################################## Other GBTIDL Features and Examples ################################## Customizing the output of the list procedure ============================================ The :idl:pro:`list` command can be used to view detailed information on records in the active input file. Because this file contains a great deal of information, it is possible to request that the :idl:pro:`list` command show only that information of interest. The following command shows how to create the sample data used in these examples: .. code-block:: bash sdfits -mode=raw -scans=177:180 -backends=acs /home/archive/test-data/tape-0002/TREG_040922 Then to access this data in GBTIDL use this command: .. code-block:: IDL filein, ’TREG_040922.raw.acs.fits’ In the first example, we use :idl:pro:`list` .. code-block:: IDL list ; Show a brief description of everything to show all the records, or spectra, currently found in the index file .. code-block:: text #INDEX SOURCE SCAN PROCEDURE POL IFNUM FDNUM INT SIG CAL 0 W3OH 177 OffOn XX 0 0 0 T T 1 W3OH 177 OffOn XX 0 0 0 T F 2 W3OH 177 OffOn XX 0 0 1 T T 3 W3OH 177 OffOn XX 0 0 1 T F 4 W3OH 177 OffOn YY 0 0 0 T T . . . 30 W3OH 180 OffOn YY 0 0 1 T T 31 W3OH 180 OffOn YY 0 0 1 T F Next, we use a simple search parameter: .. code-block:: IDL list, index=[0,1,2] ; Show a description of the first three records .. code-block:: text #INDEX SOURCE SCAN PROCEDURE POL IFNUM FDNUM INT SIG CAL 0 W3OH 177 OffOn XX 0 0 0 T T 1 W3OH 177 OffOn XX 0 0 0 T F 2 W3OH 177 OffOn XX 0 0 1 T T To see all of information associated with these records, use the verbose keyword. .. code-block:: IDL list, index=[0,1,2], /verbose This will return the parameters: .. code-block:: text # INDEX, PROJECT, FILE, EXT, ROW, SOURCE, PROCEDURE, OBSID, E2ESC, PROCS, SCAN, POL, PLNUM, IFNUM, FEED, FDNUM, INT, NUMCHN, SIG, CAL, SAMPLER, AZIMU, ELEV, LONGITUDE, LATITUDE, TRGTLONG, TRGTLAT, LST, CENTFREQ, RESTFREQ, VELOCITY, FREQINT, FREQRES, DATEOBS, TIMESTAMP, BANDWIDTH, EXPOSURE, TSYS, NSAVE Obviously, the above example is not best if you are only interested in the values of a few specific columns. You can narrow the output like so: .. code-block:: IDL list, index=[0,1,2], columns=["INDEX","INT","POLARIZATION"] .. code-block:: text #INDEX INT POL 0 0 XX 1 0 XX 2 1 XX The list command prints records in the order of the index number by default. This can be changed using the sortcol keyword. Note that the full name of the column must be used. .. code-block:: IDL list, scan=177, sortcol="INT" ; Sort by integration number returns .. code-block:: text #INDEX SOURCE SCAN PROCEDURE POL IFNUM FDNUM INT SIG CAL 0 W3OH 177 OffOn XX 0 0 0 T T 1 W3OH 177 OffOn XX 0 0 0 T F 4 W3OH 177 OffOn YY 0 0 0 T T 5 W3OH 177 OffOn YY 0 0 0 T F 2 W3OH 177 OffOn XX 0 0 1 T T 3 W3OH 177 OffOn XX 0 0 1 T F 6 W3OH 177 OffOn YY 0 0 1 T T 7 W3OH 177 OffOn YY 0 0 1 T F The liststack command is identical to the list command except that it selects from records identified by the stack. .. code-block:: IDL select, scan=177 ; Place scan 177’s records on the stack liststack, col=["INDEX","INT","CAL"], sortcol="CAL" returns .. code-block:: text #INDEX INT CAL 1 0 F 3 1 F 5 0 F 7 1 F 0 0 T 2 1 T 4 0 T 6 1 T Making postage stamp plots ========================== In displaying PointMap data, or just for displaying multiple spectra, it can be convenient to display spectra as postage stamp plots. GBTIDL currently does not have any inherent support for postage stamp plots, but it is easy to use the IDL plotter to duplicate plots as one might see from CLASS, for example. For instance, a 3x3 PointMap might be stored as calibrated, reduced spectra in an SDFITS file, with the first 9 records representing the map. These can be displayed in a postage stamp plot as follows: .. code-block:: IDL filein, ’postage.fits’ freeze !p.multi = [0,3,3] for i=0,8 do begin & $ getrec, i & $ x = getxarray() & $ y = getdata() & $ plot, x, y, xstyle=1 & $ endfor unfreeze For more flexibility in plot placement, the position parameter can be used, as in