The configuration file
dimmconfig_jsa_generic.lis is a good configuration file to use as a first
pass for reducing any data, and is the default configuration used by the pipeline’s
You can create your own personalised configuration file from scratch or copy one of the provided ones to your local directory and edit it.
The first line of each specialised configuration file is often the path to another configuration file—known as the parent configuration file. The new configuration file inherits all the parameter values defined by the parent configuration file, and then goes on to specify additional parameter settings which may supplement or override those defined in the parent configuration file. Parameters that are not set to a specific value by either configuration file assume the default values listed in Appendix I1.
Often you will want to use one of the pre-defined configuration files included within Starlink tree as the parent
configuration. Remember that any parameters appearing in your configuration file automatically
override the values supplied by the parent file. As an example, consider the following text file
The first thing to note is that blank lines and comment lines (i.e. lines beginning with the hash character “
are ignored and can be used to document your configuration file. Next note that this example file
$STARLINK_DIR/share/smurf/dimmconfig_jsa_generic.lis as its parent (the path to the
parent file must be preceded by an up-caret (
̂) character). Thus, all the parameter values set by
$STARLINK_DIR/share/smurf/dimmconfig_jsa_generic.lis are first read, before adding in other parameter
settings. In this case, values are assigned to
numiter, overriding the values provided by the parent
You can use more than one parent file if required (each one a separate line, and preceded by an up-caret). Each specified parent will be read in turn, with parameter settings read from later ones having priority over those read from earlier ones.
You can also add or amend parameters by listing them directly on the command line. They are appended to the configuration file name as a comma separated list as shown in the example below. Be sure to include all the necessary quotation marks.
For full details of all the possible ways of specifying groups of parameter values, see Section “Specifying Groups of Objects” in “Starlink User Note 95”.
What parameters can be changed?
Appendix I lists the parameters that are more likely to be of interest to you when creating your own configuration files. You can also change any of the other more esoteric parameters not included in that list—see Appendix SUN/258 within Starlink User Note 258 for a full list—but we do not advise this.
0, or some other special value.
Note: any parameter can be made wavelength dependent by adding the prefix
to both 450 m and
850 m whilst
applies to 450 m
only. Be aware that if both are specified, unqualified values (no prefix) take priority over qualified
Setting the parameter
= 1 writes out the map containing the astronomical signal after each iteration.
itermap = 2 adds the QUALITY component (see Section 8.6. These can be visually inspected
to help determine an appropriate number of iterations. Alternatively, you can view several itermaps simultaneously side-by-side (e.g. Figure 5.1) using Kappa as described in Section 5.3.2.
Viewing itermaps is useful when a fixed number of iterations have been requested (i.e. a positive value for
numiter) and the map solution diverges before they have completed. See also Section 5.3.2 for how to view
these maps whilst makemap is still running.
If the parameter
shortmaps is non-zero, a map is made from every group of adjacent time-slices. When set to -1,
a map is produced each time a full pass through the scan pattern has been completed. Any other negative value
is interpreted as a duration in seconds, and is converted to time slices using the (possibly down-sampled)
sample frequency of the data being mapped. These are stored as an NDF extension and can be viewed
Stack the individual itermaps into a single cube (Kappa PASTE can also be used).
The output map
map_itermaps can be opened
with Gaia. The data used in
this example is the Galactic
map reduced in Section 7.2.
The Spectral plot window
shows the value for a single
pixel and the three chunks are
identified. You can select the
Animation tab in the Display
image sections window and
click Start to loop through the
itermaps for each iteration.
The ‘movie’ will appear in the
main Gaia window.
These windows show the itermaps map at 1, 10, and 30 iterations. A specific iteration can be selected using the Index of plane slider on the Display image sections window.
You can view the shortmaps and itermaps more conveniently by stacking them into a single cube using the
Smurf command stackframes. This cube can then be viewed as a ‘movie’ with Gaia, using the animation option
to loop through the itermaps. See Figure 6.1 for instructions.
This parameter has been discussed in Section 9.8 and allowed you to see the model that was fit for each component specified by the
Some of the most important parameters to experiment with are the filtering options. By default, no filtering is applied during the
(see ?? and ??). A high-pass filter is used during the iterative stage if
and selected a suitable value for the filter size is crucial for maps containing extended emission. See Mairs et al.
2015  for more information about extended emission recovery, wherein model sources with known
parameters were added to the raw SCUBA-2 timestream using “
fakemap” in order to investigate the effects of
The maximum spatial scale of structure that can be recovered by the map-maker is determined by the scanning speed and frequency cut applied to the data:
The default (i.e. if no configuration is supplied) filter sizes in arcseconds are:
To make your life easier, these parameters allow you to specify the filter limits in terms of spatial scale in arcseconds—in this case 480 arcsec at 850 m and 200 arcsec at 450 m. For example, at 850 m, recovering scales of 480 arcsec at a scan speed of 600 arcsec/sec (default for a 1 degree pong) corresponds to a frequency of 1.25 Hz.
Choosing a high-pass filter is especially important for the recovery of extended emission.
dimmconfig_bright_extended configuration file sets ??
= 480 for both
450 m and
Be aware that increasing filter sizes decreases the flatness of your background. A compromise must be made
between extended structure and the flatness of your map. See Figure 6.2 for an illustration of the effect of ?? on
The scanning speeds are fixed for a given observing mode; you can find out the speed at which your data were
taken from the
SCAN_VEL keyword in the FITS header (see Section 9.2).
