Difference between revisions of "Clean"

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Deconvolve an image with selected algorithm
 
Deconvolve an image with selected algorithm
  
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                 then [45 66 123 124] is assigned to first field (imagename[0], or first line
 
                 then [45 66 123 124] is assigned to first field (imagename[0], or first line
 
                 of outlierfile).
 
                 of outlierfile).
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</pre>

Revision as of 10:45, 30 October 2009

Deconvolve an image with selected algorithm

       This is the main clean deconvolution task.  It contains many functions
 
        1)  Make 'dirty' image and 'dirty' beam (psf)
        2)  Multi-frequency-continuum images or spectral channel imaging
        3)  Full Stokes imaging
        4)  Mosaicking of several pointings
        5)  Multi-scale cleaning
        6)  Interactive clean boxing
        7)  Use starting model (eg from single dish)
 
 
       vis -- Name of input visibility file
               default: none; example: vis='ngc5921.ms'
       imagename -- Pre-name of output images:
               default: none; example: imagename='m2'
               output images are:
                 m2.image; cleaned and restored image
                        With or without primary beam correction
                 m2.psf; point-spread function (dirty beam)
                 m2.flux;  relative sky sensitivity over field
                 m2.flux.pbcoverage;  relative pb coverage over field 
                                      (gets created only for ft='mosaic')
                 m2.model; image of clean components
                 m2.residual; image of residuals
                 m2.interactive.mask; image containing clean regions
               To include outlier fields: 
                 imagename=['n5921','outlier1','outlier2'] 
       outlierfile --- Text file name which contains image names, sizes, field
                       centers
       field -- Select fields in mosaic.  Use field id(s) or field name(s).
                  ['go listobs' to obtain the list id's or names]
               default: ''= all fields
                 If field string is a non-negative integer, it is assumed to
                 be a field index otherwise, it is assumed to be a 
                 field name
                 field='0~2'; field ids 0,1,2
                 field='0,4,5~7'; field ids 0,4,5,6,7
                 field='3C286,3C295'; field named 3C286 and 3C295
                 field = '3,4C*'; field id 3, all names starting with 4C
       spw -- Select spectral window/channels
               NOTE: This selects the data passed as the INPUT to mode
               default: ''=all spectral windows and channels
                 spw='0~2,4'; spectral windows 0,1,2,4 (all channels)
                 spw='0:5~61'; spw 0, channels 5 to 61
                 spw='<2';   spectral windows less than 2 (i.e. 0,1)
                 spw='0,10,3:3~45'; spw 0,10 all channels, spw 3, 
                                   channels 3 to 45.
                 spw='0~2:2~6'; spw 0,1,2 with channels 2 through 6 in each.
                 spw='0:0~10;15~60'; spectral window 0 with channels 
                                    0-10,15-60
                 spw='0:0~10,1:20~30,2:1;2;3'; spw 0, channels 0-10,
                      spw 1, channels 20-30, and spw 2, channels, 1,2 and 3
       selectdata -- Other data selection parameters
               default: True

  >>> selectdata=True expandable parameters
               See help par.selectdata for more on these