the following procedure: .. code-block:: IDL pro plotpos, x, y, xpos, ypos, xsize, ysize if (n_elements(xsize)) eq 0 then xsize = 0.1 if (n_elements(ysize)) eq 0 then ysize = 0.1 freeze plot,x,y,position=[xpos-xsize/2,ypos-ysize/2,xpos+xsize/2,ypos+ysize/2], /noerase, xstyle=1 unfreeze end The procedure might be used as follows: .. code-block:: IDL erase getrec,0 plotpos, getxarray(), getdata(), 0.5, 0.5, 0.25, 0.25 getrec,1 plotpos, getxarray(), getdata(), 0.2, 0.5, 0.25, 0.25 getrec,2 plotpos, getxarray(), getdata(), 0.8, 0.5, 0.25, 0.25 getrec,3 plotpos, getxarray(), getdata(), 0.5, 0.2, 0.25, 0.25 getrec,4 plotpos, getxarray(), getdata(), 0.5, 0.8, 0.25, 0.25 Example reduction sessions with sample data sets ================================================ This section describes a few sample data sets for users who may wish to experiment with GBTIDL but who do not yet have any data to play with. You may wish to experiment with GBTIDL before you have an appropriate data set of your own. With each data set is an example of how the data might be reduced and analyzed in GBTIDL. The examples are simply guides, and there are many ways to reduce the data in each case. HI Position Switched Data ^^^^^^^^^^^^^^^^^^^^^^^^^ This is a strightforward observation of HI in a galaxy, observed using position switching. The data set is “clean”, so all the data can be included in the averaging. The example data reduction is terse in this case, and aims just to produce an HI spectrum calibrated as antenna temperature (K). The RMS noise and integrated flux density of the HI source are measured. * Retrieve the data: ngc5291.fits (http://safe.nrao.edu/wiki/pub/GB/Data/GBTIDLExampleAndSampleData/ngc5291.fits) * Example data reduction: Get the data into GBTIDL and show a summary of the scans: .. code-block:: IDL filein, ’ngc5291.fits’ summary Calibrate and accumulate the data for each scan, and for each polarization: .. code-block:: IDL for i=51,57,2 do begin getps, i, plnum=0 & accum & end for i=51,57,2 do begin getps, i, plnum=1 & accum & end ave Set a baseline region and subtract the baseline: .. code-block:: IDL chan nregion,[3300,14800,17900,31000] nfit,3 sety, 0.2, 0.5 bshape baseline unzoom Apply some smoothing, then measure statistics: .. code-block:: IDL hanning,/decimate bdrop, 2500 edrop, 2500 velo stats, 2000, 3000 ; this gives the RMS: 13.5 mJy stats, 3900, 4800 ; this gives the integrated area: 60.439 K km/s boxcar, 8 ; more smoothing OH/HI Frequency Switched Data ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ This is a slightly more involved data set than the previous one. In this case, there are 2 spectral windows, or “IFs”. One records the 1665/1667 MHz OH masers and the other records the HI emission toward W3(OH). The data are frequency switched. This data includes some integrations in which there are bad data, and so the observer must be careful to inspect and average the data selectively. * Retrieve the data: W3OH.fits (http://safe.nrao.edu/wiki/pub/GB/Data/GBTIDLExampleAndSampleData/W3OH.fits) .. todo:: Make the file available for download here. * Example data reduction: Get the data into GBTIDL and show a summary of the scans: .. code-block:: IDL filein, ’W3OH.fits’ summary Begin by visually inspecting the data. Note not all the data is “good” so we will need to be selective in the averaging. The “wait” command simply pauses to give the observer a chance to look at the data. .. code-block:: IDL for i=79, 83 do begin getfs, i, plnum=1, ifnum=0 & wait, 2 & end Zoom in to the baseline and repeat: .. code-block:: IDL sety, -2, 2 for i=79, 83 do begin getfs, i, plnum=1, ifnum=0 & wait, 2 & end Inspect individual integrations within scan 83. Note that within a scan some integrations are good and some bad. .. code-block:: IDL for i=0,5 do begin getfs, 83,intnum=i, plnum=1, ifnum=0 & wait, 2 & end We must average only the good integrations. There are many ways to approach this problem. It would be natural to use the flagging commands, but here we use a different method which is