Raw ACSIS data follow this naming convention:
a20131115_00055_03_0001.sdf. The first ‘a’ represents ACSIS. The UT date
and observation number (OBSNUM) serve as an identifier for any given night of observing.
ACSIS observations may include up to four frequency settings given by the different
subsystems (00-03), while long observations may require multiple subscans to avoid a file size
Use the Starlink application Gaia to visualise your raw data. The is initiated by:
Loading a file in Gaia produces two windows (see Figure 4.1). The main window shows a map of the HARP receptors (along the -axis; note the 16 pixels) for a given sample of the observation (time on the -axis). You can track the performance of an individual receptor by following a column from bottom to top to check its consistency. In Figure 4.1 H03 is dead for the whole observation. The spectrum for a receptor at one of the time slices can be seen by clicking on the pixel. This will bring up a third window—the Spectral plot (see Figure 4.2). This spectrum will be replaced when you click on a different pixel.
You can change the way the data is displayed in the Display image sections of a cube window by changing the Axis. Selecting Axis number two will display spectra against time while Axis number three gives spectra against receptors. You can scroll through your data by moving the Index of plane slider.
A second way to scroll through your spectrum is to click and drag the vertical red bar on the Spectral plot window. As you do so array shown in the main window will automatically update.
You will likely want to change the auto cut of the colour scale, the colour scheme and the zoom factor—all of which are controlled by buttons on the sidebar in the main window.
See the Gaia manual for full details.
You can mask bad receptors in the time-series data with the Kappa command chpix. In the example below all
data for Receptors 7 and 8 (on the second axis) are turned off by setting them to BAD. Note the commas in the
SECTION parameter which specify which axis is being referred to; here the first (spectra) and third (time) axes are
unchanged so no range is defined. You will have to repeat the command for non-contiguous receptor
You can also mask a subset of the time stream for a particular receptor. The example below masks out time Steps 18 to 33 for receptor H01. See Figure 4.3 for instructions on how to identify the affected time range.
Note that the numbering for the 16 receptors here is 1–16; this is in contrast to 0–15 that you will encounter with the pipeline.
For jiggle maps, where the receptors do not cover multiple sky positions, bad receptors can be identified in the reduced cubes. For raster maps, however, bad receptors are most easily identified in the time-series data. Once you have opened your raw cube in Gaia it is useful to select the second axis (receptor) which gives spectral dispersion along the -axis and time along the -axis. You can use the cube control panel to step through each receptor looking for bad spectra (see Figures 4.3 and 4.4).