01, 1.01, 1.01, 1.01] OBSERVE_TAR
GET#OFF_SOURCE,CALIBRATE_WVR#OFF_SOURCE
           (nRows = Total number of rows per scan) 
Fields: 1
  ID   Code Name                RA               Decl           Epoch   SrcId    nRows  nUnflRows
  0    none M100                12:22:54.899040 +15.49.20.57200 J2000   0        16588       0.00
Spectral Windows:  (17 unique spectral windows and 2 unique polarization setups)
  SpwID  Name                           #Chans   Frame   Ch1(MHz)  ChanWid(kHz)  TotBW(kHz) BBC Num  Corrs  
  0      WVR#NOMINAL                         4   TOPO  184550.000   1500000.000   7500000.0       0  XX
  1      ALMA_RB_03#BB_1#SW-01#FULL_RES    128   TOPO  101942.187    -15625.000   2000000.0       1  XX  YY
  2      ALMA_RB_03#BB_1#SW-01#CH_AVG        1   TOPO  100926.562   1781250.000   1781250.0       1  XX  YY
  3      ALMA_RB_03#BB_2#SW-01#FULL_RES    128   TOPO  103757.337    -15625.000   2000000.0       2  XX  YY
  4      ALMA_RB_03#BB_2#SW-01#CH_AVG        1   TOPO  102741.712   1781250.000   1781250.0       2  XX  YY
  5      ALMA_RB_03#BB_3#SW-01#FULL_RES    128   TOPO  111814.962     15625.000   2000000.0       3  XX  YY
  6      ALMA_RB_03#BB_3#SW-01#CH_AVG        1   TOPO  112783.712   1781250.000   1781250.0       3  XX  YY
  7      ALMA_RB_03#BB_4#SW-01#FULL_RES    128   TOPO  113689.962     15625.000   2000000.0       4  XX  YY
  8      ALMA_RB_03#BB_4#SW-01#CH_AVG        1   TOPO  114658.712   1781250.000   1781250.0       4  XX  YY
  9      ALMA_RB_03#BB_1#SW-01#FULL_RES   4080   TOPO  101945.850      -488.281   1992187.5       1  XX  YY
  10     ALMA_RB_03#BB_1#SW-01#CH_AVG        1   TOPO  100949.756   1992187.500   1992187.5       1  XX  YY
  11     ALMA_RB_03#BB_2#SW-01#FULL_RES   4080   TOPO  103761.000      -488.281   1992187.5       2  XX  YY
  12     ALMA_RB_03#BB_2#SW-01#CH_AVG        1   TOPO  102764.906   1992187.500   1992187.5       2  XX  YY
  13     ALMA_RB_03#BB_3#SW-01#FULL_RES   4080   TOPO  111811.300       488.281   1992187.5       3  XX  YY
  14     ALMA_RB_03#BB_3#SW-01#CH_AVG        1   TOPO  112806.906   1992187.500   1992187.5       3  XX  YY
  15     ALMA_RB_03#BB_4#SW-01#FULL_RES   4080   TOPO  113686.300       488.281   1992187.5       4  XX  YY
  16     ALMA_RB_03#BB_4#SW-01#CH_AVG        1   TOPO  114681.906   1992187.500   1992187.5       4  XX  YY
Sources: 19
  ID   Name                SpwId RestFreq(MHz)  SysVel(km/s) 
  0    M100                0     -              -            
  0    M100                17    -              -            
  0    M100                18    -              -            
  0    M100                1     -              -            
  0    M100                2     -              -            
  0    M100                3     -              -            
  0    M100                4     -              -            
  0    M100                5     -              -            
  0    M100                6     -              -            
  0    M100                7     -              -            
  0    M100                8     -              -            
  0    M100                9     100950         0            
  0    M100                10    100950         0            
  0    M100                11    102794.1       0            
  0    M100                12    102794.1       0            
  0    M100                13    112794.1       0            
  0    M100                14    112794.1       0            
  0    M100                15    114669.1       0            
  0    M100                16    114669.1       0            
Antennas: 2:
  ID   Name  Station   Diam.    Long.         Lat.                Offset from array center (m)                ITRF Geocentric coordinates (m)        
                                                                     East         North     Elevation               x               y               z
  0    PM01  T704      12.0 m   -067.45.16.2  -22.53.22.1         42.8992     -520.1885       22.2159  2225113.044955 -5440122.820877 -2481517.728410
  1    PM04  T703      12.0 m   -067.45.16.2  -22.53.23.9         42.8809     -575.6904       21.7744  2225104.701420 -5440102.470120 -2481568.688227


combine all executions to one MS

Concatenate all of the calibrated measurement sets into one for imaging. The CASA task "concat" will do this.

In CASA
os.system('rm -rf concat_m100.ms')
concat(vis='uid___A002_X60b415_X39a.ms.cal.split', 'uid___A002_X60b415_X6f7.ms.cal.split', 'uid___A002_X6218fb_X264.ms.cal.split', 'uid___A002_X6218fb_X425.ms.cal.split', 'uid___A002_X6321c5_X3a7.ms.cal.split', 'uid___A002_X6321c5_X5ca.ms.cal.split'],
       concatvis='concat_m100.ms',
       freqtol='10MHz')

The individual calibrated MSs have slightly different observing frequencies, although the rest frequencies are the same. The freqtol parameter sets the tolerance for considering whether the different spectral windows from the input datasets should be output as the same spectral window ID.


Image the Total Power Data

Run listobs on the total power data to see what spw contains the CO

In CASA
os.system('rm -rf concat_m100.ms.listobs')
listobs(vis='concat_m100.ms',listfile='concat_m100.ms.listobs')

Spectral window SPWID=3 contains the 115.27 GHz line, so we image this window. The task "sdimaging" will do this.

In CASA
os.system('rm -rf TP_CO_cube')
sdimaging(infile='concat_m100.ms',
          field=0,spw=3,
          specunit='km/s',restfreq='115.271204GHz',
          dochannelmap=True,
          nchan=70,start=1400,step=5,
          gridfunction='gjinc',imsize=[50,50],
          cell=['10arcsec','10arcsec'],
          outfile='TP_CO_cube')

The restfreq parameter must be specified when using "km/s" as the units, as in this case. Start and step parameters are specified in units that the user chooses for specunit. The numbers here are chosen so that the resulting image has the same number of channels, velocity range and channel width as the 7m and 12m array images. The gridfunction is the weighting function that is used to grid the observed flux to individual pixels in the image. "SF" is a spheroidal function, which minimizes aliasing effects. "BOX" is a pillbox function, which defaults to a kernel box size of 1 pixel. The "PB" (primary beam) assumes an Airy disk, corresponding to an antenna with 10.7m diameter, the effective diameter of an ALMA 12m antenna. The "GAUSS" is a gaussian, and its size can be defined by additional subparameters (truncate and gwidth). "GJINC" is a gaussian convolved with the Bessel function, and can minimize the broadening of the effective beam. Any of the functions which require the obseving frequency for determining the beam size will read the frequency from the dataset, and the user can use the default.

The cell size should be chosen so that it is about 1/3 to 1/4 of the FWHM of the effective beam.