               timerange  -- Select data based on time range:
                   default: '' (all); examples,
                   timerange = 'YYYY/MM/DD/hh:mm:ss~YYYY/MM/DD/hh:mm:ss'
                   Note: if YYYY/MM/DD is missing date defaults to first 
                         day in data set
                   timerange='09:14:0~09:54:0' picks 40 min on first day
                   timerange='25:00:00~27:30:00' picks 1 hr to 3 hr 
                             30min on NEXT day
                   timerange='09:44:00' pick data within one integration 
                             of time
                   timerange='>10:24:00' data after this time
               uvrange -- Select data within uvrange (default units meters)
                   default: '' (all); example:
                   uvrange='0~1000klambda'; uvrange from 0-1000 kilo-lambda
                   uvrange='>4klambda';uvranges greater than 4 kilo lambda
               antenna -- Select data based on antenna/baseline
                   default: '' (all)
                   If antenna string is a non-negative integer, it is 
                   assumed to be an antenna index, otherwise, it is
                   considered an antenna name.
                   antenna='5&6'; baseline between antenna index 5 and 
                                 index 6.
                   antenna='VA05&VA06'; baseline between VLA antenna 5 
                                       and 6.
                   antenna='5&6;7&8'; baselines 5-6 and 7-8
                   antenna='5'; all baselines with antenna index 5
                   antenna='05'; all baselines with antenna number 05 
                                (VLA old name)
                   antenna='5,6,9'; all baselines with antennas 5,6,9 
                                   index numbers
               scan -- Scan number range.
                   default: '' (all)
                   example: scan='1~5'
                   Check 'go listobs' to insure the scan numbers are in order.
       mode -- Frequency Specification:
               NOTE: See examples below:
               default: 'mfs'
                 mode = 'mfs' means produce one image from all 
                      specified data.
                 mode = 'channel'; Use with nchan, start, width to specify
                         output image cube.  See examples below
                 mode = 'velocity', means channels are specified in 
                      velocity.
                 mode = 'frequency', means channels are specified in 
                      frequency.

  >>> mode='mfs' expandable parameters 
               Make a continuum image from the selected frequency
               channels/range using Multi-frequency synthesis
               algorithm for wide-band narrow field imaging.
               nterms is the number of Taylor terms to be used to
               model the frequency dependence of the sky emission.
               nterms=1 is equivalent to assuming no frequency
               dependence.  nterms=2 is equivalent to the
               Sault-Wieringa algorithm (AandAS, 1994)
               reffreq is the reference frequency about which the
               Taylor expansion is done.

  >>> mode expandable parameters (for modes other than 'mfs')
               Start, width are given in units of channels, frequency 
                  or velocity as indicated by mode (note: only nearest neighbour 
                  interpolation is available at this time).
               nchan -- Number of channels (planes) in output image
                 default: 1; example: nchan=3
               start -- Start input channel (relative-0)
                 default=0; example: start=5
               width -- Output channel width in units of the input
                     channel width (>1 indicates channel averaging)
                 default=1; example: width=4
               interpolation -- Interpolation type of spectral data when gridded on
                  the uv-plane
                 default = 'nearest'
                    HOWEVER, 'linear' is recommended
               outframe -- velocity reference frame of output image (for mode='velocity' or 'frequency')
                 Options: '','LSRK','LSRD','BARY','GEO','TOPO','GALACTO','LGROUP','CMB'
                 default: ''; same as input data; example: frame='bary' for Barycentric frame 
               veltype -- (for mode='velocity') velocity definition
                 Options: 'radio','optical','true' (='relativistic')
                 veltype='true' (or equivalently 'relativistic') 
                 for velocity defined without approximations using the relativistic expression 
                 default: 'radio'
           examples:
               spw = '0,1'; mode = 'mfs'
                  will produce one image made from all channels in spw 
                       0 and 1
               spw='0:5~28^2'; mode = 'mfs'
                  will produce one image made with channels 
                       (5,7,9,...,25,27)
               spw = '0'; mode = 'channel': nchan=3; start=5; width=4
                  will produce an image with 3 output planes
                  plane 1 contains data from channels (5+6+7+8)
                  plane 2 contains data from channels (9+10+11+12)
                  plane 3 contains data from channels (13+14+15+16)
               spw = '0:0~63^3'; mode='channel'; nchan=21; start = 0; 
                   width = 1
                  will produce an image with 20 output planes
                  Plane 1 contains data from channel 0
                  Plane 2 contains date from channel 2
                  Plane 21 contains data from channel 61
               spw = '0:0~40^2'; mode = 'channel'; nchan = 3; start = 
                   5; width = 4
                  will produce an image with three output planes
                  plane 1 contains channels (5,7)
                  plane 2 contains channels (13,15)
                  plane 3 contains channels (21,23)

       psfmode -- method of PSF calculation to use during minor cycles:
               default: 'clark': Options: 'clark','clarkstokes', 'hogbom'
               'clark'  use smaller beam (faster, usually good enough);
                for stokes images clean components peaks are searched in the I^2+Q^2+U^2+V^2 domain 
               'clarkstokes' locate clean components independently in each stokes image
               'hogbom' full-width of image (slower, better for poor 
               uv-coverage)
               Note:  psfmode will be used to clean is imagermode = ''
       imagermode -- Advanced imaging e.g mosaic or Cotton-Schwab clean
               default: imagermode='': Options: '', 'csclean', 'mosaic'
               default ''  => psfmode cleaning algorithm used

  >>> gridmode='' expandable parameters

               The default value of '' has no effect.
        
