linmos (Linear Mosaic Applicator)

This page provides instruction for using the linmos program. The purpose of this software is to perform a linear mosaic of a set of images.

Running the program

It can be run with the following command, where “config.in” is a file containing the configuration parameters described in the next section.

$ linmos -c config.in

The linmos program is not parallel/distributed.

Parallel linmos (linmos-mpi)

There is a parallel version of linmos which will divide the mosaic over the number of ranks. This improves the run time markedly as the I/O is distributed. Furthermore this also reduces the memory load.

Configuration Parameters

The following table contains the configuration parameters to be specified in the config.in file shown on above command line. Note that each parameter must be prefixed with “linmos.”. For example, the weighttype parameter becomes linmos.weighttype.

Note

During the BETA campaign there is no default option for weighttype. This option must be set.

Parameter Type Default Description
names vector<string> none Names of the input images. If these images start with “image” and have associated sensitivity images, the latter are integrated into a sensitivity image for the mosaic.
weights vector<string> null Optional parameter (required if using weight images). Names of input images containing pixel weights. There must be one weight image for each image, and the size must match. Ignored if weighttype=FromPrimaryBeamModel or if findmosaics=true.
outname string none Name of the output image. Ignored if findmosaics=true.
outweight string none Name of output image containing pixel weights. Ignored if findmosaics=true.
weighttype string none

How to determine the pixel weights. Options:

  • FromWeightImages: from weight images. Parameter weights must be present and there must be a one-to-one correspondence with the input images.
  • FromPrimaryBeamModel: using a Gaussian primary-beam model. If beam centres are not specified (see below), the reference pixel of each input image is used.
weightstate string Corrected

The weighting state of the input images. Options:

  • Corrected: Direction-dependent beams/weights have been divided out of input images.
  • Inherent: Input images retain the natural primary-beam weighting of the visibilities.
  • Weighted: Full primary-beam-squared weighting.
cutoff float 0.01 Desired cutoff of the gain function used to form weights, relative to the maximum gain.
psfref uint 0 Which of the input images to extract restoring-beam information from. The default behaviour is to use the first image specified (indices start at 0).
nterms uint -1 Process multiple taylor-term images. The string “taylor.0” must be present in both input and output image names (including weights images), and it will be incremented from 0 to nterms-1. Ignored if findmosaics=true.
findmosaics bool false Instead of specifying specific input and output files to mosaic, search the current directory for suitable mosaics. Parameter names is used to specify a vector of tags, and all groups of images that have names that are equal apart from these tags are mosaicked together. Groups must have one image per tag. Currently only groups with prefixes of “image” and “residual” are allowed, with prefixes “weights” and “sensitivity” special cases that are searched for once groups are identified. Parameters weights, outname, outweight and nterms are ignored if findmosaic=true.

If input images need to be regridded, the following ImageRegrid options are available:

Parameter Type Default Description
regrid.method string linear ImageRegrid interpolation method: nearest, linear, cubic or lanczos.
regrid.decimate uint 3 ImageRegrid decimation factor. In the range 3-10 is likely to provide the best performance/accuracy tradeoff
regrid.replicate bool false ImageRegrid replicate option.
regrid.force bool false ImageRegrid force option.

Definition of beam centres

If weights are generated from primary-beam models (weighttype=FromPrimaryBeamModel), it is possible to set the beam centres from within the parset. Since this is most likely useful when each input image comes from a different multi-beam feed, feeds offset parameters from other applications are used for this. If the origin of the beams offset system is not specified, using either feeds.centre or feeds.centreref, any offsets are ignored and the reference pixel of each input image is used as the primary-beam centre.

The feeds parameters can be given either in the main linmos parset or a separate offsets parset file set by the feeds.offsetsfile parameter.