Flattening the background
There is an option to reduce the noise in your background introduced by setting a high value for the large-scale filter. The parameter ?? filters the regions outside your
AST mask (see Section 3.5.1) on a shorter scale for the last
iteration only, thereby producing a much flatter background. Note that this is probably a bad idea if you intend
to co-add several observations, as it removes potentially real structure in the background regions that could
otherwise be recovered by co-adding several observations. In general, use of
should be seen as a cosmetic enhancement, since it results in differing filter sizes being used inside and outside
Also note that when using
flt.filt_edge_largescale_last the variances stored in the final map are from the
penultimate iteration in order to avoid using the artificially reduced variances created on the last
A useful option to improve the flatness of your maps is to fit the
COM model independently for
each sub-array. This is particularly effective if you find you have one sub-array noisier than the
This comes with the warning however that you will lose information on any scales larger than the area covered by a single sub-array (200. It is therefore not recommended if you have very large-scale extended structure.
To initialise this option set
Bolometers that have higher noise levels are down-weighted when forming the map. By default, a separate noise estimate is created for each 15 second section4 of each bolometer time-stream, but an alternative length can be specified using parameter ??.
Dividing each bolometer up into sections helps to remove ‘scuffs’ or other noise artefacts you might see in your error map due to a sub-array (or arrays) temporarily jumping to a higher noise state. As the section length tends to 1 second we find some of the source signal being down-weighted. Higher than this 15 seconds and the map-maker becomes less sensitive to the higher noise states.
Other parameters you may want to try include
flagslow. You may find that setting
less than the default of 1000 arcsec/sec will help reduce the effect of any ‘smearing’ of sources (and of noise) in
maps, while setting
flagslow greater than the default of 300 arcsec/sec helps to flatten the edges of maps. To
determine reasonable values for your data-set you should do jcmtstate2cat and view the scan speed using
Topcat. See Section 9.3 for details.
For an introduction to the purpose and effects of masking, see Section 3.5 and Mairs et al. (2015) .
As an S/N mask is redetermined after each iteration it changes with the map which can sometimes cause convergence problems. The mask will also depend on the amount of data going into the map and the pixel size. A fixed externally supplied mask can get around these problems.
The sequence below is a summary of the procedure for generating and supplying an external mask. In this example the mask is generated from the map produced by an initial run through the map-maker. Alternatively, SNR maps or flux contours calculated from data obtained by other observatories can be used.
These steps are followed in the example in Section 7.2.
|Step 1||Generate a map covering your region. This may be by simply running the map-maker on your data as
The alternative is to access a map from a different data-set or even a different telescope, e.g. a map
downloaded from the Herschel Science Archive. For instructions on converting from FITS to NDF see
|Step 2||Make a signal-to-noise map using the Kappa command makesnr.|
|Step 3||Threshold this S/N map to set everything below
to 0 and everything above to 1.
This generates a mask which has an unrealistic hard 3 cut-off. Step 4 is performed to smooth the the edges of your mask.
|Step 4||Smooth the thresholded map with a Gaussian filter of FWHM of 5 pixels (= 20 arcsec at
using the default pixel size). Then it is again thresholded, this time keeping everything above 5 % of the 0
level as the mask and setting the rest to |
|Step 5||Finally the map is re-made with this mask supplied as an external file. Notice that the extra parameters required to pick up this external mask are being appended to the configuration file on the command line rather than editing the file itself.|
Traditionally, the map-maker divides a non-contiguous sequence of time-series data into chunks. It processes each chuck independently before co-adding them as a final step in the the reduction—see Figure 6.3.
This means for each chunk the map-maker has to start from scratch determining the
AST model, and the benefit
of long integration times spent building up the signal is lost. Configuration files that use signal-to-noise masks
especially suffer from this approach as the signal-to-noise in each individual chunk can remain low and fainter
extended structure is not recovered.
The skyloop command is a script that runs makemap multiple times performing just a single iteration on each
occasion. It starts by performing a single iteration of makemap from which a co-added map is generated. This
map is then supplied as an initial estimate of the sky for the next invocation of makemap. On this next
invocation, the initial sky estimate is subtracted from the cleaned time-series data and the
models are subtracted. This produces a new model of the sky (from the current iteration) to which the sky
estimate (from the previous iteration) is then added. In this way the signal from all of the chunks
is built up over the iterations and is all included in the final map estimate when convergence is
Be aware that skyloop uses a lot of disk space. Setting environment variable
STAR_TEMPto a suitable
location before you start will prevent skyloop from crashing if you run out of temporary storage
skyloop can then be called in a way very similar to makemap, with a configuration file specified on the command line.
I have blobs in my map that look like big thumbprints.
In addition, check you are not using
I want to recover more extended structure.
There is a trade off between extended emission and noise in your
map. If you are willing to accept more low frequency noise you can
increase the filter scale with ??. The default is 480 arcsec but you
could try 600 arcsec. To reduce the increased background noise you
can set ??
I want a flatter background.
I have linear striations in my map making my background look scratchy.
Try setting ??
My map will not converge.
1These default values are defined in the file
415 seconds is half a sub-scan.