Removing bad skydip data from the fit

Occasionally it is necessary to remove bad points from skydip data prior to fitting. This is implemented in the same way as it is implemented for other SCUBA data by using change_quality. The following extra steps are required:

1. Run reduce_switch to calculate the sky brightness temperature for each integration at each airmass (measurement). The cold load temperature for each sub instrument will be requested.

   % reduce_switch 70
   SURF: Opening 19971115_dem_0070 in /scuba/observe/19971115/dem
   SURF: run 70 was a SKYDIP observation
   SURF: file contains data for 1 switch(es) in 1 exposure(s) in 10 integration(s)
   in 10 measurement(s)
   OUT - Name of output file to contain reduced switch data /'o70'/ > 
   T_COLD - Temperature of cold load for SHORT_DC /95/ > 
   T_COLD - Temperature of cold load for LONG_DC /55/ >
   

   Figure: Skydip data after processing with reduce_switch (left) and after measurement 5 has been removed with change_quality (right).

   

2. The resulting output file looks just like a file produced by reduce_switch on map data: it contains a 2 dimensional data array of sub-instrument (bolometer) number along the first axis and sample number (number of integrations times number of measurements) along the second axis. You can find the sub-instrument corresponding to each `bolometer' number either by running skydip and noting the order of the listed sub-instruments or by using the KAPPA fitslist command:

   % fitslist o70 | grep SUB_
   SUB_1   = 'SHORT   '           / SCUBA instrument being used
   SUB_2   = 'LONG    '           / SCUBA instrument being used
   SUB_3   = 'not used'           / SCUBA instrument being used
   SUB_4   = 'not used'           / SCUBA instrument being used
   SUB_5   = 'not used'           / SCUBA instrument being used
   

   For example, the data for the second sub-instrument (in this case the LONG array) can be plotted by using:

   % linplot mode=2 device=xwindows 'o70(2,)'
   

   Fig. shows an example. Note that, in contrast with other observing modes, the second axis is labelled in measurements rather than integrations.

3. Once a bad measurement has been identified, it can be switched off using change_quality:

   % change_quality 'o70{b2;m5}' yes
   SURF: run 70 was a SKYDIP observation of not used
   SURF: file has data for 2 bolometers, measured at 100 positions.
    - there are data for 1 exposure(s) in 10 integration(s) in 10 measurements.
   

   The main thing here is that the m identifier should be used to specify measurements¹³ and that only bolometer (i.e. sub-instrument) 2 should be affected.

4. Now skydip(or sdip) can be run on the file:

   % skydip o70
   SURF: run 70 was a SKYDIP observation
   SURF: observation started at sidereal time 1 10 41 and ended at 1 16 38
   SURF: file contains data for the following sub-instrument(s)
    - SHORT with filter 350
    - LONG with filter 750
   SUB_INSTRUMENT - Name of sub-instrument to be analysed /'SHORT'/ > long
   SURF: file contains data for 10 integration(s) in 10 measurement(s)
   ETA_TEL - Telescope efficiency /0.87/ > 
   B_VAL - B parameter /-1/ > 
   SCULIB: fit for filter 750 and sub-instrument LONG_DC
    eta =  0.87 +/-  0.00  b =  0.86 +/-  0.01  tau =   0.667 +/- 0.007
    Standard Deviation of fit residual =   0.81 K (X=     0.9 N=    7)
   

   The fit is shown in Fig. . skydip is the only task that can process raw demodulated data and data processed with reduce_switch.

   Figure: Skydip plus model without measurement 5