Parameter Type Default Description
feeds.centre vector<string> none Optional parameter (it or feeds.centreref required when specifying beam offsets). Two-element vector containing the right ascension and declination that all of the offsets are relative to.
feeds.centreref int none Optional parameter (it or feeds.centre required when specifying beam offsets). Which of the input images to use to automatically set feeds.centre. Indices start at 0. If neither of these parameters are set, the reference pixel of each input image is used as the primary-beam centre.
feeds.spacing string none Optional parameter (required when specifying beam offsets in the main linmos parset). Beam/feed spacing when giving offsets in the main linmos parset. If feeds.offsetsfile is given, this parameter will be ignored.
feeds.names[i] (one per input image) vector<string> none Optional parameter (required when specifying beam offsets in the main linmos parset). Two-element vector containing the beam offset relative to the feeds.centre parameter. Offsets correspond to hour angle and declination. names[i] should match the names of the input images, given in linmos.names (see above). If feeds.offsetsfile is given, these parameters will be ignored.
feeds.offsetsfile string none Optional parameter. Name of the optional beam/feed offsets parset. If present, any offsets specified in the main linmos parset will be ignored.
feeds.names vector<string> none Optional parameter (required either here or below when specifying a beam offsets parset). The beam offsets parset should have one line per input image, with parameter keys (minus the feeds. prefix) specified by this parameter. If the offsets parset also contains a names parameter, the main linmos entry will hold, to allow a subset of beams from a general to be chosen.

If feed offsets are provided via an additional parset (i.e. not that one passed directly to the linmos program), the file shall have the following format:

Note

These parameters, specified in the external file, do not require the “limos.” prefix.

Parameter Type Default Description
feeds.names vector<string> null Optional parameter (required either here or above when specifying a beam offsets parset). The beam offsets parset should have one line per input image, with parameter keys (minus the feeds. prefix) specified by this parameter. If the offsets parset also contains a names parameter, the main linmos entry will hold, to allow a subset of beams from a general to be chosen.
feeds.spacing string none Beam/feed spacing. When using this extra offsets parset, the spacing needs to be specified in this parset.
feeds.beamnames[i] (one per input image) vector<string> none Two-element vector containing the beam offset relative to the feeds.centre parameter. Offsets correspond to hour angle and declination. beamnames[i] should match the names given in feeds.names* (see above).

Alternate Primary Beam Models

It is possible to select the model that is used for the weighting. This is selected in the linmos parset by the key “primarybeam”

Parameter Type Default Description
primarybeam string “GaussianPB” Optional parameter that allows the user to select which primary beam will be used in weighting. The parameters of which can also be altered if required

Gaussian Primary Beam Options

You can choose the aperture size and scaling parameters both of the FWHM of the beam and a scaling of the exponent. In the parfile these are sub parameters of the Primary beam type. (e.g linmos.primarybeam.GaussianPB.aperture)

Parameter Type Default Description
aperture double 12 Aperture size in metres.
fwhmscaling double 1.0 Scaling of the full width half max of the Gaussian
expscaling double 4 log(2) Scaling of the primary beam exponent

Primary Beam Corrections to the Taylor terms

The primary beam is a function of frequency. Therefore the apparent spectral index of a point source away from beam centre will contain a contribution from the frequency dependence of the primary beam. It is possible to estimate this contribution and remove it by scaling the Taylor term images appropriately.

Parameter Type Default Description
removebeam bool false Remove beam from the Taylor term images

Examples

Example 1:

Example linmos parset to combine individual feed images from a 36-feed simulation. Weights images are used to weight the pixels.

linmos.weighttype = FromWeightImages

linmos.names      = [image_feed00..35_offset.i.dirty.restored]
linmos.weights    = [weights_feed00..35_offset.i.dirty]

linmos.outname    = image_mosaic.i.dirty.restored
linmos.outweight  = weights_mosaic.i.dirty

Example 2:

Example linmos parset to combine the four inner-most feed images from a 36-feed observation. Gaussian primary-beam models are used to weight the pixels. The primary-beam offsets are provided in an external file.

