Difference between revisions of "Clean"

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Revision as of 16:43, 16 March 2012

Help on clean task:

Invert and deconvolve images with selected algorithm

       The clean task has many options:
        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)  Widefield cleaning
        7)  Interactive clean boxing
        8)  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: 
       outlierfile --- Text file name which contains image names, sizes, field
       field -- Select fields to image or mosaic.  Use field id(s) or 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: channels de-selected here will contain all zeros if
               selected by the parameter mode subparameters.    
               Channel selection behaves differently in clean (e.g. The multiple
               ranges are not supported yet).
               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.
       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: Channels deselected with spw parameter will contain all
               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. 
                 mode = 'velocity', channels are specified in velocity.
                 mode = 'frequency', 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. ** Note that the 
               software implementation of the algorithm for nterms>1 
               is still experimental and will be fully available in a 
               later release. **

  >>> mode='channel', 'velocity', and 'frequency' expandable parameters
               nchan -- Total number of channels in the output image.
                 Example: nchan=100. 
                 Default: -1; Automatically selects enough channels to cover 
                 data selected by 'spw' and consistent with 'start' and 'width'. 
                 It is often easiest to leave nchan at the default value. 
               start -- First channel, velocity, or frequency. 
                 For mode='channel'; This selects the channel index number 
                 from the MS (0 based) that you want to correspond to the first 
                 channel of the output cube. The output cube will be in frequency 
                 space with the first channel having the frequency of the
                 MS channel selected by start.  start=0 refers to the first 
                 channel in the first selected spw, even if that channel 
                 is de-selected in the spw parameter. Channels de-selected by 
                 the spw parameter will be filled with zeros if included by
                 the start parameter. For example, spw=3~8:3~100 and start=2
                 will produce a cube that starts on the third channel (recall 0
                 based) of spw index 3, and the first channel will be blank.
                 For mode='velocity' or 'frequency': default=''; 
                 starts at first input channel of first input spw
                 examples: start='5.0km/s', or start='22.3GHz'.
               width -- Output channel width
                 For mode='channel', default=1; >1 indicates channel averaging
                 example: width=4.
                 For mode=' 'velocity' or 'frequency', default=''; width of
                 first input channel, or more precisely, the difference 
                 in frequencies between the first two selected channels. 
                 (for example if channels 1 and 3 are selected with spw, 
                  then the default width will be the difference between their
                  frequencies, and not the width of channel 1)
                 When not using the default, one must give units
                 examples: width='1.0km/s', or width='24.2kHz'.
                 Setting width>0 gives channels of increasing frequency for 
                 mode='frequency', and increasing velocity for mode='velocity'. 
               interpolation -- Interpolation type for spectral gridding onto 
                 the uv-plane. Options: 'nearest', 'linear', or 'cubic'.
                 default = 'linear'
               chaniter -- specify how spectral CLEAN is performed, 
                 default: chaniter=False;
                 example: chaniter=True; step through channels 
                  WARNING: The interactive clean with chaniter=True for
                    optical velocity mode
                    (mode='velocity' and veltype='optical') is
                    NOT YET IMPLEMENTED.
               outframe -- For mode='velocity', 'frequency', or 'channel':  velocity
                 reference frame of output image
                 Options: '','LSRK','LSRD','BARY','GEO','TOPO','GALACTO',
                 default: ''; same as input data
                 example: frame='bary' for Barycentric frame 
               veltype -- for mode='velocity' gives the velocity definition
                 Options: 'radio','optical' 
                 default: 'radio'
                 NOTE: the viewer always defaults to displaying the 'radio'
                   frame, but that can be changed in the position tracking
                   pull down.
           mode='mfs' 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 

           mode='channel' examples:
               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 
               Note:  psfmode will also be used to clean if 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
               Corrects 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):
               Make a mosaic of the different pointings (uses csclean style
               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 mosaic;
                   Options: 'ft' (standard interferometric gridding), 'sd'
                   (standard single dish), 
                   and 'mosaic' (grid using PB as convolution function).
                   default: 'mosaic'; 
                   ONLY if imagermode='mosaic' is chosen and
                   ftmachine='mosaic', is heterogeneous imaging (CARMA, ALMA)
                   possible using the right convolution of primary beams 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. 
                             be acheived by setting pbcor=True.
                     'PBCOR' uses the SAULT scaling scheme for
                             deconvolution, but if interactive=True shows the
                             primary beam corrected image during interactive. 

  >>> 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 
                   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 with 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
                 interactive update of the mask.  It is important to modify
                 this number interactively during the cleaning, starting with
                 a low number like 20, but then increasing as more extended
                 emission is encountered.

       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',
               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: the on-sky FWHM in arcsec is roughly
                   the uv taper/200 (klambda).
                   default: outertaper=[]; no outer taper applied
                   example: outertaper=['5klambda']  circular taper 
                                FWHM=5 kilo-lambda
                            outertaper=['10arcsec'] on-sky FWHM 10 arcseconds
                            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
       weighting -- Weighting to apply to visibilities:
               default='natural'; example: weighting='uniform';
               Options: 'natural','uniform','briggs', 

  >>> 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" 
                   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 arcseconds example:
                        restoringbeam=['10.0','5.0','45.0deg'] 10"x5" 
                        at 45 degrees
       pbcor -- Output primary beam-corrected image
                If pbcor=False, the final output image is NOT corrected for the 
                PB pattern (particularly important for mosaics), and therefore is
                not "flux correct". Correction can also be done after the 
                fact using immath to divide <imagename>.image by 
                the <imagename>.flux image. 
               default: pbcor=False; output un-corrected image 
               example: pbcor=True; output pb-corrected image (masked outside
       minpb -- Minimum PB level to use default=0.2;
               The flux image is used to determine this
               except for the case of mosaic with ftmachine='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

              2. Masks for flanking fields are specified in same way as 
                 in the single output field case, but need extra '[ ]' to
                 distinguish each field. 
                    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
                 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).