  >>> gridmode='widefield' expandable parameters

               Apply corrections for non-coplanar effects during imaging
               using the W-Projection algorithm (Cornwell et al. IEEE JSTSP
               (2008)) or faceting or a combination of the two.

               wprojplanes is the number of pre-computed w-planes used for
                   the W-Projection algorithm.  wprojplanes=1 disables
                   correction for non-coplanar effects. 
               facets is the number of facets used.  W-Projection is done
                   for each facet.

  >>> gridmode='aprojection' expandable parameters

               Correct for the (E)VLA polarization squint using the
               A-Projection algorithm (Bhatnagar et al., AandA (2008)).

               cfcache is the name of the directory to be used to cache the
                   convolution functions.  These functions can be reused again if
                   the image parameters are unchanged.  If the image parameters
                   change, a new cache must be created (or the existing one
                   removed). 

               painc (in degrees) is the Parallactic Angle increment used to
                   compute the convolution functions.

  >>> imagermode='mosaic' expandable parameter(s):
               Image as a mosaic of the different pointings (uses csclean style too)
               mosweight -- Individually weight the fields of the mosaic
                   default: False; example: mosweight=True
                   This can be useful if some of your fields are more
                   sensitive than others (i.e. due to time spent 
                   on-source); this parameter will give more weight to 
                   higher sensitivity fields in the overlap regions.
               ftmachine -- Gridding method for the image;
                   Options: ft (standard interferometric gridding), sd
                   (standard single dish) both (ft and sd as appropriate),
                   mosaic (gridding use PB as convolution function)
                   default: 'mosaic'; example: ftmachine='ft'
                   if imagermode mosaic is chosen and ftmachine is mosaic, 
                   heterogenous arrays like Carma or Alma are recognized
                   and the right Primary Beam (depending on the size of the dish)
                   is used for each baseline. 
               scaletype -- Controls scaling of pixels in the image plane.
                   (Not fully implemented...for now only controls 
                   what is seen if interactive=True...but in the future will 
                   control the image on which clean components are searched)
                   default='SAULT'; example: scaletype='PBCOR'
                   Options: 'PBCOR','SAULT'
                     'SAULT' when interactive=True shows the residual
                             with constant noise across the mosaic. If
                             pbcor=False, the final output image is NOT
                             corrected for the PB pattern, and therefore is
                             not "flux correct". Division of SAULT
                             <imagename>.image by the <imagename>.flux image
                             will produce a "flux correct image", can also
                             be acheived by setting pbcor=True.
                     'PBCOR' uses the SAULT scaling scheme for
                             deconvolution, but if interactive=True shows the
                             primary beam corrected image; the final PBCOR
                             image is "flux correct" if pbcor=True.

  >>> imagermode='csclean' expandable parameter(s): 
               Image using the Cotton-Schwab algorithm in between major cycles
               cyclefactor -- Change the threshold at which the deconvolution 
                   cycle will stop, degrid and subtract from the visibilities.  
                   For poor PSFs, reconcile often (cyclefactor=4 or 5); 
                   For good PSFs, use cyclefactor 1.5 to 2.0. 
                   Note: threshold = cyclefactor * max sidelobe * max residual.
                   default: 1.5; example: cyclefactor=4
               cyclespeedup -- Cycle threshold doubles in this number of 
                   iterations 
                   default: -1;
                   example: cyclespeedup=3
                   try cyclespeedup = 50 to speed up cleaning 

       multiscale -- set of scales to use in deconvolution.  If set,
               cleans with several resolutions using hobgom clean. The
               scale sizes are in units of cellsize.  So if
               cell='2arcsec', a multiscale scale=10 = 20arcsec.  First
               scale should always be 0 (point), we suggest second on
               the order of synthesized beam, third 3-5 times
               synthesized beam, etc. For example if synthesized beam
               is 10" and cell=2", try multscale = [0,5,15]. Note,
               multiscale is currently a bit slow.
               default: multiscale=[] (standard CLEAN using psfmode algorithm,
               no multi-scale). Example:  multiscale = [0,5,15] 