terse but efficient. We loop through each integration of each scan, test the RMS in the data, and accumulate only the good integrations. The use of freeze before the loop and unfreeze after the loop speeds up the processing by turning off the automatic update of the plotter after each getfs call. .. code-block:: IDL velo freeze for i=79,83 do begin & $ for j=0,5 do begin & $ for k=0,1 do begin & $ getfs, i, units=’Jy’, intnum=j, plnum=k, ifnum=0 & $ stats,-3000,-2000,ret=a,/quiet & $ if a.rms lt 0.5 then accum else print, ’Skipping’ ,i, j, k & $ end end end unfreeze ave The next example illustrates the flagging approach. The bad integrations are first flagged and then the scans for ifnum=0 are averaged, using both polarizations. Note that the loop over integrations can now be eliminated. The getfs command averages all integrations and since the bad integrations are now flagged, they do not contribute to the average. .. code-block:: IDL flag,[80,82], intnum=[1,3], plnum=1, ifnum=0, idstring=’corrupt’ flag, 83, intnum=[2,4], plnum=1, ifnum=0, idstring=’corrupt’ listflags,/summary freeze for i=79,83 do begin & $ for k=0,1 do begin & $ getfs,i,units=’Jy’, plnum=k, ifnum=0 & $ accum & $ end end unfreeze ave Extract a region of interest: .. code-block:: IDL chan my_spec = dcextract(!g.s[0],7500,9500) bdrop, 0 edrop, 0 show,my_spec !g.s[0] = my_spec show Set the baseline regions using the mouse cursor and subtract a baseline. .. code-block:: IDL sety, -0.2,0.4 ; Zoom in a bit setregion nfit, 7 bshape baseline Fit Gaussians to one of the maser complexes. Use fitgauss to specify a 3-component fit. .. code-block:: IDL velo setx, -60, -30 freey fitgauss Follow the instructions for fitgauss. H2O Total Power Nod Data ^^^^^^^^^^^^^^^^^^^^^^^^ This data set contains an observation of a maser line, observed in total power nod mode. In the first example below we show the simplest (but verbose) method to average and reduce the data. The second example is more involved. We use the stack to gather the scans for averaging. We store the individual scans in internal buffers, and display them all overlaid. Finally we average the data and write the final spectrum to disk. * Retrieve the data: IC1481.fits (http://safe.nrao.edu/wiki/pub/GB/Data/GBTIDLExampleAndSampleData/IC1481.fits) .. todo:: Make the file available for download here. * Simple reduction of this data set: Get the data into GBTIDL and accumulate some of the data: .. code-block:: IDL filein, ’IC1481.fits’ getnod, 182, plnum=0 accum getnod, 182, plnum=1 accum getnod, 184, plnum=0 accum getnod, 184, plnum=1 accum The other scans can be accumulated similarly. Now, average the accumulated data and fit a baseline. .. code-block:: IDL ave setregion nfit, 3 baseline * Alternative reduction: Get the data into GBTIDL and show a summary of the scans: .. code-block:: IDL filein, ’IC1481.fits’ summary Clear the stack, then fill it with even scan numbers in the range 182-188. .. code-block:: IDL emptystack sclear addstack, 182, 188, 2 tellstack Now loop through each scan pair, retrieve the calibrated spectrum, accumulate it and also store it in a memory buffer. The use of freeze and unfreeze before and after the loop speeds up the processing by disabling the automatic update of the plotter after each getnod. .. code-block:: IDL freeze for i = 0, !g.acount-1 do begin & $ getnod, astack(i), plnum=0, units=’Jy’, tsys=60 & accum & $ copy, 0, i*2+2 & $ getnod, astack(i), plnum=1, units=’Jy’, tsys=60 & accum & $ copy, 0, i*2+3 & $ end unfreeze ave Fit a baseline: .. code-block:: IDL setregion nfit, 3 bshape baseline Smooth the spectrum, then save it to disk. .. code-block:: IDL hanning, /decimate fileout, ’saved.fits’ keep Create a plot showing each individual spectrum (2 polarizations per scan pair) on a single plot, with offsets to make it easier to see the spectra: .. code-block:: IDL copy, 2, 0 baseline show copy, 0, 2 freeze for i=3,9 do begin copy, i, 0 & baseline & bias, float(i-2)*0.2 & copy, 0, i & end show, 2 unfreeze for i=3,9 do oshow, i, color=!red