Content-type: text/html Manpage of mosmem

mosmem

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NAME

mosmem - Maximum Entropy deconvolution for a mosaiced image  

PERSON RESPONSIBLE

rjs  

CATEGORIES

deconvolution  

DESCRIPTION

MOSMEM is a MIRIAD task which performs a maximum entropy deconvolution of a mosaiced image. Optionally it can also perform a joint deconvolution of a mosaic and single dish image.

MOSMEM will also work correctly on a single-pointing observation interferometric observation. In this case, it will be less efficient than MAXEN, but it could be used when combining single dish data with a single pointing.

MOSMEM spits out some information as it goes:

RMSFAC is the ratio (actual rms)/(theoretical rms). It measures the residuals (i.e. the difference between the dirty image and the model modified by the point spread function). RMSFAC should converge to 1.

NormGrd is normalised gradient in the maximisation process. Convergence requires this to be less than 0.05

Flux is the sum of all the pixel values in the model.  

PARAMETERS

map
One or perhaps two input dirty images (or cubes). These should have units of Jy/beam. The first should be produced by INVERTs mosaic mode. The optional second dirty map can be a single-dish image. It must be on exactly the same pixel grid as the first image. If necessary, use REGRID to make this so. If two inputs are given, then a joint deconvolution of the two is performed.
beam
One or perhaps two input dirty beams. The first, corresponding to the first input dirty map, will be produced by INVERTs mosaic mode. There is no default. The second dirty beam (which must be given if there are two dirty map inputs) gives the point-spread function of the single dish dirty map. This second dirty beam need not be the same image size as the input dirty maps, and may be appreciably smaller. This single-dish beam is assumed to be position-independent, but it need not be symmetric.
model
An initial estimate of the deconvolved image. For point sources, giving a good initial model may help convergence. In principle, this only helps convergence, but should not affect the final solution. The model could be the output from a previous run of MOSMEM or any other deconvolution task. It must have flux units of Jy/pixel. The default is a flat estimate, with the correct flux.
default
The default image. This is the image that the final solution will tend towards. The final result will be influenced by this default if the constrains that the data put on the solution are weak. The default is a flat estimate, with the correct flux.
out
The name of the output map. The units of the output will be Jy/pixel. It can be input to RESTOR to produce a restored image, or alternatively to MOSMEM, as a model, to continue the deconvolution process.
niters
The maximum number of iterations. The default is 30.
region
This specifies the region to be deconvolved. See the Users Manual for instructions on how to specify this. The default is the entire image.
measure
The entropy measure to be used, either "gull" (-p*log(p/e)) or "cornwell" (-log(cosh(p)) -- also called the maximum emptiness criteria). Using the maximum emptiness criteria is not recommended.
tol
Tolerance of solution. There is no need to change this from the default of 0.01.
q
One or two values (corresponding to the mosaic and single dish observations). These give estimates of the number of points per beam. MOSMEM can usually come up with a good, image-dependent estimate.
rmsfac
MOSMEM must be able to the theoretical rms noise of the input dirty map(s), and will, by default, attempt to reduce the residuals to have the same rms as this. If the true rms noise is different from the theoretical, you may give the factor to multiply by to convert from theoretical to true rms noise.

The theoretical rms will usually be an optimistic estimate of the true noise level. The true noise will be increased by calibration errors, confusion, poorly understood distant sidelobes, etc. The rmsfac factor gives some `fudge factor' (usually greater than 1) to scale the theoretical noise estimate by. Either one or two values can be given, with the second value corresponding to the single dish input.

For a mosaic, the theoretical rms is position dependent, and is determined from information save by INVERT (the mostable table). For a single dish image, the rms is assumed to be constant across the field, and given by the "rms" item in the image. If the single dish input does not contain this item, then this must be added before using MOSMEM. This is easily done: for image xxxx, use

  puthd in=xxxx/rms value=????
where "????" is the rms noise in Jy/beam.
factor
The flux calibration factor. This is only relevant when doing a joint deconvolution of a mosaic and a single-dish image. It gives the factor which the single-dish data should be multiplied by to convert it to the same flux units as the mosaic. The default is 1. If the ``dofactor'' options is used (see below), MOSMEM solves for this parameter.
flux
An estimate of the integrated flux of the source. This parameter is generally not useful if there is an input single dish image. Giving MOSMEM a good value for the integrated flux will help it find a good solution. On the other hand, giving a poor value may do harm. Normally MOSMEM will NOT constrain the integrated flux to be this value, but see the ``doflux'' option below. The default is image-dependent for measure=gull, and zero for measure=cornwell. A value can be given for each plane being deconvolved.
options
Task enrichment parameters. Several can be given, separated by commas. Minimum match is used. Possible values are:
  doflux     Constrain the solution to have the correct integrated flux
             (normally the integrated flux is not constrained). The
             integrated flux is determined from the "flux" parameter or
             (if no flux parameter is given) from the default image.
             This option cannot be used if a single dish input map is
             also given.
  dofactor   Solve for the flux calibration factor.
  verbose    Give lots of messages during the iterations. The default
             is to give a one line message at each iteration.


 

Index

NAME
PERSON RESPONSIBLE
CATEGORIES
DESCRIPTION
PARAMETERS

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Time: 18:35:38 GMT, July 05, 2011