  >>> multiscale expandable parameter(s): 
               negcomponent -- Stop component search when the largest scale has
                   found this number of negative components; -1 means continue
                   component search even if the largest component is
                   negative.  default: -1; example: negcomponent=50
               smallscalebias -- A bias toward smaller scales. 
                   The peak flux found at each scale is weighted by 
                   a factor = 1 - smallscalebias*scale/max_scale, so
                   that Fw = F*factor.
                   Typically the values range from 0.2 to 1.0.
                   default: 0.6

       imsize -- Image pixel size (x,y).  DOES NOT HAVE TO BE A POWER OF 2
               default = [256,256]; example: imsize=[350,350]
               imsize = 500 is equivalent to [500,500]
               If include outlier fields, e.g., [[400,400],[100,100]] or
               use outlierfile.
               Avoid odd-numbered imsize.
       cell -- Cell size (x,y)
               default= '1.0arcsec';
               example: cell=['0.5arcsec,'0.5arcsec'] or
               cell=['1arcmin', '1arcmin']
               cell = '1arcsec' is equivalent to ['1arcsec','1arcsec']
               NOTE:cell = 2.0 => ['2arcsec', '2arcsec']
       phasecenter -- direction measure  or fieldid for the mosaic center
               default: '' => first field selected ; example: phasecenter=6
               or phasecenter='J2000 19h30m00 -40d00m00'
               If include outlier fields, 
                e.g. ['J2000 19h30m00 -40d00m00',J2000 19h25m00 -38d40m00']
               or use outlierfile.
       restfreq -- Specify rest frequency to use for output image
               default='' Occasionally it is necessary to set this (for
               example some VLA spectral line data).  For example for
               NH_3 (1,1) put restfreq='23.694496GHz'
       stokes -- Stokes parameters to image
               default='I'; example: stokes='IQUV';
               Options: 'I','IV''QU','IQUV','RR','LL','XX','YY','RRLL','XXYY'
       niter -- Maximum number iterations,
               if niter=0, then no CLEANing is done ("invert" only)
               default: 500; example: niter=5000
       gain -- Loop gain for CLEANing
               default: 0.1; example: gain=0.5
       threshold -- Flux level at which to stop CLEANing
               default: '0.0mJy'; 
               example: threshold='2.3mJy'  (always include units)
                        threshold = '0.0023Jy'
                        threshold = '0.0023Jy/beam' (okay also)
       interactive -- use interactive clean (with GUI viewer)
               default: interactive=False
               example: interactive=True
               interactive clean allows the user to build the cleaning
               mask interactively using the viewer.  The viewer will
               appear every npercycle interation, but modify as needed
               The final interactive mask is saved in the file
               imagename_interactive.mask.  The initial masks use the
               union of mask and cleanbox (see below).

  >>> interactive=True expandable parameters
               npercycle -- this is the  number of iterations between each clean
                   to update mask interactively.  It is important to modify
                   this number interactively during the cleaning, starting wiht
                   a low number like 20, but then increasing as more extended
                   emission is encountered.
               chaniter -- specify how interactive CLEAN is performed, 
                  either by stepping through channels or do jointly for all channel
                   default: chaniter='joint'; 
                   example: chaniter='channel'; step through channels 