linmos.weighttype       = FromPrimaryBeamModel

linmos.names            = [image_feed14..15.i.dirty.restored, image_feed20..21.i.dirty.restored]

linmos.outname          = image_mosaic.i.dirty.restored
linmos.outweight        = weights_mosaic.i.dirty

linmos.feeds.centre     = [12h30m00.00, -45.00.00.00]

# specify a beam offsets file
linmos.feeds.offsetsfile = linmos_beam_offsets.in

# Specify which feeds from the "offsetsfile" (specified above) are to be used
linmos.feeds.names       = [PAF36.feed14..15, PAF36.feed20..21]

Below is the linmos_beam_offsets.in file refered to in the above parameter set:

feeds.spacing            = 1deg
<snip>
feeds.PAF36.feed14       = [-0.5, -0.5]
feeds.PAF36.feed15       = [-0.5,  0.5]
<snip>
feeds.PAF36.feed20       = [0.5, -0.5]
feeds.PAF36.feed21       = [0.5,  0.5]
<snip>

Example 3:

Example linmos parset to combine the four inner-most feed images from a 36-feed simulation. The primary-beam offsets directly in the parameter set.

linmos.weighttype       = FromPrimaryBeamModel

linmos.names            = [image_feed14..15.i.dirty.restored, image_feed20..21.i.dirty.restored]

linmos.outname          = image_mosaic.i.dirty.restored
linmos.outweight        = weights_mosaic.i.dirty

linmos.feeds.centre     = [12h30m00.00, -45.00.00.00]

linmos.feeds.spacing    = 1deg
linmos.feeds.image_feed14.i.dirty.restored = [-0.5, -0.5]
linmos.feeds.image_feed15.i.dirty.restored = [-0.5,  0.5]
linmos.feeds.image_feed20.i.dirty.restored = [0.5, -0.5]
linmos.feeds.image_feed21.i.dirty.restored = [0.5,  0.5]

Example 4:

Example linmos parset to combine individual feed images from a 36-feed simulation for each of three separate taylor terms 0, 1 and 2. The location of taylor.* in all inputs and outputs is given explicitly.

linmos.weighttype = FromWeightImages

linmos.names      = [image_feed00..35_offset.i.dirty.taylor.0.restored]
linmos.weights    = [weights_feed00..35_offset.i.dirty.taylor.0]

linmos.outname    = image_mosaic.i.dirty.taylor.0.restored
linmos.outweight  = weights_mosaic.i.dirty.taylor.0

linmos.nterms = 3

Example 5:

Example linmos parset to combine individual feed images from a 36-feed simulation. A mosaics is made for each set of 36 images that has one image for each tag (param “names”) but filenames that are otherwise the same. Only the “image” and “residual” prefixes are currently supported. For example, if the outputs produced for Data Challenge 1A were produced for each feed and stored in a single directory, the following mosaics would be made: image_linmos.i.clean.taylor.0, image_linmos.i.clean.taylor.0.restored, image_linmos.i.clean.taylor.1, image_linmos.i.clean.taylor.1.restored, image_linmos.i.dirty.restored, residual_linmos.i.clean.taylor.0 and residual_linmos.i.clean.taylor.1. Associated weights and sensitivity images would also be made, however in situations where multiple mosaics have the same weights or sensitivites (e.g. image_linmos.i.clean.taylor.0, image_linmos.i.clean.taylor.0.restored and residual_linmos.i.clean.taylor.0), only one would be made.

Furthermore, since the DC1A does not seem to produce weights.*.taylor.2 and we have specified weighttype FromWeightImages, mosaic image_linmos.clean.taylor.2 would not be made. It would be produced if weighttype were FromPrimaryBeamModel.

linmos.weighttype  = FromWeightImages
linmos.findmosaics = true
linmos.names       = [feed00..35_offset]