       mask -- Specification of cleanbox(es), mask image(s), and/or
               region(s) to be used for CLEANing. As long as the image has
               the same shape (size), mask images from a previous
               interactive session can be used for a new execution. NOTE:
               the initial clean mask actually used is the union of what
               is specified in mask and <imagename>.mask default: [] (no
               masking); Possible specification types: (a) Explicit
               cleanbox pixel ranges example: mask=[110,110,150,145] clean
               region with blc=110,100; trc=150,145 (pixel values) (b)
               Filename with cleanbox pixel values with ascii format:
               example: mask='mycleanbox.txt' <fieldid blc-x blc-y
               trc-x trc-y> on each line 
               1 45 66 123 124 
               2 23 100 300 340
               (c) Filename for image mask example: mask='myimage.mask'
               (d) Filename for region specification (e.g. from viewer)
               example: mask='myregion.rgn' (e) Combinations of any of the
               above example: mask=[[110,110,150,145],'mycleanbox.txt',
                                    'myimage.mask','myregion.rgn']
               If include outlier fields, then mask need to be specified in
               nested lists: 
                 e.g. mask=[[[110,110,150,145],'myimage.mask'],[],[20,20,40,40]]
               (A clean box with [110,110,150,145] and a image mask for main field, 
               no mask for 1st outlier field, 1 clean box for second outlier field.)
       uvtaper -- Apply additional uv tapering of the visibilities.
               default: uvtaper=False; example: uvtaper=True

  >>> uvtaper=True expandable parameters
               outertaper -- uv-taper on outer baselines in uv-plane
                   [bmaj, bmin, bpa] taper Gaussian scale in uv or 
                   angular units. NOTE: uv taper in (klambda) is roughly on-sky 
                   FWHM(arcsec/200)
                   default: outertaper=[]; no outer taper applied
                   example: outertaper=['5klambda']  circular taper 
                                FWHM=5 kilo-lambda
                            outertaper=['5klambda','3klambda','45.0deg']
                            outertaper=['10arcsec'] on-sky FWHM 10"
                            outertaper=['300.0'] default units are meters 
                                in aperture plane
               innertaper -- uv-taper in center of uv-plane
                   [bmaj,bmin,bpa] Gaussian scale at which taper falls to 
                   zero at uv=0
                   default: innertaper=[]; no inner taper applied
                   NOT YET IMPLEMENTED        
       modelimage -- Name of model image(s) to initialize cleaning. If
               multiple images, then these will be added together to
               form initial staring model NOTE: these are in addition
               to any initial model in the <imagename>.model image file
               default: '' (none); example: modelimage='orion.model'
               modelimage=['orion.model','sdorion.image'] Note: if the
               units in the image are Jy/beam as in a single-dish
               image, then it will be converted to Jy/pixel as in a
               model image, using the restoring beam in the image
               header
       weighting -- Weighting to apply to visibilities:
               default='natural'; example: weighting='uniform';
               Options: 'natural','uniform','briggs', 
                       'superuniform','briggsabs','radial'

  >>> Weighting expandable parameters
               For weighting='briggs' and 'briggsabs'
                   robust -- Brigg's robustness parameter
                   default=0.0; example: robust=0.5;
                   Options: -2.0 to 2.0; -2 (uniform)/+2 (natural)
               For weighting='briggsabs'
                   noise   -- noise parameter to use for Briggs "abs" 
                   weighting
                   example noise='1.0mJy'
               npixels -- uv-cell area used for weight calculation
                   example npixels=1
                   Default = 0
                   superuniform:  0 Means 3x3 cells for weighting
                     the cell weight is proportional to the weight of
                     the 3x3 cells centered on it.
                   superuniform = F means 1x1 cell for averaging weights.
                   briggs/briggsabs: 0 is similar to 1x1 cell weight.
                     1 may? be similar to 3X3 cells.
                   Only npixels 0 or 1 recommended
                   
       restoringbeam -- Output Gaussian restoring beam for CLEAN image
               [bmaj, bmin, bpa] elliptical Gaussian restoring beam
               default units are in arc-seconds for bmaj,bmin, degrees
               for bpa default: restoringbeam=[]; Use PSF calculated
               from dirty beam. 
               example: restoringbeam=['10arcsec'] circular Gaussian 
                        FWHM 10" example:
                        restoringbeam=['10.0','5.0','45.0deg'] 10"x5" 
                        at 45 degrees
       pbcor -- Output primary beam-corrected image 
               default: pbcor=False; output un-corrected image 
               example: pbcor=True; output pb-corrected image (masked outside
                        minpb) Note: if you set pbcor=False, you can later
                        recover the pbcor image by dividing by the .flux image
                        (e.g. using immath)
       minpb -- Minimum PB level to use default=0.1;
               The flux image is used to determine this
               except for the case of mosaic with ft='mosaic'
               where the flux.pbcoverage image is used.
               example:
                        minpb=0.01 Note: this minpb is always in effect
                        (regardless of pbcor=True/False) 
       calready -- if True will create scratch columns if they are 
               not there. And after clean completes the predicted model 
               visibility is from the clean components are written to the ms.
       async -- Run asynchronously 
               default = False; do not run asychronously


        ======================================================================

                             HINTS ON CLEAN WITH FLANKING FIELDS

              1. Decide if the images will be specified directly in the
                 inputs or with an outlier file.  For more than a few fields,
                 an outlier file more convenient.

                Direct Method:

                   cell = ['1.0arcsec', '1.0arcsec']
                   imagename = ['M1_0','M1_1','M1_2]
                   imsize = [[1024,1024],[128,128],[128,128]]
                   phasecenter = ['J2000 13h27m20.98 43d26m28.0',
                             'J2000 13h30m52.159 43d23m08.02', 'J2000 13h24m08.16 43d09m48.0']

                 Text file method  (in outlier.txt)

                   imagename = 'M1'
                   outlierfile = 'outlier.txt'
                      [phasecenter, imsize ignored]

                   Contents of outlier.txt 
                   C 0   1024 1024   13 27 20.98     43 26 28.0
                   C 1    128  128   13 30 52.158    43 23 08.00
                   C 2    128  128   13 24 08.163    43 09 48.00

                In both cases the following images will be made:
                    M1_0.image, M1_1.image, M1_2.image     cleaned images
                    M1.0.model, M1_1.model, M1_2.model     model images
                    M1.0.residual, M1_1.residual, M1_2.residual     residual images
                 an outlier file more convenient.

                Direct Method:

                   cell = ['1.0arcsec', '1.0arcsec']
                   imagename = ['M1_0','M1_1','M1_2]
                   imsize = [[1024,1024],[128,128],[128,128]]
                   phasecenter = ['J2000 13h27m20.98 43d26m28.0',
                             'J2000 13h30m52.159 43d23m08.02', 'J2000 13h24m08.16 43d09m48.0']

                 Text file method  (in outlier.txt)

                   imagename = 'M1'
                   outlierfile = 'outlier.txt'
                      [phasecenter, imsize ignored]

                   Contents of outlier.txt 
                   C 0   1024 1024   13 27 20.98     43 26 28.0
                   C 1    128  128   13 30 52.158    43 23 08.00
                   C 2    128  128   13 24 08.163    43 09 48.00

                In both cases the following images will be made:
                    M1_0.image, M1_1.image, M1_2.image     cleaned images
                    M1.0.model, M1_1.model, M1_2.model     model images
                    M1.0.residual, M1_1.residual, M1_2.residual     residual images

              2. Masks for flanking fields are specified in same way as 
                 in the single output field case, but need extra '[ ]' to
                 distinguish each field. 
                    mask=[['myregion.rg',[100,100,150,150]],['myimage1.mask'],[]]
                    would apply masks:
                    for the first field (main field),
                      myregion.rg and a box defined by [100,100,150,150] in pixels
                    for the seconf field (first outlier), myimage1.mask 
                    for the third field (second outlier), no mask (produce a mask for
                    whole field) 
                 However, if boxfiles are given, ids in the first column of the files
                 are used to match with fields (using order given imagename or
                 outlierfile. 
                 So, if the content of  a boxfile looks like this,
                         0 45 66 123 124 
                         1 23 100 300 340
                         2 20 20 40 40
                 then [45 66 123 124] is assigned to first field (imagename[0], or first line
                 of outlierfile).